can we classify cancer using cell signaling?
TRANSCRIPT
![Page 1: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/1.jpg)
Can we classify cancer using cell signaling?
![Page 2: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/2.jpg)
Central hypotheses (big ideas)
• “Alterations to signaling genes would cause leukemic cells to
react in an inappropriate or sensitized manner to environmental
inputs and this differential signaling can be read out by flow
cytometry.”
• Classification of patients by this differential cell signaling will
reveal groups of patients with shared clinical outcomes and
identify signaling events driving leukemia aggressiveness.
![Page 3: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/3.jpg)
Background & rationale:
Signaling => Cancer
![Page 4: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/4.jpg)
Why measure signaling?
(in healthy cells, cancer, and other human diseases)
![Page 5: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/5.jpg)
Cell Signaling Programs Cell Function and Fate
J. Irish
![Page 6: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/6.jpg)
Cell Signaling Programs Cell Function and Fate
J. Irish
![Page 7: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/7.jpg)
Cell Signaling Programs Cell Function and Fate
J. Irish
![Page 8: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/8.jpg)
Cell Signaling Programs Cell Function and Fate
J. Irish
![Page 9: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/9.jpg)
Changes to Cell Signaling
are Important Steps in Cancer Progression
Kinzler and Vogelstein, Cell 1996
Healthy CellsAltered Cells
(still benign)
Cancer
Cells
Aggressive
Cancer Cells
Normal Tissue Invasive Cancer
Mutation 1 Mutation 2, 3, 4 Mutation 5, 6
![Page 10: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/10.jpg)
Changes to Cell Signaling
are Important Steps in Cancer Progression
Kinzler and Vogelstein, Cell 1996
Healthy CellsAltered Cells
(still benign)
Cancer
Cells
Aggressive
Cancer Cells
Normal Tissue Invasive Cancer
Mutation 1 Mutation 2, 3, 4 Mutation 5, 6
Hanahan and Weinberg, Cell 2000
Self-sufficient growth
Insensitive to anti-growth
Evading cell death
Limitless replication potential
Growing blood vessels
Tissue invasion
Acquired Capability
![Page 11: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/11.jpg)
Changes to Cell Signaling
are Important Steps in Cancer Progression
Kinzler and Vogelstein, Cell 1996 Hanahan and Weinberg, Cell 2000
Self-sufficient growth
Insensitive to anti-growth
Evading cell death
Limitless replication potential
Growing blood vessels
Tissue invasion
Acquired Capability
Altered signaling supports
cancer cell survival,
aggressive behavior
↑ RAS/RAF/ERK signaling
↓ STAT1, PTEN signaling
↑ STAT5, ↓ p53 signaling
↑ AKT signaling
↑ VEGF signaling
↑ EGFR, WNT signaling
}Irish, Kotecha, and Nolan, Nat Rev Cancer 2006
Example Signaling Alteration
![Page 12: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/12.jpg)
Blocking Malignant Signaling Can Kill Cancer Cells
In CML,
BCR-ABL mutation
alters signaling} CML cell survival,
aggressive behavior
Druker et al., New Eng J Med 2001
>95% of chronic myelogenous leukemia (CML) patients
have a ‘BCR-ABL’ gene mutation that alters cell signaling
![Page 13: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/13.jpg)
Blocking Malignant Signaling Can Kill Cancer Cells
In CML,
BCR-ABL mutation
alters signaling} CML cell survival,
aggressive behavior
Druker et al., New Eng J Med 2001
![Page 14: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/14.jpg)
Blocking Malignant Signaling Can Kill Cancer Cells
In CML,
BCR-ABL mutation
alters signaling} CML cell survival,
aggressive behavior
Druker et al., New Eng J Med 2001
Block BCR-ABL with Gleevec,
shut down altered cancer cell signaling
![Page 15: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/15.jpg)
Blocking Malignant Signaling Can Kill Cancer Cells
In CML,
BCR-ABL mutation
alters signaling} CML cell survival,
aggressive behavior
Druker et al., New Eng J Med 2001
Block BCR-ABL with Gleevec,
shut down altered cancer cell signaling
Leukemia cells died
![Page 16: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/16.jpg)
Can we generalize the ‘targeted therapy approach’
by identifying driving signaling events in other cancers?
![Page 17: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/17.jpg)
Can tumors be described in terms of cell signaling?
Study Design: • Map signaling mechanisms across tumors
and construct a signaling taxonomy.
Rationale: • Signaling mutations are common, vary across
tumors, and contribute to pathology.
• Will rigorously describe molecular differences among tumors.
• Will inform drug development and individual assessment of therapy and risk.
Hypotheses: • 1) Heritable changes to cancer cells will
detectably modify signaling networks.
• 2) Patients whose tumors share mechanisms of proliferative signaling will respond similarly to tumor cell killing.
Tumor Patient A
Tumor Patient B
![Page 18: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/18.jpg)
Constructing a Toolset to Probe Signaling
• Immunology: Measure events at the individual cell level
• Molecular Biology: Monitor signaling biochemistry (phosphorylation)
• Genomics: Detect and display numerous events, statistical tools
Combine strengths from multiple disciplines…
… to ask new questions about
tumor signaling mechanisms
![Page 19: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/19.jpg)
Background: Acute Myeloid Leukemia
![Page 20: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/20.jpg)
AML blasts
dysregulated growth
Acute Myeloid Leukemia
Reya and Weissman, Nature 2001
Acute Myeloid Leukemia
![Page 21: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/21.jpg)
Classic AML Classification
• M0 – undifferentiated AML
• M1 – myeloblastic, immature
• M2 – myeloblastic, mature
• M3 – promyelocytic
• M4 – myelomonocytic
• M5 – monocytic
Cytogenetics + Flt3 mutation
• translocations, deletions, etc.
• frequent alterations to signaling genes
• many patients intermediate risk
• mechanism of pathology not well
understood.
FAB (primarily morphology)
![Page 22: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/22.jpg)
Course 1
• Cytarabine (Ara-C) (pyrimidine
analog, DNA synthesis inhibitor)
• An anthracycline (e.g.,
daunorubicin or idarubicin, DNA
binding Topoisomerase II
inhibitors)
Response
• Frequent relapse and < 50%
treatment efficacy
• Only used with younger,
healthier patients due to
associated toxicity.
Gajewski et al., Blood 1997; Bruserud et al., Oncologist 2000
Leukemia free survival at 5 years: < 26% +/- 8%
AML Induction Chemotherapy
![Page 23: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/23.jpg)
1) A proliferative advantage, often from aberrant signal transduction
Flt-3 mutations
Increased STAT activity
2) Inhibition of apoptosis and
differentiation
Bcl-2 family expression
Inactivation of p53 pathway?
Mechanisms of AML Oncogenesis
1. Classify / stratify patient risk based on signaling potential?
2. Identify signaling profiles linked with chemotherapy resistance?
3. Link signaling profiles with oncogene expression?
Arrayed phospho-specific flow cytometry, response panel profiles
![Page 24: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/24.jpg)
New terms used in/around this manuscript
• Biosignature – For a disease, the biosignature includes those features
that vary more in the disease than in controls
• Potentiated / Attenuated – Strengthened / Weakened• “Interrogating the potentiation of signaling pathways” = stimulating a network
to reveal its signaling potential
• Signaling Node & State – A signaling event. • A signaling node can be a protein, like STAT1. The state of the signaling node might be
phosphorylation of Y701 at 15 minutes following 20 ng/mL IFNγ. For more information,
see Irish et al. Nature Reviews Cancer 2006.
• Unsupervised vs. Supervised• Whether the features used to classify were selected based on prior
knowledge of their ability to classify
• Arrayed flow cytometry• An array is a systematic arrangement of objects, usually in rows and columns.
• Early way of referring to showing aggregate data in a heat map
![Page 25: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/25.jpg)
Tools: Phospho-specific flow cytometry
(phospho-flow)
![Page 26: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/26.jpg)
Permeabilize
Flow Cytometry Measures Signaling in Every Cell within a Sample
Stimulate
Signaling
can store
fix/perm’d cells
Fix
Measure Each Cell
(flow cytometry)Stain Cells
Non-cancer cells
Cancer cells
Protein phosphorylation
Non-cancer
cells
Cancer cells
Compare Signaling Responses
phosphorylation
phosphorylation
J. Irish
![Page 27: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/27.jpg)
Background: Phospho-specific flow cytometry
![Page 28: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/28.jpg)
Flow cytometry can measure both phospho-
and total protein levels in single cells
Cells: GM0536 / GM536
(lymphoblastoid CD19+
precursor B cells
transformed by EBV,
ATM+/+ p53+/+,
derived from healthy cells)
Stim: 8 Gray of γ IR
![Page 29: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/29.jpg)
Background: What was known prior?
![Page 30: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/30.jpg)
Basal (constitutive) phosphorylation
is common in AML
Unstimulated
healthy blood
CD33+ cells
Unstimulated
AML blasts
(>95%)
![Page 31: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/31.jpg)
Basal p-STAT5 in AML is not associated with FLT3 mutation
![Page 32: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/32.jpg)
Figures
![Page 33: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/33.jpg)
Figure 1A: Creation of a 6 x 6 phospho-flow cytokine response panel
U937 cell line: myeloid histiocytic lymphoma
![Page 34: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/34.jpg)
A 36-Spot Cytokine Response Panel
![Page 35: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/35.jpg)
+4.3 Fold
(19.6X)
No
change
-4.3 Fold
Scale: log2 ( E / B )
Arraying Flow Cytometry Experiments
![Page 36: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/36.jpg)
Figure 1B: Individual AML patients display unique signaling profiles
HL60: acute promyelocytic leukemia (APML) cell line
CD33: In the same sialoadhesin family as CD22, contains ITIMs, expressed on early myeloid lineage cells
![Page 37: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/37.jpg)
Expansion to 30 AML Patient Samples
• We applied the cytokine response panel to 30 AML patient samples
• Goal: survey both the basal phosphorylation and the cytokine response in AML patient samples.
• Find statistically significant differences between patients and use these to define and classify signaling network subgroups (that correlate with prognosis…)
![Page 38: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/38.jpg)
Figure 2A: Identification of an AML ‘biosignature’
![Page 39: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/39.jpg)
Cytokine Responses of 30 AML Samples
![Page 40: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/40.jpg)
Cytokine Responses of 30 AML Samples
![Page 41: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/41.jpg)
Figure 2B: 13 Signaling node states displayed significant variance
![Page 42: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/42.jpg)
Figure 2C: Some high magnitude signaling events
were not significantly variable in AML
![Page 43: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/43.jpg)
Figure 6A: Filtering by variance identifies an AML biosignature
![Page 44: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/44.jpg)
Figure 3: Grouping AML patients by signaling
stratifies multiple clinical features
![Page 45: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/45.jpg)
Figure 3: Grouping AML patients by signaling
stratifies multiple clinical features
![Page 46: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/46.jpg)
Figure 3: Grouping AML patients by signaling
stratifies multiple clinical features
![Page 47: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/47.jpg)
Did other signaling events matter?
Did we miss important features?
![Page 48: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/48.jpg)
Supp Table 3: IL-3 ► p-ERK & G-CSF ► p-STAT1 were next on the list(including them in the clustering didn’t change the 4 main cluster groups)
![Page 49: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/49.jpg)
Supp Table 3: IL-3 ► p-ERK & G-CSF ► p-STAT1 were next on the list(including them in the clustering didn’t change the 4 main cluster groups)
![Page 50: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/50.jpg)
What if we had just clustered
on basal signaling?
![Page 51: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/51.jpg)
Clustering AML by Basal Signaling Alone
Irish et al., Cell 2004
![Page 52: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/52.jpg)
Clustering AML by Basal Signaling Alone
Irish et al., Cell 2004
![Page 53: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/53.jpg)
Clustering AML by Basal Signaling Alone
Irish et al., Cell 2004
![Page 54: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/54.jpg)
AML Signaling Profile: Evoked Signaling
p-Erk1/2
p-p38
p-Stat1
p-Stat3
p-Stat5
p-Stat6
J. Irish
= signaling varied significantly across AML patients
(more variation in AML than in healthy samples)
Add in signaling network inputs
upstream of available p-proteins
‘Interrogating’ signaling reveals:
- Potentiated (strengthened)
signaling responses
- Attenuated (weakened)
signaling responses
=> ‘Rewired’ signaling networks
Att. Pot.
![Page 55: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/55.jpg)
A Signaling Profile of AML Therapy Resistance
Irish et al., Cell 2004
![Page 56: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/56.jpg)
A Signaling Profile of AML Therapy Resistance
Irish et al., Cell 2004
![Page 57: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/57.jpg)
A Signaling Profile of AML Therapy Resistance
Irish et al., Cell 2004
![Page 58: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/58.jpg)
A Signaling Profile of AML Therapy Resistance
Irish et al., Cell 2004
![Page 59: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/59.jpg)
A Signaling Profile of AML Therapy Resistance
Irish et al., Cell 2004
![Page 60: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/60.jpg)
A Signaling Profile of AML Therapy Resistance
Irish et al., Cell 2004
![Page 61: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/61.jpg)
Figure 4: Mutation of FLT3 (ITD) is associated with abnormal signaling
![Page 62: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/62.jpg)
Figure 5: Subsets of cells exist within SC-NP cases
and explain the SC-P2 phenotype
![Page 63: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/63.jpg)
Group Patients by Signaling →
Describe Key Signaling Features → Compare Outcomes
Irish, Kotecha, and Nolan, Nat Rev
Cancer 2006Irish et al., Cell 2004
![Page 64: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/64.jpg)
Group Patients by Signaling →
Describe Key Signaling Features → Compare Outcomes
Irish, Kotecha, and Nolan, Nat Rev
Cancer 2006Irish et al., Cell 2004
![Page 65: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/65.jpg)
Group Patients by Signaling →
Describe Key Signaling Features → Compare Outcomes
Irish, Kotecha, and Nolan, Nat Rev
Cancer 2006Irish et al., Cell 2004
![Page 66: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/66.jpg)
Figure 6B: Signaling Profile of Patients
with Better Clinical Outcomes
Irish et al, Cell 2004
![Page 67: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/67.jpg)
Figure 6B: Signaling Profile of Patients
that Resisted Course 1 Chemotherapy
Irish et al, Cell 2004
![Page 68: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/68.jpg)
Figure 7: Personalizing therapy based on signaling network profile
![Page 69: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/69.jpg)
Individual Variation in Signaling Mechanisms
![Page 70: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/70.jpg)
Signaling Profile of Patients with Better Clinical Outcome
Irish et al, Cell
2004
![Page 71: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/71.jpg)
Signaling Profile of Patients that Resisted Therapy
Irish et al, Cell
2004
![Page 72: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/72.jpg)
Irish et al, Cell
2004
Map for AML Patient 21 (Flt3-LM, Resisted Chemotherapy)
![Page 73: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/73.jpg)
Summary: Tumor Signal Transduction Profiling
• Conclusions: – 1) Heritable changes to tumors linked to modified signaling networks.
– 2) Patients whose tumors shared mechanisms of proliferative signaling responded similarly to tumor cell killing (course 1 chemotherapy).
– 3) The absolute level of phospho-proteins in cells is not as important to tumor survival as the signaling potential of the tumor cell network.
– 4) Cell by cell enumeration of signaling mechanisms reveals tumor heterogeneity and distinguishes tumor cell subsets.
• Summary: – Mapped signaling mechanisms across tumors and constructed a
signaling taxonomy of AML.
– Characterized the state of phospho-protein signaling nodes within the tumor cell network at rest and following exposure to environmental cues.
![Page 74: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/74.jpg)
What’s Next for AML?
• Expand understanding of AML signaling: – 1) Do signaling profiles change during therapy?
– 2) Does inhibition of Flt3 signaling affect (kill) cells with the Flt3 signaling profile?
• Turn the panel into a clinical diagnostic for AML:
– Prune the non-biosignature nodes.
– Retest the model in more samples. (BTG has 30-60 new patients w/ extremely detailed Flt3 mutational analysis).
– Follow up on cytogenetics in different (cytogenetically defined) patient pools.
![Page 75: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/75.jpg)
Signaling Profiles of Lymphoma
• Specific Aim I: Create in vitro flow cytometry assaysfor cell signaling functions in lymphoma cell lines and primary tissues.
• Specific Aim II: Classify lymphomas (FL) based on signal transduction mechanisms.
• Specific Aim III: Develop and test a predictive modelof lymphoma clinical outcome based on profiles of cancer cell signaling.
![Page 76: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/76.jpg)
AML Response Panel
p-Erk1/2
p-p38
p-Stat1
p-Stat3
p-Stat5
p-Stat6
![Page 77: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/77.jpg)
Expansion » Lymphoma Response Panel
p-Erk1/2
p-p38
p-Stat1
p-Stat3
p-Stat5
p-Stat6
p-Syk
p-Lck
p-GSK3b
p-JNK
p-PLCg
p-IkB
p-NFkB
Literature or experimentally predicted (normal or tumor)
![Page 78: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/78.jpg)
Status of Lymphoma Response Panel
p-Erk1/2
p-p38
p-Stat1
p-Stat3
p-Stat5
p-Stat6
p-Syk
p-Lck
p-GSK3b
p-JNK
p-PLCg
p-IkB
Literature predicted (normal or tumor)Not seen/tested yet Ready, working positive Ready, not predicted
Available w/ caveatsAntibody or stimulus not yet tested
p-NFkB
![Page 79: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/79.jpg)
Overall Goal: Use Signaling Biology to Improve Therapies
J. Irish
Molecular profiles
guide therapy
Molecular profile (based on cell signaling)
1 Cancer cells
Immune cells
Stimuli Sig
nalin
g
Re
ad
ou
ts
Tu
mo
r-in
filtra
tin
g
imm
une
ce
lls
Cancer cells
Sig
nalin
g
Re
ad
ou
t
2Identify cancer
cell subsets
based on signaling
Characterize
signaling in major
cell populations
3Model signaling
networks to identify
therapy opportunities
Clinical signaling profile
Clinical outcome
Molecular profiles
guide therapy Sample of live
primary cells
Patient, at therapy
decision point
![Page 80: Can we classify cancer using cell signaling?](https://reader030.vdocuments.us/reader030/viewer/2022012410/616a589011a7b741a3517dde/html5/thumbnails/80.jpg)
Developing a Clinical Signaling Profile
Begins with Choosing Stimuli and Readouts