The DNMT3B -579G>T Polymorphism Is Significantly Associated With the Risk of Gastric Cancer but not Lung Cancer in Chinese Population

An updated meta-analysis investigating the association between DNMTs gene polymorphism andgastric cancer risk

Gastric cancer (GC) is a prominent global health issue, as it ranks as the fifth most prevalent type of cancer and the fourth most significant cause of cancer-related mortality worldwide. Although H. pylori is known to play a role in the development of GC, genetic factors also play a role in its onset and progression. Recent studies have shown that genetic polymorphisms are strongly associated with the development of GC and that certain single nucleotide polymorphisms (SNPs) can be used as biomarkers for early diagnosis and prevention. Epigenetic disturbances, such as DNA methylation, are involved in the development of GC, and mutations in the DNA methyltransferase (DNMT) gene have been found to increase the risk of GC. However, previous findings on the association between DNMTs SNPs and GC risk have been inconsistent. In this study, an updated meta-analysis of three well-studied and controversial DNMTs polymorphic loci, DNMT1 rs16999593, DNMT3A rs1550117 and DNMT3B rs1569686, was performed to provide more reliable results. It was found that DNMT1 rs16999593 was not associated with GC, DNMT3A rs1550117 may have a positive association with GC risk, and DNMT3B rs1569686 may be a protective factor for GC. These findings may provide valuable information for early diagnosis and prevention of GC, but further studies are needed to confirm these results.

Investigation of the DNMT3B -579 G>T Promoter Polymorphism in Patients with Colorectal Cancer in an Azerbaijani Population

OBJECTIVE

The main aim of the present study was to determine the clinical significance of the DNA methyltransferase 3B (DNMT3B) gene -579 G>T polymorphism in colorectal cancer (CRC) patients.

METHODS

A total of 140 patients with CRC and 164 healthy individuals were included in the study. According to the manufacturer's instructions, DNA was isolated from blood, and genotypes were determined on agarose gel by the PCR-RFLP method. Genotype confirmation was performed using Sanger sequencing in randomly selected samples.

RESULTS

When comparing the case and control groups, heterozygous GT (OR=0.53; 95% CI=0.32-0.88), under the dominant model (OR=0.53; 95% CI=0.33-0.87), and the mutant T allele (OR=0.71; 95% CI=0.51-0.98) were statistically associated with a reduced risk of CRC. However, when the age, pathological tumor grade and stage, smoking habit, and alcohol consumption were compared, no significant relationship was determined (P>0.05). Furthermore, among males, heterozygous GT was associated with a reduced risk of CRC (OR=0.40; 95% CI=0.19-0.84).

CONCLUSION

Our study highlighted that the -579 G>T polymorphism of the DNMT3B gene plays a protective role against CRC development.

Differential analysis of RNA methylation regulators in gastric cancer based on TCGA data set and construction of a prognostic model

Background

Methylation is one of the common forms of RNA modification, which mainly include N6-methyladenosine (m6A), C5-methylcytidine (m5C), and N1-methyladenosine (m1A). Numerous studies have shown that RNA methylation is associated with tumor development. We aim to construct prognostic models of gastric cancer based on RNA methylation regulators.

Methods

The transcriptome and clinical data of gastric cancer and normal samples were obtained from the National Cancer Institute Genome Data Commons (NCI-GDC). Use Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis to construct risk models for different types of RNA methylation. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive efficiency of risk characteristics. Cluster heat maps are used to assess the correlation with clinical information. Univariate and multivariate Cox analyses were used to analyze prognostic effects of risk scores. Gene Set Enrichment Analysis (GSEA) analyzes the functional enrichment of RNA methylation genes. And make a separate analysis of the data of Asians.

Results

The expression of most of the 30 RNA methylation regulators were significantly different in cancer and paracancerous tissues (P<0.05). Three methylated genes (FTO, ALKBH5, and RBM15) were screened from m6A by LASSO Cox regression analysis. Five methylated genes (FTO, ALKBH5, TRMT61B, RBM15, and YXB1) were selected from the population, and were used to construct two risk ratio models. Survival analysis showed that the survival rate of patients in the low-risk group was significantly higher than that in the high-risk group (P<0.05). All ROC curves indicated that the predictive efficiency of risk characteristics was good [area under the ROC curve (AUC): 0.6-1].Cluster analysis reveals differences in clinical data between the two groups. Univariate and multivariate Cox regression results show that the risk score has independent prognostic value. GSEA showed that pathways such as cell cycle were significantly enriched in the low-risk group, while pathways such as calcium signaling pathway were significantly enriched in the high-risk group. In addition, three methylation models that can predict the prognosis of Asian gastric cancer patients were obtained.

Conclusions

The methylation prognosis model constructed in this study can effectively predict the prognosis of gastric cancer patients.

Associations of BNIP3 and DAPK1 gene polymorphisms with disease susceptibility, clinicopathologic features, anxiety, and depression in gastric cancer patients

The purpose of this study is to explore the associations of BNIP3 and DAPK1 polymorphisms with disease susceptibility, clinicopathologic characteristics, depression, and anxiety in gastric cancer (GC) patients. In this study, 150 GC patients and 100 healthy controls were recruited. 1000 Genomes database and Haploview 4.0 software were used to select tag SNPs. Improved multiplex ligase detection reaction was used for genotyping. Data were analyzed using Chi-square test (χ² test) and univariate and multivariate logistic regression. The results demonstrated that the rs10781582 of BNIP3 in the dominant model was associated with a reduced risk of GC in the younger group (P _BH = 0.015), and the minor allele G of rs1329600 at DAPK1 was associated with reduced risk of GC (P _BH = 0.018). In the stratified analysis, the rs3793742 and rs10781582 of BNIP3 in the dominant model were associated with gender and age of GC patients, respectively (rs3793742: P _BH = 0.033; rs10781582: P _BH = 0.030). The rs10781582 of BNIP3 in the dominant model was correlated with depression in GC patients (P _BH = 0.003). However, no association was found between BNIP3 and DAPK1 polymorphisms and differentiation degree, TNM stage, lymph node metastases, visceral metastasis, and anxiety. In summary, polymorphisms of BNIP3 and DAPK1 were associated with a protective effect against GC. So far, this is the first study to explore the association between BNIP3 and DAPK1 gene polymorphism and GC risk, which may provide new insight about biologic mechanisms of GC pathogenesis.

Comparative analysis of three data mining techniques in diagnosis of lung cancer

There is a lot of abnormal information in the development of lung cancer, and how to extract useful knowledge is urgent from massive information. Data mining technology has become a popular tool for medical classification and prediction. However, each technology has its advantage and disadvantage, and several data mining methods will be applied to conduct the in-depth analysis step by step. And the prediction results of different models are compared. A total of 180 lung cancer patients and 243 lung benign individuals were collected from the First Affiliated Hospital of Zhengzhou University from October 2014 to March 2016, and the prediction models based on epidemiological data, clinical features and tumor markers were developed by artificial neural network (ANN), decision tree C5.0 and support vector machine (SVM). The results showed that there were significant differences between the lung cancer group and the lung benign group in terms of seven tumor markers and 10 epidemiological and clinical indicators. The accuracy rates of ANN, C5.0 and SVM were 76.47, 89.92 and 85.71%, respectively. The results of receiver operating characteristic curve (ROC) curve revealed the area under the ROC curve (AUC) of ANN was 0.811 (0.770-0.847), the AUC of C5.0 was 0.897 (0.864-0.924) and the AUC of SVM was 0.878 (0.843-0.908). It was shown that the decision tree C5.0 model has the least error rate and highest accuracy, and it could be used to diagnose lung cancer.

Methyltransferase DNMT3B in leukemia

DNA methyltransferases (DNMTs) are highly conserved DNA-modifying enzymes that play important roles in epigenetic regulation and they are involved in cell proliferation, differentiation, and apoptosis. In mammalian cells, three active DNMTs have been identified: DNMT1 acts as a maintenance methyltransferase to replicate preexisting methylation patterns, whereas DNMT3A and DNMT3B primarily act as de novo methyltransferases that are responsible for establishing DNA methylation patterns by adding a methyl group to cytosine bases. The expression of DNMT3B is widespread in a variety of hematological cells and it is altered in each type of leukemia, which is associated with its pathogenesis, progression, treatment, and prognosis. Here, we review current information on DNMT3B in leukemia, including its expression, single-nucleotide polymorphisms, mutations, regulation, function, and clinical value for anti-leukemic therapy and prognosis.

Effect of docetaxel-loaded lipid microbubble in combination with ultrasound-triggered microbubble destruction on the growth of a gastric cancer cell line

Although gastric cancer therapy has been improved, more efficient treatment strategies still need to be developed. In the present study, a docetaxel (DOC)-loaded lipid microbubble (DLLD) was prepared and the effect of DLLD combined with ultrasound-triggered microbubble destruction (UTMD) on the growth of a gastric cancer cell line was investigated. The following four groups were included in the present study: Control, DOC, DLLD and DLLD plus UTMD. The determined entrapment efficiency of DLLD is 76±3.5%. The present study demonstrated that treatment with DLLD plus UTMD could significantly inhibit the growth of the cultured gastric cancer cell line BGC-823 via arresting the cell cycle in G₂/M phase, inhibiting cell DNA synthesis, promoting cell apoptosis and disrupting mitochondrial membrane potential, as compared with treatment with DOC or DLLD alone. Furthermore, the expression of p53, p21 and Bax were identified to be significantly upregulated, while that of Bcl-2 was significantly downregulated in the DLLD plus UTMD group. Therefore, treatment with DLLD plus UTMD was more efficient in inhibiting cell proliferation and inducing cell apoptosis in the gastric cancer cell line, when compared with treatment with DOC or DLLD alone, suggesting that DLLD plus UTMD could serve as a promising strategy for the treatment of gastric cancer.

Therapeutic approach of Cancer stem cells (CSCs) in gastric adenocarcinoma; DNA methyltransferases enzymes in cancer targeted therapy

Cancer stem cells (CSCs) show a remarkable sub class of cancer cells population which have a potential to organize and regulate stemness properties which possess a main particular responsibility for uncontrolled growth in carcinogenesis, production of different cancers in differentiated situation and also resistancy to radiotherapy and chemotherapy. Correspondingly, gastric cancer (GC) as a very serious type in cancer mortality in the world, has received a deep attention in molecular therapy recently. Besides the main characteristics of CSCs like differentiation, epithelial mesenchymal transition, self-renewal and metastasis, they are so effective in expression of stemness genes resistancy in radiotherapy and chemotherapy. In this way, the regulation of epigenetic elements including DNA methylation and the performance of DNA methyltransferase (DNMT) which is a notable epigenetic trait in GC, is of great importance. Inhibitors of DNA methylation are the first epigenetic drugs in cancer therapy. Considerably, recent studies indicate that low doses of DNMT inhibitors have a high potential in sustaining reduced DNA methylation and related with re-expression of silenced genes in tumorigenesis. Importantly, these certain doses have the ability to decrease the carcinogenesis and tumorigenesis in CSC populations within GC. Meaningly, the inhibition of DNMTs are able to reduce the accumulation of tumorigenic ability of GC CSCs. Furthermore, many epigenetic drugs have a great potential in cancer therapy, including histone methyltransferases, lysine demethylases, histone deacetylasesand, bromodomain and extra-terminal domain proteins and DNA methyltransferases inhibitors. In this review article, we try to focus on the therapeutic mechanism of DNMTs alongside with their impact on CSCs in GC.

Genetic polymorphisms and gastric cancer risk: a comprehensive review synopsis from meta-analysis and genome-wide association studies

Objective

In the past few decades, more than 500 reports have been published on the relationship between single nucleotide polymorphisms (SNPs) on candidate genes and gastric cancer (GC) risk. Previous findings have been disputed and are controversial. Therefore, we performed this article to summarize and assess the credibility and strength of genetic polymorphisms on the risk of GC.

Methods

We used Web of Science, PubMed, and Medline to identify meta-analyses published before July 30th, 2018 that assessed associations between variants on candidate genes and the risk of GC. Cumulative epidemiological evidence of statistical associations was assessed combining Venice criteria and a false-positive report probability (FPRP) test.

Results

Sixty-one variants demonstrated a significant association with GC risk, whereas 29 demonstrated no association. Nine variants on nine genes were rated as presenting strong cumulative epidemiological evidence for a nominally significant association with GC risk, including APE1 (rs1760944), DNMT1 (rs16999593), ERCC5 (rs751402), GSTT1 (null/presence), MDM2 (rs2278744), PPARG (rs1801282), TLR4 (rs4986790), IL-17F (rs763780), and CASP8 (rs3834129). Eleven SNPs were rated as moderate, and 33 SNPs were rated as weak. We also used the FPRP test to identify 13 noteworthy SNPs in five genome-wide association studies.

Conclusions

Sixty-one variants are significantly associated with GC risk, and 29 variants are not associated with GC risk; however, five variants on five genes presented strong evidence for an association upgraded from moderate. Further study of these variants may be needed in the future. Our study also provides referenced information for the genetic predisposition to GC.

DNA methyltransferases and gastric cancer: insight into targeted therapy

Gastric cancer is a major health problem worldwide occupying most frequent causes of cancer-related mortality. In addition to genetic modifications, epigenetic alterations catalyzed by DNA methyltransferases (DNMTs) are a well-characterized epigenetic hallmark in gastric cancer. The reversible nature of epigenetic alterations and central role of DNA methylation in diverse biological processes provides an opportunity for using DNMT inhibitors to enhance the efficacy of chemotherapeutics. In this review, we discussed key factors or mechanisms such as SNPs, infections and genetic modifications that trigger DNMTs level modification in gastric cancer, and their potential roles in cancer progression. Finally, we focused on how inhibitors of the DNMTs can most effectively be used for the treatment of gastric cancer with multidrug resistance.