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Todd Pihl

Other affiliations: National Institutes of Health
Bio: Todd Pihl is an academic researcher from SRA International. The author has contributed to research in topics: DNA methylation & Genome. The author has an hindex of 33, co-authored 38 publications receiving 55251 citations. Previous affiliations of Todd Pihl include National Institutes of Health.

Papers
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Journal ArticleDOI
04 Oct 2012-Nature
TL;DR: The ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity.
Abstract: We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.

9,355 citations

Journal ArticleDOI
Donna M. Muzny1, Matthew N. Bainbridge1, Kyle Chang1, Huyen Dinh1  +317 moreInstitutions (24)
19 Jul 2012-Nature
TL;DR: Integrative analyses suggest new markers for aggressive colorectal carcinoma and an important role for MYC-directed transcriptional activation and repression.
Abstract: To characterize somatic alterations in colorectal carcinoma, we conducted a genome-scale analysis of 276 samples, analysing exome sequence, DNA copy number, promoter methylation and messenger RNA and microRNA expression. A subset of these samples (97) underwent low-depth-of-coverage whole-genome sequencing. In total, 16% of colorectal carcinomas were found to be hypermutated: three-quarters of these had the expected high microsatellite instability, usually with hypermethylation and MLH1 silencing, and one-quarter had somatic mismatch-repair gene and polymerase e (POLE) mutations. Excluding the hypermutated cancers, colon and rectum cancers were found to have considerably similar patterns of genomic alteration. Twenty-four genes were significantly mutated, and in addition to the expected APC, TP53, SMAD4, PIK3CA and KRAS mutations, we found frequent mutations in ARID1A, SOX9 and FAM123B. Recurrent copy-number alterations include potentially drug-targetable amplifications of ERBB2 and newly discovered amplification of IGF2. Recurrent chromosomal translocations include the fusion of NAV2 and WNT pathway member TCF7L1. Integrative analyses suggest new markers for aggressive colorectal carcinoma and an important role for MYC-directed transcriptional activation and repression.

6,883 citations

Journal Article
01 Sep 2013-Nature
TL;DR: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels as mentioned in this paper.
Abstract: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.

4,634 citations

Journal ArticleDOI
Adam J. Bass1, Vesteinn Thorsson2, Ilya Shmulevich2, Sheila Reynolds2  +254 moreInstitutions (32)
11 Sep 2014-Nature
TL;DR: A comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project is described and a molecular classification dividing gastric cancer into four subtypes is proposed.
Abstract: Gastric cancer was the world’s third leading cause of cancer mortality in 2012, responsible for 723,000 deaths1. The vast majority of gastric cancers are adenocarcinomas, which can be further subdivided into intestinal and diffuse types according to the Lauren classification2. An alternative system, proposed by the World Health Organization, divides gastric cancer into papillary, tubular, mucinous (colloid) and poorly cohesive carcinomas3. These classification systems have little clinical utility, making the development of robust classifiers that can guide patient therapy an urgent priority. The majority of gastric cancers are associated with infectious agents, including the bacterium Helicobacter pylori4 and Epstein–Barr virus (EBV). The distribution of histological subtypes of gastric cancer and the frequencies of H. pylori and EBV associated gastric cancer vary across the globe5. A small minority of gastric cancer cases are associated with germline mutation in E-cadherin (CDH1)6 or mismatch repair genes7 (Lynch syndrome), whereas sporadic mismatch repair-deficient gastric cancers have epigenetic silencing of MLH1 in the context of a CpG island methylator phenotype (CIMP)8. Molecular profiling of gastric cancer has been performed using gene expression or DNA sequencing9–12, but has not led to a clear biologic classification scheme. The goals of this study by The Cancer Genome Atlas (TCGA) were to develop a robust molecular classification of gastric cancer and to identify dysregulated pathways and candidate drivers of distinct classes of gastric cancer.

4,583 citations

Journal ArticleDOI
Timothy J. Ley1, Christopher A. Miller1, Li Ding1, Benjamin J. Raphael2, Andrew J. Mungall3, Gordon Robertson3, Katherine A. Hoadley4, Timothy J. Triche5, Peter W. Laird5, Jack Baty1, Lucinda Fulton1, Robert S. Fulton1, Sharon Heath1, Joelle Kalicki-Veizer1, Cyriac Kandoth1, Jeffery M. Klco1, Daniel C. Koboldt1, Krishna L. Kanchi1, Shashikant Kulkarni1, Tamara Lamprecht1, David E. Larson1, G. Lin1, Charles Lu1, Michael D. McLellan1, Joshua F. McMichael1, Jacqueline E. Payton1, Heather Schmidt1, David H. Spencer1, Michael H. Tomasson1, John W. Wallis1, Lukas D. Wartman1, Mark A. Watson1, John S. Welch1, Michael C. Wendl1, Adrian Ally3, Miruna Balasundaram3, Inanc Birol3, Yaron S.N. Butterfield3, Readman Chiu3, Andy Chu3, Eric Chuah3, Hye Jung E. Chun3, Richard Corbett3, Noreen Dhalla3, Ranabir Guin3, An He3, Carrie Hirst3, Martin Hirst3, Robert A. Holt3, Steven J.M. Jones3, Aly Karsan3, Darlene Lee3, Haiyan I. Li3, Marco A. Marra3, Michael Mayo3, Richard A. Moore3, Karen Mungall3, Jeremy Parker3, Erin Pleasance3, Patrick Plettner3, Jacquie Schein3, Dominik Stoll3, Lucas Swanson3, Angela Tam3, Nina Thiessen3, Richard Varhol3, Natasja Wye3, Yongjun Zhao3, Stacey Gabriel6, Gad Getz6, Carrie Sougnez6, Lihua Zou6, Mark D.M. Leiserson2, Fabio Vandin2, Hsin-Ta Wu2, Frederick Applebaum7, Stephen B. Baylin8, Rehan Akbani9, Bradley M. Broom9, Ken Chen9, Thomas C. Motter9, Khanh Thi-Thuy Nguyen9, John N. Weinstein9, Nianziang Zhang9, Martin L. Ferguson, Christopher Adams10, Aaron D. Black10, Jay Bowen10, Julie M. Gastier-Foster10, Thomas Grossman10, Tara M. Lichtenberg10, Lisa Wise10, Tanja Davidsen11, John A. Demchok11, Kenna R. Mills Shaw11, Margi Sheth11, Heidi J. Sofia, Liming Yang11, James R. Downing, Greg Eley, Shelley Alonso12, Brenda Ayala12, Julien Baboud12, Mark Backus12, Sean P. Barletta12, Dominique L. Berton12, Anna L. Chu12, Stanley Girshik12, Mark A. Jensen12, Ari B. Kahn12, Prachi Kothiyal12, Matthew C. Nicholls12, Todd Pihl12, David Pot12, Rohini Raman12, Rashmi N. Sanbhadti12, Eric E. Snyder12, Deepak Srinivasan12, Jessica Walton12, Yunhu Wan12, Zhining Wang12, Jean Pierre J. Issa13, Michelle M. Le Beau14, Martin Carroll15, Hagop M. Kantarjian, Steven M. Kornblau, Moiz S. Bootwalla5, Phillip H. Lai5, Hui Shen5, David Van Den Berg5, Daniel J. Weisenberger5, Daniel C. Link1, Matthew J. Walter1, Bradley A. Ozenberger11, Elaine R. Mardis1, Peter Westervelt1, Timothy A. Graubert1, John F. DiPersio1, Richard K. Wilson1 
TL;DR: It is found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients and the databases from this study are widely available to serve as a foundation for further investigations of AMl pathogenesis, classification, and risk stratification.
Abstract: BACKGROUND—Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined The relationships between patterns of mutations and epigenetic phenotypes are not yet clear METHODS—We analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis RESULTS—AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes Of these, an average of 5 are in genes that are recurrently mutated in AML A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcriptionfactor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumorsuppressor genes (16%), DNA-methylation–related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%) Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories CONCLUSIONS—We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification (Funded by the National Institutes of Health) The molecular pathogenesis of acute myeloid leukemia (AML) has been studied with the use of cytogenetic analysis for more than three decades Recurrent chromosomal structural variations are well established as diagnostic and prognostic markers, suggesting that acquired genetic abnormalities (ie, somatic mutations) have an essential role in pathogenesis 1,2 However, nearly 50% of AML samples have a normal karyotype, and many of these genomes lack structural abnormalities, even when assessed with high-density comparative genomic hybridization or single-nucleotide polymorphism (SNP) arrays 3-5 (see Glossary) Targeted sequencing has identified recurrent mutations in FLT3, NPM1, KIT, CEBPA, and TET2 6-8 Massively parallel sequencing enabled the discovery of recurrent mutations in DNMT3A 9,10 and IDH1 11 Recent studies have shown that many patients with

3,980 citations


Cited by
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Journal ArticleDOI
TL;DR: The 2016 World Health Organization Classification of Tumors of the Central Nervous System is both a conceptual and practical advance over its 2007 predecessor and is hoped that it will facilitate clinical, experimental and epidemiological studies that will lead to improvements in the lives of patients with brain tumors.
Abstract: The 2016 World Health Organization Classification of Tumors of the Central Nervous System is both a conceptual and practical advance over its 2007 predecessor. For the first time, the WHO classification of CNS tumors uses molecular parameters in addition to histology to define many tumor entities, thus formulating a concept for how CNS tumor diagnoses should be structured in the molecular era. As such, the 2016 CNS WHO presents major restructuring of the diffuse gliomas, medulloblastomas and other embryonal tumors, and incorporates new entities that are defined by both histology and molecular features, including glioblastoma, IDH-wildtype and glioblastoma, IDH-mutant; diffuse midline glioma, H3 K27M-mutant; RELA fusion-positive ependymoma; medulloblastoma, WNT-activated and medulloblastoma, SHH-activated; and embryonal tumour with multilayered rosettes, C19MC-altered. The 2016 edition has added newly recognized neoplasms, and has deleted some entities, variants and patterns that no longer have diagnostic and/or biological relevance. Other notable changes include the addition of brain invasion as a criterion for atypical meningioma and the introduction of a soft tissue-type grading system for the now combined entity of solitary fibrous tumor / hemangiopericytoma-a departure from the manner by which other CNS tumors are graded. Overall, it is hoped that the 2016 CNS WHO will facilitate clinical, experimental and epidemiological studies that will lead to improvements in the lives of patients with brain tumors.

11,197 citations

Journal ArticleDOI
TL;DR: A practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics, which makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries.
Abstract: The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

10,947 citations

Journal ArticleDOI
23 Jan 2015-Science
TL;DR: In this paper, a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level.
Abstract: Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

9,745 citations

Journal ArticleDOI
Ludmil B. Alexandrov1, Serena Nik-Zainal2, Serena Nik-Zainal3, David C. Wedge1, Samuel Aparicio4, Sam Behjati1, Sam Behjati5, Andrew V. Biankin, Graham R. Bignell1, Niccolo Bolli5, Niccolo Bolli1, Åke Borg2, Anne Lise Børresen-Dale6, Anne Lise Børresen-Dale7, Sandrine Boyault8, Birgit Burkhardt8, Adam Butler1, Carlos Caldas9, Helen Davies1, Christine Desmedt, Roland Eils5, Jorunn E. Eyfjord10, John A. Foekens11, Mel Greaves12, Fumie Hosoda13, Barbara Hutter5, Tomislav Ilicic1, Sandrine Imbeaud14, Sandrine Imbeaud15, Marcin Imielinsk15, Natalie Jäger5, David T. W. Jones16, David T. Jones1, Stian Knappskog11, Stian Knappskog17, Marcel Kool11, Sunil R. Lakhani18, Carlos López-Otín18, Sancha Martin1, Nikhil C. Munshi19, Nikhil C. Munshi20, Hiromi Nakamura13, Paul A. Northcott16, Marina Pajic21, Elli Papaemmanuil1, Angelo Paradiso22, John V. Pearson23, Xose S. Puente18, Keiran Raine1, Manasa Ramakrishna1, Andrea L. Richardson19, Andrea L. Richardson22, Julia Richter22, Philip Rosenstiel22, Matthias Schlesner5, Ton N. Schumacher24, Paul N. Span25, Jon W. Teague1, Yasushi Totoki13, Andrew Tutt24, Rafael Valdés-Mas18, Marit M. van Buuren25, Laura van ’t Veer26, Anne Vincent-Salomon27, Nicola Waddell23, Lucy R. Yates1, Icgc PedBrain24, Jessica Zucman-Rossi15, Jessica Zucman-Rossi14, P. Andrew Futreal1, Ultan McDermott1, Peter Lichter24, Matthew Meyerson19, Matthew Meyerson15, Sean M. Grimmond23, Reiner Siebert22, Elias Campo28, Tatsuhiro Shibata13, Stefan M. Pfister11, Stefan M. Pfister16, Peter J. Campbell3, Peter J. Campbell29, Peter J. Campbell30, Michael R. Stratton3, Michael R. Stratton31 
22 Aug 2013-Nature
TL;DR: It is shown that hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types, and this results reveal the diversity of mutational processes underlying the development of cancer.
Abstract: All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

7,904 citations

Journal ArticleDOI
19 May 2016-Blood
TL;DR: The 2016 edition of the World Health Organization classification of tumors of the hematopoietic and lymphoid tissues represents a revision of the prior classification rather than an entirely new classification and attempts to incorporate new clinical, prognostic, morphologic, immunophenotypic, and genetic data that have emerged since the last edition.

7,147 citations