Pathway-based analysis using genome-wide association data from a Korean non-small cell lung cancer study

PLoS One. 2013 Jun 6;8(6):e65396. doi: 10.1371/journal.pone.0065396. Print 2013.


Pathway-based analysis, used in conjunction with genome-wide association study (GWAS) techniques, is a powerful tool to detect subtle but systematic patterns in genome that can help elucidate complex diseases, like cancers. Here, we stepped back from genetic polymorphisms at a single locus and examined how multiple association signals can be orchestrated to find pathways related to lung cancer susceptibility. We used single-nucleotide polymorphism (SNP) array data from 869 non-small cell lung cancer (NSCLC) cases from a previous GWAS at the National Cancer Center and 1,533 controls from the Korean Association Resource project for the pathway-based analysis. After mapping single-nucleotide polymorphisms to genes, considering their coding region and regulatory elements (±20 kbp), multivariate logistic regression of additive and dominant genetic models were fitted against disease status, with adjustments for age, gender, and smoking status. Pathway statistics were evaluated using Gene Set Enrichment Analysis (GSEA) and Adaptive Rank Truncated Product (ARTP) methods. Among 880 pathways, 11 showed relatively significant statistics compared to our positive controls (PGSEA≤0.025, false discovery rate≤0.25). Candidate pathways were validated using the ARTP method and similarities between pathways were computed against each other. The top-ranked pathways were ABC Transporters (PGSEA<0.001, PARTP = 0.001), VEGF Signaling Pathway (PGSEA<0.001, PARTP = 0.008), G1/S Check Point (PGSEA = 0.004, PARTP = 0.013), and NRAGE Signals Death through JNK (PGSEA = 0.006, PARTP = 0.001). Our results demonstrate that pathway analysis can shed light on post-GWAS research and help identify potential targets for cancer susceptibility.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Asian Continental Ancestry Group
  • Carcinoma, Non-Small-Cell Lung / diagnosis
  • Carcinoma, Non-Small-Cell Lung / ethnology
  • Carcinoma, Non-Small-Cell Lung / genetics*
  • Carcinoma, Non-Small-Cell Lung / metabolism
  • Case-Control Studies
  • Databases, Genetic
  • Female
  • Gene Expression Regulation, Neoplastic*
  • Genetic Predisposition to Disease*
  • Genome, Human
  • Genome-Wide Association Study*
  • Humans
  • Logistic Models
  • Lung Neoplasms / diagnosis
  • Lung Neoplasms / ethnology
  • Lung Neoplasms / genetics*
  • Lung Neoplasms / metabolism
  • Male
  • Metabolic Networks and Pathways / genetics*
  • Middle Aged
  • Models, Genetic
  • Polymorphism, Single Nucleotide*
  • Signal Transduction

Grant support

The research was supported by National Cancer Center research grant 1210360. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.