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Updated: May 9, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Expression of polycomb targets predicts breast cancer prognosis
Alba Jene-Sanz1, Renáta Váraljai, Alexandra V Vilkova
1Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
Abstract:
Global changes in the epigenome are increasingly being appreciated as key events in cancer progression. The pathogenic role of enhancer of zeste homolog 2 (EZH2) has been connected to its histone 3 lysine 27 (H3K27) methyltransferase activity and gene repression; however, little is known about relationship of changes in expression of EZH2 target genes to cancer characteristics and patient prognosis. Here we show that through expression analysis of genomic regions with H3K27 trimethylation (H3K27me3) and EZH2 binding, breast cancer patients can be stratified into good and poor prognostic groups independent of known cancer gene signatures. The EZH2-bound regions were downregulated in tumors characterized by aggressive behavior, high expression of cell cycle genes, and low expression of developmental and cell adhesion genes. Depletion of EZH2 in breast cancer cells significantly increased expression of the top altered genes, decreased proliferation, and improved cell adhesion, indicating a critical role played by EZH2 in determining the cancer phenotype.
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