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NGS testing for CYP gene and variation in drug responses

Among the most researched pharmacogenes is the CYP gene superfamily (Fukunaga et al., 2021), which influences drug-metabolising enzymes (DMEs) for phase I (enzymes responsible for reactions involving oxidation, reduction, and hydrolysis) and is thought to cause up to 60% of drug-induced toxicity (Maggo et al., 2016)

Four major phenotypes emerge concerning drug metabolism when considering polymorphisms in the CYP gene family; poor metaboliser, intermediate metaboliser, extensive metaboliser or ultra-rapid metaboliser.

Phase II enzymes (enzymes catalysing the conjugation reactions) polymorphisms contribute to further variation in drug responses. These include:

  • N-acetyl transferase type 2 (NAT2) - associated with isoniazid toxicity;

  • Thiopurine methyltransferases (TPMT) - associated with thiopurine toxicity;

  • Dihydropyrimidine dehydrogenase (DPD) - associated with 5-fluorouracil toxicity;

  • Uridine diphosphate-glucuronosyl transferases (UGT) - are associated with irinotecan toxicity.

Additional diversity in drug reactions can be influenced by drug transporter polymorphisms, which affect the distribution of the chemical components (Lauschke & Ingelman-Sundberg, 2019).

egSEQ library preparation and targeted sequencing solutions, including specific panels with maximised coverage on oncology-related targets and full bioinformatics solutions with reporting offer a customisable solution for cancer screening and genomic profiling to provide researchers working on effective cancer diagnosis, treatment, and prevention with invaluable genomic data that will lead to revolutionary new strategies in dealing with cancer.


Fukunaga, K., Momozawa, Y., & Mushiroda, T. (2021). Update on next-generation sequencing of pharmacokinetics-related genes: development of the PKseq panel, a platform for amplicon sequencing of drug-metabolizing enzyme and drug transporter genes. Drug Metabolism and Pharmacokinetics, 37, 100370.

Lauschke, V. M., & Ingelman-Sundberg, M. (2019). Prediction of drug response and adverse drug reactions: from twin studies to next generation sequencing. European Journal of Pharmaceutical Sciences, 130, 65-77.

Maggo, S. D., Savage, R. L., & Kennedy, M. A. (2016). Impact of new genomic technologies on understanding adverse drug reactions. Clinical Pharmacokinetics, 55(4), 419-436.


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