A wide pharmacogenomic panel from a single oncology center in São Paulo: Data from 103 patients since 2005.

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e22050 Background: Pharmacogenomics has recently emerged as a major tool in the clinical analysis of cancer treatment efficacy. Understanding how mutations alter drug metabolism is crucial for both prognosis and choosing the most likely beneficial drug for each individual patient. Methods: 103 patients' files were studied and the most common malignancies were breast's (43 patients) and colorectal's (19 pts). The median age was 55 years (IQR 46-65), 32 (31%) were men. We performed a retrospective analysis of the pharmacogenetic-assay results and clinical files, which were recorded between 2005 and 2013. The goal of the study was to correlate the mutagenic profile of cancer patients, by identifying mutations in genes responsible for drug metabolism and DNA repair. Results: All distributions were in Hardy Weinberg, except for UGT1A1. The UGT1A1 analysis revealed that 14/51 patients were at increased risk of neutropenia during treatment with irinotecan due to mutations in that gene. Analysis of mutations affecting fluoropyrimidine metabolism, which upregulate both TS and DPD2A genes, yielded the following results: TS-TYMS mutations in 40/73 pts; MTHFR (55/ 89), and DPD2A (1/74), which were associated with higher toxicity in those patients. As for genes encoding DNA repair proteins such as XRCC1 Arg194, XRCC1 Arg 399 , XRCC3, XRCC7, 52/54 patients had mutations in this gene family. In the study of COMT Val, responsible for the proliferative potential and the carcinogenic effect, mutations were found in 30/45 patients. At least one mutation was found in 48/61 patients in genes encoding DNA-repair and cell detoxification enzymes, such as GSTM1, GSTT1 and GSTP1. As for the CYP2D6 family (variants 3,4,5,6,10), responsible for Tamoxifen metabolism, 12/31 patients presented at least one mutation. Conclusions: Most patients showed genetic variations in drug-metabolizing enzymes. Pharmacogenomics has become a useful tool in the selection of the best drug for each individual patient, thereby decreasing the probability of poor clinical responses and allowing a better control of side effects.