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Dive into the research topics where Michael S. Lawrence is active.

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Featured researches published by Michael S. Lawrence.


Cancer Cell | 2010

Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

Roel G.W. Verhaak; Katherine A. Hoadley; Elizabeth Purdom; Victoria Wang; Yuan Qi; Matthew D. Wilkerson; C. Ryan Miller; Li Ding; Todd R. Golub; Jill P. Mesirov; Gabriele Alexe; Michael S. Lawrence; Michael O'Kelly; Pablo Tamayo; Barbara A. Weir; Stacey Gabriel; Wendy Winckler; Supriya Gupta; Lakshmi Jakkula; Heidi S. Feiler; J. Graeme Hodgson; C. David James; Jann N. Sarkaria; Cameron Brennan; Ari Kahn; Paul T. Spellman; Richard Wilson; Terence P. Speed; Joe W. Gray; Matthew Meyerson

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.


Nature | 2013

Mutational heterogeneity in cancer and the search for new cancer-associated genes.

Michael S. Lawrence; Petar Stojanov; Paz Polak; Gregory V. Kryukov; Kristian Cibulskis; Andrey Sivachenko; Scott L. Carter; Chip Stewart; Craig H. Mermel; Steven A. Roberts; Adam Kiezun; Peter S. Hammerman; Aaron McKenna; Yotam Drier; Lihua Zou; Alex H. Ramos; Trevor J. Pugh; Nicolas Stransky; Elena Helman; Jaegil Kim; Carrie Sougnez; Lauren Ambrogio; Elizabeth Nickerson; Erica Shefler; Maria L. Cortes; Daniel Auclair; Gordon Saksena; Douglas Voet; Michael S. Noble; Daniel DiCara

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.


Nature | 2010

The landscape of somatic copy-number alteration across human cancers

Rameen Beroukhim; Craig H. Mermel; Dale Porter; Guo Wei; Soumya Raychaudhuri; Jerry Donovan; Jordi Barretina; Jesse S. Boehm; Jennifer Dobson; Mitsuyoshi Urashima; Kevin T. Mc Henry; Reid M. Pinchback; Azra H. Ligon; Yoon-Jae Cho; Leila Haery; Heidi Greulich; Michael R. Reich; Wendy Winckler; Michael S. Lawrence; Barbara A. Weir; Kumiko Tanaka; Derek Y. Chiang; Adam J. Bass; Alice Loo; Carter Hoffman; John R. Prensner; Ted Liefeld; Qing Gao; Derek Yecies; Sabina Signoretti

A powerful way to discover key genes with causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Here we present high-resolution analyses of somatic copy-number alterations (SCNAs) from 3,131 cancer specimens, belonging largely to 26 histological types. We identify 158 regions of focal SCNA that are altered at significant frequency across several cancer types, of which 122 cannot be explained by the presence of a known cancer target gene located within these regions. Several gene families are enriched among these regions of focal SCNA, including the BCL2 family of apoptosis regulators and the NF-κΒ pathway. We show that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival. Finally, we demonstrate that a large majority of SCNAs identified in individual cancer types are present in several cancer types.


Nature | 2008

Somatic mutations affect key pathways in lung adenocarcinoma

Li Ding; Gad Getz; David A. Wheeler; Elaine R. Mardis; Michael D. McLellan; Kristian Cibulskis; Carrie Sougnez; Heidi Greulich; Donna M. Muzny; Margaret Morgan; Lucinda Fulton; Robert S. Fulton; Qunyuan Zhang; Michael C. Wendl; Michael S. Lawrence; David E. Larson; Ken Chen; David J. Dooling; Aniko Sabo; Alicia Hawes; Hua Shen; Shalini N. Jhangiani; Lora Lewis; Otis Hall; Yiming Zhu; Tittu Mathew; Yanru Ren; Jiqiang Yao; Steven E. Scherer; Kerstin Clerc

Determining the genetic basis of cancer requires comprehensive analyses of large collections of histopathologically well-classified primary tumours. Here we report the results of a collaborative study to discover somatic mutations in 188 human lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are probably involved in carcinogenesis. The frequently mutated genes include tyrosine kinases, among them the EGFR homologue ERBB4; multiple ephrin receptor genes, notably EPHA3; vascular endothelial growth factor receptor KDR; and NTRK genes. These data provide evidence of somatic mutations in primary lung adenocarcinoma for several tumour suppressor genes involved in other cancers—including NF1, APC, RB1 and ATM—and for sequence changes in PTPRD as well as the frequently deleted gene LRP1B. The observed mutational profiles correlate with clinical features, smoking status and DNA repair defects. These results are reinforced by data integration including single nucleotide polymorphism array and gene expression array. Our findings shed further light on several important signalling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment.


Science | 2011

The Mutational Landscape of Head and Neck Squamous Cell Carcinoma

Nicolas Stransky; Ann Marie Egloff; Aaron D. Tward; Aleksandar D. Kostic; Kristian Cibulskis; Andrey Sivachenko; Gregory V. Kryukov; Michael S. Lawrence; Carrie Sougnez; Aaron McKenna; Erica Shefler; Alex H. Ramos; Petar Stojanov; Scott L. Carter; Douglas Voet; Maria L. Cortes; Daniel Auclair; Michael F. Berger; Gordon Saksena; Candace Guiducci; Robert C. Onofrio; Melissa Parkin; Marjorie Romkes; Joel L. Weissfeld; Raja R. Seethala; Lin Wang; Claudia Rangel-Escareño; Juan Carlos Fernández-López; Alfredo Hidalgo-Miranda; Jorge Melendez-Zajgla

The mutational profile of head and neck cancer is complex and may pose challenges to the development of targeted therapies. Head and neck squamous cell carcinoma (HNSCC) is a common, morbid, and frequently lethal malignancy. To uncover its mutational spectrum, we analyzed whole-exome sequencing data from 74 tumor-normal pairs. The majority exhibited a mutational profile consistent with tobacco exposure; human papillomavirus was detectable by sequencing DNA from infected tumors. In addition to identifying previously known HNSCC genes (TP53, CDKN2A, PTEN, PIK3CA, and HRAS), our analysis revealed many genes not previously implicated in this malignancy. At least 30% of cases harbored mutations in genes that regulate squamous differentiation (for example, NOTCH1, IRF6, and TP63), implicating its dysregulation as a major driver of HNSCC carcinogenesis. More generally, the results indicate the ability of large-scale sequencing to reveal fundamental tumorigenic mechanisms.


Nature Biotechnology | 2013

Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples.

Kristian Cibulskis; Michael S. Lawrence; Scott L. Carter; Andrey Sivachenko; David M Jaffe; Carrie Sougnez; Stacey Gabriel; Matthew Meyerson; Eric S. Lander; Gad Getz

Detection of somatic point substitutions is a key step in characterizing the cancer genome. However, existing methods typically miss low-allelic-fraction mutations that occur in only a subset of the sequenced cells owing to either tumor heterogeneity or contamination by normal cells. Here we present MuTect, a method that applies a Bayesian classifier to detect somatic mutations with very low allele fractions, requiring only a few supporting reads, followed by carefully tuned filters that ensure high specificity. We also describe benchmarking approaches that use real, rather than simulated, sequencing data to evaluate the sensitivity and specificity as a function of sequencing depth, base quality and allelic fraction. Compared with other methods, MuTect has higher sensitivity with similar specificity, especially for mutations with allelic fractions as low as 0.1 and below, making MuTect particularly useful for studying cancer subclones and their evolution in standard exome and genome sequencing data.


Cell | 2012

A Landscape of Driver Mutations in Melanoma

Eran Hodis; Ian R. Watson; Gregory V. Kryukov; Stefan T. Arold; Marcin Imielinski; Jean Philippe Theurillat; Elizabeth Nickerson; Daniel Auclair; Liren Li; Chelsea S. Place; Daniel DiCara; Alex H. Ramos; Michael S. Lawrence; Kristian Cibulskis; Andrey Sivachenko; Douglas Voet; Gordon Saksena; Nicolas Stransky; Robert C. Onofrio; Wendy Winckler; Kristin Ardlie; Nikhil Wagle; Jennifer A. Wargo; Kelly K. Chong; Donald L. Morton; Katherine Stemke-Hale; Guo Chen; Michael S. Noble; Matthew Meyerson; John E. Ladbury

Despite recent insights into melanoma genetics, systematic surveys for driver mutations are challenged by an abundance of passenger mutations caused by carcinogenic UV light exposure. We developed a permutation-based framework to address this challenge, employing mutation data from intronic sequences to control for passenger mutational load on a per gene basis. Analysis of large-scale melanoma exome data by this approach discovered six novel melanoma genes (PPP6C, RAC1, SNX31, TACC1, STK19, and ARID2), three of which-RAC1, PPP6C, and STK19-harbored recurrent and potentially targetable mutations. Integration with chromosomal copy number data contextualized the landscape of driver mutations, providing oncogenic insights in BRAF- and NRAS-driven melanoma as well as those without known NRAS/BRAF mutations. The landscape also clarified a mutational basis for RB and p53 pathway deregulation in this malignancy. Finally, the spectrum of driver mutations provided unequivocal genomic evidence for a direct mutagenic role of UV light in melanoma pathogenesis.


Nature | 2014

Discovery and saturation analysis of cancer genes across 21 tumour types

Michael S. Lawrence; Petar Stojanov; Craig H. Mermel; James Robinson; Levi A. Garraway; Todd R. Golub; Matthew Meyerson; Stacey Gabriel; Eric S. Lander; Gad Getz

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.


Cell | 2012

Mapping the Hallmarks of Lung Adenocarcinoma with Massively Parallel Sequencing

Marcin Imielinski; Alice H. Berger; Peter S. Hammerman; Bryan Hernandez; Trevor J. Pugh; Eran Hodis; Jeonghee Cho; James Suh; Marzia Capelletti; Andrey Sivachenko; Carrie Sougnez; Daniel Auclair; Michael S. Lawrence; Petar Stojanov; Kristian Cibulskis; Kyusam Choi; Luc de Waal; Tanaz Sharifnia; Angela N. Brooks; Heidi Greulich; Shantanu Banerji; Thomas Zander; Danila Seidel; Frauke Leenders; Sascha Ansén; Corinna Ludwig; Walburga Engel-Riedel; Erich Stoelben; Jürgen Wolf; Chandra Goparju

Lung adenocarcinoma, the most common subtype of non-small cell lung cancer, is responsible for more than 500,000 deaths per year worldwide. Here, we report exome and genome sequences of 183 lung adenocarcinoma tumor/normal DNA pairs. These analyses revealed a mean exonic somatic mutation rate of 12.0 events/megabase and identified the majority of genes previously reported as significantly mutated in lung adenocarcinoma. In addition, we identified statistically recurrent somatic mutations in the splicing factor gene U2AF1 and truncating mutations affecting RBM10 and ARID1A. Analysis of nucleotide context-specific mutation signatures grouped the sample set into distinct clusters that correlated with smoking history and alterations of reported lung adenocarcinoma genes. Whole-genome sequence analysis revealed frequent structural rearrangements, including in-frame exonic alterations within EGFR and SIK2 kinases. The candidate genes identified in this study are attractive targets for biological characterization and therapeutic targeting of lung adenocarcinoma.


Nature | 2011

Initial genome sequencing and analysis of multiple myeloma

Michael Chapman; Michael S. Lawrence; Jonathan J. Keats; Kristian Cibulskis; Carrie Sougnez; Anna C. Schinzel; Christina L. Harview; Jean Philippe Brunet; Gregory J. Ahmann; Mazhar Adli; Kenneth C. Anderson; Kristin Ardlie; Daniel Auclair; Angela Baker; P. Leif Bergsagel; Bradley E. Bernstein; Yotam Drier; Rafael Fonseca; Stacey B. Gabriel; Craig C. Hofmeister; Sundar Jagannath; Andrzej J. Jakubowiak; Amrita Krishnan; Joan Levy; Ted Liefeld; Sagar Lonial; Scott Mahan; Bunmi Mfuko; Stefano Monti; Louise M. Perkins

Multiple myeloma is an incurable malignancy of plasma cells, and its pathogenesis is poorly understood. Here we report the massively parallel sequencing of 38 tumour genomes and their comparison to matched normal DNAs. Several new and unexpected oncogenic mechanisms were suggested by the pattern of somatic mutation across the data set. These include the mutation of genes involved in protein translation (seen in nearly half of the patients), genes involved in histone methylation, and genes involved in blood coagulation. In addition, a broader than anticipated role of NF-κB signalling was indicated by mutations in 11 members of the NF-κB pathway. Of potential immediate clinical relevance, activating mutations of the kinase BRAF were observed in 4% of patients, suggesting the evaluation of BRAF inhibitors in multiple myeloma clinical trials. These results indicate that cancer genome sequencing of large collections of samples will yield new insights into cancer not anticipated by existing knowledge.

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