Bioinformatics-based Mining Of The Immunological Role Of MEF2C In Ovarian Cancer And Construction Of A Prognostic Model

ObjectivesOvarian cancer is a common female reproductive system cancer,and the mortality rate is the first place in gynecological malignant tumors.Previous studies have shown that MEF2 C is expressed in a variety of cancers and is significantly related to the prognosis,which is closely related to human immunity,but it is still unclear with immune infiltration in ovarian cancer.This study explores the expression level,biological function and correlation with immune infiltration of MEF2 C in ovarian cancer through biological information analysis methods,and provides new ideas and theoretical basis for ovarian cancer special symbols and ovarian cancer diagnosis and treatment solutions.Methods1.Through the Xian Tao analysis platform and the PROGNOSCAN database to explore the expression and prognosis of MEF2 C genes in pan-cancer,the GEPIA2 database and Kaplan-Meier plotter online software explore the MEF2C’s expression and prognosis in ovarian cancer.Usig the Linkedomics database to excavate MEF2 C to co-expressed genes.GO enrichment analysis,KEGG pathway analysis and the construction of protein-protein interaction networks(PPI)were conducted through the Metascape to analyze MEF2 C gene function.2.The TIMER database was used to evaluate the correlation between MEF2 C gene expression in ovarian cancer and the abundance of immunoinfiltrating cells,immune cell gene markers and ovarian cancer tumor purity.TISIDB was used to study the expression distribution of MEF2 C gene in different immune subtypes of ovarian cancer,to explore the immunoregulatory factors significantly related to MEF2 C expression,and combined with Kaplan-Meier plotter online software to further determine the immune regulatory factors related to the prognosis of ovarian cancer.Clinical and transcriptome data for ovarian cancer samples were obtained from the Cancer Genome Atlas(TCGA)and the Integrated Gene Expression Database(GEO).The LASSO-cox regression analysis method was used to construct the Cox prognostic risk model of ovarian cancer.The optimal cut-off value of risk score was used as the boundary to divide ovarian cancer patients into high and low risk groups.Multivariate survival analysis,prognostic correlation heat map,Kaplan-Meier survival analysis and receiver operating characteristic curve evaluated the prognostic value of the model and compared the survival difference between the high and low risk groups,and verified the accuracy of Cox prognostic risk model.Results1.MEF2 C genes have increased in 10 cancer tissues such as CHOL and DLBC,while 19 kinds of cancers such as ACC,BLCA and OC have decreased,and the differences were statistically significant(P <0.05).2.High MEF2 C expression was significantly associated with shortened OS in patients with acute myeloid leukemia,colorectal cancer,and ovarian cancer.Patients with follicular lymphoma,lung adenocarcinoma and non-small cell lung cancer with high MEF2 C expression had higher OS than those with low MEF2 C expression.The difference was statistically significant(P<0.05).Secondly,high expression of MEF2 C was significantly correlated with longer DSS in patients with multiple myeloma and breast cancer,and with DFS in patients with breast cancer.Longer DFS was associated with shorter DFS in ovarian cancer patients(P<0.05).3.GEPIA2 and Kaplan-Meier plotter analysis showed that MEF2 C expression levels were significantly reduced in ovarian cancer and when overexpressed were associated with poorer PFS and OS,and the difference is statistically significant(P<0.05).4.Genes significantly positively or negatively associated with MEF2 C were obtained from the Linked Omic database.The enrichment analysis in Metascape database showed that MEF2 C was enriched in processes related to immune responses such as leukocyte activation,inflammatory responses,immune response regulatory signalling pathways,osteoclast differentiation,microglia and so on.The PPI network results shows that the main functions associated with MEF2 C proteins are neutrophil degranulation,GPCR ligand binding,and diseases of immune system and more.5.The analysis of TIMER database showed that MEF2 C expression was positively correlated with the infiltration levels of B cells,CD8 + T cells,macrophages,dendritic cells,CD4 + T cells and neutrophils in ovarian cancer,but negatively correlated with the tumor purity of ovarian cancer(P<0.05).CD4+ T cells increased when MEF2 C arm level was absent,and CD8+ T cells decreased significantly when MEF2 C chromosome was highly amplified(P<0.05).At the same time,MEF2 C was also significantly positively correlated with 22 of the 42 immune cell markers,and the difference is statistically significant(P <0.05).6.Analysis of the TISIDB database showed that for the different ovarian cancer immune subtypes,MEF2 C expression was highest in the inflammatory immune subtype and lowest in wound healing subtype.In addition,the TISIDB database combined with Kaplan-Meier plotter online software obtained six immunomodulators were correlated with MEF2 C gene expression and ovarian cancer prognosis.7.LASSO-cox regression analysis showed that the prognostic immunoregulatory factors CXCL12,TGFBR1,TNFSF13 B and MEF2 C could participate in the establishment of Cox risk model.The results of multifactor survival analysis and prognostic heat map showed that MEF2 C,CXCL12 and TGFBR1 genes were prognostic risk factors of ovarian cancer,and TNFSF13 B genes were protective factors.The above four genes had good prognostic significance.Kaplan-Meier survival analysis showed that the overall survival rate of high-risk group was significantly lower than that of low-risk group,and the difference was statistically significant(P<0.05).ROC curve showed that the area under ROC curve of 1 year,3year and 5 year were 0.69,0.63 and 0.60 respectively,indicating that the model had good predictive performance.Conclusions1.The MEF2 C gene is differentially expressed in a variety of cancers and is significantly associated with prognosis.The MEF2 C gene is low in ovarian cancer and its overexpression is associated with poor prognosis in ovarian cancer patients.2.The main biological functions and signalling pathways of the MEF2 C gene are associated with processes related to the immune response.The level of MEF2 C expression in ovarian cancer is significantly and positively correlated with the level of infiltration of multiple immune cells,immune cell markers and inflammatory subtype.MEF2 C may be involved in the progression of ovarian cancer through its immunomodulatory role,and thus affect the prognosis of patients with ovarian cancer.3.The prognostic risk model based on MEF2 C gene and three prognostic immunoregulatory factors of ovarian cancer has been proved to be a prognostic model of ovarian cancer.