P01.05.A DRUG-RESPONSE ANALYSIS AND SINGLE NUCLEUS RNA SEQUENCING ON PATIENT-DERIVED NEUROSPHERES TO REVEAL DRUG RESPONSE AND RESISTANCE MECHANISMS IN GLIOBLASTOMA

Abstract BACKGROUND Glioblastoma is an aggressive primary malignant brain tumour with poor survival. Unsuccessful improvement of treatment could be due to transcriptional plasticity of the cancer cells including stem-like cancer cells. Short-term cultured patient-derived neurospheres consisting of c...

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Published inNeuro-oncology (Charlottesville, Va.) Vol. 26; no. Supplement_5; p. v31
Main Authors Lü, M J S, Hendriksen, J D, Ariey-Bonnet, J, Anand, A, Michaelsen, S R, González, F G R, Locallo, A, Azam, A, Skjøth-Rasmussen, J, Hamerlik, P, Nørøxe, D S, Hasselbalch, B, Vik-Mo, E, Kristensen, B W, Urup, T, Lassen, U, Poulsen, H S, Wennerberg, K, Weischenfeldt, J
Format Journal Article
LanguageEnglish
Published 17.10.2024
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Summary:Abstract BACKGROUND Glioblastoma is an aggressive primary malignant brain tumour with poor survival. Unsuccessful improvement of treatment could be due to transcriptional plasticity of the cancer cells including stem-like cancer cells. Short-term cultured patient-derived neurospheres consisting of cancer cells and stem-like cancer cells are used in this project to find individual drug sensitivities via drug screening. Drug resistance mechanisms on transcriptome level is further explored at high resolution using single nucleus RNA sequencing (snRNA-seq) on drug- and mock-treated neurospheres to find drug vulnerabilities. METHODS Neurospheres were established from patients included in Protarget, a Phase II, prospective, non-randomized clinical trial. A library including BET-inhibitors was used for high-throughput drug screening to evaluate ex vivo patient drug sensitivities. DMSO-treated and drug-treated neurospheres were prepared for snRNA-seq using 10X genomics. We analyzed snRNA-seq using state-of-the art bioinformatic methods to derive e.g. differentially expressed genes, transcriptional states, and large-scale somatic copy number alterations. RESULTS Through integrative analysis of drug- and DMSO-treated neurosphere cultures, we identified drug-specific differences in both transcriptional state, cell cycle, and stem-like signatures. We found that major copy number changes were preserved between the primary tumour surgical sample and neurosphere culture, exhibiting low average divergence. We found tumour-cell specific transcriptomic differences with clusters exhibiting more extreme drug-responses, implying that neurosphere cultures either sustain or develop sub-clonal, intrinsic cell-type specific drug-responses. One glioblastoma patient underwent treatment with a BET-inhibitor as part of a clinical trial and had initial good clinical response. The transcriptional response following treatment with the same BET-inhibitor on neurospheres from the same patient revealed an increased block in cell cycle, induced transcriptional state changes towards MES2- and OPC-like states, and revealed small clusters of tumour cells showing reduced response to the BET-inhibitor, indicating a pattern of drug resistance. CONCLUSION We find overall high concordance between the initial tumour surgical sample, assessed by whole-genome sequencing, and patient-derived neurospheres at the level of large-scale copy number changes. Transcriptional subtypes change during treatment including response to a BET-inhibitor on sensitive patient-derived neurospheres. We conclude that combining high-throughput drug screening with snRNA-seq on DMSO-treated and drug-treated neurospheres is a feasible way to access response and resistance mechanisms in glioblastoma, and targeting transcriptional states could be a promising way to treat glioblastoma patients.
ISSN:1522-8517
1523-5866
DOI:10.1093/neuonc/noae144.093