Induced B cell receptor diversity predicts PD-1 blockade immunotherapy response

• 成果类型: Article
• 署名作者: Che, Yonglu; Lee, Jinwoo; Abou-Taleb, Farah; Rieger, Kerri E.; Satpathy, Ansuman T.; Chang, Anne Lynn S.; Chang, Howard Y.
• 署名单位: Stanford University; Stanford University; Stanford University; Howard Hughes Medical Institute; Stanford University
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-12230
• DOI: 10.1073/pnas.2501269122
• 发表日期: 2025-05-06
• 关键词: t-cells; cancer; survival

摘要

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.