OS06.7A METPlatform identifies brain metastasis vulnerabilities and predicts patient response to therapy

OS06.7A METPlatform 可识别脑转移瘤的脆弱性并预测患者对治疗的反应

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Abstract

BACKGROUND: The diagnosis of brain metastasis involves high morbidity and mortality and remains an unmet clinical need in spite of being the most common tumor in the brain. Exclusion of these cancer patients from clinical trials is a major cause of their limited therapeutic options. MATERIAL AND METHODS: We report a novel drug-screening platform (METPlatform) based on organotypic cultures which allows identifying effective anti-metastasis agents in the presence of the organ microenvironment. We have applied this approach to clinically relevant stages of brain metastasis using both experimental models and human tumor tissue (by performing patient-derived organotypic cultures - PDOCs -). We have also used METPlatform to perform unbiased proteomics of brain metastases in situ to identify potential novel mediators of this disease and explore resistance mechanisms to targeted therapy. Finally, we have exploited METPlatform as “avatars” to predict response to therapy in patients with primary brain tumors. RESULTS: We identified heat shock protein 90 (HSP90) as a promising therapeutic target for brain metastasis. DEBIO-0932, a blood-brain barrier permeable HSP90 inhibitor, shows high potency against mouse and human brain metastases from different primary origin and oncogenomic profile at clinically relevant stages of the disease, including a novel model of local relapse after neurosurgery. Furthermore, in situ proteomic analysis of brain metastases treated with the chaperone inhibitor revealed non-canonical clients of HSP90 as potential novel mediators of brain metastasis and actionable mechanisms of resistance driven by autophagy. Combined therapy using HSP90 and autophagy inhibitors showed synergistic effects compared to sublethal concentrations of each monotherapy, demonstrating the potential of METPlatform to design and test rationale combination therapies to target metastasis more effectively. Finally, we show that brain tumor PDOCs predict the response of the corresponding patient to standard of care, thus proving the potential of METPlatform for improving personalized care in cancer. CONCLUSION: Our work validates METPlatform as a potent resource for metastasis research integrating drug-screening and unbiased omic approaches that is fully compatible with human samples and questions the rationale of excluding patients with brain metastasis from clinical trials. We envision that METPlatform will be established as a clinically relevant strategy to personalize the management of metastatic disease in the brain and elsewhere.

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