Article
Characterisation of heterogeneous antigen-expression pattern comparing glioblastoma cell lines, patient-derived cells and patients’ glioblastoma tissue
Charakterisierung des heterogenen Antigenexpressionsmusters von Glioblastom-Zelllinien, Primärzellen von Patienten und Tumorgewebe
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Authors
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Vera Dufner
- Universitätsklinikum Julius Maximilians Universität Würzburg, Neurochirurgische Klinik und Poliklinik, Würzburg, Deutschland
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Ellina Schulz
- Universitätsklinikum Julius Maximilians Universität Würzburg, Neurochirurgische Klinik und Poliklinik, Würzburg, Deutschland
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Camelia Monoranu
- Universitätsklinikum Julius Maximilians Universität Würzburg, Institut für Pathologie, Würzburg, Deutschland
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Michael Hudecek
- Universitätsklinikum Julius Maximilians Universität Würzburg, Medizinische Klinik II, Würzburg, Deutschland
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Carsten Hagemann
- Universitätsklinikum Julius Maximilians Universität Würzburg, Neurochirurgische Klinik und Poliklinik, Würzburg, Deutschland
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Ralf-Ingo Ernestus
- Universitätsklinikum Julius Maximilians Universität Würzburg, Neurochirurgische Klinik und Poliklinik, Würzburg, Deutschland
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Mario Löhr
- Universitätsklinikum Julius Maximilians Universität Würzburg, Neurochirurgische Klinik und Poliklinik, Würzburg, Deutschland
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Thomas Nerreter
- Universitätsklinikum Julius Maximilians Universität Würzburg, Medizinische Klinik II, Würzburg, Deutschland
| Published: | June 4, 2021 |
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Outline
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Objective: Immunotherapeutic treatment of glioblastoma (GBM) is one of the most challenging tasks due to heterogeneous surface expression of target antigens. It has previously been reported that GBM cell lines (GCL), patient-derived cells (PDC) and patients’ tumour tissue (PT) differ strongly in their level of antigen expression. Here, we analysed the surface expression of the 8 most frequently therapeutically addressed antigens in vitro by flow cytometry. Subsequently, the expression patterns displayed by GCL, PDC and PT were compared.
Methods: 7 GCL (GaMG, U87, U373, U343, U251, U138, DKMG), 7 PDC, as well as PT of 9 patients were stained for GD2, CSPG4, CD133, CD70, HER2, Il13Rα2, EGFRvIII and EphA2, measured by flow cytometry (BD FACSCanto II) and analysed using FlowJo software (TreeStar). Antigen expression was scored (0-1.0: low, 1.1-2.0: medium and 2.1-3.0: high expression) and the mean expression and range were calculated.
Results: GD2 was mildly expressed in GCL (x̅=1.3), but showed higher levels in PDC (x̅=2.6) and PT (x̅=2.4). In contrast, CSPG4 displayed low expression in GCL (x̅=0.3) and PT (x̅=0.4), but medium expression in PDC (x̅=1.9). Interestingly, CD133, a stem cell marker, showed low expression in GCL (x̅=0.8) and PDC (x̅=0.4), whereas the expression in PT was medium (x̅=1.4). CD70 and Il13Rα2 were both weakly expressed in GCL, PDC and PT (x̅=0.2, 0.4, 0.0 and 0.5, 0.6, 0.4, respectively). HER2 displayed medium expression in GCL (x̅=1.4) and PDC (x̅=1.4) and only low expression in PT (x̅=0.6). For EGFRvIII, medium expression was detectable in all three entities (x̅=1.4, 1.1 and 1.1). EphA2 was mildly expressed in GCL (x̅=0.1), medium expressed in PT (x̅=2.0) and highly expressed in PDC (x̅=2.6). Overall, high variability of antigen surface expression was visible even within the groups (Table 1 [Tab. 1]).
Conclusion: Surface expression cannot be assumed to be similar in GCL, PDC and PT and even within these groups there was high variability. GCL and even PDC do not represent PT features. Rupture of cell-cell-contacts during lysis, duration of cultivation, lack of tumor microenvironment and hypoxic gradients might be reasons for changes in antigen surface patterns. New ex vivo models like organoids or tumour slices might overcome these hurdles.
