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Head and Neck Squamous Cell Carcinoma (HNSCC) remains a significant health burden due to tumor heterogeneity and treatment resistance, emphasizing the need for improved biological understanding and tailored therapies. This study enrolled 31 HNSCC patients for the establishment of patient-derived tumor organoids (PDOs), which faithfully maintained genomic features and histopathological traits of primary tumors. Long-term culture preserved key characteristics, affirming PDOs as robust representative models. PDOs demonstrated predictive capability for cisplatin treatment responses, correlating drug sensitivity with patient outcomes. Bulk and single-cell RNA sequencing unveiled molecular subtypes and intratumor heterogeneity (ITH) in PDOs, paralleling patient tumors. Notably, a hybrid epithelial-mesenchymal transition (hEMT)-like ITH program is associated with cisplatin resistance and poor patient survival. Functional analyses identified amphiregulin (AREG) as a potential regulator of the hybrid epithelial/mesenchymal state. Moreover, AREG contributes to cisplatin resistance via EGFR pathway activation, corroborated by clinical samples. In summary, HNSCC PDOs serve as reliable and versatile models, offer predictive insights into ITH programs and treatment responses, and uncover potential therapeutic targets for personalized medicine.
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http://dx.doi.org/10.1101/2024.06.28.601068 | DOI Listing |
J Med Chem
September 2025
Applied Pharmaceutical Science, Inc., Building 10-1, No.2, Jingyuan North Street, BDA, Beijing 100176, China.
This study reports the discovery and preclinical activity of APS03118, a novel selective RET inhibitor featuring a novel tricyclic pyrazolo[3',4':3,4]pyrazolo[1,5-]pyridine hinge-binding scaffold designed to overcome acquired resistance to first-generation selective RET inhibitors (SRIs). By enhancing hydrogen bonding with conserved hinge residues (Glu805, Ala807), APS03118 potently inhibits wild-type RET and diverse resistance mutations, including solvent-front (G810R/S/C), gatekeeper (V804M/L/E), roof (L730I/M), and hinge (Y806C/N/H) variants. In preclinical models, APS03118 induced complete tumor regression in KIF5B-RET and CCDC6-RET V804 M patient-derived xenografts (PDXs) and significantly prolonged survival in an intracranial CCDC6-RET metastasis model.
View Article and Find Full Text PDFJ Med Chem
September 2025
Repare Therapeutics, 7171 Frederick-Banting, Building 2, H4S 1Z9 Montréal, Québec, Canada.
DNA polymerase theta (Polθ) plays a critical role in repairing DNA double-strand breaks through microhomology-mediated end joining (MMEJ) and has emerged as a key synthetic lethal drug target in cancers with homologous recombination (HR) deficiencies. Its inhibition has shown a strong potential to synergize with PARP inhibitors, particularly in tumors with deleterious or mutations. Here, we describe the discovery and preclinical development of RP-2119, a selective, potent, and bioavailable Polθ ATPase inhibitor.
View Article and Find Full Text PDFCancer Res Commun
September 2025
Fred Hutchinson Cancer Center, Seattle, WA, United States.
Metastatic and relapsed osteosarcoma (OS) remains difficult to treat despite advanced surgical techniques, intensified chemotherapy, and targeted therapies. Adoptive immunotherapies such as chimeric antigen receptor (CAR) T cells, are in their nascent stage, but remain a viable therapeutic strategy for patients with aggressive solid tumors such as OS. Folate receptor- (FOLR1) has been functionally implicated in OS pathophysiology, providing rationale as a potential therapeutic target.
View Article and Find Full Text PDFNAR Genom Bioinform
September 2025
School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.
The translatability of patient-derived xenograft (PDX)-generated clinical data into patient-specific outcomes for therapeutic guidance is limited by the challenges in generalizability of models across patients, treatments, and cancer types. Previously, machine learning (ML) models have been developed for the two most abundant cancer types, i.e.
View Article and Find Full Text PDFAn integrated approach is proposed to rapidly evaluate the effects of anticancer treatments in 3D models, combining a droplet-based microfluidic platform for spheroid formation and single-spheroid chemotherapy application, label-free morphological analysis, and machine learning to assess treatment response. Morphological features of spheroids, such as size and color intensity, are extracted and selected using the multivariate information-based inductive causation algorithm, and used to train a neural network for spheroid classification into viability classes, derived from metabolic assays performed within the same platform as a benchmark. The model is tested on Ewing sarcoma cell lines and patient-derived xenograft (PDX) cells, demonstrating robust performance across datasets.
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