Cancer Cells Exploit Eif4e2-Directed Translation to Enhance Their Proliferation, Migration and Invasion

Cancer cells exploit eIF4E2-directed translation to enhance their proliferation, migration and invasion

Joseph F. Varga

A Thesis presented to The University of Guelph

In partial fulfilment of requirements for the degree of Master of Science in Molecular and Cellular Biology

Guelph, Ontario, Canada

ABSTRACT

Cancer cells exploit eIF4E2-directed translation to enhance their proliferation, migration and invasion

Joseph F. Varga Advisor: University of Guelph, 2016 Professor James Uniacke

Despite the diversity found in the genetic makeup of cancer, many cancers share the same tumor microenvironment. Hypoxia, an aspect of the tumor microenvironment, causes the suppression of the primary translational machinery. Hypoxic cells switch from using the eukaryotic initiation factor 4E (eIF4E) to using a homologue of eIF4E (eIF4E2), in order to initiate the translation of select mRNAs. This thesis investigates the role of eIF4E2-directed translation in a panel of cancer cell lines during autonomous proliferation, migration and invasion. In this thesis, we show that silencing eIF4E2 abrogates the autonomous proliferation of colon carcinoma.

Silencing eIF4E2 in glioblastoma cells resulted in decreased migration and invasion. Furthermore, we link eIF4E2-directed translation of cadherin 22 with the hypoxic migration of glioblastoma.

These findings answer questions regarding the biology of cancer and expand the current knowledge of genes exploited during tumor progression. This data also highlights eIF4E2 as a potential therapeutic target. Acknowledgements

I would like to express my sincere gratitude to Dr. James Uniacke for taking me on as a graduate student in his laboratory and providing me with the opportunity to contribute to scientific research. I would also like to thank him for his continued support and commitment to my project and also for allowing me to attend several conferences to share my research. From day one, he has challenged me to do my best as a graduate student and was always available if I wanted to chat.

To Erin Specker our lab manager, thank you for all of your support and involvement in this project.

You were a joy to work with. To my lab mates both past and present; Andrea Brumwell, Sonia

Evagelou, Brianna Guild, Sara Timpano, Gaelen Melanson, Dr. Phil Medeiros, Nicole Kelly,

Crystal Gong, Shannon Sproul, Lorian Fay, Vincent Lau and Christina Romeo, I am grateful for your friendship and continued support over the years. I am truly privileged to have been part of this laboratory under the guidance of Dr. Uniacke. He has instilled in me a passion for hypoxic research which I hope to continue. To my fellow graduate students; Sherise Charles, Haidun Liu,

Ashley Brott, Kathryn Reynolds, Jordan Willis and Richard Preiss, thank you for being part of this journey.

To the advisory committee: Dr. Marc Coppolino and Dr. Alicia Viloria-Petit, thank you for your support and insight over the course of my project. Thank you to Cheryl Craag, Dr. Kelly

Meckling, Dr. Éva Nagy, Dr. Tony Mutsaers and Dr. Joseph Lam for stimulating and encouraging my passion for scientific research, you gave me the research bug! To my friends and family: thank you for your patience and understanding. To this amazing institution which I have called home for the past six years, the University of Guelph and graduate school, thank you for teaching me so much about myself and life in general. You pushed me to my limits more than once but these two years have been the best years of my life! Cadherins: thanks for keeping everything together. III

Declaration of Work Performed

Erin Brouwers formed the stable MDA-MB-231, eIF4E2 shRNA knockdowns. Stable

U87-MG and HCT-116 eIF4E2 shRNA knockdowns were formed by Dr. James Uniacke at the

University of Ottawa and brought to our lab at the University of Guelph. Christina Romeo assisted in some of the Bromodeoxyuridine Assays with U87-MG cell lines. Nicole Kelly and Sonia

Evagelou formed the stable U87-MG, CDH22 shRNA knockdowns. The author performed all other experiments.

List of Figures

Figure 1. Schematic of Hypoxia Inducible Factors (HIFs) stimulating the transcription of

hypoxic response genes...... 9

Figure 2. Schematic diagram of an alternative hypoxic protein synthesis machinery...... 13

Figure 3. The proposed hypoxic switch between cadherins during tumor progression...... 20

Figure 4. BrdU incorporation in HCT-116 cells under hypoxia and normoxia in serum-free

and complete media...... 37

Figure 5. BrdU incorporation in MDA-MB-231 cells under hypoxia and normoxia in

serum-free and complete media...... 38

Figure 6. BrdU incorporation in U87-MG cells under hypoxia and normoxia in serum-free

and complete media...... 39

Figure 7. Inhibition of eIF4E2 enhances the migration of HCT-116 cells...... 41

Figure 8. Inhibition of eIF4E2 impairs the hypoxic migration of U87-MG cells...... 43

Figure 9. Re-introduction of exogenous eIF4E2 rescues the loss of migration observed in

eIF4E2-depleted cells...... 44

Figure 10. U87-MG cells harbouring shRNA against eIF4E2 exhibit less migration...... 45

Figure 11. Inhibition of eIF4E2 impairs the hypoxic invasion of U87-MG cells...... 47

Figure 12. CDH22 protein accumulates in hypoxia but not the mRNA...... 50

Figure 13. The addition of neutralizing antibody against CDH1 and CDH22 impairs the

hypoxic migration of U87-MG wild-type cells...... 51

Figure 14. The addition of neutralizing antibody against CDH22 reduced the migration and

invasion of U87-MG cells...... 52

Figure 15. Depletion of CDH22 reduces the hypoxic migration of U87-MG cells...... 54

Figure 16. Inhibition of CDH22 impairs the hypoxic migration of U87-MG cells and

enhances invasion...... 55

Figure 17. Morphology of CDH22-depleted cells under normoxia...... 56

Figure 18. Depletion of CDH22 in U87-MG cells does not affect proliferation under hypoxia

or normoxia...... 58

List of Tables

Table 1. eIF4E2-dependence of genetically distinct human cancer cell lines on autonomous proliferation, migration and invasion…………………………………………………………73

Table 2. CDH22-dependence of the U87-MG cell line on proliferation, migration and Invasion………………………………………………………………………………………….76

VII

List of Abbreviations

EGFR Epidermal Growth Factor Receptor

TAF Tumor Angiogenesis Factor

HIFs Hypoxia-Inducible Factors

ATP Adenosine triphosphate

HRE Hypoxia Response Element

ARNT Aryl Hydrocarbon Receptor Nuclear Translocator

PHDs Prolyl-4-hydroxylase Domains pVHL Von Hippel-Lindau Tumor Suppressor Protein

EPO Erythropoietin

EIFs Eukaryotic Initiation Factors eIF4E Eukaryotic Translation Initiation Factor 4E eIF4E2 Eukaryotic Translation Initiation Factor 4E Family Member 2

4EBP 4E Binding Proteins

RBM4 RNA-Binding Protein-4 mTOR Mammalian Target of Rapamycin

IRES Internal Ribosome Entry Site

VIII

PAR-CLIP Photoactivable Ribonucleoside-Enhanced Crosslinking and

Immunoprecipitation rHRE RNA Hypoxia Response Element

PDGFRA Platelet Derived Growth Factor Receptor Alpha

EMT Epithelial to Mesenchymal Transition

CDH1 E-cadherin

CDH22 Cadherin 22

CDH11 Osteoblast-cadherin

ECM Extracellular Matrix

MMPs Matrix Metalloproteinases

RCC Renal Cell Carcinoma

4E-T Eukaryotic Translation Initiation Factor 4E Transporter

CRM1 Chromosome Maintenance 1 Protein Homologue

BrdU Bromodeoxyuridine

PDVF Polyvinylidene Difluoride

PBS-T Phosphate Buffered Saline with Tween 20

GAPDH Glyceraldehyde 3-phosphate dehydrogenase

PBS Phosphate Buffered Saline

IGF1-R Insulin-Like Growth Factor Receptor 1

L1CAM L1 Cell Adhesion Molecule

BCAM Basal Cell Adhesion Molecule

MTDH Metadherin

ADAM11 ADAM metallopeptidase domain 11

ADAM12 ADAM metallopeptidase domain 21

Table of Contents ABSTRACT ...... II Acknowledgements ...... III Declaration of Work Performed ...... IV List of Figures ...... V List of Tables ...... VII List of Abbreviations ...... VIII Chapter 1 - Introduction ...... 1 1.1 Cancer and Personalized Medicine ...... 1 1.2 The Hypoxic Tumor Microenvironment and the Hallmarks of Cancer ...... 3 1.3 The Hypoxia Inducible Factor Regulatory Pathways...... 6 1.4 Differential Roles of HIF-1α and HIF-2α in Tumor Pathogenesis and Disease Progression ... 10 1.5 Protein Synthesis and Translational Control under Hypoxic Stress ...... 11 1.7 The Role of Hypoxia in Tumor Migration and Invasion ...... 17 1.8 Targeting the Hypoxic Tumor Microenvironment and eIF4E2 in Cancer Therapy ...... 23 1.9 Experimental Objectives ...... 26 Chapter 2 - Materials and Methods ...... 29 2.1: Cell Culture ...... 29 2.2: Creation of Stable Cell Lines ...... 29 2.3: Western Blotting ...... 30 2.4: Bromodeoxyuridine Assay ...... 31 2.5: Scratch Wound Migration Assay ...... 32 2.6: Boyden Chamber Migration Assay ...... 32 2.7: Matrigel Invasion Assay ...... 32 2.8: RNA extraction ...... 33 2.9: Quantitative real-time PCR (qPCR) ...... 33 2.10: Statistical Analyses ...... 34 Chapter 3 – Results ...... 35 3.1: HCT-116 cells depend on eIF4E2 for their autonomous proliferation ...... 35 3.2: Inhibition of eIF4E2 increases the migration of HCT-116 cells ...... 40 3.3: eIF4E2 is required by U87-MG cells for their hypoxic migration and invasion in vitro ...... 42 3.4: Inhibition of CDH22 impairs U87-MG migration but not invasion in vitro ...... 48 3.6: U87-MG cells do not depend on CDH22 for their proliferation ...... 57

Chapter 4 – Discussion ...... 59 Chapter 5 – Summary ...... 68 References ...... 70

XII

Chapter 1 - Introduction 1.1 Cancer and Personalized Medicine

Cancer is recognized as one of the leading causes of mortality and morbidity worldwide, with 14 million cases and 8.2 million cancer-related deaths in 2014 (World Cancer Report, 2014).

Cancer includes more than 100 distinct diseases with diverse risk factors and epidemiology, making it one of the most complex diseases of modern day. It is characterized by the rapid, uncontrolled proliferation of abnormal cells that are able to metastasize to distant organs and invade tissues (Stratton et al., 2009). During normal tissue homeostasis, there is persistent crosstalk between normal cells and the surrounding environment, which keeps cellular proliferation at bay.

However in cancer, this system goes awry. Cancer cells gain the ability to proliferate independently due to the accumulation of mutations within their genomes. These mutations, combined with a chaotic tissue microenvironment, drive the development of cancer. The development of cancer is an evolutionary process, where mutant cells compete for space and nutrients, evade the immune system and disperse to new organs, forming colonies (Merlo et al.,

2006). This evolutionary process is strongly supported by the tumor microenvironment (Stratton et al., 2009).

The tumor microenvironment includes a heterogeneous mix of malignant, and stromal cells such as cancer-associated fibroblasts, immune cells and endothelial cells (Hanahan & Coussens,

2012). During the development of a tumor, cancer cells are exposed to a variety of environmental stressors, including: oxidative stress, acidosis, starvation and hypoxia among others. Unlike normal cells, cancer cells are able to overcome these environmental stressors due to the accumulation of beneficial mutations. Stress within the tumor microenvironment also contributes to selective pressure on specific populations of cancer cells. This is a crucial aspect of tumor 1

development, which is dependent on two continuous processes: the heritability of genetic variation in single cells and natural selection acting on the resultant phenotypic diversity due to the accumulation of mutations (Stratton et al., 2009). By continuously selecting for advantageous phenotypes, cells acquire the ability to autonomously proliferate and survive more effectively than their neighbours (Stratton et al., 2009).

Understanding the processes behind tumor development is one of the main goals of cancer research. In medicine, the understanding of these processes fuels the advancement of prevention, detection and treatment (Chin, Andersen, & Futreal, 2011). Recent advances in genomics have contributed significantly to cancer research and modern day medicine. Genomic advancements have made it possible to quickly identify genetic variants that underlie a specific cancer phenotype and have also contributed to the development of novel cancer therapies that are highly precise.

These therapies are unique to each individual patient and are known as personalized medicine.

Currently, cancer therapy is shifting from cytotoxic anticancer drugs to genotype-directed therapy

(Mendelsohn, 2016). This approach has proven to be successful and has improved treatment outcomes in several cancers (Bai, Staedtke, & Riggins 2011; Sequist et al. 2011; Schroth et al.,

2011). In metastatic colorectal cancer for example, RAS mutations actually predicted a lack of response in patients who received the commonly used drug panitumumab, an epidermal growth factor receptor (EGFR) inhibitor. However, in tumors that harboured a wildtype-RAS, panitumumab was very effective and increased overall survival by 10.5 months (Tabernero et al.,

2013). Despite the advancements in genomic sequencing and molecular profiling, cancer is still considered a complex disease due to molecular heterogeneity and phenotypic diversity within the total tumor cell population. Molecular heterogeneity and phenotypic diversity are influenced by genetic and non-genetic factors (Marusyk, Almendro, & Polyak, 2012).

1.2 The Hypoxic Tumor Microenvironment and the Hallmarks of Cancer

Regardless of their tissue of origin or genetic makeup, solid tumors share a feature commonly known as the hypoxic tumor microenvironment. Due to the rapid uncontrolled proliferation of abnormal cells, tumors rapidly outgrow their vasculature, creating pockets of hypoxia. Hypoxia is universal across solid tumor microenvironments, since the diffusion limit of oxygen is only 150 μm from a blood vessel in human tissue (Possible & For, 1955). In tumors more than 1 mm in diameter, an oxygen gradient exists as a result of restricted diffusion. The core of the tumor is necrotic, the intermediate layer surrounding the core is hypoxic and the outermost layer, which is surrounded by vascular networks of capillaries, is oxygenated (Li et al., 2007;

Brahimi-Horn, Chiche, & Pouysségur, 2007). Therefore, over the course of tumor development, the cells within the microenvironment are exposed to varying amounts of oxygen.

In an attempt to combat hypoxia, cancer cells undergo a process known as angiogenesis, in which new blood vessels are formed upon pre-existing vasculature (Risau, 1997). This process was first described by Judah Folkman in 1971 and is now recognized as one of the hallmarks of cancer (Folkman et al., 1971; Hanahan & Weinberg, 2011). As a pioneer of angiogenesis, Folkman isolated a tumor factor that is responsible for angiogenesis and named it Tumor Angiogenesis

Factor (TAF) (Folkman et al., 1971). Based upon his previous work, he also suggested that the inhibition of TAF may arrest tumor growth. Prior to this, Folkman et al. demonstrated that when perfused organs were isolated from mice and injected with melanoma cells, tumors would form but would only reach a maximum size of 1 – 2 mm3 and never became vascularized (Folkman et al., 1963). However, when the same tumor cells were implanted into organs within mice, the tumors grew well beyond 1 – 2 mm3 and established a vascular network (Folkman et al., 1963).

This was also one of the first lines of evidence to support the idea that the environment in which cancer cells are located, is crucial to tumor progression. Today, it is well established that the hypoxic tumor microenvironment promotes angiogenesis in solid tumors (Hanahan & Weinberg,

2011; Pugh & Ratcliffe, 2003). In fact, one of the best studied hypoxic responses is the production of growth factors which stimulate angiogenesis (Waleh et al., 1995; Sinor et al., 1998; Tsuzuki et al., 2012). This adaptation process is largely regulated by hypoxia-inducible factors (HIFs) which are transcription factors that induce the expression of many genes enabling cellular adaptation to hypoxia (Fallone, Britton, Nieto, Salles, & Muller, 2013). However, unlike blood vessel formation in the embryo, termed vasculogenesis, these blood vessels are chaotic, leaky and unevenly distributed, exacerbating hypoxia (Chan & Bristow, 2010).

There are currently two types of hypoxia within tumors, the first is known as diffusion- limited or chronic hypoxia (Possible & For, 1955). The second type is known as acute or perfusion- limited hypoxia and was first described by Brown in 1979. Acute hypoxia is characterized by fluctuations in the perfusion of tumor vasculature. In acute hypoxia, oxygenation of the tissue depends on the integrity of the vessel itself (Span & Bussink, 2015). The feeding vessel may supply sufficient oxygen for quite some time but then becomes blocked for a short period, due to tumor cell aggregates or thromboembolisms (Span & Bussink, 2015). However, it remains controversial whether or not chronic hypoxia predominates in the solid tumor microenvironment (Treffer et al.,

2002; Hsieh et al., 2010). To date, the interaction between chronic and acute hypoxia in solid tumors has not been elucidated (Overgaard, 2007). Nevertheless, hypoxia has been recognized as the driving force behind many aggressive cancer phenotypes and has been implicated in the development of radio and chemo resistance (Gatenby et al., 1988) (Brizel et al., 1997). It is also

associated with poor clinical outcome, thus serving as an attractive therapeutic target. For example,

Hsieh et al. demonstrated that cycling hypoxia promotes radioresistance in glioblastoma cells when compared to uninterrupted hypoxic stress ( Hsieh et al., 2010). This is more representative of the situation that occurs in vivo, within the tumor microenvironment, where oxygen levels also fluctuate, creating a dynamic system.

Recently, chronic hypoxia was shown to be associated with a more aggressive cancer phenotype (Ragnum et al., 2014). Using a hypoxic stain known as pimonidazole, aggressive prostate tumors were evaluated for their gene expression patterns. Computational gene expression analyses were carried out and aggressive hypoxic prostate cancer tissue harboured a robust transcriptional program that included upregulation of genes involved in proliferation and DNA repair (Ragnum et al., 2014). This gene signature increased with the stage of the tumors, suggesting that hypoxia is associated with tumor progression and plays a significant role in the modulation of genotype while affecting phenotype. By upregulating genes that are involved in processes such as proliferation and DNA repair, cancer cells are able to adapt to stressors in the tumor microenvironment. This enables cancer cells to acquire characteristics that are different from normal cells, known as the hallmarks of cancer, such as resistance to growth inhibition, proliferation in the absence of additional growth factors, invasion and metastasis and evasion of apoptosis (Ruan, Song, & Ouyang, 2009) (Hanahan & Weinberg, 2011) . Since hypoxia has a profound role in stimulating the hallmarks of cancer, it serves as an attractive target in cancer therapy for three main reasons: hypoxia is common amongst solid tumors, targeting hypoxia would result in affecting several cancer hallmarks simultaneously, and therapy would be specific to hypoxic areas. Current cancer treatments are focused on targeted therapy, specific to certain genes or receptors which unfortunately leads to resistance over time due to tumor heterogeneity and

clonal evolution (Wigerup, Sven, & Bexell, 2016). However a more general approach, such as targeting hypoxia may prove to be beneficial, since several hypoxia activated genes can be targeted at the same time that are specific to hypoxic regions of tumors.

1.3 The Hypoxia Inducible Factor Regulatory Pathways

Oxygen is required by most animals as it is the final electron acceptor in the electron transport chain of the mitochondria. This allows the synthesis of sufficient amounts of adenosine triphosphate (ATP) through oxidative phosphorylation, which cells use as their primary energy source. Under hypoxic conditions, oxidative phosphorylation is not sustainable. Therefore hypoxia stimulates a metabolic switch from oxidative phosphorylation to glycolysis that stalls growth and proliferation. However unlike normal cells, cancer cells are able to survive and adapt to hypoxic stress. How cancer cells adapt to hypoxia is a major area of focus in the cancer research community and the hypoxia inducible transcription factors (HIFs) have been shown to play a crucial role in adaptive responses. Besides activating a number of survival genes, HIFs also ensure that there is a continued energy supply during hypoxic stress (Wouters et al., 2005).

HIFs are heterodimeric proteins that consist of the oxygen-regulated HIF-1α or HIF-2α subunits. There is also a third isoform of HIF known as HIF-3α which encodes a polypeptide that antagonizes hypoxia response element (HRE)-dependent gene expression (Ratcliffe, 2007). The fact that three different isoforms exist raises questions about the specificities of their action and also which target genes are regulated by specific subunits (Loboda, Jozkowicz, & Dulak, 2010).

The cytoplasmic subunits that are regulated via oxygen levels (HIF-1α, HIF-2α and HIF-3α) are able to bind to HIF-1β in the nucleus to induce transcription. HIF-1β, is also known as aryl hydrocarbon receptor nuclear translocator (ARNT), is constitutively expressed and localized to the

nucleus (Harris, 2002; Gilkes, Semenza, & Wirtz, 2014). There are currently five known isoforms of ARNT. Besides their role in hypoxia, they are also involved in toxin exposure and xenobiotic metabolism (Freeburg & Abrahamson, 2004).

During conditions of normal oxygen tension, where there is sufficient oxygen within the cell, HIFs are hydroxylated by oxygen-sensing enzymes known as prolyl-4-hydroxylase domains

(PHDs) at specific proline residues. Currently there are three known paralogues of PHDs, PHD 1

– 3 (Henze et al., 2010). Once hydroxylated by PHDs, the HIFs are recognized and bind to Von

Hippel-Lindau tumor suppressor protein (pVHL) E3-ligase complex and are degraded via the ubiquitin-proteasome system (Harris, 2002; Jaakola et al., 2015).

In contrast, when there is a reduction in oxygen tension, oxygen becomes a rate-limiting step for proline hydroxylation. Therefore the HIFs remain stable in the cytoplasm and can translocate to the nucleus. Once inside the nucleus, HIFs associate with HIF-1β and bind hypoxia response elements on DNA. Hypoxia response elements consist of a core sequence; RCGTG

(R:A/G) which are conserved among many hypoxia response genes in the promoter region

(Semenza et al., 1996). This leads to the active transcription of target genes involved in processes such as proliferation, invasion and apoptosis. The stable dimerization of HIF-1α or HIF-2α with

HIF-1β involves various cofactors. The cofactors serve two main functions: they stabilize the transcription initiation complex, containing RNA polymerase II and they also contain histone acetyltransferase (Loboda et al., 2010). Histone acetyltransferase is an enzyme that is required for the polymerase to access DNA within chromatin; in order for it to be transcribed into RNA

(Loboda et al., 2010).

Figure 1. Schematic of Hypoxia Inducible Factors (HIFs) stimulating the transcription of hypoxic response genes. Under normoxic conditions, the oxygen-regulated HIFs remain in the cytoplasm because they are hydroxylated by PHDs and bind to Von Hippel-Lindau protein (pVHL) which targets them for degradation to the proteasome. However under hypoxia, where oxygen is limited and PHDs are inhibited, both HIF-1α and HIF-2α can translocate to the nucleus, heterodimerize with HIF-1β and activate the transcription of hypoxic response genes by binding to Hypoxia Response Elements (HREs) on DNA.

1.4 Differential Roles of HIF-1α and HIF-2α in Tumor Pathogenesis and Disease Progression

Initial studies on hypoxia focused on erythropoietin (EPO), a hematopoietic growth factor released by the kidney in response to low arterial oxygen (Jacobson et al., 1957). EPO increases the production of erythrocytes and controls oxygen homoeostasis through increasing the oxygen- carrying capacity of blood (Ratcliffe, 2007). Under extreme hypoxic conditions, it was observed that EPO mRNA and EPO protein production within renal cells increased by 1000-fold or more

(Ratcliffe, 2007). HIF-1α was identified as a DNA-binding protein that activated EPO gene transcription (Semenza et al., 1991). Subsequently, Semenza et al. determined that HIF-1α DNA binding activity, also occurred in cells that did not produce EPO, which led to the discovery that

HIF-1α is involved in hypoxia signaling and transcriptional regulation (Semenza et al., 1995). .

HIF-2α has recently become an important regulator of the hypoxic response to stress

(Loboda et al., 2010). Both α subunits are highly conserved at the protein level, share similarities in their domain structure, heterodimerize with HIF-1β and bind to the same DNA sequence on the

HRE (Loboda et al., 2010). However, the ways in which they affect gene expression differ greatly.

HIF-2α, unlike the widely expressed HIF-1α, is expressed only by certain tissues, which include the endothelium, kidney, heart and small intestine (Gordan et al., 2007). Therefore the transcription of target genes mediated by HIF-2α may be tissue specific and in the case of tumors, it would depend on the tissue of origin.

Knockout studies in mice have shown that both HIF-1α and HIF-1β subunits are crucial for development; however knockout embryos succumb early in development and exhibit different phenotypes. HIF-1α -/- embryos succumb by gestation day 11 due to cardiac and vascular defects, whereas HIF-2α -/- embryos are not able to survive past gestation day 16.5 due to bradycardia,

vascular defects and incomplete lung maturation (Loboda et al., 2010; L.E. Huang & Bunn, 2003;

Compernolle et al., 2002). This finding not only supports the idea that HIF-2α is involved in the expression of distinct genes but also that HIF-2α embryos survive longer than HIF-1α knockouts.

This suggests that HIF-2α predominates in chronic hypoxic states. Perhaps as the embryo grows larger, there is an increase in proliferation and therefore a greater demand for oxygen. Thus, the growing embryo may depend on HIF-2α under chronic hypoxia, to activate the transcription of select genes involved in development and survival. Which is very similar to tumor growth.

Moreover, there is evidence to support that HIF-2α protein levels continue to accumulate during prolonged periods of hypoxia while HIF-1α is degraded over time under chronic hypoxia (1% O2)

(Holmquist-Mengelbier et al., 2006). Holmquist-Mengelbier et al. showed that HIF-1α activity peaks at 4 hours under 1% O2 and then begins to rapidly decline in activity, whereas HIF-2α activity increases between 6 – 8 hours and persists until 72 hours under 1% O2 (Holmquist-

Mengelbier et al., 2006). By 48 hours in hypoxia, HIF-1α activity is completely abolished

(Holmquist-Mengelbier et al., 2006). Therefore HIF-1α mediates acute responses to hypoxia whereas HIF-2α mediates chronic responses to hypoxia (Holmquist-Mengelbier et al., 2006).

1.5 Protein Synthesis and Translational Control under Hypoxic Stress

Within the dynamic environment of cells, protein synthesis (translation) is crucial for the expression of specific genes that help to combat stressful situations such as hypoxia. The hypoxic response is initiated through a HIF-mediated transcriptional program, but paradoxically the protein synthesis machinery is repressed to survive this energy-limiting condition. Translation involves four steps: initiation, elongation, termination, and recycling. The entire process is heavily influenced by the rate-limiting initiation step, which is carried out by 12 eukaryotic initiation factors (eIFs) (Spilka et al., 2013). Cap-dependent translation begins with the assembly of a

trimeric complex known as eIF4F, which consists of eukaryotic translation initiation factor 4E

(eIF4E), which binds to the 7-methylguanosine 5’ cap on mRNA; eIF4A, an RNA helicase and eIF4G, which is a scaffolding protein required to recruit the 40S ribosomal subunit (A. C. Hsieh

& Ruggero, 2010). At the 3’ UTR, Poly A Binding Protein binds to eIF4G, which leads to the circularization and active translation of mRNA (Grzmil & Hemmings, 2012). eIF4E is tightly regulated through post-translational processes such as phosphorylation or through its interaction with partners such as 4E Binding Proteins (4EBP) that inhibit eIF4E activity and decrease translation (Hsieh et al., 2010). 4EBPs also compete with eIF4G, to bind to the dorsal surface of eIF4E (Hsieh et al., 2010). Hypoxia leads to the hypophosphorylation of 4EBPs, which prevents the formation of the eIF4F complex by blocking the binding of eIF4G to eIF4E (Figure 3) (Hsieh et al., 2010)

Figure 2. Schematic diagram of an alternative hypoxic protein synthesis machinery. Hypoxia inhibits mTOR which results in the accumulation of hypophosphorylated 4E- Binding Proteins (4E-BPs). Hypophosphorylated 4E-BPs are able to bind to eIF4E and interfere with its interaction with eIF4G, thus repressing translation. In addition, 4E-BPs have a higher binding affinity for eIF4E than they do for its homologue, eIF4E2. The formation of the eIF4E2- RBM4-HIF-2α complex begins with eIF4E2 binding to the 5’ 7-methyl guanosine cap of the mRNA. This recruits HIF-2α to the 3’ UTR and RNA-Binding Protein – 4 (RBM4), where RBM4 binds to RNA Hypoxia Response Elements (rHREs) on mRNA. Therefore, transcripts that harbour rHREs can escape mTOR mediated repression.

The mammalian target of rapamycin (mTOR) is a master regulator of protein synthesis, growth and survival. Under the stimulation of mTOR, 4EBP undergoes extensive phosphorylation at multiple sites which leads to a conformational change and disrupts its ability to bind eIF4E.

Therefore eIF4E is activated because 4EBP is inactive and eIF4E can bind eIF4G, to form an active eIF4F complex which initiates translation (Liu et al., 2007; Knaup et al., 2009). However, mTOR is inhibited under hypoxia which results in many hypophosphorylated 4EBPs which bind to eIF4E and reduce the rate of global protein synthesis (Figure 3) (Knaup et al., 2009). mTOR is inhibited in order to shut down energetically-demanding processes such as protein synthesis in an attempt to conserve energy under stress. However, translation under hypoxic stress is necessary in order to undergo adaptive responses. Although global protein synthesis is drastically decreased under hypoxia, select mRNAs are preferentially translated (Young et al., 2008). The majority of proteins within a cell, approximately 95%, are synthesized under cap-dependent translation.

However, 3 – 5% are believed to be translated via the internal ribosome entry site (IRES) mechanism (Young et al., 2008).

IRES involves a 40S ribosomal subunit which is recruited to mRNAs with structured 5’

UTRs by IRES trans acting factors (Young et al., 2008). It has been shown that several mRNAs regulated by hypoxia contain IRES elements, which provide an alternative translation pathway when cap-dependent translation is compromised (Young et al., 2008). Nevertheless, there are unexplained instances such as viral infections, where both cap-dependent and cap-independent mechanisms are active concurrently (Komar & Hatzoglou, 2011). Furthermore, Young et al.

(2008) found that cellular IRES-mediated translation accounted for less than 1% that of the level of cap-dependent translation and they also observed that hypoxic stress failed to activate cap- independent translation of stress-regulated mRNAs such as HIF-1α, HIF-2α and glucose

transporter-like protein 1 (Young et al., 2008). This suggests that an alternative mechanism of protein synthesis exists because these mRNAs are still translated and usually abundant in hypoxic cells. Which leads us to ask the question; how are select mRNAs still translated under eIF4E inhibition and oxygen stress?

1.6 eIF4E2-directed Translation and its Role in Cancer

Alternative mechanisms of mRNA translation in cancer remain poorly understood and there is still a substantial amount of work to be done in this field (Meric & Hunt, 2002). Uniacke et al. (2012) have demonstrated that there is a hypoxic cap-dependent translation mechanism that is responsible for translating the majority of hypoxic response mRNAs when the eIF4E system is repressed (Uniacke et al., 2012). eIF4E2, also known as 4E Homologous Protein, an eIF4E homologue, binds to the 5’ UTR of mRNA while it recruits HIF-2α and RNA-binding protein

(RBM4) to the 3’ UTR, forming an oxygen-regulated translation initiation complex (Figure 3)

(Uniacke et al., 2012).

Through photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation

(PAR-CLIP) analysis, an RNA hypoxia response element (rHRE) was identified (Uniacke et al.,

2012). Through an immunoprecipitation experiment by Tee et al. (2004) it was determined that

4EBP has a greater affinity for eIF4E than it does for eIF4E2 (Tee et al., 2004). Therefore, select mRNA transcripts containing rHRE sequences are able to evade mTOR-mediated repression of eIF4E (Figure 3) and are translated under hypoxic conditions (Uniacke et al., 2012). Many of the mRNAs that were found to associate with the eIF4E2 complex, through RNA immunoprecipitation, such as EGFR and platelet derived growth factor receptor alpha (PDGFRA) harbour these rHREs and play a functional role in the hallmarks of cancer. The hypoxic translation

of these select mRNAs was investigated in U87-MG glioblastoma cells expressing eIF4E2 shRNA using polysome fractionation, a method that isolates actively translating ribosomes via sucrose density centrifugation. It was determined that EGFR and PDGFRA were translated in an eIF4E2- dependent manner under hypoxia (Uniacke et al., 2012).

In contrast, Zuberek et al. (2007) has demonstrated that eIF4E2 binds to the 5’ cap with a very low affinity (30 – 100 fold lower than that of eIF4E) (Zuberek et al., 2007). This prevents competition for the cap between eIF4E and eIF4E2, which therefore inhibits translation via eIF4E2 under normoxia since it is less efficient (Zuberek et al., 2007). However Yi et al. (2013) argued that eIF4E is still active under hypoxic conditions and is induced by HIF-1α (Yi, Papadopoulos,

Hagner, & Wagner, 2013). This observation may hold true in acute hypoxia where HIF-1α is more pronounced, but in chronic hypoxia HIF-1α levels decrease and HIF-2α predominates (Holmquist-

Mengelbier et al., 2006). Interestingly, by knocking down HIF-1α, eIF4E2 expression is not attenuated under hypoxia; however eIF4E is reduced (Yi et al., 2013). This supports the findings by Uniacke et al. (2012) that HIF-2α is required for eIF4E2 activity within the cell. Yi et al. (2013) also observed that eIF4E promotes the translation of specific transcripts, such as c-Myc, cyclin D1 and eIF4G1 in a HIF-1α-dependent manner. This suggests that certain mRNA transcripts involved in cancer proliferation and survival are translated via different eukaryotic initiation factors under hypoxia. Furthermore it supports the idea that eIF4E-mediated translation alone is insufficient for adaptation under hypoxic conditions (Uniacke et al., 2012). When eIF4E2 was silenced via shRNA, tumors grew poorly in nude mice xenografts, compared to the control (Uniacke et al.,

2014). Moreover, in vitro experiments demonstrated that eIF4E2 inhibition in spheroids could not exceed a diameter of 500 µm and were loose, fragile and fully oxygenated (Uniacke et al., 2014).

This observation suggests that eIF4E2 is involved in the production of cell-cell adhesion proteins,

such as cadherins and proliferation or survival factors. As discussed previously, there is evidence that select cadherins are known mRNA targets of eIF4E2-directed translation as shown through

PAR-CLIP analysis (Uniacke et al., 2012).

1.7 The Role of Hypoxia in Tumor Migration and Invasion Cadherins are cell-cell adhesion molecules that play an essential role in normal cellular processes but are also involved in pathogenic events such as tumor progression. A switch in cadherin profiles governs the process of epithelial to mesenchymal transition (EMT), which is common during embryonic development, organogenesis, wound healing and repair but is also involved in the early stages of malignant transformation. During EMT, cells lose E-cadherin, which is an epithelial marker and upregulate mesenchymal markers such as N-cadherin among others. Ultimately, this reduction in E-cadherin (also known as CDH1) allows cells to detach from neighbouring cells, acquire a spindle-shaped morphology and metastasize or invade tissues.

Hypoxia has been shown to repress E-cadherin through increasing the expression of its transcriptional repressors, SNAIL and SLUG (Imai et al., 2003; Zhang et al., 2013). Although hypoxia modulates the transcription of genes, it also reduces the global rate of mRNA translation in an attempt to conserve energy. However select mRNA transcripts that harbour rHRE sequences are able to escape mTOR-mediated repression. One of these transcripts is known as Cadherin 22

(CDH22) is a cell-cell adhesion molecule. Through RNA immunoprecipitation it was identified as a target of eIF4E2-directed translation and thus may be translated in an eIF4E2-dependent manner under hypoxia (Uniacke et al., 2012). CDH22 is involved in mammalian neural development but has also been associated with increased migration and invasion in human colorectal cancer (J.

Zhou et al., 2009). Its role in hypoxic tumor progression has not been investigated.

Mayer et al. 2010, examined the role of CDH22 expression in the developing mouse brain.

It was determined that in embryos between embryonic day 15.5 and birth, there is a significant 3- fold increase in CDH22 expression at the transcript level. Prior to this, at day embryonic 12.5, there was also an increase in the level of CDH22 expression (Mayer et al., 2010). Interestingly,

Lee et al. has shown that the developing mouse brain is extremely hypoxic during this period of development. This is due to the extensive proliferation and migration of vascularizing endothelial cells to secrete ventricular fluid into the fourth ventricle of the brain (Lee et al., 2001). Perhaps the upregulation of CDH22 observed by Mayer et al. may be attributed to extensive proliferation and hypoxia during embryonic neural development.

Besides embryonic development, CDH22 is also involved in the migration and invasion of cancer cells. CDH22 over-expression at the mRNA and protein level has been observed in colorectal cancer and is associated with increased migration and invasion (J. Zhou et al., 2009).

There is also evidence to support that the loss of CDH22 in metastatic melanoma is associated with tumor progression and a more aggressive phenotype (Piche et al., 2011). Interestingly and in agreement with our hypothesis, Piche et al. observed that significantly fewer metastatic melanomas stained positive for CDH22 than dysplastic nevi or primary melanomas. Indicating that CDH22 expression plays a more important role in the migration and invasion of melanoma than during early tumorigenesis (Piche et al., 2011). Piche et al. also determined that the expression of CDH22 at the protein level among seven melanoma cell lines under normoxia was reduced. Moreover, they compared CDH22 staining between thick (≥ 2 mm) and thin (< 2 mm) sections of primary human melanomas and discovered that thick primary melanomas were more often CDH22 negative. Given that the diffusion limit of oxygen is about 1 mm in human tissue, hypoxia may have been present in these samples but was not examined. Piche et al. also argue that the loss of

CDH22 gives cancer cells a more mesenchymal phenotype and might increase in primary tumors to facilitate cell-cell adhesion and therefore limit migration and invasion. There is additional evidence to support this claim by Zhou et al. who determined that CDH22 expression was strongest in primary colorectal tumors but also observed this phenomenon in lymph node metastases.

Together, these results suggest that the role of CDH22 in cancer may be tissue and stage specific.

Figure 3. The proposed hypoxic switch between cadherins during tumor progression. Epithelial to Mesenchymal Transition (EMT) is characterized by a change in cadherin profiles from classical cadherins such as E-cadherin, to mesenchymal cadherins, such as N- cadherin. Hypoxia represses E-cadherin and may increase the expression of other cadherins such as CDH22 which have been shown to aid in metastasis and invasion. (A) During the initial stages of transformation and early on in hypoxia, E-cadherin levels remain stable and are highly expressed, facilitating contact between cells. (B) As the cells become more hypoxic, E-cadherin expression is repressed and the cells begin to lose cell-cell contact. In order to break off from the primary tumor, cells may undergo a “hypoxic switch” in their cadherin profile and increase the expression of cadherins such as CDH22, which may aid in migration (C) As hypoxia reaches a chronic state, CDH22 expression may increase and the cells acquire a more mesenchymal phenotype, becoming longer and more spindle-like which aids in invasion.

Nevertheless, a switch in cadherin profiles during EMT also promotes the invasion of cancer cells under hypoxia. It is well established that hypoxia supresses E-cadherin, leading to enhanced cell mobility and invasion (Chen et al., 2012; Jing et al., 2013). Mesenchymal cadherins such as CDH11, or osteoblast-cadherin, increase heterotypic cadherin-mediated interactions with endothelial and stromal cells (van Roy, 2014), which suggests that they may stimulate local invasion (van Roy et al., 2014). Interestingly, cadherin profiles may also predict the sites at which invasion occurs. For example, Huang et al. found that when CDH11 is upregulated in prostate cancer, it stimulates the expression of several invasion-related genes but also facilitates interactions with osteoblasts (Huang et al., 2010). When seeded onto a layer of osteoblasts, prostate cancer cells expressing CDH11 were able to extend filopodia, which are cellular extensions, into the osteoblast layer (Huang et al., 2010). This may explain why bone metastasis and invasion are very common among prostate cancer patients (Huang et al., 2010). It is also possible that this environment enhances cadherin activity, since cadherins are calcium-dependent adhesion molecules. Given that the amino acid sequence of CDH22 shares 51.4% homology with CDH11, perhaps the same phenomenon occurs, where CDH22-expressing cancers prefer sites of high

CDH22 expression for metastasis and invasion such as the pituitary and brain, due to cadherin- mediated interactions.

In a mouse model of surgical orthotopic implantation, where CDH22 was knocked down and compared to a control group, metastases were only found in the lung, liver, lymph nodes and pancreas (Zhou et al., 2009). However in the knockdown group, tumors were undetectable in the lung or liver (Zhou et al., 2009). The reason for this organotropism during metastasis remains unclear but there is evidence to show that CDH22 expression leads to a more invasive phenotype in colorectal cancer (Zhou et al., 2009). Knockdown of CDH22 in colorectal cancer cells reduces

invasion by 2.65 fold, compared to Mock cells (Zhou et al., 2009). Mock cells were wild-type cells that harboured control siRNA against CDH22. To date, the mechanism behind CDH22 and its role in invasion remains unknown. However, in order to invade tissues, cancer cells must not only make contact with the endothelial cells and stroma but also degrade the surrounding basement membrane and extracellular matrix (ECM).

It is well known that extensive extracellular matrix remodelling occurs during hypoxia

(Gilkes et al., 2014). ECM remodelling is controlled by matrix metalloproteinases (MMPs) which include: collagenases, gelatinases, stromelysins and cell-membrane bound MMPs, each with different substrate specificities (Gilkes et al., 2014). HIFs lead to the activation of a robust transcriptional program that allows cancer cells to degrade the basement membrane and promote invasion (Gilkes et al., 2014). Hypoxia has been shown to stimulate breast cancer invasion using the highly invasive breast cancer cell line MDA-MB-231 through activating MT1-MMP and

MMP-2 (Munoz-Najar, 2006). When MMP inhibitors were employed during hypoxic experiments, it resulted in the repression of invasion (Munoz-Najar et al., 2006) suggesting that

MMPs play an essential role in the hypoxic invasion of breast cancer cells. Munshi et al. have proposed a model in which they suggest that MMPs can regulate the function or the expression of

E-cadherin (Munshi & Stack, 2006). This model states that the activated proteinases disrupt cell- cell junctional integrity via ectodomain catalysis and shedding of E-cadherin either by interfering with the stability of the cadherin-catenin complex or by stimulating Snail expression which represses E-cadherin (Munshi & Stack, 2006). In support of this hypothesis, hypoxia also stimulates Snail expression and E-cadherin repression (Sun et al., 2015).

1.8 Targeting the Hypoxic Tumor Microenvironment and eIF4E2 in Cancer Therapy A substantial amount of progress has been made in the field of translation and its role in cancer. Translational control directly affects the synthesis of proteins involved in processes such as invasion, proliferation, angiogenesis, metastasis and survival. It is also well established that translation underlies both spontaneous and sporadic cancer formation along with numerous ribosomopathies with a predisposition for cancer development (Silvera, Formenti, & Schneider,

2010). Much of the research in oncology to date has focused on targeting the protein machinery that normal cells use. However, this has led to many problems; the major one being how does one inhibit protein synthesis in a tumor, without affecting surrounding tissue? Alternative cap- dependent protein synthesis machinery induced via hypoxic stress such as the HIF-2α- RBM-4- eIF4E2 complex may allow researchers to target protein synthesis that is limited to hypoxic areas within the body, such as the core of tumors where drug delivery is difficult, due to poor vascularization. In a way, this is similar to the development of antibiotics, which target only bacterial protein synthesis and not that of the human host. Targeting the HIF-2α-RBM-4-eIF4E2 complex would not halt global protein synthesis completely but would have a significant effect on mRNA transcripts which harbour an rHRE sequence such as EGFR, PDGFRA and CDH22, which are involved in the hallmarks of cancer.

Regardless of the fact that eIF4E is commonly elevated in tumors, no eIF4E specific therapy has been developed to date (Graff et al., 2007). eIF4E remains an attractive target in cancer therapy and may be useful in reducing the expression of select mRNAs such as c-Myc and Cyclin

D1. Graff et al. (2007) report that eIF4E-specific antisense oligonucleotides delivered intravenously, significantly reduced eIF4E expression in human xenografts thereby supressing tumor growth (Graff et al., 2007). Even though eIF4E expression was reduced by 80% in mouse hepatocytes, there were no signs of illness, liver enzyme function, stress or a change in body weight

(Graff et al., 2007). In contrast, Uniacke et al. (2014) used a direct approach and showed that glioblastoma and colorectal carcinoma xenografts that were injected with lentiviral shRNA- targeting eIF4E2 had a reduced volume compared to controls (Uniacke et al., 2014). More importantly, eIF4E2-depleted cells in normoxic conditions showed no negative effects (Uniacke et al., 2014). Thus eIF4E2 may be an ideal and novel target for cancer therapy, directed specifically towards poorly oxygenated solid tumors, without harming the surrounding oxygenated tissue. On the outer edge of the tumor, where oxygen is still present enabling eIF4E activity, mTOR signalling persists. mTOR signaling has been an attractive target in cancer therapy since the early 1990s due to the development of rapamycin, an mTOR inhibitor, but only a few drugs have been developed to target this pathway (Yuan et al., 2009). The use of mTOR inhibitors in combination with other drugs has the potential to induce strong anticancer effects. Preclinical data have supported the pivotal role of mTOR in cancer progression and led to the development of cancer therapeutics

(Yuan et al., 2009). Two small molecule inhibitors of mTOR in renal cell carcinoma have been licensed to date: temsirolimus and everolimus (both analogues of rapamycin)(Yuan et al., 2009).

These drugs have been extensively studied in Renal Cell Carcinoma (RCC).

Besides mTOR inhibitor development, RCC has also been useful in hypoxic studies because of its characteristic genetic lesion, the loss of VHL function (Semenza, 2003). The loss of

VHL causes HIF-1α and HIF-2α to accumulate within the cell and the transcripts are regulated in an oxygen-independent manner (Semenza, 2003). This loss of VHL function makes RCC a good candidate for HIF targeted therapy. However, some RCC cell lines such as 786-O, only express

HIF-2α but not HIF-1α (Semenza, 2003). Therefore, it is important to consider cancer patients individually and know their mutational status. In glioblastoma, increased HIF-1α expression has been correlated with PTEN loss of function and EGFR gain of function. PTEN loss of function

mutations increase HIF-1α levels (Semenza, 2003). Since its discovery by Semenza et al. (1997), there have been several attempts to identify inhibitors of HIF-1α. Inhibitors of HIF could decrease mRNA levels, decrease protein synthesis, increase degradation, decrease subunit heterodimerization, decrease binding to DNA and decrease transcriptional activity (Semenza,

2013). Therefore, targeting the HIF pathway could have a plethora of off-target effects that would be restricted to hypoxic areas.

Healthy adults do not have regions of chronic hypoxia. This is a transient event under normal physiology and a drug that specifically targets hypoxic protein synthesis would not harm the primary normoxic protein synthesis machinery. In addition, eIF4E2 is 5 to 10 times less abundant than eIF4E, which would limit the potential negative side effects of an eIF4E2-targeted therapy (Rom et al., 1998). Also, the fact that the primary protein machinery is repressed under hypoxia through mTOR, adds an interesting avenue for drug development. Hypoxia sequesters eIF4E and its nuclear import factor, Eukaryotic Translation Initiation Factor 4E Transporter (4E-

T) to the nucleus, thus directly impacting the translation initiation machinery and serving as a form of protection (Wouters & Koritzinsky, 2008). Unlike eIF4E, eIF4E2 does not shuttle through the nucleus through 4E-T but in a chromosome maintenance 1 protein homolog (CRM1)-dependent manner (Kubacka et al., 2013). Although, it is unknown whether eIF4E2 undergoes sequestration during hypoxia, it is unlikely since it has been found in the cytoplasm of hypoxic cells and orchestrates hypoxic cap-dependent translation.

Uniacke et al. have demonstrated that the delivery of shRNA targeting eIF4E2 through a lentiviral vector significantly decreases tumor volume in a mouse model (Uniacke et al., 2014).

Modern cancer therapies that target protein synthesis expose cancer patients to a variety of extremely toxic and harmful side effects. Thus, the development of safer and more specific protein

synthesis inhibitors is required. In the first study of oral everolimus (a common mTOR inhibitor) on solid tumors, it was reported that 66% of patients experienced gastrointestinal toxicity (Donnell et al., 2008). Studies on other mTOR inhibitors such as temsirolimus, on solid tumors have reported side effects such as mucositis, anorexia, dehydration, hyperglycemia and hypertriglyceridemia (Fleming et al., 2012) (Piatek et al., 2014). The effects of temsirolimus have been well characterized due to its use in organ transplantation as an immunosuppressive agent.

Tesirolimus is associated with pulmonary toxicity, however the underlying mechanisms of toxicity remain unclear (Duran et al., 2006). The combined effects of immunosuppression and pulmonary toxicity predispose patients to pulmonary infections, which may lead to serious complications

(Duran et al., 2006). Therefore the need for alternative protein synthesis inhibitors with greater specificity and limited side effects are crucial to the advancement of modern cancer therapy. The development of an eIF4E2 inhibitor may be a safer alternative to current therapies, due to greater specificity, which may also limit side effects and improve treatment outcomes.

1.9 Experimental Objectives There are six core hallmarks of cancer: sustained proliferative signaling, evasion of growth suppression, activation of invasion and metastasis, enablement of replicative immortality, resistance to cell death and induction of angiogenesis (Hanahan & Weinberg, 2011). The tumor microenvironment supports these hallmarks and contributes to tumorigenesis (Hanahan &

Weinberg, 2011). As tumorigenesis occurs, there is an increase in proliferation and thus an increase in the demand for oxygen, which results in hypoxia. This is accompanied by a hypoxic switch in the protein synthesis machinery, as demonstrated by Uniacke et al. (2012), where eIF4E2 interacts with its binding partners, HIF-2α and RBM-4 forming a complex that binds to rHREs on select mRNAs. Through RNA immunoprecipitation, a number of direct eIF4E2 targets were identified. eIF4E2 targets such as CDH22, EGFR and PDGFRA harbour rHREs in their 3’ UTRs, which allow

them to escape mTOR-mediated repression under hypoxia (Uniacke et al., 2012). These genes have been implicated in several hallmarks of cancer. The objective of this study is to examine the role of eIF4E2-directed hypoxic protein synthesis in a panel of human cancer cell lines in regards to autonomous proliferation, invasion and metastasis based on the previously mentioned eIF4E2 targets. All experiments in this study will be performed under hypoxia (1% O2) and normoxia

(21% O2). Therefore, the hypothesis of this study is that eIF4E2-directed hypoxic protein synthesis is required for autonomous proliferation, migration and invasion during tumor progression.

To test this hypothesis, the aims of this thesis are as follows:

Aim 1: To examine the role of eIF4E2-mediated translation in the autonomous proliferation of breast, glioblastoma and colorectal cell lines.

This will be achieved through Bromodeoxyuridine (BrdU) assays using cell lines that harbour shRNA against eIF4E2. The cells will be starved to stimulate autonomous proliferation,

BrdU will be added to the cells and fluorescence microscopy will be used to analyze BrdU incorporation. Polysome profiling will be used to examine the association of transcripts involved in autonomous proliferation such as EGFR and PDGFRA with polysomes. Thus the role of eIF4E2 in autonomous proliferation of cancer cells will be examined.

Aim 2: To examine the role of eIF4E2-mediated translation in the migration and invasion of breast, glioblastoma and colorectal cell lines.

This will be achieved through standard scratch wound assays. A monolayer of cancer cells harbouring shRNA against eIF4E2 will be scratched and wound closure will be monitored over time to determine the role of eIF4E2 in migration. This will be followed by Boyden Chamber

Migration Assays where the same cells will be placed in a two-chamber system and will be

attracted via a chemoattractant to migrate through pores in a membrane. The number of migrated cells will then be assessed. To examine the functional significance of CDH22, a bona fide target of eIF4E2, in migration, a CDH22 neutralizing antibody will be employed and these experiments will be repeated. In addition, polysome profiling will be used to examine the role of eIF4E2- mediated translation of CDH22 during hypoxia. The translation of CDH22 is predicted to play an important role in migration but is also expected to be translated in an eIF4E2-dependent manner under hypoxia.

Invasion will be examined by employing the same two-chamber system as the Boyden

Chamber but with the addition of a Reduced Growth Factor Matrigel layer, which the cells are required to invade. Again, the number of invaded cells will be assessed. To examine the functional significance of CDH22 in invasion, CDH22 neutralizing antibody will be employed and these experiments will be repeated. The translation of CDH22 is predicted to play an important role in invasion during hypoxia.

Chapter 2 - Materials and Methods

2.1: Cell Culture MDA-MB-231 (HTB-26), U87-MG (HTB-14) and HCT-116 (CCL-247) cells were obtained from the American Type Culture Collection. These particular cell lines were chosen based on their genetic backgrounds, MDA-MB-231 (p53 mutation), U87-MG (PTEN and

EGFRvIII mutation) and HCT-116 (KRAS mutation). This will provide a unique platform to investigate the role of eIF4E2-mediated hypoxic translation in the presence of common genetic mutations acquired in human cancers. These cell lines have also been used in hypoxic studies and endogenously express HIF-2α, RBM-4 and eIF4E2, which makes these cell lines ideal candidates to investigate eIF4E2-mediated translation under hypoxia (Uniacke et al., 2012, Uniacke et al.,

2014). The cells were maintained as suggested in cultured in Dulbecco’s modified Eagle’s medium

(Sigma) and were supplemented with 10% FBS (Sigma). Cells used in experiments were between

3 and 15 passages. For normoxic experiments, the cells were maintained in an incubator under the

º presence of atmospheric air (21% O2), 5% CO2 and 37 C. In order to achieve hypoxic culture conditions, the Whitley H35 hypoxystation was used. In this specialized chamber, the cells were maintained at 1% O2, 5% CO2, 94% N2 and 37 ºC.

2.2: Creation of Stable Cell Lines GIPZ Lentiviral Human eIF4E2 shRNA-mir (ThermoScientific) was used to target the eIF4E2 CDS [V2LHS_68401 short hairpin RNA (shRNA)-1 sequence

TGAACAGAATATCAAA] or the 3’ UTR (V3LHS_405000 shRNA-2 sequence

CAGCTGAGATCACTTAATAA). A non-targeting shRNA in a pGIPZ vector was used as a control. Briefly, 24 hours before transfection, 5x104 cells were seeded into a 6-well plate. 100 μL of plasmid DNA was diluted in 3 mL of growth media supplemented with 7.5% FBS. The cells were then cultured at 37 °C for an additional 24 hours and 1 μg/mL of puromycin was added to

the growth media for selection. Clones were then selected by plating the remaining cells at low confluency and culturing them until colonies were visible. Individual colonies were then isolated with a pipette and cultured in a separate dish. The clones produced are identified by their clone number (KD1 and KD2) and the shRNA that is present in these clones targets the coding sequence or the 3’UTR respectively. Rescue clones were made by transfecting U87-MG eIF4E2 knockdown cells with an eIF4E2 ORF cDNA construct (GeneCopoeia) or a vehicle control containing a neomycin resistance gene. Briefly, 24 hours before transfection, 5x104 cells were seeded into a 6- well plate. 100 μL of plasmid DNA was diluted in 3 mL of growth media supplemented with 7.5%

FBS. The cells were then cultured at 37 °C for an additional 24 hours and 1 μg/mL of G418 was added to the growth media for selection. Clones were isolated in the same manner as the shRNA knockdowns. The eIF4E2 rescue clones were chosen and named (Res1 and Res2) and are both

KD1 rescues which harbour a vector 3’UTR that is not recognized by the endogenous eIF4E2.

These clones also vary in the abundance of eIF4E2 at the protein level. Western blotting was used to verify the stable knockdown or rescue clones.

2.3: Western Blotting Whole cell lysate were collected and then resolved on 12% polyacrylamide gels, except for

CDH22 blots, which were resolved on 10% polyacrylamide gels. Then transferred to PDVF membrane (Fisher), washed with Phosphate Buffered Saline plus Tween (PBS-T) and then blocked for 1 hour in 5% milk in PBS-T. The membranes were then incubated with primary antibody diluted in blocking solution (1:5,000) except for CDH22 (1:3,000), overnight at 4 ºC. Primary antibodies used were: anti-GAPDH (Cell Signaling Technologies, D16H11, Lot Number: 6), anti- eIF4E2 (GeneTex, GTX82524), anti-CDH22 (Aviva Systems Bio, ARP49648_P050), anti-IgG

(Santa Cruz Biotechnology, sc-2027, Lot Number: D1415). The membranes were washed three times for 10 minutes with PBS-T and then incubated at room temperature with secondary 30

antibodies diluted in blocking solution (1:10,000), either horseradish peroxidase- conjugated anti- mouse or anti-rabbit for 1 hour. Secondary antibodies used were: Anti-Rabbit IgG HRP Conjugate

(Promega, W401B), Anti-Mouse HRP Conjugate (Promega, W4028). GAPDH served as a loading control for all experiments.

2.4: Bromodeoxyuridine Assay Cells were grown in 10 cm dishes to 70 – 80% confluency at which point they were trypsinized, counted and seeded (8 X 104 cells/dish) into 6 mm dishes containing three coverslips

(Fisher). Once the cells had reached a confluency of 70% they were either starved in serum-free media or given serum-containing media for another 24 hours. The Bromodeoxyuridine Labeling and Detection Kit I (Roche) was used for all reagents. Bromodeoxyuridine (BrdU) was added to each dish at a final concentration of 1:1000 for 1 hour. The cells were then fixed with a chilled solution containing (750μL of 1 M Glycine, 14.25 mL of H2O and 35 mL of ethanol) and were kept in -20 ºC for 45 minutes. The cover slips were washed three times for 5 minutes with PBS.

They were then covered in anti-BrdU antibody and allowed to incubate at room temperature for 1 hour in a humidified chamber. The washes were repeated and the cover slips were then incubated with Goat Anti-Mouse IgG (Alexa Fluor ®555) at a concentration of (1:1000) for 30 minutes at

37 ºC in a humidified chamber. The washes were repeated and the cover slips were incubated for

7 minutes with Hoechst (1:35000). The washes were repeated and the cover slips were quickly inverted and mounted onto glass slides with ProLong Gold antifade reagent (Life Technologies).

They were maintained at room temperature overnight in the absence of light. The coverslip edges were sealed with nail polish the following day and they were stored at -20 ºC in a freezer box for further analysis. The Nikon Eclipse Ti microscope (Nikon) was used to capture images of the inverted coverslips at 60X magnification with oil immersion.

2.5: Scratch Wound Migration Assay Cells were grown to confluency in 6 well plates. The wells were then washed twice with

PBS and the media was replaced. For hypoxic experiments, the media was pre-conditioned along with the cells for 24 hours prior to scratching. The scratches were induced with a 200 μL pipette tip at a 45º angle. Three scratches were made in each well. Images were taken via light microscopy at 10X magnification using the Nikon Eclipse Ti Microscope (Nikon) and wound closure was measured over 12 hours by measuring three different areas on each scratch via NIS Elements software (Nikon).

2.6: Boyden Chamber Migration Assay All cells were serum starved for 24 hours prior to the experiment in serum-free media. For hypoxic experiments, the media was pre-conditioned along with the cells for 24 hours prior to trypsinization, which also was performed inside the hypoxia chamber. The membranes were coated with 100 μL of fibronectin overnight at 4°C and allowed to dry. 4 X 104 cells were re- suspended in 250 μL of serum-free media and seeded into the upper compartment of the chamber.

The bottom well was filled with 750 μL of media with serum. After 4 hours, the membranes were washed with PBS, fixed with methanol, and stained with crystal violet. A damp cotton swab was used to wipe the cells that did not migrate from the top of the membrane. Five random fields of view were captured via bright field microscopy and the number of migrated cells was then analyzed by counting the number of crystal violet stained cells.

2.7: Matrigel Invasion Assay Invasion Assays were performed with Growth Factor Reduced Matrigel Invasion

Chambers, 8.0 Micron (Corning). For hypoxic experiments, the media was pre-conditioned along with the cells for 24 hours prior to trypsinization which also was performed inside the hypoxia chamber. 4 X 104 cells were re-suspended in 250 μL of serum-free media and seeded into the

invasion chamber. The bottom well was filled with 750 μL of media with serum. After 4 hours, the membranes were washed with PBS, fixed with methanol, and stained with crystal violet. A damp cotton swab was used to wipe the cells that did not invade from the top of the membrane and the number of invaded cells was then analyzed.

2.8: RNA extraction The phenol chloroform method was used to isolate RNA. 1 mL polysome fractions were incubated with 50 μL of Proteinase K solution at 55 ºC for 1 hour and 600 μL of phenol:chloroform:isoamyl alcohol (25:24:1) was added to each fraction. The fractions were then centrifuged for 5 minutes and the aqueous phase was collected. To the aqueous phase, 700 μL of chloroform (Fisher Scientific) was added. Then 60 μL of 3M sodium acetate (pH 5.2) was added, along with 1 mL of absolute ethanol and the samples were precipitated overnight at -20 ºC. The pellets were washed with 1 mL of cold 70% ethanol and the samples were centrifuged at 7500 rpm for 5 minutes at 4ºC. The samples were allowed to dry briefly at 37 ºC and the RNA pellet was re- suspended in 20 μL of RNase-free water.

2.9: Quantitative real-time PCR (qPCR) Total RNA was extracted from 60-70% confluent U87-MG cells under 21% O2 and 1%

O2, using TRIzol reagent (AMRESCO) as described by the manufacturer. Standard qRT-PCR reactions consisting of 2X SsoAdvanced Universal SYBR Green Supermix (Bio-Rad), 1 μM of reverse primer, 1 μM of forward primer, 100 ng of cDNA template and water up to 20 μL were added to a 96-well plate and covered with an optical adhesive lid (Bio-Rad). qRT-PCR was performed in a CFX-96 Real-Time PCR System (Bio-Rad) under the following protocol: An initial denaturation and polymerase activation step at 95 °C was followed by forty cycles of 95°C for 30s and 55°C for 25s. Melt curves were then established at 65 °C for 30s until it reached 95 °C, with a ramp speed of 0.5 °C/cycle. Amplification curves and melting curve data were analyzed using 33

CFX manager software (CFX Manager™ Software, BioRad) for gene expression analysis. All samples had three technical replicates and each experiment had three biological replicates. Gene expression data was normalized to the reference gene RPLPO. Non-template reactions were used as controls. The following primer sets were used for qRT-PCR: CDH1, FW 5’ –

TGCCCAGAAAATGAAAAAGG -3’, RV 5’-GTGTATGTGGCAATGCGTTC-

3’;CDH22,FW5’–TCCCGCAGAAGATGTACCAG-3, RV 5’-GCTGTCTGTGGTGACCTTGA-

3’; RPLPO, FW 5’-AACATCTCCCCCTTCTCC-3’, RV 5’-CCAGGAAGCGAGAATGC-3’.

2.10: Statistical Analyses The mean of three independent experiments is shown where the error bars represent the standard error of the mean. For both hypoxic and normoxic treatments, the knockdown group was compared to the control group using the Student’s t-test, where p = 0.05. In some cases, One-Way

ANOVA was also used assuming equal variances. An asterisk represents a statistically significant difference between groups (p < 0.05). Microsoft excel was used to perform statistical analyses.

Chapter 3 – Results

3.1: HCT-116 cells depend on eIF4E2 for their autonomous proliferation Previously, it was shown by Uniacke et al. that eIF4E2 was required for the hypoxic proliferation of HCT-116 and U87-MG cells (Uniacke et al., 2014). However, the effects of silencing eIF4E2 on the hypoxic autonomous proliferation in these cell lines was not investigated.

In order to assess autonomous proliferation, the HCT-116, MDA-MB-231 and U87-MG cell lines were serum-starved for 3 days and grown to confluency. At this point, a 1% insulin-transferrin- selenium solution was applied and BrdU, a thymidine analogue, was added for 1 hour prior to fixation. Here we show that under hypoxic, serum-free conditions, eIF4E2 is required by HCT-

116 cells but not U87-MG and MDA-MB-231 cells for autonomous proliferation (Figure 4). For the first time, we also show the effects of silencing eIF4E2 in the MDA-MB-231 cell line on proliferation, with and without serum.

Silencing eIF4E2 in HCT-116 cells led to a 30% reduction in normoxic autonomous proliferation, but this effect was more pronounced under hypoxia with a 50% reduction (Figure

4A). Under conditions with serum, no significant differences were observed (Figure 4B and D). In

MDA-MB-231 cells, silencing eIF4E2 did not have a significant effect on autonomous proliferation under hypoxia (Figure 5A) but did significantly impair the ability of these cells to autonomously proliferate under normoxic, serum-free conditions (Figure 5C). In knockdown 1

(KD1), which targets the coding sequence and knockdown 2 (KD2), which targets the 3’ untranslated region, there was a 50% reduction in autonomous proliferation when compared to the control (Figure 5B). In addition, the inhibition of eIF4E2 also significantly impaired the proliferation of these cells under hypoxia with serum (Figure 5C) but had no effect in normoxia with serum (Figure 5D).

Under hypoxic serum-free conditions, U87-MG cells were impaired in their ability to proliferate but this was not statistically significant (Figure 6A). In media with serum, however, the inhibition of eIF4E2 either enhanced the proliferation of U87-MG cells as seen in knockdown 1 or had little effect, as seen in knockdown 2 within the U87-MG cell line (Figure 6D).

Figure 4. BrdU incorporation in HCT-116 cells under hypoxia and normoxia in serum-free and complete media. Quantification of BrdU incorporation in HCT-116 cells harbouring shRNA against eIF4E2 relative to the control cells expressing non-targeting shRNA (A) Hypoxic serum- free media. (B) Hypoxic media with serum (C) Normoxic serum-free media (D) Normoxic media with serum. (E) Immunofluorescence imaging of BrdU incorporation under hypoxic serum-free conditions. Scale bar, 15 μm. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.05 = *, p <0.01 = ** and p < 0.001 = ***). 37

Figure 5. BrdU incorporation in MDA-MB-231 cells under hypoxia and normoxia in serum- free and complete media. Quantification of BrdU incorporation in MDA-MB-231 cells harbouring shRNA against eIF4E2 relative to the control cells expressing non-targeting shRNA (A) Hypoxic serum-free media. (B) Hypoxic media with serum (C) Normoxic serum-free media (D) Normoxic media with serum.(E) Immunofluorescence imaging of BrdU incorporation under hypoxic serum-free conditions. Scale bar, 15 μm. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the (where p < 0.05 = * and p <0.01 = **.

Figure 6. BrdU incorporation in U87-MG cells under hypoxia and normoxia in serum-free and complete media. Quantification of BrdU incorporation in U87-MG cells harbouring shRNA against eIF4E2 relative to the control (A) Hypoxic serum-free media. (B) Hypoxic media with serum (C) Normoxic serum-free media (D) Normoxic media with serum.(E) Immunofluorescence imaging of BrdU incorporation under hypoxic, serum-free conditions. Scale bar, 15 μm. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.05 = * and p <0.01 = **).

3.2: Inhibition of eIF4E2 increases the migration of HCT-116 cells It is well known that hypoxia increases the migration of cancer cells (Neurath et al., 2006)

(Hongo et al., 2013). Hypoxia leads to the transcription of several hypoxia response genes that may aid in migration, however it also activates eIF4E2-mediated translation (Uniacke et al., 2012).

The role of eIF4E2 in cancer cell migration and invasion has not been explored. To assess the effect of eIF4E2 inhibition on the migration of HCT-116 cells, the scratch wound method was used. Cells stably expressing shRNA targeting eIF4E2 were grown to confluency and a scratch was induced with a 200 µL pipette tip. Images were taken at 0 and 12 hours after scratching and the width of the gap between the two leading edges of the monolayer was quantified. eIF4E2 inhibition significantly enhanced the migration of HCT-116 cells, especially under hypoxia

(Figure 7B). Increased migration was not limited to hypoxia, the migration of knockdown 1 increased by 40% under normoxia as well (Figure 7C). However under normoxia, the migration of knockdown 2 was inhibited compared to the control (Figure 7C).

Figure 7. Inhibition of eIF4E2 enhances the migration of HCT-116 cells. (A) The migration of HCT-116 cells during 12 hours in hypoxic media. Scale bar, 300 μm (B) Quantification of migration under hypoxia (C) Quantification of migration under normoxia. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.001 = ***).

3.3: eIF4E2 is required by U87-MG cells for their hypoxic migration and invasion in vitro To determine if eIF4E2 was involved in the migration of U87-MG cells, scratch wound assays were employed using shRNA knockdowns of eIF4E2. The cells were grown to confluency and a wound was created with a pipette tip. The relative average migration of cells was determined by taking images at 0 and 12 hours after scratching and measuring the distance of the gap between the leading edges of the confluent monolayer of cells. Both knockdowns of eIF4E2 were significantly impaired in their ability to fill in the wound over 12 hours compared to the control

(Figure 8A and B). Under normoxia, eIF4E2 knockdown had no effect on migration (Figure 8C and D). Upon re-introduction of exogenous eIF4E2, the migratory impairment observed in the hypoxic migratory experiments with knockdown 1 was rescued. The migration of cells stably expressing exogenous eIF4E2 increased when compared to knockdown 1 but was similar to that of the control (Figure 9A and B). In normoxia, the migration of rescue 2 cells stably expressing exogenous eIF4E2, was slightly enhanced, however this was not statistically significant (Figure

9C).

Further study of the role of eIF4E2 in migration yielded similar results. Another migratory assay was employed, the Boyden Chamber Migration Assay. This requires cells in the upper chamber with serum-free media to undergo haptotaxis and migrate through a porous membrane, coated with fibronectin, towards a lower chamber containing serum. Under hypoxic conditions, the migration of knockdown 1 was significantly impaired with a 6-fold decrease in migration

(Figure 10A and C). Whereas the cells stably expressing exogenous eIF4E2 migrated more, especially rescue 2 (Figure 10C). Under normoxic conditions, knockdown 1, knockdown 2 and rescue 1 were significantly impaired in their migratory abilities, compared to the control (Figure

10C).

Figure 8. Inhibition of eIF4E2 impairs the hypoxic migration of U87-MG cells. (A) Migration of cells over 12 hours in hypoxic-conditioned media, showing the quantification of migration (B) Images showing the hypoxic migration and wound closure over time. (C) The migration of cells during 12 hours in normoxia, showing the quantification of migration (D) Images showing the normoxic migration over time. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.001 = ***).

Figure 9. Re-introduction of exogenous eIF4E2 rescues the loss of migration observed in eIF4E2-depleted cells. (A). Images of hypoxic migration and wound closure over 12 hours. (B) Quantification of migration under hypoxia (C) Quantification of migration under normoxia. Where (CTRL) represents control eIF4E2 shRNA that is non-targeting, knockdown 1 (KD1) targeting the coding sequence or knockdown 2 (KD2) targeting the 3’ untranslated region. Exogenous eIF4E2 is represented by rescue 1 (RES1) and rescue 2 (RES2). Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.001 = ***).

Figure 10. U87-MG cells harbouring shRNA against eIF4E2 exhibit less migration. (A) The migration of U87-MG cells during 4 hours in hypoxic-conditioned media. (B) Protein abundance of eIF4E2 in shRNA knockdowns and rescues from whole cell lysate. GAPDH served as a loading control. (C) Quantification of migration under normoxia and hypoxia. Where (CTRL) represents control eIF4E2 shRNA that is non-targeting, knockdown 1 (KD1) targeting the coding sequence or knockdown 2 (KD2) targeting the 3’ untranslated region. Exogenous eIF4E2 is represented by rescue 1 (RES1) and rescue 2 (RES2). Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p <0.01 = ** and p < 0.001 = ***).

To assess invasion of eIF4E2 knockdowns, a transwell matrigel system was used. Similar to the Boyden Chamber Assay, this system also contains two chambers. The cells are placed in the upper chamber without serum and the lower chamber contains serum. Between them is a layer of matrigel, composed of re-constituted murine extracellular matrix, into which the cells invade. The bottom of this layer is coated with fibronectin, which requires cells to undergo haptotaxis. Hypoxia reduced the invasive ability of U87-MG cells by 2.5-fold (Figure 11C). There was also an increase in invasion by 5-fold and 3.5-fold with regards to rescues 1 and 2 respectively (Figure 11C). In normoxia, cells stably expressing exogenous eIF4E2 were significantly impaired in their invasive abilities. There was a 4-fold and 2-fold decrease in invasion with regards to rescues 1 and 2 respectively (Figure 11C). Rescue 1 and Rescue 2, exhibited differences in their abundance of eIF4E2 protein (Figure 11B).

Figure 11. Inhibition of eIF4E2 impairs the hypoxic invasion of U87-MG cells. (A) The invasion of U87-MG cells during 4 hours in hypoxic-conditioned media. (B) Protein abundance of eIF4E2 in shRNA knockdowns and rescues from whole cell lysate. GAPDH served as a loading control. (C) Quantification of invasion under normoxia and hypoxia. Where (CTRL) represents control eIF4E2 shRNA that is non-targeting, knockdown 1 (KD1) targeting the coding sequence or knockdown 2 (KD2) targeting the 3’ untranslated region. Exogenous eIF4E2 is represented by rescue 1 (RES1) and rescue 2 (RES2). Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.001 = ***).

3.4: Inhibition of CDH22 impairs U87-MG migration but not invasion in vitro Since eIF4E2 inhibition led to a reduction in migration and invasion in the U87-MG cell line, we chose to examine an eIF4E2 target known as cadherin 22 (Uniacke et al., 2012). CDH22 has been shown to increase the migration of colorectal cancer cells (Zhou et al., 2009). However, its role in glioblastoma and hypoxic migration has not been investigated. Here we show that

CDH22 accumulates at the protein level under hypoxia and is undetectable under normoxia (Figure

12C). Quantitative real-time PCR, was used to determine the level of CDH22 mRNA expression.

It was determined that CDH22 decreases at the mRNA level under hypoxia but this is not statistically significant (Figure 12B). Another cadherin was analyzed as a positive control, since it is downregulated transcriptionally under hypoxia CDH1 (Imai et al., 2003). CDH1 expression at the mRNA level decreased, again this was not statistically significant (Figure 12A).

We next investigated whether or not the addition of a neutralizing antibody against CDH1 and CDH22 would affect the migration and invasion of wild-type U87-MG cells. The scratch wound assay was utilized to study migration and images were taken at 0 and 12 hours after scratching. The antibody blockade was achieved by adding neutralizing antibody against CDH1 and CDH22 to the media, immediately after scratch induction. Neutralizing antibodies against cadherins work by binding to the extracellular domain and therefore inhibit typical homotypic interactions. IgG served as a negative control for all experiments. The width of the gap between the leading edges of the monolayer was measured and relative average migration was quantified.

A significant reduction in migration under hypoxia but not normoxia was observed in both CDH1 and CDH22 treated wells (Figure 13B).

To further study the role of CDH22 inhibition in migration and invasion, the Boyden

Chamber Assay was used, as previously discussed but neutralizing antibodies against CDH1 and

CDH22 were added immediately to serum-starved cells in the upper chamber. The migration of cells treated with CDH22 antibody significantly decreased under hypoxia (Figure 14A) but this effect was more pronounced in normoxia where migration was reduced by 67% (Figure 14B). The addition of CDH22 antibody also impaired the invasion of U87-MG wild-type cells. Under normoxia, there was a 1.5-fold reduction in invasion (Figure 14D) but under hypoxia, there was a

5-fold reduction in invasion (Figure 14C). The migration of cells treated with CDH1 antibody significantly decreased under hypoxia but not normoxia (Figure 14A). The invasion of U87-MG wild-type cells was drastically reduced under hypoxia and to a lesser extent in normoxia (Figure

14 C and D).

Figure 12. CDH22 protein accumulates in hypoxia but not the mRNA. (A). Relative mRNA expression of CDH1 from a confluent monolayer of wild-type U87-MG cells under hypoxia and normoxia. RPLPO served as a control. (B). Relative mRNA expression of CDH22 from a confluent monolayer of wild-type U87-MG cells under hypoxia and normoxia. RPLPO served as an endogenous control. (C). Western blot of whole cell lysate from wild-type U87-MG cells showing the protein abundance of CDH22 under both conditions. GAPDH served as a loading control.

Figure 13. The addition of neutralizing antibody against CDH1 and CDH22 impairs the hypoxic migration of U87-MG wild-type cells. (A) Images showing the hypoxic migration of wild-type U87-MG cells treated with CDH22 neutralizing antibody over 12 hours. Bar = 2000 µm. (B) Quantification of normoxic and hypoxic migration, IgG served as a control for all experiments. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.001 = ***).

Figure 14. The addition of neutralizing antibody against CDH22 reduced the migration and invasion of U87-MG cells. (A) The hypoxic migration of U87-MG cells treated with neutralizing antibodies against CDH1 and antibodies against CDH22 (B) The normoxic migration of U87-MG cells treated with neutralizing antibodies against CDH1 and CDH22. (C) The hypoxic invasion of U87-MG cells treated with neutralizing antibodies against CDH1 and CDH22. (D) The normoxic invasion of U87-MG cells treated with neutralizing antibodies against CDH1 and CDH22. The bar graphs represent quantification of migration and invasion from five, random fields of view. IgG served as a negative control for all experiments. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.05 = * and p < 0.001 = ***).

However the results obtained here may not be specific to the role of CDH22 in the migration and invasion of these cells since neutralizing antibody assays may have off target effects and bind other cadherins with a similar structure to cadherin 22. The antibody concentration also varies depending on the batch received by the supplier. A more specific approach, such as shRNA knockdown of CDH22 would be beneficial. Next, we repeated the migration and invasion assays with stable shRNA CDH22 knockdowns in the U87-MG cell line. The migration of CDH22- depleted U87-MG cells was significantly impaired under hypoxia, however the normoxic migration of both knockdown 1 and knockdown 2 was unaffected (Figure 15A-D). Consistent with our observations in the scratch wound assays, the hypoxic migration of cells harbouring shRNA against CDH22 exhibited a reduction in the transwell migration assays (Figure 16A and C). There was a 5-fold reduction in hypoxic migration with respect to knockdowns 1 and 2 (Figure 16C). In normoxia, the migration of knockdown 1 was surprisingly enhanced compared to the control

(Figure 16C and E). The depletion of CHD22 increased invasion under hypoxia in both knockdowns (Figure 16 D and E). The hypoxic invasion of knockdown 1 cells were significantly enhanced by 3.5-fold (Figure 16E). Whereas in normoxia, invasion was reduced in both knockdowns compared to the control (Figure 16). The knockdown of CDH22 also induced changes in morphology (Figure 17A and B). Knockdown 1 cells maintained cell-cell contact and appeared more compact comparable to the control, nevertheless the cells were elongated. In contrast, knockdown 2 cells displayed fewer cell-cell contacts and had very pronounced, elongated spindle- like projections (Figure 17).

Figure 15. Depletion of CDH22 reduces the hypoxic migration of U87-MG cells. (A) Images showing the hypoxic migration of U87-MG cells harbouring shRNA against CDH22 over 12 hours in hypoxic-conditioned media. (B) Quantification of hypoxic migration. (C). Quantification of normoxic migration. Where (CTRL) represents control CDH22 shRNA that is non-targeting, knockdown 1 (KD1) targeting the coding sequence or knockdown 2 (KD2) targeting the 3’ untranslated region. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.001 = ***). (D). Western blot of hypoxic whole cell lysates from U87-MG cells, harbouring shRNA against CDH22. Hypoxic wild- type cells were used as a positive control and GAPDH served as a loading control.

Figure 16. Inhibition of CDH22 impairs the hypoxic migration of U87-MG cells and enhances invasion. (A) The migration of U87-MG cells harbouring shRNA knockdown of CDH22 over 4 hours in normoxia and hypoxia (B) Protein abundance of CDH22 in shRNA knockdowns from hypoxic whole cell lysate. GAPDH served as a loading control. (C) Quantification of migration under normoxia and hypoxia. (D) The invasion of U87-MG cells harbouring shRNA knockdown of CDH22 over 4 hours in normoxia and hypoxia (E) Quantification of invasion under normoxia and hypoxia. Where (CTRL) represents control CDH22 shRNA that is non-targeting, knockdown 1 (KD1) targeting the coding sequence or knockdown 2 (KD2) targeting the 3’ untranslated region. Means are representative of three independent experiments, ± S.E.M. Asterisk represents a significant difference from the control (where p < 0.001 = ***).

Figure 17. Morphology of CDH22-depleted cells under normoxia. (A) Equal amounts of cells were seeded into a 10 cm dish and images were taken once they reached confluency. Where (CTRL) represents control CDH22 shRNA that is non-targeting, knockdown 1 (KD1) targeting the coding sequence or knockdown 2 (KD2) targeting the 3’ untranslated region. Bar = 5,000 µm. Pictures were taken at 40X magnification via bright field microscopy. (B) Equal amounts of cells were seeded into a 10 cm dish and images were taken once they reached confluency. Where (CTRL) represents control CDH22 shRNA that is non-targeting, knockdown 1 (KD1) targeting the coding sequence or knockdown 2 (KD2) targeting the 3’ untranslated region. Pictures were taken of fixed cells on coverslips at 60X magnification via bright field microscopy.

3.6: U87-MG cells do not depend on CDH22 for their proliferation The role of CDH22 in the proliferation of U87-MG cells was also assessed based on previous findings by Zhou et al. who demonstrated that CDH22 knockdown in colorectal cancer cells inhibited proliferation in vivo and in vitro (Zhou et al., 2009). CDH22 knockdowns were grown to confluency on glass cover slips and the BrdU assay was used as previously described.

The proliferation of U87-MG cells harbouring shRNA against CDH22 did not change under hypoxia or normoxia.

Figure 18. Depletion of CDH22 in U87-MG cells does not affect proliferation under hypoxia or normoxia. Quantification of BrdU incorporation in U87-MG cells harbouring shRNA against CDH22 relative to the control (A) Hypoxic proliferation (B) Immunofluorescence imaging of BrdU incorporation under hypoxia. Scale bar, 15 µm. (C) Normoxic proliferation (D) Immunofluorescence imaging of BrdU incorporation under normoxia. Where (CTRL) represents control CDH22 shRNA that is non-targeting, knockdown 1 (KD1) targeting the coding sequence or knockdown 2 (KD2) targeting the 3’ untranslated region. Scale bar, 500 μm. Means are representative of three independent experiments, ± S.E.M.

Chapter 4 – Discussion It is well established that under hypoxia the canonical eIF4E-dependent protein synthesis machinery is repressed by mTOR in order to conserve energy. An alternative cap-dependent translation mechanism involving eIF4E2 and its binding partners HIF-2α and RBM-4 is activated

(Uniacke et al., 2012; Uniacke et al., 2014). This allows select transcripts to escape mTOR- mediated repression and become actively translated under hypoxia. Hypoxic tumor cells exploit this machinery to synthesize cancer-driving proteins during tumor progression (Uniacke et al.,

2014). The transcripts that are translated by eIF4E2 under hypoxia harbour rHREs in their 3’ UTRs and several have been confirmed targets of eIF4E2 (Uniacke et al., 2012; Uniacke et al., 2014;

Timpano & Uniacke, 2016). Some of these transcripts are common receptor tyrosine kinases upregulated in cancer cells, such as EGFR and PDGFRA (Francovic et al., 2007; Oseini & Roberts,

2009). Both of these transcripts have been associated with increased proliferation of cancer cells under hypoxia.

Here, we report that HCT-116 cells require eIF4E2 to autonomously proliferate under hypoxia without the addition of external growth factors (Figure 4). Although the translation of

EGFR and PDGFRA was not assessed in this study, there is evidence to support that inhibition of eIF4E2 abrogates the hypoxic translation of EGFR and PDGFRA (Uniacke et al., 2014). Both of these transcripts play an important role in driving the proliferation of HCT-116 cells (Patel et al.,

2008; Chun et al., 2010). Since EGFR and PDGFRA translation is reduced under hypoxia without eIF4E2, this may explain the observed differences in the autonomous proliferation of HCT-116 cells. Under hypoxia, there was a reduction in autonomous proliferation (Figure 4A). Whereas under normoxia, there was a decrease in autonomous proliferation (Figure 4C). Although eIF4E2- directed translation requires HIF-2α to become stabilized, the reduction in autonomous

proliferation observed in normoxia may be attributed to serum-starvation and a partially active eIF4E complex.

It is important to consider that both of these groups were serum-starved. Similar to how hypoxia represses the standard protein synthesis machinery by inhibiting mTOR, nutrient deprivation also leads to the inhibition of mTOR (Jewell & Guan, 2014). Perhaps the inhibition of mTOR was not as strong under nutrient-deprivation alone in normoxia and eIF4E was partially active. Compared to hypoxic experiments, in which hypoxia and nutrient-deprivation combined, may have increased the inhibition of mTOR and led to a strong inhibition of eIF4E. Making HCT-

116 cells more dependent on eIF4E2 for their autonomous proliferation in hypoxia. In addition,

HCT-116 cells are characterized by a mutation in the K-ras oncogene which remains constitutively active, independent of ligand binding (Simi et al., 2008). KRAS mutations lead to rapid proliferation of cells by stimulating downstream signaling pathways (Liu et al., 2011). However, even the presence of this genetic mutation was not able to overcome the loss of eIF4E2 under both normoxic and hypoxic serum-starved conditions. When these cells were supplied with sufficient external growth factors under normoxia and hypoxia, the observed phenotypes were abolished, suggesting that eIF4E2 is required by HCT-116 cells to autonomously proliferate.

Similar to the HCT-116 cell line, the MDA-MB-231 and U87-MG cell lines are characterized by distinct mutations which may aid in autonomous proliferation and overcome the loss of eIF4E2. MDA-MB-231 cells are characterized by a TP53 mutation, which stimulates the cell cycle and prevents apoptosis (Negrini et al., 1994). This cell line also expresses wild-type

EGFR unlike the U87-MG cell line which harbours an EGFR variant (EGFRvIII) (Wikstrand et al., 1995). EGFRvIII does not have an rHRE sequence and therefore is not translated by eIF4E2.

However, there is evidence to support the fact that EGFRvIII translation is strongly upregulated

under hypoxia (Li et al., 2008). The mechanism behind the hypoxic translation of EGFRvIII remains unclear. It is well established that the hypoxic translation of wild-type EGFR is eIF4E2- dependent (Uniacke et al., 2012). EGFR leads to the activation of downstream signaling pathways such as RAS which induce proliferation.

It has been shown that without eIF4E2, the hypoxic translation of EGFR is reduced in the

U87-MG cell line (Uniacke et al., 2012). This would lead to a reduction in proliferation because downstream signaling pathways would be impaired, resulting in less proliferation. However, in the

MDA-MB-231 cells, which harbour a wild-type EGFR gene, eIF4E2 depletion did not affect hypoxic autonomous proliferation more than normoxic (Figure 5A and C). Although EGFR harbours an rHRE, MDA-MB-231 cells may not depend on eIF4E2 for the hypoxic translation of

EGFR. Further studies are needed such as polysome analysis to determine if EGFR mRNA transcripts actually associate with polysomes under hypoxia in eIF4E2 shRNA knockdowns. Other proliferation assays such as the clonogenic assay would also be beneficial.

In this study, we used the BrdU Assay which only considers the S Phase of the cell cycle.

Since MDA-MB-231 cells have a p53 mutation, proliferation is somewhat deregulated in this cell line. Mutated p53 has been associated with stimulating the cell cycle into S Phase from G1

(Levesque et al., 2005). Therefore it is possible that more cells could have been in the S Phase in the MDA-MB-231 BrdU experiments compared to HCT-116 and U87-MG experiments. HCT-

116 and U87-MG cells harbour wild-type alleles of p53. Regardless of p53 status, U87-MG cells displayed a decrease in autonomous proliferation under normoxia and hypoxia; however this was not statistically significant (Figure 6A and C). In comparison, the inhibition of eIF4E2 increased proliferation in media with serum under normoxia and hypoxia. This increase in proliferation, which was heightened in hypoxia, may be attributed to an increase in EGFRvIII translation, which

is able to compensate for the depletion of eIF4E2 and stimulate downstream signaling pathways.

Therefore, unlike the colorectal cell line, these cell lines do not depend on eIF4E2 for their hypoxic autonomous proliferation.

The second aim of this study was to characterize the role of eIF4E2 in the migration and invasion of cancer cells. We have also shown that U87-MG cells, but not HCT-116, are dependent on eIF4E2 for their hypoxic migration. The depletion of eIF4E2 actually enhances the migration of HCT-116 cells under hypoxia and normoxia. In hypoxia, both knockdowns exhibit significantly enhanced migration (Figure 7B) suggesting that eIF4E2 may not be involved in the migration of

HCT-116 cells. The hypoxic migration of U87-MG cells was shown to be eIF4E2-dependent

(Figure 8). When exogenous eIF4E2 was re-introduced into these cells, the reduction in hypoxic migration was rescued (Figure 9). Therefore we carried out further studies of migration and invasion in these cells using Boyden Chamber Migration Assays which yielded similar results. We confirmed that the hypoxic migration of U87-MG cells was indeed eIF4E2-dependent, where the migration of knockdown 1 was drastically reduced compared to controls (Figure 10).

The observations made here suggest that excess eIF4E2 can play an inhibitory role in the migration of U87-MG cells under normoxia but not hypoxia (Figure 10C). This is consistent with the literature which has characterized eIF4E2 as a translational repressor under normoxia. eIF4E2 has been shown to repress translation under normoxia in Drosophila melanogaster development

(Cho et al., 2005). Moreover, Morita et al. have demonstrated that eIF4E2 associates with Grb10- interacting GYF protein 2 (GIGYF2) to repress translation during mammalian embryonic development (Morita et al., 2012). Although the GIGYF2-eIF4E2 translational repressor complex has not been investigated in U87-MG, an interaction between GIGYF1, Grb10 and Insulin-Like

Growth Factor Receptor 1 (IGF1-R) has been identified (Giovannone et al., 2003). Giovannone et

al. determined that Grb10, an adaptor protein, along with GIGYF1, are recruited to the cell surface and bind to IGF1-R. Thus participating in downstream signaling, upon activation of IGF1-R, through ligand binding (Giovannone et al., 2003). GIGYF1 and GIGYF2 share the same 17 amino acid GYF motif that facilitates binding to Grb10 (Giovannone et al., 2003). Recently, IGF1-R a bona fide target of eIF4E2, has been shown to increase the migration of U87-MG (Zhou et al.,

2016). In addition, the use of an IGF1-R specific inhibitor, PQ401, significantly reduced the migration of U87-MG cells under normoxia ( Zhou et al., 2016).

The decrease in migration observed in our study may be attributed to the decrease in the hypoxic translation of IGF1-R in eIF4E2-depleted U87-MG cells. Whereas the decrease in migration of U87-MG eIF4E2 rescues may be attributed to enhanced GIGYF2-eIF4E2 interactions within the cytoplasm. Since IGF1-R is upregulated under hypoxia, it is possible that there is less

IGF1-R disribution across the cell membrane during normoxia (Nurwidya et al., 2014). This alone would decrease normoxic migration, since IGF1-R increases the migration of U87-MG cells. A reduction in IGF1-R at the cell surface would decrease the recruitment of GIGYF2 to the cell membrane, therefore it would remain distribited throughout the cytoplasm, increasing its potential to interact with eIF4E2 and therefore repressing normoxic translation. The eIF4E2 rescues display significantly higher amounts of eIF4E2 and thus more would be available to participate in the formation of a GIGYF2-eIF4E2 translational repressor complex. This is not the case in hypoxia, where additional eIF4E2 aids in the migration of cells (Figure 10). Polysome analysis of the rescues under normoxia and hypoxia would cofirm that the the hypoxic translation of IGF1-R increases.

Table 1: eIF4E2-depedence of genetically distinct human cancer cell lines on autonomous proliferation, migration and invasion

Autonomous Migration Invasion proliferation U87-MG No Yes Yes HCT-116 Yes No N/A MDA-MB-231 No N/A N/A

We were also interested in characterizing the role of CDH22 in U87-MG cell hypoxic migration and invasion as this has not been explored. Here we show that the migration and invasion of U87-MG cells is dependent on CDH22. The expression of CDH22 at the mRNA level did not change significantly under hypoxia or normoxia, however the protein levels were higher. CDH22 protein was undetectable in normoxia but was significantly higher under hypoxia (Figure 12C).

This suggests that CDH22 is under translational and not transcriptional control. Scratch wound assays with wild-type U87-MG cells treated with neutralizing antibody against CDH22 showed that the hypoxic migration of cells was significantly impaired. Furthermore, the addition of neutralizing antibody against CDH22 in Boyden Chamber Migration and Invasion Assays revealed that normoxic migration and invasion were significantly impaired (Figure 14). A greater effect was observed in hypoxic invasion, compared to hypoxic migration which prompted further study of the role of CDH22 in these processes.

As with any antibody blocking assay, it is important to consider that neutralizing antibodies may have off-target effects and may not be specific to select targets such as cadherins. Especially since CDH22 shares homology with other classical cadherins, such as cadherin 11. Therefore stable shRNA knockdowns of CDH22 were created and verified by Western Blotting (Figure

15D). Scratch wound assays with the CDH22 knockdowns revealed a 2-fold reduction in the hypoxic migration of knockdown 2 but not knockdown 1 cells (Figure 15C). This was similar to

the migration results obtained in eIF4E2-depleted cells under hypoxia. Further study of the role of

CDH22 in the migration of U87-MG cells using the Boyden Chamber Migration Assay demonstrated that CDH22-depleted cells showed a 5-fold reduction in their hypoxic migration

(Figure 16A and C). However, unlike the scratch wound assays, normoxic migration was also significantly impaired (Figure 16A and C). Zhou et al. observed that knockdown of CDH22 in colorectal cancer significantly impaired the migration of cells under normoxia (Zhou et al., 2009).

The fact that CDH22 is undetectable in U87-MG cells at the protein level in normoxia suggests that this protein may be more abundant in other cell lines such as the colorectal cell line SW480.

In addition, the CDH22-depleted cells had fully functional eIF4E2, despite CDH22 shRNA knockdown. Thus it is possible that they were able to synthesize hundreds of other hypoxic- response mRNAs that may have compensated for the loss of CDH22. Nevertheless, a decrease in migration was still observed in both hypoxia and normoxia, which highlights a dual role of CDH22 under two different oxygen tensions in the migration of U87-MG cells.

In addition, the invasion of CDH22-depeleted cells was enhanced under hypoxia (Figure

16 D and E). This observation was different from the antibody blockade experiments, which demonstrated a decrease in invasion, but as previously discussed, the use of antibodies may result in non-specific binding. The invasion of CDH22-depleted cells was also different from what was observed in eIF4E2-depleted cells. In the CDH22-depeleted cells, there is fully functioning eIF4E2. Hypothetically, eIF4E2-depleted cells are not able to synthesize hypoxia-response mRNAs under hypoxia however CDH22-depleted cells are still able to synthesize these proteins due to a fully functioning eIF4E2-mediated translation complex. There were several genes identified through RNA immunopreciptation that are considered eIF4E2 targets, some of which are involved in invasion, such as: L1 cell adhesion molecule (L1CAM), basal cell adhesion

molecule (BCAM), metadherin (MTDH), ADAM metallopeptidase domain 11 (ADAM11) and

ADAM metallopeptidase domain 21 (ADAM21) among others (Uniacke et al., 2012). For example, L1CAM is involved in the tumor invasive front where it is cleaved by A disintegrin and metalloproteinases (ADAMs) producing soluble L1CAM (Kiefel et al., 2012). It also interacts with surrounding integrins on adjacent tumor cells, stromal cells or leukocytes leading to the activation of NFkB, promoting invasion (Kiefel et al., 2012). Metadherin is associated with increased invasiveness in breast cancer by upregulating Snail and Slug, transcriptional repressors of E- cadherin (Li et al., 2011). In addition, CDH22-depletion induced phenotypic changes in U87-MG cells, which may aid in migration and invasion (Figure 17). Knockdown 1 cells remained in close contact, comparable to the control but they were elongated. In contrast, knockdown 2 displayed fewer cell-cell contacts and had elongated spindle-like projections, which may be responsible for the enhanced invasion that was observed in CDH22-depleted cells under hypoxia (Figure 17).

However, further experiments using collagen-coated instead of fibronectin-coated Transwell

Invasion Assays would be required to fully characterize the role of CDH22 in invasion.

Fibronectin, although attached to collagen, is located beneath the collagen layer in the ECM.

Therefore during invasion in vivo, cells must invade the collagen layer before reaching the fibronectin layer in the ECM. Taken together, these results suggest that CDH22 is required for the hypoxic migration of U87-MG cells and enhances the hypoxic invasion of U87-MG cells. Lastly, we chose to investigate whether or not CDH22 was involved in the proliferation of U87-MG cells based on previous findings by Zhou et al. who demonstrated that CDH22 knockdown inhibited the proliferation of SW480 colorectal cancer cells (Zhou et al., 2009). Here we show that proliferation did not change under hypoxia or normoxia within the CDH22-depleted cells (Figure 18). Although the role of CDH22 in proliferation is poorly understood, it may be cell line or tumor specific.

Table 2: CDH22-depedence of the U87-MG cell line on proliferation, migration and invasion

Proliferation Migration Invasion

U87-MG No Yes No

Chapter 5 – Summary The aims of this thesis were to investigate the role of eIF4E2-directed translation in the autonomous proliferation, migration and invasion of HCT-116, U87-MG and MDA-MB-231 cell lines. We determined that HCT-116 cells require eIF4E2 in order to autonomously proliferate.

U87-MG and MDA-MB-231 cells autonomously proliferate in an eIF4E2-independent manner.

Here, we also show that HCT-116 cells do not depend on eIF4E2 for migration and the loss of eIF4E2 actually enhanced the migration of these cells. However, U87-MG cells were dependent on eIF4E2 for their hypoxic migration. U87-MG cells were also dependent on eIF4E2 for their hypoxic invasion. When eIF4E2 was re-introduced, the reduction in migration and invasion were restored. Interestingly, we have also shown that eIF4E2 in excess, plays an inhibitory role in translation, especially under normoxia. This suggests that eIF4E2 may be an ideal target of cancer therapy. Targeting eIF4E2 would be specific to hypoxic areas, such as the core of tumors and may result in decreasing metastases and invasion in glioblastoma.

We also characterized the role of CDH22, a bona fide target of eIF4E2, in U87-MG cells.

It was determined that U87-MG cells depend on CDH22 for their hypoxic migration but not invasion. CDH22-depletion also induced morphological changes which may enhance the invasion of glioblastoma cells, suggesting that the loss of CDH22 enhances invasion. However, further invasion studies are warranted. Moreover, CDH22-depletion did not affect cellular proliferation under hypoxia or normoxia. Taken together, these results suggest that CDH22 is involved in the migration and invasion of U87-MG cells and this may be eIF4E2-dependent. A mouse xenograft model using CDH22-depleted cells would be useful to investigate the role of CDH22 during tumor progression in vivo. Overall, this research has led to a deeper understanding of migration and invasion in cancer. It has also improved our understanding of cadherin 22 and advanced our

understanding of eIF4E2-directed translation under different oxygen tensions. The development of an eIF4E2 inhibitor would be specific to hypoxic areas such as the core of tumors and leave the standard protein synthesis machinery unharmed. Besides cancer, eIF4E2 may also serve as an attractive therapeutic target in other ischemic diseases such a stroke, cardiac and pulmonary diseases.

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