{"doi":"10.1038/s41467-024-54569-4","title":"Human single cell RNA-sequencing reveals a targetable CD8+ exhausted T cell population that maintains mouse low-grade glioma growth","abstract":"In solid cancers, T cells typically function as cytotoxic effectors to limit tumor growth, prompting therapies that capitalize upon this antineoplastic property (immune checkpoint inhibition; ICI). Unfortunately, ICI treatments have been largely ineffective for high-grade brain tumors (gliomas; HGGs). Leveraging several single-cell RNA sequencing datasets, we report greater CD8+ exhausted T cells in human pediatric low-grade gliomas (LGGs) relative to adult and pediatric HGGs. Using several preclinical mouse LGG models (Nf1-OPG mice), we show that these PD1+/TIGIT+ CD8+ exhausted T cells are restricted to the tumor tissue, where they express paracrine factors necessary for OPG growth. Importantly, ICI treatments with α-PD1 and α-TIGIT antibodies attenuate Nf1-OPG tumor proliferation through suppression of two cytokine (Ccl4 and TGFβ)-mediated mechanisms, rather than by T cell-mediated cytotoxicity, as well as suppress monocyte-controlled T cell chemotaxis. Collectively, these findings establish a previously unrecognized function for CD8+ exhausted T cells as specialized regulators of LGG maintenance. With the emergence of immune checkpoint inhibitor therapies for cancer, the authors use single-cell sequencing to assess exhausted T cell content in human glioma samples and leverage these findings in mouse models to define the mechanisms by which exhausted T cells regulate low-grade glioma growth.","journal":"Nature Communications","year":2024,"id":425802,"datarank":0.5452366530315705,"base_score":2.995732273553991,"endowment":2.995732273553991,"self_citation_contribution":0.4493598410330987,"citation_network_contribution":0.09587681199847185,"self_endowment_contribution":0.4493598410330987,"citer_contribution":0.09587681199847185,"corpus_percentile":null,"corpus_rank":null,"citation_count":19,"citer_count":15,"citers_with_citation_signal":7,"citers_with_endowment":7,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9344,"is_data_producer":true,"deposit_databanks":{"GEO":["GSE244433","GSE222850","GSE102130","GSE138794"]},"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":663297,"name":"Jit Chatterjee","orcid":"0000-0002-2444-9748","position":1,"is_corresponding":false},{"id":1224076,"name":"Rui Mu","orcid":"0009-0005-4221-4159","position":2,"is_corresponding":false},{"id":1224611,"name":"Xuanhe Qi","orcid":null,"position":3,"is_corresponding":false},{"id":255604,"name":"Xingxing Gu","orcid":"0000-0001-8202-189X","position":4,"is_corresponding":false},{"id":232061,"name":"Igor Smirnov","orcid":"0000-0003-2373-6742","position":5,"is_corresponding":false},{"id":309691,"name":"Olivia Cobb","orcid":null,"position":6,"is_corresponding":false},{"id":1224612,"name":"Karen Gao","orcid":null,"position":7,"is_corresponding":false},{"id":1224613,"name":"Angelica Barnes","orcid":null,"position":8,"is_corresponding":false},{"id":109378,"name":"Jonathan Kipnis","orcid":"0000-0002-3714-517X","position":9,"is_corresponding":false},{"id":295596,"name":"David H. Gutmann","orcid":"0000-0002-3127-5045","position":10,"is_corresponding":false},{"id":1224075,"name":"Rasha Barakat","orcid":"0000-0003-2371-9109","position":0,"is_corresponding":true}],"reference_count":73,"raw_metadata":null,"created_at":"2026-07-19T01:58:32.160975Z","pmid":"39609412","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":[]}