Niknafs Noushin, Najjar Mimi, Dennehy Colum, Stouras Ioannis, Anagnostou Valsamo
The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Lung Cancer Precision Medicine Center of Excellence, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Clin Cancer Res. 2025 Jul 15;31(14):2850-2863. doi: 10.1158/1078-0432.CCR-23-0824.
Tumor mutational burden (TMB) is considered a prototypic feature of tumor foreignness and has been established as a tumor-agnostic FDA-approved biomarker at a threshold of 10 mut/Mb for immune checkpoint inhibitors (ICI). Despite its clinical utility as a companion diagnostic for ICI across cancers, a high TMB does not consistently predict response due to technical and biological limitations. Tumor heterogeneity and purity, blood versus tissue sampling, variation in next-generation sequencing, and algorithmic evaluation attenuate the predictive value of TMB. In addition to technical standardization and moving beyond TMB as a numeric or binarized value, it is of paramount importance to consider the underlying biology and the differential contribution of mutation subsets to tumor foreignness and immunogenicity. The importance of consideration of mutations within the overall TMB that are unlikely to be immunoedited together with the density of immunogenic "quality" mutation-associated neoantigens introduces the concept of biological calibration of TMB that may enhance its clinical utility. Mutagenic processes such as microsatellite instability and ultra-mutation and cancer lineage-dependent co-mutation patterns also represent biological modifiers that enable the interpretation of the overall TMB in different contexts. In this perspective, we dissect TMB on a biological and technical level, followed by a critical assessment of the predictive role of TMB in capturing ICI response in the setting of clinical trials across human cancers. The standardization of technical methodologies, together with the interpretation of TMB on the basis of the tumor genomic landscape, represents key steps toward maximizing the predictive value of TMB for cancer immunotherapy.
肿瘤突变负荷（TMB）被认为是肿瘤异质性的一个典型特征，并且已被美国食品药品监督管理局（FDA）批准为一种不依赖肿瘤类型的生物标志物，用于免疫检查点抑制剂（ICI）时的阈值为每兆碱基10个突变。尽管TMB作为ICI在各种癌症中的伴随诊断具有临床应用价值，但由于技术和生物学限制，高TMB并不能始终如一地预测疗效。肿瘤异质性和纯度、血液与组织取样、下一代测序的差异以及算法评估都会削弱TMB的预测价值。除了技术标准化以及超越将TMB作为数值或二值化值之外，考虑潜在生物学特性以及突变亚群对肿瘤异质性和免疫原性的不同贡献至关重要。考虑总体TMB中不太可能被免疫编辑的突变以及免疫原性“优质”突变相关新抗原的密度的重要性，引入了TMB生物校准的概念，这可能会增强其临床应用价值。微卫星不稳定性和超突变等诱变过程以及癌症谱系依赖性共突变模式也代表了生物学修饰因子，能够在不同背景下解读总体TMB。从这个角度出发，我们在生物学和技术层面剖析TMB，随后对TMB在跨人类癌症的临床试验中捕捉ICI反应的预测作用进行批判性评估。技术方法的标准化以及基于肿瘤基因组格局对TMB的解读，是最大化TMB对癌症免疫治疗预测价值的关键步骤。
