p53, CLIC, AND THE JAK/STAT PATHWAY: INVESTIGATING THE LINK BETWEEN CANCER STRESSES AND CELL DEATH IN DROSOPHILA MELANOGASTER

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1 Chang 1 p53, CLIC, AND THE JAK/STAT PATHWAY: INVESTIGATING THE LINK BETWEEN CANCER STRESSES AND CELL DEATH IN DROSOPHILA MELANOGASTER A Thesis Presented to The Honors Tutorial College Ohio University In Partial Fulfillment of the Requirements for Graduation from the Honors Tutorial College with the degree of Bachelor of Science in Biological Sciences by Samantha J. Chang May 2014

2 Chang 2 This thesis has been approved by The Honors Tutorial College and the Department of Biological Sciences Dr. Soichi Tanda Professor, Biological Sciences Thesis Adviser Dr. Soichi Tanda Honors Tutorial College, DOS Biological Sciences Jeremy Webster Dean, Honors Tutorial College

3 Chang 3 Abstract Cancer is very prevalent in our society, and encompasses more than 100 different diseases. Additionally, each cancer can act distinctly, and current cancer therapies, such as chemotherapy and radiation, can lead to future complications. These facts implicate the need for new avenues of safer and more effective treatments. Oncogenic stresses are a hallmark characteristic of cancer, arising from the rapid growth and proliferation of cells. In response to these oncogenic stresses, the cells respond in a variety of ways, such as cell cycle arrest, DNA repair mechanisms, and cell death, in an attempt to overcome these stresses in and proliferate. Additionally, cancer is characterized by the activation of oncogenes and the loss of tumorsuppressor genes, which are involved in cell cycle arrest, as well as cell death. Therefore, in this project we investigated the link between cell death and cancer stresses by examining the interaction of p53, Clic, and the JAK/STAT pathway, all of which are known to be mutated in some cancers. The results presented in this thesis suggest that the activation of JAK/STAT pathway through the hop Tum mutation creates a pro-apoptotic environment that likely stimulates p53 function. Furthermore, this stimulation is activating the canonical p53/apoptotic pathway, as well as a noncanonical p53 cell death pathway. Our results also implicate that Clic is acting in an anti-apoptotic manner.

4 Chang 4 Table of Contents Introduction...8 Background...8 Overview of Cancer and its Progression...9 Oncogenes and Tumor Supressor Genes...10 Cancer Stem Cells (CSCs)...12 Oncogenic Stress Programmed Cell Death...16 p dp p53, JNK, and the apoptotic feedback loop...22 CLICs...23 JAK/STAT pathway...25 Drosophila lymph gland...28 Hypothesis and Objectives...31 Materials and Methods...32 GAL4-UAS lines and experimental design...32 Maintenance of fly cultures...37 Genotyping larvae...37 Live cell hemocyte count...38 q-pcr...39 Results...41

5 Chang 5 Activation of the JAK/STAT pathway through hop Tum creates a pro-apoptotic environment and likely stimulates p53 function...41 Activation of the JAK/STAT pathway and p53 stimulates the canonical p53 pathway...44 Activation of a non-canonical p53 cell death pathway...47 The JNK protein exhibits anti-apoptotic properties in response to oncogenic stress...50 Clic acts in an anti-apoptotic manner and is involved in the canonical p53 pathway...52 Discussion...56 Activation of the JAK/STAT pathway through hop Tum creates a pro-apoptotic environment and likely stimulates p53 function...56 Activation of the JAK/STAT pathway and p53 stimulates the canonical p53 pathway...57 The stimulation of p53 by oncogenic stresses may additionally trigger a noncanonical cell death pathway, such as programmed necrosis...58 The JNK protein exhibits anti-apoptotic properties in response to oncogenic stress...59 Clic acts in an anti-apoptotic manner and is involved in the canonical p53 pathway...60 Revised hypothesis...61 Significance and future directions...63

6 Chang 6 Bibliography...65 Appendix...71

7 Chang 7 Index of figures and tables Figure Figure Figure Figure Figure Figure Table Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Table

8 Chang 8 Introduction The focus on cancer, while not a new area of research, has increased in recent years. The American Cancer Society states that half of all men and one-third of all women in the US will develop cancer during their lifetimes and estimates that approximately 1.6 million people died from cancer in ( These statistics are staggering, implicating the need for both treatments, and possibly, an eventual cure. Some of the most common cancers include bladder, colon, lung, prostate, skin, and breast cancer, and one of the most complicated hurdles surrounding cancer research is the fact that each individual cancer can behave distinctly ( Currently, there is a myriad of research focused on eliminating cancer, including disrupting the function of oncogenic genes, as well as promoting tumor suppressive genes, both of which are known to be involved in the formation and promotion of cancer. Many new, synthetic drugs are currently in use to slow the progression or halt the spread and development of cancer. Methods such as chemotherapy and irradiation therapy are other means of eradicating cancer; however, these methods are not without their problems. For example, irradiation can lead to DNA damage, resulting in further complications, such as additional mutations in the DNA, and could potentially lead to new cancer. Additionally, both methods have numerous side effects including fatigue, anemia, hair loss, nausea and vomiting, and infection (

9 Chang 9 I. Overview of cancer and its progression Cancer is the result of normal cells that acquire mutations and then grow and divide at a rapid pace. The Biology of Cancer (2007), by Robert A. Weinberg, notes that although cancer can stem from a myriad of specialized cells, epithelial cells are responsible for more than 80% of the cancer-related deaths in the Western world. Additionally, cancer cells differ from normal cells because they have the ability to invade nearby tissues and spread, or metastasize, throughout the body. While most cancers can be identified by the fact that they stem from tumors (an abnormal mass of cells that may or may not have cancerous potential) some cancers, such as leukemia, rarely form tumors ( Additionally, benign tumors are a mass of cells that cannot invade nearby tissues, but still cause problems. For example, if they reach a large enough size, they can press on healthy organs and tissues, resulting in decreased function. It is of note that benign tumors may possess cancer stem cells, as shown by Xu et al (2009), but not all benign tumors necessarily progress to malignant tumors. Cancer often results from epigenetic, genetic changes, or both (Weinberg, 2007). Two types of substances are linked to epigenetic alteration of the genome: mutagens and carcinogens. Mutagens act to mutant the DNA, but may not necessarily lead to cancer. Carcinogens, however, are aptly named for their ability to cause cancer. During each of these cases, chromosome structure is often affected, resulting in either a more open or closed conformation, which in turn causes either an increase or decrease in the expression of a particular gene. Additionally, epigenetic alterations can

10 Chang 10 affect the chromatin structure of the DNA, resulting in either increased or decreased expression of a particular gene. This change in expression can result from many different factors including micrornas, which are involved in the regulation of genes, as well as chromatin remodelers, which affect the state of the chromatin. Furthermore, Weinberg (2007) notes that many tumor cells carry chromosomal translocations, in which parts of chromosomes switch with another section of an unrelated chromosome. Post-transcriptionally, the structure of a protein also contributes to whether or not an oncogene or tumor-suppressor gene can promote the formation of tumors. In his book, Weinberg notes that it is usually not a single mutation, but the collaboration between two or more mutant genes that act in a pleiotropic manner that induces the transformation of a normal cell into a cancer cell. A predisposition to cancer, inherited by one s parents, also plays a role in the likeliness that one will develop cancer. Cancer can be prevented somewhat by avoiding mutagens, which include cigarette smoke and sun exposure; however, cancer can develop in even the healthiest people. II. Oncogenes and Tumor Suppressor Genes Genes known as oncogenes and tumor suppressor genes, are often mutated in cancer cells, and are the primary genes responsible for perpetuating the acquired properties of cancer cells. In normal conditions, genes known as proto-oncogenes are characterized as genes that have the potential to become oncogenes, when activated by certain conditions. These oncogenes are then constitutively active or highly expressed in the cell, perpetuating cancer cell properties. Proto-oncogenes may be activated

11 Chang 11 through a variety of different mechanisms including mutations, chromosomal rearrangements, stress-related post-transcriptional alterations, etc. For example, it is known that in some brain and stomach cancers, the endothelial growth factor (EGF) receptor gene lacks most of its extracellular domain in cancer cells, and thus, its normal function is altered, resulting in its activation as an oncogene. This loss of the domain stems from a chromosomal rearrangement in which two parts of separate chromosomes exchange places. In the case of the EGF receptor gene, when the rearrangement occurs, the segment that confers the extracellular domain is separated and lost (Weinberg 2007). In addition to oncogenes, tumor-suppressor genes, which are considered antigrowth genes, are able to help counteract some of the effects of oncogenes. Normally, these genes function to suppress cell proliferation, but in most tumors these genes are often lost or inactivated. The loss of tumor suppressor genes, in combination with the activation of oncogenes, further perpetuates cell proliferation. Furthermore, Weinberg notes that promoter methylation, which is indicative of decreased gene expression, often occurs on tumor suppressor genes in cancer cells. Therefore, some researchers have focused on restoring the activity of tumor suppressors in cancer cells as a means of cancer therapy. One of the most well-known tumor suppressor genes is the p53 protein. Mallette et al (2007) note that the p53 pathway participates in the DNA damage response, along with another tumor-suppressor: Rb. The Rb, or retinoblastoma, pathway involves the family of proteins known as the E2Fs, which act as transcription

12 Chang 12 factors, and promote or repress genes involved in cell cycle progression. In wild-type conditions, the Rb protein binds and inhibits E2F proteins, and thus results in cell cycle suppression. Additionally, the Rb protein is able to reduce the expression of MDM2, the protein responsible for sequestering and inactivating p53. Current research has also been focused on the family of chloride intracellular channels (CLIC) proteins, which are shown by Suh et al (2012) to exhibit anti-tumor activity and are known to be commonly altered in cancer cells. However, Clic proteins have also been shown to perpetuate cancer progression in other occasions; the research surrounding these proteins is still very infantile, and further research will need to be done to determine the role of these proteins in cancer cells. Thus, a great deal of research has been aimed at targeting the upregulation of these tumor-suppressor genes in an attempt to reverse or slow the process of cancer development. III. Cancer Stem Cells (CSCs) Additional focus has recently been placed on cancer stem cells (CSCs) a somewhat controversial area of cancer research. Many theories currently exist regarding the origin of CSCs; for example, some scientists claim that CSCs originate from normal adult stem cells and generate tumors when they accumulate mutations; however, this does not mean that tissues or organs that do not contain adult stem cells are immune from developing cancer. Another theory proposes that CSCs are normal cells that acquire stem cell like properties through various mutations and undergo dedifferentiation, much like the state of stem cells.

13 Chang 13 Yu et al (2012) notes that like regular stem cells, cancer stem cells are characterized by their ability to self-renew; however, CSCs are also thought to have the capability to spawn tumors. Milas et al (2009) lists some of the characteristics that they believe are inherent to all CSCs. These characteristics include the expression of specific cell surface markers, the upregulation of certain pathways, such as the Wnt and Notch pathways, increased proliferation, relative resistance to certain treatments, and quiescence. Furthermore, Wang et al (2013) claims that CSCs are able to help other cancer cells metastasize and integrate into other parts of the body. Additionally, they state that CSCs have been found in a variety of different cancers, such as colon, pancreatic, breast, lung, and prostate cancer. Many believe that cancer often comes back after treatment, because these CSCs are not killed, thus allowing them to perpetuate the regeneration of the cancer. Further research will have to be conducted in order to characterize these special types of cancer cells; Hu et al (2010), note that the first step would be to identify the varying types of cancer stem cells. IV. Oncogenic Stress Since the nature of cancer cells differs greatly from wild-type cells, it is not surprising that the extrinsic and intrinsic environment surrounding each of these types of cells is also very different. Intrinsic changes include a change in the expression of certain transcription factors, while extrinsic factors affect the way cells behave and the way they influence surrounding cells. These environments are often due to the various types of oncogenic stresses that arise due to the rapid progression of cancer. A review

14 Chang 14 by Luo et al (2009) lists some of the different types of oncogenic stresses, which include DNA replication, proteotoxic, mitotic, metabolic, oxidative, hypoxia and nutrient stresses. In cancer cells, one of the most prominent of these stresses is DNA replication stress, characterized by the accumulation of deletions and chromosomal rearrangements. Many cancer cells tend to accumulate these mutations because it is often the genes that are involved in DNA damage repair and preventing excessive proliferation, that are altered in cancer cells. Genotoxic (DNA damaging) stresses can also be induced by UV radiation and ionizing radiation, two methods commonly employed in cancer therapies. When this type of stress occurs, the DNA damage pathway is activated, and the cell cycle is halted in an attempt to repair these mutations. This DNA damage leads to the induction of the ATM protein, resulting in the phosphorylation and stabilization of p53, protecting it from degradation. The p53 protein then leads to the upregulation of the p21 protein, resulting in cell cycle arrest. When non-genotoxic (non-dna damaging, such as metabolic and oxidative), stresses induce p53, the outcome is different, often leading to the apoptotic, or cell death, pathway. Schramek et al., (2011), also demonstrate that in response to non-genotoxic oncogenic stress, the JNK protein is activated and can then phosphorylate and activate p53. Mitotic, or replication, stress is also quite common due to the rapid replication and proliferation of cancerous cells. Thus, it is clear that many of these oncogenic stresses act in a combinatorial fashion to promote cancer and to change the microenvironments induced by cancer.

15 Chang 15 Bartkova et al (2006) note that oncogenes and oncogenic stress often induce senescence, or the inactive state, of cells; however, this finding counteracts typical cancer progression. In their paper, they suggest that the senescence induced by oncogenic stress is part of the tumorigenesis barrier induced by DNA damage. In their study, they demonstrate that the progression of the carcinoma was characterized by decreased activation of the double stranded break (DSB) pathway, as well as senescence. Therefore, this indicates that the induction of senescence is yet another method that could be employed to slow or act as a barrier to the progression of cancers. Thus, focus on factors that promote senescence, such as the induction of cell cycle arrest through p53, are essential to further understanding and creating potential new cancer therapies. Another response to oncogenic stress that cells employ is compensatory cell proliferation. Much like senescence, compensatory cell proliferation results in cell cycle arrest; however, this arrest only occurs long enough for cells to repair damage caused by the stress, the cell then comes out of arrest and begins proliferating again. In a review by Martin et al, (2009), they term these cells undead cells, and state that they exist in both Drosophila and mammalian systems. Additionally, a review by Fuchs et al, (2011), notes that p53 and one of its downstream targets, Dronc, act synergistically to produce compensatory proliferation. Furthermore, the same authors state the JNK protein may also be involved in this pathway, and contribute to compensatory proliferation; p35, which inhibits caspaces involved in apoptosis, is also necessary for sustaining the state of undead cells. A study by Fan et al, (2014), noted

16 Chang 16 that compensatory proliferation in apoptotic tissue, which they termed apoptosisinduced proliferation, may link cancer cell properties to cells that undergo compensatory proliferation. Most importantly, the authors note that cancer cells resemble undead cells because they can initiate, but not execute, the apoptotic pathway when overgrowth occurs. V. Programmed cell death Programmed cell death (PCD) may serve as a last resort for cells that are beyond the point of repair. PCD protects cells from foreign invasion that may threaten the immune system, irreparable DNA damage, and cell cycle perturbations (Fuchs et al., 2011). Additionally, Ouyang et al., (2012), note that the three main types of PCD are apoptosis, autophagy, and programmed necrosis. Each different form of PCD is distinguished by varying characteristics. For example, apoptosis is characterized by shrinkage in the cell, as well as nuclear condensation, while the formation of autophagosomes occurs during autophagy. The authors also note that both apoptosis and autophagy are largely involved in regulating the growth of cancer cells. For instance, autophagy, which occurs in response to certain stresses such as nutrient starvation, can act as both a pro- and anti-tumor process in cancer cells, depending on the stage of progression. Furthermore, research demonstrates that some cross-link can occur between these different types of PCD, and that apoptosis and autophagy can sometimes act synergistically. The figure below by Ouyang et al, (2012), demonstrates

17 Chang 17 the cross talk between these different types of PCD in cancer cells, as well as the role of p53 in this cross talk. Figure 1. Cross-talk between programmed cell death pathways involving p53 (Ouyang et al, 2012) During programmed necrosis, the damaged cells swell and lyse; Ouyang et al (2012), also notes that necrosis, which is caspase-independent, acts as a backup mechanism for apoptosis when caspases are inactivated or inhibited. VI. p53 Often during oncogenic stresses, anti-tumor pathways are activated; thus, focus has been placed on the key players in these pathways: tumor-suppressor genes. One of the most studied tumor-suppressor genes is p53 and its downstream targets. Joerger et al., (2007) note that about half of all cancers contain a mutation, usually a single missense point mutation, in the p53 gene. Due to this mutation, p53 expression is

18 Chang 18 usually lost, promoting the survival and proliferation of cancer cells, since the cells become somewhat apoptosis-resistant. Additionally, Horn et al (2007) note that even in cancers that contain functional p53, many of the pathways that are upstream or downstream of p53 are disrupted. Therefore, p53 function, either indirectly or directly, is lost in almost all tumors, elucidating how critical this gene is to further our understanding of cancer, as well as creating potential new therapies for cancer treatment. Under wild-type (normal) conditions, p53 acts as a transcription factor that activates many downstream targets involved in both apoptosis and cell cycle arrest, but has a myriad of other downstream targets that are involved in a variety of different processes, as seen in the figure below: Figure 2. p53 pathways and protein interactions in a mammalian systems (Nii et al., 2012).

19 Chang 19 A review by Mirzayans et al. (2012), notes that in normal cells p53 is maintained at relatively low levels within the cell. MDM2, another target of some cancer therapies, is the main regulator of p53 and facilitates its degradation. Therefore, if MDM2 can be targeted for degradation or prevented from performing its normal function, the levels of p53 available in cancer cells could be increased in an attempt to ameliorate some of the effects of the cancer. Additionally, different types of p53 modifications can affect the way the protein functions. These post-translational modifications include phosphorylation, acetylation, sumolyation, and methylation, in which a phosphate, acetyl, SUMO, or methyl group is added to the protein. Various types of stresses can induce posttranslational modification in the p53 protein, subsequently altering its normal function. For example, p53 is phosphorylated by the c-jun N-terminal kinase (JNK) protein at serine 20 and threonine 81, which stabilizes and activates the p53 pathway that is involved in apoptosis (Gowda et al., 2012). Additionally, phosphorylation of p53 at serine 15 can result in the enhancement of the association of p53 and the histone modeling protein p300, as well as increases p53 s sensitivity to the ATM/ATR proteins, which are known to activate p53 in response to DNA damage. Furthermore, it has been shown that many chemotherapeutic drugs also lead to p53 phosphorylation. One of the reasons that p53 is largely targeted as a potential gene in cancer therapy, is its ability to prevent cells from passing their DNA damage onto daughter cells, and is involved in the death of overproliferative cancer cells. Additionally, p53 is activated by ionizing radiation, a method commonly used in cancer therapy and

20 Chang 20 known to induce DNA damage (Mirzayans, 2012). By re-inducing p53 expression in cancer cells, scientists hope to trigger the lethality, through apoptosis or growth arrest, of the cancer cells. If the apoptotic pathway is triggered, p53 will activate downstream targets, eventually leading to the activation of effector caspaces, the last step before the cell is killed. Additionally, one of the downstream targets of p53, p21, has recently been the focus of some cancer, as well as stem cell, research. p21, when induced by p53, is able to facilitate cell cycle arrest in response to DNA breaks, one form of oncogenic stress. Therefore, p53 acts to prevent proliferation through induction of both cell cycle arrest and apoptosis. Furthermore, a review by Mirzayans et al (2012) notes that current cancer studies are focused on targeting non-oncogenic genes for cancer therapy, such as Bcl-2, which is also involved in apoptosis. VII. dp53 The fruit fly Drosophila melanogaster is one of the most employed animal models for studying genetics and the effects of various mutations on normal cell function. Drosophila are often used as genetic tools because they have a short generation time, and contain many of the same genes as humans (Potter et al 2000). Additionally, most of the genes in Drosophila only have a single copy, making flies much easier to manipulate. Brodsky et al (2000) note that most of the DNA binding hotspots in Drosophila p53 (or more commonly dp53/dmp53) correspond to those in mammalian p53. Clustal alignment results performed in Clustal Omega, also show that dmp53 shares many similar amino acids with mammalian p53, indicating that dmp53

21 Chang 21 and p53 are closely related in their function. However, while p53 and dp53 share many similarities, some of the greatest problems surrounding p53 as a target for cancer research are the differences between them. Dp53 can trigger apoptosis, but Sutcliffe (2004) notes that unlike the findings in mammalian systems, it does not appear that p53, through p21, plays any role in cell cycle arrest. Figure 3. Comparison of the cell death pathway in Drosophila and mammalian systems (Hay et al. 2004) Wells et al (2006) also note that dp53 is involved in compensatory proliferation in Drosophila imaginal discs. In their study, they note that cells, which

22 Chang 22 they deemed undead, or in a senescent state, were responsible for the proliferation and that cell cycle arrest precedes this proliferation. Additionally, they saw that the induction of dp53 in the undead cells was able to induce a global signaling of other factors that contributed to the increase in proliferation, as well as the formation of a blastema in the imaginal discs, an essential structure found in many regenerating systems. This study thus suggests that dp53 may play a role in regeneration. Since it is already known that compensatory proliferation can occur in mammalian cells, this study provides greater evidence that dp53 is a suitable model for studying mammalian p53, specifically in the case of p53 s response to cancer stresses. Additionally, this study demonstrates that p53 may not only be a novel target for cancer research, but also for regenerative medicine. Further research would have to be conducted to confirm this thought. VIII. p53, JNK, and the apoptotic feedback loop Despite the knowledge surrounding p53 in the apoptotic pathway, research has also shown that the JNK protein may be important in cancer stress response and tumor suppression (Shramek et al, 2011). They note that MKK7, upstream of JNK, aids in the regulation of tumor initiation and is involved in tumor suppression. Furthermore, the authors note a deficiency in MKK7 severely affects the stability of p53, indicating that JNK could be important in the activation of p53 in oncogenic stress environments. For example, Haigis et al., (2011), note that JNK is able to detect oncogene-induced senescence, and subsequently activate p53. Furthermore, Shlevkov et al. (2012) also

23 Chang 23 note that JNK can activate p53, and vice versa, resulting in a positive feedback loop. They state that this feedback loop is essential to the apoptotic stress response in Drosophila. Additionally, they demonstrated that JNK can bypass p53 to activate its downstream genes, reaper, hid, and grim when p53 is inactivated or lost. Fan et al. (2014) also found that Dronc, an initiator caspace downstream of p53, is able to activate both p53 and JNK. Furthermore, Gowda et al. (2012) show that p53 was able to prevent the inactivation of JNK. Some researchers also believe that the JNK protein may be involved in caspace-independent cell death; a review by Kroemer et al. (2005) notes that c-jun N-terminal kinase (JNK) can induce the expression of two proteins, cathepsin B and D, during lysosomal stress through a caspace-independent manner. This implicates that two different types of cell death could be occurring in response to cancer cell stresses. IX. CLICs The family of chloride intracellular channels (CLICs) has been shown to be commonly altered in cancer cells, and some are upregulated, while others are downregulated. A study by Suh et al. (2005) demonstrates that CLIC4 anti-sense RNA, which acts to block CLIC4 function, is able to induce apoptosis and inhibit the growth of cancer cells, indicating CLIC exhibits anti-apoptotic properties. Additionally, when they added TNF-α, a commonly used cancer therapy drug, they saw an increase in cellular apoptosis. Unfortunately, they did not see a combinatorial effect due to both the anti-sense CLIC and TNF-α in anti-tumor activity. They do note,

24 Chang 24 however, that CLIC4 had more of an effect than TNF-α. Additionally, they found that CLIC and p53 show similar expression patterns, in that when CLIC was decreased in tumor cells, so was p53. Another study published by the same group in 2012, shows that CLIC4 often decreases when tumors progress from benign to malignant. Additionally, Suh et al. (2012) demonstrate that an increase in CLIC expression exhibits anti-tumor activity when translocated to cancer cell nuclei. They noted that this anti-tumor activity was independent of p53 expression levels, but did shift the environment of the cancer cells to a more oxidative state. This is of note, because a more oxidative state is not ideal for cancer cells to thrive. The fact that these two studies seem to contradict themselves, lead us to further investigate the link between p53 and CLIC, and their roles in cancer cells; however, CLIC is regarded by most to be a tumor suppressor and increase proliferation. Both papers by Suh et al (2005; 2012) also note the modifications that are made to the CLIC proteins, not only in cancer cells, but in other instances of mutation of the CLIC gene. For example, a portion of the N-terminus that normally contains a cysteine residue can be altered in cancer cells, affecting the wild-type function of CLIC. Additionally, the CLIC protein contains a negatively charged loop, which can become protonated and hydrophobic at lower phs. This protonation causes the protein to insert into the cellular membrane, and thus, it loses its function as a cytoplasmic protein. This is important to note, because as Suh et al. (2012) found, CLIC must be translocated into the nucleus in order to exhibit anti-tumor activity.

25 Chang 25 X. JAK/STAT Pathway The normal function of the JAK/STAT pathway is the activation of genes important to cell proliferation and survival. Figure 4. The JAK/STAT pathway in mammalian systems (Singh et al., 2008) Stat proteins have been shown to be modified or constitutively active in some cancers. Modifications to the Stat3 protein, such as an introduction of a pair of cysteine residues, as Weinberg (2007) notes, can cause the protein to dimerize spontaneously. This results in constant activity of the Stat protein, and an increase in the transcription of the target genes that Stat3 can activate. Research has also shown that the JAK/STAT pathway is involved in a myriad of myeloproliferative disorders, which are characterized by their hypersensitivity to factors involved in hematopoiesis,

26 Chang 26 mainly cytokines, as well as an increase in the activity of the JAK/STAT pathway (James et al 2005). These diseases parallel cancer cells for the fact that there is an extreme increase in proliferation of cells. Furthermore, it has been shown that angiogenesis, the formation of new blood vessels, is very critical to the growth and metastasis of cancer. James et al (2005) note that a point mutation in the JAK2 gene is the leading cause of the myleoproliferative disease Polycythemia vera, which results in an increase in the number of circulating red blood cells. They also found that the point mutation, which results in an amino acid change, was able to activate STAT-mediated transcription. Additionally, the JAK2 mutation inhibits the auto-inhibitory activity of the JH2 domain in JAK2; normally, the JAK2 protein is able to self-inhibit its function, but in the JAK2 mutant, the JH2 domain is rendered nonfunctional, and the JAK2 protein is constitutively functional. Based on their results, James et al (2005), concluded that the JAK/STAT pathway plays a principal role in the abnormal cytokine response seen in Polycythemia vera patients, as well as the intrinsically active properties of JAK2, resulting in the increase of red blood cells. Taken together, these results suggest a positive proliferative advantage to producing hematopoietic stem cells, thus providing a better understanding of the complex mechanisms and different factors that contribute to the generation of adult stem cells, in general. Although a great deal of research has been focused on human myeloproliferative diseases, research on JAK/STAT and its link to hematopoeisis was first characterized in the fly model Drosophila melanogaster.

27 Chang 27 Harrison et al (1995) note that the hopscotch (hop) gene encodes the Drosophila JAK protein; a single amino acid substitution results in a mutation which has been termed hop Tum. This mutation causes increased phosphorylation of the tyrosine sites and a hyperactive JAK kinase, subsequently resulting in an increase in hemocytes or Drosophila blood cells. Additionally, research has shown that loss of function of this hop gene results in lethality and a decrease in proliferation, while a gain of function promotes the formation of tumors and an increase in the size of the hematopoietic organs. In their study, Harrison et al (1995) note that there was tumor formation in the lymph glands of the hop Tum mutants. Therefore, this study indicates that the Drosophila model is an appropriate model for studying human hematopoiesis because of the similarities that the Drosophila models have with human Polycythemia vera. Another study by Luo et al (1997) demonstrates that an additional hop mutation showed similar characteristics to the hop Tum mutation. They observed that the JAK2 mutant they found caused higher levels of phosphorylation on the tyrosine site of the JAK/STAT receptor in Drosophila, as well as higher levels of Stat phosphorylation, which agrees with the results seen by James et al (2005) in Polycythemia vera. Taken together, both of these studies further indicate that the hop Tum mutation in flies is similar to the JAK mutations that cause an increase in the proliferation of blood cells in mammals, and thus is a suitable model for studying these proliferative disorders, as well as cancer cells, which also notably demonstrate overactive proliferation of cells.

28 Chang 28 XI. Drosophila Lymph Gland Focus on the Drosophila lymph gland has been essential to the research surrounding Drosophila hematopoiesis, since it is the organ which produces hemocytes. The lymph gland originates from the cardiogenic mesoderm during embryogenesis, and continues to grow during larval development. The lymph gland gives rise to three distinctive types of hemocytes: plasmatocytes, crystal cells, and lamellocytes. Jung et al. (2005) note that plasmatocytes make up the largest portion of hemocytes (95%) and are involved in the removal of dead cells and pathogens. Furthermore, crystal cells make up the second largest proportion of hemocytes, at roughly 5%, and contribute to humoral immune responses and wound healing. Lastly, lamellocytes represent the smallest number of hemocytes and are involved in encapsulation and neutralization of large foreign particles, such as wasp eggs. Lamellocytes are the least common type of hemocyte and usually only differentiate due to various stresses, e.g. the introduction of wasp eggs as shown by Rizki et al (1992). At the first stages of development, the lymph gland consists of only a single pair of lobes containing very few cells. During the second larval instar, the morphology of the lymph gland changes drastically and two to three new lobes are now present, as well as increased in size. By the third larval instar phase, the lymph gland has grown dramatically in size and the medullary and cortical zones become distinct, and expressing different factors. The first lobes of the lymph gland are composed of three distinct zones: the cortical zone, medullary zone, and the posterior signaling center. The maturing

29 Chang 29 hemocytes are restricted to the cortical zone, while the medullary zones contain prohemocytes that will later mature in the cortical zone. Tokusumi et al. (2012) note that the JAK/STAT pathway is activated in the medullary zone. Additionally, Krzemien et al (2007) found that the JAK/STAT pathway acts to induce the production of domeless, which acts to positively regulate cellular proliferation, in the medullary zone where it is involved in promoting hemocytes to the cortical zone for maturation. This evidence, therefore, makes the JAK/STAT pathway important for studying hematopoeisis. The posterior signaling center is fairly different from either of these two zones and has been shown to closely resemble a stem cell niche, as it nonautonomously maintains the hemocyte progenitor population (Krezemien, 2007). Tokusumi et al (2012) also note that hedgehog (hh), Suppressor of hairless (SuH), collier (col), Antennapedia (Antp), wingless (wg), and odd-skipped (odd), are involved in the formation and maintenance of the lymph gland. Jung et al (2005) states that the first factors expressed during the development of the lymph gland are odd-skipped (odd) and serpent (srp), which are expressed during the late embryo phase. Mandal et al (2007) demonstrate the importance of hh and Antp in maintaining the posterior signaling center (PSC). They note that the expression of Antp is closely linked to homothorax (hth) expression, and when they created hth loss of function mutations in flies, there was also a loss of the lymph gland. Additionally, the loss of col and Antp caused a drastic change in the morphology of the lymph gland, indicating that col and Antp are necessary for the formation and maintenance of the PSC. Krezemien et al (2007) additionally show that

30 Chang 30 the PSC is important in the control of blood cell homeostasis in Drosophila and actively blocks the expression of genes that promote the maturation of hemocytes. This study demonstrates that col mutants result in an increase in crystal cell differentiation, suggesting that the PSC has a general role in controlling hemocyte homeostasis. Additionally, they show that Notch signaling is involved in maintaining normal levels of col expression, and thus is also important in PSC maintenance. Mandel et al (2007) additionally demonstrate that without the PSC, lamellocytes were not formed. Therefore, they conclude that the PSC acts to block the expression of genes that induce the differentiation of prohemocytes, further supporting the idea that PSC acts as a stem cell niche for Drosophila hemocytes. Krzemien et al (2007) also show that filopodia in the cells in the PSC are necessary for the communication of the cells in the PSC with the cells in the medullary zone, in order to promote maturation of the hemocytes. This evidence can thus link the factors involved in the PSC to the CLIC genes, which are also closely linked to actin and the formation of filopodia.

31 Chang 31 Hypothesis and Objectives Figure 5 is a protein interaction map that shows, based on various studies (Mallette, 2007; Suh, 2012; Mirzayans, 2012; Sutcliffe, 2004; James, 2005; Harrison, 1995), what is known of apoptosis in the Drosophila model thus far: Figure 5. Protein interactions and the apoptotic pathway in Drosophila Based on a literature review, the apoptotic pathway (figure 5) in response to the overactivation of the JAK/STAT pathway through the hop Tum mutation, was constructed. For this project, we aimed to investigate whether or not the overproliferation caused by the dominant mutation in JAK, created a pro-apoptotic environment that would stimulate p53 function, shown in green in figure 5 (objective 1). Additionally, we sought to determine if the stimulation of p53 by oncogenic stresses was leading to apoptosis through the canonical apoptotic pathway, shown in black in figure 5. Furthermore, we aimed to elucidate the role of the Clic protein in the canonical apoptotic pathway triggered by oncogenic stresses, shown in red in figure 5 (objective 2).

32 Chang 32 Materials and Methods UAS-GAL4 Lines and Experimental Genotypes In order to make the different genetic backgrounds needed for this project, we used standard genetic manipulations, such as the GAL4- UAS system, in order to combine multiple mutations and genetic elements (Greenspan, 2004). The GAL4 system borrows the GAL4 transcriptional activator from yeast. In yeast, the GAL4 activator binds the upstream activating sequence (UAS) to activate transcription of the target gene. This system allows expression to be driven by fusing the gene of interest with a tissue specific enhancer promoter, which allows the gene of interest to be expressed in only certain tissues (Phelps et al. 1998). The tissue specific promoter used in the genetic backgrounds in this project was the Collagen IV (Cg) gene, which is expressed by hemocytes, the tissue we were interested in, as well as fat bodies. Females that contained the CgGAL4 driver were crossed with male flies carrying the gene of interest fused to the UAS sequence. The F 1 generation, or the offspring of the flies crossed, then contained both of the components necessary for the transcription of the target gene: the CgGAL4 driver, and the UAS directly upstream of the target gene. The F 1 generation, therefore, expressed the target gene(s) in a tissue specific manner; in the case of this experiment, only hemocytes and fat bodies.

33 Chang 33 Figure 6. Schematic diagram of the UAS-GAL4 system in Drosophila and how it works (Botella et al., 2009). To test the interaction of the different proteins we were interested in, we created a variety of different genetic backgrounds that contained a combination of the different genes in which we were interested. These genotypes were created using the GAL4-UAS system, as described above, and mating female and male flies containing the components necessary for the GAL4-UAS system. The table below shows the control and experimental genotypes that we examined. A list containing the female and male genotypes used to generate the F 1 generation, as well as the experimental and control counts of all genotypes used in this study, can be found in Appendix I.

34 Chang 34 Control Experimental y w/y; CyO, y+/+; +/TM6, y+ y w/y; CgGAL4/+; +/TM6, y+ y w/y; CgGAL4/+; UAS-p53/+ y v hop Tum /Y; +/ CyO, y+ y v hop Tum /Y; CgGAL4/+; UAS-p53/+ y w Clic 109 /Y; CyO, y+/+; +/TM6, y+ y w Clic 109 /Y; CgGAL4/+; +/TM6, y+ y w Clic 109 /Y; CgGAL4/+; UAS-p53/+ FM7i, act-gfp/y; CgGAL4/+; UAS-p53/+ y v hop Tum Clic 109 /Y; CgGAL4/+; UAS- p53/+ y v hop TUM /Y; CyO, y+/+; +/TM6C, SbTb y v hop TUM /Y; CgGAL4/+; +/TM6C, SbTb y v hop TUM / Y; CgGAL4/+; UAS-p53, UAS-DIAP/+ y v hop Tum /Y; CyO, y+/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; Nc 51 /+

35 Chang 35 y v hop Tum /Y; CyO, y+/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; Nc 51, UAS-p53/+ y v Clic 109 /Y; CyO, y+/+; +/TM6C, SbTb y v Clic 109 /Y; CgGAL4/+; +/TM6C, SbTb y v Clic 109 /Y; CgGAL4/+; Nc 51, UAS-p53/+ y v hop Tum /Y; CyO, y+/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; th 4 /+ y v hop Tum /Y; CyO, y+/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; th 4, UAS-p53/+ y v hop Tum /Y; CyO, y+/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; Df(3L)H99/+ y v hop Tum /Y; CyO, y+/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; +/TM6C, SbTb y v hop Tum /Y; CgGAL4/+; Df(3L)H99, UAS-p53/+

36 Chang 36 y v hop TUM /Y; CyO, y+/+; +/+ y v hop TUM /Y; CgGAL4/+; +/+ y v hop TUM /Y; CgGAL4/+; bsk 1 cn 1 bw 1 sp 1 /+ y v hop TUM /Y; CyO, y+/+; +/TM6C, SbTb y v hop TUM /Y; CgGAL4/+; +/TM6C, SbTb y v hop TUM /Y; CgGAL4/+; puc 1 red 1 e 4 /+ Table 1. Genotypes of the control and experimental genetic backgrounds that were tested. Each chromosome is separated by a semicolon.

37 Chang 37 In the genetic backgrounds in Table 1, CyO, y+ (on the second chromosome) and TM6C, Sb Tb (on the third chromosome) are balancers. The genotypes with hop Tum contain the dominant JAK mutation, and the genotypes with CgGAL4 and no additional mutations in the first chromosome indicate a wild-type background. Furthermore, in genotypes with Clic 109, Clic function is removed, and in genotypes containing th 4, IAP function is reduced. Genotypes containing Df(3L)H99 indicate that there is 50% reduction in RHG function, while Nc 51 indicates that Dronc function is reduced by 50%. Genotypes with DIAP overexpress the Drosophila inhibitors of apoptosis, and p53 indicates overexpression of p53 in each genetic background. Maintenance of fly cultures Each cross was cultured at 22 C and stored in vials containing fly food. Fly food was made by combining 2280g of JazzMix, 360g of activated dry yeast, and 12L of water in a large kettle, which was then stirred at 65 revolutions per minute and heated to a boil. After boiling for 10min, heat was turned off and the mixture was continuously stirred while cooling for 20min. The cooled mixture was then added to a pouring apparatus, distributed in plastic vials, and stored in a refrigerator for later use. Genotyping larvae In order to genotype the larvae that would be examined for live hemocyte count, bromophenol blue dye, which stains the fly food, was added the day before the cross was examined, in order to help determine larvae in the late third larval instar

38 Chang 38 stage. Flies on the side of the vial with dye in their intestines, indicating that they had ingested the dye, were then removed and placed into a small dish with ddh 2 O. The F 1 males were separated from females using a light microscope. The males were then divided using specific markers, such as beak color or fluorescence, in order to determine the control from the experimental larvae. Live hemocyte count In order to examine the effects of these mutations, live hemocyte count was recorded for each genetic background. In order to perform the live hemocyte count, larvae in the late wandering stage were bled onto a hemocytometer, which contains a grid with twenty-five squares, and observed through a Nikon microscope. After counting cells in a set number of squares (for this experiment, nine squares were counted), the following equation was used to estimate the total number of cells per ml of hemolymph in the larvae: The live cell count was used to determine the effects our mutations have on the total cell count, and therefore, cellular proliferation and apoptosis. The results were then compiled into a table (which can be seen in Appendix I), and the different genotypes were compared. The control and experimental counts for each genotype were compared using a t-test, and statistical significance was determined based on a p-

39 Chang 39 value of p<0.05. Additionally, a Chi-squared test was employed to determine if there was significance between the ratios of the experimental to control hemocyte counts between genotypes. q-pcr: To further investigate the link between the p53 pathway and cancer-stress related apoptosis, we performed a quantitative polymerase chain reaction (q-pcr), which measures the mrna levels of each gene expressed in specific genetic backgrounds. In order to perform the q-pcr, RNA was extracted from a variety of genetic backgrounds including hop Tum, and wild-type using the Qiagen RNeasy mini kit and following the manufacturer s protocol for purification of total RNA from animal tissues. It should be noted that the optional part of step 6 was performed, and then the protocol was resumed at step 8. cdna was then synthesized from the extracted RNA through a reverse transcriptase (RT) PCR reaction, and following the protocol in the RT 2 RNA QC PCR Array Handbook for cdna synthesis using the RT 2 first strand kit. Three different mixtures were then made with the cdna for the q- PCR. The components and volume needed for each mixture can also be found in the RT 2 RNA QC PCR Array Handbook we followed the protocol for Real-Time PCR for RT 2 RNA QC PCR Arrays. The three different reactions were then pipetted into a 96-well plate. The plate was then spun down and inserted into the CFX96 Real-Time System machine with a C100 Thermal Cycler, and a set protocol (Table 6 in the protocol for RT 2 RNA QC PCR Arrays) was used to run the q-pcr. Once each plate

40 Chang 40 was run, CFX manager software v.1.5 was used in order to view the results. The output C(t) values were then copied and pasted into Microsoft excel, so that the data could be analyzed. The ΔC(t) and ΔΔC(t) values were calculated using the C(t) values and the ΔΔC(t) values were used to determine the relative fold expression of each gene comparatively in genotypes (Livak et al 2001). It should be noted that this experiment is not yet completed, and thus, the results are not shown.

41 Chang 41 Results Activation of the JAK/STAT pathway through hop Tum creates a pro-apoptotic environment and likely stimulates p53 function In order to determine whether the activation of the JAK/STAT pathway through the hop Tum mutation creates a pro-apoptotic environment, and thus stimulates p53 function, we compared the control and experimental total hemocyte count per ml of hemolymph of genetic backgrounds that combined the hop Tum mutation with overexpression of p53 (figure 7). Figure 7. Control and experimental total hemocyte count per ml of hemolymph in three different genetic backgrounds: wild-type (with overexpression (OE) of p53), hop Tum (with overexpression of p53), and hop Tum (with loss of the reaper, hid, and grim (RHG) genes). The red bars represent the control hemocyte count (either wild-type or

42 Chang 42 hop Tum alone), while the green bars correspond to the experimental hemocyte count. ** indicates statiscal significance of a p-value<0.01, as determined by t-tests. Comparison of the control (12.9±2.71) to the experimental (9.27±3.64) hemocyte count (x10 6 ) in wild-type with overexpression of p53 shows that there is a significant decrease in hemocyte count of the experimental compared to the control. Additionally, there was a significant increase in control hemocyte counts when comparing the wild-type genetic background (12.9±2.71) to the hop Tum background (34.1±3.29). In the hop Tum and overexpression of p53 genotype, there was a significant decrease in the experimental hemocyte count (10.8±1.95) compared to the control (34.1±3.29). Furthermore, the percentages of the experimental to the control hemocyte count, represented by the arrows in figure 8, were compared for the wildtype background overexpressing p53, the hop Tum background overexpressing p53, and the hop Tum background with the Df(3L)H99 mutation (loss of the RHG genes).

43 Chang 43 Figure 8. Graphic representation of the increase/decrease in hemocyte count of the experimental and control generated from the raw data shown in figure 7. The dotted line represents the ratio of the experimental and control hemocyte count of overexpression of p53 in the wild-type background. Red arrows indicate a decrease in the experimental to the control hemocyte count, while the white arrow indicates an increase in experimental to control hemocyte count. Chi-squared tests were used to determine the statistical significance of the decrease or increase among genotypes.** indicates a p-value<0.01. The decrease in the experimental to control hemocyte count of the wild-type background is represented by the first red arrow in figure 8, while the decrease in hemocyte count of the hop Tum background overexpressing p53 is indicated by the second red arrow. Comparing the ratios for both of these genotypes using a Chi-

44 Chang 44 squared test indicates that the decrease in the percentage of experimental to control hemocyte count of the genetic background with the hop Tum mutation and overexpression of p53 was statistically significant from the decrease of the wild-type background overexpressing p53. Additionally, the genotype containing Df(3L)H99 (loss of the RHG genes) in the hop Tum background shows that there was a significant increase in the experimental hemocyte count (27.4±4.51) compared to the control count (18.2±3.94), as demonstrated by the white arrow in figure 8. It should be noted that the Df(3L)H99 mutation not only deletes the reaper, hid, and grim genes, but also sickle, for a total of four pro-apoptotic genes. Taken together, the hemocyte counts for these genetic backgrounds suggest that the activation of the JAK/STAT pathway through the hop Tum mutation creates a pro-apoptotic environment, and is likely stimulating p53 function. Activation of the JAK/STAT pathway and p53 stimulates the canonical p53 pathway In order to test whether or not the stimulation of p53 by the JAK/STAT pathway was consequently activating the canonical p53/apoptosis pathway (figure 3), we created a variety of different genetic backgrounds that either removed, or overexpressed, DIAP, the RHG genes, and Dronc, in addition to the overexpressing p53.

45 Chang 45 Figure 9. Total live hemocyte count per ml of hemolypmh of genetic backgrounds overexpressing (OE) p53 and either increasing (OE) or reducing (loss) expression of DIAP, RHG, or Dronc. Red bars indicate the control hemocyte count, while the green bars indicate experimental counts. The experimental and control hemocyte counts were compared using a t-test. ** indicates a statistically significant p-value of p<0.01. The control to the experimental hemocyte counts were compared using a t-test to determine if the increase or decrease seen in the experimental count was statistically significant to the control count. All genotypes in figure 9 indicate that there is a significant decrease in the experimental hemocyte counts compared to the control. In order to further determine whether or not there was an effect on hemocyte count due to the various mutations involving the proteins downstream of p53, the percentage of the

46 Chang 46 experimental to control hemocyte counts were calculated and compared to the ratio of the experimental to control hemocyte count of the genetic background containing the JAK mutation and overexpression of p53 (figure 10). Figure 10. Graphic representation of the increase/decrease in hemocyte count of experimental to control generated from the raw data shown in figure 9. The dotted line represents the ratio of the experimental to control hemocyte count of overexpression of p53 in the hop Tum background. Red arrows indicate a decrease in the experimental to control hemocyte count, while the white arrow indicates an increase in experimental to control hemocyte count. A Chi-squared test was used to determine the significance of the percentage of the experimental to control hemocyte count. * indicates a p-value<0.1, while ** indicates a p-value<0.01.

47 Chang 47 Compared to the ratio of the experimental to control hemocyte count of overexpression of p53 in the hop Tum background, the genetic background with overexpression of p53 and reduced DIAP function shows a reduction in hemocyte count (figure 10, second red arrow). Additionally, the background containing overexpression of p53 with loss of Dronc function results in approximately a 47% increase in hemocyte count compared to the background overexpressing p53 with hop Tum. The genotype overexpressing both p53 and DIAP in the hop Tum background showed no significant change in the percentage of the experimental to control hemocyte count compared to the genetic background overexpressing p53 in the hop Tum background. Taken together, the hemocyte count for these genetic backgrounds suggests that the canonical p53 pathway is being activated by the stimulation of oncogenic stresses induced by the hop Tum mutation. Activation of a non-canonical p53 cell death pathway The genetic background with overexpression of p53 and loss of the RHG genes, seen in figure 9, shows that there is a significant decrease in total hemocyte count of the experimental (4.90±1.12) to control count (19.3±2.46), indicating an increase in apoptosis. This decrease is clearly illustrated in figure 10, which shows that the percentage of the experimental to control count was less than the ratio of experimental and control hemocyte of overexpression of p53 in the hop Tum background, as indicated by the red arrow. These results do not comply with the

48 Chang 48 canonical p53/apoptotic pathway, and could implicate that a non-canonical p53 cellular death pathway is activated by oncogenic stresses. Therefore, we further investigated the possibility that a non-canonical p53 pathway was being activated in response to the induction of oncogenic stresses by the dominant JAK mutation. We compared the control and experimental hemocyte counts containing a loss of Dronc, with and without overexpression of p53, in the hop Tum background (figure 11). Figure 11. Control and experimental hemocyte counts per ml of hemolymph of genetic backgrounds with loss of Dronc in the hop Tum background. Red bars indicate control hemocyte count, while green bars are experimental counts. The experimental and control hemocyte counts were compared using a t-test. ** indicates a statistically significant p-value of p<0.01.

49 Chang 49 The genotype with the loss of Dronc in the hop Tum background shows that there is a significant decrease in hemocyte count in the experimental (9.26±1.77) compared to the control (11.4±1.91). Reduction of Dronc and overexpression of p53 in the hop Tum background also demonstrate that there was a decrease in hemocyte count of the experimental (13.5±2.92) compared to the control (28.8±5.27) count. The percentage of the experimental to the control hemocyte counts, shown in figure 12, illustrates that there is an increase in the ratio of the experimental to control hemocyte count in the hop Tum background with loss of Dronc with and without overexpression of p53 when compared to the hop Tum background overexpressing p53. Figure 12. Graphic representation of the increase in hemocyte count of experimental to control generated from the raw data in figure 11. The white arrows indicate an

50 Chang 50 increase in hemocyte count of the experimental to control genotypes. A Chi-squared test was used to determine the significance of the percentage of the experimental to control hemocyte count. ** indicates a p-value<0.01. The increase, represented by the white arrow in figure 12, in the ratio of experimental to control hemocyte count of the genetic backgrounds containing the loss of Dronc compared to the hop Tum background overexpressing p53, indicates that Dronc is a pro-apoptotic protein, as shown in the canonical p53 pathway (figure 3). However, the increase in the hop Tum background with loss of Dronc and overexpression of p53 was not as great as the increase of the hop Tum background with loss of Dronc. This might be due to another non-canonical p53/cell death pathway, as suspected from the results shown in figures 9 and 10. The JNK protein exhibits anti-apoptotic properties in response to oncogenic stresses The JNK pathway has been shown to respond to oncogenic stresses, as well as activate p53 function in response to oncogenic stresses (Haigis et al 2011). In order to test whether or not the JNK pathway was involved in the response to oncogenic stresses by the hop Tum mutation, we created genetic backgrounds in which we removed puckered (puc), a protein downstream of JNK, which negatively regulates JNK function, as well as basket (bsk), which is the JNK protein in Drosophila.

51 Chang 51 Figure 13. Control and experimental total hemocyte count per ml hemolymph of genetic backgrounds containing the JAK mutation and components of the JNK pathway (bsk and puc). The red bars represent the control hemocyte count, while the green bar are the experimental hemocyte counts. The experimental and control hemocyte counts were compared using a t-test, ** indicates a statistically significant p-value of p<0.01. Comparing the control (36.0±3.33) and experimental hemocyte (16.5±2.62) of the hop Tum background with loss the JNK gene demonstrates that there is a decrease in the experimental count, and likely an increase in apoptosis. On the other hand, removing the function of puc, downstream of the JNK protein, shows there was an increase in hemocyte count compared to the control, indicating a decrease in

52 Chang 52 apoptosis. The data in figure 13, therefore, suggests that the JNK pathway may be involved in the response to oncogenic stresses induced by the hop Tum mutation. These results also suggest that in the hop Tum background, JNK is acting in an anti-apoptotic manner in response to oncogenic stresses. Further research would need to be conducted in order to determine the interaction of the JNK pathway and p53 pathway in response to oncogenic stresses, and whether or not JNK function is still antiapoptotic when p53 is overexpressed. Clic acts in an anti-apoptotic manner and is involved in the canonical p53 pathway In order to study the function of the Clic protein, and how it fits into the canonical apoptotic pathway that responds to oncogenic stress, we created genetic backgrounds with loss of Clic function, as well as backgrounds that contained loss of Clic as well as overexpression of p53, hop Tum plus overexpression of p53, and hop Tum with loss of Clic alone (figure 14).

53 Chang 53 Figure 14. Live cell hemocyte count per ml hemolymph of genetic backgrounds containing loss of Clic function. Red bars indicate control hemocyte count, while green bars represent experimental count. The hemocyte count for the control and experimental larvae were compared using a t-test. ** indicates statistical significance of a p-value<0.01. In the loss of Clic background with overexpression of p53, there is a significant decrease in the experimental count (4.41±1.42) compared to the control (12.2±3.92), suggesting an increase in apoptosis, shown in figure 14. Additionally, comparing the experimental to the control count of the double mutant containing the hop Tum mutation and loss of Clic function with overexpression of p53, the experimental count (7.23±1.98) was significantly lower than the control (12.6±2.46), indicating an increase in apoptosis. Furthermore, in the genotype with loss of Clic,

54 Chang 54 overexpression of p53, and loss of Dronc function, there was a slight decrease in experimental hemocyte count (8.03±2.45) compared to the control (9.93±2.96), although this decrease was not statistically significant. The raw data was then converted to a ratio of the experimental to control hemocyte count and the genetic backgrounds with loss of Clic function were compared to the wild-type background containing overexpression of p53 (figure 15). Figure 15. Graphic representation of the increase/decrease in the hemocyte count of the experimental to the control of genetic backgrounds with loss of Clic function generated from the raw data shown in figure 14. Red arrows indicate a decrease in the experimental hemocyte count compared to the control, while white arrows represent an increase. A chi-squared test was used to determine the significance of the

55 Chang 55 percentage of the experimental to control hemocyte count. * indicates a p-value<0.1, while ** indicates a p-value<0.01. The percentage of experimental to control hemocyte in the loss of Clic background with overexpression of p53 compared to wild-type with overexpression of p53 indicates that there was a decrease in the experimental to control ratio, suggesting more apoptosis. Additionally, in the Clic and hop Tum double mutant overexpressing p53, hemocyte count also decreases when compared to wild-type overexpressing p53, signifying an increase in apoptosis. However, in the genetic background with loss of Clic, overexpression of p53, and loss of Dronc function, there was an increase in the percentage of experimental to control hemocyte count, compared to the genotype overexpressing p53 in the hop Tum background, suggesting a decrease in apoptosis, and therefore, an increase in cellular proliferation. Taken together, these results suggest that the Clic protein is acting in an anti-apoptotic manner in response to the activation of the canonical p53 pathway stimulated by oncogenic stresses.

56 Chang 56 Discussion The activation of the JAK/STAT pathway induces oncogenic stress, creating a proapoptotic environment, and likely stimulates p53 function The dominant JAK mutation, i.e. hop Tum, increases control hemocyte count when compared to the wild-type background (figure 7). This observation suggests that the hop Tum mutation is behaving as an oncogene, which agrees with previous studies (James et al 2005 and Harrison et al 1995). Additionally, the decrease in the experimental count for the hop Tum genotype overexpressing p53 compared to the control count indicates that there is a significant decrease in hemocyte count, and that overexpression of p53 has a pronounced effect in the hop Tum background. This decrease suggests that overactivation of the JAK/STAT pathway through the hop Tum mutation, creates a pro-apoptotic environment and likely stimulates p53 function, leading to an increase in apoptosis. If no pro-apoptotic environment was created, we would expect that the experimental and control hemocyte count of the genetic background with the hop Tum mutation with overexpression of p53 would be similar. These results also indicate that p53 and the JAK/STAT pathway genetically interact. This is supported by the genotype hop Tum with loss of the RHG genes, which are directly downstream of p53 and are pro-apoptotic, as seen in both figure 7 and 8. By removing these genes, an increase in hemocyte count is anticipated, which is what was observed (figure 8, white arrow). Taken together, these data suggest that the oncogenic stress induced by the dominant JAK mutation is creating a pro-apoptotic environment, and likely stimulating p53 function.

57 Chang 57 The stimulation of p53 by oncogenic stress activates the canonical p53/apoptosis pathway The results for the genotypes involving overexpression of p53, as well as either gain or loss of function of genes downstream of p53 (RHG, DIAP, and Dronc) demonstrate that the canonical p53/apoptotic pathway is being activated. When DIAP is overexpressed or removed, the decrease and increase in hemocyte count, respectively, occurs as if the canonical pathway was activated (Hay et al 2004). Additionally, removing Dronc while overexpressing p53 in the hop Tum background, complies with what we would expect if the canonical p53/apoptotic pathway is activated. The activation of the canonical p53/apoptotic pathway is supported by comparing the experimental count of the hop Tum background removing Dronc and overexpressing p53 to the hemocyte count for the experimental genotype hop Tum with overexpression of p53 and loss of DIAP function. In this background, there is an increase in apoptosis, suggesting that the IAPs are participating in the cellular response to oncogenic stresses, and that the canonical p53/apoptotic pathway is being activated (Hay et al 2004). Taken together, the data presented in figures 9 and 10 strongly suggests that the canonical apoptotic pathway is being activated in response to oncogenic stress. The experimental to control hemocyte count of the overexpression of p53 and DIAP in the hop Tum background could indicate that these two proteins act antagonistically to each other, again, suggesting that the canonical pathway is being activated.

58 Chang 58 The stimulation of p53 by oncogenic stresses may additionally trigger a non-canonical cell death pathway, such as programmed necrosis The decrease seen in the experimental hemocyte count compared to the control of the hop Tum background with loss of the RHG genes and overexpression of p53 was unexpected (figures 11 and 12). The Df(3L)H99 deficiency, which deletes the RHG genes, also removes a fourth gene, sickle. All of these genes are pro-apoptotic so, by deleting four pro-apoptotic genes, it would be expected that apoptosis decrease; however, this is the opposite of what was observed. Additionally, the ratio of the experimental to control hemocyte count of this background was lower than the ratio for the hop Tum background overexpressing p53 (figure 12). It should be noted that these results were reproducible when tested again, reducing the possibility that the first test was due to outside factors or human error. Therefore, disruption of the canonical p53/apoptotic pathway during oncogenic stresses may lead to activation of an additional cell death pathway. This suggests that a non-canonical cell death pathway may be activated in response to oncogenic stress if the stress is too great or the canonical pathway is blocked or disrupted. This therefore strongly implies that overexpression of p53 under oncogenic stress can lead to the activation of both a canonical and non-canonical cell death pathway under varying circumstances and conditions. Furthermore, the increase in percentage of the hemocyte count of the last genotype in figure 12, (loss of Dronc and overexpression of p53 in the hop Tum background), is not as great as that of the genetic background containing the hop Tum

59 Chang 59 mutation and loss of Dronc alone. This, therefore, implies that cell death, other than apoptosis, is occurring. These results further suggest that the non-canonical p53/cell death pathway is being triggered in response to oncogenic stresses. Additionally, this is supported by recent studies that show p53 is involved in cross talk between the apoptotic and programmed necrosis cell death pathways (figure 3). Activation of the JNK protein exhibits anti-apoptotic properties in response to oncogenic stresses The results observed for the genetic background with the hop Tum mutation, overexpression of p53, and loss of the RHG genes (figures 9 and 10) strongly suggest that stimulation of the p53 protein under oncogenic stress could be triggering a noncanonical pathway if the canonical pathway is blocked. Studies have demonstrated that p53 is involved in a positive feedback loop with JNK and Dronc, and can prompt programmed necrosis in certain cases, which may explain the results observed in our study (Shlevkov et al 2011 and Ouyang et al 2012). It has also been shown that the activated JNK pathway can bypass the RHG genes and stimulate the function of Dronc (Fan et al 2014). However, the results for the crosses involving bsk and puc suggest that the JNK pathway may not be working to activate cell death in the hop Tum background. The decrease in hemocyte count of experimental count compared to the control in the genetic background removing bsk function in the hop Tum background instead suggests that JNK acts in an anti-apoptotic manner in response to oncogenic stresses. This is

60 Chang 60 supported by the increase in experimental to control hemocyte count in the genotype with the dominant JAK mutation and removal of puc, a downstream target of the JNK pathway, which negatively regulates JNK function. Further research would need to be conducted in order to determine the function of the JNK pathway in response to oncogenic stresses, but our results suggest that there is genetic interaction between the JAK/STAT pathway and the JNK pathway. Furthermore, overexpressing p53 in the hop Tum background in addition to manipulation of the JNK pathway would further elucidate the interaction of the JNK pathway and p53 in response to oncogenic stresses. The JNK protein has also been shown to be involved in caspace-independent cell death so, stimulation of the JNK protein through p53 or oncogenic stresses could be leading to caspace-independent cell death (Kroemer et al 2005). Cell death assays, which can demonstrate whether or not caspaces are activated, would allow us to indicate if apoptosis, or some other form of cell death, was occurring in response to oncogenic stresses. Clic acts in an anti-apoptotic manner and is involved in the canonical p53 pathway The decrease in experimental hemocyte count in the loss of Clic background overexpressing p53, when compared to the control count, strongly suggests that Clic is likely acting in an anti-apoptotic manner, and working against the cell s response to oncogenic stresses. Furthermore, in the double mutant removing Clic in the hop Tum background, while overexpressing p53, there is a significant decrease in apoptosis

61 Chang 61 when compared to the experimental hemocyte count of overexpression of p53 the wild-type background. This decrease further suggests that Clic is acting in an antiapoptotic manner. By removing Clic function, the stimulation of the IAPs by Clic cannot occur, as demonstrated by the increase in apoptosis. The decrease may not be as great, however, as loss of Clic with overexpression of p53, because the JAK/STAT pathway has been known to promote IAP function (Betz et al 2008). This data complies with what we would expect from removing a pro-apoptotic protein. Revised hypothesis Figure 16. Revised hypothesis of the cell death pathways activated during oncogenic stresses The data observed demonstrate that a non-canonical p53 cell death pathway may be activated during oncogenic stresses if the canonical pathway is blocked. Based on literature, it is possible that p53 could be stimulating programmed necrosis (shown