Abstract |
There is a lack of robust generalizable predictive biomarkers of response to immune checkpoint blockade in multiple types of cancer. We develop hDirect-MAP, an algorithm that maps T cells into a shared high-dimensional (HD) expression space of diverse T cell functional signatures in which cells group by the common T cell phenotypes rather than dimensional reduced features or a distorted view of these features. Using projection-free single-cell modeling, hDirect-MAP first removed a large group of cells that did not contribute to response and then clearly distinguished T cells into response-specific subpopulations that were defined by critical T cell functional markers of strong differential expression patterns. We found that these grouped cells cannot be distinguished by dimensional-reduction algorithms but are blended by diluted expression patterns. Moreover, these identified response-specific T cell subpopulations enabled a generalizable prediction by their HD metrics. Tested using five single-cell RNA-seq or mass cytometry datasets from basal cell carcinoma, squamous cell carcinoma and melanoma, hDirect-MAP demonstrated common response-specific T cell phenotypes that defined a generalizable and accurate predictive biomarker.
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Authors | Yong Lu, Gang Xue, Ningbo Zheng, Kun Han, Wenzhong Yang, Rui-Sheng Wang, Lingyun Wu, Lance D Miller, Timothy Pardee, Pierre L Triozzi, Hui-Wen Lo, Kounosuke Watabe, Stephen T C Wong, Boris C Pasche, Wei Zhang, Guangxu Jin |
Journal | Briefings in bioinformatics
(Brief Bioinform)
Vol. 23
Issue 2
(03 10 2022)
ISSN: 1477-4054 [Electronic] England |
PMID | 35037026
(Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
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Copyright | © The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]. |
Chemical References |
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Topics |
- Biomarkers
- Humans
- Immunotherapy
- Melanoma
(drug therapy, genetics)
- T-Lymphocytes
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