PDF(Pubmed)
Abstract：
Although driver genes in hepatocellular carcinoma (HCC) have been investigated in various previous genetic studies, prevalence of key driver genes among heterogeneous populations is unknown. Moreover, the phenotypic associations of these driver genes are poorly understood. This report aims to reveal the phenotypic impacts of a group of consensus driver genes in HCC. We used MutSigCV and OncodriveFM modules implemented in the IntOGen pipeline to identify consensus driver genes across six HCC cohorts comprising 1,494 samples in total. To access their global impacts, we used The Cancer Genome Atlas (TCGA) mutations and copy-number variations to predict the transcriptomics data, under generalized linear models. We further investigated the associations of the consensus driver genes to patient survival, age, gender, race, and risk factors. We identify 10 consensus driver genes across six HCC cohorts in total. Integrative analysis of driver mutations, copy-number variations, and transcriptomic data reveals that these consensus driver mutations and their copy-number variations are associated with a majority (62.5%) of the mRNA transcriptome but only a small fraction (8.9%) of miRNAs. Genes associated with TP53, CTNNB1, and ARID1A mutations contribute to the tripod of most densely connected pathway clusters. These driver genes are significantly associated with patients\' overall survival. Some driver genes are significantly linked to HCC gender (CTNNB1, ALB, TP53, and AXIN1), race (TP53 and CDKN2A), and age (RB1) disparities. This study prioritizes a group of consensus drivers in HCC, which collectively show vast impacts on the phenotypes. These driver genes may warrant as valuable therapeutic targets of HCC.
摘要：
虽然肝细胞癌（HCC）中的驱动基因已经在以前的各种遗传研究中进行了研究，异质人群中关键驱动基因的患病率未知.此外，对这些驱动基因的表型关联了解甚少.本报告旨在揭示一组共识驱动基因在HCC中的表型影响。我们使用在IntOGen管道中实施的MutSigCV和OncodriveFM模块来识别六个HCC队列中的共识驱动基因，总共包含1,494个样本。为了了解它们的全球影响，我们使用癌症基因组图谱（TCGA）突变和拷贝数变异来预测转录组学数据，在广义线性模型下。我们进一步调查了共识驱动基因与患者生存的关联，年龄,性别,种族,和风险因素。我们总共在六个HCC队列中确定了10个共识驱动基因。驱动突变的综合分析，拷贝数变化，和转录组数据显示，这些共有驱动突变及其拷贝数变异与大部分（62.5%）mRNA转录组相关，但只有一小部分（8.9%）miRNA。与TP53，CTNNB1和ARID1A突变相关的基因有助于最密集连接的途径簇的三脚架。这些驱动基因与患者的总体生存率显著相关。一些驱动基因与HCC性别显著相关(CTNNB1，ALB，TP53和AXIN1)，种族（TP53和CDKN2A），年龄（RB1）差异。这项研究优先考虑了HCC中的一组共识驱动因素，它们共同显示出对表型的巨大影响。这些驱动基因可以保证作为HCC的有价值的治疗靶标。
