Screening, Analysis And QPCR Verification Of Prostate Cancer Biomarkers Related To Diagnosis

Prostate cancer(PCa)is a common disease of elderly men at present.In China,the development of society and economy has caused the population to age.With the change of living environment,the incidence rate of PCa has increased year by year.Prostate specific antigen(PSA),as a single detection index for prostate cancer,has low specificity,low sensitivity,low early diagnosis rate,and poor prognosis.A large proportion of patients have lost the best time for surgery at the time of consultation and mortality Higher.At present,many scholars have studied the biomarkers of PCa,but different laboratories and different researchers choose different genes and adopt different research methods.The results were also different,and even contradictory conclusions appear.There is an urgent need to find potential biomarkers for early diagnosis and prognosis of PCa.In this study,meta-analysis was performed to systematically and comprehensively analyze the existing prostate cancer biomarker research results in clinical studies,and to screen out specific sensitive markers of PCa;and in the Gene Expression Omnibus(GEO)database,the relevant data sets about PCa were studied,the data sets were screened to obtain new potential markers related to prostate cancer by R language,and provide more accurate reference for the diagnosis,prognosis and treatment of PCa;finally The quantitative real-time PCR(qPCR)was used to experimentally verify the screened markers in blood and urine in order to find blood and urine biomarkers for prostate cancer that are suitable for clinical diagnosis and prognosis.The results are as follows:1.By searching PubMed,Embase,Web of Science and the Chinese CNKI,Wanfang database,the published articles on biomarkers related to PCa were collected.According to the inclusion and exclusion criteria of meta analysis literature,the articles were screened and relevant data were extracted from them.The latest data sets GSE69223,GSE55945,GSE45016 and gene expression profiling interactive analysis(GEPIA)were used to verify the selected markers,Finally,AMACR,p53(TP53),Ki67(MK167),PCA3 and GSTP1 genes were determined as biomarkers for prostate cancer diagnosis.PCA3 and GSTP1 genes were the optimal biomarkers for prostate cancer diagnosis,and P53(TP53)gene could be used for prostate cancer prognosis.2.The data sets of GSE69223,GSE55945 and GSE45016 in GEO database were downloaded by R language,then the chip quality evaluation,background correction,standardized processing and data analysis were carried out,| log2 fold change(FC)|≥1.0 and P<0.05 were used as screening conditions of differential gene(DEG)between PCa tissues and normal tissues,A total of 787 DEGs were screened from GSE69223 data set,including 354 up-regulated genes and 433 down-regulated genes;1617 down-regulated genes were screened from GSE55945 data set,including 80 up-regulated genes and 1537 down-regulated genes;652 down-regulated genes were screened from GSE45016 data set,including 30 up-regulated genes and 622 down-regulated genes.The protein interaction network of different genes was analyzed by using string online tool and Cytoscape software,and further the key genes were screened.The key genes screened from GSE69223 data set are EGF、SNAI2、WNT5A、ITGA1、BMP4、FOXA1,the key genes screened from GSE55945 data set are PIK3R1、AGT,ITGA1、LPAR1、ANXA1,and the key genes screened from GSE45016 data set are s TAT3、IL6、JUN、LPAR1、CXCL8、CXCL1.Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis and Gene Ontology(GO)functional enrichment analysis showed that these key genes were mainly involved in GPCR mediated signal pathway,proteoglycan mediated signal pathway and glucocorticoid receptor signal pathway,and involved in signal transduction,cell growth and immune response.Based on the screening results of three data sets,two key genes,namely ITGA1 and LPAR1,were selected as prostate cancer genes related potential genes.GEPIA online tool and Oncomine database were used for differential expression verification and survival analysis of key genes.The results showed that ITGA1 and LPAR1 had differential expression in the PCa group and normal group,which could be used as potential biomarkers for the diagnosis of prostate cancer,but not applicable in the prognosis.3.Real-time PCR was used to verify the PCa biomarkers(AMACR,P53(TP53),KI67(MKI67),PCA3,GSTP1,ITGA1,and LPAR1)screened in Meta and GEO databases.The results showed that these genes were differentially expressed between PCa patients and normal controls.They can all be used as potential biomarkers of blood and urine for prostate cancer diagnosis,and the PCA3 gene has strong specificity.