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Investigating Heterogeneity of Growth
and Drug Response in Mesotheliomas.
By
Roxanne Mae Pangilan Otadoy
Dr. Cleo Robinson Primary Supervisor Tumour Immunology Group National Centre for Asbestos Related Diseases School of Medicine and Pharmacology University of Western Australia 4th Floor, G Block, Queen Elizabeth II Medical Centre Nedlands, Western Australia, 6000 Assoc. Prof. Wayne Greene Co-Supervisor Molecular Genetics School of Veterinary and Biomedical Sciences Murdoch University Room 3.041, Veterinary Biology, 90 South Street Murdoch, Western Australia, 6150
This thesis is presented for the
Honours degree in Biomedical Science at Murdoch University November 2013.
I
Declaration
I declare this thesis is my own account of my research and contains as its main content, work which has not been previously submitted for a degree at any tertiary educational institution. Signed: _________________________ Name: Roxanne Mae Pangilan Otadoy Date: 4/ November / 2013
II
Abstract
The prognosis for patients with malignant mesothelioma is very poor with patient
response to therapy highly variable. This project was aimed at investigating the
degree of heterogeneity in the responses to treatment amongst mesothelioma cell
lines which have all arisen due to asbestos exposure. Despite the use of the same
carcinogen, a number of variabilities amongst these cancers are still present.
Avenues of investigation initially tried to determine if the variability in response was
due to heterogeneity in the proliferation of malignant mesothelioma cells. Different
growth rates were observed for cell lines grown in culture and in vivo. Cells showed
different degrees of response to treatment with different chemotherapeutic agents.
An attempt was made to determine the mode of cell death undergone by cells in their
response to the treatments. Further investigation is warranted into the validity of
these results because if the differences found in the phenotype of the cells were
accurate, it could direct individualised therapeutic strategies to target the uniqueness
of malignant mesothelioma.
III
Table of Contents
Declaration I
Abstract II
Acknowledgments VII
Chapter One: Introduction 1
1.0.0 Mesothelioma 2-4
1.1.0 Disease risk associations 4-6
1.2.0 Diagnostic aids 6-9
1.3.0 Therapies 10-13
1.3.1 Classic chemotherapy 13-22
1.4.0 Cell culture 22-24
1.4.1 The in vitro assay 25-29
1.5.0 Animal models 29-30
1.5.1 The MexTAg mouse model 30-31
1.5.2 The transplantation model 31-33
1.6.0 The genetic dimension 33-36
1.6.1 CGH arrays 36-37
1.6.2 DNA microarrays 37
1.6.3 Next generation sequencing 38
1.7.0 Project hypotheses 39
IV
Chapter Two: Materials and methods 40
2.0.0 Cell culture 41-43
2.1.0 Proliferation 43-45
2.2.0 In vivo tumour growth 46-47
2.3.0 MTT assay 47-53
2.4.0 ATP assay 54-57
2.5.0 Caspase assay 57-58
2.6.0 DNA extraction 58-59
Chapter Three: The growth rate of cell lines in vitro 60
3.0.0 Proliferation rates of mesothelioma cell lines 61-63
3.1.0 Proliferation comparisons 64
3.2.0 A summary of the proliferation assay results 64-66
Chapter Four: The growth rate of cell lines in vivo 67
4.0.0 Establishing cell growth in vivo 68-71
4.1.0 Fast growing wild-types 72-73
4.2.0 A summary of the in vivo cell growth results 73-74
Chapter Five: The heterogeneic response of mesothelioma cell lines
to chemotherapy
75
5.0.0 Assessment of the cell line response to chemotherapy 76-85
5.1.0 The heterogeneity of response of mesothelioma cell lines
to chemotherapy treatment
85-86
5.2.0 A summary of the MTT assay 87-88
V
Chapter Six: Investigating the death of cells in response to
chemotherapy
89
6.0.0 The release of ATP and caspase 3/7 90
6.1.0 Establishing a reading for ATP luminescence 90-94
6.2.0 A summary of ATP assay issues and results 95-96
6.3.0 Establishing a reading for caspase luminescence 97-98
6.4.0 Caspase signal detected 99-100
6.5.0 High purity in the extraction of DNA 100-101
Chapter Seven: Discussion 102
7.0.0 Discussion 103-109
References 110-135
Appendix I: List of tables 136
Appendix II: List of figures 137-138
Appendix III: Data analysis 139-140
VI
Acknowledgements
I would like to thank my Primary Supervisor, Dr. Cleo Robinson, for her continual
guidance and support throughout such a rewarding project. Major thanks also
go to my Co-supervisor Assoc. Prof. Wayne Greene and the Honours Chair
Assoc. Prof. Alan Lymbery, without whom, this project would not have even begun.
I have been so fortunate to receive such a huge amount of help from a long list of
generous people with regards to equipment, reagents, advice and general good
company for keeping one sane, that I can’t thank these people enough (listed in no
particular order): The NCARD/T.I.G. team; fellow honours students: Steph, Wayne,
Alice, Keyuri and Clara; the School of Medicine and Pharmacology department at
UWA which includes administration staff as well as laboratory staff; the baking
club: for providing the necessary tea breaks in between; the LIWA team; the UWA
and Murdoch Universities; The Asbestos Diseases Society of WA and, of course, our
suppliers.
A special thank you goes to Prof. George Yeoh and Mr. Ken Woo for the access and
training of their Cellavista system.
Finally, to my mum Lilia, brother Rommel, sister Jena, extended family, very special
friends Ben and Desiree and everyone else who has been so patient with me during
this year of honours, “THANK YOU!” a million times for all your love and support.
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Chapter One:
Introduction
2
1.0.0 Mesothelioma
The World Health Organisation (WHO) recorded 57 million deaths for the year 2008
with a reported 36 million of these, approximately 63%, being caused by
noncommunicable diseases, including cancers (Alwin et al. 2011). Cancer is found in
many sites of the human body and is an increasing burden on human health globally
(Jemal et al. 2011). There are emotional costs on families and other members of
society, costs for patient treatment, subsidy costs from health systems and in some
cases, insurance companies must payout claims (Greenberg et al. 2010).
Mesothelioma, or malignant mesothelioma (MM), is a cancer of the serosal surfaces
that was once considered to be a rare disease, but it is one that is still growing in
incidence. However, it does have a huge economic and health burden, due to
hospitalisation and compensation claims (Robinson & Lake 2005). MM is a disease
in which governments have the option to take action, in order to curb the number of
resulting deaths, by removing human exposure to known carcinogens, such as
asbestos fibres, that are associated with the development of MM in exposed
individuals (Carbone et al. 2012).
In many countries, mining and the use of asbestos has been banned. For example, the
Wittenoom mine in Western Australia was closed down in 1966 when the
association of asbestos exposure with disease was first proven and a complete ban of
asbestos use in Australia was enforced in 2003 (Leigh & Driscoll 2003). However,
there are countries where asbestos is still being mined and manufactured into
3
products, countries such as Russia, China, Canada, India and Kazahkstan
(LaDou 2010). Reportedly, there are also individuals who develop the disease
without first being exposed to asbestos fibres, thus indicating that other factors may
be involved (Kinoshita et al. 2013).
The serosal surfaces in which MM arises are made up of simple squamous
epithelium, a class of epithelium that is typically located in vascular systems, body
cavities, and respiratory spaces with a major function of exchange and lubrication
(Kumar et al. 2010). It produces serous fluid for smooth lining of the body cavities,
namely those of the pleura, pericardium and peritoneum. These linings, in which
both visceral and parietal surfaces are affected (Figure 1.1) (Kumar et al. 2010), are
referred to as the body’s mesothelium (Saladin 2010). A cancer arising from these
linings, monolayers of mesothelial cells (Mutsaers 2004), has profound effects on the
individual. They usually present with severe chest pains and respiratory problems, in
the case of malignant pleural mesothelioma, or incur intestinal obstruction that can
lead to death, as in the case of malignant peritoneal mesothelioma
(Kumar et al. 2010). A big indicator of malignant pleural mesothelioma is combined
chest pain and unexplained pleural effusions (Robinson & Lake 2005).
Disparity in prognosis and responses observed in clinical treatments is likely to be
due to the heterogeneity observed in MMs (Szulkin et al. 2013) which are already
histologically sub-typed into 3 main groups: epitheliod, sarcomatoid and biphasic
(Raja, Murthy & Mason 2011). Sarcomatoid mesotheliomas are more aggressive
than epitheloid (Grigoriu et al. 2007). These mesothelial cells are also known to
4
change their phenotype depending on their environment, fibroblast like in culture but
epithelial like back in vivo (Mutsaers 2004).
As a cancer, MM exhibits the distinguishing feature of cancers including sustaining
proliferative signalling, evading growth suppressors, activating invasion and
metastasis, enabling replicative immortality, inducing angiogenesis and resisting cell
death (Hanahan & Weinberg 2011). Recent evidence suggests it is most likely that
there are a series of mutations that occur during tumorigenesis
(Mossman et al. 2013). The importance of fully characterising MM in order to aid in
distinguishing it from other cancers is highlighted by the fact that the epitheliod
subtype already histologically resembles adenocarcinoma, a cancer of the epithelium
(Kumar et al. 2010). Diagnosis is usually 2-3 months from the start of symptoms, a
late stage of diagnosis (Robinson, Musk & Lake 2005). It is only with correct
diagnosis that patients may receive the proper treatment (Webb & Pass 2004).
Undeniably, the prognosis for patients with MM is still very poor, just a matter of
months (Musk et al. 2011).
1.1.0 Disease risk associations
The latency period of MM, the time between initial exposure to a carcinogen and the
diagnosis of the disease, is varied and an approximate range is 25-71 years with a
median latency of 40 years (Carbone et al. 2012). The associated risks for the
5
development of MM are also varied and can come from occupational, i.e. working
with, (Leigh & Driscoll 2003) or geographical exposures, i.e. working around and
simply living in an area where there is that exposure to asbestos (Pan et al. 2005).
These include people who have worked in asbestos mines, such as the Wittenoom
Gorge in Western Australia (Figure 1.2) (de Klerk et al. 1996; Asbestos Diseases
Society of Australia Inc. 2012), or are working with asbestos materials in factories at
present in China (Wang et al. 2013) as well as those who have lived nearby naturally
occurring erionite (Carbone et al. 2012).
Exposure to asbestos fibres is a confirmed risk factor, but only about 10-20% of
highly exposed individuals will develop the disease (Jasani & Gibbs 2012). Low
levels of exposure to erionite, a naturally occurring material that bears similar
fibrous morphology to asbestos, as observed in Turkey, could be more adept in
instigating the development of the disease (Carbone & Yang 2012).
The monkey simian virus 40 (SV40) can cause MM in rodents but its role in humans
for contributing to asbestos carcinogenicity is still unproven. This is despite the
SV40 T-antigen oncogene having once been confirmed as present in human MM
samples (Rizzo et al. 2001). Evidence has since emerged that false positives were
brought about by contamination of PCR samples with laboratory plasmids when
examining the link between SV40 deoxyribonucleic acid (DNA) sequences and MM.
This makes exposure to asbestos still the more likely cause of MM
(López-Ríos et al. 2004). Nonetheless, the SV40 T-antigen has been shown to
6
interact with replication at the replication forks of DNA (Murakami & Hurwitz
1993), especially in the unwinding of the DNA to make the DNA more accessible to
transcription machinery (Foster & Simmons 2010).
Other aetiologies for MM have emerged. In one study, radiotherapy treatment has
been reported to cause MM. The study sample size is small but the disease is present
and the study is relatively new so more investigation is still needed to confirm its
role in being a risk factor for the development of MM (De Bruin et al. 2009;
Goodman, Nascarella & Valberg 2009). Similarly, more data on the various types of
carbon nanotubes and the way in which reactive species that may be produced by
carbon nanotubes to cause breaks in the DNA is still needed (Jaurand 2009;
Donaldson et al. 2010).
Acquisition is not only dependant on a patient’s level of exposure to a carcinogen.
Factors such as patient gender, age, MM subtype and location, the facilities for early
diagnosis and the level of therapeutic management that is at the patient’s disposal
also have a bearing on the patient’s quality of life (van der Bij et al. 2012).
1.2.0 Diagnostic aids
Negative and positive histological markers for MM are in existence. This includes
carcinoembryonic antigen (CEA) as a negative marker and calretinin, Wilms’
7
tumour gene (WT1) and mesothelin as positive markers (Ordóñez 2003). More
recently, the overexpressed and hypoglycosylated variety of MUC1/EMA has been
identified as a useful marker of diagnosis for MM (Creaney et al. 2008). However,
the use of histology in the hands of an experienced pathologist is not the only means
for diagnosis nowadays (Jaklitsch, Grondin & Sugarbaker 2001).
Diagnostic tools include computed tomography (CT) scans, magnetic resonance
imaging (MRI) and positron emission tomography (PET) for visualising and
distinguishing malignancy from benign disease without being too invasive.
Ultrasound guided biopsies (Figure 1.3) (Stigt, Boers & Groen 2012), a form of
surgery, is useful to obtain a sample from a patient in order to conduct diagnostic
tests to confirm the presence of MM (Jaklitsch, Grondin & Sugarbaker 2001).
Adequately acquired specimens are required for accuracy of classification as
indicated by a study on the sensitivity, 93%, and specificity, 31%, of biopsies from
MM (Kao et al. 2011). However, samples can be obtained from tumour resections,
pleural effusions (Relan et al. 2013) as well as ascites fluid, which commonly builds
up due to the cancer (Hassan, Bera & Pastan 2004), for culturing and testing in the
laboratory.
8
a)
b) c)
Figure 1.1. Malignant mesothelioma in a bisected lung. a) The white tumour is
spread out in the pleural space to encase the lung. b) An epitheliod histological
subtype of malignant mesothelioma. c) A biphasic histological subtype of malignant
mesothelioma stained to show calretinin under the immunoperoxidase method. These
images are from Kumar et al. (2010).
9
Figure 1.2. Wittenoom Asbestos Mine in Western Australia. The mine was
closed down in 1966 when asbestos became known to be associated with malignant
mesothelioma. This image is from the Asbestos Diseases Society of Australia Inc.
website (2012).
Figure 1.3. Ultrasound guided biopsy of malignant pleural mesothelioma. A
needle biopsy of the tissue core of malignant pleural mesothelioma visualised via
ultrasound with the arrow on the right indicating the needle and the larger arrow on
the left the expanded pleura. This image is from Stigt, Boers & Groen (2012).
10
1.3.0 Therapies
Therapies used to treat mesothelioma include surgery, radiotherapy, immunotherapy,
chemotherapy (Grégoire 2010), photodynamic therapy (Friedberg 2012) and gene
therapy (Vachani, Moon & Albelda 2011), either alone or in a multimodal fashion
(Liu et al. 2010).
The role of radical surgery in treatment is complete resection of the disease but the
determination of survival benefit is difficult, so whether this is the best option is still
being debated (Kaufman & Flores 2011). There is little evidence for the effective
treatment of MM using radiotherapy, but rather, this technique is seen to have a role
in pain reduction for the patient when other pain controllers, such as opiates, no
longer have an effect (Price 2011; Patel et al. 2013). Strategies for enhancing
radiotherapy efficacy are being looked into (Sudo et al. 2012). Extrapleural
pneumonectomy, a surgery for resecting tumour burdened parts of the lung, pleura,
ipsilateral diaphragm and pericardium, in conjunction with the use of hemithoracic
intensity modulated radiotherapy, has shown improved local control of MM
(Rice et al. 2007).
Immunotherapy strategies can involve dendritic cells, an antigen presenting cell and
unique protein markers expressed on the surfaces of MM cells, such as WT1
(Scattone et al. 2012) which in the case of WT1 would not normally be highly
expressed in normal adult tissues. It involves the identification of tumour associated
antigens (Cornelissen et al. 2012) and stimulation of the body’s own immune
11
response for killing off tumour cells (Mossman et al. 2013) whilst bearing in mind
that in the development of a therapy, be it viral or non-viral based,
a major factor for consideration in immunotherapy is autoimmunity
(Ireland, Kissick & Beilharz 2012).
Systemically, mesothelin is a target for immunotherapy due to the over expression of
it in epithelioid mesothelioma when compared to expression levels in normal adult
cells (Grosso & Scagliotti 2012). Programmed death-1 (PD-1) and cytotoxic
T lymphocyte antigen 4 (CTLA-4), which are inhibitory co-receptors on activated
T and B cells, are additional focal points of study (Lesterhuis, Haanen & Punt 2011).
Immunotherapy can be used as an adjunct to chemotherapy. For instance,
Gemcitabine depletes lymphocytes of the humoural immune response but the
adaptive immune system’s antigen-specific CD4+ and CD8+ T-cell responses are
enhanced (Nowak, Robinson & Lake 2002). However, the acquired immune
response works better, in the setting of immunotherapy with antigen presenting cells
being loaded with cancer specific antigens after apoptosis because the immune
system “sees” cells as being dead and “act” towards them in a certain way which is
dependent on the many feedback events that lead up to the induction of apoptosis
(Lake & Robinson 2005).
Immunotherapy has been tested as an adjuvant in combination with chemotherapy
post partial resection of the tumour to yield an 80% cure rate in mice
(Broomfield et al. 2005). Additionally, IL-2 injected intratumorally at high doses has
12
been shown to boost cytotoxic T lymphocyte activity whilst hindering angiogenesis
associated with tumours so that the body rejects the tumour (Jackaman et al. 2003).
With respect to chemotherapy, only 20-40% of patients respond to chemotherapy
and, at best, median survival is prolonged 5-9 months (Jakobsen & Sørensen 2011).
Chemotherapy is still the most frequent method used for treating MM (Nowak 2012)
despite the different side effects experienced by patients (Cheok 2012).
Gene therapy strategies that have shown some efficacy include suicide gene therapy,
cytokine gene therapy and gene-modified T-cells for adoptive transfer (Vachani,
Moon & Albelda 2011). In suicide gene therapy (Figure 1.4), a gene is introduced
into a cell that is transcribed and translated into an enzyme that converts a prodrug
into a toxic drug that can kill that cell (Duarte et al. 2012; Wu 2009). Cytokine gene
therapy uses cationic liposomes to deliver the cytokine gene, such as IFN-β, into the
cell for transcription and translation so that the particular cytokine is locally
up-regulated (Ohno et al. 2012; Kruklitis et al. 2004). Gene modified T-cells are
T-cells with specific antigen receptors generated to antigens coming from the
individual tumour and engineered on the surface of cells, these are adoptively
transferred into a patient in order to initiate the body’s immune response
(Stauss & Morris 2013). Some clinical trials for these have been performed
(Vachani, Moon & Albelda 2011).
Photodynamic therapy is relatively new and is a 3 component light-based
experimental treatment for MM to be used in conjunction with surgery to cause
13
physical cell damage, induction of apoptosis and immune response stimulation
(Friedberg 2009).
However, despite combined treatments being utilized, patient survival is still poor
and an optimal therapy is still elusive so the search for effective treatments continues
(Liu et al. 2010). A case of watch this space.
Figure 1.4. Suicide gene therapy. A suicide gene is introduced into a cell. When
transcribed and translated an enzyme is produced that is able to convert a prodrug
into a toxic drug to kill the cell. This image is from Duarte et al. (2012).
1.3.1 Classic chemotherapy
In consideration of the “classic” method for treating MM, that is, treatment with
chemotherapy, there are varying responses between individual MM patients for
single-agent treatment of chemotherapeutic drugs including Cisplatin,
Cyclophosphamide, Doxorubicin, Epirubicin, Etoposide, Gemcitabine, Ifosfamide,
14
Methotrexate, Paclitaxel, Pemetrexed and Vincristine, whereby a percentage of
patients respond to treatment and a percentage do not (Tomek & Manegold 2004).
Chemotherapeutic drugs each have different characteristics and modes of action such
that cells respond differently to them (Baas 2002). It is important to test a wide range
of these chemotherapeutic drugs in mesothelioma cell lines to determine patterns of
efficacy. Some chemotherapeutic drugs used in the clinical setting are summarised in
Table 1.1.
Cisplatin may initially bind to plasma proteins, mainly albumin, that leads to its
inactivation (Fuertes et al. 2003). It may alternatively reach the cell surface and enter
via passive diffusion. In some cases uptake may be via facilitated or via active
transport mechanisms. Inside the cell, cations of 2 species of Cisplatin are formed
which are very reactive to nucleophile sites. However, less than 1% of Cisplatin
actually binds to DNA by chance as most end up binding to other biomolecules, such
as proteins (Fuertes et al. 2003). Once it binds DNA in the cell nucleus, it interferes
with normal transcription, or DNA replication, thus blocking the functions of
important cellular proteins, eg. Hsp90 the adenosine triphosphate (ATP) binding
chaperone, leading to deregulation of the cell cycle. There is DNA degradation in
180 base pair (bp) fragments, cell blebbing and cell shrinkage that all indicate
apoptosis. In cell lines with drug resistance one can see features of necrotic cell
death. This is evidence that both types of cell death may occur simultaneously
(Fuertes et al. 2003). Cisplatin is one of the most effective chemotherapies used
currently with treatment in testicular, ovarian, bladder, small-cell and non-small cell
lung, head and neck cancers, other solid cancers (Siddik 2003) and MM
(Ong & Vogelzang 1996; Spugnini et al. 2006). A response rate of 12% was
15
observed in a study (Favoni et al. 2012). A median survival of 12.1 months when
combined with Pemetrexed has been shown on another study (Dowell et al. 2012).
Cyclophosphamide is an alkylating agent (Fleming 1997). It is also a prodrug
(Wu 2009; Fleming 1997) as it requires activation by hepatic microsomal enzymes to
be metabolized into their cytotoxic form. Cell death is caused by the inhibition of
DNA synthesis through DNA being alkylated to form DNA-DNA crosslinks
(Fleming 1997). Biological activity is dose dependent and is immunostimulatory. It
also induces the immune system to migrate to the tumour site for “mopping up” of
necrotic or apoptotic cells by inducing calreticulin to translocate to the tumour cell
surface to signal to phagocytes that it requires “mopping up” (Sistigu et al. 2011).
Leukopenia limits toxicity (Fleming 1997). The drug acts on immune cells in vivo to
treat cancer, cells such as DCs, TH1/TH2, NK and B cells (Sistigu et al. 2011). In
MM, lymphocytopenia is incited in patients by pre-treating them with
Cyclophosphamide to precondition the environment in which tumour infiltrating
lymphocytes (TILs) are to be adoptively transferred. This preconditioning has been
found to be necessary for the survival of the TILs (Lesterhuis, Haanen & Punt 2011).
In this way, Cyclophosphamide is acting in an immunotherapeutic manner, but in the
other instance, when Cyclophophamide metabolites induce the formation of DNA
intra-strand and inter-strand crosslinks (Emadi, Jones & Brodsky 2009), it is seen to
act in a chemotherapeutic manner. It is used to treat Melanoma (Sistigu et al. 2011)
and other malignant diseases such as testicular cancer, lung cancer, sarcomas,
lymphomas, breast, ovarian, cervical cancers (Fleming 1997) and MM
(Emadi, Jones & Brodsky 2009).
16
Ifosfamide is an alkylating agent similar to cyclophosphamide, a prodrug (Fleming
1997; Wu 2009), which requires activation by hepatic microsomal enzymes and
metabolized into their cytotoxic form. Cell death is also caused by the inhibition of
DNA synthesis through DNA being alkylated to form DNA-DNA crosslinks
(Fleming 1997). Neurotoxicity limits toxicity. It is also more readily eliminated by
the body than Cyclophosphamide (Fleming 1997). It is used to treat neuronal and
renal cells (Brüggemann, Kisro & Wagner 1997) along with testicular cancer, lung
cancer, sarcomas, lymphomas, breast, ovarian, cervical cancers (Fleming 1997) and
MM (Tomek et al. 2003).
Doxorubicin is an anthracyline drug isolated from Streptomyces peuceitus
var. caesius which inserts into the DNA to disrupt topoisomerase-II mediated DNA
repair, along with “poisoning” the enzyme itself, as well as create free radicals that
can damage membranes and other cellular components that can lead to apoptosis
(Thorn 2011). The drug is not very effective as a single agent and thus it is rarely
given on its own as a treatment, but usually in combination with Cisplatin
(Mirarabshahii et al. 2012; Baas 2002) and has been shown to be effective in a
phase-II clinical trial in Italy (Ardizzoni et al. 1991). Its serious side effects include
cardiomyopathy and myelosuppression (Tan, Choong & Dass 2009). It is used for
malignant melanoma (Frank et al. 2005), breast, lung, gastric, ovarian, thyroid,
non-Hodgkins and Hodgkins lymphoma, multiple myeloma, scarcoma and pediatric
cancers (Thorn 2011). It has been shown to display 20% response rates in MM
patients although more studies are needed to find out why (Tomek et al. 2003).
17
Epirubicin is similar to Doxorubicin in that it has a reorientation of the hydroxyl
group in the 4’ position of the daunosamine ring (Khasraw, Bell & Dang 2012). It
intercalates DNA to inhibit topoisomerase-II enzyme activity thus preventing DNA
repair. It also generates free radicals to interfere with cellular components such as in
protein synthesis and therefore leading to apoptosis (Khasraw, Bell & Dang 2012). It
is used in the treatment of breast (Khasraw, Bell & Dang 2012), uroethelial (Engeler
et al. 2012), muscle invasive cancers (Herr et al. 2007) and MM with responses
ranging from 0-20% in MM (Garland 2011).
Gemcitabine enters the cell via nucleoside transporters. Once inside, it transforms
into Gemcitabine Diphosphate and Triphosphate which are responsible for its
cytotoxic effects. They insert into the DNA to inhibit DNA polymerase
(DNA synthesis) and if a few are incorporated into the DNA it leads to termination
of DNA elongation so DNA repair enzymes are inhibited leading to cell apoptosis
(Mini et al. 2006). It is used in a broad range of solid tumours such as ovarian
cancer, non-small cell lung cancer (Mini et al. 2006) and has been shown to have
activity in MM with patient response ranges of 12-40% on one study
(Garland 2011).
Methotrexate is a competitive inhibitor of dihydrofolate reductase which prevents the
formation of folate cofactors needed for de novo purine and pyrimidine synthesis, a
cell cycle block in DNA synthesis, specifically in S-phase (Chan & Cronstein 2010;
Held-Warmkessel 2000). It is used to act on T-cells and various cancer cells such as
18
breast, head, neck, bladder and lung (Held-Warmkessel 2000). In MM, systemic
treatment can yield responses of 37% in clinical trials (Ellithy et al. 2013).
Pemetrexed, more commonly known by its brand name Alimta
(Chattopadhyay, Moran & Goldman 2007), inhibits thymidylate synthase,
dihydrofolate reductase, and glycinamide ribonucleotide formyltransferase enzymes
that metabolise folate and are involved in purine and pyrimidine for the synthesis of
DNA (Adjei 2004). It is transported into cells by a carrier and is converted into its
active form by folypolyglutamate synthase, and its polyglutamated form equates to
higher intracellular retention when compared to Methotrexate (Adjei 2004). It is used
to treat non-small cell lung cancers (Hanna et al. 2004), a variety of solid tumours
(Adjei 2004) and MM with a retreatment response rate of 19% in one study of MM
(Ceresoli et al. 2011). It is currently a standard therapy for MM when combined with
Cisplatin and vitamin supplementation to yield response rates of 41% with a median
survival of 12.1 months (Garland 2011).
Etoposide Phosphate is a highly water soluble form of Etoposide. This prodrug is
converted into its active form Etoposide by alkaline phosphatase in physiological
conditions. It produces cell cycle blocks at S and early G2 phases and can produce
single as well as double stranded breaks. It prevents the strand rejoining activity by
the topoisomerase enzyme (Witterland, Koks & Beijnen 1996). It is used for treating
small cell lung cancer (Witterland, Koks & Beijnen 1996), sarcoma, melanoma,
19
renal cell carcinoma (Hande 1998), and MM with 0-4% response rate as a single
agent treatment in one study on MM (Ryan, Herndon & Vogelzang 1998).
Paclitaxel is a drug that targets the microtubules of the cell. Mitosis fails due to the
destabilisation of the cell microtubule polymerisation (Alexandre et al. 2007).
Tubulin polymers are formed (McGuire et al. 1996). Transport of organelles is also
affected and hence cellular function (Alexandre et al. 2007). It is used for treatment
of squamous cervical cancer cells (McGuire et al. 1996), melanoma, leukaemia, lung
tumours (McGuire et al. 1996) and MM with a 9% response rate as a single agent in
one study of MM (Ryan, Herndon & Vogelzang 1998) and no therapeutic response
in another study (van Meerbeeck et al. 1996).
Vincristine acts to inhibit the formation and the disruption of the cell’s mitotic
spindle at metaphase (Himes et al. 1976). The target molecule is tubulin
(Himes et al. 1976). At higher concentrations, it may have effect at interphase
(Madoc-Jones & Mauro 1968). It is used for the treatment of mammary cells in
breast cancer, lymphomas, lung small cell carcinomas (Himes et al. 1976) and MM
with very little therapeutic response as a single agent treatment for MM
(Mårtensson & Sörenson 1989).
Bleomycin belongs to a family of glycopeptide antibiotics and has been isolated
from Streptomyces verticillus. There are many analogues of the drug
(Chen & Stubbe 2005). It forms a complex with Fe (II) and O2. The DNA is attacked
20
by a complex formed from this initial complex. At some sites the DNA bases are
released from their glycosidic linkages and at other sites the DNA backbone is
cleaved at the C3-C4 sites (Burger, Peisach & Band Horwitz 1981). It is a
hydrophilic molecule that can also bind other transition metals. It cannot freely
diffuse through the cell membrane and its uptake may be mediated by its positively
charged tail (Chen & Stubbe 2005). The most common outcomes of this treatment
are extended cell cycle arrest, apoptosis and mitotic cell death
(Chen & Stubbe 2005). It is used in the treatment of testicular cancer
(Chen & Stubbe 2005), leukemia (Bonadonna et al. 1972), early-stage Hodgkin’s
lymphoma (Engert et al. 2010) and squamous cell carcinomas (Cai et al. 2011) just
to name a few. In MM it is used in combination with chemotherapeutic drugs such as
Cisplatin and Doxorubicin (Baas 2002).
Aside from the variation in chemotherapeutic drugs alone, variation in response not
only exists in single-agent treatments but also in combination treatments
(Berghmans et al. 2002) such as Doxorubicin combined with Cisplatin, Bleomycin
and Mytomycin C (Baas 2002). If variation in chemotherapeutic drug sensitivity
between MM cell lines is anything to go by, there is a need for personalized therapy
(Szulkin et al. 2013), be it single-agent, combination chemotherapy or in
conjunction with other forms of therapy such as immunotherapy
(McCoy, Nowak & Lake 2009). The order in which the treatments are applied in
combination (Zanellato et al. 2011) and the dosage amount (Veltman et al. 2010) are
also factors for consideration.
21
Furthermore, treatment development requires consideration of the immune response
that, for example, can manifest as inflammation induced by asbestos exposure,
involving HMGB1 and the Nalp3 inflammasome, a feature that promotes the growth
and survival of the MM cells. Targeting against these in treatment could lead to
prevention or a delay in the disease onset of MM in patients
(Carbone & Yang 2012). There is a need for modelling the disease in vivo
(Carbone et al. 2004) and in vitro to thoroughly test the efficacy of any proposed
treatment either as single agents or in combination before they are introduced into
the clinical setting.
Table 1.1. Chemotherapeutic and anti-proliferative drugs. Brief summary of
chemotherapeutic drugs for treating cancer grouped according to their mechanisms
of action.
Drug Mechanism of action Reference
Cisplatin, Cyclophosphamide, Ifosfamide
Alkylating agent, stops DNA replication Favoni et al. 2012
Doxorubicin, Epirubicin
Anthracycline, DNA intercalating agent to inhibit DNA systhesis Favoni et al. 2012
Gemcitabine, Methotrexate, Pemetrexed
Anti-metabolite, terminates DNA replication Favoni et al. 2012
Etoposide Topoisomerase inhibitor, inhibit DNA syntheis Hande 1998
Paclitaxel, Vincristine
Natural alkyloid/Vinca alkyloid compound, anti-mitotic to inhibit cell division Favoni et al. 2012
Bleomycin Anti-proliferative, DNA-strand breakage Cai et al. 2011
22
1.4.0 Cell culture
For research purposes, patient or animal samples can be purified and cultured in vitro
and used for both in vitro and in vivo studies. MM cell lines can be established from
ascites by placement in tissue culture flasks and provided with nutrients. They can
then be grown as a monolayer and maintained in vitro (Davis et al. 1992) for several
months (Klominek et al. 1989) in humidity with 5% CO2 at 37°C
(Liu & Klominek 2003) or preserved at freezing temperatures, such as in a -80°C
freezer or in liquid nitrogen (Kubo et al. 2011). Cells in flasks (Figure 1.5) may
utilize varying amounts of media and supplements, such as foetal calf serum (FCS)
in RPMI: 5% in one study (Liu & Klominek 2003), 10% in another (Pass et al. 1995)
and 15% FCS in yet another study (Holloway et al. 2006). There is serum
dependence for growth of cell lines in vitro which vary depending on the particular
cell’s requirement (Klominek et al. 1989). Purified cell cultures can be immortalized
by providing them with the telomerase catalytic subunit that maintains and defers the
shortening of the cell’s telomeres thus allowing the cell to proliferate indefinitely
(Alberts et al. 2008).
Cell culture in this way is of a 2-dimensional nature. The cell interacts with the cells
directly adjacent to them and their other form of contact is adhesion with the bottom
of a flask in which they are contained. In vivo, the cells exist in a
3-dimensional (3D) environment whereby cells are surrounded by other cells all
over. To better mimic this physical layout in vitro, an AlgiMatrixTM 3D alginate
scaffold plate has been devised (Godugu et al. 2013).
23
Nonetheless, the monolayer is very important for studies in MM. Monolayers exist
in the body for lining cavities (Harris et al. 2012). This is especially true in the case
of the serosal surfaces that line the pleura, pericardium and peritoneum
in which MM arises. Cell culture in monolayers have been used for many years
(Alberts et al. 2008) for obtaining data on cancers and other diseases not only in
response to therapies (Carmichael et al. 1988) but for also determining the physical
properties of cell interaction to provide information about the junction molecules
between the cells that are, for instance, readily targeted by pathogens
(Harris et al. 2012).
24
a)
b)
Figure 1.5. Cell lines grown in culture. Cells were grown in a BD T75 culture flask
in complete medium and viewed under a Nikon TMS inverted phase contrast
microscope at 10x ocular and 10x objective magnifications. The diameter of field of
view has not been shown. a) A MexTAg 299 208 mouse cell line in culture. b) A
wild-type BM 164 mouse cell line in culture.
25
1.4.1 In vitro analyses
There are a number of assays that can be performed on cultured cells that are aimed
at quantifying how a cell will respond to an agent and how this response would then
translate to a response in humans. Viability assays, including the Alamar Blue assay
(Godugu et al. 2013) and the MTT assay (Stockert et al. 2012), are useful for fast
and simple preliminary discovery of the efficacy of cytotoxic compounds by
determining the number of viable cells at an end point (Hamid et al. 2004). The
Alamar Blue assay is dependent on the conversion of a “non-fluorescent dye to a red
fluorescent dye” (Godugu et al. 2013) whilst the MTT assay is dependent on the
conversion of MTT, 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide,
into formazan crystals (Figure 1.6) by the living mitochondria in a cell
(Meerloo, Kaspers & Cloos 2011) such that there is a higher optical density reading
when more cells are viable.
It is important to determine how a cell dies when exposed to an agent such as a
chemotherapeutic drug. Cells can follow an apoptotic or necrotic pathway, a normal
or an abnormal occurrence respectively. Apoptosis is programmed cell death which
can be caused by DNA damage, accumulation of misfolded proteins and atrophy
after organ blockages. Apoptotic bodies and blebbing of the cell surface are often
seen under the microscope. In necrosis the membrane integrity of cells are
compromised such that the contents of the cell tend to leak out, the cell swells and
then bursts (Kumar et al. 2010; Alberts et al. 2008).
26
Agents that cause apoptosis, and not necrosis, have been shown to be more
beneficial for the efficacy of chemotherapy (McCoy, Nowak & Lake 2009). Assays
for determining the modulation of cell death for apoptosis includes methods for
morphological assessment such as the universal terminal deoxynucleotidyl
transferase-mediated dUTP nick-end labelling (TUNEL), an assay designed to take
advantage of the fact that endonucleases cleave DNA into fragments when the cell is
undergoing apoptosis such that a procedure of the assay labels the terminal ends of
the fragmented DNA for detection (Alberts et al. 2008). Another one in use is the
fluorescence-activated cell sorter (FACS), a preparation whereby antibodies to
apoptotic cell surface markers are coupled to a fluorescent dye and exposed to cells
before a machine is used to sort individual cells according to the fluorescent signal,
or lack thereof, being emitted as the cell passes in single file across laser detectors on
the FACS machine (Figure 1.7) (Kepp et al. 2011; Alberts et al. 2008). RT-PCR can
be used for measuring mRNA expression of the anti-apoptotic BCL-2 protein family
marker (Godugu et al. 2013). Necrosis can be measured by determining extracellular
HMGB-1 from ELISA based kits (Kepp et al. 2011). Alternatively, ATP levels can
help determine death by apoptosis or necrosis (Eguchi, Shimizu & Tsujimoto 1997).
Inflammation is important in the study of MM because cells exposed to asbestos
fibres, the main risk associated with MM, make pro-inflammatory cytokines along
with other host cells to initiate inflammation, a response directed against the cancer
cells themselves (Pinato et al. 2012). It has been suggested that inflammation could
be used to predict overall survival (OS) (Suzuki et al. 2011). Neutrophil-to-
lymphocyte ratios (NLR) have been associated with prognosis but further
27
investigation is required (Kao et al. 2010). Inflammation occurs not only in the
development of MM but in other cancers too, such as melanoma and lung carcinoma
(Sriram Krishnamoorthy Kenneth 2006). Similarly, inflammation has been found to
precede MM in a mouse model (Hillegass et al. 2010). Inflammation markers, such
as C reactive protein (CRP), VEGF and IL-6, can be tested using commercially
available ELISA kits (Kao et al. 2013). Light microscopy
(Michael H. Ross & Wojciech 2011) and FACS (Figure 1.7) can be used for
determining the number of neutrophils and lymphocytes for the NLR analysis
(Harvey Lodish et al. 2008).
Figure 1.6. Formazan crystals formed in cells. A paper by Stockert and colleagues
(2012) showing the formation of formazan crystals in cells during an MTT assay.
The formazan crystals are labelled with MTT-F with arrows indicating their position
in the cell. The crystals have also been shown in pink.
28
Figure 1.7. Fluorescence-activated cell sorter (FACS). The suspension of labelled
cells is passed in single-file for detection by a laser beam with their emitted and
scattered lights measured for discrimination between different cell types. This image
is from Harvey Lodish et al. (2008).
29
1.5.0 Animal models
Animal models for studying disease in a controlled environment are a requirement
(Kane 2006) especially since the rarity of MM is a limitation when gathering useful
information. Animal welfare is of great importance however, animal use in research
is indispensable in aiding our understanding of diseases and the provision of
preclinical data about all aspects of cancer development and treatments
(Workman et al. 2010; Carbone et al. 2004).
Rats, mice and hamsters are just some of the species that have been used to reveal
the carcinogenicity of asbestos fibres as well as various other compounds and
chemicals in relation to MM (Kane 2006). Mouse models are widely used, some
genetically engineered (Kane 2006), and there are several MM mouse models
available; heterozygous Nf2 (+/-) (Altomare et al. 2005), nude
(Spugnini et al. 2006), AB1-HA (van der Most et al. 2009), BALB/c NLRP3 (-/-)
(Chow et al. 2012) and MexTAg mice (Robinson et al. 2012) just to name a few.
The replication of the onset and progression of human cancer are essential criterion
for an ideal mouse model, however, it is difficult to generate a mouse model that will
faithfully replicate all the characteristics and variants of a human cancer. Thus a
mouse model is chosen according to the specific aims of investigation, be it genetic,
aetiological and therapeutic response or insights (Hann & Balmain 2001). Among
other phenotypic issues, spontaneous tumours can develop in some of the animal
models, such that these need to be distinguished from mesothelioma development
30
and can interfere with the investigation (Workman et al. 2010). For MM, the
MexTAg asbestos-induced model has the most features in common with human MM
and there is no interference from other tumours. MM only arises in the presence of
asbestos (Robinson 2011).
Animal experiments are an avenue for providing supporting evidence for the efficacy
of a novel therapy of a disease (Workman et al. 2010). How the results of testing
exactly translate to human disease cures is a line of questioning that the researcher
needs to consider when they are setting up their animal study (Workman et al. 2010).
Predicting how a patient will respond to treatment is just as important as finding
ways to kill off these MM cells (Francis et al. 2007). Rigorous preclinical testing in
response to treatments first in the animal model is still an area in which more work is
needed (Workman et al. 2010).
1.5.1 The MexTAg mouse model
The MexTAg is a transgenic (Figure 1.8) mouse model developed for mesothelial
cell expression of the SV40 T-antigen through use of the cell specific mesothelin
promoter. Four successful MexTAg mouse lines were produced with respective copy
numbers of the SV40 T-antigen of 100, 32, 15 and 1: “299h (high), 304i
(intermediate high), 270i (intermediate low) and 266s (single)”
(Robinson et al. 2006). For the development of MM in these mouse lines, asbestos
exposure is a requirement as mice without asbestos exposure do not develop MM.
The MexTAg mouse shows low incidence of other tumours (Robinson et al. 2011).
31
The wild-type counterparts only show an incidence of 20-30% of developing MM
after asbestos exposure, which is low when compared to the 299h mouse lines, on
the other hand, that show an incidence of 100% (Robinson et al. 2006). The latency
period of MM in the mouse model is comparable to that in human time span along
with the location of the tumour when it does develop (Robinson et al. 2011).
Furthermore the same carcinogen is used to induce disease. This model is useful for
testing novel therapies, cancer prevention strategies, early molecular changes in
disease development and preclinical studies for optimisation of effectiveness, dose
and scheduling of chemo or immunotherapies, single use or in combination.
1.5.2 The transplantation model
Tumours can be introduced into a mouse, and have it relatively contained, by
injecting cultured cells subcutaneously into the flank of mice
(Tomayko & Reynolds 1989). Figure 1.9 shows the schematic location of the
subcutaneous layer of the skin (Alberts et al. 2008). The main advantage of this type
of model is that tumour growth can be readily measured using callipers to monitor
response to therapy. Tumour growth is typically faster compared to the carcinogen
induced models, so experimental data can be achieved more rapidly. Additionally,
chemotherapeutic agents can be administered directly into the tumour for treatment
(Tomayko & Reynolds 1989).
In MM, subcutaneous (sc) as well as intraperitoneal (ip) injections for implantation
of tumours is used in mouse models (Varghese et al. 2012). Chemotherapy
32
treatments can be administered in mice in parallel with administration in human
patients, that is, via ip (Yan et al. 2009).
Figure 1.8. Creation of a transgenic mouse. To create a transgenic mouse,
embryonic stem cells (ES) are grown in culture. An altered version of a target gene is
made. This is introduced into the ES and allowed to grow. The cells are tested to find
the one where the target gene in the ES has been replaced with the altered version.
That is then injected into an early embryo that has been isolated from a female
mouse. If successful, a hybrid early embryo is formed and injected into a female
mouse. Offspring are tested for the presence of the mutant gene and those are
selectively bred to produce the required transgenic mouse. This mage is from
Alberts et al. (2008).
33
Figure 1.9. Layers of the skin. The Epidermis at the top of the image, faces a “free
surface” that is not in connection with other cells. The layer labelled ‘hypodermis’,
at the bottom of the image, is the subcutaneous layer. This image is from
Alberts et al. (2008).
1.6.0 The genetic dimension
It has been proposed that a contributing factor in the variation of prognosis is genetic
predisposition (Carbone & Pass 2006) and that there exists an increased risk for
certain individuals for acquiring the disease when exposed to asbestos due to their
genetic predisposition as indicated in a genome-wide association study (GWAS)
(Cadby et al. 2013; Matullo et al. 2013). This notion is further supported by the
discovered germline BAP-1 mutation in MM whereby it is seen to gain genetic
material at a locus but then in another MM a focal deletion occurs inside of a larger
Subcutaneous injection is in this layer, the
hypodermis.
34
deletion (Testa et al. 2011). However, in a Western Australian GWAS of 428 MM
cases and 1269 controls with Italian study case-controls for reference, there was not
a single nucleotide polymorphism of statistical significance detected. Although
SKD1, encoding for adhesion molecules, did show up comparably between the
Australian and Italian studies. CRTAM, for cell adhesion, and RASGRF2, converts
movements in cells from elongation to rounding, were also highlighted in the study
(Cadby et al. 2013). More genetic studies are needed.
Molecular tools such as comparative genomic hybridization (CGH) arrays
(Figure 1.10) and DNA microarrays have greatly advanced the way in which we
visualise and thus classify cancers (Pollack 2007). Microarray data enables the
researcher to identify targets for the production of potential treatments. Such targets
include those associated with energy, remodelling of the cytoskeleton and the
translation of proteins which are up-regulated during testing of MM cells in vitro
(Robinson & Lake 2005).
MM is marked by deletions rather than gains as seen when chromosomal
karyotyping is performed (Musti et al. 2006). Through the use of CGH array, gains
and losses in the “5p, 7p, 7q, 8q, and 17q” and “1p, 3p, 6q, 9p, 13q, 14q, 15q and
22q” chromosomal regions respectively with different frequencies of gains and
losses when MM are grouped into its subtypes (Musti et al. 2006).
The deletion of the CDKN2 locus is most common in MM and found in up to 80%
of MMs. Notably, deletions are observed for CDK2NA and CDK2NB that encode
for p16 and p15 (Musti et al. 2006). This region encodes cyclin dependent kinase
35
inhibitors p16 and p15, which are important in cell cycle regulation and are classed
as tumour suppressor proteins. The p53 and Rb tumour-suppressor genes which are
frequently absent or inactivated by mutation in other cancers are not targeted in MM,
perhaps because the genes for p16 and p15, which are in the same pathway as p53
and Rb, are absent instead (Robinson & Lake 2005). NF2 deletions are the next most
common, in about 50% of MMs. In MM, BAP-1 is observed to have a high rate of
deletion; in 23% of malignant pleural mesothelioma cases
(Bott et al. 2011). The LATS2 gene on the 13q12 chromosome is also seen to be
deleted in MM, but is more rare (Murakami et al. 2011).
The molecular mechanism underlying development of malignancies due to exposure
to asbestos fibres are not yet fully understood (Liu, Cheresh & Kamp 2013).
However, it has been indicated that reactive oxygen species (ROS) may play a role
in the cytotoxicity and mutagenicity of asbestos induced MM such that ROS can lead
to breaks in the DNA strand as well as changes in the DNA itself with
8-OHdG causing GT modification to name one example of its effect
(Xu et al. 1999).
There is heterogeneity in the human population for MM as seen in chromosomal
aberrations in which some variants are yet to be discovered as acquiring “snap shots”
of the state of the disease at all possible time points is a big undertaking especially
due to the long latency period of MM (Musti et al. 2006). Varying levels of
expression and activation, or lack thereof, of markers and pathways linked to the
lengthy transformation and tumour progression of mesothelial cells are being
investigated (Carbone & Yang 2012). AP-1, NF-κB and Phosphoinositide 3-
36
kinase/AKT pathways are just a few of the areas in which research is being
conducted (Carbone & Yang 2012; Jagadeeswaran et al. 2006). TAM67 has been
used to target the AP-1 pathway for treating cancer by impairing directed movement
that leads to a change in cell morphology via cell cycle arrest in the G1 phase of the
cell cycle (Libermann & Zerbini 2006). Bortezomib has been used in a phase-II
clinical trial with efficacy in reducing NF-κB activity in vitro and in vivo on MM
cell lines (O’Brien et al. 2013). Unfortunately, only a small portion of patients
benefit from pathway interference of these specific therapies developed from those
formally mentioned (Carbone & Yang 2012). The Wnt pathway has been found to be
disordered in MM with “secreted frizzled-related proteins” (sFRP) primarily
involved in the disruption of the pathway (Lee et al. 2004). The hippo pathway has
also been shown to be modified, or disrupted, in MM. A key player in this is NF2,
which encodes for Merlin and regulates signalling pathways involved in cell growth.
As mentioned above NF2 is frequently found to be inactivated in MM. Targeting
NF2 could lead to a treatment option (Jean et al. 2012).
1.6.1 CGH arrays
Comparative genomic hybridization (CGH) enables the user to identify unregulated,
or down regulated, parts of the genome through the use of fluorescently labelled
DNA fragments which are competitively bound to normal metaphase chromosomes
with repeating sequences, such as those blocked by Cot-1 DNA
(Inazawa, Inoue & Imoto 2004). Red signals deletion and green signals amplification
(Figure 1.10). This process reveals copy number variation and can be applied to
37
tumour samples to give information on the genetic changes that could be involved in
tumourigenesis (Inazawa, Inoue & Imoto 2004). It is possible that specific genetic
changes could account for determining sensitivity or resistance of an individual’s
cancer to treatment. However, its application is limited in that prior knowledge of
regions of interest in the DNA is needed to design the array for a study
(Davies, Wilson & Lam 2005). Due to recent technological advances, applications
such as CGH array have become more affordable and accessible to researchers
(Guan, Wang & Shih 2010).
1.6.2 DNA microarrays
Specific nucleotide sequences are arranged on a special glass slide to act as probes
for hybridizing samples of fluorescent DNA along with reference samples
(Alberts et al. 2008). For instance, if gene expression is high, in the sample that has
hybridized onto the probes on the glass slide when compared to the expression level
of the reference sample, then the spot is scanned as red. The spot is green if there is
low expression of the target gene and it is yellow if there is no difference between
the target and reference expressions. All this is then combined for complex analysis,
such as the cluster analysis, that permits the researcher to look at a large number of
genes which are regulated in a coordinated manner (Alberts et al. 2008).
38
1.6.3 Next generation sequencing
Next generation sequencing (NGS) overcomes the bias limitation of CGH arrays in
that more of the genome can be targeted for inspection because little knowledge of
the DNA sequence is need to provide a more comprehensive insight into the genome
with added advantage that the machines are capable of parallel processing millions
of DNA sequence reads in a single run (Mardis 2008). The cost of running a NGS is
also exponentially decreasing, making it a more affordable option for discovering
genomic variations (Koboldt et al. 2013). As always, correct analysis of the data is
required but the volume of data is so large that at present data storage and
computational infrastructures are limiting the ability of the researcher to examine the
dataset quickly (Koboldt et al. 2013).
Figure 1.10. CGH Array. Genomic DNA from tumour and normal tissues are
fluorescently labelled and hybridized onto a DNA micro array plate with the ratios of
the red and greed signals plotted. This image is from Alberts et al. (2008).
39
1.7.0 Project hypotheses
1. A heterogeneic response to chemotherapy will exist and cell lines will segregate
into clear groups of good and poor responders.
2. Response to chemotherapy will correlate with genotype.
40
Chapter Two:
Materials and methods
41
2.0.0 Cell culture
One major area of interest in the project, from the hypothesis that response to
chemotherapy will correlate with genotype, was in the SV40 T-antigen’s interaction
with replication at the replication forks of DNA (Murakami & Hurwitz 1993),
particularly in its role in the unwinding of the DNA (Foster & Simmons 2010). As
unknown genes in the genome were made more accessible to transcriptional
machinery by this antigen (Foster & Simmons 2010), it was important to determine
whether or not this change in accessibility would actually affect the environment
within the cell, or on the cell surface, such that the response to chemotherapy was
also altered. As such the MexTAg cell lines which already have the SV40 T-antigen
DNA fragment in their genome were selected for this project along with their
transgenic negatives, the wild-type cell lines, as controls for comparison.
All cell lines (Table 2.1) were grown in complete medium composed of Roswell
Park Memorial Institute (RPMI) 1640 medium, 5% foetal calf serum (FCS), 5%
newborn calf serum (NCS), 9 mL of 10 mM hepes, 0.5 mL of 60 mg/L
benzylpenicillin and 0.66 mL of 50 mg/mLgentamicin. They were placed in
BD T75 culture flasks for in vitro assays or BD T175 culture flasks for in vivo
assays and into a humidified 37°C / 5% CO2 incubator. At about 80% - 95%
confluence they were either passaged, to continue growth of the cell line, or utilized
in an assay.
42
Table 2.1. The cell lines used in this project. There were 7 wild-type and
7 MexTAg mesothelioma cell lines which originated from C57BL/6 mice which had
all been phenotyped as sarcomatoid.
For each passage of a BD T75 culture flask of cells, the following steps were taken:
1) The old complete medium was removed by suction and the cells were briefly
washed with 5 mL of phosphate buffered saline (PBS) with the PBS also
removed by suction.
a. Note that 10 mL of PBS was used for BD T175 cultures.
2) After the addition of 1.5 mL of trypsin the flask was placed in a humidified
37°C / 5% CO2 incubator for about 1 min, or until the cells were detached from
the flask surface as viewed under an inverted microscope.
a. Note that 3 mL of trypsin was used for BD T175 cultures.
Cell Line Cell Type Description
299 376299 62
C57BL/6 mice were injected with asbestos in the peritoneum. Ascites were collected from different mice and cultured as wild-type cell lines. All
previously phenotyped as sarcomatoid.
Transgenic mice were created from embryos of the C57BL/6 mice. The SV40 Large T antigen was introduced to embryonic stem cells grown in culture. The stem cells in which one copy of a normal gene was replaced by the introduced
DNA fragment were injected into isolated partly formed early embryos and permitted to grow in female C57 black mice. These mice were then injected with asbestos in the peritoneum and the ascites collected from different mice
and cultured as MexTAg cell lines. These cell lines have 100 copies of the SV40 Large T antigen in its genome. All previously phenotyped as sarcomatoid.
wild-type
MexTAg
299 210
AE 3
AE 16
AE 17
AE 19
BM 109
BM 163
BM 164
299 166
299 170
299 175
299 208
43
3) After a few taps of the flask, 8.5 mL of complete medium was added, the
contents of the flask transferred into a 50 mL BD falcon tube, the tube
centrifuged in a Hettich Rotina 420R centrifuge, or Eppendorf 5702 centrifuge,
for 5 mins at 1200 rpm, the supernatant removed by suction.
a. Note that 7 mL of complete medium was added to the flask for spinning
down of BD T175 cultures.
4) The pellet of cells was resuspended in 5 mL of complete medium.
a. Note that the pellet of cells was not resuspended in complete medium in
the case of BD T175 cultures. Refer to section 2.5.0: In vivo tumour
growth.
5) In order to keep the cell line going, a volume of this cell suspension was
transferred into a fresh BD T75 culture flask with 13 mL of complete medium.
This flask was then placed back into a humidified 37°C / 5% CO2 incubator for
cell growth.
a. Note that cell suspensions from cell cultures that originated from
BD T175 flasks were used for in vivo cell growth experiments only.
2.1.0 Proliferation
The cell lines in complete medium were plated onto BD 96-well flat bottom plates at
4 different concentrations in triplicate wells and permitted at least 3 hrs to attach to
the bottom of the well in a humidified 37°C / 5% CO2 incubator. The plates were
then placed in the Cellavista Innovatis system (Cellavista) machine hardware, by
Roche Diagnostics GmbH, with the following image adjustments, in the Cellavista
control and evaluation software version 2.0.1.860, to focus the camera on the
44
adherent cells: bright-field exposure 1, UPLFLN 10x objective, 100% intensity and
white rim focus offset setting of 2. The plates were analysed for cell confluence
percentage on the Cellavista at 2 time points each day for at least 8 time points in
1 week. The plates were placed back into a humidified 37°C / 5% CO2 incubator for
cell growth between readings.
Two variables of interest were exported from the Cellavista: the cell confluence
percentage for each cell line in each well and the number of hours since the initial
reading. As the adherent cells proliferated on the surface of a BD 96-well plate, the
cell confluence percentage, as measured by the Cellavista system, also increased. At
4 different plating densities (5.00x103, 2.50x103, 1.25x103 and 1.00x103 cells/well)
on the BD 96-well flat bottom plate, the cell confluence percentage of 3 wells for
each cell line was obtained at different time points which was as far apart in a day as
possible. These 2 bits of data were exported onto a Microsoft (MS) Excel
spreadsheet for processing.
The exponential growth phase of a cell line was determined by eye from a growth
curve that was plotted using data from the Cellavista. The mean cell confluence
percentage and the standard deviation (SD) of 3 wells for each plating density of
each cell line were plotted against a time span from the point of initial reading. The
exponential growth phase was represented by the steepest, longest and near linear
slope of each plot as determined by eye.
The line of best fit through the exponential growth phase of a cell line was then
determined. A minimum of 3 cell confluence percentage data points at 3 time spans
45
with relatively small SDs between the triplicate data points were used for the linear
regression analysis in Graphpad Prism version 6.02 (Graphpad) which outputted the
equations of the lines of best fit for each well on the plate. Any point along the
equation of the line of best fit represented the points that could be used to determine
the doubling time of a cell line in each well.
The proliferation rate was defined by the doubling time (Appendix III). The
proliferation assay was repeated until at least 3 doubling times were obtained for
each cell line. All statistical data analysis performed in this project was conducted in
the Graphpad software. Levels of statistical significance as grouped in the software
have been listed in Table 2.2.
Table 2.2. Statistical significance levels. The different levels of statistical
significance in Graphpad has been listed in this table both in words and as symbols
grouped according to p-values.
P-value Words Symbol
< 0.0001 Extremely significant ****
0.0001 to 0.001 Extremely significant ***
0.001 to 0.01 Very significant **
0.01 to 0.05 Significant *
≥ 0.05 Not significant ns
46
2.2.0 In vivo tumour growth
The pellet of cells prepared from BD T175 culture flasks was resuspended in 10 mL
of PBS and put into a Hettich Rotina 420R centrifuge, or Eppendorf 5702 centrifuge,
for 5 mins at 1200 rpm, the supernatant removed by suction and the pellet of cells
resuspended again in 10 mL of PBS. A sample of this was diluted in PBS and mixed
with 0.4% trypan blue stain in a ratio of 1:1, loaded onto a Countess cell counting
chamber slide and the viable cells were counted using an Invitrogen Countess
automated cell counter. The remaining cell suspension was centrifuged again for
5 mins at 1200 rpm, the supernatant removed by suction and the pellet of cells made
up to the volume required in PBS for a final cell suspension concentration of
1x107 cells/mL. The cells were double contained in a 5 mL tube and put on ice for
transport.
A BD Ultra-Fine 0.5 mL needle was used to inject each of the wild-type mice with
0.1 mL of the 1x107 cells/mL wild-type cell suspension. The MexTAg mice were
each injected subcutaneously in the right hind flank with 0.1 mL of the
1x107 cells/mL MexTAg cell suspension. Mice were weighed with an Ohaus Scout
Pro SP401 set of scales, tumour sizes were measured using the Sylvac S_Cal PRO
digital caliper and measurements recorded automatically on Studylog version 1.9.8
and manually by hand on paper as backup. Pins, tumours that were too small for the
digital calipers to measure but were the start of tumour growth detection as they had
felt like a grain of rice under the skin, were approximated to a size of 0.25 mm2 for
small pins with slightly bigger pins approximated to a size of 1.00 mm2. A
qualitative scoring system was put in place to assess the well-being of mice: activity,
47
alertness, body condition and coat were checked. All mice were acclimatised to their
environments and handled for at least 1 week prior to the subcutaneous injections.
Data was recorded on Studylog version 1.9.8 and exported into MS Excel 2007
before being copied into Graphpad for the production of graphs and execution of
statistical analysis.
2.3.0 MTT assay
A sample of cell suspension was mixed in a ratio of 1:1 with trypan blue. A
haemocytometer was used to count viable cells. A cell suspension in complete
medium with a concentration of 5x104 cells/mL was made. From this suspension,
0.1 mL was pipetted onto a BD 96-well flat bottom plate to yield 5x103 cells/well for
testing. This test plate was put into a humidified 37°C / 5% CO2 incubator for 24
hrs.
The chemotherapeutic drugs (Table 2.3) were obtained from Sir Charles Gardiner
Hospital (SCGH) Pharmacy. All drugs excluding Cisplatin were frozen down and
used after the first thaw. Cisplatin was only refrigerated. All drugs were used before
1 month had elapsed after freezing. The thawed drugs were serially diluted 10-fold in
complete medium in a BD 96-well round bottom plate.
A Thermo Scientific Finnpipette multichannel pipette was used to transfer 0.1 mL
from each well of the inoculation plate into the test plate that had been incubating for
24 hrs. This test plate was put back into a humidified 37°C / 5% CO2 incubator for a
further 48 hrs after which 0.05 mL of 2 mg/mL filtered MTT was added to all the
48
wells of the test plate and the plate returned to a humidified 37°C / 5% CO2
incubator for a further 4 hrs of incubation.
Table 2.3. The chemotherapeutic drugs supplied by Sir Charles Gardiner
Hospital Pharmacy. The highest concentration made available for each
chemotherapeutic drug has been listed in this table. The drugs were diluted in
complete medium as necessary.
Chemotherapy Concentration (mg/mL)
Bleomycin 1 Cisplatin 1 Cyclophosphamide 20 Doxorubicin 2 Epirubicin 2 Etoposide Phosphate 20 Gemcitabine 40 Ifosfamide 100 Methotrexate 100 Paclitaxel 6 Pemetrexed 25 Vincristine 1
The plate was taken out and put into a Hettich Rotina 420R centrifuge for 5 mins at
2000 rpm. The supernatant of each well was removed using a Thermo Scientific
Finnpipette multichannel pipette set at 0.275 mL, before 0.100 mL of dimethyl
sulfoxide (DMSO) was added and mixed into to all the wells. The plate was covered
in aluminium foil and put on a Ratek E0M5 orbital shaker for 15 mins at speed 3
before the optical density (OD) reading of the homogeneous mixture was obtained at
a wavelength of 570 nm from a Molecular Devices SpectraMAX 250
spectrophotometer.
49
The data outputted from the Molecular Devices SpectraMAX 250
spectrophotometer, which was exported into MS Excel 2007, had the labels “Wells”
in one column and “Values” in another. The former column contained the row and
column coordinates, on the BD 96-well flat bottom test plate, of the well that
matched the OD reading placed in the adjacent “Values” column. The OD readings
from the blank wells on the plate had already been subtracted from each of the OD
readings for each well and this result placed in the values column by the Softmax Pro
version 2.2.1 software supplied with the Molecular Devices SpectraMAX 250
spectrophotometer.
In order to compare the responses of cell lines against a chemotherapeutic drug, to
address the hypothesis that heterogeneity will exist and cell lines will segregate into
clear groups of good and poor responders, the commonly used IC50 measure for
comparing a drug’s inhibitory effectiveness was selected. It represented the
concentration of drug that provoked a cell line response which was half way between
the minimum and maximum of the dose response modelled data in the MTT assays
conducted. The MTT assay itself was repeated for each cell line against each
chemotherapeutic drug to obtain 3 IC50 values. The mean obtained from these
triplicate IC50 values represented the response of each cell line against a
chemotherpeutic drug which was then used to compare against the responses of the
other cell lines towards treatment of the same chemotherpeutic drug. The IC50 for
each cell line against each chemotherapeutic drug was obtained through a number of
steps.
50
The OD reading data was first exported from the Molecular Devices SpectraMAX
250 spectrophotometer and imported into MS Excel 2007 whereby the mean value of
the drug control, at a specific concentration, was subtracted from each of the OD
reading of the triplicate test wells which were also at the corresponding
concentration on the same test plate. The drug concentrations were converted into
their log10 values and it was these newly modified triplicate OD readings that were
put into Graphpad that then enabled the production of graphs and execution of
statistical analysis on the formatted data.
In view of the fact that there was a different range of OD values from different
experiments, the OD values were fitted to a common scale so that they were brought
into proportion with one another so that comparisons of the IC50 data were made
possible between MTT experiments. As such, the Graphpad built-in “normalize”
analysis tool was first used on the OD readings that were entered into tables of the
software. The normalized values were obtained from the division of each OD
reading by the mean OD reading of the untreated cells and then multiplied by 100.
This calculation yielded the viability percentage of the cells in the triplicate wells. A
plot was made of the viability percentage for each triplicate well against the drug
tested at the corresponding concentration used to treat the cells in the triplicate wells.
The SD of the viability percentage at each point was shown and the concentration of
the drug was converted into its log10 concentration for ease of reading on the
graphical plot. The line of best fit for the dose-response data was modelled by the
"log (inhibitor) vs. response -- Variable slope (four parameters)" dose-response
curve that was built into Graphpad. It was important that the dose-response curve
clearly defined the bounds between 0% and 100% cell growth inhibition in the wells
51
so that the concentration that inhibited the growth of 50% of cells was determined
more accurately. Thus, in the plot, 0% was defined as the viability from a mean OD
reading of 0 and 100% was defined as the viability from a mean OD reading of the
triplicate wells with cells that were incubated without a chemotherapeutic drug
inhibiting their growth, that is, the negative controls on the test plate. The IC50
intersection was manually approximated from these graphical plots using the plots of
the dotted lines available in the software (Figure 2.1).
The highest concentration of drug used in the MTT assay was increased when the
response to the dose did not yield a viability percentage close to zero. However,
when the IC50 was within a 10-fold difference of the other IC50 values for a given
cell line against a given chemotherapeutic drug, it was deemed close enough and was
kept in the determination of the mean IC50 for the assay.
52
a)
b)
Figure 2.1. Cell viability plots in the determination of the IC50 in the MTT
assay. The MexTAg 299 166 cell line was treated with Bleomycin in two different
MTT assays. The IC50 obtained were within a tenfold difference of one another.
a) The drug dose was not enough to create a curve that goes down to zero. The
standard error bars were small at the IC50 cross-hair intersection. b) The dose was
increased so that the curve went down to zero. The standard error bars were a bit
bigger compared to those at the IC50 cross-hair intersection in experiment 11.
53
The the triplicate IC50 values for the a cell line treated with each chemotherapeutic
drug was determined and the values put into a summary table of IC50 values for
1 cell line. The mean and SDs were also worked out. A table was made for each of
the 14 mesothelioma cell lines. Then, these triplicate means were put into Graphpad
so that bar graphs were made that showed the mean and SDs of the triplicate IC50 for
each cell line against each chemotherapeutic drug. The IC50 means, SDs and number
of replicates for the wild-type and the MexTAg cell lines against each
chemotherapeutic drug was also summarized. Statistical analyses were then
performed to compare the responses of mesothelioma cell lines against each
chemotherapeutic drug so that the question of whether or not heterogeneity existed in
the response of cell lines to chemotherapy such that there were clear groups of good
and poor responders, was answered.
The question was broken down into 4 main different response comparisons from the
mean IC50 values for each chemotherapeutic drug by all 14 mesothelioma cell lines:
a) The IC50 comparisons of 7 wild-type mesothelioma cell lines against each of
the 12 chemotherapeutic drugs.
b) The IC50 comparisons of 7 MexTAg mesothelioma cell lines against each of
the 12 chemotherapeutic drugs.
c) The IC50 comparisons of the combined 7 wild-type against the combined
7 MexTAg cell line responses against each of the 12 chemotherapeutic drugs.
d) The IC50 comparisons of the combined 14 mesothelioma cell lines against
each of the 12 chemotherapeutic drugs.
54
2.4.0 ATP assay
In order to validate the data from the MTT assay, it was important that another
method to compare responses to chemotherapy was utilized. A paper written in the
Cancer Research Journal, suggested that the appearance of cell death was determined
by the levels of intracellular ATP (Eguchi, Shimizu & Tsujimoto 1997). ATP is the
most widely used molecule of free energy needed by cells to drive many chemical
reactions (Alberts et al. 2008). It was suggested that extracellular ATP had caused
cell death (Zheng et al. 1991). It was found that chemotherapy induced the reduction
of intracellular ATP and an increase in extracelluar ATP from tumour cells
(Martins et al. 2009). A luciferin-based ENLITEN ATP kit was also available for
testing from Promega (Martins et al. 2009). Additionally, an extracellular ATP level
increase was also found at tumour sites in vivo (Pellegatti et al. 2008).
Thus, the question initially asked was, what information about the proliferation and
viability of cells could the levels of ATP provide on the 14 mesothelioma cell lines
treated with chemotherapy? From the papers previously mentioned, it was
determined that we expected to see a certain level of ATP before chemotherapy
treatment and a different level of ATP after chemotherapy treatment. Intracellular
ATP was expected to decrease in number whilst extracellular ATP was expected to
increase in number after exposure to chemotherapeutic drugs. A reduction in
proliferation, ie. the number of cells, due to death would affect the viability output in
the MTT assay as there would be less cells to take up the MTT and form the
formazan crystals under the assumption that cells characteristically formed the
crystals at a given rate when put through controlled environmental conditions in the
55
lab. Hence, it was determined that we would first measure extracellular ATP for a
subset of cell lines and chemotherapeutic drugs.
The cell line suspensions were counted and plated out to a concentration of
5x103 cells/well for testing in a similar manner conducted in the MTT Assay. The
layout of cells on the plate was different but the type of plate used was the same.
This test plate was put into a humidified 37°C / 5% CO2 incubator for 24 hrs.
Chemotherapeutic drugs from SCGH Pharmacy were diluted to the IC50
concentrations as determined from the MTT Assay. Each well of cells were
inoculated with 0.1 mL of the relevant drug at the IC50 concentration for that cell
line. The controls for the drugs were also added to the plate and the plate put into a
humidified 37°C / 5% CO2 incubator for 48 hrs.
The luciferin-based PerkinElmer ATPLite kit, used in a research paper
(Martins et al. 2009), was first used to establish a luminescence reading with the
available PerkinElmer Victor2 V 1420 multilabel counter. The kit was used
according to manufacturer’s instructions excluding the machine used to do the
testing as the recommended luminometer was not available.
This combination of kit and hardware did not produce a strong signal. Help was
sought out from the hardware manufacturer, PerkinElmer, who immediately doubled
checked to see if the settings on the machine were correct for the luciferin-based
ATP assay, which they were. It turned out that the ENLITEN ATP kit from Promega
56
only provided a flash signal, a very quick signal that the recommended luminometer
would have picked up.
Hence, an alternative luciferin-based PerkinElmer ATPLite kit was recommended by
the PerkinElmer people. This was then tested according to manufacturer’s
instructions. A reading was established so the PerkinElmer ATPLite kit was selected
to conduct the rest of the ATP assays instead as the difference in ATP levels before
and after chemotherapy treatment was what mattered. The signal just had to be
strong enough to be read by the available machine.
The contents of the PerkinElmer ATPLite kit, which was selected for this assay,
were all equilibrated to room temperature: ATP free water, ATP standard, ATP cell
lysis solution and the ATP reagent (comprised of the substrate buffer and luciferase
substrate). After 48 hrs, the incubated plate was put into a Hettich Rotina 420R
centrifuge for 3 mins at 1300 rpm and 21°C. The plate was then left in the biohazard
hood for 15 mins with the other ATP Lite kit reagents.
In a Corning Incorporated Costar 3610 96-well white assay treated culture plate with
clear bottom, the ATPLite kit reagents and the supernatant of the cells were added to
the test. The plate was covered in aluminium foil and put on a Ratek E0M5 orbital
shaker for 5 mins at speed 3. It was then left to dark adapt for 2 mins in the
PerkinElmer Victor2 V 1420 multilabel counter before the luminescence was read
using the “No filter – Slot A7” emission filter and 1 second counting time
parameters under a CPS normal aperture operation of the Wallac 1420 Manager
software supplied with the machine. The data from the PerkinElmer Victor2 V 1420
57
multilabel counter was also formatted in MS Excel 2007 and copied into Graphpad
for the production of graphs and execution of statistical analysis.
2.5.0 Caspase assay
The question also arose: was the reduction in viability of the cells in the MTT assay
after treatment with chemotherapy due to death by apoptosis or necrosis? It has been
suggested that drugs have been aimed at inducing apoptosis such as Bleomycin
(Chen & Stubbe 2005), Gemcitabine (Mini et al. 2006), Doxorubicin (Thorn 2011)
and Epirubicin (Khasraw, Bell & Dang 2012). However, death by apoptosis and
necrosis may occur at the same time, such as in the case of Cisplatin
(Fuertes et al. 2003). A major component leading to apoptosis has been the members
of the caspase family ranging from initiators, such as caspase 8, to effectors, such as
caspase 3, of the caspase dependent pathway to cell death (Philchenkov 2004). The
cleavage of caspase 3 and caspase 8 but not caspase 9 in the apoptotic pathway was
observed in a study whereby Cisplatin and Pemetrexed were used in combination to
treat MM (Li et al. 2012). The caspase assay was to be used to conduct an
investigation into the mode of cell death for the single chemotherapeutic treatments
with the endpoint effector caspase 3 as the target of investigation.
The cell line suspensions were counted and plated out to a concentration of
5x103 cells/well for testing in a similar manner conducted in the MTT Assay. There
was a difference in the layout of the plate and the type of plate used. The Corning
Incorporated Costar 3610 96-well white assay treated culture plate with clear bottom
test plate was put into a humidified 37°C / 5% CO2 incubator for 24 hrs.
58
After 24 hrs, each well of cells was inoculated with 0.1 mL of chemotherapeutic
drugs from SCGH Pharmacy diluted to the IC50 concentrations as determined in the
MTT Assay for each a cell line were. The controls were completed on the plate and
the plate put into a humidified 37°C / 5% CO2 incubator for 48 hrs.
The contents of the Promega Caspase Glo 3/7 kit used for this assay were all
equilibrated to room temperature. After 48 hrs, the incubated plate was left in the
biohazard hood for 15 mins before 0.025 mL of caspase reagent was added to all the
wells. The plate with its lid was covered in aluminium foil and put on the Ratek
E0M5 orbital shaker for 30 seconds at speed 2.5. The plate was incubated at room
temperature for 1 hour before the PerkinElmer Victor2 V 1420 multilabel counter
was used to read the luminescence. The “No filter – Slot A7” emission filter and
1 second counting time parameters under a CPS normal aperature operation of the
Wallac 1420 Manager software supplied with the machine were used once again.
The data was also formatted in MS Excel 2007 and copied into Graphpad for the
production of graphs and execution of statistical analysis.
2.6.0 DNA extraction
One or two BD T75 flask of cells was cultured. The cell culture passage process was
followed until step number ‘4’ whereby the pellet of cells was resuspended in 10 mL
of PBS and put into a BD 15 mL falcon tube. This was then put into an Eppendorf
5702 centrifuge for 5 mins at 1200 rpm, the supernatant removed by suction, the
pellet of cells resuspended again in 10 mL of PBS, put into an Eppendorf 5702
59
centrifuge for 5 mins at 1200 rpm and frozen down as a pellet in -80°C until DNA
extraction could be performed. The Qiagen DNeasy Blood & Tissue kit was used for
DNA extraction of the frozen down pellet of cells, according to the manufacturer’s
instructions.
The eluted DNA was quantified using Thermo Scientific’s NanoDrop 2000
spectrophotometer. The nucleic acid group class was selected in the NanoDrop 2000
software. The pins of the NanoDrop 2000 were wiped clean with 70% ethanol and
permitted to dry. A blank was made with the elution Buffer AE, the pins cleaned
again and 0.001 mL of DNA sample was measured. A report was produced through
the NanoDrop 2000 software.
60
Chapter Three:
The growth rate
of cell lines in vitro
61
3.0.0 Proliferation rates of mesothelioma cell lines
Tumour growth and response to chemotherapy is highly variable
(Szulkin et al. 2013). To begin to understand why this was the case we first
investigated the range of growth rates of our bank of 7 wild-type and 7 MexTAg cell
lines under an inverted microscope in their culture flasks. It was noted that they took
on different shapes as they grew attached to the surface of the flask and once they
had reached maturity, a stage where they had finished dividing. For example, the
wild-type AE 17 (Figure 3.1a) cell line was small and triangular-like and the
wild-type BM 163 (Figure 3.1b) was wider and more crescent-moon-like in shape. It
was evident that coverage of the flask surface occurred at different rates. A similar
inequality in confluence percentage was observed for all 14 mesothelioma cell lines.
A quantitative measure of the proliferation of these cell lines was necessary.
a) b)
Figure 3.1. The wild-type AE 17 and BM 163 cell line grown in culture. Viewed
under a Nikon TMS inverted phase contrast microscope at 10x ocular and
10x objective magnification. This cell line was originally phenotyped as
sarcomatoid. a) The wild-type AE 17 cell line. b) The wild-type BM 163 cell line.
62
The Cellavista system was used to accurately quantify the growth rate of the cell
lines with different plating densities used to test the accuracy of the proliferation
assay. The growth rate was expected to have the same value once the cell line was in
its exponential phase of growth. For example, the equation of the line of best fit for
the wild-type AE 17 cell line was determined by linear regression analysis and the
doubling times interpolated. For triplicate well 1, the time spans were approximately
20.6 hrs (40% confluence) and 44.5 hrs (80% confluence) after the initial reading of
the plate. This yielded a doubling time of about 23.9 hrs. The doubling times for the
other wells were determined in a similar manner. The mean doubling time was
calculated, 24.4 hrs and put into a summary table so that repeats of the mean
doubling times were obtained for each cell line (Table 3.1). As some cell lines did
not reach exponential phase, or had reached a plateau before enough points could be
taken to draw up the line of best fit, these plots were not included. Other conditions
for inclusions have been listed in Table 3.1.
Figure 3.2. The proliferation time determined at 40% and 80% confluence for
the wild-type AE 17 cell line at a plating density of 5.00x103 cells/well. Points
interpolated from these linear models were used for determining cell growth rates.
63
Table 3.1. Inclusions and exclusions in the determination of doubling times. The
mean and standard deviations of the doubling times have been calculated for each
cell line. The plots that were included in this calculation had to meet certain
criteria listed in the table. The 4 initial concentrations were 5.00x103 cells/well,
2.50x103 cells/well, 1.25 x103 cells/well and 1.00 x103 cells/well. The proliferation
assay was conducted over a period of 1 week and repeated at least twice for each cell
line.
5.00x10^3 2.50x10^3 1.25x10^3 1.00x10^3 5.00x10^3 2.50x10^3 1.25x10^3 1.00x10^3 5.00x10^3 2.50x10^3 1.25x10^3 1.00x10^3
DT1 DT2 DT3 DT4 DT5 DT6 DT7 DT8 DT9 DT10 DT11 DT12
299 166 27.5 - 30.2 - 29.3 28.4 - - - - - - 28.9 1.2
299 170 34.9 33.6 - - - - - - 28.9 - - - 32.5 3.2
299 175 37.9 37.3 - - 31.3 36.2 - - - - - - 35.7 3.0
299 208 22.1 22.3 25.6 28.5 - 23.4 - 24.6 - - - - 24.4 2.4
299 210 - - 28.1 26.0 - - - - 30.8 - - - 28.3 2.4
299 376 33.8 35.7 - - 31.1 31.7 - - 35.7 - - - 33.6 2.2
299 62 32.4 32.0 - - - 27.9 - - - - - - 30.8 2.5
AE 3 - 30.9 30.5 - - 27.2 - - - - - - 29.5 2.0
AE 16 - 34.5 - - 28.0 31.1 - - - - - - 31.2 3.3
AE 17 24.4 24.9 25.1 26.0 32.2 26.9 - 32.1 - - - - 27.4 3.4
AE 19 - - - 22.6 22.7 21.9 23.2 22.1 - - - - 22.5 0.5
BM 109 - - - 29.6 23.4 - - - 26.7 - - - 26.6 3.1
BM 163 - 27.0 27.3 - 23.4 23.0 - - - - - - 25.2 2.3
BM 164 27.4 28.1 - - 29.3 28.1 - - - - - - 28.2 0.8
* Criteria for inclusions: The line plotted was included in the calculation of the mean doubing time when the conditionthat the line of best fit had three time points or more was met, that the line through the points had an R-squared valuegreater than 0.9, that the triplicate cell confluence readings had small standard deviation error bars and that the line wasdrawn through the established exponential phase of growth for the cell line. The line plotted was excluded in thecalculation of the doubling time when these conditions were not met. The lines that were included in the calculationswere used to then interpolate values for 40% and 80% confluence in working out the doubling time of the cell line.** This experimental week has two replicates on the same plate in which the replicate with the smallest error bars isselected for consideration. Additionally, not all the cell lines were tested in week 3.
Cell line Wk 1 Wk 2 Wk 3 ** Mean doubling
time (hrs) *
SD doubling
time (hrs)
Doubling Times (hrs) Doubling Times (hrs) Doubling Times (hrs)
Starting conc. (cells/well) Starting conc. (cells/well) Starting conc. (cells/well)
64
3.1.0 Proliferation comparisons
Out of the 14 mesothelioma cell lines, the shortest doubling time was 22.5 hrs for
wild-type AE 19 and the longest doubling time was 35.7 hrs for MexTAg 299 175.
Thus the wild-type AE 19 cell line was approximately 1.67 times faster in
proliferating than the MexTAg 299 175 cell line. The doubling time of the wild-type
AE 19 had a SD of 0.5 whilst the MexTAg 299 175 had a SD of 3.0.
Comparison of proliferation amongst 7 wild-type mesothelioma cell lines showed
significantly diverse median doubling times (p-value = 0.0069). The shortest
doubling time was approximately 22.5 hrs for wild-type AE 19 and the longest
doubling time was approximately 31.2 hrs for wild-type AE 16. Thus it took
approximately 1.4 times longer for the wild-type AE 16 cell line to double in number
when compared to the wild-type AE 19 cell line. In comparing each wild-type cell
line against each one of the other wild-type cell lines, to determine which pairs had
significantly different doubling times, only 1 out of 21 comparisons yielded a
statistical difference which was between the slowest and fastest growing lines:
wild-type AE 16 and wild-type AE 19 (p-value = 0.0117). Similar statistical analysis
was made for comparisons of proliferation amongst MexTAg mesothelioma cell
lines, wild-type against MexTAg cell lines and amongst all 14 cell lines.
3.2.0 A summary of the proliferation assay results
There was statistically significant diversity in proliferation between the cell lines
investigated when comparisons were made of the doubling times amongst
65
7 wild-type cell lines (p-value = 0.0069), amongst 7 MexTAg cell lines
(p-value = 0.0021), between 7 wild-type and 7 MexTAg cell lines (p-value = 0.0027)
and amongst all 14 mesothelioma cell lines (p-value <0.0001). Statistical differences
were also found between pairs of cell lines within the main comparisons (Table 3.2).
It could be seen that there were some deviation from concordance with the doubling
times for these and other cell lines which would affect the accuracy of the doubling
times for comparisons. This was probably due to plating several different cell lines
on 1 plate. The Cellavista takes images of adherent cells on the bottom of the plate
which depends on how well they were focused at the beginning of the first reading.
If cells had not fully adhered to the surface of the plate when doing the initial
focusing then it would have had difficulty reading the confluence of cells in the
bottom of the well when they had finally fully adhered. Additionally, a range of
wells were focused in the first week of this experiment so that cells were not left out
for too long outside the incubator. Taking them in and out could have caused the step
wise growth in some of the plots. A line of best fit was still made to get an
approximate doubling time.
Nonetheless, there were still two wild-type cell lines that had SDs of 0.5 hrs and
0.8 hrs with a statistically significant difference between their means. This may
change as more repeats of the experiment are made but because different passages
were used for the repeats and the repeat still showed relatively small SD between
them for the 2 wild-types AE 19 and BM 164, this proliferation assay may still yield
a result that heterogeneity exists in their growth.
66
Table 3.2. The diversity in proliferation rates of 14 mesothelioma cell lines. A
summary table of the main comparisons performed on the proliferation assay data
along with the pair-wise comparisons within the 4 main proliferation comparisons.
Figure 3.3. The proliferation rates of wild-type and MexTAg mesothelioma cell
lines are heterogeneic. There was heterogeneity in growth and 4 out of 91 pair-wise
comparisons yielded a statistically significant difference in proliferation rates.
Proliferation Comparisons P-value
Amongst wild-types 0.0069wild- type AE 16 vs. wild-type AE 19 0.0117
Amongst MexTAgs 0.0021MexTAg 299 175 vs. MexTAg 299 208 0.0031MexTAg 299 376 vs. MexTAg 299 208 0.0173
Wild-types against MexTAgs 0.0027
Amongst all cell lines < 0.0001MexTAg 299 175 vs. MexTAg 299 208 0.0184MexTAg 299 175 vs. wild-type AE 19 0.0014MexTAg 299 208 vs. MexTAg 299 376 0.0366MexTAg 299 376 vs. wild-type AE 19 0.0026
67
Chapter Four:
The growth rate of
cell lines in vivo
68
4.0.0 Establishing cell growth in vivo
Out of the 14 mesothelioma lines, only 10 had established growth in vivo. These
10 cell lines were comprised of 3 wild-type cell lines and 7 MexTAg cell lines. The
time it took for the tumours to double in size, length x width of subcutaneous
growth, was determined by a similar manner in Graphpad as in the proliferation
assay. For example, the MexTAg 299 166 cell line was subcutaneously injected into
3 MexTAg mice and the growth in tumour size plotted (Figure 4.1).
Figure 4.1. In vivo growth of MexTAg 299 166. The subcutaneous growth of the
cell line in 3 MexTAg mice plotted and modelled with the exponential growth
equation. The doubling times were determined from tumour sizes 40 mm2 and
80 mm2 using Graphpad’s built-in function for determining doubling time.
69
The automatic option for determining the doubling time was was selected in Graphad
as the workings of the function had already been derived in the proliferation assay,
and was deemed to be accurate. The determination of the doubling time was
performed in a similar manner for the other 9 cell lines. The model for the lines of
best fit changed depending on which model gave the better R-squared value in the
goodness of fit test, which was also available as a function in Graphpad (Figure 4.2).
The MexTAg 299 170 was calculated manually at 20 mm2 and 40 mm2 in size
because all 3 of the growing tumours for this cell line did not reach a size of 80 mm2.
Additionally, there was no quick feature in Graphpad to automatically work out
doubling times from a linear model of the MexTAg 299 170. The maths for doubling
time determination was still correct, but just like the cell lines in vitro, the cells may
have only just started to establish progression and so their exponential rate of growth
was not yet fully established, hence this cell line was excluded from the
comparisons. By this same reasoning, the wild-type AE 19 cell line also did not
reach the 40 mm2 and 80 mm2 mark and was therefore excluded.
The wild-type BM 109 was excluded from the comparisons when it was determined
that a mean doubling time could not be obtained because 1 of the 3 mice did not
have enough points for the exponential curve to model. Similarly, the MexTAg
299 376, MexTAg 299 210, MexTAg 299 175 and MexTAg 299 170 were excluded
from comparisons because 1 of the 3 mice did not have a tumor that reached the
80 mm2 mark. However the 2 that did grow had similar growth curves for each of the
5 cell lines mentioned (Figure 4.3). Another unknown confounding factor was most
70
likely present in the third mouse that such that the tumours were seen to not grow at
the same rate.
Figure 4.2. The exponential and linear growths. Out of the 10 mesothelioma cell
lines that grew in vivo, the MexTAg 299 208 was the fastest growing exponentially
whilst the MexTAg 299 62 had a very linear growth pattern.
71
Figure 4.3. The excluded growth curves from analysis. Out of the 10
mesothelioma cell lines that grew in vivo, these 6 were excluded from analysis due
to outliers in the replicates or not reaching a size of 80 mm2.
72
4.1.0 Fast growing wild-types
Out of the 10 cell lines that grew in vivo, the fastest growing cell line was wild-type
BM 164 and the slowest growing cell line was MexTAg 299 62 (Table 4.1). Out of
the 3 wild-type cell lines that grew in mice, the wild-type BM 164 cell line was the
only one that was deemed okay to make doubling time comparisons with. Hence, no
comparisons in the doubling times could be performed between wild-type cell lines.
Following this, there were not enough data points to make the consistent comparison
of triplicate mean doubling times between MexTAg and wild-type cell lines.
Table 4.1. The fastest and slowest growing cell lines in vitro and in vivo. A rank
comparison of the mean doubling times for 10 cell lines. In the in vivo calculations
of the mean doubling time, the means for 2 mice were calculated in a few.
Mean SDwild-type AE 19 22.5 0.5MexTAg 299 208 24.4 2.4wild-type BM 109 26.6 3.1wild-type BM 164 28.2 0.8MexTAg 299 210 28.3 2.4MexTAg 299 166 28.9 1.2MexTAg 299 62 30.8 2.5MexTAg 299 170 32.5 3.2MexTAg 299 376 33.6 2.2MexTAg 299 175 35.7 3.0
Mean SDwild-type BM 164 3.6 0.4MexTAg 299 208 7.2 0.3MexTAg 299 210 8.5 0.9wild-type BM 109 14.2 0.9wild-type AE 19 15.1 3.7MexTAg 299 175 18.6 1.9MexTAg 299 166 20.5 3.7MexTAg 299 376 29.3 10.6MexTAg 299 170 30.7 6.0MexTAg 299 62 31.2 1.9
In Vitro Doubling Times (hrs)
Cell LineIn Vivo Doubling Times (days)
Cell Line
73
Out of the 6 MexTAg cell lines that grew in mice, only 3 were determined to be
appropriate for making comparisons between MexTAgs. There was significantly
diverse median times to reach a tumour size of 80 mm2 between the 3 MexTAg cell
lines (p-value = 0.0036). The shortest doubling time was approximately 7.20 days
(168 hrs) for wild-type BM 164 and the longest doubling time was approximately
31.2 days (749 hrs) for MexTAg 299 62. Thus it took approximately 4 times longer
for the MexTAg 299 62 cell line to grow in vivo and reach a size of 80 mm2 when
compared to the MexTAg 299 208 cell line. In pair-wise comparisons of MexTAg
cell lines to determine which pairs had significantly different doubling times, only
1 out of 3 comparisons yielded a statistical difference which was between the
slowest and fastest growing lines: MexTAg 200 208 and MexTAg 299 62
(p-value = 0.0219). No significant diversity in growth was found between the 4 cell
lines investigated when comparisons were made of the growth amongst 1 wild-type
and 3 MexTAg cell lines (p-value = 0.1145).
4.2.0 A summary of the in vivo cell growth results
There was no consistent comparison of triplicate mean doubling times possible for in
vivo growth between wild-type cell lines or between MexTAgs and wild-types due
to insufficient data points. However, the comparison between MexTAg cell lines
revealed that there was a difference between 3 of the cell lines with the biggest
difference in growth rate between MexTAg 299 208 and MexTAg 299 62
(p-value = 0.0219). Although this is not extremely statistically significant, it is
surprising because the MexTAgs were meant to be more similar because they all had
74
SV40 T-antigen and they were all injected with cell lines on the same day. The
experiment will need to be repeated with the same lines and then other cell lines for
making comparisons to confirm this finding.
Additionally, there was no statistically significant difference in growth amongst
wild-type BM 164, MexTAg 299 166, MexTAg 299 208 and MexTAg 299 62 to
indicate that there was no heterogeneity in the growth of mesothelioma cell lines in
vivo. However, from the graphs, the cell lines were clearly growing at different rates.
The disparity between the maths and the observations could be because of variability
amongst mice, a confounding factor in the experiment.
The wild-type BM 164 cell line was faster growing in vivo than 2 out of 3 MexTAg
cell lines: MexTAg 299 166 and MexTAg 299 62. The SD of the means was
approximately 0.4 days (9.6 hrs), 3.7 days (88.8 hrs) and 1.9 days
(45.6 hrs) respectively. Additionally, the wild-types were generally faster growing in
vivo and in vitro when compared to MexTAgs (Table 4.1). Overall, the doubling
times were longer in vivo compared to in vitro which was to be expected as there
were only a few factors hindering cell growth in vitro compared to in vivo.
75
Chapter Five:
The heterogeneic response
of mesothelioma cell lines
to chemotherapy
76
5.0.0 Assessment of the cell line response to chemotherapy
The response of a cell line to chemotherapy is typically assessed by measurement of
the IC50 value: that is the concentration at which 50% of cell growth is inhibited. In
these first experiments to test the hypothesis that “heterogeneity will exist and cell
lines will segregate into clear groups of good and poor responders”, the MTT assay
was used. The ability of the MTT assay to represent proliferation is tested and
discussed later in the thesis.
To enable comparisons to be made between cell lines, optimisation of the techniques
and data analysis was required. The MexTAg cell line 299 208 treated with the
chemotherapeutic drug Gemcitabine was used to work through the process and
analysis of the results from 3 separate experiments performed in triplicate have been
described here. These steps were eventually applied to the experimental repeats of
each cell line treated against each chemotherapeutic drug.
In experimental repeat number 1, the MexTAg 299 208 cell line was treated with
Gemcitabine at 10-fold serial concentrations from 1,000 ng/mL down to 0.01 ng/mL
and proliferation measured 48 hrs later by MTT assay. However, these
concentrations were converted into their log10 concentration from 3 ng/mL down to
-3 ng/mL respectively for ease of reference when they were put into Graphpad. In
experimental repeat 2 and 3, the maximum concentration of Gemcitabine was
increased to 10,000 ng/mL with 10-fold serial concentrations down to 0.01 ng/mL
used in both experiments and their log10 concentration was converted accordingly.
77
Normalisation of raw data
The OD readings, raw data minus the blank control, obtained from the MTT assay
for each triplicate well of the test plate was normalized across each MTT experiment
so that a trend between the MexTAg 299 208 cell line against Gemcitabine, or lack
thereof, was identified. The mean OD reading of the MexTAg 299 208 untreated
cells for experiment number 1, 2 and 3 were all mid range ( 0.615, 0.502 and 0.577
respectively) and had similar accuracy (SDs were 0.020, 0.043, and 0.034
respectively). There were some negative values in the OD readings at the higher end
of Gemcitabine concentration when all values were expected to have been zero or
above (Table 5.1, 5.2 and 5.3). This was most likely due to inaccuracy in pipetting
because the majority of values at these concentrations were generally positive and
the negative values were practically zero.
The normalization function in Graphpad was used such that the viability of the
untreated cells was taken to be 100%. Each OD reading in the test wells was divided
by the mean OD reading of the control wells, the untreated cells, and then that value
was multiplied by 100. The medians between normalized OD values of the
3 experiments were not statistically significantly different (p-value = 0.7396).
Determining the IC50
The viability percentage for the cell line was obtained by taking the mean of the
3 normalized OD readings for each concentration of Gemcitabine tested and plotted
against the relevant concentrations of Gemcitabine. The line of best fit for the
78
dose-response data was inserted. The IC50 intersection was manually approximated
for all 3 experimental repeats (Figure 5.1).
Table 5.1. The triplicate well OD readings for experimental repeat number 1 of
the MexTAg 299 208 treated with Gemcitabine. a) The 3 OD readings for each
Gemcitabine concentration used in the MTT assay that were put into Graphpad.
b) The normalized OD values, each representing the cell percentage viability for
each well of the MexTAg 299 208 treated with Gemcitabine.
a)
b)
79
Table 5.2. The triplicate well OD readings for experimental repeat number 2 of
the MexTAg 299 208 treated with Gemcitabine. a) The 3 OD readings for each
Gemcitabine concentration used in the MTT assay that were put into Graphpad.
b) The normalized OD values, each representing the cell percentage viability for
each well of the MexTAg 299 208 treated with Gemcitabine.
a)
b)
80
Table 5.3. The triplicate well OD readings for experimental repeat number 3 of
the MexTAg 299 208 treated with Gemcitabine. a) The 3 OD readings for each
Gemcitabine concentration used in the MTT assay that were put into Graphpad.
b) The normalized OD values, each representing the cell percentage viability for
each well of the MexTAg 299 208 treated with Gemcitabine.
a)
b)
81
Figure 5.1. Triplicate IC50 values determined from plots of MexTAg 299 208
treated with Gemcitabine. The sigmoidal dose-response model was used for line of
best fit through the experimental points. The blue dotted cross-hairs marked the
intersection where the cell line was at 50% viability when treated with approximately
7 ng/mL of Gemcitabine. This model was affected by the accuracy of the points such
that a slight difference in the shape of the curve was shown. The top left hand plot
represents experimental repeat 1. The top right hand plot represents experimental
repeat 2. The bottom plot represents experimental repeat 3. Three different passages
of the MexTAg 299 208 cell line were used in the experiments on 3 different days
yet IC50s with very small SDs were obtained from the MTT assay.
82
Gemcitabine inhibited growth of MexTAg 299 208 with a range of IC50 values:
8.7 ng/mL, 3.5 ng/mL and 7.6 ng/mL for experimental repeats 1, 2 and 3
respectively. The mean of the 3 was 6.6 ng/mL with a SD of 2.8 ng/mL. Overall
they were the same order of magnitude. Proliferation of the cells in the wells was
seen to be hindered with chemotherapeutic treatment at various high concentrations
of chemotherapeutic drugs. Hence, cell proliferation was directly proportional to the
concentration of chemotherapeutic drug it was treated with. The negative values
noted previously did not have a great impact on the shape of the curve but the values
would have affected the curve more had they been more negative and positioned at
the IC50, at the 50% viability mark on the plot.
The IC50 values for the MexTAg 299 208 cell line treated with the other
chemotherapeutic drugs were determined in the same manner (Table 5.4). There
were a few points noted about the replicates for the MexTAg 299 208 cell line. The
SDs were quite large in some of the replicate IC50 values particularly against
chemotherapeutic drugs that yielded IC50 values at the higher end of the log10
concentration spectrum. Adjustments were made to cover the optimal concentrations
such that IC50 would fall midrange where possible. However, this was not possible
for every drug.
The IC50 values of chemotherapeutic drugs grouped into their mechanisms of action
yielded higher IC50 values for alkylating agents compared to anti-metabolites.
Cisplatin yielded an IC50 which was about 300 times less than the other two
alkylating agents. Hepatic microsomal enzymes were not included in the test for
Cyclophosphamide and Ifosfamide yet these prodrugs, drugs that required aid to be
83
converted into their active form (Wu 2009; Fleming 1997), yielded an IC50 of
534,000 ng/mL and 261,000 ng/mL respectively. The smallest IC50 value was from
Gemcitabine, 6.59 ng/mL, and the largest was from Cyclophosphamide,
534,000 ng/mL. Thus, for Gemcitabine, a concentration of about 81,000 times less
than Cyclophosphamide was needed to illicit a cell line response that inhibited 50%
of cell growth.
A similar table of IC50 replicates was completed for the other 13 mesothelioma cell
lines and put into Graphpad for statistical analysis. The IC50 mean and SDs for the
wild-type and the MexTAg cell lines against each chemotherapeutic drug along with
the number of repeats were summarized in Table 5.5 and Table 5.6 respectively.
Table 5.4. The IC50 replicates for the MexTAg 299 208 cell line. The replicate
values determined from dose-response curves and rounded to 3 significant figures.
Chemotherapy
1480 1450Mean IC50 = 1460 SD IC50 = 17.3
617 562Mean IC50 = 603 SD IC50 = 36.5
537000 562000Mean IC50 = 534000 SD IC50 = 30700
63.1 95.5Mean IC50 = 70.4 SD IC50 = 22.4
24.5 17.8Mean IC50 = 21.9 SD IC50 = 3.59
12600 9770Mean IC50 = 11400 SD IC50 = 1450
8.71 7.59Mean IC50 = 6.59 SD IC50 = 2.76
257000 302000Mean IC50 = 261000 SD IC50 = 39200
55.0 14.1Mean IC50 = 30.8 SD IC50 = 21.4
776 513Mean IC50 = 601 SD IC50 = 152
89.1 67.6Mean IC50 = 82.0 SD IC50 = 12.4
17.4 33.8Mean IC50 = 18.9 SD IC50 = 14.2
Vincristine5.62
Paclitaxel513
Pemetrexed89.1
Ifosfamide224000
Methotrexate23.4
Etoposide Phosphate11700
Gemcitabine3.47
Doxorubicin52.5
Epirubicin23.4
Bleomycin1450
Cisplatin631
Cyclophosphamide501000
The MexTAg 299 208 cell line IC50 replicates with sample mean and standard deviation (ng/mL)
84
Table 5.5. The IC50 summary table for all the wild-type cell lines. The mean, SD
and number of replicates for each wild-type cell line is shown.
Table 5.6. The IC50 summary table for all the MexTAg cell lines. The mean, SD
and number of replicates for each MexTAg cell line is shown.
AE 3 AE 16 AE 17 AE 19 BM 109 BM 163 BM 164(Wild-Type) (Wild-Type) (Wild-Type) (Wild-Type) (Wild-Type) (Wild-Type) (Wild-Type)
3,590 2,080 311 2,040 738 394 9,850SD= 4270 ; RPT= 3 SD= 384; RPT= 3 SD= 89.3; RPT=3 SD= 850; RPT= 3 SD= 131; RPT= 3 SD= 118; RPT=3 SD= 348; RPT=3
6,470 1,100 639 2,740 693 736 1,160SD= 2870; RPT= 3 SD= 386; RPT= 3 SD= 81.4; RPT=3 SD= 1640; RPT= 3 SD= 115; RPT= 3 SD= 19.7; RPT=3 SD= 218; RPT=3
2,010,000 2,880,000 674,000 2,330,000 750,000 955,000 2,170,000SD= 435000; RPT= 3 SD= 885000; RPT= 3 SD= 199000; RPT=3 SD= 793000; RPT= 3 SD= 241000; RPT= 3 SD= 311000; RPT=2 SD= 919000; RPT=3
369 309 181 63.9 118 160 1,310SD= 199; RPT= 3 SD= 147; RPT= 3 SD= 20.9; RPT=3 SD= 21.8; RPT= 3 SD= 41.7; RPT= 3 SD= 61.0; RPT=3 SD= 410; RPT=3
175 133 69.6 43.4 69.5 91.6 680SD= 67.3; RPT= 3 SD= 50.0; RPT= 3 SD= 20.1; RPT=3 SD= 7.88; RPT= 3 SD= 38.5; RPT= 3 SD= 11.3; RPT=3 SD= 217; RPT=3
59,500 87,500 14,100 35,300 27,400 10,300 53,800SD= 25700; RPT= 3 SD= 21800; RPT= 3 SD= 5140; RPT=3 SD= 8040; RPT= 3 SD= 4990; RPT= 3 SD= 2320; RPT=3 SD= 12200; RPT=3
15.0 3.45 7.09 10.6 7.94 3.95 7.13SD= 4.25; RPT= 3 SD= 0.812; RPT= 3 SD= 1.50; RPT=3 SD= 1.09; RPT= 3 SD= 0.0; RPT= 3 SD= 0.54; RPT=3 SD= 1.73; RPT=3
748,000 719,000 636,000 631,000 194,000 365,000 739,000SD= 43600; RPT= 3 SD= 107000; RPT= 3 SD= 141000; RPT=3 SD= 0.0; RPT= 3 SD= 33000; RPT= 3 SD= 297000; RPT=3 SD= 140000;RPT=3
46,100 2,990 11.0 9,020 408 45.6 130SD= 32600; RPT= 3 SD= 2870; RPT= 3 SD= 1.36; RPT=3 SD= 8320; RPT= 3 SD= 350; RPT= 3 SD= 36.1; RPT=3 SD= 42.7; RPT=3
1,550 316 46.1 197 37.6 491 1,860SD= 741; RPT= 3 SD= 89.6; RPT= 3 SD= 25.3; RPT=3 SD= 44.3; RPT= 3 SD= 8.47; RPT= 3 SD= 160; RPT=3 SD= 237; RPT=3
3,520,000 7,090,000 20.9 269,000 7,730 7,650.0 61,400SD= 2260000; RPT= 3 SD= 3200000; RPT= 3 SD= 8.08; RPT=3 SD= 101000; RPT= 3 SD= 5290; RPT= 3 SD= 2510; RPT=3 SD= 27300; RPT=3
6,670 5,900 7.80 57,900 40.1 7.61 512SD= 3540; RPT= 3 SD= 1060; RPT= 3 SD= 4.03; RPT=3 SD= 37300; RPT= 3 SD= 37.3; RPT= 3 SD= 2.25; RPT=3 SD= 250; RPT=3
Bleomycin
Cisplatin
Cyclophosphamide
Doxorubicin
Chem
othe
rapy
Ifosfamide
Methotrexate
Paclitaxel
Pemetrexed
Vincristine
Epirubicin
Etop. Phosphate
Gemcitabine
Cell line IC50 sample means and standard deviations (ng/mL) with the number of replicates.
299 166 299 170 299 175 299 208 299 210 299 376 299 62(MexTAg) (MexTAg) (MexTAg) (MexTAg) (MexTAg) (MexTAg) (MexTAg)
261 248 2,650 1,460 1,340 1,340 2,640SD= 144; RPT=3 SD= 100; RPT=3 SD= 1000; RPT=3 SD= 19.4; RPT=3 SD= 341; RPT=3 SD= 533; RPT=3 SD= 933; RPT=3
982 555 564 603 199 474 2,660SD= 113; RPT=3 SD= 47.2; RPT=3 SD= 45.9; RPT=3 SD= 36.2; RPT=3 SD= 18.0; RPT=3 SD= 97.8; RPT=3 SD= 1680; RPT=3
531,000 452,000 640,000 534,000 183,000 395,000 2,090,000SD= 376000; RPT=3 SD= 22100; RPT=2 SD= 242000; RPT=3 SD= 30700; RPT=3 SD= 27800; RPT=3 SD= 87800; RPT=3 SD= 470000; RPT=3
134 71.2 142 70.4 116 200 366SD= 9.73; RPT=3 SD= 20.0; RPT=3 SD= 62.4; RPT=3 SD= 22.4; RPT=3 SD= 4.09; RPT=3 SD= 149; RPT=3 SD= 91.1; RPT=3
67.4 18.3 45.7 21.9 60.1 84.3 153SD= 44.1; RPT=3 SD= 12.2; RPT=3 SD= 40.4; RPT=3 SD= 3.63; RPT=3 SD= 20.2; RPT=3 SD= 16.4; RPT=3 SD= 24.5; RPT=3
9,880 3,600 11,200 11,400 5,530 17,400 31,800SD= 1260; RPT=3 SD= 47.7; RPT=3 SD= 3000; RPT=3 SD= 140; RPT=3 SD= 818; RPT=3 SD= 1080; RPT=3 SD= 5890; RPT=3
9.78 8.58 4.51 6.59 5.07 4.24 11.0SD= 1.47; RPT=3 SD= 1.27; RPT=3 SD= 1.46; RPT=3 SD= 2.76; RPT=3 SD= 2.42; RPT=3 SD= 2.05; RPT=3 SD= 1.27; RPT=3
568,000 254,000 239,000 261,000 247,000 324,000 323,000SD= 39500; RPT=3 SD= 238000; RPT=3 SD= 41300; RPT=3 SD= 39200; RPT=3 SD= 30500; RPT=3 SD= 27000; RPT=3 SD= 63500; RPT=3
59,800 43.4 37.0 30.8 14.3 19.7 261,000SD= 34100; RPT= 3 SD= 30.6; RPT=3 SD= 43.4; RPT=3 SD= 21.4; RPT=3 SD= 4.50; RPT=3 SD= 15.9; RPT=3 SD= 88900; RPT=3
372 540 878 601 866 357 3,470SD= 194; RPT=3 SD= 315; RPT=3 SD= 859; RPT=3 SD= 152; RPT=3 SD= 377; RPT=3 SD= 126; RPT=3 SD= 2460; RPT=3
14.2 17.1 63.8 82.0 79.1 151.0 4,480,000SD= 1.63; RPT=3 SD= 7.52; RPT=3 SD= 35.7; RPT=3 SD= 12.4; RPT=3 SD= 14.0; RPT=3 SD= 55.1; RPT=3 SD= 2590000; RPT= 3
41.6 43.2 48,700 18.9 35.0 1,960.00 46,700SD= 14.8; RPT=3 SD= 10.1; RPT=3 SD= 24900; RPT=3 SD= 14.2; RPT=3 SD= 24.0; RPT=3 SD= 736; RPT= 3 SD= 20900; RPT=3
Ifosfamide
Methotrexate
Paclitaxel
Pemetrexed
Vincristine
Epirubicin
Etop. Phosphate
Gemcitabine
Chem
othe
rapy
Cell line IC50 sample means and standard deviations (ng/mL) with the number of replicates.
Bleomycin
Cisplatin
Cyclophosphamide
Doxorubicin
85
It was important to note a few things from Table 5.5, the wild-type BM 163 cell line
only had two completed IC50 replicates against the chemotherapeutic drug
Cyclophosphamide. The IC50 values for each of the chemotherapeutic drugs were
not identical. The large difference in SD at the higher IC50 values noted for the
MexTAg 299 208 cell line had remained for all the other wild-type cell lines with
high IC50 values. Cisplatin still yielded an IC50 value of approximately 300 times
less than the other 2 alkylating agents, Cyclophosphamide and Ifosfamide, for all the
7 wild-type cell lines. Hepatic microsomal enzymes were again not included in the
test for Cyclophosphamide and Ifosfamide, yet these still yielded an IC50 value. The
smallest IC50 values were from Gemcitabine across all 7 wild-type cell lines and the
largest IC50 value was from Cyclophosphamide in 5 out of 7 wild-type cell lines.
Thus, a majority of wild-type cell lines were more sensitive to Gemcitabine than
Cyclophosphamide. Similar notes were observed for Table 5.6.
5.1.0 The heterogeneity of response of mesothelioma cell
lines to chemotherapy treatment
The 7 wild-types were first compared between one another against their response to
Bleomycin and were found to have significantly different responses to the drug: the
median IC50 varied significantly (p-value = 0.0060). The smallest IC50 was
approximately 3.11x102 ng/mL for AE 17 and the largest IC50 was approximately
9.85x103 ng/mL for BM 164. Thus the wild-type AE 17 cell line was approximately
32 times more sensitive to Bleomycin than the wild-type BM 164 cell line.
Following a comparison of each wild-type cell line against each one of the other
86
wild-type cell lines to determine which pairs had significantly different IC50 values,
2 out of 21 comparisons yielded a statistical difference between the following cell
lines: wild-type AE 17 vs. wild-type BM 164 (p-value = 0.0167) and wild-type BM
163 vs. wild-type BM 164 (p-value = 0.0334). This line of reasoning was conducted
for the other chemotherapeutic drugs. There were significant differences in the
response by wild-type cell lines against 11 out of 12 chemotherapeutic drugs. In
these responses, 3 out of 11 were significant and 8 out of 11 were very significant
(Table 5.7). The response of MexTAgs were analysed, then wild-types against
MexTAgs and then the overall differences between the mesothelioma cell lines
against each of the 12 chemotherapeutic drugs.
Table 5.7. The level of difference in response to chemotherapy by the wild-type
cell lines. The level of significance in the difference of response to each
chemotherapeutic drug have been indicated in symbols and words according to their
p-values in levels derived from the Graphpad analysis software.
Level of statistical significance Chemotherapeutic
Drug P-value In Symbol In Words
Bleomycin 0.0060 ** Very significant Cisplatin 0.0140 * Significant Cyclophosphamide 0.0274 * Significant Doxorubicin 0.0096 ** Very significant Epirubicin 0.0113 * Significant Etoposide Phosphate 0.0052 ** Very significant Gemcitabine 0.0058 ** Very significant Ifosfamide 0.0899 ns Not significant Methotrexate 0.0054 ** Very significant Paclitaxel 0.0050 ** Very significant Pemetrexed 0.0041 ** Very significant Vincristine 0.0041 ** Very significant
87
5.2.0 A summary of the MTT assay
When the OD values of the control wells, cells with no drug, were compared to the
test wells, cells treated with a drug, proliferation was seen to be hindered by
chemotherapy at various high concentrations in the test wells. The 4 major IC50
comparisons of the MM cell lines against the 12 chemotherapeutic drugs indicated
that there was heterogeneity in the proliferation of cell lines after treatment.
In the IC50 comparisons of 7 wild-type mesothelioma cell lines against each of the
12 chemotherapeutic drugs: statistically significant differences in response to
chemotherapy treatment were observed for 12 out of 12 chemotherapeutic drug
comparisons. In these responses, 4 out of 12 were significant and 8 out of 12 were
very significant. Multiple comparisons yielded statistically significant differences in
responses to chemotherapy between pairs of cell lines in 9 out of
12 chemotherapeutic drugs tested.
In the IC50 comparisons of 7 MexTAg mesothelioma cell lines against each of the
12 chemotherapeutic drugs: statistically significant differences in response to
chemotherapy treatment were observed for 11 out of 12 chemotherapeutic drug
comparisons. In these responses, 1 out 12 was not significant, 6 out of 12 were
significant and 5 out of 12 were very significant. Multiple comparisons yielded
statistically significant differences in responses to chemotherapy between pairs of
cell lines in 6 out of 12 chemotherapeutic drugs tested.
88
In the IC50 comparisons of 7 wild-type against 7 MexTAg cell lines treated with
each of the 12 chemotherapeutic drugs: statistically significant differences in
response to chemotherapy treatment were observed for 6 out of 12 chemotherapeutic
drug comparisons. In these responses, 6 out 12 were not significant, 2 out of 12 were
very significant and 4 out of 12 were extremely significant. Multiple comparisons
yielded statistically significant differences in responses to chemotherapy between
pairs of cell lines in 6 out of 12 chemotherapeutic drugs tested. Amongst all the cell
lines compared against each chemotherapeutic drug,
In the IC50 comparisons of 7 wild-type combined with 7 MexTAg cell lines treated
against each of the 12 chemotherapeutic drugs: statistically significant differences in
response to chemotherapy treatment were observed for 12 out of
12 chemotherapeutic drug comparisons. In these responses, 6 out 12 were very
significant and 6 out of 12 were extremely significant. Multiple comparisons yielded
statistically significant differences in responses to chemotherapy between pairs of
cell lines in 11 out of 12 chemotherapeutic drugs tested. The largest statistical
difference in response was against Pemetrexed between wild-type AE 16 and
MexTAg 299 166 (7.90x106 ng/mL). Excluding Ifosfamide, which showed no
statistical difference between all 14 cell lines, the smallest statistical difference in
response was between wild-type AE 3 and wild-type AE16 against Gemcitabine
(1.16x101 ng/mL).
The MTT assay is limited in that there are so many places that variation can be
introduced: from the pipetting right through to the timing of when cells are taken out
of the incubator and any loss of volume in the media due to evaporation.
89
Chapter Six:
Investigating the death of cells in
response to chemotherapy
90
6.0.0 The release of ATP and caspase 3/7
When cells die, either by apoptosis or necrosis, ATP is released. It was found that
chemotherapy induced the reduction of intracellular ATP and an increase in
extracelluar ATP from tumour cells (Martins et al. 2009). When cells die by
apoptosis, caspase expression increases (Philchenkov 2004). Chemotherapeutic
drugs have been aimed at inducing apoptosis (Chen & Stubbe 2005;
Mini et al. 2006). The apoptosis pathway for cell death is preferred and the
relationship between ATP and caspase levels to give an idea of what chemotherapy
was doing to cell growth was important. The levels were expected to be different
between therapies but would it be different between cell lines for the same therapy?
We wished to find out. Additionally, the levels of ATP ought to mirror the MTT
assay as there was a link between viable and dying cells to ATP levels.
6.1.0 Establishing a reading for ATP luminescence
It was thought that more ATP in the supernatant of treated cells would correlate with
more cell death and hence less viability. The luciferin-based PerkinElmer ATPLite
kit, used in a research paper (Martins et al. 2009) was not compatible with the
PerkinElmer Victor2 V 1420 multilabel counter available in the lab. The
manufacturer of the PerkinElmer Victor2 V 1420 multilabel counter suggested an
alternative to the luciferin-based kit, the PerkinElmer ATPLite kit, because the
Promega ENLITEN ATP kit only emitted a flash signal, a very quick signal that the
recommended luminometer would detect that the PerkinElmer Victor2 V 1420
multilabel counter could not. Hence the luciferin-based PerkinElmer ATPLite kit
91
was ordered. The small number of cell lines that were available at the time included:
MexTAg 299 166, MexTAg 299 208, wild-type AE 17 and wild-type BM 164.
There were also 5 chemotherapeutic drugs that had different mechanisms of actions
available: Bleomycin, Cisplatin, Doxorubicin, Gemcitabine and Paclitaxel.
Undiluted supernatant from cells that had been incubated for 48 hrs with or without
chemotherapeutic drugs, was used in the test for extracellular ATP levels. As an
example, the plate layout for the MexTAg 299 166 cell line and the luminescence
results after 1 hr of incubation with the luciferase reagent in the kit, as per the
manufacturer’s instructions, has been shown in Figure 6.1.
Figure 6.1. The ATP assay plate layout of results. The luminescence readings
were put into their respective well from the template used in the ATP experiment.
1 2 3 4 5 6 7 8 9 10 11 12
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
rL/L + LB + ATPFW
+ ATP
1.0E-02 1.0E-03 1.0E-04 1.0E-05 1.0E-06 1.0E-07 1.0E-08 1.0E-09 1.0E-10 1.0E-11 1.0E-12 1.0E-13
B
C
D
E
F
G
H =
1 2 3 4 5 6 7 8 9 10 11 12
A 1449960 2681967 1180700 223273 22739 3176 604 233 148 115 92 75
B 11228 16609 9356 3888 1539 762 367 215 170 123 80 70
C 1917 2240 1987 1382 1019 655 341 232 173 120 104 80
D 936 1152 901 779 650 495 348 237 203 103 74 75
E 625 598 529 501 422 324 186 156 127 90 66 67
F 394 356 392 307 266 220 169 126 103 84 91 71
G 239 253 197 245 199 145 126 93 100 74 67 64
H 190 232 182 169 174 114 90 93 84 73 64 61
The ATP assay plating layout and luminescence readings for the MexTAg 299 166 cell line.
Total volume in each well at reading
is 200μL.
Well contents are abreviated as follows: ATP = Adenosine triphosphate, ATPFW = ATP Free Water, rL/L = reconstituted Luciferase/Luciferin reagent, M = Media, LB = Lysis Buffer, CS = Cell Supernatant, Bleo = Bleomycin, Cis = Cisplatin, Cyc = Cyclophosphamide, Dox = Doxorubicin, Epir = Epirubicin, EtoP = Etoposide Phosphate, Gem = Gemcitabine, Ifos = Ifosfamide, Meth = Methotrexate, Pac = Paclitaxel, Peme = Pemetrexed, Vinc = Vincristine.
=
Luminescence readings from the PerkinElmer Victor2 V 1420 multilabel counter using the built-in Wallac software. Readings are in counts per second (CPS) with readings for each well set at 1 second. The plate is Corning Incorporated's Costar 3610: 96-well assay plate, white, clear bottom with lid, tissue culture treated and made of polystyrene.
rL/L + LB + M + EtoP + CS
rL/L + LB + M + Bleo
Drug control and drug test wells in triplicate. =
Negative controls for rL/L and cells.
rL/L + LB + M + Cis
rL/L + LB + M + Cyc
rL/L + LB + M + Dox
rL/L + LB + M + Epir
rL/L + LB + M + EtoP
ATP Standard. Dilutions in ATPFW, 10 fold serial dilutions. Additionally, 50μL of rL/L and 50μL of LB are in each well. ATP Molar concentration is indicated. Missing a negative control well of zero ATP.
=
rL/L + LB + M + Gem + CS
rL/L + LB + M + Ifos + CS
rL/L + LB + M + Meth + CS
rL/L + LB + M + Gem
rL/L + LB + M + Ifos
rL/L + LB + M + Meth
rL/L + LB + M rL/L + LB + M + CS ATPFW + LB + M + CS ATPFW + LB + M
A
rL/L + LB + M + Pac + CS
rL/L + LB + M + Peme + CS
rL/L + LB + M + Vinc + CS
rL/L + LB + M + Pac
rL/L + LB + M + Peme
rL/L + LB + M + Vinc
rL/L + LB + M + Bleo + CS
rL/L + LB + M + Cis + CS
rL/L + LB + M + Cyc + CS
rL/L + LB + M + Dox + CS
rL/L + LB + M + Epir + CS
92
The readings were performed without mixing of the well contents. The RLU units
were defined as CPS 200 mL-1. Figure 6.2 shows an attempt was made to fit a model
to the curve. An exact fit was yet to be found but the Weibull model, in the red line,
was the best so far. The luminescent readings were also plotted (Figure 6.3). The
legend and the combinations of tests in the ATP assay for Figure 6.3 has been
magnified in Figure 6.4 for ease of reference. The plot has shown that a signal was
established using the recommended kit for the PerkinElmer Victor2 V 1420
multilabel counter available in the lab.
Figure 6.2. The standard curve from a 48 hr test of the ATPlite kit from
PerkinElmer against the MexTAg 299 166. The luminescence reading is as
expected with the exception of the slight dip at the highest concentration for both
curves. The reading was performed without mixing of the well contents.
93
Figure 6.3. The ATP assay graphed results for the MexTAg 299 166 cell line.
The luminescence readings showing a decreasing gradient of luminescent signal
from wells that were closest to the positive ATP control. Cross-talk has been
suspected here.
94
Figure 6.4. The legend for the ATP bar graph. The legend for all 4 bar graph plots
has been magnified here. The greyed out boxes from left to right represent the
position of the tests conducted for each ATP assay graphed results for the MexTAg
299 166, MexTAg 299 208, wild-type AE 17 and wild-type BM 164 cell lines. The
grey boxes represent the label position along the x-axis of the plot from left to right.
LEGENDATPFW = ATP Free Water rL/L = reconstituted Luciferase/Luciferin reagent M = MediaNCD = No chemotherapeutic drug - Media top upNCL = No cell lineWCL = With cell line LB = Lysis BufferCS = Cell SupernatantBleo = BleomycinCis = CisplatinCyc = CyclophosphamideDox = DoxorubicinEpir = EpirubicinEtoP = Etoposide PhosphateGem = GemcitabineIfos = IfosfamideMeth = MethotrexatePac = PaclitaxelPeme = PemetrexedVinc = Vincristine
LB + ATPFW + M + NCD + NCLLB + rL/L + M + NCD + NCLLB + rL/L + M + NCD + WCLLB + rL/L + M + Bleo + NCLLB + rL/L + M + Bleo + WCLLB + rL/L + M + Cis + NCLLB + rL/L + M + Cis + WCLLB + rL/L + M + Cyc + NCLLB + rL/L + M + Cyc + WCLLB + rL/L + M + Dox + NCLLB + rL/L + M + Dox + WCLLB + rL/L + M + Epir + NCLLB + rL/L + M + Epir + WCLLB + rL/L + M + EtoP + NCLLB + rL/L + M + EtoP + WCLLB + rL/L + M + Gem + NCLLB + rL/L + M + Gem + WCLLB + rL/L + M + Ifos + NCLLB + rL/L + M + Ifos + WCLLB + rL/L + M + Meth + NCLLB + rL/L + M + Meth + WCLLB + rL/L + M + Pac + NCLLB + rL/L + M + Pac + WCLLB + rL/L + M + Peme + NCLLB + rL/L + M + Peme + WCLLB + rL/L + M + Vinc + NCLLB + rL/L + M + Vinc + WCL
95
6.2.0 A summary of ATP assay issues and results
With reference to the results for MexTAg 299 166 (Figure 6.3), there were a few
things to note. The wells without cells and without the rL/L were expected to have
the lowest luminescent signal over the entire plate. This premise held true. The
lowest signal should ideally have come from a well without ATP, ie ATP free water
with LB and rL/L only. However, this negative control was missing from the design
of this plate so the next best negative control has come from the wells without cells
and without rL/L.
The highest concentration of the ATP standard was expected to have the highest
luminescent signal. This premise held true. The highest luminescent signal had a
value of 1449960 cps and the lowest value was 61 cps yielding a range of
1449899 cps. The range of values between the control groups of with or without
rL/L was 232cps - 61cps = 171 cps. Despite the fact that one lot was showing a
higher signal than the other lot, it was important to note that a difference of 171 cps
was small compared to what the difference could be on a larger scale as the range in
luminescence on the plate was 1449899 cps.
The drug control wells were expected to have similar luminescent signal levels as
that of the control wells without cells but with rL/L. Half the tests indicated this and
the other half did not. Only half the tests indicated that the drug controls had a
similar luminescent signal when compared to the wells without cells. These were
wells B10-G12, the half that is furthest away from the wells expected to give out the
96
highest luminescent signal. The other half of the tests have unexpected results. The
wells B1-G3 showed a gradient luminescent signal that was decreasing down the
plate away from the wells that produce the highest luminescent signal. Suspect
crosstalk was the reason for the unexpected result in one half of the tests. Cross talk
(Berthold, Herick & Siewe 2000) may have been affecting the signals of the controls
hence a repeat of this ATP assay would need a better plate design.
The standard curve turned out as expected with the exception of the slight dip at the
highest concentration. This may have been due to pipetting error or some other
factor. This data is inconclusive in terms of providing the relationship between ATP
levels and the mode of cell death due to chemotherapy but at least a signal was
obtained from the kit and the machine.
The ATP assay would need to be repeated with the changes for a better design:
Plating with gaps in between the samples being tested if retesting is to be done in the
same white 96-well plate, possible use of black 96-well plates to absorb the light and
therefore reducing the cross-talk, lowering the range of ATP Standard as the sample
test readings do not reach anywhere near the highest 3 luminescent readings and
finally, the inclusion of a negative control with no ATP.
97
6.3.0 Establishing a reading for caspase luminescence
As in the ATP assay, it was important to establish a luminescent reading from the
equipment available for testing. The MexTAg 299 208 cell line was used to plate out
the cells in a Corning Incorporated Costar 3610 96-well white assay treated culture
plate with clear bottom test plate. The chemotherapeutic drugs were made up to the
IC50 concentration for the MexTAg 299 208 cell line and then added to the cells in
their corresponding wells which was a mistake in that the drugs should have been
made up to double the concentration of the IC50 determined in the MTT assay as it
was diluted when 0.100 mL of the drug was added to 0.100 mL of the contents of
each well. This fact was noticed after the cells had been incubating with the drugs for
48 hrs. Additionally, there was not enough of the caspase reagent available for this
test so the caspase reagent was not added to all the wells. The kit was used as per the
manufacturer’s instructions.
Luminescence readings were made from the same plate at 4 different incubation time
points to empirically determine what time the reading was best obtained: 1 hr,
1.5 hrs, 2 hrs and 2.5 hrs. After a reading the plate was removed from the machine
and covered in aluminium foil at room temperature. The relative light unit (RLU)
was defined as CPS 100 mL-1 for plotting (Figure 6.5).
98
Figure 6.5: The decreasing output from a Wallac 1420 manager program on
PerkinElmer’s Victor2 V multilabel counter for caspase experiment 1 shown for
1 hr and 1.5 hr time points. The readings were done after incubation with the
Promega Caspase Glo 3/7 reagent. RLU = CPS 100 mL-1. The luminescent signal
detected was decreasing as the plate was left to incubate for longer than 1 hr.
99
6.4.0 Caspase signal detected
In a plot of each time point reading it could be seen that as time progressed, the
luminescent signal had decreased (Figure 6.4 and Figure 6.5). At first glance, there
appeared to be caspase activity in all the wells as there was a luminescent signal
from each sample group. However, the control wells without cells appeared to have a
very small luminescent signal when they were not expected to. This may be
attributed to background luminescence from crosstalk between the wells, which in
this case, was very small. These were therefore used as blanks.
As expected, because there were no cells for the caspase pathway to be triggered, the
media only and drug in media controls had the lowest luminescent signals. This
suggested that there is no need to control for drug in media only especially when the
media only negative control will suffice. The caspase activity in the “Cells +
Cyclophosphamide” and “Cells + Vincristine” sample groups were lower than that of
the “Control – Media and Cells”. This was unexpected as the two drugs should have
caused more death of the cells in these wells.
These tests would definitely need to be repeated. There was error in the planning of
the plate as only half the IC50 concentration was used to treat the cells. Additionally,
the media and cell controls had a higher than expected luminescence. It should have
been near the luminescence value of the “Control - Media Only” because the cells
were not treated with any drug. The cells in the wells may have become over
100
confluent and this would add variability in the luminescent signal. Unfortunately,
pictures were not taken of the wells in the plate when the plate was removed from
the incubator just prior to the Promega Caspase Glo 3/7 reagent being added. If over
confluence is a factor then the doubling time from proliferation data would need to
be looked at for making sure that the plating density for this particular cell line is
appropriate in future experiments.
The first experiment established that it was possible to obtain a luminescent signal. It
also established that the 1 hr time point was a good point for reading the luminescent
signal. However, the data was inconclusive in terms of what it could reveal about the
caspase activity at the 48hr time point when the cell line was treated with
chemotherapeutic drugs at the IC50 concentration.
6.5.0 High purity in the extraction of DNA
Four early passages of cell lines were cultured and frozen down into pellets until all
were ready for DNA extraction. The Qiagen DNeasy Blood & Tissue kit, used
according to the manufacturer’s instructions, yielded high purity of DNA
(Desjardins & Conklin 2001) allowing for further CGH array and exome sequencing
analysis (Figure 6.6). High purity of DNA was obtained from using the Qiagen kit in
the first try that allowed for the samples to be sent off for CGH array analysis. Other
cell lines have already been sent off for CGH array analysis and exome sequencing.
101
Figure 6.6. The purity of DNA extracted. The DNA of the wild-type AE 3,
MexTAg 299 177, MexTAg 299 69 and MexTAg 299 21 at low passages were
extracted with high purity according to their 260/280 and 260/230 ratios.
102
Chapter Seven:
Discussion
103
7.0.0 Discussion
The prognosis for patients with MM is very poor, and as for most cancers, patient
response to therapy is highly variable (Musk et al. 2011). This preliminary project is
aimed at investigating this by establishing the degree of heterogeneity amongst
mesothelioma cell lines which have all arisen due to asbestos exposure. Despite the
use of the same carcinogen, a number of variabilities amongst these cancers are still
present.
Could the poor prognosis for patients with MM be due to how it is acquired?
Although there are some other risk associations with mesothelioma development,
asbestos exposure remains the main cause. There is such a strong link between
asbestos exposure and mesothelioma, that in this respect, the initial development of
this cancer could be thought of as quite homogenous. In this respect, this study
mimics that, as all of the lines arose due to asbestos exposure.
Could the poor prognosis come from a problem with finding and identifying the
disease?
MM is usually diagnosed at late stage. Patients present with respiratory problems
that could be assigned to other conditions before MM is brought up for
consideration. There is currently a variety in the diagnostic aids employed. MM cells
are currently isolated from a population of cells by identifying unique exclusion,
104
CEA marker (Ordóñez 2003), and inclusion, overexpressed and hypoglycosylated
MUC1/EMA (Creaney et al. 2008) markers expressed by cells. CT, PET and
ultrasounds are other tools used to aid in diagnosis (Stigt, Boers & Groen 2012). The
body itself has its own immune system for identifying and killing off tumour cells
that is present in patients to do work even before the patient seeks help from a
physician (Mossman et al. 2013). A range of diagnosis tools are available but there is
room for improvements in this area as a long and variable latency period is still
present for patients with MM.
Is the variability in growth of MM in patients due to the MM cells being so different?
This is most likely as mesothelial cells already look different under a microscope
(Raja, Murthy & Mason 2011) and their phenotype changes depending on their
environment such that pathological process are affected (Mutsaers 2004). MMs in
culture have been observed to adopt a more fibroblast phenotype after many
passages (Mutsaers 2004). The prognosis is worse for patients with sarcomatoid
mesotheliomas than those with epitheloid meotheliomas (Grigoriu et al 2007). We
have shown variable growth rates for cell lines established from inbred, thus
homogenous, mice all exposed to the exact same amount of asbestos, and all housed
in the same environment and fed the same food. In humans the diversity is likely to
be much more extensive. In this respect, it is easier to initially investigate the link
between the response of cell lines to chemotherapy, and their genetic makeup, by
first removing confounding factors, such as smoking, age, diet, viral infection and
genetic variation between populations.
105
Different confluence rates of cells growing in culture flasks were clearly observed by
examination under a microscope. This was the first indication that the cell lines had
significantly different rates of proliferation. Growth was measured quantitatively
using the Cellavista. Analysis of the data showed that heterogeneity in the growth
rate of the 14 mesothelioma cell lines was observed. The result that the MexTAg cell
lines were slower to proliferate than the wild-type cell lines was surprising. The
MexTAg cell lines all expressed high levels of the well-studied SV40 T-antigen,
which has direct interactions with the tumour suppressors p53 and RB such that the
tumour suppressors are unable to arrest the cell cycle. This may indicate that once a
tumour has established its growth, the existence of certain oncogenes is irrelevant,
and other subsequent mutations become the key regulatory factors.
Is the variability in growth of MM in patients due to the difference in the patient’s
immune system for killing off tumour cells?
Animal models are used for studying disease in a controlled environment
(Kane 2006). Laboratory mice are highly in bred and thus have a very similar gene
pool and an intact immune system. Although the mesothelioma cell lines grew at
different rates in vivo, the differences in growth rates did not reach statistical
significance amongst wild-type BM 164, MexTAg 299 166, MexTAg 299 208 and
MexTAg 299 62 to indicate that there was no heterogeneity in the growth of
mesothelioma cell lines in vivo. This is different to the result found in the
proliferation assay where the cell lines were growing almost uninhibited by things
such as an intact immune system. What it does demonstrate is that when equal
106
quantities of the same batch of cells are injected into in bred mice, tumour
development is variable between individual mice.
The wild-type BM 164 cell line grows faster in vivo than the MexTAg 299 166 and
MexTAg 299 62 cell lines. This correlates with the proliferation assay data. For the
majority, MexTAgs are ranked slower to grow in vitro and in vivo. Perhaps it is
worth comparing the data for these 4 cell lines, at least, with viability data when they
are subjected to treatment.
Is the treatment being used for MM the right one?
There is a variety of treatments used for MM with different levels of success in the
goal to cure patients of the disease: surgery, radiotherapy, immunotherapy,
chemotherapy (Grégoire 2010), photodynamic therapy (Friedberg 2012) and gene
therapy (Vachani, Moon & Albelda 2011), either alone or in a multimodal fashion
(Liu et al. 2010). The classic treatment of MM is through chemotherapy, each one
with a specific mode of action to target different ways in which MM can develop and
progress in the patient. When used as a single agent, some patients do respond and
some do not (Tomek & Manegold 2004). It would be good to figure out if there
really is a difference in the growth of MM cells when treated with single agent
chemotherapies and which ones they respond to best.
Overall, there was heterogeneity in the response to chemotherapy amongst the 7
wild-type and 7 MexTAg cell lines treated against each of the 12 chemotherapeutic
107
drugs. In these responses, 6 out 12 were very significant and 6 out of 12 were
extremely significant. Multiple comparisons yielded statistically significant
differences in responses to chemotherapy between pairs of cell lines in 11 out of 12
chemotherapeutic drugs tested. The largest difference in response overall exists
against Pemetrexed between wild-type AE 16 and MexTAg 299 166
(7.90x106 ng/mL) whilst the smallest difference in response is between wild-type AE
3 and wild-type AE16 against Gemcitabine (1.16x101 ng/mL). Based on the overall
largest and smallest differences one cannot say that good and poor responders exist
because we need to still correlate the in vitro and in vivo data that still requires
validating despite care being taken to try and keep conditions as consistent as
possible in the MTT assay. The data requires validation from a more sensitive assay
or a number of other assays combined. The MTT assay does have the advantage that
it is relatively cheap to conduct per experiment for preliminary investigation.
What is causing the difference in response to treatments?
The MTT data needs to be verified. The phenotypes are different and a difference in
phenotype relates to genetic differences. We know for one that the MexTAgs are
different to the wild-types because of the insertion of 100 copies of the SV40
T-antigen gene, but there was variability in the response to chemotherapy between
the MexTAg cell lines as well. This suggests that other events on top of the inserted
SV40 T-antigen gene are more important in determining response to chemotherapy.
The answer may lie in the genome.
108
As a cancer, MM exhibits the hallmarks of a cancer: sustaining proliferative
signalling, evading growth suppressors, activating invasion and metastasis, enabling
replicative immortality, inducing angiogenesis and resisting cell death
(Hanahan & Weinberg 2011). MM cells acquire traits in a stepwise fashion towards
tumorigenesis (Mossman et al. 2013). Perhaps asbestos could be the first ‘trigger’.
Then, together with the presence of the SV40 T-antigen, tumour development is
accelerated which may be why in MexTAg mice we see a faster rate of disease
development after asbestos exposure compared to in wild-type mice. It may explain
why there is also 100% incidence in MexTAg mice compared to 20-30% incidence
in wild-type mice (Robinson et al. 2006). In this case, the second step towards
tumorigenesis could be the SV40 T-antigen, but not so in wild-type mice. There are
clearly other steps occurring in the wild-types for tumour progression to be
established.
The ATP assay and the caspase assays are still in the process of being optimised but
detecting a signal for both is possible with the equipment available. The DNA
extraction had high purity and is currently undergoing CGH array analysis. Some of
the lines are also being exome sequenced. Hence a follow up study is to see what the
differences are, if any, between the cell lines and if there are any correlations
between drug response or growth rate in vitro or in vivo. Maybe cell lines that
respond to a particular drug by the same magnitude of diversity may have the same
gene variant in common.
109
Concluding remarks on the project:
More time is needed to optimise each of the assays conducted in this study. The
results are approximate at best. The proliferation assay can be repeated given time to
more accurately plate out the cells on separate plates. The doubling times are
approximate because the removing of cells from the incubator and exposure to light
may have an effect on their growth. If images were taken where the cells were
growing, the confounding factor of a change in environmental condition would be
removed. Still, patterns of fast and slow growing cell lines can be observed, how
much of that difference is due to confounding factors is yet to be known. The
confounding factors in the mice experiments also need to be sorted out before “cause
and effect” can be implied from the results. Practically, differences in growth can be
seen between cell lines in vitro and in vivo but more accurate data needs to be
analysed for the statistics to fully correlate heterogeneity in growth.
Validating the results of the MTT assay is a priority as the rest of the work is
dependent on the fact the heterogeneity in response to chemotherapy was found.
Against Pemetrexed, MexTAg 299 166 is about 556,000 times more sensitive than
wild-type AE 16. In 4 out of 12 chemotherapeutic drugs, wild-type BM 164 is least
responsive to chemotherapy, followed by wild-type AE 16 in 3 out of 12
chemotherapeutic drugs. The most responsive cell line is MexTAg 299 170 in 3 out
of 12 drugs. If the findings of differences in the phenotype of the cells were accurate
it could lead to individualised therapeutic strategies to target the uniqueness of MM.
110
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Appendix I: List of tables
Table 1.1 Chemotherapeutic and anti-proliferative drugs. 22
Table 2.1 The cell lines used in this project. 42
Table 2.2 Statistical significance levels. 45
Table 2.3 The chemotherapeutic drugs supplied by Sir Charles Gardiner
Hospital Pharmacy.
48
Table 3.1 Inclusions and exclusions in the determination of doubling times. 63
Table 3.2 The diversity in proliferation rates of 14 mesothelioma cell lines. 66
Table 4.1 The fastest and slowest growing cell lines in vitro and in vivo. 72
Table 5.1 The triplicate well OD readings for experimental repeat
number 1 of the MexTAg 299 208 treated with Gemcitabine.
78
Table 5.2 The triplicate well OD readings for experimental repeat
number 2 of the MexTAg 299 208 treated with Gemcitabine
79
Table 5.3 The triplicate well OD readings for experimental repeat
number 3 of the MexTAg 299 208 treated with Gemcitabine.
80
Table 5.4 The IC50 replicates for the MexTAg 299 208 cell line. 83
Table 5.5 The IC50 summary table for all the wild-type cell lines. 84
Table 5.6 The IC50 summary table for all the MexTAg cell lines. 84
Table 5.7 The level of difference in response to chemotherapy by the
wild-type cell lines.
86
137
Appendix II: List of figures
Figure 1.1 Malignant mesothelioma in a bisected lung. 8
Figure 1.2 Wittenoom Asbestos Mine in Western Australia. 9
Figure 1.3 Ultrasound guided biopsy of malignant pleural mesothelioma. 9
Figure 1.4 Suicide gene therapy. 13
Figure 1.5 Cell lines grown in culture. 24
Figure 1.6 Formazan crystals formed in cells. 27
Figure 1.7 Fluorescence-activated cell sorter (FACS). 28
Figure 1.8 Creation of a transgenic mouse. 32
Figure 1.9 Layers of the skin. 33
Figure 1.10 CGH Array. 38
Figure 2.1 Cell viability plots in the determination of the IC50 in the MTT
assay.
52
Figure 3.1 The wild-type AE 17 and BM 163 cell line grown in culture. 61
Figure 3.2 The proliferation time determined at 40% and 80% confluence
for the wild-type AE 17 cell line at a plating density of
5.00 x 103 cells/well .
62
Figure 3.3 The proliferation rates of wild-type and MexTAg mesothelioma
cell lines are heterogeneic.
66
Figure 4.1 In vivo growth of MexTAg 299 166. 68
Figure 4.2 The exponential and linear growths. 70
Figure 4.3 The excluded growth curves from analysis. 71
138
Figure 5.1 Triplicate IC50 values determined from plots of MexTAg 299 208
treated with Gemcitabine.
81
Figure 6.1 The ATP assay plate layout of results. 91
Figure 6.2 The standard curve from a 48 hr test of the ATPlite kit from
PerkinElmer against the MexTAg 299 166.
92
Figure 6.3 The ATP assay graphed results for the MexTAg 299 166 cell line. 93
Figure 6.4 The legend for the ATP bar graph. 94
Figure 6.5 The decreasing output from a Wallac 1420 manager program on
PerkinElmer’s Victor2 V multilabel counter for caspase experiment
1 shown for 1 hr and 1.5 hr time points.
98
Figure 6.6 The purity of DNA extracted. 101
139
Appendix III: Data analysis
Proliferation and in vivo tumour growth analysis
In the proliferation assay, it was noted that a number of cell lines had entered the
exponential phase of growth at about 40% cell confluence and was still in this
exponential phase at about 80% cell confluence. Hence, 3 time span values were
conveniently interpolated from the 3 lines of best fit for the triplicate wells of each
cell line plating densities at 40% and 80% cell confluence. The doubling time was
obtained from subtracting the time span at 40% cell confluence from the time span at
80% cell confluence. The option to “Interpolate unknowns from standard curve” was
also selected. It was noted that each cell doubling yielded an exponential increase in
numbers and as such the exponential growth equation was used. A “non-linear
regression (curve fit)” analysis using the exponential growth equation was applied to
model the growth of the cell lines from these new time span values. Having worked
out, through a linear model, how long it took for the cell lines in each well to get to
40% and 80% confluence, the doubling time for each well was then determined by
subtracting the time span at 40% cell confluence from the time span at 80% cell
confluence in Graphpad. The proliferation assay was repeated until at least
3 doubling times were obtained for each cell line and statistical analysis performed.
In the proliferation or in vivo growth experiments, where applicable, an approximate
two-tailed p-value was obtained from an unmatched and non-parametric one-way
ANOVA, the Kruskal-Wallis test, for comparing the doubling times between all the
140
wild-type, or all the MexTAg, cell lines at the α = 0.05 level of statistical
significance, so that the chance of incorrectly finding a difference in mean doubling
times would occur no more than 5% of the time. The null hypothesis was that the
means were all the same and the alternative hypothesis was that the means were not
all the same. A Dunn’s correction for multiple comparisons was applied and a
two-tailed p-value was obtained for the determination of which pairs of mean
doubling times were significantly different and which pairs were not.
A D’Agostino-Pearson omnibus K2 normality test, offered in Graphpad, was used at
the α = 0.05 level of statistical signifiance to obtain a two-tailed p-value of for the
the combined mean doubling times of the wild-type, or MexTAg, cell lines. The null
hypothesis was that the sample had come from a normally distributed population and
the alternative hypothesis was that the sample did not come from a normally
distributed population. When the test was passed by both the wild-type and MexTAg
cell lines, the Gaussian distribution was assumed. An unpaired parmetric t-test with
Welch’s correction, as it was assumed that the SDs were not equal, was used in the
comparison of their mean doubling times at the α = 0.05 level of statistical
significance.
A Kruskall-Wallis test at an α = 0.05 level of statistical significance was used to
obtain an approximate two-tailed p-value in the comparison of doubling times
amongst all 14 mesothelioma cell lines. A Dunn’s correction for multiple
comparisons was also applied to the data to obtain a two-tailed p-value so that the
pairs of mean doubling times which were significantly different and those pairs that
were not were determined.