{"doi":"10.1101/2025.08.13.670223","title":"Single-cell clonal lineage tracing identifies the transcriptional program controlling the cell fate decisions by neoantigen-specific CD8 <sup>+</sup> T cells","abstract":"Abstract Neoantigen-specific T cells specifically recognize tumor cells and are critical for cancer immunotherapies. However, the transcriptional program controlling the cell fate decisions by neoantigen-specific T cells is incompletely understood. Here, using joint single-cell transcriptome and TCR profiling, we mapped the clonal expansion and differentiation of neoantigen-specific CD8 + T cells in the tumor and draining lymph node in mouse prostate cancer. Compared to other antitumor CD8 + T cells and bystanders, neoantigen-specific CD8 + tumor-infiltrating lymphocytes (TILs) upregulated gene signatures of T cell activation and exhaustion. In the tumor draining lymph node, we identified TCF1 + TOX - T SCM , TCF1 + TOX + T PEX , and TCF1 - TOX + effector-like T EX subsets among neoantigen-specific CD8 + T cells. Clonal tracing analysis of neoantigen-specific CD8 + T cells revealed greater clonal expansion in divergent clones and less expansion in clones biased towards T EX, T PEX , or T SCM . The T PEX subset had greater clonal diversity and likely represented the root of neoantigen-specific CD8 + T cell differentiation, whereas highly clonally expanded effector-like T EX cells were positioned at the branch point where neoantigen-specific clones exited the lymph node and differentiated into T EX TILs. Notably, T SCM differentiation of neoantigen-specific CD8 + clones in the lymph node negatively correlated with exhaustion and clonal expansion of the same clones in the tumor. In addition, the gene signature of neoantigen-specific clones biased toward tumor infiltration relative to lymph node residence predicted a poorer response to immune checkpoint inhibitor. Together, we identified the transcriptional program that controls the cell fate choices by neoantigen-specific CD8 + T cells and correlates with clinical outcomes in cancer patients.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":558784,"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":0.9495,"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":412055,"name":"Yao Chen","orcid":"0000-0001-5460-0149","position":1,"is_corresponding":false},{"id":623483,"name":"Tuoqi Wu","orcid":"0000-0002-4003-1034","position":2,"is_corresponding":false},{"id":1459590,"name":"Luo Ying","orcid":"0000-0002-6236-7559","position":0,"is_corresponding":true}],"reference_count":65,"raw_metadata":null,"created_at":"2026-07-19T02:55:30.312295Z","pmid":"40894735","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":[]}