The role of prion protein in breast cancer cell metabolism

THE ROLE OF PRION PROTEIN IN BREAST CANCER CELL METABOLISM WONG HUIMIN IRA BMedSc (Hons) Flinders University A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF SCIENCE DEPARTMENT OF PHYSIOLOGY NATIONAL UNIVERSITY OF SINGAPORE 2012 I DECLARATION I hereby declare that the thesis is my original work and it has been written by me in its entirety. I have duly acknowledged all sources of information which have been used in the thesis. This thesis has also not been submitted for any degree in any university previously. ____________________________________ Wong Huimin Ira Feb 2013 II A. Acknowledgements I would like to thank my supervisor, Dr Wong Boon Seng, for his support and advice. Next, I would like to thank the (past and present) members of the lab including Lim Mei Li, Dr. Chua Li Min, Yong Shan May, Ong Qi Rui, Dr. Goh Hong Heng, H’ng Shiau Chen, and Elizabeth Chan. I would like to acknowledge advice, support, and friendship from Dr. Alvin Loo and Dr. Irwin Cheah. Lastly, I would like to thank those who are not named in this thesis who have contributed and supported me. III Table of Contents Declaration ..........................................................................................................I A. Acknowledgements .................................................................................. III B. Summary .................................................................................................. VI C. List of Tables ......................................................................................... VII D. List of Figures ....................................................................................... VIII E. Abbreviations ............................................................................................ II 1. Introduction ................................................................................................ 1 1.1. A review of the role of prion protein................................................... 1 1.1.1. Functional characteristics of PrP ................................................. 2 1.1.2. Structural aspects of PrP .............................................................. 3 1.1. Physiological function of PrP .............................................................. 5 1.2. Overview of cancer biology ................................................................ 7 1.2.1. Hallmarks of cancer ..................................................................... 8 1.2.2. The Warburg effect and its effect on cancer cell proliferation .. 11 1.2.3. PI3K/AKT signalling pathway and altered metabolism in cancer cells ............................................................................................ 15 1.2.4. p53 and its role in altered cancer cell metabolism ..................... 18 1.3. The Role of PrP in cancer biology .................................................... 21 1.3.1. PrP and apoptosis ....................................................................... 21 1.3.2. PrP and cancer biology .............................................................. 24 1.3.3. PrP and breast cancer biology .................................................... 26 1.4. Aims and hypothesis ......................................................................... 27 2. Materials and Methods ............................................................................. 30 2.1. Materials ............................................................................................ 30 2.2. Cell culture/cell lines ......................................................................... 32 2.2.1. MCF10A (CRL-10317TM) ......................................................... 32 2.2.2. MCF7 (HTB-22) ........................................................................ 33 2.2.3. SK-BR-3 (HTB-30) ................................................................... 33 2.2.4. MDA-MB-231 (HTB-26) .......................................................... 33 2.3. Quantitative real-time PCR analysis ................................................. 33 2.3.1. Isolation of total RNA ................................................................ 33 2.3.2. Reverse transcription of RNA .................................................... 34 2.3.3. Quantitative real-time PCR ........................................................ 34 2.3.4. TaqMan® probes ....................................................................... 35 2.4. Western blotting ................................................................................ 36 2.4.1. Cell lysis..................................................................................... 36 2.4.2. Tissue lysis ................................................................................. 36 2.4.3. SDS PAGE and western blotting ............................................... 37 2.5. Molecular cloning ............................................................................. 40 2.5.1. Gateway cloning ........................................................................ 40 2.5.2. LR cloning ................................................................................. 41 2.6. Cell transfection ................................................................................ 42 2.6.1. Dose response curve of MCF7 cells .......................................... 42 2.6.2. Stable transfection of cell lines using nucleofection.................. 43 2.6.3. Selection of transfected cell clones ............................................ 44 2.7. BrdU assay ........................................................................................ 44 2.8. Lactate assay ..................................................................................... 45 2.9. Pyruvate assay ................................................................................... 46 2.10. Lactate dehydrogenase activity assay ............................................ 47 IV 2.11. Statistical analysis.......................................................................... 47 3. Results ...................................................................................................... 48 3.1. Breast cancer tissues.......................................................................... 48 3.1.1. Low PrP protein expression in breast cancer tissues ................ 48 3.1.2. p53 protein expression remains unchanged in breast cancer tissues ......................................................................................... 49 3.1.3. Breast cancer tissue have increased total Akt protein expression but not phosphorylated Akt ........................................................ 50 3.2. Breast cancer cell lines ...................................................................... 53 3.2.1. PrP expression is higher in normal breast cell line than breast cancer cell lines .......................................................................... 53 3.2.2. Low PrP expression correlates with high proliferation rate in breast cancer cell lines. .............................................................. 55 3.2.3. p53 expression is markedly up-regulated in breast cancer cell lines SK-BR-3 and MDA-MB-231 ............................................ 57 3.2.4. Low PrP expressing breast cancer cell lines is associated with high Akt and induce Akt phosphorylation ................................. 58 3.2.5. Low PrP expression is correlated with increased glycolytic flux metabolites ................................................................................. 61 3.3. Transfected cell lines ......................................................................... 64 3.3.1. Over-expressing PrP in MCF7 cell line ..................................... 64 3.3.2. PrP reduces cell proliferation rate .............................................. 66 3.3.3. PrP reduces lactate production in HuPrP/MCF7 cells .............. 67 3.3.4. Overexpression of PrP reduced phospho-Akt (ser473) but has no effect on total Akt and phospho-Akt (thr307)............................ 68 3.3.5. PrP does not modulate p53 expression ...................................... 71 3.3.6. Over-expressed PrP reduced GLUT4 but not GLUT1 expression in MCF7 cells. ............................................................................ 72 4. Discussion ................................................................................................ 74 4.1. Concluding remarks and future directions ........................................ 87 5. References ................................................................................................ 90 V B. Summary Breast cancer is the major cause of cancer death in women in Singapore. The incidence of breast cancer will continue to escalate, owing to multiple factors. These include increased life expectancy and earlier detection, which ironically, arise from better nutrition, improved medical and healthcare, and national screening programs. The current paucity of early diagnostic markers, calls for a need to further understand the aetiology of breast cancer to provide better treatment and prevention. Breast cancer cells have been shown to exhibit the Warburg effect characterised by increased levels of glycolytic enzymes, glucose consumption and lactate production. Prion protein (PrP), a highly conserved cell surface glycoprotein known to cause neurodegenerative prion disease in human has also been implicated in cancer progression. In this project, we assessed the effect of PrP in breast cancer cells using two PrP over-expressing cell lines, namely human PrP MCF7 clone A (HuPrP/MCF7 clone A) and HuPrP/MCF7 clone B, in order to ratify our hypothesis. We found that increased PrP expression was associated with reduced proliferation rate both in a variety of breast cancer cell lines and in PrP over-expressing MCF7 cells. Our results, while preliminary, showed that PrP is associated with phosphorylated Akt at serine 473 reducing glucose transporter 4 (GLUT4) expression, resulting in increased lactate production. We speculate that PrP modulates breast cancer metabolism and is likely to be linked to the Warburg effect. VI C. List of Tables List of Tables Table 1 Table 2 Table 3 Table 4 Table 5 Title Biochemical and biophysical properties of PrPC and PrPSC Role of p53 in metabolism PCR reaction mix Antibodies for Western blotting analysis Cycling conditions for PCR VII Page 3 19 35 39 40 D. List of Figures List of Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Figure 19 Figure 20 Figure 21 Title Picture showing primary structure of PrP Picture showing the difference between oxidative phosphorylation, anaerobic glycolysis, and aerobic glycolysis (Warburg effect) Picture showing the downstream substrates of Akt and its respective function Schematic overview of PI3K/Akt signaling pathway A representative standard curve with six points for protein quantification by BCA protein assay A representation of the lactate standard curve PrP expression is reduced in breast ancer tissue p53 expression remains unchanged in breast cancer tissue Breast cancer tissue is associated with increased total Akt but not phosphorylated Akt expression PrP expression is higher in normal breast cell line (MCF10A) than breast cancer cell lines (MCF7, SK-BR-3, and MDA-MB-231) Proliferation rate in breast cancer cell lines Up-regulation of p53 in breast cancer cell lines but not MCF7 Low PrP expression in breast cancer cell lines is associated with high Akt expression and induced Akt phosphorylation Correlation between LDH-A activity, intracellular levels of pyruvate and lactate production in breast cancer cell lines Over-expressing PrP in MCF7 breast cell line Over-expressing PrP in transfected MCF7 cells reduces cell proliferation rate Over-expressing PrP in transfected MCF7 cells reduces lactate production Over-expressing PrP in transfected MCF7 cells reduces p-Akt (ser473) but has no effect on total Akt and p-Akt (thr308) Over-expressed PrP in MCF7 cells does not affect p53 expression Over-expressing PrP in transfected MCF7 cells reduces GLUT4 expression but not GLUT1 PrP expression correlates with invasiveness/malignancy of the breast cancer cell lines VIII Page 4 14 15 16 38 46 48 49 51-52 54 56 57 59-60 62-63 65 66 67 69-70 71 72-73 78 Figure 22 Figure 23 Figure 24 Schematic overview of the role of PrP in breast cancer metabolism in the study model Picture showing different lactate production in normal and cancer situation Schematic overview of the role of PrP in cancer metabolism in breast cancer cells I 80 82 83 E. Abbreviations AMV RT Avian myeloblastosis virus reverse transcriptase ANOVA Analysis of Variance ATP Adenosine triphosphate BCA Bicinchoninic acid BLAST Basic local alignment search tool BrdU Bromodeoxyuridine BSA Bovine serum albumin cDNA Complementary deoxyribonucleic acid CJD Creutzfeldt-Jakob disease CNS Central nervous system DMEM Dulbecco’s Modified Eagle’s Medium dNTP Deoxynucleotide triphosphate ER Estrogen receptor FBS Fetal bovine serum GLUT1 Glucose transporter 1 GLUT4 Glucose transporter 4 hEGF Human epidermal growth factor HRP Horseradish peroxidase HEK293 Human embryonic kidney 293 LB Luria-Betani LDH Lactate dehydrogenase mTORC2 Mammalian target of rapamycin complex 2 NAD+ Nicotinamide adenine dinucleotide II NADH Nicotinamide adenine dinucleotide (reduced) NADPH Nicotinamide adenine dinucleotide phosphate NCBI National Centre for Biotechnology Information NUS National University of Singapore PBS Phosphate buffered saline PBST Phosphate buffered saline tween-20 PCR Polymerase chain reaction PDK1 3-phosphoinositide-dependent protein kinase-1 PI3K Phosphoinositide 3-kinase PIP2 Phosphatidylinositol (3,4,5)-triphosphate PIP3 Phosphatidylinositol (3,4,5)-triphosphate PrP Prion protein PrPC Cellular prion protein PrPSc Scrapie form of prion protein PTEN Phosphatase and tensin homolog RIPA Radioimmunoprecipitation assay ROS Reactive oxygen species RT Room temperature SCO2 Synthesis of cytochrome c oxidase 2 S.D. Standard deviation Ser473 Serine 473 S.E.M. Standard error of the mean TCA Tricarboxylic acid TEMED N,N,N',N'-tetramethylethylenediamine Thr308 Threonine 308 III TIGAR TP53-induced glycolysis and apoptosis regulator TNF-α Tumor necrosis factor-α TSE Transmissible spongiform encephalopathy IV 1. INTRODUCTION 1.1. A review of the role of prion protein Prion is an acronym for proteinaceous infectious particle (Prusiner, 1982). Prion diseases, also known as transmissible spongiform encephalopathies (TSEs) (Sy et al., 2002), are a group of animal and human neurodegenerative disorders that are invariably fatal. They are often characterized by a long incubation period resulting in neuronal loss, spongiform changes and astrogliosis (Belay, 1999). Some examples of TSEs include CJD, GerstmannStraussler-Scheinker syndrome, fatal familial insomnia, kuru and many more (McNally et al., 2009). Prion diseases are infectious from exogenous sources, sporadic and/or genetic where the gene encoding the PrP is mutated (Prusiner, 1998). The mechanism of how prion causes brain damage is poorly understood. It was hypothesized that the key event underlying the development of prion disease is the post-translational conversion of normal cellular PrP (PrPC), a cell surface glycoprotein, into its pathogenic isoform, the scrapie prion (PrPSc) (Prusiner et al., 1998, Tuite and Serio, 2010) leading to progressive neuronal accumulation of the latter. This in turn causes irreversible damage to the neurons and reduces the availability of PrPC which may interfere with the presumed neuroprotective role of the protein, thus resulting in the underlying neurodegenerative process (Belay et al., 2005). 1 Prion diseases have received the limelight following an outbreak of bovine spongiform encephalopathy (BSE) infecting several cattle in Europe and scientific evidence implicating foodborne transmission of BSE to humans resulting in a lethal disease called variant CJD (Will et al., 1996). Although much is known of the role of PrP in disease processes, the normal function of PrP remains unclear. Our research laboratory has extensive experience working on prion diseases (Wong et al., 2001a, Wong et al., 2001b, Wong et al., 2001c). With the recent research emphasis on PrP and its role in cancer, we decided to divest our efforts into this area as well. Before we proceed further, it is perhaps pertinent that we first look at the normal functions and current understanding of PrP in both normal, as well as in cancer development. Unless otherwise stated, the term ‘PrP’ as used in this thesis denotes the normal cellular form PrPC. 1.1.1. Functional characteristics of PrP PrP is encoded by the highly conserved PRNP gene, consisting of two or three exons depending on the species. In humans, the PRNP gene has two exons with the entire open reading frame located in a single exon, localized in p12/p13 region of chromosome 20 (Basler et al., 1986). PrP is expressed in many organs such as the lung, heart, kidneys, gastrointestinal tract, muscle, and mammary glands, with the highest expression found in the central nervous system (Stahl et al., 1987, Brown et al., 1990, Bendheim et al., 1992). Although both the PrPc and PrPsc share the same primary structures, the 2 former is rich in α-helical secondary structures (Riek et al., 1997, Knaus et al., 2001), soluble in mild detergents (Meyer et al., 1986), exists in a stable monomeric state, and is sensitive to proteinase-K degradation (Stohr et al., 2008, Prusiner et al., 1983). Table 1 shows the comparison between the biochemical and biophysical characteristics of PrPc and PrPsc. Table 1: Biochemical and biophysical properties of PrPc and PrPsc. (Table modified from (Govaerts et al., 2004). PrPC PrPSc Non infectious Infectious Mainly α-helices Mainly β-sheets Protease K sensitive Protease K insensitive Does not aggregate Aggregate 1.1.2. Structural aspects of PrP In humans, PrP is initially synthesized as a pre-pro-PrP of 253 amino acids in the cytosol. PrP contains a hydrophobic N-terminal signal peptide of 22 amino acids while the last 22 amino acids at the C-terminus encompass the GPI anchor peptide signal sequence. Cleavage of both of these sequences results in the mature 209 amino acid residue PrP being exported to the cell surface as an N-glycosylated, glycosylphosphatidylinositol-anchored protein. Nuclear magnetic resonance at acidic pH reveals that PrP consists of a highlyconserved hydrophobic region (residues 106-126), a NH2-terminal flexible tail (residues 23-124), and a COOH-terminal globular domain (residues 125-228), 3 arranged in three monomeric α-helices, and two short β -strands flanking the first α -helix (Zahn et al., 2000). A single disulfide bond is found between cysteine residues 179 and 214. There are three sites responsible for copper binding which are found in the octarepeat region (residues 51-91) (AronoffSpencer et al., 2000). Figure 1 shows the primary structure of PrP. Full-length human PrP consists of two N-glycosylation sites at asparagine 181 and 197 (Haraguchi et al., 1989, Stahl et al., 1987) and can exist in three forms as the di-, mono-, or unglycosylated isoforms (Harris, 1999, Lehmann et al., 1999). The functions of N-linked glycans include glycoprotein trafficking, structure maintenance, and may contribute to the functional properties of membrane-associated PrP (Fiedler and Simons, 1995, Varki, 1993). Figure 1: Picture showing primary structure of PrP. (Figure taken from (Ermonval et al., 2003). PrP consists of a highly-conserved hydrophobic region, a N-terminal region, and a C-terminal region. The latter composed of three monomeric α-helices, and two short β-strands flanking the first α-helix. A single unique disulphide bridge between the two cysteines is also found in the C-terminus domain. An octarepeat region encompassing the codon 51 through 91 of the N-terminus is responsible for copper binding. 4 1.1. Physiological function of PrP While most studies are focused on the role of PrP in neurodegenerative diseases, its function outside the nervous system remains unclear. Some of the hypothesized functions of PrP include protection against apoptosis and oxidative stress, cellular survival, proliferation, differentiation, cellular uptake or binding of copper ions, transmembrane signalling, formation and maintenance of synapses and adhesion to the extracellular matrix (Nicolas et al., 2009, Westergard et al., 2007). The role of PrP in cell signalling pathways has been shown in a study where PrP was found to be localized in the lipid raft domains on the plasma membrane enriched in sphingolipids and cholesterol (Petrakis and Sklaviadis, 2006). Further research into the signal transduction patterns suggests that PrP might have a role in activating various transmembrane signalling pathways responsible for neurite outgrowth, neuronal survival or differentiation and neurotoxicity (Westergard et al., 2007). Using Prnp0/0 mice, where PrP had been deleted, impairment of the PI3K/Akt signalling pathway upon downregulation of post-ischaemic phospho-Akt expression, following postischaemic Caspase-3 activation, and neuronal injury aggravation after focal cerebral ischaemia was shown. This thus suggested a neuroprotective role of PrP through regulation of the PI3K/Akt pathway (Weise et al., 2006). Contrariwise, the neurotoxic effect of PrP was demonstrated to be induced via specific signalling cascade. Synthetic peptide PrP 106-126 which displays similar biochemical properties with PrPSC triggers PrPC signalling pathways 5 possibly through the JNK/c-Jun pathway where its activation is responsible for the PrPC mediated neurotoxicity(Carimalo et al., 2005, Pietri et al., 2006). The role of PrP in synapses was predicated upon PrP expression being upregulated at synapses, suggesting that it might play an important role in synaptic structure, function and maintenance. Kanaani et al. showed that exposure of cultured rat fetal hippocampal neurons to purified recombinant PrP resulted in rapid elaboration of axons and dendrites, and increase in synaptic contacts (Kanaani et al., 2005). Similarly, in another study, PrP facilitated synaptic transmission by inducing acetylcholine release potentiation at the neuromuscular junction (Re et al., 2006). Others have also shown PrP involvement in synapse formation and function which include reorganization of mossy fibre, circadian activity alterations, and cognition deficits in mice devoid of PrP (Colling et al., 1997, Criado et al., 2005, Tobler et al., 1996). The role of PrP in cell adhesion regulation was demonstrated in a study where PrP interacts with cell adhesion molecules such as neural cell-adhesion molecule (N-CAM). This led to the redistribution of N-CAM to lipid rafts and the activation of fyn kinase, an enzyme involved in N-CAM-mediated signalling. This process subsequently further enhanced neurite outgrowth in cultured hippocampal neurons (Santuccione et al., 2005). Graner et al. demonstrated using PC12 cells and hippocampal neurons that PrP was saturable, having specific and high-affinity receptors to laminin, which are responsible for cell proliferation, neurite outgrowth, and cellular migration (Graner et al., 2000). 6 1.2. Overview of cancer biology Cancer, also known as malignant neoplasm, is a type of genetic disease where a group of cells display uncontrolled growth (cell division beyond normal limits), invasion (invade and disrupt adjacent tissues), and oftentimes metastasis (spread to other parts of the body via the blood or lymph) (Alteri, 2011). Cancer is the leading cause of death worldwide accounting for 7.6 million deaths, approximately 13% of all deaths in 2008. The top cancer deaths include lung, stomach, liver, colon, and breast cancer. Deaths from cancer worldwide are expected to continue increasing, with an estimated 13 million deaths in 2030 (WHO, 2012). In Singapore alone, cancer is the major cause of death (Singstat, 2011). As such no effort has been spared in the search for curative, as well as palliative treatments over the past several decades. Success has been limited and the field remains a vibrant and actively researched area. Several hallmarks of cancer contribute to these challenges encountered in research and are detailed in the following sections. As an example, breast cancer is a malignancy that affects breast tissue, in particular, the inner lining of milk ducts or the lobules that supply the duct with milk (Sariego, 2010). These are termed ductal and lobular respectively. Breast cancer is the leading cause of cancer mortality in Singaporean females (MOH, 2012). Amongst all the different kinds of cancer, breast cancer is ranked fifth highest in terms of mortality rate (WHO, 2008), while according 7 to the Singapore Cancer Registry, 1 in 17 women will develop breast cancer in her lifetime in Singapore. The risk of getting breast cancer increases with age, with the most prevalent age between 50 to 59 years in Singapore women (HPB, 2009). 1.2.1. Hallmarks of cancer How then is a cancer cell different from a normal cell? Many researchers over the past decades have been studying this question. They found that most, if not all cancers have acquired the same set of features during their development as they become cancerous. These hallmarks include the ability to generate selfsustaining growth signals, insensitivity to growth-suppressor signals, resistance to programmed cell death (apoptosis), unlimited replication potential, sustained angiogenesis, tissue invasion and metastasis (Hanahan and Weinberg, 2000) and altered metabolism (DeBerardinis et al., 2008, Warburg, 1956). As the cells progress to the cancerous stage, the reliance on exogenous growth stimulation decreases and are replaced by their own signalling which involves alteration of extracellular growth signals, transcellular transducers of those signals, or intracellular circuits that translate those signals into action (Hanahan and Weinberg, 2000). Platelet-derived growth factor and tumour growth factor alpha (TNFα) are examples of cancer cell’s growth signals in glioblastomas and sarcomas respectively. Cancer cells have the ability to act as though growth hormones are present (despite an actual absence of it), thus 8 creating a positive feedback loop known as autocrine stimulation (Heasley, 2001). Nonetheless, cancer cells are capable of evading antigrowth signals possibly via modifying the components governing the transit of cells through the G1-phase of its proliferative cycle. This in turn allows the cancer cell to maintain their replicative capacities and fuel their uncontrolled growth and division (Hanahan and Weinberg, 2000). Apoptosis is an important process for normal development and it is a way to remove cells with DNA damage. Unlike normal cells, cancer cells are able to evade apoptosis, which result in infinite growth and division (Hanahan and Weinberg, 2000). p53, the tumour suppressor gene, is an important target of cancer. Approximately 50% of all human cancers show defects involving p53, resulting in functional inactivation of its product and subsequent removal of a key component of the DNA damage sensor that can induce the apoptotic effector cascade (Harris, 1996). Also, under normal circumstances, with each successive cell division, telomeres progressively shorten by about 50-100 bp. This eventually halts cell division as the telomeres become too short, hence resulting in replicative cell senescence (Counter et al., 1992). Cancer cells however achieve immortalization and infinite replicative potential through lengthening their telomeres via the addition of hexanucleotide repeats by the action of telomerase enzyme on the ends of telomeric DNA (Bryan and Cech, 1999). 9 In order for cancer cells to sustain growth, cellular function and survival, it is essential for cancer cells to induce angiogenesis (formation of new blood vessels and sustained blood vessel growth) for oxygen and nutrient supply (Hanahan and Weinberg, 2000). This switch is induced by modulating the balance of angiogenesis inducers and countervailing inhibitors, probably involving gene transcription (Hanahan and Folkman, 1996). As cancer cells acquire genetic alterations making them autonomous, it gives them the ability to separate from the primary tumour, spreading via the lymphatics and blood vessels, and invading into other parts of the body to form secondary lesions. This ability to spread and ‘reside’ in other parts of the body is known as metastasis — the final stage of cancer development that causes 90% of human cancer deaths (Sporn, 1996). Altered metabolism is a hallmark initially described nearly a century ago, showing the differential aspects of cellular metabolism in cancer cells relative to normal differentiated cells (DeBerardinis et al., 2008, Warburg, 1956). This hallmark is very important for cancer cells as they need to satisfy the intense demands for growth and proliferation. Advancements over the past decade have shown that the aberrant cellular metabolism of cancer is caused by a combination of genetic lesions and nongenetic factors such as the tumour microenvironment (Hsu and Sabatini, 2008, Vander Heiden et al., 2009). However, there remains innumerable gaps in our knowledge of how, what, and where cancer cells rewire their cellular metabolism, due to the fact that cancer itself is a disease that is complex and heterogenous in nature. As such, a single 10 model of altered tumour metabolism will not fully encapsulate the sum of metabolic changes that can support cancer cell growth (Greaves and Maley, 2012). Thus, any investigation into cancer cell metabolism will lend support to delineating missing pieces of the puzzle, with the grand aim of advancing knowledge that leads ultimately to discoveries of novel cancer treatment options. In the next section, I will discuss in greater depth what the altered metabolism in cancer cells is, how it differs from normal cells, and why this is so vital to cancer cell proliferation. 1.2.2. The Warburg effect and its effect on cancer cell proliferation Generally, the cellular processes for cell proliferation and metabolism are closely knit (Fritz and Fajas, 2010). The metabolic programme of normal resting cells function to maintain homeostatic processes through adenosine triphoshate (ATP) production (Vander Heiden et al., 2009). In the presence of oxygen, most normal resting cells metabolize glucose to pyruvate through glycolysis, and then completely oxidize a large fraction of the generated pyruvate to carbon dioxide in the mitochondria through oxidative phosphorylation. This process yields 36 ATP from one molecule of glucose (Fig 2). However, in the absence of oxygen, normal cells redirect pyruvate away from mitochondrial oxidation or tricarboxylic acid (TCA) cycle and instead largely reduce it to lactate via anaerobic glycolysis (Vander Heiden et al., 2009). 11 In normal proliferating cells, the metabolic programme must generate enough energy to support cell replication and also meet the energetic requirements for anabolic demands from macromolecular biosynthesis and maintenance of cellular redox homeostasis in response to increased production of toxic reactive oxygen species (ROS). ROS are produced during stressful situations in the cell and they are highly reactive radicals capable of causing significant damage to cell structures. Too much ROS in the cells cause oxidative stress, resulting in cells arresting in cell-cycle, and after prolonged arrest, death from apoptosis. This is not favourable to cells which are undergoing proliferation (Burhans and Heintz, 2009). However, ROS are not always deleterious: they act as messengers in signalling cascades involved in cell proliferation and differentiation. For example, ROS are produced at low concentrations during the interaction between growth factors and receptors. This is essential to activate proliferative signalling for cell division (Chiu and Dawes, 2012). Thus there is a need for redox homeostasis in the cell. This process is also a significant requirement for a growing tumour cell (Cantor and Sabatini, 2012). In contrast to normal cells, rapidly proliferating cells or cancer cells metabolize glucose to lactate, even in the presence of oxygen, despite the process being far less efficient in net ATP production per molecule of glucose (Fig 2) (Vander Heiden et al., 2009). Such a process is called ‘aerobic glycolysis’ or the Warburg effect. Although aerobic glycolysis has low efficiency in ATP yield per molecule of glucose, it can generate far more energy than oxidative phosphorylation by producing ATP at a faster rate (Pfeiffer et al., 2001). It was hypothesized that aerobic glycolysis or the 12 Warburg effect benefits cancer cells in several ways. Firstly, the glycolysis process is highly interconnected with several other metabolic pathways — particularly those associated with de novo synthesis of cellular building blocks where many glycolytic intermediates serve as substrates. This is important for fast cell growth as it maintains large pool sizes of glycolytic intermediates such as nicotinamide adenine dinucleotide phosphate (NADPH), acetyl-coA, and ATP, which are needed for anabolic reactions (Hume and Weidemann, 1979, Vander Heiden et al., 2009). Next, increased aerobic glycolysis is postulated to support cancer cell survival, growth and invasion by conditioning the tumour microenvironment (Koukourakis et al., 2006) through starving their neighbours. This provides cancer cells more opportunities for invasion and gaining of space for growth (Gillies and Gatenby, 2007). Thirdly, with more glycolysis more ROS will be produced to increase cell proliferation and survival via post-translational modification of kinases and phosphatases (Giannoni et al., 2005, Lee et al., 2002). The Warburg effect has been clinically exploited for diagnostic benefit through the use of Positron Emission Tomography (PET) with the glucose analogue, 2-deoxy-2-[18F] fluoro-D-glucose (FDG), as a tool for detecting and staging malignancies (Groves et al., 2007). However, drugs that act by targeting the metabolic alteration in cancer have yet to be developed — despite much speculation — and may be a potential therapeutic target for tumour tissues within cancer patients. However, there are challenges that need to be resolved when targeting tumour metabolism, given that normal proliferating cells share similar metabolic needs and adaptations (Wang and 13 Green, 2012). In addition, although the mode of metabolic alteration necessary to support proliferative requirements is a hallmark of cancer, a single conceptual model for the cancer metabolic programme does not exist. This is due to the biological variability across cancer types, the diversity among tumours of the same subtype, and the heterogeneities present even within a single tumour ‘clone’ (Cantor and Sabatini, 2012). Thus it is expected that many metabolic signatures and distinct dependencies may arise across the neoplastic cells. Figure 2: Picture showing the difference between oxidative phosphorylation, anaerobic glycolysis, and aerobic glycolysis (Warburg effect). Figure taken from (Vander Heiden et al., 2009). 14 Accordingly, normal cells possess a variety of checkpoints to enable correct maintenance of the signalling and transcriptional circuitry that modulates cell growth, but various tumorigenic lesions impart cancer cells with the ability to evade proper regulation. 1.2.3. PI3K/AKT signalling pathway metabolism in cancer cells and altered Dysregulation of oncogene signalling cascades is implicated in altered metabolism, apoptosis and other phenotypic features observed in cancer cells (DeBerardinis, 2008). In this section, emphasis will be placed on the molecular mechanisms of Akt in cancer. In particular, the way Akt is involved in the metabolic switch to favour aerobic glycolysis (Warburg effect) in cancer cells will be discussed. Figure 3: Picture showing the downstream substrates of Akt and its respective function. Figure taken from (Bellacosa et al., 2005). 15 Akt has pleiotropic functions and is a central player in several distinct pathways. Once activated, Akt can phosphorylate many intracellular targets to mediate several downstream signalling cascades leading to several diverse biological effects such as cell proliferation, survival, glucose uptake, and metabolism as shown in Fig 3 (Bellacosa et al., 2005; (Coffer et al., 1998, Lawlor and Alessi, 2001). As Akt is implicated in numerous pathways that are crucial for cancer development, it is obvious why Akt is a major therapeutic target for cancer (Bellacosa et al., 2005). With Akt having such central yet diverse roles in cancer progression, we decided to begin dissecting the interconnections through a focus on its role in the metabolic pathway (Fig 4). Hopefully, this will cast new insights and open up further avenues for research. Figure 4: Schematic overview of PI3K/Akt signalling pathway. 16 A discussion of Akt will invariably need to start from its upstream effector, phosphoinositide 3-kinase (PI3K). PI3K is a heterodimeric protein consisting of two functional subunits, the 85 kDa regulatory subunit, and a 110 kDa catalytic subunit. Activation of the PI3K signalling pathway is induced by prosurvival signals such as cytokines, growth factors, hormones, and Ras activation. Ras binds directly to the Src homology 2 domain in the p85 regulatory subunit. This leads to the activation of the p110 catalytic subunit resulting in the phosphorylation of phosphatidylinositol 4,5-bisphosphate (PIP2) to phosphatidylinositol (3,4,5)-triphosphate (PIP3). This process is inhibited by phosphatase and tensin homolog (PTEN), a tumour suppressor. PTEN is located on chromosome 10 and its deletion or mutation leads to several human cancers (Vivanco and Sawyers, 2002). PTEN works as a negative regulator of PI3K dephosphorylating PIP3 back to PIP2 resulting in the deactivation of PI3K signaling pathway. Now, an important downstream effector of the PI3K pathway is protein kinase B, also known as Akt. Through its pleckstrin homology domain, Akt interacts with PIP3 and undergoes a conformational change allowing 3- phosphoinositide-dependent protein kinase-1 (PDK1) to phosphorylate Akt at threonine 308 (thr308). Mammalian target of rapamycin complex 2 (mTORC2) phosphorylates a second site on Akt, serine 473 (ser473) to allow maximum activation of Akt (Guertin and Sabatini, 2007). 17 Over-activation of PI3K/Akt signalling pathway is important for cancer survival and progression as it contributes to the Warburg effect via several mechanisms. Firstly, the activation of Akt signalling pathway promotes the translocation of glucose transporter (GLUT4) from the cytosol to the plasma membrane, thus increasing glucose uptake (Whiteman et al., 2002, Lawlor and Alessi, 2001). Secondly, activation of Akt stimulates mitochondria-associated hexokinase activity, a glycolytic enzyme, promoting HKII translocation to the outer mitochondrial membrane and interacts with the permeability transition pore to promote cell survival (Gottlob et al., 2001). The stimulated hexokinase activity also initiates glycolysis and the pentose phosphate pathway by phosphorylating glucose to form glucose-6-phosphate resulting in increased influx of glucose into the cell along its concentration gradient (Robey and Hay, 2006). Thirdly, activation of Akt pathway induces the expression of another glycolytic enzyme, phosphofructokinase, that phosphorylates fructose-6phosphate to fructose-1,6-bisphosphate, thus driving up glycolysis rate (Vander Heiden et al., 2001). 1.2.4. p53 and its role in altered cancer cell metabolism Recent studies have pointed to the multifaceted role for p53 in metabolic control (Gottlieb and Vousden, 2010). p53 transcription factor is one of the important components for protecting cells against stresses that may otherwise initiate tumorigenic progression. Activation of p53 offers anticancer mechanisms via maintainence of genomic integrity, DNA repair, cell-cycle arrest, and apoptosis (Vogelstein et al., 2000). This makes p53 an important tumour suppressor as approximately 50% of all human cancers consist of 18 mutations or deletions in the TP53 encoding gene. Baker et al. reported in their study that 26% of women with breast cancer harboured p53 mutations. (Baker et al., 2010). Since p53 has protective functions against tumorigenic progression, it is not surprising that p53 also directs metabolic characteristics consistent with those of normal resting cells, in particular, their involvement in glucose metabolism through regulating glycolysis and the concomitant stimulation of oxidative phosphorylation. The functions of p53 in metabolism is shown in Table 2 and further elaborated below. Table 2: Roles of p53 in metabolism. Studies that demonstrated p53 roles in metabolism. Roles of p53 in metabolism Induces synthesis of TP53-induced Bensaad et al., 2006 glycolysis and apoptosis regulator (TIGAR) expression Induces synthesis of cytochrome Matoba et al., 2006 oxidase 2 (SCO2) Involved in glucose metabolism in a Jiang et al., 2011 transcription-independent manner Repress the transcriptional activity of Schwartzenberg-Bar-Yoseph et al., GLUT1 and GLUT4 gene promoters 2004 p53 transcriptionally induces synthesis of TIGAR expression which lowers fructose-2,6-bisphosphate levels in cells. This results in an inhibition of glycolysis (Bensaad et al., 2006). p53 also transcriptionally induces the synthesis of SCO2 which is needed for correct assembly of the cytochrome c 19 oxidase complex in the mitochondrial electron transport chain. This ensures mitochondrial respiration takes place without disruption (Matoba et al., 2006). Next, p53 may also be involved in glucose metabolism in a transcriptionindependent manner via direct binding and inhibition of glucose-6-phosphate dehydrogenase (G6PDH) in the cytoplasm (Jiang et al., 2011). G6PDH, is involved in a rate-limiting step catalysing the first reaction in the diversion of glucose-6-phosphate to the oxidative pentose phosphate pathway (PPP). Consequences for G6PDH inactivation include dampening of the biosynthetic programmes, arising from reductions to ribose-5-phosphate (nucleoside biosynthesis) and NADPH (lipid biosynthesis) levels. p53 is also found to repress the transcriptional activity of GLUT1 and GLUT4 gene promoters (Schwartzenberg-Bar-Yoseph et al., 2004). The reduction of GLUT1 and GLUT4 can lead to dampening of glycolysis as glucose flux into the cells is decreased and is thus able to inhibit the Warburg effect in cancer cells. In addition, compared to wild-type p53, the p53-deficient cells demonstrate increased glucose flux into the oxidative PPP and marked elevation of NADPH levels and lipogenic rates (Jiang et al., 2011). Therefore, the above points show that p53 plays a major role in the metabolism of cells. Apart from these, it was reported that p53 directly regulates the transcription of PrPC (Vincent et al., 2009) but its role in 20 metabolism, particularly cancer metabolism, is not known. So it is of great interest to investigate the relationships, if any, between prion, p53 and Akt in cancer metabolism. 1.3. The Role of PrP in cancer biology Although PrP is known to be highly expressed in the nervous system, this protein has been detected in various other systems throughout the body such as lymphoid cells, lung, heart, kidney, gastrointestinal tract, muscle, and mammary glands. Since then, emerging studies have implicated PrP in cancer biology, involving the cells’ resistance to apoptosis, proliferation, and metastasis. 1.3.1. PrP and apoptosis The role of PrP in anti-apoptotic activity has been studied in a range of experimental systems such as in mice, cultured mammalian cells, and yeast. However, the role of PrP remains unclear although their results suggest a common mechanism for its cytoprotective activity. The generation of a PrP knockout mice using homologous recombination in embryonic stem cells such as Prnp0/0 (Zürich I) and Prnp-/- (Edinburgh) display distinct neurophysiological alterations and progressive demyelination in the peripheral nerves (Bueler et al., 1992, Mehrpour and Codogno, 2010). 21 Following that, the development of PrP knockout mice lines such as Prnp-/(Nagasaki), Rcm0, and Prnp-/- (Zürich II) displayed ataxia and age-related Purkinje cell loss. The reintroduction of Prnp-encoding transgene into Nagasaki, Zürich II, and Rcm0 PrP-null mice has been shown to reverse the neurodegeneration effect, suggesting a neuroprotective function of PrP (Moore et al., 1999, Sakaguchi et al., 1996). The use of N-terminally deleted forms of PrP in transgenic mice also demonstrated the neuroprotective activity of PrP. Following PrP deletions (∆32-121 or ∆32-134), the mice displayed severe ataxia and progressive neurodegeneration limited to the granular layer of the cerebellum as early as 1-3 months after birth. The introduction of single copy wild-type PrP gene completely abolishes the defect (Shmerling et al., 1998). Utilising human primary neurons, PrP (having the intact octarepeat region) was found to inhibit Bax (Bcl-2 associated X protein)-mediated neuronal apoptosis in spite of the GPI anchor signal peptide truncation (Bounhar et al., 2001). It was therefore hypothesized that the octarepeat region of PrP is important for the anti-Bax function since the domain displays similarity with the BH2 domain of B-cell lymphoma (Bcl-2) which is required for inhibition of apoptosis. In another study, familial PrP mutations D178N and T183A associated with the human prion diseases has been shown to partially or completely abolish the neuroprotective function of PrP against Bax (Roucou and LeBlanc, 2005). Using co-expression of various Syrian hamster PrP mutants in MCF-7 cells and primary human neurons, it was found that the PrP in the cytosol is responsible for the Bax inhibition activity (Lin et al., 2008, Roucou et al., 2003). However, the physiological importance of cytosolic PrP 22 remains uncertain as in vivo generation of this form of PrP from the wild-type molecule appears to be modest (Stewart and Harris, 2003). Studies indicate that the cytoprotective effect of PrP is very specific for Bax. Nevertheless, it was proposed that PrP does not interact directly with Bax to prevent cell death but rather, works with Bcl-2 to maintain the inactive state of Bax and thence grant neuroprotection in mammalian cells (Roucou et al., 2005, Roucou and LeBlanc, 2005). Notwithstanding, it currently remains inconclusive whether PrP really has its role in Bax to confer neuroprotection. This is because in a yeast study (S.cerevisiae), a form of mouse PrP encompassing a charged region of residue 23-31 and containing a modified signal peptide has been shown to dampen cell death in yeast expressing mammalian Bax from a galactose-inducible promoter despite the deletion of the octapeptide repeat region (Li and Harris, 2005, Westergard et al., 2007). In addition, in the Bax-expressing yeast study, cytosolic PrP (23-231) failed to demonstrate a rescue effect in growth, suggesting that the anti-apoptotic activity requires targeting of PrP to destinations of the secretory pathway (Li and Harris, 2005, Westergard et al., 2007). Therefore, the anti-apoptotic effect of PrP in yeast appears to be dependent on its interactions with endogenous yeast proteins downstream of Bax during cellular stress (Li and Harris, 2005). In contrast to these studies, using cultured hippocampal neurons, primary cultures of mouse cerebral endothelial cells expressing PrP and retina, the hydrophobic, amyloid PrP fragment 106-126 has been shown to increase toxicity (Deli et al., 2000, Ettaiche et al., 2000). Extending these studies, PrP 23 fragment 106-126 exposure to primary culture of murine cortical neurons and transgenic mice 338 cortical neurons has resulted in neuronal death within 24 hours which might be due to activation of c-Jun-N-terminal kinase (Crozet et al., 2008). Overexpression of PrP in human embryonic kidney 293 cell lines, rabbit epithelial Rov9 cell lines, and murine cortical TSM1 cell line resulted in cells sensitive to the apoptotic inducer, stauroporine, a response involving Caspase-3 activation via transcriptional and post-transcriptional control of p53 (Paitel et al., 2003, Paitel et al., 2004) 1.3.2. PrP and cancer biology Supporting studies have shown plausible implications of the role of PrP in cancer biology. PrP has been found to be required for the proliferation of enterocytes and this could be due to its interaction with desmoglein and c-Src, observed using co-immunoprecipitation experiments (Morel et al., 2008). cSrc is a tyrosine kinase and its activation promotes cellular proliferation and survival (Marcotte et al., 2012) thus suggesting that PrP might be involved in the activation of c-Src to induce cell proliferation. Given that PrP is needed for cell proliferation in enterocytes, it is not surprising that PrP has also been shown to play a role in colon cancer. PrP neutralising antibodies have been shown to suppress tumour growth in HCT116, a human colon cancer cell line model (McEwan et al., 2009). PrP has also been found to be essential in ensuring cell survival after cells receive apoptotic signals (Ponder, 2001, Kumar et al., 2004, Makin and Dive, 24 2001). Overexpression of PrP has been shown to prevent tumour necrosis factor alpha (TNF-α)-induced apoptosis in MCF7 cells. The exact mechanism is unknown but PrP is able to prevent cytochrome c release from mitochondria and nuclear condensation (Diarra-Mehrpour et al., 2004). Subsequent studies show that silencing of PrP expression in human breast adenocarcinoma TNFrelated apoptosis inducing ligand (TRAIL) sensitive MCF7 cell line and its two resistant counterparts, the multidrug resistant MCF7/ADR and TRAILresistant clones, have been shown to mediate Bax activation upon downregulation of Bcl-2 expression. This in turn sensitizes breast cancer cells to TRAIL-induced apoptosis associated with caspase processing, Bid cleavage and MCL-1 degradation (Clohessy et al., 2006, Mehrpour and Codogno, 2010). Subsequent studies using siRNA to knockdown PrPc expression in gastric cancer MKN28 cells resulted in the cells becoming sensitive to hypoxiainduced drug sensitivity (Liang et al., 2007). PrP has also been shown to promote cancer metastasis and invasiveness. Pan et al. showed that PrPc expression in gastric cancer lines SGC7901 and MKN45 significantly promotes adhesive, invasive, and in vivo metastatic capabilities of the cells in conjunction with increased promoter activity and up-regulation of matrix metalloproteinase-11 (MMP11) expression, a protease which is needed for cancer cell invasion. The N-terminal fragment of PrPc was implicated to promote invasion and metastasis at least in part of the MEK/ERK pathway activation and subsequent MMP11 transactivition upon activity of ERK1/2 phosphorylation (Pan et al., 2006). In another study PrPc over-expression was demonstrated to promote carcinogenesis, G1/S-phase 25 transition, and proliferation in SGC7901 and AGS gastric cancer cells at least in part via mediating the PI3K/Akt pathway activation and subsequent CyclinD1 transactivation, in which the octapeptide repeat region might play an obligatory role (Liang et al., 2007). As PrP has been shown to affect multiple aspects of cancer development, it has been suggested that PrP might serve as a biomarker for cancer aggressiveness. The incompletely processed form of PrP, the pro-prion, could be used as a biomarker for pancreatic cancer because a subpopulation of pancreatic cancer patients with pro-prion displays shorter survival than patients without it (Li et al., 2009a). 1.3.3. PrP and breast cancer biology The contribution of PrP to breast cancer biology has been shown by several studies (Li et al., 2009b, Li et al., 2011, Liang et al., 2009, Meslin et al., 2007b, Roucou et al., 2005, Yu et al., 2012). The role of PrP in MCF7 in inhibiting TNF (Diarra-Mehrpour et al., 2004) or Bax induced cell death (Roucou et al., 2005) was explained in the previous section. Studies by Meslin et al. have demonstrated that the expression of PrPc is associated with adjuvant chemotherapy resistance in patients with estrogen receptor (ER)-negative breast cancer, where 15% patients displayed positive PrPc expression in primary breast cancer tissue. Therefore, tumours expressing PrPc did not seem to benefit from chemotherapy (Meslin et al., 2007a). 26 Silencing of PrP expression in adriamycin-resistant MCF7 (MCF7/Adr cells) was reported to sensitise the cells to TRAIL inducing cell death (Meslin et al., 2007b). More recently, an opposing study indicated that PrP knockdown in MDA-MB-435 breast cancer cell increased resistance of the cells to chemotherapeutic drug doxorubicin-induced cytotoxicity (Yu et al., 2012). These disparate results clearly indicate that the role of PrP in cancer biology is far from being clear and that further studies are definitely required to understand the role PrP has in breast cancer biology, for us to be able to elucidate the physiological function of PrP. Against this backdrop of possible roles PrP play in cancer development, it is perhaps helpful for us to return to a consideration of some fundamental aspects of cancer biology and its signalling pathways. This way, it would provide us with further insights into outstanding uncertainties in the relationship between PrP and cancer development. 1.4. Aims and hypothesis Since there are numerous studies demonstrating strong association between the metabolic pathways and other factors that regulate the hallmarks of cancer such as uncontrolled proliferation and resistance to apoptosis, a thorough investigation of the many metabolic enzymes, intermediates and products governing the switch of metabolic activities in cancer is crucial to expand possible areas for disease-modifying therapies and discovery of new biomarkers for the presence and progression of tumourigenesis. 27 Taken together, the reports suggest PrP has a role in increasing the aggressiveness of cancers. This has been shown to be mediated by the c-Src and MEK/ERK pathway. As discussed in section 1.2.3 and 1.2.4, Akt activation and aerobic glycolysis also contributes to a more aggressive cancer phenotype. However the link between PrP, p53, Akt activation and aerobic glycolysis has never been investigated As such, we hypothesize that PrP might activate Akt which in turn leads to increased proliferation and the metabolic switch from oxidative phosphorylation to aerobic glycolysis. Given that breast cancer is the most common form of cancer in women in Singapore, we chose to base our studies on breast cancer tissues and cells, to address our hypothesis. This will then lead on to the finding of early markers for therapeutic intervention that has disease modifying effect, in hope of bringing down death due to breast cancer. In addition, the contribution of PrP to breast cancer biology has been shown by various studies, yet the role of PrP is still unclear. Thus far, it remains unclear what role PrP has in breast cancer metabolism. In this study, we will use (a) normal breast tissue vs breast cancer tissue, (b) normal breast cell line vs breast cancer cell lines, and (c) breast cancer cell line clones overexpressing PrP. Hence the aim of our study is to investigate: 28 1) If PrP is differentially expressed in: a. Normal breast tissue vs breast cancer tissue b. Normal breast cancer cell line vs breast cancer cell lines 2) Differences, if any, between (1a) and (1b) in terms of: a. p53 b. Akt c. Surrogate markers for metabolic activity, i.e. pyruvate, LDH-A, lactate production, and/or glucose transporters 3) To verify the results using breast cancer cell line clones stably overexpressing PrP. 29 2. MATERIALS AND METHODS 2.1. Materials Avian myeloblastosis virus reverse transcriptase (AMV RT), deoxynucleotide triphosphates (dNTPs), Oligo(dT) primer and CytoTox 96 Non-radioactive Cytotoxicity Assay kit were purchased from Promega (Madison, WI, USA). Radioimmunoprecipitation assay (RIPA) buffer, anti-p53 (Cat# 9282), antiAkt (pan) (Cat# 4691), anti phospho-Akt (ser473) (Cat# 9271), anti phosphoAkt (thr308) (Cat# 9275), and anti-Glut4 (Cat# 2299) were purchased from Cell Signaling Technology (Danvers, MA, USA). Anti PrP 8H4 was from Case Western Reserve University. Anti-Glut1 (Cat# 07-1401), Horse Radish Peroxidase (HRP)-conjugated goat anti-mouse IgG (Cat# AP181p), and HRPconjugated goat anti-rabbit IgG (Cat# AP187p) were purchase from Millipore (USA). Rabbit anti-beta actin (Cat# A2066), mouse anti-beta actin (Cat# A5316), cholera toxin, and ponceau S were purchased from Sigma-Aldrich (USA). Phosphatase inhibitor cocktail, PhosSTOP, and protease inhibitor cocktail, and cell proliferation ELIZA, BrdU were purchased from Roche (Basel, Switzerland). Fetal Bovine Serum (FBS), Dulbeccos Modified Eagles Medium (DMEM), sodium pyruvate, horse serum, human epidermal growth factor (hEGF), and One Shot TOP10 E. Coli, TRIzol, Taqman probes, pENTR™ Directional 30 TOPO® Cloning Kit , pcDNA6.2/V5-DEST, LR clonase, and blasticidin S were purchased from Invitrogen (Eugene, OR, USA). Bicinchoninic acid (BCA) protein assay kit was purchased from Pierce (USA). Nitrocellulose membrane 0.22 µm pore size, 30% acrylamide/bis 37.5:1 solution, ammonium persulfate N,N,N',N'-tetramethylethylenediamine (TEMED), 0.5 M Tris-HCl pH 6.8, 1.5 M Tris-HCl, pH 8.8, and Precision Plus protein dual color standards were purchased from Bio-Rad (Hercules, CA, USA). Gels were cast according to instructions from Bio-Rad (Hercules, CA, USA) and used within 3 days of casting. Phosphate buffered saline (PBS) was prepared from 10X concentrated solutions purchased from 1st Base Asia (Singapore). Molecular biology grade agarose, and sodium dodecyl sulfate (SDS) were also purchased from the same company. RNeasy Mini kit, and Plasmid Midi Kits were purchased from Qiagen (Hilden, Germany). Luria-Bertani (LB) broth was purchased from BD Dilfco (NJ, USA). For cell cloning, we used Amaxa® Cell Line Optimization Nucleofector® Kit which was purchased from Lonza (Germany). The lactate assay and pyruvate assay kit were purchased from BioVision (CA, USA). 31 2.2. Cell culture/cell lines MCF10A cell line was a generous gift from Dr. Lih Wen Deng, Department of Biochemistry, National University of Singapore (NUS). MCF7, SK-BR-3, and MDA-MB-231 cell lines were generous gifts from Prof. H. Phillip Koeffler, Department of Medicine, Yong Loo Lin School of Medicine, NUS. MCF10A cells are cultured in DMEM with 10% horse serum, 100 ng/mL cholera toxin, 10 µg/mL hEGF, and 0.5 mg/mL hydrocortisone. The rest of the cell lines used in this study were cultured in DMEM supplemented with 10% FBS, with sodium pyruvate. All cell lines were subsequently maintained at 37°C in a humidified incubator supplied with 5% CO2. 2.2.1. MCF10A (CRL-10317TM) MCF10A cells are immortalized, non-transformed epithelial cell line derived from human fibrocystic mammary tissue. They are defined as “normal” breast epithelial cells because they have a near diploid karyotype and are dependent on exogenous growth factors for proliferation. Studies have shown that they do not have the ability to form tumours in nude mice and are unable to grow in anchorage independent assays (Soule et al., 1990). 32 2.2.2. MCF7 (HTB-22) MCF7 cells are immortalized, adherent epithelial cells derived from human adenocarcinoma mammary tissue. They are estrogen receptor (ER) positive cell lines having hypertriploidy to hypotetraploidy karyotype. 2.2.3. SK-BR-3 (HTB-30) SK-BR-3 cells are immortalized, adherent epithelial cells derived from human breast adenocarinoma. They are ER negative near triploid cell line. 2.2.4. MDA-MB-231 (HTB-26) MDA-MB-231 cells are immortalized, adherent epithelial cells derived from human breast adenocarinoma. They are ER negative near triploid cell line. 2.3. Quantitative real-time PCR analysis 2.3.1. Isolation of total RNA RNA extraction for all cell lines was done using TRIzol reagent. A confluent T-25 flask (Nunc) of cultured cells was used. Cells were scraped and harvested in 1X PBS, which was followed by a centrifugation step to yield a cell pellet. This is followed by adding 500 µL of Trizol reagent. To ensure thorough lysis of cell pellet, the lysate was homogenized by 20 passages through a 22G 33 needles. The lysate was then processed following manufacturer’s instructions provided in the material datasheet up to the RNA precipitation stage. The precipitated RNA fraction was then subjected to an additional clean-up step using the RNeasy Mini kit. RNA samples were typically eluted twice in 40 µL of RNase free water provided in the kit. Consequently, Nanodrop™ 2000 was utilized for determination of the purity and concentration of RNA. 2.3.2. Reverse transcription of RNA Typically, 1 µg of total RNA extracted was adjusted to a total volume of 11 µL with sterile Milli-QTM water and then heated at 70 °C for 10 mins and placed on ice before master-mix containing the AMV reverse transcriptase was added. The master-mix consists of 4 µL 5X reverse transcription buffer, 2 µL 10 mM dNTP mixture, and 1.5 µL oligo(dT)15 Primer. The resulting mixture was then incubated at 42°C for 20 mins to allow for cDNA synthesis. Lastly, the cDNA was heated at 95°C for 5 mins and placed on ice for another 5 mins to inactivate the reverse transcriptase enzyme. The complementary deoxyribonucleic acid (cDNA) is now ready to use for quantitative RT-PCR. 2.3.3. Quantitative real-time PCR Each real-time PCR reaction was performed using 200 ng of cDNA. Samples were ran in duplicates in volumes of 20 µL each. Specific TaqMan probes were used for the detection of various gene products. A typical reaction setup consists of the following components: 34 Table 3: PCR reaction mix Component Volume (µL) 2× TaqMan® Gene Expression Master Mix 20× TaqMan® probe Nuclease free water cDNA Total volume Volume (µL) 10 1 7 200 ng 20 Reactions were then run in a 96-well format on a StepOnePlus™ Real-time PCR system (Life Technologies, Carlsbad, California USA) using the default cycling conditions. For each real-time PCR, a minimum of n=3 sets of samples were used and each sample ran in duplicates to ensure accuracy. Statistical analysis of the results was done using the Student’s t-test. 2.3.4. TaqMan® probes The expression levels of the following genes were investigated using quantitative real-time PCR and TaqMan probe-based chemistry (Life Technologies, Carlsbad, California USA); Human actin (Hs99999903_m1), and human PrP (Hs00175591_m1). These probes span the exon(s) of the targeted genes and the assays were performed according to the manufacturer’s instructions. 35 2.4. Western blotting 2.4.1. Cell lysis Cells for western blot analysis were cultured in T75 flasks. Cells are harvested at approximately 80% confluency. Briefly, the complete media was removed from the flask and was rinsed with 1X PBS twice to remove excess media. The cells were then mechanically scraped using a cell scraper (SPL Life Sciences, Korea). Cells were collected in ice-cold PBS and centrifuged at 600 g for 5 mins to obtain a cell pellet. Subsequently, the cell pellet is resuspended in 1X RIPA buffer. 1X RIPA buffer was prepared by adding one tablet of Complete Mini protease inhibitor tablet and one tablet of PhosSTOP phosphatase inhibitor cocktail tablet and topped up to 10 mL. The suspended pellet was then subjected to sonication for 3 mins to ensure thorough lysis. The resulting lysate was then incubated on ice for 30 mins. Finally, lysates were centrifuged at 14,000 g for 10 mins at 4°C to collect the supernatant. Lysates were stored as aliquots in –80°C prior to use. 2.4.2. Tissue lysis The human breast tissues were from NUH-NUS tissue repository. All breast tumour tissue samples were invasive ductal carcinoma (grade 3) while normal breast tissues were from the same donor. Invasive ductal carcinoma is the most common invasive breast cancer. Grade 3 denotes tumours are spreading more aggressively. 36 Breast tissues were weighed using an electronic balance and 1X RIPA buffer was added at 20% (w/v) ratio. The tissues were homogenized using a PowerGen homogenizer (ThermoFisher Scientific, Waltham, USA) on ice and then sonicated on ice for 3 times at 10 seconds each, until cells were completely disrupted. The homogenate was then centrifuged at 14,000 g for 30 mins at 4°C. The supernatant was collected in aliquots and stored at –80°C. 2.4.3. SDS PAGE and western blotting The protein concentration of the samples and protein standards were processed by diluting with assay reagent and assayed with BCA protein assay. Absorbance was read at 562 nm after 30 mins of incubation at 37 °C. Background absorbance was substracted from readings of all standards, controls and samples, including the no-protein control. The values for the protein standards were plotted with a linear regression line through the standard points. The protein concentrations of the samples were then calculated from the equation of the absorbance-concentration relationship, followed by multiplying with the dilution factor. Lysates were added to a 4X loading buffer, and boiled at 95°C for 5 mins. Samples were loaded, electrophoresed on 5% stacking gel at 70 V and either 7.5% or 10% SDSPAGE gel at 100 V for 1 to 2 hrs using Mini-PROTEAN Tetra electrophoresis system (Bio-Rad Laboratories, Hercules, California USA). The Precision Plus protein standard dual colour was used as a molecular weight standard and ran alongside the samples on the same gel. 37 Figure 5: A representative standard curve with six points for protein quantification by BCA protein assay. The thick line is linear regression for the entire set of standard points. Dashed line represents interpolations for a test sample having absorbance 0.6. Proteins were transferred to a 0.22 µm nitrocellulose membrane using Mini Trans-Blot cell for 2 hours at 100 V. The blot transfer efficiency is verified using Ponceau S staining. The membrane was washed with PBS with 0.1% Tween-20 (PBST) twice for 5 mins each to remove the Ponceau S stain before being blocked with 5% (w/v) non-fat milk in PBST for 30 mins at room temperature (RT) with gentle agitation using the orbital shaker and then incubated with the appropriate primary antibody (Table 5) overnight at 4°C with constant gentle agitation using an orbital shaker. Following that, the membrane was washed with PBST 3 times for 5 minutes each before incubation with the appropriate HRP conjugated secondary antibody dissolved in 3% non-fat milk in PBST for 1 hour at RT with gentle agitation with orbital shaker. The membrane was then washed again 3 times for 5 mins each with PBST. The bands were developed 38 using chemiluminescence. For this study, two substrates were employed for chemiluminescence detection on the blot. SuperSignal West Dura substrate was used or SuperSignal West Femto substrate as appropriate. All the blots were developed using KODAK Image Station 4000R (Carestream Health Inc, New York, USA). The membrane was stripped using Restore Western Blot Stripping Buffer for 20 mins at RT, then washed with 1X PBST 3 times for 5 mins each, followed by blocking membrane with low-fat milk. Subsequently, the next target was examined via incubating the blot with another primary antibody following the same protocol used above. After the development of the bands, stripping method was repeated until all target used in this study was analysed. Typically, the blot is stripped for a maximum of two times. Table 4: Antibodies for Western blotting analysis Antibodies anti-PrP 8H4 anti-p53 anti-Akt (pan) anti-phosphoAkt (ser473) anti-phosphoAkt (thr 308) anti-Glut-1 anti-Glut4 anti-beta actin anti-beta actin HRP-conjugated goat anti-mouse IgG HRP-conjugated goat anti-rabbit IgG Source Mouse Rabbit Rabbit Rabbit Rabbit Rabbit Rabbit Rabbit Mouse 39 Dilution 1:1,000 1:5,000 1:2,000 1:1,000 1:1,000 1:1,000 1:1,000 1:5,000 1:5,000 1:10,000 1:10,000 2.5. Molecular cloning 2.5.1. Gateway cloning The cDNA of PRNP was purchased from Origene. Blunt end polymerase chain reaction (PCR) products were produced using PCR primers designed by the author for specificity to human cellular PrP. The PCR primers used were 5’-CACCATGGCGAACCTTGGC-3’ (forward) and 5’-TCCTCATCCCACTATCAGGAAGATGAG-3’ (reverse). Basic Local Alignment Search Tool (BLAST) from National Centre for Biotechnology Information (NCB1, MD) was used to ensure that the chosen sequences were specific, and target sequences were aligned to the human genome database. Full length human PrP (accession no. BC012844) cDNA was amplified via PCR at the following condition as shown in Table 5. Subsequently, the PCR product is cloned into pENTR™/D-TOPO vector following standard procedures provided in the pENTR™ Directional TOPO® Cloning Kit. Table 5: Cycling conditions for PCR Temperature (°C) Time Number of Cycles Initial denaturation 95 5 min 1 Denaturation 95 30 sec Annealing 53 30 sec Extension 72 1 min Final extension 72 7 min 1 Cooling 4 Forever 1 Step 40 25 Following transformation using One Shot® TOP10 Escherichia coli, positive clones were selected using 100 µg/mL kanamycin agar plates and scaled up in LB broth for isolation of plasmid DNA using QIAGEN Plasmid Midi Kits. The presence of the gene insert was confirmed by PCR analysis using the designed primers as mentioned above. The verified plasmids via sequencing were retained and used for subsequent LR cloning reactions. 2.5.2. LR cloning LR cloning was subsequently performed to transfer the PRNP gene insert from the pENTR™/D-TOPO vector into the pcDNA6.2/V5-DEST expression vector via an LR recombination reaction. The LR Clonase™ II enzyme mix was used and the recombination reaction was performed following instructions in the protocol provided. Positive clones were selected using 100 µg/mL carbenicillin agar plates and screened using colony PCR, before they were scaled up in LB broth for isolation of plasmid DNA. Plasmids were then sequence verified using T7 forward and V5 reverse primer. Once the correct positive clone of interest was obtained, it was transformed into One Shot® TOP10 E. coli and plasmid purification was carried out using QIAGEN Plasmid Midi Kits. Stock of plasmid DNA was stored at –80°C for future purposes. The empty vector, pcDNATM 6.2 was used as a negative control throughout this study. 41 2.6. Cell transfection 2.6.1. Dose response curve of MCF7 cells Prior to transfection, a dose response was performed to determine the optimum concentration of blasticidin S that could kill all non-transfected cells within a week. To simulate conditions similar to transfection, cells were kept in antibiotic- and serum-free media for 24 hours overnight and allowed to recover for 6 h in normal DMEM before blasticidin S was added. The selection media containing blasticidin S was prepared from a 10 mg/mL stock of blasticidin S diluted in DMEM. Concentrations of blasticidin S used were: 3 µg/mL, 5 µg/mL, 7 µg/mL and 10 µg/mL. Culture media was changed once every 3 days and the extent of cell death was visually inspected on an inverted microscope. The optimum concentration of blasticidin S for selection of stable cell clone was at 7 µg/mL because there was 100% cell mortality rate within a week of culture. Higher concentrations of blasticidin S were not suitable as they killed the cells at a rapid rate resulting in complete cell death in less than 3 days after addition of the antibiotic. 42 2.6.2. Stable transfection of cell lines using nucleofection MCF7 cells were seeded into T75 flasks and maintained at 37°C in a humidified incubator supplied with 5% CO2 until 80% confluency. Prior to transfection, culture media from the cells was removed and washed once with PBS and harvested by trypsinization. The reaction was stopped by adding DMEM containing FBS and cells were centrifuged (800 rpm, 10 min, 4°C). After counting, the required number of cells (1 x 106 cells per sample) was centrifuged at 200 g for 10 min at 4°C. The pellet was resuspended in 100 µL of Nucleofector solution (room temperature) with 1 µg of the relevant plasmid DNA added. The sample was transferred into an Amaxa cuvette, which was inserted into the cuvette holder and the appropriate programme (P-020 for high transfection efficiency) was started. Both PrP DNA containing plasmid and empty plasmid were subjected to nucleofection while the latter served as a mock control. Then, 500 µL of pre-warmed culture medium was added and the sample was transferred into plates, which were pre-incubated with medium. The samples were then gently transferred into 6-well plates and put back to the humidified incubator at 37°C supplied with 5% CO2. Sixteen hours later, media containing the transfection mixture was removed and substituted with normal DMEM. The cells were then returned to the incubator and allowed to recover for 6 h before selecting for positively-transfected clones via the addition of blasticidin S. 43 2.6.3. Selection of transfected cell clones DMEM containing 7 µg/mL of blasticidin S was added to the cells and selection of stable cell clones was done for a week. Subsequently cells that survived the antibiotic selection were trypsinized and plated column-wise at serial dilutions of 2-fold each in 96-well microplates, starting from a concentration of 50 cells per well in column 1 and by columns 6–8, it would end up with 1 cell per well. The cells were then cultured in maintenance media containing 5 µg/mL blasticidin S in DMEM and the presence of isolated cell colonies were determined through visual inspection on a microscope. Cell colonies were allowed to grow for approximately 2 weeks in microwells before they were trypsinized and further cultured in 24-well plates. Once the cells reached 100% confluency, they were trypsinized and maintained in T-25 flasks. Half the contents of a confluent T-25 flask were cryopreserved and stored at –150°C. The remaining half was scaled up for screening of protein expression using western blotting. 2.7. BrdU assay Proliferation rate was examined using BrdU assay. All solutions mentioned were from the bromodeoxyuridine BrdU ELISA kit. Cells (5 x 103/well) were seeded onto 96-well plate. The following day, the medium was removed and replaced with medium containing the BrdU labelling solution prior to fixation. After 18 h, the medium were removed by inverting the plate and cells were fixed with 200 µL fixative/denaturing solution for 30 mins. After that, the 44 fixative/denaturing solution was removed by tapping it off and 100 µL of the antiBrdU antibody (1:100 in antibody dilution buffer) was added to the cells for one hour at room temperature. Cells were washed three times with 1X wash buffer and 100 µL of peroxidase goat anti-mouse IgG HRP conjugate was added for 30 mins at RT. Cells were again washed three times with washing buffer. After tapping dry completely, cells were incubated with 100 µL substrate solution for 15 mins at RT in the dark. The reaction product was quantified by measuring the chemiluminescence using a Tecan Infinite M200 plate reader. 2.8. Lactate assay Cells were seeded in 96-well plates at 10 × 105 cells/well. When the cells reached at 90% confluency, the media was changed and incubated. Culture media was collected at 8 hours and stored at − 20°C until they were assayed within 3 days. Lactate production in the medium was detected using lactate assay kit. Briefly, lactate is oxidized by lactate dehydrogenase to generate a product which interacts with the probe to produce a colour. Standards for the assay were prepared following the manufacturer’s instructions. Fluorescence in the wells were then allowed to develop for 30 mins in the dark before values were read at excitation wavelength of 535 nm and emission wavelength of 590 nm. All values including the sample readings and standards were subtracted from the no-lactate control to correct for background. The standard curve was plotted as shown in Fig 6 and the sample readings were applied to the standard curve to obtain lactate concentration. The results were normalized based on the amount of total protein of the cells. The total protein was extracted via 45 scraping the bottom of the 96-well plates with 7 µl of RIPA buffer to lyse the cells. Then, the lysate’s protein concentration was analyzed using BCA protein quantification mentioned in section 2.3.3. Figure 6: A representation of the lactate standard curve. The line is curve for the entire set of standard points. Dashed line represents interpolations for a test sample having absorbance 0.4. 2.9. Pyruvate assay Pyruvate is an important molecule made from glucose through glycolysis. Pyruvate is used to provide further energy either via the Kreb’s cycle or broken down anaerobically to produce lactate. In our experiments, cells were seeded in 96-well plates at 10 × 105 cells/well. When the cells reached 90% confluency, they were lyzed to analyse the pyruvate concentration in the cells using the pyruvate assay kit from BioVision. Standards were prepared similar to the lactate assay in section 2.8 above and all readings were read using fluorescence at Ex/Em = 535/590 nm in a black microplate. 46 2.10. Lactate dehydrogenase activity assay Lactate dehydrogenase (LDH) is a stable cytoplasmic enzyme present in most cells. It is release from the cell upon damage to the plasma membrane. In our experiments, cells were seeded in 96-well plates at 10 × 105 cells/well. When the cells reached at 90% confluency, the cell culture media was removed. The cells were then washed twice with PBS before performing cell lysis. LDH activity in the cell was measured via the release of cytoplasmic content using CytoTox 96 Non-radioactive Cytotoxicity Assay kit from Promega. The reaction product was quantified by measuring the absorbance using a Tecan Infinite M200 plate reader. 2.11. Statistical analysis Results presented were from representative experiments and data expressed as mean ± standard error of the mean (SEM) of at least two independent experiments performed in triplicates, unless otherwise stated. Tissue data were analysed with Microsoft Excel 2007 (Microsoft Corp., WA) using paired twotail Student’s t-test. The rest of the results were analysed with analysis of variance (ANOVA) followed by post-hoc Dunnett’s test or Bonferroni’s test. The statistical analysis was performed using Graphpad PrismTM software version 2.0 (Graphpad Software Inc., San Diego, CA, U.S.A.). A p-value of less than 0.05 was considered as statistically significant, as per indicated by asterisks in the graphs. 47 3. RESULTS 3.1. Breast cancer tissues 3.1.1. Low PrP protein expression in breast cancer tissues As an initial effort to characterize the role of PrP in breast cancer, the PrP expression was analysed in breast cancer tissue (n = 5) and compared with adjacent normal breast tissues. A decreased PrP expression was observed in breast cancer tissue compared to the normal tissue counterpart. Figure 7: PrP expression is reduced in breast cancer tissue. (A), anti-PrP (8H4) immunoblot of lysates prepared from breast cancer tissue compared to their corresponding normal breast tissue (n=5). Equal loading of the different lysates was verified by anti-beta actin immunoblotting. (B), band density was normalized against beta actin and expressed as fold change compared to normal breast tissue. Results shown were average ± S.E.M. Paired-samples ttest indicates that the differences between the normal and breast cancer tissue is significant. *denotes p-value < 0.05. 48 3.1.2. p53 protein expression remains unchanged in breast cancer tissues No statistical difference was observed in p53 level between the normal and breast cancer tissues. This corroborates with a recent study showing that PrP enhances response to doxorubicin induced cytotoxity in a p53-independent manner (Yu et al., 2012). Figure 8: p53 expression remains unchanged in breast cancer tissue. (A), representative blot of p53. (B), densitometry results of blots. Results expressed as average fold change ± S.E.M. Statistical analysis revealed no statistically difference between breast cancer tissue with respect to their normal breast tissue (p-value = 0.059). 49 3.1.3. Breast cancer tissue have increased total Akt protein expression but not phosphorylated Akt Next, we investigated the levels of Akt in breast cancer tissues. Akt is a central player in many distinct pathways and is deregulated in many cancers (Vivanco and Sawyers, 2002). Studies have demonstrated correlation of high Akt expression with breast cancer progression (Bacus et al., 2002, Perez-Tenorio et al., 2002). Constitutive activation of Akt is one of the characteristics of cancer cells that are highly dependent on glucose utilisation for energy and proliferation (Robey and Hay, 2009, Tomas et al., 2012). In our study, the total Akt expression was higher in breast cancer tissue compared to normal breast tissue (Fig 9 A-B). However, Akt phosphorylation did not differ between normal and breast cancer tissue (Fig 9 C-F). Nonetheless, Akt expression showed sufficient difference to warrant the continuation of the study. 50 A B C D 51 E F Figure 9: Breast cancer tissue is associated with increased total Akt but not phosphorylated Akt expression. Total lysates were prepared from breast cancer tissue compared to their corresponding normal breast tissue. (A, C, E) Western blots shown are detecting for Akt, p-Akt (ser473), and p-Akt (thr308) respectively. (B) Band density was normalized against beta actin and (D, F) were normalized against total Akt. All was expressed as old change compared to normal breast tissues. Results shown were average ±S.E.M. of 5 experiments. p-values were calculated using Paired-samples t-test. *denotes p-value < 0.05. 52 3.2. Breast cancer cell lines 3.2.1. PrP expression is higher in normal breast cell line than breast cancer cell lines To extend our studies with an in vitro system, we similarly examined the expression of PrP in commercially available cell lines (normal and cancer): MCF10A, MCF7, SK-BR-3, MDA-MB-231. The PrP expression in the cancer cell lines were markedly reduced especially in MCF7 and SK-BR-3 when compared against the normal breast cell line MCF10A. Cancer cell line MDAMB-231 had a non-significant reduction. 53 Figure 10: PrP expression is higher in normal breast cell line (MCF10A) than breast cancer cell lines (MCF7, SK-BR-3, and MDA-MB-231). (A) Western blots shown are representative of 3 independent experiments which show similar trend. (B) Band density was normalized against beta actin and expressed as fold change compared to normal breast cell line. Results shown were average ± S.E.M. of 3 experiments. The differences between normal breast and breast cancer cell lines were compared using Bonferroni post hoc test. * denotes p-value < 0.05. 54 3.2.2. Low PrP expression correlates with proliferation rate in breast cancer cell lines. high Besides invasion and metastasis, cell proliferation is also an important aspect of cancer progression. PrP-overexpression in gastric cancer cell lines versus their wild-type counterpart has been shown to increase proliferation (Liang et al., 2007). However, little is known about how PrP affects proliferation in breast cancer. The use of cell lines allows us to investigate this proliferative effect, which is not ethically possible clinically. BrdU was employed to examine the proliferation rate. It was observed that the proliferation rate of breast cancer cell lines with low PrP expression are significantly increased compared to that of the normal cell line MCF10A, suggesting possible correlations between differential PrP expression in normal versus breast cancer cell proliferation. As our cell line model presented the possibility that PrP might have a role in modulating proliferation rate in breast cancer cells, we proceeded to investigate the pathways that could be involved. 55 Figure 11: Proliferation rate in breast cancer cell lines. BrdU proliferation assay of human breast cancer cells vs. normal breast cells. Results were expressed as means ± S.E.M. One-way ANOVA. *** denotes p-value < 0.001. 56 3.2.3. p53 expression is markedly up-regulated in breast cancer cell lines SK-BR-3 and MDA-MB-231 Although we did not observe significant differences in p53 expression between normal and breast cancer tissues, we investigated if the result is similar in the in vitro model. We found that p53 protein expression is markedly increased in the breast cancer cell lines SK-BR-3 and MDA-MB231 when compared to normal breast cell line MCF10A. No significant difference was observed in MCF7 (cancer cell line). Figure 12: Up-regulation of p53 in the breast cancer cell lines but not MCF7. (A) Western blot of the p53 status in breast cell lines. (B) Band density of p53 was normalized against beta actin and expressed as fold change compared to normal breast cell line, MCF10A. All blots shown were representatives of 3 independent experiments and densitometry results are mean ± S.E.M. of the 3 experiments. p-values were calculated using One way ANOVA. * denotes p value < 0.05, ** p values < 0.01. 57 3.2.4. Low PrP expressing breast cancer cell lines is associated with high Akt and induce Akt phosphorylation Next, we investigated the levels of Akt in the breast cell lines to verify our observations in breast tissues. The level of Akt expression was higher in all breast cancer cell lines compared with the normal breast cell line MCF10A. A statistical significance was seen especially with MCF7 cancer cell line. Further analyses on the phosphorylation status of Akt in these cell lines were studied, to determine correlation, if any, with PrP expression. As shown in Fig 13D, only SK-BR-3 had increased phosphorylated Akt (ser473) compared to MCF10A. No difference was observed in other breast cancer cell lines. No significant difference was observed between the normal and breast cancer cell lines in the expression of phosphorylated Akt (thr308) (Fig 13 E-F) . 58 59 Figure 13: Low PrP expression in breast cancer cell lines is associated with high Akt expression and induced Akt phosphorylation. (A, C, E) Western blots shown are representative of 3 independent experiments which show similar trend. (B) Band density was normalized against beta actin while (D, F) were normalized against total Akt; they are expressed as fold change compared to normal breast cancer cell, MCF10A. Results shown were average ± S.E.M. of 3 experiments. Test of significance between normal and breast cancer cells were carried out using Dunnett’s post hoc test comparing the breast cancer cell lines with normal breast cell line. * denotes p-value < 0.05 and ** denotes p-value < 0.01. 60 3.2.5. Low PrP expression is correlated with increased glycolytic flux metabolites We then examine the level of common metabolites such as lactate, pyruvate and LDH-A, the enzyme responsible for converting pyruvate into lactate in the glycolysis pathway in the breast cancer cell lines to see the metabolic status of these cells in relation to PrP. LDH-A is known to be up-regulated in cancer cells (Goldman et al., 1964). LDH-A activity in breast cancer cell lines SK-BR-3 and MDA-MB-231 were markedly increased compared with MCF10A, the normal breast cell line. No difference was observed in MCF7 (Fig 14A). Next, we investigated the glycolytic flux status in our breast cancer cells and examine if it is associated with the level of PrP. The intracellular levels of pyruvate and lactate production in these cells were measured. The levels of pyruvate were markedly reduced in cancer cells, particularly in MCF7 and SK-BR-3 compared with MCF10A (Fig 14B). On the other hand, lactate production was marked increased in all breast cancer cells compared with MCF10A (Fig 14C). Taken together, we show for the first time proliferative breast cancer cells have lower PrP expression compared with MCF10A. Total Akt was found to be highly expressed in breast cancer cells, this, being in line with our breast cancer tissue results. Extending our study to look at the metabolic status of the 61 breast cancer cells, we found that breast cancer cells have high LDH-A activity, low pyruvate level in cells, and high lactate output compared with MCF10A. A relationship was observed between PrP with p53 and phosphorylated Akt (ser473) in our breast cancer cell lines model. To validate that PrP plays a role in proliferation and metabolic status in breast cancer, we selected one of the breast cancer cell line (MCF7) that produces the lowest level of PrP for generation of PrP-overexpression clones. A 62 B C Figure 14: Correlation between LDH-A activity, intracellular levels of pyruvate and lactate production in breast cancer cell lines. (A) The LDHA activity measured from the cells. (B) Intracellular pyruvate level in cells. (C) Lactate production from cells. Results are analyzed by One-way ANOVA and p-values were calculated using Dunnett’s post-hoc test. ** denotes p-value < 0.01, *** p-values < 0.001. 63 3.3. Transfected cell lines 3.3.1. Over-expressing PrP in MCF7 cell line To examine the effects of upregulated PrP expression in low PrP expressing breast cancer cells, the PRNP gene was stably transfected into MCF7 breast cancer cells and we have generated stable clones of MCF7 cells overexpressing PrP (HuPrP/MCF7) or containing vector alone as a control (Mock/MCF7). The MCF7 cell line was selected for this study because it is a widely used in vitro model of breast cancer, expresses very low PrP levels, and it has an intact wild-type p53. These cells were then used to investigate the causal relationship between PrP in cancer progression and metabolic switch. Assessment of the presence of PrP was performed using real-time reverse transcription polymerase chain reaction to measure the amount of PrP mRNA as shown in Fig 15A. PrP expression was further confirmed with Western blot analysis using anti-PrP mAB 8H4. We successfully generated 2 clones of MCF7 expressing PrP that were higher than Mock/MCF7 (Fig 15C). 64 Figure 15: Over-expressing PrP in MCF7 breast cancer cell line. (A) Graphs showing the Ct value of PrP expression in PrP-expressing stable clone. (B) Western blots shown were representative of 3 independent experiments which show similar trend. (C) Band density was normalized against beta actin and expressed as fold change compared to vector control, Mock/MCF7. Results shown were average ± S.E.M. of 3 experiments. Test of significance between vector control and PrP-expressing stable clones were carried out using Dunnett’s post hoc test. ** denotes p-value < 0.01. 65 3.3.2. PrP reduces cell proliferation rate BrdU assay was employed to examine the effect of PrP on the proliferation rate in the transfected MCF7 cells. PrP overexpression was found to reduce proliferation rate in HuPrP/MCF7 clone A and B. It appears that PrP might confer anti-proliferative effect. Figure 16: Over-expressing PrP in transfected MCF7 cells reduces cell proliferation rate. BrdU proliferation assay of HuPrP/MCF7 and Mock/MCF7 cells. Results were expressed as means ± S.E.M. One-way ANOVA. *** denotes p-value < 0.001. 66 3.3.3. PrP reduces lactate production in HuPrP/MCF7 cells Under the Warburg effect, one of the observations is that cancer cells produce large amounts of lactate without fully oxidising it into CO2. Here, lactate production was examined in HuPrP/MCF7 cells to determine the effect of overexpressed PrP. Both HuPrP/MCF7 clones were found to have marked reduction in the lactate production compared to Mock/MCF7 (Fig 17). This led us to question if PrP has a role in reducing glycolytic flux and thence inhibiting the Warburg effect in our cell model. Figure 17: Over-expressing PrP in transfected MCF7 cells reduces lactate production. Lactate production assay of HuPrP/MCF7 cells and mock/MCF7 were assayed at 8 h following media changed. The results are normalized with their protein concentration. Results were expressed as means ± S.E.M. Oneway ANOVA. *** denotes p-value < 0.001 67 3.3.4. Overexpression of PrP reduced phospho-Akt (ser473) but has no effect on total Akt and phospho-Akt (thr307) In our breast tissue and cell line study, we found that high PrP expression is correlated with a low Akt expression. To verify that the relationship is causal, Akt expression was examined in the MCF7 cells over-expressing PrP. More importantly, the molecular events leading to a glycolytic phenotype in breast cancer are not well known (Gillies et al., 2008). Akt has been implicated in regulating aerobic glycolysis (Elstrom et al., 2004), so we want to investigate if PrP is involved. In comparison to Mock/MCF7, over-expressing PrP was not found to affect Akt expression (Fig.18 A-B). However, PrP over-expression significantly decreased Akt phosphorylation at ser473 for clone B. Akt phosphorylation at ser473 was also decreased in clone A but the difference was not statistically significant (Fig 18 C-D). No change in levels of phosphorylation was observed at thr307 (Fig 18 E-F). So it appears that PrP might play a role in regulating aerobic glycolysis via exerting its effect through activating Akt at ser473. More study is required to investigate if PrP affects the downstream effector of Akt using our cell lines model. 68 69 Figure 18: Over-expressing PrP in transfected MCF7 cells reduces p-Akt (ser473) but has no effect on total Akt and p-Akt (thr308). (A, C, E) Western blots shown are representative of 3 independent experiments. (B) Band density was normalized against beta actin while (D, F) were normalized against total Akt; they are expressed as fold change compared to Mock/MCF7. Results shown were average ± S.E.M. of 3 experiments. Test of significant between Mock/MCF7 and HuPrP/MCF7 were carried out using Bonferroni post hoc test. 70 3.3.5. PrP does not modulate p53 expression Next, we used PrP over-expressing MCF7 cell model to verify the observation in breast cancer tissue. As shown, there was no change in p53 expression between the over-expressed PrP MCF7 cells and Mock/MCF7. Hence, the role of PrP in modulating breast cancer metabolism might be p53 independent. Figure 19: Over-expressed PrP in MCF7 cells does not affect p53 expression. (A) Western blot of p53 status in Mock/MCF7 and HuPrP/MCF7. (B) Band density of p53 was normalized against beta actin and expressed as fold change compared to Mock/MCF7. All blots shown were representatives of 3 independent experiments and densitometry results are mean ± S.E.M. of the 3 experiments. Statistical analysis revealed no statistically difference between HuPrP/MCF7 and mock/MCF7. HuPrP/MCF7 clone A (p-value = 0.083), HuPrP/MCF7 clone B (p-value = 0.707). 71 3.3.6. Over-expressed PrP reduced GLUT4 but not GLUT1 expression in MCF7 cells. Over-expressing PrP significantly decreased GLUT4 for clone B. There is decreased GLUT4 in clone A but the difference was not statistically significant (Fig 20 A-B). Over-expressing PrP was not found to affect GLUT1 expression (Fig 20 C-D). Studies have shown that Akt mediates GLUT4 trafficking (Foran et al., 1999, Zhou et al., 2004); however, Akt is not required for GLUT1 trafficking in some cells such as adipocytes (Foran et al., 1999). It appears that the effect of PrP on GLUT4 might be mediated by Akt. 72 Figure 20: Over-expressing PrP in transfected MCF7 cells reduces GLUT4 expression but not GLUT1. (A, C) Western blots shown are representative of 3 independent experiments. (B, D) Band densities were normalized against beta actin and are expressed as fold change compared to Mock/MCF7. Results shown were average ± S.E.M. of 3 experiments. Test of significant between Mock/MCF7 and HuPrP/MCF7 were carried out using Bonferroni post hoc test. * denotes p-value < 0.05. 73 4. DISCUSSION Cancer cells generally have altered metabolism (Warburg effect) to satisfy their need for proliferation and survival. Whilst genetic alterations have been intensively researched on in breast cancers, the corresponding metabolomics modulation have not been well characterized (Brauer et al., 2012). The expression of PrP in human breast cancer tissue was first observed by Meslin, F. et al., demonstrating that PrP was mainly expressed by myoepithelial cells in normal breast tissue using immunohistochemical staining (Meslin et al., 2007a). Endogenous PrP expression has also been demonstrated to correlate with tumour grade in breast cancer cell lines (McEwan et al., 2009). As an initial effort to characterize the role of PrP in breast cancer, expression levels of PrP in normal and breast cancer tissues were examined. Using immunoblotting analysis on 5 sets of tissues, the expression of PrP was shown to be significantly lower in tumour compared to adjacent normal tissues. However, with a small sample size, caution is pertinent as the findings might not be generally applicable. Hence, we carried out the investigation of PrP expression in a panel of breast cancer cell lines and found that PrP was significantly reduced in the tumour-derived cell lines compared with normal breast cell MCF10A, which is in agreement with our earlier observations with cancer tissues. Despite a small sample size (n=5), our results were consistent with the in vitro breast cancer cell line model. More work is required to investigate the correlation of PrP expression with histological grades in breast cancer tissue to understand definitively the role of PrP in human tumour progression and also to verify the cell line results observed by McEwan et al. 2009. 74 While larger tissue numbers are warranted to allow better powered analysis of characterizing the role of PrP in breast cancer, an important next step is to understand if endogenous PrP correlate with metabolic subgroups. Several studies indicated that PrP enhances cancer cell proliferation and plays a role in poor prognosis for certain cancers, proposing PrP as a contributing factor in cancer biology (Li et al., 2009a, Meslin et al., 2007a). For example overexpression of ectopic PrP promotes proliferation of gastric cancer cells (SGC7901 and AGS) (Liang et al., 2007). Using antibodies to nullify the effect of PrP, McEwan et al. found that PrP promoted proliferation in colon cell line (HCT116) (McEwan et al., 2009). When we sought to examine the involvement of PrP in the proliferation of breast cancer cells, our BrdU assay revealed that the proliferation rate of low PrP expressing breast cancer cell lines are markedly increased compared with the normal breast cell line MCF10A. This suggests that deficient endogenous PrP expression in breast cancer cells could aggravate their growth. However, different genetic environment between the normal breast cell line (non-cancer environment) and breast cancer cell lines (cancer environment) might contribute to the observation instead of the difference in PrP levels. To show the differential effects of PrP expression on cell proliferation, PRNP gene was stably transfected into MCF7 cells and we demonstrated that the PrP transfected MCF7 resulted in a marked reduction in the proliferation rate. This result is opposite in trend to other studies such as that in the study on gastric cancer cell lines, where researchers showed that PrP is overexpressed in gastric cancer tissues (Liang et al., 2006b) as well as in multi-drug-resistant gastric cancer cell lines (Zhao et al., 2002). Overexpression of PrP was found in gastric 75 cancers and it correlated with histopathological differentiation parameters (Liang et al., 2006a) and also promoted proliferation and tumour progression (Liang et al., 2007). These studies indicated that PrP plays a role in promoting proliferation and progression in gastric cancer cells. An immediate response to why our results differed from these studies could simply be differences in the role played by PrP in different cancer cells. However, closer scrutiny of our results show a trend of increasing expression of PrP correlating with increasing metastasis profile of the breast cancer cells, particularly when MDA-MB-231 is compared to MCF7 as shown in Fig. 21A (modified from Fig. 10, for comparison with McEwan’s results in Fig. 21B). Our results corroborated with that of McEwan et al. who used ELISA assay to detect PrP. There, they found that PrP expression correlated with invasiveness and malignancies in breast cancer cell lines, reflecting differences in tumour grade and metastatic potential as shown in Fig. 21B. (McEwan et al., 2009). Based on this result, it might be tempting to look further into the role of PrP in the cancer cell lines though it may not be clinically relevant when compared to normal cells. This is because in order to understand how cancer works, it is important to first understand how the body’s cells normally function. 76 A B Figure 21: PrP correlates with invasiveness/malignancy of the breast cancer cell lines (A) Western blots results – modified from Fig 10. Results shown were average ± S.E.M. of 3 experiments. One-way ANOVA. * denotes p-value < 0.05. (B) ELISA results of PrP level correlating with aggressiveness of breast cancer cell lines (McEwan et al., 2009). Another plausible reason for the apparent contradictory results could lie in a difference in the PrP form between our study versus that of other groups. However, this remains to be verified experimentally. What we gathered was that Li et al. has discovered that human pancreatic ductal adenocarcinoma cell lines (n=7) have upregulated expression of PrP, with islet cells of the normal pancreas expressing PrP. More importantly, they further demonstrated that only pro-PrP, the immature form of PrP, was detected in human pancreatic ductal adenocarcinoma cells, with the GPI anchor peptide signal sequence retained. Pro-PrP contains filamin A binding motif and binds to filamin A, a scaffolding protein and an integrator of cell mechanics and signalling. Binding of pro-PrP to filamin A disrupts the normal function of filamin A, which Li et al. hypothesized is likely responsible for the growth advantage of human pancreatic ductal adenocarcinoma cell lines (Li et al., 2009a). In other words, Li et al. 2009a had shown that expression of pro-PrP is a marker for poorer 77 prognosis in pancreatic cancer. This is corroborated by Xin W, et al. reporting that pro-PrP and mature PrP have different biological functions (Xin W., et al. 2013). It is understood that the interaction between pro-PrP and filamin A does not occur in all tumour cells — human neuroblastoma cell lines do not express PrP nor filamin A. While other cancer cell lines such as melanoma and human hepatocarcinoma cell lines express both proteins (Li et al., 2010, Li et al., 2009a), it is still unknown (1) why some cancer cells express pro-PrP and filamin A while others do not, and (2) whether breast cancer cells exhibit both pro-PrP and filamin A. It is thus paramount that subsequent work first identify the form of PrP in order to provide relevant insight into the mechanisms where it modulates tumour cell biology. Also, polymorphism in codon 129 (M129V) of the PrP gene, PRNP, is associated with neurodegenerative disease development and severity. There is however, not much information available regarding its role in cancer incidence and disease progression. Antonacopoulou et al. investigated retrospectively the potential role of M129V in 110 patients with colorectal cancer and 124 healthy donors by genotyping the M129V single nucleotide polymorphism via real time polymerase chain reaction. They found that M129V is not a risk factor for colorectal cancer, as the results between patients and healthy controls were similar (Antonacopoulou et al., 2010). Nevertheless, the role of M129V in breast cancer and other cancers remains yet unknown. Consequently, it would be interesting to investigate if M129V is a risk factor for breast cancer, and if so, how much of a role it might play in proliferation vis-à-vis the difference between our results and that of others. 78 We also hypothesized that PrP level differences between the normal and breast cancer have correlation with signalling pathways that are involved in proliferation, i.e. p53 and/or Akt pathway, and that these interactions contribute to the distinct metabolic differences and associations with PrP. It has been demonstrated that PI3K signal is an important downstream effector of PrP (Diarra-Mehrpour et al., 2004, Krebs et al., 2006, Vassallo et al., 2005). In addition, using a two-site chemiluminescence-linked immunosorbent assay to measure primary human breast cancer tissue, Cicenas et al. found that Akt activation which requires phosphorylation of both thr308 and ser473, is associated with tumour proliferation and poor prognostic outcome (Cicenas et al., 2005). Intriguingly, overexpression of PrP decreased the phosphorylated Akt expression particularly at ser473 proposing a possible fundamental role in slowing down proliferation rate in breast cancer cells. Our results contradicted with Liang et al. who showed that PrP increased proliferation of gastric cancer cell, SGC7901 (Liang et al., 2007), and induced multi-drug resistance in the gastric cancer via activation of the PI3K/Akt pathway (Liang et al., 2009). It was reported that the use of cancer cell lines may have limitations in investigating resistance to chemotherapy drugs and consequently, results from such models should be viewed circumspectly. (Phillips, C. 2011). In the study of Liang et al., the gastric cancer cells were subjected to selection pressure via increasing adriamycin, a chemotherapy drug, stepwise to generate adriamycin-resistant gastric cancer cell line. This selection pressure could have altered the physiological functions of the cells and would perhaps not be able to accurately represent how tumours behave in the body. Similarly, some 79 genes involved in the PI3K/Akt pathway that are differentially expressed were found to be overexpressed in MCF7 breast cancer cell line with a 17-fold upregulation of PrP (Diarra-Mehrpour et al., 2004). Yet, such findings should be interpreted with caution as the MCF7 breast cancer cell lines used in the study were induced to become TNF-α resistant cells from the parent TNFsensitive MCF7 cell lines. Hence, it remains questionable whether the modulation of the genes involved in the PI3K/Akt pathway is due to PrP itself, or in actual fact, arises from TNF-α after the MCF7 cells were induced into becoming TNF-α resistant cells. In our study, PrP expression was not associated with p53 expression in the breast cancer tissue model. Conversely, p53 expression was markedly increased in the breast cancer cell line SK-BR-3 (Kovach et al., 1991) and MDA-MB-231 (Olivier et al., 2002) compared with MCF10A. No difference was observed in the MCF7 cells. Overexpressing PrP in MCF7 cell lines showed no association with p53 expression, this result being in line with our breast cancer tissue model. Literature review on the breast cancer cell lines showed that SK-BR-3 and MDA-MB-231 express mutated p53 while MCF7 (Lu et al., 2001) and normal breast cell MCF10A (Merlo et al., 1995) express wild-type p53. PrP was shown in studies to be associated with p53 to confer cell survival (Kim et al., 2004, Paitel et al., 2002) and p53 was recently discovered to regulate metabolic activity by preventing further escalation of the Warburg effect through enhancing entry of more pyruvate into the citrate cycle (Contractor and Harris, 2012). Therefore it is perhaps premature to conclude that PrP expression does not associate with p53 based on our breast 80 tissue and overexpression model system. Could low aberrant expression of PrP in SK-BR-3 and MDA-MB-231 be associated with high mutated p53 expression resulting in a more metastatic breast cancer possibly via modulating the metabolic pathway? This question remains to be answered by future studies. As tissue sample sizes are insufficient to fully evaluate the normal and breast cancer tissue metabolic characteristics, we addressed this limitation by combining our tissue-based observations with current established in vitro models to confirm the pathway changes as well as to study the metabolomics data which is not possible with clinical samples. While we were unable to measure all metabolites, we focused our study on lactate production as it is the final by-product and is significantly increased in cells exhibiting Warburg effect. Our results demonstrated that the expression of PrP was negatively associated with lactate production as shown in the breast cancer cell lines study and PrP over-expressing MCF7 cells. An implication of this is the possibility that a link may exist between PrP and Warburg effect. LDH-A activity in the breast cancer cell lines was markedly increased while the pyruvate level was statistically significantly lower, particularly in the SK-BR3 and MCF7 cell lines. Both results lend support to increased lactate production in low aberrant PrP expression in breast cancer cells. The association was however not observed in breast cancer cell line MDA-MB-231. Perhaps PrP has other roles apart from influencing lactate production processes in MDA-MB-231 and this warrants further in-depth study. 81 Normal Pyruvate In normal situation, some pyruvate will Lactate be converted into lactate via LDH-A LDH-A In tissue becomes cancerous, most pyruvate will be converted into Lactate lactate via LDH-A Cancer (Low PrP expression) LDH-A Pyruvate Figure 22: Picture showing different lactate production in normal and cancer situation. Figure adapted from (Vander Heiden et al., 2009). 82 It is also noteworthy that one other group has shown that LDH-A is upregulated after PrP is induced into mouse neuronal PrP deficient cells (Ramljak et al., 2008). The metabolic phenotype of PrP may have a complex interplay between species and cell type which might explain the difference we observed. Our findings, while preliminary, suggest that PrP modulates cancer metabolism and is likely to be linked to the Warburg effect. As mentioned in the introduction, the function of Akt is pleotropic. Akt plays a role in the regulation of glucose uptake into insulin responsive tissues by translocating GLUT4 from vesicular intracellular compartments to the plasma membrane. The role of Akt in this process was demonstrated using constitutively active Akt mutants that induce GLUT4 translocation in the absence of insulin (Kohn et al., 1996). In addition, depletion of Akt using small interfering RNA-mediated knockdown results in decreased insulinstimulated glucose uptake (Welsh et al., 2005). We therefore questioned if PrP modulated phosphorylated Akt (ser473) to alter glucose transporter to carry out their function in proliferation as well as cell metabolism as shown in Fig 23. 83 PrP Phosphorylated  Akt  (ser473) ??? Proliferation Lactate  production Figure 23: Schematic overview of the role of PrP in breast cancer metabolism in the study model. Li et al. (2011) observed that by abolishing PrP in colorectal cancer DLD-1 cells, GLUT1 gene was markedly altered using array hybridization analysis (Li et al., 2011). Therefore, using our overexpression model we sought to investigate the function of PrP and its association with glucose transporters. Interestingly, PrP-overexpressing MCF7 cells demonstrated marked reduction in GLUT4 expression. Notably GLUT4, the insulin regulated glucose transporter, is found in various human malignant breast tissue and cell lines including MCF7 (Birnbaum, 1989, Brown and Wahl, 1993). Therefore, it appears possible that PrP downregulates breast cancer proliferation via preferentially inhibiting phosphorylation of Akt at ser473, which might lead to the down-regulation of GLUT4. 84 Overall, our findings are surprising as it is in opposition to observations by other groups, where they demonstrated that PrP is associated with proliferation, and survival of cells (Liang et al., 2007), (Morel et al., 2008), (DiarraMehrpour et al., 2004). Several factors had been discussed as possibly contributing to this apparent discrepancy in our case and it is intriguing to note that Yu et al. found it necessary to make the following comment: “PrP knockdown in MDA-MB-435 cells may alter multiple signalling pathways. Depending on which pathway is involved in the cellular response to a particular cytotoxic stimulus, PrP knockdown may have pro- or anti-cell death effect.” (Yu et al., 2012). This shows that the physiological role of PrP in relation to cancer progression is far from being settled unambiguously. Thus, there is a possibility that the role of PrP could be even more complex across cell lines. This could arise from genetic deviations within cell lines. Jones et al. showed that there are 3 strains of MCF7 cells using genomic hydridisation and their proliferation rates differ (Jones et al., 2000). The diversity of factors that affect the proliferation in MCF7 cells suggest that the previously described proliferation effect by PrP (Diarra-Mehrpour et al., 2004) may be specific for a particular strain variant and may not be generally reproducible in other variants, much less other cell types. In addition, their use of MCF7 cells with ablated p53 that do not respond to Fas ligand (Diarra-Mehrpour et al., 2004) could cause results to differ as it might affect the proliferation rate as well as the metabolic activity of the cells. 85 We observed that our transfected cell lines yielded different results, i.e. significant levels for phosphorylated Akt (ser473) and GLUT4 were only achieved in PrP overexpressed MCF7 clone B and not in clone A. One possible cause could be our use of a transfection system that is not sitedirected. Random insertion of PrP may give rise to variability in the results. Hence, a better option would be to use a site directed insertion of the PrP construct into the MCF7, which would eliminate this potential confounder. All in all, PrP might be playing a role in modulating the progression of breast cancer, as we showed that low aberrant PrP expression in breast cancer cells led to marked proliferation rate. This effect could be due to the up-regulation of phosphorylated Akt ser473 causing the increased expression of GLUT4 which might drive the glycolysis flux as reflected in the increased lactate production. 86 4.1. Concluding remarks and future directions Figure 24: Schematic overview of the role of PrP in cancer metabolism in breast cancer cells. PrP expression reduces cellular proliferation and glycolysis via down-regulating phosphorylated Akt (ser473) and GLUT4 expression. 87 The key strength of our study lies in our in vitro work supporting the results based on the clinical samples. PrP expression in both normal breast tissue and the normal cell line MCF10A, have higher expression compared with their cancer counterparts. Overexpression of PrP in MCF7 cell line demonstrated that PrP expression dampens proliferation and reduces lactate production. The possible pathway could be via reduction of phosphorylated Akt (ser473), leading to lowered GLUT4 as shown in Fig 24. Taken together, the apparent physiological role of PrP observed from this study seems to portray PrP as having cancer protecting effect. However, we are still at the initial stages of understanding the complex interplay between PrP, cancer biology and metabolism. Investigating the underlying mechanisms that link to the physiological roles of PrP remain an important work for understanding its functions in carcinogenesis and also in prion diseases. Gene-silencing studies, such as that by Yu et al., in cell lines highly expressing PrP is a relevant next step. Subsequently, it would be desirable to extend the findings of this study to in vivo models, for example by using nude mouse bearing human MCF7 xenograph to investigate if tumour growth is inhibited by treatment with PrP. This will be essential as it can help to uncover the molecular mechanisms of the role ascribed to PrP, and how it might play a role in subverting carcinogenesis and becoming a possible targeted cancer therapy. We showed that overexpression of PrP in our study model affects Akt 88 phosphorylation (ser473) and more importantly it decreases GLUT4 expression, which is an insulin-linked glucose transporter. Hence, studying the association of PrP and the insulin pathway with cancer might shed new light in finding a potential pathway where PrP mitigates cancer progression. In addition, as we have shown that overexpression of PrP is correlated with lowered lactate production, suggesting that it may have a possible role in mitigating the Warburg effect in cancer cells. Further investigations into the oxygen and glucose consumptions are indispensable to verify the phenotype of the Warburg effect in our model. Hence, the apparent physiological role of PrP observed from our study seems to portray a close connection between PrP and cancer regression. It is still premature to suggest that overexpressing PrP in cancer cells could provide a new therapeutic strategy. Nonetheless, it provides an important insight especially in its association with GLUT4 expression. Hence, we speculate that PrP might be involved in the insulin pathway. This role might be applied in the insulin potentiation therapy against cancer. Based on our findings, it can be seen that PrP may have numerous important implications for carcinogenesis. Although the exact mechanisms involved in proliferation and metabolism remains to be elucidated definitively, the results here provide a stimulus for further studies on the role of PrP in cancer biology not just in proliferation and metabolism, but also in other hallmarks for cancer involving replicative potential, and angiogenesis. 89 5. REFERENCES ALTERI, R., BANDI, P., BRINTON, L., CASARES, C., COKKINIDES, V., ET. AL. 2011. Breast cancer facts & figures 2011-2012. Atlanta: American Cancer Soiciety, Inc. ANTONACOPOULOU, A. G., PALLI, M., MAROUSI, S., DIMITRAKOPOULOS, F. I., KYRIAKOPOULOU, U., TSAMANDAS, A. C., SCOPA, C. 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Biochem Soc Trans, 32, 817-21. 100 [...]... example, breast cancer is a malignancy that affects breast tissue, in particular, the inner lining of milk ducts or the lobules that supply the duct with milk (Sariego, 2010) These are termed ductal and lobular respectively Breast cancer is the leading cause of cancer mortality in Singaporean females (MOH, 2012) Amongst all the different kinds of cancer, breast cancer is ranked fifth highest in terms of. .. according 7 to the Singapore Cancer Registry, 1 in 17 women will develop breast cancer in her lifetime in Singapore The risk of getting breast cancer increases with age, with the most prevalent age between 50 to 59 years in Singapore women (HPB, 2009) 1.2.1 Hallmarks of cancer How then is a cancer cell different from a normal cell? Many researchers over the past decades have been studying this question They... that p53 plays a major role in the metabolism of cells Apart from these, it was reported that p53 directly regulates the transcription of PrPC (Vincent et al., 2009) but its role in 20 metabolism, particularly cancer metabolism, is not known So it is of great interest to investigate the relationships, if any, between prion, p53 and Akt in cancer metabolism 1.3 The Role of PrP in cancer biology Although... phosphorylation The functions of p53 in metabolism is shown in Table 2 and further elaborated below Table 2: Roles of p53 in metabolism Studies that demonstrated p53 roles in metabolism Roles of p53 in metabolism Induces synthesis of TP53-induced Bensaad et al., 2006 glycolysis and apoptosis regulator (TIGAR) expression Induces synthesis of cytochrome Matoba et al., 2006 oxidase 2 (SCO2) Involved in glucose metabolism. .. Structural aspects of PrP In humans, PrP is initially synthesized as a pre-pro-PrP of 253 amino acids in the cytosol PrP contains a hydrophobic N-terminal signal peptide of 22 amino acids while the last 22 amino acids at the C-terminus encompass the GPI anchor peptide signal sequence Cleavage of both of these sequences results in the mature 209 amino acid residue PrP being exported to the cell surface as... and/or genetic where the gene encoding the PrP is mutated (Prusiner, 1998) The mechanism of how prion causes brain damage is poorly understood It was hypothesized that the key event underlying the development of prion disease is the post-translational conversion of normal cellular PrP (PrPC), a cell surface glycoprotein, into its pathogenic isoform, the scrapie prion (PrPSc) (Prusiner et al., 1998, Tuite... macromolecular biosynthesis and maintenance of cellular redox homeostasis in response to increased production of toxic reactive oxygen species (ROS) ROS are produced during stressful situations in the cell and they are highly reactive radicals capable of causing significant damage to cell structures Too much ROS in the cells cause oxidative stress, resulting in cells arresting in cell- cycle, and after... cancer cells acquire genetic alterations making them autonomous, it gives them the ability to separate from the primary tumour, spreading via the lymphatics and blood vessels, and invading into other parts of the body to form secondary lesions This ability to spread and ‘reside’ in other parts of the body is known as metastasis — the final stage of cancer development that causes 90% of human cancer. .. such, a single 10 model of altered tumour metabolism will not fully encapsulate the sum of metabolic changes that can support cancer cell growth (Greaves and Maley, 2012) Thus, any investigation into cancer cell metabolism will lend support to delineating missing pieces of the puzzle, with the grand aim of advancing knowledge that leads ultimately to discoveries of novel cancer treatment options In the. .. Serio, 2010) leading to progressive neuronal accumulation of the latter This in turn causes irreversible damage to the neurons and reduces the availability of PrPC which may interfere with the presumed neuroprotective role of the protein, thus resulting in the underlying neurodegenerative process (Belay et al., 2005) 1 Prion diseases have received the limelight following an outbreak of bovine spongiform ... of the role of PrP in breast cancer metabolism in the study model Picture showing different lactate production in normal and cancer situation Schematic overview of the role of PrP in cancer metabolism. .. higher in normal breast cell line (MCF10A) than breast cancer cell lines (MCF7, SK-BR-3, and MDA-MB-231) Proliferation rate in breast cancer cell lines Up-regulation of p53 in breast cancer cell lines... highest in terms of mortality rate (WHO, 2008), while according to the Singapore Cancer Registry, in 17 women will develop breast cancer in her lifetime in Singapore The risk of getting breast cancer