Contribution of DNA repair xeroderma pigmentosum group D genotypes to pancreatic cancer risk in the Chinese Han population

Genetic polymorphisms and haplotypes of ERCC1 and ERCC2 associated with quality of life, depression, and anxiety status among patients with lung cancer

BACKGROUND

Patients with lung cancer (LC) have a poor quality of life (QoL) and easily suffer from psychological diseases. Previous studies focused less on the relationship between genetic factors and QoL, depression, and anxiety status in LC patients. The current study is intended to explore the relationship between SNPs and haplotypes of ERCC1 and ERCC2 and the QoL, depression and anxiety status of patients with LC.

METHODS

QoL, depression and anxiety status were assessed in 291 LC patients using the European Organization for Research and Treatment of Cancer (EORTC) Core Quality of Life Questionnaire (QLQ-C30), EORTC Quality of Life Questionnaire-Lung Cancer 13 (QLQ-LC13), SDS and SAS. Nine tag SNPs of ERCC1 and ERCC2 were detected using an improved multiplex ligation detection reaction (iMLDR) technique. Haplotype analysis was conducted using the software Haploview 4.2. The association between SNPs or haplotypes and QoL or depression or anxiety in LC patients was analyzed by regression analysis.

RESULTS

ERCC1 rs11615 was associated with emotional functioning (P = 0.027), and ERCC1 rs3212986 was associated with anxiety scores (P = 0.018). ERCC1 rs762562-rs3212986 haplotype was associated with cognitive function (P = 0.029), somatic function (P = 0.014) and dysphagia (OR = 3.32, P = 0.044). Patients with ERCC1 rs3212986-rs11615 AG haplotype had worse cognitive function (adjusted Beta = - 5.42) and somatic function (adjusted Beta = - 6.55) and had severer symptoms of loss of appetite (adjusted OR = 1.67) and dysphagia (adjusted OR = 4.43) (All adjusted P < 0.05). ERCC2 rs13181-rs3916874-rs238416 haplotype was associated with emotional functioning (P = 0.035), pain at other sites (OR 1.88, P = 0.014), chest pain (OR 0.42, P = 0.02), dysphagia (OR 2.82, P = 0.048), and anxiety status (OR 0.23, P = 0.009).

CONCLUSION

After adjustment for environmental factors, SNPs and haplotypes of ERCC1 and ERCC2 were associated with different domains of QoL, depression and anxiety in LC patients.

A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk

In this meta-analysis, we systematically investigated the correlation between single nucleotide polymorphisms (SNPs) and pancreatic cancer (PC) risk. We searched PubMed, Network Science, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Periodical Database (VIP), and Wanfang databases up to January 2020 for studies on PC risk-associated SNPs. We identified 45 case-control studies (36,360 PC patients and 54,752 non-cancer individuals) relating to investigations of 27 genes and 54 SNPs for this meta-analysis. Direct meta-analysis followed by network meta-analysis and Thakkinstian algorithm analysis showed that homozygous genetic models for CTLA-4 rs231775 (OR =0.326; 95% CI: 0.218-0.488) and VDR rs2228570 (OR = 1.976; 95% CI: 1.496-2.611) and additive gene model for TP53 rs9895829 (OR = 1.231; 95% CI: 1.143-1.326) were significantly associated with PC risk. TP53 rs9895829 was the most optimal SNP for diagnosing PC susceptibility with a false positive report probability < 0.2 at a stringent prior probability value of 0.00001. This systematic review and meta-analysis suggest that TP53 rs9895829, VDR rs2228570, and CTLA-4 rs231775 are significantly associated with PC risk. We also demonstrate that TP53 rs9895829 is a potential diagnostic biomarker for estimating PC risk.

A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis

BACKGROUND

Single nucleotide polymorphisms (SNPs) have been inconsistently associated with pancreatic cancer (PC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with PC.

METHODS

Databases were searched to identify association studies of SNPs and PC published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database (VIP) and Wanfang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability (FPRP) for noteworthy associations. The methodological quality of data was assessed based on the STREGA statement Stata 14.0 will be used for systematic review and meta-analysis.

RESULTS

This study will provide a high-quality evidence to find the SNP most associated with pancreatic cancer susceptibility and the best genetic model.

CONCLUSIONS

This study will explore which SNP is most associated with pancreatic cancer susceptibility.Registration: INPLASY202040023.

Associations of mRNA expression of DNA repair genes and genetic polymorphisms with cancer risk: a bioinformatics analysis and meta-analysis

A systematical bioinformatics and meta-analysis were carried out to establish our understanding of possible relationships between DNA repair genes and the development of cancer. The bioinformatics analysis confirmed that lower XPA and XPC levels and higher XPD, XPF, and WRN levels were observed in 19 types of cancer, and subsequently results indicated that elevated XPA and XPC had a better impact on overall survival, however, higher XPD, XPF, and WRN showed worse influence on cancer prognosis. The meta-analysis included 58 eligible studies demonstrated that harboring XPA rs10817938, XPD rs238406 increased overall cancer risk, however, XPA rs2808668 SNP in overall cancer analysis and XPF rs3136038 in the digestive system remarkably reduced the cancer risk. Moreover, no correlation was investigated for XPC rs1870134, WRN rs1346044 and rs1801195. These suggest that the DNA repair gene was associated with carcinogenesis, and contribute to the prognosis, and the critical SNPs further involved in affecting cancer risk.