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  • Accelerating Discovery of F...
    Chang, Matthew T; Bhattarai, Tripti Shrestha; Schram, Alison M; Bielski, Craig M; Donoghue, Mark T A; Jonsson, Philip; Chakravarty, Debyani; Phillips, Sarah; Kandoth, Cyriac; Penson, Alexander; Gorelick, Alexander; Shamu, Tambudzai; Patel, Swati; Harris, Christopher; Gao, JianJiong; Sumer, Selcuk Onur; Kundra, Ritika; Razavi, Pedram; Li, Bob T; Reales, Dalicia N; Socci, Nicholas D; Jayakumaran, Gowtham; Zehir, Ahmet; Benayed, Ryma; Arcila, Maria E; Chandarlapaty, Sarat; Ladanyi, Marc; Schultz, Nikolaus; Baselga, José; Berger, Michael F; Rosen, Neal; Solit, David B; Hyman, David M; Taylor, Barry S

    Cancer discovery, 02/2018, Letnik: 8, Številka: 2
    Journal Article

    Most mutations in cancer are rare, which complicates the identification of therapeutically significant mutations and thus limits the clinical impact of genomic profiling in patients with cancer. Here, we analyzed 24,592 cancers including 10,336 prospectively sequenced patients with advanced disease to identify mutant residues arising more frequently than expected in the absence of selection. We identified 1,165 statistically significant hotspot mutations of which 80% arose in 1 in 1,000 or fewer patients. Of 55 recurrent in-frame indels, we validated that novel duplications induced pathway hyperactivation and conferred AKT inhibitor sensitivity. Cancer genes exhibit different rates of hotspot discovery with increasing sample size, with few approaching saturation. Consequently, 26% of all hotspots in therapeutically actionable oncogenes were novel. Upon matching a subset of affected patients directly to molecularly targeted therapy, we observed radiographic and clinical responses. Population-scale mutant allele discovery illustrates how the identification of driver mutations in cancer is far from complete. Our 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. Sharing prospective genomic data will accelerate hotspot identification, thereby expanding the reach of precision oncology in patients with cancer. .