{"doi":"10.1016/j.crmeth.2023.100546","title":"A topic modeling approach reveals the dynamic T cell composition of peripheral blood during cancer immunotherapy","abstract":"We present TopicFlow, a computational framework for flow cytometry data analysis of patient blood samples for the identification of functional and dynamic topics in circulating T cell population. This framework applies a Latent Dirichlet Allocation (LDA) model, adapting the concept of topic modeling in text mining to flow cytometry. To demonstrate the utility of our method, we conducted an analysis of ∼17 million T cells collected from 138 peripheral blood samples in 51 patients with melanoma undergoing treatment with immune checkpoint inhibitors (ICIs). Our study highlights three latent dynamic topics identified by LDA: a T cell exhaustion topic that independently recapitulates the previously identified LAG-3+ immunotype associated with ICI resistance, a naive topic and its association with immune-related toxicity, and a T cell activation topic that emerges upon ICI treatment. Our approach can be broadly applied to mine high-parameter flow cytometry data for insights into mechanisms of treatment response and toxicity.","journal":"Cell Reports Methods","year":2023,"id":365884,"datarank":0.29188652235829704,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"self_citation_contribution":0.29188652235829704,"citation_network_contribution":0.0,"self_endowment_contribution":0.29188652235829704,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9538,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":307245,"name":"Jasme Lee","orcid":"0009-0006-4492-4872","position":1,"is_corresponding":false},{"id":311737,"name":"Matthew Adamow","orcid":"0000-0002-7709-0126","position":2,"is_corresponding":false},{"id":853054,"name":"Colleen Maher","orcid":"0000-0003-1117-9272","position":3,"is_corresponding":false},{"id":68931,"name":"Michael A. Postow","orcid":"0000-0002-3367-7961","position":4,"is_corresponding":false},{"id":68930,"name":"Margaret K. Callahan","orcid":"0000-0002-9087-0012","position":5,"is_corresponding":false},{"id":316498,"name":"Katherine S. Panageas","orcid":"0000-0002-6591-604X","position":6,"is_corresponding":false},{"id":1900,"name":"Ronglai Shen","orcid":"0000-0001-9694-584X","position":7,"is_corresponding":false},{"id":1121746,"name":"Xiyu Peng","orcid":"0000-0003-4232-0910","position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:14:50.885797Z","pmid":"37671017","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":[]}