Preprocessing and Analysis of DMET Data for Pharmacogenomics

This paper presents a suite of bioinformatics tools for the preprocessing and analysis of Drug Metabolism Enzymes and Transporters (DMET) Single Nucleotide Polymorphisms (SNPs) data. The DMET Affymetrix platform allows to identify genes involved in the Distribution, Metabolism, and Excretion (ADME) in case-control studies. DMET data must be preprocessed and analyzed in order to identify a correlation between the presence/absence of SNPs and the status of samples (e.g., type of drug treatment). The open-source bioinformatics platforms include the following tools, developed at the Bioinformatics Laboratory of the University of Catanzaro: DMET-Analyzer [1] is a software tool for the analysis of genotyping data in pharmacogenomics studies. It performs the association analysis among the differences in the patients' genomes and the different response to the drugs, using Fisher's test. DMET-Miner [2] is a software tool able to correlate the simultaneous presence of a set of allelic variants with the response to the drug by using association rules. OS-Analyzer (OSA) [3] is a software tool for the computation and visualization of Overall Survival (OS) and Progression-Free Survival (PFS) curves of cancer patients, using DMET data enriched with survival events. These tools have been successfully used in the following pharmacogenomics studies [4, 5]. References. 1. P.H. Guzzi, et. al "DMET-Analyzer: automatic analysis of Affymetrix DMET Data", BMC Bioiformatics, vol. 13, p. 1-19; 2. G. Agapito, et. al "DMET-Miner: Efficient discovery of association rules from pharmacogenomic data," Journal of biomedical informatics Vol. 56, pp. 273-283.; 3. Agapito G., et al. OSAnalyzer: A Bioinformatics Tool for the Analysis of Gene Polymorphisms Enriched with Clinical Outcomes. Microarrays. 2016;5(4).; 4. Di Martino MT, et. al: "A peroxisome proliferator-activated receptor gamma (PPARG) polymorphism is associated with zoledronic acid-related osteonecrosis of the jaw in multiple myeloma patients: analysis by DMET microarray profiling." Br J Haematology 2011, 154(4):529-533.; 5. Arbitrio, M. et. al: "Polymorphic Variants in NR1I3 and UGT2B7 Predict Taxane Neurotoxicity and Have Prognostic Relevance in Patients With Breast Cancer: A Case-Control Study." Clin. Pharmacol. Ther., 106: 422-431.