Obi L. Griffith

ORCID: 0000-0002-0843-4271
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About
Contact & Profiles
Research Areas
  • Cancer Genomics and Diagnostics
  • Lymphoma Diagnosis and Treatment
  • Genomics and Rare Diseases
  • Genetic factors in colorectal cancer
  • Genomics and Phylogenetic Studies
  • Immunotherapy and Immune Responses
  • Lung Cancer Treatments and Mutations
  • RNA modifications and cancer
  • Advanced Breast Cancer Therapies
  • Estrogen and related hormone effects
  • Biomedical Text Mining and Ontologies
  • Gene expression and cancer classification
  • Bioinformatics and Genomic Networks
  • Head and Neck Cancer Studies
  • vaccines and immunoinformatics approaches
  • Cancer Immunotherapy and Biomarkers
  • Monoclonal and Polyclonal Antibodies Research
  • Cervical Cancer and HPV Research
  • Hippo pathway signaling and YAP/TAZ
  • RNA Research and Splicing
  • Immune Cell Function and Interaction
  • Cancer-related gene regulation
  • HER2/EGFR in Cancer Research
  • CAR-T cell therapy research
  • Genetics, Bioinformatics, and Biomedical Research

Washington University in St. Louis
2016-2025

James S. McDonnell Foundation
2016-2025

Canada's Michael Smith Genome Sciences Centre
2005-2023

University of British Columbia
2003-2023

Alvin J. Siteman Cancer Center
2015-2023

Jewish Hospital
2022-2023

Barnes-Jewish Hospital
2022-2023

University of Winnipeg
2003-2020

National Human Genome Research Institute
2016-2019

Altor BioScience (United States)
2019

We sequenced the 29,751-base genome of severe acute respiratory syndrome (SARS)–associated coronavirus known as Tor2 isolate. The sequence reveals that this is only moderately related to other coronaviruses, including two human HCoV-OC43 and HCoV-229E. Phylogenetic analysis predicted viral proteins indicates virus does not closely resemble any three previously groups coronaviruses. will aid in diagnosis SARS infection humans potential animal hosts (using polymerase chain reaction...

10.1126/science.1085953 article EN Science 2003-05-06

The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents interactions gene druggability information from papers, databases web resources. DGIdb normalizes content 30 disparate sources allows for user-friendly advanced browsing, searching filtering ease of access through an intuitive user interface, application programming interface (API) public cloud-based server image. v3.0 represents a major update the database. Nine previously included 24 were...

10.1093/nar/gkx1143 article EN cc-by-nc Nucleic Acids Research 2017-11-07

The Drug-Gene Interaction Database (DGIdb, www.dgidb.org) is a web resource that provides information on drug-gene interactions and druggable genes from publications, databases, other web-based sources. Drug, gene, interaction data are normalized merged into conceptual groups. contained in this available to users through straightforward search interface, an application programming interface (API), TSV downloads. DGIdb 4.0 the latest major version release of database. A primary focus update...

10.1093/nar/gkaa1084 article EN cc-by Nucleic Acids Research 2020-10-23

To characterize patient-derived xenografts (PDXs) for functional studies, we made whole-genome comparisons with originating breast cancers representative of the major intrinsic subtypes. Structural and copy number aberrations were found to be retained high fidelity. However, at single-nucleotide level, variable numbers PDX-specific somatic events documented, although they only rarely functionally significant. Variant allele frequencies often preserved in PDXs, demonstrating that clonal...

10.1016/j.celrep.2013.08.022 article EN cc-by Cell Reports 2013-09-01
Daniela S. Gerhard Lukas Wagner Elise A. Feingold Carolyn M. Shenmen Lynette Grouse and 95 more Greg Schuler Steven L. Klein Susan Old Rebekah S. Rasooly Peter J. Good Mark S. Guyer Allison M. Peck Jeffery G. Derge David J. Lipman Francis S. Collins Wonhee Jang Stephen T. Sherry Mike Feolo Leonie Misquitta Eduardo Lee Kirill E. Rotmistrovsky Susan F. Greenhut Carl F. Schaefer Kenneth H. Buetow Tom I. Bonner David Haussler Jim Kent Mark Diekhans Terrence S. Furey Michael R. Brent Christa Prange Kirsten Schreiber Nicole Shapiro Narayan Bhat Ralph F. Hopkins Florence Hsie Tom Driscoll Marcelo B. Soares Maria F. Bonaldo T.L. Casavant Todd E. Scheetz Michael Brownstein Ted B. Usdin Toshiyuki Shiraki Piero Carninci Yulan Piao Dawood B. Dudekula Minoru S.H. Ko Koichi Kawakami Yutaka Suzuki Sumio Sugano C. E. Gruber M. Smith Blake A. Simmons Troy Moore Richard Waterman Stephen L. Johnson Yijun Ruan Chia Lin Wei Sinnakaruppan Mathavan Preethi H. Gunaratne Jiaqian Wu Angela Garcia Stephen W. Hulyk Edwin Fuh Ye Yuan Anna Sneed Carla Kowis Anne V. Hodgson Donna M. Muzny John D. McPherson Richard A. Gibbs Jessica Fahey Erin Helton Mark Ketteman Anuradha Madan Stephanie Rodrigues Amy Sanchez Michelle Whiting Anup Madan Alice Young Keith Wetherby Stephen J. Granite Peggy N. Kwong Charles P. Brinkley Russell L. Pearson Gerard G. Bouffard Robert W. Blakesly Eric D. Green Mark Dickson Álex Rodríguez Jonathan Wood Jeremy Schmutz R Myers Yaron S.N. Butterfield Malachi Griffith Obi L. Griffith Martin Krzywinski Nancy Liao Ryan Morrin

The National Institutes of Health's Mammalian Gene Collection (MGC) project was designed to generate and sequence a publicly accessible cDNA resource containing complete open reading frame (ORF) for every human mouse gene. initially used random strategy select clones from large number libraries diverse tissues. Candidate were chosen based on 5′-EST sequences, then fully sequenced high accuracy analyzed by algorithms developed this project. Currently, more than 11,000 10,000 genes are...

10.1101/gr.2596504 article EN cc-by-nc Genome Research 2004-10-15

The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations neoplastic cells harboring distinct mutations. A fine resolution view this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all which may have clinical implications. Single analysis already contributes to understanding these phenomena. However, cryptic subclones frequently revealed by additional patient samples (e.g., collected...

10.1371/journal.pcbi.1003665 article EN cc-by PLoS Computational Biology 2014-08-07

The Drug–Gene Interaction Database (DGIdb, www.dgidb.org) is a web resource that consolidates disparate data sources describing drug–gene interactions and gene druggability. It provides an intuitive graphical user interface documented application programming (API) for querying these data. DGIdb was assembled through extensive manual curation effort, reflecting the combined information of twenty-seven sources. For 2.0, substantial updates have been made to increase content improve its...

10.1093/nar/gkv1165 article EN cc-by Nucleic Acids Research 2015-11-03

Cancer immunotherapy has gained significant momentum from recent clinical successes of checkpoint blockade inhibition. Massively parallel sequence analysis suggests a connection between mutational load and response to this class therapy. Methods identify which tumor-specific mutant peptides (neoantigens) can elicit anti-tumor T cell immunity are needed improve predictions therapy targets for vaccines adoptive therapies. Here, we present flexible, streamlined computational workflow...

10.1186/s13073-016-0264-5 article EN cc-by Genome Medicine 2016-01-29

Tests that predict outcomes for patients with acute myeloid leukemia (AML) are imprecise, especially those intermediate risk AML.To determine whether genomic approaches can provide novel prognostic information adult de novo AML.Whole-genome or exome sequencing was performed on samples obtained at disease presentation from 71 AML (mean age, 50.8 years) treated standard induction chemotherapy a single site starting in March 2002, follow-up through January 2015. In addition, deep digital paired...

10.1001/jama.2015.9643 article EN JAMA 2015-08-25

Abstract Purpose: Cyclin-dependent kinase (CDK) 4/6 drives cell proliferation in estrogen receptor–positive (ER+) breast cancer. This single-arm phase II neoadjuvant trial (NeoPalAna) assessed the antiproliferative activity of CDK4/6 inhibitor palbociclib primary cancer as a prelude to adjuvant studies. Experimental Design: Eligible patients with clinical stage II/III ER+/HER2− received anastrozole 1 mg daily for 4 weeks (cycle 0; goserelin if premenopausal), followed by adding (125 on days...

10.1158/1078-0432.ccr-16-3206 article EN Clinical Cancer Research 2017-03-08

First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how various data types best be combined to yield optimal predictors. Collections cancer cell lines mirror many aspects pathobiology, and measurements their omic biological responses are well-suited development strategies identify most predictive feature sets. We used least squares-support vector machines random forest...

10.1186/gb-2013-14-10-r110 article EN cc-by Genome biology 2013-01-01

Abstract Summary: Visualizing and summarizing data from genomic studies continues to be a challenge. Here, we introduce the GenVisR package addresses this challenge by providing highly customizable, publication-quality graphics focused on cohort level genome analyses. provides rapid easy-to-use suite of visualization tools, while maintaining high degree flexibility leveraging abilities ggplot2 Bioconductor. Availability Implementation: is an R available via Bioconductor...

10.1093/bioinformatics/btw325 article EN cc-by Bioinformatics 2016-06-10

Pembrolizumab improved survival in patients with recurrent or metastatic head and neck squamous-cell carcinoma (HNSCC). The aims of this study were to determine if pembrolizumab would be safe, result pathologic tumor response (pTR), lower the relapse rate resectable human papillomavirus (HPV)-unrelated HNSCC.Neoadjuvant (200 mg) was administered followed 2 3 weeks later by surgical ablation. Postoperative (chemo)radiation planned. Patients high-risk pathology (positive margins and/or...

10.1158/1078-0432.ccr-20-1695 article EN Clinical Cancer Research 2020-07-14

Efficient tools for data management and integration are essential many aspects of high-throughput biology. In particular, annotations genes human genetic variants commonly used but highly fragmented across resources. Here, we describe MyGene.info MyVariant.info, high-performance web services querying gene variant annotation information. These currently accessed more than three million times permonth. They also demonstrate a generalizable cloud-based model organizing biological MyVariant.info...

10.1186/s13059-016-0953-9 article EN cc-by Genome biology 2016-05-06

Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design personalized cancer vaccines. This cross-disciplinary challenge, involving genomics, proteomics, immunology, computational approaches. We have built framework called pVACtools that, when paired with well-established genomics pipeline, produces an end-to-end solution for neoantigen characterization. supports identification altered peptides from different mechanisms, including...

10.1158/2326-6066.cir-19-0401 article EN Cancer Immunology Research 2020-01-06
Heidi L. Rehm Angela Page Lindsay Smith Jeremy Adams Gil Alterovitz and 95 more Lawrence Babb Maxmillian P. Barkley Michael Baudis Michael J. S. Beauvais Tim Beck J. Beckmann Sergi Beltrán David L. Bernick Alexander Bernier James Bonfield Tiffany Boughtwood Guillaume Bourque Sarion R. Bowers Anthony J. Brookes Michael Brudno Matthew Brush David Bujold Tony Burdett Orion J. Buske Moran N. Cabili Daniel Cameron Robert J. Carroll Esmeralda Casas-Silva Debyani Chakravarty Bimal P. Chaudhari Shu Hui Chen J. Michael Cherry Justina Chung Melissa Cline Hayley Clissold Robert Cook‐Deegan Mélanie Courtot Fiona Cunningham Miro Cupak Robert M. Davies Danielle Denisko Megan Doerr Lena Dolman Edward S. Dove Lewis Jonathan Dursi Stephanie O. M. Dyke James A. Eddy Karen Eilbeck Kyle Ellrott Susan Fairley Khalid A. Fakhro Helen V. Firth Michael S. Fitzsimons Marc Fiume Paul Flicek Ian Fore Mallory Freeberg Robert R. Freimuth Lauren A. Fromont Jonathan Fuerth Clara Gaff Weiniu Gan Elena M. Ghanaim David Glazer Robert C. Green Malachi Griffith Obi L. Griffith Robert L. Grossman Tudor Groza Jaime M. Guidry Auvil Roderic Guigó Dipayan Gupta Melissa Haendel Ada Hamosh David Hansen Reece K. Hart Dean M. Hartley David Haussler Rachele Hendricks‐Sturrup Calvin Wai-Loon Ho Ashley E. Hobb Michael M. Hoffman Oliver Hofmann Petr Holub Jacob Shujui Hsu Jean‐Pierre Hubaux Sarah Hunt Ammar Husami Julius O.B. Jacobsen Saumya S. Jamuar Elizabeth Janes Francis Jeanson Aina Jené Amber L. Johns Yann Joly Steven J.M. Jones Alexander Kanitz Yoshihiro Kato Thomas Keane Kristina Kekesi-Lafrance

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical genomic data through both harmonized aggregation federated approaches. decreasing cost sequencing (along with other genome-wide molecular assays) increasing evidence its utility will soon drive generation sequence from tens millions humans, levels diversity. In this perspective, we present GA4GH strategies addressing major challenges revolution. We...

10.1016/j.xgen.2021.100029 article EN cc-by-nc-nd Cell Genomics 2021-11-01
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