Generalized Multifactor Dimensionality Reduction (GMDR) Analysis of Drug-Metabolizing Enzyme-Encoding Gene Polymorphisms may Predict Treatment Outcomes in Indian @entity0 XXXX .

@entity1 @entity1262 @entity137 @entity15829 @entity0 @entity9769 @entity4433 @entity5396 @entity7656 @entity14042 @entity72019 @entity5878 @entity47420 @entity20986 @entity7658
BACKGROUND: Prediction of response and @entity137 of chemotherapy can help personalize the treatment and choose effective yet non-toxic treatment regimen for a @entity0 @entity1 . Interplay of variations in various drug-metabolizing enzyme (DME)-encoding genes results in variable response and @entity137 of chemotherapeutic drugs. Generalized multi-analytical (GMDR) approach was used to determine the influence of the combination of variants of genes encoding phase 0 ( @entity72019 ); phase I (CYP450, @entity5878 ); phase II ( @entity47420 , @entity9769 , @entity20986 ); and phase III ( @entity1262 ) DMEs along with confounding factors on the response and @entity137 of chemotherapeutic drugs in @entity0 @entity1 . METHODS: In an Indian @entity0 @entity1 cohort (n  =  234), response to neo-adjuvant chemotherapy (n  =  111) and grade 2-4 @entity137 to chemotherapy were recorded. @entity1 were genotyped for 19 polymorphisms selected in four phases of DMEs by PCR or PCR-RFLP or Taqman allelic discrimination assay. Binary logistic regression and GMDR analysis was performed. Bonferroni test for multiple comparisons was applied, and p value was considered to be significant at <0.025. RESULTS: For @entity1262 @entity7656 polymorphism, CT genotype was found to be significantly associated with response to @entity14042 in uni-variate and multi-variate analysis (p  =  0.018; p  =  0.013). The TT genotype of @entity5878 @entity15829 had a significant association with (absence of) grade 2-4 @entity137 in uni-variate analysis (p  =  0.021), but a non-significant correlation in multi-variate analysis. In GMDR analysis, interaction of @entity5396 *3, @entity5878 @entity15829 , and @entity1262 @entity7656 polymorphisms yielded the highest testing accuracy for response to @entity14042 (CVT  =  0.62). However, for grade 2-4 @entity137 , @entity4433 *2 and @entity1262 @entity7658 polymorphisms yielded the best interaction model (CVT  =  0.57). CONCLUSION: This pharmacogenetic study suggests a role of higher order gene-gene interaction of DME-encoding genes, along with confounding factors, in determination of treatment outcomes and @entity137 in @entity0 @entity1 . This can be used as a potential objective tool for individualizing @entity0 chemotherapy with high efficacy and low @entity137 .
