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Journal ArticleDOI

Discovery and saturation analysis of cancer genes across 21 tumour types

TL;DR: It is found that large-scale genomic analysis can identify nearly all known cancer genes in these cancer types and 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis.
Abstract: Although a few cancer genes are mutated in a high proportion of tumours of a given type (.20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600– 5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics. Comprehensive knowledge of the genes underlying human cancers is a critical foundation for cancer diagnostics, therapeutics, clinical-trial design and selection of rational combination therapies. It is now possible to use genomic analysis to identify cancer genes in an unbiased fashion, based on the presence of somatic mutations at a rate significantly higher than the expected background level. Systematic studies have revealed many new cancer genes, as well as new classes of cancer genes 1,2 . They have also made clear that, although some cancer genes are mutated at high frequencies, most cancer genes in most patients occur at intermediate frequencies (2–20%) or lower. Accordingly, a complete catalogue of mutations in this frequency class will be essential for recognizing dysregulated pathways and optimal targets for therapeutic intervention. However, recent work suggests major gaps in our knowledge of cancer genes of intermediate frequency. For example, a study of 183 lung adenocarcinomas 3 found that 15% of patients lacked even a single mutation affecting any of the 10 known hallmarks of cancer, and 38% had 3 or fewer such mutations. In this paper, we analysed somatic point mutations (substitutions and small insertion and deletions) in nearly 5,000 human cancers and their matched normal-tissue samples (‘tumour–normal pairs’) across 21 tumour types. The questions that we examine here are: first, whether large-scale genomic analysis across tumour types can reliably identify all known cancer genes; second, whether it will reveal many new candidate cancer genes; and third, how far we are from having a complete catalogue of cancer genes (at least those of intermediate frequency). We used rigorous statistical methods to enumerate candidate cancer genes and then carefully inspected each gene to identify those with strong biological connections to cancer and mutational patterns consistent with the expected function. The analysis reveals nearly all known cancer genes and revealed 33 novel candidates, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Importantly, the data show that the

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Citations
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Journal ArticleDOI
01 Jan 2014-Nature
TL;DR: In this paper, the authors report molecular profiling of 230 resected lung adnocarcinomas using messenger RNA, microRNA and DNA sequencing integrated with copy number, methylation and proteomic analyses.
Abstract: Adenocarcinoma of the lung is the leading cause of cancer death worldwide. Here we report molecular profiling of 230 resected lung adenocarcinomas using messenger RNA, microRNA and DNA sequencing integrated with copy number, methylation and proteomic analyses. High rates of somatic mutation were seen (mean 8.9 mutations per megabase). Eighteen genes were statistically significantly mutated, including RIT1 activating mutations and newly described loss-of-function MGA mutations which are mutually exclusive with focal MYC amplification. EGFR mutations were more frequent in female patients, whereas mutations in RBM10 were more common in males. Aberrations in NF1, MET, ERBB2 and RIT1 occurred in 13% of cases and were enriched in samples otherwise lacking an activated oncogene, suggesting a driver role for these events in certain tumours. DNA and mRNA sequence from the same tumour highlighted splicing alterations driven by somatic genomic changes, including exon 14 skipping in MET mRNA in 4% of cases. MAPK and PI(3)K pathway activity, when measured at the protein level, was explained by known mutations in only a fraction of cases, suggesting additional, unexplained mechanisms of pathway activation. These data establish a foundation for classification and further investigations of lung adenocarcinoma molecular pathogenesis.

4,104 citations

Journal ArticleDOI
TL;DR: Age-related clonal hematopoiesis is a common condition that is associated with increases in the risk of hematologic cancer and in all-cause mortality, with the latter possibly due to an increased risk of cardiovascular disease.
Abstract: Background The incidence of hematologic cancers increases with age. These cancers are associated with recurrent somatic mutations in specific genes. We hypothesized that such mutations would be detectable in the blood of some persons who are not known to have hematologic disorders. Methods We analyzed whole-exome sequencing data from DNA in the peripheral-blood cells of 17,182 persons who were unselected for hematologic phenotypes. We looked for somatic mutations by identifying previously characterized single-nucleotide variants and small insertions or deletions in 160 genes that are recurrently mutated in hematologic cancers. The presence of mutations was analyzed for an association with hematologic phenotypes, survival, and cardiovascular events. Results Detectable somatic mutations were rare in persons younger than 40 years of age but rose appreciably in frequency with age. Among persons 70 to 79 years of age, 80 to 89 years of age, and 90 to 108 years of age, these clonal mutations were observed in 9.5% (219 of 2300 persons), 11.7% (37 of 317), and 18.4% (19 of 103), respectively. The majority of the variants occurred in three genes: DNMT3A, TET2, and ASXL1. The presence of a somatic mutation was associated with an increase in the risk of hematologic cancer (hazard ratio, 11.1; 95% confidence interval [CI], 3.9 to 32.6), an increase in all-cause mortality (hazard ratio, 1.4; 95% CI, 1.1 to 1.8), and increases in the risks of incident coronary heart disease (hazard ratio, 2.0; 95% CI, 1.2 to 3.4) and ischemic stroke (hazard ratio, 2.6; 95% CI, 1.4 to 4.8). Conclusions Age-related clonal hematopoiesis is a common condition that is associated with increases in the risk of hematologic cancer and in all-cause mortality, with the latter possibly due to an increased risk of cardiovascular disease. (Funded by the National Institutes of Health and others.)

3,183 citations

Journal ArticleDOI
TL;DR: Recently devised sgRNA design rules are used to create human and mouse genome-wide libraries, perform positive and negative selection screens and observe that the use of these rules produced improved results, and a metric to predict off-target sites is developed.
Abstract: CRISPR-Cas9-based genetic screens are a powerful new tool in biology. By simply altering the sequence of the single-guide RNA (sgRNA), one can reprogram Cas9 to target different sites in the genome with relative ease, but the on-target activity and off-target effects of individual sgRNAs can vary widely. Here, we use recently devised sgRNA design rules to create human and mouse genome-wide libraries, perform positive and negative selection screens and observe that the use of these rules produced improved results. Additionally, we profile the off-target activity of thousands of sgRNAs and develop a metric to predict off-target sites. We incorporate these findings from large-scale, empirical data to improve our computational design rules and create optimized sgRNA libraries that maximize on-target activity and minimize off-target effects to enable more effective and efficient genetic screens and genome engineering.

2,866 citations

01 Jul 2014
TL;DR: High rates of somatic mutation were seen, including RIT1 activating mutations and newly described loss-of-function MGA mutations which are mutually exclusive with focal MYC amplification, and MAPK and PI(3)K pathway activity was explained by known mutations in only a fraction of cases, suggesting additional, unexplained mechanisms of pathway activation.
Abstract: Adenocarcinoma of the lung is the leading cause of cancer death worldwide. Here we report molecular profiling of 230 resected lung adenocarcinomas using messenger RNA, microRNA and DNA sequencing integrated with copy number, methylation and proteomic analyses. High rates of somatic mutation were seen(mean 8.9 mutations per megabase). Eighteen genes were statistically significantly mutated, including RIT1 activating mutations and newly described loss-of-function MGA mutations which are mutually exclusive with focal MYC amplification. EGFR mutations were more frequent in female patients, whereas mutations in RBM10 were more common in males. Aberrations in NF1, MET, ERBB2 and RIT1 occurred in 13% of cases and were enriched in samples otherwise lacking an activated oncogene, suggesting a driver role for these events in certain tumours. DNA and mRNA sequence from the same tumour highlighted splicing alterations driven by somatic genomic changes, including exon 14 skipping in MET mRNA in 4% of cases. MAPK and PI(3)K pathway activity, when measured at the protein level, was explained by known mutations in only a fraction of cases, suggesting additional, unexplained mechanisms of pathway activation. These data establish a foundation for classification and further investigations of lung adenocarcinoma molecular pathogenesis.

2,847 citations

Journal ArticleDOI
Dan R. Robinson1, Eliezer M. Van Allen2, Eliezer M. Van Allen3, Yi-Mi Wu1, Nikolaus Schultz4, Robert J. Lonigro1, Juan Miguel Mosquera, Bruce Montgomery5, Mary-Ellen Taplin2, Colin C. Pritchard5, Gerhardt Attard6, Gerhardt Attard7, Himisha Beltran, Wassim Abida4, Robert K. Bradley5, Jake Vinson4, Xuhong Cao1, Pankaj Vats1, Lakshmi P. Kunju1, Maha Hussain1, Felix Y. Feng1, Scott A. Tomlins, Kathleen A. Cooney1, David Smith1, Christine Brennan1, Javed Siddiqui1, Rohit Mehra1, Yu Chen8, Yu Chen4, Dana E. Rathkopf8, Dana E. Rathkopf4, Michael J. Morris8, Michael J. Morris4, Stephen B. Solomon4, Jeremy C. Durack4, Victor E. Reuter4, Anuradha Gopalan4, Jianjiong Gao4, Massimo Loda, Rosina T. Lis2, Michaela Bowden9, Michaela Bowden2, Stephen P. Balk10, Glenn C. Gaviola9, Carrie Sougnez3, Manaswi Gupta3, Evan Y. Yu5, Elahe A. Mostaghel5, Heather H. Cheng5, Hyojeong Mulcahy5, Lawrence D. True11, Stephen R. Plymate5, Heidi Dvinge5, Roberta Ferraldeschi7, Roberta Ferraldeschi6, Penny Flohr6, Penny Flohr7, Susana Miranda6, Susana Miranda7, Zafeiris Zafeiriou6, Zafeiris Zafeiriou7, Nina Tunariu6, Nina Tunariu7, Joaquin Mateo7, Joaquin Mateo6, Raquel Perez-Lopez7, Raquel Perez-Lopez6, Francesca Demichelis8, Francesca Demichelis12, Brian D. Robinson, Marc H. Schiffman8, David M. Nanus, Scott T. Tagawa, Alexandros Sigaras8, Kenneth Eng8, Olivier Elemento8, Andrea Sboner8, Elisabeth I. Heath13, Howard I. Scher8, Howard I. Scher4, Kenneth J. Pienta14, Philip W. Kantoff2, Johann S. de Bono7, Johann S. de Bono6, Mark A. Rubin, Peter S. Nelson, Levi A. Garraway2, Levi A. Garraway3, Charles L. Sawyers4, Arul M. Chinnaiyan 
21 May 2015-Cell
TL;DR: This cohort study provides clinically actionable information that could impact treatment decisions for affected individuals and identified new genomic alterations in PIK3CA/B, R-spondin, BRAF/RAF1, APC, β-catenin, and ZBTB16/PLZF.

2,713 citations

References
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Journal ArticleDOI
04 Mar 2011-Cell
TL;DR: Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.

51,099 citations

Journal ArticleDOI
TL;DR: The results for 20 world regions are presented, summarizing the global patterns for the eight most common cancers, and striking differences in the patterns of cancer from region to region are observed.
Abstract: Estimates of the worldwide incidence and mortality from 27 cancers in 2008 have been prepared for 182 countries as part of the GLOBOCAN series published by the International Agency for Research on Cancer. In this article, we present the results for 20 world regions, summarizing the global patterns for the eight most common cancers. Overall, an estimated 12.7 million new cancer cases and 7.6 million cancer deaths occur in 2008, with 56% of new cancer cases and 63% of the cancer deaths occurring in the less developed regions of the world. The most commonly diagnosed cancers worldwide are lung (1.61 million, 12.7% of the total), breast (1.38 million, 10.9%) and colorectal cancers (1.23 million, 9.7%). The most common causes of cancer death are lung cancer (1.38 million, 18.2% of the total), stomach cancer (738,000 deaths, 9.7%) and liver cancer (696,000 deaths, 9.2%). Cancer is neither rare anywhere in the world, nor mainly confined to high-resource countries. Striking differences in the patterns of cancer from region to region are observed.

21,040 citations

Journal ArticleDOI
29 Mar 2013-Science
TL;DR: This work has revealed the genomic landscapes of common forms of human cancer, which consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of "hills" (Genes altered infrequently).
Abstract: Over the past decade, comprehensive sequencing efforts have revealed the genomic landscapes of common forms of human cancer. For most cancer types, this landscape consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of “hills” (genes altered infrequently). To date, these studies have revealed ~140 genes that, when altered by intragenic mutations, can promote or “drive” tumorigenesis. A typical tumor contains two to eight of these “driver gene” mutations; the remaining mutations are passengers that confer no selective growth advantage. Driver genes can be classified into 12 signaling pathways that regulate three core cellular processes: cell fate, cell survival, and genome maintenance. A better understanding of these pathways is one of the most pressing needs in basic cancer research. Even now, however, our knowledge of cancer genomes is sufficient to guide the development of more effective approaches for reducing cancer morbidity and mortality.

6,441 citations

Journal ArticleDOI
Michael S. Lawrence1, Petar Stojanov1, Petar Stojanov2, Paz Polak3, Paz Polak1, Paz Polak2, Gregory V. Kryukov3, Gregory V. Kryukov1, Gregory V. Kryukov2, Kristian Cibulskis1, Andrey Sivachenko1, Scott L. Carter1, Chip Stewart1, Craig H. Mermel1, Craig H. Mermel2, Steven A. Roberts4, Adam Kiezun1, Peter S. Hammerman1, Peter S. Hammerman2, Aaron McKenna1, Aaron McKenna5, Yotam Drier, Lihua Zou1, Alex H. Ramos1, Trevor J. Pugh1, Trevor J. Pugh2, Nicolas Stransky1, Elena Helman1, Elena Helman6, Jaegil Kim1, Carrie Sougnez1, Lauren Ambrogio1, Elizabeth Nickerson1, Erica Shefler1, Maria L. Cortes1, Daniel Auclair1, Gordon Saksena1, Douglas Voet1, Michael S. Noble1, Daniel DiCara1, Pei Lin1, Lee Lichtenstein1, David I. Heiman1, Timothy Fennell1, Marcin Imielinski2, Marcin Imielinski1, Bryan Hernandez1, Eran Hodis1, Eran Hodis2, Sylvan C. Baca1, Sylvan C. Baca2, Austin M. Dulak2, Austin M. Dulak1, Jens G. Lohr1, Jens G. Lohr2, Dan A. Landau2, Dan A. Landau1, Dan A. Landau7, Catherine J. Wu2, Jorge Melendez-Zajgla, Alfredo Hidalgo-Miranda, Amnon Koren1, Amnon Koren2, Steven A. McCarroll2, Steven A. McCarroll1, Jaume Mora8, Ryan S. Lee2, Ryan S. Lee9, Brian D. Crompton2, Brian D. Crompton9, Robert C. Onofrio1, Melissa Parkin1, Wendy Winckler1, Kristin G. Ardlie1, Stacey Gabriel1, Charles W. M. Roberts9, Charles W. M. Roberts2, Jaclyn A. Biegel10, Kimberly Stegmaier1, Kimberly Stegmaier9, Kimberly Stegmaier2, Adam J. Bass2, Adam J. Bass1, Levi A. Garraway2, Levi A. Garraway1, Matthew Meyerson2, Matthew Meyerson1, Todd R. Golub, Dmitry A. Gordenin4, Shamil R. Sunyaev3, Shamil R. Sunyaev1, Shamil R. Sunyaev2, Eric S. Lander1, Eric S. Lander6, Eric S. Lander2, Gad Getz2, Gad Getz1 
11 Jul 2013-Nature
TL;DR: A fundamental problem with cancer genome studies is described: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds and the list includes many implausible genes, suggesting extensive false-positive findings that overshadow true driver events.
Abstract: Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer. These studies involve the sequencing of matched tumour-normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour-normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.

4,411 citations

Journal ArticleDOI
TL;DR: The MuTect algorithm for calling somatic point mutations enables subclonal analysis of the whole-genome or whole-exome sequencing data being generated in large-scale cancer genomics projects as discussed by the authors.
Abstract: The MuTect algorithm for calling somatic point mutations enables subclonal analysis of the whole-genome or whole-exome sequencing data being generated in large-scale cancer genomics projects.

3,773 citations

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