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MiRNA analysis of triple-negative breast cancers in association with clinical and molecular phenotypes

ABSTRACT: Background: This study focuses on the analysis of miRNAs expression data in a cohort of 181 well characterised breast cancer samples composed primarily of triple-negative (ER/PR/HER2-negative) tumours with associated genome-wide DNA and mRNA data, extensive patient follow-up and pathological information. Results: We identified 7 miRNAs with a prognostic role in the triple-negative tumours and an additional 8 prognostic miRNAs when the analysis was extended to the set of all ER-negative cases. miRNAs linked to an unfavourable prognosis were associated with a broad spectrum of motility mechanisms involved in the invasion of stromal tissues, such as cell-adhesion, growth factor-mediated signalling pathways, interaction with the extracellular matrix and cytoskeleton remodelling. When we compared different intrinsic molecular subtypes we found 46 miRNAs that were specifically expressed in one or more intrinsic subtypes. Integrated genomic analyses indicated these miRNAs to be largely influenced by DNA genomic aberrations and to exert a silencing effect on their targets through transcriptional down-regulation. Among others, our analyses highlighted the role of miR17-92 and miR-106b-25, two polycistronic miRNA clusters with known oncogenic functions. We showed that their basal-like specific up-regulation is influenced by increased DNA copy number and contributes to the transcriptional phenotype and the activation of oncogenic pathways in basal-like tumours.Conclusions: This is the first study analysing miRNA, mRNA and DNA data in integration with pathological and clinical information, in a large and well-annotated cohort of triple-negative breast cancers. It provides a conceptual framework, as well as integrative methods and system-level results to elucidate the role of miRNAs as biomarkers and modulators of oncogenic processes in these types of tumours.

ORGANISM(S): Homo sapiens

PROVIDER: GSE40267 | GEO | 2013/09/30

SECONDARY ACCESSION(S): PRJNA173369

REPOSITORIES: GEO

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Project description:Background: This study focuses on the analysis of miRNAs expression data in a cohort of 181 well characterised breast cancer samples composed primarily of triple-negative (ER/PR/HER2-negative) tumours with associated genome-wide DNA and mRNA data, extensive patient follow-up and pathological information. Results: We identified 7 miRNAs with a prognostic role in the triple-negative tumours and an additional 8 prognostic miRNAs when the analysis was extended to the set of all ER-negative cases. miRNAs linked to an unfavourable prognosis were associated with a broad spectrum of motility mechanisms involved in the invasion of stromal tissues, such as cell-adhesion, growth factor-mediated signalling pathways, interaction with the extracellular matrix and cytoskeleton remodelling. When we compared different intrinsic molecular subtypes we found 46 miRNAs that were specifically expressed in one or more intrinsic subtypes. Integrated genomic analyses indicated these miRNAs to be largely influenced by DNA genomic aberrations and to exert a silencing effect on their targets through transcriptional down-regulation. Among others, our analyses highlighted the role of miR17-92 and miR-106b-25, two polycistronic miRNA clusters with known oncogenic functions. We showed that their basal-like specific up-regulation is influenced by increased DNA copy number and contributes to the transcriptional phenotype and the activation of oncogenic pathways in basal-like tumours.Conclusions: This is the first study analysing miRNA, mRNA and DNA data in integration with pathological and clinical information, in a large and well-annotated cohort of triple-negative breast cancers. It provides a conceptual framework, as well as integrative methods and system-level results to elucidate the role of miRNAs as biomarkers and modulators of oncogenic processes in these types of tumours. 181 breast tumour samples were analyzed, extracted from 173 patients. For the great majority of patients (165) only one sample was extracted, while for 8 patients two samples were extracted (biological replicates).

Project description:When making treatment decisions, oncologists often stratify breast cancers into a low-risk group (ER+, low grade); an intermediate-risk group (ER+, high grade); and a high-risk group that includes Her2+ and triple-negative (ER-/PR-/Her2-) tumors. None of the currently available gene signatures correlates to this clinical classification. We aimed to develop a test that is practical for the oncologists, that offers both molecular characterization of BCs, and improved prediction of prognosis and treatment response. We investigated the molecular basis of such clinical practice by grouping Her2+ and triple-negative breast cancers together during clustering analyses on the genome-wide gene expression profiles of our training cohort, mostly derived from fine needle aspiration biopsies (FNABs) of 149 consecutive evaluable Breast cancers. The analyses consistently divided these tumors into a three-cluster pattern, similar to clinical risk-stratification groups, that was reproducible in published microarray databases (n=2487) annotated with clinical outcomes. The clinicopathologic parameters of each of these three molecular groups were also similar to clinical classification. The low-risk group had good outcomes and benefited from endocrine therapy. Both intermediate- and high-risk groups had poor outcomes and were resistant to endocrine therapy. The latter demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in MYC, E2F1, Ras, β-Catenin and IFN-γ pathways; and poor prognosis predicted by 14 independent prognostic signatures. Based on a multivariate analysis, this new gene signature, termed ClinicoMolecular Triad Classification, predicted recurrence and treatment response better than all pathologic parameters and other prognostic signatures. 149 invasive breast cancers from the 172 specimens contained 161 tumors were used in this study. Expression data of the 11 tumors with replicate was separately combined before analysis.

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MiRNA analysis of triple-negative breast cancers in association with clinical and molecular phenotypes

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