investigation of csf1-csf1r signaling in aml-bone marrow ......mem) in particular led to significant...
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Investigation of CSF1-CSF1R Signaling in AML-Bone Marrow Stromal
Cell Interactions
By
Ayesha Rashid
A thesis submitted in conformity with the requirements
for the degree of Doctor of Philosophy
Department of Medical Biophysics, University of Toronto
© Copyright by Ayesha Rashid, 2019
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ABSTRACT
CSF1-CSF1R Signaling in AML-Bone Marrow Stromal Cell Interactions
Ayesha Rashid
Department of Medical Biophysics
University of Toronto
2019
Acute myeloid leukemia (AML) is a highly heterogeneous and growth factor-dependent
disease. Colony stimulating factor 1 (CSF1) is a cytokine produced by bone marrow (BM)
stromal cells that directs the differentiation and growth of myeloid cell precursors into
monocytes and macrophages. Human CSF1 (hCSF1) exists as a soluble/secreted (hCSF1-sol),
and a transmembrane (hCSF1-mem) isoform. CSF1 acts on the CSF1 receptor (CSF1R), which
is expressed on mononuclear phagocytic cells. In this study, the CSF1-CSF1R ligand-receptor
pair was investigated in the context of AML-stromal cell interactions.
Analysis of cell surface CSF1R protein levels revealed that a subset of AML patient
samples express high levels of CSF1R (CSF1Rhigh), and that these patients have shorter overall
survival (OS) times compared to patients with low CSF1R expression (CSF1Rlow). In examining
the CSF1-CSF1R interaction experimentally, the long-term growth and survival of
CSF1Rhigh AML cells was supported by MS-5 stromal cells expressing human CSF1 (hCSF1) in
co-culture experiments. MS-5 cells expressing the membrane-bound form of CSF1 (hCSF1-
mem) in particular led to significant increases in AML cell numbers and adhesion to stroma,
compared to cells co-cultured with MS-5 empty vector (EV) or hCSF1-sol cells. Co-culture of
AML cells with MS-5 hCSF1-mem cells led to activation of mTOR signaling in AML cells as
observed through increases in pS6, increased expression of the hematopoietic stem cell markers
CD34 and c-Kit on AML cells, and distinct changes in the cytokine profiles of both AML and
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stromal cells. Further to this, deletion of the PDZ domain binding motif (PDBM) at the C-
terminal end of CSF1 ligand in MS-5 stromal cells led to decreased stromal support of AML
cells, and reduced mTOR pathway activation.
The interaction between CSF1 and CSF1R mediates supportive effects between AML
and stromal cells by fostering bilateral intracellular and intercellular signaling changes. As such,
targeting the CSF1-CSF1R interaction may prove to be an effective therapeutic strategy to
overcome and compromise the protective and supportive role of the BM niche in AML disease
pathogenesis.
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ACKNOWLEDGEMENTS
I would firstly like to thank my graduate supervisor, Dr. Mark Minden, for giving me the
opportunity to pursue research in his lab under his guidance and supervision. I am extremely
grateful to Dr. Minden for allowing me the flexibility in exploring and working through my
project, and for always lending his unconditional support. His passion and dedication to his work
have served as great inspiration and motivation for me throughout my graduate studies.
I would also like to thank my committee members Drs Vuk Stambolic, Aaron Schimmer and
Dwayne Barber for their feedback, suggestions and engaging discussions at meetings. Thank you
for your continued support all throughout. I would also like to thank Chau Dang, Daphne Sears
and Annette Chan from the Department of Medical Biophysics for their support and guidance
throughout the program.
I would like to express my gratitude to members of the Minden lab (past and present) for their
support, guidance and friendship. I am especially thankful to Dr. Ruijuan He who has been a
wonderful mentor, teacher and friend at all times. I would also like to thank Xiu-Zhi Yang, Jian
Liu, Dr. Michael Jain, Dr. John Woolley, Dr. Irakli Dzneladze, Dr. Narmin Ibrahimova, Dr.
Mohammed Fateen, Dr. Rob Laister, Dr. Jenny Jun, Dr. Youqi Han and Francesca Pulice for
their support and assistance throughout. Thank you especially to Drs John Woolley, George Ren
and Michael Jain for their invaluable scientific advice and mentorship.
This journey would not have been possible without the unwavering support of my family. I
would like to thank my parents and my sister Sarah who have supported me throughout the
journey with constant love, support and patience. Thank you to my parents for instilling in me
values of honesty, compassion, genuine hard work and the will to succeed.
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TABLE OF CONTENTS
ABSTRACT .................................................................................................................................... ii
ACKNOWLEDGEMENTS ........................................................................................................... iv
TABLE OF CONTENTS ................................................................................................................ v
LIST OF FIGURES ...................................................................................................................... vii
LIST OF TABLES ......................................................................................................................... ix
ABBREVIATIONS ........................................................................................................................ x
CHAPTER 1: Introduction .......................................................................................................... 1
1.1. HEMATOPOIESIS ...................................................................................................... 2
1.1.1. Hematopoietic growth factors and cytokines ............................................................ 5
1.2. ACUTE MYELOID LEUKEMIA.............................................................................. 10 1.2.1. AML Classification ................................................................................................. 12 1.2.2. AML Risk Groups................................................................................................... 15
1.2.3. Genetic Mutations in AML ..................................................................................... 18 1.2.4. AML Treatment ...................................................................................................... 25
1.3. HEMATOPOIETIC AND LEUKEMIC STEM CELLS............................................ 28 1.3.1. In-Vitro Hematopoietic and Leukemic Cell Colony Formation Assays ................. 28
1.3.2. In-Vivo Hematopoietic and Leukemic Cell Assays ................................................ 29
1.3.3. Hematopoietic Cell Surface Markers ...................................................................... 33
1.4. THE BONE MARROW NICHE ................................................................................ 35
1.4.1. Cells and Factors in the Bone Marrow Niche ......................................................... 36 1.4.2. Hematopoietic and Leukemic Cells in the Bone Marrow Niche ............................ 40
1.5. BONE MARROW STROMAL CELL ASSAYS ...................................................... 43
1.6. COLONY STIMULATING FACTOR 1 RECEPTOR (CSF1R) .......................................... 45 1.6.1. CSF1R Structure ..................................................................................................... 45 1.6.2. CSF1R Intracellular Signaling ................................................................................ 50
1.6.3. CSF1R in Disease ................................................................................................... 55
1.7. COLONY STIMULATING FACTOR 1 (CSF1) .................................................................. 56 1.7.1. CSF1 Gene Structure and Isoforms ........................................................................ 57 1.7.2. CSF1 in Pathology .................................................................................................. 62
1.8. INTERLEUKIN-34 (IL-34) ................................................................................................... 63
1.9. SOLUBLE VS. TRANSMEMBRANE LIGANDS ............................................................... 64
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1.10 PDZ DOMAINS AND PDZ DOMAIN BINDING MOTIFS .................................... 64 1.11. HTRA SERINE PROTEASES ................................................................................... 68 1.12. EXPERIMENTAL MODELING ............................................................................... 71 1.13. THESIS FOCUS ......................................................................................................... 72
1.14. THESIS RATIONALE, HYPOTHESES AND OBJECTIVES ................................. 74
CHAPTER 2: CSF1R is associated with poor clinical outcome and promotes a leukemic
cell phenotype in AML-stromal cell interactions ..................................................................... 76 2.1. ABSTRACT ........................................................................................................................... 77
2.2. INTRODUCTION ................................................................................................................. 78 2.3. MATERIALS AND METHODS ........................................................................................... 81 2.4. RESULTS .............................................................................................................................. 87 2.5. DISCUSSION ...................................................................................................................... 125
CHAPTER 3: CSF1 ligand signaling in AML-bone marrow stromal cell interactions ..... 132
3.1. ABSTRACT ......................................................................................................................... 133
3.2. INTRODUCTION ............................................................................................................... 134 3.3. MATERIALS AND METHODS ......................................................................................... 138 3.4. RESULTS ............................................................................................................................ 142
3.5. DISCUSSION ...................................................................................................................... 156
CHAPTER 4: Thesis discussion and significance of findings ............................................... 161
4.1. OVERALL DISCUSSION & SIGNIFICANCE OF FINDINGS ........................................ 162
4.2. FUTURE DIRECTIONS ..................................................................................................... 167
4.3. CONCLUSIONS.................................................................................................................. 169
REFERENCES .......................................................................................................................... 171
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LIST OF FIGURES
Figure 1.1. Hematopoiesis is organized as a cellular hierarchy. ..................................................... 4
Figure 1.2. Architecture of the bone marrow niche. ..................................................................... 39
Figure 1.3. Structure of CSF1R. ................................................................................................... 47
Figure 1.4. CSF1 ligand binding to CSF1R. ................................................................................. 49
Figure 1.5. CSF1R activation of intracellular signal transduction pathways. .............................. 54
Figure 1.6. Alternative splicing of CSF1 leads to different isoforms. .......................................... 60
Figure 1.7. Model of the two major variants of monomeric CSF1. .............................................. 61
Figure 1.8. Structure and function of HtrA serine proteases. ....................................................... 70
Figure 1.9. Modeling an AML-bone marrow microenvironment. ................................................ 73
Figure 2.1. CSF1R gene expression levels are high in certain prognostically significant
subgroups of AML patients. ......................................................................................................... 88
Figure 2.2. High CSF1R high levels are associated with shorter OS in AML patients. ............... 89
Figure 2.3. CSF1R cell surface protein levels are associated with poor AML clinical outcome. 93
Figure 2.4. CSF1R and CD34 co-expression patterns are associated with OS............................. 98
Figure 2.5. CSF1R expression in AML cell lines and patient samples. CSF1R cell surface ..... 100
Figure 2.6. AML cells show minimal growth responses to exogenous soluble CSF1. .............. 102
Figure 2.7. CSF1 overexpression in MS-5 stromal cell lines. .................................................... 104
Figure 2.8. MS-5 stromal cells expressing hCSF1 support the proliferation and survival of factor-
dependent CSF1R-expressing AML cell lines. ........................................................................... 107
Figure 2.9. MS-5 stromal cells that express hCSF1 support the proliferation and survival of
primary AML cells that express CSF1R. .................................................................................... 110
Figure 2.10. Blockade of CSF1R on AML cells inhibits their proliferation in co-culture with MS-
5 hCSF1 cells. ............................................................................................................................. 112
Figure 2.11. AML cells exhibit changes in cytokine production and mTOR pathway activation
after co-culture with hCSF1-expressing MS-5 cells. .................................................................. 115
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Figure 2.12. OCI/AML-5 cells exhibit mTOR pathway activation after co-culture with hCSF1-
expressing MS-5 cells. ................................................................................................................ 116
Figure 2.13. AML cells grown in co-culture with hCSF1-expressing MS-5 cells exhibit changes
in cell surface marker expression. ............................................................................................... 119
Figure 2.14. AML cells exhibit engraftment in humanized CSF1 (huCSF1) mice, with changes in
cell surface marker expression. ................................................................................................... 121
Figure 2.15. BM stromal cells derived from huCSF1 mice support AML cell proliferation. .... 123
Figure 3.1. The intracellular domain of CSF1 possesses a conserved C-terminal PDZ domain
binding motif (PDBM). ............................................................................................................... 143
Figure 3.2. CSF1-expressing MS-5 stromal cells demonstrate differential phenotypic and
signaling behaviour. .................................................................................................................... 146
Figure 3.3. CSF1 expression in MS-5 Tet-off inducible cells. ................................................... 149
Figure 3.4. CSF1-induced mTOR signaling is mediated by HtrA1 in MS-5 cells. .................... 151
Figure 3.5. Support of AML cells by hCSF1-expressing MS-5 cells. ........................................ 153
Figure 3.6. Model of CSF1-induced multi-directional signaling in AML-stromal cell interactions.
..................................................................................................................................................... 155
ix
LIST OF TABLES
Table 1-1. FAB-based classification system for AML based on morphology and cytogenetics. . 13
Table 1-2. WHO classification of myeloid neoplasms and acute leukemia, 2008. ...................... 14
Table 1-3. NCCN risk groups classification of AML. Adapted from National Comprehensive
Cancer Network (NCCN) Guidelines: Acute Myeloid Leukemia. Version 2.2019. .................... 17
Table 1-4. Types of frequently mutated genes in AML based on function .................................. 24
Table 1-5. Cross-reactivity of hematopoietic and stromal cell growth factors and cytokines
between mouse and human. .......................................................................................................... 31
Table 1-6. Classification of PDZ domain binding recognition sequences.................................... 67
Table 2-1. Table of AML patient characteristics from the PMCC/UHN dataset. ........................ 92
x
ABBREVIATIONS
AML Acute Myeloid Leukemia
α-MEM Alpha Modification Minimal Essential Medium Eagle
BM Bone Marrow
CAFC Cobblestone-Area-Forming Cell
CFC Colony Forming Cell
c-KIT KIT Proto-Oncogene Receptor Tyrosine Kinase
CR Complete Remission
CSF1 Colony-Stimulating Factor 1
CSF1R Colony-Stimulating Factor 1 Receptor
CXCL12 C-X-C Motif Chemokine Ligand 12
CXCR4 C-X-C Motif Chemokine Receptor 4
FAB French-American-British
FBS Fetal Bovine Serum
FLT3 Fms Related Tyrosine Kinase 3
FMS McDonough Feline Sarcoma Viral (V-Fms) Oncogene Homolog
GM-CSF Granulocyte-Macrophage Colony-Stimulating Factor
G-CSF Granulocyte Colony-Stimulating Factor
HSC Hematopoietic Stem Cell
HTRA1 High-Temperature Requirement A Serine Peptidase 1
IL-3 Interleukin-3
IL-6 Interleukin-6
LTC-IC Long Term Culture Initiating Cell
LSC Leukemia Stem Cell
MAPK Mitogen-Activated Protein Kinase
MSC Mesenchymal Stem Cell
mTOR Mammalian/Mechanistic Target of Rapamycin
NPM1 Nucleophosmin 1
PCR Polymerase Chain Reaction
PDBM PDZ Domain Binding Motif
PI3K Phosphoinositide 3-Kinase
PKB Protein Kinase B (AKT)
MS-5 Murine Stromal (cell line) 5
RBC Red Blood Cell
rhCSF1 Recombinant Human CSF1
(RP)S6 Ribosomal Protein S6
RTK Receptor Tyrosine Kinase
SCF Stem Cell Factor
SCID Severe Combined Immunodeficient
siRNA Short Interference Ribonucleic Acid
STAT Signal Transducers and Activators of Transcription
TNF Tumor Necrosis Factor
PVDF Polyvinylidene Difluoride
WBC White Blood Cell
WHO World Health Organization
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CHAPTER 1
Introduction
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1.1. HEMATOPOIESIS
Hematopoiesis is a highly regulated process that gives rise to the over 10 distinct cell types
of the blood. The hematopoietic stem cell (HSC) is the most primitive hematopoietic cell from
which all blood cells are derived. As a stem cell, the HSC is defined by properties of sustained
proliferation, multi-lineage differentiation and long-term self-renewal (McCulloch, 1983). The
HSC is found at a frequency of only 1 in 10,000 cells (or 0.01% of total BM cells) within the BM
(Rossi, Challen, Sirin, Lin, & Goodell, 2011). Despite its rarity, a single HSC transplanted into
immune deficient mice irradiated to ablate their BM, has the ability to re-constitute the entire
hematopoietic system.
Hematopoiesis is organized in a cellular hierarchy maintained by a pool of self-renewing
pluripotent HSCs. HSCs can have both long and short life spans: long-term HSC (LT-HSC) and
short-term HSC (ST-HSC). The HSC gives rise to progressively more differentiated progenitor
cell intermediates, leading to the formation of distinct terminally differentiated blood cells
(Figure 1.1).
There are two main lineages of hematopoietic blood cells: myeloid and lymphoid. The
pluripotent HSC is stimulated by hematopoietic growth factors and cytokines, which direct its
differentiation and maturation into hematopoietic multipotent progenitor (MPP) cells, namely the
common myeloid progenitor (CMP) and the common lymphoid progenitor (CLP) (Tsiftsoglou,
Vizirianakis, & Strouboulis, 2009). These can differentiate into more lineage-restricted
oligopotent progenitors i.e. myeloblasts and lymphoblasts, respectively, which then differentiate
into unilineage, unipotent progenitor intermediates (i.e. promyelocytes, prolymphocytes) as they
finally mature into unipotent lineage committed cells. Through myelopoiesis, myeloid
progenitors terminally differentiate into mature erythrocytes (RBCs), thrombocytes (platelets),
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monocytes and granulocytes. Monocytes can continue to differentiate into macrophages
(osteoclasts and tissue resident macrophages) and dendritic cells (Morrison & Weissman, 1994).
Granulocytes are also known as polymorphonuclear leukocytes (PML or PMNL) due to their
variably shaped multi-lobed nuclei. They also contain granular sacs throughout their cytoplasm,
which contain various toxic substances such as antimicrobial agents, enzymes, oxygen-based
free radicals and low pH vesicles that are released to fight and kill pathogens (Hickey & Kubes,
2009). There are four main types of granulocytes: neutrophils, eosinophils, basophils and mast
cells, with neutrophils being the most abundant of these (Breedveld, Groot Kormelink, van
Egmond, & de Jong, 2017). Cells of the innate immune response include monocytes, neutrophils,
basophils and eosinophils.
On the other hand, lymphoid progenitors differentiate into natural killer (NK) cells, and the
T and B lymphocytes (T cells and B cells), which are part of the adaptive immune response.
Upon activation, B cells further differentiate into specific antibody-producing plasma cells.
Leukocytes (or WBCs) include both myeloid (granulocytes, monocytes) and lymphoid
(lymphocytes) lineage-derived cells. Fully differentiated, mature cells have limited proliferative
potential and lack self-renewal capacity. Fate determination in hematopoietic precursors is
signaled by specific growth factors and cytokines that direct cell differentiation, growth and
maturation (Laurenti & Göttgens, 2018).
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Figure 1.1. Hematopoiesis is organized as a cellular hierarchy.
The hematopoietic stem cell (HSC) resides at the apex of a hematopoietic cellular hierarchy
which gives rise to progressively more differentiated cells induced by specific hematopoietic
cytokines at each stage of development. There are two main lineages of cells that the HSC gives
rise to: myeloid and lymphoid. Each differentiate into increasingly lineage-committed progenitor
cells to give rise to the different mature blood cell types. Figure adapted from: Molecular Cell
Biology (textbook). Lodish, Harvey F. 5. ed.: – New York : W. H. Freeman and Co., 2003, 973 s.
b ill. ISBN 0-7167-4366-3.
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1.1.1. Hematopoietic growth factors and cytokines
Hematopoiesis is regulated by hematopoietic growth factors and cytokines that induce the
differentiation and growth of hematopoietic cell precursors into mature, lineage-committed cells.
Specific factors govern the lineage-specific differentiation into different cell types (Figure 1.1).
Among these are the colony stimulating factors (G-CSF, GM-CSF, MCSF), stem cell factor
(SCF) erythropoietin (EPO), thrombopoietin (TPO), interleukin-3 (IL-3), interleukin-6 (IL-6)
and interleukin-11 (IL-11) (Norris, Magwood, & Bennett, 2014; Orkin & Zon, 2008).
Colony-stimulating factors (CSF) are predominantly secreted glycoprotein hematopoietic
growth factors that bind to receptors on hematopoietic cells to induce their growth,
differentiation and survival (Donald Metcalf, 2013). They were first identified based on their
ability to induce the expansion of single cells into morphologically and functionally distinct
hematopoietic cell colonies in colony forming assays (CFA). There are three major CSFs:
macrophage colony-stimulating factor (MCSF or CSF1), granulocyte-macrophage colony-
stimulating factor (GM-CSF or CSF2) and granulocyte colony-stimulating factor (G-CSF or
CSF3). Each factor is named based on the type of cell colony that it is able to give rise to i.e.
MCSF stimulates the formation of colonies of macrophages while G-CSF leads to formation of
colonies of granulocytes (Norris et al., 2014). It should be noted that the other hematopoietic
cytokines should also technically be classified as colony stimulating factors as they also have the
ability to give rise to lineage-specific hematopoietic cell colonies. While most of the CSFs are
secreted, soluble proteins, MCSF can also exist as a membrane-bound ligand, predominantly in
the BM (MCSF will be discussed in detail later on). The CSFs act in autocrine, endocrine and
paracrine signaling to elicit their effects.
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GM-CSF
GM-CSF is a monomeric glycoprotein produced and secreted by a wide array of different
cells in the BM including macrophages, mast cells, T cells, NK cells, endothelial cells and
fibroblasts (Gasson, 1991). It acts on HSCs, by binding to the GM-CSF receptor, to induce their
differentiation into granulocytes (neutrophils, basophils, eosinophils) and monocytes, which
eventually mature into macrophages and dendritic cells. It is thus involved in
immune/inflammatory responses as it leads to the expansion of core cells, particularly
macrophages, in the innate immune response. GM-CSF binds to the GM-CSF receptor (also
known as CD116) and elicits its intracellular effects through activation of STAT proteins,
namely STAT5 as well as STAT3 in some cases (Faderl et al., 2003). It is highly expressed in
rheumatoid arthritis and neoplasias, and GM-CSF inhibitors have been developed for the
potential treatment of rheumatoid arthritis in particular. GM-CSF and related derivatives are used
clinically to increase WBC counts after chemotherapy or bone marrow transplantation
(Armitage, 1998).
G-CSF
G-CSF is a cytokine and hormone that stimulates the differentiation of myeloid cells into
granulocytes. It is a soluble glycoprotein that is produced by endothelial cells, macrophages and
other immune cells within the BM. G-CSF acts on the G-CSF receptor expressed on
hematopoietic precursors to induce their proliferation, growth, survival and differentiation into
mature granulocytes, as well as neutrophils (D Metcalf, 1985; Souza et al., 1986). G-CSF elicits
these effects through activation of the JAK/STAT, MAPK/ERK and PI3K/Akt pathways which
are involved in growth, survival and differentiation (these will be discussed later). In addition, G-
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CSF also exerts potent effects on HSCs by inducing their mobilization from the BM. This has
important clinical applications as it is used to mobilize HSCs into the bloodstream of donors,
which are then collected via leukapheresis for use in allogeneic stem cell transplantation
(Schwella, Braun, Ahrens, Rick, & Salama, 2003). G-CSF is also used to treat neutropenia and
bolster WBC counts after chemotherapy (Bendall & Bradstock, 2014; Morstyn et al., 1988).
IL-6
Interleukin-6 (IL-6) is both a pro-inflammatory cytokine, and an anti-inflammatory
myokine (a cytokine produced by muscle cells), produced in inflammation, infection and
cancers. It is produced by T cells and monocytes/macrophages, in response to binding of
lipopolysaccharide (LPS) to toll-like receptor 4 (TLR4), to activate immune responses after
injury or infection, particularly those involving an inflammatory response such as burns or other
tissue damage (Richards, 1998). It is also secreted by fibroblasts, keratinocytes and endothelial
cells in response to IL-1, and by osteoblasts to activate osteoclast production (Ishimi et al.,
1990). It can also act as an anti-inflammatory cytokine by exerting inhibitory effects on pro-
inflammatory cytokines such as TNF-α, IL-1, and activating effects on IL-1Ra and IL-10
(Kishimoto, 2010). In hematopoiesis, IL-6 may play a role in the survival, self-renewal and
differentiation of HSCs and in B-cell differentiation (Bernad et al., 1994; Patchen, MacVittie,
Williams, Schwartz, & Souza, 1991). Importantly, it synergizes with other hematopoietic
cytokines, namely the GM-CSF, SCF (stem cell factor) and IL-3, to induce the survival and
differentiation of hematopoietic progenitors in-vitro and in-vivo (K. Ikebuchi et al., 1987).
In infection and inflammation, IL-6 is largely involved in mediating fever in the acute
phase response (an inflammatory response involving plasma proteins). IL-6 acts on the IL-6
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receptor (IL-6R) complex which is composed of the IL-6Rα (CD126) ligand-binding chain and
the signal transducing unit glycoprotein 130 (gp130 or CD130). Upon activation, the IL-6
ligand-receptor complex activates intracellular pathways including JAK/STAT to activate STAT
proteins (namely STAT3) and other transcription factors (Heinrich et al., 1998). There also exists
a soluble form of the IL-6R, sIL-6R, which can be isolated from human serum and urine. IL-6
stimulates inflammatory and auto-immune responses in several diseases and disorders including
diabetes, atherosclerosis, rheumatoid arthritis, Alzheimer’s disease, multiple myeloma and
prostate cancer among others (Barton, 2005; Gado, Domjan, Hegyesi, & Falus, 2000; Kristiansen
& Mandrup-Poulsen, 2005; Nishimoto, 2006; Smith, Hobisch, Lin, Culig, & Keller, 2001;
Swardfager et al., 2010). An anti-IL-6 agent (tocilizumab) has been approved for treatment of
rheumatoid arthritis and there is great interest in the use and further development of anti-IL-6
therapies for other diseases including cancer (Emery et al., 2008). Blockade of IL-6 may be
useful in advanced prostate and pancreatic cancers in which there are elevated levels of IL-6,
which is associated with poor survival outcomes (Bellone et al., 2006).
IL-3
IL-3 is a glycoprotein that binds to the IL-3 receptor (IL-3R). It is involved in the body’s
immune responses in injury and disease and has been shown to mediate inflammation in sepsis
(Weber et al., 2015). In hematopoiesis, IL-3 directs the differentiation of multipotent HSCs into
myeloid progenitor cells, as well as lymphoid progenitor cells with the addition of IL-7. In
conjunction with cytokines such as IL-6, erythropoietin (EPO) and GM-CSF, IL-3 promotes the
growth and proliferation of cells within the myeloid lineage, namely, granulocytes, monocytes
and dendritic cells (Y. C. Yang et al., 1986). It is produced and secreted by basophils and T-cells.
9
Kit ligand/Stem Cell Factor (SCF)/Steel Factor
Kit ligand (KitL), also known as steel factor or stem cell factor (SCF), is a cytokine that
binds to the class III tyrosine kinase receptor c-Kit. It exists as both soluble and transmembrane
proteins, and is involved in hematopoiesis, spermatogenesis and melanogenesis (Kent et al.,
2008; Wehrle-Haller, 2003). In the BM, SCF (both soluble and transmembrane forms) is
produced by endothelial cells and fibroblasts. SCF is seen to play an important role in HSC
survival, maintenance and homing to HSC BM niches as it is involved in adhesion (Keller, Ortiz,
& Ruscetti, 1995). Moreover, HSCs and hematopoietic progenitors are seen to preferentially
localize and migrate to areas with high SCF levels, indicating its chemotactic role. During
embryogenesis, SCF is expressed in the fetal liver and BM where it is critical for hematopoiesis
as SCF null mice die in utero due to severe anemia (Geissler et al., 1991). Upon binding to its
receptor, c-Kit, SCF induces receptor dimerization and activation, leading to stimulation of
intracellular pathways that regulate growth, survival and differentiation such as the JAK/STAT,
MAPK and PI3K/Akt pathways.
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1.2. ACUTE MYELOID LEUKEMIA
Acute Myeloid Leukemia (AML) is a highly heterogeneous and aggressive hematological
malignancy of the bone marrow (BM) characterized by the clonal expansion of hematopoietic
cell precursors that are blocked in their ability to differentiate. Its incidence increases with age
and with current therapy, overall 5-year survival ranges from 30-70%, based on disease subtype
and associated risk factors (Liersch, Müller-Tidow, Berdel, & Krug, 2014). AML affects more
males than females and age is a strong prognostic indicator, with older adults having poorer
survival outcomes compared to younger individuals (Juliusson et al., 2009). Despite achieving an
initial complete remission to treatment, more than half of all AML patients relapse within 1-2
years, likely due to the outgrowth of leukemic cells that were therapy resistant and hence evaded
and/or survived chemotherapy. The symptoms of AML are ambiguous and non-specific as they
often mimic those of the common flu, particularly fatigue and fever, but can be accompanied by
weight loss, dyspnea (shortness of breath), frequent or increased risk of infection and easy
bleeding and/or bruising (Hoffman et al., 2017). As an acute disease, AML can progress quite
rapidly and can be fatal in a span of days or weeks if left untreated. The risk factors for AML are
not entirely clear but include smoking, myelodysplastic syndrome (MDS), previous
chemotherapy or radiation therapy and exposure to the chemical benzene (Arber, 2017).
11
AML can be described as a BM failure state, characterized by decreased production of
normal hematopoietic cells and increased production of immature progenitor cells that are
blocked in their ability to differentiate; these latter cells are able to proliferate extensively in a
clonal fashion, as well as self-renew, a property essential for the maintenance of the disease
(Betz & Hess, 2010b; Ferrara & Schiffer, 2013a). AML is a malignancy of myeloid lineage cells
that arises due to acquired mutations that occur in the HSC or in early myeloid progenitor cells,
most typically in the myeloblast cell, also known as ‘blast’ cells. A major consequence of these
mutations is the disruption of differentiation signals, leading to the arrest of cells in an immature,
undifferentiated state. At the same time, growth and cell cycle checkpoints are lost, as is typical
in most cancers, resulting in uncontrolled proliferation. This leads to an accumulation of
abnormal, undifferentiated blasts, i.e. leukemia cells, in the BM which interferes with the
production of normal hematopoietic cells as they compete for space and resources. This creates a
cellularly and biochemically competitive environment where leukemic cells may out-populate
and replace normal blood cells. This is evident through reductions in numbers of normal white
blood cells (WBC) (i.e. neutrophils), red blood cells and platelets, with WBC counts that can be
either abnormally high or low (Betz & Hess, 2010b).
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1.2.1. AML Classification
AML is diagnosed based on the finding of at least 20% blasts in the peripheral blood
and/or BM, along with the presence of recurrent cytogenetic abnormalities which may include
t(15;17), t(8;21), t(16;16) or inv(16) (Betz & Hess, 2010b; Tallman et al., 2019). Diagnosis
begins with abnormal findings in a complete blood count (CBC) test, in which blasts may or may
not be detected. The CBC may show low platelet and neutrophil counts, and total WBC counts
that are higher (leukocytosis) or lower (leukopenia) than normal. A BM aspiration or biopsy is
performed to assess BM involvement i.e. the presence of blasts and other cellular abnormalities
in the BM. Blood and BM samples are assessed using cytological and molecular approaches that
involve examination of morphology, cell surface marker expression, cytogenetics and molecular
profile to make the final diagnosis and classify the subtype of disease (O’Donnell et al., 2017).
The two main classification systems for AML are the French-American-British (FAB)
system and the World Health Organization (WHO). The FAB system was first introduced in
1976 and relies largely on cell morphological characteristics and cytogenetics. It also has more
stringent requirements such as a higher blast percentage of at least 20-30% in the peripheral
blood/BM (Bennett et al., 1976). The FAB system classifies AML into eight different subtypes
that range from M0 to M7, based on the type of cell involved and its degree of maturation, which
are evaluated using light microscopy. Cytogenetics is also included in the classification, with
certain abnormalities being commonly associated with specific subtypes. Table 1-1 outlines the
eight different FAB classifications of AML. The WHO system was introduced in 2008 and is a
relatively more thorough evaluation that integrates cytogenetics, morphology, genetic markers
and immunologic makers, with the aim of providing a more clinically and prognostically relevant
assessment than the FAB system (Table 1-2) (Weinberg et al., 2009).
13
Table 1-1. FAB-based classification system for AML based on morphology and
cytogenetics.
There are 8 different subtypes of AML according to the FAB system (Bennett et al., 1976b).
14
Table 1-2. WHO classification of myeloid neoplasms and acute leukemia, 2008.
15
1.2.2. AML Risk Groups
AML is characterized by a great degree of cellular and genetic heterogeneity owing to the
diversity of molecular drivers in the disease. These include recurrently occurring driver
mutations and genomic alterations, which lead to a cellular block in differentiation and increased
proliferation. Driver mutations cause the clonal expansion of specific sub-clones, while
passenger mutations may be associated with the clonal expansion but do not confer any
functional effect. Overall, differences in leukemogenic drivers manifest in the differences seen in
clinical characteristics and treatment responses.
Large-scale genomic studies have identified and characterized driver mutations that
underlie AML evolution (Baldus & Bullinger, 2008; Cancer & Atlas, 2013; Papaemmanuil et al.,
2016b; Welch et al., 2012) For example, one study involving 1540 patients identified 5234
potential driver mutations across 76 genes and genomic regions (Papaemmanuil et al., 2016). At
least one driver mutation was identified in 96% of all AML patients, with two or more driver
mutations seen in 86% of patients. Clinically, the authors demonstrate a significant difference in
disease presentation and patient survival across the genomic subgroups.
Common genetic alterations include chromosomal rearrangements, amplifications,
deletions and point mutations. Approximately 45% of AML cases present with one or more
cytogenetic alterations, many of which are prognostically significant. 15% of patients within this
group harbour 3 or more chromosomal abnormalities which identifies a group designated
‘complex karyotype’ AML (Mrózek, Heerema, & Bloomfield, 2004). This leaves a group of 40-
50% of AMLs that do not carry any grossly obvious cytogenetic lesions and are hence deemed
cytogenetically normal (CN), although a normal karyotype does not generally predict for a
favourable outcome as there is considerable variation across individual cases.
16
Cytogenetic and molecular profiles provide important prognostic value in the prediction
of clinical outcome and guiding of treatment strategies, and are thus used to help stratify patients
based on risk. The National Comprehensive Cancer Network (NCCN) outlines three major risk
groups according to the presence (or absence) of a combination of genetic lesions: adverse,
intermediate and favourable (O’Donnell et al., 2017; Tallman et al., 2019). The adverse risk
group includes inv(3) and complex karyotype, the intermediate group includes t(9;11) and CN-
AML, while the favourable group includes t(8;21), inv(16) and t(15;17), the latter being the M3,
APL subtype that is characterized by the PML-RARA (PML = promeylocytic leukemia gene;
RARA = retinoic acid protein alpha) fusion protein. The risk groups differ with respect to
response to therapy, likelihood of relapse, and predicted long-term patient survival. The three
major risk groups are summarized in Table 1-3.
17
Table 1-3. NCCN risk groups classification of AML. Adapted from National
Comprehensive Cancer Network (NCCN) Guidelines: Acute Myeloid Leukemia. Version
2.2019.
18
1.2.3. Genetic Mutations in AML
In addition to cytogenetics, the molecular profiling of AML has becoming increasingly
important with demonstrated value in AML diagnosis and prognosis. There are a number of
recurrent molecular abnormalities that have aided in the prognostic stratification of the highly
heterogeneous group of CN-AML. Among frequently occurring molecular abnormalities are
internal tandem duplications (ITD) in FLT3 (FLT3-ITD) (25 – 30% of AML cases), mutations in
the transcriptional regulator nucleophosmin 1 (NPM1) that results in its cytoplasmic (c)
mislocalization (NPM1c) (30% of cases), MLL partial tandem duplications and a variety of
nucleotide substitutions and/or short insertions or deletions within the coding regions of the
genes NPM1, CEBPA, NRAS and WT1 (Betz & Hess, 2010a). Mutations in the tyrosine kinase
domain (TKD) of FLT3 may also occur in CN-AML but they are less common, occurring in
approximately 15% of all AML cases (Patnaik, 2018). Other recurrent mutations include
mutations in the isocitrate dehydrogenase (IDH) genes IDH1 and IDH2, TP53, RUNX1 (runt-
related transcription factor 1), TET2 (Tet methylcytosine dioxygenase 2), and DNMT3A (DNA
Methyltransferase 3 Alpha). In the prognostic stratification of AML,
DNMT3A and RUNX1 mutations have been shown to be predictors of shorter overall survival
(OS) in AML patients that are < 60 years old and with intermediate-risk cytogenetics. In
addition, NPM1 mutations in the absence of FLT3-ITD, mutated TP53, and biallelic CEBPA
mutations (discussed later) are significant molecular prognostic indicators associated with OS,
regardless of patient age (Metzeler et al., 2016). As such, FLT3-ITD, NPM1c and CEBPA are
recommended to be routinely screened for in CN-AML patients (Papaemmanuil et al., 2016b;
Roloff & Griffiths, 2018; Tallman et al., 2019).
19
FLT3-ITD
The FLT3-ITD is a recurrent mutation found in approximately 25-30% of AML cases
(Daver, Schlenk, Russell, & Levis, 2019). FLT3 is a transmembrane class III receptor tyrosine
kinase (RTK). Class III RTKs are characterized by an insert region in the intracellular tyrosine
kinase domain and a cytoplasmic auto-inhibitory juxtamembrane domain adjacent to the
transmembrane domain. Mutations in the juxtamembrane domain result in ITDs that lead to
ligand-independent auto-phosphorylation of tyrosine residues in the kinase domain, resulting in
constitutive activation of the receptor (Gary Gilliland & Griffin, 2002). The ITDs arise from the
duplication and tandem insertion of a small variably sized (3 – 400 nucleotides) fragment of the
gene. The ITDs can be readily identified using PCR based on a larger product size, indicating
presence of the duplication, as compared to the wild-type gene. FLT3 activation leads to
stimulation of intracellular signal transduction pathways involved in growth, proliferation,
survival and differentiation, namely the JAK/STAT, MAPK/ERK and PI3K/Akt pathways.
FLT3-ITD mutations have been shown to induce the aberrant activation of STAT5 while
inhibiting the activity of transcription factors involved in myeloid differentiation (Choudhary et
al., 2007, 2005; Mizuki et al., 2000). STAT5 has been shown to play an important role in HSC
self-renewal, and is also found to be constitutively activated in human leukemias including AML
(Benekli, Baer, Baumann, & Wetzler, 2003).
NPM1
NPM1 is a phosphoprotein that shuttles between the nucleus and cytoplasm to regulate a
wide range of cellular functions. It predominantly resides in the nucleolus where it is involved in
ribosomal assembly and regulation of the tumor suppressors p53 and ARF. Mutations in NPM1
20
are amongst the most common genetic aberrations in AML, occurring in 50-60% of CN-AML,
and 30% of all de novo AML cases (Welch et al., 2012). Over 40 mutations in exon 12 of the
NPM1 gene have been identified, with nearly all of them resulting in a 4-nucleotide insertion.
Mutations in NPM1 were first identified in AML based on the mislocalization of the protein in
the cytoplasm (Falini et al., 2009; Verhaak et al., 2005). The mutant (NPM1mut) form is denoted
NPM1c and was found to be associated with a CD34- immunophenotype. Clinically, NPM1c is
associated with a good response to induction therapy, lower rates of relapse and favourable
prognosis with good overall survival. Importantly, the prognostic value of NPM1c is highly
dependent on FLT3-ITD status, with NPM1c having a favourable prognosis only in FLT3-ITD
negative cases (Gale et al., 2008). For this reason, NPM1c and FLT3-ITD are now routinely
tested for clinically, in order to make more informed treatment plans and evaluate prognostic
outcomes. This highlights the significance of the contextual molecular interplay between
multiple disease markers, lending support to the notion of AML being a heterogeneous, multi-
factorial disease.
CEBPA
CCAAT enhancer binding protein alpha (CEBPA) is a transcription factor that regulates
the differentiation and development of granulocytes from hematopoietic progenitors. In
leukemogenesis, mutations in CEBPA lead to a loss in its function, which results in a block in
granulocytic differentiation (Ohlsson, Schuster, Hasemann, & Porse, 2016). CEBPA mutations
can occur either as frameshift mutations in the N-terminal region of the coding region of the
protein, leading to a truncated form of the full length p42 CEBPA protein, or C-terminal in-
frame mutations that result in defects in the dimerization and DNA binding activities of both the
21
full-length p42 CEBPA protein and a shorter p30 isoform (Pabst et al., 2001). Most AML cases
with mutations in CEBPA harbour both mutations, occurring on different alleles, and are hence
biallelic, although about 1/3 of CN-AML cases only display one of the mutations (monoallelic).
It has been reported that biallelic mutations are associated with a favourable prognosis in CN-
AML, making it important to distinguish between biallelic and monoallelic cases (Dufour et al.,
2010). CEBPA mutations are most effectively detected using DNA sequencing, which is both
time and labour intensive, thereby limiting its widespread clinical testing. CEBPA mutations
occur at a frequency of 5-10% in de novo AML and are present in nearly 15% of CN-AML
cases. CEBPA is an independent prognostic marker and is associated with good overall survival
when both alleles are affected, and lower rates of relapse, similar to what is seen for
NPM1mut/FLT3-ITDneg AML (Nerlov, 2004).
Types of AML gene mutations
AML gene mutations can be broadly divided into several categories with respect to the
protein factors that they effect. These include epigenetic modifiers, components of signal
transduction pathways, transcription factors and gene fusion protein products. These are listed in
Table 1-4.
Mutations in genes encoding epigenetic modifiers such as DNMT3A, DNMT1, IDH1/2,
ASXL1, TET2 and EZH2 are often found in the ‘founder’ clone as they occur early on in
leukemogenesis (Döhner, 2007; Papaemmanuil et al., 2016a). Mutations in these genes are found
in elderly patients with clonal hematopoiesis, which puts them at higher risk for developing
hematological malignancies (Papaemmanuil et al., 2016b). Although seen as driver mutations,
22
they are often not sufficient to drive disease, and require the acquisition of subsequent
mutation(s) to give rise to full-fledged disease.
Genes involved in signaling pathways are the most commonly mutated group of genes in
AML, representing up to 50% of all AML cases (The Cancer Genome Atlas Research Network,
2013). The most common mutations are found in genes encoding the class III receptor tyrosine
kinases FLT3 and KIT (or c-Kit), and the GTPase family of signaling mediators RAS (namely
KRAS and NRAS) (Fröhling, Scholl, Gilliland, & Levine, 2005). Activating mutations in RAS
proteins lead to their constitutive activation, contributing to the enhanced growth and
proliferation of AML cells.
Common chromosomal abnormalities in AML include t(8;21), inv(16)/t(16;16) and
t(15;17), which give rise to the RUNX1-RUNX1T1 (or RUNX1-ETO), Core-Binding Factor
(CBF)B-MYH11 and PML-RARA protein fusion products, respectively (Arber et al., 2016;
Ishikawa et al., 2009). RUNX1 and CBFB are subunits of the CBF, which is a transcription
factor involved in regulating normal hematopoiesis. As such, their gene fusion products,
resulting from the t(8;21) and inv(16)/t(16;16) rearrangements, cytogenetically define the class
of core-binding factor AMLs (Sangle & Perkins, 2011). Inv(16)/t(16;16) causes juxtaposition of
the CBF (core binding factor) gene located in 16q22 and the myosin, heavy chain 11, smooth
muscle (MYH11) gene located in 16p13, resulting in the fusion protein product (Delaunay et al.,
2003). The inv(16) rearrangement is usually associated with good prognosis (Patel et al., 2012).
AML and leukemogenesis can be seen to follow the classic ‘two-hit’ hypothesis model
wherein leukemia progenitor or initiating cells acquire two different mutations that lead to full
transformative potential and disease onset. This is highlighted by the fact that mutations in genes
from a similar group i.e. epigenetic regulators, do not occur concurrently in AML. For example,
23
mutations in epigenetic regulators such as DNMT3a occur early on in leukemogenesis, followed
by mutations in NPM1 and CEBPA, while mutations in pro-growth and -survival signaling
factors involved in disease progression such as FLT3, KIT, NRAS/KRAS and PTPN11 occur later.
Support for this is apparent through the co-expression of FLT3-ITD and NPM1 mutations in
AML.
24
Table 1-4. Types of frequently mutated genes in AML based on function
25
1.2.4. AML Treatment
The treatment for AML has remained largely unchanged for the last 40 years, however
despite this, patient outcomes have generally improved over the past few decades. This is largely
owed to advancements in supportive care, including the enhanced use and development of novel
anti-bacterial, anti-fungal and anti-emetic agents, as well as improved management and support
for therapy-related myelosuppression and platelet transfusion (Ferrara & Schiffer, 2013b).
First-line treatment for AML involves chemotherapy administered in two different
phases: induction therapy and consolidation (post-remission) therapy. The goal of induction
therapy is to achieve complete remission (CR) while consolidation therapy aims to eliminate any
residual disease in order to affect a cure. CR is defined as BM blasts less than 5%, absence of
extramedullary leukemia, neutrophil count greater than 1x109/L, platelet count greater than
100x109/L and no dependency on transfusion (Cheson et al., 2003).
The typical induction chemotherapy regimen for all of the AML FAB subtypes except for
M3 or APL, is the ‘3+7’ (or ‘7+3)’ regimen, which consists of 7 consecutive days of continuous
intravenous (IV) administration of cytarabine (also known as cytosine arabinoside or Ara-C) and
3 days administration of an anthracycline such as daunorubicin (Betz & Hess, 2010b).
Structurally cytarabine is cytosine combined with arabinose which is similar in structure to the
nitrogenous DNA base cytosine deoxyribose, and is hence incorporated into DNA during cell
replication and interferes with DNA synthesis, that ultimately results in the formation of DNA
breaks (Löwenberg et al., 2011; Rider, 2011). Daunorubicin is a DNA intercalator and can
displace histones in chromatin, leading to conformational DNA instability (Pang et al., 2013). It
also functions to stabilize topoisomerase II, which is involved in relieving DNA supercoils
formed during the unwinding of DNA, preventing it from being resealed. Like cytarabine,
26
daunorubicin produces DNA breaks, triggering an apoptotic response in the cell (Al-Aamri et al.,
2019). The M3 subtype (APL) is treated exclusively with all-trans retinoic acid (ATRA) in
conjunction with arsenic trioxide (ATO). ATRA degrades the PML-RARA fusion protein that
drives APL, which restores normal retinoic acid-mediated differentiation, leading to CR rates of
97%, and cure rates of over 90% (Khanna-Gupta & Berliner, 2007). ATO effectively targets
PML-RARA positive leukemic stem cells, leading to enhanced curative effects (Abaza et al.,
2017; Betz & Hess, 2010b; Tallman et al., 2019; Zheng et al., 2007).
Post-remission consolidation therapy is aimed at eliminating residual leukemic cells that
may lead to disease recurrence in the form of refractory or relapsed AML. Refractory disease
exists when the initial induction therapy fails to produce a state of remission with <5% blast cells
in the bone marrow. More common is AML relapse where although patients may achieve CR
from induction therapy, the disease reappears in a few months or after several years. The
mechanisms of relapse remain unclear, however there is evidence to suggest that specific
leukemic clones or sub-clones that are present at diagnosis, persist and undergo expansion post
initial therapy (Shlush et al., 2017). The extent of “consolidation therapy” is largely guided by a
patient’s prognostic factors including cytogenetics and molecular markers. For example, for
good prognosis disease i.e. inv(16), t(8;21) and t(15;17) (APL), consolidation therapy involves 3-
5 rounds of intensive high dose cytarabine containing chemotherapy. Cases with adverse
prognosis and/or having a high risk for relapse (i.e. high-risk cytogenetics, MDS, prior
chemotherapy) are recommended to undergo hematopoietic stem cell transplantation (HSCT)
(Sellar, Goldstone, & Lazarus, 2011). HSCT involves the transplantation of multipotent HSCs,
typically isolated from PB, BM or umbilical cord blood, into the patient. For patients with AML,
cells typically come from an unrelated donor or a matched sibling (allogeneic) (Felfly & Haddad,
27
2014). The procedure involves first ablating the patient’s BM and immune system using high-
dose chemotherapy and/or irradiation. While stem cell transplantation can prove to be curative, it
is a relatively high-risk procedure. Major complications of allogeneic transplants include
infection and graft-versus-host disease (GVHD) due to transplanted cells recognizing normal
host tissues (i.e. of the skin, gut and liver) as being foreign, causing significant tissue damage,
which in some cases can lead to death (Goker, Haznedaroglu, & Chao, 2001)
.
28
1.3. HEMATOPOIETIC AND LEUKEMIC STEM CELLS
Mechanisms underlying hematopoiesis and leukemogenesis have largely been elucidated
using in-vitro and in-vivo experimental models. Hematopoietic stem and progenitor cell
populations can be readily identified in in-vitro cell culture assays which assess the self-renewal
and multi-lineage differentiation properties of progenitor cells through their colony formation
ability.
1.3.1. In-Vitro Hematopoietic and Leukemic Cell Colony Formation Assays
The two main in-vitro assays used in the functional interrogation of HSCs are the colony
forming cell (CFC) and the long-term culture (LTC) assays (Dexter, Allen, & Lajtha, 1977;
Gartner & Kaplan, 1980a). The CFC assay involves plating single cells in a semi-solid medium
such as soft agar or methylcellulose with cytokine supplementation, and observing colony
formation over a period of 9-14 days. A single colony is scored when it has approximately 50
cells or more; the differentiation potential of the cell is inferred by the observed nature of the
cells in the colony. In these assays, the most primitive hematopoietic progenitor cell is the colony
forming unit (CFU), with different identifiable CFUs that each give rise to a distinct
hematopoietic lineage i.e. CFU-E (colony forming unit-erythroid), CFU-G (colony forming unit-
granulocyte, CFU-GM (colony forming unit-granulocyte-macrophage), BFU-E (burst forming
unit-erythroid), CFU-M (colony forming unit-macrophage) and CFU-GEMM (colony forming
unit-granulocyte, erythrocyte, macrophage, megakaryocyte) (Carow, Hangoc, & Broxmeyer,
1993).
LTC assays are co-culture assays that involve the use of stromal cells as a feeder layer,
along with growth factor/cytokine supplementation to help support the growth, differentiation
29
and long-term maintenance of primitive hematopoietic progenitors in culture (Gartner & Kaplan,
1980b; M. Liu, Miller, & Eaves, 2013). The assays assess the ability of hematopoietic
progenitors to give rise to clonogenic myeloid progenitors and mature granulocytes and
macrophages that can be sustained for a period of 5-7 weeks or longer, under optimal culture
conditions. LTC assays to assess lymphoid and NK cell development have also been developed
(Miller, Verfaillie, & McGlave, 1992). The hematopoietic progenitors capable of initiating and
sustaining myelopoiesis over long-term periods are called long-term culture-initiating cells
(LTC-IC) and can be identified and quantified in the LTC assay (Sutherland, Lansdorp,
Henkelman, Eaves, & Eaves, 1990). CFUs are the progeny of LTC-ICs and can be detected at
approximately from a week or so to 5 weeks in semisolid assays.
1.3.2. In-Vivo Hematopoietic and Leukemic Cell Assays
The murine model has served as a useful tool for transplantation and re-population assays
in which single cells or single populations of hematopoietic or leukemic cells can be examined
for long-term hematopoietic re-constitution ability. In the 1960s, Drs. Till and McCulloch first
reported the ability of a specific population of cells from blood-forming tissue to form colonies
in the spleen of irradiated mice (Becker, McCulloch, & Till, 1963). These macroscopic colonies
were observed to contain cells along the granulocytic, erythroid and megakaryocytic lineages,
indicating clonal differentiation and expansion from a single cell population.
While the syngeneic system was very useful for studying the nature of murine
hematopoiesis and leukemia, it was not possible to evaluate human cells due to rapid rejection by
the mouse immune system. The non-obese diabetic/severe combined immunodeficient
(NOD/SCID) mouse model overcomes this problem, in part, and has been used extensively in
30
human xenograft models. NOD/SCID mice harbour defects in both adaptive and innate immune
responses, with deficiencies in functional T, B and NK cells, which facilitates engraftment of
human cells in the murine background (Greiner et al., 1995; Larochelle et al., 1996; Shultz et al.,
2010). Through the use of such animals, the structure of the hematopoietic system first identified
for murine cells, has been confirmed for human hematopoiesis.
It is important to note that mouse models are in fact just that, models, in the study of
human cellular and molecular interactions. This is because there are significantly limited cross-
species reactivities between many human and mouse proteins. Many human growth factors do
not act on counterpart mouse receptors and vice versa, despite high protein homology among
some of the factors. Table 1-5 outlines a compiled list of protein ligands with known cross-
species receptor reactivity, along with % homology between the mouse and human forms of the
proteins. Of the dozen or so ligands listed, the overwhelming majority of mouse ligands (all
except SCF) do not act on the counterpart human receptor, despite sequence similarities of up to
91% (i.e. for HGF) between some of the human and mouse ligands. Interestingly in comparison,
about half a dozen of the listed human factors are actually active on mouse receptors, which may
suggest that placement of human cells in mice may actually induce changes in the mouse as
opposed to the other way around, which could have implications for the study model. These
considerations must be taken into account when working with animal models in general.
31
Table 1-5. Cross-reactivity of hematopoietic and stromal cell growth
factors and cytokines between mouse and human.
Courtesy Laurie Ailles - A.L. Allan (ed.), Cancer Stem Cells in Solid Tumors,
Stem Cell Biology and Regenerative Medicine. DOI 10.1007/978-1-61779-
246-5_24
32
Similar to hematopoiesis, leukemias like AML are also clonal in nature and organized into
a hierarchy with a leukemic stem cell (LSC) residing at its apex (Bonnet & Dick, 1997; Buick,
Minden, & McCulloch, 1979). McCulloch and colleagues first postulated that as with normal
hematopoiesis, leukemogenesis also consisted of multi-lineage differentiation and clonal
expansion stemming from discrete pools of stem and progenitor cells (McCulloch, 1983). This
was demonstrated by the fact that AML blasts have limited proliferative capacity, with only
about 1% of leukemic cells being capable of forming colonies in methylcellulose i.e. AML-
CFUs. Moreover, leukemias also appeared to retain many of the same growth and differentiation
properties evident in hematopoiesis. Moreover, John Dick’s group identified a rare population of
cells (1 per 1X106 leukemic blasts), termed human SCID leukemia-initiating cells (SL-IC), that
had the ability to re-populate NOD/SCID mice to propagate and re-capitulate AML in xenograft
transplants (Lapidot et al., 1994). These SL-ICs produced leukemic grafts that were
representative of the original patient’s disease with identical blast morphology and dissemination
patterns, and were thus deemed to be the cell of origin/LSC in the model. Furthermore, it has
been shown that there are several classes of LSCs, indicating the existence of a cellular hierarchy
in the disease (Hope, Jin, & Dick, 2004). For example, SL-ICs have been found to be enriched in
the CD34+/CD38- fraction, while AML-CFUs are found in the CD34+/CD38+ fraction, indicating
that the leukemic clone is organized as a hierarchy with the SL-IC as the cell of origin that gives
rise to AML-CFUs and blasts.
33
1.3.3. Hematopoietic Cell Surface Markers
Expression of cell surface markers has played an important role in characterizing the cells
of the hematopoietic system, and in particular, the identification and isolation of HSCs, LSCs
and their progenitors. These, in conjunction with functional assays, helps to confirm the
biological identity and activity of isolated cell fractions containing putative HSCs or progenitor
cells.
CD34
Cluster of differentiation 34 (CD34) is a transmembrane phosphoglycoprotein that was
originally discovered as a cell surface antigen on primitive hematopoietic cells (Batinić et al.,
1989; Civin et al., 1984; Tindle et al., 1985). Although largely expressed on hematopoietic cells,
CD34 is also expressed on several other cell types such as endothelial cells (in the BM and in
vascular tissue), mesenchymal stem cells, interstitial cells, muscle satellite cells and cells of the
placenta (Sidney, Branch, Dunphy, Dua, & Hopkinson, 2014). While its exact function is not
clearly known, CD34 is an important adhesion molecule as it helps HSCs to home to the BM,
and also aids T-cell entry into lymph nodes. It may also be involved in chemokine-mediated
migration of eosinophils and dendritic cells. In disease, CD34 is found to be expressed on the
malignant cells of pre B-ALL, AML, gastrointestinal stromal tumors, Kaposi’s sarcoma,
liposarcoma, neurofibromas, meningiomas, papillary thyroid carcinomas and alveolar soft part
sarcoma among others. In most of these cancers including AML, high CD34 levels are generally
associated with poor clinical outcome (Vergez et al., 2011).
34
c-Kit
c-Kit (CD117) is a receptor tyrosine kinase that is the cellular homolog of the feline
sarcoma viral oncogene v-kit (Yarden et al., 1987). It is also known as the proto-oncogene Kit or
the Stem Cell Growth Factor Receptor (SCFR). c-Kit is mainly expressed on the surface of
primitive hematopoietic cells i.e. stem and progenitor cells, with predominant expression on
myeloid progenitors. It is a type III receptor tyrosine kinase that binds to its ligand, Kit ligand,
which is also known as stem cell factor (SCF) (Edling & Hallberg, 2007). c-Kit is found to be
overexpressed in some cancers and activating mutations (typically in exon 11 or exon 17) are
commonly found in gastrointestinal stromal tumors, testicular seminoma, melanoma and AML
(Ashman & Griffith, 2013).
CD38
CD38 is a cell surface glycoprotein found to be mainly expressed on the surface of immune
cells including T-cells, B-cells and natural killer cells. It is also known as cyclic ADP ribose
hydrolase, a multifunctional ectoenzyme that catalyzes the synthesis and hydrolysis of cyclic
ADP ribose (Jackson & Bell, 1990). It is involved in signal transduction, calcium signaling and
cell adhesion. CD38 holds prognostic value in leukemias and is associated with shorter time to
progression in chronic lymphocytic leukemia (CLL) (Burgler, 2015). CD38 expression may be
related to cell activation, as expression levels increase when HSCs are activated. Case in point,
CD38 levels have been shown to fluctuate on CD34+ LT-HSCs, seemingly in accordance to cell
cycle state (McKenzie, Gan, Doedens, & Dick, 2007).
35
1.4. THE BONE MARROW NICHE
The bone marrow (BM) is the principal site of hematopoiesis as well as osteogenesis, or
bone formation. Sites of hematopoiesis in the BM are niche microenvironments composed of
complexes of cells, distinct spatial/anatomical regions, temperature and oxygen gradients,
extracellular matrix and signaling molecules. The oxygen content in the BM is quite low, ranging
from 0.2 – 1%, making it a relatively hypoxic environment. There are a multitude of different
cell types within the BM which include hematopoietic, osteogenic (i.e. osteocytes, osteoblasts,
osteoclasts), adipocytes, perivascular, reticular fibroblasts, neuronal-associated glial cells and
BM stromal cells (Chan et al., 2013; Gimble, Robinson, Wu, & Kelly, 1996; Méndez-Ferrer,
Michurina, Ferraro, Mazloom, MacArthur, Lira, Scadden, Mag’Ayan, et al., 2010; Sacchetti et
al., 2007). Osteocytes and osteoblasts, the latter of which are involved in bone formation and
mineral deposition, are derived from osteoprogenitor cells (which arise from mesenchymal stem
cells), while osteoclasts which resorb and remodel bone, derive from hematopoietic myeloid
cells (Nijweide, Burger, & Feyen, 2017; Teitelbaum, 2000).
In the human adult, hematopoiesis specifically occurs in the BM of the femur, ribs,
vertebrae and pelvic bones as these bones contain ‘red marrow’ or ‘myeloid tissue’. BM tissue is
composed of three main types of cells: hematopoietic, supporting stromal and adipose tissue
cells. In humans, marrow tissue exists as either ‘red’ or ‘yellow’ marrow, depending on the
proportion of hematopoietic (red) vs. adipocytes or fat cells (yellow) (Poulton, Murphy, Duerk,
Chapek, & Feiglin, 1993).
36
1.4.1. Cells and Factors in the Bone Marrow Niche
The BM is divided into two main compartments: the hematopoietic (or parenchymal) cell
component called the parenchyma, and a non-hematopoietic component called the stroma. By
definition, ‘stroma’ means ‘covering’, ‘bed’ or ‘layer’ in Greek, which points to a supportive and
protective role for it. The stroma, in biological systems, is largely made up of connective tissue
to provide structural and connective supports in tissues and organs. The stroma is composed of
osteogenic cells, adipocytes, nerves, vasculature, ducts and stromal cells such as fibroblasts,
mesenchymal cells (MSC) and endothelial cells. Fibroblasts are large, flat, thin (spindle-shaped)
cells that help establish and maintain the structural integrity and framework of tissues, and also
play critical roles in wound healing and tissue repair (Hans-Georg Kopp, Avecilla, Hooper, &
Rafii, 2005; Silzle, Randolph, Kreutz, & Kunz-Schughart, 2004). They produce collagen and
extracellular matrix protein precursors, namely glycoproteins and reticular and elastic fibres, in
addition to a number of important cytokines and growth factors. Fibroblasts have typically been
difficult to identify definitively, with identification largely based on their morphological spindle
shape, along with positive staining for the mesenchymal marker vimentin, combined with
negative staining for epithelial or other mesenchymal cell types such as muscle cells, astrocytes
or hematopoietic cells (Botstein et al., 2002). MSCs, also known as marrow stromal cells, are
multipotent stromal cells derived from the mesoderm that have the capacity to differentiate into
three main cell types: osteoblasts, adipocytes and chondrocytes which make up bone, adipose
and connective tissue, respectively (Méndez-Ferrer, Michurina, Ferraro, Mazloom, MacArthur,
Lira, Scadden, Ma’ayan, et al., 2010; Schroeder, Geyh, Germing, & Haas, 2016). Collectively,
BM stromal cells produce important adhesion, growth and signaling molecules that regulate key
BM processes including hematopoiesis.
37
The physical architecture of the BM is organized into spatial areas or zones with
differences in cell and tissue composition. Long bones primarily contain two types of bone
tissue: spongy and compact. Spongy, also known as trabecular or cancellous, bone is soft,
loosely organized, porous, highly vascular and contains red BM i.e. hematopoietic cells. It is
located in the trabecular regions, or the ends, of long bone, often near joints. Compact, or
cortical, bone tissue is more dense and forms the hard outer layers of the bone (except at joints).
Bones have an outer membranous layer called the periosteum and within the bone, there is a
layer called the endosteum that separates compact bone from spongy bone (Morrison & Scadden,
2014a; Scadden, 2006). The vasculature within the BM is sinusoidal in that the endothelial cells
covering the vessels are not covered by a layer of connective tissue and are in direct contact with
parenchymal cells (H.-G. Kopp, 2005). HSCs have been shown to preferentially localize to two
predominant niches within the BM: an ‘endosteal or osteoblastic’ niche where cells localize to
endosteal regions lined with osteoblasts within trabecular bone and a ‘perivascular niche’ where
cells localize adjacent to sinusoidal blood vessels (Figure 1.2) (Colmone et al., 2008; Guezguez
et al., 2013; Morrison & Scadden, 2014b). As HSCs differentiate, the niches that developing
cells occupy can change. For example it has been shown that while some HSCs predominantly
reside in perivascular niches, lymphoid progenitors appear to occupy endosteal niches (Ding &
Morrison, 2013).
Osteoblasts produce growth factors and cytokines involved in cellular growth and adhesion
such as G-CSF, GM-CSF, IL-1, IL-6 and TGF-β. These cells also produce the key adhesion
factor and chemokine, stromal-derived factor-1 (SDF-1), also known as CXC-chemokine ligand
12 (CXCL12), which acts on the CXCR4 receptor found on HSCs (Calvi et al., 2003; Galán-
Díez & Kousteni, 2018; Sugiyama, Kohara, Noda, & Nagasawa, 2006). CXCR4 antagonists
38
induce the mobilization of HSCs into the bloodstream, as a result of detachment and release from
the BM space (Broxmeyer et al., 2005). Osteoblasts also produce vascular and angiogenic
growth factors such as Angiopoietin-1 (Ang-1) which is thought to maintain HSC quiescence by
acting on the Tie2 receptor expressed on HSCs; activation of this pathway is involved in cell
cycle arrest and in maintaining stemness (Arai et al., 2004).
39
Figure 1.2. Architecture of the bone marrow niche.
The BM contains various zones that contain distinct supporting BM stromal cells. HSCs as well
as LSCs typically reside within the perivascular and endosteal regions. Figure adapted from
(Morrison & Scadden, 2014a).
40
1.4.2. Hematopoietic and Leukemic Cells in the Bone Marrow Niche
The BM niche is also important for the proliferation and maintenance of leukemic cells and
provides protection against toxic agents including chemotherapeutic drugs. It also maintains the
dormancy and quiescence of both HSCs and LSCs. This niche is a dynamically evolving
microenvironment as it responds to biochemical perturbations, and can become altered itself. For
example, it has been shown that osteoblasts with activating mutations in β-catenin lead to
enhanced HSC proliferation and leukemogenesis in mouse models (Kode et al., 2014).
Moreover, impaired activity of the hematopoietic transcription factor Ikaros in pre-B-cells has
been shown to lead to a stroma-dependent leukemia (Joshi et al., 2014). This underscores the
importance of components of the niche environment as functionally dynamic players in BM
homeostasis. Moreover, leukemic cells often share/compete for the same niche environments as
their normal hematopoietic cell counterparts. It has been shown that in competitive repopulation
assays, normal HSPCs in some instances can actually out-compete LSCs (Boyd et al., 2014).
This highlights the dynamic relationship that exists between normal hematopoiesis and
leukemogenesis which reside in the same microenvironments, competing for dominance.
Leukemic stem/initiating cells
The notion that stem cells may exist in cancers and be central to carcinogenic processes
emerged at around the same time normal stem cells were being studied. Central to the theory was
that similar to hematopoiesis, leukemias, are also clonal in nature and organized into a hierarchy
with a leukemic stem cell (LSC) residing at its apex (Bonnet & Dick, 1997). McCulloch and
colleagues first postulated that like normal hematopoiesis, leukemogenesis also consisted of
multi-lineage differentiation and clonal expansions stemming from discrete pools of stem and
41
progenitor cells (McCulloch, 1983). This is supported by the fact that the majority of AML blasts
have limited proliferative capacity, with only about 1% of leukemic cells being clonogenic
progenitors i.e. AML-CFUs. John Dick’s group identified in a subset of AML patients, a rare
population of cells (1 per 1X10^6 leukemic blasts), termed human SCID leukemia-initiating cells
(SL-IC). These cells had the ability to re-populate NOD/SCID mice to propagate and re-
capitulate AML in xenograft transplants (Lapidot et al., 1994). The leukemic grafts developing
from SL-IC were representative of the original patient’s disease, having identical blast
morphology and dissemination patterns, and were thus deemed to be the cell of origin/LSC in the
model. Moreover, there are distinct LSC classes, demonstrated by the fact that SL-ICs are found
to be enriched in the CD34+/CD38- fraction, while AML-CFUs are found in the CD34+/CD38+
fraction (Hope et al., 2004). This indicates that the leukemic clone is organized as a hierarchy
with the SL-IC as the cell of origin that gives rise to AML-CFUs and blasts. Furthermore,
through clonal tracking studies, distinct classes of SL-ICs were observed: short-term, long-term
and quiescent.
Clonal hematopoiesis refers to the process whereby distinct pools of stem or progenitor
cells acquire one or more somatic mutations, and undergo clonal expansion to become a
dominant clone that can give rise to disease (Bowman, Busque, & Levine, 2018; Greaves &
Maley, 2012). In essence, somatic mutations acquired throughout an individual’s life may be
predictive of disease onset later on in life. In what is termed age-related clonal hematopoiesis,
healthy individuals are seen to carry recurrent somatic mutations in specific genes associated
with hematological malignancies, namely mutations in the key epigenetic regulators DNMT3A,
TET2 and AXSL1. The frequency of these mutations increases with age and is associated with an
42
increased risk for hematological cancer and possibly cardiovascular disease as well (Jaiswal et
al., 2014). The mechanism for the latter is an area of intense investigation.
The clonal nature of hematopoiesis and leukemia begs the question as to how these clones
evolve and potentially interact with each other. Moreover, in leukemia, the question is which
clones acquire transforming mutations to become malignant, and how and when they evolve in
time and space to become the dominant clone. Tracing the evolutionary origins of distinct
disease-driving hematopoietic clones led to the identification of pre-leukemic HSCs in AML
patients. Employing deep-sequencing methods and lineage tracing, the investigators found that
HSCs from AML patients harbouring a DNMT3A mutation displayed enhanced multi-lineage
repopulation in xenografts compared to HSCs without the mutation (Jan et al., 2012; Liran I.
Shlush, Sasan Zandi, Amanda Mitchell, Weihsu Claire Chen, 2014). This DNMT3Amut
harbouring clone was deemed to be a pre-leukemic HSC clone. Pre-leukemic HSCs were also
found in remission samples, suggesting that they are able to survive chemotherapy. It therefore
appears that DNMT3A mutations occur early on in leukemogenesis, likely in HSCs, leading to
the clonal expansion of this pool of pre-leukemic HSCs that may eventually give rise to AML.
LSC clones thus evolve early on in the route to malignancy, survive therapy, and persist to give
rise to relapse. To support the latter, Shlush et al. reported that there are distinct LSC clones and
subclones that are present both at diagnosis and also found later in AML relapse (Shlush et al.,
2017). This suggests that pre-leukemic and leukemic stem cells are highly potent and persistent,
as they drive and maintain disease throughout all stages of leukemogenesis.
43
1.5. BONE MARROW STROMAL CELL ASSAYS
Classical assays used to characterize hematopoietic and leukemic cells in-vitro and ex-
vivo such as the LTC-IC assay, largely make use of BM stromal cells as a supportive feeder layer
in a co-culture system for the long-term growth of cells in culture. The murine MS-5 stromal cell
line has been widely used in hematopoietic cell co-culture assays due to the ease in their growth
and maintenance (Itoh et al., 1989). MS-5 cells were initially derived from adherent layers of
Dexter-type murine long-term marrow cultures (used to study murine hematopoiesis) as one of 7
cell lines. From these 7 cell lines, MS-5 cells were found to be the most active in supporting the
growth of HSCs (CFU-S and CFU-GM) for more than 2 months in-vitro, without the addition of
any exogenous factors (Itoh et al., 1989; Varma, el-Awar, Palsson, Emerson, & Clarke, 1992).
MS-5 cells grow as fibroblast-like cells, adhere well to plastic surfaces, typically grow in a
monolayer and produce a number of hematopoietic growth factors, making them ideal for the
support of hematopoiesis. They were also found to support the proliferation and survival of
primitive CD34+/CD38- HSCs in both short-term (5-8 weeks) and long-term (8-10 weeks) co-
cultures (Issaad, Croisille, Katz, Vainchenker, & Coulombel, 1993). MS-5 cells synthesize
extracellular matrix proteins such as fibronectin, laminin and collagen type I. In addition, these
cells produce important hematopoietic growth factors including IL-6, IL-3, GM-CSF and SCF.
Interestingly, despite the fact that many murine growth factors and cytokines do not act on their
counterpart human receptors, murine MS-5 cells are still able to effectively support human
hematopoiesis without any human growth factor supplementation. While there are a few factors
that display species cross-reactivity, namely SCF, CXCL12 and GM-CSF, their involvement is
not enough to explain the robust support that MS-5 cells provide human cells in long-term
cultures (Kobari, Dubart, Le Pesteur, Vainchenker, & Sainteny, 1995). The exact mechanisms
44
underlying the efficacy of MS-5 stromal cells in the support of human hematopoietic cells
remains unclear, but are likely attributable to unidentified factors that MS-5 cells produce in
small amounts, or to extracellular matrix protein products that may lend both structural and
biochemical support. Human stromal cell lines such as HS-5 and HS-27 can also be used in co-
culture assays but they are not as efficient in supporting hematopoietic cells in long-term assays.
Long-term hematopoietic and leukemic cell assays have certain defining features
associated with the growth of specific cell populations. For example, the culture of CD34
positive AML cells on MS-5 stromal cells leads to their long-term expansion, which can be
maintained for up to 24 weeks (van Gosliga et al., 2007) for some samples. After a period of 1-2
weeks, these cells form ‘cobblestone-area forming cells’ (CAFC) which are clusters of cells that
burrow and settle between stromal cells and the substratum (i.e. the plastic dish). CAFCs can be
visualized using phase contrast microscopy under which they appear as dull, ‘cobblestone’-like
areas (Ploemacher, van der Sluijs, Voerman, & Brons, 1989). CAFCs arise from a CD34+
progenitor pool that is present in both normal hematopoietic and leukemic cell populations.
CAFCs can be re-plated to give secondary and tertiary CAFCs, providing evidence for the
existence of a pool of pluripotent progenitor cells with self-renewal capacity and long-term
marrow repopulating ability (Ploemacher, van der Sluijs, van Beurden, Baert, & Chan, 1991).
45
1.6. COLONY STIMULATING FACTOR 1 RECEPTOR (CSF1R)
The colony stimulating factor 1 receptor (CSF1R, c-FMS, CD115) is a class III tyrosine
kinase receptor, belonging to the same family as the Platelet-Derived Growth Factor (PDGF), c-
Kit and Fms-like tyrosine kinase 3 (FLT-3) receptors (Françoise Birg, Carbuccia, Rosnet, &
Birnbaumt, 1994; Casteran, Beslu, Lecocq, Gomez, & Dubreuil, 1998). It is involved in
modulating innate immunity, inflammation as well as diseases including cancers. CSF1R is
expressed on the surface of mononuclear phagocytes, namely monocytes, macrophages and
dendritic cells and their precursors to direct their growth, survival and differentiation (Auffray,
Sieweke, & Geissmann, 2009; Sasmono et al., 2003). CSF1R is involved in a number of
physiological processes including osteoclastogenesis as related to bone and tooth development,
immune responses, mammary gland and placental development during pregnancy and microglial
cell development in the brain. During immune responses and inflammation, CSF1R is involved
in the activation of monocytes and macrophages to promote their cytotoxic, phagocytotic and
chemotactic functions through release of cytokines and chemokines (Raivich et al., 1998; Y.
Wang et al., 2012).
1.6.1. CSF1R Structure
In humans, CSF1R is encoded by the c-fms proto-oncogene, the human homologue of the
v-fms oncogene from the Susan McDonough strain of the feline sarcoma virus (Garceau et al.,
2010; Carl W. Rettenmier, Chen, Roussel, & Sherr, 1985; Charles J. Sherr et al., 1985). The gene
is located on the long arm of chromosome 5 (5q32) and is 60 kb in length with 22 exons, 21 of
which are coding exons. The mature protein product is heavily glycosylated, 972 amino acids in
length and has a molecular weight of approximately 150-165 kDa. It is a single type I pass
46
membrane protein comprised of a 512 amino acid extracellular portion containing five
immunoglobulin (Ig)-like repeat domains (D1 - D5), a single transmembrane segment, a
juxtamembrane domain that lies between the transmembrane domain and cytoplasmic domain,
and a cytoplasmic domain containing an ATP binding/activation loop, kinase insert region
(resulting in a split kinase domain), the main kinase domain and an auto-inhibitory C-terminal
tail (Figure 1.3) (Hamilton & Achuthan, 2013; Charles J. Sherr et al., 1985). In its inactive auto-
inhibited state, CSF1R is stabilized by its juxtamembrane domain, which binds to a site adjacent
to the ATP binding pocket in the kinase domain. This inhibits the activation loop from adopting
an active conformation, maintaining it in an inactive, locked state to prevent binding of ATP and
substrates (Walter et al., 2007).
47
Figure 1.3. Structure of CSF1R.
CSF1R contains an extracellular domain with five immunoglobulin loops (D1 – D5), a
juxtamembrane domain, a transmembrane domain, a split kinase domain with a kinase insert,
and a cytoplasmic tail that can be autoinhibitory.
48
Colony stimulating factor 1 (CSF1) and IL-34 are the two known ligands of CSF1R.
CSF1 binds to the first three extracellular domains (D1 - D3) of CSF1R, resulting in receptor
dimerization through interaction of the D4 and D5 domains (Figure 1.4). Upon ligand binding,
oligomerization of the receptor chains brings the kinase domains of the two chains into close
proximity, allowing for the auto and cross phosphorylation of several tyrosine residues within the
domains. These residues serve as docking sites for various cytoplasmic proteins, namely SH2
domain-containing proteins such as Grb2, phosphatidylinositide 3-kinase (PI3K) and Src family
kinases. Binding of these proteins triggers activation of signal transduction pathways involved in
cellular growth, proliferation and survival. Following CSF1 stimulation, activated CSF1R can
lead to various cellular events including actin skeleton reorganization, membrane ruffling,
immediate cytoplasmic alkalinization, increased hexose transport and induction of early response
genes such as c-fos and c-jun that participate in regulation of cellular metabolism and growth
(Yu et al., 2008); discussed in more detail below.
49
Figure 1.4. CSF1 ligand binding to CSF1R.
Homodimeric CSF1 binds to the D1 – D3 loops of the extracellular domain of CSF1R. This
leads to receptor dimerization, resulting in the autophosphorylation of tyrosine residues in
the juxtamembrane, kinase insert and kinase domains of the receptor.
50
1.6.2. CSF1R Intracellular Signaling
Interaction and binding of signaling molecules to phosphorylated tyrosine residues on
CSF1R leads to activation of key growth and survival pathways, the predominant of which
include the PI3K/Akt, MAPK/ERK and JAK/STAT pathways (Figure 1.5). CSF1R activation
leads to tyrosine phosphorylation of PI3K which is a class I PI3K heterodimer containing p85
regulatory and p110 catalytic (PIK3CA) subunits (Bunney and Katan, 2010). PI3K converts
phosphatidylinositol (4,5) bisphosphate (PI(4,5)P2) into phosphatidylinositol (3,4,5)
trisphosphate (PI(3,4,5)P3), which recruits Akt and phosphoinositol-dependent kinase 1 (PDK1)
to the cell membrane via interaction with their pleckstrin homology (PH) domains. PDK1
phosphorylates Akt on one of its residues, Thr308, with full activation requiring phosphorylation
of another residue, Ser473, which can be mediated by other kinases including PDK2, DNA
protein-dependent kinase (DNA-PK), mammalian or mechanistic target of rapamycin complex
(mTORC) and integrin-linked kinase (ILK) (Cantley, 2002; Hemmings & Restuccia, 2012;
Osaki, Oshimura, & Ito, 2004). Akt functions to regulate pathways involved in cell proliferation,
differentiation, apoptosis and survival through transcriptional level control of gene expression, or
through direct phosphorylation of effector molecules including transcription factors. Akt
activates mTOR through phosphorylation-mediated inhibition of its negative regulator, the
tuberous sclerosis (TSC) protein complex, TSC1/2, which is made up of hamartin (TSC1) and
tuberin (TSC2). TSC2 specifically has a GTPase Activating Protein (GAP) domain which
downregulates the GTPase activity of the small GTPase Rheb, which when active in its GTP-
bound form, is an activator of the mTORC1 complex (which consists of mTOR, which is the
catalytic subunit of mTORC complexes, regulatory-associated protein of TOR (Raptor), DEP
domain-containing mTOR-interacting protein (DEPTOR), mammalian lethal with SEC13 protein
51
8 (MLST8) and PRAS40). Activated mTOR phosphorylates target effectors involved in protein
synthesis, namely p70S6 Kinase (p70S6K), which phosphorylates the S6 ribosomal protein, and
the eukaryotic translation initiation factor 4E (eIF4E)-binding protein 1 (4E-BP1) (Manning &
Cantley, 2007). Akt also inhibits Glycogen Synthase Kinase-3 (GSK-3), leading to inhibition of
glycogen synthesis. In its pro-survival function, Akt both activates anti-apoptotic, and inhibits
apoptotic effectors. Some of the transcriptional targets of Akt include the Forkhead Box (FOX)O
family of transcription factors (through phosphorylation) and pro-survival genes. Akt can cause
degradation of IκB which binds to NF-κB, causing NF-κB translocation to the nucleus where it
can promote expression of caspase inhibitors such as Bcl-xL (Vanhaesebroeck & Alessi,
2000). Akt has been shown to up-regulate expression of the anti-apoptotic protein Bcl-2 through
phosphorylation of the cAMP response element binding protein (CREB), which leads to
recruitment of CREB-binding protein (CBP) to the promoter of Bcl-2 (Pugazhenthit et al., 2000;
Ross & Teitelbaum, 2005). Akt itself can translocate from the cytoplasm to the nucleus in
various cell types to elicit its transcriptional level control through interaction with various
nuclear proteins including RNA polymerase II, as well as β-actin (Carling, 2017; Coa et al.,
2019).
CSF1R also induces phosphorylation of the cytoplasmic Tyk2 tyrosine kinase belonging
to the family of JAK kinases, leading to induction of the signal transducers and activators of
transcription (STAT) protein transcription factors. CSF1 induced CSF1R activation can also lead
to Ras activation. The Ras family of GTPases are signaling proteins anchored within the cell
membrane from where they transduce signals into the cell. Ras GTPase activity is activated by
Ras guanine nucleotide exchange factors (GEF) that exchange GDP for GTP to activate the
protein. SOS is a GEF that interacts with the adaptor proteins Grb2 and Shc. Grb2 has been
52
shown to bind to the phosphorylated Y699 residue in the kinase domain of activated CSF1R.
Activated Ras can then activate MAPK/ERK signaling. ERK1 can also bind directly to several
phosphotyrosine residues in activated CSF1R. In macrophages, it has been shown that the
binding and activation of multiple signal transducers and pathways to CSF1R including Src
kinases, Akt, ERK and PLC is required for macrophage proliferation (Takeshita et al., 2007).
The autophosphorylation of specific tyrosine residues (of which there are 6-8) in the
cytoplasmic kinase domain, as well as the kinase insert region (containing Y699, Y708 and
Y723), of CSF1R leads to the binding of cytoplasmic proteins to these residues resulting in their
activation, leading to the regulation of key cellular events. The binding proteins targeted to a
number of these tyrosine sites have been elucidated. The Y809 site in the activation loop of the
receptor (Y807 in mouse) has been shown to promote differentiation in FDC-P1 myeloid cells by
acting as a key regulator of a critical switch between growth and differentiation signals
(Rohrschneider et al., 1997). Moreover ectopic expression of a substitution mutant of Y809,
Y809F, resulted in a G1 cell cycle arrest and impaired production of c-myc mRNA in ligand-
stimulated NIH3T3 murine fibroblasts, with cells being mitogenically inactive (Roussel & Sherr,
1989; Roussel, Shurtleff, Downing, & Sherr, 1990). The mitogenic activity of cells could be
rescued with c-Myc overexpression in the cells, demonstrating that c-Myc is a downstream target
of CSF1R induced in response to CSF1 ligand binding. In a CSF1R-deficient murine BM
macrophage cell line (MacCsf1r-/-), ectopic expression of wild-type CSF1R with mutations
induced in the eight different tyrosine residues revealed that the Y559F mutation in the
juxtamembrane domain and the Y807F mutation in the activation loop led to severe impairments
in proliferation and differentiation, while the Y706, Y721F, and Y974F mutations led to changes
in morphological responses, with Y706F increasing differentiation in the cells (Yu et al., 2008).
53
This demonstrates the specific phenotypic functionalities of individual tyrosine phosphorylated
residues within the kinase domain of CSF1R.
Tyrosine autophosphorylation allows for the binding of cytoplasmic proteins with SH2
domains. In Rat-2 fibroblasts transduced with murine c-fms, Y697 (Y699 in human) was
identified as a binding site for the adaptor protein Grb2 upon CSF1 stimulation. Activation of
PI3K activity in response to CSF1 has been reported, with the Y721 having been shown to be the
binding site for the p85 regulatory subunit in Rat-2 fibroblasts. In the juxtamembrane domain of
activated human CSF1R, phosphorylated Y561 (Y559 murine) may be a binding site for Src
family members. The E3 ubiquitin-protein ligase and proto-oncogene c-Cbl (murine), which is
found to be mutated in some AML cases, is also a CSF1R binding target that induces
ubiquitination of activated CSF1R by associating with tyrosine-phosphorylated Shc at the plasma
membrane. This may also involve association with PI3K to form a complex leading to receptor
ubiquitination and degradation. STAT transcription factors are also targets of CSF1-induced
CSF1R activation. Murine Y706, and human 708 of CSF1R, has been shown to be necessary for
the binding of STAT1. STAT3, STAT5 and STAT5a are also induced in response to CSF1 but
do not bind to the same residues as bound by STAT1 (Price, Choi, Rosenberg, & Stanley, 1992;
Reedijk et al., 1992).
CSF1R activity is downregulated through dephosphorylation of the receptor and its
downstream effectors by protein phosphatases such as INPP5D/SHIP-1, as well as through rapid
internalization of the activated receptor (E. Richard Stanley & Chitu, 2014).
54
Figure 1.5. CSF1R activation of intracellular signal transduction pathways.
Upon activation, CSF1R stimulates the activation of a number of intracellular signal transduction
pathways involved in regulation of cell growth, proliferation, survival, apoptosis, differentiation
and metabolism.
55
1.6.3. CSF1R in Disease
In disease, CSF1R is found to be over-expressed or mutated in several neurodegenerative
disorders. High CSF1R expression is found on microglia i.e. the resident macrophages in the
brain, in Alzheimer’s disease and amyotrophic lateral sclerosis (ALS), (Akiyama et al., 1994;
Knight, Brill, Queen, Tarwater, & Mankowski, 2018). CSF1R mutations are found in the kinase
domain of the receptor in hereditary diffuse leukoencephalopathy with spheroids (HDLS), an
autosomal dominant neurodegenerative disorder (Rademakers et al., 2012). CSF1R has been
shown to specifically regulate the density and distribution of microglia in adult-onset
leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) (Oosterhof et al., 2018).
In cancers, CSF1R has been found to be highly expressed in breast, ovarian, endometrial,
prostate and renal cancers, as well as in melanoma and classical Hodgkin lymphoma (Espinosa et
al., 2009; Ide et al., 2002; B M Kacinski, 1991; Barry M. Kacinski, 1997; Kirma et al., 2007;
Morandi, Barbetti, Riverso, Dello Sbarba, & Rovida, 2011; Tang et al., 1992). High CSF1R
expression in these cancers is usually associated with co-expression of CSF1 ligand. In most of
these solid tumors, increased CSF1R expression is found on tumor-associated macrophages
(TAM) (Edginton-White et al., 2018; Martín-Moreno et al., 2015; Q. Wang et al., 2018).
Macrophages are classically classified based on an activation state polarity of either being pro-
inflammatory (anti-tumorigenic) or anti-inflammatory (pro-tumorigenic), being termed M1 vs.
M2 macrophages, respectively. There are 2 main pathways that lead to divergent routes of
macrophage activation, with activation of distinct T cell immune responses. Classical
macrophage activation leads to production of M1 macrophages through the action of interferon
gamma (IFN-γ); these are involved in the killing of microbial pathogens. In contrast, an
alternative activation leads to production of M2 macrophages in response to IL-4 or IL-13 which
56
have been shown to fight against parasites and allergens (Gordon & Martinez, 2010; Schroder,
Hertzog, Ravasi, & Hume, 2004).
In most cancers, the predominant TAMs have the M2 phenotype and are anti-
inflammatory, immune-suppressant and hence tumor-promoting (Ley, 2017; Noy & Pollard,
2014). Myeloid cells are an important component of the tumor microenvironment as they play
key roles in tumorigenesis. These cells include TAMs, polymorphonuclear myeloid-derived
suppressor cells, (PMN-MDSC), monocytic MDSC (M-MDSC) and dendritic cells (DC) (Kumar
et al., 2017). TAMs and MDSCs have been shown to promote tumorigenesis by suppressing T-
cell functions and promoting tumor angiogenesis, proliferation, survival and metastasis
(Coussens & Pollard, 2011; Talmadge & Gabrilovich, 2013). CSF1R functions to regulate TAM
differentiation, growth and survival and is often overexpressed by the cells. As such, CSF1R has
become a therapeutic target of interest with the development of small molecule inhibitors and
antibodies, some of which are currently in clinical trials for classical Hodgkin lymphoma,
melanoma and tenosynovial giant-cell tumor (Tap et al., 2015; Von Tresckow et al., 2015).
1.7. COLONY STIMULATING FACTOR 1 (CSF1)
Colony stimulating factor 1 (CSF1, also known as macrophage colony stimulating factor,
MCSF) is a cytokine that regulates the differentiation and proliferation of monocytes and
macrophages from myeloid cell precursors (E. R. Stanley, Guilbert, Tushinski, & Bartelmez,
1983). It is highly expressed in the bone marrow, brain, liver and female reproductive tissues
(The Human Protein Atlas). CSF1 is a homodimeric glycoprotein and in the BM, it is produced
by BM stromal cells such as fibroblasts, mesenchymal cells and osteoblasts. During pregnancy,
CSF1 is involved in mammary gland and placental development, with serum and tissue
57
concentrations rising by 2-fold and levels in the uterus rising by 1000-fold (Cecchini et al.,
1994). CSF1 has pleiotropic effects as CSF1-deficient op/op mice, which have a natural
inactivating mutation in the CSF1 protein, exhibit osteopetrosis, severe growth retardation, low
fertility and decreased numbers of tissue macrophages (Begg et al., 1993; Wiktor-Jedrzejczak et
al., 1990). CSF1 acts on CSF1R, which is the only known receptor that it binds to.
1.7.1. CSF1 Gene Structure and Isoforms
CSF1 is encoded by the human CSF1 gene located on chromosome 1 (1p13.3) and
consists of 9 exons spanning approximately 21 kb. Four different human CSF1 cDNAs have
been identified with lengths of, 4.0, 2.5, 2.3 and 1.6 kb. The 4.0- and the 2.3-kb cDNAs are full-
length cDNA clones that differ in the 3’-untranslated region due to alternative use of two exons
(9 and 10). The 2.5- and 1.6 kb species are truncated due to alternative splicing in the 5’ end of
exon 6, which leads to large segments being spliced out of the full length species (Cerretti et al.,
1988; Ladner et al., 1987) (Figure 1.6).
The 4.0 kb full length mRNA species gives rise to a putative 554 amino acid, 86-150 kDa
homodimeric transmembrane-spanning precursor protein termed variant 1 (V1) or protein
isoform a (Price et al., 1992). It consists of a 32 amino acid N-terminus leader sequence, an
extracellular region with a 149 amino acid receptor binding domain, a transmembrane domain
with 24 amino acids (amino acids 464-488) and a short 37 amino acid cytoplasmic tail (Douglass
et al., 2008; E. Richard Stanley et al., 1997). Proteolytic cleavage occurs at several sites in the
extracellular domain, including those at amino acids 251, 298, and 423, to release a soluble
protein that may be secreted from the cell (Stanley et al., 1997). The full length protein is co-
translationally glycosylated in the endoplasmic reticulum, after which N-linked and O-linked
58
sugars are added to it in the Golgi apparatus. In addition to N-glycosylation and O-glycosylation
sites, the soluble/secreted isoform also has a site for the addition of one glycosaminoglycan
carbohydrate chain, to which a chondroitin sulfate molecule can be added. Addition of the
glycosaminoglycan sugar leads it to being secreted as a proteoglycan, whereas a lack of it results
in it being a glycoprotein. Both forms are secreted and accumulate rapidly with a doubling time
of approximately 40 minutes (E. Richard Stanley et al., 1997).
The secreted glycoprotein form is homodimeric and is 85 kDa, whereas the proteoglycan
can be up to 150 kDa, due to the addition of the chondroitin sulfate (Fixe et al., 1998). Mature
CSF1 protein can be as small as 150 amino acids and still function, with the first seven cysteines
being necessary for its function (Kawasaki et al., 1990). Mouse CSF1 is a 520 amino acid
membrane-spanning precursor that has significant homology to human CSF1. Despite the
homology, murine CSF1 is unable to induce activation of the human CSF1 receptor (CSF1R)
(Rettenmier at al., 1988; Price at al., 1992).
The 1.6 kb variant that results from alternate splicing of the full length mRNA species
leads to the deletion of a 298 amino acid region from the extracellular domain, which contains
proteolytic cleavage site(s) at which the biologically active, mature protein is cleaved
(Rettenmier and Roussel, 1988) (Figure 1.7). This alternatively spliced form produces a shorter
256 amino acid protein product termed variant 3 (V3) or protein isoform c that is membrane-
bound (Rettenmier et al., 1987). Expression of this species in NIH3T3 cells leads to a cell
surface-bound, membrane-spanning dimeric CSF1 protein that is 68 kDa in size. This precursor
is expressed as a relatively stable membrane-bound glycoprotein as it is not cleaved in secretory
transport vesicles. As such, it is stably expressed at the cell surface, although it can be slowly
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released as a smaller 44 kDa homodimer through proteolysis (Rettenmier et al., 1987).
Membrane-bound CSF1 is exclusively N-glycosylated as it lacks sites for O-glycosylation.
The soluble/secreted glycoprotein can only act humorally as it is released into the
circulation, whereas the soluble/secreted proteoglycan can act both humorally and locally; the
latter due to the glycosaminoglycan chains that allow it to be sequestered within the bone
marrow stroma (Stanley et al., 1997). CSF1 is found as a proteoglycan in the bloodstream at
biologically active concentrations of 10 ng/mL (Hume & MacDonald, 2012).
Taken together, there are 3 major versions of CSF1 protein that can be produced (with
two forms of the soluble/secreted version): a secreted/soluble proteoglycan, a secreted/soluble
glycoprotein and a cell surface membrane-bound glycoprotein. Homodimeric CSF1 binds to the
D1 - D3 domains of the extracellular portion of CSF1R (Chen, Liu, Focia, Shim, & He, 2008;
Felix et al., 2015; E. R. Stanley et al., 1983). The N-terminal region of CSF1 consists of an
active 149-amino acid fragment that forms a 4 α-helix bundle; for the homodimer, two bundles
of the 4 α-helices are laid end-to-end, linked by a disulfide bond (Pandit et al., 1992).
Little is known about how CSF1 expression is transcriptionally regulated but it has been
reported that angiotensin II may stimulate CSF1 transcription in vascular endothelial cells
through the action of Brahma related gene 1 (BRG1), which is a core component of the
SWI/SNF chromatin remodeling complex (Shao et al., 2019).
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Figure 1.6. Alternative splicing of CSF1 leads to different isoforms.
Alternative splicing in exon 6 of full length genomic CSF1 DNA yields the shorter membrane-
bound isoform of CSF1, termed V3 or isoform c.
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Figure 1.7. Model of the two major variants of monomeric CSF1.
The full length CSF1 cDNA precursor (4.0 kb) is processed to yield a 1.6 kb cDNA that gives
rise to a shorter, membrane-bound isoform (bottom schematic). While the full length precursor
contains both N- and O-linked glycosylation sites, along with a glycosaminoglycan site to which
chondroitin sulfate can be added, the shorter membrane-bound isoform only contains sites for O-
glycosylation.
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1.7.2. CSF1 in Pathology
Circulating levels of CSF1 increase in various pathologies including infections, chronic
inflammatory disease and cancer. In inflammation, CSF1 may be produced by macrophages
themselves, although in the mouse this does not appear to be the case as macrophages actually
fail to survive if there is no CSF1 present. CSF1 levels are regulated by tissue macrophages
through receptor-mediated endocytosis of its receptor, CSF1R, leading to intracellular uptake
and destruction in lysosomes (Hume & MacDonald, 2012). CSF1 is found to be highly expressed
in breast, ovarian, lung, prostate and renal cancers, and high circulating levels are found in
melanoma. The malignant cells in melanoma and breast cancer have been shown to produce
increased amounts of CSF1, which likely impacts disease behaviour.
Interestingly, compared to other hematopoietic myeloid growth factors such as G-CSF
and GM-CSF, CSF1 administration has not demonstrated efficacy in bone marrow
transplantation or in recovery from myelosuppressive chemotherapy (Dale, 2006; Heuser,
Ganser, & Bokemeyer, 2007). However, its potential therapeutic use is being investigated in
conjunction with other factors, particularly with GM-CSF, as both have been shown to generate
large macrophage colonies in-vivo. Moreover, a role for CSF1-stimulated macrophages is also
being explored in the treatment of fungal infections. In phase I clinical trials, soluble CSF1 has
demonstrated an ability to increase monocyte numbers (Bukowski et al., 1994). Further to this,
CD8+ T cells have been shown to induce increased production of CSF1 by melanoma cells,
which can be blocked with anti-CSF1R neutralizing antibodies, in conjunction with blockade of
programmed cell death protein 1 (PD-1) (Neubert et al., 2018).
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1.8. INTERLEUKIN-34 (IL-34)
Interleukin-34 (IL-34) is a relatively newly identified cytokine that was discovered in
2008 in a functional screen of the extracellular proteome; it was found to be a second ligand for
CSF1R (H. Lin et al., 2008)(Wei et al., 2010). Interestingly, such alternative binding by a second
ligand has not been found for other structurally similar receptors, namely c-Kit or Flt3 (Chihara
et al., 2010). While IL-34 has no structural similarity to CSF1, it has been found to function
similarly to it, in terms of promoting the differentiation, growth and survival of monocytes,
macrophages and osteoclasts, as well as the development of microglia (Baud’Huin et al.,
2010; Guillonneau, Bézie, & Anegon, 2017). However, unlike CSF1 which can only bind to
CSF1R, IL-34 was discovered to bind to two other receptors: the receptor type protein-tyrosine
phosphatase zeta (PTP-ζ) and CD138 (Syndecan 1 or SDC1) (Nandi et al., 2013; Segaliny et
al., 2015). The existence of an alternate CSF1R ligand was suggested by the observation that in
comparison to CSF1-deficient CSF1op/op mice that have reduced macrophage numbers,
osteopetrosis and other abnormalities in bone formation, CSF1R-/- mice exhibit more severe
adverse effects. This suggested that in the absence of CSF1, there may be another ligand that acts
on CSF1R to prevent the severe osteogenic phenotypes that occur when CSF1R is lost (Wei et
al., 2010). CSF1 and IL-34 have both been shown to be expressed in human and mouse brain,
but in distinct spatial regions. While CSF1 has been found to be highly expressed in the
cerebellum to mediate cerebellar microglia development, IL-34 is expressed in forebrain areas
including the cerebral cortex and the CA3 region of the hippocampus (Kana et al., 2019).
Moreover, the cells producing the ligands also differed, with glial cells producing CSF1, and
neurons producing IL-34. CSF1R was expressed on microglia throughout the brain. This
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highlights that the two CSF1R binding proteins are not redundant, but have functionally
distinctive roles in the brain.
1.9. SOLUBLE VS. TRANSMEMBRANE LIGANDS
Evidence suggests that the soluble and membrane-bound forms of growth factor ligands
differ in their functional activity. For example, it has been shown that the soluble and membrane-
bound forms of Kit ligand signal through distinct phosphotyrosine residues in the c-Kit receptor,
with the Y728 residue being required for mitogenic stimulation and leukemic growth induced by
the membrane-bound, but not soluble, ligand (Jennifer L Gommerman, Sittaro, Klebasz,
Williams, & Berger, 2000). Similarly, soluble recombinant CSF1 has been shown to fail to
promote hematopoietic and leukemic cell survival, and may actually induce cell differentiation
and cell death, whereas the membrane-bound form of the ligand supports long-term growth of
the cells (Tsuboi, Revol, Blanchet, & Mouchiroud, 2000b). This suggests that transmembrane
ligands may have distinctive functional properties, most likely involving mediation of cell
adhesion to foster enhanced cell-cell contact and bidirectional intracellular signaling.
1.10 PDZ DOMAINS AND PDZ DOMAIN BINDING MOTIFS
PDZ (Postsynaptic density 95, PSD-85; Discs large, Dlg; Zonula occludens-1, ZO-1)
domains mediate protein-protein interactions to serve as central organizers of multi-dynamic
signaling complexes and represent the most common protein-protein interaction domain (Lee &
Zheng, 2010). PDZ domains are typically 80-90 amino acids in length and found in
approximately 180 different human proteins, with multiple copies present in many proteins.
Although there are hundreds of unique PDZ domain sequences, they all contain a highly
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conserved glycine-leucine-glycine-phenylalanine sequence that gives rise to the domain’s folded,
globular, cup-like structure. This structure has the ability to recognize and bind to short, finger-
like hydrophobic peptides (Harris & Lim, 2001). The structural modules are comprised of 5-6
beta strands and 2-3 alpha helices (Doyle et al., 1996; Lee & Zheng, 2010).
PDZ domain recognition sequences
Because of their modular structure, PDZ domains usually bind to specific C-terminal sequence
motifs on protein ligands. These sequence motifs are known as PDZ domain binding motifs
(PDBM) which are typically 4-6 amino acids in length. The C-terminus residue is designated as
the P0 residue while subsequent residues towards the N-terminus are referred to as P−1, P−2, P−3,
etc. (Harris & Lim, 2001). It is suggested that the P0 and P−2 residues are the most important for
PDZ domain binding recognition (Songyang et al., 1997). In fact, studies have shown that PDZ
domains can be divided into three main classes based on their binding preferences for residues at
the P0 and P−2 sites: Class I PDZ domains recognize the motif S/T-X-Φ-COOH (where Φ is a
hydrophobic amino acid at the P0 site and X is any amino acid); class II PDZ domains recognize
the motif Φ-X-Φ-COOH; and class III PDZ domains recognize the motif X-X-C-COOH (Table
1-6) (Costa et al., 2018). There are a few other PDZ domains that do not fall in any of the three
classes. PDZ domains recognize these motifs usually only if they are located at the C-terminus of
the protein ligand. This is because the end of the peptide-binding groove of PDZ domains have a
specific carboxylate-binding loop which binds the peptide ligand terminal carboxylate to position
it in the binding groove. This specific positioning results in the side chains of the P0 and P−2
ligand residues to protrude into the base of the peptide-binding groove, with the P0 residue
pointing into a large hydrophobic pocket (Costa et al., 2018). This specific docking position
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helps explain why the P0 residue is hydrophobic. In PSD-95 (postsynaptic density protein 95),
which has a preference for valine at P0 of its binding ligand, the pocket is formed by Phe325,
Leu379 and other hydrophobic residues, while a slightly larger hydrophobic pocket in the first
PDZ domain from NHERF/EBP50 causes a preference for leucine at the P0 position (Doyle et
al., 1996; Karthikeyan, Leung, Birrane, Webster, & Ladias, 2001). The side chain of the P−2
ligand residue points into a separate pocket, which in class I PDZ domains, contains a histidine
residue that hydrogen bonds with the side chains of a serine or threonine residue. Class II
domains recognize a hydrophobic residue at position P−2, typically leucine or methionine
(Daniels, Cohen, Anderson, & Brünger, 1998).
The functional importance of the PDZ binding domains of several transmembrane
proteins have been characterized. Work by Tony Pawson’s group has shown that the PDZ
domain binding motif of the ephrin B1 ligand interacts with the PDZ domain of proteins such as
syntenin (involved in cytoskeletal organization and protein trafficking) and the tyrosine
phosphatase FAP-1 (Holland et al., 1996; D. Lin, Gish, Songyang, & Pawson, 1999). Similarly,
the C-terminal PDZ binding domain of transmembrane transforming growth factor α (TGF-α)
also interacts with syntenin, as well as the Golgi protein p59/GRASP55 in the Golgi apparatus,
both of which mediate targeting of the ligand to the cell membrane (Fernández-Larrea, Merlos-
Suárez, Ureña, Baselga, & Arribas, 1999; Kuo, 2002). Interestingly, p59 also interacts with the
transmembrane form of kit ligand (Flanagan, Chan, & Leder, 1991).
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Table 1-6. Classification of PDZ domain binding recognition sequences
PDZ domain binding motifs are divided into three main classes based on the specific residue
binding preference of interacting PDZ domains. Adapted from Lim et al., 2001.
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1.11. HTRA SERINE PROTEASES
The mammalian high temperature requirement A (HtrA) is a family of trypsin-like serine
proteases, originally identified in bacteria for their heat shock activity (Clausen, Kaiser, Huber,
& Ehrmann, 2011; Krojer, Garrido-Franco, Huber, Ehrmann, & Clausen, 2002; Lipinska, Zylicz,
& Georgopoulos, 1990). HtrA proteases also exhibit molecular chaperone and serine protease
activity, the latter of which fosters degradation of misfolded proteins (Clausen, Southan, &
Ehrmann, 2002a; Krojer et al., 2002). The human HtrA family consists of at least four members,
HtrA 1 - 4, of which HtrA2 is largely localized to the mitochondria where it regulates apoptosis
(Clausen et al., 2011; Hegde et al., 2002; Suzuki et al., 2001). The proteases contain a highly
conserved trypsin-like serine protease domain and at least one PDZ domain (Clausen et al.,
2002a; MURWANTOKO et al., 2004). HtrA1, 3 and 4 also contain an insulin-like growth factor-
binding domain as well as a Kazal-type serine protease inhibitor domain and signal peptide in the
N-terminal domain. HtrA1 is largely a secreted protease, but it can also be found in the cytosol
as a soluble peptide (Clawson, Bui, Xin, Wang, & Pan, 2008). HtrA1 is seen to play roles in cell-
cell adhesion as it degrades components of the extracellular matrix such as type III collagen and
fibronectin, and can also cleave the epithelial cell surface adhesion protein E-cadherin. HtrA1 is
expressed in the BM where it is involved in osteogenesis, bone remodeling and musculoskeletal
development (Tiaden et al., 2012a). In cancers, HtrA1 is down-regulated in ovarian cancer and
melanoma, suggesting a role for it in carcinogeneis through potential aberrant remodeling of the
tumor microenvironment (Baldi et al., 2002; Chien et al., 2004).
Structurally, HtrA1 exists as a trimer where the PDZ domains hinder access of substrates
to the inner catalytic core to mediate auto-inhibition of the protein complex. Binding of
substrates to the PDZ domain opens up the trimeric structure to expose the catalytic core, thereby
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relieving the auto-inhibition (Figure 1.8). Recent evidence has demonstrated a role for
cytoplasmic HtrA1 in regulating intracellular signaling as it has been shown to cleave
tuberin/tuberous sclerosis 2 (TSC2), a negative regulator of the mammalian target of rapamcyin
(mTOR), accompanied by activation of the mTOR targets 4E-BP1 and S6K (Campioni et al.,
2010). The identification of TSC2 as a substrate of HtrA1 proteolytic activity makes the mTOR
pathway a relevant signaling target of HtrA1.
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Figure 1.8. Structure and function of HtrA serine proteases.
HtrA1 exists as a trimer where the PDZ domains of each unit are auto-inhibitory as they block
access to the inner catalytic core. Binding of substrates to the PDZ domains opens up the
conformation of the trimeric structure to expose the active site.
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1.12. EXPERIMENTAL MODELING
Modelling human disease in experimental in-vitro and in-vivo models often presents
biological and technical challenges. Mouse model systems are limited in their recapitulation of
the human disease owing to genetic differences between organisms. In-vivo xenograft mouse
models rely on the successful engraftment of human cells in mice, which is a challenge as only
40-50 % of primary AML samples engraft in conventional immune deficient mouse models such
as the NOD/SCID mouse and its newer and improved prototypes NOD/SCIDγ (or NSG), with
large variations in actual degree of engraftment, ranging from as low as 0.1 – 50 % (Sanchez et
al., 2009). Given this, there is growing interest in the development of humanized mouse models
wherein human cells, tissues, organs and/or genes are introduced into the mouse to support the
transplantation of human cells. Mice expressing human growth factors and cytokines have been
shown to model and recapitulate a more human-based genetic and molecular background and/or
tissue microenvironment to improve engraftment and disease modeling. For example, expression
of human cytokines such as SCF, GM-CSF, M-CSF (CSF-1) and IL-3 in mouse models show
improved engraftment of human cells (Ito et al., 2013; Rathinam et al., 2011a; Walsh et al.,
2017). A humanized CSF1 knock-in mouse, where human CSF1 was inserted into the
corresponding mouse locus of Balb/c Rag2-/- γc-/- mice, shows improved frequency and function
of myeloid cells such as increased monocyte/macrophage activation and migration (Rathinam et
al., 2011b).
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1.13. THESIS FOCUS
My work in this thesis centered on the study of the CSF1-CSF1R ligand-receptor pair
because 1) the significance of CSF1R expression levels are largely unknown in AML and 2)
CSF1 is a hematopoietic ligand that is constitutively expressed in the BM stroma. CSF1-CSF1R
signaling was assessed between CSF1R-expressing AML cells and BM stromal cells engineered
to express different isoforms of the human CSF1 ligand (Figure 1.9). Moreover, potential
differences in the function of soluble vs. membrane-bound/transmembrane CSF1 were also
assessed with respect to the adhesion and long-term support of AML cells on stroma in co-
culture assays. While the binding of CSF1 to CSF1R stimulates well-described growth and
proliferative intracellular signal transduction pathways downstream of the receptor, the impact of
CSF1R binding to CSF1 ligand in stromal cells is less understood. This is of particular relevance,
as many transmembrane ligands contain signaling domains which have demonstrated potential to
reverse signal within cells. Given this, the potential phenotypic and signaling changes induced by
CSF1-CSF1R were investigated in both interacting AML, and BM stromal cells. This would
allow for a better understanding of the role of this ligand-receptor pair on leukemogenesis within
the BM microenvironment.
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Figure 1.9. Modeling an AML-bone marrow microenvironment.
Investigation of CSF1-CSF1R signaling between interacting AML and BM stromal cells
expressing the receptor and ligand, respectively.
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1.14. THESIS RATIONALE, HYPOTHESES AND OBJECTIVES
RATIONALE
Given that the CSF1-CSF1R interaction is important in regulating normal myelopoiesis, and that
CSF1R may be found to be expressed in subsets of AML patients, it is of importance and
relevance to investigate the function of this ligand-receptor interaction in the myeloid
malignancy of AML. In this project, the prognostic significance of CSF1R gene and protein
expression levels was evaluated in a cohort of AML patients, and the CSF1-CSF1R ligand-
receptor interaction was functionally interrogated in in-vitro co-culture, as well as in-vivo models
of AML.
HYPOTHESES
1) CSF1R levels are associated with clinical patient survival
2) The CSF1-CSF1R ligand-receptor pair helps mediate interactions between AML and stromal
cells to elicit phenotypic (enhanced growth, survival, adhesion) and signaling changes in
AML cells.
3) Transmembrane CSF1 can engage in bi-directional or reverse intracellular signaling in
stromal cells: CSF1 can signal within stromal cells to alter stromal cell signaling, which has
implications for its support of AML cells. AML cells can also impact the behaviour and
phenotype of stromal cells via the CSF1-CSF1R interaction between the cells.
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OBJECTIVES
1) Evaluate CSF1R expression levels in AML patient samples and examine the association
between expression levels and clinical patient outcome.
a. Interrogate CSF1R gene expression levels in publicly available gene expression
datasets and correlate it with clinical data, including patient survival (when treated
with curative intent).
b. Examine CSF1R cell surface protein expression levels on blasts of AML patient
samples using flow cytometry; use clinical patient information to evaluate
potential associations of CSF1R levels and patient survival.
2) Investigate the functional role of CSF1-CSF1R in AML-stromal cell interactions
a. Overexpress human CSF1 ligand (hCSF1) in MS-5 stromal cells: compare effects
of soluble vs. membrane-bound/transmembrane isoforms
b. Perform co-culture experiments using hCSF1-expressing MS-5 stromal cells and
CSF1R-expressing AML cells
c. Evaluate the growth, proliferation, survival, signaling, cytokine and gene
expression changes in AML cells upon exposure to CSF1 in co-cultures.
d. Utilize a humanized CSF1 mouse model to examine whether it provides improved
engraftment of primary human AML cells as well as AML cells lines.
3) Examine signaling potential of CSF1 ligand: reverse intracellular signaling within BM
stromal cells
a. In MS-5 stromal cells, delete the last five residues, which constitute a putative
PDZ domain binding motif (PDBM), at the C-terminal end of transmembrane
CSF1. Evaluate signaling and phenotypic changes occurring as a result. Examine
the role of HtrA1 as a potential signaling mediator of CSF1.
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CHAPTER 2
CSF1R is associated with poor clinical outcome and promotes a
leukemic cell phenotype in AML-stromal cell interactions
This chapter is in preparation for a manuscript to be submitted for publication
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2.1. ABSTRACT
The colony stimulating factor 1 receptor (CSF1R) is important in the regulation of normal
myelopoiesis, but its status and function remains largely unknown in Acute Myeloid Leukemia
(AML). In this work, the clinical significance of CSF1R was investigated, along with its
functionality in AML- bone marrow (BM) stromal cell interactions. It was found that a subset of
AML patient samples express high levels of CSF1R (CSF1Rhigh) and that patients with
CSF1Rhigh AML cells have shorter overall survival (OS) compared to patients with low CSF1R
(CSF1Rlow) expression. In in-vitro co-cultures, it was demonstrated that MS-5 stromal cells
expressing either the soluble (sol) or transmembrane (mem) variants of human CSF1 (hCSF1),
enhanced the long-term growth and survival of CSF1Rhigh AML cells (patient samples and
OCI/AML-4 and OCI/AML-5 cell lines); this growth advantage was not observed for CSF1Rlow
AML cells. MS-5 cells expressing the transmembrane variant of CSF1 provided greater
supportive effects compared to the soluble variant. Co-culture of CSF1Rhigh AML cells with MS-
5 hCSF1-mem cells led to increased cell surface expression of the hematopoietic stem/progenitor
cell markers CD34 and c-Kit, along with increased phosphorylation of the mTOR target S6 in
CSF1Rhigh AML cells. It also led to distinct changes in the cytokine profile of AML. Application
of a CSF1R antibody mitigated much of these effects, with decreased cell proliferation and
inhibition of mTOR signaling in AML cells. In humanized CSF1 mice, CSF1Rhigh AML cells
exhibited significantly improved engraftment compared to NOD-SCID mice. These results
suggest that CSF1-CSF1R signaling has important clinical prognostic value and biological
function to support the growth and maintenance of AML cells in AML-stromal cell interactions.
This makes CSF1-CSF1R an attractive therapeutic target within the BM microenvironment of
AML.
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2.2. INTRODUCTION
Acute Myeloid Leukemia (AML) is a highly aggressive and fatal hematological
malignancy characterized by significant heterogeneity and growth-factor dependency. Curative
intent treatment involves induction therapy, often using the ‘3+7’ regimen of
doxorubicin/daunorubicin and Ara-C (Murphy & Yee, 2017). While most patients achieve a
complete remission with such a regimen, despite further consolidation therapy, more than half of
all patients relapse with high mortality rates thereafter (Betz & Hess, 2010b; Liersch et al.,
2014). AML arises due to a block in differentiation of myeloid cell precursors known as
myeloblasts (or blasts), occurring largely as a result of molecular and cytogenetic aberrations.
The clonal expansion and accumulation of these abnormal undifferentiated precursors interferes
with normal hematopoiesis, leading to a bone marrow (BM) failure state, characterized by
anemia, thrombocytopenia and neutropenia in most patients.
The BM microenvironment is a complex niche of interconnected cells and factors that
provides supportive conditions not only for normal hematopoiesis, but also leukemic cells.
Colony stimulating factor 1 (CSF1) is a cytokine produced by BM stromal cells such as
fibroblasts, endothelial and mesenchymal cells (Hamilton & Achuthan, 2013). CSF1 exists in
several isoforms including a secreted proteoglycan or glycoprotein, and a cell surface
transmembrane glycoprotein, with the latter being the predominant form in the BM. (Horiuchi et
al., 2007; C W Rettenmier & Roussel, 1988). CSF1 binds to the CSF1 receptor (CSF1R, c-FMS,
CD115), which is a membrane-spanning class III receptor tyrosine kinase (RTK) expressed on
mononuclear phagocytic myeloid-lineage cells (F Birg, Rosnet, Carbuccia, & Birnbaum, 1994;
Rosnet & Birnbaum, 1993; C J Sherr & Rettenmier, 1986). Binding of CSF1 ligand to CSF1R
induces the differentiation and growth of myeloid cell precursors into mature monocytes and
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macrophages (Rohrschneider et al., 1997). Activation of the receptor through binding CSF1
leads to receptor oligomerization and autophosphorylation of tyrosine residues in the
cytoplasmic domain of CSF1R. Subsequently, this results in the activation of intracellular growth
and survival pathways including the PI3K/Akt, MAPK/Erk and Jak/STAT pathways (Huynh,
Kwa, Cook, Hamilton, & Scholz, 2012; Pixley & Stanley, 2004; Reedijk et al., 2018).
In cancers, CSF1R is found to be highly expressed in ovarian cancer, glioma, giant
tenosynovial giant-cell tumor, renal and pancreatic cancers, with expression being localized to
tumor-associated macrophages (TAM) in solid tumors (De et al., 2016; Swierczak et al., 2014).
CSF1R is also associated with poor clinical outcomes in renal and pancreatic cancers. In AML,
the clinical prognostic significance of CSF1R remains unknown. Moreover, while the CSF1-
CSF1R ligand-receptor pair is well established to instruct macrophage development in normal
myelopoeisis, its role and function in myeloid malignancy remains rudimentary.
In this study, we found that CSF1R is highly expressed by leukemic cells in subsets of
AML patients, with high expression (both cell surface protein levels, as well as transcript levels)
being associated with poor overall and event-free clinical survival. Furthermore, CSF1R
demonstrated significance in the subgroup stratification of FLT3 and NPM1 normal AML
patients. In the interrogation of CSF1-CSF1R signaling between AML and stromal cells in in-
vitro co-culture assays, it was found that MS-5 stromal cells expressing the transmembrane form
of human CSF1 (hCSF1-mem) provided the best support for the long-term growth and
maintenance of CSF1R-expressing AML cells compared to MS-5 control cells, and MS-5 cells
expressing the soluble hCSF1 variant. Co-culture of CSF1R-expressing AML cells with hCSF1-
expressing MS-5 cells led to distinct changes in intracellular signaling, namely activation of
mTOR targets, in addition to changes in cytokine levels in AML cells. Furthermore, increased
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cell surface expression of the hematopoietic stem cell-associated markers CD34 and c-Kit were
observed in AML cells cultured with hCSF1-expressing MS-5 cells, as well as AML cells grown
in humanized CSF1 mice. Application of a CSF1R antibody abrogated these effects, resulting in
inhibition of AML cell proliferation, and associated signaling and cytokine changes. These
findings demonstrate CSF1R to be a potentially substantive marker in predicting AML clinical
outcome, and highlights an important role for CSF1-CSF1R as a signaling mediator between
leukemic and stromal cells that may be therapeutically targeted within the AML
microenvironment.
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2.3. MATERIALS AND METHODS
AML Dataset Analyses
Normalized microarray data was downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/) and
TCGA (http://cancergenome.nih.gov/) databases. Cross-dataset frequency distribution of CSF1R
expression was visualized by transforming and mode centering CSF1R expression data in R
(http://www.r-project.org). Clinical data analysis was performed on non-transformed data.
Clinical Definitions
Complete remission (CR) was defined as the presence of normal erythropoiesis, granulopoiesis
and megakaryopoiesis, PB absolute neutrophil count ≥1 × 109 /L and platelet count ≥100 × 109
/L, and <5% leukemic blast cells in BM. Relapse was defined as recurrence of >5% blasts in the
BM. Overall survival (OS) was defined as time from diagnosis to death. Event free survival
(EFS) was defined as time from disease diagnosis until relapse or death. OS and EFS were not
calculated for patients with <28 day survival. Patients lost to follow-up were censored at the date
of last follow-up. Risk stratification of patients into good, intermediate and adverse was done in
accordance to NCCN guidelines (O’Donnell M et al., 2017).
Survival Analysis
Analysis of clinical endpoints and response to therapy in the gene expression datasets (Valk,
Metzler) was done exclusively for patients who underwent induction therapy. The univariate
association between CSF1R expression and other clinical features was assessed using the
Fisher’s exact or Wilcoxon rank-sum tests, as appropriate. Kaplan-Meier survival analysis was
used to estimate unadjusted survival curves and the log-rank test was used to compare survival
82
rates. Cox proportional hazards models were used to estimate the adjusted survival curves,
hazard ratios (HRs) and 95% confidence intervals (CIs) associated with CSF1R expression.
Flow Analysis on AML Patient Samples
Flow cytometry was performed on 146 AML patient samples obtained from the leukemia tissue
bank at the Princess Margaret Cancer Centre (PMCC) at the University Health Network (UHN)
in Toronto, Ontario, Canada. The patients had all received standard curative intent clinical
treatment for AML. The flow cytometry data was analyzed using FlowJo V10 software. AML
blasts were identified based on a CD45dim/SSClow gating parameter. CSF1R expression was
evaluated on the gated AML blast population and the percentage of positive cells was recorded.
DNA Plasmids and Gene Transduction
Human CSF1 cDNAs were purchased from Origene and cloned into a retroviral pBabe-GFP
vector. Empty vector (EV) pBabe-GFP, pBabe-GFP-hCSF1-sol and pBabe-GFP-hCSF1-mem
retroviruses were produced by calcium phosphate transfection of 293-T cells with psPAX2 and
VSVG as described elsewhere (Life Technologies). Virus rich medium was collected 48 and 72
hours post-transfection and concentrated with Lenti-X Concentrator (Clontech). MS-5 cells were
infected with virus rich medium for 24 hours with 8 μg/mL protamine sulfate. Infected cells were
selected by fluorescence activated cell sorting (FACS) for GFP fluorescence.
Cell Culture
AML cell lines were cultured in α-MEM complete medium with 10% fetal bovine serum (FBS),
100 units/mL penicillin and 100 μg/mL streptomycin at 37°C in 5% CO2 . The OCI/AML-4 and
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OCI/AML-5 cell lines were cultured with the addition of 10% conditioned medium (CM) from
5637 bladder carcinoma cells, which they require for their growth in cell culture (Meyer &
Drexler, 1999). MS-5 stromal cells were cultured in α-MEM complete medium. 293-T cells used
for lentivirus production were cultured in DMEM complete medium.
Co-culture Assays
For co-culture assays, a stromal cell feeder layer was first established by seeding 1.0 -1.5 x 105
MS-5 cells in 6-well plates and allowing them to adhere overnight. The following day, the MS-5
stromal cells were irradiated to induce growth arrest of the cells. Following this, culture medium
was removed and 1.5 x 105 AML cells (AML cell lines) were added to the MS-5 cells with
addition of fresh medium (total volume of 3 mL). The OCI/AML-4 and OCI/AML-5 cell lines
were grown in the absence of 5637-CM for the co-culture experiments. For AML patient
samples, 1X106 cells were seeded. Co-cultures were maintained by demi-depopulation of AML
cells every 2 - 3 days as described previously. Briefly, half the culture medium was removed by
gently washing medium over the stromal cells to detach any loosely attached AML cells. The
same volume of fresh medium was then added to the cultures. Cultures were maintained for
several days to several weeks, depending on the experimental assay to be conducted.
Cell Growth Curves
AML growth curves were performed by seeding 5 x 104 - 1 x 105 cells in 6-well plates. For drug
assays, the compound was added at time of seeding. Both suspension and adherent AML cells in
co-culture were retrieved for counting. Adherent cells were obtained by gently washing them off
the stromal layer. Cells were stained with trypan blue and counted using a haemocytometer. For
84
final endpoint counts of AML cells in co-culture, the cultures (including stromal cells with
adherent AML cells) were trypsinized and subjected to flow cytometry analysis where ratios of
GFP-positive MS-5 stromal cells to AML cells were obtained for calculating the counts of each.
Drug Treatment
CSF1R monoclonal antibody (Amgen) was used to treat AML and MS-5 cell co-cultures. Co-
cultures assays were set up as described above. The CSF1R antibody was added to co-cultures at
the time of AML cell seeding. Cell viability was assessed daily with trypan blue or
AlamarBlue® (Life Technologies) as described.
Quantitative RT-PCR
RNA was extracted using RNeasy Mini kit (Qiagen) and first strand cDNA synthesis was
performed using the M-MLV systems (Life Technologies). qPCR reactions were conducted
using the SYBR Green PCR Master Mix kit (Applied Biosystems) on a 7900 HT Real-Time
PCR system with SDS v2.3 software (Applied Biosystems) using standard settings: 95°C (10
min) and 40 cycles of 95°C (20 sec) and 60°C (1 min). mRNA levels were normalized to
GAPDH as a housekeeping gene. Primers used: CSF1R 5’-TGGCCACAGCTTGGCATGGT- 3’
(sense) and 5’-TGCCCACACATCGCAAGGTCA-3’ (anti-sense); sol hCSF1 5’-
CAGCAAAGGGCCAACAGC-3’ (sense) and 5’-GGTCCTCCTTCTGGCTCTG- 3’ (anti-
sense); mem hCSF1 5’-ACAAGGCCTGCGTCCGAACT-3’ (sense) and 5’-
CTCTCATGGCCTTGGCTGGAGCAT-3’ (anti-sense); GAPDH 5’-
AACAGCGACACCCACTCCTC- 3’ (sense) and 5’-CATACCAGGAAATGAGCTTGACAA-
3’ (anti-sense).
85
Immunoblotting
Protein was extracted by lysing cells in 50 - 100 μl of RIPA lysis buffer (500 mM Tris, pH 7.4,
150 mM NaCl, 0.5% Na deoxycholate, 1% NP-40, 0.1% SDS and complete protease inhibitor
preparation containing leupeptin and aprotinin), incubated on ice for 30 min and centrifuged at
14,000 X g for 15 mins. Cell lysate supernatant was collected and protein levels were quantitated
using the Bradford assay. SDS loading buffer (2% SDS, 10% glycerol, 360 mM 2-
mercaptoethanol, 100 mM Tris) was added to cell lysates and boiled for 5 min. 40 - 100 μg of
total protein was separated using SDS-polyacrylamide gel electrophoresis (PAGE) and
transferred onto PVDF membranes. Membranes were blocked with 5% milk in TBS-tween
(0.1%) wash buffer, followed by incubation with primary antibodies overnight at 4°C. The next
day, membranes were washed and incubated with HRP-conjugated secondary antibodies for 1
hour at room temperature with gentle agitation. Proteins were detected using ECL detection
reagent (GE Healthcare, Amersham, UK). Primary antibodies used: phospho-Akt (Ser 473;
rabbit), Akt rabbit, phospho S6 (Ser 235/236; rabbit), S6 rabbit, phospho CSF1R rabbit and
GAPDH rabbit from Cell Signaling Technology (CST; Danvers, MA, USA); CSF1 mouse was
purchased from Santa Cruz Biotechnology (SCB; Dallas, TX, USA).
Flow Cytometry
Expression of select surface markers on AML cells was evaluated using flow cytometry, before
and after co-culture. A surface marker panel consisting of the following antibodies was set up
and utilized: CSF1R-PE/Cy7, CD34-APC/Cy7, CD38-APC, CD4-FITC, CD11b-BV421 and
CD117-PerCP/Cy5.5 (BioLegend, San Diego, CA, USA) and CD45-PE (Beckman Coulter).
Surface staining was performed by incubating cells with a cocktail of the antibodies in a total
86
volume of 100 μL wash buffer solution (2% FBS in 1 X PBS) for 30 minutes in the dark at room
temperature. Cells were then washed and re-suspended in 0.5 mL of wash buffer solution and
analyzed on a Beckman Coulter CANTO II flow cytometer (Beckman Coulter).
Cytokine Analysis
The Luminex MAGPIX system (Toronto, Ontario, Canada) as well as the services of Eve
Technologies (Calgary, Alberta, Canada) were used to assess cytokine levels in cell culture
supernatants. Supernatant from co-cultures of AML and MS-5 stromal cells were collected and
spun down (14,000 X g for 15 minutes) to remove debris and other cellular particulates.
Supernatants could then be stored at -80°C for a prolonged period of time or until analysis.
Supernatants were incubated with a cocktail of antibodies conjugated to metal beads (purchased
in the kit) as per the manufacturer’s protocol (Luminex, Toronto, Canada). Briefly, a cocktail of
antibody conjugated magnetic beads were added to a 96-well plate (purchased from Luminex).
The beads were washed twice with wash buffer after which cell culture supernatant was added to
each well, along with standards and controls. The plate was incubated in the dark at 4°C
overnight with gentle agitation. The next day, the beads were washed and detection antibody was
added and incubated for 1 hour with gentle agitation. After several washes, the plate was read on
a MAGPIX machine and data was analyzed using Bio-Plex software (Bio-Rad).
Statistical Analysis
Unless otherwise stated, mean ± S.E.M. values are given and P values were calculated using the
two-tailed unpaired Student’s t-test.
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2.4. RESULTS
High CSF1R expression is associated with poor clinical outcome in AML
CSF1R gene expression levels were evaluated in several publically available AML gene
expression datasets including The Cancer Genome Atlas (TCGA), Valk et al. and Metzler et al
(Metzeler et al., 2008; Valk et al., 2004). Valk et al. had identified several prognostically
significant AML subgroups or clusters based on gene expression signatures (Valk et al., 2004).
Using this, CSF1R gene expression levels were evaluated in these subgroups. It was found that
CSF1R was highly expressed in several of the groups, namely groups 1, 5 and 9, with variable
levels of expression across the 285 AML cases overall (Figure 2.1A). Each of the identified
clusters or subgroups were shown to be associated with overall survival (OS). Of the groups with
high CSF1R expression, patients in group 5 had poor OS rates (Figure 2.1B). Group 9 actually
had a relatively high OS due to the presence of inv(16) in this subgroup of patients, which is
associated with favourable clinical outcome when treated with “3+7” and consolidation therapy
(Delaunay et al., 2003).
In the TCGA, Valk and Metzler gene expression datasets, CSF1R gene expression levels
were evaluated and survival analysis was conducted based on the expression levels. AML cases
were dichotomized into ‘low’ and ‘high’ subgroups (CSF1Rlow vs. CSF1Rhigh, respectively)
based on cut-offs established for CSF1R gene expression levels using decision-tree analysis. To
determine whether CSF1R expression status is associated with clinical outcome, Kaplan-Meier
survival analysis was performed to compare overall survival (OS) between the CSF1Rlow vs.
CSF1Rhigh subgroups. Survival analysis revealed that CSF1Rhigh patients have shorter OS
compared to CSF1Rlow patients. The results from the different datasets are as follows: Valk HR =
1.5, P = 0.02; Metzeler: HR = 1.357, P = 0.02; TCGA: HR = 1.490, P = 0.04 (Figure 2.2 A-C).
88
Figure 2.1. CSF1R gene expression levels are high in certain prognostically significant
subgroups of AML patients.
(A) CSF1R gene expression levels were evaluated in the subgroups/clusters identified in the
Valk et al. gene expression dataset based on molecular signatures and prognostic significance.
(B) Overall survival (OS) probabilities of the identified subgroups (panel B adapted from Valk
et al.)
A
B
89
Figure 2.2. High CSF1R high levels are associated with shorter OS in AML patients.
Univariate association between CSF1R expression and clinical features was assessed using the
Fisher’s exact or Wilcoxon rank-sum tests and the log-rank test was used to compare survival
rates in Kaplan-Meier survival analysis. Shown are Kaplan-Meier survival plots comparing OS
between CSF1Rlow
and CSF1Rhigh
AML patients in to Valk (A), Metzler (B) and TCGA (C)
gene expression datasets.
A
B
C
90
CSF1R cell surface protein levels were also evaluated in clinical AML samples. CSF1R
cell surface protein expression was evaluated by flow cytometry for 146 AML patient samples
retrieved from the leukemia tissue bank at the Princess Margaret Cancer Centre (PMCC) at the
University Health Network (UHN) in Toronto, Canada. CSF1R expression was specifically
evaluated on the surface of AML blast cells. In the flow analysis, the AML blast population was
identified and gated based on a side scatter (SSC) ‘low’ and CD45 ‘dim’ gating strategy
(Lacombe et al., 1997). AML blasts are primitive, undifferentiated progenitor cells and are hence
less granular, thereby having low SSC properties. Moreover, blasts also express low levels of the
hematopoietic cell surface marker CD45, the expression of which increases as cells differentiate.
After the blast population was identified, expression levels of CSF1R were evaluated in each of
the AML cases. Figure 2.3A outlines the gating strategy and general workflow of the analysis.
Decision tree analysis was conducted to determine an optimal cut-off for CSF1R protein
expression levels in order to dichotomize patients into clinically relevant CSF1Rhigh vs.
CSF1Rlow subgroups (Figure 2.3B). Analysis of the flow cytometry cell surface protein
expression data in the context of clinical patient information, allowed for the compilation of a
protein-based expression dataset. Kaplan-Meier survival analysis was then conducted to compare
OS in the established CSF1Rhigh and CSF1Rlow subgroups. The survival analysis showed that
CSF1Rhigh patients had shorter OS times compared to CSF1Rlow patients (Figure 2.3C). These
results were consistent with the results of the survival analysis conducted in the gene expression
datasets, indicating that CSF1R RNA transcript levels, and CSF1R cell surface protein
expression levels both identify patients with a worse outcome using standard induction therapy.
Next, in the cell surface protein expression dataset, the AML patients were stratified into
different subgroups based on molecular profiles, namely patients with and without the presence
91
of FLT3-ITD and NPM1c, which are common mutations found in approximately 25-30% and
30% of all AML cases, respectively. CSF1R expression was evaluated within these groups and it
was observed that there was a significant difference in OS between CSF1Rlow and CSF1Rhigh
patients in the FLT3-ITD negative and NPM1c negative subgroups (Figure 2.3D, E). There was
no significant difference in OS between CSF1Rlow and CSF1Rhigh patients in the counterpart
positive subgroups for both FLT3-ITD and NPM1c. This demonstrates that CSF1R levels may
be prognostically significant in the absence of core AML-associated mutations. CSF1R cell
surface protein expression levels may therefore help stratify groups of patients that may
represent a ‘molecularly normal’ AML subset.
92
Table 2-1. Table of AML patient characteristics from the PMCC/UHN dataset.
Patients were dichotomized into ‘low’ vs. ‘high’ CSF1R subgroups (CSF1Rlow
vs. CSF1Rhigh
)
based on decision tree analysis techniques.
93
Figure 2.3. CSF1R cell surface protein levels are associated with poor AML clinical
outcome.
(A) Flow cytometry gating strategy in the identification of the AML blast population from the
bulk AML cell population. (B) Decision-tree analysis to determine an optimal expression value
cut-off for CSF1R expression levels.
A
B
Gating strategy of AML blasts
Decision tree analysis of CSF1R expression
94
D
E
C
Figure 2.3. CSF1R cell surface protein levels are associated with poor AML clinical
outcome.
Continued from previous page. (C-E) Kaplan-Meier survival plots comparing overall survival
(OS) between CSF1Rlow
vs. CSF1Rhigh
in AML patients and in FLT3-ITD and NPM1c
negative vs. positive AML patient subgroups.
95
Co-expression of CSF1R and CD34 exhibits heterogeneous patterns and association with
clinical OS in AML
Cell surface co-expression protein levels of CSF1R and CD34 were evaluated using flow
cytometry. CD34 is an important hematopoietic stem and progenitor cell marker and is an
adverse prognostic marker in AML. In the analyzed flow cytometry plots, CSF1R expression is
depicted on the y-axis while CD34 expression is on the x-axis, dividing the plot into 4 different
quadrants based on the co-expression of the two markers: CSF1Rlow/CD34low,
CSF1Rhigh/CD34low, CSF1Rhigh/CD34high, CSF1Rlow/CD34high. Across the same cohort of AML
cases as in the preceding analysis, varying co-expression patterns of CSF1R and CD34 were
observed, with the existence of multiple sub-populations based on CSF1R/CD34 levels (Figure
2.4A). For example, in a given sample that could be classified as being double positive for
CSF1R and CD34 (CSF1Rhigh/CD34high), one would likely expect to see a single cell population
residing in the CSF1Rhigh/CD34high fraction or quadrant. However, it was observed that while a
sample such as 090077 (Figure 2.4A) could be CSF1Rhigh/CD34high overall, it appears to have
two distinct cell subpopulations, each being positive for a single marker, and thus the two
markers are not co-expressed on the same cells. To capture this information, the quadrant
distributions can be represented as star or radar plots where each of the four arms in the plot
corresponds to a given co-expression pattern corresponding to the four different quadrants of the
flow plots (Figure 2.4B).
To evaluate the significance of the different CSF1R/CD34 distributions, unsupervised
cluster analysis was performed, yielding 3 distinct clusters: Cluster A: CSF1Rhigh/CD34low,
Cluster B: CSF1Rlow/CD34high and Cluster C: CSF1Rlow/CD34low (Figure 2.4C). A fourth cluster,
CSF1Rhigh/CD34high, would have been generated however it only contained two patients and thus
could not be characterized as a defined cluster. To evaluate the clinical significance of these
96
subgroups or clusters, Kaplan-Meier survival analysis was conducted to evaluate whether the
identified CSF1R/CD34 subgroups have an association with clinical patient outcome. Using a
cut-off finder tool, the optimal cut-off for CSF1R was found to be 75% so that CSF1R levels
>75% were defined to be a CSF1Rhigh subgroup, while levels <75% a CSF1Rlow subgroup. A
median cut-off (50%) was established for CD34 where patients with CD34 levels >50% were
classified to be a CD34high subgroup, and <50% a CD34low subgroup. Survival analysis revealed
that patients in the CSF1Rhigh/CD34low cluster had shorter OS times compared to the
CSF1Rlow/CD34high and CSF1Rlow/CD34low clusters. The CSF1Rlow/CD34low cluster or subgroup
had the best OS outcome followed by the CSF1Rlow/CD34high subgroup (Figure 2.4D). Therefore
high levels of either CSF1R or CD34 are associated with poor OS. In CD34low patients, there was
a significant difference between OS between the CSF1Rlow/CD34low and CSF1Rhigh/CD34low
subgroups, with the patients in the latter having a worse prognosis. Therefore CSF1R is
prognostically significant in CD34low patients, identifying a CD34 low group with worse long-
term survival.
97
A B
C
98
D
Figure 2.4. CSF1R and CD34 co-expression patterns are associated with OS.
(A) Shown are plots of 6 different AML patient samples depicting co-expression patterns of
CSF1R and CD34. Each quadrant is numbered according to expression levels: 1-
CSF1Rlow
/CD34low
, 2- CSF1Rhigh
/CD34low
3- CSF1Rhigh
/CD34high
4- CSF1Rlow
/CD34high
. (B)
Co-expression patterns in AML patients (n = 146) represented in radar plot format. (C) Radar
plots of the identified clusters. (D) Kaplan-Meier survival plots
of the different clusters.
99
CSF1R expression in AML cell lines
In order to interrogate CSF1-CSF1R ligand-receptor signaling within AML-BM stromal
cell interactions, AML cell lines and patient samples were examined for CSF1R expression to
determine which cell types would be useful and relevant in the studies. For this, CSF1R cell
surface protein levels were evaluated by flow cytometry in a panel of AML cell lines. Of the
AML cell lines interrogated (OCI/AML-2, OCI/AML-4, OCI/AML-5, HL-60 and U937), all of
the lines showed positive CSF1R staining (Figure 2.5A). CSF1R cell surface expression levels in
AML patient samples were also evaluated by flow cytometry (Figure 2.5B). There was variable
expression of CSF1R in the patient samples evaluated, with some samples having high
expression, and some with little to no expression of CSF1R. For the studies in this work, samples
with exclusively high CSF1R expression vs. low CSF1R expression were used.
100
A
B
Figure 2.5. CSF1R expression in AML cell lines and patient samples. CSF1R cell surface
protein expression were evaluated by flow cytometry. Shown are a panel of (A) AML cell lines
and (B) select AML patient samples.
101
AML cells do not show significant growth responses to exogenously presented soluble CSF1
AML cells were first tested for their response to exogenously presented human
recombinant CSF1 (rhCSF1) and conditioned medium (CM) from the engineered MS-5 stromal
cell lines. The OCI/AML-4 and OCI/AMl-5 cell lines are dependent on growth factors derived
from the CM of 5637 bladder carcinoma cells. 5637-CM is enriched in factors including GM-
CSF, G-CSF, as well as CSF1 and SCF in smaller amounts (Quentmeier, Zaborski, & Drexler,
1997). For the experiments, OCI/AML-4 and OCI/AML-5 cells were grown in the absence of
5637-CM to evaluate the efficacy of CSF1 as a single factor. OCI/AML-4, OCI/AML-5 and a
CSF1Rhigh patient sample (090017) were treated with soluble recombinant human CSF1
(rhCSF1), as well as CM from the different MS-5 stromal cell lines (EV, hCSF1-sol and hCSF1-
mem) for a period of 72 hours. It was observed that treatment of AML cells with variable levels
of rhCSF1 or 10% CM from any of the MS-5 cell lines did not induce significant growth or
proliferation of AML cells in culture (Figure 2.6A). Moreover, cells did not survive in culture for
more than 72 hours with the addition of rhCSF1, and thus longer time points could not be
assessed. Higher percent concentrations of the different MS-5 CM were also tested but they
yielded results similar to the use of 10% MS-5 CM. This suggests that as an independent, soluble
factor, CSF1 is unable to induce the growth and proliferation of AML cells in culture. Moreover,
the fact that CM from any of the MS-5 cells, including hCSF1-expressing cells (particularly
hCSF1-sol MS-5 as it produces soluble CSF1 ligand) did not support AML growth, provides
further indication that the context or manner of CSF1 presentation may be of major importance
for AML cell growth.
B
102
A
B
C
Figure 2.6. AML cells show minimal growth responses to exogenous soluble CSF1.
(A-C) AML cells (OCI/AML-4, OCI/AML-5 and patient sample 090017) were treated with
recombinant human CSF1 (rhCSF1; 10 ng/mL) and 10% conditioned medium (CM) from the
different MS-5 stromal cell lines for 72 hours (initial cell number: 1x10^5). Cell counts were
performed using trypan blue.
103
CSF1 transduction in the MS-5 stromal cell line
Since soluble recombinant CSF1 protein was unable to exert any significant effects on
the proliferation and survival of AML cells in culture, the effects of stromal cell-presented CSF1
were evaluated through AML-MS-5 cell co-cultures. For this, the murine MS-5 stromal cell line
was transduced with either soluble human CSF1 (hCSF1-sol) or membrane-
bound/transmembrane hCSF1 (hCSF1-mem). The system was designed as such because as noted
in Chapter 1 (section 1.3.2. and Table 1-5), many factors, such as ligand-receptor pairs, do not
show cross-species compatibility, including mouse CSF1, which does not act on human CSF1R
(Garceau et al., 2010). Given this, expressing the human ligand in mouse cells would allow for
the specific interrogation of the human CSF1-CSF1R interaction, with limited interference from
other factors because of the species incompatibility between the cells.
Despite being a murine stromal cell line, the MS-5 cell line has been shown to be able to
support both the short- and long-term growth and maintenance of human hematopoietic and
leukemic cells in-vitro (Berthier et al., 1997; Nishi et al., 1997). The MS-5 cell lines generated
were: MS-5-EV (empty vector), MS-5 hCSF1-sol and MS-5 hCSF1-mem. The overexpression of
CSF1 was confirmed by qPCR and western blotting (Figure 2.7A, B).
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A
B
Figure 2.7. CSF1 overexpression in MS-5 stromal cell lines.
MS-5 cells were transduced with a retroviral vector containing soluble human CSF1 (hCSF1-sol)
and membrane-bound human CSF1 (hCSF1-mem). CSF1 gene and protein expression were
evaluated by (A) qPCR and (B) western blot.
105
CSF1 promotes the growth, survival and adhesion of AML cells in AML-stromal cell co-
culture
The goal of the co-culture studies was to observe the effect of continuously exposing
AML cells to CSF1 ligand directly produced, and presented by stromal cells. CSF1R positive
AML cell lines (OCI/AML-4, OCI/AML-5, OCI-AML-2 and U937) were tested for growth and
survival in the stromal cell co-culture assays. 5637-CM was not added to the co-cultures of
OCI/AML-4 and OCI/AML-5 cells in order to create minimal growth conditions for the
evaluation of CSF1 as a single factor. The growth of AML primary patient samples in stromal
cell co-cultures was also evaluated.
For the co-culture assays, MS-5 cells were plated in 6-well plates and allowed to adhere
overnight, creating a feeder layer for the AML cells. AML cells were then directly plated on the
stromal cells to form a co-culture system (see Materials & Methods) with each of the three
different MS-5 cell lines. The long-term growth and proliferation of AML cells was assessed
over an average period of 2 weeks. It was found that the OCI/AML-2 and U937 cell lines
exhibited no significant difference in their growth and proliferation in co-cultures with hCSF1-
expressing MS-5 cells (both hCSF1-sol and hCSF1-mem) vs. non hCSF1-expressing MS-5-EV
control cells (Figure 2.8A). Both cell lines grew effectively on the three types of MS-5 stromal
cells, and in fact grew at such a rapid rate that they caused the co-cultures to ‘crash’, with
overgrowth of the AML cells causing the stromal cell layer to detach from the bottom of the dish
and die out. The growth of OCI/AML-2 and U937 cells was actually comparable to their growth
in normal cultures (without stromal cells) because these cell lines are growth-factor independent
and grow well in cultures without any added growth factor supplementation. Therefore,
providing any additional support, in the form of stromal cells and CSF1 in this case, did not
confer any additional advantage to the cells. On the other hand, hCSF1-expressing MS-5 cells
106
(both hCSF1-sol and hCSF1-mem) provided a significant proliferative advantage to OCI/AML-4
and OCI/AML-5 cell lines (grown in the absence of 5637-CM) compared to MS-5-EV control
cells (Figure 2.8B). The growth advantage conferred by hCSF1-expressing MS-5 cells was
readily apparent in the short term (i.e. 72 hours), and was sustained and enhanced in longer term
cultures of 2 weeks. These cells fared poorly in co-cultures with MS-5 EV cells, with little to no
cells surviving beyond a period of 2 weeks. In particular, MS-5 hCSF1-mem cells were better
able to support their growth compared to MS-5 hCSF1-sol cells, with a 3-fold increase in
OCI/AML-4 and OCI/AML-5 cells co-cultured with MS-5 hCSF1-mem cells compared to MS-
5-EV cells, and a 1.5-fold increase compared to MS-5 hCSF1-sol cells over a 2-week co-culture
period (P < 0.05). This demonstrates that CSF1 presented by MS-5 stromal cells supports the
proliferation and survival of growth factor-dependent AML cells (as opposed to cells that are
growth factor-independent), highlighting a CSF1-stromal cell dependency for these cells.
OCI/AML-4 and OCI/AML-5 cells demonstrated a significant amount of adhesion
(approximately 50-60%) to MS-5 hCSF1-mem cells compared to MS-5-EV and hCSF1-sol cells.
AML cells exhibited very little adhesion to the MS-5-EV cells and significantly less adhesion to
MS-5 hCSF1-sol cells (approximately 10%). In addition, the proliferation and growth of
OCI/AML-4 and OCI/AML-5 cells, particularly on MS-5 hCSF1-mem cells, was found to be
comparable to their growth under native 5637-CM supplemented conditions, indicating that
hCSF1-expressing MS-5 cells can compensate for, and act in lieu of 5637-CM supplementation
to provide the conditions necessary for cell growth. Taken together, these results highlight the
fact that there may potentially be key differences in how AML cells expressing CSF1R interact
with, and respond to the soluble vs. transmembrane forms of CSF1 ligand.
107
Figure 2.8. MS-5 stromal cells expressing hCSF1 support the proliferation and survival
of factor-dependent CSF1R-expressing AML cell lines.
(A) OCI/AML-2 and U937 AML cells were co-cultured with MS-5 EV, hCSF1-sol and
hCSF1-mem stromal cells for a period of 2 weeks. Images were taken of the co-cultures (left)
and AML cell numbers were quantified (right). (B) The factor-dependent OCI/AML-4 and
OCI/AML-5 AML cell lines were also co-cultured with the MS-5 stromal cell lines. Shown are
quantitations from n = 2 - 3 independent experiments ± SEM. *P < 0.001, **P < 0.0001.
A
B
108
AML primary samples are also highly growth factor-dependent ex vivo. Despite
supplementation with a host of growth factors, they cannot survive for more than a few days in
in-vitro cell cultures, which is the same case for OCI/AML-4 and OCI/AML-5 cells without
5637-CM supplementation. In this way, OCI/AML-4 and OCI/AML-5 cells are quite reflective
of primary samples in terms of their growth-factor dependency, as well as cellular characteristics
including morphology and adhesion.
The growth, proliferation and survival of primary AML samples with high CSF1R levels
(CSF1Rhigh) were compared to those with low CSF1R levels (CSF1Rlow) in co-cultures with the
MS-5 stromal cells. All of the primary AML samples chosen were selected to have low CD34
levels because it is a strong stem cell and adhesion marker, and clinically associated with poor
patient prognosis; being a strong factor, it may confound the effects of other factors, including
CSF1, and was thus excluded. CSF1Rhigh samples exhibited significantly higher proliferation,
with higher cell numbers in 5-week long-term co-cultures with both MS-5 hCSF1-sol and MS-5
hCSF1-mem cells compared to MS-5 EV cells (Figure 2.9A,B). AML cell numbers were 2-fold
higher after co-culture with MS-5 hCSF-1 mem cells compared to MS-5 hCSF1-sol cells.
CSF1Rhigh cells displayed a significant growth advantage particularly with MS-5 hCSF-1 mem
cells, with an average 11.5-fold difference in proliferation of cells cultured with MS-5 hCSF-1
mem cells compared to MS-5 EV cells (Figure 2.9C). On the other hand CSF1Rlow samples
displayed no growth and survival advantage on hCSF1-expressing MS-5 cells, with little to no
cells surviving in the co-cultures. Moreover, CSF1Rhigh cells also demonstrated significantly
more adhesion to MS-5 hCSF1-mem cells compared to MS-5 EV and hCSF1-sol cells.
MS-5 hCSF1-mem cells supported the long-term survival and maintenance of CSF1Rhigh
patient cells, with average survival times of 80 days, compared to MS-5 hCSF1-sol cells that
109
were able to maintain AML cells for 72 days and MS-5-EV cells for 50 days (Figure 2.9D). In
fact one sample (090077) was sustained on MS-5 hCSF1-mem cells for as long as 6 months.
This indicates that MS-5 hCSF1-mem cells in particular, not only enhance the growth and
proliferation of AML cells, but also the long-term survival of AML cells.
110
A
C
D
B
Figure 2.9. MS-5 stromal cells that express hCSF1 support the proliferation and survival of
primary AML cells that express CSF1R.
(A) CSF1Rhigh vs. CSF1Rlow AML patient samples were grown with the different MS-5
stromal cells (EV, hCSF1-sol, hCSF1-mem). Shown are images of co-cultures of representative
samples. (B) AML cell numbers (of 6 different primary samples) after co-culture with the
different MS-5 cells for a period of 2 weeks. (D) Days survival of AML patient samples co-
cultured with MS-5 cells.
111
Blockade of CSF1R inhibits AML growth in co-cultures
To show the direct and specific involvement of CSF1R in the observed support of AML
cells in CSF1-expressing MS-5 co-cultures, a CSF1R monoclonal antibody (Amgen) was used to
block the interaction between CSF1R and hCSF1. It was observed that addition of the CSF1R
antibody to AML-MS-5 co-cultures led to the reduced growth and proliferation of both
OCI/AML-4 and OCI/AML-5 cells particularly cultured with MS-5 hCSF1-expressing cells
(Figure 2.10A-D). Significantly marked reductions in AML cell numbers were observed in co-
cultures of MS-5 hCSF1-sol and hCSF1-mem cells, but not MS-5-EV cells. This indicates that
the CSF1R antibody is specific to blocking the CSF1-CSF1R interaction, which is why AML
cells in the MS-5 hCSF1 co-cultures were sensitive to the drug. In OCI/AML-5 cells there was a
dose-dependent effect of the CSF1R antibody up to a concentration of 0.001 µg/mL, above
which there was no significant difference in the activity of the antibody in terms of inhibiting cell
growth. At concentrations of 0.001 µg/mL, there was a 2-fold decrease in the number of cells
compared to in untreated co-cultures (co-cultures of both MS-5 hCSF1-sol and hCSF1-mem).
This indicates that blocking the CSF1-CSF1R interaction between stromal and AML cells has a
significant impact on AML cell proliferation, providing further evidence that this interaction is
important in promoting and supporting the growth and survival of AML cells.
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Figure 2.10. Blockade of CSF1R on AML cells inhibits their proliferation in co-culture
with MS-5 hCSF1 cells.
(A-D) OCI/AML-4 and OCI/AML-5 cell proliferation after addition of an anti-CSF1R
antibody (Ab) from Amgen for 72 hours to 1 week in co-cultures of MS-5 cells. Shown are
results from n = 2 independent experiments ± SEM.
A
C
B
D
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Co-culture of AML and hCSF1-expressing MS-5 stromal cells leads to changes in signaling
and cytokine levels in AML cells
Given the significant effects of stromal cell-presented hCSF1 on AML cell growth and
survival, it was postulated that the binding of CSF1R to CSF1 might result in the production of
signaling molecules and cytokines that may in part, drive the enhanced growth of the cells. To
explore this, multiplexed cytokine platforms (Luminex MAGPIX, Eve Technologies) were used
to evaluate a panel of nearly 30 different secreted human cytokines relevant in cell growth,
survival and hematopoietic processes and pathways. For this, cell culture supernatants from
AML (090017 patient sample)-MS-5 cell co-cultures were collected after 48 hours of culture and
subjected to analysis. It was observed that co-culture of AML cells with MS-5 hCSF1-mem led
to increases in levels of GM-CSF, PDGF-AA, IL-8, IL-12p40, MCP-1, MIP-1α and IL-1RA
(Figure 2.11A). The cytokines observed to be upregulated in AML cells are largely those
involved in inflammatory and growth processes, with most produced and secreted by
macrophages (i.e. IL-8, IL-1RA, IL-12, MIP-1α). At the same time, levels of some cytokines,
such as MDC (macrophage-derived chemokine, or CCL22), appeared to decrease. Addition of
the CSF1R antibody to the co-cultures led to a reduction in levels of the elevated cytokines,
indicating that their regulation is dependent on a CSF1-CSF1R interaction between AML and
MS-5 stromal cells.
Potential changes in signaling effectors downstream of CSF1R were also examined in
AML cells after co-culture. For this, OCI/AML-5 cells were co-cultured with MS-5-EV and MS-
5 hCSF1-mem cells for 24 hours, after which intracellular signaling proteins were assessed using
flow cytometry. Signaling molecules in growth and survival pathways downstream of CSF1R
were included in the panel of flow markers assessed, namely pAkt, pS6 and pERK. It was
observed that co-culture of OCI/AML-5 cells with MS-5 hCSF1-mem cells led to increased
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levels of pS6 as compared to co-culture with MS-5-EV cells (Figure 2.12A). On the other hand,
there were no changes in levels of pAkt and pERK in AML cells following co-culture. Addition
of the CSF1R antibody to the co-cultures abrogated the observed increase in pS6 in AML cells.
Given the observed increase in pS6 in OCI/AML-5 cells following co-culture with MS-5
hCSF1-mem cells, the effects of inhibition of mTOR was evaluated in the co-cultures. It was
observed that the addition of the mTOR inhibitor MK-8996, led to decreased proliferation of
OCI/AML-5 cells grown with MS5 hCSF1-mem cells (Figure 2.12B). The mTOR inhibitor had
no effect on the growth of OCI/AML-5 cells co-cultured with MS-5 EV control cells. This
indicates that mTOR signaling is activated in AML cells exposed to CSF1, via stromal cells,
helping to promote AML cell growth.
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A
Figure 2.11. AML cells exhibit changes in cytokine production and mTOR pathway
activation after co-culture with hCSF1-expressing MS-5 cells.
(A) Multiplexed cytokine array analysis reveals changes in cytokines between MS-5-EV and
MS-5 hCSF1-mem cells which are reversed with a CSF1R blocking antibody (Ab).
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A
B
Figure 2.12. OCI/AML-5 cells exhibit mTOR pathway activation after co-culture with
hCSF1-expressing MS-5 cells.
(A) Intracellular flow cytometry to measure pS6 levels which are higher in AML cells after
co-culture with MS-5 hCSF1-mem cells; levels are reduced with a CSF1R Ab. (B) Addition
of an mTOR inhibitor (MK-8996) to co-cultures of OCI/AML-5 and MS-5 hCSF1-mem
cells. Shown are results from n = 3 independent experiments.
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The CSF1-CSF1R interaction induces changes in AML cell surface markers
Since culture of AML cells with MS-5 stromal cells led to changes in growth and
signaling, it was investigated whether the CSF1-CSF1R interaction could also lead to changes in
cell surface markers. A panel of human cell surface antigens was devised containing markers
involved in growth, survival and differentiation pathways relevant to hematopoietic and/or
leukemic cells. The markers included in the panel were CD34, CD38, CD4, c-Kit and CD11b.
The cell surface proteins CD34, CD38 and c-Kit are associated with hematopoietic stem cells
and hematopoietic cell differentiation, while CD11b is a marker found on mature monocytes and
macrophages. After co-culture of OCI/AML-5 cells with MS-5 cells for 2 weeks, it was found
that there were significant increases in levels of the hematopoietic stem cell markers CD34 and
c-Kit after culture with hCSF1-expressing MS-5 cells, particularly hCSF1-mem cells (Figure
2.13A,B). There was also an observed decrease in levels of CSF1R. Reduction of cell surface
levels of CSF1R may indicate receptor internalization and downregulation resulting from
regulation of receptor engagement and signaling. While there were some changes in these
markers after culture with MS-5-EV cells, they were not as significant when compared to culture
with MS-5 hCSF1-mem cells. Addition of the blocking CSF1R antibody (Ab) reversed these
effects with reductions in cell surface levels of CD34 and c-Kit on OCI/AML-5 cells (Figure
2.13C). The increased expression of hematopoietic stem cell markers (CD34 and c-Kit) may
indicate a cellular re-programming of cells to a more primitive, immature phenotype. This could
seemingly help create a pool of self-renewing progenitor cells in the leukemia.
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A
119
Figure 2.13. AML cells grown in co-culture with hCSF1-expressing MS-5 cells exhibit
changes in cell surface marker expression.
(A) OCI/AML-5 cells were grown in co-culture with MS-5 EV, hCSF1-sol and hCSF1-mem
cells for 2 weeks. Surface marker expression was assessed using flow cytometry. (B) Addition
of a CSF1R blocking antibody (for 48 hours). Shown are representative results from n = 3
independent experiments.
B
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Human AML cells exhibit enhanced engraftment in humanized CSF1 mice
As discussed in the introduction, over 50% of AML primary samples fail to engraft in
conventional mouse models such as the NOD/SCID mouse. OCI/AML-5 cells also do not engraft
in NOD/SCID mice based on work in our lab. Given this, humanized knock-in mouse models
can offer an advantage where mice are ‘humanized’ through transgenic introduction of human
factors such as human cytokines and growth factors. In this work, a humanized CSF1 (huCSF1)
transgenic knock-in mouse from Jackson Laboratories/Regeneron was used to investigate
whether the presence of human CSF1 in the mouse may help the engraftment of CSF1R positive
AML cells that do not engraft in conventional mouse models. For this, OCI/AML-5 cells, as well
as several patient samples that were found to be non-engrafting in NOD/SCID mice, were
separately injected into huCSF1 mice and engraftment was assessed after a period of 5 -7 weeks.
It was observed that there was significant engraftment of the AML cells in the BM of the mice,
as assessed by cell surface staining of the human (h) hematopoietic cell marker CD45 (hCD45)
(Figure 2.14A). OCI/AML-5 cells demonstrated engraftment of up to 70%, while for primary
samples, it was over 35 – 40 %. This suggests that hCSF1 is an important factor in the homing
and engraftment of AML cells within the BM. OCI/AML-5 cells were isolated from the BM and
evaluated for cell surface marker expression. It was observed that there were increases in the
levels of the hematopoietic stem/progenitor markers CD34 and c-Kit on the surface of
OCI/AML-5 cells after growth in the huCSF1 mice (Figure 2.14B). This was similar to the
observed increases in these markers in the AML-MS-5 co-cultures, where OCI/AML-5 cells
displayed increases after co-culture with MS-5 hCSF1-mem cells. This indicates that both the
hCSF1 stromal cell co-culture and the humanized CSF1 mouse models are able to mimic and re-
capitulate each other’s characteristics for the growth of AML cells as driven by CSF1.
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Figure 2.14. AML cells exhibit engraftment in humanized CSF1 (huCSF1) mice, with
changes in cell surface marker expression.
(A) Plot of engraftment levels of OCI/AML-5 cells in huCSF1 mice as determined by percent
cell surface human CD45 (hCD45) expression evaluated by flow cytometry. (B) Cell surface
marker expression on OCI/AML-5 cells was evaluated by flow cytometry. The first column of
histograms on the left shows the cell surface marker expression profile of OCI/AML-5 cells
grown under endogenous conditions in culture. Shown are results from n = 3 independent
experiments (B).
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Further to this, BM stromal cells were isolated from the huCSF1 mice and grown in co-
culture with OCI/AML-5 cells. hCSF1 expression in the BM stromal cells was first confirmed by
western blot analysis (with use of a human specific antibody), which showed expression of
hCSF1 in the cells (Figure 2.15A). In particular, the cells appeared to express hCSF1-mem and
not hCSF1-sol. Co-culture of OCI/AML-5 cells with the huCSF1 mouse BM stromal cells led to
significant proliferation of the cells on the stromal cells compared to MS-5 EV control cells
(Figure 2.15B). The growth and proliferation of the OCI/AML-5 cells in culture with the
huCSF1 mouse BM stromal cells was in fact comparable to their growth on MS-5 hCSF1-mem
cells, indicating that the huCSF1 mouse-derived BM cells are likely similar in nature and
function to the MS-5 hCSF1-mem stromal cell line used in these studies. Furthermore, addition
of the CSF1R blocking antibody led to the reduced proliferation of OCI/AML-5 cells (Figure
2.15C). Finally, cell surface marker expression was also altered on OCI/AML-5 cells after co-
culture with the huCSF1 BM stromal cells, with significant increases in levels of CD34 and c-Kit
which were reversed with addition of the CSF1R antibody (Figure 2.15D). This is consistent
with the results of co-culturing OCI/AML-5 cells with MS-5 hCSF1-mem cells, as well as
injecting them into the huCSF1 mouse itself. Taken together, this demonstrates that the huCSF1
mouse is an improved mouse model for AML, as it provides the improved engraftment of human
AML cells that express CSF1R. Moreover, AML cells grown in huCSF1 mice re-capitulate
much of the cellular growth and phenotypic features seen in the in-vitro MS-5 hCSF1 stromal
cell co-culture model.
Taken together, the data presented in this chapter supports a role for CSF1, particularly
transmembrane CSF1, in promoting the growth, signaling and leukemic phenotype of AML
cells.
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A
B
C
Figure 2.15. BM stromal cells derived from huCSF1 mice support AML cell proliferation.
(A) Western blot of hCSF1 expression in BM stromal cells derived from huCSF1 mice. (B)
OCI/AML-5 cells co-cultured with BM stromal cells from huCSF1 mice, along with the MS-5
EV and hCSF1-mem cell lines, for a period of 2 weeks. (C) Addition of CSF1R Ab to co-
cultures of OCI/AML-5 and huCSF1 mouse-derived BM stromal cells. (D) Changes in cell (48
hours culture). Surface marker expression by flow cytometry after culture of OCI/AML-5 cells
with huCSF1 mouse-derived BM stromal cells for a period of 2 weeks. Significance at *P <
0.001, **P < 0.0001, ***P < 0.002 compared to MS-5 EV control. Results from n = 3
independent experiments.
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D
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2.5. DISCUSSION
As an important factor in the differentiation of myeloid cells, CSF1R has been classically
studied in the context of monocyte/macrophage development in normal individuals, where
normal cell immune cells infiltrate sites of inflammation, cancer, etc. In contrast, its role in
myeloid malignancy has not been deeply explored, likely to its consideration as a marker of
differentiation and more mature type cells. Herein, we have shown that in AML: 1) CSF1R is a
clinically significant marker that shows an association with clinical patient outcome, and 2) the
CSF1-CSF1R ligand-receptor pair supports and promotes leukemogenesis in the context of
AML-BM stromal cell interactions.
In this work, CSF1R was shown to be a clinically relevant marker that may help
prognostically stratify AML patients at both the gene and protein expression levels. Interrogation
of AML gene expression datasets and protein expression data revealed significant associations
between CSF1R levels and overall survival (OS). In the Valk et al. gene expression dataset,
CSF1R gene expression levels were found to be high in specific, previously identified subgroups
or clusters.(Figure 2.1A). Overall, in the Valk dataset, as well as two other gene expression
datasets (Metzler and TCGA), the dichotomization of AML patients into CSF1Rhigh and
CSF1Rlow subgroups revealed that CSF1Rhigh patients had poorer OS survival compared to
CSF1Rlow patients (Figure 2.2), indicating that CSF1R may aid in the stratification of AML
patients receiving induction style chemotherapy. This was further validated at the protein level
where high levels of cell surface protein levels of CSF1R on the blast cells of AML patients were
associated with poor OS, compared to low CSF1R levels (Figure 2.3C). The results obtained
from the gene expression datasets and cell surface flow cytometry data, were consistent with
each other, highlighting the relevance and potential usefulness of both RNA and protein-based
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approaches in the evaluation of CSF1R as a potential clinical marker in prognostic and/or
predictive clinical evaluations. Overall, CSF1R was demonstrated to be a significant clinical
marker across the cohorts of AML patients evaluated with its high expression levels in certain
AML cases, and its significant association with clinical survival. In addition, CSF1R was also
found to predict poor clinical outcome in subgroups of AML patients that do not harbour
common AML mutations such as FLT3-ITD and NPM1c (Figure 2.3D, E). This indicates that
CSF1R may help stratify subsets of AML that are ‘molecularly’ normal with respect to some of
the most common AML gene mutations. In this way, CSF1R could present as a potential
prognostic clinical marker, as it may help improve the stratification and treatment of AML
patients in less adverse risk groups.
CSF1R is highly expressed during monocytic differentiation and is thus typically
regarded as a marker of more differentiated cells in the monocytic-myeloid lineage. However,
we observed high levels of CSF1R expression on the blasts of nearly 70% of patients in our
AML cohort (Figure 2.3A and Table 2-1), suggesting that CSF1R may be aberrantly expressed
on more undifferentiated cells in a disease setting like AML. In line with this, CSF1R was
observed to be co-expressed with the stem cell marker CD34 on the blast cells of some AML
samples (Figure 2.4). Different patterns of CSF1R and CD34 co-expression were also found to
be associated with OS, with CSF1Rhigh/CD34low patients exhibiting poorer OS compared to
CSF1Rlow/CD34low patients. This again highlights the ability of CSF1R to be predictive of
clinical patient outcome in patients with less aggressive clinical characteristics such as low CD34
expression and/or the absence of gross molecular abnormalities like the presence of FLT3-ITD
or NPM1c.
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The clinical analyses highlighted CSF1R to be a prognostically significant clinical
marker in AML. This provided the rationale and basis for studying CSF1R functionally and in
the context of its ligand, CSF1, within a simulated BM microenvironment. Classic ligand-
receptor interactions are at the heart of juxtacrine signaling between cells, giving rise to distinct
microenvironments. To study the specific CSF1-CSF1R interaction, CSF1R-positive AML cells
and MS-5 stromal cells expressing hCSF1 were grown together in co-culture assays. The
expression of hCSF1 by mouse cells allowed the opportunity to determine what was happening
in the human AML cells, and the modified mouse stromal cells (Chapter 3). It was observed that
MS-5 hCSF1-mem and -sol cells enhanced and supported the long-term growth of the growth-
factor dependent cell lines OCI/AML-4 and OCI/AML-5, as well as AML patient samples
(Figure 2.8B). The proliferation and survival of CSF1R-expressing AML cells was almost
exclusively dependent on the CSF1-CSF1R interaction as MS-5-EV cells failed to support long-
term AML cell growth, primary AML cells expressing low levels of CSF1R (CSF1Rlow) failed to
grow on hCSF1 stroma, and addition of an anti-CSF1R antibody inhibited the proliferation of
OCI/AML-4 and OCI/AML-5 cells (Figure 2.10).
The proliferation and survival of OCI/AML-4 and OCI/AML-5 cells were significantly
supported by MS-5 hCSF1-mem cells in particular, with proliferation rates and numbers
comparable to growth under native conditions involving 5637-CM supplementation. Substituting
5637-CM with stromal cell-presented CSF1 therefore provided the same optimal growth
conditions for the growth of the cells. This highlights a role for CSF1 as an important context-
dependent factor (i.e. presentation by stromal cells) in supporting the proliferation and survival
of highly growth factor-dependent AML cells such as OCI/AML-4 and -5, and primary AML
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samples. This helps define more specified conditions (stroma) and factors (CSF1) for the support
of a subset of AML that expresses CSF1R.
AML cells exhibited significant adhesion to MS-5 hCSF1-mem cells compared to MS-5-
EV and hCSF1-sol cells, to which cells demonstrated little to no adhesion. The potent growth-
promoting properties of the membrane-bound/transmembrane form of CSF1 found in this study
is consistent with other studies. One study showed the membrane-bound form of CSF1 to
provide enhanced support of CSF1R-expressing myeloid cells compared to soluble CSF1, with
enhanced cell-cell adhesion and increased cellular growth (Tsuboi, Revol, Blanchet, &
Mouchiroud, 2000a). This suggests that the membrane-anchored form of the ligand may
effectively engage and support AML cells not only by directly binding to CSF1R on the surface
of AML cells, but also by potentially promoting additional adhesive connections between AML
and stromal cells; this provides added layers of support in addition to canonical ligand-receptor
binding. In this way, CSF1 may potentially cooperate with other stromal cell factors in the
physical, structural and biochemical support of AML cells.
Within stromal cells, transmembrane CSF1 may exert more robust effects compared to
soluble CSF1 because of its physical anchorage within the cell, which may provide it increased
stability and function. Moreover, the immobilization and anchorage of CSF1 ligand within the
stromal cell would seemingly provide AML cells continuous unhindered/uninterrupted exposure
to CSF1 compared to soluble CSF1, which could be readily depleted or undergo spatio-temporal
changes in terms of localization. Therefore, both the manner of growth factor ligand presentation
(i.e. by stromal cells) and isoform specificity are critical in dictating the nature of CSF1’s effects
on target AML cells that express CSF1R. Different forms of a ligand can indeed elicit distinct
effects as it has been shown that the soluble and membrane-bound forms of Kit ligand induce
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phosphorylation of different intracellular tyrosine residues on the c-Kit receptor to activate
different intracellular signaling pathways. This leads to varying effects on leukemic cell growth
and survival, with the soluble ligand failing to support leukemogenesis in-vivo (J L Gommerman,
Sittaro, Klebasz, Williams, & Berger, 2000). It therefore appears that membrane-anchored
proteins may harbour uniquely different functional properties compared to their soluble
counterparts.
It was observed that AML cells co-cultured with hCSF1-expressing MS-5 stromal cells
developed a LSC-like phenotype, with increased cell surface levels of CD34 and c-Kit (Figure
2.13). This may be suggestive of a re-programming of distinct AML cell populations to render a
more primitive, immature stem-cell phenotype. It could also be that a pre-existing sub-population
of CD34+/c-Kit+ cells are selected for by CSF1-expressing MS-5 stromal cells. This suggests
that the CSF1-CSF1R interaction between AML and stromal cells may drive the expansion and
maintenance of primitive pools of progenitor leukemic cells.
Notable changes in cytokine production were also observed after exposure of AML cells
to hCSF1-mem ligand. Primary AML cells were observed to have increased production of
inflammatory cytokines such as GM-CSF, IL-8 and MIP-1α among others (Figure 2.11A).
Levels of these were reduced with the addition of a CSF1R blocking antibody, indicating that the
CSF1-CSF1R interaction between AML and stromal cells directly induces the observed changes
in cytokine levels in AML cells. IL-8 and MIP-1α are largely pro-inflammatory cytokines that
are involved in chemotactic recruitment of inflammatory cell mediators including neutrophils
(Harada et al., 1994). Extracellular secretion of these cytokines in response to the CSF1-CSF1R
interaction has implications for added communication between AML and stromal cells. A recent
study reported that a CSF1R-expressing AML ‘support’ cell population exposed to CSF1 and
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Hepatic Growth Factor (HGF) led to further upregulation of HGF and other cytokines in the cells
(in a positive feedback loop), and that these paracrine signaling cytokines could be blocked by a
CSF1R inhibitor (GW-2580) (Edwards et al., 2019). Interestingly, the authors were unable to
identify or characterize the CSF1R-expressing ‘support’ cells, but it appeared that the cells were
a part of the bulk cell population of the primary AML samples assessed. Signaling cytokines can
therefore mediate cross-talk between cells to elicit and sustain production of cytokine factors
through feedback loops. Moreover, transfer of materials, including exosomes and entire
organelles such as mitochondria, has been shown to occur between stromal and AML cells
(Moschoi et al., 2016; H. Yang et al., 2018). This highlights how potentially different, and
secondary, modes of cell-cell communication can arise and be fostered by primary ligand-
receptor interactions.
mTOR signaling appeared to be activated in OCI/AML-5 cells exposed to MS-5 hCSF1-
mem cells, as observed through increases in pS6 (Figure 2.12A). This was blockable with a
CSF1R inhibitor. Moreover, use of an mTOR inhibitor in OCI/AML-5 – MS-5 hCSF1-mem cell
co-cultures was able to reduce the proliferation of OCI/AML-5 cells, indicating that mTOR is an
important target activated in AML cells as a result of the CSF1-CSF1R interaction. It therefore
appears that interacting AML and BM stromal cells display a dependency on a CSF1-CSF1R
axis which can potentially be therapeutically targeted at various levels.
The employment of a humanized CSF1 mouse model provided predicted and promising
in-vivo results, with demonstrated engraftment of CSF1R+ AML cells (OCI/AMl-5 and primary
AML samples) that do not engraft in traditional NOD-SCID mouse models (Figure 2.14A). This
highlighted a CSF1 dependency for the engraftment of CSF1R-expressing AML cells, indicating
a potential role for the ligand-receptor pair in the adhesion and homing of AML cells within the
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BM. BM stromal cells obtained and propagated from the huCSF1 mice were able to support
OCI/AML-5 cell growth in co-culture assays (Figure 2.15B,C); this was accompanied by the
same cell surface marker changes observed in cells directly engrafted in the huCSF1 mice
(Figure 2.14 B and 2.15D). These cell surface marker changes were also consistent with those
observed in OCI/AML-5 cells co-cultured with MS-5 hCSF1-mem cells, not only confirming the
results, but also demonstrating that the in-vitro and in-vivo systems are similar to each other.
These models can therefore serve as effective experimental tools for the study of the CSF1-
CSF1R interaction within the BM microenvironment of AML.
Taken together, CSF1R appears to be a biologically and clinically relevant marker in
AML, as it demonstrates a significant association with clinical patient outcome, and plays an
important role in AML-stromal cell interactions. The CSF1-CSF1R interaction enhances AML
cell growth, promotes an undifferentiated LSC-like phenotype, and induces changes in
intracellular and cytokine signaling factors, within a BM stromal cell context. Moreover, the
transmembrane form of CSF1 elicits significantly more potent effects compared to soluble CSF1,
highlighting the significance of structural and functional differences between CSF1 isoforms on
the support of AML cells. The CSF1-CSF1R axis thus holds considerable biological and clinical
value in AML and its microenvironment, thereby presenting as an attractive target for future
AML therapies.
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CHAPTER 3
CSF1 ligand signaling in AML-bone marrow stromal cell interactions
This chapter is in preparation for a manuscript to be submitted for publication
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3.1. ABSTRACT
In this study, the potential signaling role of the hematopoietic ligand colony stimulating
factor 1 (CSF1) was investigated in AML in the context of a BM stromal cell microenvironment.
It was found that CSF1 contains a potential, highly conserved PDZ domain binding motif
(PDBM) in its C-terminus that may interact with the serine protease HtrA1 to activate mTOR
signaling in MS-5 stromal cells, which in turn appears to impact on the paracrine support of
AML cells. While overexpression of transmembrane human CSF1 (hCSF1-mem) in MS-5 cells
was found to enhance the long-term growth and survival of AML cells, engineered deletion of
CSF1’s PDBM (hCSF1 ΔPDBM) resulted in reduced AML cell proliferation in in-vitro co-
culture assays. hCSF1-expressing MS-5 cells were observed to have a higher proliferation rate,
changes in cytokine production, and activation of mTOR signaling, as observed through
decreased TSC2 and increased pS6 levels, compared to non-hCSF1 expressing MS-5 cells. These
effects were lost and/or reversed in MS-5 hCSF1 ΔPDBM cells. Moreover, siRNA-mediated
knockdown of HtrA1 in MS-5 hCSF1-mem cells led to increased TSC2 and decreased pS6
levels, indicating inhibition of mTOR signaling. Taken together, these results demonstrate that
CSF1 has the ability to signal within MS-5 stromal cells to activate a CSF1-HtrA1-S6 axis.
Modulation of the stroma by CSF1 in turn has implications for its support of AML cells. As a
stromal cell ligand, CSF1 may therefore participate in bi-directional/multi-component signaling,
including PDZ-based intracellular signaling, to promote supportive interactions between AML
and BM stromal cells.
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3.2. INTRODUCTION
Acute Myeloid Leukemia (AML) is a highly complex and heterogeneous clonal disorder
of the bone marrow (BM). Its incidence increases with age and despite showing an initial
response to treatment, more than half of all AML patients relapse within 1-2 years of remission
and subsequently die of their disease (Liersch et al., 2014). AML can be described as a BM
failure state, characterized by decreased production of normal cells and increased production of
immature cells that are blocked in their ability to differentiate; these latter cells are able to
proliferate extensively as well as self-renew, a property essential for the maintenance of the
disease (Betz & Hess, 2010b; Ferrara & Schiffer, 2013b).
The BM is the principal site of hematopoiesis. The BM is a niche microenvironment
comprised of cells, growth factors and other structural elements, collectively known as the
stroma, which is important in regulating hematopoiesis (Morrison & Scadden, 2014b).
Alterations in components of the BM niche may occur to support malignant processes. For
example, it has been shown that osteoblasts with activating mutations in β-catenin leads to
enhanced HSC proliferation and development of leukemia (Kode et al., 2014). On the other
hand, malignant cells may effectively usurp their microenvironment to make it conducive for
tumorigenesis (Colmone et al., 2008). Both scenarios underscore the importance of the BM
microenvironment as a functionally important player in maintaining hematopoietic homeostasis.
Colony-stimulating factor 1 (CSF1) is a cytokine produced by stromal cells in the BM
that directs the differentiation, growth and maturation of myeloid-lineage cell precursors into
mature monocytes, macrophages and dendritic cells via binding to the cell surface receptor,
CSF1R, on target cells. CSF1 is structurally related to other hematopoietic ligands including Kit
ligand and Flt3 ligand. CSF1 regulates a number of other important biological processes
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including development of the placenta, uterine contractions and microglial cell development in
the brain, and serves as an unfavourable prognostic marker in some cancers such as renal and
liver cancers. In its active form, CSF1 exists as a disulfide-linked homodimer. There are two
predominant isoforms of CSF1, the first a heavily glycosylated membrane-bound or
transmembrane glycoprotein, and the second as either a soluble secreted glycoprotein or
proteoglycan. Transmembrane CSF1 can actually be slowly cleaved to release a soluble version
of the ligand (Horiuchi et al., 2014). In the BM, the transmembrane form of CSF1 predominates
and is largely produced by BM stromal cells such as fibroblasts and endothelial cells. It has been
shown that different ligand isoforms can elicit distinctly different phenotypic and signaling
effects. For example, the soluble and membrane forms of Kit ligand induce phosphorylation of
different intracellular tyrosine residues on the c-Kit receptor and subsequently activate different
intracellular signaling pathways (J L Gommerman et al., 2000).
Intracellular signal transduction pathways are mediated by interactions between proteins
possessing unique signaling domains, and proteins containing specific recognition binding sites
for these domains. PDZ (Postsynaptic density 95, PSD-85; Discs large, Dlg; Zonula occludens-1,
ZO-1) domains are amongst the most common protein-protein interaction domains found in
mammalian species. PDZ domains are typically 80-90 amino acids in length and found in
approximately 180 different human proteins (Doyle et al., 1996; Lee & Zheng, 2010). PDZ
domains bind to short structural sequences or motifs known as PDZ domain binding motifs
(PDBM). PDBMs are typically 4-6 amino acids in length and located at the extreme C-terminus
of target proteins where they serve as docking sites for the recruitment and activation of PDZ
domain-containing proteins.
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Amongst transmembrane proteins, the Ephrin family of ligands has been well described,
largely through the work of Tony Pawson, to participate in reverse intracellular, or bi-directional
signaling through PDZ-based protein-protein interactions. The Ephrin B1 ligand in particular has
been shown to interact with the PDZ domain of intracellular proteins such as syntenin and the
tyrosine phosphatase FAP-1 which are involved in cytoskeletal organization and protein
trafficking in neurons (Holland et al., 1996; D. Lin et al., 1999). Similarly, the C-terminal PDBM
of transmembrane transforming growth factor α (TGF-α) has been demonstrated to interact with
syntenin as well as the Golgi protein p59/GRASP55 in the Golgi apparatus, both of which
mediate targeting of the ligand to the cell membrane (Fernández-Larrea et al., 1999; Kuo, 2002).
Moreover, in cells of the BM, it has been shown that RANK secreted from osteoclasts (via
vesicles) can bind to transmembrane RANK ligand (RANKL) expressed on osteoblasts to
activate reverse signaling to promote bone formation (Y. Ikebuchi et al., 2018).
Previous unpublished work by our group revealed that the specific PDBM sequence of
Kit ligand (KitL) binds to intracellular HtrA1 (data not shown). The mammalian high
temperature requirement A (HtrA) is a family of trypsin-like serine proteases that contains at
least one C-terminal PDZ domain in its structure (Clausen, Southan, & Ehrmann, 2002b;
MURWANTOKO et al., 2004). HtrA proteases function as molecular chaperones and help
mediate the degradation of misfolded proteins (Clausen et al., 2002b; Krojer et al., 2002). The
human HtrA family consists of at least four members, HtrA 1 - 4, of which HtrA1 is primarily
soluble/secreted and expressed in the BM (Clausen et al., 2011). In the BM, HtrA1 plays key
roles in osteogenesis, bone remodelling and musculoskeletal development (Tiaden et al., 2012b).
Cytoplasmic HtrA1 has been shown to cleave tuberin/tuberous sclerosis 2 (TSC2), a negative
regulator of the mammalian target of rapamcyin (mTOR), followed by activation of the mTOR
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targets 4E-BP1 and S6K (Campioni et al., 2010). Because CSF1 shares high sequence and
PDBM similarity to KitL, it was postulated that HtrA1 may also be a CSF1 binding partner.
Furthermore, since HtrA1 has been shown to be a regulator of TSC2, this provided rationale for
examining mTOR signaling in the proposed setting.
Based on the hypothesis that the C-terminus of CSF1 contains a PDZ binding motif we
specifically set out to test the functionality of the PDBM of transmembrane CSF1 (hCSF1-mem)
using stromal cells engineered to express natural or mutant forms of hCSF1. Based on this it was
evident that CSF1 can function as a signaling ligand in both intracellular and intercellular
communication through multi-directional pathways (i.e. forward and reverse signaling).
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3.3. MATERIALS AND METHODS
DNA Plasmids and Gene Transduction
The full length membrane-bound/transmembrane variant of human CSF1 (hCSF1) cDNA was
purchased from OriGene (Rockville, MD, USA). It was used as a template to generate a PDBM
deletion mutant (ΔPDBM) by PCR reaction using the following PCR primers: 5’-
GAAGATCTACCATGACCGCGCCGGGCGCC-3’ (forward) and 5’
GGAATTCCTACTGTCTGTCATCCTGAGTC -3’ (reverse). Full length hCSF1-mem and
hCSF1-mem ΔPDBM were cloned into the Lenti-X Tet-off Advanced Inducible Expression
System (Clontech, Mountain View, CA, USA). These constructs were transduced into murine
MS-5 cells by first producing lentivirus through calcium phosphate transfection of 293-T cells
with psPAX2 and VSVG as described previously (Life Technologies). Virus rich medium was
collected 48 and 72 hours post-transfection. MS-5 cells were infected with the lentivirus for 24
hours with addition of 8 μg/mL protamine sulfate. Infected cells were obtained by puromycin
selection. The MS-5 Tet-off cell lines generated were: EV, hCSF1-mem and hCSF1-mem
ΔPDBM.
Cell Culture
Murine MS-5 stromal cells were cultured in α-MEM complete medium with 10% fetal bovine
serum (FBS), 100 units/mL penicillin and 100 μg/mL streptomycin at 37°C in 5% CO2. Human
OCI/AML-4 and OCI/AML-5 cell lines were cultured in the same conditions as the MS-5 cells,
but with the addition of 10% conditioned medium (CM) from 5637 bladder carcinoma cells.
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Co-culture Assays
For co-culture assays, a stromal cell feeder layer was first established by seeding 1.5 x 105 MS-5
cells in 6-well plates and allowing them to adhere overnight. The following day, the culture
medium was removed and 1.5 x 105 AML cells (OCI/AML-4 and OCI/AML-5 cell lines) were
added to the MS-5 cells with addition of fresh medium. Co-cultures were maintained by demi-
depopulation of AML cells every 2-3 days as described previously. Briefly, half the culture
medium was removed by gently washing medium over the stroma to detach some of the adherent
AML cells in order to remove them. The same volume of fresh medium was then added to the
cultures.
Growth Curves
MS-5 growth curves were performed by seeding 1 x 105 cells in 6-well plates (separate plates for
each different time point). Cells were counted daily by trypsinizing the cells and staining them
with trypan blue. Cells were counted manually using a haemocytometer.
Immunoblotting
Protein was extracted by lysing cells in 50-100 μL of RIPA lysis buffer (500 mM Tris, pH 7.4,
150 mM NaCl, 0.5% Na deoxycholate, 1% NP-40, 0.1% SDS and complete protease inhibitor
preparation containing leupeptin and aprotinin), incubated on ice for 30 min and centrifuged at
14,000 X g for 15 mins. Cell lysate supernatant was collected, and protein levels quantified using
the Bradford assay. SDS loading buffer (2% SDS, 10% glycerol, 360 mM 2-mercaptoethanol,
100 mM Tris) was added to cell lysates and boiled for 5 min. 40 - 100 μg of total protein was
separated using SDS-polyacrylamide gel electrophoresis (PAGE) and transferred onto PVDF
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membranes. Membranes were blocked with 5% milk in TBS-tween (0.1%) wash buffer,
followed by incubation with primary antibodies overnight at 4°C. The next day, membranes were
washed, and incubated with HRP-conjugated secondary antibodies for 1 hour at room
temperature with gentle agitation. Proteins were detected using ECL detection reagent (GE
Healthcare, Amersham, UK). The primary antibodies phospho-Akt (Ser 473), Akt, phospho S6
(Ser 235/236), S6 and GAPDH were purchased from Cell Signaling Technology (CST, Danvers,
MA, USA). CSF1 and HtrA1 primary antibodies were purchased from Santa Cruz Biotechnology
(SCB, Dallas, TX, USA).
Cytokine Analysis
The Luminex MAGPIX system was used to measure cytokine levels in cell culture supernatants.
Supernatant from co-cultures of AML and MS-5 stromal cells were collected and centrifuged
(14,000 X g for 15 minutes) to remove debris and other cellular particulates. Supernatants could
then be stored at -80°C for a prolonged period of time, or until analysis. Supernatants were
incubated with a cocktail of antibodies conjugated to metal beads (purchased in the kit) as per the
manufacturer’s protocol (Luminex, Toronto, Canada). Briefly, a cocktail of antibody conjugated
magnetic beads were added to a 96-well plate (purchased from Luminex). The beads were
washed twice with wash buffer after which cell culture supernatant was added to each well,
along with standards and controls. The plate was incubated in the dark at 4°C overnight with
gentle agitation. The next day, the beads were washed, and detection antibody was added and
incubated for 1 hour with gentle agitation. After several washes, the plate was read on a
MAGPIX machine and data was analyzed using Bio-Plex software (Bio-Rad).
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HtrA1 knockdown
HtrA1 and non-targeting control luciferase and GFP siRNA oligonucleotides were purchased
from Sigma-Aldrich (Oakville, ON, Canada). MS-5 cells were transfected with the siRNAs using
RNAiMax transfection reagent purchased from Thermo Fisher. Cells were transfected with 50 –
100 nM of siRNA according to the manufacturer’s protocol. 48 hours post-transfection, cells
were harvested, and subjected to western blotting analysis to evaluate levels of HtrA1 protein.
Statistical Analysis
Unless otherwise stated, mean ± S.E.M. values are given and P values were calculated using the
two-tailed unpaired Student’s t-test.
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3.4. RESULTS
Identification of a PDZ binding motif (PDBM) in CSF1
Based on sequence analysis and previous work by our group showing that KitL contains a
C-terminus PDBM, we wondered whether two other important hematopoietic transmembrane
ligands, CSF1 and Flt3L, might also contain a PDBM. PDBMs can vary in length from between
5-20 amino acids. Sequence analysis confirmed that KitL and CSF1 contain PDBMs in their
cytoplasmic regions, with the last amino acid (typically a valine residue in PDBMs) being
incompatible with binding to a PDZ domain (Figure 3.1A, top panel). Flt3L is unlikely to have a
PDBM as it lacks a terminal valine and shows considerable species variation; the latter was not
the case for KitL or CSF1.
While both the PDBMs of CSF1 and KitL contain 5 amino acids, their sequences differ.
The PDBM sequence of CSF1 is VELPV, which consists of largely hydrophobic amino acids
whereas the PDBM sequence of KitL is EFQEV, which is more varied with both hydrophilic and
acidic amino acids. The hydrophobic terminal amino acid, valine, however is common to both
CSF1 and KitL and most known PDBMs. The intracellular domain of CSF1 is highly conserved
across species, with high sequence similarity between human, mouse, rat and cow (Figure 3.1A,
bottom panel). The PDBM of CSF1 shows 100% sequence similarity between human, mouse
and rat. This indicates that the PDBM is likely an important functional domain in CSF1.
Results from a yeast two-hybrid screen revealed that KitL binds to the serine protease
HtrA1 via its PDBM. HtrA1 contains one PDZ domain at the end of its C-terminus (Figure
3.1B). Because KitL is structurally related to CSF1, particularly with respect to its cytoplasmic
domain, HtrA1 was also posited to be a potential binding partner of CSF1 based on its potential
for participating in PDZ-based interactions.
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Figure 3.1. The intracellular domain of CSF1 possesses a conserved C-terminal PDZ
domain binding motif (PDBM).
(A) The type III RTK hematopoietic ligands CSF1, Kit and Flt3 contain a conserved
intracellular domain with a C-terminal recognition sequence (last 5 amino acids) for proteins
with PDZ domains. This is referred to as the PDZ domain binding motif (PDBM). (B) The
intracellular domain and PDBM of CSF1 shows high conservation across species.
A
B
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Phenotypic and signaling profiles of hCSF1-expressing MS-5 cells
Given that CSF1 may harbour an intracellular signaling potential through its C-terminal
PDBM, the behaviour of cells expressing hCSF1 were examined. The growth and signaling of
murine MS-5 stromal cells overexpressing transmembrane hCSF1 (MS-5 hCSF1-mem)
engineered in our previous work, were compared to MS-5 control empty vector cells (MS-5-EV).
It was found that MS-5 hCSF1-mem cells grew at a faster rate compared to MS-5-EV cells
(Figure 3.2A). After 96 - 120 hours, MS-5 hCSF1-mem cells were almost double in number
compared to the number of MS-5-EV cells.
Based on the hypothesis of a plausible CSF1-HtrA1 binding interaction, levels of TSC2,
a reported substrate of HtrA1, were examined. It was observed that TSC2 levels were indeed
lower in MS-5 hCSF1-mem cells compared to MS-5-EV control cells, indicating a possible
activation of HtrA1 proteolytic activity in CSF1-expressing cells (Figure 3.2B). Since TSC2 is a
negative regulator of mTOR activity, lower TSC2 levels should relieve its inhibition of mTOR.
To address this, phosphorylated (p), and hence active, levels of the mTOR target S6 were
examined. In keeping with my hypothesis there were indeed higher levels of pS6 (S235/236) in
MS-5 hCSF1-mem cells compared to MS-5-EV cells (Figure 3.2B). There were no detectable
differences in levels of pAkt between MS-5 hCSF1-mem cells and MS-5-EV cells, suggesting
that the increased levels of pS6 observed are likely due to Akt-independent mechanisms
involving HtrA1-mediated degradation of TSC2. Lower TSC2 levels along with concomitantly
higher pS6 levels helped to confirm mTOR pathway activation in the hCSF1-expressing MS-5
cells. Activation of a pro-growth mTOR pathway downstream of hCSF1 helps to explain the
observed differences in cell growth rates between MS-5 hCSF1-mem and MS-5-EV cells.
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In addition to differences in growth and signaling differences, it was observed that MS-5
hCSF1-mem cells had a distinctly different cytokine profile than MS-5-EV cells, with higher
levels of G-CSF, IL-6, MCP-1, KC (keratinocyte chemoattractant, also known as CXCL1), and
lower levels of MIP-1a and VEGF (Figure 3.2C). Levels of these cytokines were reversed with
the addition of a blocking CSF1R antibody (Ab), demonstrating the direct implication of CSF1
in inducing the production of these signaling cytokines.
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A B
C
Figure 3.2. CSF1-expressing MS-5 stromal cells demonstrate differential phenotypic and
signaling behaviour.
(A) The growth rates of MS-5 Tet-off EV vs. hCSF1-mem cells were compared over a period
of five days. Cells were plated and counted each day using trypan blue. (B) Signaling proteins
relevant to the mTOR pathway were evaluated using western blot. (C) Cytokine production
was evaluated using multiplexed cytokine arrays. Shown are results from n = 3 independent
experiments.
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Generation of a ΔPDBM mutant to interrogate the function of CSF1’s PDBM
To investigate the potential role of CSF1’s PDBM in the observed phenotypes and
signaling events in hCSF1-expressing MS-5 cells, the PDBM of hCSF1 was deleted (terminal 5
amino acids) to create a deletion mutant (hCSF1 ΔPDBM); this was transduced into MS-5 cells.
An inducible tetracycline-based ‘OFF’ (Tet-off) vector system was used so that hCSF1
expression could be regulated i.e. ‘turned off’ or inhibited with the addition of doxycycline
(Dox), which is a more stable analog of tetracycline, in order to assess phenotypic and signaling
changes associated with hCSF1 expression. The MS-5 Tet-off cell lines generated upon
transduction of the different constructs were: MS-5 Tet-off 1) Empty Vector (EV), 2) hCSF1-
mem and 3) hCSF1-mem ΔPDBM. To assess and confirm expression of hCSF1 in the
engineered MS-5 cells, western blotting was performed to evaluate hCSF1 protein levels. It was
observed that there was robust expression of hCSF1 in both MS-5 Tet-off hCSF1-mem and
hCSF1-mem ΔPDBM cells in the non-induced (silenced) cells (Figure 3.3A). Interestingly, the
molecular weight of hCSF1-mem ΔPDBM appeared to be slightly less than that of full length
hCSF1-mem. While the removal of 5 amino acids may lend to the observed smaller size, there
may be potential differences in post-translational modifications (i.e. glycosylation, prenylation
etc.) between the full length and deletion mutant that may account for the size difference.
To confirm and test the functionality of the Tet-off system, increasing concentrations of
doxycycline were added to the MS-5 Tet-off cells in order to inhibit hCSF1 expression.
According to the manufacturer’s protocol, protein expression levels can be regulated in a
doxycycline concentration-dependent manner. Upon addition of Dox, it was observed that there
was a significant reduction in hCSF1 protein levels at comparable amounts (approximately 90%)
in both hCSF1-mem and hCSF1-mem ΔPDBM cells (Figure 3.3B). The regulatable system is
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quite sensitive, as concentrations as low as 0.001 µg/mL led to almost complete elimination of
hCSF1 expression in both cell lines. This shows that the system is quite robust and not ‘leaky’ in
terms of rendering optimal inhibition of protein expression levels. Moreover, higher Dox
concentrations did not achieve greater inhibition of expression. A Dox concentration of 1 µg/mL
was chosen and used for subsequent experiments as this was found to be an optimal
concentration according to our tests, in addition to being a commonly used concentration in such
inducible systems.
To investigate whether the observed activation of mTOR signaling in MS-5 hCSF1-mem
cells (Figure 3.2B) was directly linked to CSF1 expression and activity, MS-5 Tet-off cells were
treated with Dox to ‘turn off’ and inhibit the expression of CSF1. It was observed that inhibition
of CSF1 in MS-5 Tet-off hCSF1-mem cells led to decreased levels of pS6 compared to untreated
cells (Figure 3.3C). Levels of pS6 were almost entirely diminished and comparable to those in
the MS-5 Tet-off EV cells.
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Figure 3.3. CSF1 expression in MS-5 Tet-off inducible cells.
(A) MS-5 cells were transduced with full length hCSF1-mem, hCSF1-mem ΔPDBM or empty
vector (EV). hCSF1 expression was confirmed by western blotting. (B) Increasing
concentrations of doxycycline (Dox) were added to the MS-5 Tet-off cells to ‘turn off’ or
inhibit hCSF1 expression. CSF1 levels were evaluated by western blotting. (C) MS-5 Tet-off
cells were treated with Dox (1 µg/mL) and levels of pS6 were examined using western
blotting.
A
B
C
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CSF1 activates mTOR signaling via HtrA1
To examine the role of hCSF1’s PDBM in the observed activation of mTOR signaling,
pS6 levels were examined in MS-5 Tet-off cells expressing full length hCSF1 vs. the PDBM
deletion mutant. It was observed that pS6 levels were lower, and in fact completely abolished, in
MS-5 Tet-off hCSF1-mem ΔPDBM cells compared to hCSF1-mem cells, at levels comparable to
those in MS-5-EV cells (Figure 3.4A). These results indicate that CSF1 induces activation of
mTOR signaling, as observed through increased levels of pS6 in hCSF1-expressing MS-5 cells,
specifically through its PDBM. There were also observed differences in cell growth between
MS-5 Tet-off cells with the hCSF1-mem exhibiting greater cell numbers after 72 hours
compared to EV and hCSF1-mem ΔPDBM cells (Figure 3.4B). The growth rates of EV and
hCSF1-mem ΔPDBM were comparable, indicating that loss of the PDBM from hCSF1
significantly impacts the growth of the stromal cell. In addition, cytokine analysis revealed that
levels of cytokines such as IL-6 and KC were lower in MS-5 Tet-off hCSF1-mem ΔPDBM cells
compared to hCSF1-mem cells (Figure 3.4C). This indicates that the production of these
cytokines is dependent on the presence of CSF1’s PDBM, which fosters signaling mechanisms
that lead to control of cytokine production.
To examine the role of HtrA1 as a potential mediator of CSF1-induced mTOR pathway
activation in MS-5 cells, siRNA-mediated knockdown of HtrA1 was performed. It was observed
that knockdown of HtrA1 in MS-5 Tet-off hCSF1-mem cells led to an increase in levels of
TSC2, with a concomitant decrease in levels of pS6 compared to cells transfected with control
GFP siRNA (Figure 3.4D). This demonstrates that HtrA1 is a mediator of mTOR pathway
activation induced by CSF1 in MS-5 cells.
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Figure 3.4. CSF1-induced mTOR signaling is mediated by HtrA1 in MS-5 cells.
(A) pS6 levels were evaluated in MS-5 Tet-off cells expressing full length hCSF1 (hCSF1-
mem) and the hCSF1-mem PDBM deletion mutant (ΔPDBM). (B) Growth curves of the MS-5
Tet-off cells (EV, hCSF1-mem, hCSF1-mem ΔPDBM). (C) Cytokine levels were evaluated in
the MS-5 Tet-off cells using a multiplexed mouse-specific cytokine array. (D) Knockdown of
HtrA1 in MS-5 Tet-off cells was performed using siRNA transfection.
A
C
B
D
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The PDBM of CSF1 impacts the support of AML cells in AML-MS-5 cell co-cultures
To assess the impact of CSF1’s cytoplasmic PDBM on the support of AML cells by MS-
5-AML cells expressing the ligand, the MS-5 Tet-off cells (EV, hCSF1-mem and hCSF1-mem
ΔPDBM) were co-cultured with the OCI/AML-4 and OCI/AML-5 cell lines. After a two-week
co-culture period, it was observed that the MS-5 Tet-off hCSF1-mem ΔPDBM cells conferred a
reduced growth advantage to the AML cells compared to MS-5 Tet-off hCSF1-mem cells
(Figure 3.5A, B). While MS-5 Tet-off hCSF1-mem cells supported a greater than 2-fold increase
in AML cell number compared to MS-5-EV cells, AML cells grown with MS-5 Tet-off hCSF1-
mem ΔPDBM cells only showed a 1.3-fold increase in cell number. This demonstrates that the
growth-promoting properties of hCSF1-mem are significantly reduced with loss of the PDBM.
To further examine the growth-promoting properties of CSF1, the clonogenic potential of
OCI/AML-5 cells was assessed following co-culture with the different MS-5 Tet-off cells for a
period of 48 hours. After co-culture, AML cells were collected and plated into methylcellulose
with growth factors to determine the number of clonogenic cells remaining. It was observed that
OCI/AML-5 cells that had been pre-cultured with MS-5 Tet-off hCSF1-mem cells gave rise to a
larger number of colonies in the colony assays compared to cells that had been pre-cultured with
MS-5 Tet-off EV cells (Figure 3.5C). AML cells that had been co-cultured with MS-5 Tet-off
hCSF1-mem ΔPDBM cells gave rise to colony numbers that were comparable to AML cells that
had been pre-cultured with MS-5 Tet-off EV cells. This suggests that pre-culture of AML cells
with hCSF1-expressing MS-5 cells can potentiate the clonogenic ability of AML cells, and that
the PDBM of hCSF1 appears to play a role.
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Figure 3.5. Support of AML cells by hCSF1-expressing MS-5 cells.
A, B) OCI/AML-4 and OCI/AML-5 cells were co-cultured with the different MS-5 Tet-off
cells. Shown are cell numbers after a 2-week co-culture period. (C) OCI/AML-5 cells were
pre-cultured with the MS-5 Tet-off cells for 48 hours and then plated into methylcellulose.
Colonies (a colony was scored as having more than 30 cells) were counted after 10 days.
Significance at * P < 0.001. Shown are results from n = 2 independent experiments.
A
B
C
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Model of multi-directional CSF1 ligand signaling
The results here demonstrate that hCSF1 has the ability to activate the mTOR pathway, in
a reverse manner via its PDBM. Specifically, a CSF1-HtrA1-pS6 signaling axis appears to be
activated in which hCSF1 and HtrA1 interact via PDZ interactions. This is demonstrated by the
fact that both deletion of hCSF1’s PDBM and knockdown of HtrA1 lead to abolishment of pS6
levels in MS-5 cells. Therefore a proposed model for hCSF1 intracellular signaling within MS-5
cells involves hCSF1-induced activation of HtrA1’s proteolytic activity, leading to degradation
of TSC2 and hence activation of S6, which can then lead to changes in gene expression and
production of secondary signaling cytokines (such as IL-6, KC and TNFα). In this way, as a
signaling ligand, hCSF1 can elicit multiple signals in multiple directions through various
mechanisms to ultimately impact the support of AML cells: 1) CSF1-CSF1R receptor-ligand
engagement (‘forward’ signal), 2) reverse intracellular signaling via PDZ-mediated protein-
protein interactions 3) production of secondary/tertiary signaling molecules resulting from
hCSF1 reverse signaling (Figure 3.6B).
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Figure 3.6. Model of CSF1-induced multi-directional signaling in AML-stromal cell
interactions.
(A) CSF1 interacts with HtrA1 via its C-terminal PDBM to activate mTOR signaling, which
can lead to changes in cytokine production and gene expression. (B) CSF1 can elicit multiple
signals in multiple directions to impact the support of AML in the BM.
A
B
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3.5. DISCUSSION
The results from this work indicate that hCSF1 possesses intrinsic signaling function by
means of its C-terminal PDBM, which allows it to reverse signal within MS-5 stromal cells to
activate a hCSF1-HtrA1-S6 signaling axis. Activation of this axis may modulate the phenotype
and behaviour of MS-5 stromal cells, which in turn, appears to positively support AML cell
growth and survival. The existence of a putative PDBM in the structure of CSF1 was first
identified through sequence analysis which confirmed that CSF1 contains one PDBM located at
its C-terminus (Figure 3.1A). The PDBMs of CSF1, and the related KitL, both have a C-terminal
hydrophobic valine, which is almost invariably found as the last residue, i.e. in the P0 position, of
most PDBMs. The intracellular domain of CSF1 is highly conserved across species, with 100%
conservation of the PDBM in particular, highlighting its potential physiological importance
(Figure 3.1B).
Phenotypic modulation of MS-5 stromal cells by the presence of CSF1 was highlighted
by observed differences in growth rates and signaling between MS-5 cells expressing the ligand
vs. cells that do not. MS-5 hCSF1-mem cells were found to proliferate faster than MS-5-EV
cells, with almost a two-fold difference in growth rates (Figure 3.2A). Loss of the PDBM of
CSF1 led to reduced proliferation to levels comparable to MS-5 Tet-off EV cells (Figure 3.5D).
Potential mechanisms underlying these phenotypic differences were examined with respect to
potential CSF1 binding partners and signaling mediators. Previous work from our group has
shown that the serine protease HtrA1 is a binding partner of the related KitL. Because HtrA1 has
been shown to degrade the mTOR regulator TSC2 (Campioni et al., 2010), it was hypothesized
that a CSF1-HtrA1 interaction would lead to activation of mTOR signaling in MS-5 stromal cells
expressing CSF1. To support this hypothesis, it was found that MS-5 hCSF1-mem cells indeed
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had lower levels of TSC2, and concomitantly higher levels of pS6 ribosomal protein levels
compared to MS-5-EV cells (Figure 3.2B). CSF1 was found to be directly implicated in the
observed mTOR pathway activation, as inhibition of CSF1 expression through addition of Dox
to the MS-5 Tet-off hCSF1-mem cells caused a reduction in levels of pS6 (Figure 3.3C). The
enhanced growth that CSF1-expressing MS-5 cells experience, compared to cells that don’t
express CSF1, could potentially be explained by the activation of mTOR signaling in the cells, as
activated S6 (as part of the ribosomal complex) leads to increased protein production through
stimulation of cap-dependent mRNA translation via activation of eukaryotic translation initiation
factor 4E (eIF4E).
A direct implication for CSF1’s PDBM role in eliciting reverse intracellular signaling in
MS-5 stromal cells was demonstrated by the fact that the deletion of the PDBM led to lower
levels of pS6, indicating the inhibition/de-activation of mTOR signaling in the cells (Figure
3.4A). The absence of CSF1’s PDBM also led to changes in levels of cytokines such as IL-6
(Figure 3.4C). Moreover, downstream of CSF1, HtrA1 was demonstrated to be a mediator of the
observed mTOR pathway activation, as knockdown of HtrA1 led to increased levels of TSC2
and decreased levels of pS6 in MS-5 hCSF1-mem cells (Figure 3.4D). This mimicked the effects
of CSF1 PDBM deletion, which showed that a loss of function of either CSF1 or HtrA1 results in
inhibition of mTOR signaling in CSF1-expressing MS-5 cells. This work was therefore able to
identify a novel CSF1-HtrA1-mTOR signaling axis in BM stromal cells.
There were also observable differences in the cytokine profiles of hCSF1-expressing vs.
non-CSF1-expressing MS-5 cells (Figure 3.2C) with higher levels of cytokines such as IL-6, KC
(CXCL1) and MCP-1, which are factors associated with growth and inflammatory pathways. Co-
culture of AML cells with the MS-5 cells led to further changes in these cytokines, with addition
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of a CSF1R antibody leading to a reversal in the changes, as did deletion of the PDBM of CSF1
(Figure 3.2C, 3.5D). This indicates that intracellular CSF1 ligand signaling can directly induce
changes in cytokine secretion. Interestingly, the observed activation of mTOR signaling in
hCSF1-expressing cells could potentially induce IL-6 production in the cells. This is likely due
to the known ability of activated mTOR to stimulate the transcriptional regulator NF-κB, which
can induce transcription of IL-6 and other signaling cytokines (Brasier, 2010; Dan et al., 2008; T.
Liu, Zhang, Joo, & Sun, 2017). IL-6 is an important inflammatory and hematopoietic cytokine.
When produced by BM stromal cells, it can contribute to the protective properties of the tumor
microenvironment as it can promote inflammation, immune suppression, osteolysis (leading to
release of additional inflammatory cytokines including IL-6 itself) and tumorigenesis (Harmer,
Falank, & Reagan, 2019). In fact, IL-6 levels are found to be upregulated in multiple myeloma
and some solid tumors. In a paediatric AML study, high IL-6 levels in the BM (assessed in BM
aspirates) were shown to be associated with poor clinical outcome (Sanchez-Correa et al., 2013;
Stevens, Miller, Munoz, Gaikwad, & Redell, 2017). This highlights a role for IL-6 in the
microenvironment of AML, production of which could be driven by CSF1-CSF1R signaling.
CSF1-induced activation of pro-growth signaling pathways such as mTOR-S6, along
with changes in the production of signaling cytokines, could help explain the increased growth
and survival of MS-5 cells expressing hCSF1. These phenotypic and signaling differences
indicate that the presence of hCSF1 in MS-5 stromal cells can intrinsically alter their
characteristics and behaviour. Similarly, it has been shown that Ephrin B ligand reverse signaling
within neuronal cells induces morphological changes such as membrane blebbing and cell
retraction through engagement with proteins such as ROCK (Rho-associated protein kinase)
(Bochenek, Dickinson, Astin, Adams, & Nobes, 2010). This highlights a role for reverse ligand
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signaling in the functionality of the ligand-expressing host cell. Interestingly, CSF1 demonstrates
activity within the MS-5 stromal cell without any required binding or engagement by an external
protein or receptor. In other words, it does not appear that CSF1 needs to be ‘activated’ by
binding to its receptor (i.e. CSF1R) in order to elicit signaling within the cell. This could be
explained in two ways: 1) CSF1 is normally expressed as a homodimer and as such, it may be
constitutively active in its ability to reverse signal without binding to its receptor; 2) in the
engineered CSF1 inducible overexpression system, high CSF1 levels may alter its distribution on
the cell surface, i.e. forming signaling complexes in lipid rafts for example, resulting in its
constitutive activation and signaling.
In previous work (Chapter 2), the CSF1-CSF1R ligand-receptor pair was investigated
within the context of AML-stromal cell interactions. Data from that work showed that hCSF1-
expressing MS-5 cells effectively support the long-term growth and survival of AML cells in co-
culture assays. To investigate whether CSF1’s cytoplasmic PDBM plays a role in this,
OCI/AML-4 and OCI/AML-5 cell were co-cultured with MS-5 Tet-off hCSF1-mem vs. hCSF1-
mem ΔPDBM, and EV control cells. It was observed that MS-5 hCSF1-mem ΔPDBM cells
provided reduced support (approximately 1.5 fold lower) for the OCI/AML-5 and OCI/AML-4
cells in co-culture compared to MS-5 hCSF1-mem cells (Figure 3.5A, B). The reduced support
of AML cells by MS-5 cells expressing PDBM-deleted hCSF1 suggests that the PDBM lends
important functionality and structure to CSF1, as its absence fails in mediating the full
supportive capacity of stromal cells for growth factor/cytokine dependent AML cells. Because
CSF1 can reverse signal within MS-5 stromal cells via its PDBM, this may allow it to interact
with various intracellular proteins involved in structure and adhesion. For example, the
scaffolding protein NHERF1, which contains two PDZ domains, has been shown to mediate the
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binding of the cystic fibrosis transmembrane conductance regulator (CFTR) to the actin
cytoskeleton (Li, Callaway, & Bu, 2009). Such mechanisms may increase the stability and
functionality of transmembrane CSF1 within the stromal cell that it is anchored in, which may
enhance its binding to AML cells via CSF1R engagement and/or other adhesive mechanisms.
Taken together, these results demonstrate that CSF1 is capable of reverse signaling
within BM stromal cells to activate a CSF1-HtrA1-S6 axis via PDZ-based interactions (Figure
3.6A). CSF1 ligand appears to be a dynamic functional player in AML-stromal cell interactions
as it may participate in bi-directional, reverse signaling to elicit multi-directional and multi-
faceted effects in the support of AML cells (Figure 3.6B). In this model, CSF1 not only binds to
its receptor on target leukemic cells in the ‘forward’ direction, but it also has the ability to alter
the behaviour of host stromal cells through reverse signaling, inducing the production of
signaling cytokines that could act in both autocrine and juxtacrine manners to influence the
stromal cell, residual normal cells and surrounding leukemic cells. Cell-cell communication
through the exchange of factors and materials between leukemic and stromal cells can help
create a transformed BM niche conducive for leukomogenesis.
Identifying elements and factors within the BM that may be involved in promoting a
malignant microenvironment is critical to enhancing our understanding of BM malignancies like
AML. In this work, a novel CSF1-HtrA1-S6 axis was identified in BM stromal cells that may be
therapeutically targeted to reduce support for subpopulations of CSF1R positive AML cells. This
highlights an important role for ligand signaling within BM stromal cells, which can actively
participate in cell-cell communication within the tumor microenvironment. Targeting these
cellular interactions within the BM niche is thus critical in the design of future therapeutic
approaches for AML.
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CHAPTER 4
Thesis discussion and significance of findings
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4.1. OVERALL DISCUSSION & SIGNIFICANCE OF FINDINGS
The BM niche is a complex milieu of cells and molecules that establish symbiotic
relationships to help to sustain and propagate, life essential cells. The BM microenvironment is
therefore a dynamic infrastructure susceptible to perturbations and adaptations. In BM disease
settings where leukemic cells often outcompete normal hematopoietic cells for space and
resources, supporting BM cells likely play a pivotal role in the transformative and malignant
process by offering leukemia supportive and normal hematopoietic disruptive forces. The
sequence of events in a ‘microenvironmental’ transformation remains unclear i.e. do malignant
cells usurp and exploit their microenvironments in a parasitic fashion to alter it, or is the
microenvironment first transformed in order to support carcinogenesis and malignancy?
Regardless of the exact sequence of events, it is clear that BM stromal cells lend important
supportive functions for the maintenance and sustenance of both normal hematopoietic and
leukemic cells within the BM.
AML is a highly aggressive malignancy of the BM with dismal long-term clinical
outcomes. While patients may benefit from initial induction chemotherapy, the vast majority of
patients relapse and succumb to their disease. In recent years, there has been growing interest in
investigating mechanisms underlying AML relapse, with focus on the investigation of sub-clones
that may resist or evade chemotherapy altogether, as well as tracing the evolution of leukemias
from pre-leukemia through to the full blown leukemic state. Cells that lie at the heart of relapse
evade initial chemotherapy or, as is becoming more evident, exist as smaller sub-populations of
drug resistant progenitor-like cells that may later evolve and undergo expansion to give rise to
the dominant relapse clone. It is suggested that the tumor microenvironment serves to protect
these types of quiescent evolving leukemic clones and thus targeting BM niches for the treatment
163
of leukemias is a topic of great research and clinical interest. In this work, I identified a
functional supportive role for the CSF1-CSF1R interaction where the growth and signaling of
AML cells expressing CSF1R were positively supported by CSF1-expressing stromal cells.
Inhibition of this interaction through the use of a CSF1R antibody was shown to have efficacy in
abrogating these supportive effects, leading to reduced AML cell proliferation and mTOR/S6
growth signaling. This highlights a role for the targeting of CSF1-CSF1R as a means to inhibit
signals from BM stromal cells to specifically sever the supportive effects of CSF1-producing
stromal cells.
CSF1R as a Significant Prognostic Indicator in AML
In this thesis, the outcomes of the CSF1-CSF1R interaction, as mediated between
interacting AML and stromal cells, were explored for their effects on both AML and stromal cell
phenotypes and signaling. High level CSF1R expression at the level of RNA and protein was
demonstrated to be a significant prognostic marker in the prediction of patient outcome in
subsets of AML patients, and an important functional receptor that when activated by CSF1
ligand, promoted AML cell proliferation and production of signaling molecules associated with
cell growth and inflammation. CSF1R could also effectively stratify subsets of AML cases that
do not bear the common AML mutations FLT3-ITD and NPM1c, which highlights a potential
role for it in sub-classifying AML. This is promising because CSF1R could serve as a functional,
actionable target in this subgroup of AML patients; this is important as we move from ‘one size
fits all’ therapy, to targeted therapy driven by knowledge of specific mutations and protein/gene
expression.
164
The Significance of Transmembrane CSF1 in AML Growth and Adhesion
In this thesis I have found that the CSF1-CSF1R interaction is specifically significant
within the context of signaling between AML and stromal cells. I have found that the manner of
ligand presentation is of major importance in the responses of CSF1R-expressing AML cells to
stimulation by CSF1 ligand, with membrane bound ligand being more active than secreted
ligand. This may be due to the enhanced cell-cell contact that transmembrane CSF1 may
promote due to its physical anchorage within stromal cells, which when binding to CSF1R on
AML cells, fosters the cells to be brought into close physical proximity with each other. While
the binding of CSF1 to CSF1R may in itself serve as an adhesive function between the cells,
interacting CSF1-CSF1R may potentially promote the upregulation of adhesion molecules such
as integrins and other components of the extracellular matrix to further enhance adhesion.
The isoform specificity and other specifics associated with the CSF1-CSF1R interaction
underscores the relevance of ‘Baserga’s caveats’, attributed to Dr. Renato Basergo, which were
introduced to me by my supervisor at the onset of this project. These caveats speak to the
importance of the specificity of conditions for any given experimental concept, trial or clinical
treatment. The three main caveats are: 1) These cells or these patients (i.e. cellular, molecular,
clinical characteristics), 2) These conditions or treatment 3) At this time. These caveats highlight
the importance of determining the precise characteristics and context of any experimental design.
This could not hold any more true for CSF1, as it was found to function optimally as a
transmembrane ligand vs. soluble ligand in the specific context of interacting AML and BM
stromal cells. Changing the conditions of the experimental design such as using different cell
types or altering the properties of the signaling ligand (as was done with the PDBM deletion)
would impact the outcome of results, which in essence would highlight the significance of the
165
initial components and context. In this case, CSF1 was found to operate at its best as a
transmembrane ligand anchored within BM stromal cells.
CSF1 as a Signaling Ligand within BM Stromal Cells: Reverse, Bi-Directional Signaling
While the binding of CSF1 to CSF1R on AML cells is a more canonical ligand-receptor
interaction that mediates signaling and cell-cell contact between AML and stromal cells, the role
of CSF1 as a functional intracellular signaling ligand, and not just a static binding partner
ofCSF1R, was also explored. This work showed that CSF1 has a PDZ binding motif (PDBM) in
its cytoplasmic tail that is capable of modifying downstream signaling proteins, resulting in
reverse intracellular signaling within the stromal cell. A specific CSF1-HtrA1-S6 signaling axis,
dependent on PDZ-mediated interactions between CSF1 and HtrA1, was suggested in MS-5
hCSF1-mem cells, as knockdown of HtrA1 abrogated the effect of CSF1-mem. Activation of this
pathway may underlie the phenotypic effects for hCSF1-expressing MS-5 stromal cells, namely
increased growth and changes in cytokine production. Identification of this pathway also
revealed potential actionable targets such as CSF1-CSF1R, HtrA1 and components of the mTOR
pathway, including S6 within the stroma, and secreted cytokines such as IL-6. Interestingly,
increased phosphorylation of S6 was observed in both AML and stromal cells, indicating that
mTOR signaling is potentially activated in both cell types. This has promising implications for
the dual targeting of both CSF1R+ AML cells and CSF1+ stromal cells given that they share a
common target.
The observed stromal cell changes induced by AML cells may in turn impact the manner
in which they feed back to support AML cells, demonstrating a functionally dynamic role for
166
supporting BM stromal cells. This lends support to the idea that the stroma is not a static entity in
the BM, but rather that it has active function, and is modifiable.
The interaction between AML and stromal cells yields the dynamic modulation of both
cell types. Co-culture of AML and stromal cells induced changes in signaling and in the cytokine
profiles of both cell types. Production of secondary signaling molecules such as cytokines and
other growth factors by both AML and stromal cells as induced by the CSF1-CSF1R interaction
could function in autocrine and juxtacrine manners on the cells. For example, molecules
produced in response to CSF1R activation by CSF1 on AML cells, could act on stromal cells and
vice versa, adding additional pathways of interaction and support between AML and stromal
cells. In this way, leukemic cells may actively support stromal cells to foster the genesis of its
own supportive microenvironment.
Taken together, this work demonstrates the importance of studying AML in the context
of its BM microenvironment. By employing an AML-stromal cell co-culture system, the role of
CSF1-CSF1R signaling was investigated under more ‘native’ conditions in aims of capturing and
re-capitulating features of the BM as pertaining to the supporting stroma. This helped identify
the CSF1-CSF1R axis as an actionable target that has a dual impact on interacting AML and
stromal cells. Dually targeting AML and supporting stromal cells could be achieved by blocking
the bi-directional support between the cells (CSF1R inhibitor), or by targeting common targets
(mTOR/pS6) in the cells, or the combination of the two. The significance of tumor cell niches as
protective microenvironments has important implications for drug resistance, evasion of immune
responses and other defense mechanisms that potentially give rise to more aggressive, sustained
tumorigenesis. Therapeutic targeting of elements within the microenvironment in BM
167
malignancies like AML may thus be critical in achieving more favourable clinical responses, and
perhaps even potential disease eradication.
4.2. FUTURE DIRECTIONS
In the continuation of this work, future studies could involve further investigation of
CSF1R as a clinical prognostic marker in AML. While the studies herein identified an
association between CSF1R expression levels and patient survival, further analyses in more gene
expression and protein expression datasets could be employed to verify and lend greater
robustness to the findings. Clinical analyses are often limited by sample numbers and in this
study, there were 146 AML patient cases for which cell surface protein expression profiling, of
CSF1R was performed by flow cytometry. Future work could involve obtaining more patient
samples for CSF1R expression profiling, so as to increase the number of samples in the compiled
protein expression dataset. In addition, for the clinical analyses, more detailed analysis on
disease subtypes, and molecular profiles could be performed, particularly as molecular profiling
is now becoming more mainstream in the clinical diagnosis of AML.
While a CSF1R antibody was employed in this study to block the CSF1-CSF1R
interaction, other identified targets downstream of CSF1R such as the PI3k/Akt pathway, as well
as newly identified targets induced by CSF1 including HtrA1 and S6 could be targeted by
specific inhibitors. Moreover, it appears that S6 is activated in both AML and hCSF1-expressing
stromal cells, making it a common target that could be inhibited with added advantage, as the
pathway would be blocked both in the AML cell, and the stroma cells that contribute to the
growth and survival of the AML cells. While HtrA1 was identified as a downstream target of
CSF1 in MS-5 stromal cells, other binding partners of CSF1 could be identified using a CSF1-
168
specific yeast-two-hybrid screen that incorporates the PDBM, or through BioID approaches or
pull down-mass spectometry studies; in any case it will be critical to maintain the last 5 amino
acids of CSF1.
In addition, immune-based therapies such as CAR (chimeric antigen receptor)-T cell
therapy could be employed where cells could be engineered to express CSF1 ligand to target
CSF1R positive AML cells; such a CAR-T would not only eliminate CSF1R expressing AML
cells but also infiltrating macrophage derived from residual cells and that may be providing an
immune suppressive effect (M2-macrophage). At the same time, CAR-T cells could also be
made to express the domain of CSF1R that binds CSF1. These T cells would be targeted to
CSF1-expressing stromal cells within the BM to target cases of CSF1-driven disease. This could
help prevent the adhesion and homing of CSF1R positive AML cells to CSF1-expressing BM
stromal cells, thereby severing supportive interactions between the cells. This could also help
mobilize CSF1R positive AML cells from the bone marrow, making them more accessible to be
targeted by chemotherapeutic agents. Finally the elimination of CSF1-expressing stroma would
reduce the production of cytokines and adhesion molecules that can contribute to the growth of
the AML cells.
While levels of CSF1R were assessed on the peripheral blood blasts of AML patients,
future work should also involve examining CSF1 levels within the BM cells of AML patients.
This work is actually being currently carried out with the assistance of collaborators. For this
work, bone marrow biopsies are being obtained which will be stained with CSF1 antibodies, as
well as antibodies against pS6, to evaluate CSF1 levels and downstream activation of mTOR
signaling inBM stromal cells. This would lend further support and clinical relevance to the
findings in this work. The potential of finding that there is variable expression of CSF1 in the
169
stroma of AML cases would provide the impetus to identify the factors that enhance the
production of CSF1, and the identification of means to mitigate that expression.
Finally, more in-vivo studies should be performed including engraftment studies with
more patient samples in the humanized CSF1 mouse model. The CSF1R antibody should also be
tested in these mice to evaluate whether it can block engraftment of CSF1R positive AML cells
within the BM. Engrafted AML cells should be interrogated for cell surface markers as well as
intracellular signaling markers; these latter studies could be performed using CyTOF technology
for multiplexed ‘discovery’ screening of novel and/or relevant markers. Much of this work is
currently underway and will be continued given that the preliminary in-vivo findings from the
humanized CSF1 mouse model have proven to be quite promising.
4.3. CONCLUSIONS
The work herein has identified significant roles for CSF1 and its receptor CSF1R in AML
clinical prognosis, and in the AML BM niche. Signaling between CSF1 and CSF1R was shown
to foster supportive connections between the stromal and AML cells expressing them,
respectively. The CSF1-CSF1R-dependent interaction between AML and BM stromal cells
improved the proliferation, survival and adhesion of AML cells, through changes in signaling
and cell surface immunophenotypes, in in-vitro and in-vivo models. The CSF1-CSF1R
interaction was not only supportive of AML cells, but also drove signaling changes within MS-5
stromal cells through the bi-directional, reverse signaling action of CSF1 ligand. CSF1 could
signal within the stromal cell via its cytoplasmic PDBM to activate mTOR signaling, and induce
changes in cytokine secretion. CSF1-CSF1R may promote cellular cross-talk between AML and
supporting stromal cells through an interplay of multi-directional forward/reverse signaling,
170
producing a symbiotic relationship that propagates and sustains leukemogenesis. A CSF1R-
driven AML is proposed to be an aggressive disease subset, supported by the fact that high
CSF1R levels were shown to be associated with poor clinical survival. Taken together, CSF1-
CSF1R is a biologically and clinically relevant signaling axis that may be therapeutically
targeted in AML and its supportive microenvironment.
171
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