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Research Article
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Human organotypic brain slice culture: a novel framework for environmental research in neuro-oncology

View ORCID ProfileVidhya M Ravi  Correspondence email, View ORCID ProfileKevin Joseph, Julian Wurm, Simon Behringer, Nicklas Garrelfs, Paolo d’Errico, Yashar Naseri, Pamela Franco, Melanie Meyer-Luehmann, Roman Sankowski, Mukesch Johannes Shah, Irina Mader, Daniel Delev, Marie Follo, Jürgen Beck, Oliver Schnell, Ulrich G Hofmann, Dieter Henrik Heiland  Correspondence email
Vidhya M Ravi
1Translational NeuroOncology Research Group, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
2Neuroelectronic Systems, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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  • ORCID record for Vidhya M Ravi
  • For correspondence: Vidhya.ravi87@gmail.com
Kevin Joseph
1Translational NeuroOncology Research Group, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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  • ORCID record for Kevin Joseph
Julian Wurm
1Translational NeuroOncology Research Group, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Simon Behringer
1Translational NeuroOncology Research Group, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Nicklas Garrelfs
1Translational NeuroOncology Research Group, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Paolo d’Errico
4Department of Neurology, Medical Centre, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Yashar Naseri
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Pamela Franco
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Melanie Meyer-Luehmann
4Department of Neurology, Medical Centre, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Roman Sankowski
5Institute of Neuropathology, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Mukesch Johannes Shah
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Irina Mader
6Clinic for Neuropediatrics and Neurorehabilitation, Epilepsy Center for Children and Adolescents, Schön Klinik, Vogtareuth, Germany
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Daniel Delev
7Department of Neurosurgery, University of Aachen, Aachen, Germany
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Marie Follo
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
9Department of Medicine I, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
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Jürgen Beck
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Oliver Schnell
1Translational NeuroOncology Research Group, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Ulrich G Hofmann
2Neuroelectronic Systems, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Dieter Henrik Heiland
1Translational NeuroOncology Research Group, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
3Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
8Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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  • For correspondence: dieter.henrik.heiland@uniklinik-freiburg.de
Published 27 June 2019. DOI: 10.26508/lsa.201900305
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  • Figure 1.
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    Figure 1. Validation of tissue collection.

    (A) Neural tissue samples from N = 26 patients (n = 5 patients with epilepsy and n = 21 tumor patients) were used in this work. (B) Density diagram of the age of tissue donors that contributed to this study. (C) Distribution of the anatomical regions that the tissue used in this study was sourced from (frontal lobe: 31%, parietal lobe: 8%, occipital lobe: 8%, and temporal lobe: 54%). (D) Preoperative planning carried out before the resection procedure to ascertain the “health” status of the resected access cortex during tumor surgery. There was a safety distance of 2 cm from the infiltrating cortex to avoid contamination by GBM cells.

  • Figure 2.
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    Figure 2. Illustration of workflow.

    (A) The relative separation of the tumor-infiltrated cortex from the healthy cortex was verified by means of hematoxylin and eosin staining. Microvascular proliferation (black arrows) is seen in (i) tumor tissue compared with (ii) healthy cortex. (B) Illustration of the workflow for the generation of the sections used for organotypic brain cultures. A vibratome was used to obtain 18–20 coronal sections of 300 μm thickness from every 1 × 2-cm tissue block, with dimensions of ∼10 × 15 mm. Sections were then transferred to the nylon membrane of an insert in a six-well plate using the blunt, fire polished end of a glass Pasteur pipette and incubated at 37°C with the surface of the media contacting the membrane, enabling diffusion for up to 14 d. Sections were then characterized at different time points using (i) MEA electrophysiology to confirm neuronal activity, (ii) immunohistochemistry to evaluate the cell composition and loss over time, (iii) ELISA to evaluate the cellular damage or cytokine measurement, and (iv) MinION RNA-sequencing/qPCR to evaluate profile changes in gene expression.

  • Figure 3.
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    Figure 3. Vitality quantification of human brain section model.

    Acute sections were collected from each batch as control. Sections cultivated for weeks were then compared with acute sections, with N = 20 patients. (A) From left to right: 5× tiled representative fluorescence images of tissue sections for Acute, DIV1, DIV4, DIV7, and DIV14. Sections were costained against the neuronal marker (NeuN), astrocyte marker (GFAP), and nuclei (DAPI Fluoromount). Scale bars are 1 mm; representative 5× image of each time point showing the cytoarchitecture of the slice. Scale bars are 200 μm; representative 20× image of each time point showing neurons (NeuN), astrocytes (GFAP), and nucleus (DAPI). Scale bars are 50 μm. (B–E) Quantification of NeuN (neurons) positive staining demonstrated a significant difference in the distribution of neuronal sections between fresh versus cultured sections (P < 0.0001). (C) Quantification of rate of neuronal loss showed a negligible reduction over DIV1–14. (D) Quantification of GFAP (astrocytes) shows an increase on fresh sections versus DIV1 because of injury (P < 0.00001), and (E) quantification of astrocytes loss shows a nonsignificant difference from DIV1 to 14 (DIV4 = −5.97%, DIV7 = −8.15%, and DIV14 = 5.58%, one-way ANOVA with Bonferroni correction for multiple comparisons). (F) Cellular necrosis in the brain slice cultures was done using a TUNEL assay for N = 3 patients at different time points. (G) Quantification of TUNEL-positive cells shows a nonsignificant difference from DIV1 to 14 (DIV4 = 6.74%, DIV7 = 11.35%, and DIV14 = 0.613%). (H) Cellular metabolism was quantified using an LDH assay in different time points. (I) Quantification of LDH assay shows a nonsignificant difference from DIV1 to 14 (DIV4 = 33.87%, DIV7 = 34.51%, and DIV14 = 26.31%). Statistics were performed using unpaired t test with Welch’s correction. *P < 0.05, **P < 0.001, ***P < 0.0001, ****P < 0.00001, ns = nonsignificant. A representative result of three independent experiments is shown (error bar represents ± SD).

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    Figure 4. Electrophysiological activity profiling by means of multi-electrode array.

    (A) Illustration of the experimental workflow. Sections were cultured for up to DIV14, and recordings were performed to assess electrophysiological activity. The sections were placed on the recording array as illustrated. Neuronal activity was evoked by means of perfusion with high K+ medium. (B) Recorded data were high-pass filtered (300 Hz), and neuronal events were extracted and averaged before plotting (red: DIV1, blue: DIV14). (C) Random sampling of the extracellular electrophysiological recording.

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    Figure 5. Gene expression analysis.

    (A) Workflow of an RNA-seq experiment with ∼500 mg tissue using Nanopore MinION. After the culture period specified, the tissue was homogenized, RNA extracted, amplified, the library prepared, and sequenced from N = 3 patients. (B) Differential bulk gene expression showing top 500 up- and down-regulated genes. The top 500 up- and down-regulated genes lay within the same expression region. (C) Comparison of the gene expression profile at different time points. The gene expression profile exhibits a change in expression from the acute to DIV7. However, the expression profile remains stable when compared between DIV7 and DIV14. (D–G) Cell-specific expression profiles of neurons, oligodendrocytes, astrocytes, and microglia. Key genes from each cell type are shown in the dotted box next to the expression plot. The cell-specific signatures were chosen based on their fidelity score. The scale bar for y-axis is global as represented in (B).

  • Figure S1.
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    Figure S1. Gene expression analysis.

    (A) Scatter plot of a RNA-sequencing gene expression analysis; on the x-axis, the mean expression of DIV7 and 14 is presented; on the y-axis, the gene expression of acute sections is indicated. The correlation was R = 0.95, P < 0.001, no significant differential expressed genes were found. Colors indicated genes from cellular gene signature. (B) Based on the cellular signature genes, a score was calculated to quantify the loss of cellular components of the sections. *P < 0.05, **P < 0.01, ***P < 0.001.

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    Figure 6. Human GBM model.

    (A) Illustration of the experimental workflow showing tumor injection on DIV1, and tumor progression was further validated using imaging. (B) (i) proliferation pattern of the TMZ-sensitive proneural GSC_CL1 over 14 d of culture. (ii) The proliferation pattern is disrupted when TMZ (50 μM) is added to the culture medium. TMZ was added to the medium 3 d postinjection of GBM cells into the slice (DIV4). (C) Scale bars are 200 μm. (C) (i) proliferation pattern of the mesenchymal cell type GSC_CL2 over 14 d. (ii) The proliferation is uninterrupted when TMZ (50 μM) is added to the culture medium. TMZ was added to the medium 3 d postinjection of GBM cells into the slice (DIV4). Scale bars are 200 μm. (D) Quantification of the increase in the area of the injected tumor for GSC:CL1 and GSC:CL2 shows +59.2% fold change for GSC:CL2 while +32.3% for GSC:CL1, P < 0.0001, and in the presence of 50 μM TMZ, GSC_CL1 shows halted growth, whereas the GSC_CL2 shows a minor response to the treatment. (E) 3D imaging and reconstruction was performed using two-photon microscopy. The left images demonstrate the tumor core in GSC_CL1 and GSC_CL2, and the right images represent the infiltrative margin of the tumor for GSC_CL1 and GSC-CL2. Scale bars are 50 μm. Unpaired t test with Welch’s correction were used.

  • Figure S2.
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    Figure S2. Visualization of tumor migration after DIV14.

    (A, B) The figure represents that after DIV14, proneural cell type GSC_CL1 migrates only until the border of the section, (B) whereas mesenchymal cell type GSC_CL2 migrates beyond the boundary of the slice and infects the Millipore insert. Scale bars are 200 μm.

  • Figure S3.
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    Figure S3. Glioma cell migration and presence of cell types in glioma model.

    (A) The figure shows that proneural GSC_CL1 cell type invades only into the white matter regions and avoided the cortex after DIV7, whereas mesenchymal GSC_CL2 cell type invades both white matter and the cortex. Scale bars are 200 μm. (B) Immunohistochemistry of sections for astrocytes (GFAP, white) and neurons (NeuN, red) in the tumor environment (tumor cells, pZsGreen) shows the vitality of sections. Scale bars are 50 μm.

  • Figure S4.
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    Figure S4. Visualization and quantification of vasculature in glioma model.

    Vibro-sections (300 μm) were prepared from the human tissue specimens, incubated for 2 wk, then postfixed and stained for collagen IV antibody. (A) Top to bottom: Shows the sections from acute, control DIV14, DIV14 GSC:CL1 and DIV14 GSC_CL2 stained for collagen IV antibody (red), tumor (pZsGreen), and DAPI (blue). Scale bars are 50 μm. (B) (i–iv) Shows the number of intersections (y-axis) and 3D distance of a blood vessel for acute, control DIV14, DIV14 GSC:CL1, and DIV14 GSC:CL2.

  • Figure 7.
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    Figure 7. Cytokine profile of different GBM cell types: cytokine environment of sections with and without tumor injection.

    The cytokine profiling shows that there are significant changes in sections because of the development of the TME using one-way ANOVA test with Bonferroni’s multiple comparison test. *P < 0.05, **P < 0.001, ***P < 0.0001, ****P < 0.00001.

  • Figure 8.
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    Figure 8. Astrocyte profiling using ex vivo model.

    (A) Astrocyte extraction protocol from the cultured sections. MACS was used to extract the astrocytic cells with biotin-labelled antibody. (B) qPCR-based heat map of signature astrocytic genes that mark the different reactive state of the extracted astrocytes. Signature genes were extracted from publicly available datasets. (C) Expression analysis of reactive marker genes selected by specificity for humans and astrocytic fidelity score, in astrocytes purified from GBM patients and our human slice model with tumor injection.

  • Figure S5.
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    Figure S5. Quantifying tumor cell contamination in samples using FACS.

    To check the purity of extracted astrocytes using GLAST antibody, FACS analysis was carried out. (A, B) The obtained data were initially gated for 72.28% cell type populations with FSC area versus SSC area followed by (B) gating for singlets (86.97%) with FSC area versus FSC width. (C, D) The live cells (83.39%) were gated with FSC area and DAPI area, and finally (D), the tumor cells were gated using pZsgreen area versus GLAST area. The figure shows that there is <0.05% of tumor cells in the samples prepared for astrocyte extraction.

Supplementary Materials

  • Figures
  • Table S1 Patients: age, gender, origin of tissue classification, diagnosis, the time between diagnosis and surgery in days.

  • Video 1

    The video depicts the GSC_CL1 (proneural) penetration into the slice after 14 d in the culture.Download video

  • Video 2

    The video depicts the GSC_CL2 (mesenchymal) penetration into the slice after 14 d in the culture.Download video

  • Video 3

    The video depicts the blood vessel in the acute section. The blood vessel was stained using anti-collagen IV antibody.Download video

  • Video 4

    The video depicts the blood vessel in the cultured section for 14 d. The blood vessel was stained using anti-collagen IV antibody.Download video

  • Video 5

    The video depicts the blood vessel in the cultured section for 14 d along with the GSC_CL1 (proneural). The blood vessel was stained using anti-collagen IV antibody.Download video

  • Video 6

    The video depicts the blood vessel in the cultured section for 14 d along with the GSC_CL2 (mesenchymal). The blood vessel was stained using anti-collagen IV antibody.Download video

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Novel slice model in neuro-oncology
Vidhya M Ravi, Kevin Joseph, Julian Wurm, Simon Behringer, Nicklas Garrelfs, Paolo d’Errico, Yashar Naseri, Pamela Franco, Melanie Meyer-Luehmann, Roman Sankowski, Mukesch Johannes Shah, Irina Mader, Daniel Delev, Marie Follo, Jürgen Beck, Oliver Schnell, Ulrich G Hofmann, Dieter Henrik Heiland
Life Science Alliance Jun 2019, 2 (4) e201900305; DOI: 10.26508/lsa.201900305

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Novel slice model in neuro-oncology
Vidhya M Ravi, Kevin Joseph, Julian Wurm, Simon Behringer, Nicklas Garrelfs, Paolo d’Errico, Yashar Naseri, Pamela Franco, Melanie Meyer-Luehmann, Roman Sankowski, Mukesch Johannes Shah, Irina Mader, Daniel Delev, Marie Follo, Jürgen Beck, Oliver Schnell, Ulrich G Hofmann, Dieter Henrik Heiland
Life Science Alliance Jun 2019, 2 (4) e201900305; DOI: 10.26508/lsa.201900305
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Volume 2, No. 4
August 2019
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