免疫疗法已成为最有前途的癌症治疗方法之一，但只有少数患者对其有反应，这表明迫切需要更有效的生物标志物。这项研究开发了一种名为 PathwayTMB 的通路分析方法，用于识别基因组突变通路，作为预测免疫治疗临床结果的潜在生物标志物。 PathwayTMB 首先计算患者特定的基于通路的肿瘤突变负荷 (PTMB)，以反映每个通路的累积突变程度。然后，它筛选突变的生存获益相关途径，以构建基于 PTMB (IPSP) 的免疫相关预后特征。在黑色素瘤训练集中，IPSP 高的患者比 IPSP 低的患者表现出更长的总生存期和更高的缓解率。此外，与TMB相比，IPSP显示出更优异的预测效果。此外，IPSP 的预后和预测价值在两个独立的验证集中得到了一致的验证。最后，在多癌症数据集中，PathwayTMB 也表现出了良好的性能。我们的结果表明 PathwayTMB 可以识别预测免疫治疗生存的突变途径，它们的组合可以作为免疫检查点抑制剂治疗的潜在预测生物标志物。© 2023 作者。

Immunotherapy has become one of the most promising therapy methods for cancer, but only a small number of patients are responsive to it, indicating that more effective biomarkers are urgently needed. This study developed a pathway analysis method, named PathwayTMB, to identify genomic mutation pathways that serve as potential biomarkers for predicting the clinical outcome of immunotherapy. PathwayTMB first calculates the patient-specific pathway-based tumor mutational burden (PTMB) to reflect the cumulative extent of mutations for each pathway. It then screens mutated survival benefit-related pathways to construct an immune-related prognostic signature based on PTMB (IPSP). In a melanoma training set, IPSP-high patients presented a longer overall survival and a higher response rate than IPSP-low patients. Moreover, the IPSP showed a superior predictive effect compared with TMB. In addition, the prognostic and predictive value of the IPSP was consistently validated in two independent validation sets. Finally, in a multi-cancer dataset, PathwayTMB also exhibited good performance. Our results indicate that PathwayTMB could identify the mutation pathways for predicting immunotherapeutic survival, and their combination may serve as a potential predictive biomarker for immune checkpoint inhibitor therapy.© 2023 The Authors.