hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy

doi:10.1093/bib/bbab575

CSpace > 应用数学研究所

	hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy
	Lu, Yong 4,5; Xue, Gang 4; Zheng, Ningbo 4; Han, Kun 4; Yang, Wenzhong 6; Wang, Rui-Sheng 7; Wu, Lingyun8 ; Miller, Lance D.1; Pardee, Timothy 9; Triozzi, Pierre L.9; Lo, Hui-Wen 1; Watabe, Kounosuke 1; Wong, Stephen T. C.10,11; Pasche, Boris C.1; Zhang, Wei 1; Jin, Guangxu 1,2,3
	2022-03-10
发表期刊	BRIEFINGS IN BIOINFORMATICS
ISSN	1467-5463
卷号	23 期号:2 页码:16
摘要	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.
关键词	single-cell RNA sequencing (scRNA-seq) single-cell mass cytometry (CyTOF) Pareto optimization projection-free single-cell modeling response to immune checkpoint blockade
DOI	10.1093/bib/bbab575
收录类别	SCI
语种	英语
资助项目	National Cancer Institute[K99CA190910] ; National Cancer Institute[4R00CA190910-03] ; Wake Forest start-up funds ; National Foundation for Cancer Research ; National Center for Advancing Translational Sciences of the National Institutes of Health[UL1TR001420] ; Endowed Hanes and Willis Family Professor in Cancer at the Wake Forest Baptist Comprehensive Cancer Center
WOS研究方向	Biochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS类目	Biochemical Research Methods ; Mathematical & Computational Biology
WOS记录号	WOS:000804196500059
出版者	OXFORD UNIV PRESS
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/61536
专题	应用数学研究所
通讯作者	Lu, Yong; Zhang, Wei; Jin, Guangxu
作者单位	1.Wake Forest Sch Med, Dept Canc Biol, 1 Med Ctr Blvd, Winston Salem, NC 27157 USA 2.Wake Forest Baptist Comprehens Canc Ctr WFBCCC, Bioinformat Shared Resource BISR, Winston Salem, NC USA 3.Wake Forest Sch Med, Ctr Precis Med, Winston Salem, NC 27101 USA 4.Wake Forest Sch Med, Dept Microbiol & Immunol, Winston Salem, NC 27101 USA 5.Houston Methodist Hosp, Canc Ctr, Weill Cornell Med, Houston, TX 77030 USA 6.Wake Forest Sch Med, Dept Internal Med, Winston Salem, NC 27101 USA 7.Harvard Med Sch, Dept Med, Brigham & Womens Hosp, Boston, MA 02115 USA 8.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 9.Wake Forest Baptist Med Ctr, Sect Hemtol & Oncol, Dept Internal Med, Winston Salem, NC USA 10.Houston Methodist Hosp, Weill Cornell Med, Dept Pathol, Houston, TX 77030 USA 11.Houston Methodist Hosp, Weill Cornell Med, Dept Genome Med, Houston, TX 77030 USA
推荐引用方式 GB/T 7714	Lu, Yong,Xue, Gang,Zheng, Ningbo,et al. hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy[J]. BRIEFINGS IN BIOINFORMATICS,2022,23(2):16.
APA	Lu, Yong.,Xue, Gang.,Zheng, Ningbo.,Han, Kun.,Yang, Wenzhong.,...&Jin, Guangxu.(2022).hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy.BRIEFINGS IN BIOINFORMATICS,23(2),16.
MLA	Lu, Yong,et al."hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy".BRIEFINGS IN BIOINFORMATICS 23.2(2022):16.