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

ABSTRACT: 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.

SUBMITTER: Lee D

PROVIDER: S-EPMC3675130 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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

Lee Donghoon D Lee Geon Kook GK Yoon Kyong-Ah KA Lee Jin Soo JS

PloS one 20130606 6

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 ca ...[more]

PMID: 23762359

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Project description:BackgroundInterindividual variation in genetic background may influence the response to chemotherapy and overall survival for patients with advanced-stage non-small cell lung cancer (NSCLC).MethodsTo identify genetic variants associated with poor overall survival in these patients, we conducted a genome-wide scan of 307,260 single-nucleotide polymorphisms (SNPs) in 327 advanced-stage NSCLC patients who received platinum-based chemotherapy with or without radiation at the University of Texas MD Anderson Cancer Center (the discovery population). A fast-track replication was performed for 315 patients from the Mayo Clinic followed by a second validation at the University of Pittsburgh in 420 patients enrolled in the Spanish Lung Cancer Group PLATAX clinical trial. A pooled analysis combining the Mayo Clinic and PLATAX populations or all three populations was also used to validate the results. We assessed the association of each SNP with overall survival by multivariable Cox proportional hazard regression analysis. All statistical tests were two-sided.ResultsSNP rs1878022 in the chemokine-like receptor 1 (CMKLR1) was statistically significantly associated with poor overall survival in the MD Anderson discovery population (hazard ratio [HR] of death = 1.59, 95% confidence interval [CI] = 1.32 to 1.92, P = 1.42 × 10(-6)), in the PLATAX clinical trial (HR of death = 1.23, 95% CI = 1.00 to 1.51, P = .05), in the pooled Mayo Clinic and PLATAX validation (HR of death = 1.22, 95% CI = 1.06 to 1.40, P = .005), and in pooled analysis of all three populations (HR of death = 1.33, 95% CI = 1.19 to 1.48, P = 5.13 × 10(-7)). Carrying a variant genotype of rs10937823 was associated with decreased overall survival (HR of death = 1.82, 95% CI = 1.42 to 2.33, P = 1.73 × 10(-6)) in the pooled MD Anderson and Mayo Clinic populations but not in the PLATAX trial patient population (HR of death = 0.96, 95% CI = 0.69 to 1.35).ConclusionThese results have the potential to contribute to the future development of personalized chemotherapy treatments for individual NSCLC patients.

Dataset Information

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

Publications

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

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