Investigation of PIN1 as a Genetic Modifier in Li-Fraumeni Syndrome

Transcription

1 Investigation of PIN1 as a Genetic Modifier in Li-Fraumeni Syndrome by Anita Villani, BSc, MD, FRCPC A thesis submitted in conformity with the requirements for the degree of Master of Science Institute of Medical Science University of Toronto Copyright by Anita Villani 2015

2 Investigation of PIN1 as a Genetic Modifier in Li-Fraumeni Syndrome Anita Villani Master of Science Institute of Medical Science University of Toronto 2015 ABSTRACT Li-Fraumeni syndrome (LFS) is a heterogeneous cancer predisposition syndrome caused by germline mutations in TP53. Some of this phenotypic variability can be explained by presence of oncogenic mutant p53 proteins in patients with missense TP53 mutations. Recent data suggest that the prolyl-isomerase, PIN1, serves a fundamental role in mutant TP53 oncogenic gain-of-function (GOF). We hypothesized that alterations in expression of PIN1, mediated by the promoter SNP(-)842G>C (rs ), modify the cancer phenotype of LFS patients. We demonstrate that the PIN1(-)842 GG genotype is associated with increased PIN1 expression at the transcript and protein level. Overexpression of PIN1 selectively enhances the clonogenicity and chemotherapy resistance of LFS fibroblasts harbouring R248Q mutant p53. Concordantly, LFS patients with the PIN1(-)842 GG genotype develop cancer earlier than those with GC/CC genotypes, with a prominent effect in pediatric patients. The GG genotype may also be associated with some predilection for the development of carcinomas. ii

3 ACKNOWLEDGEMENTS I would like to sincerely thank Dr. David Malkin for his invaluable mentorship and encouragement prior to, and over the course of my Masters of Science Degree. I would also like to thank my committee members, Dr. Meredith Irwin and Dr. Irene Andrulis for their thoughtful guidance. My appreciation is further extended to members of the Malkin lab for their instruction, insights and friendship. Finally, I would like to acknowledge my family, and particularly my husband, for their love and support as I strove to pursue and complete this degree. CONTRIBUTIONS Noa Alon carried out DNA extraction of study participant peripheral blood leukocytes for the Malkin Lab. Fabio Fuligni, Bioinformatics Analyst and Richard de Borja, in the laboratory of Dr. Adam Shlien, in the Department of Paediatric Laboratory Medicine at The Hospital for Sick Children, carried out analysis of publically-available datasets for the correlation of PIN1 (- )842 genotype and PIN1 gene expression. Lentiviral transduction was carried out by the SPARC Biocentre at The Hospital for Sick Children. iii

4 TABLE OF CONTENTS CHAPTER 1: INTRODUCTION Li-Fraumeni Syndrome Introduction and definition Introduction Clinical definitions of LFS LFS epidemiology and tumor spectrum LFS biology and pathogenesis LFS and the link to TP Studies of other drivers of LFS Genotype-Phenotype Correlations and Modifier Genes Tumor protein p Introduction p53 structure p53 regulation Brief overview the p53 program TP53 mutants and gain-of-function In-vitro evidence of p53 gain-of-function In-vivo evidence of p53 gain-of-function Proposed mechanisms of p53 gain-of-function PIN Introduction PIN1 structure and regulation PIN1 functions Cell cycle control Cell proliferation and oncogenesis PIN1 and p PIN1 and mutant p CHAPTER 2: RESEARCH AIMS AND HYPOTHESES CHAPTER 3: MATERIALS AND METHODS CHAPTER 4: RESULTS iv

5 1. Influence of PIN1 (-)842 genotype on cancer phenotype in patients with LFS and germline TP53 mutations Characteristics of study cohort Individuals with PIN1 (-)842 GG genotype demonstrate an earlier age of cancer onset PIN1 SNP (-) 842 does not appear to affect the number of primary cancers or the distribution of tumor histologies PIN1 SNP (-)842 influences the proportion of carcinomas in subjects with gain-of-function TP53 mutations Influence of PIN1 (-)842 genotype on expression of PIN PIN1 (-) 842 genotype GG results in increased PIN1 mrna and PIN1 protein levels in lymphoblastoid cell lines Influence of PIN1 (-) 842 SNP on expression of PIN1 is not validated in an independent cohort Influence of PIN1 overexpression on cellular proliferation and apoptosis in LFS patient-derived fibroblasts PIN1 overexpression selectively increases proliferative capacity of LFS patient-derived fibroblasts with the R248Q mutation PIN1 overexpression leads to decreased sensitivity to doxorubicin/avoidance of cell death in LFS patient-derived fibroblasts with the R248Q mutation CHAPTER 5: DISCUSSION CHAPTER 6: APPENDICES REFERENCES v

6 LIST OF ABBREVIATIONS DSB Double-strand break CDK Cyclin-dependent kinase CNV Copy number variant CPC Choroid plexus carcinoma DNA Deoxyribonucelic acid GOF Gain-of-function LFL Li-Fraumeni-like Syndrome LFS Li-Fraumeni Syndrome MEF Mouse embryonic fibroblasts MOI Multiplicity of infection p53 Tumor protein, 53kDa PARP Poly(ADP-ribose) polymerase PCR Polymerase chain reaction PIN1 Peptidyl-prolyl cis/trans isomerase, NIMA-interacting 1 RNA Ribonucleic acid SEM Standard error of the mean SNP Single nucleotide polymorphism WT Wild type vi

7 LIST OF TABLES Table 1: Table 2: Table 3: Table 4: Clinical Criteria for LFS Characteristics of study cohort Allele frequency of PIN1 (-)842 SNP in study cohort Characteristics of study cohort, by PIN1 (-)842 genotype vii

8 LIST OF FIGURES Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Tumor spectrum associated with germline TP53 mutations Codon distribution of germline TP53 mutations Mechanisms of mutant p53 gain-of -function Overview of PIN1 structural domains and function Mechanisms by which PIN1 determines the fate of cellular phosphoproteins Effect of PIN1 on wild-type versus mutant p53 TP53 mutation spectrum in study cohort Influence of PIN1 (-)842 genotype on age of first primary tumor Influence of PIN1 (-)842 genotype on age of first primary tumor in subjects wit gain-of-function missense mutations Figure 10: Proportion of individuals with multiple primary tumors, by PIN1 (-)842 genotype Figure 11: Figure 12: Influence of PIN1 (-)842 genotype on distribution of tumor histologies/types Influence of PIN1 (-)842 genotype on distribution of tumor histologies/types in subset of individuals with gain-of-function germline TP53 mutations Figure 13: Figure 14: Figure 15: Influence of PIN1(-)842 genotype on expression of PIN1 Influence of PIN1 overexpression of fibroblast clonogenicity Sensitivity of LFS patient-derived fibroblasts to doxorubicin treatment viii

9 APPENDICES I. Supplemental Figures Figure S1: Figure S2: Figure S3: Figure S4: Figure S5: Bioanalyzer results of RNA integrity of lymphoblastoid cell line RNA qpcr standard curve, amplification curve and melting curve for PIN1 Vector map for lentiviral vector plx302 Representative fibroblast cell line following transduction with plx302-gfp Representative kill curve used to establish puromycin concentration for selection of transduced fibroblast cells Figure S6: Figure S7: Figure S8: Western blot confirming overexpression of PIN1 in LFS fibroblasts Age distribution of study cohort Spectrum of tumor histologies and specific tumor types in study patient cohort Figure S9: Age of first cancer diagnosis in study cohort Figure S10: Age of first cancer diagnosis by TP53 mutation subtype Figure S11: Influence of PIN1 (-)842 genotype on age of first primary tumor in subjects with missense mutations Figure S12: Analysis of PIN1 transcript levels by PIN1 (-)842 genotype based on 1000 Genomes whole genome sequencing and RNAseq data ix

10 II. Supplemental Tables Table S1: Influence of PIN1 (-)842 genotype on distribution of tumor histologies and types Table S2: Characteristics of LFS patient-derived lymphoblastoid cell lines Table S3: Gain of function properties reported for p53 mutant, R248Q x

11 CHAPTER 1: INTRODUCTION Portions of this Introduction have been submitted for publication as a book chapter to Springer: Villani A, Frebourg T, Malkin D (2015). Li-Fraumeni syndrome Submitted. D. Malkin (Ed.) The Hereditary Basis of Childhood Cancer. New York: Springer. 1. Li-Fraumeni Syndrome 1.1 Introduction and definition Introduction Li-Fraumeni Syndrome (LFS; OMIM #151623) is a prototypic cancer susceptibility syndrome, resulting from highly-penetrant germline mutations in the tumor suppressor gene, TP53. Originally described in 1969 as a familial syndrome characterized by soft tissue sarcoma, breast cancer and other neoplasms in children and young adults, work over the ensuing decades has led to the recognition of an expanded phenotype of early onset cancers with varying degrees of aggressiveness (Li and Fraumeni, 1969). The marked clinical heterogeneity in site and age of cancer onset represents one of the challenges inherent in managing patients with this autosomal dominant disorder. Advances in our understanding of the genetic and genomic basis of LFS will play an important role in refining genotype: phenotype correlations within and between LFS families. Furthermore, it can also be expected that the role of p53 in human cancer more generally will be more clearly articulated through the ongoing study of the progression to cancer in these patients. 1

12 1.1.2 Clinical definitions of LFS A number of clinical definitions for LFS have been proposed (Table 1). The classic definition, based on a prospective analysis of 24 kindreds, has been compared to more inclusive criteria ( Li-Fraumeni like syndrome ) described by Birch and Eeles, and to more recent criteria proposed by Chompret, et al which includes a subset of patients to be tested even in the absence of a suggestive family history (Li et al., 1988, Birch et al., 1994, Eeles, 1995, Chompret et al., 2001, Chompret et al., 2000, Gonzalez et al., 2009b). The sensitivity and specificity of classic LFS criteria for detecting a germline TP53 mutation was reported to be 40% and 91%, respectively. When classic criteria are combined with the Chompret criteria, the sensitivity increases to 95%, and specificity is 52% (Gonzalez et al., 2009b). Chompret s criteria were revised in 2009 and represent the most current clinical criteria for diagnosing LFS (Tinat et al., 2009). 2

13 Table 1: Clinical Criteria for LFS Criteria Description Classic A proband with sarcoma diagnosed under age 45 years, and (Li et al., 1988) A first-degree relative with any cancer under 45 years, and Birch (Birch et al., 1994) Eeles (Eeles et al., 1995) Chompret (Chompret et al., 2000, Chompret et al., 2001) Revised Chompret (Tinat et al., 2009) Another first- or second-degree relative with either any cancer under 45 years, or a sarcoma at any age Among families that do not conform to classic LFS: A proband with any childhood cancer or sarcoma, brain tumor, or adrenocortical carcinoma diagnosed under 45 years, and A first- or second-degree relative with a typical LFS-related cancer (sarcoma, breast cancer, brain tumor, leukemia, or adrenocortical carcinoma) diagnosed at any age, and A first-or second-degree relative in the same genetic lineage with any cancer diagnosed under 60 years Among families that do not conform to classic LFS: Two different tumors that are part of extended LFS in first- or second-degree relative at any age (sarcoma, breast cancer, brain tumor, leukemia, adrenocortical tumor, melanoma, prostate cancer, and pancreatic cancer) Proband with sarcoma, brain tumor, breast cancer, or adrenocortical carcinoma before age 36 years, and At least one first-or second-degree relative with cancer (other than breast cancer if the proband has breast cancer) under 46 years or A relative with multiple primaries at any age Or A proband with multiple primary tumors, two of which are sarcoma, brain tumor, breast cancer, and/or adrenocortical carcinoma, with the initial cancer occurring before the age of 36 years, regardless of family history Or A proband with adrenocortical carcinoma at any age, regardless of family history A proband with tumor belonging to LFS tumor spectrum (soft tissue sarcoma, osteosarcoma, brain tumor, premenopausal breast cancer, adrenocortical carcinoma, leukemia, lung bronchoalveolar cancer) before 46 years, and At least one first- or second-degree relative with LFS tumor (except breast cancer if proband has breast cancer) before age 56 years, or with multiple tumors Or Proband with multiple tumors (except multiple breast tumors), two of which belong to LFS tumor spectrum and first of which occurred before age 46 years Or Patient with adrenocortical carcinoma or choroid plexus tumor, irrespective of family history 1.2 LFS epidemiology and tumor spectrum A number of epidemiological studies have quantified the remarkable lifetime cancer risk observed in individuals with LFS. A frequently cited, hospital-based study estimated the lifetime risk of cancer for TP53 mutation carriers to be 73% for males and nearly 100% for females (Chompret et al., 2000). While the higher penetrance in females was almost entirely accounted for by breast cancer diagnoses, the risk for females was consistently higher than males across all age groups. When sexes were clustered, the overall risks were 15% in those <15 years of age, 54% in those years of age, and 68% in those >45 years 3

14 of age. A study published by Nichols et al. evaluated 45 families with LFS and germline TP53 mutations from two large American centres, in addition to 140 cases in the literature. 30% of the 738 cancers occurring in these kindreds developed before the age of 20 years, while 36% occurred in the third and fourth decades of life (Nichols et al., 2001). A study conducted in the United Kingdom evaluated a cohort of 28 families with germline TP53 mutations, including 501 individuals, among whom 148 cancers developed. Using national cancer statistics for England and Wales, the ratios of observed to expected number of cancers were reported to be 51.2 in those 0-14 years, 32.7 in those years, 20.2 in those years, 6.7 in those years, and 1.4 in those years, highlighting a striking trend of increasing cancer risk with decreasing age of onset (Birch et al., 2001). Indeed, if LFS families are usually characterized by early onset tumours affecting children and young adults, germline TP53 mutations can also be detected in families with later onset cancers occurring after 40 years of age, highlighting the heterogeneity that defines this tumor syndrome (Bougeard et al., 2008, Kast et al., 2012). The exceptional cancer risks for patients with LFS are further defined by the propensity for the development of multiple primary cancers (Li et al., 1988, Chompret et al., 2000, Hisada et al., 1998). In a study of 200 cancer patients from 24 LFS kindreds, the cumulative probability of a second cancer occurrence was reported to be 57% at 30 years following the diagnosis of a first cancer (Hisada et al., 1998). An exceptionally high relative risk of second cancer 83.0 was reported for survivors of childhood cancer (0-19 years), while those with first cancers occurring at ages years and >45 years had relative risks of 9.7 and 1.5, respectively (Hisada et al., 1998). 4

15 Classic LFS-component tumors have traditionally been defined as soft-tissue sarcomas, osteosarcomas, premenopausal breast cancer, brain tumors, leukemias and adrenocortical carcinoma. This tumor spectrum has not only been expanded, (Garber et al., 1991, Hisada et al., 1998, Nichols et al., 2001) (Figure 1) but also further refined, by a number of epidemiological studies, and important lessons have emerged. Figure 1: Tumor spectrum associated with germline TP53 mutations (N=1485). Adapted from IARC TP53 Database, R17, November 2013 (Petitjean et al., 2007). Firstly, common carcinomas in the general population, including lung, colon, cervix, ovary, and prostate are seen infrequently in carriers of a germline TP53 mutation (Nichols et al., 5

16 2001, Birch et al., 2001). Their occurrence, however, is characterized by a much earlier age of onset compared to sporadic tumors in the general population - up to two to three decades sooner (Birch et al., 2001, Olivier et al., 2003, Nichols et al., 2001, Wong et al., 2006, Masciari et al., 2011). This phenotypic switch may be a reflection of the differential effects of a late mutational event in TP53, as commonly occurs in sporadic lung and colon cancer, as opposed to an early event in oncogenesis in individuals with germline TP53 mutations. The second lesson, which continues to develop, is that certain specific histologic and molecular subtypes of classic LFS component tumors appear to be enriched in the LFS population. Among CNS tumors, % of choroid plexus carcinomas (CPC) have been shown to be associated with germline TP53 mutations, and have been incorporated into more recent clinical criteria, as outlined above (Gonzalez et al., 2009b, Tinat et al., 2009, Krutilkova et al., 2005). Sonic-Hedgehog (SHH)-medulloblastoma also appears to be related (Rausch et al., 2012). Among soft tissue sarcomas, anaplastic rhabdomyosarcoma has recently been shown to be particularly enriched in carriers of a germline TP53 mutation (Hettmer S, 2013). In addition, nearly 50% of patients with low-hypodiploid ALL (32-39 chromosomes) have been shown to carry a germline TP53 mutation (Holmfeldt et al., 2013). Finally, among women with breast cancer and TP53 mutations, 63-83% of the tumors have been reported to be HER2-positive (Melhem-Bertrandt et al., Wilson et al., 2010). 1.3 LFS biology and pathogenesis LFS and the link to TP53 Two decades following its original clinical description, the underlying genetic alteration resulting in the Li-Fraumeni phenotype was discovered to be germline mutation in the TP53 6

17 tumor suppressor gene (Malkin et al., 1990). Subsequent studies have documented the presence of a TP53 germline mutation in approximately 70% of patients fulfilling the classic LFS criteria, up to 40% of patients meeting LFL criteria, and 29-35% of patients meeting the Chompret criteria (Varley, 2003, Varley et al., 1997, Bougeard et al., 2008, Gonzalez et al., 2009b). The population frequency of germline TP53 mutations has been estimated to be as high as 1 in 5,000-20,000, although with more efficient recognition of patients with possible LFS through next generation sequencing efforts, and prompt referral for counseling and genetic testing, the actual prevalence may, in fact, be substantially higher (Lalloo et al., 2003, Gonzalez et al., 2009b). Up to 20% of TP53 mutations occur de novo, with the rest being inherited in an autosomal dominant fashion (Gonzalez et al., 2009a) Studies of other drivers of LFS The lack of detectable germline TP53 mutations in a proportion of families with LFS has led to efforts to identify other candidate genes. CHEK2 is a cell cycle checkpoint kinase which activates p53 in response to DNA damage. Germline mutations in CHEK2 were originally described in a small number of LFS families; however, some of these mutations were subsequently shown to be polymorphisms and many studies have since failed to demonstrate CHEK2 as a major susceptibility gene for LFS (Sodha et al., 2002, Bell et al., 1999, Ruijs et al., 2009, Siddiqui et al., 2005). The specific CHEK2 c.1100delc mutation has been associated with hereditary breast cancer, but has not been found to play a major role in LFS, even in a large Dutch cohort with a high prevalence of this allelic variant (Ruijs et al., 2009, Nevanlinna and Bartek, 2006, Weischer et al., 2008). Other candidate genes, including PTEN, CDKN2, BCL 10, TP63 and BAX have also been shown not to have a causal 7

18 role (Burt et al., 1999, Portwine et al., 2000, Stone et al., 1999, Bougeard et al., 2001, Barlow et al., 2004). Methylation of the TP53 gene promoter has been explored as a mechanism of epigenetic silencing, as occurs in hereditary non-polyposis colon cancer, but this was not found to be a frequent cause of LFS in families with no detectable TP53 germline mutation (Finkova et al., 2009). More recently, a French study evaluated for the presence of rare germline copy number variants (CNVs) in 64 patients with early-onset tumors, meeting the Chompret criteria for LFS, and without detectable germline TP53 mutations (Aury-Landas et al., 2013). They identified 20 copy number variants in 15 unrelated patients which were absent in 600 controls, using a custom-designed highresolution array CGH. Interestingly, these included four regions which encompassed genes encoding p53 partners which are involved in chromatin remodeling. The study did not perform a systematic segregation analysis, and thus some of these CNVs may be nonpathogenic. Unless confirmed by further study, it is also not possible to exclude that some of these variants may be insufficient on their own to confer cancer risk. Of note, this array found no CNVs in 24 genes involved in the p53 pathway or Mendelian predisposition to cancer, or in six micrornas of the p53 pathway Genotype-Phenotype Correlations and Modifier Genes The vast majority of TP53 mutations cluster in regions II to V, within the DNA binding domain, encoded by exons 5 to 8 of the 11-exon gene (Figure 2) (Varley, 2003, Petitjean et al., 2007). Interestingly, most of these (>70%) are missense mutations. Splice site, nonsense, frameshift and intronic mutations have also been described, in addition to large partial or complete deletions of the gene or its promoter (Petitjean et al., 2007, Bougeard et 8

19 al., 2003, Bougeard et al., 2008). Genotype-phenotype studies of patients with LFS suggest that missense mutations in the core DNA binding domain are associated with earlier age of cancer diagnosis and higher cancer incidence, particularly for breast and brain tumors, compared with mutations resulting in protein truncation or inactivation (Birch et al., 1998). Missense mutations were shown to be associated with a nine year earlier mean age of first tumor onset compared to other types of alterations, while TP53 null mutations were found in pedigrees characterized by a late tumor onset, in a more recent study (Bougeard et al., 2008). These clinical data support a gain of function potential for such missense mutations, including activation of cell cycle target genes by the mutant p53 protein, or alternatively a dominant negative effect, whereby the mutant protein interferes with wildtype p53 DNA binding. Pre-clinical data supporting this notion will be discussed in detail below. Notably, retention of the wild-type TP53 allele has been shown in two-thirds of tumors from patients carrying a missense mutation in the central DNA binding domain, demonstrating a reduction of selective pressure for loss of the wild-type allele (Chene, 1998). This is in contrast to the invariable loss of heterozygosity associated with tumors from families harbouring functionally null TP53 germline mutations, which is more in keeping with typical tumor suppressor genetics (Malkin, 2011). 9

20 Figure 2: Codon distribution of germline TP53 mutations (N=636), against domains of TP53. Adapted from IARC TP53 Database, R17, November 2013 (Petitjean et al., 2007). TAD = transactivation domain, SH3 = Src homology 3-like domain, DBD = DNA-binding domain, TD = tetramerization domain, RD = regulatory domain. Other studies of LFS families have described tissue-specific genotype-phenotype correlations. Missense mutations in the L2 and L3 loops within the DNA-binding domain (see below) have been linked with CNS tumors, while mutations outside the DNA binding surface have been linked with adrenocortical carcinoma (Olivier et al., 2003). Of particular note, the unique Brazilian germline mutation at codon R337H, a low-penetrance (~10%) allele, has a striking association with adrenocortical carcinoma conferring a remarkable 20,000-fold increased risk although other LFS-component tumors have occasionally been 10

21 described in these families (Ribeiro et al., 2001, Petitjean et al., 2007, Wasserman et al., 2012). While these few genotype-phenotype correlations have been described, they are not consistently validated throughout the literature. Furthermore, the diversity of tumor types and presentations within a given LFS kindred suggests the possibility of genetic and epigenetic modifiers as contributors to phenotypic variability. MDM2 is a negative regulator of p53, and acts by targeting it for proteosomal degradation. The SNP309 T>G variation (rs ) increases MDM2 levels and thus potentially amplifies this effect. A number of studies have demonstrated accelerated tumor formation in TP53 mutation carriers harbouring the MDM2 SNP309 polymorphism (Bond et al., 2004). The mean age of tumor onset was found to be 10 years earlier in carriers of a G allele. This effect was amplified by the presence of the TP53 codon 72 Arginine (R) polymorphism (rs ), a variant which has a higher affinity towards MDM2, compared to the Proline (P) variant (Bougeard et al., 2006, Bougeard et al., 2008). Similar findings were reported in a larger, more recent study of TP53 mutation carriers with MDM2 SNP 309, with a particularly pronounced effect in females, although the TP53 codon 72P variant was associated with increased cancer risk (Fang et al., 2010). Among TP53 mutation carriers with MDM2 SNP 309, accelerated tumor formation was more specifically and in some cases more dramatically documented in patients with soft tissue sarcoma and breast cancer, although these findings are limited by small numbers (Marcel et al., 2009, Wu et al., 2011). More recently, an interaction between MDM2 SNP 285 and 309 was documented in a series of 11

22 195 LFS patients: the 285G-309G haplotype was shown to be associated with a 5 year earlier age of tumor onset (Renaux-Petel et al., 2014). The TP53 PIN3 polymorphism (rs ), represented by a 16bp duplication in intron 3, has also been shown to be a modifier of the germline TP53 mutation phenotype. Its presence was associated with a 19 year difference in the mean age of tumor diagnosis among 25 TP53 mutation carriers in a Brazilian study (Marcel et al., 2009). All patients who developed cancer before the age of 35 were found to be homozygous for the nonduplicated allele, and the modifier effect was particularly marked for soft tissue sarcoma (32.3 year difference in age of tumor onset). This finding was not restricted to those with the R337H TP53 mutation. In contrast, a study of 152 germline mutation carriers reported that the duplication allele confers an increased cancer risk in men, and no effect was found on age of first cancer diagnosis (Fang et al., 2011). A genome-wide study of germline DNA copy number variation (CNV) in LFS families shows a significant increase in CNVs in germline TP53 mutation carriers (Shlien et al., 2008). Furthermore, offspring were more likely to have increased CNVs compared to their parents, and those mutation carriers affected by cancer showed a trend for greater number of CNVs compared to those carriers not affected by cancer. Together, these data may suggest an association between CNV frequency and severity of phenotype. The authors also demonstrated copy number variability in cancer-related genes in the LFS cohort, and suggest that CNV changes are among the earliest manifestations conferred by TP53 mutations, and predispose to other genetic events leading to tumorgenesis. 12

23 Telomere attrition has also been studied as a mechanism leading to genetic anticipation, via increased genomic instability. Indeed, in families with LFS, telomere length was found to be shorter in individuals with cancer than in non-affected carriers, and the latter group was shown to have a faster rate of telomere attrition than normal controls (Tabori et al., 2007, Trkova et al., 2007). The occurrence of accelerated telomere attrition is one potential explanation for the earlier age of tumor onset observed in successive generations of a given family with identical TP53 genotype. TP53 mutations have been observed in some tumors exhibiting a recently described mechanism of tumorigenesis termed chromothripsis, in which it is postulated that a single catastrophic event results in massive chromosome rearrangements (Rausch et al., 2012). Whole-genome sequencing-based analysis of Sonic-Hedgehog medulloblastoma (SHH-MB) from a patient with LFS revealed highly complex chromosome rearrangements. These findings were demonstrated in three additional SHH-MB patient samples, and were associated with an amplification of known medulloblastoma oncogenes as a result of chromothripsis. Furthermore, 36% of other LFS-associated tumors tested from eleven LFS patients were shown to have rearrangements consistent with chromothripsis. The authors suggest that earlytp53 mutations may confer a state in cells that is permissive for chromothripsis and/or facilitate cell survival following such catastrophic DNA rearrangements. An opposing (or, perhaps alternate) view to that of accumulated DNA damage is one of genetic regression, a concept recently coined in a genomic study of 13 members of an LFS kindred (Ariffin et al., 2014). The authors could not demonstrate an accumulation in CNVs, 13

24 telomere attrition or contribution of commonly reported modifier genes to account for apparent anticipation and heterogeneity in phenotype among carriers. Instead, using whole genome sequencing, they showed Mendelian segregation of rare susceptibility/resistance variants affecting the penetrance of germline TP53 mutations. By further comparing 293 pedigrees from the IARC (International Agency for Research on Cancer) TP53 database, they demonstrate that apparent anticipation is caused by delayed occurrence of cancer in the first generations of multi-generation families, rather than by accelerated cancer onset in subsequent generations. In an intriguing argument, they postulate that modifier effects of a wide array of rare variants influence the penetrance of germline TP53 mutations; that tolerant genetic backgrounds in some de novo mutation carriers become diluted in subsequent generations; and that furthermore, non-carrier parents may contribute susceptibility alleles to their progeny, that suppress the resistance alleles and accelerate tumor onset. Interestingly, studies in mice also support the importance of genetic background in determining tumor phenotype. For instance, when the p53 null allele is back-crossed onto a BALB/c background (a strain susceptible to induction of mammary tumors), BALB/c-p53 +/- mice predominantly develop mammary adenocarcinoma, as opposed to a predominance of osteosarcoma, soft tissue sarcoma and lymphomas that characterize p53 +/- mice on a 129S4/SvJae background (Kuperwasser et al., 2000, Harvey et al., 1993a, Donehower et al., 1995). 14

25 2. Tumor protein p Introduction The TP53 gene is the most commonly mutated gene in human cancer (Kandoth et al., 2013). Its protein product, p53, was first identified in 1979 in a complex with simian virus 40 (SV40) large T-antigen (Linzer and Levine, 1979). A decade of initial research supporting the notion of p53 as a proto-oncogene was overturned by seminal findings of loss of heterozygosity at the TP53 locus in >50% of colorectal carcinomas a hallmark of tumor suppressor genes (Baker et al., 1989). A great number of studies have since confirmed the role of p53 as a tumor suppressor gene, including evidence from p53 -/- mice demonstrating a pronounced susceptibility to tumor development (Donehower et al., 1992, Harvey et al., 1993b). Indeed, the p53 protein has long been regarded as having one of the most central roles in cancer biology. 2.2 p53 structure The TP53 gene is located at 17p13.1 and encodes a 393-amino acid protein product, which is divided into four main structural domains that allow it to fulfill its main role as a transcription factor (Figure 2) (Soussi and May, 1996, Kern et al., 1991). The N-terminal transcriptional activation domain (actually, two domains) interacts with transcriptional machinery to regulate gene expression, while the DNA-binding domain contains a Zn 2+ ion and folds into a specific secondary structure of β-sheets and α-helical loops to interact directly with DNA (the L1, L2 and L3 loops) (Cho et al., 1994, Zhu et al., 1998). p53 binds to a consensus DNA sequence (5 -PuPuPuC(A/T)-3 ) that exists as two pairs of inverted repeats (Cho et al., 1994, Levine, 1997). Greater than 90% of missense mutations are located in this DNA-binding domain; 40% of missense mutations are specifically localized to 6 hotspot 15

26 residues (R175, G245, R248, R249, R273, and R282), which are either classified as structural mutants or contact mutants, owing to their important roles in defining the conformation of this domain, and in allowing contact with DNA, respectively (Petitjean et al., 2007, Levine, 1997, Cho et al., 1994). The tetramerization domain permits p53 to assume its homo-tetramer conformation, and the final C-terminal, lysine-rich regulatory domain is important for nuclear localization and post-translational modification of p p53 regulation As a potent inhibitor of cell growth, the activity of p53 is tightly regulated within the cell. Indeed, the half-life of p53 is only approximately 20 minutes, owing to a variety of regulatory mechanisms (Levine, 1997). The MDM2 protein is one of the chief regulators of p53; it functions as an E3 ligase, which ubiquitinates p53 and targets it for degradation by the proteosome (Honda et al., 1997). MDM2 has also been shown to directly inhibit p53 s transcriptional activity, and furthermore, it is involved in the nuclear export of p53 (Momand et al., 1992, Geyer et al., 2000). Indeed, MDM2 function is inhibited by a variety of mechanisms when p53 is induced in response to stress. For instance, in response to DNA double-strand breaks caused by ionizing radiation, Chk1 and Chk2 (DNA damage-induced kinases) phosphorylate the N-terminus of p53, thereby inhibiting its interaction with MDM2 and preventing its degradation (Hirao et al., 2000). In response to other stresses, such as oncogene activation, the ARF (p14) protein binds to MDM2 directly to cause its inhibition (Sherr and Weber, 2000). The importance of MDM2 regulation of p53 is demonstrated by the phenotype of MDM2 -/- mice, which are embryonic lethal, due to aberrant apoptosis driven by p53 (de Rozieres et al., 2000). This phenotype is rescued by deletion of TP53 16

27 (Montes de Oca Luna et al., 1995). In fact, MDM2 is a transcriptional target of p53, thus creating an autoregulatory feedback loop to assist in controlling the p53 response (Barak et al., 1993). p53 localization, more specifically its nuclear localization, is also closely regulated. p53 is actively transported to the nucleus by its interaction with microtubules, and a nuclear localization signal within the C-terminal domain allows for nuclear import (Giannakakou et al., 2000). Ubiquitination by MDM2 promotes nuclear export (Geyer et al., 2000). The chief mechanism of p53 activation is by removal of inhibition through post-translational modification, rather than by increased transcription. These modifications include phosphorylation, sumoylation, methylation and acetylation and are made in the transactivation and regulatory domains (Gostissa et al., 1999). Phosphorylation is the dominant modification and is achieved by multiple protein kinases in addition to Chk1 and Chk2, including ATR (A-T and Rad3-related), ATM (mutated in ataxia-telangiectasia), and JNK (Jun NH2-terminal kinase) (Lavin and Gueven, 2006). Certain residues are constitutively phosphorylated, namely Ser376 and Ser378, and their de-phosphorylation is in fact what stabilizes and activates p53 in response to radiation damage (Waterman et al., 1998). Histone acetylases, such as p300/cbp and P/CAF, and PML act on several lysine residues at the C-terminal end of p53 to alter the confirmation of this region and enhance p53 s DNAbinding activity (Fogal et al., 2000, Liu et al., 1999). The coordination of a series of post-translational modifications, culminating in the stabilization and activation of p53, is likely to exist. It has been proposed that modifications to p53 occur in an ordered pattern in response to cellular stresses, beginning with a rapid 17

28 phosphorylation of Ser15 as a priming event, followed by phosphorylation of other residues such as Thr18 and Ser20, and the recruitment of C-terminal acetylases (Lavin and Gueven, 2006). Subsequent to phosphorylation of specific sites, other protein partners, such as PIN1, can then bind to p53 to effectively alter its confirmation and enhance its activity, as will be discussed in detail below (Zacchi et al., 2002). The series of posttranslational modifications to p53, in response to specific cellular stresses and activation of signaling molecules, in part determines the choice of cellular response to p53 activation. Finally, it is interesting to note that, in a number of tumors with wild-type p53, perturbations in mechanisms of p53 stabilization, nuclear localization and post-translational modification have been shown to be impaired, underscoring the importance of p53 structure to its function (Ryan et al., 2001). 2.4 Brief overview the p53 program p53 is stabilized and activated in response to a variety of cellular stresses, including DNA damage, hypoxia, oncogene activation, glucose starvation, nucleoside depletion and telomere attrition (Ryan et al., 2001, Levine, 1997). Several cellular responses are then coordinated by p53, including inhibition of angiogenesis, DNA repair, senescence and regulation of metabolism, but its most prominent and well-studied functions are inducing cell cycle arrest and apoptosis (Ryan et al., 2001, Li et al., 2012). In inducing these critical processes, p53 prevents the propagation of cells that harbour harmful and potentially oncogenic changes. p53 stimulates the expression of p21 WAF1/CIP1, which is an inhibitor of cyclin-dependent kinases (CDK); these kinases interact with cyclin proteins to ensure smooth transition 18

29 between the phases of the cell cycle: G1, S, G2 and M (el-deiry et al., 1994). p21 inhibition of CDKs results in cell-cycle arrest at the G1-S and G2-M checkpoints, thus allowing for repair of DNA damage, if required (Agarwal et al., 1995). Two cyclin-dependent kinases, CDK2 and CDK4, are blocked from phosphorylating and inactivating the prb protein, which, in turn maintains its repression of E2F transcription factors (Levine, 1997, Weinberg, 1995). The E2F family regulates a number of genes required to initiate and propagate the S phase of the cell cycle, thus their repression results in arrest at the G1-S checkpoint. p21 also prevents PCNA from activating DNA polymerase δ, which is needed for DNA replication; this underlies a second mechanism for promoting cell cycle arrest in the S phase (Waga et al., 1994). In addition to its activation of p21, p53 induces ᵟ and GADD45, which together inhibit the cyclinb/cdc2 complex that is required for the G2-M transition (Hermeking et al., 1997). Once DNA damage is repaired, p53 and p21 levels decrease, leading to resumption of the cell cycle. The p53 apoptotic response is mediated by both transcription-dependent and independent mechanisms. p53 target genes can act as contributors to the death-receptor apoptotic pathway ( extrinsic pathway ), or the mitochondrial pathway ( intrinsic pathway ). p53 induces expression of various death receptors, including Fas, Killer/DR5, and PIDD (Lin et al., 2000, Ryan et al., 2001). p53 is also involved directly in the relocalization of death receptors, such as Fas, to the cell membrane (Bennett et al., 1998). These death receptors form a death-induced signaling complex (DISC) that recruit initiator caspases 8 and 10, which go on to activate the effector caspases 3, 6 and 7. These caspases 19

30 cleave cellular targets to trigger apoptosis and the classic morphologic changes that define it. p53 s involvement in the intrinsic pathway of apoptosis relies on its control of a subset of the Bcl-2 family of proteins. This family consists of both pro-apoptotic members, such as Bax and Bak, and the BH3-only proteins (such as Puma, Noxa, and Bid) and antiapoptotic/pro-survival members including Bcl-2 and Bcl-XL. p53 shifts the balance to favour pro-apoptotic members, which triggers mitochondrial depolarization and cytochrome c release from the intermembrane space into the cytoplasm (Miyashita and Reed, 1995, Nakano and Vousden, 2001, Oda et al., 2000). Here, it combines with APAF-1 and procaspase-9, which form the apoptosome. This interaction activates caspase 9 and it goes on to activate the effector caspases, as occurs in the extrinsic pathway. 2.5 TP53 mutants and gain-of-function A review of the TP53 literature reveals that the earliest studies of this intensivelyinvestigated gene suggested that it was in fact, an oncogene, as mentioned above. The documentation of elevated levels of the p53 protein product in cancer cells, (DeLeo et al., 1979) and its ability to transform primary cells in culture (Parada et al., 1984) was in effect the result of use of a mutant version of TP53 that had been isolated from tumor cells (Levine and Oren, 2009). These early studies set the stage for significant research activity into the characterization of mutant p53 proteins as oncoproteins the so-called gain-offunction mutants. As mentioned above, there is a prevalence of missense TP53 mutations in the majority of patients with LFS. This finding is mirrored in sporadic tumors, in contrast to the majority of 20

31 other well- known tumor suppressors, which are predominately inactivated by null mutations (RB1, APC, VHL, NF1) (Levine et al., 1995). These descriptions, coupled with observations from in vitro systems of increased tumorigenic potential of TP53 -/- cells transformed with mutant TP53 constructs, findings of accelerated spontaneous or carcinogen-induced tumorigenesis in transgenic mouse models, and altered expression of novel sets of genes, support the notion of an oncogenic function of mutant p53, as will be discussed below In-vitro evidence of p53 gain-of-function Over 20 years ago, the effects of expression of mutant p53 proteins in p53-null cell lines was tested. Human osteosarcoma and murine fibroblast cells lines expressing transfected hotspot p53 mutants were shown to form tumors in nude mice and to form colonies on soft agar, unlike parental cells or cells transfected with vector alone (Dittmer et al., 1993a). These experiments demonstrated a growth advantage conferred by mutant p53, in the absence of wild-type p53 protein. The study went on to show the ability of mutant p53 constructs to enhance the expression of a multi-drug resistance gene. Further direct evidence of drug-resistance/avoidance of cell death as a gain-of-function property of mutant p53 proteins was provided by introducing various p53 mutants into p53-null human lung adenocarcinoma cell lines (H1299) (Blandino et al., 1999). Clonogenic survival assays confirmed resistance to etoposide and cisplatin chemotherapy treatments, and furthermore, the rate of etoposide-induced apoptosis was also shown to be reduced in cell lines expressing R175H, R248W and R273H p53 mutants. There is also more recent exciting data to suggest that mutant p53 can potentiate somatic stem cell reprogramming (that is, 21

32 the reprogramming of differentiated somatic cells into pluripotent stem cells). For instance, in breast tissue expressing the Wnt transgene and R175H mutant p53, multiple different tumors could be initiated and expanded (Lu et al., 2013). A breadth of studies has since expanded on the gain-of function properties of mutant p53 proteins; these include invasion, increased migration, propagation of the cell cycle, anchorage-independent growth, genomic instability, xenograft growth, formation of metastases, angiogenesis and epithelialmesechymal transition (extensively reviewed in (Muller and Vousden, 2014) and (Freed- Pastor and Prives, 2012)). What has become clear from these studies and from data derived from experiments in mutant p53 mouse studies, is that different p53 mutants exhibit distinct gain-of-function and loss of wild-type activities. Furthermore, a given mutant may function differently in diverse tissue types, which may reflect differences in the expression of its targets (Blandino et al., 1999, Halevy et al., 1990, Sarig et al., 2010, Muller and Vousden, 2014) In-vivo evidence of p53 gain-of-function The generation of knock-in mouse models harbouring p53 missense mutations has been invaluable to furthering our understanding of gain-of-function properties of mutant p53. First, the majority of tumors which develop in mice harbouring p53 missense mutations retain the wild-type allele; (Chene, 1998, Liu et al., 2000) these findings point to a survival advantage mediated by either a gain-of-function of the mutant allele, or alternatively, a dominant-negative effect, whereby mutant p53 inactivates its wild-type counterpart (resulting from the formation of mutant-wild-type p53 tetramers and/or mutant-induced co-aggregation of wild-type p53). Mice heterozygous for the p53 R172H mutation (equivalent 22

33 to the TP53 R175H hot-spot mutation in humans) develop a tumor spectrum notably different from mice heterozygous for a null mutation: while showing a similar susceptibility to sarcomas, they develop more carcinomas, and slightly less lymphomas (Liu et al., 2000, Lang et al., 2004). Furthermore, osteosarcomas and carcinomas metastasize frequently in p53 R172H mice, in contrast to the rare occurrence of metastases in p53 +/- mice. Consistent with these findings, embryonic fibroblasts from p53 R172H /R172H mice display enhanced cell proliferation and transformation potential. Mice heterozygous for the contact mutant, p53 R270H (equivalent to the TP53 R273H hot-spot mutation in humans) also develop a tumor distribution distinct from p53 +/- mice, and show more carcinomas and less osteosarcomas than p53 R172H mice (both created on a 129S4/SvJae background, in contrast to a C57Bl/6 background in (Liu et al., 2000) and (Lang et al., 2004)), demonstrating allele-specific tumor spectra (Olive et al., 2004). Specifically in support of gain-of-function effects, p53 R270H/- and p53 R172H/- mice show different tumor spectra than p53 -/- mice, including more aggressive carcinomas and angiosarcomas; in addition p53 R172H/- mice have a greater incidence of multiple tumors (Olive et al., 2004). Age-of-onset effects have also been explored in mouse models: the humanized R248Q p53 knock-in mouse shows an earlier age of tumor onset and a reduced overall survival compared to p53 -/- mice (Hanel et al., 2013). Interestingly, the same phenotypic effects were not demonstrated by the humanized R248W p53 knock-in mouse (Song et al., 2007), once again pointing to the complexity of mutant p53 gain-of-function biology. 23

34 2.5.3 Proposed mechanisms of p53 gain-of-function The mechanisms by which mutant p53 exerts its gain-of-function effects have started to be elucidated. Three hypotheses have been proposed, and it is likely that all of these mechanisms are at play, depending on the cellular context. The first conjecture is that mutant p53 interacts with cytoplasmic proteins to affect processes such as apoptosis and autophagy (Chee et al., 2013, Morselli et al., 2008); the second is that it transcriptionally activates novel target genes by directly binding their promoters (Weisz et al., 2007); and the third is that mutant p53 interacts with other transcription factors to enhance or eliminate their activity (Lozano, 2007, Walerych et al., 2012) (Figure 3). This latter activity the indirect effect on gene expression is thought to be the major mechanism underlying the novel activities of mutant p53 proteins. Figure 3: Mechanisms of mutant p53 gain of function (Freed-Pastor and Prives, 2012). Used with permission (Cold Spring Harbor Laboratory Press, 7/21/2015). 24

35 The most extensively-studied interactions of mutant p53 are with its transcription factor family members, p63 and p73. While sharing significant homology with certain domains of p53, p63 and p73 also have various isoforms due to the presence of alternate promoters and/or alternative splicing (Pietsch et al., 2008). While both p63 and p73 can transactivate targets of p53, such as the cell cycle inhibitor p21 and pro-apoptotic genes such as Bax and cyclin G, their N isoforms can show a dominant negative effect and promote antiapoptotic and cell cycle progression signals (Gaiddon et al., 2001, Jost et al., 1997, Miyashita and Reed, 1995, Okamoto and Prives, 1999). In addition, p73 has been shown to be activated in response to cellular stresses such as DNA-damaging treatments with specific chemotherapeutic agents and gamma-irradiation (Gong et al., 1999, Irwin et al., 2003, White and Prives, 1999). While wild type p53 does not bind to its homologues, various mutant p53 proteins have been shown to bind to p63 and p73, leading to their inhibition, and resulting in a reduction of their transcriptional activity and ability to promote an apoptotic response (Di Como et al., 1999, Gaiddon et al., 2001, Irwin et al., 2003). These interactions have also been associated with the mutant p53 s ability to promote migration, invasion and chemoresistance (Adorno et al., 2009, Muller et al., 2009, Irwin et al., 2003). While p73 -/- and p63 -/- knockout mice (lacking all isoforms) show developmental anomalies in the nervous and immune systems of the former and in skin and limb development of the latter (Yang et al., 1999, Yang et al., 2000) intriguingly, studies of mice heterozygous for both p53 and either p63 or p73 demonstrate that loss of p63 or p73 mimics the metastatic phenotype of mice with mutant p53 (Gaiddon et al., 2001, Flores et al., 2005, Lang et al., 2004, Olive et al., 2004). 25

36 Recently, mutant p53 has been shown to down-regulate Dicer, the protein responsible for cellular generation of mature micrornas (non-coding RNAs with pervasive posttranscriptional gene regulation effects), and a target of p63 (Su et al., 2010). This was shown to be achieved via both p63-dependent and independent mechanisms, with resulting invasive behavior of cells (Muller et al., 2014). Indeed, a variety of microrna expression is influenced by mutant p53, with presumed far-reaching effects on cellular functions (Donzelli et al., 2014). Mutant p53 has been shown to transactivate a wide array of genes involved in tumorigenesis (reviewed in (Freed-Pastor and Prives, 2012)). These include genes involved in the promotion of cell proliferation, including MYC, EGFR, CDK1 and MAP2K3, among many others, and htert, allowing for ongoing proliferative capacity (Scian et al., 2004) (Frazier et al., 1998, Ludes-Meyers et al., 1996, Di Agostino et al., 2006, Gurtner et al., 2010). Genes involved in inhibition of apoptosis are also known targets, such as NFKB2, BCL2L1 and IGF2 (Scian et al., 2005, Bossi et al., 2008, Lee et al., 2000). Interestingly, mutant p53 has also been shown to alter the expression of genes involved in sterol biosynthesis and metabolism (Freed-Pastor et al., 2012, Zhou et al., 2014), and recently, it was demonstrated that mutant p53 drives the Warburg effect; that is, the phenomenon by which tumor cells use aerobic glycolysis for energy production (Zhang et al., 2013). This is achieved by upregulation of positive regulators of RhoA, which in turn promotes GLUT1 translocation to the plasma membrane; these activities were shown to underlie mutant p53 s ability to promote tumorigenesis in both in vitro and in vivo assays (Zhang et al., 2013). 26

37 How mutant p53 transactivates such a wide array of genes remains elusive, particularly in light of the fact that no specific mutant p53 response element has been identified to date (Freed-Pastor and Prives, 2012). One popular proposed explanation is that mutant p53 proteins interact with other transcription factors, and up- or down-regulate their specific target responses. In support of this notion, mutant p53 binds NF-Y in order to upregulate cyclins and cyclin-dependent kinases (Di Agostino et al., 2006), Ets-1 to influence drug efflux proteins and chemoresistance (Sampath et al., 2001), Sp-1 to influence proliferation (Chicas et al., 2000), and E2F-4, resulting in downregulation of RAD17 and BRCA1, with consequent impairment of DNA repair mechanisms and genomic instability (Valenti et al., 2015). Intriguingly, wild type p53 also interacts with many of these transcription factors, albeit with opposite outcome; these contrasting results may be the consequence of recruitment of different cofactors, such as epigenetic modifier proteins (Di Agostino et al., 2006). The mechanisms underlying mutant p53 s interference with the DNA double-strand break (DSB) damage response have also been investigated. Data suggests that p53 directly interacts with the MRN (Mre11-Rad50-NBS1) complex, and suppresses its binding to DSBs, thereby interfering with ATM activation (Song et al., 2007). 3. PIN1 3.1 Introduction PIN1 (Protein interacting with NIMA (never in mitosis A)-1) is a member of a large family of ubiquitous, evolutionarily-conserved enzymes termed peptidyl-prolyl cis/trans isomerases (PPIases), whose function is to catalyze the cis/trans isomerization of peptidyl-prolyl 27

38 peptide bonds (Lu and Zhou, 2007). Prolines produce conformation-restrained peptide bonds which will change between isomers spontaneously, but not in a biologically relevant timeframe, which informs the utility of PPIases to the cell. A change in protein conformation is associated with a change in function: as a result of prolyl-isomerization, the actions of PPIases can influence a protein s stability, subcellular localization, protein-protein interactions and catalytic activity. Other members of the PPIase family include cyclophilis (Cyps) and FK506-binding proteins (FKBPs). However, PIN1 is the sole PPIase that specifically recognizes phosphorylated Ser/Thr-Pro peptide sequences, that is, phosphorylated Ser or Thr residues that precede a proline residue (although, others may exist) (Figure 4b) (Lu et al., 1996, Ranganathan et al., 1997, Yaffe et al., 1997). Cells are equipped with a large superfamily of Pro-directed protein kinases, which include cyclindependent protein kinases (CDKs), extracellular signal-regulated kinases (ERKs), stressactivated protein kinases/c-jun-n-terminal kinases (SAPKs/JNKs), Polo-like kinases, p38 kinases and glycogen synthase kinase-3 (GSK-3)(Blume-Jensen and Hunter, 2001). These kinases have diverse and important roles in cellular growth regulation, stress responses and neuronal survival, and therefore, PIN1 s conformational regulation of their substrates has significant impact on crucial cellular processes. 3.2 PIN1 structure and regulation The PIN1 gene is located at human chromosome 19p13.2, contains 4 exons, and encodes a 163-amino acid protein product. It has a two-domain structure, consisting of an N-terminal WW domain, and a C-terminal PPIase domain (Figure 4a). The WW domain binds specific 28

39 pser/thr-pro motifs, while the PPIase domain catalyses the isomerization of these motifs in the protein substrate, to regulate its conformation and thus its function (Lu et al., 1999). As with the regulation of Pro-directed phosphorylation signaling, PIN1 function is tightly regulated at multiple levels. This is in contrast to most other PPIases, which are constitutively active (Fischer and Aumuller, 2003). In general, PIN1 expression is associated with a cell s proliferative state: its transcription is regulated by the E2F family of transcription factors, and it has been shown to be suppressed by the tumour suppressor BRCA1 (MacLachlan et al., 2000, Ryo et al., 2002). Furthermore, PIN1 has been shown to be upregulated in many human cancers (Bao et al., 2004, Ryo et al., 2001, Wulf et al., 2001). PIN1 is also subject to post-translational modifications. The best described among these is phosphorylation of Ser16 of the WW domain (Lu et al., 2002). This modification occurs in a cell-cycle-dependent manner, and it prevents PIN1 from interacting with pser/thr-pro motifs. Polo-like kinase-1 has also been shown to phosphorylate Ser65 of PIN1, which reduces its ubiquitination and thereby increases its stability (Eckerdt et al., 2005). 29

40 a) b) Figure 4: Overview of PIN1 structural domains and function a) The WW domain binds specific pser/thr-pro motifs, and the PPIase domain catalyses the cis/trans isomerization of these motifs, as shown in b) (Lu and Zhou, 2007). Used with permission (Nature Publishing Group, 06/18/ 2015). 3.3 PIN1 functions PIN1 is involved in governing a wide array of cellular processes, and often it regulates multiple targets in a given pathway to help direct the cell along a specific course. PIN1 determines the fate of cellular phosphoproteins through a variety of mechanisms, by 30

41 regulating their recycling, further post-translational modification, and degradation (Figure 5). There is an extensive literature related to the role of PIN1 in neuronal function and protection against neuronal degeneration in Alzheimer s disease, but these topics are beyond the scope of this review. Figure 5: Mechanisms by which PIN1 determines the fate of cellular phosphoproteins (Liou et al., 2011). Used with permission (Elsevier, 06/18/2015) Cell cycle control In 1996, intriguing insights into PIN1 cellular functions were made by Lu et al. when it was demonstrated that depletion of PIN1 by use of an antisense construct induced mitotic 31

42 arrest in HeLa cells (and showed the same phenotype by manipulating its homologue in yeast) (Lu et al., 1996). Indeed, this same study identified PIN1 by its ability to interact with NIMA, a mitotic kinase in Aspergillus nidulans, and suppress its ability to induce mitotic catastrophe. These results were expanded upon by the same group in 2002 when they showed that a mutant PIN1 construct induced mitotic block and apoptosis (Lu et al., 2002). PIN1 was shown to interact with a subset of mitotic phosphoproteins including Cdc25, Myt1, Wee1, Plk1 and Cdc27 (Shen et al., 1998). In a Xenopus laevis model, it was determined that PIN1 is required for the DNA replication checkpoint: in the presence of a DNA replication inhibitor, egg extracts inappropriately transitioned from the G2 to M phase when they were depleted of PIN1, a phenotype that was only reversed by wild-type PIN1 (Winkler et al., 2000). An additional interesting observation was made from the generation of Pin1 -/- mice. These mice demonstrated phenotypic changes consistent with proliferation defects, including retinal hypoplasia, testicular atrophy, decreased body weight, and mammary gland hypoproliferation in pregnancy (Liou et al., 2002). The authors noted that these phenotypes were similar to Cyclin D1 -/- mice. They went on to show reduced levels of Cyclin D1 in various tissues of Pin1-deficient mice, and that Cyclin D1 was a substrate for Pin1 and was stabilized by this interaction. Together, these findings point to PIN1 s role in coordinating mitotic events Cell proliferation and oncogenesis As mentioned above, overexpression of PIN1 is a prevalent finding in human cancers; more than half of 60 types of tumors showed increased levels of PIN1, compared to corresponding normal tissue (Bao et al., 2004). Consistent with this finding, PIN1 has been 32

43 shown to activate a number of oncogenes/growth promoting proteins, including NF-kB, Stat3, Notch1, c-jun, and to inactivate some tumor suppressor/growth inhibitory genes, such as PML and Bax (Shen et al., 2009, Ryo et al., 2003, Rustighi et al., 2009, Reineke et al., 2008, Lufei et al., 2007). PIN1 s promotion of tumor growth has been linked to its stabilization of cyclin D1. In addition to its direct binding to the cyclin D1 protein at pthr286-pro, PIN1 can indirectly upregulate cyclin D1 by activating the c-jun/ap1, β- catenin/tcf, and NF-kB transcription factors (Ryo et al., 2001, Ryo et al., 2003, Wulf et al., 2001). Concordantly, in vivo evidence of PIN1 s cooperation with oncogenes is provided by a Pin1 -/- mouse model expressing a MMTV-c-Neu/Her2/ErbB2 or v-ha-ras transgene (Wulf et al., 2004). In this system, approximately 90% of these mice remained free of breast carcinomas, compared to transgenic littermates with intact Pin1. Furthermore, the induction of cyclin D1 by Neu or Ras was blocked by Pin1 ablation, and early properties of transformation in mammary epithelial cells from the Pin1-deficient mice were rescued by overexpression of cyclin D1, further supporting the link between these two proteins. More recently, oncogenic cooperation between PIN1 and the c-myc transcription factor has been described (Farrell et al., 2013). PIN1 enhanced the recruitment of Ser62- phosporylated c-myc to promoters of genes involved in cell growth and metabolism. PIN1 also promoted Myc s release from DNA and its degradation. In cancer cells, however, only Myc DNA binding was enhanced by PIN1. A body of literature is also emerging about the role of PIN1 in breast cancer stem cell control. Rustighi et al. performed in vivo and in vitro functional studies and demonstrated that PIN1 regulates normal and cancer cell cells through its interaction with Notch family 33

44 proteins (Rustighi et al., 2014). By virtue of their interaction with PIN1, Notch1 and Notch4 evade degradation by the ubiquitin ligase, Fbxw7α. PIN1 was then shown to be required for Notch-dependent breast cancer and normal breast stem cell self-renewal, and breast cancer tumor growth and metastases in vivo. Another recent report establishes that PIN1 is an important target of mir200c, a strong inhibitor of breast cancer stem cells (Luo et al., 2014). PIN1 was shown to be a key mediator of mir200c function, in that a mir200c-resistant PIN1 construct could rescue mir200c-induced reduction of breast cancer stem cells. Furthermore, mir200c expression was unsuccessful at reducing the breast cancer stem cell population among human mammary epithelial cells deficient in PIN1. The authors went on to show that overexpession of PIN1 drives the invasiveness and tumorgenicity of breast cancer stem cells, and that PIN1 inhibition reduces their self-renewal capacity PIN1 and p53 Thus far, this review has elaborated some of the evidence around the involvement of PIN1 in cell cycle control and oncogenesis, but its interactions with p53 and its family of proteins deserve specific consideration. PIN1 has been shown to play a critical role in p53 s response to DNA damage. Following genotoxic stress, p53 is phosphorylated on many residues, as described above. Among these are a series of Ser/Thr-Pro sites (such as 33, 46, 81 and 315) that are acted on by important stress kinases, including ATM, JNK, CDK2, CDK9 and p38 MAPK, among others (Meek and Anderson, 2009). PIN1 interacts with p53 in a phosphorylation-dependent manner following exposure of various cells lines to an array of genotoxic stresses, including treatment with UV-and gamma-irradiation, and chemotherapeutic drugs (doxorubicin, 34

45 bleomycin and camptothecin), and to oncogene expression (Zacchi et al., 2002, Zheng et al., 2002). In stressed cells lacking PIN1, the half-life of p53 is diminished due to its inability to dissociate from MDM2 (Zacchi et al., 2002). Furthermore, in these stressed conditions, use of an antisense PIN1 construct was shown to decrease p53 transcriptional activity specifically, by assessing MDM2 and p21-luciferase reporter activities while induction of PIN1 expression increased protein expression of both MDM2 and p21 (Zheng et al., 2002). These results were corroborated in PIN1 -/- MEFs, and similar results were shown when analyzing Bax and Killer/DR5 transcript levels by Northern blot (Zacchi et al., 2002, Zheng et al., 2002). Additional studies have demonstrated that PIN1 interacts with p53 at the level of chromatin binding, whereby it facilitates a structural rearrangement of the C-terminus of p53 and p300-mediated acetylation, promoting transcription of target genes (Mantovani et al., 2007). PIN1 has also been shown to have an integral role in p53-mediated apoptosis. Phosphorylation of p53 at Ser46 following severe or persistent stress stimuli is thought of as a death signal that directs p53 to induce apoptosis as opposed to cell cycle arrest (Mantovani et al., 2015). PIN1 not only stabilizes the pro-apoptotic kinase, HIPK2 one of the kinases responsible for p53 Ser46 phosphorylation but also then induces a conformational change of the pser46-thr47 site, thereby facilitating the detachment of p53 from iaspp, an apoptosis inhibitor (Mantovani et al., 2007, Bitomsky et al., 2013). Upon stress signals, PIN1 also stimulates monoubiquitination of p53, which serves as a trafficking signal for its nuclear export and movement to the mitochondria, where p53 induces 35

46 transcription-independent actions to promote apoptosis, including activation of Bak (Leu et al., 2004, Sorrentino et al., 2013). PIN1 s interactions with the p53 family members, p63 and p73, have been less well characterized, but a few studies do suggest its role in potentiating their apoptotic activity in response to DNA damage. Reminiscent of its activity towards p53, PIN1 was shown to bind to and stabilize p63α, by decreasing its association with the E3 ligase, WWP1, and also enhances p63-mediated transcription of Bax and Puma (Li et al., 2013a). Interestingly, PIN1 could also interact with the N isoform of p63α and potentiate its roles in tumorigenesis. In an elegant series of experiments using p53-null cell lines, Mantovani et al. demonstrated that PIN1 stabilizes p73 under normal and stressed conditions, and showed an impairment in the induction of p73 targets and apoptosis in cell lines lacking PIN1 (due to knock-out in MEFs or silencing in H1299 cells) upon treatment with cisplatin (Mantovani et al., 2004). These effects were shown to be mediated by PIN1 s promotion of p73 modification by the acetyl-transferase, p PIN1 and mutant p53 Intriguing insights into the integration of PIN1 and mutant p53 have been recently described (Girardini et al., 2011). The authors demonstrated that PIN1 plays a fundamental role in mutant p53 oncogenic gain of function activity. These investigators used mutant p53 R172H (human R175H) knock-in mice and generated compound mice with the following genotypes: p53 M/+ Pin1 +/+, p53 M/+ Pin1 -/- (where M denotes R172H). They first assessed the overall effect of PIN1 expression on tumorigenesis. Mice not expressing Pin1 had increased tumor-free survival, displayed a reduced number of lymphomas and interestingly, a 36

47 complete absence of carcinomas (Girardini et al., 2011). These effects were specific to mice expressing mutant p53 (there were no differences in tumor-free survival, tumor frequency or tumor spectrum between p53 +/- Pin1 +/+ and p53 +/- Pin1 -/- mice). To explore the role of PIN1 as a transducer of oncogenic signaling, they showed that p53 M/M Pin1 +/+ mouse embryonic fibroblasts (MEFs) transduced with H-Ras v12 had enhanced anchorage-independent growth and developed significantly larger tumors when injected into immunocompromised mice, compared with p53 M/M Pin1 -/- MEFs (Girardini et al., 2011). Accordingly, Ras v12 expression was associated with phosphorylation of Pin1 binding motifs on mutant p53, and increased interaction between mutant p53 and Pin1. This interaction was also verified in human H1299 cells, transfected with the mutant p53 construct, p53k280 (Girardini et al., 2011). Knock-down of PIN1 also impaired migration (by transwell migration assay) and invasion (lung colonization) of the human triple negative breast cancer cell line, MDA-MB-231. This effect was confirmed to be mediated by PIN1 s interaction with mutant p53: PIN1 overexpression did not increase migration in MDA-MB-231 cells expressing a modified form of mutant p53, unable to bind PIN1. In keeping with previous literature (see above), demonstrating that mutant p53 sequesters and inactivates p63 to orchestrate its pro-migratory and pro-invasion functions, (Adorno et al., 2009, Gaiddon et al., 2001), PIN1 overexpression in MDA-MB-231 cells increased the association between mutant p53 and endogenous p63. Furthermore, this effect was associated with reduced expression of the p63 targets, CCNG2 and Sharp-1 in a mutant-p53 dependent fashion. PIN1 silencing led to their upregulation, and also increased the expression of other p63 target genes, such as Dicer1 (Girardini et al., 2011). Beyond impacting p63 targets, the 37

48 authors go on to identify a mutant p53/pin1 transcriptional program : a group of genes that are synergistically induced in MDA-MB-231 cells by PIN1 and mutant p53. The top 10 of these genes show both PIN1 and p53 recruitment to their promoters, and many were shown to be key effectors for Pin/mutant p53-dependent cell migration (Girardini et al., 2011). Together, these data support the notion that PIN1 activates mutant p53 oncogenic gain of function. Overall, it appears that PIN1 orchestrates important roles to fine-tune cellular processes; yet, when such processes are perturbed, either by oncogene activation, or TP53 mutation, PIN1 continues to activate its targets, thereby contributing to aberrant cell signaling (Figure 6). Figure 6: Effect of PIN1 on wild-type versus mutant p53 (Napoli et al., 2011). 38

49 The clinical relevance of a PIN1/mutant p53 axis has been suggested, mainly in relation to breast cancer. Girardini and colleagues reported that the gene signature determined in their study cited above predicted poor prognosis in a cohort of patients with breast cancer (Girardini et al., 2011). PIN1 itself has also been evaluated for its impact on breast cancer prognosis outside of its association with mutant p53. In a study linking PIN1 to aberrant Notch1 signaling in breast cancer stem cells, an analysis of 19 independent breast cancer expression studies revealed a prognostic impact of high PIN1 expression in the context of active Notch1 signaling in a subset of patients (Rustighi et al., 2014). Beyond these, specific polymorphisms in the PIN1 promoter have been evaluated in case-control studies of cancer susceptibility. The (-)842G>C promoter variant has been assessed for association with cancer risk in breast, lung, esophageal, hepatocellular, laryngeal squamous cell and nasopharyngeal carcinomas. Multiple meta-analyses of these studies, comprising of over 4000 cases and controls, have demonstrated a significantly reduced cancer risk associated with the GC genotype at locus (-842) of the PIN1 promoter, compared to the wildtype, GG genotype (Li et al., 2013b, Peng et al., 2013, Xu et al., 2013). While most of the included studies were based on populations of Asian patients, this variant was also shown to be associated with breast cancer and head/neck squamous cell carcinoma risk in Caucasian individuals (Han et al., 2010, Lu et al., 2009). In this latter population, the PIN1 C allele at locus (-)842 demonstrated decreased PIN1 expression in a luciferase assay (Lu et al., 2009). 39

50 CHAPTER 2: RESEARCH AIMS AND HYPOTHESES Li-Fraumeni syndrome is an autosomal dominant cancer susceptibility syndrome caused by germline mutations in TP53 (Malkin et al., 1990). LFS is characterized by a wide spectrum of early-onset tumors (Nichols et al., 2001), which poses significant challenges to the management of this patient population. A number of genetic modifiers have been investigated to explain this marked clinical heterogeneity, including polymorphisms in MDM2, the TP53 codon 72 and PIN3 polymorphisms, in addition to more genome-wide entities such as copy number variation (Bond et al., 2004, Bougeard et al., 2006, Fang et al., 2010). Furthermore, a number of studies have demonstrated genotype-phenotype correlations for various classes of TP53 mutations. Specifically, missense mutations show a more aggressive phenotype than truncating/null mutations (Dittmer et al., 1993b, Lang et al., 2004, Olive et al., 2004, Bougeard et al., 2008, Birch et al., 1998). These data, along with a significant body of in vitro and in vivo pre-clinical studies, have suggested that mutant p53 proteins show a neomorphic gain of function; that is, they acquire novel functions in promoting tumorigenesis (Muller and Vousden, 2014). PIN1 (peptidyl-prolyl cis/trans isomerase, NIMA-interacting 1) is a peptidyl-prolyl isomerase that transduces phosphorylation post-translational modifications into structural changes of its target proteins, affecting protein stability, subcellular localization, protein-protein interactions and catalytic activity, translating into the regulation of cellular mitosis, proliferation, and oncogenic signaling. Based on recent literature implicating an important role for PIN1 in mutant p53 oncogenic functions (Girardini et al., 2011), the objective of my 40

51 thesis project is to investigate PIN1 as modifier of the LFS phenotype. The cooperation of PIN1 and mutant p53 to enhance tumorigenesis and promote aggressive features by tumor cells is demonstrated by a number of findings. First, the knock-in of the mutant p53 allele (R172H) on a Pin1 wildtype background (p53 M/+ Pin1 +/+ ) resulted in mice with earlier tumor onset and increased tumor frequency than those mice deficient in Pin1 (p53 M/+ Pin1 -/- ), and influenced the tumor spectrum. In addition, Pin1 enhances H-ras-induced transformation of MEFs, and can potentiate p53-dependent human breast cancer cell migration and invasion. These aggressive phenotypes result from inhibition of the antimetastatic factor, p63, and from induction of a transcriptional program, both promoted by synergistic actions of PIN1 and mutant p53. Based on these findings, my hypothesis is that alterations in the expression of PIN1 modify the cancer phenotype conferred by a germline p53 mutation. One approach that was employed in my thesis to evaluate of the effect of PIN1 expression levels on cancer phenotype is the analysis of the PIN1 (-)842G>C(rs ) promoter SNP, which has previously been associated with expression changes of the PIN1 protein, and with cancer risk (Han et al., 2010, Lu et al., 2009, Lu et al., 2011). The following aims will address my research objective and hypothesis: Aim 1: Describe associations of the PIN1 promoter SNP (-)842G>C with cancer phenotype in individuals with LFS and germline TP53 mutations. The PIN1 promoter variant is hypothesized to mediate increased PIN1 expression, thereby potentiating mutant p53 gain of function activity and contributing to a more severe cancer phenotype in study subjects. In this context, cancer phenotype was evaluated by various metrics including penetrance 41

52 (presence of a cancer diagnosis), markers of expressivity (median age of first tumor onset, number of primary tumors), and tissue specificity/tumor type. A sub-aim was to verify changes in PIN1 transcript and protein levels based on PIN1 (-)842 genotype, and to validate this association with publically-available, genomic data. Aim 2: Determine the impact of PIN1 overexpression on cellular proliferation and apoptosis in LFS study subject-derived primary cultured fibroblasts. To further explore the role and biologic relevance of PIN1 expression levels in LFS patients, fibroblast cell lines from study subjects were evaluated for potentiation of mutant p53 gain-of-function activities, including colony formation and cytotoxic drug resistance/avoidance of cell death, upon overexpression of PIN1. 42

53 CHAPTER 3: MATERIALS AND METHODS Study Subjects This study included 114 germline TP53 mutation carriers who met clinical criteria for either LFS (by classic or Chompret criteria) or LFL, and for whom germline DNA was available for analysis. Clinical information including sex, ethnicity, age at last contact, age at first tumor onset, and tumor diagnoses was collected. All study participants provided written informed consent, and this study was approved by the Research Ethics Board at The Hospital for Sick Children in Toronto, Canada. Subject recruitment for the CEU, FIN, GBR, TSI and YRI subjects included in The 1000 Genomes Project is described elsewhere (Genomes Project et al., 2012). 462 samples were included from these data sets based on availability of whole genome sequencing data from the 1000 Genomes Project and paired RNA-seq data from the Geuvadis project (Lappalainen et al., 2013). DNA Extraction DNA was previously extracted from peripheral blood leukocytes using standard methods, and DNA quantification was performed on a NanoDrop 1000 Spectrophotometer (Thermo Scientific). 43

54 PIN1 (-)842 Genotyping The PIN1 (-)842 genotype was determined by Sanger sequencing. PCR was first used to amplify 361-bp region encompassing the (-)842 locus. PCR primer sequences were as follows: Forward: 5 -CGCATAGCAAGTGTCAGTCCC-3, Reverse: 5 - GGTGCCGACATTGACATTCAT-3. PCR was carried out using the following conditions: 2.5mM MgCl2, 0.2mM dntp, 0.4uM forward and reverse primers, 1U Taq Gold; protocol: 10 min hot start at 95 o C, 36 cycles of denaturing (95 o C x 30s), annealing (60 o C x 30s), and elongation (72 o C x 30s), followed by final extension for 3 min at 72 o C. Specificity of amplification was confirmed by agarose gel electrophoresis, and an aliquot of each sample was then digested with ExoSAP-IT (Affymetrix). Sanger sequencing was carried out by The Centre for Applied Genomics at The Hospital for Sick Children, Toronto, Canada. Cell Culture Study subject-derived, early passage (P1-2) EBV-immortalized lymphoblastoid cell lines and primary cultured fibroblasts were maintained in RPMI (Wisent) and AMEM (Wisent), respectively, with 10% Fetal Bovine Serum (Wisent) and were passaged by standard techniques. Six lymphoblastoid cell lines (3 with each of GG and GC genotypes at PIN1 (-)842) were used for eventual PIN1 expression studies. Four fibroblast cell lines with various TP53 mutations were used for lentiviral transduction and overexpression of PIN1 for functional studies: wild type, truncating (C275X), and missense mutation with evidence for gain of function (two distinct lines harboring the R248Q mutation: R248Q-a and R248Q-b). 44

55 Quantitative RT-PCR RNA extraction from six lymphoblastoid cell lines was carried out using TRIZOL reagent (Lifetech) and chloroform (Sigma) according to standard techniques. RNA quantification and integrity were assessed by The Centre for Applied Genomics Microarray Facility of the Hospital for Sick Children in Toronto, Canada, using the Agilent 2100 Bioanalyzer (Agilent Technologies) (Figure S1). A RIN value of >8.0 was considered acceptable. Reverse transcription was carried out using 500ng of extracted RNA and SuperScript II First-Strand Synthesis Reverse Transcriptase (Invitrogen) with random primers, as per the manufacturer s instructions. Both no-template and no-reverse transcriptase controls were included to assess for primer-dimers and for the presence of genomic DNA. Primers were designed at exon-exon boundaries and produced a 163-bp fragment (Forward: 5 - GGAGCTGATCAACGGCTACATC-3, Reverse: 5 CGCAAACGAGGCGTCTTCAA-3 ). Primers were optimized and validated using pooled cdna. A thermal gradient was run to optimize the annealing temperature, and efficiency was determined to be 100.0% by generation of a standard curve (Figure S2). The qpcr product was also validated by agarose gel electrophoresis and by Sanger sequencing. The qpcr reaction was carried out using Sso Advanced Universal SYBR Green Supermix (Bio- Rad) and 500nM of each primer. Three replicates of each cdna were run in a Bio-Rad CFX96 (Bio-Rad), using the following protocol: polymerase activation/dna denaturation (30s at 95 o C), 40 cycles of denaturation (15s at 95 o C) and annealing/extension(30s at 60 o C), followed by a denaturation step (30s at 95 o C) and melt-curve analysis (65 o C-95 o C, 0.5 o C increments every 5s). A reference gene panel (Bio-Rad) was used to determine the most 45

56 stable reference genes to use to normalize the data. B2M and RPL13A were found to be the most stable across the different cell lines with an associated stability (M) value of and 0.081, respectively, in concordance with the MIQE guidelines (Bustin et al., 2009). Relative changes in gene expression were quantified using the 2-delta delta Ct method (Livak and Schmittgen, 2001, Pfaffl, 2001) by the Bio-Rad CFX Manager 3.1 Program (Bio-Rad). Transcript levels were expressed as the mean expression from three biological replicates (+/- SEM), relative to one of the cell lines with the PIN1 (-)842 GC genotype. Western Blotting Cellular protein from lymphoblastoid and fibroblast cell lines was extracted using either icecold EBC lysis buffer or RIPA lysis buffer, with the addition of Complete Mini Protease Inhibitor Tablets and PhosSTOP Phosphatase Inhibitor Cocktail Tablets (Roche). Following quantification by Bradford protein assay, lysates were run on a 12% SDS-PAGE gel, transferred to a PVDF membrane (Millipore Immobilon-FL), and blocked for one hour in Odyssey Blocking Buffer (LI-COR Biosciences). Membranes were incubated overnight at 4 o C with primary antibodies: PIN1 (Santa Cruz: G8 sc-46660), p53 (Cell Signaling: 9282), cleaved PARP (Cell Signaling: 9541), V5 tag (Invitrogen: ), Vinculin (Millipore). Membranes were incubated for 40 minutes at room temperature with anti-rabbit (680nm) or antimouse (800nm) infrared dye-tagged secondary antibodies (LI-COR Biosciences). Membranes were then scanned using the Odyssey Infrared Imaging System (LI-COR Biosciences) at 700nm and 800nm. Membranes requiring reanalysis for different proteins were stripped with PVDF stripping buffer (LI-COR Biosciences), re-blocked and re-probed. Background- 46

57 adjusted densitometric values were determined using Image Studio Software Version (LI-COR Biosciences). Results were normalized to vinculin loading control. Analysis of 1000 Genomes Data In order to validate expression data derived from lymphoblastoid cell lines in this study, an analysis of whole genome sequencing data from the 1000 Genomes Project and paired RNAseq data (Genomes Project et al., 2012, Lappalainen et al., 2013) was carried out by Richard de Borja and Fabio Fuligni. Briefly, the genotype at position (-)842 in the PIN1 gene (corresponding to position 19: on reference genome assembly GRCh37) was downloaded from the Geuvadis EBI public repository ( along with RPKM values (reads per kilobase of exon per million mapped reads) ( and raw transcript count data ( 1/GD660.TrQuantCount.txt.gz). Both RPKM data and trimmed-mean of M-values normalization method from raw transcript count data were plotted, and statistical comparison of the three genotypes were carried out using the Wilcoxon signed-rank test using the R software package (R Core Team (2015). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL 47

58 Lentiviral transduction of LFS fibroblasts A PIN1 cdna clone (ID number 4406) was selected from the Human ORFeome 5.1 library (Open Biosystems) and obtained in the pdonr223 entry vector within DH5α E.coli from SPARC BioCentre at The Hospital for Sick Children. Colonies were amplified in selective LB broth, and plasmids were isolated (Qiagen Miniprep Kit, Cat #27106, and Qiagen Endo-free Plasmid Maxi Kit, Cat#12362; per manufacturer s protocol). The cdna insert was then transferred into the plx302 lentiviral vector (Addgene) by SPARC BioCentre, and again amplified in selective broth, but at reduced temperature (30 o C). This vector houses a CMV promoter, a puromycin resistance cassette, and adds a C-terminal V5 amino acid tag (Figure S3). The insert was sequenced bidirectionally to confirm accuracy. The same procedure was carried out for GFP, which served as a negative control. Preparation of lentivirus and transduction of fibroblasts were carried out by SPARC BioCentre at The Hospital for Sick Children. Briefly, 30,000 early passage fibroblasts (P4-5) were seeded in 24 well plates. Cells were transduced with either plx302-pin1 or plx302- GFP: lentivirus was added to cells at a multiplicity of infection (MOI) of 20, with the addition of polybrene and 4 hours of serum starvation to increase transduction efficiency. Media was changed after 24 hours, and cells were washed at 72 hours with fresh media added. Based on fluorescent microscopy of GFP-transduced lines at 72 hours, transduction efficiency neared 100% (Figure S4). Cells were passaged into 6-well plates, and after 48 hours, puromycin selection was carried out using 0.5ug/mL puromycin for 6 days, with antibiotic replacement every 2 days (Figure S5). Confirmation of PIN1 overexpression was evaluated by western blot (Figure S6). 48

59 Drug treatments Stably-transduced fibroblast cell lines were plated in 6-well plates at a density of 2x10 5 cells/well. Once adhered (approximately 6 hours), cells were treated with 1uM of doxorubicin for 48 hours or vehicle (Sigma: 44583). Cell lysates were then prepared as described for western blotting. Cell Viability Assay Cell viability of stably-transduced fibroblasts following doxorubicin treatment was assessed by the colorimetric MTS assay (Promega). 5,000 cells were seeded with six replicates into 96-well plates. Once adhered (approximately 6 hours), cells were treated with 1uM doxorubicin or vehicle for 24 hours (Sigma: 44583). The culture media was then replaced, and after 24 hours, MTS reagent was added to each well. Absorbance at 490nm was recorded after 2 hours of incubation with MTS reagent. Raw values (after adjusting for background) were normalized to the vehicle average. Data from each set of technical replicates was averaged, and mean values from 3 biologic replicates were used for statistical analysis (expressed as mean relative absorbance +/- SEM). Colony Forming Assay The propensity of stably-transduced fibroblasts to form colonies was assessed by the colony forming assay. 5,000 cells were seeded in 100 mm culture plates with 3-5 technical replicates for each cell line. Cells were incubated at 37 o C for 14 days. Culture media was 49

60 replaced at 7 days. Following the incubation period, colonies were fixed, stained with crystal violet and counted. Data from each set of technical replicates was averaged, and mean values from 3 biologic replicates were used for statistical analysis (expressed as mean number of colonies +/- SEM). Statistical Analysis The Mann-Whitney-U non-parametric test was used to compare continuous variables including median ages of cancer onset. Nominal data expressed as proportions were analyzed using the Fisher s exact test. All experimental data was analyzed by the unpaired Student s t-test. A p-value of <0.05 was considered to be statistically significant. All analyses were carried out using GraphPad Prism 5 for Windows (Version 5.01) (GraphPad Software, Inc). 50

61 CHAPTER 4: RESULTS 1. Influence of PIN1 (-)842 genotype on cancer phenotype in patients with LFS and germline TP53 mutations 1.1 Characteristics of study cohort 114 germline TP53 mutation carriers who met clinical criteria for either LFS (either classic or Chompret criteria) or LFL, and for whom germline DNA was available, were included in this analysis. The characteristics of this study cohort are detailed in Table 2. Other clinical characteristics, including age spectrum of the cohort, spectrum of tumor histologies, and age of first cancer diagnosis by TP53 mutation subtype, are included in the appendix (Figures S7-S10). The TP53 mutation spectrum in this study cohort is generally similar to the IARC TP53 database (Petitjean et al., 2007), with a slight underrepresentation of missense mutations (Figure 7). All study subjects were genotyped at the PIN1 (-)842 locus and allele frequencies were found to be consistent with public SNP datasets (NCBI dbsnp database: (Table 3). Table 2: Characteristics of study cohort N 114 Females 67 (58.8%) Median age 20.11* Number with cancer 80 (70.2%) Total number of tumors 144 Median age at first cancer diagnosis (Range ) a * based on 112 patients (age unknown for 2 patients) a based on 79 patients (age unknown for 1 patient) 51

62 a) Frameshift 7% Deletion 4% Intron 2% Splice 11% Nonsense 17% Missense 59% b) Figure 7: a) TP53 mutation spectrum in LFS study cohort (n = 114). b) Mutation spectrum in individuals with TP53 germline mutations from IARC TP53 database (n=1485) (version R17, November 2013). Adapted from (Petitjean et al., 2007). 52

63 Table 3: Allele frequency of PIN1 (-)842 SNP in study cohort and in NCBI dbsnp database Genotypes in this cohort Allele Frequencies in this NCBI dbsnp cohort GG: 85 GC: 27 CC: 2 G: 86.4% C: 13.6% Minor Allele Frequency: 15.1%/2503 samples (1000 genomes) 1.2 Individuals with PIN1 (-)842 GG genotype demonstrate an earlier age of cancer onset Study subjects were divided into two groups based on their PIN1 (-)842 genotype (Table 4): GG or GC/CC. There was no difference in the overall percentage of patients with cancer, and median ages were similar in both groups. No differences were observed in the number of patients with multiple tumors (and the median ages of those who have had cancer were also similar). The median age of first cancer onset was found to be 10.6 years younger in individuals with the PIN1 (-)842 GG genotype, which approached statistical significance (6.2 years vs years; p = ) (Table 4, Figure 8). This finding was not explained by an unequal distribution of patients with TP53 missense mutations between groups. It was also notable that among pediatric patients with cancer, almost all (92%) individuals with the GG genotype developed their first cancer in the first decade of life, compared to approximately 65% of patients carrying a C allele (p = ) (Table 4, Figure 8b & 8c). This difference was not due to a predominance of young unaffected individuals in the C allele group. 53

64 Table 4: Characteristics of study cohort, by PIN1 (-)842 genotype (-)842 GG (-)842 GC + CC p-value N 85 (74.6%) 29 (25.4%) - Current median age Female 47 (55.3%) 20 (69%) Number with cancer 60 (70.6%) 20 (69%) Number of primary cancers Number with >1 primary cancer 28 (46.7%) 8 (40%) Current median age of those with cancer Proportion of cancer patients with TP53 missense mutations 38/60 (63.3%) 12/20 (60%) Median age of first cancer 6.2 ( ) 16.8 ( ) Proportion of pediatric 34/37 (91.9%) 7/11 (64.6%) patients <11 yo Median age of unaffected patients 23.1 (n=24)* 16.1 (n=7) *Age not known for one patient 54

65 a) p= Age of first cancer b) 0 80 GG n=59 tumors (-) 842 genotype GC + CC n=20 tumors Number of individuals GG GC + CC Age of first primary c) Percentage of unaffected subjects GG GC + CC p= Age (years) Figure 8: Influence of Pin1 (-) 842 genotype on age of first primary tumor. a) Median age of first cancer is approximately 10 years earlier in individuals with a GG genotype. b) and c) Cumulative frequency histogram and time-to-event curves demonstrate a clustering of cancer diagnoses in the first decade of life in study subjects with GG genotype. 55

66 As discussed in the Introduction, the literature supports a role for PIN1 in potentiating the gain of function activity of mutant p53 with missense mutations (Girardini et al., 2011). Two subgroup analyses were therefore carried out: firstly, study subjects with missense mutations, and secondly, study subjects with missense mutations with reported gain-offunction ability (as reported on the IARC database (Petitjean et al., 2007), or as reported in comprehensive, recently published reviews (Freed-Pastor and Prives, 2012, Muller and Vousden, 2014)). Sixty-seven individuals in the study cohort had missense mutations: 48 individuals with GG genotype and 19 individuals with a C allele at PIN1 (-) % of individuals with GG genotype developed cancer, as opposed to 63.2% with GC or CC genotypes (p=0.2174). A higher proportion of patients had multiple tumors in the GG group, (55.3% vs. 41.7%; p= ) and their median age of first cancer was slightly lower (11 years vs years; p=0.3943), although neither of these reached statistical significance (See Supplemental Figure S11). Fifty patients in the study cohort carried missense mutations with known gain-of-function potential (38 with the GG genotype, 12 with a C allele). In this subgroup, individuals with the GG genotype at PIN1 (-) 842 had a slightly higher incidence of cancers (81.6% vs. 66.7% in individuals with a C allele; p=0.424), and did not show evidence of increased propensity for multiple tumors (58% vs. 50%; p=0.7089) (Figure 9). There was a trend towards earlier median age of first cancer in individuals with the GG genotype, and again, a clustering of first cancer diagnoses is evident in the first decade of life (Figure 9). 56

67 a) Genotype N Number with cancer (%) Number of tumors Number with >1 tumor (%) Tumors/patient GC + CC 12 8/12 (66.7) 22 4/8 (50) 1.5 GG 38 31/38 (81.6) 78 18/31 (58) 2.06 p-value b) 60 p= Age of first cancer diagnosis c) 0 40 GG n=31 n=8 (-) 842 genotype GC+CC GC+CC Number of Individuals GG d) Percentage of unaffected patients Age of first primary p= GC+CC GG Age (years) Figure 9: Influence ofpin1 (-) 842 genotype on age of first primary tumor in subjects with gain-of-function missense mutations. a) There is a trend twoard increased cancer indicence in subjects with a GG genotype, but no clear propensity for multiple tumors. b) Median age of first cancer is slightly earlier in individuals with a GG genotype. c) and d) Cumulative frequency histogram and time-to-event curves demonstrate a clustering of cancer diagnoses in the first decade of life in study subjects with GG genotype. 57

68 1.3 PIN1 SNP (-) 842 does not appear to affect the number of primary cancers or the distribution of tumor histologies In the entire study cohort, there was no significant difference in the number of individuals with >1 primary cancer (Table 4: 46.7% in GG group vs. 40% in GC+CC group; p=0.7958). As shown in Figure 10, there does not to be a significant difference in the proportion of patients with a 3 rd, 4 th or 5 th primary tumor between groups. Percentage GG (-)842 genotype GC+CC 1st 2nd 3rd 4th 5th Proportion of cancer patients with: p-value 2 nd tumor rd tumor th tumor 1 5 th tumor Figure 10: Proportion of individuals with multiple primary tumors, by PIN1 (-)842 genotype. There is some suggestion in the literature that PIN1 expression could influence the types of tumors manifested in the setting of a germline TP53 mutation (Girardini et al., 2011). Analysis of proportions of patients with carcinomas, sarcomas and hematologic cancers was not different between groups (Figure 11a and Table S1). The proportion of specific tumor types was mostly similar between groups, with the exception of a higher proportion of CPC and a lower proportion of glioma in individuals with GG genotype at PIN1 (-) 842 (6/60 vs. 1/20 CPCs in individuals with GG vs. GC+CC genotypes, respectively, p=0.668; 4/60 vs. 4/20 58

69 gliomas in individuals with GG vs. GC+CC genotypes, respectively, p=0.1023; Figure 11b and Table S1). a) Percentage GG (n=60) GC + CC (n=20) Tumor histology b) Percentage GG (n=60) GC + CC (n=20) Tumor type Figure 11: Influence of PIN1 (-) 842 genotype on distribution of tumor histologies/types. a) There are similar proportions of broad categories of tumor histologies between groups. Other = non-cpc CNS tumors (gliomas (4), medulloblastoma (1) in GC+CC group; gliomas (4), 59

70 medulloblastoma (3), myxopapillary ependymoma (1) in GG group). b) The proportion of specific tumor types was mostly similar between groups, with the exception of a higher proportion of choroid plexus carcinoma and a lower proportion of glioma in individuals with GG genotype at PIN1 (-)842. Other = stomach cancer in GG group, papillary thyroid cancer and placental choriocarcinoma in GC+CC group. ACC = adrenocortical carcinoma, CPC = choroid plexus carcinoma, STS = soft-tissue sarcoma. 1.4 PIN1 SNP (-)842 influences the proportion of carcinomas in subjects with gain-offunction TP53 mutations In subset analyses of subjects with gain-of-function missense mutations, there is an increased proportion of carcinomas in individuals with a GG genotype (Figure 12a). On further analysis of specific tumor types, this increase in carcinomas is mostly the result of a 16.1% incidence of each of breast and adrenocortical carcinomas in subjects with GG genotype, compared to an absence of these diagnoses in patients with GC+CC genotypes (Figure 12b). The carcinomas in the GC+CC group are one choroid plexus carcinoma and one papillary thyroid carcinoma in a 33 year old female (the latter diagnosis is common at this age in the general population). The choroid plexus carcinoma in the GC+CC group occurred at the age of 4.39 years, while those in the GG group occurred at an average age of 9 months. If a composite LFS common carcinoma category is looked at comprising breast, adrenocortical and choroid plexus carcinomas 41.9% (13/31) of first primary tumors fall into this category in individuals with a GG genotype, compared to 12.5% (1/8) of first primary tumors in individuals with a GC or CC genotype (Figure 12b; p=0.2179). It is also notable that there is a significantly greater proportion of gliomas in individuals with PIN1 (-)842 GC or CC genotypes (Figure 12b; p= ). 60

71 a) Absolute numbers Proportions/Percent Sarcoma Carcinoma Hematologic Other Sarcoma Carcinoma Hematologic Other GG (n=31) GG (n=31) GC + CC (n=8) GC + CC (n= p-value Percentage Sarcoma Carcinoma Hematologic Other Tumor Histology GG (n=31) GC + CC (n=8) b) Absolute numbers Osteosarcoma STS Breast ACC Glioma CPC Other CNS Hematologic Other GG (n=31) GC + CC (n=8) Proportions/Percent Osteosarcoma STS Breast ACC Glioma CPC Other CNS Hematologic Other GG (n=31) GC + CC (n=8) p-value Percentage GG (n=31) GC + CC (n=8) Tumor Type Figure 12: Influence of PIN1 (-) 842 genotype on distribution of tumor histologies/types in subset of individuals with gain-of-function germline TP53 mutations. a) There is an increased proportion of carcinomas in subjects with a GG genotype. Other= non-cpc CNS tumors (gliomas (3), medulloblastoma (1) in GC+CC group; gliomas (2), medulloblastoma (2), myxopapillary ependymoma (1) in GG group). b) There is a notable absence of breast and adrenocortical carcinoma, and an increased proportion of gliomas in those with a GC or CC genotypes. Other = papillary thyroid cancer in GC+CC group. ACC = adrenocortical carcinoma, CPC = choroid plexus carcinoma, OS = osteosarcoma, STS = soft-tissue sarcoma. 61

72 2. Influence of PIN1 (-)842 genotype on expression of PIN1 The hypothesis that PIN1 SNP (-)842 influences the cancer phenotype in individuals with germline TP53 mutations rests on the assumption that the genotype at this locus influences the expression of the PIN1 gene. To investigate this, PIN1 transcript levels and protein levels were measured by qpcr and western blot, respectively, from 6 lymphoblastoid cells lines of LFS patients 3 with the GG genotype and 3 with the GC genotype (Supplemental Table S2). 2.1 PIN1 (-) 842 genotype GG results in increased PIN1 mrna and PIN1 protein levels in lymphoblastoid cell lines PIN1 transcript levels were approximately 6-fold more abundant in cell lines with the GG genotype at position (-) 842, compared to those cell lines with the GC genotype (Figure 13a). Quantification of PIN1 protein extracted at the same time as PIN1 mrna showed a 2- fold increase in cell lines expressing the GG genotype (Figure 13b&c). 2.2 Influence of PIN1 (-) 842 SNP on expression of PIN1 is not validated in an independent cohort In an attempt to validate expression data derived from lymphoblastoid cell lines, an analysis of whole genome sequencing data from the 1000 Genomes Project and paired RNAseq data (Genomes Project et al., 2012, Lappalainen et al., 2013) was carried out. These analyses failed to demonstrate a significant difference in PIN1 transcript levels between samples with the GG, GC or CC genotypes (Supplementary Figure S12). 62

73 a) b) 8 * 2.5 ** Relative Expression Relative Densitometry GG (-) 842 genotype GC GG GC (-) 842 genotype c) Figure 13: Influence of PIN1 (-)842 genotype on expression of PIN1. a) PIN1 expression in lymphoblastoid cell lines, measured by qpcr (n=3 with (-)842 GG genotype and n=3 with (- )842 GC genotype). Expression was normalized to B2M and RPL13A housekeeping genes, and is relative to one of the GC cell lines. This experiment was repeated in triplicate. Statistical analysis done using two-tailed Student s t-test (Mean +/- SEM). b) and c) Western blot analysis of PIN1 protein levels in lymphoblastoid cell lines (n=6) according to PIN1 (-) 842 genotype. Background-adjusted mean (+/- SEM) densitometric values, normalized to loading control (vinculin), and relative to one of the GC cell lines (defined as 1). Statistical analysis done using two-tailed Student s t-test (Mean +/- SEM). *=p<0.05; **=p<

74 3. Influence of PIN1 overexpression on cellular proliferation and apoptosis in LFS patientderived fibroblasts To demonstrate the biologic impact of PIN1 expression level changes in LFS patients, we studied the effect of PIN1 overexpression in LFS patient-derived fibroblast cell lines. We compared the effects in two cell lines with the R248Q missense mutation (R248Qa and R248Qb), which has been shown to demonstrate gain-of-function properties (Supplementary Table S3), to a cell line with a truncating/null mutation (C275X) and to one expressing wild type TP PIN1 overexpression selectively increases proliferative capacity of LFS patient-derived fibroblasts with the R248Q mutation Colony forming assays were carried out to assess changes in the clonogenicity of LFS patient-derived fibroblasts. Cells were transduced with either PIN1 or GFP control. As expected, fibroblasts with TP53 mutations produced more colonies than those with wild type TP53 (Figure 14). An untransduced line was also assayed to ensure that the presence of GFP was not negatively influencing proliferation. As seen in figure 14a, there was no significant difference in the number of colonies produced between untransfected and GFPtransduced cells for the R248Q-a cell line. PIN1 overexpression selectively increased the clonogenicity of fibroblast cell lines with the R248Q gain-of-function mutation; no significant differences were seen between PIN1- and GFP-overexpressing cells in lines with a truncating TP53 mutation or WT TP53 (Figure 14 a&b). 64

75 a) 150 ** Number of colonies GFP Untr Pin1 GFP Pin1 GFP Pin1 GFP Pin1 TP53 mutation R248Q-a R248Q-b C275X WT Cell line b) GFP Pin1 R248Q-a R248Q-b C275X Figure 14: Influence of PIN1 overexpression on fibroblast clonogenicity. Fibroblasts were transduced with either GFP or PIN1 and plated at a 5000 cell density in 10mm dishes. a) and b) PIN1 overexpression causes increased colony formation compared to GFP controls specifically in cell lines expressing the R248Q gain-of-function TP53 mutation. Data represent the mean of three independent experiments +/- SEM. ** = p< Untr = untransduced. 65

76 3.2 PIN1 overexpression leads to decreased sensitivity to doxorubicin/avoidance of cell death in LFS patient-derived fibroblasts with the R248Q mutation Sensitivity to chemotherapy/avoidance of apoptosis was also explored as a gain-of-function property of mutant p53 which could potentially be enhanced by PIN1 expression. Fibroblast cell lines were treated with 1uM doxorubicin and viability was assessed by an MTS assay. PIN1 overexpression was specifically associated with decreased sensitivity to doxorubicin treatment in cell lines expressing the R248Q p53 mutant. This effect was statistically significant in the R248Q-a cell line, and a trend towards decreased sensitivity was seen in the R248Q-b cell line. No effect of PIN1 overexpression was observed in cells with wild type TP53 or with the truncating mutant, C275X (Figure 15a). Concordantly, on western blot assessment, upon overexpression of PIN1, cell lines harbouring the R248Q mutant show reduced amounts of cleaved PARP (a marker of apoptosis generated from cleavage by caspase-3) following doxorubicin treatment, in contrast to cell lines harbouring the truncating mutant, C275X (Figure 15b). 66

77 a) Relative absorbance (490nm) TP53 mutation * Untr Untr + Dx GFP GFP + Dx Pin1 Pin1 + Dx GFP GFP + Dx Pin1 Pin1 + Dx GFP GFP + Dx Pin1 Pin1 + Dx R248Q-a R248Q-b C275X WT Treatment condition GFP GFP + Dx Pin1 Pin1 + Dx b) Figure 15: Sensitivity of LFS patient-derived fibroblasts to doxorubicin treatment. a) MTS assay results demonstrating decreased sensitivity to doxorubicin treatment specifically in R248Q-cell lines overexpressing PIN1. Values represent absorbance at 490nm, relative to untreated control for each cell line and represent the mean +/- SEM of three experiments. *= p< Untr = untransduced control, GFP =cell line transduced with GFP (control), PIN1 = cell line transduced with PIN1, Dx = Treatment with doxorubicin. b) Western blot demonstrates a reduction in p53 and c-parp induction in response to doxorubicin treatment in fibroblasts with R248Q-mutant p53, in contrast to fibroblasts with the C275X mutant. Densitometry values are normalized to vinculin and relative to control for each cell line. n=3 independent experiments. Lanes 5 and 16 are protein-markers. G =cell line transduced with GFP, P = cell line transduced with PIN1. 67

78 CHAPTER 5: DISCUSSION In this study, we provide evidence for a modifying role of PIN1 on the cancer phenotype conferred by a germline TP53 mutation in patients with Li-Fraumeni syndrome, and provide biologic correlates of this effect in LFS patient-derived, untransformed cells. To date, most of the proposed modifiers in LFS have been polymorphisms and alterations in the TP53 gene itself. PIN1 is the only regulator of p53 that we are aware of to be investigated in this context, besides MDM2. Since post-translational modifications remain the primary mode of p53 regulation, it seems likely that members of p53 s regulatory network would be attractive candidates to influence its function. Indeed, in the minority of sporadic cancers with wild-type p53, perturbations in mechanisms of p53 stabilization, nuclear localization and post-translational modification have been shown to be impaired, underscoring the importance of p53 structure to its function (Ryan et al., 2001). PIN1 is an especially intriguing target since compelling data also highlight evidence of its interactions with mutant p53 itself (Girardini et al., 2011). As described in detail in the Introduction, PIN1 associates with mutant p53 in response to oncogene expression, alters the tumor spectrum of LFS mice, and enhances various mutant p53 gain-of-function activities (Girardini et al., 2011). We chose to evaluate the SNP at position (-)842 of the PIN1 gene as a surrogate for PIN1 expression for the following reasons. Firstly, its position in the promoter region of the gene lends biologic plausibility to the hypothesis that it influences gene expression. Second, it 68

79 has been demonstrated in a number of case-control studies that this polymorphism is associated with cancer risk (Han et al., 2010, Lu et al., 2009, Xu et al., 2013). Finally, the minor allele frequency makes it possible to have representation of various genotypes in this study cohort. We demonstrate that the GG genotype at position (-)842 of the PIN1 gene is associated with features of a more aggressive cancer phenotype among patients with LFS. The median age of cancer onset was determined to be 10.6 years earlier in individuals with the GG genotype compared to those with GC/CC genotypes, (6.2 years vs years; p = ) (Table 4, Figure 8). This effect appeared to be particularly pronounced in the pediatric age group. Nearly all (92%) pediatric patients with the GG genotype developed their first cancer in the first decade of life, compared to approximately 65% of patients carrying a C allele (p = ) (Table 4, Figure 8b & 8c). While this effect size appears to be relatively modest, it is expected if one considers the infinitesimal model of disease susceptibility, which postulates that common variants are a significant source of genetic variance, where hundreds of loci contribute, each with small effect (Gibson, 2011). Furthermore, given the more prominent effect in pediatric patients, one may argue that a delay in tumor onset until the second decade of life is, in fact, a clinically relevant, significant outcome. We would have expected this effect size to be enriched in subgroup analyses of individuals with gain-of-function missense mutations; however, the small sample size may have hindered this determination. 69

80 Individuals with LFS are also prone to developing multiple tumors over the course of their lifetime; however, this is also variable between and within kindred. The PIN1 (-)842 genotype did not influence the frequency of multiple tumors in our study cohort (Table 4, Figures 9a & 10). Among all endpoints, however, multiplicity of tumors as a marker of expressivity is difficult to study, since it has a strong environmental determinant, namely, the exposure to multiple DNA-damaging agents as part of therapy of previous cancers. This is particularly relevant in the case of LFS patients, as it has been shown that various chemoand radiotherapies can stabilize mutant p53 and augment its gain-of-function activity (Suh et al., 2011). In our subgroup analysis of individuals with gain-of-function missense TP53 mutations, we observed an intriguing predilection for LFS-component carcinomas in those with the GG genotype at PIN1 (-)842(42% of primary tumors, vs. 12.5% in individuals with the GC/CC genotype; Figure 12). The single carcinoma in the GC/CC group is a CPC, arising at the age of 4.39, while the CPCs in the GG group arose at an average age of 9 months. Interestingly, an older age of onset of CPC is more in keeping with p53-wildtype CPCs (Merino et al., 2015). These results are in keeping with data generated from the study of LFS mouse models. Compared to mice with heterozygous truncating mutations, mice with missense mutations show a higher incidence of carcinomas (Lang et al., 2004, Olive et al., 2004, Liu et al., 2000). Even more striking is the complete absence of carcinomas in p53 M/+ Pin1 -/- compound mice (Girardini et al., 2011). These studies suggest mutant p53, specifically in 70

81 the context of increased PIN1 expression, may have particular oncogenic activities in tissues of epithelial origin. Also notable was the significantly greater proportion of gliomas in individuals with PIN1 (- )842 GC or CC genotypes (Figure 12b). PIN1 protein expression has been shown to be highest in cells of the central nervous system (Lu and Zhou, 2007). One may postulate that PIN1 regulates several proteins important for neuronal function, and that decreased PIN1 expression, mediated by the PIN1 (-)842 genotype, may lead to perturbations resulting in uncontrolled cellular growth. There are a few limitations to the above set of analyses that deserve consideration. First, since there are other documented modifiers of the LFS phenotype, and likely still many others that are unknown, one must consider the possibility of their unequal distribution between groups, thus confounding results. A comprehensive assessment of all known modifiers, using statistical methods which consider multiple variables of small effect, would be an ideal approach. Second, it must be considered that PIN1 may not influence all p53 mutants to the same degree. Girardini and colleagues only assessed the cooperation of PIN1 and mutant p53 in the context of a mouse model of the human R175H p53 mutant, and in breast cancer cells harbouring R280K mutant p53 (Girardini et al., 2011). Furthermore, it has been well documented that different p53 mutants have different gainof-function activities, and that tissue type may also influence the activity of a given p53 mutant (Hanel et al., 2013, Olive et al., 2004, Song et al., 2007). There may also be some contribution of the context of mutant p53 activation whether by oncogenic stimuli, or 71

82 genotoxic insults. These factors may influence the contribution of PIN1 to the overall outcome of mutant p53 activity, and may be variable in a study cohort, resulting in a modest effect when evaluating a group of heterogeneous patients as a whole. Still, the results presented here provide some insights into a potential role for PIN1 as a modifier of the LFS phenotype. An important component of the hypothesis that the PIN1 (-)842 genotype influences mutant p53 gain-of-function and LFS phenotype is that it alters the expression of the PIN1 gene. To test this, we isolated paired RNA and protein extracts from lymphoblastoid cell lines. Based on published data of the integral role of PIN1 in mutant p53 gain-of-function, and our own findings of an earlier age of cancer onset in the subgroup of LFS study subjects with the PIN1 GG genotype, we would expect this genotype to be associated with a higher PIN1 expression. Indeed, we demonstrate that the GG genotype at the (-)842 locus causes an approximate six-fold increase in PIN1 transcript levels as determined by qpcr, and a twofold increase in PIN1 protein levels (Figure 13). The asymmetrical rise is likely due to inherent differences in sensitivity between qpcr and Western blot densitometry, and from post-transcriptional and post-translational modifications that affect ultimate protein levels. Although these results were reproducible in replicate experiments, we attempted to validate our findings in a larger sample set. An analysis of whole genome sequencing data from the 1000 Genomes Project and paired RNA-seq data generated from lymphoblastoid cell lines failed to find a difference in PIN1 transcript levels among individuals with different PIN1 (-)842 genotypes (Figure S12). These findings do not necessarily invalidate our own 72

83 experimental findings. First, one must consider the choice of the validation cohort; this in fact was not a clear-cut decision. We elected not to use genomic data from cancer cell lines/tumor specimens, since PIN1 is known to be regulated by a number of proteins involved in cell growth, that may be perturbed in cancer genomes, such as E2F, Notch1, and BRCA1, (MacLachlan et al., 2000, Ryo et al., 2002) and furthermore, PIN1 has been shown to be upregulated in a significant number of cancers (Bao et al., 2004). These circumstances would preclude an accurate evaluation of the impact of a SNP on gene expression. The subjects recruited for the 1000 Genomes Project can be assumed to be generally free of a cancer diagnosis. They are also likely to be wildtype for TP53, in contrast to our samples, which were derived from patients with LFS and harboured TP53 missense mutations. While we are not aware of any data implicating that mutant p53 affects the expression of PIN1, a recent report describes circumstances of downregulation of PIN1 by wildtype p53, and identifies a p53 response element in the PIN1 promoter (Jeong et al., 2014). Since mutant p53 loses its ability to transactivate wild type p53 gene targets, one might assume that PIN1 is not directly regulated at the transcriptional level by mutant p53. A luciferase assay could be used to assess the effect of a nucleotide change in isolation, and in fact one study corroborates our data and reports a significant increase in relative luciferase activity in samples with the GG genotype at position (-)842 of the PIN1 gene (Lu et al., 2009). It should also be noted that most of the genomic data analyzed from the 1000 Genomes Project were derived from its Phase 1 dataset, with low-coverage (2-4x) read depth, thus raising the possibility of some inaccurate SNP calls. Also, the use of EBV-immortalized lymphoblastoid cell lines (LCLs) for human genetic studies requires careful consideration; LCLs acquire 73

84 expression changes during long-term subculture, in pathways including NF-κB and in carcinogen-related genes (Lee et al., 2010). Our LCLs were early passage (P1-P2), but we are not certain of the conditions associated with the LCLs used for RNA extraction of 1000 Genomes samples. Having established a role for PIN1 expression in modifying the phenotype of patients with LFS, we sought to ascertain biologic evidence of an effect of PIN1 expression in a context relevant to human LFS. We chose to use LFS patient-derived fibroblasts for this purpose. Some may question the utility of this system given that LFS-component tumors do not usually include those derived from the skin (although, fibroblasts are of mesenchymal origin, like other connective tissues, including muscle and bone). However, these cell lines are unique in that they harbor TP53 mutations in an untransformed state, and thus serve as a correlate for the status of all cells in LFS patients. As such, they may be useful for evaluating factors that participate in the early stages of tumorigenesis, those which may have a role in determining endpoints such as age of cancer onset. Furthermore, a cancer cell line, such as a sporadic rhabdomyosarcoma cell line, would also not be a representative system. Not only would it be an already established cancer genome, but the mechanisms of tumorigenesis are necessarily different from those occurring in LFS-associated tumors, in which p53 mutations are, by definition, an early event. Finally, specifically with respect to the evaluation of PIN1, the use of a cancer cell line may be particularly problematic given that PIN1 has such a wide array of protein targets, many of which participate in cell growth regulation and oncogenesis, as outlined in the introduction. 74

85 We used two fibroblast cell lines with the R248Q p53 mutation one of six hot-spot mutations in LFS patients which has been shown to have gain-of-function activity (Table S3). We compared the effects of PIN1 overexpression in these cell lines to those with a truncating TP53 mutation (C275X) and wildtype TP53. PIN1 overexpression selectively increased the clonogenicity of fibroblast cell lines with the R248Q gain-of-function mutation; indeed, no significant differences were seen between PIN1- and GFPoverexpressing cells in lines with a truncating TP53 mutation or WT TP53 (Figures 14 a&b). We also demonstrate avoidance of apoptosis in response to genotoxic (doxorubicin) stress: cell lines expressing the R248Q p53 mutant showed sustained viability as assessed by an MTS assay, and this correlated with decreased production of cleaved PARP. These results provide evidence for an influence of PIN1 expression on the behavior of gain-of-function p53 mutant proteins in patients with LFS. The two fibroblast cell lines harbouring R248Q p53 mutations did not behave identically. R248Q-a produced more dramatic, statistically significant results, compared to R248Qb, which demonstrated the same direction of effect but not to the same degree (Figures 14 and 15). Data from mouse studies (Donehower et al., 1995, Harvey et al., 1993a, Kuperwasser et al., 2000) have demonstrated the importance of the genetic background in the ultimate phenotype produced by mutant p53 proteins, thus this may explain some of the lack of complete concordance. R248Q-a and R248Q-b are fibroblast cell lines derived from a son and father with LFS, respectively. It is tempting to speculate that there 75

86 may be a form of genetic regression at play in this circumstance, as described in the introduction, in reference to a study completed by Arrifi and colleagues (Ariffin et al., 2014). Tumor resistance alleles of various modifiers in the father may have been diluted in subsequent generations, or a susceptibility allele may have been inherited by the son from his mother, that suppresses resistance alleles and provides a more permissive background for cellular growth. We may have expected to demonstrate an increase/stabilization of p53 by overexpression of PIN1 in these experiments. Zacchi et al. report that p53-wildtype MEFs which are deficient in PIN1 show impaired p53 stabilization upon UV treatment, due to its inability to dissociate from MDM2 (Zacchi et al., 2002). However, MEFs expressing endogenous PIN1 (similar to our fibroblasts) do not demonstrate further p53 stabilization in response to UV treatment upon overexpression of PIN1. The effect of PIN1 overexpression on p53 levels in this system is also subject to the influence of cellular context, the genotoxic agent and dose intensity used; these variables affect the kinases acting on p53 and thus may influence its interaction with PIN1. In support of this notion, Zacchi et al. did not detect differences in p53 stabilization in gamma-irradiated thymocytes from the same mice that generated the MEFs (Zacchi et al., 2002). Furthermore, Girardini and colleagues did not demonstrate an effect of modulation of PIN1 levels on p53 stability in MEFs and thymic lymphomas derived from p53 M/+ mice, despite showing an impressive effect on anchorage-independent growth and tumorigenic potential (Girardini et al., 2011). It can still be interpreted with some certainty that the avoidance of apoptosis by R248Q fibroblasts in response to doxorubicin treatment in this study is at least in part mediated by 76

87 the effects of PIN1 on mutant p53, since a control group (with a truncating mutant) of the same cell type and exposed to the same genotoxic stress was comparatively more sensitive to treatment. 77

88 FUTURE DIRECTIONS To further build on the results of this study, a number of modifications and further experiments can be considered. As mentioned in the Discussion, an account of confounding variables (that is, other modifier genes) is needed for the proper interpretation of any apparent impact on clinical phenotype. A comprehensive assessment of all known modifiers, using statistical methods which consider multiple variables of small effect, would be an ideal approach. The efficient determination of multiple risk loci could be facilitated by the use of next generation sequencing technologies, such as whole exome or whole genome sequencing. An increased cohort size, afforded by multi-institutional collaboration, would also facilitate an analysis of this nature. An interrogation of the modifying role of other SNPs in the PIN1 gene on the LFS phenotype would be an interesting and worthwhile endeavour. Furthermore, one could consider investigating epigenetic changes, as opposed to SNPs, as a mode of differential PIN1 gene expression. For instance, a comprehensive assessment of the methylation status of the PIN1 promoter, its effect on PIN1 expression, and the resulting association with LFS phenotypic variability could be pursued. Additional functional work is also needed to further validate the effects of PIN1 expression on the LFS phenotype. An evaluation of cell lines with other TP53 gain-of-function mutations, and the use of other genotoxic agents, would strengthen the results of the current study. Cell lines more relevant to the LFS tumor spectrum could be generated for this purpose, potentially via induced pluripotent stem cells, as has been done in a recent 78

89 study (Lee et al., 2015). Specifically in regard to PIN1 SNP (-)842, it would be interesting and more physiologically-relevant to directly assess for differences in growth and apoptosis of cell lines based on their genotype at this locus, as opposed to using a model which employs overexpressing the gene. Furthermore, other readouts of p53 gain-offunction could be explored. More robust apoptosis assays in response to cytotoxic damage, such as Annexin V, would allow for a more reliable interpretation of this endpoint. One could also evaluate effects on invasion, migration, and propagation of the cell cycle. The influence of PIN1 expression on the metabolic effects of mutant p53 would also be interesting to pursue further, including its involvement in promoting cellular aerobic glycolysis. This would be particularly interesting, in light of recent data showing increased oxidative phosphorylation of skeletal muscle in individuals with germline TP53 mutations (Wang et al., 2013). This thesis established an association between PIN1 expression and R248Q mutant p53, which is the first description we are aware of. The LFS knock-in mouse model used to demonstrate the interaction between PIN1 and mutant p53 harboured p53 R172H (human R175H). Future in vivo studies utilizing knock-in mice harbouring the R248Q mutant p53 would be of interest to further the results of this thesis. One could evaluate the tumor spectrum (and specifically, incidence of carcinomas), xenograft growth, and metastatic potential in compound mice which either express Pin1 or lack Pin1 expression (i.e., Pin1 knockout). Finally, further study on the apparent propensity for carcinoma development in LFS patients with the PIN1 (-)842 GG genotype (a variant that mediates increased PIN1 expression) is 79

90 merited. The association of PIN1 expression and breast cancer cell migration and invasion, via an increased binding of mutant p53 to p63 and subsequent suppression of its downstream targets, has been demonstrated (Girardini et al., 2011). Furthermore, PIN1 expression has been shown to be a prognostic marker in a cohort of breast cancer patients. It would be also interesting to evaluate this association in LFS- associated breast carcinoma, as opposed to sporadic breast cancer cell lines, and in other classic LFS-associated carcinomas, including adrenocortical carcinoma and CPC. This could potentially be pursued via in silico analysis of publically-available datasets. Ultimately, should further study produce additional robust evidence for a modifying role of PIN1 in LFS, its status may be used to help tailor management strategies for this patient population. 80

91 CONCLUSIONS We demonstrate that PIN1 expression enhances gain-of-function properties of mutant p53 in cell lines derived from patients with Li-Fraumeni Syndrome. This was specifically shown using the R248Q mutant, which has not been previously reported in the literature. Concordantly, we show that a SNP in the PIN1 promoter region that mediates expression changes of the PIN1 gene modifies the cancer phenotype of LFS patients. Individuals with the GG genotype at the PIN1(-)842 locus, associated with an increased expression of PIN1, demonstrate an earlier age of cancer onset, which is particularly pronounced in the pediatric age group. A predilection for development of carcinomas may also be associated with this genotype. It is likely that the phenotype of carriers of germline TP53 mutations represents a complex interplay of a number of modifying genetic/epigenetic and genomewide processes. The goal will be to identify a composite of genetic changes that reliably inform risk estimates for tumorigenesis and ultimately translate these into the stratification of management practices for patients with LFS. 81

92 CHAPTER 6: APPENDICES I. Supplemental Figures RIN values: Figure S1: Bioanalyzer results of RNA integrity of RNA extracted from lymphoblastoid cell lines. 82

93 Figure S2: qpcr standard curve, amplification curve and melting curve for PIN1. Efficiency of reaction = 100% (slope ). Blue = B2M, green = RPL13A, Pink = PIN1. 83

94 Figure S3: Vector map for lentiviral vector plx302, containing CMV promoter, C-terminal V5 tag, and puromycin resistance gene. 84

95 Figure S4: Representative fibroblast cell line following transduction with plx302-gfp, demonstrating near-total transduction efficiency ug/ml % confluency ug/ml ug/ml ug/ml 40 1 ug/ml 20 2 ug/ml 5 ug/ml days 10 ug/ml Time (hours) of puromycin exposure Figure S5: Representative kill curve used to establish puromycin concentration for selection of transduced fibroblast cells (completed on all cell lines). 85

96 a) b) Figure S6: a) Western blot of fibroblast lysates post transduction of cells with plx302-gfp (G) or plx302-pin1 (P), demonstrating overexpression of PIN1 in plx302-transduced lines. As shown in b), the slower migrating band corresponds to the overexpressed PIN1-V5 tag construct. 86