Data resources for the identification and interpretation of actionable mutations by clinicians
A. Prawira, T. J. Pugh, T. L. Stockley, L. L. Siu; Data resources for the identification and interpretation of actionable mutations by clinicians. Ann Oncol 2017; 28 (5): 946-957.
This review will describe data resources pertinent to the identification and interpretation of actionable genomic aberrations by clinicians, and highlight relevant issues in the clinical application of tumor molecular profiling results
Folowing initial characterization of the reference human genome, initiatives have evolved worldwide to identify genomic aberrations in cancer with the aim of deriving diagnostic, prognostic and predictive information. However, the functional and clinical relevance of many somatic variants in cancer are presently unknown and there is no consensus definition of ‘actionability’ for genomic aberrancies. Therefore, while robust detection of a variety of genetic aberrations in clinical specimens remains a technical hurdle, the greater challenge lies in the interpretation of these alterations. Critical evaluation of genomic variation in cancer requires the integration of available clinical and preclinical evidence related to their frequencies, functions and roles as therapeutic targets. Many publicly accessible data resources have compiled such evidence to facilitate the understanding of genomic results and ultimately translating results to clinical action. Information for these data resources is derived from various sources including large population genomic datasets, curation of published literature, and data sharing by the scientific community. Currently, there is no widely accepted guidance to definitively assess and integrate the diagnostic, prognostic and predictive information of somatic variants using these knowledge databases.
© 2017 Oxford University Press
doi: 10.1093/annonc/mdx023
