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T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing
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ImmunoMap: A Bioinformatics Tool for T-cell Repertoire Analysis.

John-William Sidhom1,2, Catherine A Bessell3,4, Jonathan J Havel5,6

  • 1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Cancer Immunology Research
|December 22, 2017
PubMed
Summary

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ImmunoMap, a novel phylogenetic sequencing analysis, reveals distinct T-cell receptor repertoires in self- versus foreign antigen responses and predicts immunotherapy outcomes. This method offers new insights into immune responses and guides cancer immunotherapy.

Area of Science:

  • Immunology
  • Bioinformatics
  • Computational Biology

Background:

  • T-cell receptor (TCR) sequencing generates vast data, but few methods biologically parse it for new immune response insights or to guide immunotherapy.
  • Existing TCR sequencing analyses often lack the depth to reveal clinically relevant immune signatures.

Purpose of the Study:

  • To develop and validate ImmunoMap, a novel bioinformatic method for analyzing TCR repertoire relatedness using a phylogenetics-inspired approach.
  • To assess ImmunoMap's ability to differentiate immune responses to self- versus foreign antigens and predict clinical outcomes in cancer immunotherapy.

Main Methods:

  • ImmunoMap employs a sequence analysis approach inspired by phylogenetics to examine TCR repertoire relatedness.
  • The method was applied to analyze CD8 T-cell responses to self-antigen (K b-TRP2) and foreign antigen (K b-SIY) in mice.

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  • ImmunoMap was also used to analyze TCR sequencing data from tumor-infiltrating lymphocytes in patients treated with anti-PD-1 therapy.

    • Main Results:

    • ImmunoMap analysis revealed differences in TCR repertoires between self- and foreign antigen-specific responses in mice, potentially indicating tumor immune pressure.
    • Lymphoid organ-specific differences in TCR repertoires were also detected.
    • In clinical trial data, ImmunoMap identified a predictive signature in pre- and post-therapy samples from patients receiving anti-PD-1, which standard TCR analyses did not detect.

    Conclusions:

    • ImmunoMap provides a powerful new tool for biologically parsing TCR sequencing data, offering deeper insights into immune responses.
    • The method demonstrates potential for guiding immunotherapeutic interventions by identifying predictive biomarkers.
    • ImmunoMap's ability to reveal clinically predictive signatures highlights its value in cancer immunology research and patient treatment stratification.