Decoding variants in drug-metabolizing enzymes and transporters in solid tumor patients by whole-exome sequencing.

Saudi J Biol Sci

Stem Cell Unit, Department of Anatomy, College of Medicine, King Saud University, P.O. Box 2925 (28), Riyadh 11461, Saudi Arabia.

Published: January 2021

Background: Pharmacogenetics is involved in customizing therapy according to the genetic makeup of an individual, and is applicable for chemotherapy, radiotherapy as well as targeted therapy. Drug metabolizing enzymes (DMEs) involving both phase I, and phase II reactions are widely studied. Our study was involved in whole exome sequencing (WES) of cancer patients, followed by analysis for identifying key variations in DMEs, and associated transporters that have a potential impact on treatment outcome.

Methodology: A total of 181 solid tumor patients at stage >/= III were subjected to WES by the SureSelect Human All Exon V6 + UTR library preparation kit, and sequencing in the Illumina NextSeq 550 system. Bioinformatics analysis involved use of GATK pipeline, and the variants were further assessed for population frequency, functional impact with annovar insilico algorithms. Further variant information from significant DMEs, and transporters were extracted and analyzed with PharmGKB to assess level of evidence and infer their impact on the pathways involved in drug response.

Results: The total study cohort of 181 solid tumor patients included 60 males, and 121 females respectively. Among DMEs, deleterious mutation in dihydropyrimidine dehydrogenase ( rs67376798), solute carrier organic anion transporter family member 1B1 (), and cytochrome P450 2D6 () associated with metabolism of anticancer drugs was detected to be in high frequency of 26%, 21% and 25% respectively.

Conclusion: Our analysis detected variations in both phase I and phase II DMEs, as well as associated transporter genes which has been documented to reduce drug efficacy, as well as cause grade 3 and 4 toxicity. Our study reiterates the significance of pharmacogenomics in stratifying patients for appropriate therapy regimen focused at better treatment outcome and quality of life.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7783809PMC
http://dx.doi.org/10.1016/j.sjbs.2020.10.052DOI Listing

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