{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Wang X"],"funding":["NIDCR NIH HHS","NCI NIH HHS","U.S. Department of Health & Human Services | NIH | National Institute of Dental and Craniofacial Research (NIDCR)"],"pagination":["9968"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12615696"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(1)"],"pubmed_abstract":["Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, yet predicting patient response remains a major challenge. Carcinoma ecotypes, which capture the cancer-immune interactions, show promise as prognostic biomarkers but remain untested in real-world settings. We compile and analyze the ORIEN Avatar ICI cohort of 1610 patients with matched gene expression data from a broader dataset of 14,997 individuals. Using EcoTyper-based immunophenotyping, we define ecotypes and assess their prognostic value across cancers, with a focused analysis in melanoma. Distinct cell states and ecotypes are consistently associated with survival outcomes across cancer types. We further develop a melanoma-specific ICI predictive model and validate it using data from the phase III ECOG-ACRIN E1609"],"journal":["Nature communications"],"pubmed_title":["Multicellular immune ecotypes within solid tumors predict real-world therapeutic benefits with immune checkpoint inhibitors."],"pmcid":["PMC12615696"],"funding_grant_id":["UG1 CA233324","U10 CA180794","UG1 CA233191","UG1 CA233180","U10 CA180820","UG1 CA233184","U10 CA180821","U10 CA180888","UG1 CA233331","UG1 CA233178","P30 CA076292","R01DE030493","R01 DE030493"],"pubmed_authors":["McCarter M","Eljilany I","Ratan A","Agius P","Sukrithan V","Marin-Acevedo JA","Arnold S","Churchman M","Radmacher M","Naqash AR","Salhia B","Li T","Soupir A","Ganesan S","Rodriguez PC","Hwu P","Colman H","Dalton WS","Wang X","Weiner GJ","Puzanov I","Tarhini AA"],"additional_accession":[]},"is_claimable":false,"name":"Multicellular immune ecotypes within solid tumors predict real-world therapeutic benefits with immune checkpoint inhibitors.","description":"Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, yet predicting patient response remains a major challenge. Carcinoma ecotypes, which capture the cancer-immune interactions, show promise as prognostic biomarkers but remain untested in real-world settings. We compile and analyze the ORIEN Avatar ICI cohort of 1610 patients with matched gene expression data from a broader dataset of 14,997 individuals. Using EcoTyper-based immunophenotyping, we define ecotypes and assess their prognostic value across cancers, with a focused analysis in melanoma. Distinct cell states and ecotypes are consistently associated with survival outcomes across cancer types. We further develop a melanoma-specific ICI predictive model and validate it using data from the phase III ECOG-ACRIN E1609","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Nov","modification":"2026-06-05T12:09:32.816Z","creation":"2026-05-16T03:13:07.697Z"},"accession":"S-EPMC12615696","cross_references":{"pubmed":["41233329"],"doi":["10.1038/s41467-025-65016-3"]}}