Identification of novel biomarkers and candidate small molecule drugs in non-small-cell lung cancer by integrated microarray analysis
Open Access
- 1 May 2019
- journal article
- research article
- Published by Taylor & Francis Ltd in OncoTargets and Therapy
- Vol. ume 12, 3545-3563
- https://doi.org/10.2147/ott.s198621
Abstract
Background: Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC. Methods: The microarray datasets of GSE18842, GSE30219, GSE31210, GSE32863 and GSE40791 from Gene Expression Omnibus database were downloaded. The differential expressed genes (DEGs) between NSCLC and normal samples were identified by limma package. The construction of protein–protein interaction (PPI) network, module analysis and enrichment analysis were performed using bioinformatics tools. The expression and prognostic values of hub genes were validated by GEPIA database and real-time quantitative PCR. Based on these DEGs, the candidate small molecules for NSCLC were identified by the CMap database. Results: A total of 408 overlapping DEGs including 109 up-regulated and 296 down-regulated genes were identified; 300 nodes and 1283 interactions were obtained from the PPI network. The most significant biological process and pathway enrichment of DEGs were response to wounding and cell adhesion molecules, respectively. Six DEGs (PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5) which significantly up-regulated in NSCLC tissues, were selected as hub genes according to the results of module analysis. The GEPIA database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. Additionally, CMap predicted the 20 most significant small molecules as potential therapeutic drugs for NSCLC. DL-thiorphan was the most promising small molecule to reverse the NSCLC gene expression. Conclusions: Based on the gene expression profiles of 696 NSCLC samples and 237 normal samples, we first revealed that PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5 could act as the promising novel diagnostic and therapeutic targets for NSCLC. Our work will contribute to clarifying the molecular mechanisms of NSCLC initiation and progression.Keywords
This publication has 43 references indexed in Scilit:
- The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics DataCancer Discovery, 2012
- MultiContrast Delayed Enhancement (MCODE) improves detection of subendocardial myocardial infarction by late gadolinium enhancement cardiovascular magnetic resonance: a clinical validation studyJournal of Cardiovascular Magnetic Resonance, 2012
- Antiangiogenic Agents in Combination with Chemotherapy in Patients with Advanced Non-Small Cell Lung CancerCancer Investigation, 2011
- Cytoscape 2.8: new features for data integration and network visualizationBioinformatics, 2010
- Correlation of mRNA and protein in complex biological samplesFEBS Letters, 2009
- Systematic and integrative analysis of large gene lists using DAVID bioinformatics resourcesNature Protocols, 2008
- PTTG: an important target gene for ovarian cancer therapyJournal of Ovarian Research, 2008
- The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and DiseaseScience, 2006
- BiNGO: a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in Biological NetworksBioinformatics, 2005
- Gene Expression Omnibus: NCBI gene expression and hybridization array data repositoryNucleic Acids Research, 2002