Role of novel and GWAS originated PLCE1 genetic variants in susceptibility and prognosis of esophageal cancer patients in northern Indian population
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Recent genome-wide association studies (GWAS) have identified variants in phospholipase C epsilon1 (PLCE1) as novel susceptibility markers for esophageal squamous cell carcinoma (ESCC) in Chinese population. Although few studies have replicated this findings in other populations, but results are contradictory. So, we aimed to replicate association of two previously reported non-synonymous polymorphisms (rs2274223A>G and rs3765524C>T) from haplotype block 10 and evaluated a novel variant (rs7922612C>T) from haplotype block 2 of PLCE1 with susceptibility and prognosis of ESCC in northern Indian population. The genotyping of PLCE1 variants were performed in 293 histopathologically confirmed incident ESCC cases (including 177 follow-up cases) and 314 age-, gender-, and ethnicity-matched controls using PCR RFLP. All statistical analyses were performed through SPSS version 15.0. Modeling and functional prediction of two non-synonymous variants were carried out using bioinformatics tools. PLCE1 polymorphisms were not associated with susceptibility to ESCC or its clinical phenotypes (tumor location/lymph node metastasis). No interaction with environmental risk factors was found. In silico analysis suggested negligible effect on structure of PLCE1 protein due to PLCE1 rs2274223 (H1927R) and rs3765524 (T1777I) polymorphisms. Survival analysis showed PLCE1 rs7922612CT + TT genotype conferred adverse outcome to ESCC patients. Our study for the first time suggests that GWAS originated PLCE1 variants do not have independent role in susceptibility of ESCC in northern Indian population; however, a novel haplo-tagging SNP rs7922612 may modify survival outcome of ESCC patients.
KeywordsEsophageal cancer PLCE1 Polymorphisms Prognosis RFLP
Fellowship grant support from Indian Council of Medical Research (ICMR), New Delhi, is acknowledged. Funders had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in decision to submit the article for publication. The authors also want to acknowledge scholars from School of Telemedicine and Biomedical Informatics, SGPGIMS, for their help in in silico analysis.
Conflicts of interest
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