Identification of Salivary Biomarkers from Gene Expression Data of Multiple Cancer Types Using Bioinformatics Analysis

Objective Cancer is recognized as the primary factor causing clinical and socio-economic pressure among diseases. This study investigates common salivary mRNA biomarkers in five types of cancer: ovarian, stomach, breast, lung, and pancreatic, using gene expression profiling by microarray. Methods The Gene Expression Omnibus (GEO) database was utilized to obtain salivary datasets and Differentially expressed genes (DEGs) were identified using GEO2R. Gene ontology and pathway analyses were conducted via the Enrichr database. External validation was performed using The Cancer Genome Atlas (TCGA) data, and the expression of immune subgroups was analyzed through the Tumor-Immune System Interaction Database (TISIDB). Results This study analyzed datasets including control and cancer groups and identified 80 common DEGs across the datasets. Genes such as IRAK3, SERPINA1, SUB1, and RBM6 showed both significant differences in expression in cancerous tissues and association with reduced survival rates. Additionally, gene expression correlated with immune cell infiltration in various cancers, suggesting that IRAK3 and RBM6 may serve as markers for immunotherapy efficacy. Conclusion This study identifies key differentially expressed genes associated with cancer prognosis and immune infiltration, and introduces IRAK3 and RBM6 as potential biomarkers for multi-cancer screening, risk stratification and as companion biomarkers for therapy selection.