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Molecular stratification within triple-negative breast cancer subtypes.

ABSTRACT: Triple-negative breast cancer (TNBC) has been subdivided into six distinct subgroups: basal-like 1 (BL1), basal-like 2 (BL2), mesenchymal (M), mesenchymal stem-like (MSL), immunomodulatory (IM), and luminal androgen receptor (LAR). We recently identified a subgroup of TNBC with loss of the tumor suppressor PTEN and five specific microRNAs that exhibits exceedingly poor clinical outcome and contains TP53 mutation, RB1 loss and high MYC and WNT signalling. Here, show that these PTEN-low/miRNA-low lesions cluster with BL1 TNBC. These tumors exhibited high RhoA signalling and were significantly stratified on the basis of PTEN-low/RhoA-signalling-high with hazard ratios (HRs) of 8.2 (P?=?0.0009) and 4.87 (P?=?0.033) in training and test cohorts, respectively. For BL2 TNBC, we identified AKT1 copy gain/high mRNA expression as surrogate for poor prognosis (HR?=?3.9; P?=?0.02 and HR?=?6.1; P?=?0.0032). In IM, programmed cell death 1 (PD1) was elevated and predictive of poor prognosis (HR?=?5.3; P?=?0.01 and HR?=?3.5; P?

SUBMITTER: Wang DY

PROVIDER: S-EPMC6911070 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Molecular stratification within triple-negative breast cancer subtypes.

Wang Dong-Yu DY Jiang Zhe Z Ben-David Yaacov Y Woodgett James R JR Zacksenhaus Eldad E

Scientific reports 20191213 1

Triple-negative breast cancer (TNBC) has been subdivided into six distinct subgroups: basal-like 1 (BL1), basal-like 2 (BL2), mesenchymal (M), mesenchymal stem-like (MSL), immunomodulatory (IM), and luminal androgen receptor (LAR). We recently identified a subgroup of TNBC with loss of the tumor suppressor PTEN and five specific microRNAs that exhibits exceedingly poor clinical outcome and contains TP53 mutation, RB1 loss and high MYC and WNT signalling. Here, show that these PTEN-low/miRNA-low ...[more]

PMID: 31836816

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Project description:Triple-negative breast cancer (TNBC) is a heterogeneous disease that can be classified into distinct molecular subtypes by gene expression profiling. Considered a difficult-to-treat cancer, a fraction of TNBC patients benefit significantly from neoadjuvant chemotherapy and have far better overall survival. Outside of BRCA1/2 mutation status, biomarkers do not exist to identify patients most likely to respond to current chemotherapy; and, to date, no FDA-approved targeted therapies are available for TNBC patients. Previously, we developed an approach to identify six molecular subtypes TNBC (TNBCtype), with each subtype displaying unique ontologies and differential response to standard-of-care chemotherapy. Given the complexity of the varying histological landscape of tumor specimens, we used histopathological quantification and laser-capture microdissection to determine that transcripts in the previously described immunomodulatory (IM) and mesenchymal stem-like (MSL) subtypes were contributed from infiltrating lymphocytes and tumor-associated stromal cells, respectively. Therefore, we refined TNBC molecular subtypes from six (TNBCtype) into four (TNBCtype-4) tumor-specific subtypes (BL1, BL2, M and LAR) and demonstrate differences in diagnosis age, grade, local and distant disease progression and histopathology. Using five publicly available, neoadjuvant chemotherapy breast cancer gene expression datasets, we retrospectively evaluated chemotherapy response of over 300 TNBC patients from pretreatment biopsies subtyped using either the intrinsic (PAM50) or TNBCtype approaches. Combined analysis of TNBC patients demonstrated that TNBC subtypes significantly differ in response to similar neoadjuvant chemotherapy with 41% of BL1 patients achieving a pathological complete response compared to 18% for BL2 and 29% for LAR with 95% confidence intervals (CIs; [33, 51], [9, 28], [17, 41], respectively). Collectively, we provide pre-clinical data that could inform clinical trials designed to test the hypothesis that improved outcomes can be achieved for TNBC patients, if selection and combination of existing chemotherapies is directed by knowledge of molecular TNBC subtypes.

Project description:Triple-negative breast cancer (TNBC) is a highly heterogeneous group of cancers, and molecular subtyping is necessary to better identify molecular-based therapies. While some classifiers have been established, no one has integrated the expression profiles of long noncoding RNAs (lncRNAs) into such subtyping criterions. Considering the emerging important role of lncRNAs in cellular processes, a novel classification integrating transcriptome profiles of both messenger RNA (mRNA) and lncRNA would help us better understand the heterogeneity of TNBC.Using human transcriptome microarrays, we analyzed the transcriptome profiles of 165 TNBC samples. We used k-means clustering and empirical cumulative distribution function to determine optimal number of TNBC subtypes. Gene Ontology (GO) and pathway analyses were applied to determine the main function of the subtype-specific genes and pathways. We conducted co-expression network analyses to identify interactions between mRNAs and lncRNAs.All of the 165 TNBC tumors were classified into four distinct clusters, including an immunomodulatory subtype (IM), a luminal androgen receptor subtype (LAR), a mesenchymal-like subtype (MES) and a basal-like and immune suppressed (BLIS) subtype. The IM subtype had high expressions of immune cell signaling and cytokine signaling genes. The LAR subtype was characterized by androgen receptor signaling. The MES subtype was enriched with growth factor signaling pathways. The BLIS subtype was characterized by down-regulation of immune response genes, activation of cell cycle, and DNA repair. Patients in this subtype experienced worse recurrence-free survival than others (log rank test, P = 0.045). Subtype-specific lncRNAs were identified, and their possible biological functions were predicted using co-expression network analyses.We developed a novel TNBC classification system integrating the expression profiles of both mRNAs and lncRNAs and determined subtype-specific lncRNAs that are potential biomarkers and targets. If further validated in a larger population, our novel classification system could facilitate patient counseling and individualize treatment of TNBC.

Dataset Information

Molecular stratification within triple-negative breast cancer subtypes.

Publications

Molecular stratification within triple-negative breast cancer subtypes.

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