Lack of predictive tools for conventional and targeted cancer therapy: Barriers to biomarker development and clinical translation
Nikolaos Batis, Jill Brooks, Karl Payne, Neil Sharma, Paul Nankivell, Hisham Mehanna
Abstract
Predictive tools, utilising biomarkers, aim to objectively assessthe potentialresponse toa particular clinical intervention in order to direct treatment.Conventional cancer therapy remains poorly served by predictive biomarkers, despite being the mainstay of treatment for most patients. In contrast, targeted therapy benefits from a clearly defined protein target for potential biomarker assessment. We discuss potential data sources of predictive biomarkers for conventional and targeted therapy, including patient clinical data andmulti-omicbiomarkers (genomic, transcriptomic and protein expression).Key examples, either clinically adopted or demonstrating promise for clinical translation, are highlighted. Following this, we provide an outline of potential barriers to predictive biomarker development; broadly discussing themes of approaches to translational research and study/trial design, and the impact of cellular and molecular tumor heterogeneity. Future avenues of research are also highlighted.