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      Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity

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          Mutational hotspots indicate selective pressure across a population of tumor samples, but their prevalence within and across cancer types is incompletely characterized. An approach to detect significantly mutated residues, rather than methods that identify recurrently mutated genes, may uncover new biologically and therapeutically relevant driver mutations. Here we developed a statistical algorithm to identify recurrently mutated residues in tumour samples. We applied the algorithm to 11,119 human tumors, spanning 41 cancer types, and identified 470 hotspot somatic substitutions in 275 genes. We find that half of all human tumors possess one or more mutational hotspots with widespread lineage-, position-, and mutant allele-specific differences, many of which are likely functional. In total, 243 hotspots were novel and appeared to affect a broad spectrum of molecular function, including hotspots at paralogous residues of Ras-related small GTPases RAC1 and RRAS2. Redefining hotspots at mutant amino acid resolution will help elucidate the allele-specific differences in their function and could have important therapeutic implications.

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          Most cited references 24

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          Genome sequencing identifies a basis for everolimus sensitivity.

          Cancer drugs often induce dramatic responses in a small minority of patients. We used whole-genome sequencing to investigate the genetic basis of a durable remission of metastatic bladder cancer in a patient treated with everolimus, a drug that inhibits the mTOR (mammalian target of rapamycin) signaling pathway. Among the somatic mutations was a loss-of-function mutation in TSC1 (tuberous sclerosis complex 1), a regulator of mTOR pathway activation. Targeted sequencing revealed TSC1 mutations in about 8% of 109 additional bladder cancers examined, and TSC1 mutation correlated with everolimus sensitivity. These results demonstrate the feasibility of using whole-genome sequencing in the clinical setting to identify previously occult biomarkers of drug sensitivity that can aid in the identification of patients most likely to respond to targeted anticancer drugs.
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            Oncogenic ERBB3 mutations in human cancers.

            The human epidermal growth factor receptor (HER) family of tyrosine kinases is deregulated in multiple cancers either through amplification, overexpression, or mutation. ERBB3/HER3, the only member with an impaired kinase domain, although amplified or overexpressed in some cancers, has not been reported to carry oncogenic mutations. Here, we report the identification of ERBB3 somatic mutations in ~11% of colon and gastric cancers. We found that the ERBB3 mutants transformed colonic and breast epithelial cells in a ligand-independent manner. However, the mutant ERBB3 oncogenic activity was dependent on kinase-active ERBB2. Furthermore, we found that anti-ERBB antibodies and small molecule inhibitors effectively blocked mutant ERBB3-mediated oncogenic signaling and disease progression in vivo. Copyright © 2013 Elsevier Inc. All rights reserved.
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              Effect of KRAS oncogene substitutions on protein behavior: implications for signaling and clinical outcome.

              Mutations in the v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) play a critical role in cancer cell growth and resistance to therapy. Most mutations occur at codons 12 and 13. In colorectal cancer, the presence of any mutant KRas amino acid substitution is a negative predictor of patient response to targeted therapy. However, in non-small cell lung cancer (NSCLC), the evidence that KRAS mutation is a predictive factor is conflicting. We used data from a molecularly targeted clinical trial for 215 patients with tissues available out of 268 evaluable patients with refractory NSCLC to examine associations between specific mutant KRas proteins and progression-free survival and tumor gene expression. Transcriptome microarray studies of patient tumor samples and reverse-phase protein array studies of a panel of 67 NSCLC cell lines with known substitutions in KRas and in immortalized human bronchial epithelial cells stably expressing different mutant KRas proteins were used to investigate signaling pathway activation. Molecular modeling was used to study the conformations of wild-type and mutant KRas proteins. Kaplan-Meier curves and Cox regression were used to analyze survival data. All statistical tests were two-sided. Patients whose tumors had either mutant KRas-Gly12Cys or mutant KRas-Gly12Val had worse progression-free survival compared with patients whose tumors had other mutant KRas proteins or wild-type KRas (P = .046, median survival = 1.84 months) compared with all other mutant KRas (median survival = 3.35 months) or wild-type KRas (median survival = 1.95 months). NSCLC cell lines with mutant KRas-Gly12Asp had activated phosphatidylinositol 3-kinase (PI-3-K) and mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK) signaling, whereas those with mutant KRas-Gly12Cys or mutant KRas-Gly12Val had activated Ral signaling and decreased growth factor-dependent Akt activation. Molecular modeling studies showed that different conformations imposed by mutant KRas may lead to altered association with downstream signaling transducers. Not all mutant KRas proteins affect patient survival or downstream signaling in a similar way. The heterogeneous behavior of mutant KRas proteins implies that therapeutic interventions may need to take into account the specific mutant KRas expressed by the tumor.

                Author and article information

                Nat Biotechnol
                Nat. Biotechnol.
                Nature biotechnology
                17 October 2015
                30 November 2015
                February 2016
                30 May 2016
                : 34
                : 2
                : 155-163
                [1 ]Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
                [2 ]Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
                [3 ]Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA
                [4 ]Department of Medicine, University of California, San Francisco, CA
                [5 ]Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
                [6 ]Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, CA
                [7 ]Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
                [8 ]Bioinformatics Core, Memorial Sloan Kettering Cancer Center, New York, NY
                [9 ]Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
                [10 ]Weill Cornel Medical College, Cornell University, New York, NY
                [11 ]Epidemiology and Biostatistics, University of California, San Francisco, CA
                [12 ]Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA
                Author notes
                To whom correspondence should be addressed: taylorb@

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