Multicellular immune ecotypes within solid tumors predict real-world therapeutic benefits with immune checkpoint inhibitors

Xuefeng Wang (), Tingyi Li, Islam Eljilany, Alex Soupir, Michael Radmacher, Phaedra Agius, Vineeth Sukrithan, Aakrosh Ratan, Martin McCarter, Bodour Salhia, Howard Colman, Abdul R. Naqash, Igor Puzanov, Susanne Arnold, Julian A. Marin-Acevedo, Shridar Ganesan, Michelle Churchman, Patrick Hwu, Paulo C. Rodriguez, William S. Dalton, George J. Weiner and Ahmad A. Tarhini ()
Additional contact information
Xuefeng Wang: H. Lee Moffitt Cancer Center and Research Institute
Tingyi Li: H. Lee Moffitt Cancer Center and Research Institute
Islam Eljilany: H. Lee Moffitt Cancer Center and Research Institute
Alex Soupir: H. Lee Moffitt Cancer Center and Research Institute
Michael Radmacher: Aster Insights
Phaedra Agius: Aster Insights
Vineeth Sukrithan: Ohio State University and Arthur G James Comprehensive Cancer Center
Aakrosh Ratan: University of Virginia
Martin McCarter: University of Colorado Cancer Center
Bodour Salhia: University of Southern California
Howard Colman: University of Utah
Abdul R. Naqash: University of Oklahoma Health Sciences Center
Igor Puzanov: Roswell Park Comprehensive Cancer Center
Susanne Arnold: University of Kentucky Markey Cancer Center
Julian A. Marin-Acevedo: Indiana University Melvin and Bren Simon Comprehensive Cancer Center
Shridar Ganesan: Robert Wood Johnson Medical School
Michelle Churchman: Aster Insights
Patrick Hwu: H. Lee Moffitt Cancer Center and Research Institute
Paulo C. Rodriguez: H. Lee Moffitt Cancer Center and Research Institute
William S. Dalton: Aster Insights
George J. Weiner: University of Iowa Health Care
Ahmad A. Tarhini: H. Lee Moffitt Cancer Center and Research Institute

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: 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 trial as well as in external harmonized melanoma datasets. Together, these findings establish an ecotype-based framework and provide real-world evidence for their translational utility as clinically actionable biomarkers with prognostic and predictive value to guide ICI therapy.

Date: 2025
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DOI: 10.1038/s41467-025-65016-3

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