The role of ethnicity in personalized dosing of small molecule tyrosine kinase inhibitors used in oncology

Introduction

The development of molecular targeted therapies, such as small molecule tyrosine kinase inhibitors (smTKIs), has revolutionized the treatment of some cancers, offering many patients a larger survival benefit with a lower toxicity profile and better quality of life, compared to traditional cytotoxic chemotherapy. However, despite their targeted mechanism of action, smTKIs exhibit large inter-individual variability in their systemic exposure (pharmacokinetics) and effects (pharmacodynamics) (1-3). Inter-individual variability in pharmacokinetics is particularly pertinent in oncology, as anticancer agents are frequently administered at doses close to maximally tolerable intensity, and most smTKIs are considered to have a narrow therapeutic index (3). Therefore, small changes in plasma concentrations may lead to serious adverse drug reactions or the potential for therapeutic failure (4). For some smTKIs, including axitinib, imatinib, sunitinib and pazopanib, there is sound evidence that systemic exposure correlates with clinical outcomes, thereby highlighting the importance of precision dosing (1,3,5). However, all smTKIs are still initiated at fixed doses, putting patients at risk of unpredictable efficacy and toxicity (3). Understanding reasons for variability in the pharmacokinetics and pharmacodynamics of smTKIs is fundamental to reducing the incidence of suboptimal outcomes.

There is growing evidence to suggest that ethnicity may be a factor contributing to the inter-individual variability observed in the exposure and response to smTKIs (6,7). The same dose of a smTKI prescribed to people from different ethnic backgrounds can result in different systemic exposures, efficacy and toxicity (8,9). Outcomes from smTKI treatment are influenced by a complex interplay of both intrinsic and extrinsic factors affecting their pharmacokinetic and pharmacodynamic pathways (6,10). Thus, inter-ethnic differences in the outcomes of treatment with smTKIs are likely a reflection of population differences in these intrinsic and extrinsic determinants (6). Intrinsic factors are those relating to an individual’s physiological characteristics, such as renal/hepatic function and body weight/composition, and genetic characteristics, considering both somatic and germline genetics (6,7). These include ethnic variation in the expression or activity of genes encoding for drug metabolizing enzymes and transporters (11-15), as well as genes involved in the mechanism of action of a drug, such as mutations in drug target proteins that cause particular sensitivities or resistance to the drug (15-19). Extrinsic factors, such as tobacco use, complementary and herbal medicine use and dietary habits, can vary between people of different geographic ancestries and can also influence the pharmacokinetics of a drug, its concentration at the target site, and thus drug response (6).

Recognition of inter-ethnic differences in anticancer treatment outcomes, as well as understanding reasons for these differences, can help identify populations that are predisposed to treatment resistance or susceptibility to adverse effects. The ethnicity of a patient could serve as a marker or predictor, alerting prescribers of patients who may need further investigation (e.g., genotyping critical pathways) to guide initial dose selection. It can also help identify patients who may need therapeutic drug monitoring to achieve adequate drug concentrations with minimal risk of harmful effects. Adverse drug reactions can greatly impact patient adherence, and may even result in cessation of treatment. Thus, identifying patients who are at risk of severe toxicities due to certain intrinsic/extrinsic factors, and personalizing their dose regimen with careful monitoring to reflect their pharmacokinetic and pharmacodynamic characteristics, can avoid treatment failure and improve a patients’ quality of life. By incorporating knowledge of a patients’ physiology, genetic predisposition and environmental influences into prescribing practices, we can move to a model of precision medicine and optimally utilize the life-changing drugs that are available. It may be possible to make earlier interventions, thereby reducing the likelihood of disease progression and ineffective treatment.

The aim of this review is to summarize the known information on inter-ethnic differences relevant for smTKIs in the treatment of cancer, discussing pharmacokinetic, efficacy and safety perspectives. This review will also illustrate how smTKI prescribing practices can be informed by considering a patients’ ethnicity.

Inter-ethnic differences in tyrosine kinase inhibitor treatment outcomes

The efficacy of some smTKIs has been found to differ between European and East Asian populations (Table 1). There is good evidence that people of East Asian ancestry have significantly higher response rates and superior survival outcomes to erlotinib, gefitinib, lapatinib and regorafenib, when compared to non-East Asian patients (8,9,44-48,51,65,66,83-85). No inter-ethnic differences in treatment response have been reported for ruxolitinib and osimertinib (71,72,86,87,114-116). Additionally, there are known ethnic differences in the tolerability profile of some smTKIs (Table 2). Many studies have demonstrated that Asian patients, in particular East Asians, experience more severe and more frequent smTKI-related adverse events when compared to people of European ancestry (79,90,97,121,125), with the exceptions of ceritinib and crizotinib, where Asian patients appear less susceptible to adverse events (32,118), and osimertinib, which does not appear to display inter-ethnic differences in harmful effects (71). Accordingly, with most smTKIs, higher rates of toxicity-related dose reductions, dose interruptions and drug discontinuations have been reported in patients of East Asian than European ancestry (20,45,46,51,52,67,76,89,124,125).

Table 1 Small molecule tyrosine kinase inhibitor efficacy outcomes across ethnic groups
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Table 2 Small molecule tyrosine kinase inhibitor adverse event reports across ethnic groups
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Inter-ethnic differences in pharmacokinetic pathways

Tyrosine kinase inhibitor pharmacokinetics

Pharmacokinetics describes the relationship between the drug dose and the resulting plasma and tissue drug concentrations (126). The processes of absorption, distribution, metabolism and excretion of a drug all contribute to the concentration-time profile observed in a patient undergoing smTKI treatment (4).

Absorption and bioavailability

For orally administered drugs, bioavailability influences systemic exposure (2), which is highly variable for most smTKIs (2). Bioavailability is a product of the fraction of the dose that is absorbed into enterocytes, the dose that reaches the hepatic portal vein unchanged, and the fraction that is not metabolized by enzymes in the liver (2,127). Therefore, membrane transporters and metabolizing enzymes can be important determinants of smTKI bioavailability (10,126,127). Once smTKIs enter the enterocyte from the gut lumen, they can undergo metabolism (10,126,127). Subsequently the smTKI may either undergo efflux back into the gut lumen, or be transferred into the portal circulation via passive or active (efflux) transport (10,126,127). Upon presentation to the liver via the portal circulation, smTKIs can be taken into the hepatocytes where they can be metabolized, excreted into bile or transported back to the systemic circulation (10,126,127).

Membrane transport proteins include ATP-dependent (ABC) and solute carrier transporters (SLC) (1,2). ABC transporters mediate drug efflux, and include P-glycoprotein (P-gp; encoded by ABCB1/MDR1), Breast Cancer Resistant Protein (BCRP; encoded by ABCG2) and Multidrug Resistance Protein (MRP; encoded by ABCC) (1,2,128,129). ABC transporters are expressed on various cells, including the apical/luminal membrane of enterocytes, where they can act as a barrier to intestinal drug absorption (2,128,129). All TKIs except for cabozantinib, ibrutinib, regorafenib, ruxolitinib and trametinib are substrates for either P-gp or BCRP efflux transporters (Table S1) (1,130). SLC transporters mediate drug uptake into the cell and include organic anion transporters OATP1B1 (SLC01B1) and OATP1B3 (SLC01B3), and the organic cation transporter OCT1 (SLC22A1) (1,2,131). SLC transporters are expressed on various cells, including the apical and basolateral membranes of enterocytes, where they facilitate intestinal absorption (1,2,131). They are also expressed on the basolateral membrane of hepatocytes, where they promote hepatocellular drug uptake required for substrate metabolism and biliary excretion (1,2,131). In vitro studies suggest that most smTKIs cannot be considered significant substrates for uptake transporters, with the exception of axitinib for OATP1B1 and OATP1B3, regorafenib for OATP1B1 as well as nintedanib and dasatinib for OCT1 (Table S1) (1).

Distribution

Many smTKIs have extensive tissue distribution, with an apparent volume of distribution typically between 100 and 1,000 L, and a terminal half-life between 24 to 48 hours (Table S1) (3,132). Additionally, all smTKIs are extensively protein bound (>90%) to albumin or the acute phase protein α₁-acid glycoprotein (AGP) (3,132). Finally, membrane transporters play a key role in smTKI distribution (126). ABC transporters are expressed on capillary endothelial cells of tissue barriers (including the blood-brain barrier), acting as a barrier to penetration of substrate drugs (2,126,128,129). SmTKIs must also access cancer cells and intracellular molecular targets, in which case uptake into, and efflux out of, the target cell via transporters are key determinants of drug delivery and action (126). The ABC transporters may also contribute to multidrug resistance in tumors by removing substrates from cancer cells (133).

Metabolism

Drug metabolism usually occurs in the liver after distribution to the body, but some drugs undergo first-pass (pre-systemic) metabolism in the intestinal wall (enterocytes) and liver after oral administration prior to reaching the systemic circulation (134). SmTKIs are metabolized by phase 1 reactions, primarily catalyzed by cytochrome-P450 (CYP) enzymes, and phase 2 reactions catalyzed by enzymes including UDP-glucuronosyltransferases (UGTs) (Table S1) (134). Metabolism can render drug molecules inactive, or may produce a compound that is of equivalent or greater pharmacological activity (2). For example, sunitinib and imatinib are primarily metabolized by CYP3A4 to produce biologically active metabolites N-desethyl (SU12662) and N-demethylated piperizine, respectively, which have similar potencies to their parent drugs (135,136). Clinical responses must be considered in light of the concentrations of the parent drug and active metabolite. Sorafenib and erlotinib are also metabolized to pharmacologically active metabolites, sorafenib N-oxide and OSI-420, respectively (15,137). Since these metabolites are not present at high concentrations, they are not expected to play a major role in determining the clinical activity observed after administration of each parent compound (15,137).

Excretion

SmTKIs are primarily cleared through hepatic metabolism and P-gp mediated biliary excretion, with elimination of unchanged drug in urine accounting for less than 10% of total systemic clearance (Table S1) (134). Most smTKIs are extensively metabolized prior to biliary excretion, with the exception of afatinib, as it is mainly eliminated unchanged in feces (138). Membrane transporters play a role in the excretion of smTKIs. ABC transporters are expressed on bile caniculi of hepatocytes and are therefore involved in the biliary excretion of substrates. They are also expressed on renal epithelial cells, where they export substrates from the cytoplasm of the renal tubular cells to the urine (1,2,131).

Ethnic factors influencing pharmacokinetic determinants of TKIs

Expression levels and activities of drug transporters and metabolizing enzymes are influenced by genetic and environment factors, and may have important consequences for drug or metabolite(s) concentrations at the site of action and hence the efficacy and tolerability of smTKIs.

Genetic factors can be cis or trans acting elements (4). Cis acting elements include non-synonymous single nucleotide polymorphisms (SNPs), which are single nucleotide substitutions that lead to an amino acid change, a premature stop codon, or altered splicing (4). For example, the non-synonymous SNPs 34G>A (Val12Met) and 421C>A (Gln141Lys) in the coding regions (exon) of ABCG2 are associated with decreased BCRP expression and activity, reduced efflux and increased plasma and cellular exposure of several BCRP substrates (130,139-141). SNPs in introns (non-coding region) can also have functional consequences. The 6986A>G SNP in CYP3A5 (CYP3A5*3) creates an alternative splice acceptor site in intron 3, shifting the reading frame and causing a premature stop codon and non-functional protein (142). Conversely, the A allele is associated with the expresser phenotype of CYP3A5 (CYP3A5*1) (143). Synonymous SNPs can also affect the activity of the protein, and thus should not be disregarded (4,144). Although they do not result in an amino acid change, they can still cause “fitness consequences” and phenotypic differences (4,144). For example, the ABCB1 3435C>T SNP results in a synonymous change (ATC isoleucine, ATT isoleucine) that has been found to affect mRNA stability and the timing of co-translational folding, thereby altering P-gp conformation and the structure of interaction sites (144-146). However, its functional effect on P-gp expression is inconclusive, with studies associating the TT genotype with decreased P-gp expression (146-149), increased expression (150), or no effect (151). Haplotypes, which are SNPs that are inherited together in a particular pattern on the same chromatid, can also have pharmacokinetic implications (4). The ABCB1 3435T>C/1236T>C/2677T>G/A TTT haplotype combination results in decreased P-gp expression, and has been associated with increased plasma exposure of P-gp substrates (145). Furthermore, nucleotide insertions and deletions in exons and introns can affect protein structure and activity, by shifting the reading frame (4). Finally, sequence variations in the DNA binding site may affect the binding affinity of regulatory molecules (4). The presence of an additional TA repeat in the TATA sequence of the UGT1A1 promotor (UGT1A1*28) results in reduced transcription and reduced UGT1A1 enzyme activity (152). Trans acting elements can also contribute to pharmacokinetic variability. They include the nuclear receptors, PXR (pregnane X receptor, NR1I2) and CAR (constitutive androstane receptor, NR1I3), which regulate the transcription of genes encoding drug metabolizing enzymes and transporters (4,126). Polymorphisms in NR1I2 and NR1I3 can affect the expression and activity of metabolizing enzymes and transporters (153).

Inter-ethnic differences in the pharmacokinetics of a drug can be due to variability in allele frequencies, and in the types of allelic variants of drug metabolizing enzymes, transporters and nuclear receptors in people from different ethnic backgrounds (4,126). Many variants in drug metabolizing enzymes and transporters have been described, which can result in either loss-of-function of the protein or increased activity. An ethnic group with a higher prevalence of an allelic variant of an efflux transporter that has impaired function, would have reduced drug efflux, and therefore increased plasma and cellular concentrations of the drug at a standard dose (4). This could potentially result in more frequent and severe adverse drug reactions, compared to people from other ethnic populations who have a lower frequency of this allelic variant (4). Additionally, an ethnic population with a higher frequency of a metabolizing enzyme with increased activity, would have higher mean clearance and lower mean plasma exposure, and thus possibly reduced efficacy and/or less frequent adverse events (4). The clinical relevance of these polymorphisms depends on whether the drug of interest is a substrate of the metabolizing enzyme or transporter, whether plasma or tissue concentrations correspond to efficacy and toxicity, and whether the metabolites produced are pharmacologically active. Additionally, since smTKIs have a narrow therapeutic index, polymorphisms contributing to aberrant drug metabolism and transport can result in clinically significant changes to drug response (126).

Other environmental (non-genetic) factors may also contribute to ethnic variability in pharmacokinetics and therefore response to tyrosine kinase inhibitors, such as tobacco smoking, diet and the use of complementary and herbal medicines (4). These factors are discussed below.

Ethnic differences in genetic determinants of TKI pharmacokinetics

Many studies have correlated polymorphisms in genes encoding metabolizing enzymes or transporters with toxicity and efficacy of smTKIs. Variability in the frequency and the types of these genetic variants among people from different ethnic populations can, in part, explain the inter-ethnic differences observed in smTKI exposure, efficacy and adverse drug outcomes (Table 3).

Table 3 Pharmacogenetic variants linked to ethnic differences in small molecule tyrosine kinase inhibitor outcomes
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Sunitinib

High sunitinib systemic exposure has been correlated with an increased risk of adverse events, as well as improved tumor response rates, time to progression (TTP) and overall survival (OS) in patients with gastrointestinal stromal tumors (GIST) and metastatic renal cell carcinoma (RCC) (209). A number of population pharmacokinetic studies have demonstrated that Asian patients have lower clearance of sunitinib and greater sunitinib plasma exposure compared to people from a non-Asian background (209-211). Accordingly, many studies have demonstrated that East Asians are more susceptible than people from a European background to sunitinib-related adverse events (Figure 1) (97,98,157,212-214).

Figure 1 Incidence (95% confidence interval) of grade 3 or more adverse events in Asian and Caucasian patients with metastatic renal cell carcinoma administered sunitinib, as calculated by a meta-analysis of 28 clinical studies (97).

This altered pharmacokinetic profile in East Asian patients can be explained in part by the higher prevalence of the ABCG2 421C>A allele and the ABCB1 3435CC genotype in East Asians than Europeans (154). Both variants are independently associated with significantly lower clearance and higher plasma exposure of sunitinib (143,158,159,169,171,215). The ABCG2 421AA genotype has also been correlated with a significantly higher risk of sunitinib-induced toxicities, including thrombocytopenia [odds ratio (OR) =9.90, P=0.04], neutropenia (OR =18.20, P=0.02) and Hand-Foot Syndrome (HFS) (OR =28.46, P=0.01) in Asian cohort studies (157-159). A case report in 2014 described a Japanese patient with RCC who was homozygous for ABCG2 421AA and developed severe thrombocytopenia, transaminase elevation, hypoxia, and pleural effusion on a 50 mg daily dose of sunitinib, due to elevated sunitinib and metabolite (SU12662) plasma concentrations (160). Additionally, Asian patients carrying the ABCB1 3435CC genotype had a significantly higher risk of all-grade rash [relative risk (RR) =3.00] and mucositis (RR =1.60), compared to T allele carriers (169). A separate study demonstrated a 10-fold reduction in the risk of neutropenia (P=0.01) and 3-fold reduction in the risk of diarrhoea (P=0.02) in patients expressing the ABCB1 3435T allele (171). Furthermore, the ABCB1 TTT haplotype (3435T>C/1236T>C/2677T>G/A), which is more prevalent in East Asians and South Asians than Europeans, has been associated with an increased risk of sunitinib-induced HFS (0R =2.56, P=0.035) (175). Recently, a case was reported of a Japanese patient that developed severe toxicities with sunitinib and gemcitabine, including grade 3 thrombocytopenia, neutropenia, respiratory distress, and elevated transaminases (173). The patient was found to have the ABCB1 TTT haplotype, as well as high sunitinib and SU12662 concentrations (173).

Metabolizing enzymes also play an important role in the inter-ethnic variability of sunitinib exposure and response. An exploratory study in patients with GIST and RCC found a significant correlation between the CYP1A1 2455A>G variant and an increased risk of leukopenia (OR =6.24, P=0.029) and mucosal inflammation (OR =4.03, P=0.021) (175). This G allelic variant is associated with increased CYP1A1 catalytic activity, and therefore is hypothesized to increase sunitinib conversion to the SU12662 metabolite (154). Excessive accumulation of SU12662 has been associated with grade 3 thrombocytopenia and leukopenia (216). Additionally, CYP3A5*1 has been associated with an increased risk of sunitinib dose reductions secondary to toxicity (180,181), and increased progression-free survival (PFS) in RCC patients treated with sunitinib [hazard ratio (HR) =0.266, P<0.05] (179). The increased catalytic activity of CYP3A5 associated with this variant results in increased conversion of sunitinib to SU12662 (143). It is hypothesized that this increased conversion to SU12662, which has a longer elimination half-life than sunitinib, results in increased exposure and therefore altered clinical outcomes (143). Furthermore, the CYP3A4 rs4646437G>A SNP has been correlated with an increased risk of hypertension in sunitinib treated RCC patients (OR =2.4, P=0.021) (177). It is hypothesized that hypertension is due to inhibition of vascular endothelial growth factor receptor-2 (VEGFR-2), leading to a reduced amount of nitric oxide and therefore vasoconstriction (177,217). All these CYP variants are more prevalent in South Asian and East Asian, compared to European populations (154), a possible explanation for the greater incidence of sunitinib-induced adverse events observed in Asians.

It has been suggested that people of Asian ancestry are started on lower doses of sunitinib to reduce the likelihood of severe toxicities (218). A study in Singapore evaluated sunitinib outcomes at an attenuated dosing regimen of 37.5 mg/day (4 weeks on, 2 weeks off), which is lower than the conventional dosing of 50 mg daily (4 weeks on, 2 weeks off) (218). Both regimens demonstrated comparable survival outcomes, however, there was a significantly lower rate of toxicities (P=0.0088) and toxicity-related dose reductions (P=0.005) with the attenuated dose regimen (218).

Imatinib

Higher imatinib systemic exposure is associated with improved response rates, time to response, and event-free survival in patients with chronic-myeloid leukaemia (CML) (161,219-222). In patients with GIST, imatinib systemic exposure is correlated to clinical response and disease progression (223). There is a growing body of evidence to suggest that East Asian patients with GIST or CML are more susceptible to imatinib-related adverse events, and are more likely to respond to treatment (39,60-63,224-228). This variability in response is possibly a reflection of inter-ethnic differences in imatinib exposure, due to inter-ethnic variability in the activity and expression of BCRP and P-gp.

A study conducted in Chinese patients with GIST correlated the T allele of ABCB1 3435T>C with significantly higher steady-state imatinib plasma concentrations (184). They hypothesized that this polymorphism resulted in reduced P-gp production, thereby lowering drug clearance (184). In a meta-analysis of ABCB1 gene polymorphisms, the T allele of ABCB1 3435T>C and G allele of ABCB1 2677T>G/A were predictors of worse imatinib response in patients with chronic-phase CML (170). Both of these allelic variants are more common in Europeans than East Asians, which could contribute to the observed inter-ethnic differences in imatinib outcomes (154). The ABCG2 421C>A allelic variant has also been correlated with decreased imatinib clearance, and increased imatinib plasma and cellular concentrations (141,161-163). A study in Korean patients with GIST demonstrated a significantly superior 5-year PFS rate in patients with the ABCG2 421AA genotype (92.3% vs. 65%, P=0.047) (164). Similarly, in CML patients, this AA genotype has been associated with increased major molecular response (MMR) rates (155). The ABCG2 34GG genotype, which is more prevalent in Europeans than East Asians, has also been correlated with significantly poorer cytogenetic response rates (major: MCyR, complete: CCyR) (155). This variant is associated with normal BCRP expression, thus reducing imatinib intestinal absorption and systemic exposure (229). Together, these studies indicate that genotyping for ABCG2 421C>A and 34G>A, as well as ABCB1 2677T>G/A and 3435T>C, may be useful in identifying patients at risk of sub-therapeutic response and toxicity, particularly among Asian populations. This may identify patients who will benefit from therapeutic drug monitoring, or dose-adjustment.

Variability in the activity of nuclear receptors can contribute to variability in treatment outcomes. A study in Chinese GIST patients correlated the CC wild-type genotype of NR1I2 rs3814055, with significantly higher imatinib trough plasma concentrations (P=0.0066) and a higher incidence of imatinib-induced edema (OR =13.48, P=0.003), compared to T allele carriers (184). The T allelic variant of rs3814055, which is more frequent in Europeans than East Asians (154), is associated with increased CYP3A4 and ABCB1 transcription and metabolic activity, and therefore increased imatinib clearance (153).

Erlotinib

There are known inter-ethnic differences in erlotinib pharmacokinetics and outcomes. East Asians are more susceptible than Europeans to erlotinib-related adverse events (45,46,121). Additionally, African Americans are reported to have higher erlotinib clearance and lower erlotinib systemic exposure, when compared to East Asians and people of European ancestry, as reflected in their substantially lower incidence of adverse events (120,230). It is known that erlotinib trough concentrations are an independent risk factor for the development of grade ≥2 diarrhea (P=0.037) and skin rash (P=0.031) (165), and therefore ethnic variability in erlotinib pharmacokinetic determinants has the potential to result in inter-ethnic differences in toxicity.

For example, the ABCB1 TTT haplotype (3435T>C/1236T>C/2677T>G/A) has been correlated with significantly higher erlotinib plasma exposure (P=0.021), and a greater risk of erlotinib-related grade 2/3 toxicities including skin rash (P=0.012) (171,174). Additionally, a population pharmacokinetic-pharmacodynamic model in Japanese patients noted a significantly higher incidence of grade ≥2 diarrhea in patients with the ABCG2 421C>A allelic variant (P=0.035) (165). This reduced function variant of BCRP is uncommon in African-Americans (154), and has been correlated with decreased erlotinib and OSI-420 clearance, higher erlotinib plasma exposure, and higher erlotinib cerebrospinal fluid penetration (165,231). Furthermore, a study in Japanese patients with non-small cell lung cancer (NSCLC) noted significantly higher erlotinib plasma exposure in patients carrying the CYP1A1 2455GG genotype (P=0.0151) and CYP3A5 6986GA/GG genotypes (P=0.0198) (176). These variants are more prevalent in East Asians than Europeans and African-Americans (154), a possible explanation for inter-ethnic differences in erlotinib adverse-event susceptibility. Conversely, the AA genotype of CYP3A5 (*1/*1) is found in 50% of African-Americans, compared to only 5.8% of East Asians and 4.5% of people of European ancestry (154).

Gefitinib

Inter-ethnic differences in BCRP expression may contribute to the ethnic disparities observed in gefitinib-related adverse events. The ABCG2 34G>A allelic variant has been correlated with gefitinib-induced skin toxicity (P=0.046) (156), and the ABCG2 421C>A allelic variant with grade ≥2 diarrhea (P=0.0046) (166,167). Both variants are associated with higher gefitinib plasma concentration at steady-state (166,167), an independent risk factor for developing gefitinib-induced diarrhea (P=0.006) and hepatotoxicity (P=0.024) (232). These variants are more prevalent in East Asians than Europeans (154), which is in line with the higher incidence of gefitinib-related adverse events observed in East Asians (51,52,121).

Sorafenib

East Asian patients have increased susceptibility to sorafenib-induced HFS (89-93,124,233-236). A study in Korean patients with hepatocellular carcinoma (HCC) identified the UGT1A9 IVS1-37431 AA variant as an independent risk factor for the development of high-grade HFS (OR =18.7, P=0.02) (183). Given that this genotype is more prevalent in East Asians than Europeans (154), it could explain some of the observed inter-ethnic variability in sorafenib toxicity (90).

Ethnic differences in physiological factors determining TKI pharmacokinetics

Plasma protein binding

Plasma protein binding has an important role in the distribution of anticancer drugs, including smTKIs (4,237-240). Many studies have demonstrated that a reduction in AGP concentration leads to an increase in the unbound fraction of imatinib and a reduction in total plasma imatinib concentrations, due to the rapid distribution of unbound imatinib into extravascular space and effects on hepatic clearance (238-240). Serum AGP concentrations have also been correlated with imatinib efficacy in CML, with a study suggesting that AGP concentrations (an inflammatory marker) are associated with the in vivo load of leukemic cells (240). There are inter-ethnic differences in plasma protein binding, with East Asian healthy subjects reported to have lower AGP concentrations than Europeans (241). A recent study in people with breast cancer noted significantly lower AGP concentrations in Chinese patients when compared to Malays and Indians (242). It could therefore be postulated that the greater toxicity and efficacy observed in East Asian patients treated with imatinib, could be a reflection of lower AGP concentrations, correlating to increased imatinib cellular and tissue distribution.

Body size and weight

For many drugs, body size (usually assessed by total body weight) can explain the inter-ethnic differences observed in pharmacokinetics. Generally, South Asian and East Asian populations have a higher portion of body fat with a lower body-mass-index (BMI), lean body mass (LBM), and body surface area (BSA), when compared to people of European ancestry (243-246). These factors have the potential to affect drug distribution and elimination. For lipophilic drugs, such as some smTKIs, apparent volume of distribution (V/F) can increase in people with a higher portion of body adipose tissue (247). For some drugs, lower LBM has been associated with lower clearance, related to organ size and blood flow (247). In population pharmacokinetic studies of imatinib, higher total body weight (TBW) has been correlated with increased V/F and clearance, consistent with increased body fat and body mass (248-250). Low TBW and BSA have also been correlated with higher imatinib plasma trough concentrations, and correspondingly improved response rates with increased toxicities (221,251). Additionally, low BMI and muscle mass have been identified as significant predictors of sorafenib (252) and sunitinib-related dose-limiting toxicities (253). Recently, LBM was also identified as a predictor of sunitinib plasma exposure and toxicities (215). Furthermore, lenvatinib clearance has been correlated to TBW (254). A subgroup analysis of patients enrolled in the SELECT trial demonstrated no difference in lenvatinib plasma exposure between the Japanese and non-Japanese subgroups after adjusting for TBW (67). For all aforementioned smTKIs, there is good evidence that East Asian patients are more susceptible than Europeans to drug-related adverse events (39,67,68,73,89,90,97,124) (Table 2). The lower LBM and higher body-fat percentage of East Asians could be a factor contributing to this inter-ethnic variability in tolerability. Therapeutic drug monitoring and body-weight based dosing may help reduce the incidence of severe smTKI-related adverse events, particularly in Asian patients.

Ethnic differences in extrinsic factors and TKI pharmacokinetics

Extrinsic factors should be considered as a possible source of inter-ethnic differences in drug response, as they can influence the pharmacokinetics and pharmacodynamics of smTKIs.

Complementary and herbal medicine use

The use of complementary and herbal medicines varies between people from different ethnic groups, due to different cultural and health beliefs, with the highest level of complementary and herbal medicine use reported in Asians (255,256). A study by Hsiao et al. noted greater use of green tea, ginseng, and soy products among Asian Americans compared to Americans of European ancestry (255). Additionally, complementary and herbal medicines are commonly used among cancer patients, with studies in Europe, America, Malaysia and Korea reporting use in 35.9%, 63%, 70.2% and 78.5% of patients, respectively (257-260). Importantly, many cancer patients are using complementary and herbal medicines in combination with their conventional anticancer therapy, with most patients (up to 72%) not informing their physicians about their complementary medicines (261). A study in patients undergoing treatment for melanoma demonstrated that 85.1% of patients that were using complementary and herbal medicine with their anticancer agent were at risk of drug interactions (262). Considering the narrow therapeutic index of most smTKIs, drug- drug interactions could lead to serious adverse events or reduced therapeutic effect of the smTKI.

Most smTKIs are metabolized primarily by CYP3A4, and are substrates of P-gp and BCRP membrane transporters (Table S1) (10,263). Therefore, there is a high potential for serious interactions when smTKIs are co-administered with complementary and herbal medicines that have modulatory effects on P-gp, BCRP and CYP3A4 (Figure 2) (10,263). Some herbal medicines that are inducers of CYP3A4, BCRP or P-gp have the potential to increase smTKI metabolism, and promote hepatic and renal excretion (10,263). The increased elimination and reduced plasma exposure of the smTKI could result in therapeutic failure. Conversely, inhibition of BCRP, P-gp or CYP3A4 by complementary and herbal medicines could result in enhanced intestinal absorption, reduced metabolism, and reduced renal and hepatic excretion (10,263). The increased smTKI exposure could result in severe drug-related toxicities. Case reports of these complementary medicine or herbal TKI interactions are presented in Table S2. Physicians must consider a patients’ use of complementary and herbal medicines prior to smTKI treatment, to ensure appropriate doses are initiated for efficacy and safety. Understanding inter-ethnic differences in the use of complementary and herbal medicines can also assist clinicians in educating patients, and in identifying possible reasons for suboptimal treatment outcomes.

Figure 2 Potential drug-drug interactions for tyrosine kinase inhibitors with complementary and herbal medicines (264-286).

Tobacco smoking

Tobacco smoking prevalence differs by ethnicity, both within and between countries. For example, in the US, the Center for Disease Control and Prevention reported that in 2010–2013 cigarette smoking prevalence was lowest in Asian Americans (10.9%) and highest in Native Americans (38.9%) (287). In addition, in many countries, including in Asia, smoking prevalence is higher in men than women. For example, in China in 2010 52.9% of men and 2.4% of women were reported to be current tobacco smokers (288).

Polycyclic aromatic hydrocarbons in tobacco smoke have the potential to affect drug metabolism, as they are potent CYP1A1 and CYP1A2 inducers (289). A pharmacokinetic study of erlotinib reported a 2.8-fold lower area under the concentration-time curve (AUC) in smokers and a 8.3-fold lower median steady-state plasma concentration (C_24h) in smokers compared to non-smokers (290). Erlotinib is metabolized in part by CYP1A2 and CYP1A1, thereby resulting in greater erlotinib clearance and lower plasma concentrations in smokers. In a population pharmacokinetic analysis of NSCLC patients, the median C_24h and clearance of erlotinib in current smokers were 60% and 143% of the values in a non-smoking group (291). Non-smokers also had a greater incidence of adverse events compared to smokers, consistent with higher erlotinib exposure (178). A meta-analysis of epidermal growth factor receptor (EGFR)-positive NSCLC patients treated with EGFR-smTKIs (erlotinib or gefitinib) demonstrated that non-smoking was associated with significantly prolonged PFS (HR=0.73, P=0.001) compared to ever smokers (292). The ethnic variability in cigarette smoking prevalence may be a factor contributing to superior response rates and greater toxicity observed in East Asian patients treated with these EGFR-smTKIs. Therefore, lower starting doses are recommended in heavy smokers (>20 cigarettes/day). A study in head and neck cancer patients’ demonstrated comparable efficacy outcomes in current smokers receiving an adjusted erlotinib dose of 300 mg daily, and in non-smokers receiving standard doses of 150 mg daily (293). With tobacco smoking potentially influencing drug response, population differences in the incidence of smoking can contribute to the inter-ethnic difference in efficacy and safety reported for some smTKIs.

Inter-ethnic differences in pharmacodynamic pathways

Pharmacodynamics refers to the relationship between drug concentrations and effects (126). Individuals with similar drug plasma or tissue concentrations can have significantly different responses, indicating that non-pharmacokinetic mechanisms can be involved in variable drug action (126). Pharmacodynamic variability can arise from genetic variability in the activity or expression of target genes or candidate genes involved in the therapeutic pharmacological pathway of a drug (10,126). The prevalence and activity of smTKI target variants in different ethnic populations can contribute to inter-ethnic differences in smTKI treatment outcomes.

Erlotinib and gefitinib

Many studies have demonstrated superior response rates and survival outcomes with erlotinib and gefitinib in East Asian patients compared to Europeans with NSCLC (Figure 3) (8,9,44-48,51-53,294-297). This variation in response has been correlated to inter-ethnic differences in the frequency of EGFR activating mutations, namely the in-frame deletion in exon 19 and L858R point mutation in exon 21 (201,202). These activating mutations are found in approximately 30% of East Asian patients with NSCLC, compared to only 8% of Europeans (201,202). EGFR-positive NSCLC patients show significantly greater tumor shrinkage, objective response rates (ORR), OS and PFS with gefitinib and erlotinib, compared to EGFR-negative patients (185-198), irrespective of the mutation type (197,199,200). However, studies selective for EGFR-positive NSCLC still show significantly superior outcomes with gefitinib and erlotinib in East Asians compared to other ethnic groups, indicating that other factors are also contributing to variable response (48). Similarly, East Asian patients with pancreatic cancer show more profound benefits with erlotinib than non-East Asians (49,50). This is likely due to inter-ethnic differences in EGFR mutation profiles, with EGFR activating mutations (L778P and I821T in exon 20, K728R and W731X in exon 19) significantly more common in Chinese than European patients with pancreatic cancer (50,203). These mutations are associated with significantly greater disease control rates (DCR), longer PFS and longer OS (50).

Figure 3 Overall survival benefit with gefitinib or placebo in (A) patients of Asian ancestry and (B) patients of non-Asian ancestry enrolled in the phase III placebo-controlled ISEL (IRESSA Survival Evaluation in Lung Cancer) trial (51).

Imatinib

It appears that South Asian patients with CML do not respond as well as patients with an East Asian or European ancestry to imatinib treatment (224). Ethnic diversity in the expression of genes involved in imatinibs’ apoptotic pathway can explain some of the observed inter-ethnic variability in response. Bcl-2-like protein-1 (encoded by BCL2L11/BIM) plays a central role in the apoptosis of BCR-ABL cells, a pathway essential to imatinib-induced cell death (298). In a French cohort study, the T allelic variant of BCL2L11 465T>C significantly delayed MMR achievement (P=0.0407) and increased the risk of imatinib resistance (P=0.0049) (204). This variant is more common in South Asians than Europeans and East Asians (154), mirroring the poorer outcomes observed in South Asians. It is hypothesized that this polymorphism may reduce BIM activity and expression (204). Another candidate pathway involved in imatinib response is interferon (IFN) signaling. Variability in IFN-gamma expression affects hematopoietic stem cell expansion and proliferation, thereby altering the sensitivity of CML to imatinib (205). A study in CML patients correlated the CC genotype of IFNG rs2069705 with higher CCyR rates (HR =1.727, P=0.005) and MMR rates (HR =1.912, P=0.002) (205). Inter-ethnic differences in the frequency of the CC genotype correlate with the lower response rates observed in South Asian patients with chronic-phase CML (154).

Pazopanib

Pazopanib is an angiogenesis inhibitor targeting VEGFR, platelet-derived growth factor receptors (PDGFR) and the stem cell factor receptor, c-Kit. When pazopanib is used as second line treatment of advanced RCC, it appears that people of European ancestry have superior response rates and survival outcomes compared to East Asians (74,75). A polymorphism in the HIF1A gene (1790G>A) has been correlated with pazopanib efficacy, with the AG genotype associated with poorer PFS (20 vs. 44 weeks, P=0.03) and ORR (30% vs. 43%, P=0.02) compared to the GG wild-type (206). This variant results in higher transcriptional activity of the hypoxia-inducible factor-1 (HIF1) protein, which is a transcription factor that upregulates genes involved in angiogenesis, including vascular endothelial growth factor (VEGF) and platelet derived growth factor (PDGF) (299,300). Therefore, patients with this variant have increased angiogenesis capability, rendering anti-angiogenesis agents like pazopanib less effective (299). The AG genotype is more common in East Asians than Europeans (154), which could potentially explain the inferior outcomes observed.

Sorafenib

East Asians are more susceptible than people with European ancestry to sorafenib-induced adverse events such as HFS and hypertension, and are therefore more likely to discontinue treatment (90). Inter-ethnic differences in genes relevant to tumor angiogenesis can explain some of the ethnic variability observed in sorafenib response. A cohort study in Korean patients with HCC identified the GG genotype of tumor-necrosis factor-α (TNF-α) -308G>A as an independent risk factor for developing high-grade sorafenib-induced HFS (OR =44, P=0.02) (183). This genotype is associated with higher levels of the TNF-α cytokine (183), resulting in increased anti-vascular and anti-angiogenic activity, and reduced tumor blood-flow (301,302). It is hypothesized that the poor vascular exchange associated with increased TNF-α, leads to an inflammatory response that manifests as HFS (183). This genotype is more prevalent in East Asians than Europeans (154), which may explain their enhanced susceptibility to sorafenib-induced HFS. In a small cohort study in Japanese patients with RCC, patients with the HLA-A*24 variant were at a significantly higher risk of sorafenib-induced HFS (207). Furthermore, a Korean case-series described three cases of sorafenib cutaneous reactions, of which two patients expressed HLA-A*24 (208). Binding of an antigenic drug to the human leukocyte antigen (HLA) protein activates cytotoxic T lymphocytes, a possible mechanism for skin toxicities (207). Interestingly, HLA-A*24 is more common in populations of Japanese ancestry than European ancestry (303), another explanation for the increased susceptibility to sorafenib-induced HFS in East Asians. However, larger studies are required to validate these associations.

Sunitinib

Genetic polymorphisms in sunitinib target proteins, such as VEGFR-2 and FMS-like tyrosine kinase-3 (FLT3), have been linked to increased sunitinib-induced toxicity (175). In an exploratory study of patients with GIST and RCC, the risk of sunitinib-induced high-grade toxicity was increased with the VEGFR-2 1191C>T allelic variant (OR =2.39, P=0.046) (175). This variant is associated with a lower binding efficiency of VEGF to the VEGFR-2 (304), and is more prevalent in East Asians than Europeans (154). This study also correlated leukopenia with the FLT3 738C>T allelic variant (OR =2.8, P=0.008) (175), which is also more prevalent in East Asians than Europeans (154). Similarly, a retrospective study of Asian RCC patients demonstrated a significantly increased risk of leukopenia (OR =8.0, P=0.03) and neutropenia (OR =2.7; P=0.04) in patients expressing the FLT3 738TT genotype (171). These studies suggest that Asian patients comprise a subgroup with increased potential for target-related adverse events when treated with sunitinib.

Challenges for clinical practice

Ethnicity is an important factor accounting for inter-individual differences in smTKI response. However, there are challenges faced by prescribers when translating this evidence into clinical practice. The concept of ethnicity is complex, and there is a lack of concordance across studies in the descriptions of ethnic groups. Some studies define patients as White vs. non-White, whilst others nominate nationality (e.g., Korean) or geographic ancestry. Another challenge faced is the limited sample size of many studies, which have insufficient patient numbers from each ethnic group to perform statistical analyses of potential inter-ethnic differences in treatment outcomes. Additionally, small sample sizes may allow potentially important but uncommon genetic polymorphisms to be missed. Furthermore, comprehensive datasets on smTKI outcomes, pharmacokinetic profiles and genetic variants in all ethnic groups are not available. Almost all research has described East Asian, European and African-American populations, and information on many other ethnic groups who utilize these treatments is not available. Moreover, there may be undefined factors which affect an individual’s response to treatment and which contribute to ethnic differences across populations. Understanding all of these factors is fundamental to precision medicine, in order to assist with drug and dose selection for a specific patient of a particular ancestry.

Conclusions

It is clear that ethnicity is an important factor accounting for some of the inter-individual differences observed in smTKI treatment outcomes. Identifying factors that influence outcomes of anticancer drugs, including smTKIs, is a crucial step toward enabling physicians to make personalized treatment decisions. Receiving an appropriate first-line treatment after a cancer diagnosis is critical, as early response has been shown to predict long-term PFS and OS (305-310). We know certain ethnic groups have altered expression/activity of metabolizing enzymes and transporters, thereby influencing smTKI pharmacokinetics and response. Additionally, some ethnic populations have a higher frequency of mutations in candidate genes or biological pathways associated with sensitivity to smTKIs, while others are more likely to have a higher frequency of mutations associated with smTKI resistance. Knowledge of these genetic polymorphisms involved in smTKI pharmacokinetic and pharmacodynamic pathways, and how they influence response, can enable personalized medicine using genotype-based drug and dose selection. Ethnicity could be used as a surrogate to identify patients at risk of severe toxicities or suboptimal treatment, triggering genotype testing. When considered in conjunction with non-genetic factors, such as body weight and extrinsic influences, ethnicity can be used to individualize therapy in terms of both initial drug and dose selection, and to identify patients who would benefit from therapeutic drug monitoring. Finally, understanding the influence of ethnicity on drug pharmacokinetics and pharmacodynamics will better inform the design of future targeted therapies, and also help improve the dose rationale for clinical trials of smTKIs.

Table S1 Targets, pharmacokinetic determinants and pharmacokinetic properties of small molecule tyrosine kinase inhibitors
Full table

Table S2 Case reports of tyrosine kinase inhibitor drug-drug interactions with complementary and herbal medicines
Full table

Acknowledgments

Funding: This work was supported by the Peter Coates Postgraduate Scholarship in Ethnopharmacology [to JA Touma].

Footnote

Provenance and Peer Review: This article was commissioned by the Guest Editors (Michael Sorich and Andrew Rowland) for the series “Precision dosing of targeted anticancer drugs” published in Translational Cancer Research. The article has undergone external peer review.

Conflicts of Interest: AS Gross is an employee and shareholder of GSK. The others have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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