ArticleInternational journal of molecular medicine2017
Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung.
Article in International journal of molecular medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- What genes are differentially expressed in individuals with schizophrenia? A systematic review.Molecular psychiatry · 2022Pooled it
- Comparative analysis of key flavonoid synthesis genes in the transcriptome of Cayratia Japonica and therapeutic target prediction for ulcerative colitis : Functional & integrative genomics.Functional & integrative genomics · 2025Article
- Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma.BMC complementary medicine and therapies · 2023Article
- Identification of high expression profiles of miR-31-5p and its vital role in lung squamous cell carcinoma: a survey based on qRT-PCR and bioinformatics analysis.Translational cancer research · 2019Article
- Mechanisms of Compound Kushen Injection for the Treatment of Lung Cancer Based on Network Pharmacology.Evidence-based complementary and alternative medicine : eCAM · 2019Article
- Predicting hepatocellular carcinoma through cross-talk genes identified by risk pathways.Oncotarget · 2018Article
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Abstract
Asbestos-related lung carcinoma is one of the most devastating occupational cancers, and effective techniques for early diagnosis are still lacking. In the present study, a systematic approach was applied to detect a potential biomarker for asbestos-related lung cancer (ARLC); in particular asbestos-related squamous cell carcinoma (ARLC-SCC). Microarray data (GSE23822) were retrieved from the Gene Expression Omnibus database, including 26 ARLC-SCCs and 30 non-asbestos-related squamous cell lung carcinomas (NARLC-SCCs). Differentially expressed genes (DEGs) were identified by the limma package, and then a protein-protein interaction (PPI) network was constructed according to the BioGRID and HPRD databases. A novel scoring approach integrating an expression deviation score and network degree of the gene was then proposed to weight the DEGs. Subsequently, the important genes were uploaded to DAVID for pathway enrichment analysis. Pathway correlation analysis was carried out using Spearman's rank correlation coefficient of the pathscore. In total, 1,333 DEGs, 391 upregulated and 942 downregulated, were obtained between the ARLC-SCCs and NARLC-SCCs. A total of 524 important genes for ARLC-SCC were significantly enriched in 22 KEGG pathways. Correlation analysis of these pathways showed that the pathway of SNARE interactions in vesicular transport was significantly correlated with 12 other pathways. Additionally, obvious correlations were found between multiple pathways by sharing cross-talk genes (EGFR, PRKX, PDGFB, PIK3R3, SLK, IGF1, CDC42 and PRKCA). On the whole, our data demonstrate that 8 cross-talk genes were found to bridge multiple ARLC-SCC-specific pathways, which may be used as candidate biomarkers and potential multi-effect targets. As these genes are involved in multiple pathways, it is possible that drugs targeting these genes may thus be able to influence multiple pathways simultaneously.
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