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Current Pathobiology Reports

, Volume 5, Issue 1, pp 23–34 | Cite as

Insights from Global Analyses of Long Noncoding RNAs in Breast Cancer

RNA in Pathobiology (AW Duncan, Section Editor)
Part of the following topical collections:
  1. Topical Collection on RNA in Pathobiology

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.

Keywords

Long noncoding RNAs Breast cancer Biomarkers The Cancer Genome Atlas Transcriptomics 

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

Notes

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).

Compliance with Ethical Standards

Conflict of Interest

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

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Computer Science, Biology and Biomedical Informatics, University of Pittsburgh Cancer Institute AcademiesUniversity of PittsburghPittsburghUSA
  2. 2.Chemistry DepartmentUniversity of PittsburghPittsburghUSA
  3. 3.Department of Biomedical InformaticsUniversity of PittsburghPittsburghUSA

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