scholarly journals No association between HMGB1 polymorphisms and cancer risk: evidence from a meta-analysis

2018 ◽  
Vol 38 (5) ◽  
Author(s):  
Xing-yan Li ◽  
Chun-hua Liang ◽  
Ye-jing Yang ◽  
Lei Liu ◽  
Yong-jun Du ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Large Scale ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
High Mobility ◽  
Statistical Association ◽  
Cancer Risks ◽  
Data Collection Sheet ◽  
Language Restriction ◽  
Risk Of Cancer

The aim of the present study was to determine whether High mobility group box 1 (HMGB1) polymorphism was associated with cancer susceptibility. PubMed, Embase, and ISI Web of Science were extensively searched without language restriction. Data were extracted using a standardized data collection sheet after two reviewers scanned studies independently. The association between HMGB1 polymorphism and cancer risks was indicated as odds ratio (OR) along with its related 95% confidence interval (95%CI). Meta-analysis was conducted via RevMan 5.3 software. A total of ten studies comprising 4530 cases and 5167 controls were included in our study. Meta-analysis revealed no statistical association between rs1045411, rs1360485, rs1412125, or rs2249825 polymorphisms in HMGB1 gene and risk of cancer, either did subgroup analysis of rs1045411 stratified by cancer types and ethnic groups. Our results revealed no statistical association between current four polymorphism loci and cancer risks, suggesting that the attempt of applying HMGB1 variants as a therapeutic target or a prognosis predictor might still require a second thought. However, HMGB1 is deemed to play pleiotropic roles in cancers, we strongly call for large-scale studies with high evidence level to uncover the exact relationship between HMGB1 gene variants and cancer progression.

scholarly journals Genetic variants in the MicroRNA biosynthetic pathway Gemin3 and Gemin4 are associated with a risk of cancer: a meta-analysis

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1724 ◽  
Author(s):  
Wenbo Zhu ◽  
Jun Zhao ◽  
Jieyu He ◽  
Daxun Qi ◽  
Lina Wang ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Biosynthetic Pathway ◽  
Web Of Science ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
China National Knowledge Infrastructure ◽  
Knowledge Infrastructure ◽  
Language Restriction ◽  
On Line ◽  
Risk Of Cancer

The effects of the microRNA (miRNA) processing genes Gemin3 and Gemin4 on cellular signaling pathways could have a major impact on the risk of cancer. Several studies concerning the association between the Gemin3 rs197412, Gemin4 rs7813 and Gemin4 rs2740348 polymorphisms with cancer susceptibility have been published. The present meta-analysis summarized this evidence and evaluated the precision of these relationships. Relevant studies (published prior to December 16th, 2015) without language restriction were identified using the PubMed, Web of Science and China National Knowledge Infrastructure (CNKI) on-line databases. The data were extracted from the eligible studies and were processed using Stata 12.0 software. Seven studies (2,588 cases and 2,549 controls) indicated that the rs7813 polymorphism was significantly associated with increased cancer risk (TT vs TC + CC, OR = 1.18 95% CI [1.05–1.32]). Six studies (1,314 cases and 1,244 controls) indicated that rs2740348 was associated with an increased cancer risk (GG vs. GC + CC, OR = 1.41 95% CI [1.00–1.83]). However the rs197412 polymorphism was not associated with an increased cancer risk (OR = 0.97 95% CI [0.80–1.19]). Our results suggest that the Gemin4 rs7813 T > C and rs2740348 G > C polymorphisms are associated with cancer susceptibility.

scholarly journals The association between XRCC3 rs1799794 polymorphism and cancer risk: a meta-analysis of 34 case–control studies

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Weiqing Liu ◽  
Shumin Ma ◽  
Lei Liang ◽  
Zhiyong Kou ◽  
Hongbin Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Thyroid Cancer ◽  
Cancer Risk ◽  
Large Scale ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Cancer Type ◽  
Increased Risk ◽  
Risk Of Cancer

Abstract Background Studies on the XRCC3 rs1799794 polymorphism show that this polymorphism is involved in a variety of cancers, but its specific relationships or effects are not consistent. The purpose of this meta-analysis was to investigate the association between rs1799794 polymorphism and susceptibility to cancer. Methods PubMed, Embase, the Cochrane Library, Web of Science, and Scopus were searched for eligible studies through June 11, 2019. All analyses were performed with Stata 14.0. Subgroup analyses were performed by cancer type, ethnicity, source of control, and detection method. A total of 37 studies with 23,537 cases and 30,649 controls were included in this meta-analysis. Results XRCC3 rs1799794 increased cancer risk in the dominant model and heterozygous model (GG + AG vs. AA: odds ratio [OR] = 1.04, 95% confidence interval [CI] = 1.00–1.08, P = 0.051; AG vs. AA: OR = 1.05, 95% CI = 1.00–1.01, P = 0.015). The existence of rs1799794 increased the risk of breast cancer and thyroid cancer, but reduced the risk of ovarian cancer. In addition, rs1799794 increased the risk of cancer in the Caucasian population. Conclusion This meta-analysis confirms that XRCC3 rs1799794 is related to cancer risk, especially increased risk for breast cancer and thyroid cancer and reduced risk for ovarian cancer. However, well-designed large-scale studies are required to further evaluate the results.

scholarly journals Validation of a Semiautomated Natural Language Processing–Based Procedure for Meta-Analysis of Cancer Susceptibility Gene Penetrance

2019 ◽  
pp. 1-9 ◽  
Author(s):  
Zhengyi Deng ◽  
Kanhua Yin ◽  
Yujia Bao ◽  
Victor Diego Armengol ◽  
Cathy Wang ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Susceptibility Gene ◽  
Cancer Susceptibility Genes ◽  
Traditional Procedure ◽  
Meta Analyses ◽  
Risk Of Cancer

PURPOSE Quantifying the risk of cancer associated with pathogenic mutations in germline cancer susceptibility genes—that is, penetrance—enables the personalization of preventive management strategies. Conducting a meta-analysis is the best way to obtain robust risk estimates. We have previously developed a natural language processing (NLP) –based abstract classifier which classifies abstracts as relevant to penetrance, prevalence of mutations, both, or neither. In this work, we evaluate the performance of this NLP-based procedure. MATERIALS AND METHODS We compared the semiautomated NLP-based procedure, which involves automated abstract classification and text mining, followed by human review of identified studies, with the traditional procedure that requires human review of all studies. Ten high-quality gene–cancer penetrance meta-analyses spanning 16 gene–cancer associations were used as the gold standard by which to evaluate the performance of our procedure. For each meta-analysis, we evaluated the number of abstracts that required human review (workload) and the ability to identify the studies that were included by the authors in their quantitative analysis (coverage). RESULTS Compared with the traditional procedure, the semiautomated NLP-based procedure led to a lower workload across all 10 meta-analyses, with an overall 84% reduction (2,774 abstracts v 16,941 abstracts) in the amount of human review required. Overall coverage was 93%—we are able to identify 132 of 142 studies—before reviewing references of identified studies. Reasons for the 10 missed studies included blank and poorly written abstracts. After reviewing references, nine of the previously missed studies were identified and coverage improved to 99% (141 of 142 studies). CONCLUSION We demonstrated that an NLP-based procedure can significantly reduce the review workload without compromising the ability to identify relevant studies. NLP algorithms have promising potential for reducing human efforts in the literature review process.

scholarly journals Association of IL-6 -174G>C (rs1800795) polymorphism with cervical cancer susceptibility

2018 ◽  
Vol 38 (5) ◽  
Author(s):  
Hai-Xia Duan ◽  
You-Yi Chen ◽  
Juan-Zi Shi ◽  
Nan-Nan Ren ◽  
Xiao-Juan Li
Keyword(s):  
Cervical Cancer ◽  
Large Scale ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Case Control ◽  
Case Control Studies ◽  
Cervical Cancer Risk ◽  
Hardy Weinberg Equilibrium ◽  
The Relationship ◽  
Multifunctional Cytokine

Interleukin-6 (IL-6) is a multifunctional cytokine that has been implicated in the etiology of cancer. Several case–control studies have been conducted to assess the association of IL-6 -174G>C (rs1800795) polymorphism with the risk of cervical cancer, yet with conflicting conclusions. To derive a more precise estimation of the relationship, we performed this meta-analysis updated to June 2018. A total of seven original publications were identified covering IL-6 -174G>C (rs1800795) polymorphism. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the relationship strengths. Statistically significant relationship was observed between IL-6 -174G>C polymorphism and cervical cancer risk (OR = 0.61, 95% CI: 0.40–0.94 for GG vs. CC, and OR = 0.77, 95% CI: 0.64–0.93 for G vs. C). Moreover, the significant association was found among Asians (OR = 0.46, 95% CI: 0.29–0.75 for GG vs. CC, and OR = 0.70, 95% CI: 0.57–0.89 for G vs. C); hospital-based subgroup (OR = 0.53, 95% CI: 0.38–0.72 for GG vs. CC, and OR = 0.73, 95% CI: 0.61–0.87 for G vs. C); and Hardy–Weinberg equilibrium ≤0.05 (OR = 0.56, 95% CI: 0.37–0.86 for GG vs. GC, and OR = 0.66, 95% CI: 0.47–0.93 for G vs. C). This meta-analysis showed the evidence that the IL-6 -174G>C polymorphism was a low-penetrance susceptibility variant for cervical cancer. Further large-scale case–control studies are needed to confirm these results.

scholarly journals Meta-analysis and trial sequential analysis of LncRNA H19 polymorphic variants on susceptibility to cancer

2020 ◽  
Author(s):  
Kunpeng Wang ◽  
Zheng Zhu ◽  
Yiqiu Wang ◽  
Dayuan Zong ◽  
Peng Xue ◽  
...  
Keyword(s):  
Subgroup Analysis ◽  
Sequential Analysis ◽  
Cancer Susceptibility ◽  
Human Cancer ◽  
Meta Analysis ◽  
Population Based ◽  
Trial Sequential Analysis ◽  
Control Group ◽  
Cancer Risks ◽  
Polymorphic Variants

Abstract Background: Although myriad researches upon the associations between LncRNA H19 polymorphic variants (rs2839698 G﹥A, rs3024270 C﹥G, rs2107425 C﹥T, rs2735971 A﹥G and rs217727 G﹥A) and the susceptibility to cancer have been conducted, these results remained contradictory and perplexing. Basing on that, a systematic review and updated meta-analysis was conducted to anticipate a fairly precise assessment about these associations. Methods: We retrieved the electronic databases EMBASE, PubMed and Web of Science for valuable academic studies before October 1st, 2019. Ultimately, 24 of which were encompassed after screening, and the available data was extracted and integrated. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) was adopted to evaluate the strength of these associations. For multi-level investigation, subgroup analysis derived from source of controls together with genotypic method was preformed. Eventually, 24 articles altogether embodying 52 studies were included. Results: The results illuminated that LncRNA H19 SNPs mentioned above were all irrelevant to cancer susceptibility. Nevertheless, crucial results were found concentrated in population-based control group when subgroup analysis by source of controls were performed in H19 mutation rs2839698 and rs2735971. Meanwhile, in the stratification analysis by genotypic method, apparent cancer risks were discovered by TaqMan method in H19 mutation rs2107425 and rs3024270. Then, trial sequential analysis (TSA) demonstrated that the results about such associations were firm evidence of effect, except rs2735971 polymorphism. Conclusion: Therefore, this meta-analysis indicated that LncRNA H19 SNPs were not associated with the susceptibility to human cancer. However, after the stratification analysis, inconsistent results still existed in different genotypic method and source of control. Thus, more high-quality studies on cancer patients of different factors were needed to confirm these findings.

Association Between LncRNA MALAT1 Polymorphisms and Cancer Risk: A Meta-Analysis Based on7007 Cases and 8791 Controls

2020 ◽  
Author(s):  
Lei Zheng ◽  
Lijuan Rong ◽  
Zhenyun Cheng
Keyword(s):  
Cancer Risk ◽  
Confidence Interval ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Dominant Model ◽  
Digestive Cancer ◽  
Increased Risk ◽  
Lncrna Malat1 ◽  
Risk Of Cancer ◽  
Allelic Model

Abstract Background: LncRNA metastasis associated with lung adenocarcinoma transcript-1 (MALAT1) was involved in pathogenesis and progress of diverse cancers. To investigate the association of MALAT1 and cancer susceptibility, this meta-analysis was appraised.Methods: 12 studies including 7007 cancer patients and 8791 controls were selected for this meta-analysis. Ratio radiation (ORS) and 95% confidence interval (CIS) were used to assess cancer susceptibility.Results: There was no significant association between rs3200401 polymorphism and the risk of cancer. However, rs3200401 was correlated with an increased risk of digestive cancer in allelic model (OR=1.15, 95%CI=1.04-1.28, P=0.009) and dominant model (OR=1.16, 95%CI=1.02-1.31, P=0.02). There was a borderline association between rs664589 and cancer susceptibility under the dominant model (OR=1.17, 95%CI=1.00-1.38, P=0.05). Rs619586 was associated with decreased cancer risk in all populations under four models (G vs A: OR=0.86, 95%CI=0.78-0.94, P=0.001; GG vs AA: OR=0.60, 95%CI=0.42-0.84, P=0.003; GG+AG vs AA: OR=0.87, 95%CI=0.78-0.97, P=0.009; GG vs AG+AA: OR=0.61, 95%CI=0.44-0.84, P=0.003). Moreover, rs1194338 was decreased associated with cancer susceptibility (A vs C: OR=0.89, 95%CI=0.80-0.98, P=0.01; AA vs CC: OR=0.77, 95%CI=0.62-0.96, P=0.02; AA+AC vs CC: OR=0.87, 95%CI=0.77-1.00, P=0.04; AA vs AC+CC: OR=0.82, 95%CI=0.67-1.00, P=0.05).Conclusion: Our results suggest that rs619586 and rs1194338 are associated with decreased cancer risk, while rs3200401 and rs664589 correlated with increased digestive cancer risk.

scholarly journals The association of FOXP3 gene polymorphisms with cancer susceptibility: a comprehensive systemic review and meta-analysis

2019 ◽  
Vol 39 (3) ◽  
Author(s):  
Yan Chen ◽  
Xiaoxue Qi ◽  
Ce Bian ◽  
Chen Ling ◽  
Tao Yi ◽  
...  
Keyword(s):  
Gene Polymorphisms ◽  
Chinese Population ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Systemic Review ◽  
Cancer Type ◽  
Case Control Studies ◽  
Foxp3 Gene ◽  
Cancer Types ◽  
Risk Of Cancer

Abstract The role of forkhead box P3 (FOXP3) protein in tumorigenesis has long been controversial and existing data on the association between FOXP3 gene polymorphisms and cancer susceptibility were inconsistent. Here, we conducted a meta-analysis to better clarify the relationship. A comprehensive search of studies published from July 2008 to June 2018 was conducted. The statistical analyses of the pooled odds ratios (ORs) and the corresponding 95% confidence intervals (95% CIs) were performed using the Revman 5.2 software. A total of 12 articles with 19 case–control studies and 10389 participants were included. Three FOXP3 polymorphisms and six cancer types were evaluated. While no significant results were observed in overall and breast cancer groups for rs3761548 (A/C) polymorphisms, the pooled data showed an elevated risk of cancer in variant AA genotypes and A allele for Chinese population (AA vs. AC+CC: OR = 1.61, 95% CI = 1.09, 2.39; AA vs. CC: OR = 1.74, 95% CI = 1.05, 2.89; A vs. C: OR = 1.34, 95% CI = 1.00, 1.78). Neither the overall group analyses nor the subgroup analyses stratified by cancer type and ethnicity proposed any significant association of rs2280883 (C/T) and rs3761549 (T/C) polymorphisms with cancer susceptibility. This meta-analysis suggested that FOXP3 rs3761548 (A/C) polymorphisms were associated with increased cancer risk in Chinese population while rs2280883 (C/T) and rs3761549 (T/C) polymorphisms were not. More large-sample researches with diverse ethnicities and cancer types are needed to draw a concrete conclusion.

scholarly journals Association between PD-1 and PD-L1 Polymorphisms and the Risk of Cancer: A Meta-Analysis of Case-Control Studies

Cancers ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1150 ◽  
Author(s):  
Mohammad Hashemi ◽  
Shima Karami ◽  
Sahel Sarabandi ◽  
Abdolkarim Moazeni-Roodi ◽  
Andrzej Małecki ◽  
...  
Keyword(s):  
Cell Death ◽  
Cancer Risk ◽  
Programmed Cell Death ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Case Control ◽  
Case Control Studies ◽  
Programmed Cell Death 1 ◽  
Risk Of Cancer ◽  
The Impact

A number of case-control studies regarding the association of the polymorphisms in the programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) genes with the risk of cancer have yielded inconsistent findings. Therefore, we have conducted a comprehensive, updated meta-analysis study to identify the impact of PD-1 and PD-L1 polymorphisms on overall cancer susceptibility. The findings revealed that PD-1 rs2227981 and rs11568821 polymorphisms significantly decreased the overall cancer risk (Odds Ratio (OR) = 0.82, 95% CI = 0.68–0.99, p = 0.04, TT vs. CT+CC; OR = 0.79, 95% CI = 0.67–0.94, p = 0.006, AG vs. GG, and OR = 0.82, 95% CI = 0.70–0.96, p = 0.020, AG+AA vs. GG, respectively), while PD-1 rs7421861 polymorphism significantly increased the risk of developing cancer (OR = 1.16, 95% CI = 1.02–1.33, p = 0.03, CT vs. TT). The PD-L1 rs4143815 variant significantly decreased the risk of cancer in homozygous (OR = 0.62, 95% CI = 0.41–0.94, p = 0.02), dominant (OR = 0.70, 95% CI = 0.50–0.97, p = 0.03), recessive (OR = 0.76, 95% CI = 0.60–0.96, p = 0.02), and allele (OR = 0.78, 95% CI = 0.63–0.96, p = 0.02) genetic models. No significant association between rs2227982, rs36084323, rs10204525, and rs2890658 polymorphisms and overall cancer risk has been found. In conclusions, the results of this meta-analysis have revealed an association between PD-1 rs2227981, rs11568821, rs7421861, as well as PD-L1 rs4143815 polymorphisms and overall cancer susceptibility.

scholarly journals Association of theMDM2SNP285 Polymorphism with Cancer Susceptibility: A Meta-Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Ping Wang ◽  
Meilin Wang ◽  
Sanqiang Li ◽  
Lingjun Ma ◽  
Shoumin Xi ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Negative Regulator ◽  
Large Sample Size ◽  
Mouse Double Minute ◽  
Precise Estimation ◽  
Double Minute ◽  
Risk Of Cancer

Themouse double minute 2(MDM2) gene encodes a negative regulator for p53, and the polymorphism SNP285 in the promoter region ofMDM2gene has been implicated in cancer risk, but individual published studies had inconclusive results. Therefore, we performed this meta-analysis to obtain a more precise estimation betweenMDM2SNP285 polymorphism and risk of cancer. A systematic literature search was performed using the PubMed, Embase, and Chinese Biomedical (CBM) databases. Ultimately, 16 published studies comprising 14,573 cases and 9,115 controls were included. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of associations. Overall,MDM2SNP285 polymorphism was significantly associated with a decreased overall cancer risk with the heterozygous model (OR = 0.89, 95% CI = 0.79–0.99), and reduced ORs were observed with other genetic models (dominant: OR = 0.90, 95% CI = 0.79–1.01 and allele comparison: OR = 0.91, 95% CI = 0.80–1.03) but not reaching statistical significance. Stratification analysis indicated a decreased risk for ovarian cancer, Caucasians, and studies with relatively large sample size. Despite some limitations, this meta-analysis indicated that theMDM2SNP285 polymorphism was associated with a decreased cancer risk, which warrants further validation in large and well-designed studies.

Sign in / Sign up

Export Citation Format

Share Document