摘要
Patients with high tumor mutational burden(TMB)levels do not consistently respond to immune checkpoint inhibitors(ICIs),possibly because a high TMB level does not necessarily result in adequate infiltration of CD8^(+)T cells.Using bulk ribonucleic acid sequencing(RNA-seq)data from 9311 tumor samples across 30 cancer types,we developed a novel tool called the modulator of TMB-associated immune infiltration(MOTIF),which comprises genes that can determine the extent of CD8^(+)T cell infiltration prompted by a certain TMB level.We confirmed that MOTIF can accurately reflect the integrity and defects of the cancer-immunity cycle.By analyzing 84 human single-cell RNA-seq datasets from 32 types of solid tumors,we revealed that MOTIF can provide insights into the diverse roles of various cell types in the modulation of CD8^(+)T cell infiltration.Using pretreatment RNA-seq data from 13 ICI-treated cohorts,we validated the use of MOTIF in predicting CD8^(+)T cell infiltration and ICI efficacy.Among the components of MOTIF,we identified EMC3 as a negative regulator of CD8^(+)T cell infiltration,which was validated via in vivo studies.Additionally,MOTIF provided guidance for the potential combinations of programmed death 1 blockade with certain immunostimulatory drugs to facilitate CD8^(+)T cell infiltration and improve ICI efficacy.
作者
钱政宇
潘艺芊
李薛鑫
陈衍行
吴灏祥
刘泽先
Martin Kosar
Jiri Bartek
王梓贤
徐瑞华
Zheng-Yu Qian;Yi-Qian Pan;Xue-Xin Li;Yan-Xing Chen;Hao-Xiang Wu;Ze-Xian Liu;Martin Kosar;Jiri Bartek;Zi-Xian Wang;Rui-Hua Xu(Department of Medical Oncology,Sun Yat-sen University Cancer Center,State Key Laboratory of Oncology in South China,Collaborative Innovation Center for Cancer Medicine,Guangdong Provincial Clinical Research Center for Cancer,Research Unit of Precision Diagnosis and Treatment for Gastrointestinal Cancer,Chinese Academy of Medical Sciences,Guangzhou 510060,China;Science for Life Laboratory,Division of Genome Biology,Department of Medical Biochemistry and Biophysics,Karolinska Institute,Stockholm S-17121,Sweden;Department of General Surgery,The Fourth Affiliated Hospital,China Medical University,Shenyang 110032,China;Bioinformatics Platform,Sun Yat-sen University Cancer Center,Guangzhou 510060,China;Zhejiang University-University of Edinburgh Institute,Zhejiang University School of Medicine,Haining 314400,China;Edinburgh Medical School,Biomedical Sciences,College of Medicine and Veterinary Medicine,The University of Edinburgh,Edinburgh EH11LT,UK;Danish Cancer Society Research Center,Copenhagen DK-2100,Denmark;Laboratory of Artificial Intelligence and Data Science,Sun Yat-sen University Cancer Center,Guangzhou 510060,China)
基金
supported by the National Natural Science Foundation of China(81930065,82173128,82102921,and 82003269)
the Cancer Innovation Research Program of Sun Yat-sen University Cancer Center(CIRP-SYSUCC-0004)
the Swedish Research Council(VR-MH 2014-46602-117891-30)
the CAMS Innovation Fund for Medical Sciences(CIFMS)(2019-I2M-5-036)
the Youth Teacher Cultivation Program of Sun Yat-sen University
Guangdong Provincial Clinical Medical Research Center for Malignant Tumors(84000-31660002)
the China Postdoctoral Science Foundation(2023M744049)
the Chih Kuang Scholarship for Outstanding Young Physician-Scientists of Sun Yat-sen University Cancer Center(CKS-SYSUCC-2023001)。