Abstract
Tumor suppressors play a major role in the etiology of human cancer, and typically achieve a tumor-promoting effect upon complete functional inactivation. Bi-allelic inactivation of tumor suppressors may occur through genetic mechanisms (such as loss of function mutation, copy number (CN) loss, or loss of heterozygosity (LOH)), epigenetic mechanisms (such as promoter methylation or histone modification), or a combination of the two. We report systematically derived status of 69 known or putative tumor suppressors, across 799 samples of the Cancer Cell Line Encyclopedia. In order to generate such resource we constructed a novel comprehensive computational framework for the assessment of tumor suppressor functional "status". This approach utilizes several orthogonal genomic data types, including mutation data, copy number, LOH and expression. Through correlation with additional data types (compound sensitivity and gene set activity) we show that this integrative method provides a more accurate assessment of tumor suppressor status than can be inferred by expression, copy number, or mutation alone. This approach has the potential for a more realistic assessment of tumor suppressor genes for both basic and translational oncology research. (C) 2013 Federation. of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.