Dalicia N. Reales

TL;DR: A large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer are compiled and identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types.

TL;DR: The data reported here suggest that broader, early testing for molecular alterations that have not yet been recognized as standard-of-care predictive biomarkers of drug response could accelerate the development of targeted agents for rare mutational events and could result in improved clinical outcomes.

TL;DR: The authors' systematic computational, experimental, and clinical analysis of hotspot mutations in approximately 25,000 human cancers demonstrates that the long right tail of biologically and therapeutically significant mutant alleles is still incompletely characterized.

TL;DR: The results suggest that the application of artificial intelligence to predict tissue of origin in oncologic practice can act as a useful complement to conventional histologic review to provide integrated pathologic diagnoses, often with important therapeutic implications.

TL;DR: PURPOSECancer classification is foundational for patient care and oncology research as discussed by the authors, and it is used in the International Classification of Diseases for Oncology (ICD-O), Systematized Nomenclature of Medi...