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1. Therapeutically Increasing MHC-I Expression Potentiates Immune Checkpoint Blockade

Author

Henry W. Long, Blair Stewig, Alba Font-Tello, Xiaoqing Wang, Michael Manos, Ziyi Li, X. Shirley Liu, Jingxin Fu, Paloma Cejas, Gordon J. Freeman, Alok K. Tewari, Scott J. Rodig, Yi Zhang, Zexian Zeng, F. Stephen Hodi, Clifford A. Meyer, Yingtian Xie, Xia Bu, Wubing Zhang, Collin Tokheim, Avinash Das Sahu, Jason L. Weirather, Jake Conway, Klothilda Lim, Myles Brown, Jin Hua Liang, Evisa Gjini, Shengqing Stan Gu, Ana Lako, Peng Jiang, Benjamin Kroger, Nicole Traugh, and Benjamin E. Gewurz

Subjects
0301 basic medicine, T cell, medicine.medical_treatment, B7-H1 Antigen, Article, 03 medical and health sciences, 0302 clinical medicine, Downregulation and upregulation, Neoplasms, MHC class I, Tumor Microenvironment, Data Mining, Humans, Medicine, Immune Checkpoint Inhibitors, biology, business.industry, Gene Expression Profiling, Histocompatibility Antigens Class I, Cancer, Immunotherapy, medicine.disease, Immune checkpoint, Blockade, 030104 developmental biology, medicine.anatomical_structure, Oncology, 030220 oncology & carcinogenesis, Cancer cell, Cancer research, biology.protein, business
Abstract

Immune checkpoint blockade (ICB) therapy revolutionized cancer treatment, but many patients with impaired MHC-I expression remain refractory. Here, we combined FACS-based genome-wide CRISPR screens with a data-mining approach to identify drugs that can upregulate MHC-I without inducing PD-L1. CRISPR screening identified TRAF3, a suppressor of the NFκB pathway, as a negative regulator of MHC-I but not PD-L1. The Traf3-knockout gene expression signature is associated with better survival in ICB-naïve patients with cancer and better ICB response. We then screened for drugs with similar transcriptional effects as this signature and identified Second Mitochondria-derived Activator of Caspase (SMAC) mimetics. We experimentally validated that the SMAC mimetic birinapant upregulates MHC-I, sensitizes cancer cells to T cell–dependent killing, and adds to ICB efficacy. Our findings provide preclinical rationale for treating tumors expressing low MHC-I expression with SMAC mimetics to enhance sensitivity to immunotherapy. The approach used in this study can be generalized to identify other drugs that enhance immunotherapy efficacy. Significance: MHC-I loss or downregulation in cancer cells is a major mechanism of resistance to T cell–based immunotherapies. Our study reveals that birinapant may be used for patients with low baseline MHC-I to enhance ICB response. This represents promising immunotherapy opportunities given the biosafety profile of birinapant from multiple clinical trials. This article is highlighted in the In This Issue feature, p. 1307

Published
2021

2. Integrated Informatics Analysis of Cancer-Related Variants

Author

Ben Busby, Kyle Moad, Rachel Karchin, Rick Kim, Lily Zheng, Collin Tokheim, Kymberleigh A. Pagel, and Michael T. Ryan

Subjects
MEDLINE, Computational biology, Biology, Workflow, User-Computer Interface, 03 medical and health sciences, 0302 clinical medicine, Neoplasms, Databases, Genetic, medicine, Humans, 030304 developmental biology, 0303 health sciences, Extramural, Genetic variants, Computational Biology, Cancer, ORIGINAL REPORTS, General Medicine, medicine.disease, Neoplasm Proteins, Neoplasms diagnosis, Informatics, Mutation, Mutation (genetic algorithm), Special Series: Informatics Tools For Cancer Research and Care, Software, 030217 neurology & neurosurgery
Abstract

PURPOSE The modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, and in silico variant effect prediction tools. Because variant prioritization is a multifactorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, Web dependencies that expose protected data, or limited scalability. METHODS We present the Open Custom Ranked Analysis of Variants Toolkit 1 (OpenCRAVAT) a new open-source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result, the catalog is being actively developed and growing every month. Resources made available via the store are well suited for analysis of cancer, as well as Mendelian and complex diseases. RESULTS OpenCRAVAT offers both command-line utility and dynamic graphical user interface, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants. CONCLUSION OpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding, and noncoding variants.

Published
2020

3. Systematic characterization of mutations altering protein degradation in human cancers

Author

Jun Ge, Stephen J. Elledge, Myles Brown, X. Shirley Liu, Cynthia Chen, Wubing Zhang, Binbin Wang, Boning Zhang, Xiaoqing Wang, Jun Chu, Elijah L. Mena, Collin Tokheim, Richard T. Timms, Timms, Richard [0000-0001-7275-597X], and Apollo - University of Cambridge Repository

Subjects
Protein degradation, Biology, medicine.disease_cause, Article, 03 medical and health sciences, 0302 clinical medicine, Deep Learning, Cell Line, Tumor, Neoplasms, medicine, Humans, Molecular Biology, Transcription factor, 030304 developmental biology, 0303 health sciences, Tumor microenvironment, Mutation, Models, Genetic, HEK 293 cells, GATA3, Cancer, Cell Biology, medicine.disease, Neoplasm Proteins, HEK293 Cells, Proteolysis, Cancer research, Degron, 030217 neurology & neurosurgery
Abstract

The Ubiquitin-Proteasome System (UPS) is the primary route for selective protein degradation in human cells. The UPS represents an attractive target for novel cancer therapeutics, but the precise UPS genes and substrates important for cancer growth are incompletely understood. Leveraging multi-omics data across more than 9,000 human tumors and 33 cancer types, we found that over 19% of all cancer driver genes impact UPS function. We implicate transcription factors as important substrates, and show that c-Myc stability is modulated by CUL3. Moreover, we developed a deep learning model (deepDegron) to identify mutations that result in degron loss, and experimentally validated predictions that gain-of-function truncating mutations in GATA3 and PPM1D result in increased protein stability. Lastly, we identified UPS driver genes associated with patient prognosis and the tumor microenvironment. This study demonstrates the important role of UPS dysregulation in human cancers and underscores the potential therapeutic utility of targeting the UPS.

Published
2021

4. The Genetic Evolution of Treatment-Resistant Cutaneous, Acral, and Uveal Melanomas

Author

Amanda Zucker, Christine A. Iacobuzio-Donahue, Rachel Karchin, Jody E. Hooper, Vladimir Makarov, Nicholas D. Socci, Timothy A. Chan, Paul B. Chapman, Barry S. Taylor, Jungeui Hong, Suzanne L. Topalian, Michael A. Postow, Priscilla Baez, Rajya Kappagantula, David B. Solit, Akimasa Hayashi, Zachary Kohutek, Nadeem Riaz, Collin Tokheim, Alvin Makohon-Moore, Craig M. Bielski, and Evan J. Lipson

Subjects
0301 basic medicine, Oncology, Uveal Neoplasms, Cancer Research, medicine.medical_specialty, Skin Neoplasms, Somatic cell, medicine.medical_treatment, Autopsy, Disease, Article, Metastasis, Evolution, Molecular, 03 medical and health sciences, 0302 clinical medicine, Genetic Evolution, Internal medicine, Biomarkers, Tumor, Medicine, Humans, Treatment resistant, Melanoma, business.industry, Immunotherapy, medicine.disease, Prognosis, 030104 developmental biology, Drug Resistance, Neoplasm, 030220 oncology & carcinogenesis, Mutation, business
Abstract

Purpose: Melanoma is a biologically heterogeneous disease composed of distinct clinicopathologic subtypes that frequently resist treatment. To explore the evolution of treatment resistance and metastasis, we used a combination of temporal and multilesional tumor sampling in conjunction with whole-exome sequencing of 110 tumors collected from 7 patients with cutaneous (n = 3), uveal (n = 2), and acral (n = 2) melanoma subtypes. Experimental Design: Primary tumors, metastases collected longitudinally, and autopsy tissues were interrogated. All but 1 patient died because of melanoma progression. Results: For each patient, we generated phylogenies and quantified the extent of genetic diversity among tumors, specifically among putative somatic alterations affecting therapeutic resistance. Conclusions: In 4 patients who received immunotherapy, we found 1–3 putative acquired and intrinsic resistance mechanisms coexisting in the same patient, including mechanisms that were shared by all tumors within each patient, suggesting that future therapies directed at overcoming intrinsic resistance mechanisms may be broadly effective.

Published
2020

5. Determinants of transcription factor regulatory range

Author

Changxin Wan, Jun Liu, Myles Brown, Collin Tokheim, Clifford A. Meyer, Qin Tang, Rongbin Zheng, Jingyu Fan, Xin Dong, X. Shirley Liu, and Chen-Hao Chen

Subjects
Epigenomics, 0301 basic medicine, Science, Quantitative Trait Loci, General Physics and Astronomy, Context (language use), Computational biology, Biology, Polymorphism, Single Nucleotide, Chromatin structure, Article, General Biochemistry, Genetics and Molecular Biology, Cell Line, Histones, Mice, 03 medical and health sciences, 0302 clinical medicine, Gene density, Animals, lcsh:Science, Transcription factor, Gene, Regulation of gene expression, Multidisciplinary, Models, Genetic, Lysine, Acetylation, General Chemistry, Chromatin, Gene regulation, 030104 developmental biology, Histone, Gene Expression Regulation, 030220 oncology & carcinogenesis, biology.protein, lcsh:Q, Data integration, Gene expression, Transcription Initiation Site, Chromatin immunoprecipitation, Genome-Wide Association Study, Protein Binding, Transcription Factors
Abstract

Characterization of the genomic distances over which transcription factor (TF) binding influences gene expression is important for inferring target genes from TF chromatin immunoprecipitation followed by sequencing (ChIP-seq) data. Here we systematically examine the relationship between thousands of TF and histone modification ChIP-seq data sets with thousands of gene expression profiles. We develop a model for integrating these data, which reveals two classes of TFs with distinct ranges of regulatory influence, chromatin-binding preferences, and auto-regulatory properties. We find that the regulatory range of the same TF bound within different topologically associating domains (TADs) depend on intrinsic TAD properties such as local gene density and G/C content, but also on the TAD chromatin states. Our results suggest that considering TF type, binding distance to gene locus, as well as chromatin context is important in identifying implicated TFs from GWAS SNPs., Characterization of the distance over which TF binding influences gene expression is important for inferring target genes. Here the authors study this relationship using thousands of genomic data sets, finding two classes of TFs with distinct ranges of regulatory influence modulated by chromatin states of topologically associated domains.

Published
2020

6. High-throughput prediction of MHC Class I and Class II neoantigens with MHCnuggets

Author

Lily Zheng, Benjamin Kaminow, Maria Bonsack, Dylan Hirsch, Xiaoshan M. Shao, I K Ashok Sivakumar, Angelika B. Riemer, Rohit Bhattacharya, Rachel Karchin, Victor E. Velculescu, Justin C. Huang, Valsamo Anagnostou, Kymberleigh A. Pagel, Collin Tokheim, and Ashton Omdahl

Subjects
Cancer Research, medicine.medical_treatment, In silico, Immunology, Mutation, Missense, Plasma protein binding, Computational biology, CD8-Positive T-Lymphocytes, Major histocompatibility complex, Cancer Vaccines, Article, 03 medical and health sciences, 0302 clinical medicine, Antigen, Cancer immunotherapy, Antigens, Neoplasm, Artificial Intelligence, Predictive Value of Tests, Neoplasms, MHC class I, medicine, Data Mining, Humans, Missense mutation, Allele, Gene, 030304 developmental biology, 0303 health sciences, biology, Histocompatibility Antigens Class I, Histocompatibility Antigens Class II, Computational Biology, 3. Good health, 030220 oncology & carcinogenesis, biology.protein, Biomarker (medicine), Neural Networks, Computer, Algorithms, Software, CD8, Protein Binding, 030215 immunology
Abstract

Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins is an emerging biomarker for predicting patient response to cancer immunotherapy. Current neoantigen predictors focus onin silicoestimation of MHC binding affinity and are limited by low positive predictive value for actual peptide presentation, inadequate support for rare MHC alleles and poor scalability to high-throughput data sets. To address these limitations, we developed MHCnuggets, a deep neural network method to predict peptide-MHC binding. MHCnuggets is the only method to handle binding prediction for common or rare alleles of MHC Class I or II, with a single neural network architecture. Using a long short-term memory network (LSTM), MHCnuggets accepts peptides of variable length and is capable of faster performance than other methods. When compared to methods that integrate binding affinity and HLAp data from mass spectrometry, MHCnuggets yields a fourfold increase in positive predictive value on independent MHC-bound peptide (HLAp) data. We applied MHCnuggets to 26 cancer types in TCGA, processing 26.3 million allele-peptide comparisons in under 2.3 hours, yielding 101,326 unique candidate immunogenic missense mutations (IMMs). Predicted-IMM hotspots occurred in 38 genes, including 24 driver genes. Predicted-IMM load was significantly associated with increased immune cell infiltration (p2 patients, with 61.7% of these derived from driver mutations. Our results provide a new method for neoantigen prediction with high performance characteristics and demonstrate its utility in large data sets across human cancers.SynopsisWe developed a newin silicopredictor of Major Histocompatibility Complex (MHC) ligand binding and demonstrated its utility to assess potential neoantigens and immunogenic missense mutations (IMMs) in 6613 TCGA patients.

Published
2019

7. Exome-Scale Discovery of Hotspot Mutation Regions in Human Cancer Using 3D Protein Structure

Author

Derek M. Gygax, David L. Masica, Rohit Bhattacharya, Michael C. Ryan, Collin Tokheim, Noushin Niknafs, Rick Kim, and Rachel Karchin

Subjects
0301 basic medicine, Cancer Research, Protein Conformation, Protein domain, Genomics, Biology, medicine.disease_cause, Article, 03 medical and health sciences, Protein structure, Neoplasms, Biomarkers, Tumor, medicine, Humans, Missense mutation, Exome, Gene, Genetics, Computational Biology, High-Throughput Nucleotide Sequencing, 030104 developmental biology, Oncology, Mutation, Mutation testing, Carcinogenesis
Abstract

The impact of somatic missense mutation on cancer etiology and progression is often difficult to interpret. One common approach for assessing the contribution of missense mutations in carcinogenesis is to identify genes mutated with statistically nonrandom frequencies. Even given the large number of sequenced cancer samples currently available, this approach remains underpowered to detect drivers, particularly in less studied cancer types. Alternative statistical and bioinformatic approaches are needed. One approach to increase power is to focus on localized regions of increased missense mutation density or hotspot regions, rather than a whole gene or protein domain. Detecting missense mutation hotspot regions in three-dimensional (3D) protein structure may also be beneficial because linear sequence alone does not fully describe the biologically relevant organization of codons. Here, we present a novel and statistically rigorous algorithm for detecting missense mutation hotspot regions in 3D protein structures. We analyzed approximately 3 × 105 mutations from The Cancer Genome Atlas (TCGA) and identified 216 tumor-type–specific hotspot regions. In addition to experimentally determined protein structures, we considered high-quality structural models, which increase genomic coverage from approximately 5,000 to more than 15,000 genes. We provide new evidence that 3D mutation analysis has unique advantages. It enables discovery of hotspot regions in many more genes than previously shown and increases sensitivity to hotspot regions in tumor suppressor genes (TSG). Although hotspot regions have long been known to exist in both TSGs and oncogenes, we provide the first report that they have different characteristic properties in the two types of driver genes. We show how cancer researchers can use our results to link 3D protein structure and the biologic functions of missense mutations in cancer, and to generate testable hypotheses about driver mechanisms. Our results are included in a new interactive website for visualizing protein structures with TCGA mutations and associated hotspot regions. Users can submit new sequence data, facilitating the visualization of mutations in a biologically relevant context. Cancer Res; 76(13); 3719–31. ©2016 AACR.

Published
2016

8. CHASMplus reveals the scope of somatic missense mutations driving human cancers

Author

Collin Tokheim and Rachel Karchin

Subjects
Histology, Somatic cell, Carcinogenesis, Mutation, Missense, Datasets as Topic, Computational biology, Biology, Genome, Models, Biological, Article, Pathology and Forensic Medicine, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Cancer Medicine, Cancer genome, Neoplasms, medicine, Missense mutation, Humans, Gene, 030304 developmental biology, 0303 health sciences, Cancer type, Cancer, Computational Biology, Cell Biology, medicine.disease, Frequency spectrum, 3. Good health, Benchmarking, 030220 oncology & carcinogenesis, human activities, 030217 neurology & neurosurgery, Algorithms
Abstract

SummaryLarge-scale cancer sequencing studies of patient cohorts have statistically implicated many genes driving cancer growth and progression, and their identification has yielded substantial translational impact. However, a remaining challenge is to increase the resolution of driver prediction from the gene level to the mutation level, because mutation-level predictions are more closely aligned with the goal of precision cancer medicine. Here we present CHASMplus, a computational method, that is uniquely capable of identifying driver missense mutations, including those specific to a cancer type, as evidenced by significantly superior performance on diverse benchmarks. Applied to 8,657 tumor samples across 32 cancer types in The Cancer Genome Atlas, CHASMplus identifies over 4,000 unique driver missense mutations in 240 genes, supporting a prominent role for rare driver mutations. We show which TCGA cancer types are likely to yield discovery of new driver missense mutations by additional sequencing, which has important implications for public policy.SignificanceMissense mutations are the most frequent mutation type in cancers and the most difficult to interpret. While many computational methods have been developed to predict whether genes are cancer drivers or whether missense mutations are generally deleterious or pathogenic, there has not previously been a method to score the oncogenic impact of a missense mutation specifically by cancer type, limiting adoption of computational missense mutation predictors in the clinic. Cancer patients are routinely sequenced with targeted panels of cancer driver genes, but such genes contain a mixture of driver and passenger missense mutations which differ by cancer type. A patient’s therapeutic response to drugs and optimal assignment to a clinical trial depends on both the specific mutation in the gene of interest and cancer type. We present a new machine learning method honed for each TCGA cancer type, and a resource for fast lookup of the cancer-specific driver propensity of every possible missense mutation in the human exome.

Published
2018
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9. Comprehensive Characterization of Cancer Driver Genes and Mutations

Author

Matthew H. Bailey, Collin Tokheim, Eduard Porta-Pardo, Sohini Sengupta, Denis Bertrand, Amila Weerasinghe, Antonio Colaprico, Michael C. Wendl, Jaegil Kim, Brendan Reardon, Patrick Kwok-Shing Ng, Kang Jin Jeong, Song Cao, Zixing Wang, Jianjiong Gao, Qingsong Gao, Fang Wang, Eric Minwei Liu, Loris Mularoni, Carlota Rubio-Perez, Niranjan Nagarajan, Isidro Cortés-Ciriano, Daniel Cui Zhou, Wen-Wei Liang, Julian M. Hess, Venkata D. Yellapantula, David Tamborero, Abel Gonzalez-Perez, Chayaporn Suphavilai, Jia Yu Ko, Ekta Khurana, Peter J. Park, Eliezer M. Van Allen, Han Liang, Michael S. Lawrence, Adam Godzik, Nuria Lopez-Bigas, Josh Stuart, David Wheeler, Gad Getz, Ken Chen, Alexander J. Lazar, Gordon B. Mills, Rachel Karchin, Li Ding, Samantha J. Caesar-Johnson, John A. Demchok, Ina Felau, Melpomeni Kasapi, Martin L. Ferguson, Carolyn M. Hutter, Heidi J. Sofia, Roy Tarnuzzer, Zhining Wang, Liming Yang, Jean C. Zenklusen, Jiashan (Julia) Zhang, Sudha Chudamani, Jia Liu, Laxmi Lolla, Rashi Naresh, Todd Pihl, Qiang Sun, Yunhu Wan, Ye Wu, Juok Cho, Timothy DeFreitas, Scott Frazer, Nils Gehlenborg, David I. Heiman, Pei Lin, Sam Meier, Michael S. Noble, Gordon Saksena, Doug Voet, Hailei Zhang, Brady Bernard, Nyasha Chambwe, Varsha Dhankani, Theo Knijnenburg, Roger Kramer, Kalle Leinonen, Yuexin Liu, Michael Miller, Sheila Reynolds, Ilya Shmulevich, Vesteinn Thorsson, Wei Zhang, Rehan Akbani, Bradley M. Broom, Apurva M. Hegde, Zhenlin Ju, Rupa S. Kanchi, Anil Korkut, Jun Li, Shiyun Ling, Wenbin Liu, Yiling Lu, Kwok-Shing Ng, Arvind Rao, Michael Ryan, Jing Wang, John N. Weinstein, Jiexin Zhang, Adam Abeshouse, Joshua Armenia, Debyani Chakravarty, Walid K. Chatila, Ino de Bruijn, Benjamin E. Gross, Zachary J. Heins, Ritika Kundra, Konnor La, Marc Ladanyi, Augustin Luna, Moriah G. Nissan, Angelica Ochoa, Sarah M. Phillips, Ed Reznik, Francisco Sanchez-Vega, Chris Sander, Nikolaus Schultz, Robert Sheridan, S. Onur Sumer, Yichao Sun, Barry S. Taylor, Jioajiao Wang, Hongxin Zhang, Pavana Anur, Myron Peto, Paul Spellman, Christopher Benz, Joshua M. Stuart, Christopher K. Wong, Christina Yau, D. Neil Hayes, Joel S. Parker, Matthew D. Wilkerson, Adrian Ally, Miruna Balasundaram, Reanne Bowlby, Denise Brooks, Rebecca Carlsen, Eric Chuah, Noreen Dhalla, Robert Holt, Steven J.M. Jones, Katayoon Kasaian, Darlene Lee, Yussanne Ma, Marco A. Marra, Michael Mayo, Richard A. Moore, Andrew J. Mungall, Karen Mungall, A. Gordon Robertson, Sara Sadeghi, Jacqueline E. Schein, Payal Sipahimalani, Angela Tam, Nina Thiessen, Kane Tse, Tina Wong, Ashton C. Berger, Rameen Beroukhim, Andrew D. Cherniack, Carrie Cibulskis, Stacey B. Gabriel, Galen F. Gao, Gavin Ha, Matthew Meyerson, Steven E. Schumacher, Juliann Shih, Melanie H. Kucherlapati, Raju S. Kucherlapati, Stephen Baylin, Leslie Cope, Ludmila Danilova, Moiz S. Bootwalla, Phillip H. Lai, Dennis T. Maglinte, David J. Van Den Berg, Daniel J. Weisenberger, J. Todd Auman, Saianand Balu, Tom Bodenheimer, Cheng Fan, Katherine A. Hoadley, Alan P. Hoyle, Stuart R. Jefferys, Corbin D. Jones, Shaowu Meng, Piotr A. Mieczkowski, Lisle E. Mose, Amy H. Perou, Charles M. Perou, Jeffrey Roach, Yan Shi, Janae V. Simons, Tara Skelly, Matthew G. Soloway, Donghui Tan, Umadevi Veluvolu, Huihui Fan, Toshinori Hinoue, Peter W. Laird, Hui Shen, Wanding Zhou, Michelle Bellair, Kyle Chang, Kyle Covington, Chad J. Creighton, Huyen Dinh, HarshaVardhan Doddapaneni, Lawrence A. Donehower, Jennifer Drummond, Richard A. Gibbs, Robert Glenn, Walker Hale, Yi Han, Jianhong Hu, Viktoriya Korchina, Sandra Lee, Lora Lewis, Wei Li, Xiuping Liu, Margaret Morgan, Donna Morton, Donna Muzny, Jireh Santibanez, Margi Sheth, Eve Shinbrot, Linghua Wang, Min Wang, David A. Wheeler, Liu Xi, Fengmei Zhao, Julian Hess, Elizabeth L. Appelbaum, Matthew Bailey, Matthew G. Cordes, Catrina C. Fronick, Lucinda A. Fulton, Robert S. Fulton, Cyriac Kandoth, Elaine R. Mardis, Michael D. McLellan, Christopher A. Miller, Heather K. Schmidt, Richard K. Wilson, Daniel Crain, Erin Curley, Johanna Gardner, Kevin Lau, David Mallery, Scott Morris, Joseph Paulauskis, Robert Penny, Candace Shelton, Troy Shelton, Mark Sherman, Eric Thompson, Peggy Yena, Jay Bowen, Julie M. Gastier-Foster, Mark Gerken, Kristen M. Leraas, Tara M. Lichtenberg, Nilsa C. Ramirez, Lisa Wise, Erik Zmuda, Niall Corcoran, Tony Costello, Christopher Hovens, Andre L. Carvalho, Ana C. de Carvalho, José H. Fregnani, Adhemar Longatto-Filho, Rui M. Reis, Cristovam Scapulatempo-Neto, Henrique C.S. Silveira, Daniel O. Vidal, Andrew Burnette, Jennifer Eschbacher, Beth Hermes, Ardene Noss, Rosy Singh, Matthew L. Anderson, Patricia D. Castro, Michael Ittmann, David Huntsman, Bernard Kohl, Xuan Le, Richard Thorp, Chris Andry, Elizabeth R. Duffy, Vladimir Lyadov, Oxana Paklina, Galiya Setdikova, Alexey Shabunin, Mikhail Tavobilov, Christopher McPherson, Ronald Warnick, Ross Berkowitz, Daniel Cramer, Colleen Feltmate, Neil Horowitz, Adam Kibel, Michael Muto, Chandrajit P. Raut, Andrei Malykh, Jill S. Barnholtz-Sloan, Wendi Barrett, Karen Devine, Jordonna Fulop, Quinn T. Ostrom, Kristen Shimmel, Yingli Wolinsky, Andrew E. Sloan, Agostino De Rose, Felice Giuliante, Marc Goodman, Beth Y. Karlan, Curt H. Hagedorn, John Eckman, Jodi Harr, Jerome Myers, Kelinda Tucker, Leigh Anne Zach, Brenda Deyarmin, Hai Hu, Leonid Kvecher, Caroline Larson, Richard J. Mural, Stella Somiari, Ales Vicha, Tomas Zelinka, Joseph Bennett, Mary Iacocca, Brenda Rabeno, Patricia Swanson, Mathieu Latour, Louis Lacombe, Bernard Têtu, Alain Bergeron, Mary McGraw, Susan M. Staugaitis, John Chabot, Hanina Hibshoosh, Antonia Sepulveda, Tao Su, Timothy Wang, Olga Potapova, Olga Voronina, Laurence Desjardins, Odette Mariani, Sergio Roman-Roman, Xavier Sastre, Marc-Henri Stern, Feixiong Cheng, Sabina Signoretti, Andrew Berchuck, Darell Bigner, Eric Lipp, Jeffrey Marks, Shannon McCall, Roger McLendon, Angeles Secord, Alexis Sharp, Madhusmita Behera, Daniel J. Brat, Amy Chen, Keith Delman, Seth Force, Fadlo Khuri, Kelly Magliocca, Shishir Maithel, Jeffrey J. Olson, Taofeek Owonikoko, Alan Pickens, Suresh Ramalingam, Dong M. Shin, Gabriel Sica, Erwin G. Van Meir, Hongzheng Zhang, Wil Eijckenboom, Ad Gillis, Esther Korpershoek, Leendert Looijenga, Wolter Oosterhuis, Hans Stoop, Kim E. van Kessel, Ellen C. Zwarthoff, Chiara Calatozzolo, Lucia Cuppini, Stefania Cuzzubbo, Francesco DiMeco, Gaetano Finocchiaro, Luca Mattei, Alessandro Perin, Bianca Pollo, Chu Chen, John Houck, Pawadee Lohavanichbutr, Arndt Hartmann, Christine Stoehr, Robert Stoehr, Helge Taubert, Sven Wach, Bernd Wullich, Witold Kycler, Dawid Murawa, Maciej Wiznerowicz, Ki Chung, W. Jeffrey Edenfield, Julie Martin, Eric Baudin, Glenn Bubley, Raphael Bueno, Assunta De Rienzo, William G. Richards, Steven Kalkanis, Tom Mikkelsen, Houtan Noushmehr, Lisa Scarpace, Nicolas Girard, Marta Aymerich, Elias Campo, Eva Giné, Armando López Guillermo, Nguyen Van Bang, Phan Thi Hanh, Bui Duc Phu, Yufang Tang, Howard Colman, Kimberley Evason, Peter R. Dottino, John A. Martignetti, Hani Gabra, Hartmut Juhl, Teniola Akeredolu, Serghei Stepa, Dave Hoon, Keunsoo Ahn, Koo Jeong Kang, Felix Beuschlein, Anne Breggia, Michael Birrer, Debra Bell, Mitesh Borad, Alan H. Bryce, Erik Castle, Vishal Chandan, John Cheville, John A. Copland, Michael Farnell, Thomas Flotte, Nasra Giama, Thai Ho, Michael Kendrick, Jean-Pierre Kocher, Karla Kopp, Catherine Moser, David Nagorney, Daniel O’Brien, Brian Patrick O’Neill, Tushar Patel, Gloria Petersen, Florencia Que, Michael Rivera, Lewis Roberts, Robert Smallridge, Thomas Smyrk, Melissa Stanton, R. Houston Thompson, Michael Torbenson, Ju Dong Yang, Lizhi Zhang, Fadi Brimo, Jaffer A. Ajani, Ana Maria Angulo Gonzalez, Carmen Behrens, Jolanta Bondaruk, Russell Broaddus, Bogdan Czerniak, Bita Esmaeli, Junya Fujimoto, Jeffrey Gershenwald, Charles Guo, Christopher Logothetis, Funda Meric-Bernstam, Cesar Moran, Lois Ramondetta, David Rice, Anil Sood, Pheroze Tamboli, Timothy Thompson, Patricia Troncoso, Anne Tsao, Ignacio Wistuba, Candace Carter, Lauren Haydu, Peter Hersey, Valerie Jakrot, Hojabr Kakavand, Richard Kefford, Kenneth Lee, Georgina Long, Graham Mann, Michael Quinn, Robyn Saw, Richard Scolyer, Kerwin Shannon, Andrew Spillane, Jonathan Stretch, Maria Synott, John Thompson, James Wilmott, Hikmat Al-Ahmadie, Timothy A. Chan, Ronald Ghossein, Anuradha Gopalan, Douglas A. Levine, Victor Reuter, Samuel Singer, Bhuvanesh Singh, Nguyen Viet Tien, Thomas Broudy, Cyrus Mirsaidi, Praveen Nair, Paul Drwiega, Judy Miller, Jennifer Smith, Howard Zaren, Joong-Won Park, Nguyen Phi Hung, Electron Kebebew, W. Marston Linehan, Adam R. Metwalli, Karel Pacak, Peter A. Pinto, Mark Schiffman, Laura S. Schmidt, Cathy D. Vocke, Nicolas Wentzensen, Robert Worrell, Hannah Yang, Marc Moncrieff, Chandra Goparaju, Jonathan Melamed, Harvey Pass, Natalia Botnariuc, Irina Caraman, Mircea Cernat, Inga Chemencedji, Adrian Clipca, Serghei Doruc, Ghenadie Gorincioi, Sergiu Mura, Maria Pirtac, Irina Stancul, Diana Tcaciuc, Monique Albert, Iakovina Alexopoulou, Angel Arnaout, John Bartlett, Jay Engel, Sebastien Gilbert, Jeremy Parfitt, Harman Sekhon, George Thomas, Doris M. Rassl, Robert C. Rintoul, Carlo Bifulco, Raina Tamakawa, Walter Urba, Nicholas Hayward, Henri Timmers, Anna Antenucci, Francesco Facciolo, Gianluca Grazi, Mirella Marino, Roberta Merola, Ronald de Krijger, Anne-Paule Gimenez-Roqueplo, Alain Piché, Simone Chevalier, Ginette McKercher, Kivanc Birsoy, Gene Barnett, Cathy Brewer, Carol Farver, Theresa Naska, Nathan A. Pennell, Daniel Raymond, Cathy Schilero, Kathy Smolenski, Felicia Williams, Carl Morrison, Jeffrey A. Borgia, Michael J. Liptay, Mark Pool, Christopher W. Seder, Kerstin Junker, Larsson Omberg, Mikhail Dinkin, George Manikhas, Domenico Alvaro, Maria Consiglia Bragazzi, Vincenzo Cardinale, Guido Carpino, Eugenio Gaudio, David Chesla, Sandra Cottingham, Michael Dubina, Fedor Moiseenko, Renumathy Dhanasekaran, Karl-Friedrich Becker, Klaus-Peter Janssen, Julia Slotta-Huspenina, Mohamed H. Abdel-Rahman, Dina Aziz, Sue Bell, Colleen M. Cebulla, Amy Davis, Rebecca Duell, J. Bradley Elder, Joe Hilty, Bahavna Kumar, James Lang, Norman L. Lehman, Randy Mandt, Phuong Nguyen, Robert Pilarski, Karan Rai, Lynn Schoenfield, Kelly Senecal, Paul Wakely, Paul Hansen, Ronald Lechan, James Powers, Arthur Tischler, William E. Grizzle, Katherine C. Sexton, Alison Kastl, Joel Henderson, Sima Porten, Jens Waldmann, Martin Fassnacht, Sylvia L. Asa, Dirk Schadendorf, Marta Couce, Markus Graefen, Hartwig Huland, Guido Sauter, Thorsten Schlomm, Ronald Simon, Pierre Tennstedt, Oluwole Olabode, Mark Nelson, Oliver Bathe, Peter R. Carroll, June M. Chan, Philip Disaia, Pat Glenn, Robin K. Kelley, Charles N. Landen, Joanna Phillips, Michael Prados, Jeffry Simko, Karen Smith-McCune, Scott VandenBerg, Kevin Roggin, Ashley Fehrenbach, Ady Kendler, Suzanne Sifri, Ruth Steele, Antonio Jimeno, Francis Carey, Ian Forgie, Massimo Mannelli, Michael Carney, Brenda Hernandez, Benito Campos, Christel Herold-Mende, Christin Jungk, Andreas Unterberg, Andreas von Deimling, Aaron Bossler, Joseph Galbraith, Laura Jacobus, Michael Knudson, Tina Knutson, Deqin Ma, Mohammed Milhem, Rita Sigmund, Andrew K. Godwin, Rashna Madan, Howard G. Rosenthal, Clement Adebamowo, Sally N. Adebamowo, Alex Boussioutas, David Beer, Thomas Giordano, Anne-Marie Mes-Masson, Fred Saad, Therese Bocklage, Lisa Landrum, Robert Mannel, Kathleen Moore, Katherine Moxley, Russel Postier, Joan Walker, Rosemary Zuna, Michael Feldman, Federico Valdivieso, Rajiv Dhir, James Luketich, Edna M. Mora Pinero, Mario Quintero-Aguilo, Carlos Gilberto Carlotti, Jose Sebastião Dos Santos, Rafael Kemp, Ajith Sankarankuty, Daniela Tirapelli, James Catto, Kathy Agnew, Elizabeth Swisher, Jenette Creaney, Bruce Robinson, Carl Simon Shelley, Eryn M. Godwin, Sara Kendall, Cassaundra Shipman, Carol Bradford, Thomas Carey, Andrea Haddad, Jeffey Moyer, Lisa Peterson, Mark Prince, Laura Rozek, Gregory Wolf, Rayleen Bowman, Kwun M. Fong, Ian Yang, Robert Korst, W. Kimryn Rathmell, J. Leigh Fantacone-Campbell, Jeffrey A. Hooke, Albert J. Kovatich, Craig D. Shriver, John DiPersio, Bettina Drake, Ramaswamy Govindan, Sharon Heath, Timothy Ley, Brian Van Tine, Peter Westervelt, Mark A. Rubin, Jung Il Lee, Natália D. Aredes, Armaz Mariamidze, Bailey M.H., Tokheim C., Porta-Pardo E., Sengupta S., Bertrand D., Weerasinghe A., Colaprico A., Wendl M.C., Kim J., Reardon B., Ng P.K.-S., Jeong K.J., Cao S., Wang Z., Gao J., Gao Q., Wang F., Liu E.M., Mularoni L., Rubio-Perez C., Nagarajan N., Cortes-Ciriano I., Zhou D.C., Liang W.-W., Hess J.M., Yellapantula V.D., Tamborero D., Gonzalez-Perez A., Suphavilai C., Ko J.Y., Khurana E., Park P.J., Van Allen E.M., Liang H., Caesar-Johnson S.J., Demchok J.A., Felau I., Kasapi M., Ferguson M.L., Hutter C.M., Sofia H.J., Tarnuzzer R., Yang L., Zenklusen J.C., Zhang J.J., Chudamani S., Liu J., Lolla L., Naresh R., Pihl T., Sun Q., Wan Y., Wu Y., Cho J., DeFreitas T., Frazer S., Gehlenborg N., Getz G., Heiman D.I., Lawrence M.S., Lin P., Meier S., Noble M.S., Saksena G., Voet D., Zhang H., Bernard B., Chambwe N., Dhankani V., Knijnenburg T., Kramer R., Leinonen K., Liu Y., Miller M., Reynolds S., Shmulevich I., Thorsson V., Zhang W., Akbani R., Broom B.M., Hegde A.M., Ju Z., Kanchi R.S., Korkut A., Li J., Ling S., Liu W., Lu Y., Mills G.B., Ng K.-S., Rao A., Ryan M., Wang J., Weinstein J.N., Zhang J., Abeshouse A., Armenia J., Chakravarty D., Chatila W.K., de Bruijn I., Gross B.E., Heins Z.J., Kundra R., La K., Ladanyi M., Luna A., Nissan M.G., Ochoa A., Phillips S.M., Reznik E., Sanchez-Vega F., Sander C., Schultz N., Sheridan R., Sumer S.O., Sun Y., Taylor B.S., Anur P., Peto M., Spellman P., Benz C., Stuart J.M., Wong C.K., Yau C., Hayes D.N., Parker J.S., Wilkerson M.D., Ally A., Balasundaram M., Bowlby R., Brooks D., Carlsen R., Chuah E., Dhalla N., Holt R., Jones S.J.M., Kasaian K., Lee D., Ma Y., Marra M.A., Mayo M., Moore R.A., Mungall A.J., Mungall K., Robertson A.G., Sadeghi S., Schein J.E., Sipahimalani P., Tam A., Thiessen N., Tse K., Wong T., Berger A.C., Beroukhim R., Cherniack A.D., Cibulskis C., Gabriel S.B., Gao G.F., Ha G., Meyerson M., Schumacher S.E., Shih J., Kucherlapati M.H., Kucherlapati R.S., Baylin S., Cope L., Danilova L., Bootwalla M.S., Lai P.H., Maglinte D.T., Van Den Berg D.J., Weisenberger D.J., Auman J.T., Balu S., Bodenheimer T., Fan C., Hoadley K.A., Hoyle A.P., Jefferys S.R., Jones C.D., Meng S., Mieczkowski P.A., Mose L.E., Perou A.H., Perou C.M., Roach J., Shi Y., Simons J.V., Skelly T., Soloway M.G., Tan D., Veluvolu U., Fan H., Hinoue T., Laird P.W., Shen H., Zhou W., Bellair M., Chang K., Covington K., Creighton C.J., Dinh H., Doddapaneni H., Donehower L.A., Drummond J., Gibbs R.A., Glenn R., Hale W., Han Y., Hu J., Korchina V., Lee S., Lewis L., Li W., Liu X., Morgan M., Morton D., Muzny D., Santibanez J., Sheth M., Shinbrot E., Wang L., Wang M., Wheeler D.A., Xi L., Zhao F., Hess J., Appelbaum E.L., Bailey M., Cordes M.G., Ding L., Fronick C.C., Fulton L.A., Fulton R.S., Kandoth C., Mardis E.R., McLellan M.D., Miller C.A., Schmidt H.K., Wilson R.K., Crain D., Curley E., Gardner J., Lau K., Mallery D., Morris S., Paulauskis J., Penny R., Shelton C., Shelton T., Sherman M., Thompson E., Yena P., Bowen J., Gastier-Foster J.M., Gerken M., Leraas K.M., Lichtenberg T.M., Ramirez N.C., Wise L., Zmuda E., Corcoran N., Costello T., Hovens C., Carvalho A.L., de Carvalho A.C., Fregnani J.H., Longatto-Filho A., Reis R.M., Scapulatempo-Neto C., Silveira H.C.S., Vidal D.O., Burnette A., Eschbacher J., Hermes B., Noss A., Singh R., Anderson M.L., Castro P.D., Ittmann M., Huntsman D., Kohl B., Le X., Thorp R., Andry C., Duffy E.R., Lyadov V., Paklina O., Setdikova G., Shabunin A., Tavobilov M., McPherson C., Warnick R., Berkowitz R., Cramer D., Feltmate C., Horowitz N., Kibel A., Muto M., Raut C.P., Malykh A., Barnholtz-Sloan J.S., Barrett W., Devine K., Fulop J., Ostrom Q.T., Shimmel K., Wolinsky Y., Sloan A.E., De Rose A., Giuliante F., Goodman M., Karlan B.Y., Hagedorn C.H., Eckman J., Harr J., Myers J., Tucker K., Zach L.A., Deyarmin B., Hu H., Kvecher L., Larson C., Mural R.J., Somiari S., Vicha A., Zelinka T., Bennett J., Iacocca M., Rabeno B., Swanson P., Latour M., Lacombe L., Tetu B., Bergeron A., McGraw M., Staugaitis S.M., Chabot J., Hibshoosh H., Sepulveda A., Su T., Wang T., Potapova O., Voronina O., Desjardins L., Mariani O., Roman-Roman S., Sastre X., Stern M.-H., Cheng F., Signoretti S., Berchuck A., Bigner D., Lipp E., Marks J., McCall S., McLendon R., Secord A., Sharp A., Behera M., Brat D.J., Chen A., Delman K., Force S., Khuri F., Magliocca K., Maithel S., Olson J.J., Owonikoko T., Pickens A., Ramalingam S., Shin D.M., Sica G., Van Meir E.G., Eijckenboom W., Gillis A., Korpershoek E., Looijenga L., Oosterhuis W., Stoop H., van Kessel K.E., Zwarthoff E.C., Calatozzolo C., Cuppini L., Cuzzubbo S., DiMeco F., Finocchiaro G., Mattei L., Perin A., Pollo B., Chen C., Houck J., Lohavanichbutr P., Hartmann A., Stoehr C., Stoehr R., Taubert H., Wach S., Wullich B., Kycler W., Murawa D., Wiznerowicz M., Chung K., Edenfield W.J., Martin J., Baudin E., Bubley G., Bueno R., De Rienzo A., Richards W.G., Kalkanis S., Mikkelsen T., Noushmehr H., Scarpace L., Girard N., Aymerich M., Campo E., Gine E., Guillermo A.L., Van Bang N., Hanh P.T., Phu B.D., Tang Y., Colman H., Evason K., Dottino P.R., Martignetti J.A., Gabra H., Juhl H., Akeredolu T., Stepa S., Hoon D., Ahn K., Kang K.J., Beuschlein F., Breggia A., Birrer M., Bell D., Borad M., Bryce A.H., Castle E., Chandan V., Cheville J., Copland J.A., Farnell M., Flotte T., Giama N., Ho T., Kendrick M., Kocher J.-P., Kopp K., Moser C., Nagorney D., O'Brien D., O'Neill B.P., Patel T., Petersen G., Que F., Rivera M., Roberts L., Smallridge R., Smyrk T., Stanton M., Thompson R.H., Torbenson M., Yang J.D., Zhang L., Brimo F., Ajani J.A., Gonzalez A.M.A., Behrens C., Bondaruk J., Broaddus R., Czerniak B., Esmaeli B., Fujimoto J., Gershenwald J., Guo C., Lazar A.J., Logothetis C., Meric-Bernstam F., Moran C., Ramondetta L., Rice D., Sood A., Tamboli P., Thompson T., Troncoso P., Tsao A., Wistuba I., Carter C., Haydu L., Hersey P., Jakrot V., Kakavand H., Kefford R., Lee K., Long G., Mann G., Quinn M., Saw R., Scolyer R., Shannon K., Spillane A., Stretch J., Synott M., Thompson J., Wilmott J., Al-Ahmadie H., Chan T.A., Ghossein R., Gopalan A., Levine D.A., Reuter V., Singer S., Singh B., Tien N.V., Broudy T., Mirsaidi C., Nair P., Drwiega P., Miller J., Smith J., Zaren H., Park J.-W., Hung N.P., Kebebew E., Linehan W.M., Metwalli A.R., Pacak K., Pinto P.A., Schiffman M., Schmidt L.S., Vocke C.D., Wentzensen N., Worrell R., Yang H., Moncrieff M., Goparaju C., Melamed J., Pass H., Botnariuc N., Caraman I., Cernat M., Chemencedji I., Clipca A., Doruc S., Gorincioi G., Mura S., Pirtac M., Stancul I., Tcaciuc D., Albert M., Alexopoulou I., Arnaout A., Bartlett J., Engel J., Gilbert S., Parfitt J., Sekhon H., Thomas G., Rassl D.M., Rintoul R.C., Bifulco C., Tamakawa R., Urba W., Hayward N., Timmers H., Antenucci A., Facciolo F., Grazi G., Marino M., Merola R., de Krijger R., Gimenez-Roqueplo A.-P., Piche A., Chevalier S., McKercher G., Birsoy K., Barnett G., Brewer C., Farver C., Naska T., Pennell N.A., Raymond D., Schilero C., Smolenski K., Williams F., Morrison C., Borgia J.A., Liptay M.J., Pool M., Seder C.W., Junker K., Omberg L., Dinkin M., Manikhas G., Alvaro D., Bragazzi M.C., Cardinale V., Carpino G., Gaudio E., Chesla D., Cottingham S., Dubina M., Moiseenko F., Dhanasekaran R., Becker K.-F., Janssen K.-P., Slotta-Huspenina J., Abdel-Rahman M.H., Aziz D., Bell S., Cebulla C.M., Davis A., Duell R., Elder J.B., Hilty J., Kumar B., Lang J., Lehman N.L., Mandt R., Nguyen P., Pilarski R., Rai K., Schoenfield L., Senecal K., Wakely P., Hansen P., Lechan R., Powers J., Tischler A., Grizzle W.E., Sexton K.C., Kastl A., Henderson J., Porten S., Waldmann J., Fassnacht M., Asa S.L., Schadendorf D., Couce M., Graefen M., Huland H., Sauter G., Schlomm T., Simon R., Tennstedt P., Olabode O., Nelson M., Bathe O., Carroll P.R., Chan J.M., Disaia P., Glenn P., Kelley R.K., Landen C.N., Phillips J., Prados M., Simko J., Smith-McCune K., VandenBerg S., Roggin K., Fehrenbach A., Kendler A., Sifri S., Steele R., Jimeno A., Carey F., Forgie I., Mannelli M., Carney M., Hernandez B., Campos B., Herold-Mende C., Jungk C., Unterberg A., von Deimling A., Bossler A., Galbraith J., Jacobus L., Knudson M., Knutson T., Ma D., Milhem M., Sigmund R., Godwin A.K., Madan R., Rosenthal H.G., Adebamowo C., Adebamowo S.N., Boussioutas A., Beer D., Giordano T., Mes-Masson A.-M., Saad F., Bocklage T., Landrum L., Mannel R., Moore K., Moxley K., Postier R., Walker J., Zuna R., Feldman M., Valdivieso F., Dhir R., Luketich J., Pinero E.M.M., Quintero-Aguilo M., Carlotti C.G., Dos Santos J.S., Kemp R., Sankarankuty A., Tirapelli D., Catto J., Agnew K., Swisher E., Creaney J., Robinson B., Shelley C.S., Godwin E.M., Kendall S., Shipman C., Bradford C., Carey T., Haddad A., Moyer J., Peterson L., Prince M., Rozek L., Wolf G., Bowman R., Fong K.M., Yang I., Korst R., Rathmell W.K., Fantacone-Campbell J.L., Hooke J.A., Kovatich A.J., Shriver C.D., DiPersio J., Drake B., Govindan R., Heath S., Ley T., Van Tine B., Westervelt P., Rubin M.A., Lee J.I., Aredes N.D., Mariamidze A., Godzik A., Lopez-Bigas N., Stuart J., Wheeler D., Chen K., and Karchin R.

Subjects
0301 basic medicine, Oncology, Entropy, Programmed Cell Death 1 Receptor, biochemistry, genetics, molecular Biology (all), Biochemistry, B7-H1 Antigen, structure analysi, Principal Component Analysi, Neoplasms, Databases, Genetic, LS2_1, LS4_6, Missense mutation, Statistical analysis, 610 Medicine & health, Exome sequencing, Confusion, Principal Component Analysis, Melanoma, Sciences bio-médicales et agricoles, structure analysis, Algorithm, oncology, Cancer gene, Adenocarcinoma, Microsatellite Instability, ALGORITMOS, medicine.symptom, Algorithms, Human, medicine.medical_specialty, driver gene discovery, Computational biology, Biology, Characterization (mathematics), General Biochemistry, Genetics and Molecular Biology, Article, NO, 03 medical and health sciences, Internal medicine, medicine, Humans, mutations of clinical relevance, Gene, Biochemistry, Genetics and Molecular Biology(all), Microsatellite instability, Computational Biology, Cancer, medicine.disease, Cancérologie, 030104 developmental biology, Precision oncology, Mutation, Neoplasm, Human genome, Colon adenocarcinoma, human activities, Genetics and Molecular Biology(all)
Abstract

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%–85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors. A comprehensive analysis of oncogenic driver genes and mutations in >9,000 tumors across 33 cancer types highlights the prevalence of clinically actionable cancer driver events in TCGA tumor samples., 0, info:eu-repo/semantics/published

Published
2018

10. Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

Author

Li Ding, Matthew H. Bailey, Eduard Porta-Pardo, Vesteinn Thorsson, Antonio Colaprico, Denis Bertrand, David L. Gibbs, Amila Weerasinghe, Kuan-lin Huang, Collin Tokheim, Isidro Cortés-Ciriano, Reyka Jayasinghe, Feng Chen, Lihua Yu, Sam Sun, Catharina Olsen, Jaegil Kim, Alison M. Taylor, Andrew D. Cherniack, Rehan Akbani, Chayaporn Suphavilai, Niranjan Nagarajan, Joshua M. Stuart, Gordon B. Mills, Matthew A. Wyczalkowski, Benjamin G. Vincent, Carolyn M. Hutter, Jean Claude Zenklusen, Katherine A. Hoadley, Michael C. Wendl, llya Shmulevich, Alexander J. Lazar, David A. Wheeler, Gad Getz, Samantha J. Caesar-Johnson, John A. Demchok, Ina Felau, Melpomeni Kasapi, Martin L. Ferguson, Heidi J. Sofia, Roy Tarnuzzer, Zhining Wang, Liming Yang, Jean C. Zenklusen, Jiashan (Julia) Zhang, Sudha Chudamani, Jia Liu, Laxmi Lolla, Rashi Naresh, Todd Pihl, Qiang Sun, Yunhu Wan, Ye Wu, Juok Cho, Timothy DeFreitas, Scott Frazer, Nils Gehlenborg, David I. Heiman, Michael S. Lawrence, Pei Lin, Sam Meier, Michael S. Noble, Gordon Saksena, Doug Voet, Hailei Zhang, Brady Bernard, Nyasha Chambwe, Varsha Dhankani, Theo Knijnenburg, Roger Kramer, Kalle Leinonen, Yuexin Liu, Michael Miller, Sheila Reynolds, Ilya Shmulevich, Wei Zhang, Bradley M. Broom, Apurva M. Hegde, Zhenlin Ju, Rupa S. Kanchi, Anil Korkut, Jun Li, Han Liang, Shiyun Ling, Wenbin Liu, Yiling Lu, Kwok-Shing Ng, Arvind Rao, Michael Ryan, Jing Wang, John N. Weinstein, Jiexin Zhang, Adam Abeshouse, Joshua Armenia, Debyani Chakravarty, Walid K. Chatila, Ino de Bruijn, Jianjiong Gao, Benjamin E. Gross, Zachary J. Heins, Ritika Kundra, Konnor La, Marc Ladanyi, Augustin Luna, Moriah G. Nissan, Angelica Ochoa, Sarah M. Phillips, Ed Reznik, Francisco Sanchez-Vega, Chris Sander, Nikolaus Schultz, Robert Sheridan, S. Onur Sumer, Yichao Sun, Barry S. Taylor, Jioajiao Wang, Hongxin Zhang, Pavana Anur, Myron Peto, Paul Spellman, Christopher Benz, Christopher K. Wong, Christina Yau, D. Neil Hayes, Joel S. Parker, Matthew D. Wilkerson, Adrian Ally, Miruna Balasundaram, Reanne Bowlby, Denise Brooks, Rebecca Carlsen, Eric Chuah, Noreen Dhalla, Robert Holt, Steven J.M. Jones, Katayoon Kasaian, Darlene Lee, Yussanne Ma, Marco A. Marra, Michael Mayo, Richard A. Moore, Andrew J. Mungall, Karen Mungall, A. Gordon Robertson, Sara Sadeghi, Jacqueline E. Schein, Payal Sipahimalani, Angela Tam, Nina Thiessen, Kane Tse, Tina Wong, Ashton C. Berger, Rameen Beroukhim, Carrie Cibulskis, Stacey B. Gabriel, Galen F. Gao, Gavin Ha, Matthew Meyerson, Steven E. Schumacher, Juliann Shih, Melanie H. Kucherlapati, Raju S. Kucherlapati, Stephen Baylin, Leslie Cope, Ludmila Danilova, Moiz S. Bootwalla, Phillip H. Lai, Dennis T. Maglinte, David J. Van Den Berg, Daniel J. Weisenberger, J. Todd Auman, Saianand Balu, Tom Bodenheimer, Cheng Fan, Alan P. Hoyle, Stuart R. Jefferys, Corbin D. Jones, Shaowu Meng, Piotr A. Mieczkowski, Lisle E. Mose, Amy H. Perou, Charles M. Perou, Jeffrey Roach, Yan Shi, Janae V. Simons, Tara Skelly, Matthew G. Soloway, Donghui Tan, Umadevi Veluvolu, Huihui Fan, Toshinori Hinoue, Peter W. Laird, Hui Shen, Wanding Zhou, Michelle Bellair, Kyle Chang, Kyle Covington, Chad J. Creighton, Huyen Dinh, HarshaVardhan Doddapaneni, Lawrence A. Donehower, Jennifer Drummond, Richard A. Gibbs, Robert Glenn, Walker Hale, Yi Han, Jianhong Hu, Viktoriya Korchina, Sandra Lee, Lora Lewis, Wei Li, Xiuping Liu, Margaret Morgan, Donna Morton, Donna Muzny, Jireh Santibanez, Margi Sheth, Eve Shinbrot, Linghua Wang, Min Wang, Liu Xi, Fengmei Zhao, Julian Hess, Elizabeth L. Appelbaum, Matthew Bailey, Matthew G. Cordes, Catrina C. Fronick, Lucinda A. Fulton, Robert S. Fulton, Cyriac Kandoth, Elaine R. Mardis, Michael D. McLellan, Christopher A. Miller, Heather K. Schmidt, Richard K. Wilson, Daniel Crain, Erin Curley, Johanna Gardner, Kevin Lau, David Mallery, Scott Morris, Joseph Paulauskis, Robert Penny, Candace Shelton, Troy Shelton, Mark Sherman, Eric Thompson, Peggy Yena, Jay Bowen, Julie M. Gastier-Foster, Mark Gerken, Kristen M. Leraas, Tara M. Lichtenberg, Nilsa C. Ramirez, Lisa Wise, Erik Zmuda, Niall Corcoran, Tony Costello, Christopher Hovens, Andre L. Carvalho, Ana C. de Carvalho, José H. Fregnani, Adhemar Longatto-Filho, Rui M. Reis, Cristovam Scapulatempo-Neto, Henrique C.S. Silveira, Daniel O. Vidal, Andrew Burnette, Jennifer Eschbacher, Beth Hermes, Ardene Noss, Rosy Singh, Matthew L. Anderson, Patricia D. Castro, Michael Ittmann, David Huntsman, Bernard Kohl, Xuan Le, Richard Thorp, Chris Andry, Elizabeth R. Duffy, Vladimir Lyadov, Oxana Paklina, Galiya Setdikova, Alexey Shabunin, Mikhail Tavobilov, Christopher McPherson, Ronald Warnick, Ross Berkowitz, Daniel Cramer, Colleen Feltmate, Neil Horowitz, Adam Kibel, Michael Muto, Chandrajit P. Raut, Andrei Malykh, Jill S. Barnholtz-Sloan, Wendi Barrett, Karen Devine, Jordonna Fulop, Quinn T. Ostrom, Kristen Shimmel, Yingli Wolinsky, Andrew E. Sloan, Agostino De Rose, Felice Giuliante, Marc Goodman, Beth Y. Karlan, Curt H. Hagedorn, John Eckman, Jodi Harr, Jerome Myers, Kelinda Tucker, Leigh Anne Zach, Brenda Deyarmin, Hai Hu, Leonid Kvecher, Caroline Larson, Richard J. Mural, Stella Somiari, Ales Vicha, Tomas Zelinka, Joseph Bennett, Mary Iacocca, Brenda Rabeno, Patricia Swanson, Mathieu Latour, Louis Lacombe, Bernard Têtu, Alain Bergeron, Mary McGraw, Susan M. Staugaitis, John Chabot, Hanina Hibshoosh, Antonia Sepulveda, Tao Su, Timothy Wang, Olga Potapova, Olga Voronina, Laurence Desjardins, Odette Mariani, Sergio Roman-Roman, Xavier Sastre, Marc-Henri Stern, Feixiong Cheng, Sabina Signoretti, Andrew Berchuck, Darell Bigner, Eric Lipp, Jeffrey Marks, Shannon McCall, Roger McLendon, Angeles Secord, Alexis Sharp, Madhusmita Behera, Daniel J. Brat, Amy Chen, Keith Delman, Seth Force, Fadlo Khuri, Kelly Magliocca, Shishir Maithel, Jeffrey J. Olson, Taofeek Owonikoko, Alan Pickens, Suresh Ramalingam, Dong M. Shin, Gabriel Sica, Erwin G. Van Meir, Hongzheng Zhang, Wil Eijckenboom, Ad Gillis, Esther Korpershoek, Leendert Looijenga, Wolter Oosterhuis, Hans Stoop, Kim E. van Kessel, Ellen C. Zwarthoff, Chiara Calatozzolo, Lucia Cuppini, Stefania Cuzzubbo, Francesco DiMeco, Gaetano Finocchiaro, Luca Mattei, Alessandro Perin, Bianca Pollo, Chu Chen, John Houck, Pawadee Lohavanichbutr, Arndt Hartmann, Christine Stoehr, Robert Stoehr, Helge Taubert, Sven Wach, Bernd Wullich, Witold Kycler, Dawid Murawa, Maciej Wiznerowicz, Ki Chung, W. Jeffrey Edenfield, Julie Martin, Eric Baudin, Glenn Bubley, Raphael Bueno, Assunta De Rienzo, William G. Richards, Steven Kalkanis, Tom Mikkelsen, Houtan Noushmehr, Lisa Scarpace, Nicolas Girard, Marta Aymerich, Elias Campo, Eva Giné, Armando López Guillermo, Nguyen Van Bang, Phan Thi Hanh, Bui Duc Phu, Yufang Tang, Howard Colman, Kimberley Evason, Peter R. Dottino, John A. Martignetti, Hani Gabra, Hartmut Juhl, Teniola Akeredolu, Serghei Stepa, Dave Hoon, Keunsoo Ahn, Koo Jeong Kang, Felix Beuschlein, Anne Breggia, Michael Birrer, Debra Bell, Mitesh Borad, Alan H. Bryce, Erik Castle, Vishal Chandan, John Cheville, John A. Copland, Michael Farnell, Thomas Flotte, Nasra Giama, Thai Ho, Michael Kendrick, Jean-Pierre Kocher, Karla Kopp, Catherine Moser, David Nagorney, Daniel O’Brien, Brian Patrick O’Neill, Tushar Patel, Gloria Petersen, Florencia Que, Michael Rivera, Lewis Roberts, Robert Smallridge, Thomas Smyrk, Melissa Stanton, R. Houston Thompson, Michael Torbenson, Ju Dong Yang, Lizhi Zhang, Fadi Brimo, Jaffer A. Ajani, Ana Maria Angulo Gonzalez, Carmen Behrens, Jolanta Bondaruk, Russell Broaddus, Bogdan Czerniak, Bita Esmaeli, Junya Fujimoto, Jeffrey Gershenwald, Charles Guo, Christopher Logothetis, Funda Meric-Bernstam, Cesar Moran, Lois Ramondetta, David Rice, Anil Sood, Pheroze Tamboli, Timothy Thompson, Patricia Troncoso, Anne Tsao, Ignacio Wistuba, Candace Carter, Lauren Haydu, Peter Hersey, Valerie Jakrot, Hojabr Kakavand, Richard Kefford, Kenneth Lee, Georgina Long, Graham Mann, Michael Quinn, Robyn Saw, Richard Scolyer, Kerwin Shannon, Andrew Spillane, Jonathan Stretch, Maria Synott, John Thompson, James Wilmott, Hikmat Al-Ahmadie, Timothy A. Chan, Ronald Ghossein, Anuradha Gopalan, Douglas A. Levine, Victor Reuter, Samuel Singer, Bhuvanesh Singh, Nguyen Viet Tien, Thomas Broudy, Cyrus Mirsaidi, Praveen Nair, Paul Drwiega, Judy Miller, Jennifer Smith, Howard Zaren, Joong-Won Park, Nguyen Phi Hung, Electron Kebebew, W. Marston Linehan, Adam R. Metwalli, Karel Pacak, Peter A. Pinto, Mark Schiffman, Laura S. Schmidt, Cathy D. Vocke, Nicolas Wentzensen, Robert Worrell, Hannah Yang, Marc Moncrieff, Chandra Goparaju, Jonathan Melamed, Harvey Pass, Natalia Botnariuc, Irina Caraman, Mircea Cernat, Inga Chemencedji, Adrian Clipca, Serghei Doruc, Ghenadie Gorincioi, Sergiu Mura, Maria Pirtac, Irina Stancul, Diana Tcaciuc, Monique Albert, Iakovina Alexopoulou, Angel Arnaout, John Bartlett, Jay Engel, Sebastien Gilbert, Jeremy Parfitt, Harman Sekhon, George Thomas, Doris M. Rassl, Robert C. Rintoul, Carlo Bifulco, Raina Tamakawa, Walter Urba, Nicholas Hayward, Henri Timmers, Anna Antenucci, Francesco Facciolo, Gianluca Grazi, Mirella Marino, Roberta Merola, Ronald de Krijger, Anne-Paule Gimenez-Roqueplo, Alain Piché, Simone Chevalier, Ginette McKercher, Kivanc Birsoy, Gene Barnett, Cathy Brewer, Carol Farver, Theresa Naska, Nathan A. Pennell, Daniel Raymond, Cathy Schilero, Kathy Smolenski, Felicia Williams, Carl Morrison, Jeffrey A. Borgia, Michael J. Liptay, Mark Pool, Christopher W. Seder, Kerstin Junker, Larsson Omberg, Mikhail Dinkin, George Manikhas, Domenico Alvaro, Maria Consiglia Bragazzi, Vincenzo Cardinale, Guido Carpino, Eugenio Gaudio, David Chesla, Sandra Cottingham, Michael Dubina, Fedor Moiseenko, Renumathy Dhanasekaran, Karl-Friedrich Becker, Klaus-Peter Janssen, Julia Slotta-Huspenina, Mohamed H. Abdel-Rahman, Dina Aziz, Sue Bell, Colleen M. Cebulla, Amy Davis, Rebecca Duell, J. Bradley Elder, Joe Hilty, Bahavna Kumar, James Lang, Norman L. Lehman, Randy Mandt, Phuong Nguyen, Robert Pilarski, Karan Rai, Lynn Schoenfield, Kelly Senecal, Paul Wakely, Paul Hansen, Ronald Lechan, James Powers, Arthur Tischler, William E. Grizzle, Katherine C. Sexton, Alison Kastl, Joel Henderson, Sima Porten, Jens Waldmann, Martin Fassnacht, Sylvia L. Asa, Dirk Schadendorf, Marta Couce, Markus Graefen, Hartwig Huland, Guido Sauter, Thorsten Schlomm, Ronald Simon, Pierre Tennstedt, Oluwole Olabode, Mark Nelson, Oliver Bathe, Peter R. Carroll, June M. Chan, Philip Disaia, Pat Glenn, Robin K. Kelley, Charles N. Landen, Joanna Phillips, Michael Prados, Jeffry Simko, Karen Smith-McCune, Scott VandenBerg, Kevin Roggin, Ashley Fehrenbach, Ady Kendler, Suzanne Sifri, Ruth Steele, Antonio Jimeno, Francis Carey, Ian Forgie, Massimo Mannelli, Michael Carney, Brenda Hernandez, Benito Campos, Christel Herold-Mende, Christin Jungk, Andreas Unterberg, Andreas von Deimling, Aaron Bossler, Joseph Galbraith, Laura Jacobus, Michael Knudson, Tina Knutson, Deqin Ma, Mohammed Milhem, Rita Sigmund, Andrew K. Godwin, Rashna Madan, Howard G. Rosenthal, Clement Adebamowo, Sally N. Adebamowo, Alex Boussioutas, David Beer, Thomas Giordano, Anne-Marie Mes-Masson, Fred Saad, Therese Bocklage, Lisa Landrum, Robert Mannel, Kathleen Moore, Katherine Moxley, Russel Postier, Joan Walker, Rosemary Zuna, Michael Feldman, Federico Valdivieso, Rajiv Dhir, James Luketich, Edna M. Mora Pinero, Mario Quintero-Aguilo, Carlos Gilberto Carlotti, Jose Sebastião Dos Santos, Rafael Kemp, Ajith Sankarankuty, Daniela Tirapelli, James Catto, Kathy Agnew, Elizabeth Swisher, Jenette Creaney, Bruce Robinson, Carl Simon Shelley, Eryn M. Godwin, Sara Kendall, Cassaundra Shipman, Carol Bradford, Thomas Carey, Andrea Haddad, Jeffey Moyer, Lisa Peterson, Mark Prince, Laura Rozek, Gregory Wolf, Rayleen Bowman, Kwun M. Fong, Ian Yang, Robert Korst, W. Kimryn Rathmell, J. Leigh Fantacone-Campbell, Jeffrey A. Hooke, Albert J. Kovatich, Craig D. Shriver, John DiPersio, Bettina Drake, Ramaswamy Govindan, Sharon Heath, Timothy Ley, Brian Van Tine, Peter Westervelt, Mark A. Rubin, Jung Il Lee, Natália D. Aredes, Armaz Mariamidze, Ding L., Bailey M.H., Porta-Pardo E., Thorsson V., Colaprico A., Bertrand D., Gibbs D.L., Weerasinghe A., Huang K.-L., Tokheim C., Cortes-Ciriano I., Jayasinghe R., Chen F., Yu L., Sun S., Olsen C., Kim J., Taylor A.M., Cherniack A.D., Akbani R., Suphavilai C., Nagarajan N., Stuart J.M., Mills G.B., Wyczalkowski M.A., Vincent B.G., Hutter C.M., Zenklusen J.C., Hoadley K.A., Wendl M.C., Shmulevich L., Lazar A.J., Wheeler D.A., Getz G., Caesar-Johnson S.J., Demchok J.A., Felau I., Kasapi M., Ferguson M.L., Sofia H.J., Tarnuzzer R., Wang Z., Yang L., Zhang J.J., Chudamani S., Liu J., Lolla L., Naresh R., Pihl T., Sun Q., Wan Y., Wu Y., Cho J., DeFreitas T., Frazer S., Gehlenborg N., Heiman D.I., Lawrence M.S., Lin P., Meier S., Noble M.S., Saksena G., Voet D., Zhang H., Bernard B., Chambwe N., Dhankani V., Knijnenburg T., Kramer R., Leinonen K., Liu Y., Miller M., Reynolds S., Shmulevich I., Zhang W., Broom B.M., Hegde A.M., Ju Z., Kanchi R.S., Korkut A., Li J., Liang H., Ling S., Liu W., Lu Y., Ng K.-S., Rao A., Ryan M., Wang J., Weinstein J.N., Zhang J., Abeshouse A., Armenia J., Chakravarty D., Chatila W.K., de Bruijn I., Gao J., Gross B.E., Heins Z.J., Kundra R., La K., Ladanyi M., Luna A., Nissan M.G., Ochoa A., Phillips S.M., Reznik E., Sanchez-Vega F., Sander C., Schultz N., Sheridan R., Sumer S.O., Sun Y., Taylor B.S., Anur P., Peto M., Spellman P., Benz C., Wong C.K., Yau C., Hayes D.N., Parker J.S., Wilkerson M.D., Ally A., Balasundaram M., Bowlby R., Brooks D., Carlsen R., Chuah E., Dhalla N., Holt R., Jones S.J.M., Kasaian K., Lee D., Ma Y., Marra M.A., Mayo M., Moore R.A., Mungall A.J., Mungall K., Robertson A.G., Sadeghi S., Schein J.E., Sipahimalani P., Tam A., Thiessen N., Tse K., Wong T., Berger A.C., Beroukhim R., Cibulskis C., Gabriel S.B., Gao G.F., Ha G., Meyerson M., Schumacher S.E., Shih J., Kucherlapati M.H., Kucherlapati R.S., Baylin S., Cope L., Danilova L., Bootwalla M.S., Lai P.H., Maglinte D.T., Van Den Berg D.J., Weisenberger D.J., Auman J.T., Balu S., Bodenheimer T., Fan C., Hoyle A.P., Jefferys S.R., Jones C.D., Meng S., Mieczkowski P.A., Mose L.E., Perou A.H., Perou C.M., Roach J., Shi Y., Simons J.V., Skelly T., Soloway M.G., Tan D., Veluvolu U., Fan H., Hinoue T., Laird P.W., Shen H., Zhou W., Bellair M., Chang K., Covington K., Creighton C.J., Dinh H., Doddapaneni H., Donehower L.A., Drummond J., Gibbs R.A., Glenn R., Hale W., Han Y., Hu J., Korchina V., Lee S., Lewis L., Li W., Liu X., Morgan M., Morton D., Muzny D., Santibanez J., Sheth M., Shinbrot E., Wang L., Wang M., Xi L., Zhao F., Hess J., Appelbaum E.L., Bailey M., Cordes M.G., Fronick C.C., Fulton L.A., Fulton R.S., Kandoth C., Mardis E.R., McLellan M.D., Miller C.A., Schmidt H.K., Wilson R.K., Crain D., Curley E., Gardner J., Lau K., Mallery D., Morris S., Paulauskis J., Penny R., Shelton C., Shelton T., Sherman M., Thompson E., Yena P., Bowen J., Gastier-Foster J.M., Gerken M., Leraas K.M., Lichtenberg T.M., Ramirez N.C., Wise L., Zmuda E., Corcoran N., Costello T., Hovens C., Carvalho A.L., de Carvalho A.C., Fregnani J.H., Longatto-Filho A., Reis R.M., Scapulatempo-Neto C., Silveira H.C.S., Vidal D.O., Burnette A., Eschbacher J., Hermes B., Noss A., Singh R., Anderson M.L., Castro P.D., Ittmann M., Huntsman D., Kohl B., Le X., Thorp R., Andry C., Duffy E.R., Lyadov V., Paklina O., Setdikova G., Shabunin A., Tavobilov M., McPherson C., Warnick R., Berkowitz R., Cramer D., Feltmate C., Horowitz N., Kibel A., Muto M., Raut C.P., Malykh A., Barnholtz-Sloan J.S., Barrett W., Devine K., Fulop J., Ostrom Q.T., Shimmel K., Wolinsky Y., Sloan A.E., De Rose A., Giuliante F., Goodman M., Karlan B.Y., Hagedorn C.H., Eckman J., Harr J., Myers J., Tucker K., Zach L.A., Deyarmin B., Hu H., Kvecher L., Larson C., Mural R.J., Somiari S., Vicha A., Zelinka T., Bennett J., Iacocca M., Rabeno B., Swanson P., Latour M., Lacombe L., Tetu B., Bergeron A., McGraw M., Staugaitis S.M., Chabot J., Hibshoosh H., Sepulveda A., Su T., Wang T., Potapova O., Voronina O., Desjardins L., Mariani O., Roman-Roman S., Sastre X., Stern M.-H., Cheng F., Signoretti S., Berchuck A., Bigner D., Lipp E., Marks J., McCall S., McLendon R., Secord A., Sharp A., Behera M., Brat D.J., Chen A., Delman K., Force S., Khuri F., Magliocca K., Maithel S., Olson J.J., Owonikoko T., Pickens A., Ramalingam S., Shin D.M., Sica G., Van Meir E.G., Eijckenboom W., Gillis A., Korpershoek E., Looijenga L., Oosterhuis W., Stoop H., van Kessel K.E., Zwarthoff E.C., Calatozzolo C., Cuppini L., Cuzzubbo S., DiMeco F., Finocchiaro G., Mattei L., Perin A., Pollo B., Chen C., Houck J., Lohavanichbutr P., Hartmann A., Stoehr C., Stoehr R., Taubert H., Wach S., Wullich B., Kycler W., Murawa D., Wiznerowicz M., Chung K., Edenfield W.J., Martin J., Baudin E., Bubley G., Bueno R., De Rienzo A., Richards W.G., Kalkanis S., Mikkelsen T., Noushmehr H., Scarpace L., Girard N., Aymerich M., Campo E., Gine E., Guillermo A.L., Van Bang N., Hanh P.T., Phu B.D., Tang Y., Colman H., Evason K., Dottino P.R., Martignetti J.A., Gabra H., Juhl H., Akeredolu T., Stepa S., Hoon D., Ahn K., Kang K.J., Beuschlein F., Breggia A., Birrer M., Bell D., Borad M., Bryce A.H., Castle E., Chandan V., Cheville J., Copland J.A., Farnell M., Flotte T., Giama N., Ho T., Kendrick M., Kocher J.-P., Kopp K., Moser C., Nagorney D., O'Brien D., O'Neill B.P., Patel T., Petersen G., Que F., Rivera M., Roberts L., Smallridge R., Smyrk T., Stanton M., Thompson R.H., Torbenson M., Yang J.D., Zhang L., Brimo F., Ajani J.A., Gonzalez A.M.A., Behrens C., Bondaruk J., Broaddus R., Czerniak B., Esmaeli B., Fujimoto J., Gershenwald J., Guo C., Logothetis C., Meric-Bernstam F., Moran C., Ramondetta L., Rice D., Sood A., Tamboli P., Thompson T., Troncoso P., Tsao A., Wistuba I., Carter C., Haydu L., Hersey P., Jakrot V., Kakavand H., Kefford R., Lee K., Long G., Mann G., Quinn M., Saw R., Scolyer R., Shannon K., Spillane A., Stretch J., Synott M., Thompson J., Wilmott J., Al-Ahmadie H., Chan T.A., Ghossein R., Gopalan A., Levine D.A., Reuter V., Singer S., Singh B., Tien N.V., Broudy T., Mirsaidi C., Nair P., Drwiega P., Miller J., Smith J., Zaren H., Park J.-W., Hung N.P., Kebebew E., Linehan W.M., Metwalli A.R., Pacak K., Pinto P.A., Schiffman M., Schmidt L.S., Vocke C.D., Wentzensen N., Worrell R., Yang H., Moncrieff M., Goparaju C., Melamed J., Pass H., Botnariuc N., Caraman I., Cernat M., Chemencedji I., Clipca A., Doruc S., Gorincioi G., Mura S., Pirtac M., Stancul I., Tcaciuc D., Albert M., Alexopoulou I., Arnaout A., Bartlett J., Engel J., Gilbert S., Parfitt J., Sekhon H., Thomas G., Rassl D.M., Rintoul R.C., Bifulco C., Tamakawa R., Urba W., Hayward N., Timmers H., Antenucci A., Facciolo F., Grazi G., Marino M., Merola R., de Krijger R., Gimenez-Roqueplo A.-P., Piche A., Chevalier S., McKercher G., Birsoy K., Barnett G., Brewer C., Farver C., Naska T., Pennell N.A., Raymond D., Schilero C., Smolenski K., Williams F., Morrison C., Borgia J.A., Liptay M.J., Pool M., Seder C.W., Junker K., Omberg L., Dinkin M., Manikhas G., Alvaro D., Bragazzi M.C., Cardinale V., Carpino G., Gaudio E., Chesla D., Cottingham S., Dubina M., Moiseenko F., Dhanasekaran R., Becker K.-F., Janssen K.-P., Slotta-Huspenina J., Abdel-Rahman M.H., Aziz D., Bell S., Cebulla C.M., Davis A., Duell R., Elder J.B., Hilty J., Kumar B., Lang J., Lehman N.L., Mandt R., Nguyen P., Pilarski R., Rai K., Schoenfield L., Senecal K., Wakely P., Hansen P., Lechan R., Powers J., Tischler A., Grizzle W.E., Sexton K.C., Kastl A., Henderson J., Porten S., Waldmann J., Fassnacht M., Asa S.L., Schadendorf D., Couce M., Graefen M., Huland H., Sauter G., Schlomm T., Simon R., Tennstedt P., Olabode O., Nelson M., Bathe O., Carroll P.R., Chan J.M., Disaia P., Glenn P., Kelley R.K., Landen C.N., Phillips J., Prados M., Simko J., Smith-McCune K., VandenBerg S., Roggin K., Fehrenbach A., Kendler A., Sifri S., Steele R., Jimeno A., Carey F., Forgie I., Mannelli M., Carney M., Hernandez B., Campos B., Herold-Mende C., Jungk C., Unterberg A., von Deimling A., Bossler A., Galbraith J., Jacobus L., Knudson M., Knutson T., Ma D., Milhem M., Sigmund R., Godwin A.K., Madan R., Rosenthal H.G., Adebamowo C., Adebamowo S.N., Boussioutas A., Beer D., Giordano T., Mes-Masson A.-M., Saad F., Bocklage T., Landrum L., Mannel R., Moore K., Moxley K., Postier R., Walker J., Zuna R., Feldman M., Valdivieso F., Dhir R., Luketich J., Pinero E.M.M., Quintero-Aguilo M., Carlotti C.G., Dos Santos J.S., Kemp R., Sankarankuty A., Tirapelli D., Catto J., Agnew K., Swisher E., Creaney J., Robinson B., Shelley C.S., Godwin E.M., Kendall S., Shipman C., Bradford C., Carey T., Haddad A., Moyer J., Peterson L., Prince M., Rozek L., Wolf G., Bowman R., Fong K.M., Yang I., Korst R., Rathmell W.K., Fantacone-Campbell J.L., Hooke J.A., Kovatich A.J., Shriver C.D., DiPersio J., Drake B., Govindan R., Heath S., Ley T., Van Tine B., Westervelt P., Rubin M.A., Lee J.I., Aredes N.D., Mariamidze A., Clinical sciences, Medical Genetics, Medical Sociology, SAIC-F-Frederick, Inc, and Leidos Biomedical Research, Inc.

Subjects
0301 basic medicine, oncogenic process, INFORMATION, DNA Repair, Tumor Microenvironment/genetics, Carcinogenesis, Cancer Genome Atlas Research Network, medicine.disease_cause, Genome, Biochemistry, Germline, Transcriptome, oncogenic proce, Neoplasms, Databases, Genetic, LS2_1, Tumor Microenvironment, LS4_6, SOMATIC POINT MUTATIONS, 610 Medicine & health, 11 Medical and Health Sciences, Carcinogenesi, Metabolic Networks and Pathways/genetics, cancer genomic, CARCINOGÊNESE, Genomics, TUMORS, Neoplasms/genetics, omics, Proteome, Physique des particules élémentaires, Microsatellite Instability, Life Sciences & Biomedicine, Metabolic Networks and Pathways, Human, EXPRESSION, Biochemistry & Molecular Biology, cancer, cancer genomics, TCGA, omic, Computational biology, Biology, BREAST, CLASSIFICATION, General Biochemistry, Genetics and Molecular Biology, Article, NO, 03 medical and health sciences, DNA Repair/genetics, medicine, Humans, Tumor microenvironment, Science & Technology, LANDSCAPE, IDENTIFICATION, Biochemistry, Genetics and Molecular Biology(all), Metabolic Networks and Pathway, Cell Biology, Epigenome, 06 Biological Sciences, 030104 developmental biology, DISCOVERY, Mutation, DRIVER, Neoplasm, Carcinogenesis/genetics, Developmental Biology, Genetics and Molecular Biology(all), Genes, Neoplasm
Abstract

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing. A synthesized view on oncogenic processes based on PanCancer Atlas analyses highlights the complex impact of genome alterations on the signaling and multi-omic profiles of human cancers as well as their influence on tumor microenvironment., 0, info:eu-repo/semantics/published

Published
2018

11. CRAVAT 4: Cancer-Related Analysis of Variants Toolkit

Author

Rachel Karchin, Kyle Moad, Rohit Bhattacharya, Michael C. Ryan, Christopher Douville, Collin Tokheim, David L. Masica, and RyangGuk Kim

Subjects
0301 basic medicine, Cancer Research, Internet, Mutation, Computer science, Somatic cell, Computational Biology, Context (language use), Genomics, medicine.disease_cause, Omics, Data science, Article, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Oncology, 030220 oncology & carcinogenesis, Neoplasms, Mutation (genetic algorithm), medicine, Humans, Exome, Gene, Software
Abstract

Cancer sequencing studies are increasingly comprehensive and well-powered, returning long lists of somatic mutations that can be difficult to sort and interpret. Diligent analysis and quality control can require multiple computational tools of distinct utility and producing disparate output, creating additional challenges for the investigator. The Cancer-Related Analysis of Variants Toolkit (CRAVAT) is an evolving suite of informatics tools for mutation interpretation that includes mutation projecting and quality control, impact prediction and extensive annotation, gene- and mutation-level interpretation including joint prioritization of all nonsilent consequence types, and structural and mechanistic visualization. Results from CRAVAT submissions are explored in an interactive, user-friendly web-environment with dynamic filtering and sorting designed to highlight the most informative mutation, even in the context of very large studies. CRAVAT can be run on a public web-portal, in the cloud, or downloaded for local use, and is easily integrated with other methods for cancer omics analysis.Conflict of interestAll authors declare no potential conflict of interest.

Published
2017
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12. Matching phenotypes to whole genomes: Lessons learned from four iterations of the personal genome project community challenges

Author

Sohini Sengupta, Marco Carraro, Roger A. Hoskins, Silvio C. E. Tosatto, Jean Fan, Nikki Kiga, Christopher Douville, Binghuang Cai, Steven E. Brenner, Dewey Kim, Mark Diekhans, Susanna Repo, Hannah Carter, Manuel Giollo, Rohit Bhattacharya, John Moult, Lipika R. Pal, Jason Bobe, Biao Li, Sean D. Mooney, Rachel Karchin, Emanuela Leonardi, Jan Zaucha, Julian Gough, Yun-Ching Chen, Timothy Bergquist, Hui Ting Grace Yeo, Violeta Beleva-Guthrie, Carlo Ferrari, Tychele N. Turner, Madeleine Ball, George M. Church, Noushin Niknafs, Melissa S. Cline, Collin Tokheim, Yizhou Yin, Chen Hsin Yu, Chen Cao, Janita Thusberg, and Mario Stanke

Subjects
0301 basic medicine, Matching (statistics), biomedical informatics, phenotype, Population, Clinical Sciences, Quantitative Trait Loci, Computational biology, Biology, Quantitative trait locus, Genome, Article, 03 medical and health sciences, personal genome project, 0302 clinical medicine, personal genome project (PGP), Human Genome Project, Genetics, Humans, Genetic Predisposition to Disease, education, genome, Genetics (clinical), Whole genome sequencing, Genetics & Heredity, education.field_of_study, Whole Genome Sequencing, genome interpretation, Small number, community challenge, Human Genome, open consent, High-Throughput Nucleotide Sequencing, Personal Genome Project, 030104 developmental biology, Good Health and Well Being, Phenotype, Area Under Curve, Trait, critical assessment, 030217 neurology & neurosurgery, Biotechnology
Abstract

The advent of next-generation sequencing has dramatically decreased the cost for whole-genome sequencing and increased the viability for its application in research and clinical care. The Personal Genome Project (PGP) provides unrestricted access to genomes of individuals and their associated phenotypes. This resource enabled the Critical Assessment of Genome Interpretation (CAGI) to create a community challenge to assess the bioinformatics community's ability to predict traits from whole genomes. In the CAGI PGP challenge, researchers were asked to predict whether an individual had a particular trait or profile based on their whole genome. Several approaches were used to assess submissions, including ROC AUC (area under receiver operating characteristic curve), probability rankings, the number of correct predictions, and statistical significance simulations. Overall, we found that prediction of individual traits is difficult, relying on a strong knowledge of trait frequency within the general population, whereas matching genomes to trait profiles relies heavily upon a small number of common traits including ancestry, blood type, and eye color. When a rare genetic disorder is present, profiles can be matched when one or more pathogenic variants are identified. Prediction accuracy has improved substantially over the last 6 years due to improved methodology and a better understanding of features.

Published
2016

13. Evaluating the Evaluation of Cancer Driver Genes

Author

Nickolas Papadopoulos, Rachel Karchin, Kenneth W. Kinzler, Collin Tokheim, and Bert Vogelstein

Subjects
0301 basic medicine, Mutation rate, Computer science, Somatic cell, Gene prediction, Computational biology, Biology, Gene mutation, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Mutation Rate, Neoplasms, Databases, Genetic, medicine, Humans, Cancer mutations, Gene, 030304 developmental biology, Genetics, 0303 health sciences, Multidisciplinary, Models, Genetic, Computational Biology, Cancer, Oncogenes, Gold standard (test), medicine.disease, 3. Good health, 030104 developmental biology, 030220 oncology & carcinogenesis, Mutation, Physical Sciences, human activities, Software
Abstract

Sequencing has identified millions of somatic mutations in human cancers, but distinguishing cancer driver genes remains a major challenge. Numerous methods have been developed to identify driver genes, but evaluation of the performance of these methods is hindered by the lack of a gold standard, i.e., bona fide driver gene mutations. Here, we establish an evaluation framework that can be applied when a gold standard is not available. We used this framework to compare the performance of eight driver gene prediction methods. One of these methods, newly described here, incorporated a machine learning-based ratiometric approach. We show that the driver genes predicted by each of these eight methods vary widely. Moreover, the p-values reported by several of the methods were inconsistent with the uniform values expected, thus calling into question the assumptions that were used to generate them. Finally, we evaluated the potential effects of unexplained variability in mutation rates on false positive driver gene predictions. Our analysis points to the strengths and weaknesses of each of the currently available methods and offers guidance for improving them in the future.SignificanceModern large-scale sequencing of human cancers seeks to comprehensively discover mutated genes that confer a selective advantage to cancer cells. Key to this effort has been development of computational algorithms to find genes that drive cancer, based on their patterns of mutation in large patient cohorts. However, since there is no generally accepted gold standard of driver genes, it has been difficult to quantitatively compare these methods. We present a new machine learning method for driver gene prediction and a rigorous protocol to evaluate and compare prediction methods. Our results suggest that most current methods do not adequately account for heterogeneity in the number of mutations expected by chance and consequently have many false positive calls. The problem is most acute for cancers with high mutation rates and comprehensive discovery of drivers in these cancers may be more difficult than currently anticipated.

Published
2016

14. WHOLE-GENOME SEQUENCING OF SALIVARY GLAND ADENOID CYSTIC CARCINOMA

Author

Nickolas Papadopoulos, Luigi Marchionni, Sian Jones, Nishant Agrawal, Eleni M. Rettig, Mark Sausen, Rachel Karchin, Kenneth W. Kinzler, C. Conover Talbot, Michael Considine, Carole Fakhry, Laura D. Wood, Justin A. Bishop, Collin Tokheim, Bert Vogelstein, Noushin Niknafs, Elana J. Fertig, Patrick K. Ha, and Sarah J. Wheelan

Subjects
0301 basic medicine, Cancer Research, Pathology, medicine.medical_specialty, Oncogene Proteins, Fusion, Carcinogenesis, Notch signaling pathway, Biology, medicine.disease_cause, Translocation, Genetic, Article, 03 medical and health sciences, 0302 clinical medicine, medicine, Humans, RNA, Messenger, Gene, Gene Rearrangement, Receptors, Notch, Gene Expression Profiling, Gene rearrangement, Sequence Analysis, DNA, Salivary Gland Neoplasms, Carcinoma, Adenoid Cystic, Salivary Gland Adenoid Cystic Carcinoma, Gene expression profiling, NFI Transcription Factors, 030104 developmental biology, Oncology, NFIB, 030220 oncology & carcinogenesis, Cancer research, Transcription Factor Gene, Signal Transduction
Abstract

Adenoid cystic carcinomas (ACC) of the salivary glands are challenging to understand, treat, and cure. To better understand the genetic alterations underlying the pathogenesis of these tumors, we performed comprehensive genome analyses of 25 fresh-frozen tumors, including whole-genome sequencing and expression and pathway analyses. In addition to the well-described MYB–NFIB fusion that was found in 11 tumors (44%), we observed five different rearrangements involving the NFIB transcription factor gene in seven tumors (28%). Taken together, NFIB translocations occurred in 15 of 25 samples (60%, 95% CI, 41%–77%). In addition, mRNA expression analysis of 17 tumors revealed overexpression of NFIB in ACC tumors compared with normal tissues (P = 0.002). There was no difference in NFIB mRNA expression in tumors with NFIB fusions compared with those without. We also report somatic mutations of genes involved in the axonal guidance and Rho family signaling pathways. Finally, we confirm previously described alterations in genes related to chromatin regulation and Notch signaling. Our findings suggest a separate role for NFIB in ACC oncogenesis and highlight important signaling pathways for future functional characterization and potential therapeutic targeting. Cancer Prev Res; 9(4); 265–74. ©2016 AACR.

Published
2016

15. Systematic Functional Annotation of Somatic Mutations in Cancer

Author

Nikolaus Schultz, Daniel Cui Zhou, Shuangxing Yu, Hu Chen, Ken Chen, Yiu Huen Tsang, Christopher P. Vellano, Stephanie Soewito, Li Ding, Shan Shao, Sohini Sengupta, Yiling Lu, Amber Johnson, Rachel Karchin, Gordon B. Mills, Richard Tran, Jia Zeng, Matthew Wester, Kang Jin Jeong, Hengyu Lu, Darlan Conterno Minussi, Patrick Kwok Shing Ng, Collin Tokheim, Song Yi, Zixing Wang, Venkata Hemanjani Bhavana, Carman K.M. Ip, Yongsheng Li, Funda Meric-Bernstam, Han Liang, Kenna R. Shaw, Daniela Moreno, Jianjiong Gao, Kenneth L. Scott, Kathleen Kong, Turgut Dogruluk, Nidhi Sahni, Lydia W.T. Cheung, Zhenlin Ju, and Jun Li

Subjects
Proteomics, 0301 basic medicine, Cancer Research, Genomics, Computational biology, Biology, medicine.disease_cause, Article, 03 medical and health sciences, Neoplasms, Biomarkers, Tumor, medicine, Humans, Precision Medicine, Biomarker discovery, Mutation, Proteomic Profiling, Point mutation, High-Throughput Nucleotide Sequencing, Cell Biology, 030104 developmental biology, Oncology, Drug development, Functional genomics, Algorithms
Abstract

The functional impact of the vast majority of cancer somatic mutations remains unknown, representing a critical knowledge gap for implementing precision oncology. Here, we report the development of a moderate-throughput functional genomic platform consisting of efficient mutant generation, sensitive viability assays using two growth-factor–dependent cell models, and functional proteomic profiling of signaling effects for select aberrations. We apply the platform to annotate >1000 genomic aberrations, including gene amplifications, point mutations, indels, and gene fusions, potentially doubling the number of driver mutations characterized in clinically actionable genes. Further, the platform is sufficiently sensitive to identify weak drivers. Our data are accessible through a user-friendly, public data portal (http://bioinformatics.mdanderson.org/main/FASMIC). Our study will facilitate biomarker discovery, prediction algorithm improvement, and drug development.

Published
2018

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