Amplification patterns of three genomic regions predict distant recurrence in breast carcinoma

39Citations
Citations of this article
21Readers
Mendeley users who have this article in their library.

Your institution provides access to this article.

Abstract

Currently used clinical and histopathological parameters imprecisely define the risk of distant recurrence in breast cancer, underscoring the need for more informative prognostic markers. In the present fluorescence in situ hybridization study of archived surgical specimens, we derived an algorithm for computing a prognostic index (PI) from DNA copy numbers of three genomic regions (CYP24, PDCD6IP, and BIRC5) for estrogen/progesterone receptor-positive (ER/PR+) cancers and a distinct PI (based on NR1D1, SMARCE1, and BIRC5) for estrogen/ progesterone receptor-negative (ER/PR-) cancers. Among independent test cases stratified by PI, recurrence rates were significantly higher among high-risk patients than low-risk patients for both ER/PR+ (odds ratio = 9.52, 95% confidence interval >2.12, P = 0.0024) and ER/PR- (odds ratio = 12.3, 95% confidence interval >1.45, P = 0.0188) cancers. Among the entire population, recurrences were significantly more prevalent for cases with PI above the medians for both ER/PR+ (Fisher's exact, P = 1.19 × 1-5) and ER/PR- (P = 0.0025) patients and for the node-negative subsets (ER/PR+ node-negative, P = 0.042 and ER/PR- node-negative, P = 0.039). In conclusion, these markers perform well in comparison with other criteria for recurrence risk assessment and can be used with routinely formalin-fixed, paraffin-embedded surgical specimens. Copyright © American Society for Investigative Pathology and the Association for Molecular Pathology.

Cite

CITATION STYLE

APA

Davis, L. M., Harris, C., Tang, L., Doherty, P., Hraber, P., Sakai, Y., … Hozier, J. (2007). Amplification patterns of three genomic regions predict distant recurrence in breast carcinoma. Journal of Molecular Diagnostics, 9(3), 327–336. https://doi.org/10.2353/jmoldx.2007.060079

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free