Emerging mechanisms of kinase inhibitor escape and clinical implications of ponatinib in advanced gastrointestinal stromal tumor

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal malignancies of the gastrointestinal tract. Oncogenic, gain-of-function mutations in KIT and PDGFRA genes are detected in approximately 85% and 5% of cases, respectively (1,2). Both receptors are single-pass transmembrane tyrosine kinases (TK) composed of an extracellular, ligand-binding and dimerization domain (partly encoded by KIT exon 9), an autoinhibitory juxtamembrane domain (exon 11 in KIT and exon 12 in PDGFRA), and a split cytoplasmic kinase domain. The kinase domain comprises an ATP-binding pocket (AP), encoded by KIT exons 13 and 14 and by PDGFRA exons 14 and 15, and an activation loop (AL), encoded by KIT exons 17 and 18 and by PDGFRA exon 18 (3).

The treatment landscape of metastatic GISTs has undergone a remarkable transformation since the introduction of imatinib more than two decades ago, establishing oncogene-directed therapy as a paradigm in solid tumors (4). Despite successive generations of tyrosine kinase inhibitors (TKIs), resistance remains inevitable for most patients with dismal prognosis and effective options beyond ripretinib remain limited (3,5,6). Moreover, the emergence of secondary AP and AL mutations after ripretinib highlights the need for new strategies and next-generation KIT inhibitors (3). In this context, the phase II POETIG trial reported by Falkenhorst and colleagues provides a timely and nuanced evaluation of a lower dose of ponatinib as salvage therapy, while offering important translational insights into the evolving biology of KIT resistance and the promise of precision-guided treatment selection (6).

A central concept reinforced is the recognition that KIT remains the dominant oncogenic driver throughout the natural history of GIST, even in late-line disease (3,5,7). During the early use of imatinib, a characteristic pattern of disease progression was observed after an initial clinical response (8,9). On computed tomography (CT) imaging, this pattern appeared as a newly growing focal lesion within or adjacent to previously responding tumor masses and was termed a “resistant nodule” (8,9). Molecular profiling of these nodules demonstrated that they represent true disease progression driven by resistant subclones rather than independent neoplasms (8,9). Secondary progression was shown to be associated with newly acquired KIT mutations, consistently located within the kinase domain (exons 13, 14, and 17, 18) (8,9). The close spatial relationship between resistant nodules and the original tumor supports a model of clonal evolution from pre-existing tumor cells (3,7-9).

Collectively, these observations have driven the development of multiple generations of TKIs and the realization that effective long-term control of GIST requires mutation-matched inhibition of distinct KIT conformations and resistance mechanisms (Table 1). Recent ctDNA studies further confirm that resistance is predominantly mediated by heterogeneous secondary KIT mutations rather than pathway bypass or lineage plasticity (10-13).

Bleckmann and colleagues also demonstrated a strong correlation between ctDNA levels and tumor volume while noting that up to 30% of patients with GIST may not shed detectable ctDNA. With progressive disease, tumor burden correlated more closely with ctDNA levels than conventional Response Evaluation Criteria In Solid Tumors (RECIST) 1.1 assessments, and ctDNA became undetectable in patients achieving effective treatment responses. These findings indicate that ctDNA monitoring can provide a sensitive, non-invasive marker of disease burden and treatment efficacy, with the potential to complement and, in selected settings, outperform routine radiologic surveillance (13). ctDNA also offers a practical advantage in assessing and therapeutic decisions in metastatic GIST, as it provides a less invasive alternative to CT-guided tissue biopsy. This is particularly relevant when metastatic lesions are not always safely accessible for percutaneous sampling (10-13).

The cytoplasmic kinase domain of receptor TK enzyme dynamically transitions between active and inactive conformations, regulated by key structural elements including the glycine-rich loop, the αC-helix, and the DFG motif within the AL. Secondary mutations affecting these elements can shift the conformational equilibrium toward the active state, leading to sustained kinase activation and potential drug resistance. These resistance mutations predominantly cluster within two functional regions of the kinase domain: the AP and the AL (3,14,15).

Secondary and tertiary KIT mutations are rarely present before first-line imatinib and instead arise under treatment pressure in slowly proliferating residual clones (3). During early imatinib therapy, a single secondary mutation in the AP or AL hotspot is usually sufficient to restore KIT signaling (9,16). Simultaneous acquisition of additional (both AP/AL) mutations on the same allele is unlikely because it confers little further growth advantage and may even be a disadvantage to the proliferating tumor cells (16). Although treatment duration contributes to the accumulation of resistance, the inhibitory spectrum of each TKI is a key determinant of which mutations ultimately dominate (16).

The clinical relevance of this distinction has become increasingly apparent, as different TKIs exhibit strikingly complementary inhibitory profiles. Sunitinib preferentially inhibits AP mutations, whereas ripretinib and avapritinib show greater activity against AL mutations (3,15,17). Sunitinib effectively suppresses the common imatinib-resistant AP mutation (V654A) but has little activity against AL mutants, allowing AL mutant subclones to expand under selective pressure and drive progression. By contrast, ripretinib partially suppresses AL mutants but is weaker against many AP alterations, which explains why combined AP/AL resistance patterns are most frequently observed after ripretinib. The selective growth of AL mutants and metastases during sunitinib therapy was clearly demonstrated in the ctDNA analysis of the INTRIGUE trial (10). This trial, conducted in the second-line setting for imatinib-resistant advanced GIST, highlighted the value of ctDNA-based next-generation sequencing in characterizing the complex spectrum of KIT mutations and linking mutational profiles to therapeutic response. A clear pattern of differential drug sensitivity emerged. Patients harboring KIT exon 11 plus exon 13/14 (AP) mutations experienced greater clinical benefit with sunitinib compared with ripretinib. In contrast, patients with KIT exon 11 plus exon 17/18 (AL) mutations demonstrated superior outcomes with ripretinib relative to sunitinib. These findings underscore the importance of molecularly informed treatment selection in the second‑line setting.

In addition, due to the lesser tolerability of sunitinib, with more frequent dose interruptions and reduction, it likely limits effective kinase suppression and may facilitate clonal escape (3). Currently, no approved agent effectively targets both (AP/AL) mutation classes, and many patients in late-line settings harbor polyclonal resistance involving both domains (10). In addition, patients with KIT mutant GIST progressing on ripretinib lack approved therapeutic options (3).

Ponatinib occupies a unique position in the GIST therapeutic landscape as a type II TK inhibitor that binds and stabilizes the inactive, DFG-out conformation of the kinase (18). Unlike other approved GIST therapies, ponatinib was specifically engineered to overcome gatekeeper mutations. Its rigid carbon-carbon triple-bond linker enables the molecule to bypass steric hindrance imposed by the KIT T670I gatekeeper substitution, analogous to the BCR-ABL T315I mutation in CML (19). Whereas many TKIs lose potency when confronted with bulky gatekeeper substitutions, ponatinib can accommodate such changes, explaining its activity against T670I mutant KIT (6).

Secondly, the trifluoromethyl (CF₃) group extending into the hydrophobic back pocket enhances binding affinity and enables ponatinib to stabilize inactive KIT conformations even in the presence of AL mutations that favor the active state (6,18). Structural analyses demonstrate that key residues interacting with this CF₃ group remain relatively static during conformational transitions, enabling ponatinib to bind a range of intermediate states and inhibit KIT signaling despite AL mutations (6). This enables ponatinib to maintain activity against multiple AL (exon 17/18) mutations (20).

Preclinical and structure-based studies have demonstrated that ponatinib potently inhibits KIT AL mutants and the T670I gatekeeper mutation, a combination of resistance mechanisms insufficiently covered by other TKIs (20). In contrast, secondary AP mutations such as V654A disrupt key stabilizing interactions and induce unfavorable conformational dynamics, conferring resistance to ponatinib (6,20).

Early clinical experience with ponatinib at 45 mg daily showed signals of activity but was limited by significant cardiovascular toxicity, motivating evaluation of lower doses and biomarker-guided patient selection. In these studies, ponatinib showed limited activity in tumors with primary KIT exon 9 mutations, and disease progression was frequently associated with the emergence of V654A mutation (21).

The POETIG trial was designed in this background to evaluate the efficacy and safety of low-dose ponatinib and to explore the value of ctDNA-based biomarkers for patient stratification (6). It enrolled patients with or unresectable KIT-mutant GIST who had progressed on or were intolerant to imatinib, with a focus on second-line patients (sunitinib vs. ripretinib) stratified by the presence of (cohort A) or absence of (cohort B) V654A resistance mutation, respectively. Cohort C represented pretreated patients who progressed on imatinib, sunitinib, and regorafenib regardless of secondary resistance mutations. Due to slower accrual, both second-line cohorts (A and B) were pooled for safety and descriptive efficacy analyses.

The trial generated a dataset that integrates clinical outcome, safety, quality of life, liquid biopsy analyses, and mechanistic modeling (6). Clinically, ponatinib demonstrated limited overall activity, with clinical benefit rates at 16 weeks of approximately 26% in pooled second-line patients and 33% in late-line patients. Median progression-free survival was short, reflecting aggressive biology and the highly resistant burden in this population (6). However, a distinct subset of patients achieved durable disease control, in some cases exceeding 1 year, indicating that meaningful benefit can be obtained when ponatinib is matched to an appropriate molecular context. This is an important observation in a setting where no approved post-ripretinib options exist (3,6).

At a dose of 30 mg once daily, ponatinib showed an improved tolerability compared with earlier high-dose studies (20,21). Although adverse events were frequent, most were manageable with dose modifications. Arterial and venous occlusive events remained a concern, but severe events were infrequent and no treatment-related deaths occurred. Quality of-life measures, including fatigue, remained largely stable during therapy, with only modest increases in foot soreness, supporting the feasibility of lower-dose ponatinib in carefully selected and monitored patients (6).

The most informative findings of POETIG trial emerged from its translational analyses, particularly the integration of ctDNA profiling and structure-based modeling. Using droplet digital PCR to detect the KIT resistance mutations V654A and T670I allowed the investigators to explore the relationship between molecular genotype, inform on treatment efficacy and clinical outcome. Patients with isolated T670I mutations experienced prolonged progression-free survival, with several remaining on therapy for more than 1 year, whereas patients harboring V654A derived little benefit and typically progressed rapidly (6). The high sensitivity of this approach enables the detection of low-frequency resistant clones and provides clinically relevant information, despite being restricted to predefined mutations (22-24).

Ponatinib binds the inactive DFG-out conformation and engages conserved back-pocket residues via a CF₃ substituent, enabling inhibition of AL mutants and stabilization of intermediate inactive states (18). Its rigid ethynyl linker permits binding despite bulky gatekeeper substitutions, explaining its activity against KIT T670I. In contrast, AP mutations such as V654A change the shape and hydrophobic contacts of the binding site and alter αC-helix dynamics. This reduces compatibility with type II inhibitor binding, conferring resistance (20).

The trial also sheds light on the influence of primary KIT mutations on ponatinib efficacy. Patients with KIT exon 11 mutations, particularly those involving codon W557 variants (deletions or substitutions), showed greater benefit than those with exon 9 mutations. This is consistent with structural evidence that certain exon 11 alterations facilitate access to the inactive kinase conformation and enhance type II inhibitor binding (6,20).

Exon 9 mutations occur in the extracellular dimerization domain of KIT, producing a ligand-dependent activation mechanism that is structurally and functionally distinct from juxta membrane (exon 11) or kinase domain (exons 13–18) mutants. Exon 9 mutant GISTs show partial stem cell factor (SCF) dependence, and this ligand‑driven dimerization keeps KIT in a more active, stabilized conformation, which reduces the duration the receptor spends in the inactive state that imatinib preferentially binds. They are intrinsically less sensitive to most TKIs. This biologic difference explains the need for higher imatinib dosing and the generally reduced efficacy of several later-line TKIs in exon 9 mutant GIST. Ponatinib shows variable or limited activity, likely because the extracellular-domain mutation does not create a strong kinase-domain vulnerability (25). Nevertheless, mechanistically, ponatinib may retain activity in exon 9 mutant tumors when secondary AL mutations are present, a scenario more frequently encountered after sunitinib exposure (3,6,7,10).

These observations were corroborated in preclinical models. In isogenic GIST cell lines, ponatinib showed potent activity against exon 11 and exon 17/18 mutants and was the most effective inhibitor against the T670I gatekeeper mutation (6). However, consistent with clinical findings, ponatinib was ineffective against cell lines harboring AP mutations such as V654A or compound AP/AL mutations, highlighting the limits of its inhibitory profile (3,6,20).

Overall, the POETIG trial defines ponatinib as a precision therapy for a molecularly restricted subgroup of GIST, rather than a broadly applicable salvage agent. Its optimal use appears confined to tumors with primary exon 11 mutations and secondary resistance driven by T670I and/or AL alterations. Conversely, in tumors dominated by tertiary AP mutations, alternative strategies will be required, potentially involving next-generation inhibitors or combination approaches (6). More broadly, the study highlights the value of integrating ctDNA profiling and structure-based analyses to guide treatment selection in a disease characterized by pronounced spatial and temporal heterogeneity of resistance (10,26).

Advances in GIST management remain limited by the constraints of current diagnostic tools and the stability, availability, and specificity of existing pharmacologic therapies. Recent work has explored other drugdelivery strategies, including antibody-drug conjugates, radioligand therapy, and nanoparticle-based systems, to overcome these barriers (27).

Nanotechnology, in particular, offers opportunities for earlier detection, refined biological modeling, and more precise therapeutic targeting. These platforms can encapsulate therapeutic agents, enhance tumor targeting, and reduce systemic toxicity (28). Metalbased, polymeric, lipid-derived, magnetic, and fluorescent nanoparticles have all been investigated for potential application in GIST (29). Their accumulation within tumors is facilitated by the enhanced permeability and retention effect, and targeting specificity can be increased by functionalizing nanoparticle surfaces with tumorassociated ligands such as antibodies (28). Prolonged circulation time and partial protection from hepatic and renal clearance further improve therapeutic exposure, while alternative delivery approaches such as endoscopic instillation for intestinal tumors are being explored (28).

Nanotechnology is also advancing experimental modeling. Nanofibrous scaffolds may mimic extracellular matrix architecture and support three-dimensional culture systems that better recapitulate tumor biology than traditional monolayers. Produced through electrospinning, nanoprecipitation, or fiber swelling, these scaffolds promote cell adhesion, proliferation, and differentiation, and provide valuable platforms for drug screening and mechanistic studies. Challenges include cell manipulation, engraftment efficiency, and nutrient diffusion within dense constructs (29).

Although nanomedicine has entered several oncologic treatment pathways, continued research is needed to optimize nanoparticle design, enhance clinical translation, and integrate these technologies into personalized therapeutic strategies for GIST (28,29).

In conclusion, POETIG trial shows that ponatinib has limited activity in unselected advanced GIST, but can provide meaningful and durable benefit in carefully defined molecular subgroups. By linking structural mechanisms and resistance with ctDNA-based biomarkers, the study advances the precision treatment of KIT-driven advanced GIST. These findings highlight the need to incorporate molecular stratification and longitudinal ctDNA profiling into late-line trial design (22,23,26). Future strategies should combine high-sensitivity and broad sequencing approaches, and explore rational combinations or adaptive TKI sequencing to address polyclonal resistance. Ultimately, integrating liquid biopsy, structural biology, and precision trials will be essential to extend durable disease control in advanced GIST.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Journal of Gastrointestinal Oncology. The article has undergone external peer review.

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0120/prf

Funding: None.

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0120/coif). The author has no conflicts of interest to declare.

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

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

References

1. Hirota S, Isozaki K, Moriyama Y, et al. Gain-of-function mutations of c-kit in human gastrointestinal stromal tumors. Science 1998;279:577-80. [Crossref] [PubMed]
2. Heinrich MC, Corless CL, Duensing A, et al. PDGFRA activating mutations in gastrointestinal stromal tumors. Science 2003;299:708-10. [Crossref] [PubMed]
3. Mühlenberg T, Falkenhorst J, Schulz T, et al. KIT ATP-Binding Pocket/Activation Loop Mutations in GI Stromal Tumor: Emerging Mechanisms of Kinase Inhibitor Escape. J Clin Oncol 2024;42:1439-49. [Crossref] [PubMed]
4. Demetri GD. Targeting c-kit mutations in solid tumors: scientific rationale and novel therapeutic options. Semin Oncol 2001;28:19-26.
5. Heinrich MC, Corless CL, Blanke CD, et al. Molecular correlates of imatinib resistance in gastrointestinal stromal tumors. J Clin Oncol 2006;24:4764-74. [Crossref] [PubMed]
6. Falkenhorst J, Ivanyi P, Schulz T, et al. Phase II Trial of Ponatinib in Patients with Metastatic Gastrointestinal Stromal Tumor following Failure or Intolerance of Prior Therapy with Imatinib (POETIG Trial). Clin Cancer Res 2025;31:4059-69. [Crossref] [PubMed]
7. Bauer S, Heinrich MC, George S, et al. Clinical Activity of Ripretinib in Patients with Advanced Gastrointestinal Stromal Tumor Harboring Heterogeneous KIT/PDGFRA Mutations in the Phase III INVICTUS Study. Clin Cancer Res 2021;27:6333-42. [Crossref] [PubMed]
8. Wardelmann E, Merkelbach-Bruse S, Pauls K, et al. Polyclonal evolution of multiple secondary KIT mutations in gastrointestinal stromal tumors under treatment with imatinib mesylate. Clin Cancer Res 2006;12:1743-9. [Crossref] [PubMed]
9. Desai J, Shankar S, Heinrich MC, et al. Clonal evolution of resistance to imatinib in patients with metastatic gastrointestinal stromal tumors. Clin Cancer Res 2007;13:5398-405. [Crossref] [PubMed]
10. Heinrich MC, Jones RL, George S, et al. Ripretinib versus sunitinib in gastrointestinal stromal tumor: ctDNA biomarker analysis of the phase 3 INTRIGUE trial. Nat Med 2024;30:498-506. [Crossref] [PubMed]
11. Serrano C, Vivancos A, López-Pousa A, et al. Clinical value of next generation sequencing of plasma cell-free DNA in gastrointestinal stromal tumors. BMC Cancer 2020;20:99. [Crossref] [PubMed]
12. Gómez-Peregrina D, Cicala CM, Serrano C. Monitoring advanced gastrointestinal stromal tumor with circulating tumor DNA. Curr Opin Oncol 2024;36:282-90. [Crossref] [PubMed]
13. Bleckman RF, Haag CMSC, Rifaela N, et al. Levels of circulating tumor DNA correlate with tumor volume in gastro-intestinal stromal tumors: an exploratory long-term follow-up study. Mol Oncol 2024;18:2658-67. [Crossref] [PubMed]
14. Serrano C, Mariño-Enríquez A, Tao DL, et al. Complementary activity of tyrosine kinase inhibitors against secondary kit mutations in imatinib-resistant gastrointestinal stromal tumours. Br J Cancer 2019;120:612-20. [Crossref] [PubMed]
15. Smith BD, Kaufman MD, Lu WP, et al. Ripretinib (DCC-2618) Is a Switch Control Kinase Inhibitor of a Broad Spectrum of Oncogenic and Drug-Resistant KIT and PDGFRA Variants. Cancer Cell 2019;35:738-51.e9.
16. Bauer S, Fletcher JA, Rauh D, et al. Reply to Y. Xia et al. J Clin Oncol 2024;42:3260-1.
17. Heinrich MC, Jones RL, von Mehren M, et al. Avapritinib in advanced PDGFRA D842V-mutant gastrointestinal stromal tumour (NAVIGATOR): a multicentre, open-label, phase 1 trial. Lancet Oncol 2020;21:935-46. [Crossref] [PubMed]
18. Pereira WA, Nascimento ÉCM, Martins JBL. Electronic and structural study of T315I mutated form in DFG-out conformation of BCR-ABL inhibitors. J Biomol Struct Dyn 2022;40:9774-88. [Crossref] [PubMed]
19. Cortes JE, Kantarjian H, Shah NP, et al. Ponatinib in refractory Philadelphia chromosome-positive leukemias. N Engl J Med 2012;367:2075-88. [Crossref] [PubMed]
20. Garner AP, Gozgit JM, Anjum R, et al. Ponatinib inhibits polyclonal drug-resistant KIT oncoproteins and shows therapeutic potential in heavily pretreated gastrointestinal stromal tumor (GIST) patients. Clin Cancer Res 2014;20:5745-55. [Crossref] [PubMed]
21. George S, von Mehren M, Fletcher JA, et al. Phase II Study of Ponatinib in Advanced Gastrointestinal Stromal Tumors: Efficacy, Safety, and Impact of Liquid Biopsy and Other Biomarkers. Clin Cancer Res 2022;28:1268-76. [Crossref] [PubMed]
22. Falkenhorst J, Grunewald S, Krzeciesa D, et al. Plasma Sequencing for Patients with GIST-Limitations and Opportunities in an Academic Setting. Cancers (Basel) 2022;14:5496. [Crossref] [PubMed]
23. Mechahougui H, Hildebrand L, Haberberger J, et al. Clinical Use of Liquid-Based Comprehensive Genomic Profiling in Gastrointestinal Stromal Tumors. Lab Invest 2025;105:104116. [Crossref] [PubMed]
24. Rodriquenz MG, Pasculli B, Rendina M, et al. Comprehensive Molecular Screening by Next Generation Sequencing of Gastrointestinal Stromal Tumors (GISTs): In Silico Analysis and Classification of Rare KIT Exon 11 Mutations. Cancer Med 2025;14:e71430. [Crossref] [PubMed]
25. Napolitano A, Thway K, Smith MJ, et al. KIT Exon 9-Mutated Gastrointestinal Stromal Tumours: Biology and Treatment. Chemotherapy 2022;67:81-90. [Crossref] [PubMed]
26. Serrano C, Bauer S, Gómez-Peregrina D, et al. Circulating tumor DNA analysis of the phase III VOYAGER trial: KIT mutational landscape and outcomes in patients with advanced gastrointestinal stromal tumor treated with avapritinib or regorafenib. Ann Oncol 2023;34:615-25. [Crossref] [PubMed]
27. Klug LR, Khosroyani HM, Kent JD, et al. New treatment strategies for advanced-stage gastrointestinal stromal tumours. Nat Rev Clin Oncol 2022;19:328-41. [Crossref] [PubMed]
28. Jefremow A, Neurath MF. Nanoparticles in Gastrooncology. Visc Med 2020;36:88-94. [Crossref] [PubMed]
29. Gabellone S, Vanni S, Fausti V, et al. Exploring nanotechnology solutions for improved outcomes in gastrointestinal stromal tumors. Heliyon 2024;10:e40596. [Crossref] [PubMed]