The apoptotic network and expression of BH3-containing proteins predict phenotypic response to BET bromodomain inhibitors
Transcriptomics Dataset
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General Information
AccessionGSE69383
TitleThe apoptotic network and expression of BH3-containing proteins predict phenotypic response to BET bromodomain inhibitors
DescriptionSmall molecule inhibitors of the bromodomain and extraterminal (BET) family of proteins are in clinical trials for a variety of cancers, but patient selection strategies are limited. This is due in part to the heterogeneity of response following BET inhibition (BETi), which includes differentiation, senescence, and cell death in subsets of cancer cell lines. To elucidate the dominant features defining response to BETi, we carried out phenotypic and gene expression analysis of both treatment nave cell lines and engineered tolerant lines. We found that both de novo and acquired tolerance to BET inhibition are driven by the robustness of the apoptotic response and that genetic or pharmacological manipulation of the apoptotic signaling network can modify the phenotypic response to BETi. We further identify that ordered expression of the apoptotic genes BCL2, BCL2L1, and BAD significantly predicts response to BETi. Our findings highlight the role of the apoptotic network in response to BETi, providing a molecular basis for patient stratification and combination therapies.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE69383
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE69383
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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