Molecular signatures of antitumor neoantigen-reactive T cells from metastatic human cancers

Frank J Lowery1, Sri Krishna1, Rami Yossef1

  • 1Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.

Science (New York, N.Y.)
|February 3, 2022
PubMed

Insights

Identifying tumor-specific T cell receptors (TCRs) is crucial for cancer immunotherapy. This study reveals TCR signatures in tumor-infiltrating lymphocytes (TILs) that can predict TCR function, advancing cell-based cancer treatments.

Area of Science:

  • Immunology
  • Oncology
  • Genomics

Background:

  • Accurate identification of antitumor T cell receptors (TCRs) is a significant hurdle in developing effective cell-based cancer immunotherapies.
  • Tumor-infiltrating lymphocytes (TILs) play a critical role in anti-tumor immunity, but their specific TCRs are challenging to pinpoint.

Purpose of the Study:

  • To identify and characterize neoantigen-specific TCR clonotypes (NeoTCRs) from metastatic tumors.
  • To establish predictive signatures of neoantigen-reactive TILs based on transcriptomic data.
  • To assess the potential of these signatures for engineering cancer immunotherapies.

Main Methods:

  • Single-cell transcriptomic analysis of 55 NeoTCRs from 10 metastatic human tumors.
  • Mapping TCR clonotypes to their corresponding TIL transcriptomes to identify CD8+ and CD4+ neoantigen-reactive TILs.
  • Prospective prediction and validation of NeoTCR signatures.

Main Results:

  • Identified distinct transcriptomic signatures for CD8+ and CD4+ neoantigen-reactive TILs.
  • Neoantigen-specific TILs showed tumor-specific expansion and dysfunctional phenotypes.
  • NeoTCR signatures successfully predicted TCRs recognizing tumor antigens and autologous tumors.
  • Discovered that NeoTCR signatures target driver neoantigens and other tumor antigens, indicating a common TIL exhaustion program.

Conclusions:

  • NeoTCR signatures provide a comprehensive map of TILs in metastatic tumors.
  • Transcriptomic states of TILs can enable accurate TCR prediction for cancer immunotherapy.
  • This approach facilitates the engineering of cell-based therapies by identifying functional TCRs.