A Histone Acetylation Modulator Gene Signature for Classification and Prognosis of Breast Cancer

Abstract

Regulators of histone acetylation are promising epigenetic targets for therapy in breast cancer. In this study, we comprehensively analyzed the expression of histone acetylation modulator genes in breast cancer using TCGA data sources. A gene signature composed of eight histone acetylation modulators (HAMs) was found to be effective for the classification and prognosis of breast cancers, especially in the HER2-enriched and basal-like molecular subtypes. The eight genes consist of two histone acetylation writers (GTF3C4 and CLOCK), two erasers (HDAC2 and SIRT7) and four readers (BRD4, BRD7, SP100, and BRWD3). Both histone acetylation writer genes and eraser genes were found to be differentially expressed between the two groups indicating a close relationship exists between overall histone acetylation level and prognosis of breast cancer in HER2-enriched and basal-like breast cancer.

Potential of Dietary HDAC2i in Breast Cancer Patients Receiving PD-1/PD-L1 Inhibitors

“…HDAC2 has been identified as a crucial regulator of epigenetic control in BC and HDAC2 suppression has been further proved to be an effective approach to treating BC by numerous studies [ 24 , 25 , 26 ]. For instance, HDAC2 inhibition has been observed to inhibit cellular proliferation in a p53-dependent manner in BC cells [ 27 ].…”

Expression of DNA Helicase Genes Was Correlated with Homologous Recombination Deficiency in Breast Cancer

“…Fragments per kilobase of transcript per million mapped reads upper quartile (FPKM-UQ) is used for the normalization of RNA transcript reads. FPKM-UQ RNA-seq data were downloaded and prepared using the GDCquery, GDCdownload, and GDCprepare functions, as described in our previous publications [19][20][21].…”

AR Expression Correlates with Distinctive Clinicopathological and Genomic Features in Breast Cancer Regardless of ESR1 Expression Status

“…For breast cancer from TCGA [ 41 ], RNA-seq and clinical data of 1102 breast cancer samples were downloaded and processed using the TCGAbioloinks R/Bioconductor package (version 2.18.0) [ 42 ], as described in a series of our previous publications [ 43 , 44 , 45 , 46 ]. The Fragments Per Kilobase of transcript per Million mapped reads Upper Quartile (FPKM-UQ) RNA-seq data were log2-transformed before being further processed.…”