Insights into Molecular Classifications of Triple-Negative Breast Cancer: Improving Patient Selection for Treatment
Harvard University · Dana-Farber Cancer Institute
Abstract
Triple-negative breast cancer (TNBC) remains the most challenging breast cancer subtype to treat. To date, therapies directed to specific molecular targets have rarely achieved clinically meaningful improvements in outcomes of patients with TNBC, and chemotherapy remains the standard of care. Here, we seek to review the most recent efforts to classify TNBC based on the comprehensive profiling of tumors for cellular composition and molecular features. Technologic advances allow for tumor characterization at ever-increasing depth, generating data that, if integrated with clinical-pathologic features, may help improve risk stratification of patients, guide treatment decisions and surveillance, and help identify…
Citation impact
- FWCI
- 46.13
- Percentile
- 100%
- References
- 162
Authors
3Topics & keywords
- Breast cancer
- Selection (genetic algorithm)
- Triple-negative breast cancer
- Cancer
- Computational biology
- Triple negative
- Medicine
- Bioinformatics
- Good health and well-being