Impact of Membrane Drug Transporters on Resistance To

Feature Review

Impact of Membrane Drug

Transporters on Resistance to

Small-Molecule Tyrosine

Kinase Inhibitors

1 1 2

Claudia Neul, Elke Schaeffeler, Alex Sparreboom,

3 1,4,5, 1

Stefan Laufer, Matthias Schwab, * and Anne T. Nies

Small-molecule inhibitors of tyrosine kinases (TKIs) are the mainstay of treat-

Trends

ment for many malignancies and represent novel treatment options for other

Small-molecule TKIs are the backbone

ﬁ ﬁ

diseases such as idiopathic pulmonary brosis. Twenty- ve TKIs are currently of cancer therapy. Despite profound

success of imatinib in improving out-

FDA-approved and >130 are being evaluated in clinical trials. Increasing evi-

come of patients with chronic myeloid

dence suggests that drug exposure of TKIs may signiﬁcantly contribute to drug

leukemia, survival beneﬁts of TKIs in

resistance, independently from somatic variation of TKI target genes. Mem- other settings are varying and

moderate.

brane transport proteins may limit the amount of TKI reaching the target cells.

This review highlights current knowledge on the basic and clinical pharmacol-

In addition to genetic variation of the

ogy of membrane transporters involved in TKI disposition and their contribution targeted kinases, and diverse meta-

bolic and cellular escape mechanisms,

to drug efﬁcacy and adverse drug effects. In addition to non-genetic and

insufﬁcient TKI exposure and intracel-

epigenetic factors, genetic variants, particularly rare ones, in transporter genes

lular accumulation mediated by mem-

ﬂ

are promising novel factors to explain interindividual variability in the response brane uptake and ef ux transporters

are important for interindividual varia-

to TKI therapy.

bility of TKI response and the occur-

rence of drug resistance.

TKIs: Response Encounters Resistance While in vitro studies and studies using

Protein kinases are key players in signal transduction networks mediating fundamental knockout mice clearly demonstrate TKI

transport by efﬂux transporters, the

cellular processes including cell differentiation, proliferation, apoptosis, transcription, metab-

picture is less clear in pharmacogenetic

olism, and intercellular communication [1–3]. During the past 15 years it has become evident

association studies in humans.

that many cancers, as well as metabolic disorders and immunological, neurological, and Furthermore, the role of currently inves-

inﬂammatory diseases, may originate from dysregulation of these signaling networks [2,4,5]. tigated uptake transporters appears to

be limited.

Protein kinases, including tyrosine kinases, have thereby emerged as the most intensively

studied target structures. Concurrently, drug development has shifted towards small

Novel techniques and strategies are

ﬁ ‘

molecules that speci cally block protein kinases crucial to disease biology. These molecu- needed to better predict the relevance

larly targeted therapies’ are now routinely used in the therapy of many cancers as ﬁrst-line of membrane transporters for in vivo

TKI disposition.

therapy but are also essential in the treatment of drug-resistant malignancies as well as

of other diseases such as idiopathic ﬁbrosis and rheumatoid arthritis [5,6]. In 2001 the ﬁrst

TKI, imatinib, received accelerated approval by the USA FDA for the treatment of Phila-

delphia chromosome positive chronic myeloid leukemia (CML) [7]. Since then, 24 further Dr. Margarete Fischer-Bosch Institute

of Clinical Pharmacology, Stuttgart,

TKIs have been approved, mostly for the treatment of various cancers (Figure 1A). A plethora

and University of Tübingen, Germany

of >3000 novel agents inhibiting diverse protein kinases are currently being 2

Division of Pharmaceutics, College of

explored preclinically, covering not only a broad range of cancers but also ophthalmic Pharmacy, Ohio State University,

Columbus, OH, USA and central nervous system disorders, osteoporosis, as well as disease-related complica-

Department of Pharmaceutical

tions [2]. At present, more than 130 novel TKIs are being evaluated in clinical trials

Chemistry, University of Tübingen,

(Figure 1B). Tübingen, Germany

904 Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 http://dx.doi.org/10.1016/j.tips.2016.08.003

Department of Clinical Pharmacology,

Contrary to the profound improvement of outcomes for CML patients treated with imatinib as ﬁrst-

Institute of Experimental and Clinical

line therapy [8], the success rate of TKIs in other diseases is varying, and only moderate survival

Pharmacology and Toxicology,

beneﬁts are achieved for some disease entities [6,9,10]. Poor initial response (i.e., endogenous University Hospital, Tübingen,

Germany

resistance) or disease relapse (i.e., acquired resistance) are being discussed as major explan- 5

Department of Pharmacy and

ations. Of course, the development of mutations in the target receptor tyrosine kinases (RTK) or

Biochemistry, University of Tübingen,

intracellular non-receptor tyrosine kinases (nonRTK) (Figure 2, Key Figure) is crucial for target- Tübingen, Germany

associated drug resistance, thereby preventing kinase inhibition by the TKI in the target cells. For

example, patients with non-small cell lung cancer (NSCLC) harboring an activating mutation in the

*Correspondence:

ﬁ

RTK epidermal growth factor receptor (EGFR) initially respond very well to erlotinib and ge tinib; [email protected]

however, the acquisition of secondary somatic mutations, such as the gatekeeper mutation (M. Schwab).

Thr790Met, leads to drug resistance. The development of second- and third-generation TKIs,

such as afatinib and osimertinib, respectively, aimed to overcome this resistance [3,11–13].

Another example is provided by CML patients who become refractory to imatinib therapy as

a result of point mutations in BCR–ABL, the constitutively-active fusion kinase driving CML.

Because imatinib-resistant CML patients frequently acquire the same somatic mutations in BCR–

ABL, the second-generation TKIs dasatinib, nilotinib, and bosutinib have been developed and

approved by the USA FDA for treatment of CML patients carrying these mutations. For CML

patients with the BCR–ABL Thr315Ile gatekeeper mutation, the third-generation TKI ponatinib has

been FDA-approved [3,13,14]. In addition to this target-associated resistance, the activation of

new compensatory intracellular signaling pathways is an alternative explanation (so-called bypass

resistance) in which target cells evade the signaling pathway inhibited by TKI as ﬁrst-line therapy.

Several recent reviews excellently summarize these mechanisms of resistance [3,5,6,9–13].

For decades multidrug resistance has been well known as a cause of poor response to cancer

chemotherapy [15], and therefore might also contribute to TKI-related molecularly targeted drug

resistance [9,10]. This indicates that, in addition to acquired mutations in the target kinases,

ADME (absorption, disposition, metabolism, excretion) processes may play an important role in

the pathophysiology of drug non-response. There is an increasing body of evidence that

intracellular concentrations of TKI in target cells (Figure 2) vary substantially between patients

even after identical dosages [16–22], with consequences for drug response. By analogy, drug

resistance in HIV-infected patients receiving antiretroviral drug therapy has been signiﬁcantly

linked to interindividual variability of drug levels of protease inhibitors in peripheral blood

mononuclear cells (PBMC) [23].

Membrane transport proteins, in other words solute carrier transporters (SLC) mediating drug

uptake and ATP-dependent (ATP-binding cassette, ABC) transporters mediating drug efﬂux, are

involved in several ADME processes [24] and thus are promising candidates to explain TKI-

related non-response in cancer patients as well as drug toxicity. Membrane transporters are

necessary for TKIs to enter the target cells before they can interact with the intracellular ATP-

binding sites of the tyrosine kinases. Various mechanisms, including genetic variation, epigenetic

factors, non-genetic factors such as transporter-mediated drug–drug interaction, as well as

regulation processes, are thought to explain interindividual variability in the expression and

function of transport proteins even in cancer cells, resulting in clinical consequences (e.g., non-

response) [25–27].

This review highlights current knowledge on membrane transporters and their potential impact

on TKI disposition. Current limitations and challenges in transporter research are summarized

and strategies for future research directions are proposed.

Mechanism of Action of TKIs

The family of human tyrosine kinases consists of 90 members: 58 RTKs and 32 intracellular

nonRTKs [1]. They share the same catalytic mechanism of using ATP to phosphorylate tyrosine

Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 905

residues on target proteins [2,3,13]. This phosphorylation modiﬁes target protein activities and

leads to the activation of different downstream signaling pathways. While tyrosine kinases differ

in their amino acid sequences, the 3D structures of their kinase domains and particularly the

ATP-binding pockets are highly conserved. The kinase domains consist of an N-terminal lobe, a

C-terminal lobe, and a hinge region linking the two lobes and enabling them to move relative to

each other [3,13]. ATP binds in the active site between these two lobes of the ATP-binding

pocket. Until the 1980s the ATP-binding pockets were considered too conserved to permit the

development of kinase-speciﬁc small-molecule inhibitors. The synthesis of compounds selec-

tively inhibiting EGFR [28] was seminal to the establishment of the new therapeutic class of small-

molecule protein kinase inhibitors [5]. Twenty-two of the currently approved TKIs reversibly bind

to the ATP-binding pockets of the respective tyrosine kinase, either to their active or their inactive

conformations. Only afatinib, ibrutinib, and osimertinib irreversibly bind to the ATP-binding

pockets. A detailed description of the molecular characteristics of TKIs and their modes of

inhibition can be found in recent reviews [3,5,13].

Factors Affecting Responsiveness to Oral TKIs

Drug Exposure as a Determinant of Clinical Outcome

All currently approved TKIs are administered orally. Most of those have a relatively long

elimination half-time (Table 1) resulting in a once- or twice-daily dosing interval with beneﬁcial

consequences for adherence to TKI use. Systemic TKI plasma concentrations are affected by

various parameters: (i) the fraction of TKI absorbed in the intestine, (ii) TKI binding to serum

proteins, (iii) TKI uptake into the hepatocytes, (iv) hepatic metabolism primarily by cytochrome

P450 enzyme CYP3A4/A5, and ﬁnally (v) biliary excretion (Figure 2B). All these factors may

contribute to the large interpatient variability of TKI exposure, which is reﬂected by the area under

the plasma concentration–time curve (AUC) and coefﬁcients of variations of up to 77% (e.g.,

axitinib, Table 1). Intestinal absorption may be impaired by concomitant food intake or the use of

antacids (reviewed in [29]). Genetic variation in drug-metabolizing enzymes has been identiﬁed

as a major source of variation in the pharmacokinetics and response of many drugs [30]. It is

beyond the scope of this article to comprehensively review the contribution of genetic variation in

metabolizing enzymes to TKI pharmacokinetics and response. Only three examples for the

various effects of genetic variation on TKI response and toxicity should be given: (i) imatinib

pharmacokinetics appears to be affected only to a minor degree by genetic variation in CYP3A4/

5, CYP2C9, CYP2C19, or CYP2D6 [31–33], and had no effect on clinical response in CML

patients [33]; (ii) early sorafenib-induced severe toxicity has been associated with a genetic

variant in UGT1A9 encoding an enzyme involved in glucuronidation of sorafenib, but not with

genetic variation of CYP3A5 [34]; (iii) sunitinib-induced toxicity and hypertension are associated

with genetic variants in CYP3A5 and CYP3A4, respectively [35,36]. In addition to metabolizing

enzymes, membrane uptake and efﬂux transporters are important determinants of drug plasma

concentrations [24].

All TKIs are characterized by large AUC coefﬁcients of variation (Table 1), and it has been

suggested that this wide pharmacokinetic variability of TKI exposure can affect both TKI efﬁcacy

and toxicity [37]. Indeed, a large number of clinical studies have been conducted correlating

pharmacokinetic parameters such as the AUC or the minimum TKI steady-state plasma

concentrations with TKI response and/or adverse reactions. Selected signiﬁcant correlations

are summarized in Table 2. For example, in patients with gastrointestinal stromal tumors (GIST)

the probability of a complete/partial response and toxicity is increased 2.6- and 2.2-fold,

respectively, for every doubling of exposure to free imatinib (AUC0–24) [38]. Furthermore, a

minimum imatinib steady-state plasma concentration of >1000 ng/ml was consistently associ-

ated in ﬁve independent studies with an increased probability of complete cytogenetic or major

molecular response in CML patients (summarized in [39]). Therefore, several clinical recom-

mendations have been published suggesting therapeutic monitoring of plasma TKI levels to

906 Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 (A)

Non-small cell lung cancer Medullary thyroid cancer Erlonib (Tarceva, 2005) Cabozannib (Cometriq, 2012) Lapanib (Tykerb/Tyverb, 2007) Vandetanib (Caprelsa, 2012) Geﬁnib (Iressa, 2009) Sorafenib (Nexavar, 2013) Crizonib (Xalkori, 2012) Lenvanib (Lenvima, 2015) Afanib (Gilotrif/Giotrif, 2013) Cerinib (Zykadia, 2014) Nintedanib (Vargatef, 2014) Breast cancer Alecnib (Alecensa, 2015) Lapanib (Tykerb/Tyverb, 2008) Osimernib (Tagrisso, 2015)

Idiopathic pulmonary ﬁbrosis Renal cell carcinoma Nintedanib (Ofev, 2014) Sorafenib (Nexavar, 2005) Suninib (Sutent, 2006) Hepatocellular carcinoma Pazopanib (Votrient, 2010) Axinib (Inlyta, 2012) Sorafenib (Nexavar, 2007)

Polycythemia vera Colorectal carcinoma Ruxolinib (Jakaﬁ/Jakavi, 2012) Regorafenib (Svarga, 2012)

Mantle cell lymphoma Chronic myeloid leukemia Ibrunib (lmbruvica, 2013) Imanib (Gleevec/Glivec, 2001) Dasanib (Sprycel, 2006) Nilonib (Tasigna, 2007) Rheumatoid arthris Bosunib (Bosulif, 2013) Tofacinib (Xeljanz, 2012)

Ponanib (Iclusig, 2013) (B) Other neoplasms 20 Lung 40 10

Non-tumor al

diseases Phase I Phase II Phase III 0

5 Phase I Phase II Phase III Phase IV

0 Phase I Phase II Blood and

Solid tumors and bone marrow sarcom as 30 20 20 10 10

0 Phase I Phase II Phase III

Phase I Phase II Liver and kidney

Gastrointes nal

tract Female reprod ucve 20 system and breast

20 0 Phase I Phase II 10 10

0 0

Phase I Phase II Phase I Phase II

Figure 1. Small-Molecule Tyrosine Kinase inhibitors (TKIs) Approved (A) and in Clinical Trials (B). (A) Small-molecule TKIs approved by the US FDA and the

European Medicines agency (EMA) as of May 2016 according to their indications. Following the drug name, tradenames of the FDA/EMA are given. Only one tradename

(Figure legend continued on the bottom of the next page.)

Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 907

adjust dosages, subsequently leading to improved efﬁcacy or a reduced rate of adverse drug

reactions [20–22,29,39–42]. However, the concept of monitoring serum levels is limited by the

fact that plasma and intracellular TKI concentrations in target cells may differ [17], thereby

supporting the pharmacological rationale that determination of intracellular TKI concentrations is

likely to be a more reliable indicator [40].

Drug Transporters as Major Contributors to Drug Exposure

Membrane transporters are well recognized key determinants of therapeutic response contrib-

uting to drug resistance and drug toxicity [24,43–45]. The human genome encodes >400

membrane transporters that belong to two major groups, the ABC and the SLC superfamilies,

which mediate the cellular uptake and efﬂux of small molecules. About 20 transporters have

been particularly implicated in drug transport and have been intensively studied with respect to

their function, localization, and regulation. Because these are located in the enterocytes of the

intestine, hepatocytes of the liver, proximal tubule cells of the kidney, and endothelial cells of

tissue barriers (e.g., blood–brain barrier), they are directly involved in the absorption, distribution,

and elimination of drugs, and also indirectly inﬂuence metabolism by controlling access to drug-

metabolizing enzymes (Figure 2B–F). Transporter-mediated uptake into non-target cells may

also contribute to drug toxicity, as for example recently demonstrated for OAT6 (SLC22A20),

which regulates entry of sorafenib into keratinocytes and contributes to sorafenib-induced skin

toxicity [46]. Finally, the presence of membrane transporters in the plasma membrane of cancer

cells, either of the primary tumor or metastases, is a major determinant of drug resistance

because decreased transporter-mediated TKI influx or increased TKI efflux may lead to insuffi-

cient intracellular TKI concentrations (Figure 2A).

Table 3 summarizes currently available functional data on TKIs as substrates for uptake and

efﬂux transporters. While most transporters have only been tested incidentally, almost complete

functional data are available for the efﬂux transporters ABCB1 (MDR1 P-glycoprotein) and

ABCG2 (BCRP) as well as for the hepatic uptake transporters SLCO1B1 (OATP1B1), SLCO1B3

(OATP1B3), and SLC22A1 (OCT1). ABCB1 and ABCG2 have both been extensively charac-

terized over the past decades and have also been implicated in the multidrug resistance

phenotype against several cytotoxic chemotherapies [15,47,48]. They are recommended by

the US FDA to be tested during the drug development process [24]. Moreover, the organic anion

transporters OATP1B1 and OATP1B3 and organic cation transporter OCT1 are important

hepatocellular drug uptake transporters [24,49–51]. Because almost all TKIs must enter the

hepatocytes for metabolism and biliary elimination (Table 1), several studies have investigated

the involvement of these transporters in TKI uptake.

In Vitro Studies for the Identiﬁcation and Assessment of Transporters

A common and well-established method to identify whether TKIs are substrates for ABC

transporters is to use polarized cell lines recombinantly expressing the respective ABC trans-

porter in the apical membrane and to measure bidirectional TKI transport [52]. The cut-off for

signiﬁcant transport is typically a transport ratio of 2 (amount of apically directed transport

divided by the amount of basolaterally directed transport) [52]. Accordingly, all TKIs, except for

cabozantinib, ibrutinib, ruxolitinib and vandetanib, are substrates for at least ABCB1 or ABCG2

(Table 3). However, methodological issues, notably those associated with cell-based assays,

can signiﬁcantly alter in vitro study results [53], and hence there is still debate in the literature,

indicates that the same tradename is current in the USA and Europe with the following exceptions: (i) EMA refused the marketing authorization of tofacitinib on 25 July

2013; (ii) alectinib has not yet been approved by the EMA and has only recently been approved by the FDA (December 2015). The date indicates the FDA registration date,

except for nintedanib, which is only approved by the EMA for the treatment of lung cancer. (B) More than 130 novel TKIs are currently being evaluated in different clinical

phases. The pie chart shows their distribution to the neoplasms of the different organs and tissues (percentage of total). In the bar charts, the number of new TKIs in the

different clinical study phases is given. All data were taken from http://clinicaltrials.gov using the keyword ‘tyrosine kinase inhibitors’.

908 Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11

Key Figure

Tyrosine kinase inhibitor (TKI) resistance mechanisms in cancer cells (A)

and the location of membrane transporters involved in absorption, dis-

tribution, and excretion of TKIs (B–F)

(A) Mutaons TKI Lysosomal in RTK sequestraon

Decreased inﬂux Mutaons in Acvaon of TKI intracellular compensatory CYP kinase signaling pathways TKI metabolites Increased eﬄux

(B) (C) Oral dose Entero cyte

Blood SLC22 A4

SLCO2B1 Othe r SLCs TKI Enterocyte ABCC3 TKI TKI ABCB1 ABCC2 ABCG2

CYP Portal vein TKI metabolites

(D) Hepatocyte Blood SLCO1B1 TKI SLCO1B3

Bile SLCO2B1

CYP SLC22 A1

SLC22 A3 TKI metabolites To systemic Bile SLC22 A7 circulaon ABCB1 and target cells

Hepatocyte ABCC2

ABCG2 ABCC4 SLC47 A1 ABCC6

To feces

(E) Renal proximal (F) Brain

tubule cell endo thelial cell

Blood Blood

SLC22 A2

SLC22 A6 SLCO1A2

SLC22 A7 SLCO2B1 SLC22 A8

ABCB1

ABCB1 SLC47 A1 ABCC4 ABCC2 SLC47 A2 ABCG2 ABCC4

ABCG2

(See figure legend on the bottom of the next page.)

Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 909

particularly regarding bosutinib, nilotinib, and sorafenib, on whether these TKIs are indeed

transported by ABCB1. Therefore, standardization of cell-based transporter assays is urgently

required to better predict the relevance of ABC transporters for in vivo TKI disposition.

A common method to study function of uptake transporters is to determine substance accu-

mulation by transfected versus parental or nontransfected cells. A twofold-increased accu-

mulation by transfected cells is typically considered to demonstrate signiﬁcant transport [52]. In

general, accumulation ratios for TKIs are

considered to be substrates for uptake transporters according to recent recommendations [52].

Accumulation ratios 2.0 were only measured for OATP1B1 with axitinib and regorafenib, for

OATP1B3 with axitinib, and for OCT1 with dasatinib and nintedanib (Table 3). As noted above for

the in vitro analysis of ABC transporters, it appears essential to standardize cell-based uptake

transporter assays.

Furthermore, the currently investigated SLC transporters do not explain cellular TKI uptake,

suggesting that the major TKI uptake mechanisms have not yet been identiﬁed. However,

there is considerable debate as to whether substances, particularly uncharged molecules, can

cross biomembranes by passive diffusion or whether membrane transporters are required for

this process [54–57]. This discussion also applies to TKIs because several of them are

uncharged at the physiological pH of 7.4 (Table 3). Moreover, irrespective of their charge,

some TKIs, such as imatinib and sorafenib, have a high permeability in intestinal Caco-2 cells

[58,59]. Putative TKI uptake transporters are still elusive, but they should display the following

characteristics, as recently suggested for highly-permeable drugs [56]: they should be

equilibrative, have Km values in the low millimolar range, and should have high expression

levels in the apical and basolateral membranes of polarized cells. Novel strategies and

experimental techniques [45] will be necessary to discover additional transporters engaged

in cellular TKI uptake.

In addition to transporter-transfected cells, cancer cell lines are often used to study drug

transport processes [60] (Figure 3). However, the use of these cell models may be limited

because drug transporter expression can be downregulated as a result of DNA hyper-

methylation [61,62] and may not reﬂect expression in the primary tumor or in metastases

[62]. For example, the drug uptake transporter OCT2, which is localized in the basolateral

membrane of renal proximal tubule cells (Figure 2E), and whose expression is preserved

in primary clear cell renal cell carcinoma, cannot be studied in commonly used renal cell

lines because of a lack of OCT2 protein expression [62]. As a further example, human

hepatocellular carcinoma cell lines such as HepG2 lack OCT1, OATP1B1, and OATP1B3

protein expression [64,65], and their use in the preclinical drug development process is also

limited.

Figure 2. (A) Resistance mechanisms in target cells. Target cells are the tumor cells themselves or endothelial cells of tumor

vessels, either in the primary tumor or in metastases. Resistance mechanisms can be grouped into different categories:

(i) resistance by insufficient drug accumulation, for example by decreased influx or increased efflux mediated by membrane

transporters. In addition, sequestration in lysosomes has been recognized as novel mechanism that determines intracellular

levels of, for example, nilotinib, imatinib, and sunitinib [108,112,113]. (ii) Resistance by gatekeeper mutations in receptor

tyrosine kinases (RTKs) and intracellular non-RTKs is considered as the major reason that TKIs fail to inhibit their target

kinases. (iii) Resistance by the response of the cancer cell by upregulating and/or activating compensatory signaling

pathways, thereby bypassing the signaling pathway inhibited by the administered TKI. (B) Absorption, distribution,

metabolism, and excretion of TKIs. All currently approved TKIs are orally administered and therefore need to be taken

up by enterocytes and transported into portal blood. TKIs are then taken up into hepatocytes, where they are primarily

metabolized by cytochrome P450 enzymes (CYPs) and eliminated in the bile. (C–F) Location of major membrane

transporters contributing to drug uptake and efﬂux in enterocytes, hepatocytes, renal proximal tubule cells, and brain

endothelial cells. See Table 3 for alias transporter names.

910 Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 Table 1. Targeted Kinases and Pharmacokinetics of Approved TKIsa b d e f g h TKI Targeted Kinases Protein Dosage t1/2 (h) AUC (ng.h/ml) Metabolizing Enzyme Elimination (%) Bindingc

Major Minor Fecal Renal

Afatinib EGFR, HER2, HER4 95 40 mg single 37 3240–24 (69%) Covalent adducts to proteins, minimal metabolism 85 4

Alectinib ALK, RET >99 600 mg bid 33 74300–12 (46%) CYP3A4 98

Axitinib VEGFR1–3, PDGFR, KIT >99 5 mg bid 3–6 2650–24 (77%) CYP3A4/5 CYP1A2, CYP2C19, 41 23 UGT1A1

Bosutinib BCR–ABL, SRC, LYN, HCK >94 500 mg single 22.5 3650 (425) CYP3A4 91 3

Cabozantinib RET, MET, VEGFR1–3, KIT, 99.7 140 mg qd 55 37 8500–24 (43%) CYP3A4 54 27 TRKB, FLT3, AXL, TIE2

Ceritinib EML4–ALK, IGF-1R, INSR, 97 750 mg single 41 33900–24 (121) CYP3A 92 1 ROS1

Crizotinib EML4–ALK, MET, ROS1, 91 250 mg single 42 2192–2946 (27–31%) CYP3A4/5 63 22 MST1R

Dasatinib BCR–ABL, SRC, LCK, YES, 96 70 mg bid, 3.4 1390–24 (74%) CYP3A4 FMO3, UGT 85 4 FYN, KIT, EPHA2, PDGFRb after 1 day

Erlotinib EGFR 93 150 mg qd 36.2 24 9000–24 CYP3A4 CYP1A2, CYP1A1 83 8

Geﬁtinib EGFR 90 525 mg qd 37 14 300–15 7000–24 CYP3A4 CYP2D6 86 4 (35–59%)

Ibrutinib BTK 97.3 560 mg qd, 6.9 10520–24 (583) CYP3A CYP2D6 80 10 after 1 day Trends Imatinib BCR–ABL, KIT, PDGFR 95 400 mg qd 15 36 3410–24 (16 572) CYP3A4 CYP1A2, CYP2D6, 68 13 CYP2C9, CYP2C19 in

Pharmacological Lapatinib EGFR, ERBB2 >99 1250 mg qd 24 36 2000–t CYP3A4/5 CYP2C19, CYP2C8 Fecal <2 (23 400–56 000)

Lenvatinib VEGFR1–3, PDGFR/, 98–99 24 mg qd 28 3692steady-state CYP3A, AO 64 25 FGFR1–4, KIT, RET

Sciences, Nilotinib BCR–ABL, KIT, CSF1R, 98 400 mg bid, 17 53300–t (2210) CYP3A4 CYP2C8, CYP2J2, 94 5 PDGFR, DDR1 after 1 day CYP1A2

– / b November Nintedanib VEGFR1 3, PDGFR / , 97.8 150 mg single 9.5 0.8190–12,norm (68%) Esterases UGT1A1, UGT1A7, 93 1 FGFR1–3, FLT3 UGT1A8, UGT1A10

Osimertinib EGFR-T970M 99 80 mg single 48 6709steady-state (54%) CYP3A 68 14

2016, Pazopanib VEGFR1–3, PDGFR//b, >99 800 mg qd 30.9 1 037 5000–t (34%) CYP3A4 CYP1A2, CYP2C8 82 3

Vol. FGFR1/3, KIT, LCK, CSF1R,

37, ITK

No. Ponatinib BCR–ABL, BCR–ABL-T315I, 99 45 mg qd 24 12530–24 (73%) CYP3A4 CYP2C8, CYP2D6, 87 5

11 SRC, FLT3, FGFR, VEGFR, CYP3A5 PDGFR, KIT, RET, TIE2, EPH 911 912 Table 1. (continued)

TKI Targeted Kinasesb Protein Dosaged t (h)e AUCf (ng.h/ml) Metabolizing Enzymeg Elimination (%)h Trends 1/2 Bindingc in Major Minor Fecal Renal

Pharmacological Regorafenib FGFR1/2, PDGFR//b, 99.5 160 mg single 28 70 400 (35%) CYP3A4, UGT1A9 71 19 VEGFR1–3, KIT, RET, RAF1, BRAF, BRAF-V600E, ABL1, TIE2, EPH2A, MAPK11, FRK,

Sciences, NTRK1

Ruxolitinib JAK1/2 97 25 mg bid 1.9 1 335 0780–t ( 632 196) CYP3A4 CYP2C9 22 74

November Sorafenib VEGFR1–3, BRAF, BRAF- 99.5 400 mg bid 25–48 67 3000–12,steady-state (57%) CYP3A4, UGT1A9 77 19 V600E, RAF1, KIT, FLT3, RET, PDGFRb

2016, Sunitinib VEGFR1–3, PDGFR//b, KIT, 95 50 mg qd 40–60 1035–17060–24 (2–56%) CYP3A4 61 16

Vol. FLT3, CSF-1R, RET

37, Tofacitinib JAK1/3 40 5 mg bid, 3 1610–t (86) CYP3A4 CYP2C19 70 30

No. after 1 day

11 Vandetanib EGFR, RET, VEGFRs, PTK6, 90 300 mg qd 456 17 926–38 6110–24 CYP3A4, FMO1, 44 25 TIE2, EPHRs, SRCs (15–58%) FMO3

aAll data were extracted from the Labels and/or the Clinical Pharmacology Biopharmaceutics Reviews of the FDA homepage (www.accessdata.fda.gov/scripts/cder/drugsatfda/). AUC values are from reported studies on patients. bAbbreviations of kinases: ABL1, ABL proto-oncogene 1, non-receptor tyrosine kinase; ALK, anaplastic lymphoma kinase; AXL, AXL receptor tyrosine kinase; BCR–ABL, breakpoint cluster region–Abelson murine leukemia viral oncogene homolog; BRAF, B-Raf proto-oncogene, serine/threonine kinase; BTK, Bruton's tyrosine kinase; CSF1R, colony stimulating factor 1 receptor; DDR1, discoidin domain receptor 1; EGFR, epidermal growth factor receptor; EML4–ALK, echinoderm microtubule-associated protein-like 4–anaplastic lymphoma kinase; EPHA2, ephrin type-A receptor 2; EPH, ephrin receptors; ERBB2, Erb-b2 receptor tyrosine kinase 2; FGFR1–4, fibroblast growth factor receptors 1–4; FLT3, Fms-related tyrosine kinase 3; FRK, Fyn-related Src family tyrosine kinase; FYN, proto-oncogene tyrosine-protein kinase Fyn; HCK, hemopoetic cell kinase proto-oncogene, Src family tyrosine kinase; HER1–4, human epidermal growth factor receptors 1–4; IGF-1R, insulin-like growth factor 1 receptor; INSR, insulin receptor kinase; ITK, IL2 inducible T-cell kinase; JAK1–3, janus kinase 1–3; KIT, mast/stem cell growth factor receptor; LCK, Lck proto-oncogene, Src family tyrosine kinase; LYN, Lyn proto-oncogene, Src family tyrosine kinase; MAPK11, mitogen-activated protein kinase 11; MET, hepatocyte growth factor receptor; MST1R, macrophage stimulating 1 receptor; NTRK1, neurotrophic receptor tyrosine kinase 1; PDGFR, platelet-derived growth factor receptor; PTK6, protein tyrosine kinase 6; RAF1, rapidly accelerated fibrosarcoma 1 proto-oncogene, serine/threonine kinase; RET, Ret proto-oncogene receptor tyrosine kinase; ROS1, Ros proto-oncogene 1, receptor tyrosine kinase; SRC, Src proto-oncogene, non-receptor tyrosine kinase; TIE2, TEK receptor tyrosine kinase; TRKB, tropomyosin receptor kinase B; VEGFR1–3, vascular endothelial growth factor receptors 1–3; YES, Yes proto-oncogene 1, Src family tyrosine kinase. cProtein binding in %. dqd, once daily; bid, twice daily. e t1/2 , elimination half-time. fAUC, area under the plasma concentration-time curve; 0–12, from time 0 to 12 h; 0–24, from time 0 to 24 h; 0–t, from time 0 to next dosing; norm; dose-normalized; variability is given as coefficient of variation (%), as SD, or as range. gAO, aldehyde oxidase; CYP, cytochrome P450; FMO, flavin-containing monooxygenase; UGT, UDP-glucuronosyl transferase. hElimination measured as % radioactivity recovered in feces or urine after a single oral dose.

Table 2. Examples of Signiﬁcant Correlations of Pharmacokinetic Parameters with the Efﬁcacy and/or

Toxicity of Selected TKIs

b c

TKI PK Parameter Cancer Type Outcome

Efﬁcacyd Toxicity

Imatinib Ctrough CML Hematological, Hematological toxicity,

cytogenetic, rash, ﬂuid retention,

molecular response nausea, muscoskeletal pain

Ctrough GIST TTP, PFS Hematological toxicity

Ctrough GIST with KIT OOBR

exon 11 mutation

AUC0–24 free GIST CR, PR

AUC0–24 CML, GIST Number of adverse effects

Sorafenib Ctrough Solid tumors SUVmax

AUCmax Melanoma Tumor control,

PR + SD, PFS

cumulative AUC Solid tumors Grade 3 toxicity

Serum conc. >5.8 mg/ml RCC, HCC Grade 2 hand/foot

skin reaction

Serum conc. >4.8 mg/ml RCC, HCC Grade 2 hypertension

Ctrough Solid tumors Tumor response

Sunitinib Ctrough mRCC, GIST, Hypertension

solid tumors

AUC0–24 mRCC, GIST, TTP, OS, ORR, SD Neutropenia

solid tumors

Data extracted from [20,22,39,40] and references therein.

AUC, area under the plasma concentration–time curve; 0–24, from time 0 to 24 h; Ctrough, minimum (trough) concentration.

CML, chronic myeloid leukemia; GIST, gastrointestinal stromal tumor; HCC, hepatocellular carcinoma; KIT, mast/stem cell

growth factor receptor; mRCC, metastatic renal clear cell carcinoma; RCC, renal clear cell carcinoma.

CR, complete response; OOBR, overall objective beneﬁt rate; ORR, objective response rate; OS, overall survival; PFS,

progression-free survival; PR, partial response; SD, stable disease; SUVmax, maximum standardized uptake value; TTP,

time to progression.

Figure 3. Protein Expression of

ﬂ

Tis sue Selected Uptake and Ef ux Trans-

porters in Normal Human Liver and

Normal Tumor Metastasis Tumor cell lines

Kidney Compared to Respective

Tumor and Metastases as well as

Liver

↓

OATP1B1 OATP1B1 OATP1B1X Tumor Cell Lines. White boxes indicate

OATP1B3 OATP1B3 ↓ OATP1B3X expression in normal tissue or unchanged

expression in comparison to normal tis-

OCT1 OCT1 ↓ ? OCT1

X sue. Black boxes and down-arrows indi-

↓

ABCB1 ABCB1 ABCB1 cate reduced expression compared to

normal tissue. Black boxes with red

Kidney OCT2 OCT2 OCT2 OCT2

X crosses indicate lack of expression. Liver

ABCB1 ABCB1 ↓ ? ABCB1 data are from [64,65,91,150] and kidney

data from [62,151,152].

Knockout Mouse Studies To Assess the In Vivo Relevance of ABC

Transporters

A valuable tool to assess the in vivo relevance of ABC transporters are studies with mice

genetically deﬁcient for either Abcb1a/1b or Abcg2, or both Abcb1 and Abcg2 (Table 3). Abcb1

and Abcg2 are not only localized in enterocytes, hepatocytes, and renal proximal tubule cells,

Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 913 914 ﬂ

Table 3. TKIs as Substrates of Membrane Uptake and Ef ux Transporters

Trends TKI Charge at 7.4a ABC Transporterb,c

ABCB1 Abcb1a/b ABCG2 Abcg2 Abcb1/g2 ABCB11 ABCC1 ABCC2 ABCC4 in

In Vitro KO Mice in vitro KO mice KO Mice in vitro in vitro in vitro in vitro Pharmacological Afatinib +1 1.4 Y

Alectinib +0.3 <2 20 (4 h oral) <2

Axitinib 0 5.3 7.9 (4 h oral) 1.3 1.1 (4 h oral) 42.4 (4 h oral)

Sciences, Bosutinib +0.9 Y/N* N*

Cabozantinib 0 N N NN

November Ceritinib +1 22.6 38 (3 h oral) 2.3 0.5 (3 h oral) 90 (3 h oral)

Crizotinib +1 15.4 23.1 (4 h oral) 1 0.9 (4 h oral) 26.9 (4 h oral)

Dasatinib +0.3 27.7 5.7 (6 h oral) Y* 0.8 (6 h oral) 26.4 (6 h oral) 3.0 2016, Erlotinib 0 >3 1 (microd) Y* 5 (microd) 3 (microd) 1 N*

Vol. Geﬁtinib +0.2 8.4 4 (1.5 h oral) Y* 1 (1.5 h oral) 18 (1.5 h oral)

37,

Ibrutinib +0.1 0.1 No.

11 Imatinib +0.8 4.9 4.5 (2 h sc) 3.6 2.4* 0.9 (2 h sc) 2.5 (2 h iv) 64 (2 h sc) (2 h iv) 11.2 (1 h oral)

Lapatinib +0.3 15 6.4 (2 h iv) 2.6 1.3 (infus) 40–42 (infus) 3–4 (infus)

Lenvatinib 0 Y Y N

Nilotinib +0.1 1.0–5.6 Y*

Nintedanib +0.6 Y N N

Osimertinib +1 Y Y

Pazopanib 0 19.5

Ponatinib +0.8 Y Y

Regorafenib 0 1.3 1 (2 h oral) 2.7 3.7 (2 h oral) 7.9 (2 h oral)

Ruxolitinib 0 <1

Sorafenib 0 1.4–6.8 1.9 (4 h oral) 0.9 3.7 4.2 (6 h oral) 3.8 (infus) 8.7–27.8 (6 h oral) N* N* (6 h oral) 1.2 (infus) 9.7 (infus) Table 3. (continued) TKI Charge at 7.4a ABC Transporterb,c

ABCB1 Abcb1a/b ABCG2 Abcg2 Abcb1/g2 ABCB11 ABCC1 ABCC2 ABCC4 In Vitro KO Mice in vitro KO mice KO Mice in vitro in vitro in vitro in vitro

Sunitinib +1 2 2.9 (4 h oral) 2 1.3 (6 h oral) 23.4 (6 h oral) N* Y* 2.3 (6 h oral)

Tofacitinib +0.3 Y N

Vandetanib +1 1

TKI SLC Transporter (In Vitro)b,d Refse

SLCO1A2 SLCO1B1 SLCO1B3 SLCO2B1 SLC22A1 SLC22A2 SLC22A3 SLC22A4 SLC22A5 SLC22A6 SLC22A7 SLC22A8 SLC22A20 SLC47A1

Afatinib FDA

Alectinib FDA [114]

Axatinib Y Y FDA [115]

Bosutinib 1.0 [116,117]

Cabozantinib N N N N N N [118]

Ceritinib 1.3 1 1 1.4 FDA [119]

Crizotinib 1.2 1.3 [77,120]

Dasatinib 1.1 1.3 2.5 N [66,77,101, 116,121–125]

Erlotinib 1 1 1 1.5 0.6 1 0.9 0.8 1 1.6 [126–129]

Geﬁtinib 1.3 1.6 1.0–1.2 1 [77,129–132]

Ibrutinib FDA

Imatinib 1.5 1.2 1.6 1.0–1.7 1 0.9 1.1–1.6 1.0–1.4 0.9 0.8 0.9 1.4 [63,67,68,70, 123,133–139] Trends

Lapatinib [140,141] in

Lenvatinib N N N N N N FDA Pharmacological Nilotinib 1.2–1.3 1.6–2.0 1 N [77,101,116, 128,142,143]

Nintedanib NNNYN FDA

Osimertinib N N FDA Sciences,

November

2016,

Vol.

37,

No.

915 916 Table 3. (continued)

TKI SLC Transporter (In Vitro)b,d Refse Trends SLCO1A2 SLCO1B1 SLCO1B3 SLCO2B1 SLC22A1 SLC22A2 SLC22A3 SLC22A4 SLC22A5 SLC22A6 SLC22A7 SLC22A8 SLC22A20 SLC47A1 in

– –

Pharmacological Pazopanib 1.0 1.3 1.0 1.3 N FDA [77, 101,128]

Ponatinib N N N FDA

Regorafenib 2.5 1.2 [144,145]

Sciences, Ruxolitinib FDA

Sorafenib 0.9 1.0–1.5 1.0–1.5 1.1–1.3 1 1.3 1 1.2 Y* [46,59,66,74, 76,77,146–148]

November Sunitinib 1.0 1.0–1.4 0.9–1.0 1 1.1 1.1 1.2 1.2 FDA [76,77, 148,149]

Tofacitinib FDA 2016,

Vandetanib 1.1–1.3 1.4 N FDA [77,

Vol. 101,128]

37, a

Charge at pH 7.4 was calculated with MarvinSketch 15.9.14 using structures downloaded as SMILES from the PubChem compound library (http://www.ncbi.nlm.nih.gov/pccompound/). No. bAlternative/alias names of transporters: ABCB1, MDR1 P-glycoprotein; ABCG2, breast cancer resistance protein BCRP; ABCB11, bile salt export pump BSEP; ABCC1, multidrug resistance protein MRP1; ABCC2,

11 multidrug resistance protein MRP2; ABCC4, multidrug resistance protein MRP4; SLCO1A2, organic anion transporting polypeptide OATP1A2; SLCO1B1, organic anion transporting polypeptide OATP1B1; SLCO1B3, organic anion transporting polypeptide OATP1B3; SLCO2B1, organic anion transporting polypeptide OATP2B1; SLC22A1, organic cation transporter OCT1; SLC22A2, organic cation transporter OCT2; SLC22A3, organic cation transporter OCT3; SLC22A4, organic cation/zwitterion transporter OCTN1; SLC22A5, organic cation/zwitterion transporter OCTN2; SLC22A6, organic anion transporter OAT1; SLC22A7, organic anion transporter OAT2; SLC22A8, organic anion transporter OAT3; SLC22A20, organic anion transporter OAT6; SLC47A1, multidrug and toxin extrusion MATE1. cValues of in vitro studies are transport ratios (amount of apically directed transport divided by the amount of basolaterally directed transport) from bidirectional transport assays in polarized cell monolayers with transporter-transfected cells or Caco2 cells with transport inhibitors. Values of 2 are considered to reflect significant transport [52]. Y, yes but no transport ratios given; N, no but no transport ratios given; Y*, yes from accumulation studies with transporter-transfected cells; N*, no from accumulation studies with transporter-transfected cells. Values of knockout (ko) mice studies are fold TKI increase in brain accumulation or brain penetration in comparison to wild-type mice at indicated time points after oral administration (oral), intravenous injection (iv), subcutaneous application (sc), continuous infusion (infus) or microdialysis (microd). All brain accumulation data are for the respective parent TKI compound, except for the data of imatinib accumulation 2 h iv, which result from measurement of total radioactivity of imatinib and its metabolites [134]. dData are fold stimulation in uptake caused by the transporter. Values of 2 are considered to reflect significant transport [52]. Studies on knockout mice are only available for Slco1b and Slc22a1 and are discussed in the main text in the section ‘In Vitro and Knockout Mouse Studies To Assess the Role of OCT1 as a Transporter of Imatinib and Sorafenib’. eFDA: data from Clinical Pharmacology Biopharmaceutics Reviews downloaded from the FDA homepage (www.accessdata.fda.gov/scripts/cder/drugsatfda/).

but also in the luminal membrane of brain endothelial cells, where they efﬂux TKIs back into the

blood, thereby limiting TKI entry into the brain (Figure 2B–F). Therefore, in Abc transporter

knockout mice, the increase in brain accumulation of the investigated TKI in comparison to wild-

type mice reﬂects the contribution of the respective Abc transporters to TKI disposition.

Notably, these in vivo studies mainly support the results obtained by cell-based assays

(Table 3). Abcb1 appears to be more important than ABCG2/Abcg2 for brain disposition of

most TKIs, except for erlotinib, regorafenib, and sorafenib. Of interest, the combined knockout

of Abcb1 and Abcg2 often leads to a much higher TKI brain accumulation than anticipated from

the single knockouts of Abcb1 and Abcg2. This is particularly observed for axitinib, ceritinib,

dasatinib, geﬁtinib, imatinib, lapatinib, sorafenib, and sunitinib, indicating that deﬁciency of one

transporter may be compensated by the other. Notably, while complete knockout of Abcb1

and Abcg2 leads to 58-, 28- and 20-fold higher dasatinib, sorafenib and sunitinib brain

concentrations, respectively, brain accumulation is only 2.9-, 1.5-, and 2.4-fold, respectively,

in heterozygous mice that have 50% of the levels of Abcb1 and Abcg2 relative to wild-type mice

[66]. This indicates that the transport activity of each Abc transporter is apparently large enough

to sufﬁciently efﬂux either drug.

In Vitro and Knockout Mouse Studies To Assess the Role of OCT1 as a

Transporter of Imatinib and Sorafenib

OCT1 has been discussed most intensely and controversially as a transporter of imatinib [63,67–

71], and is given here as an example to demonstrate the difﬁculty of reconciling conﬂicting data

and the urgent need for standardized cell-based assays. Several in vitro studies using OCT1-

transfected HEK cells, which express functional OCT1 at high levels, detected only a 1.0- to 1.2-

fold increase of cellular imatinib uptake [63,67,69,70], indicating that OCT1 is not involved in

imatinib uptake. This is supported by in vivo studies in knockout mice in which the genetic

deﬁciency of Oct1 did not affect imatinib disposition [70]. Even so, another study detected a

1.7-fold increase of imatinib accumulation when OCT1 was overexpressed in the CML cell line

KCL22, which was interpreted as OCT1-mediated uptake [68]. However, according to recent

recommendations [52] this should not be considered as signiﬁcant transport. In addition,

imatinib uptake assays using ‘speciﬁc’ inhibitors to inhibit OCT1 function [72,73] should be

interpreted cautiously because those inhibitors are not speciﬁc for OCT1 and may also interfere

with non-OCT1-dependent imatinib uptake mechanisms [69,70].

OCT1 has also been suggested as uptake transporter for sorafenib in some studies [74,75], but

not in another study [76]. As for imatinib, accumulation ratios in OCT1-transfected HEK cells or

OCT1-expressing oocytes did not exceed 1.6, demonstrating that OCT1 does not transport

sorafenib. The accumulation ratio of sorafenib by OATP1B1- and OATP1B3-transfected cells is

also <1.5, and, consistent with this in vitro result, OATP1B1 and OATP1B3 had no role in in vivo

disposition of sorafenib in transgenic mice expressing human OATP1B1 and OATP1B3 [76,77].

By contrast, OATP1B1 and OATP1B3 both transport the sorafenib glucuronide, and therefore

are involved in the elimination of this inactive metabolite [77,78]. When OATP1B function is

compromised, higher sorafenib glucuronide levels may result, leading to an increased risk for

toxicity [77,78].

Factors Affecting Interindividual Variability of Transporter Function and

Expression in Humans

The interindividual variability of transporter function and expression is the consequence of

multiple factors, including epigenetic factors, genetic variants, and regulatory processes, as

well as non-genetic factors such as sex, age, organ function, and drug treatments [79–81]

(Figure 4). It is well documented that the concomitant administration of two or more drugs may

lead to transporter-mediated drug–drug interactions, thereby leading to altered transporter

function or expression [42,82,83]. For example, vandetanib inhibits ABCB1 and OCT2 and leads

Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 917 Sources of interindividual variability in drug response Non-genec factors Genec variaon Epigenecs Regulaon Histone Lipid Weight Very rare Transcriponal Age Diet modiﬁcaon miRNA environment Circadian Sex Starvaon rhythm Pregnancy Disease Exercise Renal Rare Post- funcon Smoking Cardiov. transcriponal funcon Occupaonal Common Traﬃcking G.I. Drugs Post- funcon Hepac DNA methylaon funcon translaonal

Transporter funcon and expression Transporter

expression Drug uptake CC CT TT Drug concentraon Transporter Immuno- Tissue genotype localizaon microarray

Pharmacokinecs Concentraon Time

Drug response Drug eﬃcacy Drug resistance Drug toxicity

Figure 4. Factors Affecting the Interindividual Variability of Transporter Function and Expression. Variability of transporter function and expression can be

explained by several different factors and processes, such as (i) non-genetic factors, including age, sex, organ function, underlying disease, and concomitant medications

potentially leading to drug–drug interactions; (ii) genetic variation, whereby very rare variants with minor-allele frequencies <0.1% account for approximately 83% of

variants, rare variants with minor-allele frequencies <1% account for 10%, and common variants with minor-allele frequencies >1% account for only 7% of total variants

[27]; (iii) epigenetic factors including DNA methylation, miRNA, and histone modiﬁcations; and (iv) regulatory processes affecting protein expression at different levels.

Altered transporter function and expression may lead to altered drug pharmacokinetics and thereby drug response. Abbreviation: G.I., gastrointestinal.

to higher plasma concentrations of simultaneously administered drugs whose elimination

depends on ABCB1, such as dabigatran or digoxin, or on OCT2, such as metformin [42].

Role of Genetic Transporter Variants in TKI Pharmacokinetics and Response in Humans

Pharmacokinetic studies with Abcb1 and Abcg2 knockout mice clearly show an important role

of these transporters for distribution of most TKIs (Table 3). Therefore, many studies have been

performed to elucidate the impact of genetic variants in human ABCB1 and ABCG2 on TKI

pharmacokinetics and TKI outcome by analyzing variants that have been studied in detail before

and that have been associated with drug response or altered expression [84] ((Table S1 in the

supplemental information online): for ABCB1, these are the three coding-sequence variants

1236C > T (rs1128503, p.G412G), 2677G > T/A (rs2032582, p.A893S/T), and 3435C > T

(rs1045642, p.I1145I), which occur at high allele frequencies in different ethnicities and create

a common haplotype [47,84]; for ABCC2, it is the promoter variant 24C > T (rs717620)

918 Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 Table 4. Effect of Genetic Variants on Pharmacokinetics and Outcome for Selected TKIs Transporter Genetic Variants Number of Ethnicity Effects on Drug PKa Signiﬁcant Effects on Drug Signiﬁcant Refs Tested (Common Patients Association Treatment Outcomea Association Name) with PK with Outcome Imatinib

ABCB1 1236C > T 87 Caucasian $ MMR No [153]

1236C > T 33 Caucasian $ response No [154]

2677G > T/A 96 Egyptian 2677TT: Yes [155] " CCR, MR

3435C > T 82 Caucasian $ Oral Cl No [31]

3435C > T 70 Iranian 3435CC: Yes [156] # CR

1236C > T 82 Korean $ Cmin No $ MMR No [33] 3435C > T

2677G > T/A 84 Caucasian 3435TT: Yes [90] 3435C > T " time to MMR

2677G > T/A 111 Indian $ Cmin No $ Thrombocytopenia No [157] 3435C > T

1236C > T 22 Australian Haplotype TTT: Yes [158] 2677G > T/A " Cl 3435C > T

1236C > T 90 Caucasian 1236TT: Yes 1236TT: " MMR Yes [159] 2677G > T/A " Cmin 2677G: # response 3435C > T Haplotype CGC:

Trends # MMR #

1236C > T 229 Mainly Caucasian 3435TT: OS Yes [160] in

Pharmacological 2677G > T/A 3435C > T

1236C > T 52 Chinese 1236TT: Yes [161] 2677G > T/A " resistance

3435C > T 2677GT: Sciences, " resistance 3435CC:

# resistance November

1236C > T 67 Japanese $ Cmin No $ MMR No [32] 2677G > T/A

2016, 3435C > T

Vol. 1236C > T 46 Caucasian 1236TT, 1236CT: Yes [162] " 2677G > T/A resistance 37,

3435C > T 2677TT: No. " resistance

3435TT: " 919 resistance

65 Caucasian Yes [163] 920 Table 4. (continued)

Transporter Genetic Variants Number of Ethnicity Effects on Drug PKa Signiﬁcant Effects on Drug Signiﬁcant Refs Trends Tested (Common Patients Association Treatment Outcomea Association Name) with PK with Outcome in

Pharmacological 1236C > T Haplotype TGC: 2677G > T/A " resistance 3435C > T

1236C > T 34 Japanese 3435CC: " Cl Yes [164]

2677G > T/A Sciences, 3435C > T

1236C > T 118 Brazilian Haplotype 1236CT/ Yes [165]

November 2677G > T/A 2677GT/3435CT: 3435C > T " MMR " 1236C > T 189 Caucasian 3435CC: CMR Yes [166] 2016, 2677G > T/A

Vol. 3435C > T

37, 1236C > T 215 Malaysian Haplotype CGC: Yes [167]

No. 2677G > T/A " resistance

11 3435C > T

1236C > T 60 Caucasian $ Cl No $ EFS No [89] 2677G > T/A 3435C > T

1236C > T 284 Korean $ Cmin No $ PFS No [168] 2677G > T/A 3435C > T

1236C > T 48 Chinese 1236TT: Yes [169] 2677G > T/A # CR 3435C > T

1236C > T 38 Asian Effect on Cl Yes $ Response No [170] 2677G > T/A 3435C > T Haplotype with OCT1 variants

ABCC2 24C > T 67 Japanese $ Cmin No $ MMR No [32] 24C > T 215 Malaysian Haplotype TGT: Yes [171] 1249G > A # CR, MR 3972C > T

ABCG2 421C > A 82 Caucasian $ Oral Cl No [31]

421C > A 67 Japanese 421CA/AA: " Cmin Yes $ MMR No [32] 421C > A 229 Mainly Caucasian " MMR Yes [172]

421C > A 15 Japanese $ Conc. in leukocytes No [17]

421C > A 34 Japanese $ Cl No [164]

421C > A 111 Indian $ Cmin No $ Thrombocytopenia No [157] Table 4. (continued) Transporter Genetic Variants Number of Ethnicity Effects on Drug PKa Signiﬁcant Effects on Drug Signiﬁcant Refs Tested (Common Patients Association Treatment Outcomea Association Name) with PK with Outcome

421C > A 100 Korean $ Cmin No $ CR No [33] 34G > A 229 Mainly Caucasian 34GG: # CCR Yes [160] 421C > A 421CA/CC: # MMR, CMR

34G > A 189 Caucasian $ MCR, CCR, No [166] 421C > A MMR, CMR

34G > A 118 Brazilian $ Response No [173] 421C > A

34G > A 215 Malaysian Haplotype AA: Yes [167] 421C > A " response

34G > A 284 Korean $ Cmin No 421 CC/CA: Yes [168] 421C > A # PFS

rs12505410 T > G 105 Caucasian Haplotype GG: Yes [174] rs2725252 T > G " rate of MMR (intron variants)

OCT1/SLC22A1 181C > T 32 Caucasian No $ MMR No [175]

480G > C 229 Caucasian 480GG: Yes [160] " rate of LOR

480G > C 33 Caucasian $ Response No [154]

1022C > T 15 Japanese $ Conc. in No [17] Trends leukocytes, Css $

1022C > T 34 Japanese Cl No [164] in

Pharmacological 1022C > T 82 Asian $ Cmin No $ CCR, MMR No [33] 1201G > A 132 Caucasian 1201GA: " MMR Yes [176]

480G > C 118 Brazilian $ Response No [173]

1222A > G Sciences,

480G > C 84 Caucasian $ Cmin No $ Response No [90] 1222A > G

November 156T > C 67 Japanese $ Cmin No 1222GG: " MMR Yes [32] 480G > C

1022C > T 2016, 1222A > G

Vol. 181C > T 74 Caucasian $ Cl No [67]

37, 1393G > A

No. 181C > T 167 Caucasian 1222AA/AG: Yes [177]

11 480G > C # median EFS, OS

921 922 Table 4. (continued)

Pharmacological 1222A > G 1503G > A

181C > T 136 Caucasian $ Response No [178] 262T > C 659G > T

Sciences, 1022C > T 1201G > A

1222A > G November 1258delATG 1393G > A

2016, 181C > T 65 Caucasian 1795AA: " overall Yes [163] 1222A > G inadequate response

Vol. 1258delATG

37, 1795G > A

No. 181C > T 189 Caucasian Combination of Yes [166]

11 480G > C variants: " MMR 848C > T 859C > G 1022C > T 1258delATG

181C > T 60 Caucasian 480CG/GG: # Cl, " Cmin Yes 480CG/GG: # EFS Yes [89] 480G > C 848C > T 859C > G 1258delATG

23 variants including 181C > T 336 Caucasian 1258delATG: " failure Yes [179] 480G > C 1222A > G 1258delATG

1022C > T 111 Indian $ Cmin No $ Thrombocytopenia No [157] 1222A > G 1386C > A

1201A > G 153 Caucasian 1275_1276 + 6T: Yes [180] 1222A > G " time to MMR 1239G > A 1239delATG 1275_1276 + 6T

Haplotype including 1222A > G 38 Asian effect on Cl Yes $ Response No [170] and ABCB1 variants

OCTN1/SLC22A4 1507C > T 189 Caucasian 1507TT: # MMR, $ CMR Yes [166]

1507C > T 54 Caucasian 1507CC/CT: " TTP Yes [181]

54 Caucasian 207GC/GG: " TTP Yes [181] Table 4. (continued) Transporter Genetic Variants Number of Ethnicity Effects on Drug PKa Signiﬁcant Effects on Drug Signiﬁcant Refs Tested (Common Patients Association Treatment Outcomea Association Name) with PK with Outcome 207C > G 2087G > C

OCTN2/SLC22A5 38T > C 94 Caucasian $ Css No [137] 516A > C

OATP1A2/SLCO1A2 361G > A 34 Japanese -361GG: # reduced Cl Yes [182]

516A > C 189 Caucasian $ MMR No [166]

361G > A 118 Brazilian $ CMR, MMR No [183] 516A > C

OATP1B3/SLCO1B3 334T > G 67 Japanese $ Cmin No $ MMR No [32] 334T > G 15 Japanese 334TT: " conc. in leukocytes Yes [17]

334T > G 86 Egyptian $ HR, CR, MR No [184]

334T > G 118 Brazilian 334TT: # CMR, $ MMR Yes [183]

Sorafenib

ABCB1 3435C > T 33 Japanese " Risk for grade 3 skin rash Yes [185]

2677G > T/A 54 Caucasian $ AUC No " Risk for grade 3 toxicity Yes [34] 3435C > T

ABCC2 24C > T 33 Japanese "Risk for grade 3 skin rash Yes [185]

ABCG2 34G > A 54 Caucasian $ AUC No " Risk for grade 3 toxicity Yes [34] 421C > A Trends 1143C > T

" in SLC15A2 rs2257212 C > T 174 Koreans PFS for CT and TT vs CC Yes [186]

Pharmacological Sunitinib

ABCB1 3435C > T 31 Asian 3435CC: " Cmin Yes 3435CC: " risk for rash, Yes [187] mucositis, disease progression

Sciences, 2677G > T/A 92 Caucasian $ AUC No [188] 3435C > T

November 1236C > T 333 Mainly Caucasian Haplotype CGT: Yes [35] 2677G > T/A " risk for HFS, " PFS 3435C > T

2016, 1236C > T 136 Caucasian Haplotype TCG: " PFS Yes [189]

Vol. 2677G > T/A

37, 3435C > T

No. 1236C > T 19 Japanese Haplotype TTT: No [190]

11 2677G > T/A $ AUC

3435C > T 923 101 Caucasian $ PFS, OS, toxicity No [191] 924 Table 4. (continued)

Pharmacological 1236C > T 2677G > T/A 3435C > T

1236C > T 88 Mainly Caucasian 1236TT: # PFS, OS Yes [192]

2677G > T/A Sciences, 3435C > T

1236C > T 96 Mainly Caucasian 1236TT: " time to Yes [193]

November 2677G > T/A dose reduction 3435C > T $ 1236C > T 65 Korean Risk for grade 3 toxicity No [194] 2016, 2677G > T/A

Vol. 3435C > T

37, 1236C > T 114 Mainly Caucasian 3435TT: " Cl Yes [195]

No. 2677G > T/A

11 3435C > T

1236C > T 97 Asian 1236T, 2677T, 3435T, haplotype Yes [196] 2677G > T/A TTT: # risk for neutropenia 3435C > T haplotype TTT: # PFS, OS

ABCG2 34G > A 136 Caucasian $ PFS No [189]

421C > A 19 Japanese 421CA, 421AA: Yes [190,197] " higher AUC, oral Cl

421C > A 101 Caucasian $ PFS, OS, toxicity No [191]

421C > A 65 Korean 421AA: " risk for grade 3 toxicity Yes [194]

421C > A 97 Asian 421AA: # risk for neutropenia Yes [196]

421C > A 219 Japanese 421A: " risk for thrombocytopenia Yes [198]

15622C > T 1143C > T 219 Caucasian Haplotype TT: " risk for Yes [199] grade 2 toxicity

15622C > T 333 Mainly Caucasian 421AA: " risk for hypertension Yes [35] 421C > A

15622C > T 114 Mainly Caucasian $ Cl No [195] 421 C > A 1143 C > T

34G > A 92 Caucasian 421AA: " higher AUC Yes [188] 421C > A 1143C > T

a Symbols and abbreviations: $, no effect; ", increased; #, decreased; C, concentration; Cmin , minimum concentration; Css, concentration at steady-state; CCR, complete cytogenetic response; Cl, clearance; CMR, complete molecular response; CR, cytogenetic response; EFS, event-free survival; HR, hematological response; LOR loss of response; MCR, major cytogenetic response; MMR, major molecular response; MR, molecular response; OS, overall survival; PK, pharmacokinetics; TTP: time to progression.

[84,85]; for ABCG2, the intron variants 15622C > T (rs559306529) and 1143C > T

(rs2622604), and the two coding sequence variants 34G > A (rs2231137, p.V12 M),

421C > A (rs2231142, p.Q141K), have been intensely studied [84,86].

Table 4 summarizes studies investigating the effects of transporter genetic variants on the

pharmacokinetics and outcome of the selected TKIs imatinib, sorafenib, and sunitinib. With

respect to the investigated ABC transporters, the clinical relevance of common genetic variants

in humans for TKI pharmacokinetics and TKI resistance appears to be limited despite the

convincing functional evidence of ABC transporters in TKI transport in vitro and in knockout

mouse experiments. Based on recent studies [27,87] it is likely that rare rather than common

transporter genetic variants will have much larger effects on TKI disposition, and their analyses

should therefore be the focus of future research. The reasons for the difﬁculty in translating the

preclinical in vitro and knockout mouse studies on ABC transporters into the clinical context are

manifold. Interpretation of pharmacogenetic association studies can be difﬁcult owing to the

complex variables involved, such as the small sample sizes in most studies, different ethnicities,

different genetic variants tested from one study to another, studying only common genetic

variants, and further confounders such as underlying disease and the presence of transporters

with redundant function. In addition, as detailed in the next paragraph, differential regulation of

ABC transporter expression may be an important reason for variable TKI responses.

Notably, despite the limited role of uptake transporters in the in vitro uptake of imatinib, in

addition to the other TKIs (Table 3), several pharmacogenetic association studies have been

performed to investigate the impact of common and rare OCT1/SLC22A1 genetic variants on

imatinib pharmacokinetics and response, as well as few studies on OCTN1/SLC22A4, OCTN2/

SLC22A5, OATP1A2/SLCO1A2, and OATP1B3/SLCO1B3 (Table 4). Here again, most studies

have focused on variants that were previously shown to have consequences for the transport of

prototypic substrates as well as for transporter expression and drug disposition [50,71,88]

(Table S1). Similarly to ﬁndings for ABC transporters, the results of these clinical studies are

ambiguous and sometimes contradictory. For example, one study detected a signiﬁcant

association between the genetic variant c.480G > C (Leu160Phe) in OCT1/SLC22A1 and

minimum imatinib plasma concentrations [89], while others did not [32,90]. No further variants

were associated with imatinib pharmacokinetic parameters. Based on the notion that cellular

imatinib uptake is independent from OCT1 (Table 3), correlations between OCT1/SLC22A1

genetics and clinical outcome of imatinib therapy are surprising, and suggest that the tested

genetic variants are not the primary cause underlying imatinib failure. Instead, it can be

postulated that those OCT1/SLC22A1 variants may be genetically linked to variants in other

genes relevant for imatinib uptake and subsequent action [70].

Role of Transporter Regulation for TKI Resistance

Transporter expression in non-tumor tissue has been investigated in great detail; however, data

on transporter expression, particularly at the protein level, in primary tumor or metastatic tissue

are sparse. Transporter expression may change during progression from normal tissue to tumor

tissue (Figure 3). For example, in histologically normal human liver, genetic variants in SLC22A1/

OCT1 cause interindividual differences in OCT1 expression [49]. However, in hepatocellular

carcinoma, epigenetic regulation of OCT1 is the predominant mechanism, and DNA methylation

of the SLC22A1/OCT1 gene leads to signiﬁcant downregulation of OCT1 mRNA and protein in

the tumor tissue [91]. Furthermore, epigenetic regulation by miRNAs has been identiﬁed as an

important regulatory mechanism of ABC transporter expression in hepatocellular carcinoma and

other cancer types [92–94].

In addition to genetic variation and epigenetics, numerous studies have identiﬁed various

regulatory mechanisms that affect transporter expression at different levels (Figure 4).

Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11 925

For example, at the transcriptional level, many drugs and xenobiotics, such as rifampin, Outstanding Questions

phenobarbital, and carbamazepine, induce hepatic expression of ABCB1 and ABCG2, as well Which membrane transporters medi-

ate the uptake of the currently

as of OATP1B1 and OATP1B3, by binding as ligands to the nuclear receptors pregnane X

approved TKIs?

receptor (PXR) and/or constitutive androstane receptor (CAR) [95–97]. Moreover, several

pathophysiological conditions such as inﬂammation or hypoxia have been shown to affect

Which membrane transporters are

ABCB1 gene expression by activating stress-induced transcription factors [97,98]. At the post- involved in the uptake and efﬂux of

transcriptional level, miRNAs have been recognized as important regulators of ABC transporter the >130 novel TKIs currently being

evaluated in clinical trials for cancer

expression [93,94]. It may be speculated that treatment with a drug leads to a distinct cellular

and other disease entities?

miRNA expression pattern and a drug-speciﬁc ABC transporter expression pattern [94]. For

example, earlier studies showed that chronic TKI exposure may lead to induction of drug efﬂux

What innovative techniques in preclini-

transporters ABCB1 and ABCG2, and thereby reduced intracellular accumulation, as shown for cal and early clinical drug testing are

necessary to enhance the study of

imatinib in the target CML cells [99]. Recent studies indeed identiﬁed an association between the

drug transport processes and TKI

downregulation of particular miRNAs and concomitant upregulation of ABCG2 expression by

resistance?

imatinib treatment of leukemic K562 cells in vitro [100].

How can systems-medicine

In addition to the above-described mechanisms affecting transporter expression, rapid regula- approaches and omics technologies

be used to identify the factors which

tion of transporter activity may occur by post-translational modiﬁcations within minutes. For

affect drug transporter expression and

example, a recent study showed that phosphorylation of OCT2 by the Src family kinase Yes1 is

function and which predict tumor

essential for OCT2 transport function [101]. Inhibition of Yes1 by TKIs including dasatinib

response or resistance?

resulted in reduced OCT2 function in vitro and in vivo [101]. Other post-translational modiﬁca-

tions include glycosylation, which is apparently required for proper trafﬁcking of ABCB1 to the How can an improved understanding

of the molecular basis of drug resis-

plasma membrane or for protein stability, without affecting transport function [102]. Moreover,

tance help to devise rational drug com-

interacting proteins may be required for targeting of transporters to the plasma membrane [102].

binations for selected patient

Finally, the lipid environment of the membrane, in which the transporters are embedded, and populations or individual patients?

transporter–lipid interactions have been identiﬁed as important determinants of ABCB1 and

ABCG2 expression and function [103].

These numerous studies demonstrate the variety of regulatory processes by which transporter

expression and function can be modulated. However, much more work will be necessary to fully

explore all these different aspects of regulation, not only in non-tumor but also in tumor tissues,

and their role in TKI resistance.

Concluding Remarks and Future Directions

Small-molecule TKIs have emerged as the backbone of cancer therapy and the treatment of

other diseases. However, in contrast to the remarkable success of imatinib in the improvement

of outcome of patients with CML, the degree of success of other TKIs is variable, and most

achieve only moderate survival beneﬁts. Similar to the situation when using conventional

cytotoxic chemotherapy, the occurrence of drug resistance often counteracts successful

treatment. In addition to somatic variation of the targeted tyrosine kinases, insufﬁcient drug

exposure may signiﬁcantly contribute to drug resistance. Drug uptake and efﬂux transporters in

enterocytes, hepatocytes, proximal tubule kidney epithelial cells, and not least in the cancer cells

themselves, may preclude sufﬁcient intracellular TKI accumulation.

While the role of ABC efﬂux transporters in in vitro transport and in vivo disposition in knockout

mice has been established for most TKIs, their role in TKI disposition and occurrence of drug

resistance in humans – as assessed by pharmacogenetic association studies – is less clear. As a

consequence, future research is warranted to include not only rare variants but also a compre-

hensive deﬁnition of clinical phenotypes based on representative and valid sample sizes [104].

Moreover, the currently identiﬁed and investigated uptake transporters play apparently only a

minor role in TKI uptake (see Outstanding Questions). Therefore, novel techniques such as

thermal proteomics proﬁling [105,106] will be necessary to identify novel transporters engaged in

TKI uptake. Once these are identiﬁed, the contributions of non-genetic, epigenetic, and common

926 Trends in Pharmacological Sciences, November 2016, Vol. 37, No. 11

and rare genetic variants in these transporter genes on the function and expression of the

transporters need to be assessed. In this context, it will be important to study transporter

expression not only in the primary tumor but also in metastases because therapeutic responses

to TKI may differ. As recently demonstrated for clear cell renal cell carcinoma, drug transporter

expression was shared between primary tumors and metastases, indicating comparable drug

transport processes and drug effects in tumors and metastases [62]. However, this may be

different for other tumor entities and needs to be investigated.

Because cell lines often do not correspond to the conditions in primary tumors or metastases in

vivo [62], other innovative techniques such as patient-derived tumor grafts (PDx) may be used to

study drug transport processes [107]. Furthermore, novel imaging techniques such as hyper-

spectral stimulated Raman scattering [108] and PET imaging with TKIs [109] will help to track

and quantify intracellular TKI concentrations in vivo to improve TKI efﬁcacy.

Moreover, owing to the large number of factors (non-genetic, genetic, epigenetic, regulatory)

that may affect transporter expression and function, systems-medicine approaches and omics

technologies [79] will be required for identifying novel mechanisms of drug resistance, including

drug transporters, as well as molecular signatures and genotypes that may predict tumor

response or resistance. This improved understanding of the molecular basis of drug resistance

will foster the design of rational drug combinations for selected patient populations. This is of

particular importance in view of the fact that currently >130 novel TKIs are being evaluated in

clinical trials (Figure 1B), not only for the treatment of cancer but also for other disease entities.

It can be expected that these strategies of identifying drug transporters and resistance mecha-

nisms will also be important when inhibitors for kinases other than tyrosine kinases are clinically

developed [110], as well as for novel classes of anticancer agents such as small-molecule checkpoint inhibitors [111].

Acknowledgments

This work was supported in part by the Robert-Bosch Foundation, Stuttgart, Germany, the Interfaculty Centre for

Pharmacogenomics and Pharma Research (ICEPHA) Grant Tübingen–Stuttgart, Germany, the Bundesministerium für

Bildung und Forschung, Germany (LiSyM 031L0037) and European Commission Horizon 2020 UPGx grant (668353). The

authors thank Bernd Borstel for drafting the ﬁgures.

Supplemental Information

Supplemental information associated with this article can be found online at http://dx.doi.org/10.1016/j.tips.2016.08.003.

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