Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.

INTRODUCTION: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting...

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Main Authors: Ailbhe M McDermott, Nicola Miller, Deirdre Wall, Lorcan M Martyn, Graham Ball, Karl J Sweeney, Michael J Kerin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3909065?pdf=render
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spelling doaj-363af2d371b44cc995c3619a0459e9992020-11-25T01:24:51ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0191e8703210.1371/journal.pone.0087032Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.Ailbhe M McDermottNicola MillerDeirdre WallLorcan M MartynGraham BallKarl J SweeneyMichael J KerinINTRODUCTION: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. METHODS: Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n = 54) and controls (n = 56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n = 10 Luminal A-like; n = 10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n = 44 Luminal A; n = 46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated. RESULTS: Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis (miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652). The biomarker potential of 4 miRNAs (miR-29a, miR-181a, miR-223 and miR-652) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p = 0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs (miR-29a, miR-181a and miR-652) could reliably differentiate between cancers and controls with an AUC of 0.80. CONCLUSION: This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype-specific breast tumor detection.http://europepmc.org/articles/PMC3909065?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Ailbhe M McDermott
Nicola Miller
Deirdre Wall
Lorcan M Martyn
Graham Ball
Karl J Sweeney
Michael J Kerin
spellingShingle Ailbhe M McDermott
Nicola Miller
Deirdre Wall
Lorcan M Martyn
Graham Ball
Karl J Sweeney
Michael J Kerin
Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.
PLoS ONE
author_facet Ailbhe M McDermott
Nicola Miller
Deirdre Wall
Lorcan M Martyn
Graham Ball
Karl J Sweeney
Michael J Kerin
author_sort Ailbhe M McDermott
title Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.
title_short Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.
title_full Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.
title_fullStr Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.
title_full_unstemmed Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.
title_sort identification and validation of oncologic mirna biomarkers for luminal a-like breast cancer.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description INTRODUCTION: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. METHODS: Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n = 54) and controls (n = 56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n = 10 Luminal A-like; n = 10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n = 44 Luminal A; n = 46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated. RESULTS: Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis (miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652). The biomarker potential of 4 miRNAs (miR-29a, miR-181a, miR-223 and miR-652) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p = 0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs (miR-29a, miR-181a and miR-652) could reliably differentiate between cancers and controls with an AUC of 0.80. CONCLUSION: This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype-specific breast tumor detection.
url http://europepmc.org/articles/PMC3909065?pdf=render
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