Integrative transcriptomic analysis identifies malaria-associated signaling pathways and repurposable drug candidates for ovarian cancer metastasis

Ovarian cancer metastasis remains a leading cause of cancer-related mortality and presents major challenges for effective therapy. This study aimed to identify pivotal genes, proteins, and pathways involved in ovarian cancer metastasis and to explore already approved drugs with potential to inhibit these metastatic mechanisms through a drug repurposing framework. A comparative in silico analysis was conducted using transcriptomic data from matched primary and metastatic ovarian tumors. In Phase 1, gene expression profiles from three microarray and four RNA-sequencing datasets were analyzed using R (v4.3.1) to identify differentially expressed genes (DEGs). In Phase 2, pathway enrichment and protein-protein interaction analyses were performed to pinpoint key signaling networks, followed by systematic drug repurposing using dgiDB and PanDrug databases. Top significant 100 DEGs were identified among 27,985 transcripts from the microarray datasets, while RNA-sequencing analysis revealed DEGs from 25,551 transcripts. KEGG pathway analysis highlighted ten major pathways, of which three, malaria, TGF-beta, and PPAR signaling, were common to both datasets and significantly associated with metastatic transformation. Gene literature mining identified eight genes (THBS1, VCAM1, ADIPOQ, LPL, ACKR1, CD36, FABP4, HBA1) overlapping malaria-associated and metastasis gene sets. Network analysis using the STRING database showed strong interactions among 14 of 17 key genes, with VCAM1 emerging as a central hub protein linked to adhesion and immune-related pathways. Subsequent drug-gene interaction screening identified 37 potential repurposed drug candidates, with highest-priority agents including chloroquine (ACKR1, interaction score 0.711), fenofibrate and pioglitazone (ADIPOQ/LPL, 0.622), pirfenidone (THBS1, 0.702), and bevacizumab (THBS1/VCAM1, 0.908), all approved drugs with established clinical safety profiles.These findings emphasize the convergence of TGF-beta, PPAR, and malaria-associated signaling in ovarian cancer metastasis, suggesting that repurposed drugs targeting these pathways, particularly chloroquine and PPAR agonists, may have therapeutic potential in this context. The computational identification of bevacizumab, an agent already approved for ovarian cancer, corroborates the approach. Future work will focus on in vitro validation of prioritized drug candidates, including chloroquine, PPAR agonists, and pirfenidone, against ovarian cancer cell lines to substantiate the in silico predictions and support the development of new treatment strategies derived from existing pharmacologic agents with reduced development timelines.