Comparison of the drug-drug interactions potential of ibrutinib and
acalabrutinib via inhibition of UDP-glucuronosyltransferase
Xiaoyu Wang a
, Zhe Wang a
, Xiaoyu Fan a
, Mingrui Yan a
, Lili Jiang a
, Yangliu Xia a
, Jun Cao b,**,
Yong Liu a,*
a School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin 124221, China b Department of Occupational and Environmental Health, Dalian Medical University, Dalian 116044, China
ARTICLE INFO
Keywords:
Ibrutinib
Acalabrutinib
UDP-glucuronosyltransferase
Drug-drug interaction
ABSTRACT
Ibrutinib and acalabrutinib are two Bruton’s tyrosine kinase (BTK) inhibitors which have gained Food and Drug
Administration (FDA) approval for the treatment of various B cell malignancies. Herein, we investigated the
effects of the two drugs on UDP-glucuronosyltransferase (UGT) activities to evaluate their potential risk for drugdrug interactions (DDIs) via UGT inhibition. Our data indicated that ibrutinib exerted broad inhibition on most of
UGTs, including a potent competitive inhibition against UGT1A1 with a Ki value of 0.90 ± 0.03 μM, a
noncompetitive inhibition against UGT1A3 and UGT1A7 with Ki values of 0.88 ± 0.03 μM and 2.52 ± 0.23 μM,
respectively, while acalabrutinib only exhibited weak UGT inhibition towards all tested UGT isoforms. DDI risk
prediction suggested that the inhibition against UGT1A1 and UGT1A3 by ibrutinib might bring a potential DDIs
risk, while acalabrutinib was unlikely to trigger clinically significant UGT-mediated DDIs due to its weak effects.
Our study raises an alarm bell about potential DDI risk associated with ibrutinib, however, the extrapolation
from in vitro data to in vivo drug interactions should be taken with caution, and additional systemic study is
needed.
1. Introduction
Ibrutinib and acalabrutinib are two oral small-molecule Bruton’s
tyrosine kinase (BTK) inhibitors approved for the treatment of adult
patients with chronic lymphocytic leukemia (CLL) and mantle cell
lymphoma (MCL) by blocking B-cell receptor signaling pathway to
induce tumor cell death (Advani et al., 2013; Byrd et al., 2016). Phase III
trials of both two drugs are currently underway worldwide to evaluate
their treatment effects and give more combinations of drugs, meaning
that drug-drug interactions (DDIs) may first be encountered during
clinical development (Cameron and Sanford, 2014; Markham and
Dhillon, 2018). Previous study has suggested that co-administration
acalabrutinib with itraconazole, a cytochrome P450 (CYP) 3A inhibitor, will be expected to increase its plasma concentrations which may
result in toxicity (Zhou et al., 2019). Co-treatment with ketoconazole (a
known CYP3A inhibitor) will increase the Cmax and AUC of ibrutinib by
29- and 24-fold, respectively, so that lead to potential adverse events at
therapeutic dose (de Zwart et al., 2016). Therefore, DDIs based on drug
metabolizing enzyme remain a problem of considerable clinical
significance.
In addition to giving focus on CYP enzyme driving DDIs, indeed,
UDP-glycosyltransferase (UGT) inhibition could also be implicated in
hepatotoxicity and associated with clinically DDIs (Meech et al., 2019).
UGT is an important class of phase II metabolizing enzyme superfamily
which plays a critical role in the elimination of numerous exogenous
chemicals and endogenous substances and in the pathological procedures of some diseases (Zhou et al., 2013). Particularly, UGT1A1, for
which participates in bilirubin glucuronidation and has a high level of
polymorphism, is a major concern. Several tyrosine kinase inhibitors
(TKIs) have been observed as potent UGT inhibitors implying a risk for
adverse DDIs in clinic. For example, concomitant administration of
gefitinib (700 mg/day) and irinotecan may increase the SN-38 AUC by
* Correspondence to: Y. Liu, School of Life and Pharmaceutical Sciences, Dalian University of Technology, 2 Dagong Road, Liaodongwan New District, Panjin
124221, China.
** Correspondence to: J. Cao, Department of Occupational and Environmental Health, Dalian Medical University, No. 9 W. Lvshun South Road, Dalian 116044,
China.
E-mail addresses: [email protected] (J. Cao), [email protected] (Y. Liu).
Contents lists available at ScienceDirect
Toxicology and Applied Pharmacology
journal homepage: www.elsevier.com/locate/taap
https://doi.org/10.1016/j.taap.2021.115595
Received 31 January 2021; Received in revised form 18 May 2021; Accepted 21 May 2021
Toxicology and Applied Pharmacology 424 (2021) 115595
49% via UGT1A1 inhibition (Li et al., 2015). Regorafenib and sorafenib
can potently inhibit UGT1A1 activity, which contributed significantly to
the hyperbilirubinemia observed in patients (Miners et al., 2017).
However, the issue of prediction of DDIs risk by acalabrutinib and
ibrutinib via UGT inhibition is far from exhaustive.
Here, we aimed to evaluate the inhibitory effects of two BTK inhibitors ibrutinib and acalabrutinib towards the activity of 12 human
recombinant UGT isoforms and identify the potential DDIs in vivo based
on in vitro-in vivo extrapolation (IVIVE). These results provide a new
sight for explanation of the toxicity of BTK-TKIs and might be helpful to
develop new clinical combination therapies.
2. Materials and methods
2.1. Chemical reagents
Ibrutinib, acalabrutinib, and trifluoperazine (TFP) were obtained
from Selleck Chemicals (Houston, TX, USA), umbelliferone, 4-methylumbelliferone (4-MU), 4-methylumbelliferone-β-D-glucuronide (4-
MUG), and uridine 5′
-diphosphoglucuronic acid trisodium salt (UDPGA)
were obtained from Sigma-Aldrich (St. Louis, MO, USA). Tris-HCl,
MgCl2 were purchased from Aladdin (Shanghai, China). All other
chemicals used were of HPLC grade commercially available.
Recombinant UGT supersomes (UGT1A1, UGT1A3, UGT1A4,
UGT1A6, UGT1A7, UGT1A8, UGT1A9, UGT1A10, UGT2B4, UGT2B7,
UGT2B15, and UGT2B17) were purchased from Corning Gentest
(Tewksbury, MA, USA).
2.2. Inhibition of recombinant human UGT enzymes by BTK inhibitors
The incubation systems were conducted in a final volume of 200 μL
in 50 mM Tris-HCl buffer (pH 7.4) with 10 mM MgCl2, 5 mM UDPGA,
UGTs and 4-MU. Ibrutinib and acalabrutinib (structures are shown in
Fig. 1) were dissolved in DMSO. The linear initial velocity enzymatic
conditions were used as described previously (Wang et al., 2020). Reactions were pre-incubated for 5 min at 37 ◦C and initiated by addition
of 20 μL UDPGA. Enzymatic reactions were terminated by adding equal
volume of ice-cold acetonitrile containing 1 μM umbelliferone as an
internal standard. Samples were centrifuged at 20,050g for 20 min at
4 ◦C to remove the protein.
Detection of 4-MUG was performed by ultra-performance liquid
chromatography-tandem mass spectrometry (UPLC-MS/MS) system
consisting of ACQUITY UPLC module (Waters, Milford, MA) and Qtrap
6500 (SCIEX, San Jose, CA, USA). Aliquot 2 μL of each sample was
injected on a BEH C18 column (50 × 2.1 mm, 1.7 μm). The mobile phase
was consisted of solvent A (0.1% formic acid in water) and solvent B
(0.1% formic acid in acetonitrile) with a flow rate of 0.3 mL/min. The
gradient was used as follows: 5% (v/v) B at 0–2 min, 5%–50% (v/v) B at
2–2.4 min, 50% (v/v) B at 2.4–3 min, 50%–5% (v/v) B at 3–4 min, 5%
(v/v) B at 4–5 min. The MRM m/z transitions monitored were 353.3/
177.2 for 4-MUG and 163.1/107.1 for internal standard in positive ion
mode which were identified to be optimal for quantitative analysis.
Calibration standard of 4-MUG was prepared at concentrations of
0.125–15 μM and the accuracy was within 10%.
In addition, trifluoperazine (TFP) was used as the selective substrate
in the UGT1A4 inhibition studies (Uchaipichat et al., 2006) and the
supernatant of reactions were separated by HPLC system (Waters, Milford, MA) with a Tnature C18 column (250 × 4.6 mm, 5 μm). Mobile
phase was containing 0.5% formic acid in water (A) and acetonitrile (B).
A gradient program was as follows: 29–48% (v/v) B at 0–7 min, 48%–
29% (v/v) B at 7.0–7.5 min, 29% (v/v) B at 7.5–9 min. The flow rate was
maintained at 1 mL/min and analytes were quantified with UV detection
at 254 nm. Umbelliferone (18 μM) was used as the internal standard.
Calibration standard of TFP was prepared at concentrations of 0.025–10
μM since no TFP-G standards were available (Seo et al., 2014).
2.3. Determination of IC50 and Ki
The same incubation condition as for the preliminary inhibition
study was used for each UGT isoform. The relative formation rate of 4-
MUG or TFP-G in the presence vs. absence of inhibitors was estimated.
For UGT isoforms whose activity is inhibited by >50% by individual
BTK inhibitors, half maximal inhibitory concentration (IC50) values for
TKIs were determined. Subsequent inhibition kinetic experiments were
performed for the lower IC50 values groups. The most appropriate inhibition type and Ki value were ascertained from comparison of
goodness-of-fit parameters using equations for competitive inhibition
(eq. 1), noncompetitive inhibition (eq. 2), uncompetitive (eq. 3), or
mixed inhibition (eq. 4).
v = (VmaxS)/(Km(1 + I/Ki) + S ) (1)
v = (VmaxS)/(Km + S)(1 + I/Ki) (2)
v = (VmaxS)/(Km + (1 + I/Ki)S ) (3)
v = (VmaxS)/[Km(1 + I/Ki) + S(1 + I/αKi)] (4)
where v is the velocity of the reaction, Vmax is the maximum velocity, S
and I are the substrate and inhibitor concentrations, respectively. Km is
Michaelis constant (the substrate concentration at half of the Vmax of the
reaction), Ki is inhibition constant. α reflects the effect of inhibitor on the
affinity of the enzyme for its substrate.
2.4. Predicted concentrations of TKIs at UGT active site
For IVIVE, the inhibitor concentrations ([I]) after oral administration
can be calculated using the following equation: average systemic plasma
concentration ([I]av) (eq.5), maximum systemic plasma concentration
([I]max) (eq.6), and maximum hepatic input concentration ([I]in) (eq.7)
to evaluate the highest risk (Ito et al., 2004). )
where D and τ are oral dose and dosing interval, respectively, CL/F is
apparent (oral) drug clearance, k is the elimination rate constant which
is expressed as k = 0.693/t1/2 (t1/2, half time), ka is the absorption rate
constant, Fa is the fraction absorbed from gut into the portal vein, and Qh
Fig. 1. Chemical structures of ibrutinib and acalabrutinib.
X. Wang et al.
Toxicology and Applied Pharmacology 424 (2021) 115595
is the hepatic blood flow rate, assumed to be 1450 mL/min (Davies and
Morris, 1993). The parameters of CL/F, t1/2, ka and Fa obtained from
previous publications for ibrutinib (Pharmacyclics Inc, 2013; de Jong
et al., 2015; Marostica et al., 2015) and acalabrutinib (Markham and
Dhillon, 2018; Zhou et al., 2019) were shown in Table 2.
2.5. Prediction of in vivo drug–drug interactions magnitude
The potential DDIs risk arising from inhibition of a drug metabolizing
enzyme can be determined from the Ki value generated in vitro using the
following equations (eq.8) for drugs with negligible renal clearance
(Miners et al., 2010).
AUCi/AUC = 1/(fm/(1 + [I]/Ki ) + (1 − fm) (8)
where the victim drug is metabolized by a single enzyme or has a high
hepatic clearance (fm assumed as 1), eq. (8) simplifies to
AUCi/AUC = 1 + [I]/Ki (9)
where AUCi/AUC is the ratio of areas under the plasma concentration
against time of the victim drug in the presence and absence of the inhibitor and fm is the fraction of UGT substrates metabolized by the
inhibited enzyme which ranged of 0.1–1. Here, [I]in was used to predict
the highest potential risk from the perspective of pharmacokinetics
theory (Oda et al., 2015). As for UGT1A7, only expressed in extrahepatic
tissues (Strassburg et al., 1997), [I]max was used to represent the inhibitor concentrations at UGT enzyme active site.
In the present analysis, the DDIs potential for ibrutinib and acalabrutinib were evaluated by calculating the AUC ratios. The FDA draft
guidance on drug interaction studies proposes that a 25% increase in the
AUC of victim drugs, which is normally considered to be bioequivalent,
should not merit full consideration for clinically relevant DDIs (Yu and
Tweedie, 2013). As such, the AUC ratio cut-off value of 1.25 was used
according to the FDA Guidance (USFDA, 2020) and interactions with
AUC ratio changes more than 5-fold, 2-to 5-fold, or 1.25-to 2-fold were
considered strong, moderate, or weak inhibition drug interactions,
respectively (Yu et al., 2019).
3. Results
3.1. Inhibition of UGT activities by ibrutinib and acalabrutinib
The inhibitory effects of ibrutinib and acalabrutinib on UGT activities were shown in Fig. 2. Ibrutinib (100 μM) inhibited almost all the
Fig. 2. The inhibition of ibrutinib and acalabrutinib towards human recombinant UGT isoforms. TFP was used as substrate for the inhibition studies with UGT1A4, 4-
MU was used as the substrate for all other UGT isoforms. Each bar represents the mean ± standard error of duplicate experiments.
X. Wang et al.
Toxicology and Applied Pharmacology 424 (2021) 115595
UGTs in reducing the substrate glucuronidation more than 70%. The
inhibition of acalabrutinib was observed against UGT1A1, 1A3, 1A7,
and 2B15 with corresponding residual activities were 48.68%, 28.57%,
28.13%, and 11.8%, respectively. To further investigate the inhibitory
potentials of both two BTK-inhibitors, IC50 values were further determined and corresponding inhibition curves of ibrutinib and acalabrutinib were shown in Figs. 3 and 4, respectively. As shown in Table 1,
ibrutinib potently inhibited the enzyme activities of UGT1A1 (IC50 0.70
± 0.05 μM), UGT1A3 (IC50 0.79 ± 0.05 μM), and UGT1A7 (IC50 1.05 ±
0.01 μM) (Fig. 3), and moderately inhibited of UGT1A9 (IC50 11.69 ±
0.48 μM), and UGT2B7 (6.94 ± 0.08 μM), weakly inhibited of other UGT
isoforms which IC50 values ranged from 13.65 to 80.84 μM. Meanwhile,
acalabrutinib demonstrated moderate or slight inhibition of UGT1A1,
1A3, 1A7 and UGT2B15 activities with IC50 values ranged from 8.54 to
27.62 μM, since these values are more than an order of magnitude higher
than the reported Cmax (0.69 μM) (Markham and Dhillon, 2018), and
hence Ki was not determined but estimated based on the equation Ki =
1/2 × IC50, assuming competitive inhibition (Haupt et al., 2015).
Fig. 3. Concentration-dependent inhibition of ibrutinib in recombinant human UGTs.
Fig. 4. Concentration-dependent inhibition of acalabrutinib in recombinant human UGT1A1, UGT1A3, UGT1A7, and UGT2B15.
Table 1
The IC50 of ibrutinib, acalabrutinib for the inhibition against UGT activities.
UGTs Ibrutinib (μM) Acalabrutinib (μM)
UGT1A1 0.70 ± 0.05 17.89 ± 0.72
UGT1A3 0.79 ± 0.05 8.54 ± 0.75
UGT1A4 20.26 ± 0.41 > 100
UGT1A6 24.92 ± 0.93 > 100
UGT1A7 1.05 ± 0.01 27.62 ± 2.08
UGT1A8 16.19 ± 0.71 > 100
UGT1A9 11.69 ± 0.48 > 100
UGT1A10 13.65 ± 0.11 > 100
UGT2B4 80.84 ± 4.07 > 100
UGT2B7 6.94 ± 0.08 > 100
UGT2B15 21.84 ± 0.53 19.84 ± 0.13
UGT2B17 26.08 ± 4.56 > 100
Data represent the mean ± standard error of duplicates experiments.
X. Wang et al.
Toxicology and Applied Pharmacology 424 (2021) 115595
Fig. 5. Representative Lineweaver-Burk plots and Dixon plots for the inhibition of.
4-MU glucuronidation by ibrutinib in human recombinant UGT1A1(A and B), UGT1A3(C and D), UGT1A7(E and F). All data points shown represent the mean ±
standard error of duplicate measurements.
X. Wang et al.
Toxicology and Applied Pharmacology 424 (2021) 115595
3.2. Inhibition kinetics in recombinant human UGTs by ibrutinib
Kinetic experiments were performed to further characterize the inhibition of UGT1A1, UGT1A3 and UGT1A7 activities by ibrutinib
(Fig. 5). Nonlinear regression analysis indicated that 4-MU glucuronidation in UGT1A1 was greatly inhibited by ibrutinib in a competitive
manner with a Ki value of 0.90 ± 0.03 μM, whereas inhibition of
UGT1A3 and UGT1A7 followed noncompetitive inhibition mechanism
with Ki values of 0.88 ± 0.03 and 2.52 ± 0.23 μM, respectively.
3.3. Quantitative prediction of DDIs potential risk
The calculated concentrations of [I]in and [I]max of ibrutinib and
acalabrutinib were shown in Table 2. Then the prediction results for
each TKI were calculated by eq. (8) and reported as isolines plot in
Figs. 6 and 7, respectively. Values in the line represented the AUC ratio
(AUCi/AUC) and an isoline was joining equal values of AUC ratio
generated from the corresponding oral dose and fm.
As shown in Fig. 6A, when the oral dose of ibrutinib is 560 mg/day,
co-administered substrate is mainly metabolized by UGT1A1 (fm > 0.8),
the predicted AUC ratio is approximately 2.40, which means that an
increase in the AUC of substrate of more than 140% might be observed
when substrates are co-administrated with ibrutinib. Also, when the
dose is more than 560 mg/day and fm is 1, the predicted AUC ratio is
3.05 (Fig. 6B), which means that the AUC of substrate totally metabolized by UGT1A3 will increase more than 2-fold in vivo. Specifically,
when the dose of ibrutinib was 280 mg/day and fm was more than 0.4,
the AUC ratio of victim drug cleared by UGT1A1 or UGT1A3 were
increased by at least 1.34, which indicated a clinically relevant DDI
potential for both UGT isoforms substrate. However, even when
Table 2
Calculation of possible concentrations of ibrutinib and acalabrutinib.
Drugs Ibrutinib Acalabrutinib
Dose (mg) 560 200
Dosing Interval (hr) 24 12
Cmax (μM) 0.29 0.69
Absorption Rate Constant (ka, h− 1
) 0.46 1.65
Plasma Unbound Fraction (fu,p) 2.70% 2.50%
t1/2 (h) 4 1.57
CL/F (L/h) 1060 159
Oral bioavailability (F) 67% 25%
Calculated concentrations Iav (μM) 0.05 0.23
Imax (μM) 0.21 1.20
Iin (μM) 2.05 1.17
Fig. 6. Isolines plots for relationship of AUC ratio against oral dose of ibrutinib and fm by UGT1A1 (A), UGT1A3 (B), and UGT1A7 (C) for DDI study. An isoline was
joining equal points, values in each line represent the AUC ratio (AUCi/AUC) calculated by the eq. (8) according to the corresponding oral dose of ibrutinib and fm.
X. Wang et al.
Toxicology and Applied Pharmacology 424 (2021) 115595
administered at the highest dose (700 mg/day) and an fm is 1, the AUC
ratio is 1.10 (less than the cut-off value 1.25) for the substrates metabolized by UGT1A7 (Fig. 6C), indicating minor clinical impacts on the
pharmacokinetics of UGT1A7 substrates. Consequently, ibrutinib is
likely to result into the potential for clinically significant DDIs when coadministered with UGT1A1, or UGT1A3 substrates through inhibition of
glucuronidation.
In this study, we assumed the Ki values of UGT1A1,1A3, and 1A7 by
acalabrutinib were 4.27, 8.56, and 13.81 μM, respectively. As shown in
Fig. 7, when administered acalabrutinib at the recommended dose of
200 mg/day and fm is 1, the AUC ratio of victim drugs cleared by
UGT1A1,1A3 and 1A7 are increased by 1.28, 1.14 and 1.09-fold,
respectively, which indicated that acalabrutinib could not bring the
evident changes in the AUC of the victim drugs.
4. Discussion
The advent of BTK inhibitors ibrutinib and acalabrutinib represents a
major breakthrough in the treatment of CLL and other B cell malignancies (Sibaud et al., 2020). However, the coadministration with a
range of concomitant treatments is expected to under the high risks of
DDIs. As these kinds of events are by nature essentially unprevented,
there is an urgent need for carefully evaluation of the clinical DDIs potential based on methodology and modeling methods in vitro to recognize whether adjust dose regiments (Tornio et al., 2019). It has been
reported that strong inhibitors or inducers of CYP3A may have a relevant effect on the PK of both two drugs and lead to a series of adverse
events, the effects on human UGTs still need further discussed. Previous
study revealed the inhibitory effects of ibrutinib on UGT enzymes and
gave the prediction of DDIs risk of UGT1A1, 1A4 and 1A9 (Korprasertthaworn et al., 2019). In the current study, our data offered evidence
that potent inhibition against UGT1A1 and UGT1A3 by ibrutinib might
increase the risk of clinically significant DDIs when UGT1A1, or
UGT1A3 substrates were co-administered. Acalabrutinib was unlikely to
trigger clinically significant DDIs through UGT inhibition due to its weak
effects.
UGT1A1 is the only enzyme that metabolized bilirubin and facilitates
its elimination from the body (Bosma et al., 1994). Inhibition of UGT1A1
by ibrutinib may cause hyperbilirubinemia in vivo. This result might
provide a better understanding about ibrutinib-induced acute liver
injury which initially characterized by marked elevations of bilirubin
levels (Nandikolla et al., 2017; Tafesh et al., 2019). Indeed, several TKIs
such as erlotinib, nilotinib, pazopanib, vemurafenib with potent inhibitory effect on UGT1A1 have been reported to have a high incidence of
Fig. 7. Isolines plots for relationship of AUC ratio against oral dose of acalabrutinib and fm by UGT1A1 (A), UGT1A3 (B), and UGT1A7 (C) for DDI study. An isoline
was joining equal points, values in each line represent the AUC ratio (AUCi/AUC) calculated by the eq. (8) according to the corresponding oral dose of acalabrutinib
and fm.
X. Wang et al.
Toxicology and Applied Pharmacology 424 (2021) 115595
hyperbilirubinemia (Qosa et al., 2018). Particularly, pazopanib inhibited UGT1A1-mediated SN-38 (active metabolite of irinotecan) glucuronidation and increased SN-38 AUC in recombinant human UGT1A1
Supersomes by a factor of 2.2 (Iwase et al., 2019). These results were
comparable to the ~90% increase in the AUC of SN-38 clinically
observed in patients who received 800 mg pazopanib once daily (Bennouna et al., 2015). The prediction from in vitro data demonstrated that
atazanavir (a potent UGT1A1 inhibitor) increased in molidustat AUC of
2.9-fold. In the clinical DDI study, a 2-fold increase of AUC for molidustat was also observed when pre- and co-treatment with atazanavir
which helps to confirm the assumptions made from the in vitro-in vivo
correlation(van der Mey et al., 2021). In addition, common genetic
polymorphisms of UGT1A1*28 will lead to lower drug clearance and
have an increased risk of DDIs. Therefore, co-administered of antineoplastic agents with a narrow therapeutic index such as etoposide and
irinotecan could result in excessive cytotoxic drugs exposure even a
slight increase of AUC(Wen et al., 2007) (Ichikawa et al., 2008). Taken
together, more attention should be paid when ibrutinib is coadministered with UGT1A1 substrates which may cause a buildup of
endogenous substances or toxic drug levels.
UGT1A3 is mainly responsible for metabolizing nonsteroidal antiinflammatory drugs (NSAIDs) and some important endogenous substances, such as bile acids, estrogens (Lepine et al., 2004; Kuehl et al.,
2005). Inhibition of UGT1A3 might affect the conjugation of chenodeoxycholic acid and thus to cholestasis (Trottier et al., 2006). Prior
studies have noted that cholestatic features were shown in patients with
severe acute liver injury after ibrutinib treatment (Tafesh et al., 2019).
Additionally, UGT1A3 activity is subject to about 60-fold interindividual variability, implying increased clinical risks such as significant variations of plasma concentrations and subsequent toxicity (Izukawa et al., 2009). Evidence suggested that the observed increase in
atorvastatin lactonization in carriers of one or two UGT1A3*2 alleles,
was the result of the strong increase in UGT1A3 expression. Also, data
demonstrated that UGT1A3*2 genotype has a very substantial increase
in mRNA (5-fold) and protein (7.3-fold) in the human liver (Riedmaier
et al., 2010).Therefore, it is conceivable that individuals with
UGT1A3*2/*2 may endure the toxic side effects caused by atorvastatin
lactone. In addition, UGT1A3 has been reported to catalyze the glucuronidation of ibuprofen and ketoprofen (Sakaguchi et al., 2004), so it
represents bleeding risk whilst taking ibrutinib with anti-inflammatory
drugs. Although the level of UGT1A3 expression in human liver is
much lower than that of other UGT1A isoforms(Green et al., 1998), the
co-administrated ibrutinib with xenobiotic/drug mainly cleared by
UGT1A3 needs to be taken additional caution.
Since UGT1A7 is an important extra-hepatic UGT isoform that influences the disposition of drugs within the gut (Court et al., 2012) and
plays a prominent role in the detoxification of tobacco carcinogens
benzo(α)pyrene (Fang et al., 2002). Previous study has described a
striking correlation between the UGT1A7 genotypes and the occurrence
of irinotecan-induced toxicity that inhibition of UGT1A7-medicated
glucuronidation pathway in the gut may predispose for irinotecaninduced diarrhea (Carlini et al., 2005). Additionally, it was reported
that variations in the UGT1A7 gene that reduce UGT1A7 activity may
increase the risk of smoking-related orolaryngeal cancer (Zheng et al.,
2001). A meta-analysis also demonstrated that individuals with
UGT1A7*3 allele (intermediate, and low activity UGT1A7 genotypes)
were involved in a high risk of cancer (Lu et al., 2011). It can be
anticipated that inhibition of UGT1A7 and UGT1A7*3 genotype in vivo
deserved more attention. Although the degree of DDIs risk via UGT1A7
inhibition is low in our prediction, the potent inhibition of ibrutinib on
UGT1A7 in the gut is still noteworthy.
There are several limitations to this study. First, DDIs risk based-on
IVIVE approach would be regarded as an initial discriminating screen,
therefore, prediction from in vitro data to in vivo drug interactions must
be taken with caution (Ito et al., 2004). Moreover, variable factors such
as transporters, various metabolic enzymes, the extrinsic factors (diet,
smoking) and diseases, will need consideration to progress the prediction towards a quantitative basis (Rostami-Hodjegan and Tucker, 2007).
Thus, assessing DDIs involving UGT inhibition remains challenging.
However, this research was a preliminary study. Further mechanistic
and clinical studies still need to be performed to gain more accurate
evaluation of DDIs potential associated with ibrutinib and acalabrutinib.
In conclusion, results from this research provide essential information about the inhibition of ibrutinib and acalabrutinib towards UGTs
isoforms and evaluate the possible DDIs risk. The present findings raise
an alarm bell about potential DDI risk associated with ibrutinib, however, the extrapolation from in vitro data to in vivo drug interactions
should be taken with caution, and additional systemic study is needed.
Declaration of Competing Interest
The authors declare that there is no conflict of interests regarding the
publication of this article.
Acknowledgements
This study was financially supported by the National Key Research
and Development Program of China (2017YFC1702006), the Fundamental Research Funds for the Central Universities (DUT21LK11).
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