{"doi":"10.1101/2025.05.14.654059","title":"Modeling Immunosenescence on-a-chip: a platform for cancer vaccine efficacy assessment","abstract":"Abstract Immunosenescence dramatically reduces cancer vaccine efficacy in elderly patients, who represent the majority of cancer cases. Despite this clinical reality, age-related immune decline is rarely considered in preclinical testing. Therefore, novel in vitro models to test cancer vaccine efficacy, considering immunosenescence, are needed. Our novel lymph node paracortex on-a-chip (LNPoC) platform addresses this gap by recapitulating age-dependent immune responses against cancer vaccines, specifically antigen presentation, antigen-specific T cell activation, and antitumoral responses. Using this platform, we demonstrated that bone marrow-derived antigen-presenting cells (APCs) from young mice (6-7 weeks) displayed significantly enhanced ovalbumin (OVA) peptide presentation compared to APCs from older mice (35-36 weeks). This age-dependent difference translated to significantly greater OVA-specific CD8+ T cell activation and increased cytotoxicity against B16-OVA cancer cells. These age-dependent differences are unique to our LNPoC and undetectable in traditional 2D cultures, confirming that our LNPoC was more effective than 2D cultures at recapitulating immunosenescence-mediated immune responses against cancer vaccines in vitro. The in vivo validation confirms these findings, as young mice demonstrated higher OVA-specific CD8+ T cell responses and smaller tumors than older mice. Our LNPoC is a valuable tool for assessing immunosenescence’s impact on cancer vaccines, potentially guiding more effective therapies for older adults.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":557943,"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":0.9455,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":249122,"name":"Alireza Hassani Najafabadi","orcid":"0000-0002-8215-4374","position":1,"is_corresponding":false},{"id":642198,"name":"Satoru Kawakita","orcid":"0000-0002-3781-5786","position":2,"is_corresponding":false},{"id":1025879,"name":"Danial Khorsandi","orcid":"0000-0002-5245-5555","position":3,"is_corresponding":false},{"id":1070753,"name":"Can Yilgor","orcid":"0009-0000-9214-4324","position":4,"is_corresponding":false},{"id":232584,"name":"Christopher M. Jewell","orcid":"0000-0002-6668-6928","position":5,"is_corresponding":false},{"id":958855,"name":"Neda Mohaghegh","orcid":"0000-0002-2796-4315","position":6,"is_corresponding":false},{"id":241791,"name":"Mehmet R. Dokmeci","orcid":"0000-0003-2226-9441","position":7,"is_corresponding":false},{"id":230339,"name":"Ali Khademhosseini","orcid":"0000-0002-2692-1524","position":8,"is_corresponding":false},{"id":642200,"name":"Vadim Jucaud","orcid":"0000-0003-0385-2623","position":9,"is_corresponding":false},{"id":851278,"name":"Surjendu Maity","orcid":"0000-0003-0190-248X","position":0,"is_corresponding":true}],"reference_count":112,"raw_metadata":null,"created_at":"2026-07-19T02:55:21.727661Z","pmid":null,"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":[]}