4.5 Article

Oncogenic mutations and microsatellite instability phenotype predict specific anatomical subsite in colorectal cancer patients

期刊

EUROPEAN JOURNAL OF HUMAN GENETICS
卷 21, 期 12, 页码 1383-1388

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NATURE PUBLISHING GROUP
DOI: 10.1038/ejhg.2013.66

关键词

oncogenic mutation; microsatellite instability; colorectal cancer

资金

  1. Istituto Toscano Tumori [ITT-2007]

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In colorectal cancer (CRC) oncogenic mutations such as KRAS alterations, are considered standard molecular biomarkers that predict the clinical benefit for targeted intervention with epidermal growth factor receptor (EGFR) inhibitors. In addition, these mutations are associated with specific anatomical area in colon tumor development, as BRAF mutations with the microsatellite instability (MSI). In this translational study, we aimed to assess the mutation frequencies of the EGFR (hotspot area and polyadenine deletions A13_del), KRAS, BRAF(V600E), and PIK3CA oncogenes in a series of 280 CRC patients. MSI phenotypes are also considered in this series. All patients' clinicopathological data were assessed for statistical analysis and its associations were validated. We verified multiple associations between oncogenic mutations and determined clinicopathological tumor features (1) EGFR A13_deletions are associated with right colon carcinoma (P<0.005), mucinous histotype (P = 0.042), G3 grading (P = 0.024), and MSI status (P<0.005); (2) PIK3CA mutations are related mucinous histotype (P = 0.021); (3) KRAS(G12) and KRAS(G13) mutations are correlated, respectively, with the left and right colon cancer development (P<0.005), and finally (4) MSI is associated with right colon tumors (P<0.005). Mostly, we verified a higher frequency rate of the KRAS(G13) and EGFR A13_del oncogene mutations in right colon cancer; whereas KRAS(G12) codon mutation occurs more frequently in left colon cancers. In particular, we assessed that right vs left colon cancer are associated with specific molecular characteristics. These evidences, in association with clinicopathological data, can delineate novel approaches for the CRC classification and targeted intervention.

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