FIGURE 5 from Proteasome Inhibition Reprograms Chromatin Landscape in Breast Cancer

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posted on 2024-04-16, 14:20 authored by H. Karimi Kinyamu, Brian D. Bennett, James M. Ward, Trevor K. Archer

DOCRs define important cis-regulatory regions specific to non-basal breast cancer tumors. A, Heat map showing chromatin accessibility signal (ATAC-seq) of TCGA breast cancer tumors (39) in DOCRs. Each row corresponds to a DOCR, and they are split by increase (GAIN) or decrease (LOST) in accessibility and by genomic category (PROMOTER, GENIC, INTERGENIC). N is the number of DOCRs in each category. Each column corresponds to a TCGA breast cancer tumor, split by non-basal (N = 57) and basal (N = 13) subtypes. Signal is z-score normalized by row, where red is high relative signal and blue is low relative signal. B, Venn diagram highlighting the number of SEs identified in Control only, 24H treated only, or shared between the samples. C, Heat map showing chromatin accessibility signal (ATAC-seq) of TCGA breast cancer tumors in SEs. Each row (N = 333) corresponds to a SE region, and they are split by cluster from hierarchical clustering. D, Circos plot showing chromosome coordinates of SEs, split by cluster. The outer ring shows reference chromosomes 1 through 22 in clockwise orientation. Inside rings correspond to clusters A–F from the heat map in C. The number of SE regions in each cluster per chromosome is indicated inset. Representative genes in SE regions in each cluster are shown. Color density indicates SE enrichment within each cluster and chromosome. E, Browser tracks showing the VMP1/MIR21 and SUMO1P1 SE regions. Tracks show read coverage of chromatin accessibility (ATAC), differential read coverage of accessibility (DIFF), H3K27ac read coverage, SE regions, and average ATAC read coverage for non-basal (brown) and basal (green) TCGA breast cancer tumors. Each track represents a control (0) light and 24H sample dark purple. F, Heat map showing ER ChIP-seq signal of MCF-7 cells treated with E2 (left) or Vehicle (right) in SE regions. Signal spans from 2 kb upstream of the SE, through the body of the SE, and to 2 kb downstream of the SE. Rows are split by cluster from the heat map in C. Signal is z-score normalized by row, where red is high relative signal and blue is low relative signal. G, Heat map showing ER ChIP-seq signal of breast tumor (left) or normal tissue (right) in SE regions. H, Heat maps showing differential signal for start RNA, accessibility (ATAC), RNAPII (Ser5P), K27ac and GRO-seq (E2) at non-genic TSSs that overlap GAIN (left) and LOST DOCRs (right). I, Browser tracks showing the SUMO1P1 SE region. Tracks show read coverage of chromatin accessibility (ATAC), differential accessibility (DIFF), SE regions, K27ac, RNAPII (SER5P), RNA-seq, and GRO-seq from cells treated with Veh and E2.

Funding

HHS | NIH | National Institute of Environmental Health Sciences (NIEHS)

History

ARTICLE ABSTRACT

The 26S proteasome is the major protein degradation machinery in cells. Cancer cells use the proteasome to modulate gene expression networks that promote tumor growth. Proteasome inhibitors have emerged as effective cancer therapeutics, but how they work mechanistically remains unclear. Here, using integrative genomic analysis, we discovered unexpected reprogramming of the chromatin landscape and RNA polymerase II (RNAPII) transcription initiation in breast cancer cells treated with the proteasome inhibitor MG132. The cells acquired dynamic changes in chromatin accessibility at specific genomic loci termed differentially open chromatin regions (DOCR). DOCRs with decreased accessibility were promoter proximal and exhibited unique chromatin architecture associated with divergent RNAPII transcription. Conversely, DOCRs with increased accessibility were primarily distal to transcription start sites and enriched in oncogenic superenhancers predominantly accessible in non-basal breast tumor subtypes. These findings describe the mechanisms by which the proteasome modulates the expression of gene networks intrinsic to breast cancer biology. Our study provides a strong basis for understanding the mechanisms by which proteasome inhibitors exert anticancer effects. We find open chromatin regions that change during proteasome inhibition, are typically accessible in non-basal breast cancers.