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Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis

The incidence of endometrial cancer (EC) is intensively increasing. However, due to the complexity and heterogeneity of EC, the molecular targeted therapy is still limited. The reliable and accurate biomarkers for tumor progression are urgently demanded. After normalizing the data from Gene Expressi...

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Autores principales: Yang, Linlin, Cui, Yunxia, Sun, Xiao, Wang, Yudong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906164/
https://www.ncbi.nlm.nih.gov/pubmed/33495413
http://dx.doi.org/10.18632/aging.202417
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author Yang, Linlin
Cui, Yunxia
Sun, Xiao
Wang, Yudong
author_facet Yang, Linlin
Cui, Yunxia
Sun, Xiao
Wang, Yudong
author_sort Yang, Linlin
collection PubMed
description The incidence of endometrial cancer (EC) is intensively increasing. However, due to the complexity and heterogeneity of EC, the molecular targeted therapy is still limited. The reliable and accurate biomarkers for tumor progression are urgently demanded. After normalizing the data from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), we utilized limma and WGCNA packages to identify differentially expressed genes (DEGs). The copy number variations of candidate genes were investigated by cBioPortal. Enrichment pathways analysis was performed by ClueGO and CluePedia. The methylation status was explored by UALCAN. ROC curve and survival analysis were conducted by SPSS and Kaplan–Meier. Infiltration immune cells in microenvironment were analyzed by TISIDB. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were applied to explore potential biological pathways. Immunohistochemistry staining (IHC), cell proliferation, cell apoptosis, colony formation, migration, invasion and scratch-wound assays were performed to investigate the function of key genes in vitro. In this study, four expression profile datasets were integrated to identify candidate genes. Combined with WGCNA analysis, the top ten candidates were screened out, whose abnormal methylation patterns were extremely correlated with their expression level and they were associated with tumor grades and predicted poor survival. GSEA and GSVA demonstrated they were involved in DNA replication and cell cycle transition in EC. Gene silencing of TICRR and PPIF dramatically inhibited cell growth, migration and epithelial-mesenchymal transition (EMT) and enhanced progesterone sensitivity. Additionally, from DrugBank database, cyclosporine may be effective for PPIF targeted therapy. By integrative bioinformatics analysis and in vitro experiments, our study shed novel light on the molecular mechanisms of EC. TICRR and PPIF may promise to be potential therapeutic targets for endometrial cancer.
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spelling pubmed-79061642021-03-04 Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis Yang, Linlin Cui, Yunxia Sun, Xiao Wang, Yudong Aging (Albany NY) Research Paper The incidence of endometrial cancer (EC) is intensively increasing. However, due to the complexity and heterogeneity of EC, the molecular targeted therapy is still limited. The reliable and accurate biomarkers for tumor progression are urgently demanded. After normalizing the data from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), we utilized limma and WGCNA packages to identify differentially expressed genes (DEGs). The copy number variations of candidate genes were investigated by cBioPortal. Enrichment pathways analysis was performed by ClueGO and CluePedia. The methylation status was explored by UALCAN. ROC curve and survival analysis were conducted by SPSS and Kaplan–Meier. Infiltration immune cells in microenvironment were analyzed by TISIDB. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were applied to explore potential biological pathways. Immunohistochemistry staining (IHC), cell proliferation, cell apoptosis, colony formation, migration, invasion and scratch-wound assays were performed to investigate the function of key genes in vitro. In this study, four expression profile datasets were integrated to identify candidate genes. Combined with WGCNA analysis, the top ten candidates were screened out, whose abnormal methylation patterns were extremely correlated with their expression level and they were associated with tumor grades and predicted poor survival. GSEA and GSVA demonstrated they were involved in DNA replication and cell cycle transition in EC. Gene silencing of TICRR and PPIF dramatically inhibited cell growth, migration and epithelial-mesenchymal transition (EMT) and enhanced progesterone sensitivity. Additionally, from DrugBank database, cyclosporine may be effective for PPIF targeted therapy. By integrative bioinformatics analysis and in vitro experiments, our study shed novel light on the molecular mechanisms of EC. TICRR and PPIF may promise to be potential therapeutic targets for endometrial cancer. Impact Journals 2021-01-20 /pmc/articles/PMC7906164/ /pubmed/33495413 http://dx.doi.org/10.18632/aging.202417 Text en Copyright: © 2021 Yang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Yang, Linlin
Cui, Yunxia
Sun, Xiao
Wang, Yudong
Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis
title Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis
title_full Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis
title_fullStr Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis
title_full_unstemmed Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis
title_short Overexpression of TICRR and PPIF confer poor prognosis in endometrial cancer identified by gene co-expression network analysis
title_sort overexpression of ticrr and ppif confer poor prognosis in endometrial cancer identified by gene co-expression network analysis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906164/
https://www.ncbi.nlm.nih.gov/pubmed/33495413
http://dx.doi.org/10.18632/aging.202417
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