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Linking signaling pathways to transcriptional programs in breast cancer.

ABSTRACT: Cancer cells acquire genetic and epigenetic alterations that often lead to dysregulation of oncogenic signal transduction pathways, which in turn alters downstream transcriptional programs. Numerous methods attempt to deduce aberrant signaling pathways in tumors from mRNA data alone, but these pathway analysis approaches remain qualitative and imprecise. In this study, we present a statistical method to link upstream signaling to downstream transcriptional response by exploiting reverse phase protein array (RPPA) and mRNA expression data in The Cancer Genome Atlas (TCGA) breast cancer project. Formally, we use an algorithm called affinity regression to learn an interaction matrix between upstream signal transduction proteins and downstream transcription factors (TFs) that explains target gene expression. The trained model can then predict the TF activity, given a tumor sample's protein expression profile, or infer the signaling protein activity, given a tumor sample's gene expression profile. Breast cancers are comprised of molecularly distinct subtypes that respond differently to pathway-targeted therapies. We trained our model on the TCGA breast cancer data set and identified subtype-specific and common TF regulators of gene expression. We then used the trained tumor model to predict signaling protein activity in a panel of breast cancer cell lines for which gene expression and drug response data was available. Correlations between inferred protein activities and drug responses in breast cancer cell lines grouped several drugs that are clinically used in combination. Finally, inferred protein activity predicted the clinical outcome within the METABRIC Luminal A cohort, identifying high- and low-risk patient groups within this heterogeneous subtype.

SUBMITTER: Osmanbeyoglu HU

PROVIDER: S-EPMC4216927 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Project description:Progesterone receptor (PR) and its co-activators are direct targets of activated cyclin dependent kinases (CDKs) in response to peptide growth factors, progesterone, and deregulation of cell cycle inhibitors. Herein, using the T47D breast cancer model, we probed mechanisms of cell cycle-dependent PR action. In the absence of exogenous progestin, PR is specifically phosphorylated during the G2/M phase. Accordingly, numerous PR target genes are cell cycle regulated, including HSPB8, a heat-shock protein whose high expression is associated with tamoxifen-resistance. Progestin-induced HSPB8 expression required cyclin D1 and was insensitive to anti-estrogens, but blocked by anti-progestins or inhibition of specificity factor 1 (SP1). HSPB8 expression increased with or without ligand when cells were G2/M synchronized or contained high levels of cyclin D1. Knock-down of PR abrogated ligand-independent HSPB8 expression in synchronized cells. Notably, PR and cyclin D1 co-purified in whole cell lysates of transiently transfected COS-1 cells and in PR-positive T47D breast cancer cells expressing endogenous cyclin D1. PR, cyclin D1, and SP1 were recruited to the HSPB8 promoter in progestin-treated T47D breast cancer cells. Mutation of PR Ser345 to Ala (S345A) or inhibition of CDK2 activity using roscovitine disrupted PR/cyclin D1 interactions with DNA and blocked HSPB8 mRNA expression. Interaction of phosphorylated PRs with SP1 and cyclin D1 provides a mechanism for targeting transcriptionally active PRs to selected gene promoters relevant to breast cancer progression. Understanding the functional linkage between PR and cell cycle regulatory proteins will provide keys to targeting novel PR/cyclin D1 cross-talk in both hormone-responsive and HSPB8-high refractory disease. The study contains 4 different sample groups measured in triplicate, for a total of 12 individual samples (12 arrays). In T47D human breast cancer cell lines stably expressing PR-B, cells were synchronized (or not synchronized) before G2/M phase using nocodazole. These cell lines (synchronized or not synchronized) were treated with either (1) vehicle control (ethanol) or (2) PR ligand R5020 10e-8 M for 6 hours before total RNA harvest. Thus, the experiment contains two cell lines, and two treatments (4 sample groups) treated and analyzed in triplicate (12 microarrays). Standard Illumina HT-12v4 chip controls were used during hybridization.

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Linking signaling pathways to transcriptional programs in breast cancer.

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