Exploring Molecular Signature and Prognostic Biomarkers in Ovarian Cancer: Insights From Late‐Stage, Recurrent, and Metastatic Tumors

Ovarian Cancer is a leading cause of mortality among women globally, primarily due to lack of specific and sensitive early-stage diagnostic tools. This study aims to identify hub genes associated with recurrent, late-stage, and metastatic tumors as potential prognostic biomarkers and drug targets. Gene expression data from eight National Center for Biotechnology Information (NCBI)-Gene Expression Omnibus (GEO) datasets were categorized by recurrence, tumor-stage, and metastasis. Differential gene expression and enrichment analyses were performed. Hub genes were identified by protein-protein interaction networks and validated by the University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), GEPIA2, pROC, and Kaplan-Meier plotter databases. Genetic alterations, immune cell infiltration, miRNA prediction, and drug-gene interactions were assessed using cBioPortal, CIBERSORTx, Encyclopedia of RNA Interactomes (ENCORI), and Drug-Gene Interaction Database (DGIdb), respectively. Eight hub genes (FN1, COL1A1, COL1A2, COL3A1, POSTN, LUM, IGF1, and CXCL8) were identified, with COL1A2 common across all tumor categories. Note that 19.6% of cases showed mutations in these genes, primarily COL3A1. Overexpression of most hub genes and reduced expression of CXCL8 correlated with worse survival outcomes. COL1A1 and FN1 showed strong diagnostic ability. Late-stage tumors showed elevated M2 macrophages and neutrophils. hsa-miR-29a-3p, hsa-miR-29b-3p, and hsa-miR-29c-3p were identified as the most interactive miRNAs. Ocriplasmin and pamidronate were identified as potential therapeutics. Our findings highlight the therapeutic relevance of these hub genes and identify them as potential drug targets and prognostic biomarkers in ovarian cancer.