Abstract
Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR), classification and regression tree (CART) and multifactor dimensionality reduction (MDR), was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11–2.59,p = 0.01), whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25–0.65,p<0.001 and OR = 0.51;95%CI = 0.33–0.78,p = 0.002 respectively). In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His), SULT1A1 213GG (Arg/Arg) or AA (His/His) and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33–10.55,p = 0.006), whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg) and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15–7.51,p = 0.01). MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His) and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His) with testing balance accuracy (TBA) of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with SULT1A1 Arg213His and EPHX1 Tyr113His in smokers and SULT1A1 Arg213His with GSTP1 Ile105Val and CYP1A1*2C in nonsmokers. These results identified distinct gene-gene and gene environment interactions in smokers and non-smokers, which confirms the importance of multifactorial interaction in risk assessment of lung cancer.
Highlights
Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer death globally [1]
Genotype distribution of CYP1A1*2A, EPHX1 Tyr113His, SULT1A1 Arg213His and GSTT1 null polymorphism were significantly different in cases from controls (p = 0.014, p,0.001, p = 0.01 and p = 0.04 respectively)
Heterozygous genotype in CYP1A1*2A was associated with increased risk (OR = 1.69,95% CI = 1.1122.59; p = 0.01) whereas heterozygous genotypes in EPHX1 Tyr113His and SULT1A1 Arg213His imparted reduced risk towards lung cancer (OR = 0.40;95%C.I = 0.2520.65,p,0.001 and odds ratio (OR) = 0.51;p = 0.33x2 0.78,p = 0.002 respectively)
Summary
Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer death globally [1]. In India it constitutes 6.2% of all cancers with approximately 58,000 incident cases reported in 2008 and is the most frequent cancer in males [2]. North eastern (NE) part of India is showing a steady rise in cancer incidences and lung cancer is among the ten leading sites, with the highest age-adjusted incidence rate (AAR) in Mizoram state (24.5 in males and 26.3 in females). Aizwal district alone shows an AAR of 36.0 in males and 38.7 in females which is almost three to ten times higher than Delhi [3]. Incidence of lung cancer is high among males in Silchar and Imphal districts. High incidence rates suggest role of both genetic as well as environmental factors such as smoking, tobacco use and dietary carcinogen consumption
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