The association study between CYP24A1 gene polymorphisms and risk of liver, lung and gastric cancer in a Chinese population

Association Between CYP24A1 Polymorphisms and Bladder Cancer Risk in the Chinese Han Population

In this cohort of 217 bladder cancer patients and 484 healthy controls, we explored the association between CYP24A1 variants (rs2762934, rs1570669, rs6068816, rs2296241) and bladder cancer risk in the Chinese Han population. Utilizing the Agena MassARRAY system, we genotyped four selected CYP24A1 polymorphisms. Logistic regression revealed a significant association of rs2762934 and rs1570669 with elevated bladder cancer risk, while rs6068816 exhibited a protective effect. Bioinformatics analysis of CYP24A1 expression in normal and cancerous bladder tissues indicated higher expression in normal tissue. In conclusion, our findings highlight the potential role of CYP24A1 variants in bladder cancer susceptibility.

Effect of Single Nucleotide Polymorphisms in the Vitamin D Metabolic Pathway on Susceptibility to Non-Small-Cell Lung Cancer

The pathogenesis of non-small-cell lung cancer (NSCLC) is complex, since many risk factors have been identified. Recent research indicates that polymorphisms in the metabolic pathway of vitamin D may be involved in both risk and survival of the disease. The objective of this study is to assess the effect of 13 genetic polymorphisms involved in the vitamin D metabolic pathway on the risk of suffering from NSCLC. We conducted an observational case-control study, which included 204 patients with NSCLC and 408 controls, of Caucasian origin, from southern Spain. The CYP27B1 (rs4646536, rs3782130, rs703842, rs10877012), CYP2R1 (rs10741657), GC (rs7041), CYP24A1, and VDR (BsmI, Cdx-2, FokI, ApaI, TaqI) gene polymorphisms were analyzed by real-time polymerase chain reaction. The logistic regression model, adjusted for smoking and family history of cancer, revealed that in the genotypic model, carriers of the VDR BsmI rs1544410-AA genotype were associated with a lower risk of developing NSCLC compared to the GG genotype (p = 0.0377; OR = 0.51; CI95% = 0.27-0.95; AA vs. GG). This association was maintained in the recessive model (p = 0.0140). Haplotype analysis revealed that the AACATGG and GACATGG haplotypes for the rs1544410, rs7975232, rs731236, rs4646536, rs703842, rs3782130, and rs10877012 polymorphisms were associated with a lower risk of NSCLC (p = 0.015 and p = 0.044 respectively). The remaining polymorphisms showed no effect on susceptibility to NSCLC. The BsmI rs1544410 polymorphism was significantly associated with lower risk of NSCLC and could be of considerable value as a predictive biomarker of the disease.

Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer

Background: An imbalance in the redox homeostasis has been reported in multiple cancers and is associated with a poor prognosis of disease. However, the prognostic value of redox-related genes in non-small-cell lung cancer (NSCLC) remains unclear.

Methods: RNA sequencing data, DNA methylation data, mutation, and clinical data of NSCLC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Redox-related differentially expressed genes (DEGs) were used to construct the prognostic signature using least absolute shrinkage and selection operator (LASSO) regression analysis. Kaplan–Meier survival curve and receiver operator characteristic (ROC) curve analyses were applied to validate the accuracy of the gene signature. Nomogram and calibration plots of the nomogram were constructed to predict prognosis. Pathway analysis was performed using gene set enrichment analysis. The correlations of risk score with tumor stage, immune infiltration, DNA methylation, tumor mutation burden (TMB), and chemotherapy sensitivity were evaluated. The prognostic signature was validated using GSE31210, GSE26939, and GSE68465 datasets. Real-time polymerase chain reaction (PCR) was used to validate dysregulated genes in NSCLC.

Results: A prognostic signature was constructed using the LASSO regression analysis and was represented as a risk score. The high-risk group was significantly correlated with worse overall survival (OS) (p < 0.001). The area under the ROC curve (AUC) at the 5-year stage was 0.657. The risk score was precisely correlated with the tumor stage and was an independent prognostic factor for NSCLC. The constructed nomogram accurately predicted the OS of patients after 1-, 3-, and 5-year periods. DNA replication, cell cycle, and ECM receptor interaction were the main pathways enriched in the high-risk group. In addition, the high-risk score was correlated with higher TMB, lower methylation levels, increased infiltrating macrophages, activated memory CD4⁺ T cells, and a higher sensitivity to chemotherapy. The signature was validated in GSE31210, GSE26939, and GSE68465 datasets. Real-time PCR validated dysregulated mRNA expression levels in NSCLC.

Conclusions: A prognostic redox-related gene signature was successfully established in NSCLC, with potential applications in the clinical setting.

Vitamin D Metabolic Pathway Genes Polymorphisms and Their Methylation Levels in Association With Rheumatoid Arthritis

Abnormal vitamin D metabolism is involved in the pathogenesis of rheumatoid arthritis (RA). In this study, we evaluated the association of single nucleotide polymorphisms (SNPs) and methylation levels in vitamin D metabolic pathway genes with RA susceptibility. Ten SNPs in vitamin D metabolic pathway genes (CYP2R1, CYP24A1, VDR, CYP27B1) were genotyped in 477 RA patients and 496 controls by improved multiple ligase detection reaction (iMLDR). The methylation levels of the promoter regions of these genes were detected in 122 RA patients and 123 controls using Illumina Hiseq platform. We found that the CYP2R1 rs1993116 GA genotype, CYP27B1 rs4646536 GA genotype, rs4646536 A allele frequencies were significantly increased in RA patients when compared to controls. The decreased risk of rs1993116, rs4646536 was found under the dominant mode in RA patients. However, no significant association was found between CYP2R1 rs7936142, rs12794714, CYP24A1 rs2762934, rs6068816, rs2296239, rs2296241, VDR rs11574129, rs3847987 polymorphism, and RA susceptibility. The VDR, CYP27B1 methylation levels in RA patients were significantly lower than those in controls, while CYP2R1, CYP24A1 methylation levels were not associated with RA. There were no statistical associations between CYP2R1, CYP24A1, VDR, CYP27B1 methylation levels and their respective genotype in RA patients. In addition, plasma 25OHD level in RA patients was significantly lower than that in healthy controls. In summary, our results showed that CYP2R1, CYP27B1 genetic variations were associated with the genetic background of RA, while altered VDR, CYP27B1 methylation levels were related to the risk of RA.

Establishment of non-small-cell lung cancer risk prediction model based on prognosis-associated ADME genes

PURPOSE

ADME genes are those involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs. In the present study, a non-small-cell lung cancer (NSCLC) risk prediction model was established using prognosis-associated ADME genes, and the predictive performance of this model was evaluated and verified. In addition, multifaceted difference analysis was performed on groups with high and low risk scores.

METHODS

An NSCLC sample transcriptome and clinical data were obtained from public databases. The prognosis-associated ADME genes were obtained by univariate Cox and lasso regression analyses to build a risk model. Tumor samples were divided into high-risk and low-risk score groups according to the risk score. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the differentially expressed genes and the differences in the immune infiltration, mutation, and medication reactions in the two groups were studied in detail.

RESULTS

A risk prediction model was established with seven prognosis-associated ADME genes. Its good predictive ability was confirmed by studies of the model's effectiveness. Univariate and multivariate Cox regression analyses showed that the model's risk score was an independent prognostic factor for patients with NSCLC. The study also showed that the risk score closely correlated with immune infiltration, mutations, and medication reactions.

CONCLUSION

The risk prediction model established with seven ADME genes in the present study can predict the prognosis of patients with NSCLC. In addition, significant differences in immune infiltration, mutations, and therapeutic efficacy exist between the high- and low-risk score groups.