结直肠癌中DNA甲基化与SNP热点相关性研究

Colorectal cancer (CRC), the third leading cause of worldwide cancer-related deaths in men and women, is developed by a series of steps involved accumulation of mutations, and considered as a classic model for genetic basics for tumorigenesis. Genomic instability is a hallmark of cancer, and can occur at nucleotide, microsatellite, or chromosomal level. It is still unclear how the instability arises during the cancer development, or how it relates to other factors. It has been shown that genome will interplay with epigenome and promote oncogenic transformation together. Previous researches have found that histone modification and CpG content are associated with single nucleotide polymorphisms (SNP) density. In this study, genome sequencing data will be analyzed to investigate whether there are any SNP hotspots in CRC. Meanwhile, bisulfite sequencing, DNase-Seq and ChIP-Seq data from CRC cell lines and tissues will be analyzed. By clustering, correlation test and linear modeling using the large scale datasets, the association of DNA methylation level, DNase I hypersensitive sites (DHS), CTCF binding and RNA POLⅡbinding with SNP hotspots will be evaluated. The key SNP hotspots with strong association to DNA methylation or the tested regulatory regions will then be validated in CRC tissues by Sanger sequencing technology. Also, survival test will be performed to exam whether the candidate sites are associated with CRC patients' survival time using TCGA datasets. This study attempts to discover the SNP hotspots in CRC and explain the phenomena using DNA methylation and DHS data. The key hotspots can provide potential diagnosis and prognosis biomarker for CRC. In summary, the research is designed to find whether epigenome can affect the genomic instability at single nucleic acid level, providing novel strategy for CRC diagnosis and treatment.

结直肠癌是一种死亡率极高的恶性肿瘤，是研究基因组与表观遗传组的重要模型。基因组不稳定性指的是基因组的遗传改变，可在单碱基、微卫星和染色体水平观测到，是肿瘤的重要标记，受表观遗传组的影响。已有研究发现组蛋白修饰、CpG含量与SNP密度具有较高的相关性，但目前仍不清楚影响癌症基因组中SNP密度的因素。本项目旨在通过分析多组结直肠癌来源的基因组测序、DNA甲基化测序、DNase-Seq、ChIP-Seq等多种类型的数据，运用相关性计算、聚类分析、多元回归建模等方法，探索SNP热点区域与DNA甲基化水平、DNA酶Ⅰ超敏感区、CTCF结合、RNA POLⅡ结合之间的关系，并在小规模病人组织样本中验证关键SNP区域，为结直肠癌的诊断及预后提供候选的标记物。本研究主要利用大数据研究基因组与表观组之间的相互作用，探索癌症基因组不稳定形成的机制，可为今后的肿瘤治疗提供方向。

结直肠癌是一种死亡率极高的恶性肿瘤，是研究基因组与表观遗传组的重要模型。基 因组不稳定性指的是基因组的遗传改变，可在单碱基、微卫星和染色体水平观测到，是肿 瘤的重要标记，受表观遗传组的影响。由于肿瘤具有高度异质性，个体化差异很大，较难找到频发突变，但可能存在突变密集的基因组区域。本研究主要利用肿瘤全基因组DNA测序及表观遗传数据，研究结直肠癌基因组突变热点区域及其DNA甲基化、染色体开放状态等特征。利用三组不同人群来源的结直肠癌全基因组数据，通过基于距离的聚类分析，分别得到543、1929、339个突变热点，其中包括APC基因17号外显子、KRAS基因2号外显子、TP53基因4-9号外显子、9q13重复序列区、10q11重复序列区在内的突变热点区。所得到的突变热点显著富集于外显子区，且其基因功能与嗅觉通路相关。中国人群来源的突变热点还显著富集于重复序列区，不同于分散突变区，表明重复序列不稳定也是结直肠癌发生的重要特点。C>T或G>A突变多发生于DNA高甲基化区，表明DNA甲基化状态与基因组不稳定相关。此外，不到10%的突变热点区与Pan-Cancer ATAC峰重叠，表明在结直肠癌发生过程中，蛋白质功能的改变发挥了更重要的作用，而基因表达系统的改变对癌症进展的贡献较小。这些突变热点区及其表观遗传特征有助于揭示结直肠癌发生的分子机制，探索癌症基因组不稳定形成的机制，可为今后的肿瘤治疗提供新方向。