P18.04.B GLIAMIMIC: AN IN VITRO MULTIDIMENSIONAL DRUG ASSESSMENT TOOL FOR PERSONALIZED PREDICTION OF DRUG RESPONSE AND RESISTANCE IN GLIOBLASTOMA ORGANOIDS
Abstract Glioblastoma (GBM) is a highly aggressive brain tumor with a very poor prognosis. GBM patient’s are classi- cally treated according to the Stupp’s regime including surgery, radiotherapy, and chemotherapy with te- mozolomide (TMZ). Despite the multimodal treatment, patient survival rarely exceeds 18 months, as tumor often relapses shortly after end of treatment. In this project, we translated the clinical Stupp’s regime into an in vitro multidimensional drug assessment tool called GliaMimic. Our 3D GBM tumor models included patient-derived GBM organoids (PDOs) and spheroids. The PDOs were generated from biopsies of distinct GBM tumor regions (periphery, contrast-enhancing zone, and core) to preserve cellular diversity. The spheroids were generated from GBM cell lines with different resistance profiles to TMZ. GliaMimic readouts included a morphological analysis of the 3D GBM models including confocal im- aging, cell metabolic activity assays (XTT), supernatant-based cell toxicity assays (LDH), and quantification of the apoptotic/necrotic cell fraction, which was analyzed with an automated morphological image readout algorithm applied on H&E stained tissue slices. The response to treatment and relapse capacity were cell line specific, with the spheroids from patient-de- rived cells (ZH757) being more sensitive than the commercially available cell line spheroids (U87 and U251). Interestingly, a physiological TMZ concentration (50 µM) coupled with radiotherapy induced just a 25% de- crease of metabolic activity of GBM (ZH757) spheroids, and a nearly two-fold activity increase after the treat- ment pause (indicating tumor recurrence). Overall, our data show that GliaMimic is a dynamic and multidimensional screening tool with high predictive power, that can be used to assist preclinical anti-GBM drug screening and can address current translational issues persisting in drug development.
Authors
- Natalia Vélez Char
- Wolfram Jochum (ORCID: https://orcid.org/0000-0001-6170-2020)
- Vanesa Ayala‐Nunez (ORCID: https://orcid.org/0000-0001-8401-8723)
- Anna Maria Zeitlberger (ORCID: https://orcid.org/0000-0002-9837-5534)
- Lauren Bell (ORCID: https://orcid.org/0000-0002-5408-8525)
- M Neidert
- Nadine Stokar‐Regenscheit (ORCID: https://orcid.org/0000-0003-4089-2026)
- Peter Wick (ORCID: https://orcid.org/0000-0002-0079-4344)
- Thomas Hundsberger (ORCID: https://orcid.org/0000-0002-4419-2767)
- Selina Camenisch
Institutions
- Roche (Switzerland) (CH)
- OST - Ostschweizer Fachhochschule (CH)
- Ostschweizer Kinderspital (CH)
Publication Details
- Journal
- Neuro-Oncology
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1093/neuonc/noaf193.568
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00