Candidate biomarkers predictive of anthracycline and taxane efficacy against breast cancer
- 1 January 2018
- journal article
- research article
- Published by Medknow in Journal of Cancer Research and Therapeutics
- Vol. 14 (2), 409-415
- https://doi.org/10.4103/jcrt.jcrt_1053_16
Abstract
Background: Since breast cancer shows diversity in clinical behaviors, a standard therapy does not always lead to favorable outcomes. Materials and Methods: The expression statuses of candidate markers, including topoisomerase-II alpha (TOP2A), beta-tubulin (B-tub), and tissue inhibitor of metalloprotease-1 (TIMP-1), were immunohistochemically evaluated in 70 breast cancer tissues from 68 patients with advanced breast cancers receiving chemotherapy. Results: The response rates to anthracycline and taxane were 70.5% and 67.2%, respectively. Overall, 25.1% +/- 29.7%, 8.32% +/- 10.1%, and 16.37% +/- 17.5% of cancer cells in the tumors studied were positive for B-tub, TOP2A, and TIMP-1 expressions, respectively. However, positive molecule expression did not differ between patients who did and did not exhibit clinical responses to treatment. The proportion of TOP2A-positive cancer cells was significantly higher among anthracycline responders than among nonresponders in HR-negative cancer (15.4% +/- 17.5% vs. 2.0% +/- 2.4%, respectively, P = 0.048), whereas TOP2A and TIMP-1 expression statuses did not differ in HR-positive cancer. When patients were stratified according to B-tub, TOP2A, or TIMP-1 expression statuses (B-tub >= 10% vs. = 5% vs. 20%, respectively), the proportion of patients with = 10% B-tub-positive cancer cells was significantly higher in taxane responders than in nonresponders (72.4% vs. 37.5%, respectively, P = 0.016). Anthracycline responders showed a trend to have a higher proportion of patients with either = 5% TOP2A-positive cancer cells or <= 20% TIMP-1-positive cancer cells compared to nonresponders (86.7% vs. 61.5%, respectively, P = 0.066). Conclusion: Immunohistochemical TOP2A, TIMP-1, and B-tub expression analyses are expected to be useful for predicting tumor responses to chemotherapy.Keywords
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