Illumina, Inc., San Diego, CA, United States of America.
PLoS Comput Biol. 2020 Nov 9;16(11):e1008332. doi: 10.1371/journal.pcbi.1008332. eCollection 2020 Nov.
The tumor mutational burden (TMB) is increasingly recognized as an emerging biomarker that predicts improved outcomes or response to immune checkpoint inhibitors in cancer. A multitude of technical and biological factors make it difficult to compare TMB values across platforms, histologies, and treatments. Here, we present a mechanistic model that explains the association between panel size, histology, and TMB threshold with panel performance and survival outcome and demonstrate the limitations of existing methods utilized to harmonize TMB across platforms.
肿瘤突变负担(TMB)越来越被认为是一种新兴的生物标志物,可预测癌症患者对免疫检查点抑制剂的疗效或反应改善。多种技术和生物学因素使得跨平台、组织学和治疗方法比较 TMB 值变得困难。在这里,我们提出了一个机制模型,解释了面板大小、组织学和 TMB 阈值与面板性能和生存结果之间的关联,并展示了用于跨平台协调 TMB 的现有方法的局限性。