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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月13日

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  • 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,
  • Ahmad A. Tarhini

摘要

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.