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Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis.
Zhang, Ke; Kong, Xiangjun; Feng, Guangde; Xiang, Wei; Chen, Long; Yang, Fang; Cao, Chunyu; Ding, Yifei; Chen, Hang; Chu, Mingxing; Wang, Pingqing; Zhang, Baoyun.
Afiliação
  • Zhang K; Bioengineering Institute of Chongqing University, Chongqing, China.
  • Kong X; State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China.
  • Feng G; Sichuan TQLS Animal Husbandry Science and Technology Co., Ltd, Mianyang, China.
  • Xiang W; Bioengineering Institute of Chongqing University, Chongqing, China.
  • Chen L; Bioengineering Institute of Chongqing University, Chongqing, China.
  • Yang F; Bioengineering Institute of Chongqing University, Chongqing, China.
  • Cao C; Bioengineering Institute of Chongqing University, Chongqing, China.
  • Ding Y; Bioengineering Institute of Chongqing University, Chongqing, China.
  • Chen H; Bioengineering Institute of Chongqing University, Chongqing, China.
  • Chu M; Key Laboratory of Farm Animal Genetic Resources and Germplasm Innovation of Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
  • Wang P; Bioengineering Institute of Chongqing University, Chongqing, China. wang_pq@21cn.com.
  • Zhang B; Bioengineering Institute of Chongqing University, Chongqing, China. zhangbaoyun418@sina.com.
J Ovarian Res ; 11(1): 16, 2018 Feb 26.
Article em En | MEDLINE | ID: mdl-29482638
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-1α-TGFA-EGFR-ErbB2-MYC axis. These findings will contribute to the identification of new targets for the diagnosis and treatment of ovarian cancer.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Ovarianas / Transdução de Sinais / Regulação Neoplásica da Expressão Gênica / Redes Reguladoras de Genes / Hipóxia Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Ovarianas / Transdução de Sinais / Regulação Neoplásica da Expressão Gênica / Redes Reguladoras de Genes / Hipóxia Idioma: En Ano de publicação: 2018 Tipo de documento: Article