Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung

Our plain-English summary of Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung, by J. Du, L. Zhang (International Journal of Molecular Medicine, 2017).

The study

• Authors: J. Du, L. Zhang
• Journal: International Journal of Molecular Medicine
• Published: 2017;39(3):579-586
• Cited by: 6 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

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.

In plain English

This was a computer-based reanalysis of gene activity data already published by another research group (Wright et al.) and stored in a public database. The data came from 56 squamous cell lung cancer samples. 26 were classed as asbestos-related because the nearby non-tumor lung tissue held more than 20 asbestos bodies per gram wet weight, and 30 had no asbestos bodies. The authors counted genes as different at P less than 0.05 without adjusting for multiple testing. On that basis, 1,333 genes differed between the groups: 391 were more active and 942 less active in the asbestos-related cancers. A new scoring method kept 524 genes, and a pathway analysis of these genes identified 22 enriched biological pathways at a cut-off of P less than 0.1 (12 at P less than 0.05). One pathway, SNARE interactions in vesicular transport, correlated with 12 others. Eight genes, including EGFR, PDGFB and IGF1, were shared between linked pathways. The authors concluded these genes may serve as biomarkers and drug targets. They could not test this in the laboratory because the samples were unavailable.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Computational (bioinformatics) reanalysis of previously published gene expression microarray data, using gene network and pathway analysis; no new samples were collected or tested
• Who was studied: 56 human lung squamous cell carcinoma samples from the public Gene Expression Omnibus dataset GSE23822: 26 asbestos-related (ARLC-SCC) and 30 non-asbestos-related (NARLC-SCC). Country and years are not stated in this article.
• Exposure: Asbestos exposure was judged from asbestos bodies in non-tumor lung tissue. Cases were asbestos-related if there were more than 20 asbestos bodies per gram wet weight, and non-asbestos-related if none were found. Fiber types, jobs and products are not reported.
• Main results:
  • Genes were counted as differentially expressed at P less than 0.05, using P-values before false discovery rate (multiple-testing) adjustment
  • 1,333 genes differed between the 26 asbestos-related and 30 non-asbestos-related samples: 391 upregulated and 942 downregulated in the asbestos-related cancers
  • Using the authors' new importance score, the top 50% of differentially expressed genes (524 genes) were kept for further analysis
  • Pathway enrichment analysis of the 524 genes identified 22 enriched KEGG pathways at P less than 0.1; 12 of these remained at P less than 0.05
  • Grouping by pathway scores separated asbestos-related from non-asbestos-related samples, except for one non-asbestos-related sample that grouped with the asbestos-related cluster
  • 13 significantly correlated pathway pairs were found; 12 pathways correlated with the SNARE interactions in vesicular transport pathway
  • Four cross-talk genes (EGFR, PRKX, PDGFB, PIK3R3) were shared by the MAPK signaling, glioma, regulation of actin cytoskeleton and apoptosis pathways
  • Four more cross-talk genes (SLK, IGF1, CDC42, PRKCA) linked the cell cycle, circadian rhythm, oocyte meiosis and neurotrophin signaling pathways
• The authors' conclusion: The authors concluded that the cross-talk genes deregulated in asbestos-related squamous cell lung cancer may be used as biomarkers and multi-effect drug targets
• Limitations the authors state:
  • No laboratory validation of the findings was done, because the patient samples were not available to the authors

Topics

The National Library of Medicine indexes this study under subjects our site covers: Asbestosis, Lung cancer.

Medical terms in this study, explained in our Lexicon: Biomarker, Squamous Cell Carcinoma, Carcinoma, Lung Cancer, Squamous Cell, EGFR.

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