Mutational analysis of KRAS and NRAS in metastatic colorectal cancer

Romina Oliveira Silva Mutational analysis of KRAS and NRAS in metastatic colorectal cancer Dissertação de candidatura ao grau de Mestre em Oncologia – especialização em Oncologia Molecular submetida ao Instituto de Ciências Biomédicas de Abel Salazar da Universidade do Porto. Orientador: Manuel António Rodrigues Teixeira, MD, PhD Diretor do Serviço de Genética e Centro de Investigação Instituto Português de Oncologia do Porto Professor Catedrático Convidado do Departamento de Patologia e Imunologia Molecular Instituto de Ciências Biomédicas de Abel Salazar – Universidade do Porto Coorientador: Isabel Maria da Silva Veiga dos Santos, MSc Assessora da carreira dos técnicos superiores de saúde, no ramo de Genética, no Serviço de Genética Instituto Português de Oncologia do Porto “The future belongs to those who believe in the beauty of their dreams.” Eleanor Roosevelt I AGRADECIMENTOS Ao meu orientador, Prof. Manuel Teixeira, por me ter dado a oportunidade de realizar este trabalho no seu grupo de investigação. Obrigada por toda a paciência, disponibilidade e orientação que contribuíram para o meu desenvolvimento enquanto investigadora. À minha coorientadora, Isabel, por ter partilhado comigo toda a sua experiência e conhecimento e por me ter ajudado a superar todos os obstáculos que se foram colocando no meu caminho, sempre com boa disposição e alegria. À Prof. Berta, atual diretora do Mestrado, e a todos os docentes por terem partilhado connosco todo o seu conhecimento sobre esta vasta área que é a Oncologia. A todo o Serviço de Genética do IPO-Porto, por me terem recebido da melhor forma possível e por toda a força que me deram ao longo desta etapa. Um agradecimento especial à Anita e à Susana Bizarro por terem acreditado em mim e nas minhas capacidades; à Catarina, à Paula, ao Henrique, à Sara e ao Rui por me terem proporcionado as melhores horas de almoço de que tenho memória, sempre com as histórias mais hilariantes e as risadas mais contagiantes; e à Carla, à Manuela e à Patrícia por terem sido os meus “anjos da guarda” durante toda esta fase, por me terem encorajado quando me sentia prestes a desistir e por me terem ajudado quando eu não sabia que precisava de ajuda. À Catarina Araújo, pela ajuda, compreensão e companheirismo ao longo deste percurso. Por se apresentar todos os dias com um sorriso na cara e carinho em cada abraço. Obrigada, principalmente, por me mostrares que as melhores amizades podem surgir quando menos esperamos. Às meninas da molecular do GDPN: Marta, Diana, Cláudia Martins, Natália, Isa, Liliana, Elsa e Ariana. Obrigada por me terem integrado logo no vosso grupo, por toda a paciência com os meus horários malucos e por todo o apoio nesta fase mais complicada da minha vida. II A todos aqueles que contribuíram para que nos últimos 5 anos eu tivesse a melhor experiência académica que poderia ter tido. Um agradecimento especial aos amigos que fiz durante a licenciatura que, de uma forma ou de outra, estarão sempre comigo para onde quer que eu vá; aos “Sacaninhas da Presidente”, por terem sido os meus companheiros nesta aventura e por toda a diversão, risota e momentos partilhados ao longo destes dois anos; e às meninas da Residência, por me terem recebido de braços abertos e me terem proporcionado uma experiência que nunca esquecerei, sempre com um pouco de loucura e boa disposição à mistura. Aos meus 11 magníficos: Ana, Carina, Carlos, Cati, Jeje, Joana, João, Márcia, Mari, TG e Ritinha. Obrigada por toda a cumplicidade, amizade, loucura, diversão, carinho, compreensão, dedicação, união, paciência, afeto e presença constante. Por aturarem o pior e aceitarem o melhor que há em mim. Já nada é, nem nunca mais será, o mesmo sem vocês. Ao Chris e à Inês, dos melhores amigos que a vida me poderia ter dado, pela força, pelos sorrisos, pela brincadeira e pela confiança. Mas, principalmente, por me terem dado a oportunidade de provar que a desculpa de que o tempo e a distância destroem amizades, é apenas isso, uma desculpa. À minha família, que sempre me acompanhou e esteve presente em cada etapa da minha vida, e esta não foi exceção. Obrigada por todo o apoio e força que, diariamente, me fazem alcançar todos os meus objetivos e superar todas as adversidades. Às minhas irmãs, os meus caramelos repetidos, que tantas dores de cabeça me dão mas sem as quais a minha vida não seria a mesma. Obrigada por todas as “cusquices”, risotas e palermices, mas principalmente, por tornarem a minha vida tudo menos monótona. Aos meus pais, a quem devo tudo aquilo que sou e aos quais não tenho palavras suficientes para agradecer tudo o que me foram proporcionando ao longo da vida. Obrigada por todas as palavras de encorajamento, pela força e apoio incondicionais ao longo de cada etapa e decisão da minha vida. Obrigada por simplesmente estarem lá para me ajudarem a tornar-me na melhor pessoa que posso ser. Este trabalho é dedicado a eles. III ABSTRACT The epidermal growth factor receptor (EGFR) is a transmembrane tyrosine kinase receptor that, upon activation, triggers several pathways, such as the RAS/RAF/ERK pathway, that are often deregulated in colorectal carcinomas. Two monoclonal antibodies targeting EGFR, cetuximab and panitumumab, have proven to be effective in the treatment of metastatic colorectal cancer (mCRC). However, it was discovered that patients with activating mutations in exon 2 (codons 12/13) of the KRAS gene do not respond to this therapy, establishing them as the first negative predictors of response to anti-EGFR therapy. The KRAS gene, an effector of EGFR signaling through the RAS/RAF/ERK pathway, is mutated in exon 2 in about 40% of all mCRC. In KRAS exon 2 wild-type patients, only 40 to 60% achieve a response when receiving this therapy, something that suggests that alterations in other EGFR downstream effectors may also be associated with the lack of response to this therapy. Recently, the importance of less frequent KRAS and NRAS (RAS) mutations has been uncovered based on new results from recent clinical trials, which reported that patients with rarer activating RAS mutations also do not benefit from anti-EGFR therapy. This information shows the need to identify new predictive biomarkers that might help to select patients who are most likely to benefit from anti-EGFR. In a consecutive series of 241 mCRC samples, wild-type for KRAS codons 12 and 13, we searched for less frequent RAS mutations that might act as predictor of response to anti-EGFR therapy, namely mutations in less frequent mutational hotspots in KRAS (exon 3 and 4) and NRAS (exons 2, 3 and 4). About 19% (46/241) of the cases evaluated had a mutation in the analyzed regions. All mutations were found in heteregozity and were mutually exclusive. Thirty cases (12.4%; 30/241) had a KRAS mutation and sixteen (6.6%; 16/241) had a NRAS mutation, with the following distribution: thirteen mutations were found in KRAS exon 3 (28.3%; 13/46), seventeen in KRAS exon 4 (37.0%; 17/46), eight in NRAS exon 2 (17.4%; 8/46) and eight in NRAS exon 3 (17.4%; 8/46). No mutations were found in exon 4 of the NRAS gene. One novel point mutation, not previously described in CRC, was found in exon 3 of the NRAS gene in two cases. KRAS mutations were more frequent in earlier than in later stages at diagnosis (P=0.001). In conclusion, nearly one-fifth of mCRC patients wild-type for KRAS exon 2 (codons 12/13) present other, less frequent, RAS mutations that might be associated with lack of response to anti-EGFR therapy. However, further studies are necessary to confirm these mutations as negative predictors of response to this therapy in the patients of our series. V RESUMO O recetor de fator de crescimento epidérmico (EGFR) é uma tirosina cinase transmembranar que, após ativação, inicia diversas vias de transdução de sinal, tais como a via RAS/RAF/ERK, cuja atividade está frequentemente desregulada em carcinomas colo-retais. Dois anticorpos monoclonais dirigidos ao EGFR, cetuximab e panitumumab, provaram ser eficazes no tratamento do cancro colo-retal metastático. No entanto, foi descoberto que indivíduos com mutações ativantes nos codões 12 e 13 do gene KRAS não beneficiam deste tratamento, o que as torna no primeiro biomarcador preditivo de ausência de resposta à terapia anti-EGFR. O gene KRAS, um efetor do EGFR através da via de transdução de sinal RAS/RAF/ERK, está mutado no exão 2 em cerca de 40% dos carcinomas colo-retais metastáticos. Dos doentes sem mutação no exão 2 do KRAS, só 40 a 60% respondem ao tratamento, o que sugere que alterações noutras proteínas efetoras do EGFR poderão estar envolvidas nesta ausência de resposta. Recentemente, foi revelada a importância de mutações menos frequentes nos genes KRAS e NRAS (RAS) em ensaios clínicos, que reportaram que indivíduos com estas mutações não beneficiam do tratamento com anti-EGFR. Numa série consecutiva de 241 casos de carcinoma colo-retal metastático, sem mutações nos codões 12 e 13 do KRAS, procurámos mutações RAS menos frequentes que possam ser usadas como biomarcadores preditivos de resposta à terapia com cetuximab e panitumumab. Em particular, foram pesquisadas mutações noutros codões do KRAS (exões 3 e 4) e do NRAS (exões 2, 3 e 4). Cerca de 19% (46/241) dos casos analisados apresentavam uma mutação nas regiões analisadas. Todas as mutações foram encontradas em heterozigotia e eram mutuamente exclusivas. Trinta casos (12,4%; 30/241) tinham uma mutação no KRAS e dezasseis (6,6%; 16/241) no NRAS, com a seguinte distribuição: treze mutações no exão 3 (28,3%; 13/46) e dezassete no exão 4 (37,0%; 17/46) do KRAS; oito no exão 2 (17,4%; 8/46) e oito no exão 3 (17,4%; 8/46) do NRAS. Não foram encontradas mutações no exão 4 do gene NRAS. Uma mutação pontual nova, não descrita em cancro colo-retal, foi encontrada no exão 3 do NRAS em dois casos. As mutações no KRAS foram mais frequentes nos estádios mais precoces do que nos mais tardios na altura do diagnóstico (p=0,001). Em conclusão, aproximadamente um quinto dos doentes com cancro colo-retal metastático, sem mutações nos codões 12 e 13 do KRAS, apresentam outras mutações RAS menos frequentes que podem estar associadas à ausência de resposta à terapia XIII RELEVANT ABREVIATIONS AKT – v-akt murine thymoma viral oncogene homolog APC – Adenomatous polyposis coli ARAF – v-raf murine sarcoma 3611 viral oncogene homolog BAX – BCL2-associated X protein BRAF – v-raf murine leukemia viral oncogene homolog B1 CCND1 – Cyclin D1 encoding gene CDK8 – Cyclin-dependent kinase 8 c-RAF1 – v-raf-1 murine leukemia viral oncogene homolog 1 CRC – Colorectal cancer CTNNB1 – Catenin beta 1 DCC – Deleted in colorectal cancer DNA – Deoxyribonucleic acid dNTP – Deoxyribonucleotide triphosphate EGF – Epidermal growth factor EGFR – Epidermal growth factor receptor ERBB1 – see HER1 ERBB2 – see HER2 ERBB3 – see HER3 ERBB4 – see HER4 ERK – elk-related tyrosine kinase ERK1 – elk-related tyrosine kinase 1 ERK2 – elk-related tyrosine kinase 2 FISH – Fluorescent in situ hybridization G-domain – Guanine nucleotide-binding domain GDP – Guanosine diphosphate G-protein – Guanine nucleotide-binding protein Grb2 – Growth factor receptor-bound protein 2 GTP – Guanosine triphosphate HER1 – Epidermal growth factor receptor HER2 – v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 HER3 – v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 HER4 – v-erb-b2 erythroblastic leukemia viral oncogene homolog 4 HRAS – v-H-ras Harvey rat sarcoma viral oncogene homolog IgG1 – Immunoglobulin G subclass 1 XIV IgG2 – Immunoglobulin G subclass 2 IGFIIR – Insulin-like growth factor 2 receptor JAK – Janus kinase KRAS – Kirsten rat sarcoma-2 viral (v-Ki-ras2) oncogene MAPK – Mitogen-activated protein kinase mCRC – Metastatic colorectal cancer MEK – Mitogen-activated protein kinase kinase MEK1 – Mitogen-activated protein kinase kinase 1 MEK2 – Mitogen-activated protein kinase kinase 2 MGMT – O(6)-methylguanine-DNA methyltransferase MLH1 – mutL homolog 1 MSH2 – mutS homolog 2 MSH3 – mutS homolog 3 MSH6 – mutS homolog 6 mTor – Mechanistic target of rapamycin NRAS – Neuroblastoma RAS viral (v-ras) oncogene homolog PCR – Polymerase chain reaction PI3K – Phosphoinositide-3-kinase PIK3CA – Phosphoinositide-3-kinase, catalytic, alpha polypeptide PTEN – Phosphatase and tensin homolog PLCϒ – Phospholipase C gamma SH2 – Src homolog 2 SMAD2 – SMAD family member 2 SMAD4 – SMAD family member 4 SOS – Son of sevenless STAT – Sterol O-acyltransferase 1 TCF – T cell-factor TGF-  – Transforming growth factor  TGF-β – Transforming growth factor β TGFβRII – Transforming growth factor β receptor type II TP53 – Tumor protein p53 VEGF – Vascular endothelial growth factor VEGFR – Vascular endothelial growth factor receptor I NTRODUCTION INTRODUCTION 3 I. INTRODUCTION With over 14 million new cancer cases and 8.2 million cancer deaths estimated to have occurred in 2012 (IARC, 2013), cancer is among the leading causes of death in the world. The burden of this malignancy seems to be increasing in economic developing countries, mostly due to population aging and growth, as well as a result of an increasing adoption of cancer-associated behaviors, such as smoking (Jemal et al., 2011). Despite increasing awareness, colorectal cancer (CRC) remains as one of the most common cancers worldwide. Epidemiology CRC is a major cause of morbidity and mortality throughout the world, with over 1.3 million new cases diagnosed in 2012 (Figure 1). Europe and North America are among the regions with the highest incidence rates for this type of cancer. This rate is rapidly increasing in several areas that are considered as low risk areas, such as Eastern Asia. This might be the reflection of changes in dietary and lifestyle factors associated with “westernization”, like smoking or obesity. In contrast to these high incidence trends, the occurrence of this pathology seems to be decreasing in several parts of the world, including the United States, probably due to population screening schemes that allow early detection of CRC and removal of precancerous lesions (Jemal et al., 2011; Ferlay et al., 2013; IARC, 2013). MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 4 In 2012, CRC was the second most common malignancy in Europe (excluding nonmelanoma skin cancers), with 464.000 newly diagnosed cases estimated to have occurred, which accounts for 12.1% of all cancer cases. It had the third highest incidence in men, following prostate and lung cancer, and the second in women, only surpassed by breast cancer. This malignancy is slightly more incident in men than in women. It was also the second most frequent cause of death by cancer, with almost 215 000 deaths estimated, which accounts for 12.2% of all cancer deaths (Ferlay et al., 2013). In terms of CRC incidence and mortality, Portugal follows the same patterns of Europe (Figure 2). In 2012, it was the highest incident malignancy, with 7129 new cases diagnosed. Data analysis by sex demonstrated that CRC has the second highest incidence in both sexes, after prostate (male) and breast cancer (female). It was also the leading cause of death by cancer, with 3797 deaths, which accounts for 15.7% of all cancer deaths (Ferlay et al., 2013; IARC, 2013). Figure 1. Estimated age-standardised incidence and mortality rates of CRC for male and female, in the world [Globocan, 2012 (IARC, 2013)]. INTRODUCTION 5 Risk Factors CRC is a very complex and heterogeneous disease and several etiologic factors contribute to the appearance of this malignancy. The risk of developing CRC increases with age, preferentially after the age of 40. It is estimated that more than 90% of the patients diagnosed with this malignancy are aged 50 or older (Amersi et al., 2005; Haggar & Boushey, 2009). CRC usually occurs in one of three patterns: inherited, familial or sporadic. Inherited forms are responsible for about 5-10% of all CRC cancers, and are related to recognized hereditary conditions (Figure 3). The most common are familial adenomatous polyposis (FAP) and hereditary nonpolyposis colorectal cancer (HNPCC), also know as Lynch syndrome, which are responsible for 1% and 2%-4% of all CRC cases, respectively (Amersi et al., 2005; Rustgi, 2007; Haggar & Boushey, 2009; Jasperson et al., 2010). Other inherited diseases that lead to an increased risk of CRC are MUYTH-associated polyposis (MAP), Peutz-Jeghers syndrome (PJS) and juvenile polyposis syndrome (JPS) (Rustgi, 2007; Jasperson et al., 2010). Familial cases are defined as families with increased predisposition to cancer, probably due to an hereditary basis with the involvement of genes that are less penetrant and/or the sign of shared environmental and lifestyle factors. It is estimated that about 20-30% of all CRC cases occur in this context (Rustgi, 2007; Jasperson et al., 2010). A B Figure 2. Estimated age-standardised incidence and mortality rates of CRC for male and female, in A) Europe and B) Portugal [Globocan, 2012 (IARC, 2013)]. MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 6 Although genetics, family history and susceptibility factors play an important role in the development of this disease, the majority of CRCs are sporadic (~70%), with no prior family history (Haggar & Boushey, 2009). Several epidemiological studies have confirmed the influence of numerous environmental and dietary factors in the etiology of this disease, such as a diet high in fat and low in fiber, a sedentary lifestyle, obesity, diabetes, cigarette smoking and alcohol abuse (Haggar & Boushey, 2009; Chan & Giovannucci, 2010; Gingras & Beliveau, 2011; Colussi et al., 2013). Physical activity, on the other hand, is thought to lower CRC risk. In fact, several studies report that higher overall levels of physical activity are associated with a decreased risk of CRC of ~20% (Huxley et al., 2009). Another risk factor is the presence of chronic inflammatory bowel diseases (IBD), such as Crohn’s disease or ulcerative colitis (Ilyas et al., 1999; Colussi et al., 2013). CRC Diagnosis and Staging CRC diagnosis is usually made after the onset of the symptomatology of the disease, but most of the symptoms (rectal bleeding, blood in the stools, change in bowel habits) are non-specific and consistent with other conditions besides CRC. This, along with the fact that most patients with an early-stage disease are asymptomatic, presents difficulties when trying to diagnose this disease. The most common screening techniques are the fecal occult blood test and/or colonoscopy, the latter allowing direct inspection of the entire colon and same-session biopsy necessary for histopathological diagnosis. Patients should also undergo a physical examination and may perform computed tomography (CT), magnetic resonance imaging (MRI) or fluorodeoxyglucose-positron emission Figure 3. Circle graph depicting the genotypic and phenotypic heterogeneity in CRC [adapted from (Lynch et al., 2009)]. INTRODUCTION 7 tomography (FDG-PET), which allow the identification and characterization of a possible metastatic disease (Levin et al., 2008; Van Cutsem, Nordlinger, et al., 2010; Cummings & Cooper, 2011). Once diagnosis is made, it is necessary to stage the tumor according to its pathological characteristics. Staging assessment is a key factor used to define treatment and to estimate the chance of a successful treatment outcome. The most common staging system for CRC is the TNM system (Centelles, 2012). Each of the three letters of the TNM system (Table 1), according to the American Joint Committee on Cancer (AJCC), stand for a specific meaning in regard to the characteristics of the tumor: T - size and/or extent (reach) of the primary tumor; N - amount of spread to nearby lymph nodes; and M - presence of metastasis or secondary tumors caused by the spread of cancer cells to other parts of the body (Edge et al., 2010; Centelles, 2012). It is also important to report the timing of the staging assessment. Clinical staging – or cTNM – includes any information obtained before initiation of any kind of preoperative treatment. Pathological staging – pTNM – is defined by the information obtained after the examination of the surgically removed tissues (Edge et al., 2010). Table 1. AJCC cancer stanging for colon and rectal carcinomas [adapted from (Shia et al., 2012)]. Primary Tumor (T) Tx Primary tumor cannot be assessed T0 No evidence of primary tumor Tis Carcinoma in situ: intraepithelial or invasion of lamina propria T1 Tumor invades submucosa T2 Tumor invades muscularis propria T3 Tumor invades muscularis propria into pericolorectal tissues T4a Tumor penetrates to the surface of the visceral perinoteum T4b Tumor directly invades or is adherent to other organs or structures Regional Lymph Nodes (N) Nx Regional lymph nodes cannot be assessed N0 No regional lymph node metastasis N1 Metastasis in 1 to 3 regional lymph nodes N1a Metastasis in 1 regional lymph node N1b Metastasis in 2-3 regional lymph nodes N1c Tumor deposit(s) in the subserosa, mesentery, or nonperitonealized pericolic or perirectal tissues without regional nodal metastasis N2 Metastasis in 4 or more regional lymph nodes N2a Metastasis in 4-6 regional lymph nodes N2b Metastasis in 7 or more regional lymph nodes Distant Metastasis (M) M0 No distant metastasis (no pathological M0; use clinical M to complete stage group) M1 Distant metastasis M1a Metastasis confined to 1 organ or site (eg. liver, lung, ovary, nonregional node) M1b Metastases in more than 1 organ/site or the peritoneum MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 14 Other pathways involved in CIN SMAD2, SMAD4 and DCC genes are all located in the long arm of chromosome 18 (18q21.1). SMAD2 and SMAD4 are transcription factors involved in the TGF-β signaling pathway that regulates growth as well as apoptosis. The DCC gene codes for a large membrane receptor protein, from the immunoglobulin superfamily, that promotes apoptosis in the absence of its ligand (netrin-1) (Ilyas et al., 1999; Worthley et al., 2007). LOH of 18q is associated with negative prognosis and is reported in up to 60% of CRCs (Worthley et al., 2007; Colussi et al., 2013). Mutations in the phosphoinositide-3 kinase gene (PIK3CA), detected in approximately a third of CRCs, often occur simultaneously with APC mutations, and cause increased AKT signaling even without the presence of growth factors. They also interact with a central regulator of cell growth and metabolism (mTOR) and with KRAS. Additionally, the phosphatase and tensin homolog (PTEN), which acts as a tumor suppressor gene in this pathway due to its inhibitory effect on PI3K-AKT signaling, is silenced in nearly 30% of CRC (Kanthan et al., 2012; Yu et al., 2014). Microsatellite instability (MSI) pathway Microsatellites are short repeat nucleotide sequences located throughout the genome, in both coding and non-coding regions. Because of their repetitive structure, they are prone to errors that occur during DNA replication. Those errors are recognized and repaired by the DNA Mismatch Repair (MMR) system during replication, which ensures a correct DNA synthesis (Al-Sohaily et al., 2012; Kanthan et al., 2012). The MMR system is composed of multiple interacting proteins, such as MSH2 and MLH1, and mutations in the genes encoding these proteins lead to the inactivation of the MMR system and the accumulation of several DNA replication errors, resulting in MSI (Ilyas et al., 1999; Markowitz & Bertagnolli, 2009; Al-Sohaily et al., 2012; Kanthan et al., 2012). MSI is the hallmark of the HNPCC syndrome, originated by MMR germline mutations. This pathway is also involved in the genesis of approximately 15% of sporadic CRC cases and is mostly caused by epigenetic silencing of the MLH1 gene promoter (Al-Sohaily et al., 2012; Kanthan et al., 2012; Colussi et al., 2013; Bogaert & Prenen, 2014). Tumors that develop through this particular pathway present a different phenotype from CIN positive CRCs: they are more likely to arise in the proximal colon, are poorly differentiated, often exhibit lymphocytic infiltration and, in general, patients affected by MSI-high (MSI-H) CRCs present better prognosis and survival. Sporadic MSI-H tumors are also characterized by a low frequency of APC, CTNNB1 and KRAS mutations and a high INTRODUCTION 15 frequency of BRAF mutations, a member of the RAF family involved in the mediation of cellular response through the RAS-RAF-ERK pathway. Several other genes, such as TGFβRII and BAX, are also mutated in these CRCs. TGFβRII inactivating mutations are found in more than 80% of all MSI-H CRCs and are involved in the adenoma transition to high-grade dysplasia or metastatic carcinoma. Mutations in the SMAD2 and SMAD4 genes, involved in the deactivation of TGFβ signaling, are also common in MSI-H CRCs. The pro-apoptotic tumor suppressor gene BAX is mutated in 50% of CRCs cases and allows tumor cells to evade the intrinsic apoptosis mechanisms. Additionally, mutations in other genes, such as MSH3 and MSH6, Insulin Growth Factor Type 2 Receptor (IGFIIR) or CCND1, are also frequently present in MSI-H CRCs, although at a lower frequency then the ones mentioned above (Colussi et al., 2013). CpG island methylator phenotype (CIMP) This third pathway, present in approximately 20 to 30% of CRC, consists of the aberrant hypermethylation of the CpG dinucleotide sequences localized in the promoter regions of genes involved in several functions, such as cell cycle regulation, apoptosis, DNA repair and invasion. This hypermethylation results in gene silencing, which provides an alternative mechanism for loss of function of tumor suppressor genes. In fact, the epigenetic silencing of a gene is biologically equivalent to acquiring an inactivating mutation, so it can occur as a first, second or both hits to inhibit gene expression (Worthley et al., 2007; Markowitz & Bertagnolli, 2009; Al-Sohaily et al., 2012; Colussi et al., 2013). CIMP tumors are classified as CIMP-high (CIMP-H) or CIMP-low (CIMP-L), based on the number of methylated markers (Al-Sohaily et al., 2012; Colussi et al., 2013). CIMP-H CRCs often contain BRAF gene mutations, which are associated with increased cell growth and progression of carcinogenesis. BRAF V600E (Val600Glu) mutation is present in 80 to 90% of CRC cases with sessile serrated adenomas (SSA) but is mostly absent in conventional adenomas. Additionally, BRAF mutations are present in early hyperplastic polyps (the serrated precursors) or in late dysplastic serrated adenomas that frequently have CIMP-H and MSI-H features, which leads to the hypothesis that the serrated pathway is involved in the sporadic CIMP CRCs development (Worthley et al., 2007; Leggett & Whitehall, 2010; Colussi et al., 2013). Clinically, CIMP-H tumors have a particularly poor prognosis and are usually located in the proximal site of the colon, similar to MSI tumors (Worthley et al., 2007; Bogaert & Prenen, 2014). On the other hand, CIMP-L tumors have a low level of DNA methylation MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 16 and, instead of the BRAF mutations observed in CIMP-H tumors, they are usually associated with KRAS and MGMT mutations (Worthley et al., 2007; Colussi et al., 2013; Bogaert & Prenen, 2014). KRAS and NRAS mutational status and its importance in CRC treatment The disclosure that patients with activating KRAS gene mutations do no benefit from anti-EGFR therapy (cetuximab or panitumumab) surfaced after a series of initial retrospective analyses. This made KRAS mutations emerge as the only negative biomarker predictor of response to this therapy. To better understand how KRAS activating mutations influence anti-EGFR therapy’s efficacy, it is necessary to understand the link between EGFR and RAS in CRC. EGFR signaling pathways in CRC EGFR, also known as HER1/ERBB1, belongs to the ErbB family of receptor TKs, which comprises three other members: HER2 (ERBB2/neu), HER3 (ERBB3) and HER4 (ERBB4). All proteins of this family are anchored in the cytoplasmic membrane and share a similar structure composed by an extracellular ligand-binding domain, a single hydrophobic transmembrane domain and a cytoplasmic TK-containing domain (Spano et al., 2005; Normanno et al., 2006; Scaltriti & Baselga, 2006). In normal cells, EGFR signaling pathway is activated in a ligand-dependent manner. ErbB family members can be activated by several known ligands, such as epidermal growth factor (EGF), transforming growth factor α (TGF-α), amphiregulin and epiregulin, that bind specifically to EGFR (Hynes & MacDonald, 2009). Figure 6. Genetic instability pathways and their overlapping relationships [adapted from (Markowitz & Bertagnolli, 2009)]. INTRODUCTION 17 EGFR activation by ligand binding induces the dimerization of the receptor with formation of homoand heterodimers that leads to autophosphorylation of specific tyrosine residues within the cytoplasmic tail of the receptors, initiating intracellular signaling via several pathways, namely RAS/RAF/ERK, PI3K/AKT, JAK/STAT and PLCϒ (Figure 7) (Normanno et al., 2006; Scaltriti & Baselga, 2006). These signal transduction cascades are responsible for diverse cellular responses, such as proliferation, migration, differentiation and apoptosis. Constitutional activation of these pathways can be achieved by receptor overexpression or activating mutations, which are common in several malignancies, including CRC (Normanno et al., 2006; Roberts & Der, 2007). The RAS/RAF/ERK pathway The RAS/RAF/ERK pathway is one of the most deregulated signaling pathways in human cancer. In this pathway, RAS activation leads to a sequential activation of three MAPKs (RAF, MEK and ERK), which in turn generate signals that promote regulation of several cellular responses that establish cell proliferation, survival and differentiation (Dhillon et al., 2007; Roberts & Der, 2007). Figure 7. EGFR signaling pathways [adapted from (Scaltriti & Baselga, 2006)]. MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 18 RAS proteins – KRAS, HRAS and NRAS – are important components of a large family of small GTP-binding proteins. These three members of the RAS family are composed of a C-terminal and N-terminal regions, both important for RAS proteins functions. The Cterminal region contains a CAAX motif, which is the target of post-translational modifications that allow the recruitment of the proteins to the inner face of the plasma membrane, essential for their normal function (Downward, 2003; Karnoub & Weinberg, 2008). On the other hand, the N-terminal region is an important regulator of the protein GDP-bound and GTP-bound states. The structural differences between these states reside in two regions of the N-terminal, the switch I and switch II regions. Binding of the GTP molecule alters the conformation of both switch regions and allows the RAS protein to remain in an active state. Upon the release of the GTP’s extra phosphate group, the switch regions modify their conformation and return to the inactive state (Karnoub & Weinberg, 2008; Santarpia et al., 2012). This GDP/GTP cyclic process is catalyzed by guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs), with the former facilitating the exchange from GDP to GTP and the latter promoting the hydrolysis of GTP to GDP (Figure 8). The balance between these proteins is important to determine the activation of the RAS protein and its downstream target pathways (Downward, 2003; Santarpia et al., 2012). In normal cells, RAS becomes activated upon extracellular stimuli, which activate receptor TKs such as EGFR. The autophosphorylated receptor then binds to the SH2 domain of the adaptor protein growth-factor-receptor-bound protein 2 (GRB2). Since the SOS (GEF) is connected to the same adaptor protein in the SH3 domain, the binding of the receptor to the GRB2 brings SOS in close proximity to the RAS protein, leading to its activation (Downward, 2003; Roberts & Der, 2007). Activated RAS interacts with three closely related RAF kinases (c-RAF1, BRAF and ARAF), mobilizing them to the plasma membrane, where they become activated. Then, Raf kinases phosphorylate MEK1 and MEK2 (MAPKKs), which in turns triggers the phosphorylation and activation of MAPKs (ERK1 and ERK2) (Figure 9). Once activated, ERK1 and ERK2 are translocated to the Figure 8. Upstream signaling of RAS and its control by the GDPGTP cycle [adapted from (Downward, 2003)]. INTRODUCTION 19 nucleus, where they regulate the activity of various transcription factors (Downward, 2003; Roberts & Der, 2007; Santarpia et al., 2012). Since this is a complex signaling pathway that ensures essential cellular responses, its deregulation is an important key factor to cancer progression. Several mechanisms, such as KRAS and BRAF activating mutations or EGFR overexpression, contribute to an improper activation of the pathway and have been described in several tumor types, including CRC. Furthermore, it was also identified that Erk activation can induce upregulation of EGFR ligands, which promotes an autocrine growth loop crucial for tumor growth (Roberts & Der, 2007; Santarpia et al., 2012). Predictive biomarkers of anti-EGFR therapy response As stated before, several retrospective studies of KRAS mutational status in tumors from patients treated with anti-EGFR therapy found that activating mutations in KRAS codons 12 and 13 were associated with a lack of response to these therapies (Table 3a and 3b). Mutations in these particular codons in KRAS exon 2, present in nearly 40% of all mCRC patients, cause constitutive activation of the RAS/ /ERK pathway, despite EGFR inhibition. Thus, screening for these mutations is recommended before therapy, since only patients with KRAS wild-type mCRC will benefit from it. However, among those patients with KRAS exon 2 wild-type tumors, only 40-60% responds to anti-EGFR therapy (De Roock et al., 2008; Lievre et al., 2008). This suggests that other activating mutations along this pathway may also confer resistance to anti-EGFR therapies. So, there is a Figure 9. Oncogenic activation of the RAS/RAF/ERK signaling pathway [adapted from (Roberts & Der, 2007)]. MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 20 great need to identify alternative predictive biomarkers that will distinguish patients who are most likely to benefit from this type of therapy. The first attempts to identify such biomarkers led to the discovery that positive EGFR overexpression (determined by immunohistochemistry) has no correlation with treatment response (Chung et al., 2005) and that the association between increased EGFR gene copy number (detected by FISH) and treatment response remains uncertain/controversial (Moroni et al., 2005; Laurent-Puig et al., 2009). These findings make it difficult to establish EGFR alterations as predictive biomarkers for treatment response. However, several studies have been focusing in the analysis of other targets, such as other EGFR downstream effectors (BRAF, NRAS, and PIK3CA), as well as less frequent KRAS mutations (De Roock et al., 2010; Guedes et al., 2013). Recent analyses of tumors from patients enrolled in clinical trials demonstrated that other KRAS (codons 59/61 – exon 3; codons 117/146 – exon 4) or NRAS (codons 12/13 – exon 2; codons 59/61 – exon 3; codons 117/146 – exon 4) mutations lead to increased levels of RAS-GTP. These recent studies also reported that most patients harboring these rarer mutations did not achieve an objective response with anti-EGFR therapy (Douillard et al., 2013; Seymour et al., 2013). Given this, recent guidelines for anti-EGFR CRC treatment recommend the evaluation of the mutational status of the three exons of both genes before treatment initiation with anti-EGFR therapy. Table 3. Design characteristics used in A) meta-analysis and B) the change in median progression-free survival in KRAS wild-type and mutant groups of each study [adapted from (Adelstein et al., 2011)]. A INTRODUCTION 21 1(Amado et al., 2008) 2(Karapetis et al., 2008) 3(Van Cutsem et al., 2009) 4(Van Cutsem, Lang, et al., 2010) 5(Peeters et al., 2010) 6(Bokemeyer et al., 2009) 7(Bokemeyer et al., 2011) 8(Maughan et al., 2010) 9(Douillard et al., 2010) 10(Tveit et al., 2010) 11(Hecht et al., 2009) 12(Tol et al., 2009) B A AIMS OF THE STUDY MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 30 DNA extraction from formalin-fixed paraffin-embedded tissue Whenever possible, tumor areas containing at least 50% of tumor cells were delimited, by a pathologist, in the hematoxylin and eosin (H&E) stained slides of each sample. The corresponding unstained slides were immersed in xylene [SIGMA] and twice in ethanol 100% [Merck] for 5 minutes each. Tumor areas, which were previously delimited by comparison with the correspondent H&E stained slides, were macrodissected and transferred to a microcentrifuge tube. DNA was isolated using the QIAamp® DNA FFPE Tissue Kit [QIAGEN], following manufacturer’s instructions. Finally, DNA was quantified by spectrophotometry with NanoDrop ND-1000® [NanoDrop Technologies]. Mutational status analysis All samples were initially screened by HRM for mutations in KRAS (NM_004985) exons 3 and 4 and NRAS (NM_002524.4) exons 2, 3 and 4, followed by automated DNA Sanger sequencing of one strand (forward or reverse), in order to evaluate the presence/absence of DNA alterations. A second HRM was performed in all positive samples of the initial analysis, followed by automated DNA Sanger sequencing of both strands. High Resolution Melting PCR amplification and HRM analysis were both performed on a LightCycler-480 II Real-Time System [Roche Diagnostics]. The PCR reaction mixture added to each well, of a 96 well plate, was composed of a pair of primers (forward and reverse), DNA of each sample and PCR reagents (Table 4). To prevent contamination and/or evaporation, 15µL of mineral oil were added to each well. The plate was then sealed with sealing film and centrifuged at 2000rpm for 2 minutes. Table 4. Components of the PCR reaction mixture. PCR reaction mixture components 2,5x LightScanner® Master Mix [Idaho] 4.0µL Forward primer [frilabo] 350nM Reverse primer [frilabo] 350nM DNA 20-100ng Reagent grade water [Idaho] 4.9µL Total reaction volume 10µL The primer pairs used in this study for NRAS exons 2, 3 and 4 and KRAS 3 and 4 were all designed with primer-BLAST software (http://www.ncbi.nlm.nih.gov/tools/primer-blast) and are available upon request to the Department of Genetics of IPO-Porto. MATERIALS AND METHODS 31 PCR amplification and HRM conditions were the same for all NRAS exons and for KRAS exon 3. KRAS exon 4 conditions differed from those applied to the exons mentioned above. However, all exons were subjected to an initial denaturation, followed by 35-40 cycles of amplification. After that, one cycle of heteroduplex and one of melting were done before the plate was cooled to 40ºC. The detailed conditions are described, separately, below: I. For all NRAS exons and for KRAS exon 3: An initial denaturation at 95ºC for 15 minutes was followed by 35 cycles of 10 seconds at 95ºC, 20 seconds at 69ºC and 30 seconds at 72ºC. After that, one heteroduplex cycle was done at 97ºC for 1 minute and 40ºC for 2 minutes, followed by one melting cycle from 70ºC to 95ºC with 25acquisitions/ºC. The plate was finally cooled to 40ºC for 1 minute with a ramp rate of 2.2ºC/second. II. For KRAS exon 4: Initial denaturation was done at 95ºC for 10 minutes and followed by 35 cycles of 20 seconds at 95ºC, 20 seconds at 65ºC and 20 seconds at 72ºC, with a final extension of 10 minutes at 72ºC. One heteroduplex and one melting cycle were done after that, with the samples being denatured with an initial hold of 5 minutes at 95ºC and 1 minute at 40ºC (heteroduplex cycle), followed by a melting profile from 70ºC to 90ºC with 25acquisitions/ºC (melting cycle). The plate was cooled to 40ºC in the same conditions as described before for all NRAS exons and KRAS exon 3. Amplification and melting curves were obtained and analyzed using the LightCycler® 480 Gene Scanning software v1.5 [Roche diagnostics]. Figure 10. High resolution melting analysis of KRAS exon 3. A) Normalized and B) difference graph, with wild-type (blue) and mutated (green and red) samples. A B MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 32 DNA Sequencing Before sequencing, all PCR amplification products were purified to remove excess of primers, salts, enzymes and dNTPs from the previous reaction. For that purpose, Illustra GFX PCR DNA and Gel Bad Purification Kit [GE Healthcare Life Sciences] and NZYGelpure Kit [nzytech] were used, according to the manufacturer’s protocol. After that, 1µL of each sample product was used for the sequencing reaction, which also contained 0.5µL of Big Dye® Terminator v1.1 cycle sequencing Ready Reaction Mix [Applied Biosystems], 3.4µL of Big Dye® Terminator v1.1, v1.3 5x sequencing buffer [Applied Biosystems], 350nM of one of the primers (forward or reverse) and 4.78µL of bidestilled sterile water [B. Braun], to a total volume of 10µL. Samples were then subjected to an initial denaturation at 95ºC for 4 minutes, followed by 35 cycles of 95ºC for 10 seconds, 50ºC for 10 seconds and 60ºC for 2 minutes, with a final extension of 60ºC for 10 minutes. PCR sequencing products were purified using Illustra Sephadex® G-50 fine [GE Healthcare Life Sciences] and added to 12µL of Hi-DiTM Formamide [Applied Biosystems]. The products were then run in either an ABI PRISMTM 310 Genetic Analyzer [Applied Biosystems] or a 3500 Genetic Analyzer [Applied Biosystems]. Electropherograms of each sample were analyzed with the Sequencing Analysis Software v5.4 [Applied Biosystems]. All of them were read at least twice, reviewed manually and with the Mutation Surveyor Software v4.0.8. Statistical analysis Statistical analysis was performed using either Qui-square or Fisher’s exact tests to assess statistical differences between the variants. Associations were considered statistically significant when P≤0.05. Statistical analysis was performed with the SPSS Statistics software package v.22.0. A B Figure 11. Electropherogram of KRAS exon 3 sequence, with A) a wild-type and B) a mutated sample. R ESULTS RESULTS 35 IV. RESULTS DNA from a total of 241 KRAS exon 2 wild-type mCRC samples were screened in parallel for mutations in exons 3 and 4 of KRAS and exons 2, 3 and 4 of NRAS by HRM and automated sequencing. Automated sequencing of the HRM products confirmed the presence of 46 mutations (19.1%) in KRAS exons 3/4 or NRAS exons 2/3/4, with the remaining 80.9% (195/241) being wild-type for all regions studied. All mutations were found in heterozygosity and as a single mutation. Table 5. Mutational status of the 241 mCRC samples analyzed. Samples Mutational Status Frequencies Mutant 46 Wild-type 195 Total 241 Mutational Type and Distribution Overall, 12.4% (30/241) of the cases presented a mutation in KRAS and 6.6% (16/241) were NRAS mutated. The mutational distribution of the 46 positive cases was as follows: 65.2% (30/46) in KRAS, with 28.3% (13/46) in KRAS exon 3 and 37.0% (17/46) in KRAS exon 4, and 34.8% (16/46) in NRAS, with 17.4% (8/46) in NRAS exon 2 and 17.4% (8/46) MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 36 in NRAS exon 3 (Figure 12). No mutations were found in exon 4 of NRAS. The individual mutations found in each gene are presented in Tables 6 and 7. Eleven different mutations were found in KRAS and seven different mutations were detected in NRAS. In all but two cases the mutations were missense, whereas the remaining two cases had an in frame duplication and an in frame deletion in KRAS exon 3. Table 6. KRAS mutations identified after automated sequencing. KRAS Case Exon Mutation Nr. 73 3 c.151_195dup p.Cys51_Ser65dup 1 5 3 c.176_178del p.Asp59del 1 216 3 c.175G>A p.Ala59Thr 1 175 3 c.179G>A p.Gly60Asp 1 68, 87, 138, 141, 192 3 c.182A>T p.Gln61Leu 5 39, 84, 209 3 c.183A>C p.Gln61His 3 224 3 c.183A>T p.Gln61His 1 78, 93, 213 4 c.351A>T p.Lys117Asn 3 165 4 c.351A>C p.Lys117Asn 1 19, 30, 47, 49, 108, 119, 120, 131, 173, 200, 235 4 c.436G>A p.Ala146Thr 11 149, 164 4 c.437C>T p.Ala146Val 2 Total 30 Figure 12. Distribution (%) of the 46 mutations detected in all analyzed exons in mCRC samples. RESULTS 37 B p.Gln61His Table 7. NRAS mutations identified after automated sequencing NRAS Case Exon Mutation Nr. 31, 88 2 c.34G>T p.Gly12Cys 2 40, 64, 118, 220, 228 2 c.35G>A p.Gly12Asp 5 139 2 c.37G>C p.Gly13Arg 1 13, 26, 227 3 c.181C>A p.Gln61Lys 3 38, 111 3 c.182A>G p.Gln61Arg 2 124 3 c.182A>T p.Gln61Leu 1 4, 52 3 c.183A>T p.Gln61His 2 Total 16 Novel Mutations Of the 11 different KRAS mutations and seven different NRAS mutations identified in this study, the mutation c.183A>T, p.Gln61His, is novel (Figure 13) and the remaining 17 mutations have previously been reported in the COSMIC database (COSMIC) or in the literature. A Figure 13. Electropherograms of the mutation found in NRAS exon 3 that was not previously described, with A) wild-type and B) mutant sample. MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 38 Clinicopathological Associations The establishment of associations between the tumor genetic alterations and clinicopathological features was possible in 215 out of 241 cases. Mutation frequencies in this subgroup are described below (Table 8/Figure 14). Quisquare or Fisher’s exact tests (each one used when appropriate) were done to assess differences between KRAS and NRAS mutation distribution and the following variables: sex, age and stage at diagnosis, and primary tumor site. Table 8. Mutational status in the subgroup of cases with available clinical data. Samples Mutational Status Frequencies KRAS mutant 28 NRAS mutant 12 Wild-type 175 Total 215 Figure 14. Mutational status (%) in the subgroup of cases with available clinical data. RESULTS 39 Table 9. Distribution of KRAS and NRAS mutations according to patient sex. No differences were found regarding KRAS or NRAS mutation distribution by patient gender: 12.1% in men vs. 15.2% in women (p=0.537) for KRAS and 4.7% in men vs. 7.6% in women (p=0.520) for NRAS. Sex KRAS Total Wild-Type Mutant Men 131 18 149 Women 56 10 66 Total 187 28 215 Sex NRAS Total Wild-Type Mutant Men 142 7 149 Women 61 5 66 Total 203 12 215 NRAS KRAS p=0.537 p=0.520 Figure 15. Distribution of KRAS and NRAS mutations according to patient sex. MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 46 In a consecutive series of 241 mCRC samples wild-type for KRAS codons 12 and 13, we searched for mutations in the less frequently mutated KRAS mutational hotspots in exon 3 (codons 59/61) and 4 (codons 117/146) and in exon 2 (codons 12/13), 3 (codons 59/61) and 4 (codons 117/146) of NRAS. These hotspots are located in the P-loop domain (exon 2), switch II (exon 3) and G4/G5 regions (exon 4) of the highly conserved G domain, which is a common structure among RAS proteins (Edkins et al., 2006; Schubbert et al., 2007). Initially, all samples were screened by HRM for mutations in KRAS and NRAS. Subsequently, automated DNA sequencing was performed in all HRM products, in order to identify the alterations associated with each of the mutant cases. HRM was used as a screening mutation method, instead of a regular PCR, since this technique is a very accurate, fast and sensitive method that allows the detection of a small fraction of mutated alleles in tumor samples (~5%), through the evaluation of the different melting patterns obtained from wild-type sequences vs. heterozygote variants (Krypuy et al., 2006; Pinto et al., 2011). Furthermore, sequencing of HRM products increases sensibility in mutation detection from 85% to 98% (Pinto et al., 2011). All HRM products were sequenced due to the fact that we obtained different rates of amplification among our samples and because of the use of big amplicons, such as those of KRAS and NRAS exon 4, which might decrease the sensitivity of mutation detection through HRM (Krypuy et al., 2006; Do et al., 2008). The frequency of RAS mutations in this series (46/241 – 19.1%) is similar to that reported in recent studies with KRAS exon 2 wild-type mCRC, which ranges from approximately 15 to 20% (Vaughn et al., 2011; Douillard et al., 2013; Negru et al., 2014; Sorich et al., 2014). The mutational distribution of the 46 mutations is the following: 12.4% (30/241) were found in KRAS, 5.4% (13/241) and 7.1% (17/241) in exons 3 and 4, respectively; and 6.6% (16/241) were found in NRAS, 3.3% (8/241) in exon 2 and 3.3% (8/241) in exon 3. Although this mutational distribution slightly differs from that reported by Negru and collaborators (1.9% and 3.8% for KRAS exons 3 [codons 59/61] and 4 [codons 117/146], and 7.8% and 1.9% for NRAS exons 2 [codons 12/13] and 3 [codons 59/61], respectively), it is very similar to that reported by Sorich and collaborators in a recent systematic review and meta-analysis of nine randomized controlled trials compromising a total of 5948 patients (4.3% and 6.7% for KRAS exons 3 [codons 59/61] and 4 [codons 117/146], and 3.8% and 4.8% for NRAS exons 2 [codons 12/13] and 3 [codons 59/61], respectively) (Negru et al., 2014; Sorich et al., 2014). We did not detect mutations in NRAS exon 4 (codons 117/146), which seems to be a rare event in CRC, as indicated by the reported frequency ranging from 0.2 to 1% (Douillard et al., 2013; Negru et al., 2014; Sorich et al., 2014). DISCUSSION 47 Aberrant RAS function found in cancer cells is typically associated with mutations in codons 12, 13 or 61, since these codons, located in the P-loop (codons 12 and 13) and in the switch region II (codon 61), play an important role in the maintenance of the GTP-GDP transition state. Mutations in these sites impair GTP hydrolysis and lead to the oncogenic activation of the protein (Scheffzek et al., 1997; Schubbert et al., 2007; Prior et al., 2012). Furthermore, it was demonstrated that the substitution of the Gln61 residue by other amino acids abolished GAP-dependent GTPase activation, leading to a constitutive activation of the RAS protein. This indicates that this amino acid is essential for GAP connection specificity to RAS GTPases (Nur & Maruta, 1992). In the present series only the NRAS gene was analyzed for codons 12 and 13 and the eight mutations detected resulted in three amino acid substitutions: p.Gly12Cys, p.Gly12Asp and Gly13Arg. Although the most frequent Gly12 mutant in our series was the Gly12Asp (5/8; 62.5%), its oncogenic potential is smaller than that of Gly12Val or Gly12Arg mutants (Schubbert et al., 2007; Prior et al., 2012), which we did not find. Codon 61 was analyzed in both KRAS and NRAS genes and nine mutations were found in KRAS and eight in NRAS, representing four different amino acid substitutions: p.Gln61Lys, p.Gln61Arg, p.Gln61Leu and p.Gln61His. One third (2/6) of all p.Gln61His mutants were found in NRAS and, according to the literature and the COSMIC database, this alteration has not previously been reported in this gene in CRC. Although there are no data concerning its oncogenic proprieties, the fact that it is located in Gln61 might be an indicator of its role in RAS activation. Just as for Gly12, Gln61 mutants have various transformation efficiencies that vary from 10 to 1000-fold. One of the highest transformation efficiencies is seen with the p.Gln61Leu mutant (Buhrman et al., 2007), which is also the most frequent Gln61 mutant in our series (7/17; 41.2%). However, in an analysis made by Vaughn and collaborators, p.Gln61Leu was found in only 17.1% (6/35) of KRAS and NRAS codon 61 mutations (Vaughn et al., 2011). We also observed that, despite their high degree of homology, the frequency of mutations in these three hotspots differs between these two RAS proteins. In KRAS, mutations in codons 12 and 13 are generally more frequent than in codon 61, however in our series mutations in NRAS were more frequent in codon 61 than in codons 12 and 13 (50% vs. 43.75% vs. 6.25%, respectively), which is in accordance with the literature (Fernandez-Medarde & Santos, 2011; Prior et al., 2012). Due to a persistent bias in mutation screening over the years, the role of mutations in codons such as 59, 117 or 146 has been overlooked. Mutational analysis of these three codons was performed in our series, and mutations were found in all of them. Ala59 mutants found in our series were all located in KRAS and included one point mutation (p.Ala59Thr), one in frame deletion (p.Ala59del) and one large in-frame duplication MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 48 (p.Cys51_Ser65dup). There are no sufficient data to understand how these alterations might influence RAS protein structure and function, but the fact that this codon is located in the switch region II, the same as codon 61, indicates that mutations in this codon might also influence the transition complex during GTP hydrolysis (Macaluso et al., 2002). On the other hand, mutations in codons 117 and 146, which are involved with guanine base interaction, are known to increase the GDP to GTP exchange rate without affecting the GTPase activity (Edkins et al., 2006). In fact, in vivo expression of both mutants resulted in elevated RAS-GTP expression compared with wild-type RAS, although lower than the one observed with KRAS codons 12 and 13 alleles (Janakiraman et al., 2010). In our series, mutations in these codons were also found only in KRAS, with four mutations in codon 117 and thirteen in codon 146 (23.5% and 76.5%, respectively). These mutations originated three different mutants, Lys117Asn, Ala146Val and Ala146Thr, with the latter being the most frequent mutant out of the three (11/17; 64.7%), something that is consistent with the findings in other publications (Janakiraman et al., 2010; Vaughn et al., 2011). Besides those mentioned above, we found one more mutation in KRAS exon 3, previously described by Molinari and collaborators (Molinari et al., 2011). This mutation, p.Gly60Asp, has no functional studies that can confirm its role as an activating mutation. However, this residue is a conserved amino acid in the superfamily of GTPases and is known to interact with ϒ-phosphate of GTP, which is consistent with the hypothesis that a mutation in this codon might be oncogenic (Bourne et al., 1991; Guedes et al., 2013). It is also important to mention the mutually exclusive distribution of mutations among KRAS and NRAS exons obtained in our series, since we only found single mutations in our pool of cases. This information suggests that alterations in these genes confer overlapping downstream effects due to functional redundancy, which is consistent with findings across the literature (De Roock et al., 2010; Janakiraman et al., 2010; Douillard et al., 2013). In the 215 cases with available clinical data, we tested for association between RAS mutations and clinicopathological features, such as gender, age and stage at diagnosis, and primary tumor site. Interestingly, an association was found between KRAS mutations (p=0.001) and earlier tumor stages at diagnosis, an association that was previously described (Fernandez-Medarde & Santos, 2011). No other statistically significant associations were found, but this might be due to the relatively small sample size and these findings should therefore be confirmed in larger series. Although it had been already suggested in the past (De Roock et al., 2010), the importance of RAS mutations, besides those in codons 12 and 13 of KRAS, as predictors of resistance to anti-EGFR has only recently been established. Douillard and collaborators DISCUSSION 49 published recently the results of the PRIME trial, which assessed the efficacy and safety of adding panitumumab to FOLFOX4 in RAS mutated patients (Douillard et al., 2013). Of the 1183 patients who underwent randomization, 108 patients (17%; 108/620) without KRAS mutations in exon 2 had mutations in other RAS exons. In this subgroup of patients, the analysis showed that PFS and overall survival (OS) observed were shorter in the panitumumab-FOLFOX4 group than in the FOLFOX4-alone group (7.3 vs. 8.0 months, p=0.33; 17.1 vs. 18.3 months, p=0.31). Although the difference was not significant, these outcomes were consistent with those found for the subgroup of patients with KRAS mutations in exon 2. Moreover, patients without RAS mutations in the panitumumabFOLFOX4 group were associated with a significant improvement in progression free survival (10.1 vs. 7.9 moths, p=0.004) and overall survival (26.0 vs. 20.2, p=0.04), when compared with FOLFOX-alone. Similar results, concerning the addition of cetuximab to FOLFIRI in the treatment of mCRC patients, were reported by Ciardiello and collaborators in the latest results from the CRYSTAL trial (Ciardiello et al., 2014). 1198 randomized and treated patients were evaluated in this trial, and 14.7% (63/430) of those considered wild-type for KRAS codons 12 and 13 tumors had other RAS mutations. The differences reported for PFS and OS in this subgroup, between the cetuximab-FOLFIRI and the FOLFIRI-alone groups, were not statistically significant (7.2 vs. 6.9 months, p=0.56; 18.2 vs. 20.7 months, p=0.50). However, when compared with the RAS wild-type subgroup results (11.4 vs. 8.4 months, p=0.0002; 28.4 vs. 20.2 months, p=0.0024) it is possible to conclude that the addition of cetuximab to FOLFIRI has no benefit for patients with RAS mutations. All these findings suggest that RAS activating mutations, in addition to KRAS exon 2 mutations, predict lack of response in patients who received anti-EGFR therapy (cetuximab or panitumumab). Due to the absence of information, at the time of writing, on the outcome of the RAS mutated patients treated with cetuximab/panitumumab, we could not evaluate the role of RAS mutations, as predictive biomarkers of treatment response, in this series of patients. However, considering the results obtained in our mutational analysis of 241 cases and the findings by Douillard and collaborators (Douillard et al., 2013) and Ciardiello and collaborators (Ciardiello et al., 2014), we can expect that about one-fifth of patients considered wild-type for KRAS exon 2 are unlikely to benefit from anti-EGFR therapy due to the presence of other RAS mutations. C ONCLUSIONS CONCLUSIONS 53 VI. CONCLUSIONS Taking into account the results obtained in this study, we can conclude that: I) HRM followed by automated Sanger sequencing of KRAS exons 3 and 4 and NRAS exons 2, 3 and 4 allows the detection of other RAS mutations in about one-fifth of 241 Portuguese mCRC patients wild-type for KRAS exon 2; II) The 46 additional RAS mutations found are mutually exclusive and have the following distribution: a. 5.4% in KRAS exon 3; b. 7.1% in KRAS exon 4; c. 3.3% in NRAS exon 2; d. 3.3% in NRAS exon 3; III) Eleven and seven different mutations were found in KRAS and NRAS, respectively, with a novel NRAS exon 3 mutation being found in two cases; IV) In this setting, a statistically significant association was found between KRAS exon 3/4 mutations and early tumor stage at diagnosis. FUTURE PERSPECTIVES MUTATIONAL ANALYSIS OF KRAS AND NRAS IN METASTATIC COLORECTAL CANCER 62 Cassidy, J., Saltz, L., Twelves, C., Van Cutsem, E., Hoff, P., Kang, Y., Saini, J. P., Gilberg, F., & Cunningham, D. 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