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    In: FEBS Open Bio, Wiley, Vol. 12, No. 2 ( 2022-02), p. 480-493
    Abstract: One of the major challenges in cancer research is finding models that closely resemble tumors within patients. Human tissue slice cultures are a promising approach to provide a model of the patient's tumor biology ex vivo . Recently, it was shown that these slices can be successfully analyzed by whole transcriptome sequencing as well as automated histochemistry, increasing their usability as preclinical model. Glioblastoma multiforme (GBM) is a highly malignant brain tumor with poor prognosis and little is known about its genetic background and heterogeneity regarding therapy success. In this study, tissue from the tumors of 25 patients with primary GBM was processed into slice cultures and treated with standard therapy (irradiation and temozolomide). Total RNA sequencing and automated histochemistry were performed to enable analysis of treatment effects at a transcriptional and histological level. Slice cultures from long‐term survivors (overall survival [OS]  〉  24 months) exhibited more apoptosis than cultures from patients with shorter OS. Proliferation within these slices was slightly increased in contrast to other groups, but not significantly. Among all samples, 58 protein‐coding genes were upregulated and 32 downregulated in treated vs. untreated slice cultures. In general, an upregulation of DNA damage‐related and cell cycle checkpoint genes as well as enrichment of genotoxicity pathways and p53‐dependent signaling was found after treatment. Overall, the current study reproduces knowledge from former studies regarding the feasibility of transcriptomic analyses and automated histology in tissue slice cultures. We further demonstrate that the experimental data merge with the clinical follow‐up of the patients, which improves the applicability of our model system.
    Type of Medium: Online Resource
    ISSN: 2211-5463 , 2211-5463
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2651702-4
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