Abstract
Gastrointestinal stromal tumors (GIST) are commonly treated with tyrosine kinase inhibitors (TKI). The majority of patients with advanced GIST ultimately become resistant to TKI due to acquisition of secondary KIT mutations, whereas primary resistance is mainly caused by PDGFRA p.D842V mutation. We tested the activity of avapritinib, a potent and highly selective inhibitor of mutated KIT and PDGFRA, in three patient-derived xenograft (PDX) GIST models carrying different KIT mutations, with differential sensitivity to standard TKI.
Experimental Design: NMRI nu/nu mice (n = 93) were transplanted with human GIST xenografts with KIT exon 11+17 (UZLX-GIST9KIT 11+17), exon 11 (UZLX-GIST3KIT 11), or exon 9 (UZLX-GIST2BKIT9) mutations, respectively. We compared avapritinib (10 and 30 mg/kg/once daily) versus vehicle, imatinib (50 mg/kg/bid) or regorafenib (30 mg/kg/once daily; UZLX-GIST9KIT11+17); avapritinib (10, 30, 100 mg/kg/once daily) versus vehicle or imatinib [UZLX-GIST3KIT11]; and avapritinib (10, 30, 60 mg/kg/once daily) versus vehicle, imatinib (50, 100 mg/kg/twice daily), or sunitinib (40 mg/kg/once daily; UZLX-GIST2BKIT9).
In all models, avapritinib resulted in reduction of tumor volume, significant inhibition of proliferation, and reduced KIT signaling. In two models, avapritinib led to remarkable histologic responses, increase in apoptosis, and inhibition of MAPK-phosphorylation. Avapritinib showed superior (UZLX-GIST9KIT 11+17 and -GIST2BKIT 9) or equal (UZLX-GIST3KIT 11) antitumor activity to the standard dose of imatinib. In UZLX-GIST9KIT 11+17, the antitumor effects of avapritinib were significantly better than with imatinib or regorafenib.
Avapritinib has significant antitumor activity in GIST PDX models characterized by different KIT mutations and sensitivity to established TKI. These data provide strong support for the ongoing clinical trials with avapritinib in patients with GIST (NCT02508532, NCT03465722).
Advanced gastrointestinal stromal tumors (GIST) are routinely treated with tyrosine kinase inhibitors (TKI). However, over time, the vast majority of patients develop resistance to TKI, mainly due to the acquisition of a secondary mutation in the activation loop of KIT. Both imatinib and sunitinib are ineffective in treating GIST with such mutations. Although regorafenib is active against some of these activation loop mutants, in the clinic it achieves a median progression-free survival of only 4.5 months. Avapritinib, a novel, potent, and selective inhibitor of KIT and PDGFRA activation loop mutations, showed robust in vivo antitumor activity in patient-derived GIST xenografts. Our preclinical findings indicate that avapritinib could be a relevant treatment for patients with GIST with primary or secondary resistance to approved TKI and support investigation in ongoing clinical trials in patients with GIST.
Introduction
Gastrointestinal stromal tumors (GIST) are the most common soft tissue sarcomas of the gastrointestinal tract with an annual incidence of 10 to 15 cases per million people (1). The discovery that the vast majority of GISTs are driven by activating mutations in KIT or platelet-derived growth factor receptor alpha (PDGFRA) has improved our understanding of the molecular pathogenesis of GIST and led to the successful development of targeted therapies for this malignancy (2). Mutations in KIT or PDGFRA lead to a constitutive, ligand-independent activation of kinase activity and their downstream signaling cascades, resulting in increased tumor cell proliferation and survival (2). Surgical resection is the only available curative treatment for primary, localized, and resectable GIST, yet 40% to 50% of patients will experience recurrent or metastatic disease during follow-up (3). Furthermore, a subset of patients is not eligible for surgical treatment due to anatomic limitations, general condition, or the presence of synchronous metastatic disease (1). The dependence of GIST on mutated receptor tyrosine kinase led to the exploration of tyrosine kinase inhibitors (TKI) for the systemic treatment of this rare but well-characterized malignancy. Imatinib, a small molecule with ATP-mimetic properties, has become the standard first-line treatment for patients with locally advanced, recurrent, inoperable, or metastatic disease (4). Imatinib has tremendously improved the survival of patients with GIST with advanced disease and achieves disease control in approximately 85% of the cases (5). Furthermore, the drug was found to extend relapse-free survival and overall survival when used in the adjuvant setting, after surgery in patients with high risk of relapse (1). In most patients with metastatic GIST, however, the duration of response to imatinib is limited. The occurrence of resistance, which is mainly caused by the acquisition of secondary mutations, leads to progression during treatment with imatinib or related compounds. Other small-molecule TKIs, such as sunitinib and regorafenib, are used in patients who are progressing on or are intolerant to imatinib (6). Despite their well-documented clinical activity in imatinib-refractory GIST and their broader activity against a variety of molecular targets, progression on these agents typically occurs after a median treatment duration of less than a year (6). To date, there are no established standard treatment alternatives for patients with GIST after failure on all three approved lines of TKI treatment, but a number of compounds are currently being tested in early clinical trials in patients with refractory tumors. Nevertheless, there is still an unmet medical need for novel treatment approaches, which should be tested first in preclinical settings.
Secondary mutation in KIT or PDGFRA is likely the most important event leading to TKI resistance. These mutations can occur in KIT exon 13 and 14, encoding the ATP-binding pocket of the receptor, or in exon 17 and 18, in the kinase activation loop. The latter stabilize the receptor in its active conformation, and the majority of these mutations are known to cause resistance to both imatinib and sunitinib, which are widely used as first- and second-line agents in the clinic (4). Although regorafenib is active against some of these mutated forms, a typical patient receiving this third-line treatment progresses after a median period of only 4–5 months (7, 8). Apart from the unsatisfactory efficacy of second- and third-line agents, their broader activity against multiple molecular targets leads to off-target toxicity, and many patients do not tolerate sunitinib and regorafenib as well as the first-line standard of care.
Avapritinib (BLU-285, Blueprint Medicines) is an oral, highly selective, and potent investigational inhibitor with activity against KIT exon 17 activation loop mutants, including KIT p.D816V. This mutation is a known driver mutation in systemic mastocytosis (9). In vitro, avapritinib disrupts KIT signaling as assessed by inhibition of both KIT phosphorylation and activation of downstream proteins such as AKT and STAT3 in human mast cell and leukemia cell lines (10). In vivo, avapritinib achieves dose-dependent tumor growth inhibition in a mouse model of systemic mastocytosis (10). Moreover, avapritinib also inhibits PDGFRA p.D842V (11), the mutation responsible for one out of five primary gastric GIST, for which there is no effective treatment available (12). Avapritinib is currently under investigation in patients with unresectable, treatment-resistant solid tumors including GIST (ClinicalTrials.gov: NCT02508532 and NCT03465722) and in advanced systemic mastocytosis (NCT02561988).
In this work, we assessed the preclinical activity of avapritinib in vivo, using three patient-derived xenograft (PDX) models of GIST, characterized by diverse KIT mutations and varying sensitivity to the available standard TKI therapies.
Materials and Methods
Xenograft models
For the current project, we transplanted three PDX models, established and fully characterized in the Laboratory of Experimental Oncology, KU Leuven (Leuven, Belgium). A total of 93 NMRI (nu/nu) mice (Janvier Laboratories) were bilaterally engrafted with models UZLX-GIST9KIT 11+17 (KIT: p.P577del;W557LfsX5;D820G), -GIST3KIT 11 (KIT: p.W557_V559delinsF), and -GIST2BKIT 9 (KIT: p.A502_Y503dup), which are known to retain morphologic and molecular features of the original tumor during passaging. The model characteristics and experimental set up are presented in Table 1. Xenografting of human tumors from consenting patients with GIST was approved by the Medical Ethics Committee of the University Hospitals Leuven and the animal experiments using PDX were approved by the Ethics Committee for Animal Research, KU Leuven, and performed according to its guidelines and Belgian regulations.
Detailed description of xenograft models and experimental set-up
Model name . | UZLX-GIST9KIT 11+17 . | UZLX-GIST3KIT 11 . | UZLX-GIST2BKIT 9 . |
---|---|---|---|
Model characteristics | |||
KIT mutation | Exon 11: p.P577del;W557LfsX5; exon 17: D820G | Exon 11: p.W557_V559delinsF | Exon 9: p.A502_Y503dup |
Sensitivity to imatinib in vivo | Resistant | Sensitive | Dose-dependent sensitivity |
Treatment groups | |||
Control | Vehiclea (n = 7) | Vehiclea (n = 6) | Vehiclea (n = 4) |
Imatinib | 50 mg/kg/bid (n = 7) | 50 mg/kg/bid (n = 5) | 50 mg/kg/bid (n = 4) |
n/a | n/a | 100 mg/kg/bid (n = 4) | |
Sunitinib | n/a | n/a | 40 mg/kg/qd (n = 4) |
Regorafenib | 30 mg/kg/qd (n = 7) | n/a | n/a |
Avapritinib | 10 mg/kg/qd (n = 6) | 10 mg/kg/qd (n = 6) | 10 mg/kg/qd (n = 5) |
30 mg/kg/qd (n = 6) | 30 mg/kg/qd (n = 6) | 30 mg/kg/qd (n = 5) | |
n/a | n/a | 60 mg/kg/qd (n = 5) | |
n/a | 100 mg/kg/qd (n = 6) | n/a |
Model name . | UZLX-GIST9KIT 11+17 . | UZLX-GIST3KIT 11 . | UZLX-GIST2BKIT 9 . |
---|---|---|---|
Model characteristics | |||
KIT mutation | Exon 11: p.P577del;W557LfsX5; exon 17: D820G | Exon 11: p.W557_V559delinsF | Exon 9: p.A502_Y503dup |
Sensitivity to imatinib in vivo | Resistant | Sensitive | Dose-dependent sensitivity |
Treatment groups | |||
Control | Vehiclea (n = 7) | Vehiclea (n = 6) | Vehiclea (n = 4) |
Imatinib | 50 mg/kg/bid (n = 7) | 50 mg/kg/bid (n = 5) | 50 mg/kg/bid (n = 4) |
n/a | n/a | 100 mg/kg/bid (n = 4) | |
Sunitinib | n/a | n/a | 40 mg/kg/qd (n = 4) |
Regorafenib | 30 mg/kg/qd (n = 7) | n/a | n/a |
Avapritinib | 10 mg/kg/qd (n = 6) | 10 mg/kg/qd (n = 6) | 10 mg/kg/qd (n = 5) |
30 mg/kg/qd (n = 6) | 30 mg/kg/qd (n = 6) | 30 mg/kg/qd (n = 5) | |
n/a | n/a | 60 mg/kg/qd (n = 5) | |
n/a | 100 mg/kg/qd (n = 6) | n/a |
Abbreviations: bid, twice daily; n, number of mice; n/a, not applicable; qd, once daily.
a0.5% carbomethyl cellulose with 1% Tween 80.
Drugs, reagents, and experimental design
The dosing solutions of imatinib, sunitinib, and regorafenib (all from Sequoia Research) were prepared as described earlier (13). Avapritinib, provided by Blueprint Medicines, was dissolved in 0.5% carboxymethyl cellulose supplemented with 1% Tween 80. The resulting suspension was kept at 4°C protected from light; a fresh suspension was prepared every 3 days. Chemical structures of all drugs used in the study are presented in Supplementary Fig. S1, the structure of avapritinib has been previously published by Evans and colleagues (11). When tumor growth had reached a threshold of 500 mm3, mice were treated with the oral compounds for 16 days by gavaging. The doses of 10 and 30 mg/kg avapritinib, tested in all three models, were chosen based on previous preclinical in vivo work in a KIT exon 17 mutant mastocytoma model demonstrating dose response activity that was well tolerated in vivo (11). The increased doses of avapritinib, used in models with primary mutations (i.e. UZLX-GIST3KIT 11 and UZLX-GIST2BKIT 9), were chosen based on the biochemical evaluation of avapritinib, which demonstrated IC50 of approximately 0.2–1 nmol/L on KIT exon 17 mutants, 1–2 nmol/L against KIT exon 11 mutants, and >50 nmol/L IC50 against KIT wild-type kinase domain (11) and suggested that potentially higher exposure of avapritinib might be required for inhibition of GIST tumors driven by primary KIT exon 9 and 11 mutants. The detailed information about treatment groups and doses are presented in Table 1. During the dosing period, tumor volume was measured three times per week using a digital caliper and the body weight and general well-being of the animals was followed up daily. At the end of the experiment, mice were sacrificed 2 hours after the last dose, and tumors were divided with one half snap frozen in liquid nitrogen and one half fixed in 4% buffered formaldehyde for further histopathologic and molecular assessments. Antitumor activity was assessed on the basis of the evolution of tumor volume expressed as the percentage of the normalized baseline value. Furthermore, histopathology and Western blotting were performed. For each mouse, the bilateral tumors were counted as independent events.
Western blotting and IHC were conducted using the following antibodies and reagents: KIT from Dako/Agilent; discovered on GIST 1 (DOG1) from Novocastra; phospho-KITY719 (pKITY719), phospho-KITY703 (pKITY703), phospho-AKTS473 (pAKTS473), AKT, α-tubulin, p42/44 MAPK, phospho-MAPK (pMAPK), 4-E binding protein 1 (4EBP1), phospho-4EBP1 (p4EBP1), histone H3 (HH3), phospho-HH3 (pHH3), and cleaved-PARP all from Cell Signaling Technology; Ki67 from Thermo Fisher Scientific; EnVision+ System-HRP and 3′diaminobenzidine-tetrahydrochloride (DAB), both from Dako/Agilent. For Western blotting, the secondary antibodies, conjugated with horseradish peroxidase, were from Cell Signaling Technology and Western Lightning Plus-ECL from PerkinElmer was used for band visualization.
Histopathology
Hematoxylin and eosin (H&E) staining was performed to evaluate the general tumor morphology, the histologic response (HR) to treatment, as well as to count mitotic and apoptotic cells. Stained tissue sections were analyzed using an Olympus CH-30M microscope (Olympus). Representative pictures were captured using the Olympus Color View digital camera and analyzed with Olympus Cell D imaging software. The HR was graded by assessing the magnitude of necrosis, myxoid degeneration, and/or fibrosis using a previously described grading system: grade 1 (0%–10% of tumor area), grade 2 (>10% and ≤50%), grade 3 (>50% and ≤90%), and grade 4 (>90%; refs. 14, 15). Moreover, IHC was performed for KIT and DOG1, Ki67, and pHH3 staining was used to assess proliferation, cleaved-PARP to quantify apoptosis and pMAPK to evaluate KIT pathway activity. Proliferation and apoptosis were assessed by counting the number of mitotic and apoptotic cells on H&E–stained slides and the IHC analysis was also based on counting positive cells. Both evaluations were performed in 10 high-power fields (HPF) at 400-fold magnification. The Ki67-labeling index was calculated as an average percentage of Ki67-stained nuclei in 5 digital images taken at 400-fold magnification. KIT pathway inhibition was evaluated by grading the intensity of the pMAPK staining as well as the percentage of tumor area showing positivity, as described in Supplementary Table S1.
Western blot analysis
Statistical analysis
The comparison between tumor volumes on day 1 versus day 16 was done using the Wilcoxon matched pair test (WMP). Comparisons between different treatment groups were done using the Mann–Whitney U test (MWU). A value of P < 0.05 was defined as statistically significant. STATISTICA version 13 (Dell Inc.) was used for all calculations.
Results
Tumor volume assessment
After the 16-day treatment period, vehicle-treated tumors from all models showed a steady and statistically significant increase in relative tumor volume (216% of the baseline volume for UZLX-GIST9KIT 11+17, 293% for -GIST3KIT 11, and 172% for -GIST2BKIT 9; P < 0.05 for all, WMP; Fig. 1). Consistent with previous reports, no significant difference was observed in the UZLX-GIST9KIT 11+17 model between the relative tumor volume of the vehicle- and imatinib-treated tumors (13), whereas regorafenib resulted in modest tumor regression (82% of baseline, P = 0.02 WMP). As expected, treatment with imatinib led to a regression in tumor volume (to 32% of baseline) in UZLX-GIST3KIT 11, confirming the imatinib sensitivity described previously (18). In contrast, UZLX-GIST2BKIT 9 tumors treated with the standard dose of imatinib (50 mg/kg) grew significantly. In this model, doubling the dose of imatinib led to tumor stabilization owing to the dose-dependent sensitivity to imatinib previously observed in this model and in line with the known behavior of KIT exon 9–mutated GIST in the clinic (1). Sunitinib caused significant tumor shrinkage in this model (Fig. 1).
Evolution of tumor volume during the treatment, presented as relative tumor volume (% change compared with normalized, baseline value) ± SD in UZLX-GIST9KIT 11+17 (A), -GIST3KIT 11 (B), and –GIST2BKIT 9 (C).
Evolution of tumor volume during the treatment, presented as relative tumor volume (% change compared with normalized, baseline value) ± SD in UZLX-GIST9KIT 11+17 (A), -GIST3KIT 11 (B), and –GIST2BKIT 9 (C).
In all three xenograft models, avapritinib (10 mg/kg) resulted in tumor volume stabilization compared with the baseline value. This effect was comparable to the effects induced by the higher dose of imatinib in UZLX-GIST2BKIT 9 (100 mg/kg) or to regorafenib in UZLX-GIST9KIT 11+17 (Fig. 1). Remarkably, at the dose of 30 mg/kg, avapritinib treatment resulted in substantial tumor regression as compared with baseline in two of the tested models, to 27% in UZLX-GIST9KIT 11+17 (P = 0.005) and to 26% in -GIST3KIT 11 (P = 0.008, both WMP), and tumor volume stabilization (90%) in UZLX-GIST2BKIT 9 (P = 0.08, WMP). Similarly, in UZLX-GIST3KIT 11, higher dose of avapritinib (100 mg/kg), led to a significant tumor regression to 26% of baseline value (P = 0.005, WMP), which was similar to the effect of imatinib in this model (Fig. 1B). In addition, in UZLX-GIST2BKIT 9, avapritinib at a dose of 60 mg/kg led to tumor shrinkage, which was significantly better than imatinib (at both doses) and comparable with sunitinib (Fig. 1C). Taken together, avapritinib induced remarkable and dose-dependent effects on tumor volume in all three models.
During the course of this study, the treatment with avapritinib was well tolerated, and mice had a stable body weight within ethically acceptable limits (Supplementary Fig. S2). We did observe a yellowish skin discoloration in all mice treated with 100 mg/kg of avapritinib, although it did not have any impact on the well-being of animals.
Histopathologic evaluation
In all three models, vehicle-treated tumors showed spindle cell morphology and diffuse KIT and DOG1 immunopositivity (Supplementary Fig. S3). These characteristics resembled features observed in the original patient samples used for xenografting, as well as those found in previous passages, proving stable morphology of the models. In addition, KIT mutational analysis of ex-mouse tumor samples confirmed the presence of mutations as seen in the patient biopsy.
HR was assessed on H&E–stained slides by evaluating the magnitude of the necrosis, fibrosis, and myxoid degeneration in the tumor tissue, induced by different treatments (Fig. 2A). Only minimal (grade 1) HR was observed in UZLX-GIST9KIT 11+17 tumors treated with imatinib. Regorafenib induced grade 2 HR in 36% of these tumors mainly through the induction of necrosis. As expected, and in line with our prior observations, imatinib caused grade 2 or higher HR in all treated UZLX-GIST3KIT 11 tumors, with 67% of the xenografts showing grade 3 HR. In the UZLX-GIST2BKIT 9 model, all tumors treated with imatinib (both at standard and higher dose) showed grade 1 HR.
A, Assessment of HR. B, Representative images of H&E staining after treatment (200× magnification). C, Mean number of mitotic cells in 10 HPF grouped by treatment. D, Assessment of pHH3 expression by Western blotting.
A, Assessment of HR. B, Representative images of H&E staining after treatment (200× magnification). C, Mean number of mitotic cells in 10 HPF grouped by treatment. D, Assessment of pHH3 expression by Western blotting.
In two out of three models, avapritinib resulted in remarkable HR. In UZLX-GIST9KIT 11+17, 30 mg/kg avapritinib induced grade 2 and grade 3 HR in 60% of the tumors. In UZLX-GIST3KIT 11, 10 mg/kg avapritinib induced grade 2 HR in the vast majority (80%) of the tumors. Moreover, the higher doses (30 and 100 mg/kg) led to grade 3 and grade 4 HR in this model. This effect was slightly more pronounced than in tumors treated with imatinib. Interestingly, in both UZLX-GIST9KIT 11+17 and -GIST3KIT 11, the HR observed with avapritinib was characterized mainly by the induction of myxoid degeneration, which is a typical response pattern observed in tumors collected from patients with GIST who responded to the treatment with imatinib in the clinic (ref. 19; Fig. 2A).
In all models, tumors in the vehicle-treated group showed high mitotic activity with an average of ≥45 mitotic figures in 10 HPF. Compared with vehicle, all doses of avapritinib led to a significant reduction of proliferation in all three xenograft models (Fig. 2B; Table 2). Remarkably, in the imatinib-resistant model UZLX-GIST9KIT 11+17, both 10 and 30 mg/kg avapritinib inhibited tumor proliferation significantly better than the other tested agents. The antiproliferative effect of avapritinib was comparable with imatinib in the imatinib-sensitive model, UZLX-GIST3KIT 11. In UZLX-GIST2BKIT 9, higher doses (30 and 60 mg/kg) of avapritinib inhibited the proliferation significantly better than imatinib. Moreover, avapritinib at 60 mg/kg had the same antiproliferative effect as sunitinib. These findings were confirmed by Western blotting of pHH3 and by IHC for pHH3 and Ki67 (Fig. 2B; Supplementary Fig. S4A; Table 2). The expression level of pHH3 showed a near-complete absence in avapritinib-treated tumors at both 10 and 30 mg/kg doses in UZLX-GIST9KIT 11+17, a marked decrease in -GIST3KIT 11, and a dose-dependent inhibition in -GIST2BKIT 9 (Fig. 2B).
Assessment of proliferation and apoptotic activity in GIST
. | . | UZLX-GIST9KIT 11+17 . | UZLX-GIST3KIT 11 . | UZLX-GIST2BKIT 9 . | |||
---|---|---|---|---|---|---|---|
. | . | pHH3 . | Ki67 . | pHH3 . | Ki67 . | pHH3 . | Ki67 . |
Proliferative activity | Imatinib (50 mg/kg) | = | = | ↓↓↓a | ↓↓↓a | = | = |
Imatinib (100 mg/kg) | n/a | n/a | n/a | n/a | ↓2.5a | ↓2.1a | |
Sunitinib | n/a | n/a | n/a | n/a | ↓↓↓a | ↓↓↓a | |
Regorafenib | = | = | n/a | n/a | n/a | n/a | |
Avapritinib (10 mg/kg) | ↓14.4a | ↓↓↓a | ↓↓↓a | ↓↓↓a | ↓1.3a | ↓1.9a | |
Avapritinib (30 mg/kg) | ↓↓↓a | ↓↓↓a | ↓↓↓a | ↓↓↓a | ↓3.4a | ↓3.9a | |
Avapritinib (60 mg/kg) | n/a | n/a | n/a | n/a | ↓13.9a | ↓7.9a | |
Avapritinib (100 mg/kg) | n/a | n/a | ↓↓↓a | ↓↓↓a | n/a | n/a | |
H&E | Cleaved PARP | H&E | Cleaved PARP | H&E | Cleaved PARP | ||
Apoptotic activity | Imatinib (50 mg/kg) | ↑2.1a | = | ↑6.5a | ↑6.8a | = | = |
Imatinib (100 mg/kg) | n/a | n/a | n/a | n/a | ↓6.8a | ↓2.4a | |
Sunitinib | n/a | n/a | n/a | n/a | ↓3.7 | ↓1.3a | |
Regorafenib | ↑3.0* | ↑2.6* | n/a | n/a | n/a | n/a | |
Avapritinib (10 mg/kg) | = | ↓2.6a | ↑4.5a | ↑2.3a | = | = | |
Avapritinib (30 mg/kg) | ↑3.4a | ↑3.0a | ↑5.7a | ↑17.1a | ↓2.3a | ↓1.9a | |
Avapritinib (60 mg/kg) | n/a | n/a | n/a | n/a | ↓2.6a | ↓1.9a | |
Avapritinib (100 mg/kg) | n/a | n/a | ↑8.7a | ↑18.1a | n/a | n/a |
. | . | UZLX-GIST9KIT 11+17 . | UZLX-GIST3KIT 11 . | UZLX-GIST2BKIT 9 . | |||
---|---|---|---|---|---|---|---|
. | . | pHH3 . | Ki67 . | pHH3 . | Ki67 . | pHH3 . | Ki67 . |
Proliferative activity | Imatinib (50 mg/kg) | = | = | ↓↓↓a | ↓↓↓a | = | = |
Imatinib (100 mg/kg) | n/a | n/a | n/a | n/a | ↓2.5a | ↓2.1a | |
Sunitinib | n/a | n/a | n/a | n/a | ↓↓↓a | ↓↓↓a | |
Regorafenib | = | = | n/a | n/a | n/a | n/a | |
Avapritinib (10 mg/kg) | ↓14.4a | ↓↓↓a | ↓↓↓a | ↓↓↓a | ↓1.3a | ↓1.9a | |
Avapritinib (30 mg/kg) | ↓↓↓a | ↓↓↓a | ↓↓↓a | ↓↓↓a | ↓3.4a | ↓3.9a | |
Avapritinib (60 mg/kg) | n/a | n/a | n/a | n/a | ↓13.9a | ↓7.9a | |
Avapritinib (100 mg/kg) | n/a | n/a | ↓↓↓a | ↓↓↓a | n/a | n/a | |
H&E | Cleaved PARP | H&E | Cleaved PARP | H&E | Cleaved PARP | ||
Apoptotic activity | Imatinib (50 mg/kg) | ↑2.1a | = | ↑6.5a | ↑6.8a | = | = |
Imatinib (100 mg/kg) | n/a | n/a | n/a | n/a | ↓6.8a | ↓2.4a | |
Sunitinib | n/a | n/a | n/a | n/a | ↓3.7 | ↓1.3a | |
Regorafenib | ↑3.0* | ↑2.6* | n/a | n/a | n/a | n/a | |
Avapritinib (10 mg/kg) | = | ↓2.6a | ↑4.5a | ↑2.3a | = | = | |
Avapritinib (30 mg/kg) | ↑3.4a | ↑3.0a | ↑5.7a | ↑17.1a | ↓2.3a | ↓1.9a | |
Avapritinib (60 mg/kg) | n/a | n/a | n/a | n/a | ↓2.6a | ↓1.9a | |
Avapritinib (100 mg/kg) | n/a | n/a | ↑8.7a | ↑18.1a | n/a | n/a |
NOTE: Values are presented as fold change in comparison with the vehicle-treated tumors.
Abbreviations: pHH3, phospho-histone H3.
aP < 0.05 compared with the vehicle-treated by Mann–Whitney U test.
↓Decrease.
↓↓↓>50-fold decrease.
↑Increase.
=No significant difference.
In two out of three models, avapritinib had significant proapoptotic activity. In UZLX-GIST9KIT 11+17, avapritinib (30 mg/kg) induced a significant increase in apoptosis (3.4-fold increase compared with vehicle-treated tumors, P < 0.001, MWU). This was comparable with the effects of regorafenib (3-fold increase; Table 2). In UZLX-GIST3KIT 11, all doses of avapritinib led to a significant and dose-dependent increase of apoptotic activity compared with the vehicle-treated tumors. However, the difference in the induction of apoptosis between the 30 and 100 mg/kg avapritinib or in comparison with imatinib was not statistically significant. Of note, in this model, the majority of the tumor cells in actively treated tumors were replaced by myxoid matrix, therefore counting apoptotic cells could only be done in areas with remaining viable cells, which may have had an impact on the reliability of the analysis.
Evaluation of KIT signaling
Western blot analysis showed that KIT and its downstream signaling proteins were expressed and activated in vehicle-treated tumors from all three models, as expected (Fig. 3A). In UZLX-GIST9KIT 11+17, avapritinib (30 mg/kg) inhibited phosphorylation of KITY703 as well as its downstream components, AKT and MAPK, and to a lesser extent, the phosphorylation of 4EBP1. Moreover, in UZLX-GIST3KIT 11, all treatments inhibited the phosphorylation of KIT as well as the downstream signaling proteins. In addition, the expression of total forms of the proteins was lower in imatinib- and avapritinib-treated tumors (30 and 100 mg/kg) in comparison with vehicle-treated, which was most likely related to the substantial decrease of the cellularity in the response to treatment. Similarly, expression of KIT was found to be lower in UZLX-GIST9KIT 11+17 tumors treated with 30 mg/kg avapritinib as compared with the vehicle-treated group (Fig. 3A). In UZLX-GIST2BKIT 9, phosphorylation of KITY703 and downstream proteins was inhibited by all treatments, with remarkable inhibition resulting from treatment with sunitinib and avapritinib at dose of 60 mg/kg (Fig. 3A and B). Even though avapritinib did not inhibit phospho-KIT completely in this model (Fig. 3A), the phospho-KIT expression, normalized against the total form of KIT, is significantly lower when compared with the vehicle-treated tumors (Fig. 3B). In UZLX-GIST2BKIT 9, sunitinib showed increased ability to decrease phospho-KIT, however its downstream inhibitory effect was mainly through the inhibition of phospho-AKT and not phospho-MAPK pathway, as is seen with other effective GIST agents (Fig. 3).
KIT signaling pathway. A, Assessment of the effect of treatments in different xenograft models. B, Densitometric assessment of phospho-protein forms in KIT signaling pathway.
KIT signaling pathway. A, Assessment of the effect of treatments in different xenograft models. B, Densitometric assessment of phospho-protein forms in KIT signaling pathway.
Subsequently, we also performed histopathologic assessment of KIT signaling using pMAPK immunostaining. The evaluation was based on both the staining intensity and percentage of tumor area showing positivity (Supplementary Table S1). In the two models (UZLX-GIST9KIT 11+17 and -GIST3KIT 11), we observed a strong to very strong MAPK phosphorylation in the majority of vehicle-treated tumors, whereas in UZLX-GIST2BKIT 9, staining was variable with focal positivity. In UZLX-GIST9KIT 11+17, treatment with imatinib or regorafenib did not affect MAPK phosphorylation, but in the majority of tumors treated with avapritinib, there was almost complete inhibition of phosphorylation, independent of a dose (Fig. 4). In UZLX-GIST3KIT 11, all active treatments reduced the MAPK phosphorylation substantially. In UZLX-GIST2BKIT 9, however, only a slight inhibition of phosphorylation was observed in avapritinib-treated tumors in comparison with the vehicle-treated group.
A, Evaluation of pMAPK positivity based on the intensity and percent tumor area showing pMAPK positivity. Grading system is presented in Supplementary Table S1. B, Representative images of pMAPK immunostaining of the different treatment groups at 200×.
A, Evaluation of pMAPK positivity based on the intensity and percent tumor area showing pMAPK positivity. Grading system is presented in Supplementary Table S1. B, Representative images of pMAPK immunostaining of the different treatment groups at 200×.
Discussion
Primary and acquired resistance to treatment with established TKI represents the ultimate challenge in the clinical setting of GIST, as there is no approved therapy for those who progress on agents with regulatory approval for treatment of patients with GIST. In this study, we were able to document a robust antitumor activity of avapritinib, a potent and selective KIT inhibitor, in three GIST PDX models characterized by different KIT mutations and varying sensitivity to standard TKI. All three xenografts utilized in this study were previously validated for preclinical testing of novel anti-GIST therapies (17, 20).
In the presented experiments, imatinib led to a significant tumor regression in UZLX-GIST3KIT 11 and a dose-dependent effect on tumor volume in UZLX-GIST2BKIT 9, as already observed in multiple studies, confirming once again the stable biological behavior of this model (13, 17, 18). These findings are also in line with the behavior of such tumors in the clinic; patients with KIT exon 9 mutations respond better to higher dose of imatinib, as confirmed by a clinical meta-analysis (21). Furthermore, in UZLX-GIST2BKIT 9, sunitinib caused tumor regression, which is consistent with others' observations that KIT exon 9 mutations benefit more from the therapy with sunitinib than with other agents (22). Taken together, these data demonstrate that our xenograft models exactly mirror the clinical situation and can provide further useful guidance for clinical evaluation of novel therapeutic approaches for GIST.
Avapritinib was designed to potently and selectively inhibit KIT exon 17 mutations (11). In vitro biochemical activity for the KIT p.D816V–mutated receptor was achieved with an IC50 = 0.27 nmol/L (11). This mutation is known to be causative for systemic mastocytosis, and is found in the vast majority of patients with this systemic disorder (10). Furthermore, avapritinib inhibits proliferation both in vitro and in vivo in leukemia models that harbor the KIT exon 17 p.N822K mutation (23). As expected, in our PDX model with KIT exon 11 and 17 mutations (UZLX-GIST9KIT 11+17 with KIT: p.P577del; W557LfsX5; D820G), avapritinib showed a beneficial effect on tumor volume as well as on proliferation, which most likely was caused by inhibition of KIT signaling. Of note, the secondary p.D820G exon 17 KIT mutation, present in our UZLX-GIST9KIT 11+17 model, has been reported in several TKI-resistant GIST cases with the incidence similar to other mutations affecting kinase activation loop domain of the receptor (24–27). In our UZLX-GIST9KIT 11+17–resistant model, the avapritinib dose of 10 mg/kg affected pathway activation, which resulted in a remarkable decrease of proliferation, however this dose led only to tumor stabilization and limited HR. On the other hand, the higher dose of the investigational agent (30 mg/kg) caused a striking tumor volume shrinkage (to 27% of baseline) and an impressive HR with complete absence of proliferative activity. This observation is similar to findings by Evans and colleagues where avapritinib potently inhibited the mouse equivalent of KIT p.D816Y–driven tumor growth in vivo in a dose-dependent manner (11). Moreover, in a GIST PDX model derived from a refractory GIST tumor that harbors KIT exon 11/17 (p.K557_K558del; Y823D), avapritinib again led to tumor regression from the baseline value (11). Interestingly, in our experiments, the pattern of response observed in UZLX-GIST9KIT 11+17 tumors treated with 30 mg/kg was characterized by myxoid degeneration; a phenomenon where viable tumor cells are replaced by an amorphous collagenous matrix containing only a few scattered cells. Myxoid degeneration is described frequently as a feature characteristic for GIST responding to the treatment with imatinib, both in preclinical and clinical settings (18, 19). Although in this resistant model, the effect of 30 mg/kg avapritinib on the tumor volume and histologic features was significantly better than what was achieved with 10 mg/kg, both treatment groups exposed to this novel TKI had better responses than imatinib- or regorafenib-treated tumors. The antitumor activity of avapritinib is currently being evaluated in GIST (NCT02508532 and NCT03465722; ref. 28). Of note, the maximum tolerated dose of avapritinib in patients is 400 mg/day whereas the dose of 300 mg/day is being evaluated in the currently ongoing phase III trial (NCT03465722). The animal equivalent dose, calculated on the basis of the body surface (29), is respectively 82 and 61.5 mg/kg, which falls within the range of doses tested in this study.
Subsequently, we evaluated avapritinib in two additional PDX models with a primary mutation in KIT exon 11 (UZLX-GIST3KIT 11, imatinib sensitive) or exon 9 (UZLX-GIST2BKIT 9, dose-dependent sensitivity to imatinib, sensitive to sunitinib). We observed a significant inhibition of proliferation in these models at all doses tested, suggesting broader inhibitory capacity of avapritinib against different KIT mutations outside of the activation loop region (11). In the UZLX-GIST3KIT 11 model, we found a pronounced effect on tumor volume and histologic responses at 30 and 100 mg/kg, and this observation was similar to the effect caused by imatinib. On the other hand, avapritinib in UZLX-GIST2BKIT 9 was better than imatinib, but only the dose of 60 mg/kg led to a similar efficacy as achieved with sunitinib. This observation suggests that avapritinib could also be effective in GIST with primary mutations, however higher in vivo concentrations are required for exon 9 antitumor activity. Our studies in mice suggest avapritinib is well tolerated at these higher concentrations, but clinical data will be required to fully assess the activity of avapritinib in patients with KIT exon 9–driven tumors The ongoing phase I clinical trial with avapritinib accepts patients who have failed two or more agents and likely have accumulated secondary resistance mutations, and patients with PDGFRA p.D842 mutant–driven GIST independent of prior lines of treatment. Interestingly, it is already known that avapritinib inhibits the activity of PDGFRA p.D842V–mutated receptor in vitro (11); the in vivo evaluation is hampered by the lack of relevant models with this mutation.
In our study, we found only a moderate proapoptotic effect in UZLX-GIST3KIT 11 and -GIST9KIT 11+17 (at a dose of 30 mg/kg), in part explained by the presence of myxoid degeneration as a response to avapritinib in these models. The reduced cellularity potentially leads to an underestimation of the proapoptotic effects of this treatment in our models. This speculation is supported by the observation of increased apoptosis in tumors harvested after 8 days of treatment with avapritinib, when the histologic response was not as pronounced as on day 16 (11). The proapoptotic effect of avapritinib is likely induced by inhibition of KIT signaling. This observation matches previous findings reported by our group, where potent KIT signaling inhibition resulted in an increased apoptosis (16, 17). Moreover, Evans and colleagues showed proapoptotic activity of avapritinib in a mouse mastocytoma cell line with KIT exon 17 substitution p.D814Y, the equivalent of human p.D816Y mutant (10, 23). On the other hand, in the UZLX-GIST2BKIT 9, neither of the experimental treatments led to an increase of apoptotic activity after 16 days of treatment. A trend toward a decline of apoptosis was observed with increasing dose of avapritinib. Similar observations were previously reported in this model, where treatments that led to inhibition of KIT signaling resulted in a decrease of apoptotic activity (17, 20). This effect could be a consequence of the variable expression of signaling molecules due to specific KIT genotype as reported by several groups (30–32).
Treatment with avapritinib was well tolerated in our nude mice. Although we observed yellow skin discoloration in mice treated with the highest avapritinib dose tested (100 mg/kg), it did not impact the animals' well-being. We also did not find any macroscopic or microscopic changes in their organs, including the liver. The skin color change may be due to a stronger systemic inhibition of KIT, disrupting its physiologic function in follicular melanocytes and or impairing melanogenesis (33). Skin depigmentation as a result of strong KIT inhibition was previously reported by Kim and colleagues in the evaluation of another potent KIT inhibitor, PLX3397 and was reported in metastatic renal cell carcinoma, treated with TKI sorafenib (34, 35).
As a selective inhibitor of KIT and PDGFRA p.D842V mutations, avapritinib is less likely to cause significant off target treatment-related toxicity at efficacious doses, in contrast to multitargeted agents currently being used in the clinical setting. Agents such as sunitinib, regorafenib, dasatinib, or ponatinib show effectiveness in some genotypes of resistant GIST, but dose-limiting toxicities, arising from the simultaneous blockage of several kinases, translates into higher toxicity and limit the clinical usefulness of some of these agents (36, 37). Although very preliminary data from the ongoing phase I clinical trial suggests a favorable safety profile (28), the high specificity of avapritinib can in theory increase the risk of rapid development of secondary resistance to this compound. GIST is known for its clinical inter- and intratumoral heterogeneity in terms of the mutational profile, and it is likely that some clones of this disease may lead to further progression on treatment with the novel agent. In this context, it is noteworthy that we saw broad activity in a variety of GIST genotype in our mice.
In conclusion, we provide in vivo evidence that the novel TKI avapritinib has significant antitumor activity in GIST PDX models. Our results demonstrate that in KIT exon 11+17 double mutated GIST, this inhibitor is more active than established standard treatments. Moreover, in imatinib-sensitive models with primary KIT mutations, avapritinib shows a similar or even higher level of activity in comparison with imatinib. In all models tested, the pharmacologic antiproliferative effect on tumor volume was mainly achieved through a marked inhibition of KIT signaling. Our data strongly support the scientific rationale of the ongoing exploration of avapritinib in GIST and provide arguments for exploration of the novel compound in the clinic in both imatinib-sensitive and TKI-resistant genotypes of this mesenchymal malignancy. The results seen in our mouse PDXs and the early findings reported from the ongoing clinical trial in patients with GIST suggest that avapritinib has the potential to become an important treatment option for this orphan malignancy.
Disclosure of Potential Conflicts of Interest
E. Evans, A.K. Gardino, and C. Lengauer have ownership interests (including patents) in Blueprint Medicines. No potential conflicts of interest were disclosed by the other authors.
Authors' Contributions
Conception and design: A. Wozniak, E. Evans, C. Lengauer, P. Schöffski
Development of methodology: Y.K Gebreyohannes, A. Wozniak, J. Wellens, M. Debiec-Rychter, P. Schöffski
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): Y.K Gebreyohannes, A. Wozniak, M.-E. Zhai, J. Wellens, J. Cornillie, R. Sciot, P. Schöffski
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Y.K Gebreyohannes, A. Wozniak, M.-E. Zhai, E. Evans, C. Lengauer, R. Sciot, P. Schöffski
Writing, review, and/or revision of the manuscript: Y.K Gebreyohannes, A. Wozniak, M.-E. Zhai, J. Cornillie, E. Evans, A.K. Gardino, C. Lengauer, M. Debiec-Rychter, R. Sciot, P. Schöffski
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): J. Wellens, U. Vanleeuw, M. Debiec-Rychter, P. Schöffski
Study supervision: E. Evans, C. Lengauer, P. Schöffski
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