{"doi":"10.1038/s41598-022-06830-3","title":"Identification of genomic signatures in bone marrow associated with clinical response of CD19 CAR T-cell therapy","abstract":"CD19 CAR T-cell immunotherapy is a breakthrough treatment for B cell malignancies, but relapse and lack of response remain a challenge. The bone marrow microenvironment is a key factor in therapy resistance, however, little research has been reported concerning the relationship between transcriptomic profile of bone marrow prior to lymphodepleting preconditioning and clinical response following CD19 CAR T-cell therapy. Here, we applied comprehensive bioinformatic methods (PCA, GO, GSEA, GSVA, PAM-tools) to identify clinical CD19 CAR T-cell remission-related genomic signatures. In patients achieving a complete response (CR) transcriptomic profiles of bone marrow prior to lymphodepletion showed genes mainly involved in T cell activation. The bone marrow of CR patients also showed a higher activity in early T cell function, chemokine, and interleukin signaling pathways. However, non-responding patients showed higher activity in cell cycle checkpoint pathways. In addition, a 14-gene signature was identified as a remission-marker. Our study indicated the indexes of the bone marrow microenvironment have a close relationship with clinical remission. Enhancing T cell activation pathways (chemokine, interleukin, etc.) in the bone marrow before CAR T-cell infusion may create a pro-inflammatory environment which improves the efficacy of CAR T-cell therapy.","journal":"Scientific Reports","year":2022,"id":289801,"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":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9496,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":971859,"name":"Avinash Iyer","orcid":null,"position":1,"is_corresponding":false},{"id":492481,"name":"Yingdong Zhao","orcid":"0000-0002-8514-0293","position":2,"is_corresponding":false},{"id":956532,"name":"R.P. Somerville","orcid":null,"position":3,"is_corresponding":false},{"id":314286,"name":"Sandhya R. Panch","orcid":"0000-0002-7814-9150","position":4,"is_corresponding":false},{"id":865240,"name":"Alejandra Pelayo","orcid":null,"position":5,"is_corresponding":false},{"id":233604,"name":"David F. Stroncek","orcid":"0000-0001-5867-3265","position":6,"is_corresponding":false},{"id":467695,"name":"Ping Jin","orcid":"0000-0002-3479-7607","position":7,"is_corresponding":false},{"id":467691,"name":"Lipei Shao","orcid":"0000-0003-3009-7096","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":null,"created_at":"2026-07-19T00:30:22.686776Z","pmid":"35181722","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":[]}