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Identification of Chemoresistance-Associated Key Genes and Pathways in High-Grade Serous Ovarian Cancer by Bioinformatics Analyses.

ABSTRACT: Purpose:High-grade serous ovarian cancer (HGSOC) is the leading cause of death among gynecological malignancies. This is mainly attributed to its high rates of chemoresistance. To date, few studies have investigated the molecular mechanisms underlying this resistance to treatment in ovarian cancer patients. In this study, we aimed to explore these molecular mechanisms using bioinformatics analysis. Methods:We analyzed microarray data set GSE51373, which included 16 platinum-sensitive HGSOC samples and 12 platinum-resistant control samples. Differentially expressed genes (DEGs) were identified using RStudio. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using DAVID, and a DEG-associated protein-protein interaction (PPI) network was constructed using STRING. Hub genes in the PPI network were identified, and the prognostic value of the top ten hub genes was evaluated. MGP, one of the hub genes, was verified by immunohistochemistry. Results:All samples were confirmed to be of high quality. A total of 109 DEGs were identified, and the top ten enriched GO terms and four KEGG pathways were obtained. Specifically, the PI3K-AKT signaling pathway and the Rap1 signaling pathway were identified as having significant roles in chemoresistance in HGSOC. Furthermore, based on the PPI network, KIT, FOXM1, FGF2, HIST1H4D, ZFPM2, IFIT2, CCNO, MGP, RHOBTB3, and CDC7 were identified as hub genes. Five of these hub genes could predict the prognosis of HGSOC patients. Positive immunostaining signals for MGP were observed in the chemoresistant samples. Conclusion:Taken together, the findings of this study may provide novel insights into HGSOC chemoresistance and identify important therapeutic targets.

SUBMITTER: Wu Y

PROVIDER: S-EPMC7335306 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of Chemoresistance-Associated Key Genes and Pathways in High-Grade Serous Ovarian Cancer by Bioinformatics Analyses.

Wu Yong Y Xia Lingfang L Guo Qinhao Q Zhu Jun J Deng Yu Y Wu Xiaohua X

Cancer management and research 20200630

<h4>Purpose</h4>High-grade serous ovarian cancer (HGSOC) is the leading cause of death among gynecological malignancies. This is mainly attributed to its high rates of chemoresistance. To date, few studies have investigated the molecular mechanisms underlying this resistance to treatment in ovarian cancer patients. In this study, we aimed to explore these molecular mechanisms using bioinformatics analysis.<h4>Methods</h4>We analyzed microarray data set GSE51373, which included 16 platinum-sensit ...[more]

PMID: 32636682

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Project description:Evidence indicates that high-grade serous ovarian carcinoma arises from the fallopian tube, rather than ovarian surface epithelium. This is termed the 'tubal origin' theory. The aim of the present study was to compare the immunophenotype and gene expression profiling among high-grade serous ovarian carcinoma (HGSOC), fallopian tube epithelium (FTE) and ovarian surface epithelium (OSE) based on tubal origin theory, and identify the differential genes associated with ovarian carcinogenesis. A total of 61 cases of fresh tissue samples including 21 cases of HGSOC, 20 cases of OSE, and 20 cases of FTE were obtained following surgical resection. Immunostaining was performed to detect the expression of PAX8, which has been considered as a potential immunophenotype marker of Müllerian origin. Illumina BeadChip was applied for gene expression profiling. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to confirm the differential expression of candidate genes between HGSOC and FTE. The results of the present study demonstrated that PAX8 was highly expressed in HGSOC (19/21, 90.4%) and FTE (20/20, 100%), but not in OSE (3/20, 14.3%). A dendrogram generated by cluster analysis indicated a higher similarity of gene expression profile between HGSOC and FTE than OSE. A total of 2,412 differentially expressed genes were identified (absolute fold change >2) between HGSOC and FTE, including 822 upregulated genes in cancer and 1,590 downregulated genes. S100 calcium binding protein P, Ras-interacting protein 1, Wnt family member 5A, tumor-associated calcium signal transducer 2, Dickkopf Wnt signaling pathway inhibitor 3 and tumor suppressor candidate 3 genes were identified as candidate markers, of which the differential gene expression in HGSOC and FTE was confirmed by RT-qPCR (P<0.05). The results indicate the presence of a greater similarity in the immunophenotype and gene expression profile of HGSOC and FTE, when compared with OSE, which was consistent with the tubal origin theory of HGSOC.

Dataset Information

Identification of Chemoresistance-Associated Key Genes and Pathways in High-Grade Serous Ovarian Cancer by Bioinformatics Analyses.

Publications

Identification of Chemoresistance-Associated Key Genes and Pathways in High-Grade Serous Ovarian Cancer by Bioinformatics Analyses.

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