{"doi":"10.1101/2023.03.29.534765","title":"High-Dimensional Spectral Cytometry Reveals Therapeutically Relevant Immune Subtypes in Gastric Cancer","abstract":"Summary Identification of locally advanced gastric cancer (GC) patients who might potentially benefit from immune-based strategies is limited by both the poor predictive quality of existing biomarkers, including molecular subtypes, tumor mutational burden, and PD-L1 expression, as well as inadequate understanding of the gastric cancer immune microenvironment. Here, we leveraged high-dimensional spectral cytometry to re-classify locally advanced gastric tumors based on immune composition. The gastric cancer microenvironment was comprised of a diverse immune infiltrate including high proportions of plasmablasts, macrophages, and myeloid-derived suppressor cells. Computational cell typing and sample clustering based on tiered broad immune and T-cell focused phenotyping identified three distinct immune subtypes. The most immunogenic subtype exhibited high proportions of activated CD4+ T-cells and plasmablasts and included tumors that would have been classified as non-immunogenic based on prior classifications. Analysis of gastric cancer patients treated with immune checkpoint blockade indicates that patients who responded to immunotherapy had a pre-treatment tumor composition that corresponded to higher immune scores from our analysis. This work establishes a novel immunological classification of gastric cancer including identification of patients and immune networks likely to benefit from immune-based therapies.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":406110,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9488,"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":457319,"name":"Teng Fei","orcid":"0000-0001-7888-1715","position":1,"is_corresponding":false},{"id":1185093,"name":"Ya Hui Lin","orcid":null,"position":2,"is_corresponding":false},{"id":1180312,"name":"Shoji Shimada","orcid":null,"position":3,"is_corresponding":false},{"id":645607,"name":"Harrison Drebin","orcid":null,"position":4,"is_corresponding":false},{"id":640981,"name":"Eunise Chen","orcid":"0009-0005-2203-8258","position":5,"is_corresponding":false},{"id":250490,"name":"Laura H. Tang","orcid":"0000-0001-5735-9354","position":6,"is_corresponding":false},{"id":533606,"name":"Vivian E. Strong","orcid":"0000-0001-5044-1662","position":7,"is_corresponding":false},{"id":78951,"name":"Santosha A. Vardhana","orcid":"0000-0002-3100-1298","position":8,"is_corresponding":false},{"id":1082667,"name":"Miseker Abate","orcid":"0000-0001-5060-1208","position":0,"is_corresponding":true}],"reference_count":53,"raw_metadata":null,"created_at":"2026-07-19T01:20:59.152593Z","pmid":null,"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":[]}