Opportunities for pharmacogenomics-guided supportive care in cancer
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EDITORIAL
Opportunities for pharmacogenomics-guided supportive care in cancer Jai N. Patel 1
# Springer-Verlag GmbH Germany, part of Springer Nature 2020
Variability in response Early palliative care after diagnosis with advanced cancer improves quality of life (QOL) and may prolong cancer survival [1]. Nonetheless, there is large inter-individual variability in response to drugs used to manage myriad cancer-related symptoms. For example, pain affects more than 75% of cancer patients with advanced disease, but less than one-third achieve pain improvement with conventional strategies within 1 month [2]. Depression affects about one-third of cancer patients and has been linked to poorer prognosis and survival [3]. Despite newer generation antidepressants, about half experience nonresponse to treatment with a first-line antidepressant [3]. Uncontrolled cancer-related symptoms may increase emergency room visits, reduce patient satisfaction, and disrupt cancer treatments.
Pharmacogenomics may improve prescribing Personalized supportive care medication prescribing using objective tools, such as genomics, may improve drug response [4]. Pharmacogenomics—the impact of genetic variation on drug response—can significantly alter the activity of many supportive care medications, including antidepressants, antiemetics, opioids, and nonsteroidal anti-inflammatory drugs (NSAIDs) [4]. Over 90% of patients carry a pharmacogenetic variant, while nearly one-third carry a variant contributing to supportive oncology medications [4]. The Clinical Pharmacogenetics Implementation Consortium (CPIC) (www.cpicpgx.org) publishes drug-specific, peer-reviewed guidelines on how to best apply pharmacogenomics to guide * Jai N. Patel [email protected] 1
Department of Cancer Pharmacology and Pharmacogenomics, Levine Cancer Institute, Atrium Health, 1021 Morehead Medical Dr, Charlotte, NC 28204, USA
therapeutic decision-making, at least one dozen of which are related to supportive care. Integration of pharmacogenomicsguided supportive care prescribing may improve drug efficacy and reduce symptom burden.
Antidepressants Many selective serotonin reuptake inhibitors (SSRIs), including citalopram, escitalopram, and sertraline, are hepatically metabolized and inactivated by cytochrome P450 2C19 (CYP2C19). Due to the presence of loss-of-function alleles, CYP2C19 poor metabolizers (PMs) have increased toxicity risk with such medications, including QT prolongation. Alternatively, those with gain-of-function alleles (rapid [RM] and ultrarapid metabolizers [UMs]) have lower plasma concentrations and increased risk of drug failure. CPIC recommends a 50% dose reduction for CYP2C19 PMs and drug avoidance in UMs [5]. Paroxetine is primarily metabolized by CYP2D6; thus, PMs are at increased risk of adverse effects, particularly gastrointestinal, while UMs are at risk of poor drug response. CPIC recommends avoiding paroxetine in CYP2D6 UMs and PMs [5]. Fluoxetine is metabolized by CYP2D6 and CYP2C19; thus, similar mechanisms can influence drug respon
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