Development of a general logistic model for disease risk prediction using multiple SNPs

TET3 gene rs828867 G>A polymorphism reduces neuroblastoma risk in Chinese children

Objective

Neuroblastoma (NB) is a prevalent pediatric tumor originating from primordial neural crest cells. As one of the latest epigenetics investigations focuses, RNA 5-methylcytosine (m5C) is closely related to cancer risk. TET methylcytosine dioxygenase 3 (TET3) is a demethylase for m5C modification. Whether there is an association between TET3 gene polymorphisms and neuroblastoma risk remains unclear.

Methods

We conducted an epidemiological study in 402 patients and 473 controls to evaluate the relationship between TET3 gene SNPs (rs7560668 T > C, rs828867 G > A, and rs6546891 A > G) and NB susceptibility.

Results

Our results showed that rs828867 G > A significantly reduced NB risk in Chinese children [GA vs. GG, adjusted odds ratio (OR) = 0.72, 95% confidence interval (CI) = 0.52-0.98, P=0.040; GA/AA vs. GG, adjusted OR = 0.74, 95% CI = 0.55-0.998, P=0.048]. Individuals with 2-3 risk genotypes had a significantly higher NB risk than those with 0-1 risk genotypes (adjusted OR = 1.40, 95% CI = 1.04-1.88, P=0.027). The stratified analysis showed that the rs828867 G > A associated with decreased NB risk is remarkable among children aged >18 months (adjusted OR = 0.67, 95% CI = 0.46-0.96, P=0.029) and patients at clinical III + IV stages (adjusted OR = 0.67, 95% CI = 0.45-0.98, P=0.040). Compared with the 0-1 risk genotype, the concurrence of 2-3 risk genotypes significantly increased NB risk in the following subgroups: children aged >18 months and patients at clinical III + IV stages. GTEx analysis suggested that rs828867 G > A was significantly associated with RP11-287D1.4 and POLE4 mRNA expression.

Conclusions

Overall, our results revealed that rs828867 G > A in the TET3 gene is significantly associated with predisposition to NB.

Assessment for Risk Status of Colorectal Cancer Patients: A Novel Prediction Model Based on Immune-Related Genes

Heterogeneity in patients with colorectal cancer (CRC) leads to different strategies in clinical decision making. Identifying distinctive subgroups in patients contributes to develop more individualized treatments. This study constructed a novel prediction model for the prognosis of CRC patients based on the value of risk score combining the expression status of immune-related genes and coefficients. In this study, we built an interactive network of prognosis-related immune genes and transcription factors and adopted several methods to verify the accuracy of model. Moreover, we assessed the correlation between risk score and immune infiltration. The results suggested that the model was well fit and the risk score could be an independent predictive factor for CRC patients. This model has high application value in the clinic.