AUTHOR=Li Yalun , Chen Gang , Zhang Kun , Cao Jianqiao , Zhao Huishan , Cong Yizi , Qiao Guangdong TITLE=Integrated transcriptome and network analysis identifies EZH2/CCNB1/PPARG as prognostic factors in breast cancer JOURNAL=Frontiers in Genetics VOLUME=13 YEAR=2023 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1117081 DOI=10.3389/fgene.2022.1117081 ISSN=1664-8021 ABSTRACT=
Breast cancer (BC) has high morbidity, with significant relapse and mortality rates in women worldwide. Therefore, further exploration of its pathogenesis is of great significance. This study selected therapy genes and possible biomarkers to predict BC using bioinformatic methods. To this end, the study examined 21 healthy breasts along with 457 BC tissues in two Gene Expression Omnibus (GEO) datasets and then identified differentially expressed genes (DEGs). Survival-associated DEGs were screened using the Kaplan–Meier curve. Based on Gene Ontology (GO) annotation, survival-associated DEGs were mostly associated with cell division and cellular response to hormone stimulus. The enriched Kyoto Encyclopedia of Gene and Genome (KEGG) pathway was mostly correlated with cell cycle and tyrosine metabolism. Using overlapped survival-associated DEGs, a survival-associated PPI network was constructed. PPI analysis revealed three hub genes (