PDGFRA D842V

For therapeutic categories, performance reached 0.84 for avapritinib sensitivity and 0.81 for imatinib sensitivity. Prognostic performance was comparable to pathology-based scores, with highest discrimination in the overall cohort and in patients without adjuvant therapy. DL applied to WSIs enables prediction of molecular alterations, treatment sensitivity, and RFS in GIST, performing comparably to established risk scores across international cohorts, providing a baseline for future multimodal predictors.

This study characterizes the clinicopathological and molecular profiles of 29 Caucasian GIST patients, reinforcing the critical role of molecular stratification in clinical practice.

A comprehensive multi-metric sustainability assessment-utilizing ten tools including AES, AGREE, BAGI, RGB, and RAPI-confirmed the methods' excellent greenness (e.g., AES score = 90), superior practicality, and robust analytical performance, achieving a high White Index of 94.2%. With a substantially higher throughput of ~ 500 samples/hour and minimal solvent consumption (200µL/well), the proposed MW-SPMs offers a rapid, sustainable, and cost-effective alternative to conventional chromatographic and spectrofluorimetric techniques for routine pharmaceutical analysis, aligning with multiple United Nations Sustainable Development Goals.

P2, N=40, Active, not recruiting, National Cancer Institute (NCI) | Trial completion date: Jun 2026 --> Jun 2027 | Trial primary completion date: Jun 2026 --> Jun 2027

P2, N=28, Recruiting, Asan Medical Center | Not yet recruiting --> Recruiting

P2, N=28, Recruiting, Reema A. Patel | Trial completion date: Dec 2025 --> Dec 2027 | Trial primary completion date: Dec 2025 --> Dec 2027

For therapeutic categories, performance reached 0.84 for avapritinib sensitivity, 0.81 for imatinib sensitivity. DL applied to WSIs enables prediction of molecular alterations, treatment sensitivity, and RFS in GIST, performing comparably to established risk scores across international cohorts, providing a baseline for future multimodal predictors. Deep learning on histology predicts KIT and PDGFRA mutations in a large international cohort of GISTs from multiple centers Whole-slide image models stratify recurrence-free survival comparable to pathology-based risk scores Prognostic value of deep learning is preserved in adjuvant therapy subgroups, supporting treatment duration decisions.

Targeted tyrosine kinase inhibitors (TKIs) have transformed GIST management, with imatinib as the foundational first-line therapy and subsequent agents, sunitinib, regorafenib, avapritinib, and ripretinib, addressing primary or secondary resistance driven by diverse mutational patterns. Emerging therapeutic directions include next-generation kinase inhibitors, heat shock protein inhibitors, immunotherapy, metabolic and epigenetic targeting, and biomarker-driven individualized treatment strategies. This review synthesizes contemporary advances in the histopathological, molecular, and therapeutic landscape of GISTs, emphasizing an integrated diagnostic approach and highlighting ongoing efforts to overcome therapeutic resistance and optimize personalized care.

The remaining patient had an unresectable tumor and received tyrosine kinase inhibitor therapy; however, sequential treatment with imatinib and sunitinib was clinically ineffective. However, their clinical behavior differs: D842Y-mutant GISTs consistently present as large, hypervascular tumors associated with acute complications. The therapeutic efficacy of tyrosine kinase inhibitors remains unclear, underscoring the need for further case accumulation to better define the clinical course and determine optimal treatment strategies for this rare subtype.

While imatinib revolutionized first-line therapy, resistance and specific mutation profiles necessitate subsequent generations of tyrosine kinase inhibitors (TKIs). Second- and third-generation TKIs have transformed the management of advanced GIST, extending survival and offering mutation-specific precision therapy. Ongoing research into resistance mechanisms, combination strategies, and novel inhibitors promises further optimization of patient-centered care.

P2, N=40, Active, not recruiting, National Cancer Institute (NCI) | Trial completion date: Dec 2025 --> Jun 2026 | Trial primary completion date: Dec 2025 --> Jun 2026