Transcriptomic Mutational Profiling of Gastric Adenocarcinoma in Northern Brazil

Abstract

Gastric cancer (GC) remains among the neoplasms with the worst prognosis, partly due to its biological heterogeneity and the scarcity of robust biomarkers. The characterization of mutational profiles from transcripts can reveal specific tumor signatures and point to therapeutic targets. This study investigated the landscape of mutations expressed in 102 samples of gastric adenocarcinoma from northern Brazil, which were sequenced using NGS. Readings were aligned to the reference genome using STAR (two-pass mode), and variants were called with GATK and VarDict. Annotations and impact predictions were generated using VEP, SIFT, and PolyPhen. We identified >90,000 variants; among the most frequently mutated genes, FTH1 stood out. The mutational profile was described using maftools, and signatures were inferred with MutationalPatterns. We observed a predominant distribution of SNVs, with C>T transitions as the most common event, in addition to patterns compatible with signatures related to replication damage and DNA repair. To mitigate biases inherent to RNA-seq, we applied filters for coverage, strand bias, and RNA editing hotspots. Together, the data outline a regional landscape of mutations expressed in GC and reinforce the usefulness of the transcriptome for prioritizing biomarkers and functional hypotheses that may guide genomic validations and subsequent clinical studies.