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Research Article

ImmunoMap: A Bioinformatics Tool for T-cell Repertoire Analysis

John-William Sidhom, Catherine A. Bessell, Jonathan J. Havel, Alyssa Kosmides, Timothy A. Chan and Jonathan P. Schneck
John-William Sidhom
1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.
2Bloomberg∼Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland.
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Catherine A. Bessell
3Graduate Program in Immunology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
4Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.
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Jonathan J. Havel
5Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York.
6Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, New York.
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Alyssa Kosmides
1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.
4Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.
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Timothy A. Chan
5Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York.
6Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, New York.
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Jonathan P. Schneck
4Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.
7Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
8Institute for Nanobiotechnology, Johns Hopkins Whiting School of Engineering, Baltimore, Maryland.
9Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
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  • For correspondence: jschnec1@jhmi.edu
DOI: 10.1158/2326-6066.CIR-17-0114
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Abstract

Despite a dramatic increase in T-cell receptor (TCR) sequencing, few approaches biologically parse the data in a fashion that both helps yield new information about immune responses and may guide immunotherapeutic interventions. To address this issue, we developed a method, ImmunoMap, that utilizes a sequence analysis approach inspired by phylogenetics to examine TCR repertoire relatedness. ImmunoMap analysis of the CD8 T-cell response to self-antigen (Kb-TRP2) or to a model foreign antigen (Kb-SIY) in naïve and tumor-bearing B6 mice showed differences in the T-cell repertoire of self- versus foreign antigen-specific responses, potentially reflecting immune pressure by the tumor, and also detected lymphoid organ–specific differences in TCR repertoires. When ImmunoMap was used to analyze clinical trial data of tumor-infiltrating lymphocytes from patients being treated with anti–PD-1, ImmunoMap, but not standard TCR sequence analyses, revealed a clinically predicative signature in pre- and posttherapy samples. Cancer Immunol Res; 6(2); 1–12. ©2017 AACR.

Footnotes

  • Note: Supplementary data for this article are available at Cancer Immunology Research Online (http://cancerimmunolres.aacrjournals.org/).

  • Received March 6, 2017.
  • Revision received September 12, 2017.
  • Accepted December 18, 2017.
  • ©2017 American Association for Cancer Research.
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This OnlineFirst version was published on January 10, 2018
doi: 10.1158/2326-6066.CIR-17-0114

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ImmunoMap: A Bioinformatics Tool for T-cell Repertoire Analysis
John-William Sidhom, Catherine A. Bessell, Jonathan J. Havel, Alyssa Kosmides, Timothy A. Chan and Jonathan P. Schneck
Cancer Immunol Res January 10 2018 DOI: 10.1158/2326-6066.CIR-17-0114

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ImmunoMap: A Bioinformatics Tool for T-cell Repertoire Analysis
John-William Sidhom, Catherine A. Bessell, Jonathan J. Havel, Alyssa Kosmides, Timothy A. Chan and Jonathan P. Schneck
Cancer Immunol Res January 10 2018 DOI: 10.1158/2326-6066.CIR-17-0114
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