{"doi":"10.1101/2024.12.03.626669","title":"Induced B-Cell Receptor Diversity Predicts PD-1 Blockade Immunotherapy Response","abstract":"Immune checkpoint inhibitors such as anti-PD-1 antibodies (aPD1) 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 co-localize with T-cell clones, facilitate their activation, and traffic alongside them between tumor and draining lymph nodes to enhance tumor clearance. Furthermore, we validated aPD1-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 discover that pre-treatment 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.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2024,"id":492526,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.956,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":235402,"name":"Jinwoo Lee","orcid":"0000-0003-2991-4183","position":1,"is_corresponding":false},{"id":1338769,"name":"Farah Abou-Taleb","orcid":"0009-0006-9125-7208","position":2,"is_corresponding":false},{"id":291898,"name":"Kerri E. Rieger","orcid":"0000-0002-4436-2471","position":3,"is_corresponding":false},{"id":21653,"name":"Ansuman T. Satpathy","orcid":"0000-0002-5167-537X","position":4,"is_corresponding":false},{"id":1338770,"name":"Anne Lynn S. Chang","orcid":"0000-0002-2869-2147","position":5,"is_corresponding":false},{"id":26,"name":"Howard Y. Chang","orcid":"0000-0002-9459-4393","position":6,"is_corresponding":false},{"id":671723,"name":"Yonglu Che","orcid":null,"position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":null,"created_at":"2026-07-19T02:08:56.210382Z","pmid":"39677742","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}