Genomic analysis of liver cancer unveils novel driver genes and distinct prognostic features.
Genomic analysis of liver cancer unveils novel driver genes and distinct prognostic features.
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作者：
Li X;Xu W;Kang W;Wong SH;Wang M;Zhou Y;Fang X;Zhang X;Yang H;Wong CH;To KF;Chan SL;Chan MTV;Sung JJY;Wu WKK;Yu J
目的：肝细胞癌（Hepatocellular carcinoma，HCC）是一种高度异质性的疾病，预后差.然而，HCC中的驱动基因和预后标志物仍有待确定。希望通过对肝癌基因组与临床病理学信息的深入分析，能够发现新的分子预后标志物。研究方法：我们从先前的研究中收集了1，061例HCC患者的基因组数据，并进行了整合分析，以确定显着突变的基因和分子突变因子。我们采用三种MutSig算法（MutSigCV、MutSigCL和MutSigFN）来识别显著突变的基因。使用GISTIC 2算法描绘局部扩增和缺失的基因组区域。利用非负矩阵因子分解（NMF）来破译突变签名。Kaplan-Meier生存和考克斯回归分析用于关联基因突变和拷贝数改变与生存结果。应用逻辑回归模型检验基因突变与突变特征之间的关联。结果：我们发现了11个新的驱动基因，包括RNF 213、VAV 3和TNRC 6 B，突变率范围从1%到3%。在HCC中还鉴定了七种突变特征，其中一些与经典驱动基因的突变相关（例如，TP 53，TERT）以及饮酒。还发现了TERT和其他可药用靶标（包括AURKA）的局部扩增。小分子抑制剂靶向AURKA可有效诱导HCC细胞凋亡。我们进一步证实了伴有TERT扩增的HCC患者的总生存期缩短，与其他临床病理参数无关。总之，我们的研究确定了HCC中新的癌症驱动基因和预后标志物，重申了组学数据在精准医学时代的重要性。
Objective: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with a dismal prognosis. However, driver genes and prognostic markers in HCC remain to be identified. It is hoped that in-depth analysis of HCC genomes in relation to available clinicopathological information will give rise to novel molecular prognostic markers. Methods: We collected genomic data of 1,061 HCC patients from previous studies, and performed integrative analysis to identify significantly mutated genes and molecular prognosticators. We employed three MutSig algorithms (MutSigCV, MutSigCL and MutSigFN) to identify significantly mutated genes. The GISTIC2 algorithm was used to delineate focally amplified and deleted genomic regions. Nonnegative matrix factorization (NMF) was utilized to decipher mutational signatures. Kaplan-Meier survival and Cox regression analyses were used to associate gene mutation and copy number alteration with survival outcome. Logistic regression model was applied to test association between gene mutation and mutational signatures. Results: We discovered 11 novel driver genes, including RNF213, VAV3 and TNRC6B, with mutational prevalence ranging from 1% to 3%. Seven mutational signatures were also identified in HCC, some of which were associated with mutations of classical driver genes (e.g., TP53, TERT) as well as alcohol consumption. Focal amplifications of TERT and other druggable targets, including AURKA, were also revealed. Targeting AURKA by a small-molecule inhibitor potently induced apoptosis in HCC cells. We further demonstrated that HCC patients with TERT amplification displayed shortened overall survival independent of other clinicopathological parameters. In conclusion, our study identified novel cancer driver genes and prognostic markers in HCC, reiterating the translational importance of omics data in the precision medicine era.