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Bioinformatics Analysis Of Differentially Expressed Genes And Clinical Significance In Lung Neuroendocrine Neoplasms

Posted on:2022-11-29Degree:MasterType:Thesis
Country:ChinaCandidate:S Y MaFull Text:PDF
GTID:2504306761955129Subject:Master of Clinical Medicine
Abstract/Summary:PDF Full Text Request
ObjectiveTo identify and analyze differentially expressed genes(DEGs)of lung neuroendocrine tumors(L-NETs)and lung neuroendocrine carcinomas(L-NECs)compared with DEGs in normal lung tissues through comprehensive bioinformatics analysis,and further explore potential biological targets related to their occurrence,development and prognosis.MethodsGSE1037 gene expression profiles were obtained from the GEO database.DEGs in L-NETs and L-NECs,as compared with normal lung tissues,were selected to use the GEO2 R online analyzer and Venn diagram software.GO and KEGG analyses of DEGs were performed to use R language.Subsequently,a PPI network of DEGs was generated to use STRING database and displayed via Cytoscape software.The PPI network was analyzed by MCODE Plugins and cyto Hubba Plugins,the Molecular Complex Detection app from Cytoscape,to gain the key functional modules and Hub genes.Then the Kaplan-Meier Plotter database was used to analyze the survival prognosis of the screened Hub genes.ResultsA total of 89 common DEGs in L-NECs,including 31 significantly upregulated DEGs and 58 downregulated DEGs were obtained through analyzing.The common upregulated DEGs were primarily enriched in the functions such as cell division,chromosome segregation,chromosomal structure and ubiquitin-related enzyme activity,and in the biological pathways such as cell division,cell cycle,DNA replication and mismatch repair.The common downregulated DEGs were primarily enriched in the functions such as tissue remodeling,membrane-related biogenesis,catecholcontaining compound metabolic,membrane structure,apical part of cells,organic acid binding and peptidase regulator activity,and in the biological pathways such as drug metabolism-cytochrome P450 and tyrosine metabolism.Finally,a total of 10 Hub genes were screened,all of which were the upregulated genes,and the survival analysis proved that the OS of these genes in the highexpression group was significantly shorter than those in the low-expression group.A total of 273 common DEGs in L-NETs,including 99 significantly upregulated DEGs and174 downregulated DEGs were obtained.The common upregulated DEGs were primarily enriched in the functions such as synaptic biology occurs,synaptic transmission regulation and GTPase activity,and in the biological pathways such as neuroactive ligand-receptor interaction.The common downregulated DEGs were primarily enriched in the functions such as leukocyte cell-cell adhesion,regulation of inflammatory response,regulation of the immune response,collagencontaining extracellular matrix,membrane structure,apical part of cells,peptidase regulator activity and extracellular matrix structural constituent,and in the biological pathways such as cell adhesion molecules.Finally,a total of 3 Hub genes were screened,all of which were the downregulated genes,and the survival analysis proved that the OS of these genes in the low-expression group was significantly shorter than that in the high-expression group.Conclusion1.Compared with lung normal tissues,the TOP10 Hub genes identified in the L-NECs group,namely TPX2,AURKA,NUF2,TTK,TOP2 A,UBE2C,EZH2,CENPU,RFC4 and CDCA8,were verified by survival analysis,which were determined to be possibly related to the development of L-NECs and were expected to become the biomarkers for the diagnosis,treatment and prognosis of L-NECs.2.Compared with lung normal tissues,the TOP10 Hub genes identified in the L-NETs group,were verified by the survival analysis,and three genes namely PTPRC,VWF,and CASP1 of those were determined to be possibly related to the development of L-NETs,which might be potential targets for the diagnosis,treatment and prognosis of L-NETs.
Keywords/Search Tags:Lung neuroendocrine neoplasms, Differentially expressed genes, Enrichment analysis, Survival analysis, Hub genes
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