Evaluation of the methods to identify patients who may benefit from PARP inhibitor use

    1. Joanne Ngeow2,3
    1. 1Department of Pathology, National University Health System, Singapore, Singapore
    2. 2Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
    3. 3Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre, Singapore, Singapore
    1. Correspondence should be addressed to J Ngeow; Email: Joanne.Ngeow.Yuen.Yie{at}singhealth.com.sg

    Abstract

    The effectiveness of poly (ADP-ribose) polymerase inhibitors (PARPi) in treating cancers associated with BRCA1/2 mutations hinges upon the concept of synthetic lethality and exemplifies the principles of precision medicine. Currently, most clinical trials are recruiting patients based on pathological subtypes or have included BRCA mutation analysis (germ line and/or somatic) as part of the selection criteria. Mounting evidence, however, suggests that these drugs may also be efficacious in tumors with defects in other genes involved in the homologous recombination repair pathway. Advances in molecular profiling techniques together with increased research efforts have led to a better understanding of the molecular aberrations underlying this BRCA-like phenotype and helped broaden the concept of BRCAness. Hence, it is likely that the list of predictive biomarkers for PARPi therapy will increase in future. There is currently no gold standard method of testing for PARPi response and no universal guidelines are in place on how to incorporate biomarker testing into routine clinical diagnostics. In this review, we explore the concept of BRCAness and highlight the different methods that have been used to identify patients who may benefit from the use of these anticancer agents. The identification of predictive biomarkers is crucial in improving patient selection and expanding the clinical applications of PARPi therapy.

    Keywords
    • Received 22 May 2016
    • Accepted 23 May 2016
    • Made available online as an Accepted Preprint 1 June 2016
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