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Functional Gene Clusters in Global Pathogenesis of Clear Cell Carcinoma of the Ovary Discovered by Integrated Analysis of Transcriptomes

Bibliographic Data

ID15464381
AuthorsYueh-Han Hsu (0000-0002-4142-4876, National Yang Ming Chiao Tung University), Peng‐Hui Wang (0000-0002-6048-8541, National Yang Ming Chiao Tung University), Chia-Ming Chang (0000-0003-0390-6361, National Yang Ming Chiao Tung University, corresponding author)
Year2020
Volume17
Issue11
Pages3951-3951
Publication date2020-06-02
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph17113951
PMID32498447
OpenAlexW3032939302
LanguageEN
References cited5

Clear cell carcinoma of the ovary (ovarian clear cell carcinoma (OCCC)) is one epithelial ovarian carcinoma that is known to have a poor prognosis and a tendency for being refractory to treatment due to unclear pathogenesis. Published investigations of OCCC have mainly focused only on individual genes and lack of systematic integrated research to analyze the pathogenesis of OCCC in a genome-wide perspective. Thus, we conducted an integrated analysis using transcriptome datasets from a public domain database to determine genes that may be implicated in the pathogenesis involved in OCCC carcinogenesis. We used the data obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) DataSets. We found six interactive functional gene clusters in the pathogenesis network of OCCC, including ribosomal protein, eukaryotic translation initiation factors, lactate, prostaglandin, proteasome, and insulin-like growth factor. This finding from our integrated analysis affords us a global understanding of the interactive network of OCCC pathogenesis

Bioinformatics · Biology · Carcinogenesis · Carcinoma · Clear cell carcinoma · Computational biology · Gene · Gene expression · Pathogenesis · Transcriptome · Cancer-related molecular mechanisms research · Ovarian cancer diagnosis and treatment · Reproductive System and Pregnancy · Cancer Research · Genetics · Immunology

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