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Circulating microRNAs miR-331 and miR-195 differentiate local luminal a from metastatic breast cancer

McAnena, Peter
Tanriverdi, Kahraman
Curran, Catherine
Gilligan, K.
Freedman, Jane E.
Brown, James A. L.
Kerin, Michael J.
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Abstract

BACKGROUND: Breast cancer is the leading cause of cancer related death in women, with metastasis the principle cause of mortality. New non-invasive prognostic markers are needed for the early detection of metastasis, facilitating treatment decision optimisation. MicroRNA (miRNA) are small, non-coding RNAs regulating gene expression and involved in many cellular processes, including metastasis. As biomarkers, circulating miRNAs (in blood) hold great promise for informing diagnosis or monitoring treatment responses.

METHODS: Plasma extracted RNA from age matched local Luminal A (n = 4) or metastatic disease (n = 4) were profiled using Next Generation Sequencing. Selected differentially expressed miRNA were validated on a whole blood extracted miRNA cohort [distant metastatic disease (n = 22), local disease (n = 31), healthy controls (n = 21)]. Area Under the Curve (AUC) in Receiver Operating Characteristic (ROC) analyses was performed.

RESULTS: Of 4 miRNA targets tested (miR-181a, miR-329, miR-331, miR-195), mir-331 was significantly over-expressed in patients with metastatic disease, compared to patients with local disease (p < 0.001) or healthy controls (p < 0.001). miR-195 was significantly under-expressed in patients with metastatic disease, compared to patients with local disease (p < 0.001) or healthy controls (p = 0.043). In combination, miR-331 and miR-195 produced an AUC of 0.902, distinguishing metastatic from local breast cancer.

CONCLUSIONS: We identified and validated two circulating miRNAs differentiating local Luminal A breast cancers from metastatic breast cancers. Further investigation will reveal the molecular role of these miRNAs in metastasis, and determine if they are subtype specific. This work demonstrates the ability of circulating miRNA to identify metastatic disease, and potentially inform diagnosis or treatment effectiveness.

Source

BMC Cancer. 2019 May 10;19(1):436. doi: 10.1186/s12885-019-5636-y. Link to article on publisher's site

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DOI
10.1186/s12885-019-5636-y
PubMed ID
31077182
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© The Author(s). 2019 Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.