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Gene modules associated with breast cancer distant metastasis-free survival in the PAM50 molecular subtypes.

ABSTRACT: To identify PAM50 subtype-specific associations between distant metastasis-free survival (DMFS) in breast cancer (BC) patients and gene modules describing potentially targetable oncogenic pathways, a comprehensive analysis evaluating the prognostic efficacy of published gene signatures in 2027 BC patients from 13 studies was conducted. We calculated 21 gene modules and computed hazard ratios (HRs) for DMFS for one-unit increases in module score, with and without adjustment for clinical characteristics. By comparing gene expression to survival outcomes, we derived four subtype-specific prognostic signatures for BC. Univariate and multivariate analyses showed that in the luminal A subgroup, E2F3, PTEN and GGI gene module scores were associated with clinical outcome. In the luminal B tumors, RAS was associated with DMFS and in the basal-like tumors, ER was associated with DMFS. Our defined gene modules predicted high-risk patients in multivariate analyses for the basal-like (HR: 2.19, p=2.5×10-4), luminal A (HR: 3.03, p=7.2×10-5), luminal B (HR: 3.00, p=2.4×10-10) and HER2+ (HR: 5.49, p=9.7×10-10) subgroups. We found that different modules are associated with DMFS in different BC subtypes. The results of this study could help to identify new therapeutic strategies for specific molecular subgroups of BC, and could enhance efforts to improve patient-specific therapy options.

SUBMITTER: Liu R

PROVIDER: S-EPMC5008315 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Gene modules associated with breast cancer distant metastasis-free survival in the PAM50 molecular subtypes.

Liu Rong R Zhang Wei W Liu Zhao-Qian ZQ Zhou Hong-Hao HH

Oncotarget 20160401 16

To identify PAM50 subtype-specific associations between distant metastasis-free survival (DMFS) in breast cancer (BC) patients and gene modules describing potentially targetable oncogenic pathways, a comprehensive analysis evaluating the prognostic efficacy of published gene signatures in 2027 BC patients from 13 studies was conducted. We calculated 21 gene modules and computed hazard ratios (HRs) for DMFS for one-unit increases in module score, with and without adjustment for clinical character ...[more]

PMID: 26934123

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Project description:Breast cancer is a disease that exhibits heterogeneity that goes from the genomic to the clinical levels. This heterogeneity is thought to be captured (at least partially) by the so-called breast cancer molecular subtypes. These molecular subtypes were initially defined based on the unsupervised clustering of gene expression and its correlate with histological, morphological, phenotypic and clinical features already known. Later, a 50-gene signature, PAM50, was defined in order to identify the biological subtype of a given sample within the clinical setting. The PAM50 signature was obtained by the use of unsupervised statistical methods, and therefore no limitation was set on the biological relevance (or lack of) of the selected genes beyond its predictive capacity. An open question that remains is what are the regulatory elements that drive the various expression behaviors of this set of genes in the different molecular subtypes. This question becomes more relevant as the measurement of more biological layers of regulation becomes accessible. In this work, we analyzed the gene expression regulation of the 50 genes in the PAM50 signature, in terms of (a) gene co-expression, (b) transcription factors, (c) micro-RNAs, and (d) methylation. Using data from the Cancer Genome Atlas (TCGA) for the Luminal A and B, Basal, and HER2-enriched molecular subtypes as well as normal tumor adjacent tissue, we identified predictors for gene expression through the use of an elastic net model. We compare and contrast the sets of identified regulators for the gene signature in each molecular subtype, and systematically compare them to current literature. We also identified a unique set of predictors for the expression of genes in the PAM50 signature associated with each of the molecular subtypes. Most selected predictors are exclusive for a PAM50 gene and predictors are not shared across subtypes. There are only 13 coding transcripts and 2 miRNAs selected for the four subtypes. MiR-21 and miR-10b connect almost all the PAM50 genes in all the subtypes and normal tissue, but do it in an exclusive manner, suggesting a cancer switch from miR-10b coordination in normal tissue to miR-21. The PAM50 gene sets of selected predictors that enrich for a function across subtypes, support that different regulatory molecular mechanisms are taking place. With this study we aim to a wider understanding of the regulatory mechanisms that differentiate the expression of the PAM50 signature, which in turn could perhaps help understand the molecular basis of the differences between the molecular subtypes.

Project description:BackgroundDuring pregnancy, the mouse mammary ductal epithelium branches and grows into the surrounding stroma, requiring extensive extracellular matrix (ECM) and tissue remodelling. It therefore shows parallels to cancer invasion. We hypothesised that similar molecular mechanisms may be utilised in both processes, and that assessment of the stromal changes during pregnancy-associated branching may depict the stromal involvement during human breast cancer progression.MethodsImmunohistochemistry (IHC) was employed to assess the alterations within the mouse mammary gland extracellular matrix during early pregnancy when lateral branching of the primary ductal epithelium is initiated. Primary mouse mammary fibroblasts from three-day pregnant and age-matched non-pregnant control mice, respectively, were 3D co-cultured with mammary epithelial cells to assess differences in their abilities to induce branching morphogenesis in vitro. Transcriptome analysis was performed to identify the underlying molecular changes. A signature of the human orthologues of the differentially expressed matrisome RNAs was analysed by Kaplan-Meier and multi-variate analysis in two large breast cancer RNA datasets (Gene expression-based Outcome for Breast cancer Online (GOBO) und Kaplan-Meier Plotter), respectively, to test for similarities in expression between early-pregnancy mouse mammary gland development and breast cancer progression.ResultsThe ECM surrounding the primary ductal network showed significant differences in collagen and basement membrane protein distribution early during pregnancy. Pregnancy-associated fibroblasts (PAFs) significantly enhanced branching initiation compared to age-matched control fibroblast. A combined signature of 64 differentially expressed RNAs, encoding matrisome proteins, was a strong prognostic indicator of distant metastasis-free survival (DMFS) independent of other clinical parameters. The prognostic power could be significantly strengthened by using only a subset of 18 RNAs (LogRank P ≤ 1.00e-13; Hazard ratio (HR) = 2.42 (1.8-3.26); p = 5.61e-09). The prognostic power was confirmed in a second breast cancer dataset, as well as in datasets from ovarian and lung cancer patients.ConclusionsOur results describe for the first time the early stromal changes that accompany pregnancy-associated branching morphogenesis in mice, specify the early pregnancy-associated molecular alterations in mouse mammary fibroblasts, and identify a matrisome signature as a strong prognostic indicator of human breast cancer progression, with particular strength in oestrogen receptor (ER)-negative breast cancers.

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Gene modules associated with breast cancer distant metastasis-free survival in the PAM50 molecular subtypes.

Publications

Gene modules associated with breast cancer distant metastasis-free survival in the PAM50 molecular subtypes.

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