A Model for Gastric Cancer Risk Prediction Based on MUC1 Polymorphisms and Health-risk Behaviors in a Vietnamese Population

Abstract

Background/aim: Although the expression of mucin 1(MUC1) and prostate stem cell antigen (PSCA) genes is correlated with gastric cancer development and progression, the utility of these two genes as biomarkers of gastric cancer prognosis still needs to be confirmed in clinical practice. This study aimed to develop a model predictive of gastric cancer that integrates several significant single nucleotide polymorphisms (SNPs) of MUC1 and PSCA genes, and some health-risk behavior factors in a Vietnamese population.

Patients and methods: A total of 302 patients with primary gastric carcinoma and 304 healthy persons were included in a case-control study. The generalized linear model was used with the profile of age, sex, history of smoking and using alcohol, personal and family medical history of stomach diseases, and the SNPs of MUC1 and PSCA. The prognostic value of the model was assessed by the area under a receiver operating characteristic curve (AUC) and Akaike Information Criterion (AIC) values.

Results: In male participants, the final model, consisting of age, sex, history of smoking and using alcohol, personal and family medical history of stomach diseases and SNP MUC1 rs4072037, provided acceptable discrimination, with an AUC of 0.6374 and the lowest AIC value (539.53). In female participants, the predictive model including age, sex, history of smoking and using alcohol, personal and family medical history of stomach diseases, SNPs MUC1 rs4072037 and rs2070803 had an AUC of 0.6937 and AIC of 266.80. The calibration plots of the male model approximately fitted the ideal calibration line.

Conclusion: The predictive model based on age, sex, medical history, and genetic and health-risk behavior factors has a high potential in determining gastric cancer. Further studies that elucidate other genetic variants should be carried out to define high-risk gastric cancer groups and propose appropriate personalized prevention.

Keywords: Gastroenterology; cancer genetics; molecular aspects.