Research Papers:

Discovery and replication of microRNAs for breast cancer risk using genome-wide profiling

Cenny Taslim, Daniel Y. Weng, Theodore M. Brasky, Ramona G. Dumitrescu, Kun Huang, Bhaskar VS. Kallakury, Shiva Krishnan, Adana A. Llanos, Catalin Marian, Joseph McElroy, Sallie S. Schneider, Scott L. Spear, Melissa A. Troester, Jo L. Freudenheim, Susan Geyer and Peter G. Shields _

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Oncotarget. 2016; 7:86457-86468. https://doi.org/10.18632/oncotarget.13241

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Cenny Taslim1, Daniel Y. Weng1, Theodore M. Brasky1, Ramona G. Dumitrescu2, Kun Huang1, Bhaskar V.S. Kallakury3, Shiva Krishnan1, Adana A. Llanos4, Catalin Marian1,11, Joseph McElroy5, Sallie S. Schneider6, Scott L. Spear7, Melissa A. Troester8, Jo L. Freudenheim9, Susan Geyer10, Peter G. Shields1

1Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA

2Distilled Spirits Council of the United States, Washington, DC, USA

3Department of Pathology, Georgetown University, Washington, DC, USA

4Department of Epidemiology, Rutgers University, New Brunswick, NJ, USA

5Center for Biostatistics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA

6Pioneer Valley Life Sciences Institute, Springfield, MA, USA

7Department of Plastic Surgery, Georgetown University Hospital, Washington, DC, USA

8Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

9Departement of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA

10Health Informatics Institute, University of South Florida, Tampa, FL, USA

11Victor Babes University of Medicine and Pharmacy, Timisoara, Romania

Correspondence to:

Peter G. Shields, email: [email protected]

Keywords: microRNA, epigenetics, breast cancer risk prediction, tissue-based biomarkers, healthy women

Received: September 07, 2016     Accepted: October 22, 2016     Published: November 09, 2016


Background: Genome-wide miRNA expression may be useful for predicting breast cancer risk and/or for the early detection of breast cancer.

Results: A 41-miRNA model distinguished breast cancer risk in the discovery study (accuracy of 83.3%), which was replicated in the independent study (accuracy = 63.4%, P=0.09). Among the 41 miRNA, 20 miRNAs were detectable in serum, and predicted breast cancer occurrence within 18 months of blood draw (accuracy 53%, P=0.06). These risk-related miRNAs were enriched for HER-2 and estrogen-dependent breast cancer signaling.

Materials and Methods: MiRNAs were assessed in two cross-sectional studies of women without breast cancer and a nested case-control study of breast cancer. Using breast tissues, a multivariate analysis was used to model women with high and low breast cancer risk (based upon Gail risk model) in a discovery study of women without breast cancer (n=90), and applied to an independent replication study (n=71). The model was then assessed using serum samples from the nested case-control study (n=410).

Conclusions: Studying breast tissues of women without breast cancer revealed miRNAs correlated with breast cancer risk, which were then found to be altered in the serum of women who later developed breast cancer. These results serve as proof-of-principle that miRNAs in women without breast cancer may be useful for predicting breast cancer risk and/or as an adjunct for breast cancer early detection. The miRNAs identified herein may be involved in breast carcinogenic pathways because they were first identified in the breast tissues of healthy women.

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