Yadav Anu, Gupta Annapurna, Rastogi Neeraj, Agrawal Sushma, Kumar Ashok, Kumar Vijay, Mittal Balraj
Department of Genetics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, UP, India.
Department of Radiotherapy, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, UP, India.
Tumour Biol. 2016 Feb;37(2):1835-44. doi: 10.1007/s13277-015-3929-6. Epub 2015 Aug 30.
Genes important to stem cell progression have been involved in the genetics and clinical outcome of cancers. We investigated germ line variants in cancer stem cell (CSC) genes to predict susceptibility and efficacy of chemoradiotherapy treatment in gallbladder cancer (GBC) patients. In this study, we assessed the effect of SNPs in CSC genes (surface markers CD44, ALCAM, EpCAM, CD133) and (molecular markers NANOG, SOX-2, LIN-28A, ALDH1A1, OCT-4) with GBC susceptibility and prognosis. Total 610 GBC patients and 250 controls were genotyped by using PCR-RFLP, ARMS-PCR, and TaqMan allelic discrimination assays. Chemotoxicity graded 2-4 in 200 patients and tumor response was recorded in 140 patients undergoing neoadjuvant chemotherapy (NACT). Differences in genotype and haplotype frequency distributions were calculated by binary logistic regression. Gene-gene interaction model was analyzed by generalized multifactor dimensionality reduction (GMDR). Overall survival was assessed by Kaplan-Meier survival curve and multivariate Cox-proportional methods. ALCAM Ars1157Crs10511244 (P = 0.0035) haplotype was significantly associated with GBC susceptibility. In GMDR analysis, ALCAM rs1157G>A, EpCAM rs1126497T>C emerged as best significant interaction model with GBC susceptibility and ALDH1A1 rs13959T>G with increased risk of grade 3-4 hematological toxicity. SOX-2 rs11915160A>C, OCT-4 rs3130932T>G, and NANOG rs11055786T>C were found best gene-gene interaction model for predicting response to NACT. In both Cox-proportional and recursive partitioning ALCAM rs1157GA+AA genotype showed higher mortality and hazard ratio. ALCAM gene polymorphisms associated with GBC susceptibility and survival while OCT-4, SOX-2, and NANOG variants showed an interactive role with treatment response.
对干细胞进展至关重要的基因已涉及癌症的遗传学和临床结果。我们研究了癌症干细胞（CSC）基因中的种系变异，以预测胆囊癌（GBC）患者对放化疗治疗的易感性和疗效。在本研究中，我们评估了CSC基因（表面标志物CD44、ALCAM、EpCAM、CD133）和（分子标志物NANOG、SOX-2、LIN-28A、ALDH1A1、OCT-4）中的单核苷酸多态性（SNP）对GBC易感性和预后的影响。使用聚合酶链反应-限制性片段长度多态性（PCR-RFLP）、扩增阻滞突变系统-PCR（ARMS-PCR）和TaqMan等位基因鉴别分析对总共610例GBC患者和250例对照进行基因分型。记录了200例患者的2-4级化学毒性，并对140例接受新辅助化疗（NACT）的患者的肿瘤反应进行了记录。通过二元逻辑回归计算基因型和单倍型频率分布的差异。通过广义多因素降维法（GMDR）分析基因-基因相互作用模型。通过Kaplan-Meier生存曲线和多变量Cox比例法评估总生存期。ALCAM Ars1157Crs10511244（P = 0.0035）单倍型与GBC易感性显著相关。在GMDR分析中，ALCAM rs1157G>A、EpCAM rs1126497T>C成为与GBC易感性相关的最佳显著相互作用模型，而ALDH1A1 rs13959T>G与3-4级血液学毒性风险增加相关。发现SOX-2 rs11915160A>C、OCT-4 rs3130932T>G和NANOG rs11055786T>C是预测对NACT反应的最佳基因-基因相互作用模型。在Cox比例法和递归划分法中，ALCAM rs1157GA+AA基因型均显示出更高的死亡率和风险比。ALCAM基因多态性与GBC易感性和生存率相关，而OCT-4、SOX-2和NANOG变异与治疗反应具有相互作用。
