Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of UK Essays.
Multidrug resistance (MDR) is the phenomenon that cancer cells are simultaneously resistant against several structurally and mechanistically unrelated drugs and these drugs are not effective in killing the cells. The development of MDR to chemotherapy remains a major challenge in the treatment of cancer. Numerous mechanisms including overexpression of energy-dependent efflux proteins, decreased drug uptake, increased drug efﬂux, activation of detoxifying systems, activation of DNA repair mechanisms, evasion of drug-induced apoptosis, modification of cell cycle checkpoints, inhibition of apoptosis, etc, have been recognized that cause MDR [1-3]. One of the most important mechanisms of MDR is overexpression of adenosine triphosphate (ATP)binding cassette (ABC) transporters, which efflux varieties of anticancer drugs against the concentration gradient by using ATPdriven energy .
The ABC transporters are the largest family of transmembrane proteins and are found in all living organisms. The ABC superfamily now includes more than 300 proteins. In human genome, 49 ABC proteins are known from which 48 appear to be functional. Human ABC family are divided to seven subfamilies, includes ABCA, ABCB, ABCC, ABCD, ABCE, ABCF, ABCG . The most common three important ABC transporter are P-glycoprotein (P-gp, ABCB1), multidrug resistance protein 1 (MRP1, ABCC1), and breast cancer resistance protein (BCRP, ABCG2), and these transporters (P-gp, BCRP and MRP1) are highly expressed in the gut, liver and kidneys where they restrict the bioavailability of administered drugs . The efﬂux mechanism in ABC transporters is related with MDR in cancer, thus, down-regulation the expression of ABC transporters or inhibiting the efﬂux function of these transporters is the major strategy to reverse the MDR.
Tyrosine kinases (TKs), a large and diverse category of enzymes, can catalyze the transfer of a phosphate group from ATP to target proteins and play vital roles in cell signal transduction pathways and play crucial roles in physiological processes such as embryogenesis, differentiation, cell proliferation, anti-apoptotic signaling and programmed cell death . TKs can be classified as receptor TKs (RTKs) and non-receptor TKs (NRTKs). RTKs are encoded by the largest group of oncogenes sharing structural homology, and transformations such as overexpression, dysregulation, or mutations of RTKs has been found to correlate with the development and progression of numerous cancers . Epidermal growth factor receptor (EGFR) is a trans-membrane glycoprotein which is the first receptor identified from RTKs family known as the type I receptor tyrosine kinases . Others RTKs including vascular endothelial growth factor receptor(VEGFR), fibroblast growth factor receptors(FGFR), insulin-like growth factor receptor(IGFR), and hepatocyte growth factor receptor(HGFR), etc . EGFR belongs to the ErbB family, which include ErbB1 (also known as HER-1 or EGFR), ErbB2(HER-2), ErbB3( HER-3), and ErbB4(HER-4). These tyrosine kinases of ErbB family have the similar basic structures including an extracellular ligand binding domain, a transmembrane portion, and intracellular tyrosine kinase and regulatory domains [11,12].
Overexpression and/or mutations of RTKs, particularly of ErbB family have played an important role in tumorigenesis in various types of cancers and is correlated with a poor prognosis. Therefore, RTKs has become an attractive therapeutic target for anticancer therapy, and numerous targeting drugs have been developing for treatment for EGFR-associated tumors. In recent years, the targeted therapy for EGFR family receptors is focus on ErbB1 and HER2, and the targeted drugs are divided into two categories: monoclonal antibodies (MAbs) and tyrosine kinase inhibitors (TKIs) [8,10,13-15]. In recent years, several TKIs has been successfully developed that can block protein phosphorylation mediated cellular signaling pathways which control tumor cell growth . Most of these TKIs were designed to compete with ATP at the ATP-binding site within the TKs domain. The small molecule TKIs have been designed to block the ATP-binding site or allosteric site within the intracellular catalytic domain of TKs, subsequently inhibiting phosphorylation and subsequent downstream signaling processes, thereby causing arrest of tumor cell proliferation, induction of apoptosis, tumor migration and tumor angiogenesis .
Although TKIs have had outstanding success in cancer therapy, there has been increasing evidence of resistance to TKIs . The common mechanisms for MDR against TKIs is associated with the enhanced efflux of TKIs by certain over-expressed ABC transporters, which remarkably reduce the intracellular TKIs concentrations in cancer cells . On the other hand, more and more studies have been demonstrated that some of TKIs could selectively modulate either the expression or function of ABC transporters by different mechanisms, thereby reversing the ABC transporters mediated MDR [20-22].
Dacomitinib (PF00299804) is a pan-HER family, orally active inhibitor that has activity toward EGFR, HER2, and HER4 . Although similar to the first-generation reversible EGFR inhibitors in competing with ATP in the kinase domain, dacomitinib also covalently binds at the ATP binding cleft on Cys773 of EGFR, leading to irreversible blockade of ATP to the kinase, rendering it inactive .As an irreversible EGFR TKIs, dacomitinib targets both sensitizing EGFR mutants and the secondary EGFR T790M mutant tumours . Some preclinical or clinical trials are performed to evaluate antitumor activity and pharmacokinetic properties, or compare the effects of dacomitinib to gefitinib, erlotinib and afatinib for non-small-cell lung cancer (NSCLC) [26,27].
Since some TKIs can suppress the function of ABC transporters to reverse the MDR, and ABC transporters also down-regulation the anti-tumor effect of certain TKIs [16,18,20]. As a second-generation TKIs, dacomitinib was originally designed to irreversibly block of ATP to the tyrosine kinase domains, thereby to block the signal pathways, which control tumor cell growth . The interactions between dacomitinib and ABC transporters is still unclear. In this study, we determine whether dacomitinib could reverse ABC transporter-mediated MDR.
Materials and methods
Dacomitinib (PF299804) was purchased from Chemie Tek (Indianapolis, Indiana). Dulbecco’s modified Eagle’s Medium (DMEM), Bovine serum albumin (BSA), fetal bovine serum (FBS), penicillin/streptomycin and trypsin 0.25% were purchased from Hyclone (GE Healthcare Life Science, Pittsburgh, PA). monoclonal antibody C219 (against ABCB1), monoclonal antibody BXP-34 (against ABCG2) , monoclonal antibody BA3R (against β-Actin), Alexa Fluor 488 conjugated goat anti-mouse IgG secondary antibody, SN-38 and MK571 were purchased from Thermo Fisher Scientific Inc (Rockford, IL). 3-(4,5-dimethylthiazol-yl)-2,5-diphenyltetrazolium bromide (MTT), dimethylsulfoxide(DMSO), Triton X-100, propidium iodide, paraformaldehyde, paclitaxel, doxorubicin, colchicine, cisplatin, vincristine, vinblastine, mitoxantrone, verapamil were products from Sigma-Aldrich (St. Louis, MO). KO143 was products from Enzo life Sciences (Farmingdale, NY). [3H]-paclitaxel (15 Ci/mmol) and [3H]-mitoxantrone (2.5 Ci/mmol) were purchased from Moravek Biochemicals, Inc (Brea, CA). Other chemicals were purchased from Sigma Chemical Co (St. Louis, MO).
Cell lines and cell culture
Human epidermoid carcinoma cell line KB-3-1 and its colchicine-selected ABCB1-overexpressing KB-C2 cells, human colon cancer cell line SW620 and its doxorubicin-selected ABCB1-overexpressing SW620/Ad300 cells, non-small cell lung cancer cell line NCI-H460 and its mitoxantrone-selected ABCG2-overexpressing NCI-H460/MX20 cells, ABCC1-overexpressing cell line KB-CV60, cloned from KB-3-1 cells was maintained in medium with 1 μg/mL cepharanthine and 60 ng/mL vincristine ，as well as the ABCG2-, ABCB1-, and ABCC1-overexpressing transfected HEK293 cell lines were used for the reversal study. HEK293/pcDNA3.1, HEK293/ABCB1, HEK293/ABCG2 and HEK293/ABCC1 that established by transfecting HEK293 cells with either empty pcDNA3.1 vector or vector containing full length ABCB1 (HEK293/ABCB1), ABCG2 (HEK293/ABCG2) and ABCC1 (HEK293/ABCC1) respectively, and were cultured in a medium containing 2 mg/mL of G418. All cell lines were cultured at 37°C, 5% CO2 with DMEM containing 10% FBS and 1% penicillin/streptomycin. All drug-resistance cells were grown as adherent monolayer in drug-free culture media for more than 2 weeks before assay.
Cytotoxicity and reversal experiments by MTT assay
Cytotoxicity and reversal experiments were performed using the MTT colorimetric assay as described previously . Cells were harvested and resuspended in a final concentration of 5×103 cells/well for the KB-3-1, KB-C2, KB-CV60, SW620, SW620/Ad300, NCI-H460 and NCI-H460/MX20 cells, and 6×103 cells/well for the HEK-293/pcDNA3.1, HEK/ABCB1, HEK/ABCG2, and HEK/ABCC1 cells. Cells were seeded evenly into each well with 160 µL medium in 96-well microplates in triplicate and cultured at 37 0C for 24 h. Different concentrations of chemotherapeutic drugs (20 µL/well) were added into each well after 2 h of preincubation with dacomitinib, KO143, verapamil or MK571. After 72 h of incubation, 20 µL of MTT solution (4 mg/mL) was added into each well, and the plate was incubated for an additional 4 h. Then the supernatant was discarded and DMSO (100 µL/well) was added to dissolve the formazan crystals. Finally, the absorbance was determined at 570 nm by the OPSYS microplate reader (Dynex Technology, Chantilly, VA, USA). All of the experiments were repeated at least three times, and the mean and standard deviation (SD) values were calculated. The concentrations of dacomitinib as a potential reversal agents used in this study were 0.3 µM and 1.0 µM. Verapamil (3μM), KO143 (3.0μM) and MK571 (25μM) were used as positive control inhibitors of P-gp, BCRP and MRP1, respectively, to evaluate the effects of dacomitinib. Cisplatin, which is not a substrate of ABCB1, ABCG2- and ABCC1 was used as a negative control of anticancer drug.
Western blot analysis
Cells were treated with or without dacomitinib for different times (0, 24, 36, 48, 72 h), and cells were lysed after washing twice with ice-cold PBS. Then cell extracts were prepared by incubating cells on ice for 20 min with lysis buffer (10 mM Tris HCl, pH 7.5, 1 mM EDTA, 0.1% SDS, 150 mM NaCl, 1% Triton X-100 and protease inhibitor cocktail), followed by centrifugation at 12,000× g at 4 °C for 5 min. The supernatant containing total cell lysate was collected and protein concentration was determined by bicinchoninic acid (BCATM) based-protein assay (Termo Scientifc, Rockford, IL). Equal amounts of protein were resolved by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto polyvinylidene fluoride (PVDF) membranes through electrophoresis. The PVDF membranes were immersed in blocking solution (5% skim milk) in TBST buffer (10 mM Tris–HCl, pH 8.0, 150 mM NaCl, and 0.1% Tween 20) to block nonspecific binding for 1 h at room temperature. Then membranes were immunoblotted overnight with primary monoclonal antibodie at 4°C. For ABCB1-overexpressing cells, the blot was probed with monoclonal antibodyC219 (dilution 1:200), for ABCG2-overexpressing cells, the blot was probed with monoclonal antibody BXP-21 (dilution 1:500). PVDF Membranes were then further incubated for 2 h at 370C with horseradish peroxide (HRP)- conjugated secondary antibody (1:1000 dilution). The protein–antibody complex was detected by enhanced chemiluminescence detection system (Amersham, NJ). GAPDH was used to confirm equal loading in each lane in the samples prepared from cell lysates.
Cells were seeded (2×104/well ) in 24-well plates and cultured at 37 0C for 24 h, followed by treatment with 1.0 µM dacomitinib for 0, 24, 48 and 72 h respectively. Then the cells were fixed in 4% paraformaldehyde for 15 min, permeabilized by 0.1% Triton X-100 for 10 min and then blocked with 6% BSA for 1.5 h at room temperature. Subsequently, cells were incubated with either monoclonal antibody C219 against ABCB1 (1:400, for SW620/Ad300 cells) or monoclonal antibody BXP-21 against ABCG2 (1:400, for NCI-H460/MX20 cells) overnight at 4 0C, followed by two washes with PBS. Cells were then further incubated with Alexa flour 488 goat anti-mouse IgG (1:60) for 1 h at 37 0C. After two times washes, PI (2 μg/mL) was used for nuclear counterstaining. Immunofluorescence images were collected using a Nikon TE-2000S fluorescence microscope (Nikon Instruments Inc, Melville, NY).
The vanadate-sensitive ATPase activity of ABCB1 and ABCG2 in membrane vesicles of High Five insect cells was measured as previously described . The membrane vesicles (10 μg of protein) were incubated in ATPase assay buffer [50 mmol/L MES (pH 6.8), 50 mmol/L KCl, 5 mmol/L sodium azide, 2 mmol/L EGTA, 2 mmol/L DTT, 1 mmol/L ouabain, and 10 mmol/L MgCl2] with or without 0.3 mmol/L vanadate at 37 0C for 5 min, then incubated with different concentrations of dacomitinib, ranging from 0-40 µM, at 37 0C for 3 min. The ATPase reaction was induced by the addition of 5 mmol/L MgATP, and the total volume was 0.1 mL. After incubation at 37°C for 20 min. The reaction was allowed to continue for another 20 min at 37 0C and then terminated by an addition of 100 μL 5% SDS solution to the reaction mix. The amount of Pi release was detected at 880 nm using a spectrophotometer.
[3H]-paclitaxel and [3H]-mitoxantrone accumulation assay
Since dacomitinib could reverse MDR mediated by ABCB1 and ABCG2, but could not change the expression and location of ABCB1 and ABCG2, therefore, we performed the drug accumulation and efﬂux assay to investigate the reversal mechanism. For accumulation assay of [3H]-paclitaxel in KB-3-1 and KB-C2 cells，cells (105 cells / well) were seeded in the 24-well plate and incubated at 37°C with 5% CO2. After 12 hour incubation, dacomitinib (1 or 3 μM) or verapamil (3 μM) were added and the plate was incubated at 37°C for 2 h. Cells were then incubated with 0.01 μM [3H]-paclitaxel containing medium for additional 2 h at 37°C, with or without dacomitinib (1 or 3 μM) or verapamil (3 μM), and subsequently washed twice with ice-cold PBS. For the accumulation assay, the cells were lysated and placed in 5 mL scintillation ﬂuid and radioactivity was measured in the Packard TRI-CARB 1900CA liquid scintillation analyzer (Packard Instrument, Downers Grove, IL ). Same protocol was followed by using 0.01μM [3H]-mitoxantrone in NCI-H460 and NCI-H460/MX20 cells.
[3H]-paclitaxel and [3H]-mitoxantrone efflux assay
To measure the [3H]- paclitaxel drug efflux, KB-3-1 and KB-C2 cells (105 cells / well) were seeded in the 24-well plate and incubated for 12 h. Dacomitinib (1 or 3 μM) or verapamil (3 μM) were added and the plate was incubated at 37°C for 2 h. After that, then cells were incubated with 0.01 μM [3H]-paclitaxel containing medium for additional 2 h at 37°C (accumulation phase), with or without dacomitinib (1 or 3 μM ) or verapamil (3 μM), and then [3H]-paclitaxel-free medium for 2 h (efflux phase). In the efflux phase, cells were subsequently washed twice with ice-cold PBS at 0, 30, 60 and 120 min time points respectively. After that, cells were trypsinized and then transferred in scintillation fluid. The radioactivity was measured using the Packard TRI-CARB1 190`A liquid scintillation analyzer. Same protocol was followed by using 0.01 μM [3H]-mitoxantrone in NCI-H460 and NCI-H460/MX20.
Molecular modeling of ABCB1 ( supplementABCG2)
Human ABCB1 homology model established on the basis of refined mouse ABCB1 (PDB ID: 4M1M) was kindly provided by S. Aller, and the docking grid of 25 Å at drug-binding pocket in transmembrane domains (TMD) was refined as previously described . The docking grid of 20 Å at ATP-binding site in NBD of ABCB1 was generated by selecting the residues in conserved subdomains of NBD1 as centroid . The structure of dacomitinib was built using entry editor in Maestro v11.1 and energy minimization was carried out by Macromodel v11.5 (Schrödinger, LLC, New York, NY, USA, 2017). The structure of dacomitinib was then prepared by LigPrep v4.1 (Schrödinger, LLC, New York, NY, USA, 2017) and the generated low-energy 3D structure was used for conformational search to generate at most 50 conformations of the structureconformers. The conformations were filtered with an energy windowed of 5 kcal/mol and maximum atom deviation of 0.5 Å to rule out redundant conformers. Flexible docking of 50 unique ligand conformers into human ABCB1 homology model at drug-binding site and ATP-binding site, respectively, was performed using the XP (extra precision) mode by Glide v7.4 (Schrödinger, LLC, New York, NY, USA, 2017). In order to simulate the optimal binding between ligand and receptor, induced-fit docking (IFD) by Glide v7.4, which allows shape changes of the binding pocket, was conducted. The best scored dacomitinib binding got from Glide XP docking process was used to generate receptor grid for IFD at the drug-binding site and ATP-binding site, respectively. The IFD protocol with default parameters was performed and the docking scores (kcal/mol) were calculated.
To validate the prediction of the binding, the docked ABCB1-dacomitinib complex at transmembrane site is subsequently used for short molecular dynamics (MD) simulation with Desmond MD system v4.7 (D. E. Shaw Research, New York, NY, USA, 2016; Schrödinger, LLC, New York, NY, USA, 2016). Predefined TIP3P water model was used and counter Na+/Cl- ions were added to balance the system charge. The system was built in Maestro with POPC membrane bilayer placed. Periodic boundary conditions were set up and the buffer distance between box wall and the protein-ligand complex was set to be greater than 15 Å to avoid direct interaction of the complex with its own periodic image. After establishing the solvated system, MD simulation was carried out in the NPT ensemble using OPLS 2005 force field. The temperature and pressure were retained at 300 K and 1 atmospheric pressure. A short equilibration phase simulation was involved using default Desmond protocol, followed by running the 10,000 ps (10 ns) MD simulation for the equilibrated complex system. Schrödinger simulation interactions diagram (SID) was used to evaluate the interaction between ligand and protein. The root mean square deviation (RMSD) of the ABCB1-dacomitinib complex was calculated to evaluate if there are conformational changes of the protein or internal fluctuations of the ligand. It was calculated for all frames in the simulation trajectory, with respect to the first frame as the reference frame. Similary protocol of IFD and MD simulation was performed for BCRP.
All data are expressed as mean±SD. All experiments were repeated at least three times and statistically evaluated by one-way ANOVA. Diﬀerences were considered significant when p< 0.05.
Effects of dacomitinib on substrates in cell lines overexpressing ABCB1, ABCG2 and ABCC1
In order to investigate the effects of dacomitinib on ABC transporters, we first examined the sensitivity of ABCB1-, ABCG2-, and ABCC1-overexpressing cells to dacomitinib. The cytotoxicity assay showed that IC50 values of dacomitinib to P-gp, BCRP and MRP1 over-expressing tumor cells (KB-C2, SW620/AD300, NCI-H460/MX20 and KB-CV60 ) and their parental cells (KB-3-1, SW620, NCI-H460 and KB-3-1) are all between 4-10 µM (Fig. 1 and Fig. 2). Based on this results, concentrations of 0.3 and 1.0 µM at which no significant cytotoxicity were chosen for further experiments. To further examine whether dacomitinib could reverse ABC transporters mediated MDR in these cell lines, cell survival assays were performed in the presence or absence of dacomitinib, using the drug-selective human cancer lines (KB-C2, SW620/AD300, NCI-H460/MX20 and KB-CV60) and ABCB1-, ABCG2- and ABCC1 gene transfected cell lines (HEK293/ABCB1, HEK293/ABCG2 and HEK293/ABCC1) with their corresponding parental cell lines (KB-3-1, SW620 and NCI-H460, HEK293/pcDNA3.1). As shown inTables 1 to 4, KB-C-2, SW620/Ad300, NCI-H460/MX20 and KB-CV60 cell lines had much higher IC50 values to their corresponding substrates than their parental cell lines. Dacomitinib significantly potentiated the cytotoxicity of paclitaxel, colchicine and doxorubicin in KB-C2, SW620/AD300 and HEK293/ABCB1 cell lines in a concentration dependent manner compared to KB-3-1, SW620 and HEK293/pcDNA3.1 cell lines(Tables 1 and 2). Similarly, dacomitinib significantly reduced the IC50 values of mitoxantrone and SN-38 in NCI-H460/MX20 and HEK/ABCG2 cell lines compared to NCI-H460 and HEK/pcDNA3.1 cell lines (Table 3). However, dacomitinib at 1.0 µM did not significantly alter the sensitivity of vincristine and vinblastine in ABCC1-overexpressing KB-CV60 and HEK293/ABCC1 cell lines compared to their parental KB-3-1 and HEK293/pcDNA3.1 cells lines (Table 4). As shown inTables 1 to 3,the reversal effect of dacomitinib on ABCB1-overexpressing cell lines is stronger than that of on ABCG2-overexpressing cell lines. In addition, the reversal effect of dacomitinib on HEK293/ABCB1 and HEK293/ABCG2 cell lines is stronger than that on KB-C-2, SW620/Ad300 and NCI-H460/MX20 cell lines. There was no significant change of IC50 values of cisplatin in above mentioned human cancer cell lines (KB-C2, SW620/AD300, NCI-H460/MX20, KB-CV60) or transfected cell lines (HEK293/ABCB1, HEK293/ABCG2 and HEK293/ABCC1) compared to their corresponding parental cells (Tables 1 to 4). These results suggest that dacomitinib could reverse the ABCB1- and ABCG2-mediated MDR, but not ABCC1-mediated MDR.
Fig. 1. Chemical structure of dacomitinib and concentration-response curves of ABCB1-overexpressing cell lines treated with dacomitinib alone. (A) Chemical structure of dacomitinib (2D structure and 3D structure). (B) Concentration-response curves of KB-3-1 and KB-C2 cell lines treated with dacomitinib alone. (C) Concentration-response curves of SW620 and SW620/MX20 cell lines treated with dacomitinib alone. (D) Concentration-response curves of HEK293/pcDNA3.1 and HEK/ABCB1 cell lines treated with dacomitinib alone.Each cell line was incubated with different concentrations of dacomitinib for 72 h. Cell survival rate was determined by the MTT assay as described in “Materials and methods”. Points with error bars represent the mean ± SD. Each above figure is a representative of three independent experiments, each done in triplicate.
Fig. 2. Concentration-response curves of ABCG2-, ABCC1-overexpressing cell lines treated with dacomitinib alone. (A) Concentration-response curves of NCI-H460 and NCI-H460/MX20 cell lines treated with dacomitinib alone. (B) Concentration-response curves of HEK293/pcDNA3.1 and HEK/ABCG2 cell lines treated with dacomitinib alone. (C) Concentration-response curves of KB-3-1 and KB-CV60 cell lines treated with dacomitinib alone. (D) Concentration-response curves of HEK293/pcDNA3.1 and HEK/ABCC1 cell lines treated with dacomitinib alone. Each cell line was incubated with different concentrations of dacomitinib for 72 h. Cell survival rate was determined by the MTT assay as described in “Materials and methods”. Points with error bars represent the mean±SD. Each above figure is a representative of three independent experiments, each done in triplicate.
Effect of dacomitinib on the protein expression and localization of ABCB1and ABCG2
Since the reversal of ABC transporter mediated MDR can be achieved either by decreasing ABC protein expression at the cell surface or inhibiting the function of ABC transporter,we performed Western blot analysis to confirm whether dacomitinib couldaffectthe protein expression of ABCB1 and ABCG2. As show in figure 3, we found that there was no significant change in protein expression band with a molecular weight of approximately 170-kDa in KB-C2 cell lysates after treatment with dacomitinib in different times (0, 36 and 72 h), In contrast, this band was not present in parental KB-3-1 cell lysates (Figs. 3A and 3B). The no significant change protein expression band with higher intensity of molecular weight of 72-kDa was present in the NCI-H460/MX20 cell lysates, and a much lower intensity protein expression band was present in the parental NCI-H460 cell line lysates (Figs. 3C and 3D).
Furthermore, we performed the immunofluorescence assay to analyze whether the location of ABCB1 and ABCG2 was altered after treating with dacomitinib. As shown in figure 4, ABCB1 transporters located in membrane of KB-C2 cells. The treatment of 1 μM dacomitinib did not significantly alter the subcellular distribution pattern of ABCB1 in KB-C2 cells when compared to control at 24, 48 and 72 h time points. Similarly, ABCG2 transporters located in membrane of NCI-H460/MX20 cells. The treatment of 1 μM dacomitinib did not significantly alter the subcellular distribution pattern of ABCG2 in NCI-H460/MX20 cells when compared to control at 24 h, 48 h and 72 h time points.
Fig. 3. Western blotting to detect ABCB1 and ABCG2 expression in ABCB1-overexpressing and ABCG2-overexpressing cell lines respectively. (A) The eﬀect of dacomitinib at 0.3 μM, 1.0 μM, 3.0 μM on the expression levels of ABCB1 in KBC-2 cells for 72 h. (B) The eﬀect of dacomitinib at 1.0 μM on the expression levels of ABCB1 in KBC-2 cells for 0, 36 and 72 h. (C) The eﬀect of dacomitinib at 0.3 μM, 1.0 μM, 3.0 μM on the expression levels of ABCG2 in NIC-H460 and NCI-H460/MX20 cells for 72 h. (D) The eﬀect of dacomitinib at 1.0 μM on the expression levels of ABCB1 in NIC-H460 and NCI-H460/MX20 cells for 0, 36 and 72 h. Equal amounts of total cell lysate were used for each sample.
Fig. 4.The eﬀect of dacomitinib on the subcellular localization of ABCB1 in ABCB1-overexpressing and ABCG2 in ABCG2-overexpressing cell lines.(A) The eﬀect of dacomitinib at 1.0 μM on the subcellular localization of ABCB1 in ABCB1-overexpressing SW620/Ad300 (KB-3-1) cells for 0, 24, 48 and 72 h. (B) The eﬀect of dacomitinib at 1.0 μM on the subcellular localization of ABCG2 in ABCG2-overexpressing NCI-H460/MX20 cells. ABCB1 and ABCG2 staining are shown in green. PI (propidium Iodide, red) counterstains the nuclei.
Dacomitinib increased intracellular drug accumulation in cells overexpressing ABCB1 and ABCG2
Since dacomitinib could reverse MDR mediated by ABCB1 and ABCG2, but could not change the expression and location of ABCB1 and ABCG2, therefore, we performed the drug accumulation and efﬂux assay to investigate the reversal mechanism. Intracellular [3H]-paclitaxel and [3H]-mitoxantrone were measured in ABCB1- and ABCG2-overexpressing cells in the presence or absence of dacomitinib. As shown in figure 5A, the level of intracellular accumulation of [3H]-Paclitaxel in KB-C2 cells was 23-fold lower than that in the KB-3-1 cells after 2 h incubation. Pretreatment of 3 μM dacomitinib increased the intracellular level of [3H]-Paclitaxel in KB-C2 cells to 72% of that in parental KB-3-1 cells. Pretreatment of dacomitinib increased the intracellular level of [3H]-Paclitaxel in a concentration-dependent pattern. Verapamil at 3 μM was used as positive control inhibitor for ABCB1. Similarly, the level of intracellular [3H]-Mitoxantrone in NCI-H460/MX20 cells was approximately 2-fold lower than that in the NCI-H460 cells after 2 h incubation. Pretreatment of 1 μM dacomitinib increased the intracellular [3H]-Mitoxantrone by 3.5-fold; while pretreatment of 3 μM dacomitinib increased the intracellular [3H]-Mitoxantrone by 3.8-fold. Dacomitinib at 3 μM has the approximate effect with positive control KO143 (3 μM) in increasing the intracellular [3H]-Mitoxantrone accumulation(Fig. 5B). While dacomitinib did not alter the intracellular accumulation of [3H]-paclitaxel in KB-3-1 cells or [3H]-mitoxantrone in NCI-H460 cells. These results suggested that dacomitinib significantly increased intracellular concentrations of chemotherapeutic drugs in ABCB1- or ABCG2-overexpressing cells and cause the increasing of cytotoxicity to these cells.
Fig. 5.Dacomitinib increased intracellular drug accumulation in cells overexpressing ABCB1 and ABCG2. (A) The effects of dacomitinib on accumulation of [3H]-paclitaxel in KB-3-1 and KB-C2 cells. (B) The effects of dacomitinib on accumulation of [3H]-mitoxantrone in NCI-H460 and NCI-H460/MX20 cells. Verapamil (3 μM) and Ko143 (3 μM) are used as positive control for ABCB1- or ABCG2-overexpressing cells respectively.
Dacomitinib inhibited the efﬂux activity of ABCB1 and ABCG2
To determine whether the increased intracellular accumulation of [3H]-paclitaxel or [3H]-mitoxantrone caused by dacomitinib, we examined the efflux of [3H]-paclitaxel and [3H]-mitoxantrone with or without dacomitinib at different time points (0, 30, 60, and 120 min) in ABCB1- and ABCG2-overexpressing cells. As shown in figure 6A, neither dacomitinib nor verapamil significantly altered efflux pattern in parental KB-3-1 cells. Treatment with dacomitinib or verapamil increased the retention of [3H]-paclitaxel in KB-C2 cells (Fig. 6B). Moreover, accumulation of paclitaxel increased after the treatment of dacomitinib in a concentration-dependent pattern (Fig. 6B). After 2 h efflux, dacomitinib exhibited 25% and 49% of [3H]-paclitaxel retention in KB-C2 cells at 1 μM and 3 μM, respectively. Similarly, the effect of dacomitinib on the efflux of [3H]-mitoxantrone in NCI-H460/MX20 was investigated. Compared to NCI-H460 cells, NCI-H460/MX20 cells decreased the accumulation of [3H]-mitoxantrone. With the treatment of dacomitinib, the efflux function of NCI-H460/MX20 cells was inhibited but that of parental NCI-H460 cells did not significantly change (Figs. 6C and 6D). These results suggested that dacomitinib could inhibit the efﬂux activity of ABCB1 and ABCG2.
Fig. 6.Dacomitinib inhibited the efﬂux activity of ABCB1 and ABCG2.(A, B) The effects of dacomitinib on efflux of [3H]-paclitaxel in KB-3-1 and KB-C2 cells. (C,D) The effects of dacomitinib on efflux of [3H]-mitoxantrone in NCI-H460 and NCI-H460/MX20 cells. Verapamil (3 μM) and KO143 (3 μM) is used as positive control for ABCB1- or ABCG2-overexpressing cells respectively.
Dacominitib inhibited ATPase activity of ABCB1 and ABCG2
The drug efflux function of ABC transporter is linked to ATP hydrolysis, which is stimulated in the presence of substrates. To assess the effect of dacominitib on the ATPase activity of ABCB1 and ABCGG2, we measured the ABCB1 or ABCG2 mediated ATP hydrolysis in the presence of dacominitib at various concentrations from 0-40 µM. As shown infigure 7A, dacominitib inhibited the ATPase activity of ABCB1 in a concentration-dependent manner. The concentration for 50% inhibition is 1.32 µM and the maximum inhibition is 0.62-fold. Similarly, dacominitib also inhibited the ATPase activity of ABCG2 in a concentration-dependent manner. The concentration for 50% inhibition is 0.83 µM and the maximum inhibition is 0.97-fold (Fig. 7B). This result indicated that dacominitib is an actual inhibitor to affect the ATPase activity of both ABCB1 and ABCG2.
Fig. 7. Effect of dacomitinib on Vi-sensitive ABCB1 ATPase activity and ABCG2 ATPase activity with increased concentration of dacomitinib (0–40μM). Effect of dacomitinib on Vi-sensitive ABCB1 ATPase activity (A) and ABCG2 ATPase activity(B) was measured as described in ‘‘Materials and methods”. The inset shows the effect of lower concentration ranging from 0 to 1 μM of dacomitinib on the ATPase activity of ABCB1 and ABCG2 respectively. Concentration of dacomitinib was plotted at (A) linear and (B) linear.
Docking analysis of dacominitib with human ABCB1 homology model (supplementABCG2)
To understand the inhibiting effects of dacominitib on ATPase activity and hydrolysis, docking studies were performed on ATP binding site in NBD domain of both ABCB1 and ABCG2. IFD results showed that dacomitinib exhibited a Glide gscore of -12.827 kcal/mol on human ABCB1 model at transmembrane drug-binding site, while at ATP-binding site the Glide gscore was -6.624 kcal/mol. As IFD simulation predicted much higher score of dacomitinib at ABCB1 drug-binding site, dacomitinib may have higher affinity to the drug-binding pocket than to the ATP-binding site. However, IFD protocol has very limited backbone movement, which makes it challenging to predict accurate interaction pose . Moreover, it has been reported that some well-docked protein-ligand complexes may not keep stable under dynamic conditions . Therefore, as complement to IFD simulation, a MD simulation was performed to study the dynamic of interactions between dacomitinib and ABCB1 model at transmembrane site for 10 ns. The monitored RMSD of the protein is used to indicate whether the simulation has equilibrated or the protein has undergone conformational change, while RMSD of ligand is used to indicate if there is internal fluctuation of the ligand so as to predict the stability of the interaction between ligand and the binding pocket of protein. The MD simulation for ABCB1-dacomitinib complex showed that the protein backbone RMSD deviated up to about 7 Å in the first 2 ns then remained relatively stable (deviation less than 3 Å) till the end of the simulation period, reflecting a relatively stable protein conformation. RMSD of the ligand kept stable at around 1.5 Å after 1 ns, which indicated that internal fluctuations of dacomitinib in the binding pocket were slight (Fig. 8A). Comparison between the superimpositions of dacomitinib in the binding pocket at pre- and post-MD simulation is shown in figure 8B. Ligand-protein interactions that occur more than 20.0% of the simulation time are illustrated in Figure 8C, and the docked pose of dacomitinib into the post-simulated ABCB1 drug-binding cavity is depicted in Figure 8D. The dacomitinib core structure was majorly stabilized into a hydrophobic cavity formed by residues Phe336, Ile340, Phe728 and Phe983. -cation interaction formed between the phenyl ring of Phe728 and the 2-enamide group of dacomitinib was maintained 98% of the simulation time. Besides, the phenyl group of Phe326 formed a - stacking interaction with the quinazoline ring of dacomitinib, which occurred 32% of the simulation time. Polar interactions and hydrogen bonds were formed between dacomitinib and Gln725 and Gln990.
Fig. 8. Molecular dynamics (MD) simulation interactions between ABCB1/BCRP and dacomitinib.(A) RMSD trajectory of ABCB1 and dacomitinib in the ABCB1-dacomitinib complex over the 10 ns simulation period; (B) change in superimposition of dacomitinib after simulation (blue, post-MD; red, pre-MD); (C) detailed ABCB1-dacomitinib interactions that occur more than 20.0% of the simulation time in the entire 10 ns trajectory; (D) the docked conformation of dacomitinib within the binding cavity of ABCB1 after MD simulation. Residue labels are omitted for better view except important residues suggested by per-residue interaction or residues contributed in polar interactions. Carbon and nitrogen atoms of dacomitinib are highlighted in blue and light blue, respectively. Values of the relevant distances are given in Å. (E) (F) (G) (H) ( supplement Figs of ABCG2)
Dacomitinib is a second-generation irreversible pan-ErbB receptor tyrosine kinase inhibitor that it inhibits EGFR by forming a covalent bond with cysteine 797 . It also inhibits the other three of the four ErbB family members including HER-2, HER-4 and HER-3 which has no intrinsic kinase activity but allows the activation of other ErbB receptors during the dimerization process [35,36]. Dacomitinib is designed to inhibit both the wild-type (WT) EGFR and EGFR T790M mutation. Several experimental models and preclinical studies demonstrated that dacomitinib has marked anticancer activity in many types of tumors [37-42]. Although, the preclinical studies show that dacomitinib is a potent inhibitor of EGFR-activating mutations as well as the EGFR T790M mutation both in vitro and in vivo, and it is effective in lung cancer models with EGFR and ErbB2 mutations that are resistant to gefitinib [35,36], numerous clinical trials (Phase I to Phase III ) have demonstrated that dacomitinib has failed to improve overall outcomes in pretreated NSCLC patients, and does not overcome EGFR T790M-mediated acquired resistance in EGFR-mutant NSCLCs at tolerable doses . These unexpected clinical trials demonstrated complex resistance mechanisms to irreversible EGFR TKIs and new strategies should be development to overcome the resistance of dacomitinib in NSCLCs .
As described before, the active efflux of TKIs by certain ABC transporters is the most common mechanism of resistance. On the other hand, some TKIs have been found to have the capability to overcome anticancer drug resistance by inhibiting ABC transporters [18-20]. Since many TKIs interact with ABC transporters as substrates or inhibitors, the primary aim of this study was to describe the interactions between dacomitinib and ABC transporters including ABCB, ABCC and ABCG, and identify the potential mechanism which helps to develop more effective clinical therapeutic strategies for cancers.
In this study, we selected the most common three ABC transporters P-GP, BCRP and MRP1 to identify the interactions between dacomitinib and ABC transporters. Our cytotoxicity assay showed that IC50 values of dacomitinib to P-gp, BCRP and MRP1 over-expressing tumor cells (KB-C2, SW620/AD300, NCI-H460/MX20 and KB-CV60) and their parental cells (KB-3-1, SW620, NCI-H460 and KB-3-1) are all between 4-10 µM. The similar results were shown in P-gp, BCRP and MRP1 gene transfected HEK293 cells (HEK293/ABCB1, HEK293/ABCG2, HEK293/ABCC1) and HEK293/pcDNA3.1 cells(Figs. 1 and 2). We used non-toxic concentrations of dacomitinib (0.3 µM and 1.0 µM) to do reversal assay. We found that dacomitinib (1.0 µM) significantly sensitized P-gp over-expressing KB-C2 and SW620/AD300 cells to paclitaxel, colchicine and doxorubicin as it markedly decreased the IC50 value of these substrates compared to control cells (Tables 1and 2), and the same results was showed in P-gp transfected cells HEK293/ABCB1 (Tables 1 and 2). We also found that dacomitinib (1.0 µM) significantly decreased the IC50 values of mitoxantrone and SN38 in BCRP over-expressing NCI-H460/MX20 and HEK293/ABCG2 cells compared to control cells (Table 3). However, dacomitinib (1.0 µM) did not decrease the IC50 values of vincristine and vinblastine in MRP1 over-expressing KB-CV60 and HEK293/ABCC1 cells compared to control cells(Table 4). Since ABCB1 or ABCG2 is the sole contributor for MDR in HEK293/ABCB1 or HEK293/ABCG2 cells respectively, our results of MTT assay suggests that the efficacy of dacomitinib to reverse MDR is specific to ABCB1 and ABCG2, but not ABCC1. In addition, these reversal effects are not complete and reversal effects on ABCB1 over-expressing cells are much stronger than that of on ABCG2 over-expressing cells (Tables 1, 2 and 3) .
Since the reversal of ABC-mediated MDR can be achieved either by antagonizing the function of ABC transporter or by decreasing its expression at the cell surface. Therefore, we preformed the western blotting and immunofluorescence assay to determine whether dacomitinib can affect the total expression level or change the intracellular localization of ABCB1 and ABCG2. As showed in figure 3,after treatment with different times(0h to 72h) and different concentrations(0.3µM to 3µM), dacomitinib did not significantly alter the protein expression levels of ABCB1 and ABCG2, moreover, the subcellular location of these two proteins were not significantly altered (Fig. 4). These results indicated that the reversal of ABCB1 and ABCG2 mediated MDR by dacomitinib is not through modulation of the sub-cellular protein expression or translocation, the functions change of ABCB1 and ABCG2 may be associated with reversal eﬀects of MDR. Subsequent drug accumulation studies demonstrated that dacomitinib significantly enhanced the intracellular accumulation of [3H]-paclitaxel in ABCB1 overexpressing KB-C2 cells and [3H]-mitoxantrone in ABCG2 overexpressing NCI-H460/MX20 cells by inhibiting the transported mediated drug efflux (Figs. 5 and 6). None of dacomitinib, verapamil, KO143 significantly altered efflux pattern in parental KB-3-1 or NCI-H460 cells. Therefore, we suggest that the reversal effect of dacomitinib on ABCB1 and ABCG2 in MDR cells is not due to its effect on protein expressional levels or location change, but related to its inhibition of efflux and transport function.
EGFR is a transmembrane receptor that anchored in the cytoplasmic membrane and its structure is composed of an extracellular ligand-binding domain, a short hydrophobic transmembrane region, and an intracytoplasmic tyrosine kinase domain . The second generation TKIs were designed not only act as ATP mimics but also covalently bind Cys-797 of EGFR this enables them to irreversible inhibit EGFR kinase activity even in the presence of EGFR T790M . Dacomitinib covalently bind to a unique unpaired cysteine residue within the ATP binding pocket of tyrosine kinase domain, and irreversibly inhibits EGFR kinase activity by inhibiting autophosphorylation of EGFR，thereby inhibiting downstream signaling and leading to tumor-growth inhibition and apoptosis . Since the tyrosine kinase domain of EGFR has the ATP binding pocket which can activated by ATP, thus, EGFR actually acts as one of special type of “ATPase” and dacomitinib can inhibit the activity of this specific ATPase by blocking ATP link to ATP sites in tyrosine kinase domain.
As previous studies indicated that ABC transporters are characterized by one or two nucleotide-binding domains (NBDs) and two transmembrane domains (TMDs) . The conformational changes within the TMD domains are believed to be responsible for transport of substrates. But the transport function depends on bind and hydrolysis of cytoplasmic ATP within the NBDs and the ATP hydrolysis ensures the energy for transport of substrates . Transporters use ATP hydrolysis to pump molecules across the membrane are referred to as transport ATPases, and this large superfamily includes the rotary motor F-, A-, and V-ATPases, the P-type ATPases and the ABC transporters .
Since dacomitinib covalently binds to the tyrosine kinase domain of EGFR that irreversibly inhibit EGFR-ATPase activity, in addition, both EGFR and ABC transporter have ATP binding sites and the similar ATPase functions, then, dacomitinib maybe have the ability to inhibit the ATPase activity of ABC transporter. As showed in figure 7, the result of ATPase assay indicated that dacomitinib inhibited the ATPase activity both ABCB1 and ABCG2 in a concentration-dependent manner. This result also confirms that both ABCB1 and ABCG2 transporters are two types of ATPases, and dacomitinib reverses ABCB1 and ABCG2 transporter mediated MDR by inhibiting the ATPase activity.
Though dacomitinib possesses a similar down-regulated ATPase activity of ABCB1 and ABCG2, which only suggest the modulating effect is derive from the inhibition of drug-substrate binding in TMD, inhibition of ATP hydrolysis in NBD or both, the precise binding site and mechanism are still not clear. As reported before that many TKIs interact with ABC transporters as competitive substrates by binding to the drug-binding pocket in TMD of ABC transporter and can be transported [21,27]. In addition, NBDs of ABCB1 and ABCG2 exhibited high levels of sequence homology and possessed the similar conserved secondary structure topology . To investigate the potential mechanism of dacomitinib reverses ABC transporter mediated MDR from the perspective of molecular conformation, a virtual screening and molecular docking was carried out. According to the IFD simulation results, the Glide scores of dacomitinib at ATP-binding site was much lower than those at drug-binding site. Therefore, the inhibition of ABCB1 or ABCG2 activity by dacomitinib may not be resulted from blockage of ATP binding at NBDs, but the drug-binding pocket in TMDs of ABCB1 or ABCG2.
In conclusion, the present investigation suggested that dacomitinib may reverse ABCB1 and ABCG2 mediated MDR by directly inhibiting their efflux functions. The mechanisms of this modulating effect are likely to be related to the following: first, dacomitinib is an inhibitor of ABCB1 or ABCG2 transporters which bind to drug-substrate site in TMD in a noncompetitive manner. Second, dacomitinib binds to TMD and inhibits other chemotherapeutic drugs to bind to TMD and activate ATP hydrolysis, then inhibits its drug efflux function of ABCB1 or ABCG2 transporter. Since the combination of small molecule TKIs with conventional chemotherapeutic drugs has been one of the most common therapeutic strategies in the clinic. Our results suggest that dacomitinib could be used in EGFR over-expression patients with MDR against conventional chemotherapeutic drugs that are substrates of ABCB1 or ABCG2, and this combination therapy of dacomitinib with conventional chemotherapeutic agents may enhance the anticancer effect.
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