Accelerating discovery of functional mutant alleles in cancer Journal Article


Authors: Chang, M. T.; Shrestha Bhattarai, T.; Schram, A. M.; Bielski, C. M.; Donoghue, M. T. A.; Jonsson, P.; Chakravarty, D.; Phillips, S.; Kandoth, C.; Penson, A.; Gorelick, A.; Shamu, T.; Patel, S.; Harris, C.; Gao, J.; Sumer, S. O.; Kundra, R.; Razavi, P.; Li, B. T.; Reales, D. N.; Socci, N. D.; Jayakumaran, G.; Zehir, A.; Benayed, R.; Arcila, M. E.; Chandarlapaty, S.; Ladanyi, M.; Schultz, N.; Baselga, J.; Berger, M. F.; Rosen, N.; Solit, D. B.; Hyman, D. M.; Taylor, B. S.
Article Title: Accelerating discovery of functional mutant alleles in cancer
Abstract: 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 AKT1 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. Significance: 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 signifi cant mutant alleles is still incompletely characterized. Sharing prospective genomic data will accelerate hotspot identifi cation, thereby expanding the reach of precision oncology in patients with cancer. © 2017 American Association for Cancer Research.
Keywords: gene mutation; frameshift mutation; genetic analysis; breast cancer; epidermal growth factor receptor 2; mutational analysis; retrospective study; risk factor; oncogene; western blotting; computer model; tumor gene; gallbladder cancer; b raf kinase; neratinib; polyacrylamide gel electrophoresis; genetic identification; molecularly targeted therapy; triple negative breast cancer; human; article; malignant neoplasm
Journal Title: Cancer Discovery
Volume: 8
Issue: 2
ISSN: 2159-8274
Publisher: American Association for Cancer Research  
Date Published: 2018-02-01
Start Page: 174
End Page: 183
Language: English
DOI: 10.1158/2159-8290.cd-17-0321
PROVIDER: scopus
PMCID: PMC5809279
PUBMED: 29247016
DOI/URL:
Notes: Article -- Export Date: 1 March 2018 -- Source: Scopus
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