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在批量瘤样本中评估体质突变异位基因的丰富表达时的混因素

Kohei Hagiwara¹, Andrew Thrasher¹, Nadezhda V Terekhanova¹

¹St. Jude Children's Research Hospital.

Genome research

|March 4, 2026

概括

由于瘤纯度,等位基特异性表达 (ASE) 分析可能会产生误导性. 这项研究模拟了混因素,并使用RNA数据来改善体质突变检测,特别是在低纯度样本中.

科学领域:

基因组学就是基因组学.
癌症生物学癌症生物学
生物信息学是一种生物信息学.

背景情况:

基因特异性表达 (ASE) 是通过将突变基因RNA与DNA进行比较来研究的.
在批量瘤样本中的体质突变分析因混合细胞种群而复杂.

研究的目的:

在ASE分析中建模和验证混因素.
利用RNA测序数据,在低纯度瘤中改善体质突变检测.

主要方法:

开发了一个数学模型,包括瘤/正常表达差异,等位基因剂量,瘤纯度和无意中介衰变 (NMD).
使用癌症基因组图谱 (TCGA) 实体插入/删除 (indels) 的泛癌症分析验证的模型预测.
进行单细胞分析,以评估模型对瘤内异质性的稳定性.

主要成果:

基因表达的差异和瘤纯度可以在ASE分析中产生假阳性.
在具有低瘤纯度的样本中,混效应更为明显.
基于RNA的 de novo indel调用增加了TCGA驱动器的indel谱约14%,特别是在纯度<0.4的样本中.

结论:

身体突变ASE分析需要仔细考虑瘤纯度等混因素.
RNA测序数据可以有效地用于新体突变检测,特别是在具有挑战性的低纯度样本中.
在以前低估的样本中确定了可操作的突变 (例如,EGFR,FLT3).

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