Copy number variability analysis of pharmacogenes in patients with lymphoma, leukemia, hepatocellular, and lung carcinoma using The Cancer Genome Atlas data. Issue 1 (January 2015)

• Record Type: Journal Article
• Authors: Kim, In-Wha; Han, Nayoung; Kim, Myeong Gyu; Kim, Therasa; Oh, Jung Mi
• Is Part Of: Pharmaocogenetics and genomics. Volume 25:Issue 1(2015:Jan.)
• Publication Date: 2015-01
• Subjects: copy number variation -- multiple cancers -- pharmacogenomics; Pharmacogenetics -- Periodicals; Pharmacogenomics -- Periodicals; Genetic toxicology -- Periodicals; Biomedical genetics -- Periodicals; 615.7
• DOI: 10.1097/FPC.0000000000000097
• Languages: English
• ISSNs: 1744-6872

Abstract

Abstract : Objective: Individual differences in drug efficacy and toxicity remain an important clinical concern. We investigated copy number variation (CNV) frequencies for pharmacogenes using The Cancer Genome Atlas dataset. Materials and methods: One hundred and fifty-two pharmacogenes were selected from liver hepatocellular carcinoma, lung squamous cell carcinoma (LUSC), acute myeloid leukemia, and lymphoid neoplasm diffuse large B-cell lymphoma (DLBL). The germ line and somatic CNV frequencies were analyzed. Results: We found CNVs with more than 1% frequency in drug-metabolizing enzymes including CYP2A6, CYP2D6, GSTP1, CYP2E1, GSTM1, GSTT1, and SULT1A1, drug transporters such as SLC19A1 and SLC28A1, and targets such as FHIT in normal tissue or blood. GSTM1 had the highest frequency for gene gain (45.45, 39.18, 31.01, and 34.77%, respectively) and for gene loss (18.18, 29.38, 20.89, and 26.68%, respectively) in DLBL, acute myeloid leukemia, liver hepatocellular carcinoma, and LUSC. P2RY12 and P2RY1 had the highest frequency for gene gain in LUSC (26.95 and 26.68%, respectively) whereas ABCB1 and ABL2 had the highest frequency for gene gain in DLBL (27.27%) in cancer tissue or blood. Conclusion: Germ line and somatic CNVs of pharmacogenes may play a role in determining individual variations in drug responses. Inclusion of CNVs in pharmacogenetic variations holds promise as biomarkers that can increase the benefits and reduce the risks of drug therapy on an individual level.