Challenges translating breast cancer gene signatures into the clinic

TLDR: The hurdles in the development and validation of molecular classification systems, and prognostic and predictive signatures based on microarray gene-expression profiling are discussed and it is suggested that similar challenges are likely to be encountered in translating next-generation sequencing data into clinically useful information.

Abstract: The advent of microarray-based gene-expression profiling a decade ago raised high expectations for rapid advances in breast cancer classification, prognostication and prediction. Despite the development of molecular classifications, and prognostic and predictive gene-expression signatures, microarray-based studies have not yielded definitive answers to many of the questions that remain germane for the successful implementation of personalized medicine. There are a lack of robust signatures to predict benefit from specific therapeutic agents and it is still not possible to predict prognosis or chemotherapy treatment response in specific disease subsets accurately, such as triple-negative breast cancer. We discuss the hurdles in the development and validation of molecular classification systems, and prognostic and predictive signatures based on microarray gene-expression profiling. We suggest that similar challenges are likely to be encountered in translating next-generation sequencing data into clinically useful information. Finally we highlight strategies for the development of clinically useful molecular predictors in the future.