Dataset Information

Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis.

ABSTRACT: BACKGROUND:Ovarian cancer is a leading cause of the death from gynecologic malignancies. Hypoxia is closely related to the malignant growth of cells. However, the molecular mechanism of hypoxia-regulated ovarian cancer cells remains unclear. Thus, this study was conducted to identify the key genes and pathways implicated in the regulation of hypoxia by bioinformatics analysis. METHODS:Using the datasets of GSE53012 downloaded from the Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were screened by comparing the RNA expression from cycling hypoxia group, chronic hypoxia group, and control group. Subsequently, cluster analysis was performed followed by the construction of the protein-protein interaction (PPI) network of the overlapping DEGs between the cycling hypoxia and chronic hypoxia using ClusterONE. In addition, gene ontology (GO) functional and pathway enrichment analyses of the DEGs in the most remarkable module were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID) software. Ultimately, the signaling pathways associated with hypoxia were verified by RT-PCR, WB, and MTT assays. RESULTS:A total of 931 overlapping DEGs were identified. Nine hub genes and seven node genes were screened by analyzing the PPI and pathway integration networks, including ESR1, MMP2, ErbB2, MYC, VIM, CYBB, EDN1, SERPINE1, and PDK. Additionally, 11 key pathways closely associated with hypoxia were identified, including focal adhesion, ErbB signaling, and proteoglycans in cancer, among which the ErbB signaling pathway was verified by RT-PCR, WB, and MTT assays. Furthermore, functional enrichment analysis revealed that these genes were mainly involved in the proliferation of ovarian cancer cells, such as regulation of cell proliferation, cell adhesion, positive regulation of cell migration, focal adhesion, and extracellular matrix binding. CONCLUSION:The results show that hypoxia can promote the proliferation of ovarian cancer cells by affecting the invasion and adhesion functions through the dysregulation of ErbB signaling, which may be governed by the HIF-1?-TGFA-EGFR-ErbB2-MYC axis. These findings will contribute to the identification of new targets for the diagnosis and treatment of ovarian cancer.

SUBMITTER: Zhang K

PROVIDER: S-EPMC5828062 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis.

Zhang Ke K Kong Xiangjun X Feng Guangde G Xiang Wei W Chen Long L Yang Fang F Cao Chunyu C Ding Yifei Y Chen Hang H Chu Mingxing M Wang Pingqing P Zhang Baoyun B

Journal of ovarian research 20180226 1

<h4>Background</h4>Ovarian cancer is a leading cause of the death from gynecologic malignancies. Hypoxia is closely related to the malignant growth of cells. However, the molecular mechanism of hypoxia-regulated ovarian cancer cells remains unclear. Thus, this study was conducted to identify the key genes and pathways implicated in the regulation of hypoxia by bioinformatics analysis.<h4>Methods</h4>Using the datasets of GSE53012 downloaded from the Gene Expression Omnibus (GEO), the differentia ...[more]

PMID: 29482638

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Project description:Colorectal cancer is the third most common type of cancer and the fourth leading cause of cancer-associated mortality worldwide. Serine/arginine-rich splicing factor 1 (SRSF1) is a well-characterized oncogenic factor that promotes tumorigenesis by controlling a number of alternative splicing events. However, there is limited network analysis, from a global aspect, to study the effect of SRSF1 on colorectal cancer. In the present study, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of available gene regulation data from The Cancer Genome Atlas database revealed the enriched functions and signaling pathways of SRSF1. Subsequently, Oncomine analysis was performed, which demonstrated that SRSF1 was upregulated in a number of types of colon cancer. From overlapping the analysis of 2,678 SRSF1-related genes and 3,625 colorectal cancer genes in GeneCards, 468 genes were identified as SRSF1-related colorectal cancer genes. The GO results revealed that these overlapped genes were primarily enriched in metabolic processes, response to DNA damage, regulation of the cell cycle and a number of additional biological processes. KEGG pathway analysis revealed that SRSF1-related colorectal cancer genes were associated with the cell cycle, deregulated signaling pathways associated with cancer progression and colorectal cancer signaling pathways. In addition, the Search Tool for the Retrieval of Interacting Genes/Proteins database and Cytoscape analysis demonstrated that 468 SRSF1-related colorectal cancer genes exhibit potential interaction networks in which these genes were enriched in DNA metabolic processes, cell cycle regulation and regulation of apoptosis. The results of the present study suggested that SRSF1 exhibited an increased degree of interaction with key molecules, including NUF2 NDC80 kinetochore complex component, kinesin family member 2C, structural maintenance of chromosomes 3, ATM serine/threonine kinase, BRCA1 DNA repair associated, protein kinase DNA-activated catalytic polypeptide, heat shock protein 90 alpha family class A member 1, ras homolog family member A, and phosphatase and tensin homolog. Collectively, the bioinformatics analysis of the present study indicated that SRSF1 may have key functions in the progression and development of colorectal cancer.

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Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis.

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Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis.

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