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Insights from Global Analyses of Long Noncoding RNAs in Breast Cancer

  • RNA in Pathobiology (AW Duncan, Section Editor)
  • Published:
Current Pathobiology Reports

Abstract

Purpose of Review

The goal of this review was to compare and contrast the results and implications from several recent transcriptomic studies that analyzed the expression of long noncoding RNAs (lncRNAs) in breast cancer. How many lncRNAs are dysregulated in breast cancer? Do dysregulated lncRNAs contribute to breast cancer etiology? Are lncRNAs viable biomarkers in breast cancer?

Recent Findings

Transcriptomic profiling of breast cancer tissues, mostly from The Cancer Genome Atlas, identified thousands of long noncoding RNAs that are expressed and dysregulated in breast cancer. The expression of lncRNAs alone can divide patients into molecular subtypes. Subsequent functional studies demonstrated that several of these lncRNAs have important roles in breast cancer cell biology.

Summary

Thousands of lncRNAs are dysregulated in breast cancer that can be developed as biomarkers for prognostic or therapeutic purposes. The reviewed reports provide a roadmap to guide functional studies to discover lncRNAs with critical biological functions relating to breast cancer development and progression.

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Abbreviations

lncRNA:

Long noncoding RNA

PCG:

Protein coding gene

GWAS:

Genome-wide association studies

RNAseq:

RNA sequencing

TCGA:

The Cancer Genome Atlas

ER:

Estrogen receptor

PR:

Progesterone receptor

TNBC:

Triple-negative breast cancer

SNP:

Single nucleotide polymorphism

EMT:

Epithelial-mesenchymal transition

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Acknowledgements

We acknowledge Sreeroopa Som for her comments during the planning of the manuscript. We also thank our funding sources. DB was supported in part by a Susan G. Komen Foundation Fellowship. AW was supported in part through the Computer Science, Biology, and Biomedical Informatics and the University of Pittsburgh Cancer Institute Academies, which are supported through grants from the Doris Duke Foundation-Clinical Research Experiences for High School Students at the University of Pittsburgh (grant no. 2014154), the National Cancer Institute CURE Program (3P30CA047904-27S2), and support from the Jack Kent Cook Foundation and donations from UPMC and grateful parents and patients. Additionally, we would like to thank the team from the Department of Biomedical Informatics National Library of Medicine Training Program Grant in Biomedical Informatics (T15 LM007059), the University of Pittsburgh Cancer Institute (UPCI) Cancer Center Support Grant for the Cancer Bioinformatics Service (P30 CA47904), and the Clinical and Translational Science Institute Biomedical Informatics Core (UL1 RR024153).

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  1. Computer Science, Biology and Biomedical Informatics, University of Pittsburgh Cancer Institute Academies, University of Pittsburgh, Pittsburgh, USA

    Andrew J. Warburton & David N. Boone

  2. Chemistry Department, University of Pittsburgh, Pittsburgh, USA

    Andrew J. Warburton

  3. Department of Biomedical Informatics, University of Pittsburgh, 5607 Baum Blvd, Suite 433, Pittsburgh, PA, 15206-3701, USA

    David N. Boone

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  1. Andrew J. Warburton
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Andrew Warburton and David Boone declare that they have no conflict of interest.

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This article is part of the Topical Collection on RNA in Pathobiology

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Warburton, A.J., Boone, D.N. Insights from Global Analyses of Long Noncoding RNAs in Breast Cancer. Curr Pathobiol Rep 5, 23–34 (2017). https://doi.org/10.1007/s40139-017-0122-1

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