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Patient-derived organoid modeling predicts personalized drug responses in prostate-metastatic mantle cell lymphoma: a case report.

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Anti-cancer drugs 📖 저널 OA 23.3% 2022: 0/1 OA 2023: 0/3 OA 2024: 0/3 OA 2025: 8/16 OA 2026: 6/37 OA 2022~2026 2025 Vol.36(10) p. 830-838
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Wang X, Fu G, Wan J, Lin D, Shui M, Zhou T

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Tumor heterogeneity represents a significant challenge in cancer treatment.

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↓ .bib ↓ .ris
APA Wang X, Fu G, et al. (2025). Patient-derived organoid modeling predicts personalized drug responses in prostate-metastatic mantle cell lymphoma: a case report.. Anti-cancer drugs, 36(10), 830-838. https://doi.org/10.1097/CAD.0000000000001760
MLA Wang X, et al.. "Patient-derived organoid modeling predicts personalized drug responses in prostate-metastatic mantle cell lymphoma: a case report.." Anti-cancer drugs, vol. 36, no. 10, 2025, pp. 830-838.
PMID 40762074 ↗

Abstract

Tumor heterogeneity represents a significant challenge in cancer treatment. Current therapeutic strategies frequently rely on single biopsy assessments that may not fully capture tumor complexity. In this study, we developed prostate patient-derived organoids (PDOs) from a mantle cell lymphoma (MCL) case with prostatic metastasis. Monotherapy experiments revealed that the prostate organoids were sensitive to gemcitabine but resistant to rituximab and oxaliplatin. In combination therapy experiments, the half maximal inhibitory concentration value of gemcitabine increased, indicating that the combination regimen may attenuate its efficacy. In addition, the expression of prostate cancer markers prostate-specific membrane antigen and ETS-related gene was detected in the organoids. The research findings indicate that the PDO model not only dynamically monitors changes in drug sensitivity caused by heterogeneity but also serves as a powerful tool for predicting drug responses and optimizing precision treatment strategies. This is particularly applicable to clinical decision-making for highly heterogeneous tumors like MCL.

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