IMR Press / EJGO / Volume 41 / Issue 3 / DOI: 10.31083/j.ejgo.2020.03.5153
Open Access Original Research
Survival-associated transcriptome analysis in ovarian cancer
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1 Department of Gynecology, Nanjing Drum Tower Hospital, Affiliated to Nanjing University Medical School, Nanjing, 210008, China
2 Medical College, Southeast University , Nanjing, 210008, China
3 Medical College, Nanjing University, Nanjing, 210008, China
4 Department of Gynecology, Suqian People's Hospital of Nanjing Drum Tower Hospital Group, Suqian, 223800, China
5 Department of Gynecology and Obstetrics, The pukou Hospital of Nanjing, The Fourth Affiliated Hospital of Nanjing Medical Uni-versity, Nanjing, 210031, China
Eur. J. Gynaecol. Oncol. 2020 , 41(3), 455–461; https://doi.org/10.31083/j.ejgo.2020.03.5153
Submitted: 11 January 2019 | Accepted: 9 April 2019 | Published: 15 June 2020
Abstract

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.

Keywords
Ovarian Neoplasms
Survival Analysis
Transcriptome
Figures
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