Background: Promoter hypermethylation in death-associated protein kinase 1 (DAPK1) gene has been long linked to cervical neoplasia, but the established results remained controversial. Here, we performed a meta-analysis to assess the associations of DAPK1 promoter hypermethylation with low-grade intra-epithelial lesion (HSIL), high-grade intra-epithelial lesion (HSIL), cervical cancer (CC), and clinicopathological features of CC.Methods: Published studies with qualitative methylation data were initially searched from PubMed, Web of Science, EMBASE, and China National Knowledge Infrastructure databases (up to March 2018). Then, quantitative methylation datasets, retrieved from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, were pooled to validate the results of published studies.Results: In a meta-analysis of 37 published studies, DAPK1 promoter hypermethylation progressively increased the risk of LSIL by 2.41-fold (P = 0.012), HSIL by 7.62-fold (P < 0.001), and CC by 23.17-fold (P < 0.001). Summary receiver operating characteristic curves suggested a potential diagnostic value of DAPK1 promoter hypermethylation in CC, with a large area-under-the-curve of 0.83, a high specificity of 97%, and a moderate sensitivity of 59%. There were significant impacts of DAPK1 promoter hypermethylation on histological type (odds ratio (OR) = 3.53, P < 0.001) and FIGO stage of CC . Then, a pooled analysis of nine TCGA and GEO datasets, covering 13 CPG sites within DAPK1 promoter, identified eight CC-associated sites, six sites with diagnostic values for CC , nine loci associated with the histological type of CC, and all 13 loci with down-regulated effects on DAPK1 mRNA expression.Conclusion: The meta-analysis suggests that DAPK1 promoter hypermethylation is significantly associated with the disease severity of cervical neoplasia. DAPK1 methylation detection exhibits a promising ability to discriminate CC from cancer-free controls. Cervical cancer (CC), the second most common gynecologic cancer worldwide  gene, a pro-apoptotic TSG, encodes an activator of a p19ARF/p53-dependent apoptotic checkpoint  and Gene Expression Omnibus (GEO) databases were not investigated.DNA hypermethylation, occurred at CPG islands within the proximal promoter of tumor suppressor genes (TSGs), is a common epigenetic feature of cervical carcinoma, leading to the silencing of TSGs and carcinogenesis  and (methylation or hypermethylation or promoter hypermethylation) and /carcinoma in situ (CIS)/cervical dysplasia). References in retrieved articles and relevant reviews were also screened for potential studies.This meta-analysis followed the recommendations of the PRISMA Statement  Studies providing the numbers or frequencies of DAPK1 promoter hypermethylation for calculation of odds ratios (ORs) and their 95% confidence intervals (CIs); (5) written in English or Chinese. For articles with repeated data, only the largest or the most recent studies were included. Articles were excluded if they were case reports, abstracts, in vitro or pharmacological experiments, research for normal cervix or benign cervical diseases, and studies with incomplete data.Eligible studies should meet the following criterion: (1) observational studies using cohort, case-control, or case-only designs; (2) application of standard cervical biopsy or PAP smear cytology for the diagnosis of cervical neoplasia; (3) studies investigating the effects of The following data were extracted from eligible studies by two independent reviewers (NC and XL): the first author's name, publication year, country and ethnicity, study design, sample size, source of controls, methods of methylation analysis, primer sets Table , clinicohttps://cancergenome.nih.gov/). Then, eight methylation microarray datasets, including GSE99511, GSE68339, GSE46306, GSE41384, GSE37020, GSE36637, GSE30760, and GSE20080, were collected from the GEO database (https://www.ncbi.nlm.nih.gov/gds) by using the following keywords: “Homo sapiens”, “Cervical cancer,” and “Methyation.” All datasets above used the Illumina HumanMethylation 450 or 27 K Beadchip to detect methylation signals. Methylation data of each dataset were separately normalized by a Beta Mixture Quantile dilation (BMIQ) strategy implemented in the R package, which had an advantage of correcting for different distributions of methylation signals between Infinium I and Infinium II probes  contained genetic variants at or within 10 bp from the target CPG sites , we used a genome-wide significance threshold of P < 10−7 (Bonferroni corrected) in meta-analyses of these 13 CPG sites  using a predefined scale modified from the REMARK  in methylation levels of CPG sites between cases and controls. The diagnostic value of qualitative and quantitative methylation data in CC was evaluated by a summary receiver operating characteristic (SROC) curve, which showed the sensitive, specificity, and area under the curve (AUC) of included studies.For qualitative methylation data from published literatures, ORs and their 95% CIs were estimated to assess the effects of I2 statistic. I2 values larger than 25, 50, and 75% indicated low, moderate, and high heterogeneity, respectively , overall effects were weighted using a random-effects model with the inverse variance method; otherwise, a fixed-effects model was used  and disease-free survival (DFS) analyses. Methylation quantitative trait locus (meQTL) analyses for DAPK1 were tested by the Spearman correlation test. All statistical analyses were conducted with STATA 12.0  and RevMan 5.2 programs (The Cochrane Collaboration).In the TCGA CESC dataset, the association between CPG sites of n = 5) or repeated data (n = 1), in vitro evidence (n = 5), pharmacological report (n = 1), research studying non-cancer specimens (n = 2), and datasets without CPG information (n = 4). In one remaining published article, methylation data from cervix and plasma were separately recorded  in LSIL patients. DAPK1 promoter hypermethylation conferred a 2.41-fold increased risk of LSIL (P = 0.012), with a moderate level of heterogeneity , and the heterogeneity was effectively removed (I2 = 0%). In subgroup analyses, DAPK1 promoter hypermethylation was also associated with LSIL risk in Asians, high-quality reports, and studies using healthy controls  of HSIL patients. There was a significant association between DAPK1 promoter hypermethylation and increased HSIL risk in the overall comparison  and in all subgroups , we performed a meta-regression procedure, which identified study quality as a significant source of heterogeneity (P = 0.004), accounting for 68.7% of total variance. Through analysis of subgroup heterogeneity, we found that overall heterogeneity was substantially reduced in subgroups of either high-quality studies (I2 = 5%) or low-quality reports (I2 = 11%), further supporting the results of meta-regression . DAPK1 promoter hypermethylation was constantly associated with an increased risk of CC in the overall comparison , a Galbraith plot was depicted, spotting three outliers . Meta-regression suggested that study quality explained 31.6% of total heterogeneity, with a P = 0.049  stage of CC , involving 643 CC patients and 245 controls, were pooled to analyze the associations of 13 CPG sites in P < 0.05). Out of 13 associated loci, 9 showed genome-wide significance results with P-values ranging from 1.72 × 10−8 to 1.12 × 10−15  that did not exceed the genome-wide significance threshold  involving 106 HSIL patients and 105 controls, we identified two CPG sites nominally associated with HSIL risk, but the DAPK1 promoter methylation on gene expression, meQTL analyses for DAPK1 were performed by integrating the methylation and RNA-Seq data from GSE68339 and TCGA CESC datasets. In GSE68339 with 121 CC patients, all 13 CPG sites in DAPK1 contributed to down-regulation of DAPK1 mRNA expression, with r-coefficients ranging from −0.211 to −0.507  in cancer tissues , which was a qualitative method relying on two primer sets to discriminate between methylated and unmethylated alleles   calculated from qualitative data of published studies, SROC curves of quantitative methylation datasets screened six CPG sites with stronger sensitivities of up to 81% and acceptable specificities of 74–90%, suggesting a better ability of quantitative DAPK1 methyaltion detection to predict CC. Finally, meQTL analyses of two independent cohorts constantly suggested that all 13 CPG sites contributed to down-regulation of DAPK1 mRNA expression in CC tissues. All these results together provide reliable evidence that the epigenetic silencing of DAPK1 is a predictive marker of CC, especially of SCC. However, only four CPG sites in DAPK1 exhibited nominal associations with advanced FIGO stage of CC, suggesting the exaggerated observation for DAPK1 promoter hypermethylation and FIGO stage in published studies and the necessity of validation by other data sources.By reviewing the study characteristics, we found that K1 Table , were obDAPK1 promoter hypermethylation. Larger studies with quantitative methylation data are needed to resolve this controversy. Second, most included studies used retrospective designs , some of which were hospital-based, so selection bias may be inevitable in the meta-analyses.The meta-analyses had some limitations. First, based on a small sample size of 106 HSIL patients and 105 controls, meta-analyses of four quantitative methylation datasets only screened two CPG sites nominally associated with HSIL. This finding was not consistent with the pooled results of 18 published studies (733 HSIL patients and 561 controls), which showed a substantially (OR = 7.62) increased risk of HSIL for DAPK1 promoter hypermethylation in cervical neoplasia. We suggests that DAPK1 promoter hypermethylation down-regulates DAPK1 mRNA expression, and progressively increases the risk of LSIL, HSIL, and CC. DAPK1 methylation detection exhibits a promising diagnostic value for CC, especially for SCC.In summary, the present study is the first meta-analysis that integrates the data from published studies and publicly available datasets to assess the exact roles of XW and LM conceived and designed the experiments. NC and XL conducted the literature search, study selection, and data extraction. SG and QZ performed the quality assessment for included studies. JM and JZ conducted statistical analyses. XW wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


O‐MethylTransferase (COMT) gene single‐nucleotide polymorphisms (SNPs) and schizophrenia. In this study, the aim was to conduct a meta‐analysis to achieve a pooled effect size of the association between COMT gene rs165599 SNP and schizophrenia.There are many studies with different results that examine the association between Catechol‐Odds ratio (OR) was used as an effect size to determine the association between schizophrenia and the SNP. The pooled ORs were achieved under four different genetic models. When the heterogeneity among studies was high the DerSimonian‐Laird random‐effects model, otherwise the Mantel‐Haenszel fixed‐effects model was used. Publication bias was evaluated by Egger's test.Under different genetic models no statistically significant association was found between rs165599 SNP and schizophrenia by meta‐analyses consist of 20 independent studies. There was high heterogeneity among studies, for the possible reason the population differences, although the subgroup analyzes reduced the heterogeneity, no association was obtained. However, the sex‐specific estimation of the females showed that to be a G allele carrier is a risk factor for schizophrenia  compared to AA homozygous.COMT gene rs165599 SNP does not appear to be a single‐risk factor for schizophrenia.The  The COMT gene has been mapped to 22q11.2  is a complex psychiatric disorder in which genetic and environmental factors play a role together. Catechol‐O‐methyl transferase   date up to 2017 January. To find other appropriate studies, we also examined the references of the key studies. When there is no detailed information for calculation of the effect size, we tried to contact the authors directly. The selection process of the studies included in the meta‐analysis is given detailed by the flow diagram in Figure By using the search words “schizophrenia,” “2.2COMT SNPs and schizophrenia; (b) use healthy individuals as controls in case‐control studies; (c) has a genotype distribution of control population in Hardy‐Weinberg Equilibrium (HWE) were included in meta‐analysis. The studies; on families , in which patients with different psychiatric diagnosis mixed with schizophrenia, involving only patients with violent tendencies and those involving only patients with alcohol and/or substance abuse were excluded. In all studies, the diagnostic criteria were DSM‐IV . The publications not in English could not be considered. The characteristics of the 20 studies included in meta‐analysis resulted from the selection process are given in Table The studies which: (a) concern the association between 2.3Odds ratio (OR) is a risk measure commonly used for retrospective case‐control studies. It is investigated retrospectively to determine how much of the case and control groups are exposed to the risk factor that thought to be Alpar, . OR can I2 and Cochran's Q test statistics were used for evaluation of heterogeneity among studies. If the heterogeneity was high (I2 > 50% or p < 0.05) the DerSimonian‐Laird (DSL) random effects model; otherwise, the Mantel‐Haenszel (MH) fixed effects model was used to achieve the pooled effect size. Meta‐analyses were conducted under four different genetic models: A versus G, AA versus GG, AA versus G‐allele carriers (AG + GG), and A‐allele carriers (AA + AG) versus GG. The significance of the pooled ORs was determined by a z test and publication bias was assessed by Egger's test. In addition, for the studies providing data by sex, pooled estimations are obtained with six studies and four studies, respectively, for allelic and genotypic distributions under these models. Because of the high heterogeneity among all studies included in the meta‐analyses, population subgroup analyzes were performed by eight studies of Asian origin and five studies of Caucasian origin. In all analyses, the significance level was considered to be 0.05 and all analysis performed by STATA 14.0 software .The odds ratio was used as the effect size to evaluate the association between schizophrenia and allele or genotype distribution. 3Q heterogeneity test (pQ), for the significance of the pooled estimate (pZ) and for the Egger's bias test (pE) are given in Table Literature search resulted in 20 studies that met the inclusion criteria and pooled OR estimates for these studies were performed by appropriate meta‐analytical methods. Common OR estimates and 95% confidence intervals (95% CI) under different genetic models and p values for the Between‐study heterogeneity was observed to be high. Population differences involving ethnicity is thought to be a heterogeneity source. Therefore, eight studies of Asian origin and five studies of Caucasian origin were evaluated separately by meta‐analyses. In the subgroup analyzes, the heterogeneity within populations was remarkably reduced, but no association was found between the disease and the SNP. In addition, in separate analyzes performed with the studies that provided sex‐based data, it was determined that there is no association between schizophrenia and SNP for males, but it is a risk factor to be a G allele carrier for females Figure . The ris4COMT gene and schizophrenia. However, there was not a complete consistency in the results of these studies. The aim of this study was to conduct a meta‐analysis for rs165599, one of the suspicious SNPs for schizophrenia. Okochi et al. (Many studies have examined the association between polymorphisms in i et al.  conducteCOMT SNPs was performed by Shifman et al. (A remarkable study in the literature that examined the association between schizophrenia and n et al.  with Ashn et al. . Chien, n et al.  were foun et al. , haplotyAnother study, that found an association between schizophrenia and rs165599 SNP, was conducted on the Iranians by Behbahani, Kazemi‐Nezhad, Foroughmand, and Ahmadi . HoweverFunke et al. , found aCOMT gene, including rs165599, and found no difference between patients and controls in terms of allele or genotype distributions. In addition, no association was found between the disease and the rs174697‐rs165599‐rs165728 haplotype and by the logistic regression analysis for each SNP in which age and sex were included in the model (Chen et al., COMT gene, and the association between disease and rs737865 and rs2020917 polymorphisms was found to be significant. Zhang et al. (COMT gene.Chen, Lu, Yeh, Shih, and Huang  investigg et al.  found noWhen the polymorphism considered in this study was examined according to sex, Yu, Zhang, Huang, Ding, and Li , MartoreIn the meta‐analyses including all studies, a high heterogeneity was observed between the ORs of the studies. Therefore, subgroup analyzes were conducted to take the population differences involving ethnicity into account, which is considered to be a possible source of heterogeneity. Populations according to the ethnicity indicated in the studies are pooled as Asians and Caucasians. Heterogeneity among the studies of Asians is considerably reduced and the studies of Caucasians have provided homogeneity. According to within‐population assessments, no association between schizophrenia and SNP was detected under four genetic models Table .Another source of heterogeneity among studies is thought to be the differences in the selection of control groups (Chen et al., 5In our published previous study, it was stated that there was no association between rs165599 SNP and schizophrenia (Acar et al., The author reports no conflict of interest.


Aims: The purpose of this study was to assess the relationship between genetic variants and steroid-induced osteonecrosis of the femoral head (SONFH) in steroid use populations.Methods: We searched the public databases up to April 15, 2018. This study analyzed only the single-nucleotide polymorphisms (SNPs) that have appeared in more than three studies and assessed the level of evidence by classifying the outcomes according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.Results: The ABCB1 rs1045642 C>T mutation had a protective effect against SONFH in the allelic model . The rs2032582 mutation in the ABCB1 gene showed no relationship to SONFH . In ApoB rs693, four models showed that mutations can increase SONFH risk, but the allelic model did not. The ApoB rs1042031 mutation increased SONFH risk in the dominant model .Conclusion: An allelic model of ABCB1 rs1045642 showed that mutations have a protective effect against SONFH at a very low level of evidence. The mutations in ApoB rs693 and rs1042031 increase the SONFH risk with moderate levels of evidence. Osteonecrosis of the femoral head (ONFH) is caused by the obstruction or interruption of local blood supply, resulting in tissue ischemia, necrosis, and finally bone collapse  and SONFH will help to identify the high SONFH risk population who use steroids. For these patients, it is necessary to avoid steroid application or to change the application strategy, increase the frequency of detection of SONFH, and enable early intervention. Furthermore, genetic variant-related studies can help to understand the pathogenesis of SONFH. Presently, several meta-analyses have been published that indicate that This meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines , the China Biology Medicine (CBM) Database, the China Science Periodical Database , and the VIP Journal Integration Platform (VJIP). Searches were performed for studies published up to April 15, 2018. The following terms were used in the search strategy: hormone, glucocorticoid, steroid, corticosteroid, osteonecrosis, necrosis, femoral, femur, femoris, whirlbone, polymorphism, SNP, genetic, mutation, genotype, allele, allelic, and variation. We also conducted manual searches of the reference lists of relevant reviews to avoid omissions.The following studies were included in our meta-analysis if they fulfilled the inclusion criteria: (1), study has a case-control or cohort study design; (2), steroid-using patients are included; (3), study compares ONFH and non-ONFH patients after steroid use; (4), study assesses the association between SNPs and SONFH; and (5), study indicates the frequencies of specific alleles or the effect sizes of individual genotypes between cases and controls.The exclusion criteria included the following: (1), study compares patients with SONFH to healthy populations or populations with other types of ONFH; (2), study is about family heredity; (3), study is not SNP-related; and (4), study does not report data pertaining to allelic frequencies or calculable effect size. In addition, conference reports, editor comments, reviews, and academic dissertations were also excluded from the analysis.Two authors independently extracted the following information from each eligible study: the first author's name, publication year, research location, sample size, average age, primary disease, diagnostic mode, and genes of interest. The methodological quality of the included studies was evaluated using the Newcastle-Ottawa Scale (NOS), a validated tool for evaluating the quality of observation studies that includes the following 3 subscales: selection, comparability, and exposure Stang, . We asseI2 statistic was used to estimate the degree of heterogeneity among the studies. If the I2 ≥ 50% , a random-effect model was used; otherwise, a fixed-effect model was used. Subgroup analysis was also performed according to the ethnicity and location of the population. We assessed publication bias using the Begg and Egger tests. All tests were two-tailed, and a p-value of less than 0.05 was deemed statistically significant. We analyzed the data using the R program (Version 3.3.1) and STATA (Version 14.0).The Hardy-Weinberg equilibrium (HWE) of the included populations was calculated to assess the consistencies of allele frequencies between generations  was larger than 0.2. Publication bias (reporting bias) also reduced the level of evidence. Finally, a large (OR > 2 or <0.5) or very large (OR > 5 or <0.2) effect upgraded the quality of evidence.We used GRADE to assess the level of evidence with four levels graded from high (best) to very low (worst). All objective studies used an observational study design, which downgrades the quality of evidence. Inconsistency was evaluated using the Our research returned 278 English articles and 285 Chinese articles after removing duplications. After screening the titles and abstracts, 482 of these articles were excluded. The full texts of 81 articles were assessed, among which the control group did not receive steroid therapy (25); the article was a review (7); the study was non-SNP-related (5); the research was basic (3); the study did not report frequencies or effect size results (2); the study did not include steroid-related ONFH (2); the study was a case report (2); the research was microRNA related (2); the report was a duplicate (2); and the research was of heredity SONFH (1). Finally, we collected 30 trials assessing 7,553 patients for our meta-analysis  . However, other models showed that this mutation could increase SONFH risk . rs1042031 could cause a missense mutation of glutamic acid to lysine or stop-gain mutation. Only the dominant model was analyzed, and the results showed that there was a significant relationship between this mutation and SONFH . Three studies were from China, and subgroup analysis results also indicated a significant relationship  . Thus, the level of evidence was very low . The level of evidence was moderate because of the large effect (OR>2) . Although the SEs were larger than 0.2, the OR was greater than 5. Thus, the evidence levels were also moderate . The SE of the result was less than 0.2, and the OR was greater than 2. Thus, the level of evidence was moderate  with statistical heterogeneity .ABCB1 is a member of a superfamily of ATP-binding cassette transporters that transport variant molecules across cellular membranes. Zhou et al. researched the association between ABCB1 polymorphisms and SONFH and found that rs1045642 and rs2032582 are associated with SONFH (Zhou et al., post hoc analysis of Seth E. Karol's research that excluded SNP results with very low-level evidence (Karol et al., Additionally, we performed a The present study still has several limitations. First, our study was performed at the study level instead of the individual level. Second, our study did not consider the impact of primary disease or steroid therapy strategies on the results. Third, there is a large amount of heterogeneity in the results of this study. Although random effect models are used for heterogeneous results, these heterogeneities can still have a potential impact on the results. Fourth, our study only analyzed the SNPs that were examined in more than three studies, but with new research and evidence, more SNPs may be studied. Therefore, this study was limited by the research available at the time.An allelic model of ABCB1 rs1045642 showed that mutations had a protective effect against SONFH at a very low level of evidence. The mutations in ApoB rs693 and rs1042031 increased the SONFH risk with moderate levels of evidence.XC performed the conception and design of the work. XC and LZ drafted and revised the work critically. DL and JL analyzed data for work. FL and HM acquisited data for this work. All authors provide approval for publication of the content.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Moreover, the combination of immunotherapy and gemcitabine had tolerable toxicities. Based on current evidence, fluoropyrimidine-based therapies and the combination of gemcitabine and taxanes were the most effective therapies in the advanced pancreatic cancer, and the combination of immunotherapy and gemcitabine can be developed into a new form of therapy.Both gemcitabine and fluoropyrimidine are recommended backbones in the first-line treatment of pancreatic ductal adenocarcinoma (PDAC). To compare the efficacy and safety of these two therapeutic backbones, and to investigate the optimal therapies, we conducted a network meta-analysis. By retrospective analysis of randomized controlled trials (RCT), the most preferred therapeutic regimen may be predicted. The eligible RCTs of the gemcitabine-based therapies and fluoropyrimidine-based therapies were searched up to 31 August 2019. In a frequentist network meta-analysis, treatments were compared and ranked according to overall survival (OS) and progression-free survival (PFS). Thirty-two trials with 10,729 patients were included. The network meta-analyses results for overall survival and progression-free survival showed that fluoropyrimidine-based therapy seems to be the most effective treatment choice. Compared to gemcitabine combined with taxanes or immunotherapy, fluoropyrimidine-based therapy had comparable treatment effects (PFS: 0.67,  Pancreatic cancer is the fourth most common cause of cancer-related mortality worldwide. Patients with pancreatic ductal adenocarcinoma (PDAC) constituted almost 95% of pancreatic cancer patients, and 80% of PDAC patients were diagnosed with unresectable locally advanced or metastatic cancer due to the absence of specific symptoms in the early stages. Advanced PDAC patients had a poor prognosis with a five-year survival rate of 3% . The vasGemcitabine and fluoropyrimidine are the mainstream therapies for advanced PDAC treatment ,3. To imUntil now, no head-to-head trial has been done on the various gemcitabine-based therapies and fluoropyrimidine-based therapies that demonstrate antitumor potential for advanced PDAC; therefore, the optimal treatment remains to be identified. Network meta-analysis is a biostatistical method that can estimate relative effects from direct and indirect comparisons. To clarify the roles of new gemcitabine-based therapies or fluoropyrimidine-based therapies in the first line setting, this study performed a systematic review and a network meta-analysis to compare the efficacy and toxicity of gemcitabine-based therapies and fluoropyrimidine-based therapies.A total of 222 studies were evaluated by two independent reviewers and 32 RCTs involving 10,729 patients were included to conduct a meta-analysis and indirect comparisons . The detThe quality of the included RCTs was generally good, with a low risk of bias . The mosp = 0.002, heterogeneity: p = 0.59, I2 = 0%; HR: 0.71; 95% CI: 0.62–0.82; p < 0.00001, heterogeneity: p = 0.71, I2 = 0%; HR: 0.57; 95% CI: 0.46–0.70; p < 0.00001, heterogeneity: single study). Indirect comparisons performed to compare the OS was in The results of the pairwise meta-analysis of OS were presented in p < 0.0001; heterogeneity: p = 0.13; I2 = 46%), the combination of immunotherapy and gemcitabine , fluoropyrimidine-based therapies , as well as the combination of taxanes and gemcitabine , versus gemcitabine alone. Indirect comparisons of hazards ratios of PFS were showed in the The results of the pairwise meta-analysis of PFS was presented in p < 0.0001; heterogeneity: p = 0.35; I2 = 11%), the use of fluoropyrimidine-based therapies , and the use of fluoropyrimidine alone , versus gemcitabine alone. The indirect comparison analysis of ORR showed similar results to the indirect comparison of the hazard ratio of OS that the use of the fluoropyrimidine-based therapies could have a better objective response rate than most therapies . Adding platinum drugs to gemcitabine can increase the risk of thrombocytopenia  and abnormal neutrophils counts  when compared to gemcitabine alone. On the other hand, patients treated with combination of taxanes and gemcitabine had higher neutropenia  and leukopenia . In the gastrointestinal disorders, the combination of EGFR inhibitor and gemcitabine was more toxic compared to gemcitabine alone, with the increased risk of vomiting . Moreover, increasing risks of diarrhea were observed in the use of the combination of taxanes and gemcitabine, fluoropyrimidine alone, and fluoropyrimidine-based , as compared to gemcitabine alone. A higher risk of stomatitis was found in the combination of fluoropyrimidine and gemcitabine than in the gemcitabine alone . With regard to the skin disorders, when compared to gemcitabine alone, the higher risk was observed in the combination fluoropyrimidine and gemcitabine, as well as in the combination of EGFR inhibitors and gemcitabine. Hand-foot syndrome occurred most in the combination of fluoropyrimidine and gemcitabine . In addition, the combination of antiangiogenesis and gemcitabine was associated with a greater risk of proteinuria as compared to gemcitabine alone . The indirect comparison results of the risk of all grade 3 to 5 adverse events presented in the The statistically significant results of adverse events with grade 3 to 5 were shown in No significant publication bias of primary outcomes (OS) was identified in Ranking analysis for progression-free survival (PFS) performed with P-score suggested that the fluoropyrimidine-based was the best treatment option (P-score: 0.98), followed by the combination of immunotherapy and gemcitabine (P-score: 0.85), as well as the combination of taxanes and gemcitabine (P-score: 0.78) . In termFluoropyrimidine-based and gemcitabine-based therapies are recommended as preferred first-line treatments for advanced PDAC ,3. The rThe results confirmed previous observations ,47,48,49In this study, tyrosine kinase inhibitors did not significantly reduce mortality and progression, although such treatments initially showed high response rates and tolerable toxicities. Both KRAS/BRAF mutation and gene amplification may have contributed to resistance mechanisms. Nearly 90% of patients with PDAC possess KRAS mutations, and half of the remaining patients harbor BRAF mutations. KRAS/BRAF mutations cause increasing signaling of proliferation despite the inhibition of TKIs. Aside from KRAS/BRAF mutations, TKIs-treated tumors can gradually generate persistent genetic alterations and allow tumor toleration through compensatory pathways . Our paiThe present indirect comparison utilized the latest clinical data to assess potential mechanisms and combination therapies. Nevertheless, this study had several limitations. First, integrating different drugs with similar mechanisms in one arm may cause heterogeneity. In this study, however, most arms had low heterogeneity; high heterogeneity was only observed in the combination of EGFR inhibitors and gemcitabine. The limited extent of the heterogeneity may have been due to the characteristics of some patients enrolled in the LAP07 trial , which iNotwithstanding the limitations of this study, both the potential therapeutic efficacy and safety of the combination of immunotherapy (IMI-101 and WT1) and gemcitabine were observed in this network meta-analyses. Moreover, the results of the heterogeneity analysis and the inconsistency analysis validated the quality of relative effects . These rPreferred Reporting Items for Systematic Reviews and Meta-Analyses for RCTs  was follClinicaltrial.gov) was used. The following medical subject headings (MeSH) and text words for pancreatic cancer and treatments were used: pancreatic cancer (PDAC) AND gemcitabine OR cisplatin OR oxaliplatin OR carboplatin OR paclitaxel OR docetaxel OR irinotecan OR 5-FU OR S-1 AND clinical trial.A data search of randomized controlled trials of advanced pancreatic cancer and treatment published up to 31 August 2019, was performed on the Cochrane Central Register of Controlled Trials (CENTRAL), Web of science, EMBASE and Medline. The meeting abstracts from the American Society of Clinical Oncology (ASCO) and European Society for Medical Oncology (ESMO) were also searched for eligible trials. To search for unpublished data of randomized controlled trials, the US National Institutes of Health Ongoing Trials Register  prospective randomized controlled trials reporting on efficacy and toxicity; (2) enrolled patients with unresectable locally advanced or metastatic pancreatic cancer; (3) the performance scores of enrolled patients were less than to 2 or KPS score higher than 50; (4) aged at least 18 years old, with adequate hematological, renal, and liver function; (5) the life expectancy of at least 8 weeks; (6) language limited to English or Chinese. To reduce the statistic bias of estimates of the treatment effects in the indirect comparison analysis, treatment of trial without gemcitabine alone would be excluded. Included studies were independently evaluated by two reviewers and reconciled with a third author if discrepancies occurred.The primary endpoint was overall survival (OS). The secondary endpoints were progression-free survival (PFS), objective response rate (ORR), and grade 3 to 5 adverse events . The hazard ratios (HRs) with 95% confidence intervals (CIs) of PFS and OS were extracted. As for ORR and grade 3 to 5 adverse events, the number of patients and the number of total events were extracted for estimating. In addition, each patient’s performance score, dosing regimen, study design, and follow-up time were collected. As for the risk of bias of included trials, Cochrane risk-of-bias tool (version 5.1.0) was used to score the low, high, or unknown risk of bias, according to items. Two independent reviewers performed the data extraction and risk-of-bias assessment, and a third author handled with disagreement.All analyses were performed with the frequentist model. For the efficacy evaluation, the outcome measures of overall survival and progression-free survival were the hazard ratios (HRs) with 95% CIs. For ORR, the outcome measures of response rate were risk ratios (RRs) with 95% CIs. In the outcome of toxicity, the outcome measures of grade 3 to 5 toxicities were odds ratios (ORs) with 95% CIs.http://www.R-project.org/) with netmeta package (https://CRAN.R-project.org/package=netmeta).The direct meta-analysis, odds ratio, risk ratio, and hazard ratios were pooled by using a DerSimonian-Laird random-effects model in Revman 5.3. . The random-effects model was based on the inverse-variance approach, which adjusts the study weight by considering the heterogeneity among the intervention effects. The Mantel–Haenszel method was used to calculate the odds ratio and risk ratio, and the inverse-variance method was used for estimating the hazard ratio. Next, an indirect comparison was done with the random-effects model in Frequentist framework ,55. DireI² statistic were used to evaluate the heterogeneity across the studies. Heterogeneity existed with a p-value lower than 0.05 in Cochran’s Q test [To evaluate the heterogeneity, Cochran’s Q test and the s Q test . For nets Q test . A funnes Q test .Overall, our results suggested that the combination of immunotherapy and gemcitabine could be developed as first-line therapies for advanced PDAC patients. On the other hand, fluoropyrimidine-based therapies and the combination of gemcitabine and taxanes were the most effective therapies in advanced pancreatic cancer. These findings enhanced our knowledge of the efficacy and safety of common combination therapies for advanced PDAC and increased our ability to identify the appropriate synergistic effects of combination therapies.


Several studies have suggested that long non-coding RNA (lncRNA) gene polymorphisms are associated with cancer risk. In the present study, we conducted a meta-analysis related to studies on the association between lncRNA single-nucleotide polymorphisms (SNPs) and the overall risk of cancer. A total of 12 SNPs in five common lncRNA genes were finally included in the meta-analysis. In the lncRNA antisense non-coding RNA (ncRNA) in the INK4 locus (ANRIL), the rs1333048 A/C, rs4977574 A/G, and rs10757278 A/G polymorphisms, but not rs1333045 C/T, were correlated with overall cancer risk. Our study also demonstrated that other SNPs were correlated with overall cancer risk, namely, metastasis-associated lung adenocarcinoma transcript 1 , HOXA distal transcript antisense RNA , and highly up-regulated in liver cancer . Moreover, four prostate cancer-associated ncRNA 1  SNPs were in association with cancer risk. No association was found between the PRNCR1 (rs7007694 C/T) SNP and the risk of cancer. In conclusion, our results suggest that several studied lncRNA SNPs are associated with overall cancer risk. Therefore, they might be potential predictive biomarkers for the risk of cancer. More studies based on larger sample sizes and more lncRNA SNPs are warranted to confirm these findings. As a new class of functional non-coding RNAs (ncRNAs), long ncRNAs (lncRNAs) are made up of over 200 nts and lack the ability of protein coding . RecentlCurrently, single nucleotide polymorphisms (SNPs) are the most common genetic variants of concern and universally present in lncRNA genes. It is predicted that the expression and function of lncRNAs are affected by SNPs . StudiesIn the present study, we conducted a meta-analysis of epidemiological studies to explore the associations between five lncRNA SNPs and overall cancer risk. Furthermore, our study may shed some light on the biomarkers for predicting cancer risk.P>0.05). The exclusion criteria were: (i) duplicate studies; (ii) not relevant to cancer or lncRNA SNPs; or (iii) no available data and the authors could not be contacted.A computerized literature search was performed in the Medline, PubMed, Web of Science, and Embase database up to 6 Februrary 2018. The search strategy included the terms (‘lncRNA’ or ‘long non-coding RNA’) and (‘polymorphisms’ or ‘variants’ or ‘variation’ or ‘SNP’) and (‘cancer’ or ‘carcinoma’ or ‘tumor’ or ‘neoplasm’). To be eligible for inclusion in the meta-analysis, a study must meet the following criteria: (i) case–control study or cohort study; (ii) assessing the association between lncRNA SNPs and cancer risk; (iii) having an available genotype or allele frequency for estimating an odds ratio (OR) with 95% confidence interval (95% CI) or hazard ratio (HR) with 95% CI; and (iv) genotype frequencies in controls being consistent with those expected from Hardy–Weinberg equilibrium (HWE) (Two investigators (X.H. and W.Z.) evaluated the eligibility of all retrieved studies and extracted the relevant data independently. Extracted databases were then cross-checked between the two authors to rule out any discrepancy. Disagreement was resolved by consulting with the third investigator (Z.S.). The study quality was assessed in accordance with the Newcastle–Ottawa Scale (NOS) (Supplementary Table S1). Eight items were extracted, and each item scored 1. The total scores ranged from 0 to 8. If the scores were ≥7, then the study was considered to be of high quality.P<0.05 was considered statistically significant). The genotype frequencies of the lncRNA polymorphisms for the HWE were calculated for the controls using the chi-square test, and P<0.05 was considered as significant disequilibrium. The between-study heterogeneity was evaluated by using the chi-square test and the 2I statistic. An 2I value of >50% of the 2I statistic was considered to indicate significant heterogeneity [P-value <0.05 implies a statistically significant publication bias [The statistical analysis was performed using STATA 14. Estimates were summarized as ORs with 95% CIs for each study (ogeneity . When a ion bias . We furtANRIL), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), HOXA distal transcript antisense RNA (HOTTIP), highly up-regulated in liver cancer (HULC), and prostate cancer-associated ncRNA 1 (PRNCR1)) involved in the 17 eligible studies. After removal of those records for which PHWE<0.05, seven SNPs were found to be only based on one single eligible study. They were ANRIL rs2151280, MALAT1 rs3200401, MALAT1 rs7927113, MALAT1 rs1194338, HOTTIP rs5883064, PRNCR1 rs7841060, and PRNCR1 rs7463708. Therefore, the remaining 12 lncRNA SNPs were included in our final calculation . For the rs4977574 A/G polymorphism, both the heterozygote type AG and the dominant model were associated with decreased overall risk of cancer compared with the wild-type AA . However, both the mutation type GG and the allelic model were associated with increased overall risk of cancer . For the rs10757278 A/G polymorphism, the heterozygote type AG, the dominant model, and the recessive model were associated with increased overall risk of cancer . Nevertheless, the allelic model was associated with decreased overall risk of cancer .The pooled OR and stratified analyses showed that amongst the five PRNCR1 SNPs included in the meta-analysis, only rs16901946 G/A, rs13252298 G/A, rs1016343 T/C, and rs1456315 G/A were associated with cancer risk, while the association of the rs7007694 C/T was not statistically significant .The rs16901946 G/A polymorphism was associated with increased overall risk of cancer in all genetic models .For the rs13252298 G/A polymorphism, the allelic model, the mutation type AA, the heterozygote type AG, and the dominant model were associated with decreased overall risk of cancer compared with the wild-type GG .Additionally, the rs1016343 T/C polymorphism was associated with increased overall risk of cancer in all genetic models  in the overall comparison and the subgroup analyses . We subsWe used Begg’s test and Egger’s test to evaluate potential publication bias of the included studies. No statistically significant publication bias was indicated in any of the genetic models for all lncRNA SNPs .H19, HOTAIR, ZNRD1-AS1, and PRNCR1. However, more lncRNA polymorphisms with larger sample sizes are warranted. Therefore, a total of 12 SNPs in five common lncRNA genes were finally included in our study. In addition, our study was the first meta-analysis to show the significant association between the lncRNA ANRIL, MALAT1, HOTTIP, and HULC polymorphisms and cancer risk. Compared with the studies of Lv et al. [It is known to all that over 20 lncRNA polymorphisms are associated with susceptibility of cancer. In recent studies, most of meta-analyses were conducted to focus on the association between lncRNA HOTAIR ,28 or lnv et al. , we deciINK4a, p14ARF, and p15INK4b, and the lncRNA ANRIL [INK4B [Chromosome region 9p21 is a hotspot for disease-associated polymorphisms and encodes three tumor suppressors, namely p16NA ANRIL . ANRIL iL [INK4B . FurtherL [INK4B . The cirL [INK4B  and breaL [INK4B . And preL [INK4B . MoreoveL [INK4B . In addiL [INK4B . In concmiR-214 directly and suppress the expression of MALAT1. Several studies revealed that MALAT1 has an elevated expression and was associated with a higher risk and poorer survival in many kinds of cancers [MALAT1 is located in chromosome 11q13, which is over 8000 nts long. It is enriched in nuclear speckles in interphase cells and concentrates in mitotic interchromatin granule clusters. And it is co-localized with pre-mRNA-splicing factor SF2/ASF and CC3 antigen in the nuclear speckles . It is r cancers . Our stuHOXA gene cluster. The previous study showed that rs1859168 might change the expression level of HOTTIP by affecting transcription factor binding sites [HOTTIP is an antisense non-coding transcript located at the 5′-end of the ng sites . Furtherng sites . FurtherHULC gene was located in the 6p24.3 region. Based on the Hapmap database, all the SNPs in HULC are in high linkage disequilibrium (LD). For example, rs7763881 was in complete LD with rs1328867 (r2 = 1), which is located in the promoter region of HULC. Additionally, the wild-type allele T of rs1328867 is predicted to bind with some transcription factors including C-Myc [The lncRNA HULC is approximately 1.6 k nucleotide long and contains two exons but not translated . Some stng C-Myc . It has ng C-Myc . In concPRNCR1 mRNA, altering the stability of PRNCR1 or the mRNA conformation, and giving rise to the modification of its interacting partners [The lncRNA PRNCR1, also referred to as PCAT8 and CARLo3, is transcribed from the ‘gene desert’ region of chromosome 8q24 (128.14–128.28 Mb) . MoreoveAlthough this meta-analysis revealed the significant association between lncRNA polymorphisms and cancer risk, however, some limitations still should be acknowledged. First, the number of subjects in the included studies is relatively small, which might result in a lack of statistical power and prevent a meaningful analysis of the results. Second, in stratified analyses based on ethnicity and cancer type, we failed to perform further subgroup analysis because of limited relevant reports. Third, only English articles were included in our study and it may result in publication bias. Finally, study of the association between lncRNA polymorphisms and cancer risk remains an emerging field, we concluded only representative SNPs in our study. Therefore, additional prospective studies with larger sample sizes including other polymorphisms are warranted.We systematically reviewed studies on the association between lncRNA SNPs and overall cancer risk, and used the available data to perform a meta-analysis of 19 SNPs in five common lncRNA genes. The results suggest that the association between lncRNA SNPs and cancer risk can be categorized into four types: (i) complete association, where polymorphisms are significantly associated with risk of overall cancer in all genetic models, including ANRIL rs1333048, HOTTIP rs1859168, PRNCR1 rs16901946, PRNCR1 rs1016343, and PRNCR1 rs1456315; (ii) ANRIL rs4977574, ANRIL rs10757278, MALAT1 rs619586, HULC rs7763881, and PRNCR1 rs13252298 polymorphisms are only associated with cancer risk in some genetic models; (iii) no association, where the association of polymorphisms with cancer risk are not statistically significant, including ANRIL rs1333045 and PRNCR1 rs7007694; (iv) failed to be quantitatively synthesized due to limited studies. Therefore, the lncRNA SNPs provide more alternatives for biomarkers that can predict cancer risk.More attention should be paid to several research directions in the future studies. First, more lncRNA polymorphisms and other aspects of cancer including chemotherapeutic susceptibility, metastasis, and relapse should be explored. Second, functional studies are needed to clarify the underlying mechanisms of lncRNA polymorphism in the tumorigenesis. Finally, the extensive clinical application of lncRNA polymorphisms requires further study.


I2 = 77.8%, 70.3%, and 59.2%, respectively). Four studies explored the prognostic value of LVI in patients with advanced tumor stages (T3–T4). The fixed effects model (I2 = 33.9%) showed that the pooled HR was 1.64 (95%CI = 1.35–1.99) for CSS. Egger's plots showed no significant publication bias . Our meta-analysis demonstrated that LVI is a poor prognostic factor for UTUC and is strongly associated with disease recurrence, cancer-specific mortality, and overall mortality.This study was performed to identify the prognostic impact of lymphovascular invasion (LVI) in patients with upper urinary tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU). A systematic search in PubMed, Embase, and the Cochrane Library was performed to identify relevant studies. The outcomes of interest, including progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS), were extracted, and the pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were used for effect size estimation. Subgroup, metaregression, and sensitivity analyses were performed to explore potential origins of heterogeneity. Publication bias was estimated by Egger's linear regression and funnel plot. Our meta-analysis included a total of 27 studies involving 17,453 patients. The pooled HRs were statistically significant for PFS , CSS , and OS , with high heterogeneity ( Upper urinary tract urothelial carcinoma (UTUC) accounts for 10% of renal tumors and 5% of all urothelial malignancies . RadicalLymphovascular invasion (LVI) is defined as the invasion of tumor cells into an endothelium-lined space of vascular or lymphatic vessels without underlying muscular walls . The proWe searched several electronic databases  for relevant studies up to 31 December 2018. The following search terms were used to identify studies focusing on the prognostic value of LVI in UTUC: (1) “upper urinary tract” and “carcinoma” or “cancer” and “lymphovascular invasion”; (2) “upper urinary tract” and “carcinoma” or “cancer” and “survival” or “Cox” or “multivariable.”We defined the inclusion and exclusion criteria before searching for articles. Studies were included if they met the following criteria: (1) the study evaluated LVI as a prognostic factor in patients with UTUC after RNU; (2) the study reported adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) of progression-free survival (PFS), cancer-specific survival (CSS), or overall survival (OS) in a multivariate analysis with Cox proportional hazard regression; and (3) the study was published in English. The exclusion criteria were as follows: (1) the study did not provide sufficient data to acquire the HR and its standard error, (2) the article described a review or study on cell lines or animal models, (3) the number of cases was <100, (4) surgical treatment was not limited to RNU, and (5) neoadjuvant chemotherapy was applied to the participants. When more than one article was based on the same study population, we included the most complete or the most recent study.in situ, margin status, hydronephrosis, multifocality, tumor architecture, body mass index, and adjusted HR with 95% CI of PFS, CSS, and OS). Two reviewers investigated relevant articles and extracted data, respectively. Disagreements between the two reviewers regarding data abstraction were resolved through discussion.The endpoints of our study were PFS, CSS, and OS. Disease recurrence was defined as local failure or distant metastasis after surgery. CSS included only patients who died of UTUC, and OS included all causes of deaths. The extracted items were as follows: first author, publication year, region, recruitment period, number of cases, definition of LVI, LVI percentage, inclusion and exclusion criteria, definition of recurrence, and adjusted covariates  was calculated to quantify the degree of heterogeneity. A fixed effects model was adopted to pool the HRs if I2 was ≤50%; otherwise, a random effects model was selected. We performed a subgroup analysis and a meta-regression analysis to explore potential heterogeneity. Next, a Galbraith plot was designed and a leave-one-out analysis was performed to search for studies causing heterogeneity and examine the weight of their influence on the pooled HR [P values were two-sided, and the statistical significance was set at P ≤ 0.05. Statistical analysis was performed using Stata version 15.0 .The effect measures for the outcomes of PFS, CSS, and OS were the HRs and 95% CIs in the multivariable analysis with Cox proportional hazard regression, which were extracted from all included studies. LVI was considered an independent predictor if the pooled 95% CI did not overlap with 1 and ooled HR . An inflThe process of identifying relevant studies is illustrated in Tables I2 > 50%, we used a random effects model to pool the HRs. The pooled HR was statistically significant for PFS , CSS , and OS , with high heterogeneity  , the pooled HR was 1.64 (95%CI = 1.35–1.99) for CSS (I2 = 0%)  and CSS (P = 0.011). The Galbraith plot showed that one study revealed heterogeneity in OS .To explore the source of potential heterogeneity, we classified the enrolled studies into those from Japan, Korea, China, and other regions . In PFS and CSS, the nd China . The metty in OS ; in the P = 0.443, CSS: P = 0.096, and OS: P = 0.894) , the pooled HR showed that LVI could increase the risk of cancer-specific death . Unfortunately, most articles did not investigate the relationship between LVI and different stages of UTUC; thus, adding LVI as a predictor to TNM staging requires studies that focus on stratification of the tumor stage. Novara et al. have investigated the interaction between LVI and lymph node stage [In this meta-analysis, we identified 18 studies evaluating PFS, 19 evaluating CSS, 11 evaluating OS, 4 evaluating the CSS of patients with advanced tumor stages, and 6 evaluating the PFS and CSS in node-negative patients. Given the rarity of UTUC, it is notable that the present meta-analysis has a higher sample size than that of a previously published meta-analysis  and has de stage . They fode stage . Althougde stage .We developed more stringent exclusion criteria and conducted a subgroup analysis to decrease the clinical heterogeneity. Studies with fewer than 100 patients were excluded to rule out interference with the outcomes . StudiesThe biological mechanisms of the positive association between LVI and poor UTUC outcomes are complex. LVI is defined as the presence of tumor cells within an endothelium-lined space without underlying muscular walls  and is aI2 of PFS, CSS, and OS decreased to 68%, 58%, and 0%, respectively. The heterogeneity mainly came from the geographical region (for PFS and CSS). Although a random effects model was used and many statistical methods were implemented, the conclusions reached in our meta-analysis should be interpreted with caution.To the best of our knowledge, this meta-analysis is the most comprehensive of its kind to identify the association between LVI and poor outcomes of UTUC. This meta-analysis has several strengths. First, we adopted the largest sample size , although we used more stringent inclusion and exclusion criteria. This massive study population enhances the statistical power and ensures more accurate risk estimation. Second, this is the first analysis of the influence of LVI in patients with advanced tumor stages (T3–T4) and lymph node-negative UTUC through a meta-analysis with low heterogeneity. Third, no publication bias existed in our study. Our meta-analysis also had several limitations. First, all enrolled articles were retrospective studies; thus, many confounding factors could not be corrected because of a lack of patient information. For this reason, the outcomes of our meta-analysis might deviate from the actual situation in the clinical setting. Second, significant heterogeneity was found for PFS, CSS, and OS. However, we found the potential origin of heterogeneity and the article causing heterogeneity through subgroup, meta-regression, and leave-one-out analyses. After excluding the article from China, the In conclusion, the pooled results demonstrate that LVI is a significant prognostic factor for UTUC, especially for lymph node-negative patients, and is strongly associated with disease recurrence, cancer-specific mortality, and overall mortality. It can also denote a poor prognosis of UTUC with an advanced tumor stage (T3–T4). We advocate systematic assessment of LVI after RNU using pathological specimens. The results of this meta-analysis need to be further confirmed by adequately designed prospective studies before LVI is included in the AJCC TNM staging system of UTUC.


P = 0.02). Moreover, a significant association between the patients with glioma and controls was also observed in a recessive model . In contrast, the CC genotype of the TP53 Arg72Pro was associated with a significantly increased risk of glioma compared to the GG genotype , and a significant association between the patients with glioma and controls was also observed in a recessive model . These findings suggest that the pri-miR-34b/c rs4938723CC and TP53 Arg72-Pro polymorphisms may be associated with the risk of glioma.Growing evidence indicates that p53 can regulate the expression of miRNAs, particularly the miR-34 family members, which are described as potential tumor suppressors. Loss of miR-34 suppresses TP53-mediated cell death, whereas over expression of miR-34 induced apoptosis. The study designed to investigate the association between the pir-miR-34b/c rs4938723, TP53 Arg72Pro and the risk of glioma. We genotyped the two polymorphisms in175 glioma patients and 235 healthy controls using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and DNA sequencing assay. Association analysis showed that the CC genotype of the pir-miR-34b/c rs4938723 was associated with a significantly decreased risk of glioma compared to the TT genotype (CC vs. TT: adjusted OR = 0.43;95% CI, 0.21–0.87, Glioma, a common intracranial malignant tumor in the central nervous system, has a poor prognosis and high mortality –4. The iTo date, some risk factors have been found to contribute to the pathogenesis of gliomas, such as ionizing radiation, genetic syndromes, dietary and occupational exposures , 10. WitSingle nucleotide polymorphisms (SNPs) refer to DNA sequence polymorphisms at the genomic level, which occurs in both coding and non-coding regions of genes. SNPs in the promoter regions and coding regions are associated with susceptibility of malignancy. The rs4938723C/T polymorphism in the promoter region of pri-miR-34b/c was predicted to influence the binding of transcription factor GATA-X to its target genes, and thus affect the expression levels of the target genes related to tumor differentiation and tumorigenesis –20. DefiThe study was ratified by the ethics committee of Kunming Medical University, and written informed consent was obtained from all subjects participating in this study. The case-control study population consisted of 410 unrelated Chinese Han individuals including 175 patients  newly diagnosed with glioma and 235 controls  living in Yunnan province in China. Patients who diagnosed as glioma were recruited from the First Affiliated Hospital of Kunming Medical University during a period from January 2012 to September 2015.The control group consisted of 235 healthy controls in the same hospital during the same period. Subjects with any disease in nervous system were excluded from this study.Approximately 2 ml of venous blood sample was collected from 175 glioma patients and 235 controls. Genomic DNA was extracted using a DNA extraction kit  on the basis of instructions provided by the manufacturer. The pri-miR-34b/c rs4938723 and TP53 Arg72Pro were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. The primer sequences for rs4938723 were as follows: 5′-CCTCTGGGAACCTTCTTTGACCAAT-3′ (sense) and 5′-TGAGATCAAGGCCATACCATTCAAGA-3′ (antisense). The primers for TP53 Arg72Pro were 5′-CCCCCTTGCCGTCCCAAGCAATGG-3′ (sense) and 5′-CTGCTGGTGCAGGGGCCGCG-3′ (antisense). For quality control, all gel pictures were read by two researchers double-blindly, and discrepant results were analyzed repeatedly. Moreover, all the results of PCR-RFLP which confirmed by direct sequencing were coincident.2 test for each polymorphism among control subjects. The genotype frequencies of pri-miR-34b/c rs4938723 and TP53 Arg72Pro in patients with glioma and controls were compared using χ2 test . A 5% level of significance was used in the analysis, and all statistical tests were two sided. Logistic regression analysis was performed to assess the association of pri-miR-34b/c rs4938723 and TP53 Arg72Pro with the risk of glioma by computing odds ratio (OR) and 95% confidence interval (CI). Statistical analysis of data was performed by SPSS 19.0 statistical software .Hardy–Weigliomaerg equilibrium (HWE) was analyzed by χTP53 Arg72Pro in patients with glioma and controls was determined to estimate the relationship to the risk of glioma. The genotype and allele frequencies distribution of both polymorphisms in the controls met the requirements of the HWE (p > 0.05). Tables TP53 Arg72Pro. Compared to the pri-miR-34b/c rs4938723TT genotype, the CC genotype was found to decrease the risk of glioma . Moreover, a significant association was found in a recessive model as well . In contrast, for TP53 Arg72-Pro, the CC genotype was associated with a significantly increased risk of glioma compared to the GG genotype . In addition, a significant association between glioma group and control group was detected in a recessive model  (Table TP53 Arg72Pro and the risk of glioma for allelic association analysis (Table TP53 Arg72-Pro polymorphisms showed no significant effect on glioma risk (Table A total of 175 glioma patients and 235 incognito controls were registered in our study. Table TP53 Arg72Pro polymorphisms influence the susceptibility to glioma in the Han Chinese population and we found that individuals with the CC genotype of pri-miR-34b/c rs4938723 had a lower risk of glioma than the TT genotype. In contrast, individuals with the CC genotype of TP53 Arg72-Pror had a higher risk of glioma than the GG genotype. These results suggest that the pri-miR-34b/c rs4938723 and TP53 Arg72Pro may exert different actions in the oncogenesis of glioma.We conducted a case-control study to evaluate whether the pri-miR-34b/c rs4938723 and TP53 and pri-miR-34b/c may singly and/or jointly contribute to the tumorigenesis (It is well known that igenesis . It was igenesis . Thus, migenesis . Down-reigenesis , while oigenesis . Moreoveigenesis , gastricigenesis  and esopigenesis . In contigenesis , and it igenesis  and cervigenesis . Additioigenesis , 17. TheTP53 Arg72Pro polymorphism and the risk of different kinds of cancer. A meta-analysis conducted by De-Ke Jiang et al. concluded that TP53 Arg72 carriers can significantly reduce the risk of esophageal cancer (TP53 Arg72Pro CC genotype may contribute to an increased risk of CRC, especially for rectal cancer and among Asians (TP53 Arg72-Pro CC genotype will significantly increase the risk of glioma. However, no significance was detected after combining with miR-34b/c rs4938723, implying that pri-miR-34b/c rs4938723 and TP53 Arg72Pro may be offset each other on the development of glioma.p53 inhibits the occurrence and development of cancer effectively . So far l cancer . In contl cancer . The TP5g Asians . In thisThere are some limitations that should be addressed in this study. First, the small sample size in this study may have an impact on statistical power. Second, follow-up data was not acquired which prevented our further survival analysis. Finally, the study subjects were all ethnic Han Chinese, which raised possibility that our results cannot be used directly to other populations. To address the concern, further large-scale studies among different populations are needed.TP53 Arg72-Pro may be a risk factor for glioma. Due to several limitations as discussed above, multi-racial population studies and functional analysis of rs4938723 polymorphism and TP53 Arg72-Proin gliomas are warranted. Identification of glioma susceptibility genes is a critical step toward a better understanding the underlying mechanisms of glioma carcinogenesis, potentially leading to development of novel, genetic markers and surveillance programs.In conclusion, our study provides evidence that the pri-miR-34b/c rs4938723 might be a protective factor via decreasing the risk of glioma. On the contrary, The datasets during and/or analyzed during the current study are available from the corresponding author on reasonable request.JuL and HY designed the study. JiL and XL was a major contribute or in writing the manuscript. JiL and XL carried out the molecular genetic studies, participated in the sequence alignment. YQ, RQ, SL, YG, and JG participated in the sequence alignment and performed the statistical analysis. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Q1 = 0.61, 95% confidence interval [CI] = 0.39–0.97), although there was no significant trend ; Genistein and daidzein concentrations were not significantly associated with risk . In men from Europe, circulating concentrations of genistein, daidzein and equol were not associated with risk. Circulating lignan concentrations were not associated with the risk of prostate cancer, overall or by disease aggressiveness or time to diagnosis. There was no strong evidence that prediagnostic circulating concentrations of isoflavones or lignans are associated with prostate cancer risk, although further research is warranted in populations where isoflavone intakes are high.Phytoestrogens may influence prostate cancer development. This study aimed to examine the association between prediagnostic circulating concentrations of isoflavones  and lignans (enterolactone and enterodiol) and the risk of prostate cancer. Individual participant data were available from seven prospective studies . Because of the large difference in circulating isoflavone concentrations between Japan and Europe, analyses of the associations of isoflavone concentrations and prostate cancer risk were evaluated separately. Prostate cancer risk by study‐specific fourths of circulating concentrations of each phytoestrogen was estimated using multivariable‐adjusted conditional logistic regression. In men from Japan, those with high compared to low circulating equol concentrations had a lower risk of prostate cancer  and lignans  and prostate cancer risk. They found no strong associations but point to the fact that further data are needed to examine associations based on disease aggressiveness, especially in populations with high isoflavone intakes. BMIbody mass indexCIconfidence intervalORodds ratio1in vitro studies, animal models and observational studies has suggested that this may be due to their effects on hormone metabolism and receptor signalling, or to other mechanisms such as effects on DNA repair, angiogenesis and cell proliferation.It has been hypothesised that a high dietary phytoestrogen intake may inhibit prostate cancer development.The Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (EHNBPCCG) was established to conduct collaborative analyses of individual participant data from prospective studies on the associations of circulating concentrations of hormones and nutritional biomarkers with risk of prostate cancer.22.1phyto‐oestrogens, phytoestrogens, isoflavones, genistein, daidzein, equol, enterolactone and enterodiol together with the MeSH term prostatic neoplasms and text term prostate cancer. The literature searches were conducted using articles with publication dates through to November 2017 from PubMed, Web of Science, Cochrane Library, CancerLit (up to January 2013) and Google Scholar and from discussions with colleagues. This collaborative group also includes unpublished data obtained from discussion with colleagues, which reduces the risk of publication bias.Studies were eligible to join this collaborative analysis if they had data on circulating phytoestrogens measured in blood samples collected prior to a prostate cancer diagnosis. Studies were identified by using the search terms 2.2Individual participant data were available from seven nested case–control studies by the date of dataset closure November 2017): the European Prospective Investigation into Cancer and Nutrition (EPIC) (cases diagnosed from June 1999 to January 2003 (designated Phase 1);17: the EThis large collaborative analysis has brought together and reanalysed almost all of the available prospective data on the associations of circulating isoflavone and lignan concentrations with prostate cancer incidence, representing, as far as we are aware, all of the worldwide prospective data on circulating genistein, daidzein and equol, and over 90% of the worldwide data on circulating lignans. While data on enterolactone were not available for this analysis, their results do not differ materially from those reported here, and it is unlikely that these data would have changed our summary risk estimates.The characteristics of the studies and the assay methods are shown in Tables Where available, collaborators provided data for prostate cancer cases and controls on serum or plasma phytoestrogen concentrations, dates of birth and blood collection, marital status, ethnicity, educational attainment, family history of prostate cancer, height, weight and smoking status. Most studies also provided data on cancer stage and grade and date at diagnosis. Tumour stage was categorised as localised if it was tumour‐node‐metastasis (TNM) stage ≤T2 with no reported lymph node involvement or metastases, stage ≤II, or equivalent; advanced stage if it was T3 or T4 and/or N1+ and/or M1, stage III‐IV, or equivalent; or unknown. Aggressive disease was categorised as “no” for TNM stage ≤T3 with no reported lymph node involvement or metastases or the equivalent, “yes” for TNM stage T4 and/or N1+ and/or M1 and/or stage IV disease or death from prostate cancer, or unknown. Histological grade was categorised as low‐intermediate grade if the Gleason sum was <8, or coded as well, moderately or poorly differentiated; high grade if the Gleason sum was ≥8, or coded as undifferentiated; or grade unknown.2.3The methods of analysis were similar to those described previously by this collaborative group.p‐value for trend, the categorical variable representing the fourths of phytoestrogen concentration was replaced with a continuous variable that was scored 0, 0.33, 0.67 and 1, respectively. Because the mid‐points of the lowest and highest fourths are the 12.5 and 87.5 percentage points of the study‐specific phytoestrogen concentration, a unit increase in this variable can be taken to represent a 75 percentile increase in phytoestrogen concentration. The effects of additional potential confounders  were examined by additionally adjusting for variables that were found to be associated with prostate cancer risk in this collaborative dataset,2, unknown), height , marital status , educational status  and cigarette smoking .Men were categorised into fourths of concentrations for each phytoestrogen, with cut points defined by the study‐specific quartiles of the distribution in control participants. This approach allows for any systematic differences between the studies, i.e., assay methods, blood sample types or storage conditions.vs. ≥ 65 years], years between blood collection and diagnosis [<5 vs. ≥ 5 years], year of diagnosis [pre‐2000 vs. 2000 onwards], stage [localised vs. advanced], aggressiveness [no vs. yes] and grade [low‐intermediate vs. high]), we fitted separate models for each subgroup and assumed independence of the ORs using a method analogous to a meta‐analysis. Data on tumour stage and/or grade were only available for one of the two Japanese studies,Heterogeneity in linear trends between studies was tested by comparing the chi‐squared values for models with and without a (study) × (linear trend) interaction term. To identify evidence of heterogeneity in the associations of phytoestrogens with prostate cancer risk according to case‐defined characteristics  were assessed with chi‐squared tests of interaction between the subgroup and the continuous trend test variable.Tests for heterogeneity for non‐case‐defined factors .3A total of 241 cases and 503 controls from two Japanese prospective studies, and 2,828 cases and 5,593 controls from five European prospective studies were included in this analysis. The mean age at blood collection in cases or controls across the studies ranged from 46.5 to 68.7 years . Genistein and daidzein concentrations were not significantly associated with risk . In men from Europe, circulating concentrations of genistein, daidzein and equol were not associated with risk.The ORs for prostate cancer risk by fourths of circulating isoflavone concentrations (separately by Japanese and European studies), adjusted for age, marital status, educational attainment, smoking, height and BMI are shown in FigureFiguresandpheterogeneity = 0.001): the OR for a 75 percentile increase in genistein was 0.73 (95% CI: 0.56–0.95) in EPIC Phase 1, while it was 1.51 (95% CI: 1.06–2.13) in EPIC phase 2  with a reduction in risk of prostate cancer for cases diagnosed before the year 2000  but not in cases diagnosed later   Fig..Figs.pheterogeneity = 0.028). Here, daidzein was associated with a reduced risk of prostate cancer in men with a BMI ≥ 25 kg/m2  but not in normal‐weight men   Fig..Fig. ). There was also no evidence of heterogeneity in these associations between the different studies  Fig. . There es Figs.andS10 4The results of this collaborative analysis of individual participant data show no strong evidence that prediagnostic circulating concentrations of isoflavones or lignans are associated with prostate cancer risk. Equol concentrations were weakly inversely related with overall prostate cancer risk in Japanese populations; this association was significant when we compared the highest with the lowest fourth, but we did not find a significant linear trend. When we looked into subtypes, we found some evidence of heterogeneity in three subgroups; however, given the number of comparisons made in our study, these may be chance findings.This large collaborative analysis has brought together and reanalysed almost all of the available prospective data on the associations of circulating isoflavone and lignan concentrations with prostate cancer incidence, representing, as far as we are aware, all of the worldwide prospective data on circulating genistein, daidzein and equol, and over 90% of the worldwide data on circulating lignans. While data on enterolactone from the α‐Tocopherol, β‐Carotene Cancer Prevention Study (214 case patients)Some studies have studies whether prostate cancer risk is related to the dietary intake of soya foods, but a meta‐analysis of prospective studies reported no association.In vitro and animal studies have shown that equol has anti‐androgenic and anti‐proliferative properties in the prostate,Equol is a metabolite produced in the gastrointestinal tract by bacterial metabolism of daidzein, and there is some evidence that equol has higher hormonal activity that genistein and daidzein.in vitro and clinical studies have suggested that a diet rich in precursors of mammalian lignans  may have antiproliferative effects in the early stages of prostate cancer development.Both enterolactone and enterodiol are formed from plant‐lignan glycoside precursors by the activity of the gut microbiota in the proximal colon.The current analyses have several strengths and limitations. Strengths include the large sample size, the detailed data on participant characteristics, and the consistent statistical approach used to analyse the individual participant data across the studies. Moreover, this collaboration only includes prospective studies, which allowed us to assess whether associations varied by time from blood collection to diagnosis and hence examine possible reverse causality. The limitations of these analyses include the use of a single blood sample measurement of phytoestrogens, as the true exposure of interest is medium to long‐term average levels of circulating phytoestrogens. Two studies in women have shown that the within‐person reproducibility (over a 1‐ to 3‐year period) is relatively poor for daidzein and genistein.5There was no strong evidence that prediagnostic circulating concentrations of isoflavones or lignans are associated with prostate cancer risk. However, further data are needed to examine these associations by disease aggressiveness, especially in populations following traditional East Asian diets.Supplementary Table 1. Study characteristics, including sample population, recruitment and assessment characteristics.Supplementary Table 2. Assay detailsSupplementary Figure 1. Study‐specific ORs (95% CIs) for prostate cancer associated with a 75 percentile increase in genistein concentrations. Estimates are from logistic regression conditioned on the matching variables within each study, but not further adjusted. Heterogeneity in linear trends between studies and between Japanese and European studies was tested by comparing the χ2 values for models with and without a (studies) x (linear trend) interaction term. Abbreviations: European Prospective Investigation into Cancer and Nutrition (EPIC), Japan Collaborative Cohort Study (JACC), Japan Public Health Center‐based prospective Study (JPHC).Supplementary Figure 2. Study‐specific ORs (95% CIs) for prostate cancer associated with a 75 percentile increase in daidzein concentrations. Estimates are from logistic regression conditioned on the matching variables within each study, but not further adjusted. Heterogeneity in linear trends between studies and between Japanese and European studies was tested by comparing the χ2 values for models with and without a (studies) x (linear trend) interaction term. Abbreviations: European Prospective Investigation into Cancer and Nutrition (EPIC), Japan Collaborative Cohort Study (JACC), Japan Public Health Center‐based prospective Study (JPHC).Supplementary Figure 3. ORs for prostate cancer associated with genistein concentration, according to characteristics of cases and controls in Japanese studies. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fourths of genistein concentration by a continuous variable scored as 0, 0.33, 0.67, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of genistein with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case‐control sets matched within each study and adjusted for age at blood collection (exact), body mass index , height , marital status , and cigarette smoking .Supplementary Figure 4. ORs for prostate cancer associated with daidzein concentration, according to characteristics of cases and controls in Japanese studies. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fourths of daidzein concentration by a continuous variable scored as 0, 0.33, 0.67, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of daidzein with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case‐control sets matched within each study and adjusted for age at blood collection (exact), body mass index , height , marital status , and cigarette smoking .Supplementary Figure 5. ORs for prostate cancer associated with equol concentration, according to characteristics of cases and controls in Japanese studies. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fourths of equol concentration by a continuous variable scored as 0, 0.33, 0.67, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of equol with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case‐control sets matched within each study and adjusted for age at blood collection (exact), body mass index , height , marital status , and cigarette smoking .Supplementary Figure 6. ORs for prostate cancer associated with genistein concentration, according to characteristics of cases and controls in European studies. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fourths of genistein concentration by a continuous variable scored as 0, 0.33, 0.67, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of genistein with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case‐control sets matched within each study and adjusted for age at blood collection (exact), body mass index , height , marital status , educational status , and cigarette smoking .Supplementary Figure 7. ORs for prostate cancer associated with daidzein concentration, according to characteristics of cases and controls in European studies. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fourths of daidzein concentration by a continuous variable scored as 0, 0.33, 0.67, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of daidzein with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case‐control sets matched within each study and adjusted for age at blood collection (exact), body mass index , height , marital status , educational status , and cigarette smoking .Supplementary Figure 8. ORs for prostate cancer associated with equol concentration, according to characteristics of cases and controls in European studies. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fourths of equol concentration by a continuous variable scored as 0, 0.33, 0.67, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of equol with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case‐control sets matched within each study and adjusted for age at blood collection (exact), body mass index , height , marital status , educational status , and cigarette smoking .Supplementary Figure 9. Study‐specific ORs (95% CIs) for prostate cancer associated with a 75 percentile increase in enterolactone concentrations. Estimates are from logistic regression conditioned on the matching variables within each study, but not further adjusted. Heterogeneity in linear trends between studies and between Japanese and European studies was tested by comparing the χ2 values for models with and without a (studies) x (linear trend) interaction term. Abbreviations: European Prospective Investigation into Cancer and Nutrition (EPIC), Janus Nordic Biological Specimen Biobank Working Group (NBSBWG), the Malmö Diet and Cancer Study (MDCS), Northern Sweden Health and Disease Cohort (NSHDC)Supplementary Figure 10. Study‐specific ORs (95% CIs) for prostate cancer associated with a 75 percentile increase in enterodiol concentrations. Estimates are from logistic regression conditioned on the matching variables within each study, but not further adjusted. Heterogeneity in linear trends between studies and between Japanese and European studies was tested by comparing the χ2 values for models with and without a (studies) x (linear trend) interaction term. Abbreviation: European Prospective Investigation into Cancer and Nutrition (EPIC).Supplementary Figure 11. ORs for prostate cancer associated with enterolactone concentration, according to characteristics of cases and controls. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fourths of enterolactone concentration by a continuous variable scored as 0, 0.33, 0.67, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of enterolactone with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case‐control sets matched within each study, but not further adjusted.Supplementary Figure 12. ORs for prostate cancer associated with enterodiol concentration, according to characteristics of cases and controls. Each OR is the estimate of the linear trend obtained by replacing the categorical variables representing the fourths of enterodiol concentration by a continuous variable scored as 0, 0.33, 0.67, and 1. Black squares indicate the OR, and the horizontal lines show the 95% CIs. The area of each square is proportional to the amount of statistical information (inverse of the variance of the logarithm of the OR). The vertical dotted line indicates the OR for all studies. Tests for heterogeneity are for the difference in the association of enterodiol with prostate cancer risk between subgroups. Estimates are from conditional logistic regression on case‐control sets matched within each study, but not further adjusted.Click here for additional data file.


NAT2) gene polymorphisms with isoniazid-induced hepatotoxicity, but the results obtained were inconsistent and inconclusive. A comprehensive trial sequence meta-analysis was conducted employing 12 studies comprising 3613 controls and 933 confirmed TB cases using the databases namely, EMBASE, PubMed (Medline) and Google Scholar till December 2017. A significant association was observed with individuals carrying variant allele at position 481C>T , at position 590G>A  and at position 857G>A  to higher risk of hepatotoxicity vis-à-vis wild-type allele. Likewise, the other genetic models of NAT2 gene polymorphisms have also shown increased risk of hepatotoxicity. No evidence of publication bias was observed. These results suggest that genetic variants of NAT2 gene have significant role in isoniazid induced hepatotoxicity. Thus, NAT2 genotyping has the potential to improve the understanding of the drug–enzyme metabolic capacity and help in early predisposition of isoniazid-induced hepatotoxicity.Hepatotoxicity is a severe problem generally faced by tuberculosis (TB) patients. It is a well-known adverse reaction due to anti-TB drugs in TB patients undergoing long-term treatment. The studies published previously have explored the connection of N-acetyltransferase 2 ( Mycobacterium tuberculosis is the single most prominent species responsible for tuberculosis (TB) disease. This is a commonly prevalent disease present in almost all societies of the world. It causes a significant burden of morbidity and mortality on human population. The data from the year 2015 showed that almost 10.4 million people suffered from TB leading to 1.8 million deaths (http://www.who.int/mediacentre/factsheets/fs104/en/). The current most effective control is curing the patients with anti-TB drugs like isoniazid or isonicotinylhydrazide (INH), rifampicin (RMP) and pyrazinamide (PZA). These anti-TB drugs are used in combination for 6 or more months to cure the infection completely. The most common side effect associated with the use of anti-TB drugs is idiosyncratic hepatotoxicity, worldwide  that guaranteed the stability of the overall results.To assess the individual study influence on the overall risk of INH-induced hepatotoxicity, the leave-one-out sensitivity analysis was performed and pooled ORs were recomputed for each NAT2 481C>T, 590G>A, 857G>A gene polymorphisms and INH-induced hepatotoxicity risk by minimizing the random errors. Using the dominant model as an example for all the three studied polymorphisms of NAT2 gene, the TSA was performed. The TSA results indicate insufficiency of cumulative evidence advising further trials .TSA was applied to investigate the precise association between r trials A,B,C. BeNAT2 enzyme that mediates the bioconversion of INH to its metabolite acetyl INH. Acetyl INH is hydrolyzed to acetyl hydrazine and further acetylated by NAT2 to non-toxic diacetyl hydrazine. In case of low NAT2 activity, acetyl hydrazine is predominantly oxidized by CYP2E1 leading to increased hepatotoxicity [NAT2 [NAT2 gene can affect the function of NAT2 enzyme resulting in reduced stability, altered affinity for the substrate, or a protein that is targeted for proteosome degradation [Many efforts have been done in the past decades to bring the TB disease under control, but most of them proved to be heart-wrenching. The risk for progression of anti-tuberculosis drug induced hepatotoxicity affecting humans is a serious and one of the most frequent side effects . It posetoxicity . Hydrazity [NAT2 . Hepatocty [NAT2 . Single-radation .NAT2 gene in view, previously several studies [NAT2 481C>T, 590G>A, and 857G>A gene variants and the development of INH-induced hepatotoxicity in TB patients from different populations but failed to give concrete conclusion possibly due to small size, and still the said relationship is controversial. Generally, small sample sizes makes studies statistically weak, thereby, less likely to detect small risk factors of the disease. A well-organized meta-analysis investigating the relationship between NAT2 481C>T, 590G>A, and 857G>A gene polymorphisms and risk of developing INH-induced hepatotoxicity in TB patients is still wanting. Therefore, we conducted this trial sequential meta-analysis to precisely investigate the pharmacogenetic contribution of these three polymorphisms of NAT2 gene in overall INH-induced hepatotoxicity risk. On the basis of 12 case–control design based independent publications, we in this meta-analysis proved with the help of statistical data that individuals carrying variant allele of 481C>T, 590G>A and 857G>A polymorphisms of NAT2 gene had higher risk of INH-induced hepatotoxicity than those with the wild allele of these polymorphisms. It supports the significant role of NAT2 gene polymorphisms in the etiology of hepatotoxicity. The NAT2 gene polymorphisms reduce the metabolism of INH in the liver, which is linked to an increased hepatotoxicity risk. Previously published phyenotypic studies also reported that all the anti-tuberculosis drugs, i.e. INH, RMP, PZA and EMB, usually induce hepatotoxicity and may follow different pathogenic mechanisms [M. tuberculosis is susceptible to INH; however, PZA is effective against slow growing bacilli in acidic milieus, and RMP against non-replicating bacilli [NAT2 gene plays a first key role in hepatotoxicity caused by INH and RMP combination therapies, and RMP is known to reduce NAT2 activity and may act as a potent inducer of CYP2E1 [in vitro study has also shown that INH and its toxic metabolite, hydrazine, increases the toxicity of PZA to hepatocytes [NAT2 is indirectly involved to affect the metabolism of other ATD drugs except INH.Considering the pharmacogenetic significance of  studies  have trichanisms ,52. In c bacilli . NAT2 gef CYP2E1 . An in vatocytes . In thisNAT2 genotyping is warranted before the starting of the administration of anti-tuberculosis drug therapy, this will ultimately help the clinicians to personalize and optimize the treatments régimes, making them therapeutically more efficient while simultaneously minimizing the side effects associated with the use of these drugs.Nowadays, the pharmacogenetic testing has been more and more applied to identify and exclude the individuals with a certain genetic makeup for the treatment in the clinical practice. Hence, In addition to the precise conclusion, some advantageous attributes of the present trial sequence meta-analysis are: first, the quality wise evaluation of the chosen 12 studies was sternly done by following NOS quality scoring, wherein most of the studies attained five or more stars suggesting each individual study as of modest to good quality. The NOS quality analysis took into account the sample size, inclusion criteria for TB patients with INH-induced hepatotoxicity, genotypes and inclusion of TB patients without hepatotoxicity as controls for each study. Second, strict and explicit search and preset selection procedure was adopted for the inclusion of the studies. Third, the procedural issues, e.g. publication bias and sensitivity, usually arising in meta-analysis were well explored , which further confirmed the validity and reliability of the present study. The outcome of the leave-one-out sensitivity analysis also depicted no significant effect on cumulative ORs and their corresponding CIs. Fourth, TSA was also performed for strengthening the conclusion and reducing the type I error rate.It is well established that interim analyses increase the risk of type I error in a single trial ,54. HoweThe potential limitations of the current pooled study were: (a) heterogeneity was detected in few genetic models, so random-effects model was applied to get wider CIs, (b) the studies published in English were included for the current meta-analysis, it is quite obvious that some relevant studies might published in other languages may have overlooked, (c) only most famous web-databases were searched, it is possible that some pertinent studies available in other databases may have skipped and (d) only three SNPs were considered for the current meta-analysis because of their wide reporting in independent studies; this might have led to the possibility of oversighting other SNPs affecting INH metabolism.NAT2 481C>T, 590G>A and 857G>A gene polymorphisms have increased risk of developing INH-induced hepatotoxicity. These results will help in improving the understanding related to the role of NAT2 481C>T, 590G>A and 857G>A gene polymorphisms and assist in identifying the individuals prone to disease, which could be helpful in achieving optimal treatment of individual TB patients. Further to this, the present study warrants to perform the additional studies with large sample size to investigate the potential molecular mechanism underlying INH-induced hepatotoxicity and facilitate the development of molecular approaches to detect the susceptible genotype, and to verify the current findings reported in this manuscript.In summary, our meta-analysis supports that TB affected individuals with