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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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Autores principales: McDermott, Ailbhe M., Miller, Nicola, Wall, Deirdre, Martyn, Lorcan M., Ball, Graham, Sweeney, Karl J., Kerin, Michael J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3909065/
https://www.ncbi.nlm.nih.gov/pubmed/24498016
http://dx.doi.org/10.1371/journal.pone.0087032
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author McDermott, Ailbhe M.
Miller, Nicola
Wall, Deirdre
Martyn, Lorcan M.
Ball, Graham
Sweeney, Karl J.
Kerin, Michael J.
author_facet McDermott, Ailbhe M.
Miller, Nicola
Wall, Deirdre
Martyn, Lorcan M.
Ball, Graham
Sweeney, Karl J.
Kerin, Michael J.
author_sort McDermott, Ailbhe M.
collection PubMed
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.
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spelling pubmed-39090652014-02-04 Identification and Validation of Oncologic miRNA Biomarkers for Luminal A-like Breast Cancer McDermott, Ailbhe M. Miller, Nicola Wall, Deirdre Martyn, Lorcan M. Ball, Graham Sweeney, Karl J. Kerin, Michael J. PLoS One Research Article 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. Public Library of Science 2014-01-31 /pmc/articles/PMC3909065/ /pubmed/24498016 http://dx.doi.org/10.1371/journal.pone.0087032 Text en © 2014 McDermott et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
McDermott, Ailbhe M.
Miller, Nicola
Wall, Deirdre
Martyn, Lorcan M.
Ball, Graham
Sweeney, Karl J.
Kerin, Michael J.
Identification and Validation of Oncologic miRNA Biomarkers for Luminal A-like Breast Cancer
title 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_short 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3909065/
https://www.ncbi.nlm.nih.gov/pubmed/24498016
http://dx.doi.org/10.1371/journal.pone.0087032
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