MiR-638 Targeting SOX2 Inhibits Prostate Cancer Progression

Background: Prostate cancer(PCa) is the second most common cancer among male neoplastic diseases in the world.According to statistics,it is estimated that 1.3 million new PCa cases and 359000 deaths were found in 2018.Because PCa has a relatively long natural history,it is unique in solid tumors.Most cancers respond well to androgen deprivation therapy at the initial stage,but most patients eventually develop castrated-resistant prostate cancer(CRPC).Therefore,in the context of high-risk PCa,the challenge is to find better biomarkers and treatments to detect and distinguish inert cancer from invasive cancer in time,and to obtain more effective treatment.More and more evidence shows that mRNAS and miRNAs are involved in the occurrence and development of tumors.In most cases,the identification of mRNA and miRNA can properly distinguish between cancerous state and normal state,which may be useful as potential biomarkers in the diagnosis of targeted therapy of PCa.Therefore,the regulation of mRNA and mi RNA plays an important role in many processes of PCa,providing rich sources for the development of new diagnostic and therapeutic targets.Purpose: This study will identify genes and signal pathways associated with PCa progression through integrated bioinformatics analysis.Materials and Methods: The difference of m RNA expression between prostate cancer and normal tissues was analyzed by downloading and analyzing the data of TCGA database.DAVID database was used for gene ontology enrichment analysis of differentially expressed genes.(GO) and KEGG enrichment pathways were analyzed.The selected differentially expressed genes were analyzed by protein interaction network(PPI) using the search tool(STRING) database.The Cytoscape plug-in cyto Hubba was used to screen the hub gene in the PPI network.The public database of GEO was searched with "prostate,cancer,mi RNA" as keywords,and the "GSE60117" gene chip was included in the screening criteria.GEO-2R was used to analyze the differentially expressed genes related to PCa in the two groups of chips on-line.Cooperate with miRDB,mi RTar Base,Target Scan and other online websites to predict the prospective target genes of different genes.Two groups of differentially expressed genes obtained from TCGA and GEO databases were compared and analyzed.Oncomine and Kaplan-Meierplotter databases were used to screen the expression of hub gene in prostate tissues of patients with PCa and its effect on the prognosis of patients with PCa.The relationship between the expression of target gene and different clinical and pathological parameters of prostate cancer was analyzed by limma and ggpubr package of R software.Results: TCGA downloaded mRNA expression profile data related to prostate cancer and screened 1771 differential mRNA,of which 1063 genes were down-expressed and708 genes were up-regulated in prostate cancer.The results of GO enrichment analysis showed that it was mainly involved in extracellular space,extracellular region,whole components of plasma membrane and other biological processes.),KEGG enrichment showed that it was mainly involved in signal pathways such as neuroactive ligand-receptor interaction,nicotine addiction,systemic lupus erythematosus and so on.Ten hub genes were screened from PPI network,among which the transcriptional upregulators were UBC,NMS,NMUR1,NMUR2,POMC,PENK,ADCY5,CDC20,CHRM2 and SST.Two groups of gene chips(GSE60117)were selected from GEO database,and 22 differential miRNA were screened by GEO-2R.145 target genes were obtained by cooperating with online websites such as miRDB,miRTar Base,Target Scan and so on.Based on the comparative analysis of two groups of differentially expressed genes obtained from TCGA and GEO database,it was found that HSPA1 B,TMEM184A,TMEM145,SOX2 and TUBB4 A were differential genes that appeared in the two data sets at the same time.Verification using oncomine and Kaplan-Meierplotter database showed that SOX2 was associated with poor prognosis of PCa.Limma and ggpubr packages of R software were used to analyze the relationship between the expression of SOX2 and different clinical and pathological parameters of prostate cancer.The results showed that it was not related to patient race,tumor pathological type,TNM stage and other factors,but related to patient age and gleason score.Conclusion: We downloaded the gene expression profiles related to TCGA and GEO prostate cancer.By using a series of bioinformatics analysis,we clarified the hub genes and pathways that may be involved in the progression of PCa based on the differentially expressed genes between PCa samples and normal prostate.MiR-638 and SOX2 may be involved in the occurrence and development of PCa,and may be potential prognostic biomarkers and new therapeutic targets for PCa.However,further molecular biology experiments are needed to confirm the function of candidate biomarkers in PCa.