ABSTRACT
Genetic variations are associated with individual susceptibility to gastric cancer. Recently, polygenic risk score (PRS) models have been established based on genetic variants to predict the risk of gastric cancer. To assess the accuracy of current PRS models in the risk prediction, a systematic review was conducted. A total of eight eligible studies consisted of 544842 participants were included for evaluation of the performance of PRS models. The overall accuracy was moderate with Area under the curve values ranging from 0.5600 to 0.7823. Incorporation of epidemiological factors or Helicobacter pylori (H. pylori) status increased the accuracy for risk prediction, while selection of single nucleotide polymorphism (SNP) and number of SNPs appeared to have little impact on the model performance. To further improve the accuracy of PRS models for risk prediction of gastric cancer, we summarized the association between gastric cancer risk and H. pylori genomic variations, cancer associated bacteria members in the gastric microbiome, discussed the potentials for performance improvement of PRS models with these microbial factors. Future studies on comprehensive PRS models established with human SNPs, epidemiological factors and microbial factors are indicated.
ABSTRACT
BACKGROUND: Genetic variants of Helicobacter pylori (H. pylori) are involved in gastric cancer occurrence. Single nucleotide polymorphisms (SNPs) of H. pylori that are associated with gastric cancer have been reported. The combined effect of H. pylori SNPs on the risk of gastric cancer remains unclear. AIM: To assess the performance of a polygenic risk score (PRS) based on H. pylori SNPs in predicting the risk of gastric cancer. METHODS: A total of 15 gastric cancer-associated H. pylori SNPs were selected. The associations between these SNPs and gastric cancer were further validated in 1022 global strains with publicly available genome sequences. The PRS model was established based on the validated SNPs. The performance of the PRS for predicting the risk of gastric cancer was assessed in global strains using quintiles and random forest (RF) methods. The variation in the performance of the PRS among different populations of H. pylori was further examined. RESULTS: Analyses of the association between selected SNPs and gastric cancer in the global dataset revealed that the risk allele frequencies of six SNPs were significantly higher in gastric cancer cases than non-gastric cancer cases. The PRS model constructed subsequently with these validated SNPs produced significantly higher scores in gastric cancer. The odds ratio (OR) value for gastric cancer gradually increased from the first to the fifth quintile of PRS, with the fifth quintile having an OR value as high as 9.76 (95% confidence interval: 5.84-16.29). The results of RF analyses indicated that the area under the curve (AUC) value for classifying gastric cancer and non-gastric cancer was 0.75, suggesting that the PRS based on H. pylori SNPs was capable of predicting the risk of gastric cancer. Assessing the performance of the PRS among different H. pylori populations demonstrated that it had good predictive power for cancer risk for hpEurope strains, with an AUC value of 0.78. CONCLUSION: The PRS model based on H. pylori SNPs had a good performance for assessment of gastric cancer risk. It would be useful in the prediction of final consequences of the H. pylori infection and beneficial for the management of the infection in clinical settings.
ABSTRACT
MicroRNAs (miRNAs) play an important role in the regulation of human cancers, including breast cancer (BC). In the current study, we examined the expression pattern of the miRNA miR-125a-5p in human BC tissues, tumorigenesis of BC progression. We found that miR-125a-5p was significantly downregulated in human BC tissues. Overexpression of miR-125a-5p in a xenograft mouse model indicated that miR-125a-5p may function as a tumour suppressor during carcinogenesis. To explore the molecular mechanism by which miR-125a-5p contributes to BC progression, we predicted the target genes of miR-125a-5p and identified BC susceptibility gene 1-associated protein 1 (BAP1) as a direct target. Finally, we demonstrated that BAP1 had opposing effects to those of miR-125a-5p on BC cells, suggesting that miR-125a-5p may inhibit cell proliferation and promote cell apoptosis by negatively regulating BAP1. Taken together, our findings provide the first clues regarding the role of miR-125a-5p as a tumour suppressor in BC via the inhibition of BAP1 translation.
