scholarly journals Association of miRNA biosynthesis genes DROSHA and DGCR8 polymorphisms with cancer susceptibility: a systematic review and meta-analysis

2018 ◽  
Vol 38 (3) ◽  
Author(s):  
Jing Wen ◽  
Zhi Lv ◽  
Hanxi Ding ◽  
Xinxin Fang ◽  
Mingjun Sun
Keyword(s):  
Cancer Risk ◽  
Genetic Model ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Population Based ◽  
Nucleotide Polymorphisms ◽  
Case Control Studies ◽  
Exclusion Criteria ◽  
Single Nucleotide ◽  
Stratified Analysis

Single nucleotide polymorphisms (SNPs) in miRNA biosynthesis genes DROSHA and DGCR8 were indicated to be correlated with cancer risk. We comprehensively reviewed and analyzed the effect of DROSHA and DGCR8 polymorphisms on cancer risk. Eligible articles were selected according to a series of inclusion and exclusion criteria. Consequently, ten case–control studies (from nine citations) with 4265 cancer cases and 4349 controls were involved in a meta-analysis of seven most prevalent SNPs (rs10719 T/C, rs6877842 G/C, rs2291109 A/T, rs642321 C/T, rs3757 G/A, rs417309 G/A, rs1640299 T/G). Our findings demonstrated that the rs417309 SNP in DGCR8 was significantly associated with an elevated risk of overall cancer in every genetic model. In stratified analysis, correlations of DROSHA rs10719 and rs6877842 SNPs were observed in Asian and laryngeal cancer subgroups, respectively. Moreover, associations of the rs417309 SNP could also be found in numerous subgroups including: Asian and Caucasian population subgroups; laryngeal and breast cancer subgroups; population-based (PB) and hospital-based (HB) subgroups. In conclusion, the DROSHA rs10719, rs6877842 SNPs, and DGCR8 rs417309 SNP play pivotal roles in cancerogenesis and may be potential biomarkers for cancer-forewarning.

scholarly journals Comprehensive assessment and meta-analysis of the association between CTNNB1 polymorphisms and cancer risk

2017 ◽  
Vol 37 (6) ◽  
Author(s):  
Yanke Li ◽  
Fuqiang Zhang ◽  
Dehua Yang
Keyword(s):  
Cancer Risk ◽  
Meta Analysis ◽  
Wnt Signaling Pathway ◽  
Recessive Model ◽  
Nucleotide Polymorphisms ◽  
Case Control Studies ◽  
Control Groups ◽  
Single Nucleotide ◽  
Novel Biomarkers ◽  
Stratified Analysis

CTNNB1, encoding β-catenin, is a well-known tumor-related gene in the wnt signaling pathway. It has been reported that CTNNB1 polymorphisms are associated with cancer risk. However, the data were inconsistent. In this article, we conducted a systematic review for the researches related to the association of single nucleotide polymorphisms (SNPs) in CTNNB1 with overall cancer risk. Meanwhile, a series of inclusion and exclusion criteria were set to select articles for quantitative analysis. Consequently, eight case-control studies containing 4388 cases and 4477 controls were included in a meta-analysis of four highly studied CTNNB1 SNPs (rs1798802 A/G, rs4135385 A/G, rs11564475 A/G, and rs2293303 C/T). The association between each SNP and cancer risk was estimated by calculating odds ratios (ORs) and their 95% confidence intervals (95%CIs). The results showed rs1798802 (AA compared with GG: P=0.044, OR=0.72) and rs2293303 (TT compared with CC: P=0.002, OR=2.86; recessive model: P=0.006, OR=2.91; T compared with C: P=0.004, OR=1.19) polymorphisms were associated with overall cancer risk. In stratified analysis, rs4135385 polymorphism was found to elevate the risk in Caucasian or in gastrointestinal cancer subgroup. Additionally, rs2293303 conferred to an increased cancer risk when the source of control groups was hospital-based (HB). In conclusion, the three CTNNB1 SNPs were suggested to have the potential to be novel biomarkers for risk prediction of cancer in overall population or some specific subgroups. Our study could provide research clues for further related investigations.

scholarly journals Does miR-618 rs2682818 variant affect cancer susceptibility? Evidence from 10 case–control studies

2019 ◽  
Vol 39 (8) ◽  
Author(s):  
Xingliang Feng ◽  
Dan Ji ◽  
Chaozhao Liang ◽  
Song Fan
Keyword(s):  
Breast Cancer ◽  
Cancer Risk ◽  
Structure Prediction ◽  
Genetic Model ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Case Control Studies ◽  
Stem Loop ◽  
Contrast Model ◽  
Pooled Data

Abstract Piles of evidence have supported the relationship between miR-618 rs2682818 polymorphism and tumorigenesis, but the conclusion remains inconsistent. In the present study, we conducted a meta-analysis to sniff out the potential risk between miR-618 rs2682818 and overall cancers. Crude odds ratios (ORs) and 95% confidence intervals (CIs) analyzed by Z-test were employed to estimate the potential interrelation in five genetic models. We also prospected how the rs2682818 affects the second structure of miR-618. Finally, 10 independent studies meet the enrolled criteria, along with 4099 cancer cases and 5057 healthy controls. Overall, no exceeding interrelation was sniffed out in the pooled data among five inherited models, as well as stratified analyses. Whereas, the enhanced cancer risk of miR-618 rs2682818 variant stratified by breast cancer was revealed, in heterozygote genetic model (AC vs. CC: OR = 1.291, 95%CI = 1.012–1.648, P = 0.040) and dominant contrast model (AA + AC vs. CC: OR = 1.280, 95%CI = 1.009–1.623, P = 0.042). The second structure prediction result shown that the mutant A allele might change the first stem-loop of miR-618, and the free energy of it would turn from –39.1 to –35.1 kcal/mol. All in all, our meta-analysis had successfully chased down that miR-618 rs2682818 polymorphism is not linked with overall cancer risk, but in the dominant genotype of breast cancer.

Polymorphism of HSD17B1 Ser312Gly with Cancer Risk: Evidence from 66,147 Subjects

2016 ◽  
Vol 19 (2) ◽  
pp. 136-145 ◽  
Author(s):  
Lijun Shi ◽  
Xue Yang ◽  
Xin Dong ◽  
Botao Zhang
Keyword(s):  
Cancer Risk ◽  
Large Scale ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Population Based ◽  
Dependent Manner ◽  
Hormone Metabolism ◽  
Sex Steroid Hormone ◽  
Polymorphic Variants ◽  
Stratified Analysis

Hydroxysteroid (17-beta)dehydrogenase 1(HSD17B1) plays a central role in sex steroid hormone metabolism. HSD17B1 polymorphic variants may contribute to cancer susceptibility. Numerous investigations have been conducted to assess the association between HSD17B1 Ser312Gly polymorphism and cancer risk in multiple ethnicities, yet these have produced inconsistent results. We therefore performed this comprehensive meta-analysis to attempt to provide a quality assessment of the association of interest. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to evaluate the strength of associations. After a systematic literature search of several major public databases, 20 studies involving 29,460 cases and 36,687 controls were included in this meta-analysis. No significant association was found between HSD17B1 Ser312Gly polymorphism and cancer risk. However, Ser312Gly polymorphism showed a significantly decreased risk for Caucasians (there were 44,284 Caucasians for analysis, comprising 19,889 cases and 24,395 controls) in the subgroup analysis by ethnicity (dominant: OR = 0.958, 95% CI = 0.919–0.998; and allele comparing: OR = 0.973, 95% CI = 0.947–0.999). And there was the same trend towards risk in the population-based (PB) controls (homozygous: OR = 0.951, 95% CI = 0.908–0.997 and allele comparing: OR = 0.976, 95% CI = 0.954–0.999), but not among Asians or hospital-based (HB) controls. In addition, no association was observed in the stratified analysis for breast cancer studies by source of control, ethnicity and quality score. These findings suggested that the HSD17B1 Ser312Gly polymorphism might confer genetic cancer susceptibility in an ethnic-dependent manner, especially among Caucasians. Well-designed, large-scale studies are warranted to validate these findings.

Association of microRNA Polymorphisms with the Risk of Gastric Cancer in a Romanian Population

2017 ◽  
Vol 26 (3) ◽  
pp. 231-238 ◽  
Author(s):  
Ion Rogoveanu ◽  
Florin Burada ◽  
Mihai Gabriel Cucu ◽  
Cristin Constantin Vere ◽  
Mihai Ioana ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Risk ◽  
Genetic Model ◽  
Cancer Susceptibility ◽  
Statistical Significance ◽  
Recessive Model ◽  
Nucleotide Polymorphisms ◽  
Gastric Cancer Risk ◽  
Single Nucleotide ◽  
Gastric Cancer Patients

Background & Aims: MicroRNAs (miRNAs) play an important role in the occurrence and progression of human cancers, including gastric cancer. Our hospital-based case-control study aimed to investigate whether four commonly studied single nucleotide polymorphisms (SNPs) have effects on susceptibility to gastric cancer in a Romanian population.Method: We genotyped the miR-27a rs895819, miR-146a rs2910164, miR-196a2 rs11614913 and miR-499 rs3746444 SNPs by real-time PCR using predesignated TaqMan assays in 430 individuals (142 gastric cancer patients and 288 age and gender matched cancer-free controls). The associations between the investigated miRNA SNPs and gastric cancer risk were assessed by odds ratio (OR) with 95% confidence interval (CI) using logistic regression analysis.Results: A higher frequency of the miR-27a rs895819 CC genotype (OR 1.98, 95% CI: 1.05-3.73, p=0.036) was found in the patients with gastric cancer compared with the controls. Similar results were observed in a recessive model, the CC genotype was correlated with gastric cancer susceptibility (OR 1.95, 95% CI: 1.07-3.55, p=0.032). In the stratified analysis, the association between miR-27a rs895819 SNP and gastric cancer risk was limited to noncardia (OR 2.08, 95% CI: 1.10-3.94, p=0.027) and intestinal (OR 2.27, 95% CI: 1.05-4.92, p=0.042) subgroups. However, after Bonferroni correction, all associations described above lost statistical significance. No correlation was observed for the remaining SNPs and risk of gastric cancer in any genetic model studied.Conclusion: This study showed no association of the investigated miRNA SNPs with the risk of gastric cancer in a Romanian population.Key words:  –  –  – .Abbreviations: GC: gastric cancer; miRNA: microRNA; SNP: single nucleotide polymorphism.

scholarly journals A comprehensive evaluation for polymorphisms in let-7 family in cancer risk and prognosis: a system review and meta-analysis

2018 ◽  
Vol 38 (4) ◽  
Author(s):  
Ben-Gang Wang ◽  
Li-Yue Jiang ◽  
Qian Xu
Keyword(s):  
Cancer Risk ◽  
Cancer Survival ◽  
Cancer Susceptibility ◽  
Comprehensive Evaluation ◽  
Meta Analysis ◽  
Cancer Prognosis ◽  
Nucleotide Polymorphisms ◽  
Variant Genotype ◽  
Risk Prognosis ◽  
Stratified Analysis

miRNA polymorphisms had potential to be biomarkers for cancer susceptibility and prognosis. The mature miRNA-let-7 family was considered as the most important miRNA for the cancer incidence and progression. Recently, the promising let-7 miRNAs were reported to be associated with various cancers, but the results were inconsistent. We performed a first-reported systematic review with a meta-analysis for the association of let-7 family single nucleotide polymorphisms (SNPs) with cancer risk/prognosis. Ten studies were included with a total of 3878 cancer cases and 4725 controls for the risk study and 1665 cancer patients for the prognosis study in this meta-analysis. In the risk study, the let-7i rs10877887 and let-7a-1/let-7f-1/let-7d rs13293512 were shown no significant association for the overall cancer risk. In the stratified analysis, the rs10877887 variant genotype was significantly associated with a decreased cancer risk in head and neck cancer (TC compared with TT: P=0.017; odds ratio (OR) = 0.81; TC + CC compared with TT: P=0.020; OR = 0.82). In the prognosis study, the let-7i rs10877887 SNP was shown to be associated with a higher risk for cancer prognosis in the dominate model (P=0.004; hazard ratio (HR) = 1.32). The other two SNPs (let-7a-1 rs10739971 and let-7a-2 rs629367) were not found to be associated with cancer survival. None of the let-7 family polymorphisms had potential to be biomarkers for cancer susceptibility but let-7i rs10877887 SNP had potential to be predicting markers for cancer prognosis. In the future, large-sample studies are still needed to verify our findings.

The polymorphism of miR-146a (rs2910164) and Breast Cancer Risk: A Meta-analysis of 17 Studies

MicroRNA ◽  
2020 ◽  
Vol 09 ◽  
Author(s):  
Maryam Moossavi ◽  
Maryam Shojaee ◽  
Mahsa Musavi ◽  
Reza Ibrahimi ◽  
Mostafa Ibrahimi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Genetic Model ◽  
Meta Analysis ◽  
P Value ◽  
Nucleotide Polymorphisms ◽  
Multicenter Studies ◽  
Single Nucleotide ◽  
Increased Risk

Background: Single-nucleotide polymorphisms (SNPs) in genes responsible for coding microRNAs (miRNAs) are shown to be crucial in progression of breast cancer (BC). Objective: The purpose of this meta-analysis is to obtain more definitive and reliable results due to the ambiguity and inconsistency of the previous findings in this regard. This study aimed at clarifying the association of mir14a polymorphisms with breast cancer. Method: We searched PubMed, EMBASE, Web of Science and Google Scholar databases for papers published before August 10, 2019. Afterward, genotypes’ distribution, genotyping methods and ethnicity groups were extracted and Overall analyses were conducted. A total number of seventeen researches on 7676 subjects and 7476 controls were found to meet our criteria in this meta-analysis. Results: our observations confirmed the increased risk in breast cancer with rs 2910164 polymorphism in three genetic models: allele contrast fixed genetic model, Recessive fixed genetic model and CC vs. GG genetic model (P value 0.0109, 0.0404 and 0.0019 respectively). Conclusion: the rs2910164 polymorphism is associated with increased breast cancer risk. We suggest that more multicenter studies with larger samples investigate this matter to further clarify the association and verify our findings.

scholarly journals Association between PXR polymorphisms and cancer risk: a systematic review and meta-analysis

2018 ◽  
Vol 38 (3) ◽  
Author(s):  
Jing Wen ◽  
Zhi Lv ◽  
Hanxi Ding ◽  
Xinxin Fang ◽  
Mingjun Sun
Keyword(s):  
Cancer Risk ◽  
Meta Analysis ◽  
Pregnane X Receptor ◽  
Recessive Model ◽  
Dominant Model ◽  
Nucleotide Polymorphisms ◽  
Case Control Studies ◽  
Single Nucleotide ◽  
Novel Biomarkers ◽  
Risk Of Cancer

Current studies have explored the correlation between the single nucleotide polymorphisms (SNPs) of pregnane X receptor (PXR) and cancer risk. However, the findings were conflicting. Hence, we performed a comprehensive review and meta-analysis for these researches to determine the effect of PXR polymorphisms on the risk of cancer. Eligible publications were collected based on a series of rigorous inclusion and exclusion criteria. In consequence, a total of eight case–control studies (from seven citations) covering 11143 cases and 12170 controls were involved in a meta-analysis of ten prevalent PXR SNPs (rs10504191 G/A, rs3814058 C/T, rs6785049 A/G, rs1464603 A/G, rs1523127 A/C, rs2276706 G/A, rs2276707 C/T, rs3732360 C/T, rs3814055 C/T, rs3814057 A/C). The correlations between PXR SNPs and cancer risk were estimated by odds ratios (ORs) with their 95% confidence intervals (95%CIs). The findings demonstrated that rs3814058 polymorphism (CT compared with CC: pooled OR = 1.280, P=6.36E-05; TT compared with CC: pooled OR = 1.663, P=2.40E-04; dominant model: pooled OR = 1.382, P=2.58E-08; recessive model: pooled OR = 1.422, P=0.002; T compared with C: pooled OR = 1.292, P=6.35E-05) and rs3814057 polymorphism (AC compared with AA: pooled OR = 1.170, P=0.036; dominant model: pooled OR = 1.162, P=0.037) were associated with the risk of overall cancer. In stratified analyses, rs3814058 polymorphism was revealed to increase the cancer risk in lung cancer subgroup. In summary, this meta-analysis indicates that the rs3814057 and rs3814058 polymorphisms of PXR gene play crucial roles in the pathogenesis of cancer and may be novel biomarkers for cancer-forewarning in overall population or in some particular subgroups.

scholarly journals Association of Interleukin-16 rs4778889 T>C Gene Polymorphism with Cancer Risk: a Meta-analysis

2020 ◽  
Author(s):  
Qin Lei ◽  
Zhao Jiawen ◽  
Zhao Yutong ◽  
Ma Chenjun ◽  
Li Chaobin ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Gene Polymorphism ◽  
Gene Polymorphisms ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Case Control Studies ◽  
Single Nucleotide ◽  
The Relationship ◽  
Larger Sample

Abstract BACKGROUND: Rs4778889 T>C is one of the single nucleotide polymorphisms (SNPs) in interleukin-16 (IL-16). As a growth factor, IL-16 might play a significant impact on cancer formation. Several studies have investigated the relationship between IL-16 rs4778889 T>C gene polymorphisms and cancer risk, but the results are contradictory. We conducted a meta-analysis on the association between IL-16 rs4778889 T>C gene polymorphism and cancer risk. METHODS: Twelve case–control studies with 3066 cases and 4433 controls from Web of Science, PubMed, and Embase databases were included. The data was analyzed using the STATA software and the combined odds ratio (ORs) and the corresponding 95% confidence interval (CIs) were used to identify the correlation strength. RESULTS: Our results show that no significant associations were observed between the IL-16 rs4778889 T>C gene polymorphisms and cancer risk in all genetic models (C vs. T: OR=1.06, 95% CI: 0.90–1.26, Ph<0.001; CC vs. TT: OR=1.07, 95% CI: 0.71–1.62, Ph<0.001; CT vs. TT: OR=1.07, 95% CI: 0.91–1.26, Ph=0.002; CC+CT vs. TT: OR=1.08, 95% CI: 0.90–1.30, Ph<0.001; CC vs. CT+TT: OR=1.04, 95% CI: 0.73–1.50, Ph=0.001). Subgroup and sensitivity analyses also were performed. CONCLUSIONS: The results of this meta-analysis indicate that there are no significant associations between IL-16 rs4778889 T>C gene polymorphisms and cancer risk. To verify these results, further studies with larger sample size and multiracial populations are needful. Keywords: IL-16, polymorphisms, cancer, meta-analysis

scholarly journals Effects of four single nucleotide polymorphisms of EZH2 on cancer risk: a systematic review and meta-analysis

2018 ◽  
Vol Volume 11 ◽  
pp. 851-865 ◽  
Author(s):  
Zhixin Ling ◽  
Zonghao You ◽  
Ling Hu ◽  
Lei Zhang ◽  
Yiduo Wang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Cancer Risk ◽  
Single Nucleotide Polymorphisms ◽  
Meta Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide
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