ArticleCancers2022
Multivariate Risk Analysis of RAS, BRAF and EGFR Mutations Allelic Frequency and Coexistence as Colorectal Cancer Predictive Biomarkers.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Novel paradigms in KRAS targeting: Unveiling strategies to combat drug resistance.Chinese medical journal · 2025Review
- Article
- Article
- Association of various RAS codon mutations and prognostic outcomes of patients with colorectal liver metastases after hepatectomy.Cancer medicine · 2024Article
- Genistein exerts anti-colorectal cancer actions: clinical reports, computational and validated findings.Aging · 2023Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundBiomarker profiles should represent a coherent description of the colorectal cancer (CRC) stage and its predicted evolution.
methodsUsing droplet digital PCR, we detected the allelic frequencies (AF) of KRAS, NRAS, BRAF, and EGFR mutations from 60 tumors. We employed a pair-wise association approach to estimate the risk involving AF mutations as outcome variables for clinical data and as predicting variables for tumor-staging. We evaluated correlations between mutations of AFs and also between the mutations and histopathology features (tumor staging, inflammation, differentiation, and invasiveness).
resultsKRAS G12/G13 mutations were present in all patients. KRAS Q61 was significantly associated with poor differentiation, high desmoplastic reaction, invasiveness (ypT4), and metastasis (ypM1). NRAS and BRAF were associated with the right-side localization of tumors. Diabetic patients had a higher risk to exhibit NRAS G12/G13 mutations. BRAF and NRAS G12/G13 mutations co-existed in tumors with invasiveness limited to the submucosa.
conclusionsThe associations we found and the mutational AF we reported may help to understand disease processes and may be considered as potential CCR biomarker candidates. In addition, we propose representative mutation panels associated with specific clinical and histopathological features of CRC, as a unique opportunity to refine the degree of personalization of CRC treatment.
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