European Journal of Biomedical and Pharmaceutical Sciences

COMPARATIVE PAN-CANCER ANALYSIS OF DRIVER GENE MUTATIONS, ALTERNATION PATTERNS AND ONCOGENIC PATHWAY ASSOCIATIONS ACROSS SIX TCGA TUMOR TYPES USING CBIOPORTAL

Khansa Fathima*, Mekkanti Manasa Rekha, Jayashree S., Khayati Moudgil

ABSTRACT

Background: Cancer is a diverse set of diseases with the involvement of multiple genomic abnormalities that lead to the initiation and progression of cancer. Systematic assessment of mutations in driver genes and dysregulated signaling pathways is made feasible by public cancer genomics resources, such as The Cancer Genome Atlas (TCGA) and cBioPortal. In this study, a pan-cancer bioinformatics analysis was conducted to uncover recurrent genomic alterations and some important molecular pathways in selected TCGA cohorts. Methods: A retrospective cross-sectional bioinformatics study was conducted using TCGA datasets accessed through cBioPortal. Six cancer types were included: breast invasive carcinoma (BRCA), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), colon adenocarcinoma (COAD), prostate adenocarcinoma (PRAD) and skin cutaneous melanoma (SKCM). Driver gene alterations, mutation frequencies, genomic profiles and pathway involvement were evaluated. KEGG pathway enrichment analysis was performed to identify significantly enriched biological pathways. Results: TP53 showed the highest alteration frequency (36%), followed by KRAS (15%) and PIK3CA (13%). Recurrent alterations were also identified in KMT2C, BRAF, EGFR, PTEN, APC and NF1. Pathway analysis demonstrated prominent involvement of the RTK–RAS, PI3K–AKT–mTOR, TP53, WNT and cell cycle signaling pathways. KEGG enrichment analysis revealed significant enrichment of the MAPK (adjusted p = 3.20 × 10⁻⁶), PI3K–AKT (adjusted p = 6.40 × 10⁻⁶), FOXO, PD-L1/PD-1 checkpoint and apoptosis pathways. Conclusion: This study concluded that recurrent alterations in TP53, KRAS and PIK3CA, together with significant dysregulation of RTK–RAS, PI3K–AKT–mTOR, TP53, WNT and cell cycle pathways, represent key molecular features across multiple cancers.

Keywords: Pan-cancer analysis, TCGA, cBioPortal, Driver gene mutations, TP53, KRAS, PIK3CA, Molecular pathways and Precision analysis.