by Ashwin Kotnis, Junghyun Namkung, Sadhana Kannan, Nallala Jayakrupakar, Taesung Park, Rajiv Sarin, Rita Mulherkar
In order to elucidate a combination of genetic alterations that drive tobacco carcinogenesis we have explored a unique model system and analytical method for an unbiased qualitative and quantitative assessment of gene-gene and gene-environment interactions. The objective of this case control study was to assess genetic predisposition in a biologically enriched clinical model system of tobacco related cancers (TRC), occurring as Multiple Primary Neoplasms (MPN). Methods
Genotyping of 21 candidate Single Nucleotide Polymorphisms (SNP) from major metabolic pathways was performed in a cohort of 151 MPN cases and 210 cancer-free controls. Statistical analysis using logistic regression and Multifactor Dimensionality Reduction (MDR) analysis was performed for studying higher order interactions among various SNPs and tobacco habit. Results
Increased risk association was observed for patients with at least one TRC in the upper aero digestive tract (UADT) for variations in SULT1A1 Arg213His, mEH Tyr113His, hOGG1 Ser326Cys, XRCC1 Arg280His and BRCA2 Asn372His. Gene - environment interactions were assessed using MDR analysis. The overall best model by MDR was tobacco habit/p53(Arg/Arg)/XRCC1(Arg399His)/mEH(Tyr113His) that had highest Cross Validation Consistency (8.3) and test accuracy (0.69). This model also showed significant association using logistic regression analysis. Conclusion
This is the first Indian study on a multipathway based approach to study genetic susceptibility to cancer in tobacco associated MPN. This approach could assist in planning additional studies for comprehensive understanding of tobacco carcinogenesis.