publication . Article . Other literature type . 2016

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

Hundal, Jasreet; Carreno, Beatriz M.; Petti, Allegra A.; Linette, Gerald P.; Griffith, Obi L.; Mardis, Elaine R.; Griffith, Malachi;
Open Access English
  • Published: 29 Jan 2016 Journal: Genome Medicine, volume 8 (eissn: 1756-994X, Copyright policy)
  • Publisher: BioMed Central
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 and expr...
Subjects
free text keywords: Method, Genetics(clinical), Molecular Medicine, Genetics, Molecular Biology
Funded by
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
,
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
49 references, page 1 of 4

Boon, T, Cerottini, J-C, Van den Eynde, B, van der Bruggen, P, Van Pel, A. Tumor antigens recognized by T lymphocytes. Annu Rev Immunol. 1994; 12 (1): 337-65 [PubMed] [DOI]

Trajanoski, Z, Maccalli, C, Mennonna, D, Casorati, G, Parmiani, G, Dellabona, P. Somatically mutated tumor antigens in the quest for a more efficacious patient-oriented immunotherapy of cancer. Cancer Immunol Immunother. 2015; 64 (1): 99-104 [OpenAIRE] [PubMed] [DOI]

Matsushita, H, Vesely, MD, Koboldt, DC, Rickert, CG, Uppaluri, R, Magrini, VJ. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature. 2012; 482 (7385): 400-4 [OpenAIRE] [PubMed] [DOI]

Gubin, MM, Zhang, X, Schuster, H, Caron, E, Ward, JP, Noguchi, T. Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature. 2014; 515 (7528): 577-81 [OpenAIRE] [PubMed] [DOI]

Castle, JC, Kreiter, S, Diekmann, J, Lower, M, van de Roemer, N, de Graaf, J. Exploiting the mutanome for tumor vaccination. Cancer Res. 2012; 72 (5): 1081-91 [OpenAIRE] [PubMed] [DOI]

van Rooij, N, van Buuren, MM, Philips, D, Velds, A, Toebes, M, Heemskerk, B. Tumor exome analysis reveals neoantigen-specific T cell reactivity in an ipilimumab-responsive melanoma. J Clin Oncol. 2013; 31 (32): e439-442 [OpenAIRE] [PubMed] [DOI]

Robbins, PF, Lu, YC, El-Gamil, M, Li, YF, Gross, C, Gartner, J. Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells. Nat Med. 2013; 19 (6): 747-52 [OpenAIRE] [PubMed] [DOI]

Rajasagi, M, Shukla, SA, Fritsch, EF, Keskin, DB, DeLuca, D, Carmona, E. Systematic identification of personal tumor-specific neoantigens in chronic lymphocytic leukemia. Blood. 2014; 124 (3): 453-62 [OpenAIRE] [PubMed] [DOI]

Linnemann, C, van Buuren, MM, Bies, L, Verdegaal, EM, Schotte, R, Calis, JJ. High-throughput epitope discovery reveals frequent recognition of neo-antigens by CD4+ T cells in human melanoma. Nat Med. 2015; 21 (1): 81-5 [OpenAIRE] [PubMed] [DOI]

Houghton, AN, Guevara-Patiño, J. Immune recognition of self in immunity against cancer. J Clin Invest. 2004; 114 (4): 468-71 [OpenAIRE] [PubMed] [DOI]

Reche, PA, Glutting, JP, Reinherz, EL. Prediction of MHC class I binding peptides using profile motifs. Hum Immunol. 2002; 63 (9): 701-9 [OpenAIRE] [PubMed] [DOI]

Bhasin, M, Raghava, G. A hybrid approach for predicting promiscuous MHC class I restricted T cell epitopes. J Biosci. 2006; 1 (32): 31-42

13.Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11. Nucleic Acids Res. 2008;36(Web Server issue):W509–512.

Nielsen, M, Lundegaard, C, Worning, P, Lauemoller, SL, Lamberth, K, Buus, S. Reliable prediction of T cell epitopes using neural networks with novel sequence representations. Protein Sci. 2003; 12 (5): 1007-17 [OpenAIRE] [PubMed] [DOI]

Soria-Guerra, RE, Nieto-Gomez, R, Govea-Alonso, DO, Rosales-Mendoza, S. An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J Biomed Inform. 2015; 53: 405-14 [OpenAIRE] [PubMed] [DOI]

49 references, page 1 of 4
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 and expr...
Subjects
free text keywords: Method, Genetics(clinical), Molecular Medicine, Genetics, Molecular Biology
Funded by
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
,
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
49 references, page 1 of 4

Boon, T, Cerottini, J-C, Van den Eynde, B, van der Bruggen, P, Van Pel, A. Tumor antigens recognized by T lymphocytes. Annu Rev Immunol. 1994; 12 (1): 337-65 [PubMed] [DOI]

Trajanoski, Z, Maccalli, C, Mennonna, D, Casorati, G, Parmiani, G, Dellabona, P. Somatically mutated tumor antigens in the quest for a more efficacious patient-oriented immunotherapy of cancer. Cancer Immunol Immunother. 2015; 64 (1): 99-104 [OpenAIRE] [PubMed] [DOI]

Matsushita, H, Vesely, MD, Koboldt, DC, Rickert, CG, Uppaluri, R, Magrini, VJ. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature. 2012; 482 (7385): 400-4 [OpenAIRE] [PubMed] [DOI]

Gubin, MM, Zhang, X, Schuster, H, Caron, E, Ward, JP, Noguchi, T. Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature. 2014; 515 (7528): 577-81 [OpenAIRE] [PubMed] [DOI]

Castle, JC, Kreiter, S, Diekmann, J, Lower, M, van de Roemer, N, de Graaf, J. Exploiting the mutanome for tumor vaccination. Cancer Res. 2012; 72 (5): 1081-91 [OpenAIRE] [PubMed] [DOI]

van Rooij, N, van Buuren, MM, Philips, D, Velds, A, Toebes, M, Heemskerk, B. Tumor exome analysis reveals neoantigen-specific T cell reactivity in an ipilimumab-responsive melanoma. J Clin Oncol. 2013; 31 (32): e439-442 [OpenAIRE] [PubMed] [DOI]

Robbins, PF, Lu, YC, El-Gamil, M, Li, YF, Gross, C, Gartner, J. Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells. Nat Med. 2013; 19 (6): 747-52 [OpenAIRE] [PubMed] [DOI]

Rajasagi, M, Shukla, SA, Fritsch, EF, Keskin, DB, DeLuca, D, Carmona, E. Systematic identification of personal tumor-specific neoantigens in chronic lymphocytic leukemia. Blood. 2014; 124 (3): 453-62 [OpenAIRE] [PubMed] [DOI]

Linnemann, C, van Buuren, MM, Bies, L, Verdegaal, EM, Schotte, R, Calis, JJ. High-throughput epitope discovery reveals frequent recognition of neo-antigens by CD4+ T cells in human melanoma. Nat Med. 2015; 21 (1): 81-5 [OpenAIRE] [PubMed] [DOI]

Houghton, AN, Guevara-Patiño, J. Immune recognition of self in immunity against cancer. J Clin Invest. 2004; 114 (4): 468-71 [OpenAIRE] [PubMed] [DOI]

Reche, PA, Glutting, JP, Reinherz, EL. Prediction of MHC class I binding peptides using profile motifs. Hum Immunol. 2002; 63 (9): 701-9 [OpenAIRE] [PubMed] [DOI]

Bhasin, M, Raghava, G. A hybrid approach for predicting promiscuous MHC class I restricted T cell epitopes. J Biosci. 2006; 1 (32): 31-42

13.Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11. Nucleic Acids Res. 2008;36(Web Server issue):W509–512.

Nielsen, M, Lundegaard, C, Worning, P, Lauemoller, SL, Lamberth, K, Buus, S. Reliable prediction of T cell epitopes using neural networks with novel sequence representations. Protein Sci. 2003; 12 (5): 1007-17 [OpenAIRE] [PubMed] [DOI]

Soria-Guerra, RE, Nieto-Gomez, R, Govea-Alonso, DO, Rosales-Mendoza, S. An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J Biomed Inform. 2015; 53: 405-14 [OpenAIRE] [PubMed] [DOI]

49 references, page 1 of 4
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