Patient-derived resources for decoding and targeting brain metastases ecosystems

We outline how spatial transcriptomics and proteomics are resolving the architecture of the BrM microenvironment, and assess liquid biopsy approaches, including emerging photonic biosensors, for non-invasive monitoring. Together, these resources form an interdependent toolkit..
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Abstract

Brain metastases (BrM) affect up to 30% of patients with solid tumors, yet durable intracranial control remains rare, and the biological drivers of this poor prognosis are incompletely understood. Patient-derived resources, such as clinical cohorts, biobanks, functional ex vivo models, and multi-omic platforms, are central to closing this gap, but their generation and integration face substantial logistical and technical hurdles. Drawing on the RISEbrain consortium's experience, this Perspective examines BrM-focused cohorts and biobanks, highlighting the underused potential of rapid autopsy programs to capture early metastatic seeding. We discuss patient-derived organotypic cultures and emerging organoid-based "avatar" systems as functional platforms for therapeutic profiling, alongside the complementary strengths of bulk and single-cell/-nucleus transcriptomics. We outline how spatial transcriptomics and proteomics are resolving the architecture of the BrM microenvironment, and assess liquid biopsy approaches, including emerging photonic biosensors, for non-invasive monitoring. Together, these resources form an interdependent toolkit whose coordinated deployment will advance early detection, prevention, and precision treatment of BrM.

Valiente M, Aydoğan LE, Feigin N, Gahn C, Hernandez-Oliver C, Milling F, Oktem E, Ortega-Sabater C, Priego N, Ricci AA, Capella G, Mangherini L, Serrano-Ron L, Stammberger A, Vazquez-Canto J, Weber KJ, Wehner R, Broggini T, Czabanka M, Aksu S, Al-Shahrour F, Bertero L, Schmitz M, Tirosh I, Medyouf H; RISEBrain Consortium. Patient-derived resources for decoding and targeting brain metastases ecosystems. EMBO Mol Med. 2026 Jul 3. doi: 10.1038/s44321-026-00472-y. Epub ahead of print. PMID: 42399405.

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