乙型肝炎病毒相关性肝细胞癌体细胞突变表达模式的研究

Acquired somatic mutations play major role in development, carcinogenesis and cancer progression based on the principle that cancer arises from a clone that has accumulated the requisite somatically acquired genetic aberrations. With the advent of next-generation sequencing (NGS) technology, genome (e.g., whole exome sequencing, WES) and transcriptome data (i.e., RNA-seq) have accumulated rapidly and therefore provide an opportunity to understand the complexities of somatic mutations in cancers. Additionally, mass spectrometry (MS)-based proteomics has undergone rapid development recently and enable us to identify and quantify large portions of the proteome, as well as detect single amino acid polymorphisms (SAP). Currently, NGS has identified multiple types of somatic aberrations in the liver cancer genome. However, there is still lack of systematical study of the expression of somatic mutations at the levels of transcriptome and proteome, and its molecular complexity and dynamic changes are not fully characterized. In the present proposal, we will study the patterns of somatic mutation expression at the levels of transcriptome and proteome using patients of hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). We will first characterize somatic mutations at the levels of genome, transcriptome, and proteome, respectively, using high-throughput ‘omics’ data from WES, RNA-Seq, and MS. Then, we will investigate the patterns of somatic mutation expression based on integrated analysis of ‘Multi-Omics’ data. We hypothesize that only a small fraction of tumor-mutated alleles identified at the DNA level were expressed at the levels of transcriptome and proteome. Finally, we will explore its feasibility in prioritizing patient-specific candidate cancer driver genes. The proposed study will provide valuable information regarding the complex and dynamics relationship between somatic mutations at the levels of genome and transcriptome, as well as the ultimate protein products. In addition, it may have important implications for clinical cancer genome sequencing.

下一代测序技术的发展及应用，为在基因组尺度识别肿瘤体细胞突变奠定了基础；基于质谱技术的蛋白质组学的发展使鉴定，量化大量蛋白质组分，以及识别单一氨基酸变异成为可能 。目前，肿瘤体细胞突变的研究侧重于基因组水平，例如已在肝癌基因组中识别了不同类型的体细胞异常。一个值得关注的问题是，基因组编码区影响氨基酸改变的非同义性突变, 是否通过中心法则表达，进而影响蛋白质终产物的功能。本研究拟利用NGS和MS技术，整合全外显子组，转录组与蛋白质组的高通量测序数据，研究乙型病毒性肝炎相关性肝细胞肝癌患者肿瘤突变等位基因在转录组与蛋白质组的表达模式，以探索利用该模式优化选择个体特异肿瘤driver基因/突变。该研究对阐述肿瘤体细胞突变在基因组, 转录组以及蛋白质终产物之间的复杂关系具有重要的意义，在临床癌症基因组测序中具有深刻启示。

通常，对肿瘤体细胞突变的研究依据其功能分类进行优化选择，如无义突变以及错义突变。一个值得关注的问题是：基因编码区影响氨基酸改变的错义突变，是否通过中心法则在转录本 (即mRNA)与蛋白质中表达，从而最终影响蛋白质终产物的功能。那么，对基因组水平肿瘤突变在转录组与蛋白质组表达模式的系统性分析，能够揭示体细胞突变的动态表达变化，阐述其在基因组，转录组以及蛋白质终产物之间的复杂关系。另外，体细胞突变的表达模式可能为鉴别肿瘤发生过程中个体化 (personalized）的‘driver’基因提供了另一种策略。本项目已经对10例乙型肝炎病毒相关性肝细胞癌的癌组织与癌旁正常组织进行全外显子组及转录组测序，与蛋白质组质谱分析，将不同组学高通量数据进行整合分析，鉴定到了新的肝细胞癌致癌基因VPS35，并且在体内外得到了有效的验证。同时，我们也将同样的策略应用到神经内分泌肿瘤病例，进行肿瘤进化树构建，并推测了转移发生的可能时间，并且鉴定到TSC2的双位点失活现象，由此指导了临床采取mTOR抑制剂进行治疗并取得稳定疗效。后续工作中，我们还将敲除了VPS35的肝癌细胞株进行细胞器分离，做蛋白质质谱，观察和研究VPS35敲除状态下，肝癌细胞的亚细胞结构水平的蛋白质变化。

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