4.8 Article

Profiling the inhibitory receptors LAG-3, TIM-3, and TIGIT in renal cell carcinoma reveals malignancy

Journal

NATURE COMMUNICATIONS
Volume 12, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-021-25865-0

Keywords

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Funding

  1. Takeda Science Foundation
  2. Kobayashi Foundation for Cancer Research
  3. SGH Cancer Research Grant
  4. Keio Gijuku Academic Development Funds
  5. [KAKENHI 19K16807]
  6. [18H04906]
  7. [18K19482]
  8. [19H03792]
  9. [18K09150]
  10. [18H02939]

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Targeting inhibitory receptors (IRs) LAG-3, TIM-3, and TIGIT in immunotherapy for human renal cell carcinoma is promising, with individual IR levels serving as potential biomarkers for analysis. The immunogenomic landscape of the disease can be investigated through automated single-cell counting for these IRs.
A cutting edge therapy for future immuno-oncology is targeting a new series of inhibitory receptors (IRs): LAG-3, TIM-3, and TIGIT. Both immunogenomic analyses and diagnostic platforms to distinguish candidates and predict good responders to these IR-related agents are vital in clinical pathology. By applying an automated single-cell count for immunolabelled LAG-3, TIM-3, and TIGIT, we reveal that individual IR levels with exclusive domination in each tumour can serve as valid biomarkers for profiling human renal cell carcinoma (RCC). We uncover the immunogenomic landscape associated with individual IR levels in human RCC tumours with metastases in various organs and histological subtypes. We then externally validate our results and devise a workflow with optimal biomarker cut-offs for discriminating the LAG-3, TIM-3, and TIGIT tumour profiles. The discrimination of LAG-3, TIM-3, and TIGIT profiles in tumours may have a broad impact on investigations of immunotherapy responses after targeting a new series of IRs. Targeting the inhibitory receptors (IRs) LAG-3, TIM-3 and TIGIT is a promising immune-oncology approach and the identification of biomarkers of response is crucial. Here, the authors apply automated single-cell count for these IRs in human renal cell carcinoma and investigate the immunogenomic landscape of the disease.

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