Transcriptomics driven identification of hub gene miRNA interactions for biomarker and therapeutic target discovery in gynecological cancers

Introduction MicroRNAs (miRNAs) are small, single-stranded noncoding RNAs that play critical roles in disease development, including gynecological cancers like vulvar and cervical cancer. Their high heterogeneity makes achieving an accurate diagnosis difficult in modern clinical practice. Methods In this study, we used in silico analyses to identify hub genes, miRNAs, and their interactions, enabling the discovery of potential biomarkers that may improve the diagnosis and treatment of cervical cancers following validation by quantitative gene expression analysis. Results The statistical analysis of GEOR2 yielded 16,344 differentially expressed genes (DEGs), and through robust regression analysis, 229 common DEGs were retrieved. Among them, 94 and 135 genes were downregulated and upregulated, respectively. We retrieved ten hub genes via a protein–protein interaction network and cytohubba, namely CDK1, AURKA, BUB1B, CCNB1, TOP2A, KIF11, BUB1, CCNB2, CDCA8, and BIRC5. Following extensive in silico analysis, 30 miRNAs that interact with hub genes were identified and among these miRNAs, hsa-miR-653-5p, hsa-miR-495-3p, hsa-miR-381-3p, hsa-miR-1266-5p, and hsa-miR-589-3p were the top five interactive miRNAs that targeted the most hub genes and were involved in key functions leading to colorectal cancer, cervical cancer, glioma, and TGF-beta signaling. We further validated the differential expression of hub genes in HeLa and HeLaDP cells using real-time PCR (P < 0.01). Discussion The identified miRNAs exhibit strong regulatory interactions with these hub genes, while serine/threonine protein kinases emerged as the most significantly associated group. Together, these findings highlight promising biomarker candidates and potential therapeutic targets for gynecological cancers.