Clinical Pharmacology

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1 Clinical Pharmacology Clinical Pharmacology and Pharmacotherapy of Opioid Switching in Cancer Patients Joy R. Ross, a,b Julia Riley, a Columba Quigley, c Ken I. Welsh b a Department of Palliative Medicine, Royal Marsden Hospital, London, United Kingdom; b Department of Clinical Genomics, Imperial College, London, United Kingdom; c Cancer Centre, Hammersmith Hospital, London, United Kingdom Key Words. Cancer Opioid Switching Polymorphism Learning Objectives After completing this course, the reader will be able to: 1. Describe some of the underlying mechanisms that contribute to why patients show differential responses to different opioids. 2. Identify some of the individual genes that may influence response to different opioids. 3. Critically evaluate the evidence for the therapeutic maneuver of switching. CME Access and take the CME test online and receive 1 AMA PRA Category 1 Credit at CME.TheOncologist.com Abstract Pain is one of the most common and often most feared symptoms in patients with cancer. Ongoing or progressive pain is physically debilitating and has a marked impact on quality of life. Since a third of the population will die from cancer, and of these, 80% will experience severe pain in their final year of life, effective treatment of cancer-related pain remains both a high priority and an ongoing challenge in clinical practice. Individuals with moderate to severe cancer-related pain require treatment with strong analgesics, namely opioids. There is evidence to support the therapeutic maneuver of opioid switching in clinical practice, but further evidence is needed to elucidate the underlying mechanisms for interindividual differences in response to different opioids. Large, robust clinical trials will be needed if clinical differences among side-effect profiles of different opioids are to be clearly demonstrated. This review discusses candidate genes, which contribute to opioid response; many other genes have also been implicated in pain from animal or human studies. In order to continue to evaluate the genetic contributions to both pain susceptibility and analgesic response, further candidate genes need to be considered. Good pain control remains a high priority for clinicians and patients, and there is much work to be done to further individualize analgesic therapy for patients with cancer. The Oncologist 2006;11: Introduction Pain is one of the most common and often most feared symptoms in patients with cancer. Ongoing or progressive pain is physically debilitating and has a marked impact on quality of life. Since a third of the population will die from cancer, and of these, 80% will experience severe pain in Correspondence: Joy R. Ross, M.D., Department of Palliative Medicine, Horder Ward, Royal Marsden Hospital, London SW3 6JJ, United Kingdom. Telephone: ; Fax: ; joy.ross@rmh.nhs.uk Received March 15, 2006; accepted for publication May 26, AlphaMed Press /2006/$20.00/0 The Oncologist 2006;11:

2 766 Opioid Switching in Cancer their final year of life, effective treatment of cancer-related pain remains both a high priority and an ongoing challenge in clinical practice. Individuals with moderate to severe cancer-related pain require treatment with strong analgesics, namely opioids. An important advance in promoting the principles of good pain control for cancer patients worldwide was the publication of the World Health Organization (WHO) analgesic ladder (Fig. 1) [1]. This sought to simplify pain management strategies and promote a universal step-wise increase in potency of analgesics prescribed. In addition, emphasis was placed on tailoring prescribing to each individual and encouraging the use of regular analgesia, by the oral route, with regular review and dose escalation to achieve and maintain good pain control. Whereas the recommendations for each step of the analgesic ladder have not been individually evaluated in randomized, controlled clinical trials (RCTs), the use of the analgesic ladder as a treatment strategy has been validated in the clinical setting, with up to 88% of patients obtaining satisfactory relief from pain [2, 3]. It is now widely accepted in clinical practice. Whereas morphine is the opioid of choice for the treatment of moderate to severe cancer pain (step 3 on the ladder) [1], a significant proportion of patients treated with oral morphine do not have successful outcomes either because of intolerable adverse effects, inadequate analgesia, or a combination of both [4]. These patients are often switched to alternative strong opioids. Opioid switching, or changing from morphine to an alternative opioid, is a therapeutic maneuver that is gaining popularity in pain management as a method of improving analgesic response and/or reducing adverse side effects [5, 6]. This strategy should not be confused with opioid rotation, which also includes the practice of simply switching to an alternative drug either to change the route of administration or because of either patient or clinician preference. Studies of both opioid switching and/or rotation have been extensively reviewed by one of Figure 1. The World Health Organization analgesic ladder. us (CQ) [6], and the pharmacology of individual opioids, including the advantages of different routes of administration, has been reviewed elsewhere [7]. This review focuses on opioid switching. The concept of interindividual variability in morphine analgesic response is not a new one. In the 1950s, Lasagna and Beecher [8] reported a 65% success rate with morphine in an experimental pain model. Similarly, a bimodal response to morphine analgesia has been described in dental extraction pain [9]. Whereas mild sedation and nausea and vomiting occur relatively frequently on initiation of opioids, with cautious dose titration these problems usually disappear within days. However, for a minority, these symptoms persist, preventing further dose titration and adequate analgesia. Persistent confusion, drowsiness, nausea, and nightmares are the most commonly reported adverse effects, which result in the need to switch to an alternative opioid [10]. Less common side effects and reasons reported for switching include neuromuscular disturbances such as muscle spasm, myoclonus, and pruritus. Clinically, it can be difficult to identify true opioid intolerance, particularly in patients with cancer, where symptoms such as drowsiness, nausea, and vomiting can have many causes. De Stoutz et al. [11] identified adverse effects, primarily cognitive impairment, in 41% of patients with cancer on regular opioids. However, not all symptoms resolved on switching opioids, suggesting that nonopioid causes were important. In general, a pragmatic approach is usually taken, in which, if there is a clinical suspicion that symptoms are opioid related, a trial of an alternative opioid is instigated. Two questions need to be asked: first, what is the evidence that patients who are intolerant of morphine can be correctly identified, and second, is there evidence to support the use of opioid switching to improve clinical outcome? Evidence-Based Rationale for Switching: Clinical Trials If one accepts opioid switching as a recommended therapeutic maneuver, the underlying implication is that there is a true clinical difference among different opioids. However, at present, there is little evidence to support the use of one strong opioid over another in the treatment of cancer-related pain. Drug company trials have focused on acute and/or nonmalignant pain [12, 13], such as chronic back pain, and care should be taken when extrapolating data from those trials to support use in patients with cancer who, by nature, are less well and often taking multiple concomitant medications. To date, large RCTs have not been undertaken to directly compare opioids for cancer-related pain, and smaller individual trials are underpowered to demonstrate superiority of one opioid over another [14 19]. Therefore, The Oncologist

3 Ross, Riley, Quigley et al. 767 the decision by both the WHO and the European Association for Palliative Care (EAPC) to recommend morphine as the opioid of choice is based largely on clinical expertise and pragmatic reasons, such as the general availability of morphine sulphate worldwide and the considerable clinical experience in using this drug. In terms of analgesia, all opioids should be equipotent, provided appropriate equianalgesic doses are used. However, there is variability in published dose-conversion tables and wide interindividual variability in response. In clinical practice, a dose ratio of oral morphine:oxycodone of 2 is often used. Figure 2 shows the preswitch dose of morphine and subsequent stable dose of oxycodone postswitching for 44 patients who were recruited as part of a prospective clinical trial to evaluate opioid switching [10]. Whereas the median dose ratio of morphine:oxycodone was 1.7, the range from the individual patient data was large, This illustrates the need to use conversion tables as a guide but to titrate doses for individual patients. Such problems are accentuated with opioids such as methadone, which is stored in adipose tissue and has a rapid distribution phase following oral administration followed by a slow elimination phase with slow transfer between tissue stores and plasma [20, 21]. Figure 2. Comparison of opioid dose before and after switching. Morphine dose (mg/24 hours) versus final oxycodone dose (mg/24 hours) in 44 switchers who responded to oxycodone as a second-line opioid. The median (range) dose ratio of morphine:oxycodone was 1.7 ( ). Is there a difference among opioids in relation to the adverse-effect profile? Large, randomized, controlled trials have not been done to directly compare opioids, and smaller individual trials are underpowered to demonstrate superiority of one opioid over another [14 19]. In addition, studies involving more recently available opioids have been undertaken in mainly noncancer populations. One cannot assume side-effect profiles will be the same in patients with a diagnosis of advanced cancer, often with comorbidities and taking multiple concomitant medications. This does not exclude the possibility that real differences exist clinically between morphine and other opioids. However, we do not currently have sufficient evidence to prove this point. Is there any evidence that patients who are switched achieve a better clinical outcome? A recent systematic review looked at the evidence for opioid switching as a useful therapeutic maneuver in patients (adults and children, cancer and noncancer) with pain [6]. The review highlights the lack of robust data available: no RCTs were located. Published data on opioid switching included case reports (52 studies), retrospective studies/audits (15 studies), and prospective controlled trials (14 studies). Not surprisingly, published reports tended to report positive results, improvement in pain and/or adverse effects, on switching opioids. In general, morphine tended to be the opioid of first choice, with most initial switches involving methadone. Infrequently, there have been reports of an opioid switch failing to improve symptoms [22]. A variety of confounding variables such as a change in route as well as drug, grouping neuropathic and nociceptive pain together, and failure to exclude other potential causes of adverse effects made it impossible to draw definitive conclusions in the review. A more recent study, published since the systematic review, prospectively evaluated the clinical benefits of switching from morphine to an alternative opioid [10]. One hundred eighty-six palliative care patients were recruited. Responders were treated with morphine for more than 4 weeks with good analgesia and minimal side effects. Nonresponders (switchers) either had uncontrolled pain or unacceptable morphine-related side effects. Forty-seven (of 186) patients were in the switchers group. Thirty-seven of these (79%) had a successful outcome with a second-line opioid, oxycodone. Scientific Rationale for Switching: Genetic Variation in Candidate Genes A patient s response to a drug depends on multiple factors. Pharmacokinetic determinants include drug absorption, distribution, metabolism, and elimination. Pharmacodynamic factors for example, drug concentration at the

4 768 Opioid Switching in Cancer target site, number and morphology of target receptors, and variation in downstream events after receptor ligand binding all combine to influence overall response. Pharmacodynamic and pharmacokinetic variation in drug handling may be further influenced by age, concomitant medications, underlying disease, and various environmental factors, including diet. When comparing different opioids, it is useful to consider both their routes of metabolism and their receptor profiles [7]. Little of the interindividual variation in response to morphine can be attributed to age, gender, cancer diagnosis, or renal or liver function [23], and a number of authors have highlighted the potential importance of a genetic influence on morphine responsiveness [24 27]. It would appear that, although some of the differences among individuals in terms of opioid sensitivity can be related to differences in environmental factors, age, pain severity, emotional state, and prior pain experience, much of this variation could be a result of genetic factors [28]. The genetic code, DNA, carries the complete genetic information of a cell and consists of thousands of genes. Each gene serves as a code or template for building a protein molecule, such as a receptor or an enzyme. Variation in the genetic code can alter protein expression and function. Given the broad spectrum of proteins involved in determining response to a drug, genetic variation in multiple genes could influence an individual s response to different opioids [29]. In addition, given the pharmacokinetic and pharmacodynamic differences among the opioids, such variation may favor treatment with one opioid versus another for a given individual. The evidence for genetic variation in a selection of candidate genes, influencing response to different opioids, is outlined below. Drug Transporters: P-Glycoprotein The membrane-bound drug transporter P-glycoprotein influences drug absorption and drug excretion [30, 31]. It regulates transfer of opioids across the blood brain barrier and can actively pump opioids out of the central nervous system (CNS) [32]. P-glycoprotein knockout mice, which are completely devoid of P-glycoprotein activity, have enhanced absorption and high CNS concentrations of P-glycoprotein substrates (e.g. morphine, fentanyl, and methadone) with associated prolongation of analgesia [33]. Administration of cyclosporin, a P-glycoprotein inhibitor, results in increased fentanyl- and morphine-induced analgesia [33, 34]. Interindividual variability in P-glycoprotein activity is well recognized, and genetic variation in the multidrug resistance gene MDR-1, which encodes for P- glycoprotein, has been associated with resultant alterations in P-glycoprotein activity [32, 35]. Because P-glycoprotein modulation of opioid CNS levels varies substantially among different opioids, the effects of genetic variation altering P-glycoprotein activity are different, depending on the opioid in question [34]. MDR-1, the gene that codes for P-glycoprotein, is therefore a good candidate gene for influencing analgesic response to opioids and the prevalence of opioid-induced CNS side effects. Whereas multiple single nucleotide polymorphisms (SNPs) have been identified in the MDR-1 gene, two mutations (C3435T and G2677T/A) have been associated with differences in P-glycoprotein expression or function [36, 37]. Variation in the G2677T/A genotype has also been shown to alter drug levels [38] and drug-induced side effects [39]. There are no studies to date reporting on analgesic response or opioid side-effect profiles in relation to variation in the MDR-1 genotype. Opioid Receptors During the past 20 years, three opioid receptors p, μ, δ, and κ have been identified, and the genes coding for these receptors have now been cloned [40]. Morphine and other commonly used opioids, including oxycodone, hydromorphone, methadone, and fentanyl, act primarily at the same target receptor, the μ-opioid receptor [41]. In addition, oxycodone [42], methadone [20], and buprenorphine [43] may have clinically important activity at other opioid receptors. In μ-opioid receptor knockout mice, in which the gene coding for the receptor has been disrupted, analgesic models show complete loss of analgesic and other morphine activities, reinforcing the critical importance of the μ-opioid receptor in morphine-mediated effects [44]. Changes in μ-opioid receptor densities, potentially contributed to by allelic variants, can produce changes in nociceptive responses and affect opioid response [44]. Binding studies to postmortem brain samples and in vivo positron-emission tomography radio-ligand analyses suggest 30% 50% or even larger ranges of individual human differences in μ-opioid receptor densities [45]. More than 100 polymorphisms have been identified in the human μ-opioid receptor gene, and some of these variants have been shown to alter the binding affinities of different opioids [46 49]. The most widely studied polymorphism in the μ-opioid receptor gene is the A118G nucleotide substitution, which codes for the amino-acid change asparagine to aspartic acid. It has been reported in association with both addiction and pain studies. Addiction studies have published conflicting results. While some studies have reported a protective effect of the mutant allele against drug [50] and alcohol [51] abuse, other studies found no such association [52 54]. In pain studies, there have been suggestions that the mutant allele may decrease the potency of morphine or morphine-6-glucuronide (M6G) in cancer The Oncologist

5 Ross, Riley, Quigley et al. 769 patients [52 56]. A study of 99 patients with controlled cancer pain reported that patients homozygous for the variant allele (n = 4) needed more morphine to control pain than heterozygous (n = 17) and homozygous wild-type (n = 78) individuals [57]. In a recent, prospective study in cancer patients, we evaluated genetic variation in a number of candidate genes, including the μ-opioid receptor gene, in patients with cancer pain who responded to morphine versus those who were switched to an alternative opioid [26]. No differences were seen in genotype or allelic frequencies for polymorphisms in the μ-opioid receptor gene. The μ-opioid receptor is a G-protein-coupled receptor (GPCR) [58]. Opioid receptor signaling results in inhibition of neuronal transmission of painful stimuli by a complex sequence of events [59]. GPCR signaling is regulated by receptor desensitization, endocytosis, and downregulation [60]. β-arrestin-2 is an intracellular protein that is involved at multiple points in regulating receptor phosphorylation, desensitization, and internalization [61, 62]. In animal studies, the analgesic effect of morphine is both increased and prolonged in β-arrestin-2 knockout mice [63]. Because rates of μ-opioid receptor internalization and desensitization differ according to which ligand binds [64], polymorphic variation affecting β-arrestin-2 may have a greater or lesser effect depending on the opioid given. Whereas the study by Ross et al. [26] above showed no differences between controls and switchers for polymorphisms in the μ-opioid receptor gene, a significant difference was seen in genotype and allelic frequency for the T8622C polymorphism in the β-arrestin-2 gene. This SNP in exon 11 does not result in an amino-acid change but is at a wobble position and may therefore influence mrna translation [65]. Opioid Metabolism There is no single common metabolic pathway for the metabolism of opioids. Codeine [66] and oxycodone [67] are metabolized by the cytochrome P450 (CYP)2D6 enzyme. Oral morphine and hydromorphone are primarily metabolized in the liver through the uridine-diphosphoglucuronosyltransferase (UGT) system [68]. Fentanyl [69] and methadone [70] are metabolized by the CYP3A4 enzyme, which is responsible for the complete or partial metabolism of 50% of all known drugs. Genetic variation in CYP2D6 results in poor metabolism of the opioid codeine to its active metabolite morphine [66, 71]. Other studies have shown important pharmacogenetic influences in oxycodone [67] and morphine [72] metabolism. Oral morphine is primarily metabolized in the liver by the UGT system [68]. The pharmacology of morphine and these two main metabolites in humans has been well documented [73]. Both morphine and its metabolite levels vary greatly among individuals, not only because of differences in dosing, but also because of interindividual variability in pharmacokinetics. Faura et al. [73] showed a high correlation, independent of clinical variables, between M3G and M6G, confirming that a single enzyme is responsible for metabolism of morphine, namely UGT2B7 [74]. A number of SNPs in the promoter region of UGT2B7 have been reported, but their impact on enzyme function is debated [75]. In vitro studies have demonstrated altered transcription factor binding to polymorphic regions, but these do not translate into altered promoter activity [76]. Whereas one clinical study showed that genetic variation in the promoter region correlated with serum morphine and M6G concentrations [77], this was not confirmed in a subsequent larger study [78]. One SNP in exon 2 results in an amino-acid substitution, histidine to tyrosine, at the proposed location of the substrate-binding site [76]. However, no relationship has been shown between this variant and morphine metabolism in patients with cancer [26, 79]. Although research continues in this area, it appears at the moment that polymorphisms in genes controlling the metabolism of morphine do not, in isolation, explain interindividual variability in morphine response. The CYP enzymes CYP3A4, CYP3A5, and CYP2D6 are important in the metabolism of a number of strong opioids, including oxycodone, fentanyl, and methadone. Multiple SNPs have been validated in the CYP3A4 gene, but <5% occur in the coding regions [80]. None of the amino-acid changes have been shown to affect putative substrate-binding sites, but four have been shown to affect drug metabolism in functional studies [81]. CYP3A5 demonstrates either high or low activity primarily as a result of polymorphic variation in intron 3, resulting in mrna splicing and production of a nonfunctional protein (5% 15% of whites) [82 84]. CYP2D6 is among the most widely studied of the CYP enzymes and has been extensively studied in relation to its role in codeine metabolism [71, 85]. Approximately 7% of whites have inactivating mutations in the gene encoding CYP2D6 or have complete deletion of the gene [86, 87]. The importance of CYP2D6 in determining analgesic efficacy of different opioids is debated (oxycodone, hydrocodone, dihydrocodeine) [88], although clinical differences in response to the opioid tramadol have been shown between poor and rapid metabolizers [89]. Control of Gene Expression: Transcription Factors There is marked (up to tenfold) variability in the expression of UGT2B7 mrna in human liver biopsy samples [90].

6 770 Opioid Switching in Cancer Genetic variation may affect both the function of a given protein (e.g., an enzyme or receptor) and also the amount of protein that is transcribed. Such differences in gene expression can result from alterations in the cis-acting DNA promoter and enhancer sequences that are typically found in the 5ʹ ends of genes and are often recognition sites for regulatory DNA-binding proteins [91]. These proteins include transcription factors whose primary function is to bind to specific sequences within the gene regulatory region and to interact with RNA polymerase in order to regulate the rate of transcription. Transcription of UGT2B7 is regulated by the transcription factor hepatic nuclear factor 1 alpha (HNF-1α) [90, 92]. Another transcription factor, octamer transcription factor 1, acts as a coregulatory protein by binding to HNF- 1α to increase the rate of UGT2B7 transcription [92]. Other coregulatory proteins, such as dimerization cofactor of HNF-1 (DCoH), stabilize the protein DNA complex prior to recruitment of RNA polymerase [93]. As such, genetic variation in these genes may also be important in influencing response to morphine. A number of transcription factor recognition sites have been postulated in the human μ-opioid receptor gene [91, 94]. One of these, signal tranducer and activator of transcription 6 (STAT-6) has been shown to be functionally relevant [95]. Whereas the stat-6 gene is known to be highly polymorphic, most of the validated SNPs lie in intronic, noncoding regions. Our study, comparing switchers who did not tolerate morphine with controls who responded to morphine, showed significant differences in the genotype of the stat-6 gene between switchers and controls [26]. Research continues to examine other transcription factors that may be important in influencing response to different opioids. Complexity of Pain: Other Pathways Interact Response to a painful stimulus is regulated by interactions between multiple regions within the brain via different neurochemical pathways [96]. There is evidence to support interaction between dopaminergic and adrenergic pathways and opioid signaling pathways in the CNS [97]. Catechol- O-methyltransferase (COMT) is one of the enzymes that metabolizes catecholamines and is an important modulator of neurotransmitters in the brain. Polymorphic variation in the COMT gene has been shown to affect μ-opioid neurotransmitter responses to a pain stressor [97] and to influence interindividual variation in pain sensitivity [98]. In addition, Rakvag et al. [99] have demonstrated a correlation between COMT genotype and morphine dose requirements in cancer patients. Conclusion There is evidence to support the therapeutic maneuver of opioid switching in clinical practice, but further evidence is needed to elucidate the underlying mechanisms for interindividual differences in response to different opioids. Large, robust clinical trials will be needed if clinical differences among side-effect profiles of different opioids are to be clearly demonstrated. In addition to the candidate genes described above, review of the current literature shows that approximately 500 genes have now been implicated in pain from animal or human studies. In order to continue to evaluate the genetic contributions to both pain susceptibility and analgesic response, further candidate genes need to be considered. Good pain control remains a high priority for clinicians and patients, and there is much work to be done to further individualize analgesic therapy for patients with cancer. 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