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Imaging-based drug development targeting tumor microtube networks in glioblastoma

Domínguez Azorín, Daniel

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Abstract

Glioblastomas are primary brain tumors that aggressively invade the brain and resist current therapies as multicellular networks. Tumor Microtubes (TMs) play a crucial role in both hallmarks of malignancy. Targeting these malignant networks should therefore increase brain tumor response to therapy and improve patient outcomes. However, the development of drugs that interfere with TM and network formation suffers from the lack of established drug screening pipelines that study their specific anti-TM/network activity. Therefore, to identify anti- TM drugs, I developed and validated a combined, comprehensive in vitro/in vivo drug screening approach, including novel AI-based analysis tools of TM parameters. I found that of 87 tested compounds, two Protein Kinase C (PKC) activators, PMA and TPPB, exhibited robust inhibition of TM formation and TM-mediated, Connexin 43-dependent glioblastoma cell network communication in cell-based assays. Since unconnected tumor cells display increased sensitivity to cytotoxic therapy, brain tumor-bearing mice received radiotherapy, and long-term intravital 2-photon microscopy confirmed the first anti-TM and anti-tumor effects of TPPB administration. Mechanistically, RNA sequencing revealed that TPPB treatment caused a robust decrease of Tweety-homolog 1 (TTYH1) expression, a key TM driver. Additionally, immuno- histochemistry of patient-derived tumor organoids showed tumor cell network disruption and downregulation of TTYH1 after TPPB. This study establishes a novel screening pipeline for anti-TM drug development in glioblastoma and underlines the therapeutic potential of disrupting TMs and their networks.

Document type: Dissertation
Supervisor: Martin-Villalba, Prof. Dr. Ana
Place of Publication: Heidelberg
Date of thesis defense: 8 September 2023
Date Deposited: 14 Sep 2023 10:44
Date: 2024
Faculties / Institutes: The Faculty of Bio Sciences > Dean's Office of the Faculty of Bio Sciences
DDC-classification: 500 Natural sciences and mathematics
570 Life sciences
610 Medical sciences Medicine
Controlled Keywords: Glioblastoma, Multicellular Networks, Tumor Microtubes, Drug Screening, AI-Based Analysis Tools
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