| BackgroundThe three major malignancies of the female reproductive organs are ovarian cancer,cervical cancer and endometrial cancer.Among them,ovarian cancer has the highest mortality rate and the hidden onset,which has become one of the main problems threatening women's health.Ovarian cancer is a disease associated with genetic factors,which determine the susceptibility of tumors.Therefore,it is of great importance to actively look for the related factors of ovarian cancer susceptibility and strengthen the monitoring of high-risk groups for the early detection of the disease,the promotion of early diagnosis rate,and the improvement of survival and prognosis of cancer patients.Bioinformatics is the combination of mathematics,statistics,computer informatics discipline,is today one of the major frontier in life science and natural science,public database set up based on bioinformatics,growing to a public database mining use Meta analysis and combined with tumor genomics research methods for ovarian cancer susceptibility factors research provides a great convenience,we can in the female reproductive system tumor early identification,etiology,treatment and prognosis of disease diagnosis,evolution to improve the aspects such as research,to provide a new direction in.the process of diagnosis and treatment of malignant tumor and the basis.Objectives:The public database based on biological information was mined and analyzed to screen the genes related to the susceptibility of ovarian cancer and search for the target gene loci.The Meta analysis was applied to verify the relationship between the target gene loci and the suseeptibility of ovarian eancer and to explore the correlation between the target gene and the prognosis of ovarian cancer.Methods:By exeavating "Online human Mendel database(Online human M endelian based database,OMIM)"(https://www.ncbi.nlm.nih.gov/omim/),find the exact location of the ovarian cancer related gene chromosomes,according to t he frequency of further screening on regional position,associated with ovarian cancer susceptibility for the segment chromosomal regions containing loci by e xploring,choose the purpose we are interested in genetic loci.Then,according to the characteristics of quantitative genetics,four genetic effect models of tar get gene loci were established:allele model,dominant model,recessive model and additive model.Pubmed,CNfKI,wanfang,VIP,Cochrane library database were searched by computer,and the literature on the expression of target gene loci(including genotyping),ovarian cartcer were searched,The two researchers independently screened the literature.After the original data were extracted an d the risk of bias in the included studies were evaluated,meta-analysis was pe rformed using RevMan 5.3 software.The survival curve was plotted with the k m-plotter database,and the long-term survival rate was used as the reference i ndex to further study the prognosis of target genes and ovarian cancer.Results:1.The online human Mendelian genetic database(OMIM)was used to mine and locate the chromosomal susceptible areas of ovarian cancer,and 336 genes related to ovarian cancer were found.2.Further screening of the site area related to the susceptibility of ovarian cancer showed that the gene loci in the long arm region 1,zone 3-3,zone 3 of chromosome 5 were more frequent,and their locations were concentrated in the narrow region of 5ql3.2-5q33.3.3.According to gene location 5q33.3,MiR146a SNP site rs2910164 was located at this location.Literature review shows that MiR146a is closely related to the occurrence and development of tumors in the current studies on a variety of tumors.Domestic and foreign literatures have reported that this SNP site is related to the susceptibility of ovarian cancer,but the conclusions are inconsistent4.The OR and 95%CI values of 4 genetic effect models of ovarian cancer were analyzed by Meta analysis.Allele models:OR=0.54,95%CI=0.36-0.80,P=0.002.Dominant model:OR=0.38,95%CI=0.16-0.91,P=0.03;Recessive model:OR=0.57,95%CI=0.45-0.72,P<0,00001;Additive models:OR=0.31,95%CI=0.14-066,P=0.003.The results showed that the polymorphism of miR146a rs2910164 SNP was associated with the risk of ovarian cancer,and the difference was st atistically significant(P<0.05).Among them,the risk of individuals with CC g enotype was significantly lower than that of individuals with GC and GG geno types(P<0.05).5.Km-plotter database analyzed the relationship between MiR146a level an d prognosis of ovarian cancer patients,and found that the survival rate of pati ents with ovarian cancer in the MIR 146a high expression group was better tha n that in the lo-N expression group(P<0.05).Conclusions:1.Through database information mining and meta-analysis,it was found that rs2910164 polymorphism of miR146a SNP site was associated with the reduced risk of ovarian cancer.Survival analysis suggested that the m iR146a high expression group had a better prognosis in ovarian cancer patients.It is further indicated that it may play an important role in the occurrence,d evelopment and even long-term survival of ovarian cancer.It is suggested that the polymorphism of the MIR146a SNP site rs2910164 may be clinically recog nizable to susceptible populations,and the detection of its expression level can provide a basis for early diagnosis and prognosis.2.Through online human Mendelian genetic database(OMIM)mining and Meta analysis,SNP sites of tumor susceptibility genes can be found,providin g clues and directions for subsequent studies,as a way to find and study tuno r susceptibility genes. |
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