Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes

Karel Kalecky,Joseph Taube,Rebecca Modisette,Samantha Pena,Young-Rae Cho

doi:10.1186/s12885-020-6600-6

Karel Kalecky, Joseph Taube + Show 3 more

Open Access

https://doi.org/10.1186/s12885-020-6600-6

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Journal: BMC Cancer	Publication Date: Feb 21, 2020
Citations: 18	License type: open-access

Affiliation: Baylor University, Yonsei University

Abstract

BackgroundThe term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression of estrogen receptor, progesterone receptor or HER2 amplification. To advance targeted treatment options for TNBC, it is critical that the subtypes within this classification be described in regard to their characteristic biology and gene expression. The Cancer Genome Atlas (TCGA) dataset provides not only clinical and mRNA expression data but also expression data for microRNAs.ResultsIn this study, we applied the Lehmann classifier to TCGA-derived TNBC cases which also contained microRNA expression data and derived subtype-specific microRNA expression patterns. Subsequent analyses integrated known and predicted microRNA-mRNA regulatory nodes as well as patient survival data to identify key networks. Notably, basal-like 1 (BL1) TNBCs were distinguished from basal-like 2 TNBCs through up-regulation of members of the miR-17-92 cluster of microRNAs and suppression of several known miR-17-92 targets including inositol polyphosphate 4-phosphatase type II, INPP4B.ConclusionsThese data demonstrate TNBC subtype-specific microRNA and target mRNA expression which may be applied to future biomarker and therapeutic development studies.

Highlights

The term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression of estrogen receptor, progesterone receptor or human epidermal growth factor receptor 2 (HER2) amplification
Intertumoral heterogeneity within TNBC has been revealed by recent studies [3,4,5], which show that intrinsic molecular subtyping may be used to separate TNBCs into between four and six subtypes variously labeled as basal-like 1 (BL1), basal-like 2 (BL2), mesenchymal (M), mesenchymal stem-like (MSL), immunomodulatory (IM), and luminal androgen receptor (LAR)
We show that 1) BL1, BL2, M, and LAR tumors display individually distinct microRNA expression profiles, 2) the set of predicted microRNA targets corresponds to the set of altered genes between each subtypes and 3) validation in vitro that miRNA, including miR-17-92 cluster members, expression differences predicted between BL1 and BL2 subtypes are validated in a set of breast cancer cell lines, contributing to the distinct expression of known target genes

Summary

Introduction

The term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression of estrogen receptor, progesterone receptor or HER2 amplification. To advance targeted treatment options for TNBC, it is critical that the subtypes within this classification be described in regard to their characteristic biology and gene expression. The Cancer Genome Atlas (TCGA) dataset provides clinical and mRNA expression data and expression data for microRNAs. Breast cancer is a heterogeneous group of diseases, each with characteristic etiologies and optimal treatments. Expression of hormone receptors, estrogen receptor (ER) and progesterone receptor (PR), or human epidermal growth factor receptor 2 (HER2) indicates responsiveness to therapies targeted at these proteins. For the approximately 20% of breast cancer patients with tumors negative for such markers, termed triple-negative breast cancer (TNBC), there is presently a lack of effective targeted treatment options [1].

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