{"doi":"10.1136/jitc-2025-013120","title":"CAR-T cell therapy targeting MUC17 in gastric tumors","abstract":"BACKGROUND: Chimeric antigen receptor (CAR)-T cell therapy has achieved significant success in hematologic malignancies; however, its efficacy in solid tumors remains limited. A major limitation is the difficulty in identifying suitable target antigens that are abundantly expressed on the surface of tumor cells while sparing life-sustaining normal tissues. METHODS: We identified MUC17, a membrane-tethered mucin-type glycoprotein with minimal expression in normal tissues and frequent upregulation in gastric cancers, as a potential target for CAR-T therapy. We developed and validated MUC17-specific CAR-T cells incorporating a 4-1BB/CD3ζ signaling domain. In vitro assays assessed cytotoxicity, cytokine secretion, and T cell phenotypes across multiple gastric cancer cell lines, including CRISPR-mediated MUC17 knockout controls. In vivo efficacy was evaluated using NSG xenograft models. RESULTS: MUC17 CAR-T cells exhibited potent, antigen-specific cytotoxicity, robust cytokine release, and sustained effector functions characterized by enrichment of central memory phenotypes. In vivo, MUC17 CAR-T cells significantly suppressed tumor growth without signs of toxicity in GSU and ASPC-1 models. CONCLUSIONS: These findings support MUC17 as a promising immunotherapeutic target for gastric cancer and demonstrate how targeting glycocalyx-associated antigens can expand the range of surface proteins amenable to CAR-T cell-based therapies in solid tumors.","journal":"Journal for ImmunoTherapy of Cancer","year":2025,"id":548633,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"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":0.9631,"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":655229,"name":"Christine Ho","orcid":"0009-0007-7122-5310","position":1,"is_corresponding":false},{"id":1201287,"name":"Filippo Birocchi","orcid":"0000-0002-5214-233X","position":2,"is_corresponding":false},{"id":1022195,"name":"A Wolff","orcid":"0009-0004-4209-4129","position":3,"is_corresponding":false},{"id":12715,"name":"Amanda A. Bouffard","orcid":"0009-0003-1501-4384","position":4,"is_corresponding":false},{"id":1422484,"name":"Christopher Kelly","orcid":"0009-0006-6220-4588","position":5,"is_corresponding":false},{"id":1074893,"name":"Diego Salas‐Benito","orcid":"0000-0002-8995-1499","position":6,"is_corresponding":false},{"id":50393,"name":"Giulia Escobar","orcid":"0000-0001-9177-0251","position":7,"is_corresponding":false},{"id":715564,"name":"Adele Mucci","orcid":"0000-0003-1532-4414","position":8,"is_corresponding":false},{"id":12718,"name":"Trisha R. Berger","orcid":"0000-0003-3439-3239","position":9,"is_corresponding":false},{"id":3658,"name":"Marcela V. Maus","orcid":"0000-0002-7578-0393","position":10,"is_corresponding":false},{"id":535563,"name":"Sangwoo Park","orcid":"0000-0002-2701-3114","position":0,"is_corresponding":true}],"reference_count":53,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:53:58.530220Z","pmid":"41253489","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":[]}