Open Access
Open access
Nature Communications, volume 12, issue 1, publication number 5547

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

Kimiharu Takamatsu 1
Nobuyuki Tanaka 1
Kyohei Hakozaki 1
Ryohei Takahashi* 1
Yu Teranishi 1
Tetsushi Murakami* 1
Ryohei Kufukihara* 1
Naoya Niwa 1
Shuji Mikami 2
Toshiaki Shinojima 1, 3
Takashi Sasaki 4
Yusuke Sato 5
Haruki Kume 5
Seishi Ogawa 6
Kazuhiro Kakimi 7
Takashi Kamatani 8, 9, 10
Fuyuki Miya 9
Tatsuhiko Tsunoda 8, 9, 11
Eriko Aimono 12
Hiroshi Nishihara 12
Kazuaki Sawada 13
Takeshi Imamura 14, 15
Ryuichi Mizuno 1
Mototsugu Oya 1
Show full list: 24 authors
Publication typeJournal Article
Publication date2021-09-20
scimago Q1
wos Q1
SJR4.887
CiteScore24.9
Impact factor14.7
ISSN20411723
General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy
Abstract
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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