Abstract
BackgroundLung cancer is a leading cause of cancer-related death worldwide and is the most commonly diagnosed cancer. Like other cancers, it is a complex and highly heterogeneous disease involving multiple signaling pathways. Identifying potential therapeutic targets is critical for the development of effective treatment strategies.MethodsWe used a systems biology approach to identify potential key regulatory factors in smoking-induced lung cancer. We first identified genes that were differentially expressed between smokers with normal lungs and those with cancerous lungs, then integrated these differentially expressed genes (DEGs) with data from a protein-protein interaction database to build a network model with functional modules for pathway analysis. We also carried out a gene set enrichment analysis of DEG lists using the Kinase Enrichment Analysis (KEA), Protein-Protein Interaction (PPI) hubs, and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases.ResultsTwelve transcription factors were identified as having potential significance in lung cancer (CREB1, NUCKS1, HOXB4, MYCN, MYC, PHF8, TRIM28, WT1, CUX1, CRX, GABP, and TCF3); three of these (CRX, GABP, and TCF) have not been previously implicated in lung carcinogenesis. In addition, 11 kinases were found to be potentially related to lung cancer (MAPK1, IGF1R, RPS6KA1, ATR, MAPK14, MAPK3, MAPK4, MAPK8, PRKCZ, and INSR, and PRKAA1). However, PRKAA1 is reported here for the first time. MEPCE, CDK1, PRKCA, COPS5, GSK3B, BRCA1, EP300, and PIN1 were identified as potential hubs in lung cancer-associated signaling. In addition, we found 18 pathways that were potentially related to lung carcinogenesis, of which 12 (mitogen-activated protein kinase, gonadotropin-releasing hormone, Toll-like receptor, ErbB, and insulin signaling; purine and ether lipid metabolism; adherens junctions; regulation of autophagy; snare interactions in vesicular transport; and cell cycle) have been previously identified.ConclusionOur systems-based approach identified potential key molecules in lung carcinogenesis and provides a basis for investigations of tumor development as well as novel drug targets for lung cancer treatment.
Highlights
Lung cancer is a leading cause of cancer-related death worldwide and is the most commonly diagnosed cancer
We carried out a gene-set enrichment analysis (GSEA) of Differentially expressed genes (DEG) using ChIP-x Enrichment Analysis (ChEA), Kinase Enrichment Analysis (KEA), Protein-Protein Interaction (PPI) hubs, and Kyoto encyclopedia of genes and genomes (KEGG) (Kyoto Encyclopedia of Genes and Genomes) gene-set libraries
Pathway analysis of DEG lists with PPI databases We identified DEGs using GEO2R and Python script analysis tools
Summary
Lung cancer is a leading cause of cancer-related death worldwide and is the most commonly diagnosed cancer Like other cancers, it is a complex and highly heterogeneous disease involving multiple signaling pathways. Lung cancer is a complex and highly heterogeneous disease involving multiple signaling pathways [1]. It is the leading cause of cancer mortality in men and the second leading cause in women worldwide [2]. Small cell lung carcinoma (SCLC) and non-small cell lung carcinoma (NSCLC) are the main types of lung cancer The latter represents 80% of lung cancer cases and can be subclassified as squamous cell carcinoma, adenocarcinoma, or large cell carcinoma [3, 4]. Tobacco smoke was found to cause lung cancer by inducing of IκB kinase β- and c-Jun N-terminal kinase 1-dependent inflammation [8]
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