Dataset Information

Pharmacogenomics Study of CPT-11 as the First-line Chemotherapy for mCRC

ABSTRACT: Irinotecan (CPT-11) is now widely used as the first-line chemotherapy for mCRC. There were 4 key enzymes for CPT-11 metabolizing, CYP3A4, UDP-glucuronosyltransferase, carboxylesterase(CES), and ATP-binding cassette (ABC) transporters. Genetic variations of those enzymes may cause the heterogeneity in safety and efficacy of CPT-11. The aim of this study is to figure out the correlation between the genetic polymorphism and the drug response.

DISEASE(S): Colorectal Cancer,Colorectal Neoplasms

PROVIDER: 2101269 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Similar Datasets

Project description:Myasthenia gravis (MG) is an autoimmune disease affecting the neuromuscular junction, whose clinical hallmark is muscle weakness and early fatigability. Azathioprine (AZA) is commonly used in Myasthenia Gravis therapy. AZA is a purine antagonist, which inhibits the cell cycle in the resting and DNA synthesis phases. It is usually used as an immunosuppressant to block T- and B-cell proliferation. AZA, bioconverted to 6-mercaptopurine by glutathione S-transferase (GST), can be metabolized either through the hypoxanthine phosphoribosyl transferase pathway to active 6-thioguanine nucleotides (6-TGN) or through the thiopurine S-methyltransferase (TPMT) pathway to inactive methyl-thiopurine metabolites. The incorporation of active 6-TGNs into DNA, causing breaks in DNA strands resulting in interference with RNA production and thereby protein synthesis, is responsible for the drug effect. The response to AZA is determined by which metabolic pathway is being favored. While balanced use of both HPRT and TPMT pathways results in responsiveness to AZA, hyperactivity of TPMT skews the balance towards the TPMT pathway and results in unresponsiveness to AZA with no pharmacological effect. In contrast, low TPMT activity skews the balance towards the HPRT pathway, resulting in increasing side-effects due to the accumulation of 6-TGNs. Current treatments for MG therapy are often inadequate because less than 40% of patients achieve complete remission with available drugs. This reflects the lack of drugs acting on target sites for which there is strong evidence of pathogenicity and the inability to identify responder patients. No criteria for responsiveness are available, exposing patients to unpredictable failures and unpredictable side effects. These individuals are at particular risk for adverse drug reaction (ADRs) or therapeutic failure. Genetic profiling with the Affymetrix drug metabolizing enzymes and transports genotyping array offers the ability to determine 1,931 variants and 225 genes involved in drug metabolism and disposition. Accordingly, the study of well-known drug-metabolizing genes can be involved in the specific metabolic pathway of a drug, which is more likely to define genotype-phenotype association and thereby genotype profiles relevant to drug response that can be applied as predictive biomarkers for pharmacological treatment.

Project description:In drug development, a system for predicting drug metabolism and drug-induced toxicity is necessary to ensure drug safety. Cytochrome P450 family 3 subfamily A member 4 (CYP3A4) is an important drug-metabolizing enzyme expressed in the liver and small intestine, and predicting CYP3A4-mediated drug metabolism and drug-induced toxicity is essential. We previously developed procedures to differentiate human induced pluripotent stem (iPS) cells into hepatocyte-like cells (HLCs) or intestinal epithelial-like cells (IECs) with a fetal phenotype as well as a highly efficient genome editing technology that could enhance the homologous recombination efficiency at any locus, including CYP3A4. By using human iPS cells and our genome editing technology, we generated CYP3A4-knockout (KO) iPS cell-derived HLCs and IECs for the evaluation of CYP3A4-mediated drug metabolism and drug-induced toxicity. CYP3A4 deficiency did not affect pluripotency and hepatic and intestinal differentiation capacities, and CYP3A4 activity was entirely eradicated by CYP3A4 KO. Off-target effects (e.g., inhibition of bile acid excretion) were hardly observed in CYP3A4-KO cells but were observed in CYP3A4 inhibitor-treated (e.g., ketoconazole) cells. To evaluate whether drug-induced hepatotoxicity and enterotoxicity could be predicted using our model, we exposed CYP3A4-KO HLCs and IECs to acetaminophen, amiodarone, desipramine, leflunomide, tacrine, and tolcapone and confirmed that these cells could predict CYP3A4-mediated toxicity. Finally, we examined whether the therapeutic effects of an anti-hepatitis C virus (HCV) drug metabolized by CYP3A4 would be predicted using our model. CYP3A4-KO HLCs were treated with asunaprevir (antiviral drug metabolized by CYP3A4) after HCV infection, and the anti-viral effect was indeed strengthened by CYP3A4 KO. Conclusion: We succeeded in generating a novel evaluation system for prediction of CYP3A4-mediated drug metabolism and drug-induced toxicity.

Dataset Information

Pharmacogenomics Study of CPT-11 as the First-line Chemotherapy for mCRC

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets