Integrated Analysis of mRNA Expression Profiles in Head and Neck Squamous Cell Carcinoma: Insights from Data Mining to Survival Analysis - Sneha Kumari, Alvea Tasneem, Prithvi Singh, Anuska Karmakar, Ravins Dohare, Sehrish Imran, Rida Rafiqi, Neeraj Dohare, Sunil Kumar (South Eastern European Journal of Public Health, 2025)
Background: Head and neck squamous cell carcinoma (HNSCC) is a heterogenous disease involving tumors from the mucosal lining of the oral cavity, pharynx, and larynx, with diverse etiologies, epidemiologies, and treatment strategies. HNSCC carries a poor prognosis, influenced significantly by factors such as HPV status. Innovations in data mining techniques have identified crucial biomarkers for diagnosis and prognosis, facilitating personalized treatment. Methods: Present study integrates differential gene expression analysis from the mRNA expression profile dataset of HNSCC downloaded from Gene Expression Omnibus (GEO) database. Screening of differentially expressed genes (DEGs) were performed using R packages. Protein-protein interaction network construction and pathway enrichment analysis revealed significant hub genes which were selected for overall analysis and mutational studies.Results: After screening, 322 DEGs in the OSCC tissues were obtained. Construction of protein-protein interaction network (PPIN) led to the selection of hub gene modules, while pathway and gene ontoloy (GO) term enrichment analysis identified interferon alpha/beta signaling pathway as one of the top 10 statistically significant pathways. The Kaplan-Meier (KM) OS and mutational analysis of the selected genes was conducted on patients with HNSCC from The Cancer Genome Atlas (TCGA). Total of 10 candidate genes (IFNA4, LAMA5, HES5, MAP3K5, MAT1A, SLURP1, NCAN, SF3B4, PTPN1, and UQCR10) closely related to the survival rate of patients with HNSCC were identified, and mutational analysis of genes were performed based on TCGA database. SLURP1 showed the highest mutation out of all ten genes in HNSCC patients.