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P53 regulated microRNAs in colorectal cancer P53 regulierte MicroRNAs in Darmkrebs Der Medizinischen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg zur Erlangung des Doktorgrades Dr. med. Vorgelegt von Mariana Fernanda Cordoba Hansen aus Buenos Aires, Argentinien Als Dissertation genehmigt von der Medizinischen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg Tag der mündlichen Prüfung: 11.11.2014 Vorsitzender des Promotionsorgans: Prof. Dr. med. Dr. h.c. Jürgen Schüttler Gutachter/in: Prof. Dr. rer. nat. Regine Schneider-Stock Prof. Dr. med. Arndt Hartmann Acknowledgements First, I would like to thank Prof. Schneider-Stock for giving me the opportunity to work at her lab. I appreciate all her contributions of time and ideas to make my doctoral experience productive and stimulating. Further, I would like to express my gratitude to Prof. Hartmann, for opening me the doors to the Institute of Pathology and for always being willing to help me and answer my questions. My time at the Experimental Tumor Pathology Department was made enjoyable in large part due to my nice colleagues. Special thanks to Jelena, Chirine and Natalya, who have always been ready to orientate me with their knowledge and shared with me their love for science. Big thanks to Bärbel for her help with the translation. Hard times turned to be easier thanks to these girls. I really appreciate their good humor and enthusiasm. Most of all, I am eternally grateful to my family. To my parents and my sister, for their love and support. To my three beautiful children: Máximo, Magdalena and Laurens, for learning me every day the job of my dreams: being their mother. And specially, thank you to Henrik, my husband. For believe in my abilities and me. For his optimism and his way to make complicate things look easier. For his encouragement, that made me try a completely new activity after many years of exclusive formation and surgical work. For always, no matter what, be unconditionally there for me. Contents List of abbreviations ......................................................................................... List of tables ..................................................................................................... List of figures.................................................................................................... Introduction .................................................................................................... 1 1. Introduction .......................................................................................... 1 1.1. Colorectal cancer........................................................................... 1 1.2. Tumor suppressor p53 .................................................................. 3 1.2.1. Mutation status of p53 ................................................................ 5 1.2.2. P53 mutations in CRC ................................................................ 7 1.2.3. Polymorphisms in p53 gene ....................................................... 8 1.3. K-ras .............................................................................................. 9 1.4. BRAF ........................................................................................... 11 1.5. MicroRNAs, novel gene regulatory molecules ............................. 11 1.5.1. Biogenesis of miRNAs.............................................................. 12 1.5.2. Oncogenic or tumor-suppressive miRNAs ............................... 14 1.5.3. P53 and miRNAs ...................................................................... 15 2. Aims of the study................................................................................ 17 Materials and methods................................................................................. 18 3. Materials and methods ....................................................................... 18 3.1. Samples....................................................................................... 18 3.2. Equipment ................................................................................... 19 3.3. Materials ...................................................................................... 19 3.4. Methods ....................................................................................... 22 3.4.1. DNA isolation from paraffin embedded sections ...................... 22 3.4.2. Mutational analysis of p53 ........................................................ 24 3.4.3. Mutational analysis of K-ras and BRAF .................................... 26 3.4.4. RNA isolation from paraffin embedded sections ...................... 27 3.4.5. Reverse transcription ............................................................... 27 3.4.6. Real-Time Polymerase Chain Reaction (qRT-PCR)................. 28 3.4.7. Immunohistochemical analysis of p53 (IHC) ............................ 29 Results ......................................................................................................... 30 4. Results ............................................................................................... 30 4.1. P53 mutations.............................................................................. 30 4.2. P53 polymorphisms ..................................................................... 33 4.3. Analysis of p53 mutations in CRC cell lines................................. 34 4.4. K-ras mutations ........................................................................... 35 4.5. BRAF mutations .......................................................................... 39 4.6. Associations with p53 gene mutations ......................................... 41 4.7. Immunohistochemical staining patterns of p53 ............................ 41 4.8. MiRNAs ....................................................................................... 45 4.8.1. MiR-34a .................................................................................... 45 4.8.1.1. MiR-34a gene mutation associations .................................... 48 4.8.2. MiR-34b and miR-34c .............................................................. 48 4.8.3. MiR-192, miR-215 and miR-200c ............................................. 48 Discussion ................................................................................................... 49 5. Discussion .......................................................................................... 49 5.1. Role of p53 in CRC...................................................................... 49 5.2. The different genotypes of p53 codon 72 polymorphisms have discrepancies in their biochemical and biological properties ................. 51 5.3. Addressing the Cell Line Cross-contamination problem .............. 52 5.4. K-ras gene is a marker of aggressive tumor phenotype .............. 52 5.5. V600E mutations are associated with higher risk of mortality in CRC ......................................................................................................53 5.6. Simultaneous mutations of p53, K-ras and BRAF: rare but not impossible ............................................................................................. 54 5.7. Mutated p53 can be detected by immunostaining ....................... 55 5.8. MiRNAs induced by p53 .............................................................. 58 5.8.1. MiR-34 family ........................................................................... 58 5.8.1.1. 5.8.2. MiR-34a is up-regulated in tumors with wt p53 ..................... 59 MiR-34b and miR-34c are not detectable in CRC samples ...... 61 5.8.3. Other components in the p53 network: miR-192, miR-215 and miR-200c ............................................................................................... 61 5.8.4. 5.9. MiRnas, K-ras and BRAF in CRC............................................. 63 Conclusion and outlook ............................................................... 64 6. References ......................................................................................... 67 Abstract ...................................................................................................... 105 Zusammenfassung .................................................................................... 107 Curriculum Vitae ........................................................................................ 109 List of abbreviations 5-FU µl µm µM ADR Ago APC Arg Bcl-2 CAC CDC7 cDNA CLCC COX CRC Cte Cth CYP3A4 DBD DCC DNA DTL E2F1 EGFR EMT FAP FFPE Gadd45 GOF H&E HMGA2 HNPCC HPV IARC IHC iNOS K-ras MDM2 MDMX Min miRNA Ml mRNA MSI 5-Fluoruracil Microliter/s Micrometer micromol/es Adriamycin Argonaute Adenomatous polyposis coli Arginine B-cell lymphoma 2 Colitis-associated cancer Cell division cycle 7-related protein kinase Complementary Deoxyribonucleic acid Cell line cross-contamination Cyclooxygenase Colorectal cancer Threshold cycle of the experimental gene Threshold cycle of the housekeeping gene Cytochrome p450 3A4 DNA-binding domain Deleted in colorectal cancer Deoxyribonucleic acid Denticleless protein homolog E2F transcription factor 1 Epidermal Growth Factor Receptor Epithelial-mesenchymal transition Familial adenomatous polyposis Formalin-fixed paraffin-embedded Growth arrest and DNA-damage inducible protein Gain-of-function Hematoxilin and eosin High-mobility group AT-hook 2 Hereditary non-polyposis colorectal cancer Human papilloma virus International Agency for Research on Cancer, World Health Organisation Immunohistochemestry Nitric oxide synthase Kirsten rat sarcoma viral oncogene homolog Murine double minute 2 Murine double minute X Minute/s Micro ribonucleic acid Milliliter/s Messenger ribonucleic acid Microsatellite instability MSS Mut Ng P53 PCR PIG3 Pro PTEN Puma qRT-PCR RAS RE RISC RNA RPM RT Sec UTR Wt Microsatellite stability Mutated Nanogram/s Tumor protein p53 Polymerase chain reaction P53-inducible gene 3 Proline Phosphatase and tensin homolog P53 upregulated modulator of apoptosis Real-Time-quantitative-PCR Rat sarcoma viral oncogene homolog Responsive element RNA-induced silencing complex Ribonucleic acid Revolutions per minute Reverse transcription Second/s Untranslated region Wild-type List of tables Table 1. Patient clinical characteristics ........................................................ 18 Table 2. Equipment ..................................................................................... 19 Table 3. List of chemicals ............................................................................ 19 Table 4. List of consumables ....................................................................... 20 Table 5. List of commercial kits ................................................................... 20 Table 6. List of antibodies ............................................................................ 21 Table 7. List of primers ................................................................................ 21 Table 8. Detected p53 mutations ................................................................. 31 Table 9. P53 mutations in 5 CRC cell lines ................................................. 34 List of figures Figure 1: Carcinogenic steps of four types of human colorectal cancer ........ 3 Figure 2: Tumor suppressor p53 and its signaling pathway .......................... 5 Figure 3. MiRNA biogenesis........................................................................ 13 Figure 4. P53 mutational spectrum in this project ....................................... 30 Figure 5. Distribution of the mutations......................................................... 31 Figure 6. Types of p53 mutations ................................................................ 32 Figure 7. Distribution of p53 codon 72 polymorphisms ............................... 33 Figure 8. 3 different genotypes of p53 codon 72 polymorphisms ................ 33 Figure 9. P53 mutations in CRC cell lines ................................................... 35 Figure 10. Percentage of K-ras mutations ................................................... 36 Figure 11. Distribution of K-ras mutations ................................................... 36 Figure 12. K-ras wt ...................................................................................... 37 Figure 13. G12D K-ras mutation ................................................................. 37 Figure 14. G12V K-ras mutation.................................................................. 38 Figure 15. G12S K-ras mutation.................................................................. 38 Figure 16. G12C K-ras mutation ................................................................. 38 Figure 17. G13D K-ras mutation ................................................................. 39 Figure 18. BRAF mutations ......................................................................... 39 Figure 19. BRAF wt ..................................................................................... 40 Figure 20. V600E BRAF mutation ............................................................... 40 Figure 21. Immunohistochemical staining of p53 non-mutated (wt) and mutated samples.......................................................................................... 42 Figure 22. Relationship between p53 immunohistochemical expression in wt and p53 mutated samples ............................................................................ 43 Figure 23. Relationship between p53 immunostaining and exon mutations 44 Figure 24. P53 staining patterns ................................................................. 45 Figure 25. Comparison of miR-34a levels in no tumor and tumor p53 wt samples ....................................................................................................... 46 Figure 26. Comparison of miR-34a levels in no tumor and tumor p53 mutated samples.......................................................................................... 47 Figure 27. Comparison of miR-34a levels in wt and mutated p53 tumor samples ....................................................................................................... 47 Introduction 1. Introduction 1.1. Colorectal cancer Colorectal cancer (CRC) is one of the world´s leading cancer diseases and third leading cause of cancer death worldwide (Erichsen et al. 2013; Karim and Huso 2013; Lemos et al. 2013). It is considered the second most frequent cause of cancer related mortality in the Western World (Nielsen et al. 2011). An estimated 1.2 million new cases and 608.700 deaths have occurred in 2008 (Pamukcu et al. 2013; Seretis et al. 2014). Higher CRC incidence rate was found in the New Zealand, certain countries in Europe and North America, but the incidence has considerably increased in the last decades in regions including Eastern Asia, Eastern Europe, and Spain (Chen et al. 2013). Only about 5-10% of CRC cases have a defined hereditary background due to two main diseases, familial adenomatous polyposis (FAP) and hereditary nonpolyposis colorectal cancer (HNPCC) (Jasperson et al. 2010). Most of the cases seem to occur without a hereditary background, and are related to environment factors such as smoking, alcohol drinking, physical inactivation, red and processed meat consumption, high-fat diet and inadequate intake of fiber (Stratmann et al. 2011). It has been hypothesized that obesity may also lead to an increased CRC risk, being hyperinsulinemia the proposed underlying biological mechanism for such association (Aleksandrova et al., 2012). Other studies have proposed that hyperglycemia could also modulate the association between obesity and CRC risk (Pais et al. 2009; Ramos-Nino 2013). Inflammatory bowel diseases represent a risk factor for developing cancer as well (Farraye et al. 2010; Necela et al. 2011). CRC transforms normal colonic epithelium cells to tumor cells (Lee and Yun 2010). This transformation involves a multistep process, including genetic end epigenetic changes, that leads to the activation of oncogenes and inactivation of tumor suppressor genes in cancer cells (Choong and Tsafnat 2012). At least four types of human colorectal carcinogenesis have been described: adenomacarcinoma sequence type, HNPCC type, “de novo” type, and colitis-associated cancer (CAC) type (Okayama et al. 2012; Tanaka 2012). CAC arises from the background of colitis and DNA injury, which is induced by production of free 1 radicals by the inducible nitric oxide synthase (iNOS) system in the colonic mucosa with persistent inflammation, followed by p53 mutation and development of a precancerous lesion, dysplasia (Shaked et al. 2012; Cooks et al. 2013). The progression of dysplasia into invasive CRC is mediated by cyclooxygenase- (COX-) 2, iNOS, and different cytokines produced in the infiltrating inflammatory cells and accumulation of genetic abnormality, such as a loss of the gene deleted in colorectal cancer (DCC) (Tanaka 2009; Duman-Scheel 2012). On the other hand, in sporadic CRC (adenomacarcinoma sequence type), are the adenomatous polyposis coli (APC) and Kras genes and microsatellite instability that have been proposed to be hardly involved in its development (Armaghany et al. 2012). Although it has been important progress in the diagnosis and therapy of CRC in the last years, patient’s prognosis is still poor (Li et al. 2013). The molecular mechanisms underlying the development of cancer are complex and remain generally not well understood (Kong et al. 2012; Muzes et al. 2012). 2 Figure 1: Carcinogenic steps of four types of human colorectal cancer (Tanaka 2012). 1.2. Tumor suppressor p53 P53, dubbed as the “guardian of the genome”, was the first tumor suppressor gene to be identified in 1979 (Paskulin et al. 2012). The human p53 gene is placed on chromosome 17p and consists of 11 exons and 10 introns (Saha et al. 2013). P53 acts to eliminate and inhibit the proliferation of abnormal cells, thereby preventing tumor development. Disruption of normal p53 functions is often a prerequisite for the initiation and/or progression of tumors (Feng et al. 2011). Clinical studies reported that p53 is mutated in approximately 50% of human cancers and it is estimated that more than 80% of tumors have dysfunctional p53 signaling (Feng et al. 2011; Pei et al. 2012). MDM2 and MDMX are two structurally related proteins that play a fundamental role in down-regulating P53 activity under normal conditions (Gu et al. 2002). 3 P53 responds to a big number of intrinsic and extrinsic stress signals, including DNA damage, hypoxia, mitotic spindle damage, nutritional starvation and activation of selected oncogenes (e.g. c-Myc, Ras and E2F-1) (Vogelstein et al. 2000; Ha and Breuer 2012; Garritano et al. 2013; Liang et al. 2013). These signals are detected and communicated to p53 via different enzymes that mediate the modifications of p53 protein, such as phosphorylation, acetylation and ubiquitination leading to an increase of p53 protein half-life and consequently to p53 accumulation in cells (Levine et al. 2006). The activated p53 protein in a stressed cell acquires the ability to bind to specific DNA sequences, termed p53-responsive elements (RE) adjacent to genes and enhances the rate of transcription of those genes (Feng et al. 2011; Wang and Cui 2012). In this way, activated P53 selectively transcribes its target genes to start various cellular responses (Bieging and Attardi 2012). Depending on the cell type, environmental context, and the type and/or degree of stress, P53 promotes cell cycle arrest, senescence or apoptosis to prevent the propagation of damaged or mutant cells that could potentially derive in cancerous cells (Donehower 2009). For instance, in response to mild stress signals, P53 induces its target genes involved in cell cycle arrest (e.g. p21, Gadd45, and 14-3-3 sigma) and DNA repair (e.g. p48, and p53R2) to permit cells to survive until the damage has been repaired or stress has been removed . In case of severe or sustained stress signals, p53 induces genes involved in apoptosis (e.g. Puma, Bax, Fas, PIG3, and Killer/DR5) and senescence (e.g. p21), and in this way prevents the accumulation of damaged cells (Suzuki and Matsubara 2011; Suppiah and Greenman 2013; Liu et al. 2014). Recent investigation showed that p53 exert additional tumor suppressor functions like energy metabolism (Puzio-Kuter 2011), antioxidant defense (Sablina et al. 2005) and anti-angiogenesis (Assadian et al. 2012). Moreover, a variety of negative and positive feedback loops are activated, resulting in turning off p53 regulated functions or enhanced p53 activity (Harris and Levine 2005). 4 Figure 2: Tumor suppressor p53 and its signaling pathway (Liu et al. 2013b). 1.2.1. Mutation status of p53 P53 mutations are one of the most common genetic events in human cancer (Olivier et al. 2010; Oren and Rotter 2010). As given above, 50% of all tumors exhibit mutation of p53, but in those that retain wild-type p53, its activity can be attenuated by several other mechanisms (Kim et al. 2009; Wang et al. 2011; Zhao et al. 2013). The p53 gene encodes a 393 amino-acid, 53 kDa phosphoprotein that is divided into 3 domains: an amino (-NH2) terminal region, a central “core” domain which contains the DNA-binding regions and a terminal carboxyl (-COOH) region (Brazdova et al. 2002). P53 mutations are distributed in all coding exons of the gene, with a strong predominance in exons 4-8, which encode the DNA-binding domain of the protein (Kucab et al. 2010; Rivlin et al. 2011; Suppiah and Greenman 2013). Of the mutations in this domain, about 30% fall within 6 “hotspot” residues (residues R175, G245, R248, R249, R273 and R282) (Goh et al. 2011; Rivlin et al. 2011; Eldar et al. 2013). Endogenous mutations frequently arise from spontaneous deamination of methylated CpG dinucleotides, and interestingly, the codons at 4 of these hotspot residues contain CpG dinucleotides (Yoon et al. 2001; Freed-Pastor and Prives 2012). A transition (C to T or G to A) can take place following deamination of the 5-methylcytosine, and not surprisingly this is exactly the type of nucleotide change observed at these hotspots (Hussain et al. 2001; 5 Cao et al. 2009a). P53 mutations vary in the frequency with which they occur in different tumor types, suggesting that environmental mutagens leave their mark on p53 in a tumor- and tissue- selective manner (Kucab et al. 2010). A good example of this is the finding that hepatocellular carcinomas in some developing countries have a much higher frequency of p53-R249S mutations than other tumor types or liver cancer in developed nations (Aguilar et al. 1993; Liu and Wu 2010). This mutation has a strong association with exposure to Aflatoxin B1, a carcinogenic agent present in fungal species (Aspergillus flavus) and a common contaminant of food supply in areas of sub-Saharan Africa and Asia (Pineau et al. 2008; Tillett 2010). Types of p53 mutations According to the IARC TP53 Database version R17, p53 mutations have the following distribution: missense (73%), frameshift (9%), nonsense (8%), silent (4%) and others (6%) (Petitjean et al. 2007; Suppiah and Greenman 2013). P53 is frequently inactivated by a missense mutation, a single base-pair substitution that results in the translation of a different amino acid at that position (Brosh and Rotter 2009). The vast majority of missense mutations are mapped to the DBD (DNA-binding domain) and usually abolish its sequencespecific DNA-binding activity (Jordan et al. 2010). As mentioned before, over 30% of all missense mutations arise in 1 of 6 “hotspot” codons (Goh et al. 2011). P53 mutations can also be classified in “DNA contact” or “conformational” mutants (Bullock and Fersht 2001; Brosh and Rotter 2009). The first group includes missense mutations in the amino acid residues that normally make direct contact with target DNA sequences, such as R273H. The second group, typified by R175H, comprises those missense mutations that disrupt the structure of the p53 on either a local or global level (Brosh and Rotter 2009; Lanni et al. 2012). This distinction is important in order to avoid generalizations about p53. Many mutant p53-binding partners bind with a higher affinity to a group of tumor derived p53 mutants and it is also accepted that different kind of p53 mutations are responsible for diverse cancer outcomes (Freed-Pastor 6 and Prives 2012). For example, mutant R248Q, but not R248W, enhances invasiveness of human lung cancer (Yoshikawa et al. 2010). In breast cancer, certain missense mutations (R248W and mutations at codon 179) correlate with significantly poorer prognosis compared with other missense mutations (Olivier et al. 2006). Thus, as p53 mutational status moves closer to the clinical practice, it is fundamental to keep in mind that not all p53 mutations are equivalent (Freed-Pastor and Prives 2012). 1.2.2. P53 mutations in CRC P53 mutations have been described in about 40 to 50 % of colorectal carcinomas and affect mainly 5 “hotspots” (Al-Kuraya 2009; Rivlin et al. 2011). Mutation in codon 175 occurs at a higher frequency in tumors located in the colon and mutation in codon 288 in exon 8 is more common in rectal tumors (Naccarati et al. 2012). Mutations involving the most conserved regions of p53 (exons 5-8) are more frequent in tumors located at the distal compared to proximal colon, suggesting differences in the aetiology of CRC (Iacopetta 2003; Russo et al. 2005b; Sorlie et al. 2005). Also transversion (purine to pyrimidine) rather than transition (purine to purine, pyrimidine to pyrimidine) mutations occur more frequently in distal colon tumors. Mutations in colorectal adenomas are rare (16% versus 40-50% in CRC) meaning that alterations in the gene represent a late event in adenocarcinoma progression (Naccarati et al. 2012). Based on multinational data from approximately 9000 colorectal tumors the most frequent mutations observed have been at codons 175 and 273 (Lea et al. 2009). However, the clinical significance of p53 status related with survival and response to therapy still remains controversial (Iacopetta et al. 2006). Up to date, the only reported significant predictors of poor prognosis are G245 hotspot mutation and mutations in proximal colon tumors (Naccarati et al. 2012). The effects of p53 status on the response of tumors to chemotherapy are still being widely investigated. 5-fluorouracil (5-FU) is commonly used in the treatment of a range of cancers, including CRC (Ju et al. 2007). P53 can be activated by 5-FU through different mechanisms (Garcia et al. 2011). Previous investigations reported that CRC patients with wt p53 7 tumors benefit from 5-FU based chemotherapy, while those with mutated gene tumors do not (Naccarati et al. 2012). 1.2.3. Polymorphisms in p53 gene In addition to somatic mutations, several polymorphisms in the wild-type p53 gene locus have been reported, which could alter its function and have impact in the susceptibility to sporadic CRC (Dastjerdi 2011). Theoretically, polymorphisms may affect p53 protein function through enhanced mutability due to alter DNA sequence context, increased cryptic splicing events, altered transcript stability or translation or tissue-specific expression (Petitjean et al. 2007). The most investigated polymorphism is rs1042522, a G to C transversion in codon 72 of exon 4, which results in an amino acid change from arginine to proline (Whibley et al. 2009). The TP53 Arg72Pro is located in a proline-rich region of the protein, which is important for the growth suppression and apoptotic functions (Naccarati et al. 2012). P53 genotype at codon 72 can be heterozygous (Arg/Pro) or homozygous for either arginine (Arg/Arg) or proline (Pro/Pro) (Schneider-Stock et al. 2004). The 2 isoforms of p53 due to polymorphism at codon 72 have differences in their biochemical and biological properties, and apparently the protein with Arg72 form induces apoptosis more efficiently than the Pro72 form (Dumont et al. 2003). Several investigations have examined the association between the Arg72Pro polymorphism and the modulation of CRC risk, but results are controversial. Many investigations reported a strong association of CRC risk with Pro72 allele (Goodman et al. 2006; Perfumo et al. 2006; Cao et al. 2009b; Sameer et al. 2010; Song et al. 2011) while others support an appreciable association between the Arg allele and CRC (Dastjerdi 2011). In this context, the coexistence of Arg allele and mutated p53 may be a predictor of increased tumor development due to inactivation of the apoptosis pathway mediated by p73. Opposite to this, Arg72allele association with wt p53 might potentially enhance apoptosis (Godai et al. 2009; Naccarati et al. 2012). Sharp ethnic differences in codon 72 allele frequencies have been detected (Thurow et al. 2011). The frequency of Pro72 allele is approximately of 60% in African Americans and 30-35% in Caucasian Americans (Naccarati et al. 8 2012). Interestingly, the Pro72 allele frequency increases in a North-South gradient (Beckman et al. 1994). These latitude-dependent variations may be related to winter temperature and not to UV radiation as suggested by previous studies (Shi et al. 2009). 1.3. K-ras K-ras is a proto-oncogene that encodes a small 21-kDA protein (p21Ras) (Bissonnette et al. 2000; Tan and Du 2012). The Ras protein is activated by extracellular signals such as growth factors, cytokines, and hormones, which stimulate cell surface receptors (Adjei 2001). This protein has intrinsic GTPase activity, permitting inactivation following signal transduction in the normal cellular environment (Lin et al. 2000). Activating mutations of K-ras occurring early in colorectal tumorigenesis might abolish GTPase activity, leading to increased and unregulated cellular proliferation and malignant transformation (Conlin et al. 2005; Jancik et al. 2010). In human colorectal carcinomas, K-ras mutations are very common (20-50%) and about 90% of the activating mutations are found in codons 12 (wild-type GGT) and 13 (wild-type GGC) of exon 1 identifying these codons as hotspot mutation points (Poehlmann et al. 2007). Codon 12 harbors circa 80% of these mutations (Roa et al. 2013). G12D; G12V and G13D represent approximately 86% of the total number of mutations (Neumann et al. 2009; Yokota 2012; Roa et al. 2013). The most common types of mutations are G->A transitions and G->T transversions (Russo et al. 2005a). Several publications have focused on K-ras mutations in CRC. In this context, the RASCAL study has been conducted with the aim of investigating the prognostic role of K-ras mutations in CRC progression (Arrington et al. 2012). The Rascal study was made up on 2 principal collaborative studies. In the first RASCAL study the mutational status of K-ras was analysed in 2721 patients collected from 22 centres from 13 different nations. The authors showed that mutations in the K-ras gene were important for the progression and outcome of CRC, and that some specific mutations (glycine/valine at codon 12) seemed to have a prognostic role more important than others (Andreyev et al. 1998). 9 The RASCAL II study analyzed data regarding 3439 cases of CRC collected from 35 centers from 19 different nations with a follow up of 55 months. 35% of the cases presented K-ras mutations, 26% of which were in codon 12 and 9% in codon 13. About 9% of the total mutation number showed the replacement of the amino acid glycine with valine in codon 12. No association was found between K-ras mutations and other clinicopathological variables like age, sex, tumor site, type of growth, Dukes stage, histological type, vascular invasion and, lymphocyte response (Andreyev et al. 2001). The results obtained from the RASCAL studies express that K-ras mutations might have an effect on the survival rate of CRC patients, predicting poor patient prognosis. The specific codon 12 glycine/valine mutation could play a role in the progression of this neoplasia, leading in this way to a higher risk of disease relapse or death in 30%. Furthermore, when this mutation is present in Dukes C tumors, the risk increases to 50% (Russo et al. 2005a). In 2013 Phipps et al. demonstrated that CRC patients who have a K-ras mutation have significantly poorer prognosis than those without mutation (Phipps et al. 2013). Accumulated data suggest that K-ras mutation is a marker of aggressive tumor phenotype, and therefore detecting this mutation at an earlier disease may be of importance (Li et al. 2012). This could also have significance for treatment, as patients with Dukes stage A and B tumors undergo surgery with curative intent but are not routinely offered adjuvant therapy. Thus, patients with early stage disease and K-ras mutation may benefit from an alternative more aggressive treatment regimen (Conlin et al. 2005). On the other hand, knowing the mutational status of K-ras is also relevant in order to identify those patients who will benefit from anti-EGFRtargeted therapies (Phipps et al. 2013). EGFR inhibitors such as cetuximab or panitumumab are a successful strategy for the treatment of metastatic CRC in addition to or after failure of conventional chemotherapy (Neumann et al. 2009). Only CRCs with wild-type K-ras respond to anti-EGFR treatment and therefore mutation analysis is mandatory prior to the initiation of therapy (Kim et al. 2014). It has also been suggested that wild-type BRAF is required for a successful response to those drugs (Yokota 2012). 10 1.4. BRAF BRAF is an oncogene that encodes a protein kinase involved in intracellular signaling and cell growth (Hostein et al. 2010; Dienstmann and Tabernero 2011). Evidence suggests that BRAF mutations result in uncontrolled, nongrowth factor-dependent cellular proliferation (Kalady et al. 2012). Activating mutations of BRAF are found in 10%-20% of CRCs with most (over 95%) occurring in a hotspot of amino acid position 600 by a missense substitution of valine by glutamic acid, known as the BRAF V600E mutation (Mao et al. 2012; Prahallad et al. 2012; Yokota 2012; Kuan et al. 2014). The presence of BRAF mutations is associated with significantly higher risk of mortality in CRC patients (Safaee Ardekani et al. 2012). Patients with metastatic CRC with a BRAF mutation have a very poor prognosis, with median survival of only 10 months, as compared with 35 months for patients with a wild-type BRAF (Mao et al. 2012). There is a solid association between BRAF mutations and deficient mismatch repair characterized by microsatellite instability (MSI) (Calistri et al. 2005). BRAF mutations are found in 30% to 75% of MSI-positive CRCs, in contrast to K-ras mutations that are more prevalent in MSI-negative tumors (Vandrovcova et al. 2006; Kuan et al. 2014). Combined BRAF and MSI subtyping analysis suggests that BRAF-mutated MSS tumor is an unfavorable subtype, whereas BRAF wild-type MSI-high tumor is a favorable subtype, and BRAF-mutated MSI-high and BRAF wild-type MSS tumors are intermediate subtypes (Ogino et al. 2012; Lochhead et al. 2013). The presence of a BRAF V600E mutation in CRC predicts resistance to anti-EGFR therapy in patients with K-ras wild-type (Kalady et al. 2012; Kuan et al. 2014). BRAF-mutated CRC patients do not respond to treatment with cetuximab or panitumumab (Yokota 2012). Finally, a number of inhibitors of the V600E mutant form of the BRAF protein have been tested, for example vemurafenib (Safaee Ardekani et al. 2012). Vemurafenib achieved very good results in melanoma but unfortunately, this high response rate have not extended to BRAF mutations in CRC (Mao et al. 2013). 1.5. MicroRNAs, novel gene regulatory molecules MicroRNAs (miRNAs) are short, (approximately 18-25 nucleotides), noncoding RNA molecules that regulate gene expression (Gao et al. 2013). They 11 act usually post-transcriptionally by binding to the 3´-untranslated region of target mRNAs, leading to translational arrest, mRNA cleavage or a combination of the two (Karaayvaz et al. 2013; Mallick and Ghosh 2012; Wang et al. 2013a). Each miRNA can target multiple mRNAs, and, conversely, a single mRNA can be targeted by multiple miRNAs (Thomson et al. 2011). By targeting multiple transcripts, miRNAs modulate a wide range of biological processes, including apoptosis, differentiation and cell proliferation (Wang and Cui 2012). Since the identification of the first miRNA, lin-4, in the nematode Caenorhabditis elegans in 1993, thousands of miRNA genes have been identified in animals and plants genomes (Lee et al. 1993; Raisch et al. 2013). MiRNas are highly conserved in sequence between distantly related organisms, indicating their participation in essential biological processes (Pillai 2005). According to the miRBase 2014, 1881 precursors and 2588 mature miRNAs have been notated, but estimates suggest that their actual number will keep on increasing (Kozomara and Griffiths-Jones 2014). Taking into account the fact that each miRNA can regulate approximately the expression of 100-200 target genes, the whole miRNA apparatus seem to participate in the control of gene expression for an important proportion of the mammalian gene complement (Gennarino et al. 2009). MiRNA have such fundamental biological roles, that it is obvious that its expression is tightly controlled and its deregulation may lead to various diseases, including inflammatory disorders and cancer (Coskun et al. 2013; Li et al. 2013). 1.5.1. Biogenesis of miRNAs MiRNAs are clustered and located in either the introns of protein-coding genes or between genes as intergenic miRNAs (Hackler et al. 2010). The miRNA biogenesis starts in the nucleus, where 100-1000 nucleotides precursormolecules (pri-miRNAs) are synthesized from genomic DNA by the RNA polymerase II (Ro et al. 2007). The long pri-miRNA is then cleaved by the 12 ribonuclease enzyme Drosha, into shorter, typically 70 nucleotides hairpin structures known as pre-miRNAs (Felekkis et al. 2010). Pre-miRNAs are transported into the cytoplasm by Exportin-5 and subsequently undergo further processing by the endonuclease enzyme Dicer, to liberate a double stranded mature miRNA, with approximately 22 nucleotides (Wang et al. 2013b; Zhuo et al. 2013). One strand of the duplex is loaded onto Argonaute (Ago) protein in order to produce RNA-induced silencing complex (RISC) (Doxakis 2013). It has been suggested that, whereas all Ago proteins participate in the stabilization of mature miRNA, only Ago2 (which has endonuclease activity) cleaves the miRNA strand and activates RISC (Kang et al. 2013). This idea led to the observation that Ago1 facilitated RISC-mediated translational repression and Ago2-RISC led to target mRNA cleavage (Gu et al. 2011). The mature miRNA assembled onto RISC interact through partial sequence complementarity with the 3´untranslated regions (UTR) of target mRNAs to bring about translational repression or mRNA degradation (Babalola et al. 2013). The final effect of the mature miRNA is then, the down-regulation of the expression of the target gene by preventing the production of its protein product (Mirnezami et al. 2009). Figure 3. MiRNA biogenesis. MiRNA genes are transcribed into long transcripts called primary miRNAs (Pri-miRNA) containing multiple stem-loop/hairpin structures. Pri-miRNAs undergo cleavage by the endonuclease enzyme Drosha to form approximately 70 nucleotide precursor miRNAs (Pre-miRNA). Pre-miRNAs are 13 actively exported to the cytoplasm by the nucleocytoplasmatic transport factor Exportin 5, and there undergo further processing to give rise to mature single stranded miRNAs of about 20-25 nucleotides in length. Mature miRNAs are assembled onto the RNA-induced silencing complex (RISC) in association with other co-factors, and interact with complementary sites in the 3’-UTR of target mRNAs to negatively regulate gene expression through inhibition of translation (Mirnezami et al. 2009). 1.5.2. Oncogenic or tumor-suppressive miRNAs Abnormal expression of cancer-related miRNAs is characterized by increased or decreased expression levels compared with their levels in the corresponding normal tissue (Davis-Dusenbery and Hata 2010). Accumulating data suggest that some miRNAs may function as oncogenes or tumorsuppressor genes given their inhibition of a variety of tumor-suppressive and oncogenic mRNAs, respectively (Kong et al. 2012). The miRNAs with increased expression are thought to function as oncogenes and are called oncomirs (Marsolier et al. 2013). These oncomirs negatively inhibit tumor suppressor genes and/or genes controlling cell differentiation or apoptosis, promoting in this way tumor development (Budhu et al. 2010). On the other hand, some miRNAs show decreased expression in cancer cells and are considered as tumor suppressor genes (Grammatikakis et al. 2013). They usually prevent tumor development by negatively inhibiting oncogenes and/or genes that regulate differentiation or apoptosis (Zhang et al. 2007). There are a number of miRNAs that are overexpressed in one type of cancer and down-regulated in another (Croce 2009). For example, miR-205 is upregulated in lung, bladder and endometrial cancers (Dip et al. 2012; Karaayvaz et al. 2012; Jiang et al. 2013). Contrarily, it is significantly down-regulated in prostate and breast cancers (Gandellini et al. 2012; Savad et al. 2012; Liu et al. 2013; Verdoodt et al. 2013). The action of miRNAs is dependent on their targets for mRNA, where they can have an oncogenic or a tumor suppressor function (Hua et al. 2013). Three distinct mechanisms have been proposed in order to explain how miRNAs can function as oncogenes or tumor suppressor genes (Melo and Esteller 2011). 14 1-First, oncogenic miRNAs can express a gain of function in tumors due to genomic amplifications. This has been clearly demonstrated for the miR-17-92 cluster, whose amplification in B-cell lymphomas stimulates their development (Olive et al. 2010). 2-Furthermore, tumor suppressive miRNAs could suffer loss of function in tumors due to chromosomal rearrangements, deletions or mutations (Calin and Croce 2006; Croce 2009). This has been shown for several miRNAs, including the let-7 family, whose expression can diminish lung tumorigenesis through inhibition of oncogenes like the RAS family and HMGA2 (Lambertz et al. 2010). In particular, let-7 family members are in sites of frequent deletions in human tumors, and their processing is inhibited by the oncogenic Lin28 proteins (Kumar et al. 2009; Wang et al. 2012). It has been observed that the expression levels of let-7 were frequently reduced in both in vivo and in vitro lung cancer studies and that this reduction was significantly associated with shortened postoperative survival, independently of disease state (Takamizawa et al. 2004; Esquela-Kerscher et al. 2008). 3-Finally, oncogenes can acquire mutations to remove miRNA-binding sites, which alter the interaction between the miRNAs and the mRNA targets in tumors (Ryan et al. 2010). This has been established for HMGA2, whose translocation promotes lipoma development by releasing the transcript from let-7-mediated tumor-suppression (Lee and Dutta 2007; Mayr et al. 2007). 1.5.3. P53 and miRNAs Previous studies have demonstrated that p53 directly regulates some miRNAs, and this mechanism turns out to be a critical aspect of the p53 function in regulating cell cycle and cell proliferation (Karaayvaz et al. 2011). P53 induces the transcription of several miRNAs and promotes the maturation of specific miRNAs, both of which contribute to the function of p53 in tumor suppression (Jones and Lal 2012). On the other hand, miRNAs can negatively regulate p53 protein levels and function by direct repressing the expression of p53, or positively regulate p53 activity and function through the repression of negative regulators of p53. These findings have shown that miRNAs are important 15 components in the p53 network (Xi et al. 2006; Feng et al. 2011). Among the p53 induced miRNAs are the miR-34 family, miR-145, miR-107, miR-192, miR215 and miR-200c (Xi et al. 2006; Feng et al. 2011). 16 2. Aims of the study The p53 signaling pathway is activated in response to many stress signals, allowing p53 to coordinate programmes that contribute to tumor suppression (Garritano et al. 2013). Activated p53 executes multiple functions, ranging from repair of minor damage to cessation of cell-cycle progression, induction of replicative senescence, and apoptosis (Raver-Shapira et al. 2007). Loss of p53 function, through mutations in p53 itself or alterations in pathways signaling to p53, is a common feature in most of human cancers (He et al. 2007). More than 75% of the mutations result in the expression of a p53 protein that generally has lost the wild-type function (Chang et al. 2007). In addition, mutant p53 also acquires oncogenic functions that are entirely independent of wild-type p53 (Muller and Vousden 2013). As a transcription factor, p53 transactivates or represses many protein-encoding genes (Wang and Sun 2010). Recent reports have shown that p53 is also able to regulate the expression of miRNAs and to promote the maturation of specific miRNAs, both of which contribute to the function of p53 in tumor suppression (Xi et al. 2006). On the contrary, miRNAs can negatively regulate p53 protein levels and function through direct repression of p53 expression, or positively regulate p53 activity and function through the repression of different negative regulators of p53 (Feng et al. 2011). Many miRNAs are up- or down-regulated, depending on the existence of p53, what demonstrates that miRNAs are important components in the p53 network (Shin et al. 2009). The aim of this study was to address 3 issues: 1. Identification and characterization of the mutational status of p53 in colorectal cancer and the co-existence of gene mutations in BRAF and K-ras. 2. Correlation between the mutation status and the immunohistochemical expression pattern of p53 using two different p53 antibodies. 3. Identification and characterization of miRNAs that are regulated by p53, having special focus on miR-34a. 17 Materials and methods 3. Materials and methods 3.1. Samples The samples were obtained from the Institute of Pathology, University Hospital Erlangen. They consisted in formalin-fixed paraffin-embedded (FFPE) tissue specimens and hematoxylin and eosin (H&E)-stained sections from 55 patients with histologically proven colorectal adenocarcinoma, who had been resected in 2012 and 2013. From the original 58 cases, 3 were not included in the study because no tumor was present at the slides. All the sections had a thickness of 5 µm. Material was obtained by recto-sigma resection, hemicolectomy or other form of colon resection. Tumor localization within the colon was defined as proximal (cecum through transverse colon), distal (splenic flexure, descending, and sigmoid colon) or rectal (rectosigmoid junction and rectum). Table 1. Patient clinical characteristics. Characteristic No of patients Age (median (range)) TNM stage I II III IV Tumor localization Proximal Distal Rectal Tumor differentiation Well Moderate Poor Female 25 69 (35-91) Male 30 70 (46-89) Total 55 70 (35-91) 5 7 11 2 6 13 11 0 11 20 22 2 13 0 12 5 3 22 18 3 34 0 16 9 2 20 8 2 36 17 18 3.2. Equipment Table 2. Equipment. Product C1000™ Thermal cycler, CFX96™ Real Time System Freezer Company BioRad, Munich, Germany Liebherr, Bulle, Switzerland; AEG, Frankfurt Main, Germany Fridges Liebherr, Bulle, Switzerland; AEG, Frankfurt Main, Germany HERAEUS Megafuge 16 R Thermo Scientific, Erlangen, Germany Ice Machine AF 200 Scotsman, Milan, Italy Microcentrifuge Galaxy MiniStar VWR, Darstadt, Germany HERAEUS Pico17 Centrifuge Thermo Scientific, Erlangen, Germany NanoDrop™ ND-1000 Spectrophotometer Peqlab Biotechnologie GmbH, Erlangen, Germany Pippetes (Eppendorf research 2,5; 10; 100; Eppendorf, Hamburg, Germany 200; 1000 µl) Thermomixer comfort 1.5 ml Eppendorf, Hamburg, Germany Thermomixer comfort MTP Eppendorf, Hamburg, Germany Vortex-Genie 2 Scientific Industries, New York, USA Savant DANN 120 SpeedVac® Thermo Scientific, Erlangen, Germany Concentrator PCR-Chamber Bäro Technology, Leichlingen, Germany VWR Thermocycler VWR, Darstadt, Germany SensoQuest labcycler SensoQuest, Göttingen, Germany QIAxcel BioCalculator QIAGEN, Hilden, Germany PyroMark™ Q24 Vacuum Prep QIAGEN, Hilden, Germany Workstation PyroMark Q24 QIAGEN, Hilden, Germany 3.3. Materials Table 3. List of chemicals. Product TE buffer Ethanol ≥95,5% Xylol ROTIPURAN® ≥99% Roticlear® LiChrosolv® Water PyroMark Annealing Buffer PyroMark Binding Buffer Streptavidin Sepharose™ High Performance Company Illumina, San Diego, USA Roth, Karlsruhe, Germany Roth, Karlsruhe, Germany Roth, Karlsruhe, Germany Merk, Darmstadt, Germany Qiagen, Hilden, Germany Qiagen, Hilden, Germany GE Healthcare, Freiburg, Germany Catalog number MTED970 5054.4 4436.1 A538.1 115333 979009 979006 17-5113-01 19 Table 4. List of consumables. Product 0,5 ml Eppendorf safe-lock reaction tube 1.0 ml Eppendorf safe-lock reaction tube 2.0 ml Eppendorf safe-lock reaction tube 1.5 ml Eppendorf DNA LoBind tube Filtertips 0.1-10 µL Filtertips 0-20 µL Filtertips 0-100 µL Filtertips 0-200 µL Filtertips 100-1000 µL Gloves (SensiCare Ice, powder free) Individual PCR tubes™ Low Tubes Strip; CLR Multiplate™ PCR plates 96well, clear Microseal® `B´ seal 24 PCR platte Feather disposable scalpel No. 11 Company Eppendorf, Hamburg, Germany Eppendorf, Hamburg, Germany Eppendorf, Hamburg, Germany Eppendorf, Hamburg, Germany Nerbe plus, Winsel/Luhe, Germany Nerbe plus, Winsel/Luhe, Germany Nerbe plus, Winsel/Luhe, Germany Nerbe plus, Winsel/Luhe, Germany Nerbe plus, Winsel/Luhe, Germany Medline, Kleve, Germany Catalog number 22363611 Bio-Rad Laboratories, Inc., Hercules, USA Bio-Rad Laboratories, Inc., Hercules, USA Bio-Rad Laboratories, Inc., Hercules, USA Brand, Wertheim, Germany pfm medical, Köln, Germany TLS0801 22363204 22363352 22431021 07-613-7300 07-622-7300 07-642-7300 07-662-7300 07-693-7300 486801 MLL9601 MSB1001 781411 200130011 Table 5. List of commercial kits. Product NucleoSpin® Tissue Kit MinElute™ PCR Purification Kit Qiagen Multiplex PCR Kit PyroMark Gold Q96 Reagent Kit RecoverAll™ Total Nucleic Acid Isolation Kit miScript II RT Kit Company Macherey- Nagel, Düren, Germany Qiagen, Hilden, Germany Catalog number 740.952.250 28006 Qiagen, Hilden, Germany Qiagen, Hilden, Germany 206143 972804 Ambion, Darmstadt, Germany Qiagen, Hilden, Germany AM1975 218161 20 miScript SYBR Green PCR Kit ZytoChem-Plus AP PolymerKit Qiagen, Hilden, Germany 218075 Zytomed, Berlin, Germany POLAP-100 Table 6. List of antibodies. Product BD PharmigenTM purified Mouse Anti-p53 clone, Pab 1801 Monoclonal Mouse Anti-Human p53 Protein Clone DO-7 Company BD Biosciences, Heidelberg, Germany Dako Denmark A/S, Glostrup, Denmark Catalog number 554169 M7001 Table 7. List of primers. Product P53 4A s_exon_4 P53 4B as_exon_4 P53-exon5 Fwd neu P53-exon5 Rev neu P53 6U1 s_exon_6 P53 6L1 as_exon_6 P53 in 6F s_exon_7 P53 7D as_exon_7 P53 8A s_exon_8 P53 8B as_exon_8 Pyro_BRAF_neu F Pyro _BRAF_neu R Pyro_BRAF-Seq Pyro Kras_ s_D0456 Pyro Kras_as_D0457 Sequence 5'-ATC TAC AGT CCC CCT TGC CG-3' 5'-GCA ACT GAC CGT GCA AGT CA-3' 5'-CTG CCG TGT TCC AGT TGC TT-3' 5'-AGC TGC TCA CCA TCG CTA TCT-3' 5'-ACC ATG AGC GCT GCT CAG AT-3' 5'-AGT TGC AAA CCA GAC CTC AGG C-3' 5'-CCT CAT CTT GGG CCT GTG TTA TC-3' 5'-GAG GCT GGG GCA CAG CAG GCC AGT G-3' 5'-ACT GCC TCT TGC TTC TCT TT-3' 5'-AAG TGA ATC TGA GGC ATA AC-3' 5'-TGA AGA CCT CAC AGT AAA AAT AGG-3' 5'-Biotin-AAA ATG GAT CCA GAC AAC TGT TC-3' 5'-GGT GAT TTT GGT CTA GC-3' 5'-GGC CTG CTG AAA ATG ACT G-3' 5'-Biotin-AGC TGT ATC GTC AAG GCA CTC T-3' Company Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany Metabion, Martinsried, Germany 21 Pyro Kras_Seq_ D0456 5'-CTT GTG GTA GTT GGA GC-3' Metabion, Martinsried, Germany 3.4. Methods 3.4.1. DNA isolation from paraffin embedded sections Deparaffination and xylene removing The tissue corresponding to the area of interest in the slide was removed by using a scalpel and put it in a tube containing 1,3 ml Roticlear. The tube was incubated at 37°C for 30 min and then centrifugated for 10 min at 13.300 rpm. The supernatant was removed and discharged. 1,3 ml ethanol 100% was added. The tube was centrifugated for 3 min at 13,300 rpm and the supernatant removed. Another 1,3 ml ethanol 100% were added. The tube was centrifugated during additional 3 min and the supernatant was carefully removed. The pellet was dryed in a Speed Vac (drying rate low) for 1,5 min. Cell lysis and preparation of genomic DNA The experiments were performed using the NucleoSpin® Tissue Kit (Macherey-Nagel). During this experiment, it was firstly performed lysis of the sample, releasing the DNA from the tissue. The DNA was bounded to the silica membrane under high salt/ethanolic conditions. The contaminants were washed away keeping the DNA bounded to the membrane and in the end, the DNA was eluted in low-salt buffer and was ready to be used for downstream applications. 200 uL T1 Lysisbuffer was added to the pellet and afterwards, 10 uL Proteinase K. The tube was incubated at 55°C for 18 hours. When the lysis was not complete after this incubation time, additional 5 uL Proteinase K were added and the tube was incubated at the same temperature during 2 hours. 210 uL B3 Lysisbuffer were added and incubated at 70°C for 10 min at 300 rpm. 220 uL ethanol 100% were added. The sample was transferred to the NucleoSpin® Tissue Column and centrifugated for 2 min at 11,000 x g. The eluate was discarded and 550 uL BW wash buffer was added to the column, which was centrifugated for another 2 min at 11,000 x g and the eluate 22 discarded. 600 uL BW wash buffer were incorporated to the column. A centrifugation of 2 min at 11,000 x g was performed and the eluate discarded. In order to achieve a better drying, the sample was centrifuged again for 2 min at 11,000 x g. The column was put in a new fresh tube and 40 uL hot BE elution buffer (70°C) were added to the column and incubated for 3 min at room temperature. The sample was centrifugated 2 min at 11,000 x g. Another 40 uL hot BE elution buffer (70°C) were added to the column, followed by an incubation time of 3 min and a centrifugation of 2 min at 11,000 x g. The genomic DNA concentration and purity were measured using a NanoDrop spectrophotometer. The obtained DNA was stored at 4°C. DNA isolation from cultured cells The experiment were also performed using the NucleoSpin® Tissue Kit (Macherey-Nagel). The cells (up to 107) were resuspended in 200 uL T1 Lysisbuffer. 15 uL Proteinase K were added and incubated at 56°C for 30 min at 350 rpm. In order to obtain a better suspension, another 5 uL Proteinase K were added and 30 minutes incubation at 56°C at 350 rpm performed. 210 uL B3 Lysisbuffer were added and incubated at 70°C for 20 min at 300 rpm. 220 uL ethanol 100% were added. The sample was transferred to the NucleoSpin® column and centrifuged for 2 min at 11,000 x g. The eluate was discarded and 550 uL BW wash buffer was added to the column, which was centrifugated for another 2 min at 11,000 x g and the eluate discarded. 600 uL BW wash buffer were incorporated to the column. A centrifugation of 2 min at 11,000 x g was performed and the eluate discarded. In order to achieve a better drying, the sample was centrifugated again for 2 min at 11,000 x g. The column was put in a new collection tube and 50 uL hot BE elution buffer (70°C) were added to the column and incubated for 3 min at room temperature. The sample was centrifugated 2 min at 11,000 x g. Another 50 uL hot BE elution buffer (70°C) were added to the column, followed by an incubation time of 3 min and a centrifugation of 2 min at 11,000 x g. The DNA concentration was measured by a NanoDrop and it was afterwards stored at 4°C. 23 3.4.2. Mutational analysis of p53 Polymerase Chain Reaction (PCR) amplification PCR primer pairs (sense and antisense) were designed for the flanking site of exons 4, 5, 6, 7 and 8 of the p53 gene, in which point mutations have been reported frequently. The QIAGEN Multiplex PCR Kit (Qiagen) was used to make the experiment. PCR amplification for each exon was performed in a final volume of 25 uL containing 1 uL of template DNA and 24 uL of the bellow described Master Mix. The Master Mix: Components RNase-free water- 10,1 Qiagen Multiplex PCR Master Mix 2,0 Primer Sense 10 uM Primer Antisense 10 uM- 0,7 Volume/Reaction in µL 10,1 12,5 0,7 0,7 PCR reaction was made in a VWR® Thermal Cycler and the used programs are the following: For p53 exon 4 Denaturation Denaturation Annealing Elongation Elongation Store at 95°C 95°C 58°C 72°C 72°C 10°C 15 min 20 sec 60 sec 60 sec 7 min ∞ 95°C 95°C 62°C 72°C 72°C 10°C 15 min 20 sec 60 sec 60 sec 7 min ∞ 35 cycles For p53 exon 5 Denaturation Denaturation Annealing Elongation Elongation Store at 35 cycles For p53 exon 6 Touchdown 24 Denaturation Denaturation Annealing Elongation Denaturation Annealing Elongation Denaturation Annealing Elongation Denaturation Annealing Elongation Denaturation Annealing Elongation Elongation Store at 95°C 95°C 66°C 72°C 95°C 64°C 72°C 95°C 62°C 72°C 95°C 60°C 72°C 95°C 58°C 72°C 72°C 10°C 15 min 20 sec 60 sec 60 sec 20 sec 60 sec 60 sec 20 sec 60 sec 60 sec 20 sec 60 sec 60 sec 20 sec 60 sec 60 sec 7 min ∞ 95°C 95°C 64°C 72°C 72°C 10°C 15 min 20 sec 60 sec 60 sec 7 min ∞ 95°C 95°C 58°C 72°C 72°C 10°C 15 min 20 sec 60 sec 60 sec 7 min ∞ 2 cycles 2 cycles 2 cycles 2 cycles 30 cycles For p53 exon 7 Denaturation Denaturation Annealing Elongation Elongation Store at 35 cycles For p53 exon 8 Denaturation Denaturation Annealing Elongation Elongation Store at 35 cycles The success of the PCR was verified by capillary electrophoresis using the QIAxcel system and QIAxcel BioCalculator Software (Qiagen). DNA purification The MinElute™ PCR Purification Kit (Qiagen) was used to purify doublestranded DNA fragments from PCR reactions resulting in high end 25 concentrations of DNA. Fragments from 70 bp to 4 kb were purified from primers, nucleotides, polymerases and salts using MinElute spin columns in a microcentrifuge. 25 uL of PCR product were used and treated following the instructions of the MinElute Handbook, page 19-20 (03/2008). The DNA concentration was measured by a NanoDrop. DNA sequencing Sanger sequencing was performed by to different companies: Seqlab and Source BioScience. The instructions of both laboratories were precisely followed in order to ship the purified PCR samples and primers in the correct way. 3.4.3. Mutational analysis of K-ras and BRAF Polymerase Chain Reaction (PCR) amplification The experiments were done using the QIAGEN Multiplex PCR Kit (Qiagen) in a final volume of 25 uL, where 20uL were Master Mix and 5 uL DNA. Negative and positive controls were represented by HT-29 and HCT-116 samples respectively, when analyzing K-ras mutations. For BRAF, HT-29 functioned as the positive control and HCT-116 as the negative one. The Master Mix: Components Volume/Reaction in µL RNase-free water- 10,1 Qiagen Multiplex PCR Master Mix 2,0 Primer Sense 10 uM Primer Antisense 10 uM- 0,7 6,1 12,5 0,7 0,7 Cycling was performed in a VWR® Thermal Cycler as follows: For K-ras Denaturation Denaturation Annealing Elongation Denaturation Annealing 95°C 94°C 60°C 72°C 72°C 4°C 15 min 60 sec 60 sec 60 sec 10 min ∞ 35 cycles 26 For BRAF Denaturation Denaturation Annealing Elongation Denaturation Annealing 95°C 95°C 61°C 72°C 72°C 4°C 15 min 30 sec 30 sec 30 sec 5 min ∞ 42 cycles Successful amplification was verified by capillary electrophoresis using the QIAxcel system and QIAxcel BioCalculator Software (Qiagen). Pyrosequencing Single-stranded DNA templates for pyrosequencing were obtained with the assistance of the PyroMark Q24 Vacuum Prep Workstation (Qiagen) according to manufacturer´s instructions. Briefly, 10 uL of the PCR product were immobilized on streptavidin-coated Sepharose high-performance beads (GE Healthcare) and processed to obtain single-stranded DNA. This DNA template was then incubated with 25 uL sequencing primer mix on the heat block at 80°C for 2 minutes. Pyrosequencing was performed on a PyroMark Q24 system using software version 2.0.6, and PyroMark Gold Q96 Reagent Kit (Qiagen) following the manufacturer´s guidelines. 3.4.4. RNA isolation from paraffin embedded sections To extract FFPE-RNA, the RecoverAll™ Total Nucleic Acid Isolation Kit (Ambion) was used following the RecoverAll™ Total Nucleic Acid Isolation protocol, page 8-14 (02/2011). The samples were deparaffinized using a series of xylene and ethanol washes. Next, they were subjected to an extensive protease digestion (200 uL Digestion Buffer per sample was added) with an incubation time of 60 min at 50°C and then 15 min at 80°C. RNA was then purified using a rapid glass-filter method, and was eluted into Elution Solution. The RNA was measured by a NanoDrop and stored at -20°C. 3.4.5. Reverse transcription RNA was converted with the miScript II RT Kit (Qiagen) according to the miScript PCR System Handbook, page 19-20 (10/2011). The 5x miScript 27 HiSpec Buffer was used (only mature miRNA quantification was executed). 0,25 ug RNA were used and filled up with nuclease free water up to 12 uL. From the below described Master Mix, 8 uL were added to the diluted RNA. The samples were mixed, briefly centrifugated and incubated at 37°C for 60 min. To inactivate the reverse transcriptase the samples were incubated at 95°C for 5 min. The obtained cDNA was stored at -20°C. The Master Mix: Components 5x miScript Buffer 10x miScript Nucleic Mix miScript Reverse Transcriptase Mix Volume/Reaction in µL 4 2 2 3.4.6. Real-Time Polymerase Chain Reaction (qRT-PCR) The experiments were done according to the miScript PCR System Handbook, page 22-24 (10/2011) using the miScript SYBR® Green PCR Kit (Qiagen). The cDNA concentration was measured and afterwards diluted to a 3ng/uL concentration by adding RNase-free water. As housekeeping gene RNU6 was used. Triplicates of each sample were made. The Master Mix was added to the cDNA (see below). Triplicates “not template” controls were run. The plated was sealed and centrifuged for 1 min at 1000g at 23°C. Components 2x QuantiTect SYBR Green PCR Master Mix 10x miScript Universal Primer 10x miScript Primer Assay RNase-free water cDNA Volume/Reaction in µL 12,5 2,5 2,5 6,5 1 The experiments were run on the C1000™ Thermal Cycler CFX96 realtime PCR system (Bio-Rad). The following program was used: PCR initial activation step Denaturation Annealing 95°C 94°C 55°C 15 min 15 sec 30 sec 40 cycles 28 Extension 70°C 30 sec Melting curve: 65°C to 95°C. Increment 0,5°C. Slow Ramp Rate: 1°C per sec. The obtained data was analyzed with the help of the CFX Manager™ software from Bio-Rad. The melting curve was observed and the fold induction was calculated. The used formula is the following: 2(Cth / Cte) / 2(Cch / Cce) Cth = threshold cycle of the housekeeping gene Cte = threshold cycle of the experimental gene 3.4.7. Immunohistochemical analysis of p53 (IHC) Immunohistochemistry was executed using 2 different p53 antibodies: Monoclonal Mouse Anti-human p53 Protein Clone DO-7 from DAKO and BD PharmigenTM purified Mouse Anti-p53 clone, PAb 1801. Staining with the second p53 antibody was performed on FFPE representative tumor tissue from all 55 carcinomas using the ZytoChem-Plus AP Polymer-Kit from Zytomed. Briefly, slides were deparaffinised, rehydratet and heated in EDTA buffer. Background staining caused by unspecific binding of the primary antibody to the secondary antibody in the AP polymer was minimized by incubation of the slides with a protein blocking solution. The sections were afterwards incubated with a 1:2000 dilution of the p53 antibody at room temperature overnight. After washing, enhancement reagent was applied and incubated. A second washing was followed by the application of the APpolymer. After incubation and washing, chromogenic substrate was added in order to start the enzymatic reaction of the alkaline phosphatase which leads to colour precipitation where the primary antibody is bound. 29 Results 4. Results This project can be divided in 2 principal parts. Basically, in the first part, mutations in p53 protein, in K-ras and BRAF were analyzed. In the second part, miRNAs induced by P53 were evaluated. The statistical analysis was performed using IBM SPSS Statistics 19v (SPSS Inc., Chicago, IL, USA). 4.1. P53 mutations From a total of 55 cases, 23 presented mutations in exons 4,5,6,7 or 8 (41,8%). mutated 41,8% wt 58,2% Figure 4. P53 mutational spectrum in this project. 3 mutations were found in exon 4 (13%), 6 in exon 5 (26,1%), 4 in exon 6 (17,4%), 6 in exon 7 (26,1%), and 4 in exon 8 (17,4%). 30 exon 8 17,4% exon 4 13% exon 5 26,1% exon 7 26,1% exon 6 17,4% Figure 5. Distribution of the mutations. There were 18 missense mutations, 3 frameshift mutations and 2 nonsense mutations (stop mutations). 7 mutations occurred at known hot-spot codons (1 at codon 175, 2 at codon 245, 3 at codon 248 and 1 at codon 273). One sample presented a double mutation (R273H and R213stop) and was obtained from a 46 year old male patient, who had a moderately differentiated sigma adenocarcinoma, TNM stage II. The location and the frequency of p53 are reported in Table 1. Representative DNA sequences are shown in Figure 2. Table 8. Detected p53 mutations. Nr. of Mutations Exon 1 4 1 4 1 4 3 5 1 5 1 5 1 5 1 6 1 6 Detail P89L R110L A83Frameshift A159V G154S R175H C176S R196stop N200K 31 1 1 1 2 1 2 1 1 1 1 A 6 6 7 7 7 7 8 8 8 8 Y205S R213stop S240R G245S R248Q R248W L264Frameshift G266E R273Frameshift G281Y B 32 C Figure 6. Types of p53 mutations. A-Example of missense mutation. Exon 5 codon 175, sense sequencing, CGC (Arg) to CAC (His). B- Example of stop mutation. Exon 6 codon 213, sense sequencing, CGA (Arg) to TGA (Stop). C- Example of frameshift mutation. Exon 4 codon 83, sense sequencing, 11 bp deletion. In the box below, representative parts of the normal and mutated sequences are described. Normal sequence Mutated sequence CCG GCG GCC CCT GCA CCA GCC CCG ACC AGC CCC CTC CTG GCC No significant associations between P53 mutations and clinicopathological features like age, sex, TNM stage, tumor localization and tumor differentiation were observed. 32 4.2. P53 polymorphisms The genotype distribution of p53 codon 72 polymorphisms showed 65,4% (36 cases), 27,3% (15 cases) and 7,3% (4 cases) for the Arg/Arg (R), Arg/Pro (RP) and Pro/Pro (P) genotypes respectively. RP 27,3% R 65,4% P 7,3% Figure 7. Distribution of p53 codon 72 polymorphisms. A B C Figure 8. 3 different genotypes of p53 codon 72 polymorphisms. A- Arg/Arg (R) genotype. Sense sequencing, CGC (Arg)/CGC (Arg); B- Arg/Pro (RP) genotype. 33 Antisense sequencing, CGC (Arg)/CCC (Pro); C- Pro/Pro (P) genotype. Antisense sequencing, CCC (Pro)/CCC (Pro). 4.3. Analysis of p53 mutations in CRC cell lines In this project, the p53 status of 5 CRC cell lines used at the lab was tested by DNA sequencing. All of them showed the expected mutation for each cell line. Table 9. P53 mutations in 5 CRC cell lines. Mutation type Point mutation Point mutation Point mutation Point mutation Point mutation Cell line Location Exon 6 codon 204 Exon 7 codon SW837 248 Exon 7 codon DLD1 241 Exon 8 codon SW480 273 Exon 8 codon HT29 273 CACO2 Mutation effect Glu to Stop Arg to Trp Ser to Phe Arg to His Arg to His 34 A B C D E Figure 9. P53 mutations in CRC cell lines. A- CACO2 cell line, sense sequencing. Exon 6 codon 204, GAG (Glu) to TAG (Stop). B- SW837 cell line, antisense sequencing. Exon 7 codon 248, CGG (Arg) to TGG (Trp). C- DLD1 cell line, antisense sequencing. Exon 7 codon 241, TCC (Ser) to TTC (Phe). D- SW480 cell line, antisense sequencing. Exon 8 codon 273, CGT (Arg) to CAT (His). E- HT29 cell line, antisense sequencing. Exon 8 codon 273, CGT (Arg) to CAT (His). 4.4. K-ras mutations The results revealed that 16 cases had K-ras mutations (29,1%). There were 11 cases of codon 12 mutation (68,8%) and 5 cases of codon 13 mutation (31,3%). 35 mutated 29,1% wt 70,9% Figure 10. Percentage of K-ras mutations. The most common mutation was glycine to aspartate on codon 12 (G12D) (31,3%). Other founded mutations of codon 12 were glycine to valine (G12V) (18,8%), glycine to serine (G12S) (12,5%) and glycine to cysteine (G12C) (6,3%). On codon 13, only glycine to aspartate mutations were detected (G13D) (31,3%). G13D 31,3% G12C 6,3% G12S 12,5% G12D 31,3% G12V 18,8% Figure 11. Distribution of K-ras mutations. 36 Examples of K-ras wt and different types of mutations. Figure 12. K-ras wt, GGT (Gly). Figure 13. G12D K-ras mutation, GGT (Gly)/GAT (Asp). 37 Figure 14. G12V K-ras mutation, GGT (Gly)/GTT (Val). Figure 15. G12S K-ras mutation, GTT (Gly)/AGT (Ser). Figure 16. G12C K-ras mutation, GGT (Gly)/TGT (Cys). 38 Figure 17. G13D K-ras mutation, GGC (Gly)/GAC (Asp). K-ras mutations were not significantly associated with clinicopathological factors like age, sex, TNM stage, tumor localization and tumor differentiation. 4.5. BRAF mutations 8 BRAF mutations have been identified (14,5%), being all of them a substitution of glutamic acid for valine at amino acid 600 (V600E). mutated 14,5% wt 85,5% Figure 18. BRAF mutations. 39 Examples of BRAF wt and mutated. Figure 19. BRAF wt, GTG (Val). Figure 20. V600E BRAF mutation, GTG (Val)/GAG (Glu). The BRAF mutation status was correlated with patients’ clinicopathological data using the Chi-squared test. P <0,05 was considered to be statistically significant. Significant associations were found between BRAF mutations and sex (P=0,022) and tumor localization (P=0,006). 7 from the 8 patients presenting BRAF mutations were women (87,5%). The majority of the BRAF mutations (87,5%) had proximal localization and 12,5% had rectal localization. No one presented distal localization. 40 BRAF mutated samples corresponded in most of the cases to old patients (55, 59, 68, 73, 74, 88, 89 and 90 years old). No correlation was found between BRAF mutations and TNM stage and tumor grade. 4.6. Associations with p53 gene mutations From the total 55 cases, P53 mutation associated with K-ras mutation was present in 3 patients (5,5%) distributed in exon 4, 7 and 8, and with BRAF also in 3 cases (5,5%) located in exon 5, 6 and 7. K-ras and BRAF were found simultaneously mutated in 1 case (1,8%). Interestingly, this patient presented also a silent mutation in exon 8 of p53 (L264L). Simultaneous association between p53 mutations and p53 R72P polymorphisms were seen in 16 cases (44,4%) presenting R72, 4 cases (26,7%) with R72P and 3 cases (75%) with P72. The Arg/Arg homozygous genotype was associated with K-ras mutations in 10 cases (27,8%) and with BRAF mutations in 4 (11,1%). The Pro/Pro homozygous was related with K-ras mutations in 1 case (25%) and with BRAF mutations in 2 (50%). Finally, the p53 Pro/Arg heterozygous genotype was found 5 times (33,3%) in combination with K-ras and 2 times with BRAF (13,3%). 4.7. Immunohistochemical staining patterns of p53 Immunochemistry was performed using 2 different p53 antibodies: Monoclonal Mouse Anti-human p53 Protein Clone DO-7 from DAKO and, BD PharmigenTM purified Mouse Anti-p53 clone, PAb 1801. With the first antibody (DAKO), positive p53 staining patterns were seen in 60% of the mutated p53 samples and in 58,3% of the wt p53 specimens. With the second antibody (BD PharmigenTM), positive p53 immunostaining was observed in 18 from the 23 samples presenting p53 mutations (78,3%). Only 5 mutated cases (21,7%) presented negative staining, corresponding to 1 frameshift mutations in exon 4, 2 frameshift mutations in exon 8, 1 stop 41 mutation in exon 6 and a D281Y mutation in exon 8. In the wild type group, negative p53 staining was seen in 71,9% of the samples. The results presented from this point on, refer to the second p53 antibody. Figure 21. Immunohistochemical staining of p53 non-mutated (wt) and mutated samples. Localization and details of the mutation in mutated samples with negative staining pattern: sample A (exon 8 D281Y); sample B (exon 6 R196 stop); sample C (exon 4 frameshift); sample D (exon 8 frameshift); sample E (exon 8 frameshift). The association between p53 mutations and the immunohistochemical p53 protein expression was analysed performing the T-test. P <0,05 was considered to be statistically significant. A significant correlation between them was found (P=0,001). 42 Figure 22. Relationship between p53 immunohistochemical expression in wt and p53 mutated samples (p53 wt samples: (,00), p53 mutated samples: (1,00)). The analysis of the grade of expression of p53 related to the mutated exon revealed that the highest percentage of positive tumor cell nuclei were found in samples that harboured mutations in exon 5 and 7. 43 Figure 23. Relationship between p53 immunostaining and exon mutations (wt: (,00), mutated exons: (4,00, 5,00, 6,00, 7,00 and 8,00). 44 Figure 24. P53 staining patterns. Positive (A and B), and negative (C and D) immunohistochemical p53 staining patterns. Pictures A (magnification x50) and B (magnification x400) correspond to a sample harbouring a G245S mutation in exon 7 of p53. The grade of immunostaining was estimated to be 90%. Pictures C (magnification x50) and D (magnification x400) represent a sample with wt p53. The staining grade is 0 (there are no p53 positive tumor nuclei). In all the positive stainings the intensity was high, distributed between 54 cases (98,2%) with strong staining (3+) and only one case (1,8%) of moderate staining (2+). No correlation was found between p53 immunohistochemistry and Kras/BRAF mutations. In the same way, no correlation has been seen between p53 IHC and the patients’ clinical data including sex, TNM stage, tumor localization and tumor differentiation. 4.8. MiRNAs 4.8.1. MiR-34a The levels of miR-34a in 10 histologically normal and 10 colorectal cancer samples with p53 wt, as determined by qRT-PCR revealed that miR-34a was 45 significantly up regulated in the colon cancer group. Only 1 sample did not present up-regulation. Figure 25. Comparison of miR-34a levels in no tumor and tumor p53 wt samples. In addition, miR-34a levels were analyzed comparing 2 groups of 15 samples each: one composed by histological normal (no tumor) tissues, and the other one represented by their counterpart tumors harbouring mutations in p53 protein. Many of the samples in the p53 mutated tumor group presented downregulation of miR-34a or the same expression level as in the no tumor group, what leads to the conclusion that in the cancer group the regulation is lost. 46 Figure 26. Comparison of miR-34a levels in no tumor and tumor p53 mutated samples. The expression of miR-34a in the whole set of tumor samples was evaluated by dividing them in wt p53 and mutated p53. The comparison showed no significant differences in the expression level of miR-34a between the 2 groups. Figure 27. Comparison of miR-34a levels in wt and mutated p53 tumor samples. 47 4.8.1.1. MiR-34a gene mutation associations The correlation between the expression of miR-34a and the p53 codon 72 polymorphisms was analyzed in the 55 samples, and there was found that the highest expression level of the miRNA was present in association with the Arg/Arg genotype. No association was observed between miR-34a and K-ras/BRAF mutations. No relationship was found between miR-34a and the immunohistochemical staining patterns of p53, as well as no correlation was observed between miR34a and the clinical data. 4.8.2. MiR-34b and miR-34c MiR-34b and miR-34c were also tested using qRT-PCR but no expression was observed. 4.8.3. MiR-192, miR-215 and miR-200c The samples were amplifiable but no differences in the expression of miR-192, miR-215 and miR-200c between samples with wt p53 and mutated p53 were found. 48 Discussion 5. Discussion 5.1. Role of p53 in CRC In somatic cells, p53 has a fundamental role in translating stress signals into classical processes such as apoptosis, cell cycle arrest, DNA repair and senescense, contributing to its main role as the “guardian of the genome” (Lane 1992; Aloni-Grinstein et al. 2014). P53 eliminates and inhibits the proliferation of abnormal cells, preventing tumor development and progression (Kim et al. 2009; Feng et al. 2011). Mutations or deletions in p53 are seen in approximately half of all human cancers. (Touqan et al. 2013). In this study, one of the principal aims has been to analyze the incidence of mutations of p53 protein in patients with colorectal cancer. In this connection, 41,8% of the studied tumors exhibited p53 mutations. This value is in concordance with the average percentage presented in the literature, described to be between 40 and 50 % (Naccarati et al. 2012). Research showed that p53 mutations are distributed in all coding exons of the gene, with a strong predominance in exons 4, 5, 6, 7, 8, and 9. About 30% of the mutations in these exons fall within 6 hotspot codons (175, 245,248, 249,273, and 282) (Rivlin et al. 2011). The general distribution of p53 mutational hotspots in exons 4-8 in this study showed the most common hotspots at codons 159 (13%), 248 (13%) and 245 (8,7%). The high frequency of mutations in codons 248 and 245 is comparable to the distribution pattern of p53 mutation hotspots in CRC in the International Agency for Research on Cancer TP53 mutation database (IARC TP53, version R17, November 2013). 3 mutations were present at codon 159. This codon is not described as a hotspot codon in the up-to-date published literature. Among the detected p53 mutations, 2 fall within other known hot-spots: 1 in codon 175 and 1 in codon 273 (Petitjean et al. 2007). Unlike most tumor suppressor genes, which are basically inactivated as a result of deletion or truncation, most of cancer-associated mutations in p53 are missense mutations, single base-pair substitutions that result in the translation of a different amino acid (Freed-Pastor and Prives 2012). Concordantly with 49 this, the majority of the p53 mutations identified in this work were missense (78,3%) but also 3 frameshift (13%) and 2 nonsense mutations (8,7%) were observed. While wild-type p53 under normal conditions is a very short-lived protein, missense mutations lead to the production of a protein with a prolonged half-life (Strano et al. 2007). Many of these stable mutant forms of p53 can exert a dominant-negative effect on the remaining wild-type allele, serving to annul the ability of wild-type p53 to inhibit cellular transformation. While inactivating missense mutations in p53 may be selected for during tumor progression due to their ability to act as dominant-negative inhibitors of wildtype p53, there is also strong evidence that mutant p53 can exert oncogenic or gain-of-function (GOF) activity independent of its effects on wild-type p53 (Freed-Pastor and Prives 2012). Mutp53 GOF is expressed through several biological manifestations. In this regard, mutp53 has the ability to disrupt mechanisms that maintain cellular genome integrity, for example, mutated p53 can disrupt normal spindle checkpoint control, leading to accumulation of cells with polyploid genomes (Oren and Rotter 2010). Mutp53 has also the ability to confer on cells an elevated resistance to a variety of pro-apoptotic signals, which may not only accelerate tumor progression but also hinder the response of cancer patients to anticancer therapy (Kim et al. 2009). Increased tumor aggressiveness and higher metastatic potential are also hallmarks of mutp53 GOF. These advanced stages in tumor progression are characterized by acquisition of an ability of the cancer cells to invade adjacent tissue, migrate to distant sites, and seed metastases (Kang et al. 2013). P53 missense mutations display different patterns and strengths of GOF activity in human cancers. Previous research have demonstrated that mice carrying mutations equivalent to human R175H and R273H showed no difference in survival time as compared with null mutation, although a broader tumor spectrum was observed (Lang et al. 2004; Olive et al. 2004). Recently, Xu et al. demonstrated that p53 mutations on R248 and R282 could regulate the expression of CYP3A4, which is one of the most important enzymes involved in the metabolism of chemotherapeutic drugs. Cancer cells bearing p53 R248/R282 mutations displayed resistance to multiple CYP3A4-metabolized antineoplastic drugs. These findings show that R248/R282 mutations may lead to chemoresistance, suggesting that certain types of p53 mutations have 50 unequal prognostic significance in human cancers (Xu et al. 2014). Some CRC studies have reported that somatic mutations in p53 are associated with poor prognosis, while other studies failed to show such a relationship (Naccarati et al. 2012). Until today, only mutation in the G245 hotspot and mutations in proximal tumors are related to significantly worse survival (Samowitz et al. 2002). In this project, 3 mutations of codon 248 and 2 mutation of codon 245 were found. The 3 patients carrying mutations of codon 248 were old women (70, 73 and 79 year old) with TNM stage III. The first and second woman had a proximal tumor and the third one, a distal tumor. The tumor differentiation was described as moderate, poor and moderate respectively. The 2 patients with codon 245 mutations were a 86 year old woman and a 45 year old man, with distal, moderately differentiated tumors. The TNM stage was II and III respectively. 5.2. The different genotypes of p53 codon 72 polymorphisms have discrepancies in their biochemical and biological properties P53 polymorphisms at codon 72 (Arg72Pro) have been associated with increased risk for many human cancers (Whibley et al. 2009). This polymorphism produces 2 different proteins because of a single base change modifying CGC to CCC in exon 4 of the p53 gene, altering amino acid residue 72 from Arg to Pro (Schneider-Stock et al. 2004). In this study, the genotype distribution of p53 codon 72 polymorphisms showed 65,4%, 27,3% and 7,3% for the Arg/Arg, Arg/Pro and Pro/Pro genotypes respectively. It is now accepted, that Arg/Arg genotype induces apoptosis with faster kinetics and suppresses transformation in a more efficient way than Pro/Pro (Dumont et al. 2003). During the last years, the role of the Arg/Pro polymorphism in CRC susceptibility has been examined in several investigations, which reported controversial results (Perez et al. 2006). Although this lack of consensus between studies, the majority of them support an appreciable association between the Arg allele and colorectal cancer (Dastjerdi 2011). The simultaneous presence of Arg allele in mutated form of p53 may serve as a predictor of increased tumor development due to inactivation of the apoptosis pathway mediated by p73. On the other hand, Arg72 allele over wild type p53 background might potentially enhance apoptotic ability (Godai et al. 2009; 51 Naccarati et al. 2012). In this project, a concomitant presence of p53 mutation and Arg allele has been seen in 16 cases (69,6%). 5.3. Addressing the Cell Line Cross-contamination problem During this study, the p53 mutation status of 5 different CRC cell lines used frequently at the laboratory was checked. After DNA sequencing, it was possible to infer that all of them presented the expected mutation for each cell line (Liu and Bodmer 2006). Cancer cell lines are essential tools used in many areas of biomedical research (Kniss and Summerfield 2014). They can be used for drug screening, for production of various macromolecules, for modelling human tumors or as biological test tubes for a variety of experiments (Ahmed et al. 2013). Existing data show that cross-contaminated and misidentified cell lines are still a silent and neglected danger and that extreme care should be taken as a wrong p53 status could lead to disastrous experimental interpretations (Berglind et al. 2008; Ahmed et al. 2013). A recent study indicates a CLCC of 18% at a German cell line repository (Berglind et al. 2008). To reduce this risk, the identity of each individual cell line used in the experiments should be verified and matched to external resources (CapesDavis et al. 2013; Somaschini et al. 2013). 5.4. K-ras gene is a marker of aggressive tumor phenotype K-ras is an oncogene that regulates cell proliferation, differentiation, and apoptosis and it is one of the first genes proposed to be involved in CRC development (Kosmidou et al. 2014). Mutations in K-ras are found mostly in codons 12 and 13 of exon 1, and its frequency in CRC ranges from 20-50% depending on the study and the sample source (Poehlmann et al. 2007). Additional more rare mutations occur at smaller frequencies, ranging from 1% to 4% in CRC and involve codons 61, 117 and 146 (de Macedo et al. 2014). In the present study, K-ras mutation status was evaluated by performing PCR and subsequent pyrosequencing. This analysis revealed that 16 of the 55 tested tumors, carried a K-ras mutation (29,1%). The frequencies of mutations at codon 12 and 13 were 68,8% and 31,3% respectively, which support findings previously reported in the literature (Andreyev et al. 2001; Roa et al. 52 2013; Wangefjord et al. 2013; Tong et al. 2014). No sample harboured double mutations involving both codons 12 and 13. Mutations in other codons were not analyzed. The most abundant mutation of codon 12 was G12D, followed by G12V, G12S and G12C while G13D was the predominant mutation in codon 13. Also these results are in concordance with several previous studies (Neumann et al. 2009; Yokota 2012). No significant associations were found between K-ras mutation status and clinicopathological variables like sex, age, TNM stage, tumor site and differentiation grad, which agrees with the results presented in other investigations (Andreyev et al. 2001; Wangefjord et al. 2013). K-ras mutations in CRC are associated with significantly poorer prognosis, like Phipps et al. demonstrated in their research in 2013. Accumulated data suggest that mutation of the K-ras gene is a marker of aggressive tumor phenotype, and therefore detecting this mutation at an earlier disease may be of relevance in planning individual cancer therapies (Li et al. 2012). Generally, patients with CRC Dukes A or B undergo surgery with curative intent but are not routinely offered adjuvant therapy. If these patients with early stage disease carry a K-ras mutation, they might benefit from an alternative more aggressive treatment regime (Conlin et al. 2005). On the contrary, in patients with advanced, metastatic CRC, the mutational status of K-ras serves to identify which patients in this group would be offered anti-EGFR treatment, because only CRCs with wild-type may benefit from it (Kim et al. 2014b). As exposed, both patients with early disease and the ones with advanced CRC seem to be good candidates for the routine analysis of the K-ras mutation status. 5.5. V600E mutations are associated with higher risk of mortality in CRC BRAF is another oncogene and it is mutated in up to 70 % of cancer cell lines (Safaee Ardekani et al. 2012). Activating mutations of BRAF are found in 10%20% of CRCs, with most (over 95%) occurring in a hotspot of amino acid position 600 by a missense substitution of valine by glutamic acid, what is known as BRAF V600E mutation (Mao et al. 2012; Prahallad et al. 2012; 53 Yokota 2012; Kuan et al. 2014). In this study, 14,5% of BRAF mutations have been identified and all of them were V600E. As exposed above, these findings correspond well with previously reported literature. BRAF mutations are associated with female sex, older age, proximal tumor localization, low differentiation grade and locally advanced characteristics (Li et al. 2006; Clancy et al. 2013; Wangefjord et al. 2013; Kim et al. 2014a). This investigation revealed that 87,5% of the BRAF mutations were present in women. In 2013, Clancy et al. reported that BRAF mutation was not associated with young age. This suggest that BRAF mutations are acquired mutations occurring mainly in sporadic colorectal cancers and thus, not common in younger patients. The same group informed that there is a solid association between proximal tumor location and BRAF mutations (Clancy et al. 2013). Same results were observed in this work, where 75% of the BRAF mutations corresponded to samples from patients older than 65 years old. 7 from the 8 patients with BRAF mutations were women. In 87,5% of the cases the tumor localization was proximal. The presence of BRAF mutations is associated with notably higher risk of mortality in CRC (Safaee Ardekani et al. 2012). In addition to prognosis, BRAF mutation might have clinical treatment implications. Similar to patients with Kras mutations, those patients with metastatic tumors that are being consider for anti-EGFR therapies should be tested for BRAF mutations as well (Pu et al. 2013). The presence of BRAF V600E mutation in CRC predicts resistance to anti-EGFR therapy in patients with K-ras wild-type (Kuan et al. 2014). Because K-ras is mutated more often than BRAF, first-line testing should be done for K-ras. If the tumor presents K-ras wild-type, then genotyping BRAF should be considered (Kalady et al. 2012). 5.6. Simultaneous mutations of p53, K-ras and BRAF: rare but not impossible Several research groups have studied the simultaneous expression of p53, Kras and BRAF in CRC, concluding that synchronic mutations in these genes rarely occur (Calistri et al. 2005; Chang et al. 2013). This could suggest that p53 and K-ras mutations are on separate pathways to CRC development and 54 are not part of a common pathway of accumulating genetic change (Conlin et al. 2005; Berg et al. 2010). In this study, p53 mutation associated with K-ras mutation was only present in 3 from the 55 tested patients (5,5%). In the same way, co-presence of mutations in BRAF and p53 is quite rare (Calistri et al. 2005). BRAF mutations are more frequently found in premalignant colon polyps and in early, rather than advanced, CRC (Monticone et al. 2008). Combination of mutp53 and mutBRAF was in this project, also seen in 3 patients (5,5%). As concomitant K-ras and BRAF mutations are uncommon in premalignant colon polyps and early stages of CRC, they are considered as alternative or mutually exclusive mutations (Yokota 2012). In recent studies, however, it was found that the number of simultaneous K-ras and BRAF mutations increased along with the depth of the wall invasion of sporadic MSS (microsatellite stable) CRC, suggesting that activation of both genes is likely to harbor a synergistic effect and that K-ras could give the tumor an invasive behavior (Oliveira et al. 2007; Monticone et al. 2008). In this work, the co-existence of K-ras and BRAF mutations was found in only 1 patient (1,8%), that interestingly also harboured a silent p53 mutation in exon 8 (L264L). This patient was a 55 year old woman with a proximal, moderately differentiated tumor, TNM stage I. Due to the infrequent observation of this phenomena, it is not clear whether or not tumors carrying coincident K-ras and BRAF mutations have a different biology and natural history than K-ras or BRAF mutant tumors, or which of the 2 mutations is the dominant oncogene driving tumor proliferation. Further studies are necessary to understand the true frequency and the role of concomitant K-ras and BRAF mutations. 5.7. Mutated p53 can be detected by immunostaining The application of nucleotide sequencing of p53 is the most reliable technique to detect gene mutation, but its application in pathology practice is limited. Thus, immunohistochemical analysis of p53 expression is commonly used as a substitute for mutational analysis (Yemelyanova et al. 2011). The relationship between p53 overexpression and mutation is still being 55 controversially discussed (Gao et al. 2000). A number of investigations have shown that a positive p53 expression status often equates with p53 mutation, but not always (Kruschewski et al. 2011). In this work, 2 different p53 antibodies were proved. The antibody from DAKO showed a high rate of negative stainings in samples harbouring p53 mutations (40%) and a low percentage of negative stainings in the wt group (41,7%). Not satisfied with these results, a new antibody (BD PharmigenTM) was used, obtaining staining patterns which are in concordance with the published literature. Thus, 73,8% of the mutated cases detected with sequencing presented positive immunostaining, which is in agreement with previous investigations that revealed that the positivity range of p53 expression in CRC is between 40 and 81% (Kruschewski et al. 2011). This wide range is a result of interstudy variations, including different antibodies, scoring systems, cutoff values, and study populations (Kruschewski et al. 2011; Nyiraneza et al. 2011). Wild-type p53 protein is relatively unstable and has a short half-life, which makes it undetectable by immunohistochemistry. In contrast, mutated p53 has a much longer half-life, and therefore, accumulates in the nucleus creating a stable target for immunohistochemical detection (Yu et al. 1993; Yang et al. 2013). Antibodies used for IHC can detect both wild-type and mutant p53 protein (Tabyaoui et al. 2013). P53 overexpression is generally regarded as indicative of missense mutations, but nuclear p53 overexpression could sometimes occur in the absence of mutation and vice versa (Cripps et al. 1994; Dix et al. 1994; Rossner et al. 2009). This work showed 5 mutated cases with negative staining, corresponding to 1 frameshift mutations in exon 4, 2 frameshift mutations in exon 8, 1 stop codon mutation in exon 6 and a D281Y mutation in exon 8. It is now accepted that complete lack of immunohistochemical expression may be result of mutations generating premature stop codon or frameshift mutations leading to formation of a truncated, non-immunoreactive protein (Iacopetta 2003; Yemelyanova et al. 2011). The lack of p53 immunoexpression associated with nonsense (or null) mutation is very important to recognize because some studies demonstrated worse prognosis for patients with this finding compared with patients whose tumor had a missense mutation (Hashimoto et al. 1999). Interestingly, tumors with wild-type p53 display a wide range of immunolabeling patterns, with the 56 most common pattern showing <10% of positive cells, but presenting other times overexpression. In the wild-type group of this project, positive expression of p53 was seen in 28,1% of the samples. Apart from the kind of mutation, there are several other possible explanations for the lack of perfect correlation between TP53 mutation and immunohistochemical expression. First, the number of the codons included in the analysis; the present study evaluated exons 4-8, which would identify most, but not all possible mutated loci. Second, post-translational alteration; cellular stress could result in delayed degradation of wt p53 making it detectable by IHC. Third, discrepancy of the samples used on mutational analysis and staining. Fourth, factors affecting immunolabeling, especially under-fixation (Yemelyanova et al. 2011). For these cases without detectable mutation showing positive immunohistochemical expression, the execution of microdissection could be recommended. In this technique, sections of formalin-fixed, paraffin-embedded tumor samples are mounted on slides and stained immunohistochemically with the p53 antibody. Single p53positive cells are separated from the surrounding tissue with the use of laser and they are picked up using a micromanipulator-guided needle. From these cells, DNA extraction and sequencing is carried, increasing the chance of detecting mutations (Kaserer et al. 2000). In this study, the analysis of the positivity range of expression of p53 showed the highest expression in samples with mutations in exon 5 and exon 7. The significance of this result could not have been correlated with other studies due to the lack of previous published literature addressing this issue. Expression of p53 is evaluated according to the percentage of positive tumor cell nuclei (the number of positive tumor cells over the total number of cells) (Kruschewski et al. 2011). Research groups use different cutoff values making data from different studies difficult to compare and interpret (Zlobec et al. 2007; Sarasqueta et al. 2013). In this study a cut-off of 10% was assumed as indicative of p53 overexpression. Scoring systems for p53 in CRC are in many cases based on a measure of the proportion of positive tumor cells often combined with a degree of staining intensity. Staining intensity is evaluated as 0=negative, 1=weak, 2=moderate, and 3=strong (Zlobec et al. 2007). In all the positive stainings of this investigation the intensity was high, distributed 57 between 54 cases with strong staining (3+) and only one case of moderate staining (2+). Anyway, it is recognized that the interpretation of staining intensity is not only highly subjective but may also be affected by storage time, variation in protocols, and fixation procedures (Zlobec et al. 2007). Several studies have reported that p53 overexpression is more frequently associated with right-sided colon cancers and with mucinous or poor differentiated tumors (Nyiraneza et al. 2011). In the present study, from the total 27 cases with positive immunostaining, 66,7% had rectal localization, 33,3% proximal and 11,1% distal localization. The tumor differentiation grade was moderate (77,8%), poor (18,5%) and well (3,7%). From the 5 cases with mutated p53 and negative expression in immunohistochemistry explained before, 40% had proximal localization and 80% were poorly differentiated. Included in this group, there was a 59 year old woman, who was the only one in the whole set of cases with a mucinous tumor (poorly differentiated, localized in the colon ascendens). Sanger sequencing showed a R196stop mutation in p53 protein. From the above exposed, it can be concluded that immunohistochemistry is a robust method for inferring the presence of p53 mutations; not isolated but as a complement of other techniques like sequencing. 5.8. MiRNAs induced by p53 5.8.1. MiR-34 family Several groups have reported that p53 can directly regulate the expression of the miR-34 family members (Chang et al. 2007; Raver-Shapira et al. 2007; Shin et al. 2009). The precursors of these miRNAs are transcribed from two distinct loci: the miR-34a locus on chromosome 1p36 and the miR-34b and miR-34c locus on chromosome 11q23 (Wang et al. 2009). Canonical p53binding sites are placed in the promoter regions of miR-34a, b and c. Consistent with a possible tumor-suppressor role, loss of expression of members of the miR-34 family has been reported in human cancers (Chang et al. 2007; Roy et al. 2012). Expression of miR-34a is increased by p53 in response to genotoxic stress, both in vitro and in vivo (Raver-Shapira et al. 2007). Ectopic expression of miR-34a promotes p53-mediated apoptosis, cell 58 cycle arrest and senescence, while inactivation of endogenous miR-34a strongly inhibits p53-dependent apoptosis in cells (Chang et al. 2007; He et al. 2007; Raver-Shapira et al. 2007). Recent investigations have shown that miR34 family members directly repress the expression of several targets involved in the regulation of cell cycle and in the promotion of cell proliferation and survival. Among these targets are cyclin E2, cyclin-dependent kinases 4 and 6 (CDK4 and CDK6), and BCL2 (Feng et al. 2011; Okada et al. 2014). Thus, the phenotypic output of miR-34 activation may vary by cell type depending on the spectrum of its targets that are available for repression. In accordance with their regulation by p53, comparatively low levels of miR-34s are seen in human tumors and cancer cell lines, which have a high frequency of functional p53 deficiency (He et al. 2007). 5.8.1.1. MiR-34a is up-regulated in tumors with wt p53 Recently, abnormal up- and down-regulation of several miRNAs in human CRC has been reported. However, which miRNA species are actually implicated in the development of this cancer is a question that remains open (Wang et al. 2014). Tazawa et al. revealed that the expression level of miR34a was reduced in 36 % of human CRC specimens. Using quantitative qRTPCR analysis, they demonstrated that miR-34a was highly up-regulated in a human colon cancer cell line harbouring wild-type p53, HCT 116, treated with a DNA-damaging agent, adriamycin (ADR). In this experiment, they compared the miRNA responses after ADR treatment between HCT 116 and HCT 116 p53 knockout (HCT 116 p53-/-) cell lines, and they identified miR-34a as an ADR-responsive miRNA in a p53-dependent manner. To confirm that the induction of miR-34a depends on p53, other human colon cancer cell lines, either with wild-type p53 genes (LoVo and RKO) or mutated p53 genes (DLD1 and HT29) were studied. LoVo and RKO cells, as well as HCT 116 cells, exhibited increased expression of miR-34a, but DLD1 and HT29 cells showed no change, like the HCT 116 p53 -/- cells (Tazawa et al. 2007). In this doctoral work, the level of miR-34a was compared between 2 groups of FFPE samples: one group of p53 wt tumor tissues and the other group represented by their counterpart normal tissues. The results showed a notable 59 up-regulation in the first group, which is in concordance with previous studies (Chang et al. 2007; Tazawa et al. 2007). Assuming that the expression of miR-34a is p53 dependent, this miRNA is expected to be down-regulated in specimens with mutated p53. Tazawa et al. analyzed the levels of miR-34a in human colon cancer and paired counterpart normal tissue. Nine of 25 colon cancer tissues (36%) showed decreased expression of miR-34a, suggesting that down-regulation of miR-34a may be, at least in part, involved in the development of colon cancer. They also observed that one-third of colon cancer cases presented up-regulation of miR34a, which express that there may be alternative mechanisms that remain to be identified in the regulation of miR-34a (Tazawa et al. 2007). In this study, the comparison of the expression levels of miR-34a in histologically normal samples and tumor samples harbouring p53 mutations showed that many of the specimens in the second group presented downregulation or no changes in the expression level, what suggests that in the cancer group the regulation is lost. Overall comparison between the 55 samples (including samples with wt and tumor samples with mutated p53) showed no significant differences in the expression level of mir34a. Here it would have also been expected a downregulation in the miR-34a levels in the group presenting p53 mutations. The expression of miR-34a related to p53 codon 72 polymorphisms was analyzed, concluding that the highest expression of miR-34a was associated with the Arg/Arg genotype. The association between miRNAs and K-ras/BRAF still remains undefined (Kent et al. 2010; Ito et al. 2014). Research revealed that 6 miRNAs (miR-23a, miR-125b, miR-191, miR-200c, miR-221 and miR-222) were up-regulated and 2 (let-7b and let 7i) were down-regulated under the control of oncogenic K-ras in 3D culture (Tsunoda et al. 2011). Other investigations showed that the expression of miR-31 is notable up-regulated in CRCs that present BRAF mutations. In this doctoral work, no association was observed between miR34a and K-ras/BRAF mutations. 60 5.8.2. MiR-34b and miR-34c are not detectable in CRC samples No expression of miR-34b and miR-34c in the samples was detected in the qRT-PCR experiments. Under unstressed conditions, the expression of miR34a and miR-34b/c is particularly intense in the testis, brain, and lung. MiR34b/c expression seems largely restricted to these three tissues, while miR34a is detectable, albeit at lower levels, also in several other organs including colon, liver and kidney (Concepcion et al. 2012). In 2007, 2 independent investigations working with HCT 116 cells reported that while substantial expression of miR-34a was observed, the expression levels of the miR-34b and -34c were very low or not even detectable (Chang et al. 2007; Tazawa et al. 2007). 5.8.3. Other components in the p53 network: miR-192, miR-215 and miR-200c In addition to the miR-34 family, 3 other p53 induced miRNAs were studied in this project: miR-192, miR-215 and miR-200c. No differences in the expression of these miRNAs were seen when comparing wt and mutated p53 tumor samples. A brief description of these miRNAs can be found below. MiR-192 and miR-215 MiR-215 clusters on chromosome 1 (1q41) and miR-192 on chromosome 11 (11q13.1). Both miRNAs are highly homologues to each other and share the same seed sequences (Khella et al. 2013). Previous studies demonstrated that miR-192 and -215 express at high levels in colon and liver (Barad et al. 2004; Lu et al. 2005). In the same way than miR-34a, miR-192 and -215 are among the p53 regulated miRNAs and show reduced expression levels in CRC (Karaayvaz et al. 2011; Zhai and Ju 2011). In an effort to obtain a more complete set of p53-responsive microRNAs, Braun et al. hybridized microarrays with small RNA from Nutlin3-treated cells and found that clusters encoding miR-192 and miR-215 were p53 responsive, in addition to miR-34a. The same clusters were down-regulated in colon cancer relative to normal colon tissue, supporting the idea that they might be part of a tumor-suppressing 61 program (Braun et al. 2008). In 2012, Chiang et al. studied the expression levels of miR-192 and -215 in a large number of CRC tissues, relative to their non-tumor counterparts, by real-time PCR assay. Significantly lower expression of these miRNAs was found in cancer tissues compared to nontumor counterparts. Similar significant results were obtained in CRC cell lines (Chiang et al. 2012). Functional analysis revealed that miR-192 and -215 were capable of inducing p21 expression and cell cycle arrest in a p53-dependent manner, suggesting that they may be able to activate p53 (Georges et al. 2008; Song et al. 2008). In this context, the expression of p21 was increased by miR192 and miR-215 only in cells that carried wt p53, but not in cells with p53-/status (Braun et al. 2008). Among the targets of miR-192 and -215 are a number of regulators of DNA synthesis and the G1 and G2 cell cycle checkpoints in cells, such as CDC7, MAD2L1 and CUL5 (Feng et al. 2011). Recent investigations studied the regulating mechanism of p53 level by miR192 and -215 and discovered a key target, denticleless protein homolog (DTL) (Zhai and Ju 2011). The suppression of DTL by these miRNAs generates an up-regulation of p53 and p21 (Georges et al. 2008; Song et al. 2010; Karaayvaz et al. 2011). DTL is thought to play an essential role in DNA synthesis, cell cycle progression, proliferation, and differentiation (Pan et al. 2006). MiR-200c MiR-200c has been widely reported to be elevated in tumor tissues and sera of CRC patients and has been found to correlate with poor prognosis (Chen et al. 2014). Xi et al. study demonstrated that miR-200c expression was strongly associated with the mutation status of p53 in CRC (Xi et al. 2006). In March 2014, Chen et al. published that the expression of miR-200c was significantly higher in tumor tissues than in peritumoral tissues of patients with colon cancer. They conclude, that miR-200c functions as an oncogene in colon cancer cells through regulating tumor cell apoptosis, survival, invasion, and metastasis as well as xenograft tumor growth through inhibition of PTEN expression and p53 phosphorylation (Chen et al. 2014). Previous studies reported controversial roles of miR-200c in the metastasis of colon cancer 62 such as that overexpression of miR-200c inhibited the metastatic ability of colon cancer cells in one study, whereas a positive association between miR200c expression and metastasis of CRC was observed in another (Chen et al. 2012; Hur et al. 2013). In this context, 2 independent research groups have investigated the function of miR-200c in epithelial-mesenchymal transition (EMT), a key process in tumor progression and metastasis. MiR-200c upregulated by p53, repress the expression of 2 EMT promoters (ZEB1 and ZEB2) decreasing, in this way, the activation of the EMT program. This data reveals a potential therapeutic implication to suppress EMT through activation of p53-miR-200c pathway (Chang et al. 2011; Kim et al. 2011). 5.8.4. MiRnas, K-ras and BRAF in CRC Although activating mutations in RAS oncogenes are known to result in aberrant signaling through multiple pathways, the role of miRNAs in the Ras oncogenic program still remains unclear (Kent et al. 2010). Mosakhani et al. compared miRNA profiles between 2 groups of CRC patients, one with mutant K-ras and the other one with wild-type K-ras, founding a significant differential expression between them. One of these differential expressed miRNAs was miR-92a, which showed up-regulation in CRC samples with mutated K-ras (Mosakhani et al. 2012). MiR-92 is up-regulated in several types of cancers including CRC (Ng et al. 2009). Expression of the miR-92 promotes cell proliferation, suppresses apoptosis of cancer cells and induces tumor angiogenesis (Mendell 2008). Chen et al. had experimentally validated K-ras oncogene as target of miR-143. MiR-143 is significant in suppressing CRC cell growth through inhibition of K-ras translation (Chen et al. 2009; Pichler et al. 2012). Tsunoda et al. analyzed also the relationship between miRNAs and Kras in CRC cells. In this study, they found 6 miRNAs (miR-23a, miR-125b, miR191, miR-200c, miR-221 and miR-222) to be up-regulated and 2 (let-7b and let-7i) to be down-regulated under the control of oncogenic K-ras in 3D culture (Tsunoda et al. 2011). The association between miRNAs and BRAF in CRC is also undefined. Recent studies using miRNA array analysis revealed that miR-31 expression is significantly up-regulated in CRCs with mutated BRAF (V600E), compared 63 with CRCs possessing wild-type BRAF. High miR-31 expression has been associated with BRAF and K-ras mutations and proximal location. Functional analysis showed that miR-31 inhibitor decreased cell invasion and proliferation (Ito et al. 2014; Nosho et al. 2014). 5.9. Conclusion and outlook Colorectal cancer is a leading cause of cancer-related mortality worldwide (Wang et al. 2014). Colon carcinogenesis is a multistep process, involving oncogene activation and tumor suppressor gene inactivation as well as complex interactions between tumor and host tissues, leading finally to an aggressive metastatic phenotype (Wang and Sun 2010). Among many genetic lesions, mutational inactivation of p53 tumor suppressor is the most frequent event, found in 50% of human cancers. P53 plays a critical role in tumor suppression principally by inducing growth arrest, apoptosis, and senescence, and by blocking angiogenesis. Additionally, p53 confers chemo- radiosensitivity. Thus, it is not surprising that p53 has become the most appealing target in anti-cancer drug discovery. This project aimed to increase the current knowledge concerning the role of p53 in CRC, its interaction with the oncogenes K-ras and BRAF, and its association with miRNAs. In this study, 41,8% of the tested samples presented p53 mutations; 29,1% had K-ras mutations and 14,5% showed BRAF mutations. Mutation frequencies were found to be within previously reported range supporting the representativeness of the results in this work (Andreyev et al. 2001; Naccarati et al. 2012; Yokota 2012; Kuan et al. 2014; Tong et al. 2014). Simultaneous expression of p53, K-ras and BRAF rarely occur (Chang et al. 2013). Even though, the association p53 mutation/K-ras mutation was seen in 5,5% of the samples (3 patients), and the association p53 mutation/BRAF mutation was found in other 5,5% (3 patients). The co-existence of K-ras and BRAF mutations was found in only 1 patient (2,6%). It remains unclear if tumors with coincident K-ras and BRAF mutations have a different biology and natural history than K-ras or BRAF tumors, or which of the 2 mutations acts as dominant in tumor development. 64 Mutations in p53 were detected in this project by Sanger sequencing and immunohistochemical staining. Mutated p53 has a longer half-life than the wt p53 and this is the reason why it can be detected immunohistochemically (Yu et al. 1993). Negative p53 immunostaining in association with p53 mutations was seen in 5 cases corresponding to 3 frameshift mutations, 1 stop mutation and a D281Y mutation in exon 8. The complete lack of immunohistochemical expression may be the result of mutations generating premature stop codon or frameshift mutations leading to formation of a truncated, nonimmunoreactive protein (Iacopetta 2003; Yemelyanova et al. 2011). Nuclear p53 overexpression was found in this investigation in the presence of p53 mutations using 2 different antibodies. The expression level of several p53-induced miRNAs was also evaluated. For miR-34a, using paired analysis, 2 groups of samples with wt p53 were compared: one represented by CRC tissues and the other one by normal tissues. A notable up-regulation in the levels of miR-34a was found in the first group showing that the expression of miR-34a is increased by p53 in wild-type form, in response to cellular stress. The comparison of the expression levels of miR-34a in histologically matched normal samples and tumor samples harbouring p53 mutations revealed, in most of the cases, down-regulation or no changes in the expression level of the second group, suggesting that in p53 mutated cancer the regulation is lost. No expression of miR-34b and miR-34c was detected in the samples and no significant differences in the expression of miR-34a, miR-192, miR-215 and miR-200c were found when comparing the whole tumor group with wt and with mutated p53. Some of the experiments of this work should be repeated and several other experiments could also be conducted to supplement the above exposed data. Due to time limitations the comparison between the expression of miRNAs in matched normal and tumor samples was only performed for miR-34a. It could be very interesting to investigate the behavior of the other miRNAs in the 15 paired normal/tumor samples. A DNA and RNA bank derived from the samples used in the research has been created. This represents a unique possibility for further investigations, such as 65 the study of other genes or miRNAs of interest and mutations not included in this project. Recent investigations suggest that maybe p53 is not sufficient and other proteins may be required as co-activators along with p53 to induce miRNA expression. In this context, the employement of Chip Assays could be useful tools in future investigations. 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The aim of this study was to extend the present knowledge about the role of p53 in CRC, its interactions with the oncogenes K-ras and BRAF, the correlation between the mutation status and the immunohistochemical expression patterns of p53, and the association of protein p53 with certain miRNAs. This study was based on the analysis of formalin-fixed paraffin-embedded tissues from 55 patients with histological proven colorectal adenocarcinoma. 41,8% of the samples presented p53 mutations, which is in concordance with previous published data, that estimate the p53 mutation incidence in CRC to be between 40 and 50%. The incidence of K-ras mutations was 29,1% and of BRAF 14,5%. Simultaneous expression of p53, K-ras and BRAF are not frequently reported in the literature, suggesting that they are on separate pathways to colorectal tumorigenesis and not part of a common pathway of accumulating genetic change. In this study, 3 patients presented co-existence of p53/K-ras mutations and 3 others harboured a double mutation p53/BRAF. Only 1 patient had simultaneous mutation of K-ras and BRAF. The mutant forms of p53 are stable and have longer half-life than the wild-type forms, making it possible to detect them immunohistochemically. In this work, 73,8% of the mutated p53 cases presented positive immunostaining, which is in agreement with previous investigations. Recent studies have demonstrated that miRNAs interact with p53 and its network at several levels. P53 controls the transcription expression and maturation of a group of miRNAs, which in turn, can regulate the activity of p53 through direct repression of p53 or its regulators cells. MiR-34 showed upregulation in the wt p53 cancer group compared with the normal tissue group, showing that the expression level of miR-34a is increased by p53 in the wildtype form, in response to cellular stress, like genotoxic damages, oncogene 105 activation and hypoxia. The comparison of the expression levels of miR-34a in normal samples and tumor samples that harboured p53 mutations showed that many of the specimens in the second group presented down-regulation or no changes in the expression level, suggesting that in the cancer group the regulation is lost. No difference in the expression of this miRNA was seen between tumor samples with wt p53 and mut p53 in the whole tumor group. Other p53 regulated miRNAs included in this study were miR-34b, miR-34c, miR-192, miR-215 and, miR-200c. P53 is a fundamental component of the colorectal carcinogenesis. Further research will contribute to a better understanding of its function, taking us a step forward in the process of developing personalized cancer treatment. 106 Zusammenfassung Das Kolorektale Karzinom ist weltweit eine der Hauptursachen für den Krebstod und ist verbunden mit einem abnormen Zellzyklus und einer defekten Apoptoseinduktion infolge der Aktivierung von Proto-Onkogenen und/oder der Inaktivierung von Tumorsupressorgenen. In 50% der Krebsfälle ist das p53 Tumorsupressorgen, auch Wächter des Genoms genannt, durch eine Mutation deaktiviert. Ziel dieser Studie war die Ausdehnung der bisherigen Kenntnisse über die Rolle von p53 in CRC, die Prüfung einer Korrelation zwischen dem Mutationsstatus und dem immunohistochemisch nachweisbaren Expressions-Muster von p53 sowie dessen Wechselwirkung mit verschiedenen miRNAs. Diese Studie basiert auf der Analyse der in Paraffin eingebetteten Gewebeschnitte von 55 Patienten mit einem histologisch gesicherten kolorektalen Adenokarzinom. In Übereinstimmung mit bisherigen veröffentlichen Daten, welche eine Häufigkeit der p53-Mutation bei CRC auf 40-50% schätzen, wiesen 41,8% der hier untersuchten Proben eine p53Mutation auf. Die Häufigkeit einer K-ras Mutation lag bei 29,1%, die einer BRAF Mutation bei 14,5%. Eine gleichzeitige Expression von p53, K-ras und BRAF wird in der Literatur kaum erwähnt, was zu der Annahme führt, dass sie nicht Teil eines gemeinsamen Signalweges mit einer Ansammlung genetischer Veränderungen sind, sondern über verschiedene Signalwege Einfluss auf die Tumorgenese nehmen. In dieser Studie trat bei 3 Patienten eine Koexistenz von p53/K-ras Mutationen auf, 3 weitere hatten eine Doppelmutation von p53/BRAF. Bei einem Patienten trat eine gleichzeitige Mutation von K-ras und BRAF auf. Die mutierten Formen des p53 Proteins zeigten eine hohe Stabilität und hatten eine längere Halbwertszeit als der p53 Wildtyp, wodurch es möglich war, diese immunohistochemisch nachzuweisen. In dieser Arbeit zeigten 73,8% aller Fälle mit einer p53 Mutation eine positiv p53 Immunfärbung, was mit früheren Untersuchungen übereinstimmt. Jüngste Studien haben gezeigt, dass miRNAs mit p53 und seinem Netzwerk auf mehreren Ebenen interagieren. P53 kontrolliert die Transkription, Expression und Reifung einer Gruppe von miRNAs, welche ihrerseits die p53 107 Aktivität regulieren entweder durch direkte Suppression oder über seine Regulatoren. Bei dem Vergleich der p53 Wildtyp Tumoren mit dem korrespondierenden Normalgewebe zeigte die miR-34 eine Hochregulierung. Der Vergleich der Expressionsmenge der miR-34a in gepaarten Normalproben und Tumorproben mit einer p53 Mutation zeigt in den Tumorproben eine Herunterregulation oder keine Veränderung im Expressionslevel. Dies führt zu der Annahme, dass die Regulation in der Tumorgruppe mit mutiertem p53 verloren geht. Es gab keinen Unterschied im Expressionslevel dieser miRNA im Gesamtkollektiv bei Vergleich von Wildtyp p53 und p53 mutierten Tumoren. Weitere durch p53 regulierte miRNAs wie miR-34b, miR-34c, miR-192, miR215 und miR-200c wurden in dieser Studie untersucht und zeigten keinerlei Korrelation zum p53 Status. P53 ist ein wesentlicher Bestandteil der kolorektalen Karzinogenese. Die weitere Erforschung dieses wichtigen proteins wird uns ein besseres Verständnis seiner Funktion liefern und uns somit einen Schritt in der Entwicklung einer personalisierten Krebstherapie weiterbringen. 108 Curriculum Vitae Mariana Fernanda Cordoba Hansen Date of birth: June 28 1976 Place of birth: Buenos Aires, Argentina Address: Hirtenbachstrasse 4A, 91353, Hausen, Germany Telephone: 091917362872 Mobile: 01712837681 E-mail: [email protected] Education 06/13 – 07/14 Universitätsklinikum Erlangen, Erlangen, Germany Doctoral candidate at the Experimental Tumor Pathology Department, Institute of Pathology 02/13 - 02/13 Universitätsklinikum Erlangen, Erlangen, Germany Assistenzärztin at the Department of Surgery 04/11 - 04/12 Hillerød Hospital, Hillerød, Denmark Senior resident at the Department of Surgery 01/10 - 03/11 Rigshospitalet, Copenhagen, Denmark Senior resident at the Department of Surgical Gastroenterology (12 months at the Department of Surgery and Liver Transplants and 3 month at the Department of Paediatric Surgery) 08/08 - 12/09 Herlev Hospital, Herlev, Denmark Senior resident at the Department of Surgical Gastroenterology (started as mid level resident) 05/08 -07/08 Ringsted Hospital, Ringsted, Denmark Mid level resident at the Department of Breast Surgery 11/07- 05/08 Herlev Hospital, Herlev, Denmark Mid level resident at the Department of Surgical Gastroenterology 11/05 – 10/07 Gentofte Hospital, Gentofte, Denmark Mid level resident at the Department of Surgical Gastroenterology 05/05 – 10/05 Gentofte Hospital, Gentofte, Denmark Mid level resident at the Department of Cardiothoracic Surgery 06/04 – 04/05 Gentofte Hospital, Gentofte, Denmark Started out as junior resident and advanced to mid level resident at the Department of Surgical Gastroenterology 07/01 - 07/05 Hospital Prof. Dr. Luis Güemes, Haedo, Argentina 109 4 years Residence within General Surgery (the education was financed by a scholarship from the Argentinean Ministry of Health) 07/00 – 03/01 Hospital Dr. Carlos G. Durand, Buenos Aires, Argentina Rotation round 03/95 – 07/00 Universidad de Buenos Aires, The Faculty of Medicine, Buenos Aires, Argentina Medical education Average grade: 8.69 on the 1- 10 scale 03/94 - 12/94 Universidad de Buenos Aires, CBC, Buenos Aires, Argentina Two semesters of preparation and admission study for Medical School 03/89 – 12/93 The Institute of Abate José Rey, Caseros, Argentina High school student References Christian Ross, Education responsible and Consultant, the Department of Surgical Gastroenterology, Rigshospitalet, telephone: +45 35 45 96 45 Jesper Vilandt, Consultant, the Department of Surgery (specialised in colon), Hillerød Hospital, telephone: +45 48 29 71 55 Claus Anders Bertelsen, Consultant, the Department of Surgery (specialised in colon), Hillerød Hospital, telephone: +45 48 29 59 72 Anders Ulrich Neuenschwander, Consultant, the Department of Surgery (specialised in colon), Hillerød Hospital, telephone: +45 48 29 59 42 Anders Fischer, Consultant, the Department of Surgical Gastroenterology, Herlev Hospital, telephone: +45 44 88 44 88, DECT: 82-563 Jens G. Hillingsø, Clinic Director and Consultant, the Department of Surgical Gastroenterology, Rigshospitalet, telephone: +45 35 45 87 80 Practical experience during medical school 03/98 – 07/00 Hospital Dr. Carlos G. Durand, Buenos Aires, Argentina Intern as a part of the obligatory training at medical school 03/96 – 03/98 Hospital Zonal Prof. Dr. Ramón Carrillo, Buenos Aires, Argentina Intern at the hospitals emergency room 110 08/97 – 11/97 The Argentinean Social and Health Ministry, Buenos Aires, Argentina Vaccination Campaign against influenza Courses, congresses, seminars and research 06/11 Research training Statistic and database 05/11 Endoscopy course 05/11 Gastroenterology and Hepatology I 04/11 Management and Administration II 03/11 Gastroenterology and Hepatology II 02/11 The acute surgery patient 12/10 Basic resuscitation in paediatric 09/10 Management and Administration I 09/10 Danish association of surgery, annual congress 03/10 Ultrasound 03/06 23rd course in open and laparoscopic surgical technique, Davos, Switzerland 11/03 74th Argentinean Surgical Congress Seminar for surgeons and surgical workshops Coordinator and participant at the round table Management of choledocolithiasis 11/03 XVIII Argentinean Congress of Emergentologi 11/03 Update in treatment of the venous system 11/03 International course in outpatient-surgery 11/03 International course in mini invasive surgery 10/03 Workshop: Treatment of pancreas, gallbladder and biliary tract cancer. Organised by the Asociación Argentina de Oncología Clinica 10/03 Regional seminar for doctors in Buenos Aires 08/03 Percutaneous treatment of piogenic abscesses Presented for the Asociación Argentina de Cirugía 08/03 PROACI: Development program in surgery Organised by the Argentinean Surgical Association 111 The program dealt with new trends in treatment of surgical pathologies 06/03 Seminar for surgeons 2003 Trauma course 05/03 XVI Argentinian and Latin American congress for young surgeons Seminar for young surgeons under education Author and lector of Ambulant treatment of haemorrhoids 05/03 Update in treatment of the venous system Organised by the Sociedad de Flebologia y Linfologia del Oeste Provincia de Buenos Aires 12/02 A.T.L.S (Advanced trauma life support) Organised by The committee on trauma - American College of Surgeons 11/02 XIV Workshop for young surgeons in Buenos Aires Workshops of general surgery Organiser and speaker 10/02 73rd Argentinian Surgical Congress Seminar for surgeons: Surgical workshops Coordinator and participant at the round the table Treatment of the acute thoracic trauma 10/02 4th Latin American Congress of Endoscopic Surgery 10/02 International course of cancer and laparoscopic surgery 09/02 1st Workshop for doctors Hospital Dr. Luis Güemes 09/02 XIV Workshop for young doctors under surgical education 04/02 XV Argentinian and Latin American congress for young surgeons Seminar for young surgeons under education Author of Penetrating trauma in duodenum and pancreas 11/01 72nd Argentinean Surgical Congress Seminar for surgeons: Surgical workshops Coordinator and participant at the round table 11/01 3rd Latin American Congress of Endoscopic Surgery 11/01 Regional seminar for doctors in Buenos Aires Seminar for young doctors under education Assistant in connection with the presentations of several subjects within surgery 11/00 XXXVI Annual Scientific Seminar of the Hospital Dr. Carlos Durand 112 Further information Languages Spanish (mother tongue), English (fluent) and Danish (fluent), German (good communication skills) First Certificate in English: Issued by the University of Cambridge. IT Windows, Microsoft Office Professional, Internet Personal interests Fitness and running, reading, travelling and cooking 113