Background. Multiple myeloma (MM) is characterized by inherited susceptibility and marked genetic instability. Polymorphisms in multiple absorption, distribution, metabolism and excretion (ADME) genes involved in metabolism of carcinogenic agents may contribute to cancer risk through a change in the gene expression and/or reduction of their products' activity. We investigated the relationship between MM susceptibility and xenobiotic metabolism by the drug-metabolizing enzyme and transporter (DMET(TM)) microarray Affymetrix platform, by genotyping 1936 genetic variants across 231 ADME genes by interrogating 1931 SNPs and 5 CNVs in Linkage disequilibrium (LD) in 65 MM patients matched with a dataset of 59 Caucasian HapMap-related healthy controls in a case control study. Methods. Genomic DNA, extracted from peripheral blood cells, was genotyped by Affymetrix DMET Plus microarray and the genotyping profiles were generated by DMET Console software® algorithm. Genotype frequencies and association analysis were analyzed by DMET-Analyzer software. Results of potential interest were limited to those in which the p-value was <=0.05 and if their correlation to MM risk or protection were confirmed by independent sample test analysis. LD was analyzed using Haploview. Results. Among 16 selected genes potentially associated (p<0.05) to susceptibility to MM we focused on 9 genetic variants in ALDH3A2 (rs72547554), VKORC1 (rs13336384), CHST10 (rs4149522), SULT1C2 (rs11569697), DCK (rs67437265), ADH1B (rs1229984), PPARD (rs6937483 and rs2267668) and POR (rs2286824) genes, validated by independent sample test analysis, while the SNP rs7496 in GSTA4 gene was not confirmed. All these genes were related to MM susceptibility in our training set. Conclusions. Our exploratory study identified 9 polymorphic variants in 8 genes involved in ADME metabolism of xenobiotic and carcinogenic agents as predictive for MM susceptibility to be validated in independent series of patients. DMETTM platform confirms as a robust tool for genetic biomarkers discovery and offers a new mean for investigating genetic susceptibility to MM.
Polymorphisms in ADME genes as potential predictor of multiple myeloma susceptibility
Arbitrio Mariamena;
2019
Abstract
Background. Multiple myeloma (MM) is characterized by inherited susceptibility and marked genetic instability. Polymorphisms in multiple absorption, distribution, metabolism and excretion (ADME) genes involved in metabolism of carcinogenic agents may contribute to cancer risk through a change in the gene expression and/or reduction of their products' activity. We investigated the relationship between MM susceptibility and xenobiotic metabolism by the drug-metabolizing enzyme and transporter (DMET(TM)) microarray Affymetrix platform, by genotyping 1936 genetic variants across 231 ADME genes by interrogating 1931 SNPs and 5 CNVs in Linkage disequilibrium (LD) in 65 MM patients matched with a dataset of 59 Caucasian HapMap-related healthy controls in a case control study. Methods. Genomic DNA, extracted from peripheral blood cells, was genotyped by Affymetrix DMET Plus microarray and the genotyping profiles were generated by DMET Console software® algorithm. Genotype frequencies and association analysis were analyzed by DMET-Analyzer software. Results of potential interest were limited to those in which the p-value was <=0.05 and if their correlation to MM risk or protection were confirmed by independent sample test analysis. LD was analyzed using Haploview. Results. Among 16 selected genes potentially associated (p<0.05) to susceptibility to MM we focused on 9 genetic variants in ALDH3A2 (rs72547554), VKORC1 (rs13336384), CHST10 (rs4149522), SULT1C2 (rs11569697), DCK (rs67437265), ADH1B (rs1229984), PPARD (rs6937483 and rs2267668) and POR (rs2286824) genes, validated by independent sample test analysis, while the SNP rs7496 in GSTA4 gene was not confirmed. All these genes were related to MM susceptibility in our training set. Conclusions. Our exploratory study identified 9 polymorphic variants in 8 genes involved in ADME metabolism of xenobiotic and carcinogenic agents as predictive for MM susceptibility to be validated in independent series of patients. DMETTM platform confirms as a robust tool for genetic biomarkers discovery and offers a new mean for investigating genetic susceptibility to MM.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
