Prioritising Targets for Precision Cancer Medicine
Cet article présente une méthodologie pour identifier, à partir d'une analyse du génome tumoral d'un patient, les cibles moléculaires les plus susceptibles de faire l'objet d'une thérapie ciblée
The implementation of cancer genomic testing into the clinical setting has brought major opportunities. However, as our understanding of cancer initiation, maintenance and progression improves through detailed cancer genomic studies, the challenges associated with driver identification and target classification in the clinical setting become clearer. Here we review recent insights into cancer genomic testing in the clinical setting, and suggest a target classification approach that considers the levels of evidence supporting the prioritisation of tumour drivers for therapeutic targeting in light of complex cancer clonal and subclonal structures and clinical successes and failures in the field. We argue that such classification approaches, together with transparent reporting of both positive and negative clinical data and continued research to identify the subclonal dynamics of driver events during the disease course, will facilitate inter-trial comparisons, optimise patient informed consent and provide a critically balanced evaluation of genomic testing in clinical practice.
Annals of Oncology , article en libre accès, 2014