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Integrated Analysis of Whole Genome and Transcriptome Sequencing Reveals Diverse Transcriptomic Aberrations Driven by Somatic Genomic Changes in Liver Cancers

机译:全基因组和转录组测序的综合分析揭示了肝癌中体细胞基因组变化所驱动的多种转录组畸变。

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摘要

Recent studies applying high-throughput sequencing technologies have identified several recurrently mutated genes and pathways in multiple cancer genomes. However, transcriptional consequences from these genomic alterations in cancer genome remain unclear. In this study, we performed integrated and comparative analyses of whole genomes and transcriptomes of 22 hepatitis B virus (HBV)-related hepatocellular carcinomas (HCCs) and their matched controls. Comparison of whole genome sequence (WGS) and RNA-Seq revealed much evidence that various types of genomic mutations triggered diverse transcriptional changes. Not only splice-site mutations, but also silent mutations in coding regions, deep intronic mutations and structural changes caused splicing aberrations. HBV integrations generated diverse patterns of virus-human fusion transcripts depending on affected gene, such as TERT, CDK15, FN1 and MLL4. Structural variations could drive over-expression of genes such as WNT ligands, with/without creating gene fusions. Furthermore, by taking account of genomic mutations causing transcriptional aberrations, we could improve the sensitivity of deleterious mutation detection in known cancer driver genes (TP53, AXIN1, ARID2, RPS6KA3), and identified recurrent disruptions in putative cancer driver genes such as HNF4A, CPS1, TSC1 and THRAP3 in HCCs. These findings indicate genomic alterations in cancer genome have diverse transcriptomic effects, and integrated analysis of WGS and RNA-Seq can facilitate the interpretation of a large number of genomic alterations detected in cancer genome.
机译:应用高通量测序技术的最新研究已经确定了多个癌症基因组中的几个反复突变的基因和途径。然而,尚不清楚癌症基因组中这些基因组改变的转录结果。在这项研究中,我们对22种乙型肝炎病毒(HBV)相关的肝细胞癌(HCC)及其匹配的对照的全基因组和转录组进行了综合和比较分析。全基因组序列(WGS)和RNA-Seq的比较揭示了许多证据,表明各种类型的基因组突变触发了多种转录变化。不仅剪接位点突变,而且编码区的无声突变,深度内含子突变和结构变化也导致剪接像差。 HBV整合会根据受影响的基因(如TERT,CDK15,FN1和MLL4)生成病毒-人融合转录本的多种模式。结构变异可能导致基因(例如WNT配体)的过度表达,有/没有产生基因融合。此外,通过考虑引起转录异常的基因组突变,我们可以提高已知癌症驱动基因(TP53,AXIN1,ARID2,RPS6KA3)中有害突变检测的灵敏度,并确定推定的癌症驱动基因(如HNF4A,CPS1)的反复破坏,肝癌中的TSC1和THRAP3。这些发现表明癌症基因组中的基因组改变具有多种转录组效应,而WGS和RNA-Seq的综合分析可以促进对癌症基因组中检测到的大量基因组改变的解释。

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