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MiRNA-dependent regulation of STIM1 expression in breast cancer.

ABSTRACT: Store-operated Ca2+ entry (SOCE) has been shown to be important for breast cancer metastasis in xenograft mouse models. The ER Ca2+ sensor STIM1 and Orai plasma membrane Ca2+ channels molecularly mediate SOCE. Here we investigate the role of the microRNA machinery in regulating STIM1 expression. We show that STIM1 expression is regulated post-transcriptionally by the miRNA machinery and identify miR-223 and miR-150 as regulators of STIM1 expression in the luminal non-aggressive MCF7 breast cancer cell line. In contrast, STIM1 expression in the more aggressive basal triple-negative MDA-MB-231 cell line is not significantly modulated by a single miRNA species but is rather upregulated due to inhibition of the miRNA machinery through downregulation of Ago2. Consistently, overexpression of Ago2 results in decreased STIM1 protein levels in MDA-MB-231 cells. Clinically, STIM1 and Ago2 expression levels do not correlate with breast cancer progression, however in the basal subtype high STIM1 expression is associated with poorer survival. Our findings show that STIM1 expression is differentially regulated by the miRNA machinery in different cell types and argue for a role for this regulation in breast cancer.

SUBMITTER: Kulkarni RP

PROVIDER: S-EPMC6736934 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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miRNA-dependent regulation of STIM1 expression in breast cancer.

Kulkarni Rashmi P RP Elmi Asha A Alcantara-Adap Ethel E Hubrack Satanay S Nader Nancy N Yu Fang F Dib Maya M Ramachandran Vimal V Najafi Shoushtari Hani H Machaca Khaled K

Scientific reports 20190910 1

Store-operated Ca2+ entry (SOCE) has been shown to be important for breast cancer metastasis in xenograft mouse models. The ER Ca2+ sensor STIM1 and Orai plasma membrane Ca2+ channels molecularly mediate SOCE. Here we investigate the role of the microRNA machinery in regulating STIM1 expression. We show that STIM1 expression is regulated post-transcriptionally by the miRNA machinery and identify miR-223 and miR-150 as regulators of STIM1 expression in the luminal ...[more]

PMID: 31506588

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Project description:BackgroundMicroRNAs (miRNAs) are important key regulators in multiple cellular functions, due to their a crucial role in different physiological processes. MiRNAs are differentially expressed in specific tissues, during specific cell status, or in different diseases as tumours. RNA sequencing (RNA-seq) is a Next Generation Sequencing (NGS) method for the analysis of differential gene expression. Using machine learning algorithms, it is possible to improve the functional significance interpretation of miRNA in the analysis and interpretation of data from RNA-seq. Furthermore, we tried to identify some patterns of deregulated miRNA in human breast cancer (BC), in order to give a contribution in the understanding of this type of cancer at the molecular level.ResultsWe adopted a biclustering approach, using the Iterative Signature Algorithm (ISA) algorithm, in order to evaluate miRNA deregulation in the context of miRNA abundance and tissue heterogeneity. These are important elements to identify miRNAs that would be useful as prognostic and diagnostic markers. Considering a real word breast cancer dataset, the evaluation of miRNA differential expressions in tumours versus healthy tissues evidenced 12 different miRNA clusters, associated to specific groups of patients. The identified miRNAs were deregulated in breast tumours compared to healthy controls. Our approach has shown the association between specific sub-class of tumour samples having the same immuno-histo-chemical and/or histological features. Biclusters have been validated by means of two online repositories, MetaMirClust database and UCSC Genome Browser, and using another biclustering algorithm.ConclusionsThe obtained results with biclustering algorithm aimed first of all to give a contribute in the differential expression analysis in a cohort of BC patients and secondly to support the potential role that these non-coding RNA molecules could play in the clinical practice, in terms of prognosis, evolution of tumour and treatment response.

Dataset Information

MiRNA-dependent regulation of STIM1 expression in breast cancer.

Publications

miRNA-dependent regulation of STIM1 expression in breast cancer.

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