NanoString-based breast cancer risk prediction for women with sclerosing adenosis

Stacey J. Winham, Christine Mehner, Ethan P. Heinzen, Brendan T. Broderick, Melody Stallings-Mann, Aziza Nassar, Robert A. Vierkant, Tanya L. Hoskin, Ryan D. Frank, Chen Wang, Lori A. Denison, Celine M. Vachon, Marlene H. Frost, Lynn C. Hartmann, E. Aubrey Thompson, Mark E. Sherman, Daniel W. Visscher, Amy C. Degnim, Derek C. Radisky

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Purpose: Sclerosing adenosis (SA), found in ¼ of benign breast disease (BBD) biopsies, is a histological feature characterized by lobulocentric proliferation of acini and stromal fibrosis and confers a two-fold increase in breast cancer risk compared to women in the general population. We evaluated a NanoString-based gene expression assay to model breast cancer risk using RNA derived from formalin-fixed, paraffin-embedded (FFPE) biopsies with SA. Methods: The study group consisted of 151 women diagnosed with SA between 1967 and 2001 within the Mayo BBD cohort, of which 37 subsequently developed cancer within 10 years (cases) and 114 did not (controls). RNA was isolated from benign breast biopsies, and NanoString-based methods were used to assess expression levels of 61 genes, including 35 identified by previous array-based profiling experiments and 26 from biological insight. Diagonal linear discriminant analysis of these data was used to predict cancer within 10 years. Predictive performance was assessed with receiver operating characteristic area under the curve (ROC-AUC) values estimated from 5-fold cross-validation. Results: Gene expression prediction models achieved cross-validated ROC-AUC estimates ranging from 0.66 to 0.70. Performing univariate associations within each of the five folds consistently identified genes DLK2, EXOC6, KIT, RGS12, and SORBS2 as significant; a model with only these five genes showed cross-validated ROC-AUC of 0.75, which compared favorably to risk prediction using established clinical models (Gail/BCRAT: 0.57; BBD-BC: 0.67). Conclusions: Our results demonstrate that biomarkers of breast cancer risk can be detected in benign breast tissue years prior to cancer development in women with SA. These markers can be assessed using assay methods optimized for RNA derived from FFPE biopsy tissues which are commonly available.

Original languageEnglish (US)
Pages (from-to)641-650
Number of pages10
JournalBreast Cancer Research and Treatment
Volume166
Issue number2
DOIs
StatePublished - Nov 1 2017

Keywords

  • Benign breast disease
  • Breast cancer
  • Formalin-fixed paraffin-embedded
  • NanoString
  • Risk prediction
  • Sclerosing adenosis

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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  • Cite this

    Winham, S. J., Mehner, C., Heinzen, E. P., Broderick, B. T., Stallings-Mann, M., Nassar, A., Vierkant, R. A., Hoskin, T. L., Frank, R. D., Wang, C., Denison, L. A., Vachon, C. M., Frost, M. H., Hartmann, L. C., Aubrey Thompson, E., Sherman, M. E., Visscher, D. W., Degnim, A. C., & Radisky, D. C. (2017). NanoString-based breast cancer risk prediction for women with sclerosing adenosis. Breast Cancer Research and Treatment, 166(2), 641-650. https://doi.org/10.1007/s10549-017-4441-z