Individualized patient #brain #tumor #organoid model published by Haikun Liu and team in #CellStemCell predicts #patient #response to #therapy.
🧫 Tumor organoids have transformed #cancer #research, offering patient-specific models to study disease progression and treatment response. However, existing models often struggle to maintain tumor complexity, limiting their predictive power for #clinical #applications.
🧠 A team from #DKFZ and ShanghaiTech University has tackled this challenge by developing Individualized Patient Tumor Organoids (IPTOs) - a method that integrates patient-derived tumor cells into cerebral organoids generated from induced pluripotent #stem #cells. This novel approach allows for a more faithful recreation of tumor heterogeneity, microenvironment interactions, and molecular properties.
What makes IPTOs different?
✅ Efficient and rapid generation from a wide range of CNS tumors, including glioblastomas and metastases
✅ Preservation of the original tumor’s cellular and molecular ecosystem
✅ First brain tumor organoid model to predict patient response to therapy in a prospective clinical setting
✅ Potential for use in testing chemotherapy, targeted therapies, and immunotherapies
In a study involving 35 glioblastoma patients, IPTOs successfully predicted responses to temozolomide (TMZ), a key chemotherapy drug. This represents a crucial step toward using patient-derived organoids for real-time treatment decision-making.
Looking ahead, the research team is integrating AI-driven molecular analyses to enhance #therapy #prediction. Stem cell expert Liu has founded a DKFZ #spinoff to further explore IPTOs for drug testing. His team will collect molecular data from treatments to train #AI #models, aiming to optimize drug selection for brain cancer patients. While further validation is needed, this approach offers a promising path toward #personalized cancer therapy.
Publication: https://lnkd.in/eiZuS6Pw
Congratulations to Xiujian MA, Changwen Wang, Stefan Hamelmann, Katharina Lindner, Chunxuan Shao, Julia Zaman, Weili Tian, Yue Zhuo, Yassin Harim, Nadja Stöffler, Linda Hammann, Qungen Xiao, Xiaoliang Jin, Lorena Salgueiro Ferreño, Stefan Pusch, Miriam Ratliff, Sonja Loges, Lukas Bunse, Felix Sahm, Andreas von Deimling, Michael Platten, Hai-Kun Liu and all co authors!
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