Pathway-based evaluation of 380 candidate genes and lung cancer susceptibility suggests the importance of the cell cycle pathway

Abstract

Common genetic variation may play an important role in altering lung cancer risk. We conducted a pathway-based candidate gene evaluation to identify genetic variations that may be associated with lung cancer in a population-based case-control study in Xuan Wei, China (122 cases and 111 controls). A total of 1260 single-nucleotide polymorphisms (SNPs) in 380 candidate genes for lung cancer were successfully genotyped and assigned to one of 10 pathways based on gene ontology. Logistic regression was used to assess the marginal effect of each SNP on lung cancer susceptibility. The minP test was used to identify statistically significant associations at the gene level. Important pathways were identified using a test of proportions and the rank truncated product methods. The cell cycle pathway was found as the most important pathway (P = 0.044) with four genes significantly associated with lung cancer (PLA2G6 minP = 0.001, CCNA2 minP = 0.006, GSK3 beta minP = 0.007 and EGF minP = 0.013), after adjusting for multiple comparisons. Interestingly, most cell cycle genes that were associated with lung cancer in this analysis were concentrated in the AKT signaling pathway, which is essential for regulation of cell cycle progression and cellular survival, and may be important in lung cancer etiology in Xuan Wei. These results should be viewed as exploratory until they are replicated in a larger study.

Fig. 1.

GSK3B sliding window haplotype analysis and gene map and LD blot. (a) Sliding window: y-axis is odds of lung cancer associated with each 3-SNP window. X-axis is the corresponding SNP number seen in the gene map. (b) Gene map and LD plot: color scheme is based on D′ and the logarithm of the odds of linkage (LOD) values (white: D′ < 1 and LOD < 2, blue: D′ = 1 and LOD < 2, pink/red: D′ < 1 and LOD ≥ 2 and bright red: D′1 = 1and LOD ≥ 2). Numbers in squares are D′1 values (1.0 not shown).