A Sequence Variant in the Phospholipase C Epsilon C2 Domain Is Associated With Esophageal Carcinoma and Esophagitis

作者:Wang, Li-Dong; Bi, Xiuli; Song, Xin; Pohl, Nicole M.; Cheng, Yulan; Zhou, Yixing; Shears, Stephen; Ansong, Emmanuel; Xing, Mengtao; Wang, Shaomeng; Xu, Xiao-Chun; Huang, Peng; Xu, Liyan; Wang, Liang; Fan, Zongmin; Zhao, Xueke; Dong, Huali; Meltzer, Stephen J.; Ding, Ivan; Yang, Wancai*
来源:Molecular Carcinogenesis, 2013, 52(S1): 80-86.
DOI:10.1002/mc.22016

摘要

A single-nucleotide polymorphism (rs2274223: A5780G:His1927Arg) in the phospholipase C epsilon gene (PLCE) was recently identified as a susceptibility locus for esophageal cancer in Chinese subjects. To determine the underlying mechanisms of PLCE and this SNP in esophageal carcinogenesis, we analyzed PLCE genotypes, expression, and their correlation in esophageal cancer cell lines, non-transformed esophageal cells, 58 esophageal squamous cell carcinomas and 10,614 non-cancer subjects from China. We found that the G allele (AG or GG) was associated with increased PLCE mRNA and protein expression in esophageal cancer tissues and in esophageal cancer cell lines. G allele was also associated with higher enzyme activity, which might be associated with increased protein expression. Quantitative analysis of the C2 domain sequences revealed that A:G allelic imbalance was strongly linked to esophageal malignancy. Moreover, the analysis of 10,614 non-cancer subjects demonstrated that the G allele was strongly associated with moderate to severe esophagitis in the subjects from the high-incidence areas of China (OR 6.03, 95% CI 1.59-22.9 in high-incidence area vs. OR 0.74, 95% CI 0.33-1.64 in low-incidence area; P=0.008). In conclusion, the PLCE gene, particularly the 5780G allele, might play a pivotal role in esophageal carcinogenesis via upregulating PLCE mRNA, protein, and enzyme activity, and augmenting inflammatory process in esophageal epithelium. Thus, 5780G allele may constitute a promising biomarker for esophageal squamous cell carcinoma risk stratification, early detection, and progression prediction.