research data . Dataset . 2016

pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens

Jasreet Hundal; Carreno, Beatriz; Petti, Allegra; Linette, Gerald; Obi Griffith; Mardis, Elaine; Griffith, Malachi;
  • Published: 15 Dec 2016
  • Publisher: Figshare
Abstract
Abstract 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 of therapy. Methods to identify which tumor-specific mutant peptides (neoantigens) can elicit anti-tumor T cell immunity are needed to improve predictions of checkpoint therapy response and to identify targets for vaccines and adoptive T cell therapies. Here, we present a flexible, streamlined computational workflow for identification of personalized Variant Antigens by Cancer Sequencing (pVAC-Seq) that integrates tumor mutation...
Subjects
Medical Subject Headings: natural sciencesgenetic processes
free text keywords: Medicine, Genetics, Immunology, 69999 Biological Sciences not elsewhere classified, 80699 Information Systems not elsewhere classified, 19999 Mathematical Sciences not elsewhere classified, Cancer, FOS: Biological sciences, FOS: Clinical medicine, FOS: Computer and information sciences, FOS: Mathematics
Funded by
NIH| SOMATIC NON-SYNONYMOUS MUTATIONS AS UNIQUE TUMOR ANTIGENS IN MELANOMA
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R21CA179695-02
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Large Scale Genome Sequencing
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 3U54HG003079-03S1
  • Funding stream: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
,
NIH| DEFINING THE REGULATORY, NON-CODING, MUTATIONAL LANDSCAPE OF BREAST CANCER
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1K22CA188163-01
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| INTEGRATED ANALYSIS & INTERPRETATION OF WHOLE GENOME, EXOME & TRANSCRIPTOME SEQUENCE DATA IN CANCER
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5K99HG007940-02
  • Funding stream: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
Download from
figshare
Dataset . 2016
Provider: Datacite
Abstract
Abstract 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 of therapy. Methods to identify which tumor-specific mutant peptides (neoantigens) can elicit anti-tumor T cell immunity are needed to improve predictions of checkpoint therapy response and to identify targets for vaccines and adoptive T cell therapies. Here, we present a flexible, streamlined computational workflow for identification of personalized Variant Antigens by Cancer Sequencing (pVAC-Seq) that integrates tumor mutation...
Subjects
Medical Subject Headings: natural sciencesgenetic processes
free text keywords: Medicine, Genetics, Immunology, 69999 Biological Sciences not elsewhere classified, 80699 Information Systems not elsewhere classified, 19999 Mathematical Sciences not elsewhere classified, Cancer, FOS: Biological sciences, FOS: Clinical medicine, FOS: Computer and information sciences, FOS: Mathematics
Funded by
NIH| SOMATIC NON-SYNONYMOUS MUTATIONS AS UNIQUE TUMOR ANTIGENS IN MELANOMA
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R21CA179695-02
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Large Scale Genome Sequencing
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 3U54HG003079-03S1
  • Funding stream: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
,
NIH| DEFINING THE REGULATORY, NON-CODING, MUTATIONAL LANDSCAPE OF BREAST CANCER
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1K22CA188163-01
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| INTEGRATED ANALYSIS & INTERPRETATION OF WHOLE GENOME, EXOME & TRANSCRIPTOME SEQUENCE DATA IN CANCER
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5K99HG007940-02
  • Funding stream: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
Download from
figshare
Dataset . 2016
Provider: Datacite
Any information missing or wrong?Report an Issue