Association between Cytochrome P450 Genetic Polymorphism and Hematological Toxicity of Diffuse Large B-Cell Lymphoma Patients Treated with R-CHOP Protocol

Roshdy, Mohamed Hasan Mohamed; Swellam, Menha; Mohamed, Magdy; Ezz ElArab, Lobna; Mohamed, Rania Hassan; Abd El-Kader, Nour

doi:10.21608/ejchem.2024.279486.9527

Association between Cytochrome P450 Genetic Polymorphism and Hematological Toxicity of Diffuse Large B-Cell Lymphoma Patients Treated with R-CHOP Protocol

Document Type : Original Article

Authors

¹ Cairo, Egypt

² National Research Centre, Biochemistry Department

³ Biochemistry department, Faculty of Science, Ain Shams University, Cairo, Egypt

⁴ Department of oncology and nuclear medicine, Faculty of Medicine, Ain Shams University, Cairo, Egypt

⁵ Ain Shams University, Faculty of Science Department of Biochemistry

⁶ Biochemistry department, Faculty of Science, Ain Shams university, Cairo, Egypt

10.21608/ejchem.2024.279486.9527

Abstract

Response and toxicity monitored during the treatment cycles of Diffuse Large B-cell Lymphoma (DLBCL) enable the physician to take the decision about the best treatment protocol. These differences in outcomes are related mainly to age, physiological status and genetic factors. Toxicity is a frequent outcome that may be developed from accumulation of the drug itself or its metabolites. Current study aimed to study the correlation between the polymorphism in two families of cytochrome P450 system (CYP2C19 and CYP3A4) genes and the incidence of treatment toxicity in DLBCL patients. The genotypes of 2 SNPs for 98 patients were studied (rs4986893 and rs2740574). The rs2740574 of CYP3A4 is in significant association with the incidence of hematological toxicity. The C allele of rs2740574 were found to be more frequent with patients showing hematological toxicity. The disease free survival (DFS) period was longer with TT genotype of rs2740574 than CC genotype. The current study suggests that CYP3A4 variants analysed might evaluate the incidence of hematological toxicity, hence predicting the most appropriate treatment protocol.

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