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Overdue treatment and prognostic evaluation lead to low survival rates in patients with lung adenocarcinoma (LUAD). To date, effective biomarkers for prognosis are still required. The aim of the present study was to screen differentially expressed genes (DEGs) as biomarkers for prognostic evaluation of LUAD. DEGs in tumor and normal samples were identified and analyzed for Kyoto Encyclopedia of Genes and Genomes/Gene Ontology functional enrichments. The common genes that are up and downregulated were selected for prognostic analysis using RNAseq data in The Cancer Genome Atlas. Differential expression analysis was performed with 164 samples in GSE10072 and GSE7670 datasets. A total of 484 DEGs that were present in GSE10072 and GSE7670 datasets were screened, including secreted phosphoprotein 1 (SPP1) that was highly expressed and DEGs ficolin 3, advanced glycosylation end-product specific receptor (AGER), transmembrane protein 100 that were lowly expressed in tumor tissues. These four key genes were subsequently verified using an independent dataset, GSE19804. The gene expression model was consistent with GSE10072 and GSE7670 datasets. The dysregulation of highly expressed SPP1 and lowly expressed AGER significantly reduced the median survival time of patients with LUAD. These findings suggest that SPP1 and AGER are risk factors for LUAD, and these two genes may be utilized in the prognostic evaluation of patients with LUAD. Additionally, the key genes and functional enrichments may provide a reference for investigating the molecular expression mechanisms underlying LUAD.
Pubmed ID: 29849788
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Software for fitting probe-level models and tools using these models. Probe-level models (PLM) based quality assessment tools.
View all literature mentionsBioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
View all literature mentionsSoftware package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsOpen source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.
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