已知肿瘤坏死因子(TNF)/TNF受体(TNFR)途径影响癌症患者的存活。我们假设与凋亡相关的TNF/TNFR通路基因中的单核苷酸多态性(SNP)与非小细胞肺癌(NSCLC)患者的生存有关。我们在前列腺中使用了1185例NSCLC患者,肺,结肠直肠,和卵巢癌(PLCO)筛查试验和哈佛肺癌易感性研究中的984例NSCLC患者作为发现和验证数据集,分别。我们在TNF/TNFR信号通路的71个基因中选择了6788个SNP,并从PLCO基因关联研究(GWAS)数据集中提取了它们的基因分型数据。我们进行了Cox比例风险回归分析,以评估已识别的SNP与生存率之间的关联,并验证了显着的SNP,进一步分析了它们的功能相关性。我们发现两个有效SNP的基因型,IKBKAPrs4978754CT+TT和TNFRSF1Brs677844TC+CC,以及它们的组合基因型预测了更好的总生存期(P=0.004,0.002和<0.001,分别)。通过RegulomeDB评分预测这两个验证的SNP具有潜在的功能性。此外,IKBKAPmRNA表达水平显著增高,肺癌组织中TNFRSF1BmRNA表达水平显著低于癌旁正常组织(P<0.001)。基于癌症基因组图谱(TCGA)的表达数量性状位点分析表明,在隐性模型中,IKBKAPrs4978754和TNFRSF1Brs677844基因型与其在肺癌组织中的相应mRNA表达水平显着相关(分别为P=0.035和0.045)。因此,我们确定了两个潜在的功能性SNP(IKBKAPrs4978754C>T和TNFRSF1Brs677844T>C)与NSCLC患者的生存相关.
The tumor necrosis factor (TNF)/TNF receptor (TNFR) pathway is known to influence survival of patients with cancer. We hypothesize that single nucleotide polymorphisms (SNPs) in the TNF/TNFR pathway genes related to apoptosis are associated with survival of patients with non-small cell lung cancer (NSCLC). We used 1185 patients with NSCLC in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening
Trial and 984 patients with NSCLC in the Harvard Lung Cancer Susceptibility
Study as the discovery and validation datasets, respectively. We selected 6788 SNPs in 71 genes in the TNF/TNFR signaling pathway and extracted their genotyping data from the PLCO genowide-association
study (GWAS) dataset. We performed Cox proportional hazards regression analysis to evaluate associations between the identified SNPs and survival and validated the significant SNPs, which were further analyzed for their functional relevance. We found that genotypes of two validated SNPs, IKBKAP rs4978754 CT + TT and TNFRSF1B rs677844 TC + CC, as well as their combined genotypes predicted a better overall survival (P = 0.004, 0.002 and <0.001, respectively). These two validated SNPs were predicted by the RegulomeDB score to be potentially functional. In addition, IKBKAP mRNA expression levels were significantly higher, while TNFRSF1B mRNA expression levels were significantly lower in lung cancer tissues than in adjacent normal tissues (P < 0.001). The Cancer Genome Atlas (TCGA)-based expression quantitative trait loci analysis showed that IKBKAP rs4978754 and TNFRSF1B rs677844 genotypes were significantly associated with their corresponding mRNA expression levels in lung cancer tissues in a recessive model (P = 0.035 and 0.045, respectively). Therefore, we identified two potentially functional SNPs (IKBKAP rs4978754 C > T and TNFRSF1B rs677844 T > C) to be associated with survival of patients with NSCLC.