Construction Of CeRNA Network Based On Differentially Expressed Genes Of Gastric Cancer In GEO Database And The Relationship Between CAMK2N1 And Immune Infiltration

Aim:Based on online high-throughput transcriptome sequencing datasets of online tumor database,new biomarkers related to gastric cancer were searched for by bioinformatics methods and molecular biology experiments,and their diagnostic and prognostic value was evaluated.At the same time,the potential mechanism is discussed by constructing ceRNA network.Finally,the relationship between CAMK2N1 and immune infiltration was evaluated.Mothed:Download GEO datasets(GSE13911,GSE29998,GSE26899)and TCGA-STAD related transcriptome data and clinical information.Extract the common differentially expressed genes from these three GEO datasets and then verify whether the expression of the differentially expressed genes in TCGA-STAD is consistent with the trend in GEO microarray chips.Exclude genes that have already been reported in gastric cancer through literature search.Perform prognostic analysis and diagnostic significance analysis on the screened differentially expressed genes.Further select differentially expressed genes that are both prognostically significant and consistent with their expression trend.Construct a ceRNA network for the differentially expressed genes finally selected.Further validate the expression of CAMK2N1 in gastric cancer cell lines by qPCR and Western Blot.Explore whether the abnormal expression of CAMK2N1 is associated with copy number variation in the c Bio Portal database.Analyze the correlation between the expression of CAMK2N1 and the molecular and immune subtypes of gastric cancer using the TISIDB database.Conduct prognostic subgroup analysis based on clinical-pathological staging and immune cell enrichment using the Kaplan-Meier plotter database.Analyze the correlation between clinical-pathological characteristics and CAMK2N1 expression in the TCGA-STAD dataset.Enrichment analysis of CAMK2N1-related biological functions and signaling pathways using GO,KEGG and GSEA.Analyze the relationship between CAMK2N1 and immune cell infiltration,immune matrix scoring,immune cell markers,and immune checkpoints using the ss GSEA algorithm,ESTIMATE algorithm,and TIMER 2.0 database.Results:Based on the validation of GEO dataset and TCGA gastric cancer dataset expression,and excluding reported genes,10 differently expressed genes were identified.After diagnostic and prognostic analysis of these 10 genes,7 genes were selected to construct a ceRNA network.Based on a series of bioinformatics analyses,THUMPD3/LINC00174/KCNQ1OT1/NEAT1/SNHG10/MZF1-AS1-mi R-378a-3pCAMK2N1 were identified as potential ceRNA network of differentially expressed genes.CAMK2N1 was significantly upregulated in gastric cancer cell lines by q-PCR and Western Blot experiments.Copy number variation of CAMK2N1 was positively correlated with m RNA expression according to c Bio Portal database.CAMK2N1 expression showed significant differences across different molecular subtypes and immune subgroups of gastric cancer.Prognostic analysis showed that patients with high CAMK2N1 expression had poor prognosis in most a relationship between CAMK2N1 and immune function.Further immune infiltration analysis showed that CAMK2N1 was highly correlated with immune cell infiltration,stroma score,immune markers,and immune checkpoint in gastric cancer.Conclusion:(1)THUMPD3-AS1/LINC00174/KCNQ1OT1/NEAT1/SNHG10/MZF1-AS1-mi R-378a-3p-CAMK2N1 may be a ceRNA network mechanism of differential gene CAMK2N1;(2)CAMK2N1 is highly expressed in gastric cancer tissues and cells lines and is associated with poor prognosis;(3)CAMK2N1 is significantly negatively correlated with immune cell infiltration,immune matrix scoring,and immune checkpoint.