Pharmacogenomics of anticancer drugs: Personalising the choice and dose to manage drug response

Abstract

The field of pharmacogenomics has made great strides in oncology over the last 20 years and indeed a significant number of pre‐emptive genetic tests are now routinely undertaken prior to anticancer drug administration. Many of these gene–drug interactions are the fruits of candidate gene and genome‐wide association studies, which have largely focused on common genetic variants (allele frequency>1%). Examples where there is clinical utility include genotyping or phenotyping for G6PD to prevent rasburicase‐induced RBC haemolysis, and TPMT to prevent thiopurine‐induced bone marrow suppression. Other associations such as CYP2D6 status in determining the efficacy of tamoxifen are more controversial because of contradictory evidence from different sources, which has led to variability in the implementation of testing. As genomic technology becomes ever cheaper and more accessible, we must look to the additional data our genome can provide to explain interindividual variability in anticancer drug response. Clearly genes do not act on their own and it is therefore important to investigate genetic factors in conjunction with clinical factors, interacting concomitant drug therapies and other factors such as the microbiome, which can all affect drug disposition. Taking account of all of these factors, in conjunction with the somatic genome, is more likely to provide better predictive accuracy in determining anticancer drug response, both efficacy and safety. This review summarises the existing knowledge related to the pharmacogenomics of anticancer drugs and discusses areas of opportunity for further advances in personalisation of therapy in order to improve both drug safety and efficacy.

Pharmacogenomics in cancer supportive care: key issues and future directions

“…For supportive care agents where drug exposure is related to efficacy and toxicity, therapeutic drug monitoring may address exposure variability. PGx is one component of individual variation in the required dosing but has not been routinely used to individualize drug selection or dosing because of limited robust clinical trials, barriers to accessing results in real-time at the point of care, lack of education/awareness on how to apply the results in practice, and cost [7].…”

Development of Polymer-Assisted Nanoparticles and Nanogels for Cancer Therapy: An Update

“…The most fatal cancer type was lung cancer followed by stomach and liver cancer [1]. Anticancer drugs such as cisplatin, doxorubicin, paclitaxel, and 5-fluorouracil are commonly used for chemotherapy or used in combination with radiotherapy or tumor resection [2]. However, the development of resistant tumors and high toxicity of drugs towards the normal cells highly limit the use of these drugs [2].…”

“…Anticancer drugs such as cisplatin, doxorubicin, paclitaxel, and 5-fluorouracil are commonly used for chemotherapy or used in combination with radiotherapy or tumor resection [2]. However, the development of resistant tumors and high toxicity of drugs towards the normal cells highly limit the use of these drugs [2]. Hence, the development of a novel therapeutic agent against cancer is needed.…”

Precision medicine‐based drug treatment individualization in oncology

“…The more widespread use of NGS will allow easier identification of rarer mutations associated with adverse drug reactions. The lack of routine use of pharmacogenomics is multifactorial including the expense, accessibility, the time for processing, and the complex interactions including between genomics, clinical factors, and the microbiome, which account for the individual variations 18 …”

“…They could then be used to follow-up post treatment. 16 A further tool to guide dosing of anti-cancer drugs and predicting toxicity and response prior to their administration is pharmacogenomics reviewed by Carr et al 18 Examples with the strongest evidence are assaying for dihydropyrimidine dehydrogenase (DPYD), which is the rate limiting enzyme for 5-FU metabolism, encoded by a gene with multiple variants. Identifying the variant alleles of thiopurine methyltransferase (TMPT) can identify a low activity genotype that metabolizes 6-mercaptopurine to an inactive mercaptopurine resulting in less metabolism of 6-MP to toxic thioguanine nucleotide metabolites.…”