000162186 001__ 162186
000162186 005__ 20260115130449.0
000162186 0247_ $$2doi$$a10.3390/cancers17132071
000162186 0248_ $$2sideral$$a144814
000162186 037__ $$aART-2025-144814
000162186 041__ $$aeng
000162186 100__ $$aRada Rodríguez, Marta
000162186 245__ $$aElucidating the Role of KRAS, NRAS, and BRAF Mutations and Microsatellite Instability in Colorectal Cancer via Next-Generation Sequencing
000162186 260__ $$c2025
000162186 5060_ $$aAccess copy available to the general public$$fUnrestricted
000162186 5203_ $$aMethods: We retrospectively and cross-sectionally reviewed the cases of 648 patients with a histological diagnosis of colon adenocarcinoma. Of these, 166 had partial molecular studies, and 42 cases were selected based on the availability of the genetic markers targeted in this study. We analyzed the frequency of mutations in these genes, as well as their correlation with microsatellite instability (MSI). Results: A high mutation rate was found in the KRAS gene (52.4%). NRAS mutations were less frequent (8.9%), whereas BRAF mutations were observed in 20.8% of cases. This allowed us to identify a patient subgroup with MSI, representing 12.1% of cases. Among the 42 patients analyzed for KRAS, NRAS, BRAF, and MSI mutations, a significant association was observed between KRAS mutations and microsatellite stability, while no association was found between NRAS mutations and MSI. BRAF mutations showed a statistically significant association with MSI (p < 0.05), with the most common mutation being c.1799T > A, p.Val600Glu. The objective of this study is to demonstrate that the NGS-based method for evaluating MSI is rigorously valid compared to the results obtained using IHC and PCR. Conclusions: Comprehensive NGS profiling from the start improves diagnostic efficiency by saving time, tissue, and costs compared to gene-by-gene analysis. It also enables better molecular characterization and facilitates tailored therapeutic strategies, particularly in identifying candidates for targeted therapy and immunotherapy. This approach supports efficient tumor classification based on using KRAS, BRAF, NTRK, ERBB2, and PIK3CA as key markers, along with MSI status. We recommend that, if initial NGS is not feasible, start with KRAS analysis, then test BRAF and MSI if no mutation is found.
000162186 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000162186 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000162186 700__ $$aAngulo Biedma, Bárbara
000162186 700__ $$aRodríguez Pérez, Irene
000162186 700__ $$0(orcid)0000-0001-8323-0984$$aAzúa Romeo, Javier$$uUniversidad de Zaragoza
000162186 7102_ $$11003$$2443$$aUniversidad de Zaragoza$$bDpto. Anatom.Histolog.Humanas$$cArea Histología
000162186 773__ $$g17, 13 (2025), 2071 [15 pp.]$$pCancers$$tCancers$$x2072-6694
000162186 8564_ $$s2239492$$uhttps://zaguan.unizar.es/record/162186/files/texto_completo.pdf$$yVersión publicada
000162186 8564_ $$s2690837$$uhttps://zaguan.unizar.es/record/162186/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000162186 909CO $$ooai:zaguan.unizar.es:162186$$particulos$$pdriver
000162186 951__ $$a2026-01-15-12:57:40
000162186 980__ $$aARTICLE