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Updated: Nov 17, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Tumor immunogenomic signatures improve a prognostic model of melanoma survival
Leah Morales1,2,3, Danny Simpson1,2,3, Robert Ferguson1,2,3
1Laura and Isaac Perlmutter Cancer Center, NYU Langone Health, 522 First Avenue, New York City, NY, 10016, USA.
Background:
Tumor mutation burden (TMB) has been associated with melanoma immunotherapy (IT) outcomes, including survival. We explored whether combining TMB with immunogenomic signatures recently identified by The Cancer Genome Atlas (TCGA) can refine melanoma prognostic models of overall survival (OS) in patients not treated by IT.
Methods:
Cox proportional-hazards (Cox PH) analysis was performed on 278 metastatic melanomas from TCGA not treated by IT. In a discovery and two validation cohorts Cox PH models assessed the interaction between TMB and 53 melanoma immunogenomic features to refine prediction of melanoma OS.
Results:
Interferon-γ response (IFNγRes) and macrophage regulation gene signatures (MacReg) combined with TMB significantly associated with OS (p = 8.80E-14). We observed that patients with high TMB, high IFNγRes and high MacReg had significantly better OS compared to high TMB, low IFNγRes and low MacReg (HR = 2.8, p = 3.55E-08). This association was not observed in low TMB patients.
Conclusions:
We report a model combining TMB and tumor immune features that significantly improves prediction of melanoma OS, independent of IT. Our analysis revealed that patients with high TMB, high levels of IFNγRes and MacReg had significantly more favorable OS compared to high TMB patients with low IFNγRes and low MacReg. These findings may substantially improve current melanoma prognostic models.
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