| Objective: This meta-analysis aimed to analyze the effects of vaginal microecology on Human papillomavirus(HPV)infection and cervical squamous intraepithelial lesion(SIL).Methods: Pub Med and Web of Science were systematically searched for eligible publications from January 2000 to December2017.Articles were selected on the basis of specific inclusion and exclusion criteria.The design and quality of all studies were evaluated using the Newcastle-Ottawa Scale(NOS).Odds ratios(ORs)with a 95% confidence interval(95% CI)were calculated.Results: Thirteen eligible studies were selected to evaluate the association of vaginal microecology with HPV infection and SIL.The factors related to HPV infection were bacterial vaginosis(BV)(OR 2.57,95% CI 1.78-3.71,P<0.05),Candida albicans(VVC)(OR 0.63,95% CI 0.49-0.82,P<0.05),Chlamydia trachomatis(CT)(OR 3.16,95% CI 2.55-3.90,P<0.05),and Ureaplasma urealyticum(UU)(OR 1.35,95% CI 1.20-1.51,P<0.05).BV was also related to SIL(OR 1.56,95% CI 1.21-2.00,P<0.05).T.Vaginalis(TV)was not related to HPV(OR 1.19,95%CI 0.90-1.58,P=0.22)and SIL(OR 1.41,95% CI 0.62-3.24,P=0.41).Lactobacillus was not related to HPV and VVC was not related to SIL(OR 0.99,95%CI 0.50-1.98,P=0.98).Conclusions: BV may increase the risk of HPV infection and SIL.CT and UU may increase the risk of HPV infection,and VVC may reduce the risk of HPV infection.Further large-scale studies are needed to confirm our findings.Objective: The aim of this study was to screen candidate differential gene in the five differential pathways related to cervical squamous intraepithelial lesion(SIL)of the cervical microbial community through bioinformatics approaches.Methods: The genes contained in the five pathways were searched form the KEGG(https://www.kegg.jp/kegg/)database and the genes were selected with STRING,Cytoscape,MOCDE tools and Pub Med.The correlation between candidate differential genes and the progress of bacteria and SIL was analyzed by COREMINE online software.Results: 1.A total of about 1442 genes in 5 pathways were obtained through the kegg database search.2.The protein-protein interaction network(PPI)of each pathway genes were constructed by the STRING online database,and we use Cytoscape to visually analyze the PPI and use MOCDE to further screen the genes,finally,we get five protein-protein interaction networks.We combine Pub Med for literature search,and finally we screen ten candidate differential genes(ATM、ABCG2、PCNA、XRCC1、HMGB1、OGG1、LIG1、SMUG1、FEN1、TDG).3.We performed biological annotation and text mining through the COREMINE database and found that 10 genes exist in the annotation network.PCNA,HMGB1,OGG1,SMUG1,XRCC1 and SIL progress have a direct network relationship,ATM,ABCG2,TDG,LIG1,FEN1 and SIL progress have an indirect network relationship.Besides,there is a direct network relationship between ABCG2 and the four bacteria.ATM,PCNA and Acinetobacter,OGG1 and Stenotrophom have a direct network relationship.Other genes also have an indirect network relationship with bacteria.Conclusions: Ten candidate differential genes related to SIL progression in the cervical microbial community were preliminarily screened through bioinformatics analysis.These 10 genes may be important candidate genes related to community microbial regulation of SIL progress.The research of these genes may provide a new target for preventing the progress of SIL.Objective: Ten candidate differential genes related to SIL progress in cervical microbial community screened by bioinformatics were verified for the function.Methods:The differential expression of 10 candidate differential genes in 38 normal cervical tissues,52 SIL tissues,and 30 cervical cancer tissues were detected by fluorescence quantitative PCR method.Logistic regression was used to analyze the risk factors related to the occurrence and progression of SIL.ROC curve analysis was used to predict the value of candidate genes for early warning SIL occurrence and progression.Results:1.The clinical data analysis results of the patients showed that the average age of the cervical cancer group was larger than that of the normal group and the SIL group(P <0.05).The HPV infection rate also gradually increased with the severity of cervical lesions(P <0.05).The serious result of TCT examination also increased with the severity of cervical lesions(P <0.05),but there was no significant difference in the pregnancy and parity of the patients(P> 0.05).2.The expression of ATM,ABCG2,PCNA,OGG1,TDG,LIG1,HMGB1 in three different cervical tissues was statistically significant(P <0.05),and the expression of XRCC1,SMUG1,FEN1 in different cervical tissues was not statistically significant(P> 0.05).3.ROC curve analysis showed that gene OGG1 had the highest diagnostic value for early warning of SIL occurrence,with an AUC area of 0.68(P <0.05),followed by gene HMGB1 with an AUC area of 0.63(P <0.05).The sensitivities of OGG1 and HMGB1 of early warning SIL occurrence were 57.7% and 75.0%,and the specificities were 78.9% and 57.9%,respectively.The valuable genes of early warning SIL progress are HMGB1,LIG1,ABCG2,TDG,PCNA.The AUC areas are 0.74,0.68,0.67,0.65,0.65 respectively(P <0.05),and the sensitivities are 75.0%,83.3% 96.7%,50.0%,76.7% respectively,the specificities are 57.9%,52.6%,39.5%,81.6%,57.9% respectively.4.Logistic regression analysis showed that HPV infection and the serious result of TCT are independent risk factors of early warning SIL occurrence(P <0.05).The low expression of ABCG2 and the high expression of TDG are risk factors of early warning SIL progress(P <0.05).Conclusions:1.Our preliminary analysis suggests that ATM,ABCG2,PCNA,OGG1,TDG,LIG1,HMGB1 may cooperate with HPV to play a role in the progression of SIL.2.The valuable genes for early warning of the occurrence and progress of SIL are OGG1,HMGB1 and HMGB1,LIG1,ABCG2,TDG,PCNA.The both valuable gene for early warning of the occurrence and progress of SIL is HMGB1.3.HPV infection and the serious result of TCT are independent risk factors that promote the occurrence of SIL,and the low expression of ABCG2 and the high expression of TDG are risk factors that promote the progression of SIL.Its mechanism of action with cervical microbial flora is planned to be carried out in the next experiment.Objective: The mi R-34 a gene was verified for the expression in cervical tissues and cells and HMGB1 gene was verified for the expression in cells.Methods: Fluorescence quantitative PCR was used to detect the differential expression of mi R-34 a in 29 normal cervical tissues,27 cervical squamous intraepithelial lesion(SIL)tissues,and 31 cervical cancer tissues,and to detect mi R-34 a and HMGB1 in Siha and H8 cells.Results: The expression of mi R-34 a in SIL and cervical cancer group was lower than that in normal group(P <0.05),and the expression of mi R-34 a in Siha cells was lower than that of H8 cells(P <0.05).The expression of HMGB1 in Siha cells was higher than that of H8 cells(P <0.05).Conclusions: mi R-34 a is lowly expressed in SIL and cervical cancer tissues and cells,and HMGB1 is highly expressed in cervical cancer cells. |
