A novel organoid model retaining the glioma microenvironment for personalized drug screening and therapeutic evaluation

Abstract

Glioma is an aggressive brain tumor with a poor prognosis. Establishing an in vitro culture model that closely replicates the cellular composition and microenvironment of the original tumor has been challenging, limiting its clinical applications. Here, we present a novel approach to generate glioma organoids with a microenvironment (GlioME) from patient-derived glioma tissue. These organoids maintain the genetic and epigenetic characteristics of the primary tumor and preserve cell-to-cell interactions within the tumor microenvironment, including resident immune cells. Bulk RNA sequencing, whole exome sequencing, and DNA methylation analysis were used to confirm the molecular similarities between the organoids and primary glioma tissues. Immunofluorescence and flow cytometry were used to assess immune cell viability, comparing GlioME with floating glioma organoids. GlioME exhibited high responsiveness to chemotherapy and targeted therapy, demonstrating its potential for therapeutic screening applications. Notably, GlioME accurately predicted patient response to the recently approved MET inhibitor, vebreltinib. Thus, this organoid model provides a reliable in vitro platform for glioma microenvironment-related research and clinical drug screening.

Keywords: Drug screening; Glioma; Matrigel; Organoid; Tumor microenvironment.

Graphical abstract

Fig. 1

Establishment and morphological characterization of floating organoids and glioma organoids with microenvironment (GlioME). (a) Schematic representation of the cultivation strategy and characterization for floating organoids and GlioME. (b) Overview of established glioma organoids across different subtypes and grades. (c) Representative bright-field microscopy images of floating and microenvironment-retaining glioma organoids at days 1, 7, and 14 of cultivation. (d) Fluorescent imaging of glioma organoids transduced with GFP-lentiviral particles. (e) Scanning electron microscopy (SEM) images of glioma organoids, with white arrows indicating tumor-associated macrophages and yellow arrows indicating exosomes. Scale bars: white bar, 100 μm; yellow bar, 50 μm; magenta bar, 10 μm; red bar, 2 μm.

Fig. 2

Preservation of heterogeneous histology and tumor microenvironment features in glioma organoids. (a) Contrast-enhanced T1 MRI showing sampling site (indicated by white arrow) and corresponding tumor tissue with hematoxylin and eosin (HE) staining of patient-derived glioma organoids after two weeks of cultivation. (b) Concordant expression of IDH1 R132H, CD31, GFAP, and Ki-67 in astrocytoma, oligodendroglioma, glioblastoma, and their derived organoids. Scale bars: blue bar, 200 μm; black bar, 100 μm; yellow bar, 50 μm.

Fig. 3

Glioma organoids maintain consistency with the original tumor tissues at the transcriptome, methylation, and exon mutation spectrum levels. (a) Pearson correlation plot of bulk-RNAseq gene expression data, comparing the gene expression correlation between the original tissue and the two types of glioma organoids (FG and GlioME). r: correlation coefficient. (b) Unsupervised clustering of 1421 brain cancer-related genes based on bulk RNA sequencing data of 18 samples from six patients, showing the consistency of the transcriptome between the two glioma organoids and their corresponding original tumor tissues. (c) Circle plot of the CNV spectrum obtained by whole exome sequencing, showing the similarity in CNV characteristics between GlioMEs (G) and their corresponding original tumor tissues (T). (d) Mutation spectrum of commonly mutated genes, showing the somatic mutation characteristics in GlioMEs and their original tumor tissues. (e) Principal component analysis clustering plot, showing that GlioME organoids and their corresponding patient-derived tumor tissues are clustered together, while showing subtype specificity. (f) Density plot of DNA methylation beta values, comparing tumor tissues and GlioMEs derived from five patients.

Fig. 4

Enhanced retention of macrophages in GlioMEs compared to FGs. (a) Proportions of macrophages and monocytes in each sample estimated by CIBERSORT-ABS deconvolution analysis of bulk RNA sequencing data. (b) Immunofluorescence analysis showing the expression of CD11b, IBA1, and TMEM119 markers in tumor tissue, and in FGs and GlioMEs after two weeks of cultivation. (c) FACS analysis of CD45⁺ and CD68⁺ cells in FGs and GlioMEs after two weeks of cultivation. (d) Relative FACS quantification of CD45⁺ and CD3⁺ cells in FGs and GlioMEs after two weeks of cultivation, expressed as a percentage of the gated population (live cells). P = 0.0011. Scale bars: blue bar, 200 μm; yellow bar, 50 μm; white bar, 20 μm.

Fig. 5

Enhanced retention of T cells in GlioMEs compared to FGs. (a) ssGSEA scores for four T cell-associated pathways based on bulk RNA sequencing in tissues, FGs, and GlioMEs. (b) Gene expression levels of IFNG, FOXP3, GZMA, and GZMH in tissues, FGs, and GlioMEs based on bulk RNA sequencing. (c) Immunofluorescence analysis showing the expression of CD4 and CD8 markers in tumor tissue, and in FGs and GlioMEs after two weeks of cultivation. (d) FACS analysis of CD45+/CD3+/CD4+/CD8+ cells in FGs and GlioMEs after two weeks of cultivation. (e) Relative FACS quantification of CD45⁺ and CD3⁺ cells in FGs and GlioMEs after two weeks of cultivation, expressed as a percentage of the gated population (live, preselected cells). P = 0.0476. Scale bars: blue bar, 200 μm; yellow bar, 50 μm; white bar, 20 μm.

Fig. 6

GlioME as a robust preclinical model for personalized drug screening. (a) Immunofluorescence staining of CD11b and IBA1 in GlioMEs treated with Pexidartinib (1 μM) for 6 days, with DMSO-treated organoids as controls. (b) Flow cytometry analysis of GlioME organoids treated with Pexidartinib (1 μM) for 6 days, using the gating strategy of CD45+/CD68+ to assess CD86 and CD206 expression; DMSO-treated organoids served as controls. (c) Fluorescence images of GlioMEs stained with AO/PI after 72 h of treatment with DMSO, 50 μM, and 200 μM temozolomide. (d) Dose-response curves of GlioMEs after 72 h of temozolomide treatment. (e) Dose-response curves of GlioMEs after 72 h of vebreltinib treatment. (f) Flowchart of procedures and treatments for patient P17 with MET amplification. (g) MRI images of patient P17 before surgery, after surgery, and 2 months after vebreltinib treatment (3 months post-surgery). White arrows and red boxes highlight the residual enhancing area post-surgery on contrast-enhanced imaging. Dashed lines indicate regions with abnormal T2 and T2 FLAIR signals. Scale bars: white bar, 100 μm; yellow bar, 50 μm.