Literature DB >> 32529729

Analysis of carcinogenic signaling networks in endometrial cancer identifies RAB17 as a potential target.

Xing Zhou1, Geqing Xia1, Yan Liu1, Xiaoyan Xin1, Rui Shi1, Lanfen An1, Jun Zhang1, Rong Zhao1, Yingchao Zhao2, Hongbo Wang1.   

Abstract

Endometrial cancer is one of the most common malignancies in postmenopausal women. Several potential therapeutic targets have been investigated in current research, but few have been used clinically. Therefore, further investigating the potential pathogenesis of endometrial cancer and new effective therapeutic targets for endometrial malignancies is still necessary. Our study used a The Cancer Genome Atlas dataset and two Gene Expression Omnibus datasets for weighted gene coexpression network analysis to identify important genes associated with the histological grades of endometrial cancer. In addition, we performed gene set enrichment analysis on the three datasets and found that abnormally activated signaling pathways and metabolic pathways are the main biological behaviors of endometrial cancer. Moreover, we further used different algorithms and identified the RAB17 gene as a potential study object. To further illustrate the potential role of the genes we analyzed in clinical and cellular aspects, we performed a clinical correlation analysis. Finally, we demonstrated the important roles and mechanisms of the RAB17 gene in the cell cycle, proliferation, and metastasis of endometrial cancer. Using repeated database analysis and cell-level assays, we propose RAB17 as a potential target gene for endometrial cancer for further study.
© 2020 Wiley Periodicals LLC.

Entities:  

Keywords:  RAB17; WGCNA; endometrial cancer; metastasis; proliferation

Year:  2020        PMID: 32529729     DOI: 10.1002/jcp.29845

Source DB:  PubMed          Journal:  J Cell Physiol        ISSN: 0021-9541            Impact factor:   6.384


  1 in total

1.  Knockdown of Circular RNA Hsa_circ_0000714 Can Regulate RAB17 by Sponging miR-370-3p to Reduce Paclitaxel Resistance of Ovarian Cancer Through CDK6/RB Pathway.

Authors:  Min Guo; Shuo Li; Xiaoyun Zhao; Ying Yuan; Bin Zhang; Yifu Guan
Journal:  Onco Targets Ther       Date:  2020-12-24       Impact factor: 4.147

  1 in total

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