Database of genomic biomarkers for cancer drugs and clinical targetability in solid tumors

Abstract

Comprehensive genomic profiling is expected to revolutionize cancer therapy. In this Prospective, we present the prevalence of mutations and copy-number alterations with predictive associations across solid tumors at different levels of stringency for gene-drug targetability. More than 90% of The Cancer Genome Atlas samples have potentially targetable alterations, the majority with multiple events, illustrating the challenges for treatment prioritization given the complexity of the genomic landscape. Nearly 80% of the variants in rarely mutated oncogenes are of uncertain functional significance, reflecting the gap in our understanding of the relevance of many alterations potentially linked to therapeutic actions. Access to targeted agents in early clinical trials could affect treatment decision in 75% of patients with cancer. Prospective implementation of large-scale molecular profiling and standardized reports of predictive biomarkers are fundamental steps for making precision cancer medicine a reality.

Figure 1

Workflow of analytic pipeline integrating Gene-Drug Knowledge Database (GDKD) and Clinical Targetability Index (CTI) to pan-cancer TCGA data. Statistics of GDKD: distribution of gene variant – drug associations across solid tumor types, most frequent genes and drugs with predictive associations. ampl: amplifications; del: deletions.

Figure 2

a. Prevalence of targetable events according to different Clinical Targetability Indices – CTI.1 to CTI.5 – across solid tumors in TCGA. b. Mean number of alterations per sample, starting from mutations or copy number events in Cancer Gene Census (CGC) genes and then looking at potentially targetable events according to different targetability scenarios – CTI.1 to CTI.5. Tumors in the right side do not have a gene alteration linked to FDA-approved drug (i.e. no CTI.5). c. Prevalence of gene variants associated with dramatic responses to targeted therapies (case reports) across solid tumors. For oncogenes, the proportion of variants that have been functionally validated and that remain of uncertain significance is depicted. V.U.S: variants of unknown significance.