Comprehensive bioinformatics analysis of acquired progesterone resistance in endometrial cancer cell line

Journal of Translational Medicine
Wenzhi LiJie Jiang

Abstract

Progesterone resistance is a problem in endometrial carcinoma, and its underlying molecular mechanisms remain poorly understood. The aim of this study was to elucidate the molecular mechanisms of progesterone resistance and to identify the key genes and pathways mediating progesterone resistance in endometrial cancer using bioinformatics analysis. We developed a stable MPA (medroxyprogesterone acetate)-resistant endometrial cancer cell subline named IshikawaPR. Microarray analysis was used to identify differentially expressed genes (DEGs) from triplicate samples of Ishikawa and IshikawaPR cells. PANTHER, DAVID and Metascape were used to perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and cBioPortal for progesterone receptor (PGR) coexpression analysis. GEO microarray (GSE17025) was utilized for validation. The protein-protein interaction network (PPI) and modular analyses were performed using Metascape and Cytoscape. Further validation were performed by real-time polymerase chain reaction (RT-PCR). In total, 821 DEGs were found and further analyzed by GO, KEGG pathway enrichment and PPI analyses. We found that lipid metabolism, immune system and inflammation, extracellular...Continue Reading

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Citations

Dec 19, 2019·Molecular Biology Reports·Kristijan SkokDarja Arko
Jun 20, 2020·Biochimica Et Biophysica Acta. Biomembranes·Florian RouaudSandra Citi
Dec 17, 2021·Frontiers in Cell and Developmental Biology·Shuang YuanLihua Wang

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Datasets Mentioned

BETA
GSE121367
GSE17025

Methods Mentioned

BETA
Feature Extraction
RNA-Seq
Chip-seq

Software Mentioned

STRING
SPSS
CentiScape
FunRich
PANTHER
DAVID
Agilent Feature Extraction
Cytoscape
Morpheus
GraphPad Prism

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