XPD Lys751Gln polymorphisms and the risk of esophageal cancer: an updated meta-analysis

ERCC2 rs13181 Polymorphism Association with Glioma Risk: an Update Meta-Analysis

Glioma is the most common type of primary brain tumour which accounts for about 30% of all brain and central nervous system tumours, and approximately 70% of adult malignant brain tumours. Numerous studies have been performed to assess the relationship between ERCC2 rs13181 polymorphism and the risk of glioma development, yet these findings of these studies are often inconsistent and contradictory. Therefore, the aim of this study is to conduct a systematic review and meta-analysis to assess the role of ERCC2 rs13181 in glioma developing. In this work, we have conducted a systematic review and meta-analysis. In order to collect the results of relevant studies on the association of ERCC2 rs13181 gene polymorphism with glioma, we initially searched the Scopus, Embase, Web of Science (WoS), PubMed, and ScienceDirect databases, without a lower time limit, and until June 2020. In order to analyse the eligible studies, the random effects model was used and the heterogeneity of the studies was investigated with the I 2 index. Data analysis was performed within the Comprehensive Meta-Analysis software (version 2). The total number of studies that focused on patients with glioma was 10. The odds ratio of GG vs TT genotype in patients with glioma based on meta-analysis was 1.08 (0.85-1.37: 95% confidence interval), which indicates the increasing effect of GG vs TT genotype by 0.08. The odds ratio of GG + TG vs TT genotype in patients with glioma was 1.22 (1.38-1.7: 95% confidence interval) based on meta-analysis, which indicates the increasing effect of GG + TG vs TT genotype as 0.22. The odds ratio of TG vs TT genotype in patients with glioma was 1.2 (0.38-1.4: 95% confidence interval), which shows the increasing effect of TG vs TT genotype by 0.2. The odds ratio of G vs T genotype in patients with glioma based on the meta-analysis was 1.15 (1.26-1.4: 95% confidence interval), which indicates the increasing effect of G vs T genotype by 0.15. The odds ratio of GG vs TG + TT genotype in patients with glioma based on meta-analysis was 1.22 (1.33-1.45: 95% confidence interval), which indicates the increasing effect of GG vs TG + TT genotype by 0.22. The results of this systematic review and meta-analysis show that ERCC2 rs13181 polymorphism and its genotypes are an important risk factor for genetic susceptibility to glioma tumour.

Higher order genes interaction in DNA repair and cytokine genes polymorphism and risk to lung cancer in North Indians

Context

Lung cancer pathological process involves cumulative effects exerted by gene polymorphism(s), epigenetic modifications, and alterations in DNA repair machinery. Further, DNA damage due to oxidative stress, chronic inflammation, and the interplay between genetic and environmental factors is also an etiologic milieu of this malignant disease.

Aims

The present study aims to assess the prognostic value of DNA repair, cytokines, and GST gene polymorphism in lung cancer patients who had not received any neoadjuvant therapy.

Materials and Methods

In this case-control study, 127 cases and 120 controls were enrolled. DNA from the blood samples of both patients and controls was used to genotype XRCC1Arg399Gln, XPDLys751Gln, and interleukin-1 (IL-1β) genes by polymerase chain reaction (PCR)-restriction fragment length polymorphism method, whereas multiplex PCR was performed to genotype GSTT1 and GSTM1.

Results

Binary logistic regression analysis showed that XRCC1Arg399Gln-mutant genotype (Gln/Gln, odds ratio [OR] = 4.6, 95% confidence interval [CI]: 2.2-9.6) and GSTT1 null (OR = 2.7, 95% CI: 1.6-4.5) were linked to cancer susceptibility. Generalized multidimensional reduction analysis of higher order gene-gene interaction using cross-validation testing (CVT) accuracy showed that GSTT1 (CVT 0.62, P = 0.001), XPD751 and IL-1β (CVT 0.6, P = 0.001), and XRCC1399, XPD751, and interleukin-1 receptor antagonists (IL-1RN) (CVT 0.98, P = 0.001) were single-, two-, and three-factor best model predicted, respectively, for lung cancer risk. Classification and regression tree analysis results showed that terminal nodes which contain XRCC1399-mutant genotype (AA) had increased the risk to lung cancer.

Conclusion

The present study demonstrated that XRCC1399 (Gln/Gln), GSTT1, and IL-1RN allele I, I/II served as the risk genotypes. These genes could serve as the biomarkers to predict lung cancer risk.

Cumulative evidence for association between genetic polymorphisms and esophageal cancer susceptibility: A review with evidence from meta-analysis and genome-wide association studies

An increasing number of publications had reported the association between single‐nucleotide polymorphisms (SNPs) and esophageal cancer (EC) risk in the past decades. Results from these publications were controversial. We used PubMed, Medline, and Web of Science to identify meta‐analysis articles published before 30 July 2018, that summarize a comprehensive investigation for cumulative evidence of genetic polymorphisms of EC and its subtype risk. Two methods, Venice criteria and false‐positive report probability (FPRP) tests, were used to assess cumulative evidence of significant associations. At last, 107 meta‐analyses were considered to be in conformity with the inclusion criteria, yielding 51 variants associated with EC or esophageal squamous cell carcinoma (ESCC). Thirty‐eight variants were considered to be nominally significant associated with risk of EC or ESCC, whereas the rest showed non‐association. In additional, five variants on five genes were rated as strong cumulative epidemiological evidence for a nominally significant association with EC and ESCC risk, including CYP1A1 rs1048943, EGF rs444903, HOTAIR rs920778, MMP2 rs243865, and PLCE1 rs2274223, 10 variants were rated as moderate, and 18 variants were rated as weak. Additionally, 17 SNPs were verified noteworthy in six genomewide association studies (GWAS) using FPRP methods. Collectively, this review offered a comprehensively referenced information with cumulative evidence of associations between genetic polymorphisms and EC and ESCC risk.

Exploratory analysis of ERCC2 DNA methylation in survival among pediatric medulloblastoma patients

AIM

Medulloblastoma is the most frequent malignant pediatric brain tumor. While survival rates have improved due to multimodal treatment including cisplatin-based chemotherapy, there are few prognostic factors for adverse treatment outcomes. Notably, genes involved in the nucleotide excision repair pathway, including ERCC2, have been implicated in cisplatin sensitivity in other cancers. Therefore, this study evaluated the role of ERCC2 DNA methylation profiles on pediatric medulloblastoma survival.

METHODS

The study population included 71 medulloblastoma patients (age <18years at diagnosis) and recruited from Texas Children's Cancer Center between 2004 and 2009. DNA methylation profiles were generated from peripheral blood samples using the Illumina Infinium Human Methylation 450 Beadchip. Sixteen ERCC2-associated CpG sites were evaluated in this analysis. Multivariable regression models were used to determine the adjusted association between DNA methylation and survival. Cox regression and Kaplan-Meier curves were used to compare 5-year overall survival between hyper- and hypo-methylation at each CpG site.

RESULTS

In total, 12.7% (n=9) of the patient population died within five years of diagnosis. In our population, methylation of the cg02257300 probe (Hazard Ratio=9.33; 95% Confidence Interval: 1.17-74.64) was associated with death (log-rank p=0.01). This association remained suggestive after correcting for multiple comparisons (FDR p<0.2). No other ERCC2-associated CpG site was associated with survival in this population of pediatric medulloblastoma patients.

CONCLUSION

These findings provide the first evidence that DNA methylation within the promoter region of the ERCC2 gene may be associated with survival in pediatric medulloblastoma. If confirmed in future studies, this information may lead to improved risk stratification or promote the development of novel, targeted therapeutics.