Advanced clinical stage is a problem, predictive molecular markers are a solution: a study of colorectal cancer in a Mexican adult cohort

Advanced clinical stage is a problem, predictive molecular markers are a solution: a study of colorectal cancer in a Mexican adult cohort | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Advanced clinical stage is a problem, predictive molecular markers are a solution: a study of colorectal cancer in a Mexican adult cohort Maria José Lizardo-Thiebaud, Cindy Chavira-Macias, Guillermo Andrade-Orozco, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7652654/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 7 You are reading this latest preprint version Abstract Background: Colorectal carcinoma is the 3rd most common cause of death due to cancer worldwide. Its complexity is mainly explained by its molecular heterogeneity. Scarce information exists of the molecular profile of CRC in the Mexican population. Objective: We developed a retrospective study of cases with colorectal carcinoma from a cohort of Mexican patients to evaluate the presence of predictive molecular markers. Method: KRAS, NRAS and mismatch repair genes were analyzed in cases of colorectal carcinoma. Results: The most frequent location was the rectum. The majority had an invasive colorectal carcinoma with more than 90% being intestinal adenocarcinoma. Eighty percent of the cases were moderately differentiated, and the majority presented an advanced clinical stage. KRAS was mutated in half of the cases. Mutations in the rest of the genes were identified in less than 5% of the cases. When analyzed according to molecular predictive markers, there was no difference in the follow up duration, death percentage nor in the characteristics of the tumor (site, differentiation and morphology). Conclusions: There is a high prevalence of advanced stage CRC in Mexico. Characterizing the predictive molecular biomarkers in CRC expands and optimizes the therapeutic strategies. colorectal cancer KRAS NRAS BRAF MSI Figures Figure 1 Figure 2 Introduction Despite the development of effective measures for screening colorectal carcinoma (CRC), it continues to be one of the principal causes of death (1). It is the 3 rd most common cause of death due to cancer worldwide (2). Its complexity is mainly explained by its molecular heterogeneity. This epidemiological setting highlights the need to develop precise diagnostic and therapeutic strategies, promoting research in molecular biomarkers and a personalized intervention (3). If considered a health problem, biological studies on CRC have been promising, allowing a molecular classification. The latter helps stratify cases individually (4,5). Mutations in RAS genes, specifically KRAS and NRAS, together with mutations in BRAF and the presence of microsatellite instability, are undeniable determinants in the progression and therapy response of metastatic CRC (6,7). Their identification is crucial, as tumors with mutations in RAS or BRAF V600E are resistant to therapies directed to EGFR, such as cetuximab and panitumumab (3). Nonetheless, the evidence available comes from European or North American populations and scarce information exists of the molecular profile of CRC in Mexican population. We developed a retrospective study of cases with colorectal carcinoma from a cohort of Mexican patients to evaluate the presence of predictive molecular markers. Methodology A retrospective cohort of cases from the Oncology Hospital, National Medical Center Siglo XXI in Mexico City was done including all cases of colorectal carcinoma with molecular analysis of NRAS, KRAS and BRAF, as well as immunohistochemical determination of mismatch repair (MMR) gene expression from the years 2022 to 2024. Both sexes were included. Cases without a complete biomarker analysis were excluded. The study was approved by the internal Research Ethics Committee. Formalin-fixed paraffin specimens of the primary CRC were used for analysis of KRAS (BCT005812), NRAS and BRAF (A0030/6) using Biocartis IdyllaTM System (8). MMR was studied with immunohistochemistry assays as previously described (8). Results were interpreted according to the College of American Pathologists. Statistical analysis was performed using GraphPad Prism 10. A chi-squared test was used to compare categorical groups and Mann-Whitney test was used for continuous variables. A p value of <0.05 (two-tailed) was considered significant in all the statistical tests. Results The results show 76% of patients included were in treatment. The mean age was 60 years, with a male-to-female ratio of 1:39 (Table 1). The majority had an invasive CRC. The most frequent histopathological variant was the intestinal variant, in 91% of the cases. Eighty percent of the cases were moderately differentiated. More than half of the cases of CRC were at the rectum (Fig 1). The majority presented an advanced clinical stage (67.72%). Two-thirds of the cases had metastasis in the liver, with the second most frequent location being the lung. As shown in Fig 2, more than half of the cases presented a mutation, with 50% having mutations in KRAS. The most frequently mutated region in KRAS was codon 12 (67.19%) followed by codon 13. Codon 59 was the least mutated region. Mutations in the rest of the genes were identified in less than 5% of the cases. When analyzed as groups (see Table 2), there was a statistically significant difference in the median age and male sex percentage among cases with mutation in KRAS, NRAS, BRAF and deficient MMR (dMMR). In contrast, there was no difference in their follow up duration, death percentage nor in the characteristics of the tumor (site and morphology). There was a statistical difference between the frequencies of moderately differentiated tumours among the gene groups, however, this difference was not identified in the proportion of poorly differentiated tumours. The presence of second neoplasms was more frequent in cases with dMMR when compared to the cases with mutations in KRAS, NRAS and BRAF. Further analysis grouping the cases as KRAS mutated, non-KRAS mutated and RAS/BRAF wild-type, MSS, showed differences in the percentage of male sex, the percentage of cases in treatment and those in palliative care, with the non-KRAS mutated group having more male patients, more patients in treatment and less patients in palliative care (Table 3). As when grouped among the different genes, there were no differences in the site, histopathology and differentiation of the tumor. Though there as a statistical difference in the percentage of moderately differentiated tumours, this was not seen in the proportion of cases with poor differentiation. The non-KRAS mutated group presented more metastasis in areas other than peritoneum, liver, lung and bone; however, no difference was seen when analyzed by gene (Table 2). Discussion A recent meta-analysis showed 23.7% of patients are diagnosed in stage IV clinical stage. The meta-analysis included 84 studies from 46 countries. The percentages oscillated between 16.2% in Puerto Rico and 28.2% in Oman and Latvia (9). In contrast, our results show 67.7% of the patients with CRC were in an advanced clinical stage. In Mexico, an analysis made between the years 2013 and 2016 showed that 78.1% of the patients were diagnosed in an advanced clinical stage (including stage III and IV) (10). Likewise, a clinical cohort of 305 cases reported 67.7% of their cases had metastasis (11), reflecting a late diagnosis and high tumor burden. Around two-thirds of the cases had hepatic metastasis, a frequent site for CRC metastasis as shown in the literature, with reports of 70 to 80% of cases having liver deposits (12,13). There are no precise statistics about metastatic disease in CRC in Mexico; nevertheless, most studies report advanced stages, suggesting a high prevalence of hepatic metastasis. National reports have documented rectal involvement in up to 42.8% of CRC cases, and in our cohort, 61.4% of tumors were in the rectum (14). By contrast, European and North American studies have consistently reported lower proportions, with approximately 35–40% of CRC cases arising at the rectum (2). The histopathological subtypes described by the World Health Organization include mucinous carcinoma; signet-ring cell; medullary carcinoma; serrated adenocarcinoma; micropapillary adenocarcinoma; adenosquamous carcinoma; adenoma-like adenocarcinoma; carcinomas with sarcomatoid components and undifferentiated carcinoma (15). In our cohort, more than 90% of the cases presented intestinal adenocarcinoma, in line with the literature (16). We found a signet ring cell morphology in 2% of cases (6 out of 254), a higher number than the reported in the literature. This might be explained by an error in the morphological classification, as the official criteria requires more than 50% of the tumor having a signet-ring cell morphology (15,16). In the molecular profiles analyzed, approximately half of the cases presented KRAS mutations, with alterations in codon 12 predominating and, to a lesser extent, in codon 13. An international study in metastatic colorectal cancer reported mutations in codon 12 in 67.2% and in codon 13 in 23.5% of cases (6). However, a meta-analysis that included 288 studies showed similar frequencies for both codons, around 29% (17). On the other hand, a study in Asian patients in stages I–III indicated a lower prevalence for mutations in codon 13 (9.1%) and codon 61 (1.3%), highlighting that only mutations in codon 12 were associated with a worse prognosis, suggesting a differential impact according to the mutational site (18). A cohort from western Mexico showed a similar distribution to ours in KRAS (codon 12: 75%, codon 13: 16%), NRAS (codons 12 and 13: 30% and 10%, respectively), and BRAF V600E/D (100%) (19). Regarding the overall mutation frequency, our results are consistent with those of the same study (KRAS: 45%, BRAF: 5%, NRAS: 4%) (19). However, other national multicenter studies have reported a lower prevalence of KRAS (25–45%), NRAS (7%), and BRAF (6%) mutations (14). Interestingly, male sex percentage was significantly different between groups, with more male patients presenting mutations in NRAS and dMMR. Such a difference was not found in a Mexican cohort of 500 patients (19). This might be due to our smaller population, as even BRAF mutations are reportedly more frequent in female patients (20). BRAF mutations and dMMR were more frequent in younger patients, which might reflect the biological differences in CRC. Latin-American studies show heterogenous age distribution (range from 50 to 70) for cases profiled for BRAF mutations (21). No difference was found in the subtypes and differentiation of CRC when compared between gene mutations and dMMR, although mucinous adenocarcinoma and signet-ring cell carcinoma are associated to MMR deficiency and are considered poorly differentiated tumours (16). No differences were found in the location of CRC when comparing the different gene mutations and dMMR cases, though BRAF and dMMR are more frequently found in right-sided CRC and KRAS mutations in left-sided CRC (20,22). The use of target therapy in CRC has specific indications (23). Monoclonal antibodies and kinase inhibitors are used in advanced stages. Despite the low availability of target therapy in Mexico, a third of patients with KRAS mutations, as well as those without any mutations, received target therapy, which highlights the relevance of evaluating predictive molecular markers in CRC. Conclusion The results of this study reveal a molecular profile of colorectal cancer in the Mexican population characterized by a high frequency of KRAS mutation, low incidence of BRAF and NRAS, and few cases of dMMR. These alterations have direct prognostic and predictive implications and are essential for selecting targeted therapies. Abbreviations Colorectal carcinoma – CRC Mismatch repair– MMR Deficient Mismatch repair genes - dMMR Declarations Ethics approval and consent to participate The study was approved by the internal Research Ethics Committee. The consent to participate was waivered due to the retrospective nature of the study. Consent for publication Not applicable. Availability of data and materials All data generated or analyzed during this study are included in this published article. Raw data are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests Funding Not applicable Authors' contributions MJLT and MGJDA contributed with the development of the study; MJLT and GAO contributed with the analysis; MJLT, GAO and CCM contributed with the writing of the article; MGJDA, RMG and JMMN contributed with proofreading and editing of the article. Acknowledgements Not applicable References Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut. 2017 Apr 1;66(4):683–91. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023 Jan 12;73(1):17–48. Sepulveda AR, Hamilton SR, Allegra CJ, Grody W, Cushman-Vokoun AM, Funkhouser WK, et al. 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Molecular pathological classification of colorectal cancer—an update. Virchows Archiv. 2024 Feb 1;484(2):273–85. López-Cortés A, Paz-y-Miño C, Guerrero S, Jaramillo-Koupermann G, León Cáceres Á, Intriago-Baldeón DP, et al. Pharmacogenomics, biomarker network, and allele frequencies in colorectal cancer. Pharmacogenomics Journal. 2020 Feb 1;20(1):136–58. Tables Table 1. General and Histopathological characteristics of the population studied. n=254 M:F 1.396 Mean age 60 n % In treatment 194 76.38 Palliative care 55 21.65 Invasive 252 99.21 Intramucosal 2 0.79 Histopathological variants Intestinal 233 91.73 With mucinous component 4 1.57 Mucinous 9 3.54 Signet ring cells 6 2.36 Differentiation Well-differentiated 30 11.81 Moderately differentiated 205 80.71 Poorly differentiated 19 7.48 Table 2. Characteristics found in CRC per molecular alteration KRAS (n=128) NRAS (n=10) BRAF (n=4) dMMR (n=6) P-value Median age (years) 62 (58.55-62.87) 71 (67.41-78.79) 56 (36.99-78-51) 59 (38.4-70.93) 0.012 Male sex 56.2% (72) 100% (10) 50% (2) 100% (6) 0.001 In treatment 76.5% (98) 90% (9) 100% (4) 66.6% (4) 0.590 Palliative care 19.5% (25) 10% (1) 0% 16.6% (1) 0.940 Use of biological agents 32.8% (42) 40% (4) 0% 0% 0.726 Bevacizumab 31.2% (40) 40% (4) 0% 0% Cetuximab 0.78% (1) 0% 0% 0% Regorafenib 0.78% (1) 0% 0% 0% Follow up (median) 18 (16-20) 21 (5-36) 8 (6-26) 26 (9-88) 0.230 Death percentage 32.8% (42) 30% (3) 50% (2) 16.6% (1) 0.798 Site Ascending colon 5.4% (7) 0% 0% 0% >0.9999 Transverse colon 0.78% (1) 0% 25% (1) 0% 0.065 Sigmoid 27.3% (35) 30% (3) 25% (1) 16.6% (1) >0.9999 Rectum 66.4% (85) 70% (7) 50% (2) 83.3% (5) 0.778 Invasive 98.4% (126) 100% (10) 100% (4) 100% (6) >0.9999 Intramucosal 1.56% (2) 0% 0% 0% >0.9999 Histopathological variants Intestinal 89% (114) 100% (10) 50% (2) 83.3% (5) 0.077 With mucinous component 3.1% (4) 0% 0% 16.6% (1) 0.328 Mucinous 4.6% (6) 0% 0% 0% >0.9999 Signet ring cells 1.56% (2) 0% 50% (2) 0% 0.010 Differentiation Well-differentiated 11.7% (15) 20% (2) 0% 16.6% (1) 0.560 Moderately differentiated 80.4% (103) 80% (8) 50% (2) 83.3% (5) 0.035 Poorly differentiated 7.8% (10) 0% 50% (2) 0% 0.081 Positive lymph nodes 34.3% (44) 40% (4) 100% (4) 33.3% (2) 0.061 Staging I 3.1% (4) 10% (1) 0% 0% 0.521 II 7.8% (10) 0% 0% 0% >0.9999 III 20.3% (26) 20% (2) 75% (3) 16.6% (1) 0.098 IV 68.7% (88) 70% (7) 25% (1) 83.3% (5) 0.293 Sites of metastasis Peritoneum 12.5% (16) 10% (1) 0% 0% >0.9999 Liver 46% (59) 70% (7) 25% (1) 50% (3) 0.408 Lung 32% (41) 30% (3) 0% 66.6% (4) 0.188 Bone 4.6% (6) 0% 0% 0% >0.9999 Others 5.4% (7) 10% (1) 0% 16.6% (1) 0.350 Second neoplasm 4.6% (6) 10% (1) 25% (1) 33.3% (2) 0.019 Table 3. Characteristics found in CRC with RAS mutation, without RAS mutation and without mutation. KRAS (n=128) non-KRAS (n=19) RAS/BRAF wild-type, pMMR (n = 109) P-value Median age (years) 62 (58.55-62.87) 67 (57.9-71.1) 59 (56.1-60.85) 0.0681 Male sex 56.2% (72) 94.7% (18) 55.9% (61) 0.009 In treatment 76.5% (98) 89.4% (17) 73.3% (80) <0.0001 Palliative care 19.5% (25) 10.5% (2) 24.7% (27) <0.0001 Use of biological agents 32.8% (42) 21% (4) 32.1% (35) 0.8368 Bevacizumab 31.2% (40) 21% (4) 5.5% (6) Cetuximab 0.78% (1) 0% 26.6% (29) Regorafenib 0.78% (1) 0% 0% Follow up (median) 18 (16-20) 21 (8-26) 19 (16-22) 0.9851 Death percentage 32.8% (42) 31.5% (6) 39.4% (43) 0.5129 Site Ascending colon 5.4% (7) 0% 5.5% (6) 0.8249 Transverse colon 0.78% (1) 5.2% (1) 0.9% (1) 0.2833 Sigmoid 27.3% (35) 26.3% (5) 39.4% (43) 0.1232 Rectum 66.4% (85) 73.6% (14) 57.7% (63) 0.2425 Invasive 98.4% (126) 100% (19) 100% (109) 0.5725 Intramucosal 1.56% (2) 0% 0% >0.9999 Histopathological variants Intestinal 89% (114) 89.4% (17) 97.2% (106) 0.2353 With mucinous component 3.1% (4) 5.2% (1) 2.7% (3) 0.7195 Mucinous 4.6% (6) 0% 0% 0.0659 Signet ring cells 1.56% (2) 10.5% (2) 0% 0.015 Differentiation Well-differentiated 11.7% (15) 15.7% (3) 11% (12) 0.7601 Moderately differentiated 80.4% (103) 78.9% (15) 82.5% (90) <0.0001 Poorly differentiated 7.8% (10) 10.5% (2) 6.4% (7) 0.7061 Positive lymph nodes 34.3% (44) 52.6% (10) 33.9% (37) 0.2822 Staging I 3.1% (4) 5.2% (1) 1.8% (2) 0.4638 II 7.8% (10) 0% 11% (12) 0.3249 III 20.3% (26) 31.5% (6) 21.1% (23) 0.502 IV 68.7% (88) 68.4% (13) 66% (72) 0.9355 Sites of metastasis Peritoneum 12.5% (16) 5.2% (1) 13.7% (15) 0.7038 Liver 46% (59) 57.8% (11) 45.8% (50) 0.6502 Lung 32% (41) 36.8% (7) 19.2% (21) 0.0445 Bone 4.6% (6) 0% 1.8% (2) 0.4302 Others 5.4% (7) 10.5% (2) 0.9% (1) 0.0332 Second neoplasm 4.6% (6) 21% (4) 4.5% (5) 0.0336 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 09 Dec, 2025 Reviews received at journal 03 Dec, 2025 Reviewers agreed at journal 24 Nov, 2025 Reviewers invited by journal 02 Nov, 2025 Editor assigned by journal 30 Sep, 2025 Submission checks completed at journal 30 Sep, 2025 First submitted to journal 18 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7652654","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":542716605,"identity":"5470ce00-d5bb-4e02-8608-6f52c67e80ec","order_by":0,"name":"Maria José Lizardo-Thiebaud","email":"","orcid":"","institution":"Instituto Nacional de Pediatria","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"José","lastName":"Lizardo-Thiebaud","suffix":""},{"id":542716606,"identity":"6aa34796-c327-4a25-b54c-7aebf8271115","order_by":1,"name":"Cindy Chavira-Macias","email":"","orcid":"","institution":"Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán","correspondingAuthor":false,"prefix":"","firstName":"Cindy","middleName":"","lastName":"Chavira-Macias","suffix":""},{"id":542716607,"identity":"e027497a-2235-4b70-80aa-d74c418341c3","order_by":2,"name":"Guillermo Andrade-Orozco","email":"","orcid":"","institution":"Digestive and Hepatobiliary Pathology of Morelia","correspondingAuthor":false,"prefix":"","firstName":"Guillermo","middleName":"","lastName":"Andrade-Orozco","suffix":""},{"id":542716608,"identity":"2fede0d5-c427-41c5-981a-e8199a101829","order_by":3,"name":"Jean M. 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Anda-González","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYDCCA0DMw8DGwMDeA+bz8BGvhecMmMPDRqQWIJDIgXAIauE73vzswZsaPnn5mW8PPv6YYyfDxsD88NENPFokzxwzN5xzjM2wcXZessHBbclAh7EZG+fg0WJwI8FMmoeNjbFZOsdM4uA2ZqAWHjZpvFruP/8mzfOPzb5N8gxISz0RWm7wmEnztrEl9kjwgLQcJqxF8kxOmeTcPrbkGTw5xgZntx3nYWMm4Be+48e3Sbz5dsx2fvsZwweV26rt+dmbHz7GpwUKjiGxmQkrB4Ea4pSNglEwCkbByAQAKc5FnnEXg1IAAAAASUVORK5CYII=","orcid":"","institution":"National Medical Center Siglo XXI","correspondingAuthor":true,"prefix":"","firstName":"María","middleName":"Guadalupe Jazmín","lastName":"De Anda-González","suffix":""}],"badges":[],"createdAt":"2025-09-18 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08:48:40","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":414785,"visible":true,"origin":"","legend":"","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7652654/v1/5ea90969dd3ad664b31912bb.jpg"},{"id":95807503,"identity":"68e3edca-9495-4a56-9a43-85489619e8b9","added_by":"auto","created_at":"2025-11-13 08:48:48","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1240251,"visible":true,"origin":"","legend":"","description":"","filename":"CRCFinal2025.docx","url":"https://assets-eu.researchsquare.com/files/rs-7652654/v1/afe4ca32a02c06f5e4504d5c.docx"},{"id":95807628,"identity":"24d04583-d0ef-4b74-9602-577b404eef3d","added_by":"auto","created_at":"2025-11-13 08:49:02","extension":"json","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7241,"visible":true,"origin":"","legend":"","description":"","filename":"8bc43ee2e24d40a9bb081b2067f71996.json","url":"https://assets-eu.researchsquare.com/files/rs-7652654/v1/8e21930927229a78f40b2dd7.json"},{"id":95807561,"identity":"77597912-19d5-4678-8940-015cb05f2121","added_by":"auto","created_at":"2025-11-13 08:48:55","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":155518,"visible":true,"origin":"","legend":"\u003cp\u003ePathological characteristics of the tumours included in the study. a) The pie chart shows 60% of the tumours were located at the rectum. b) The majority of tumors diagnosed were in an advanced clinical stage (68%). c) Two-thirds of the tumours had metastasized to the liver.\u003c/p\u003e","description":"","filename":"FIg1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7652654/v1/8f65921c59d980ecb701edbb.jpg"},{"id":95807493,"identity":"952f0e24-891c-4b30-adba-0c8a02fe5d15","added_by":"auto","created_at":"2025-11-13 08:48:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":414785,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular characteristics of the cohort: a) KRAS, b) NRAS, c) BRAF and, d) status of mismatch repair proteins and their different patterns of deficiency.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7652654/v1/38cce08342923c4e8eafc2bb.jpg"},{"id":95810483,"identity":"877744d0-616a-47e7-95d6-00239e8352ee","added_by":"auto","created_at":"2025-11-13 08:52:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1245912,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7652654/v1/328096f6-a2a0-4a81-a044-d55e308a3288.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Advanced clinical stage is a problem, predictive molecular markers are a solution: a study of colorectal cancer in a Mexican adult cohort","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDespite the development of effective measures for screening colorectal carcinoma (CRC), it continues to be one of the principal causes of death (1). It is the 3\u003csup\u003erd\u003c/sup\u003e most common cause of death due to cancer worldwide (2). Its complexity is mainly explained by its molecular heterogeneity. This epidemiological setting highlights the need to develop precise diagnostic and therapeutic strategies, promoting research in molecular biomarkers and a personalized intervention (3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIf considered a health problem, biological studies on CRC have been promising, allowing a molecular classification. The latter helps stratify cases individually (4,5). Mutations in RAS genes, specifically KRAS and NRAS, together with mutations in BRAF and the presence of microsatellite instability, are undeniable determinants in the progression and therapy response of metastatic CRC (6,7). Their identification is crucial, as tumors with mutations in RAS or BRAF V600E are resistant to therapies directed to EGFR, such as cetuximab and panitumumab (3).\u003c/p\u003e\n\u003cp\u003eNonetheless, the evidence available comes from European or North American populations and scarce information exists of the molecular profile of CRC in Mexican population. We developed a retrospective study of cases with colorectal carcinoma from a cohort of Mexican patients to evaluate the presence of predictive molecular markers.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eA retrospective cohort of cases from the Oncology Hospital, National Medical Center Siglo XXI in Mexico City was done including all cases of colorectal carcinoma with molecular analysis of NRAS, KRAS and BRAF, as well as immunohistochemical determination of mismatch repair (MMR) gene expression from the years 2022 to 2024. Both sexes were included. Cases without a complete biomarker analysis were excluded. The study was approved by the internal Research Ethics Committee.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFormalin-fixed paraffin specimens of the primary CRC were used for analysis of KRAS (BCT005812), NRAS and BRAF (A0030/6) using Biocartis IdyllaTM System (8). MMR was studied with immunohistochemistry assays as previously described (8). Results were interpreted according to the College of American Pathologists.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using GraphPad Prism 10. A chi-squared test was used to compare categorical groups and Mann-Whitney test was used for continuous variables. A p value of \u0026lt;0.05 (two-tailed) was considered significant in all the statistical tests.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe results show 76% of patients included were in treatment. The mean age was 60 years, with a male-to-female ratio of 1:39 (Table 1). The majority had an invasive CRC. The most frequent histopathological variant was the intestinal variant, in 91% of the cases. \u0026nbsp;Eighty percent of the cases were moderately differentiated. More than half of the cases of CRC were at the rectum (Fig 1). The majority presented an advanced clinical stage (67.72%). Two-thirds of the cases had metastasis in the liver, with the second most frequent location being the lung.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs shown in Fig 2, more than half of the cases presented a mutation, with 50% having mutations in KRAS. The most frequently mutated region in KRAS was codon 12 (67.19%) followed by codon 13. Codon 59 was the least mutated region. Mutations in the rest of the genes were identified in less than 5% of the cases.\u003c/p\u003e\n\u003cp\u003eWhen analyzed as groups (see Table 2), there was a statistically significant difference in the median age and male sex percentage among cases with mutation in KRAS, NRAS, BRAF and deficient MMR (dMMR). In contrast, there was no difference in their follow up duration, death percentage nor in the characteristics of the tumor (site and morphology). There was a statistical difference between the frequencies of moderately differentiated tumours among the gene groups, however, this difference was not identified in the proportion of poorly differentiated tumours. The presence of second neoplasms was more frequent in cases with dMMR when compared to the cases with mutations in KRAS, NRAS and BRAF.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther analysis grouping the cases as KRAS mutated, non-KRAS mutated and RAS/BRAF wild-type, MSS, showed differences in the percentage of male sex, the percentage of cases in treatment and those in palliative care, with the non-KRAS mutated group having more male patients, more patients in treatment and less patients in palliative care (Table 3). As when grouped among the different genes, there were no differences in the site, histopathology and differentiation of the tumor. Though there as a statistical difference in the percentage of moderately differentiated tumours, this was not seen in the proportion of cases with poor differentiation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe non-KRAS mutated group presented more metastasis in areas other than peritoneum, liver, lung and bone; however, no difference was seen when analyzed by gene (Table 2).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA recent meta-analysis showed 23.7% of patients are diagnosed in stage IV clinical stage. The meta-analysis included 84 studies from 46 countries. The percentages oscillated between 16.2% in Puerto Rico and 28.2% in Oman and Latvia (9). In contrast, our results show 67.7% of the patients with CRC were in an advanced clinical stage. In Mexico, an analysis made between the years 2013 and 2016 showed that 78.1% of the patients were diagnosed in an advanced clinical stage (including stage III and IV) (10). Likewise, a clinical cohort of 305 cases reported 67.7% of their cases had metastasis (11), reflecting a late diagnosis and high tumor burden.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAround two-thirds of the cases had hepatic metastasis, a frequent site for CRC metastasis as shown in the literature, with reports of 70 to 80% of cases having liver deposits (12,13). There are no precise statistics about metastatic disease in CRC in Mexico; nevertheless, most studies report advanced stages, suggesting a high prevalence of hepatic metastasis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNational reports have documented rectal involvement in up to 42.8% of CRC cases, and in our cohort, 61.4% of tumors were in the rectum (14). By contrast, European and North American studies have consistently reported lower proportions, with approximately 35\u0026ndash;40% of CRC cases arising at the rectum (2).\u003c/p\u003e\n\u003cp\u003eThe histopathological subtypes described by the World Health Organization include mucinous carcinoma; signet-ring cell; medullary carcinoma; serrated adenocarcinoma; micropapillary adenocarcinoma; adenosquamous carcinoma; adenoma-like adenocarcinoma; carcinomas with sarcomatoid components and undifferentiated carcinoma (15). \u0026nbsp;In our cohort, more than 90% of the cases presented intestinal adenocarcinoma, in line with the literature (16). We found a signet ring cell morphology in 2% of cases (6 out of 254), a higher number than the reported in the literature. This might be explained by an error in the morphological classification, as the official criteria requires more than 50% of the tumor having a signet-ring cell morphology (15,16).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the molecular profiles analyzed, approximately half of the cases presented KRAS mutations, with alterations in codon 12 predominating and, to a lesser extent, in codon 13. An international study in metastatic colorectal cancer reported mutations in codon 12 in 67.2% and in codon 13 in 23.5% of cases (6). However, a meta-analysis that included 288 studies showed similar frequencies for both codons, around 29% (17). On the other hand, a study in Asian patients in stages I\u0026ndash;III indicated a lower prevalence for mutations in codon 13 (9.1%) and codon 61 (1.3%), highlighting that only mutations in codon 12 were associated with a worse prognosis, suggesting a differential impact according to the mutational site (18). A cohort from western Mexico showed a similar distribution to ours in KRAS (codon 12: 75%, codon 13: 16%), NRAS (codons 12 and 13: 30% and 10%, respectively), and BRAF V600E/D (100%) (19). Regarding the overall mutation frequency, our results are consistent with those of the same study (KRAS: 45%, BRAF: 5%, NRAS: 4%) (19). However, other national multicenter studies have reported a lower prevalence of KRAS (25\u0026ndash;45%), NRAS (7%), and BRAF (6%) mutations (14).\u003c/p\u003e\n\u003cp\u003eInterestingly, male sex percentage was significantly different between groups, with more male patients presenting mutations in NRAS and dMMR. Such a difference was not found in a Mexican cohort of 500 patients (19). This might be due to our smaller population, as even BRAF mutations are reportedly more frequent in female patients (20). BRAF mutations and dMMR were more frequent in younger patients, which might reflect the biological differences in CRC. Latin-American studies show heterogenous age distribution (range from 50 to 70) for cases profiled for BRAF mutations (21).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo difference was found in the subtypes and differentiation of CRC when compared between gene mutations and dMMR, although mucinous adenocarcinoma and signet-ring cell carcinoma are associated to MMR deficiency and are considered poorly differentiated tumours (16). No differences were found in the location of CRC when comparing the different gene mutations and dMMR cases, though BRAF and dMMR are more frequently found in right-sided CRC and KRAS mutations in left-sided CRC (20,22). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe use of target therapy in CRC has specific indications (23). Monoclonal antibodies and kinase inhibitors are used in advanced stages. Despite the low availability of target therapy in Mexico, a third of patients with KRAS mutations, as well as those without any mutations, received target therapy, which highlights the relevance of evaluating predictive molecular markers in CRC.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results of this study reveal a molecular profile of colorectal cancer in the Mexican population characterized by a high frequency of KRAS mutation, low incidence of BRAF and NRAS, and few cases of dMMR. These alterations have direct prognostic and predictive implications and are essential for selecting targeted therapies.\u003c/p\u003e\n"},{"header":"Abbreviations","content":"\u003cp\u003eColorectal carcinoma \u0026ndash; CRC\u003c/p\u003e\n\u003cp\u003eMismatch repair\u0026ndash; MMR\u003c/p\u003e\n\u003cp\u003eDeficient Mismatch repair genes - dMMR\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the internal Research Ethics Committee. The consent to participate was waivered due to the retrospective nature of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article. Raw data are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMJLT and MGJDA contributed with the development of the study; MJLT and GAO contributed with the analysis; MJLT, GAO and CCM contributed with the writing of the article; MGJDA, RMG and JMMN contributed with proofreading and editing of the article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut. 2017 Apr 1;66(4):683\u0026ndash;91. \u003c/li\u003e\n\u003cli\u003eSiegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023 Jan 12;73(1):17\u0026ndash;48. \u003c/li\u003e\n\u003cli\u003eSepulveda AR, Hamilton SR, Allegra CJ, Grody W, Cushman-Vokoun AM, Funkhouser WK, et al. Molecular biomarkers for the evaluation of colorectal cancer: Guideline from The American Society for Clinical Pathology, College of American Pathologists, Association for Molecular Pathology, and the American Society of Clinical Oncology. Journal of Clinical Oncology. 2017 May 1;35(13):1453\u0026ndash;96. \u003c/li\u003e\n\u003cli\u003eBramsen JB, Rasmussen MH, Ongen H, Mattesen TB, \u0026Oslash;rntoft MBW, \u0026Aacute;rnad\u0026oacute;ttir SS, et al. Molecular-Subtype-Specific Biomarkers Improve Prediction of Prognosis in Colorectal Cancer. Cell Rep. 2017 May 9;19(6):1268\u0026ndash;80. \u003c/li\u003e\n\u003cli\u003eHarada S, Morlote D. Molecular Pathology of Colorectal Cancer. Advances in Anatomical Pathology [Internet]. 2020;27(1):20\u0026ndash;6. Available from: www.anatomicpathology.com\u003c/li\u003e\n\u003cli\u003eLavacchi D, Fancelli S, Roviello G, Castiglione F, Caliman E, Rossi G, et al. Mutations matter: An observational study of the prognostic and predictive value of KRAS mutations in metastatic colorectal cancer. Front Oncol. 2022 Nov 29;12. \u003c/li\u003e\n\u003cli\u003eLiu J, Zeng W, Huang C, Wang J, Yang D, Ma D. Predictive and Prognostic Implications of Mutation Profiling and Microsatellite Instability Status in Patients with Metastatic Colorectal Carcinoma. Gastroenterol Res Pract. 2018;2018. \u003c/li\u003e\n\u003cli\u003eGuadalupe Jazm\u0026iacute;n De Anda Gonz\u0026aacute;lez M, Maria Jos\u0026eacute; LT, Braulio MB, Jean MNM, Guzm\u0026aacute;n Rafael M, Anda-Gonz\u0026aacute;lez Mar\u0026iacute;a Guadalupe Jazm\u0026iacute;n D. Molecular characteristics of left-sided, advanced stage colorectal cancer: A Mexican perspective. Journal of Gastroenterology Research and Practice. 2024;4:1\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eGuo L, Wang L, Cai L, Zhang Y, Feng X, Zhu C, et al. Global Distribution of Colorectal Cancer Staging at Diagnosis: An Evidence Synthesis. Clinical Gastroenterology and Hepatology. 2024 Dec; \u003c/li\u003e\n\u003cli\u003eLozano-Esparza S, S\u0026aacute;nchez-Blas HR, Huitzil-Mel\u0026eacute;ndez FD, Meneses-Medina MI, Van Loon K, Potter MB, et al. Colorectal cancer survival in Mexico: Leveraging a national health insurance database. Cancer Epidemiol. 2025 Feb;94:102698. \u003c/li\u003e\n\u003cli\u003eQuezada-Guti\u0026eacute;rrez C, \u0026Aacute;lvarez-Ba\u0026ntilde;uelos MT, Morales-Romero J, Sampieri CL, Guzm\u0026aacute;n-Garc\u0026iacute;a RE, Montes-Villase\u0026ntilde;or E. Factors associated with the survival of colorectal cancer in Mexico. Intest Res. 2020 Jul 30;18(3):315\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eBrouwer NPM, van der Kruijssen DEW, Hugen N, de Hingh IHJT, Nagtegaal ID, Verhoeven RHA, et al. The Impact of Primary Tumor Location in Synchronous Metastatic Colorectal Cancer: Differences in Metastatic Sites and Survival. Ann Surg Oncol. 2020 May 1;27(5):1580\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eAlexandrescu ST, Anastase DT, Grigorie RT, Zlate CA, Andrei S, Costea R, et al. Influence of the primary tumor location on the pattern of synchronous metastatic spread in patients with stage iv colorectal carcinoma, according to the 8th edition of the ajcc staging system. 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Surg Pathol Clin. 2020 Sep 1;13(3):503\u0026ndash;20. \u003c/li\u003e\n\u003cli\u003eLevin-Sparenberg E, Bylsma LC, Lowe K, Sangare L, Fryzek JP, Alexander DD. A Systematic Literature Review and Meta-Analysis Describing the Prevalence of KRAS, NRAS , and BRAF Gene Mutations in Metastatic Colorectal Cancer . Gastroenterology Res. 2020;13(5):184\u0026ndash;98. \u003c/li\u003e\n\u003cli\u003eAhn HM, Kim DW, Oh HJ, Kim HK, Lee HS, Lee TG, et al. Different oncological features of colorectal cancer codon-specific \u003cem\u003eKRAS\u003c/em\u003e mutations: Not codon 13 but codon 12 have prognostic value. World J Gastroenterol. 2023 Aug 28;29(32):4883\u0026ndash;99. \u003c/li\u003e\n\u003cli\u003eSanchez-Ibarra HE, Jiang X, Gallegos-Gonzalez EY, Cavazos-Gonz\u0026aacute;lez AC, Chen Y, Morcos F, et al. KRAS, NRAS, and BRAF mutation prevalence, clinicopathological association, and their application in a predictive model in Mexican patients with metastatic colorectal cancer: A retrospective cohort study. PLoS One. 2020 Jul 1;15(7). \u003c/li\u003e\n\u003cli\u003eRequena DO, Garcia-Buitrago M. Molecular Insights Into Colorectal Carcinoma. Arch Med Res. 2020 Nov;51(8):839\u0026ndash;44. \u003c/li\u003e\n\u003cli\u003eHern\u0026aacute;ndez-Sandoval JA, Guti\u0026eacute;rrez-Angulo M, Maga\u0026ntilde;a-Torres MT, Alvizo-Rodr\u0026iacute;guez CR, Ram\u0026iacute;rez-Plascencia HHF, Flores-L\u0026oacute;pez BA, et al. Prevalence of the BRAF p.v600e variant in patients with colorectal cancer from Mexico and its estimated frequency in Latin American and Caribbean populations. Journal of Investigative Medicine. 2020 Jun 1;68(5):985\u0026ndash;91. \u003c/li\u003e\n\u003cli\u003eDunne PD, Arends MJ. Molecular pathological classification of colorectal cancer\u0026mdash;an update. Virchows Archiv. 2024 Feb 1;484(2):273\u0026ndash;85. \u003c/li\u003e\n\u003cli\u003eL\u0026oacute;pez-Cort\u0026eacute;s A, Paz-y-Mi\u0026ntilde;o C, Guerrero S, Jaramillo-Koupermann G, Le\u0026oacute;n C\u0026aacute;ceres \u0026Aacute;, Intriago-Balde\u0026oacute;n DP, et al. Pharmacogenomics, biomarker network, and allele frequencies in colorectal cancer. Pharmacogenomics Journal. 2020 Feb 1;20(1):136\u0026ndash;58. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"384\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 384px;\"\u003e\n \u003cp\u003eTable 1. General and Histopathological characteristics of the population studied. n=254\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eM:F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eMean age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eIn treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e76.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003ePalliative care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e21.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eInvasive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e99.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eIntramucosal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eHistopathological variants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eIntestinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e91.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eWith mucinous component\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eMucinous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eSignet ring cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eDifferentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eWell-differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e11.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003eModerately differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e80.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 271px;\"\u003e\n \u003cp\u003ePoorly differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e7.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u0026nbsp;\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"688\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 688px;\"\u003e\n \u003cp\u003eTable 2. Characteristics found in CRC per molecular alteration\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eKRAS (n=128)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eNRAS (n=10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eBRAF (n=4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003edMMR (n=6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eMedian age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e62 (58.55-62.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e71 (67.41-78.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e56 (36.99-78-51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e59 (38.4-70.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e56.2% (72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e100% (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e50% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e100% \u0026nbsp;(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIn treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e76.5% (98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e90% (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e100% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e66.6% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003ePalliative care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e19.5% (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e10% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e16.6% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eUse of biological agents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e32.8% (42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e40% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eBevacizumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e31.2% (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e40% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eCetuximab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0.78% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eRegorafenib\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0.78% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eFollow up (median)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e18 (16-20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e21 (5-36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e8 (6-26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e26 (9-88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eDeath percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e32.8% (42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e30% (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e50% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e16.6% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 688px;\"\u003e\n \u003cp\u003eSite\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eAscending colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e5.4% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eTransverse colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0.78% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e25% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eSigmoid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e27.3% (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e30% (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e25% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e16.6% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e66.4% (85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e70% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e50% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e83.3% (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eInvasive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e98.4% (126)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e100% (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e100% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e100% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIntramucosal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.56% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 688px;\"\u003e\n \u003cp\u003eHistopathological variants\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIntestinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e89% (114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e100% (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e50% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e83.3% (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eWith mucinous component\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e3.1% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e16.6% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eMucinous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e4.6% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eSignet ring cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.56% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e50% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 688px;\"\u003e\n \u003cp\u003eDifferentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eWell-differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e11.7% (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e20% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e16.6% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eModerately differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e80.4% (103)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e80% (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e50% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e83.3% (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003ePoorly differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e7.8% (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e50% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003ePositive lymph nodes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e34.3% (44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e40% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e100% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e33.3% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 688px;\"\u003e\n \u003cp\u003eStaging\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e3.1% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e10% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e7.8% (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e20.3% (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e20% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e75% (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e16.6% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e68.7% (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e70% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e25% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e83.3% (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.293\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 688px;\"\u003e\n \u003cp\u003eSites of metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003ePeritoneum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e12.5% (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e10% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e46% (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e70% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e25% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e50% (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e32% (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e30% (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e66.6% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e4.6% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e5.4% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e10% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e16.6% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eSecond neoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e4.6% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003e10% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003e25% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e33.3% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u0026nbsp;\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"611\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 611px;\"\u003e\n \u003cp\u003eTable 3. Characteristics found in CRC with RAS mutation, without RAS mutation and without mutation.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003eKRAS (n=128)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003enon-KRAS (n=19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003eRAS/BRAF wild-type, pMMR (n = 109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eMedian age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e62 (58.55-62.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e67 (57.9-71.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e59 (56.1-60.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.0681\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e56.2% (72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e94.7% (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e55.9% (61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eIn treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e76.5% (98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e89.4% (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e73.3% (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003ePalliative care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e19.5% (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e10.5% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e24.7% (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eUse of biological agents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e32.8% (42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e21% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e32.1% (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.8368\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eBevacizumab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e31.2% (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e21% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e5.5% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eCetuximab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.78% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e26.6% (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eRegorafenib\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.78% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eFollow up (median)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e18 (16-20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e21 (8-26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e19 (16-22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.9851\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eDeath percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e32.8% (42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e31.5% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e39.4% (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.5129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 611px;\"\u003e\n \u003cp\u003eSite\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eAscending colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e5.4% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e5.5% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.8249\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eTransverse colon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.78% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e5.2% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e0.9% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.2833\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eSigmoid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e27.3% (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e26.3% (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e39.4% (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.1232\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e66.4% (85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e73.6% (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e57.7% (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.2425\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eInvasive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e98.4% (126)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e100% (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e100% (109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.5725\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eIntramucosal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1.56% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026gt;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 611px;\"\u003e\n \u003cp\u003eHistopathological variants\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eIntestinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e89% (114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e89.4% (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e97.2% (106)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.2353\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eWith mucinous component\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e3.1% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e5.2% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e2.7% (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.7195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eMucinous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e4.6% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.0659\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eSignet ring cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1.56% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e10.5% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 611px;\"\u003e\n \u003cp\u003eDifferentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eWell-differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e11.7% (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e15.7% (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e11% (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.7601\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eModerately differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e80.4% (103)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e78.9% (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e82.5% (90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003ePoorly differentiated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e7.8% (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e10.5% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e6.4% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.7061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003ePositive lymph nodes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e34.3% (44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e52.6% (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e33.9% (37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.2822\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 611px;\"\u003e\n \u003cp\u003eStaging\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e3.1% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e5.2% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e1.8% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.4638\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e7.8% (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e11% (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.3249\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e20.3% (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e31.5% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e21.1% (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e68.7% (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e68.4% (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e66% (72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.9355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 611px;\"\u003e\n \u003cp\u003eSites of metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003ePeritoneum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e12.5% (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e5.2% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e13.7% (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.7038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e46% (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e57.8% (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e45.8% (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.6502\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e32% (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e36.8% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e19.2% (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.0445\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eBone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e4.6% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e1.8% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.4302\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e5.4% (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e10.5% (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e0.9% (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.0332\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond neoplasm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\n \u003cp\u003e4.6% (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 128px;\"\u003e\n \u003cp\u003e21% (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 194px;\"\u003e\n \u003cp\u003e4.5% (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0336\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"[email protected]","identity":"surgical-and-experimental-pathology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"saep","sideBox":"Learn more about [Surgical and Experimental Pathology](http://surgexppathol.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/SAEP/default.aspx","title":"Surgical and Experimental Pathology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"colorectal cancer, KRAS, NRAS, BRAF, MSI","lastPublishedDoi":"10.21203/rs.3.rs-7652654/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7652654/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Colorectal carcinoma is the 3rd most common cause of death due to cancer worldwide. Its complexity is mainly explained by its molecular heterogeneity. Scarce information exists of the molecular profile of CRC in the Mexican population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eObjective: We developed a retrospective study of cases with colorectal carcinoma from a cohort of Mexican patients to evaluate the presence of predictive molecular markers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethod: KRAS, NRAS and mismatch repair genes were analyzed in cases of colorectal carcinoma.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: The most frequent location was the rectum. The majority had an invasive colorectal carcinoma with more than 90% being intestinal adenocarcinoma. Eighty percent of the cases were moderately differentiated, and the majority presented an advanced clinical stage. KRAS was mutated in half of the cases. Mutations in the rest of the genes were identified in less than 5% of the cases. When analyzed according to molecular predictive markers, there was no difference in the follow up duration, death percentage nor in the characteristics of the tumor (site, differentiation and morphology).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusions: There is a high prevalence of advanced stage CRC in Mexico. Characterizing the predictive molecular biomarkers in CRC expands and optimizes the therapeutic strategies.\u003c/p\u003e","manuscriptTitle":"Advanced clinical stage is a problem, predictive molecular markers are a solution: a study of colorectal cancer in a Mexican adult cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 08:08:18","doi":"10.21203/rs.3.rs-7652654/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-09T15:12:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-03T13:59:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265598289851780306610562613748026944319","date":"2025-11-24T15:47:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-02T21:24:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-30T09:54:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-30T09:54:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Surgical and Experimental Pathology","date":"2025-09-18T19:56:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"[email protected]","identity":"surgical-and-experimental-pathology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"saep","sideBox":"Learn more about [Surgical and Experimental Pathology](http://surgexppathol.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/SAEP/default.aspx","title":"Surgical and Experimental Pathology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5b49162e-2284-4b84-8b1e-160fdbab2848","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2025-12-09T15:23:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-13 08:08:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7652654","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7652654","identity":"rs-7652654","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}