Survival-associated transcriptome analysis in ovarian cancer

Purpose of investigation: Ovarian Cancer (OC) is one of the most lethal gynecologic cancers worldwide. Despite the standard treatment, including radical resection, systemic chemotherapy, and targeted drugs for patients, survival rates remain low. This study provides new ideas for the diagnosis and treatment of Ovarian Cancer. Material and Methods: We performed Kaplan-Meier analysis on the transcriptome of Ovarian Cancer based on RNA-Seq data from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment were used for pathway and functional enrichment. Protein-protein interaction (PPI) network was constructed and visualized by SRING and Cytoscape. Results: A total of 1693 genes associated with survival were identified. The Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology enrichment analysis revealed that these selected genes were differently enriched in numerous functional pathways. The top ten hub genes (RIPK4, HSPA8, FOS, STAT1, CD40LG, FGF2, RAC1, CXCR4, PRPF19, and CXCL10) were identified in our PPI network. Three highly connected cluster modules were differently enriched in several functional pathways. Conclusion: These key biomarkers in Ovarian Cancer may have diagnostic and therapeutic value in the future.

Ovarian Neoplasms; Survival Analysis; Transcriptome

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