Abstract 1084: AI-aided drug development for disconnecting glioma tumor microtube networks

Abstract

Abstract Diffuse infiltrating gliomas, especially glioblastomas, are the most common incurable primary brain tumors in adults. The aggressive growth and high resistance against cytotoxic agents are mediated by ultra-long tubular membrane protrusions, Tumor Microtubes (TMs), that interconnect single glioblastoma cells via gap junctions to multicellular communicating and resistant networks. Early studies showed that targeting these malignant networks increases response to therapy. Thus, the disconnection of such networks has emerged as a new therapeutic strategy to decrease radioresistance. However, the development of drugs that interfere with TM- and network formation is compromised by the lack of established drug screening pipelines to study a compound‘s specific anti-TM and network-inhibiting activity in combination with radiotherapy. To identify compounds with anti-TM activity, we first developed an in vitro medium-throughput imaging-based drug screening. Human-derived primary glioblastoma cells were seeded in a newly developed 2D monolayer where tumor cells form TMs and networks. The cells were treated with compounds with potential anti-TM activity. Using high-resolution laser scanning microscopy, morphological readouts were obtained and analyzed. The most promising compounds were then evaluated in a xenograft chronic cranial window mouse model. Treatments were administered with concomitant radiotherapy (6Gy per day for 3 days). By observing TM and tumor cell network changes via longitudinal in vivo 2-photon microscopy, tumor cell count, growth, and TM parameters were measured in the live mouse over up to 12 weeks. Among the 87 compounds tested in vitro, 42 significantly inhibited TMs. Two of these hits showed a higher count of dead cells in combination with radiotherapy as opposed to glioblastoma cells treated with radiotherapy alone and were therefore studied in the in vivo pipeline. One of these two agents showed reductions of TM length and striking responses in a combinatorial treatment regime with radiotherapy in individual mice that were not observed in control animals treated with radiotherapy only; however, the responses observed were heterogeneous between regions and mice. Further studies revealed this compound directly phosphorylates the gap junction protein Connexin 43 on S368, which contributes to a decrease in intercellular communication of glioblastoma cells. By applying different imaging techniques and AI algorithms we successfully established a novel in-vitro-to-in-vivo drug screening pipeline for the development of disconnecting agents. Most importantly, our data shows that disconnecting multicellular brain tumor networks increases response to radiotherapy. Further studies will be needed to develop reliable anti-TM agents as novel co-treatment options to sensitize glioblastomas to cytotoxic therapy. Citation Format: Daniel D. Azorín, Sophie Weil, Dirk C. Hoffmann, David Hausmann, Erik Jung, Matthias Osswald, Jill Reckless, Nigel Ramsden, Simon Thompson, David Grainger, Wolfgang Wick, Frank Winkler. AI-aided drug development for disconnecting glioma tumor microtube networks [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1084.