Predicting The Mechanism Of MALAT1 In Tumors Based On GEO Data

lncRNA research is one of the hot areas of cancer research.There have been reports in the literature on the role and function of MALAT1 in tumors,but the mechanism by which MALAT1 causes cancer is still unclear.Therefore,this article explores the molecular mechanism of MALAT1 causing tumorigenesis and development through meta analysis,GEO database mining,and PPI analysis.Collected article data of the study on the correlation between MALAT1 and cancer prognosis as of January 2018,and a total of 25 studies were included,including 2497 patients.Meta analysis of STATA software showed a correlation between MALAT1 overexpression and poor overall survival(OS)(merged HR = 2.18;95% CI 1.93 ～ 2.45;p=0.135),and MALAT1 overexpression was also correlated with progression-free survival(PFS)(merged HR = 1.34,95% CI 0.91-1.97;p=0.178).The GSE raw data downloaded from the GEO database undergoes preprocessing and data quality control analysis,and finally 8 data sets with 675 cancer samples are obtained for differential expression gene analysis.First,the ovarian cancer GSE18520 data set was used to analyze the differential expression of ovarian cancer,and 4948 differentially expressed genes were obtained;then,according to the ovarian cancer MALAT1 gene expression level,it was divided into high and low expression groups,and finally 154 differentially expressed genes were obtained;The 8 GSE data sets were divided into two groups according to the high and low expression of MALAT1 and analyzed for differentially expressed genes,and 17,954 differentially expressed genes were obtained.The results of the three groups are intersected to obtain 85 target genes with significantly differential expression that may cause tumorigenesis and development.Four lncRNAs and seven miRAN target prediction databases were used to predict the target genes that MALAT1 may directly or indirectly regulate,and combined with the target genes of GEO differential expression analysis,5 miRNAs and 11 core target genes were obtained.Gene function enrichment analysis has enriched 25 GO term and 4 KEGG signal pathways.PPI analysis showed that there are certain interactions among the six core target genes of CUL5,CCNT2,INO80 D,ATF7IP,HNRNPA2B1 and ZNF207.LPP and PTK2 also have a certain interaction relationship.Further GDSC target drug analysis,screening target drugs with statistical significance(p <0.01),the results are as follows: 3target drugs of LPP genes,1 target drug of CLOCK gene;4 target drugs of RAB14 genes;2 target drugs of INO80 D genes;2 target drugs of ZNF207 genes;6 target drugs of ATF7 IP genes;2 target drugs of PTK2 genes;6 target drugs of SEC11 A genes;1 target drug of HNRNPA2B1 gene.This paper uses meta analysis to show that MALAT1 is related to tumor prognosis.Through GEO data mining and multiple bioinformatics databases,the core target molecules of MALAT1 are mined and enriched into four key KEGG signaling pathways that lead to tumorigenesis and development.