Fig. 5: Prediction of ICI response using the neoantigen landscape model. | Nature Communications

Fig. 5: Prediction of ICI response using the neoantigen landscape model.

From: NeoPrecis: enhancing immunotherapy response prediction through integration of qualified immunogenicity and clonality-aware neoantigen landscapes

Fig. 5: Prediction of ICI response using the neoantigen landscape model.

a Criteria for patient inclusion in the analysis. b Hazard ratio of metrics related to allele benefit scores derived from the Cox proportional hazards model with sex and age as confounders. Overall survival (OS) is used for melanoma (n = 276 patients), while progression-free survival (PFS) is used for NSCLC (n = 245). “Dual” is the metric considering both MHC-I and MHC-II. “CombinedScore” is the product of “logTMB” and “BenefitScore-dual”. Data are presented as the estimated Hazard Ratio (center dot) and 95% confidence interval (error bars). c Cliff’s Delta effect sizes comparing the impact of different mutation burdens on ICI response, including tumor mutation burden (TMB), tumor neoantigen burden (TNB), and NeoPrecis-Immuno burden (NPB), for melanoma (n = 277; #positives = 98) and NSCLC (n = 248; #positives = 97). d AUROC comparison of ICI response prediction using TMB, TNB, and NeoPrecis-LandscapeSum (NP-Sum) in melanoma and NSCLC. e Kaplan-Meier survival curves stratified by NP-LandscapeSum, with log-rank P-values for melanoma (OS) and NSCLC (PFS). “Top” refers to the top half of patients with higher NP-LandscapeSum scores, while “bot” refers to the bottom half of patients with lower NP-LandscapeSum scores. Shaded areas indicate the 95% confidence interval. NP denotes NeoPrecis.

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