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

Wenzhi Li1, Shufen Wang2, Chunping Qiu1

  • 1Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, No. 107 Wenhua Road, Jinan, 250012, Shandong, China.

Journal of Translational Medicine
|March 1, 2019
PubMed
Abstract

Insights

This study investigated progesterone resistance in endometrial cancer. Bioinformatics analysis identified key genes and pathways involved in resistance, offering potential therapeutic targets for this condition.

Area of Science:

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background:

  • Progesterone resistance is a significant challenge in endometrial carcinoma.
  • The molecular mechanisms underlying progesterone resistance are not well understood.
  • Identifying these mechanisms is crucial for developing effective treatments.

Purpose of the Study:

  • To elucidate the molecular mechanisms of progesterone resistance in endometrial cancer.
  • To identify key genes and pathways mediating progesterone resistance.
  • To utilize bioinformatics analysis for comprehensive gene network determination.

Main Methods:

  • Development of a medroxyprogesterone acetate (MPA)-resistant endometrial cancer cell subline (IshikawaPR).
  • Microarray analysis to identify differentially expressed genes (DEGs) between resistant and sensitive cells.
  • Bioinformatic analyses including Gene Ontology (GO), KEGG pathway enrichment, coexpression analysis, and protein-protein interaction (PPI) network construction.

Main Results:

  • Identified 821 DEGs, with significant enrichment in lipid metabolism, immune system, inflammation, and extracellular environment pathways.
  • Discovered 7 progesterone receptor (PGR) coexpressed genes significantly altered in resistant cells, with 4 showing clinical significance.
  • Identified 8 hub genes and 4 molecular complex detection modules within the gene network.

Conclusions:

  • Bioinformatics analysis successfully identified a comprehensive gene network associated with progesterone resistance in endometrial cancer.
  • Several potential mechanisms contributing to progesterone resistance were proposed.
  • Identified novel therapeutic and prognostic targets for progesterone resistance in endometrial cancer.
Keywords:
BioinformaticsEndometrial carcinomaProgesterone receptorProgesterone resistance

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