Yonglu Che, Jinwoo Lee, Farah Abou-Taleb, Kerri E. Rieger, Ansuman T. Satpathy, Anne Lynn S. Chang, Howard Y. Chang
{"title":"Induced B cell receptor diversity predicts PD-1 blockade immunotherapy response","authors":"Yonglu Che, Jinwoo Lee, Farah Abou-Taleb, Kerri E. Rieger, Ansuman T. Satpathy, Anne Lynn S. Chang, Howard Y. Chang","doi":"10.1073/pnas.2501269122","DOIUrl":null,"url":null,"abstract":"Immune checkpoint inhibitors such as anti-Programmed Death-1 antibodies (aPD-1) can be effective in treating advanced cancers. However, many patients do not respond, and the mechanisms underlying these differences remain incompletely understood. In this study, we profile a cohort of patients with locally advanced or metastatic basal cell carcinoma undergoing aPD-1 therapy using single-cell RNA sequencing, high-definition spatial transcriptomics in tumors and draining lymph nodes, and spatial immunoreceptor profiling, with long-term clinical follow-up. We find that successful responses to PD-1 inhibition are characterized by an induction of B cell receptor (BCR) clonal diversity after treatment initiation. These induced BCR clones spatially colocalize with T cell clones, facilitate their activation, and traffic alongside them between tumor and draining lymph nodes to enhance tumor clearance. Furthermore, we validated aPD-1-induced BCR diversity as a predictor of clinical response in a larger cohort of glioblastoma, melanoma, and head and neck squamous cell carcinoma patients, suggesting that this is a generalizable predictor of treatment response across many types of cancers. We find that pretreatment tumors harbor a characteristic gene expression signature that portends a higher probability of inducing BCR clonal diversity after aPD-1 therapy, and we develop a machine learning model that predicts PD-1-induced BCR clonal diversity from baseline tumor RNA sequencing. These findings underscore a dynamic role of B cell diversity during immunotherapy, highlighting its importance as a prognostic marker and a potential target for intervention in non-responders.","PeriodicalId":20548,"journal":{"name":"Proceedings of the National Academy of Sciences of the United States of America","volume":"43 1","pages":""},"PeriodicalIF":9.4000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the National Academy of Sciences of the United States of America","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1073/pnas.2501269122","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Immune checkpoint inhibitors such as anti-Programmed Death-1 antibodies (aPD-1) can be effective in treating advanced cancers. However, many patients do not respond, and the mechanisms underlying these differences remain incompletely understood. In this study, we profile a cohort of patients with locally advanced or metastatic basal cell carcinoma undergoing aPD-1 therapy using single-cell RNA sequencing, high-definition spatial transcriptomics in tumors and draining lymph nodes, and spatial immunoreceptor profiling, with long-term clinical follow-up. We find that successful responses to PD-1 inhibition are characterized by an induction of B cell receptor (BCR) clonal diversity after treatment initiation. These induced BCR clones spatially colocalize with T cell clones, facilitate their activation, and traffic alongside them between tumor and draining lymph nodes to enhance tumor clearance. Furthermore, we validated aPD-1-induced BCR diversity as a predictor of clinical response in a larger cohort of glioblastoma, melanoma, and head and neck squamous cell carcinoma patients, suggesting that this is a generalizable predictor of treatment response across many types of cancers. We find that pretreatment tumors harbor a characteristic gene expression signature that portends a higher probability of inducing BCR clonal diversity after aPD-1 therapy, and we develop a machine learning model that predicts PD-1-induced BCR clonal diversity from baseline tumor RNA sequencing. These findings underscore a dynamic role of B cell diversity during immunotherapy, highlighting its importance as a prognostic marker and a potential target for intervention in non-responders.
期刊介绍:
The Proceedings of the National Academy of Sciences (PNAS), a peer-reviewed journal of the National Academy of Sciences (NAS), serves as an authoritative source for high-impact, original research across the biological, physical, and social sciences. With a global scope, the journal welcomes submissions from researchers worldwide, making it an inclusive platform for advancing scientific knowledge.