美国麻省理工学院和哈佛大学的博德研究所Gad Getz、Michael S. Lawrence等研究人员合作解析了癌症中的伴随性热点突变。这一研究成果发表在2019年9月16日出版的《癌细胞》上。

研究人员表示，目前用于评估热点显著性的统计模型并不能恰当地解释特定位点突变性的变化，从而产生许多假阳性结果。

因此，研究人员详述了对数正态泊松（LNP）背景模型，该模型以与诱变模型一致的方式解释了这种可变性。研究人员用它来表明伴随性热点来自所有常见的突变过程;，并将其应用于大约10000名患者队列，来鉴定与传统方法相比具有更少假阳性的驱动热点。

总体而言，研究人员发现在多个肿瘤的同一基因组位点重复出现的许多癌症热点突变实际上是伴随事件，重复地发生在没有正选择的固有可变基因组位点。

附：英文原文

Title: Passenger Hotspot Mutations in Cancer

Author: Julian M. Hess, Andre Bernards, Jaegil Kim, Mendy Miller, Amaro Taylor-Weiner, Nicholas J. Haradhvala, Michael S. Lawrence, Gad Getz

Issue&Volume:Volume 36 Issue 3

Summary: 

Current statistical models for assessing hotspot significance do not properly account for variation in site-specific mutability, thereby yielding many false-positives. We thus (i) detail a Log-normal-Poisson (LNP) background model that accounts for this variability in a manner consistent with models of mutagenesis; (ii) use it to show that passenger hotspots arise from all common mutational processes; and (iii) apply it to a ∼10,000-patient cohort to nominate driver hotspots with far fewer false-positives compared with conventional methods. Overall, we show that many cancer hotspot mutations recurring at the same genomic site across multiple tumors are actually passenger events, recurring at inherently mutable genomic sites under no positive selection.

DOI: 10.1016/j.ccell.2019.08.002

Source: https://www.cell.com/cancer-cell/fulltext/S1535-6108(19)30370-8