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Updated: Jun 30, 2026

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
Published on: April 18, 2025
Tissue Proteomic Signatures of BRAF-Mutated Colorectal Cancer Reveal New Insights into Aggressiveness, Immune
Gianmaria Miolo1, Wally Marus2, Giovanni Canil3
1Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081Aviano (PN), Italy.
None:
Colorectal cancer (CRC) is characterized by molecular heterogeneity, with BRAF-mutated tumors being particularly aggressive and refractory to standard therapies. This study aimed to identify distinctive proteomic signatures associated with the BRAF V600E mutation through comparative tumor tissue profiling. Thirty-three tumor tissues were analyzed: 9 BRAF-mutated, 14 RAS-mutated, and 10 wild-type (WT). Proteomic profiling was performed on formalin-fixed, paraffin-embedded (FFPE) tissues using bottom-up LC-MS/MS in a data-independent acquisition mode. Protein identification and relative expression were achieved by using DIA-NN label-free analysis. Group differences were evaluated through multiparametric analyses, and Cox proportional hazard models were applied to identify proteins associated with overall survival. BRAF-mutated tumors showed distinct proteomic alterations, including overexpression of dipeptidyl peptidase 4 (DPP4) and lysophosphatidylcholine acyltransferase 1 (LPCAT1) alongside the downregulation of quinolinic phosphoribosyltransferase (QPRT) involved in NAD+ biosynthesis. Pathway analysis revealed the enrichment of protein folding associated with endoplasmic reticulum (ER) stress. Prognostic accuracy improved when tumor genotype was combined with the expression of activator of HSP90 ATPase activity 1 (AHSA1) and thioredoxin domain-containing 5 (TXNDC5), involved in ER-associated protein folding. These findings define a distinctive proteomic signature in BRAF-mutated CRC, characterized by dysregulated protein folding associated with ER stress and supporting the development of targeted therapies and more precise prognostic models.
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