Yang Howard H, Liu Huaitian, Hu Nan, Su Hua, Wang Chaoyu, Giffen Carol, Goldstein Alisa M, Taylor Philip R, Lee Maxwell P
Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Cancers (Basel). 2022 Mar 23;14(7):1629. doi: 10.3390/cancers14071629.
We integrated ESCC expression and GWAS genotyping, to investigate eQTL and somatic DNA segment alterations, including somatic copy number alteration, allelic imbalance (AI), and loss of heterozygosity (LOH) in ESCC. First, in eQTL analysis, we used a classical approach based on genotype data from GWAS and expression signals in normal tissue samples, and then used a modified approach based on fold change in the tumor vs. normal samples. We focused on the genes in three pathways: inflammation, DNA repair, and immunity. Among the significant (p < 0.05) SNP-probe pairs from classical and modified eQTL analyses, 24 genes were shared by the two approaches, including 18 genes that showed the same numbers of SNPs and probes and 6 genes that had the different numbers of SNPs and probes. For these 18 genes, we found 28 SNP−probe pairs were correlated in opposite directions in the two approaches, indicating an intriguing difference between the classical and modified eQTL approaches. Second, we analyzed the somatic DNA segment alterations. Across the 24 genes, abnormal gene expression on mRNA arrays was seen in 19−95% of cases and 26−78% showed somatic DNA segment alterations on Affymetrix GeneChip Human Mapping Arrays. The results suggested that this strategy could identify gene expression and somatic DNA segment alterations for biological markers (genes) by combining classical and modified eQTLs and somatic DNA evaluation on SNP arrays. Thus, this study approach may allow us to understand functionality indicative of potentially relevant biomarkers in ESCC.
我们整合了食管癌（ESCC）的表达数据和全基因组关联研究（GWAS）的基因分型，以研究表达定量性状位点（eQTL）和体细胞DNA片段改变，包括食管癌中的体细胞拷贝数改变、等位基因不平衡（AI）和杂合性缺失（LOH）。首先，在eQTL分析中，我们基于GWAS的基因型数据和正常组织样本中的表达信号采用了一种经典方法，然后基于肿瘤样本与正常样本的倍数变化采用了一种改进方法。我们关注炎症、DNA修复和免疫这三条通路中的基因。在经典和改进的eQTL分析中显著（p < 0.05）的单核苷酸多态性（SNP）-探针组对中，两种方法共有24个基因，其中18个基因的SNP和探针数量相同，6个基因的SNP和探针数量不同。对于这18个基因，我们发现两种方法中有28个SNP-探针组对呈相反方向相关，这表明经典和改进的eQTL方法之间存在有趣的差异。其次，我们分析了体细胞DNA片段改变。在这24个基因中，19%-95%的病例在mRNA阵列上出现异常基因表达，26%-78%在Affymetrix GeneChip Human Mapping Arrays上显示体细胞DNA片段改变。结果表明，该策略可通过结合经典和改进的eQTL以及SNP阵列上的体细胞DNA评估来识别生物标志物（基因）的基因表达和体细胞DNA片段改变。因此，这种研究方法可能使我们了解食管癌中潜在相关生物标志物的功能指示。
