Genomic analyses to select patients for adjuvant chemotherapy: trials and tribulations
B Weigelt1, J S Reis-Filho, C Swanton
1Cancer Research UK London Research Institute, London, UK.
Abstract:
Despite improvements in adjuvant chemotherapy regimens in breast cancer, personalised use of specific cytotoxic regimens remains a clinical challenge. Defining the correct therapeutic strategy for individual patients with breast cancer based on the genomic and transcriptomic characteristics of the tumour and the patient remains an area of unmet clinical need. Despite the promise of microarray-based predictors of response to chemotherapy, clinical decisions are still guided by a limited constellation of biomarkers. In this review we will address current genomic and transcriptomic approaches to the stratification of adjuvant therapies in breast cancer, the reasons for the limited success in the incorporation of novel multi-gene predictors of response to chemotherapy in clinical practice and focus on new approaches that aim to understand the clonal evolution of the disease. The polygenic nature of drug resistance, and inter- and intra-tumour heterogeneity are considered as important research areas, given that they may constitute important challenges for the development of chemotherapy-specific response predictors.
Insights
Personalized breast cancer chemotherapy faces challenges. Genomic and transcriptomic approaches are explored to improve treatment selection, addressing tumor heterogeneity and drug resistance for better patient outcomes.
Area of Science:
- Oncology and Genomics
- Translational Cancer Research
Background:
- Adjuvant chemotherapy for breast cancer has improved, but personalized cytotoxic regimen selection remains a clinical challenge.
- Current clinical decisions rely on limited biomarkers, despite the potential of genomic and transcriptomic predictors for chemotherapy response.
- There is an unmet clinical need for defining optimal therapeutic strategies based on individual tumor and patient genomic/transcriptomic profiles.
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