Abstract

   Malignant transformation (MT) is commonly seen in IDH-mutant gliomas.
   There has been a growing research interest in revealing its underlying
   mechanisms and intervening prior to MT at the early stages of the
   transforming process. Here we established a unique pair of matched 3D
   cell models: 403L, derived from a low-grade glioma (LGG), and 403H,
   derived from a high-grade glioma (HGG), by utilizing IDH-mutant
   astrocytoma samples from the same patient when the tumor was diagnosed
   as WHO grade 2 (tumor mutational burden (TMB) of 3.96/Mb) and later as
   grade 4 (TMB of 70.07/Mb), respectively. Both cell models were
   authenticated to a patient’s sample retaining endogenous expression of
   IDH1 R132H. DNA methylation profiles of the parental tumors referred to
   LGG and HGG IDH-mutant glioma clusters. The immunopositivity of SOX2,
   NESTIN, GFAP, OLIG2, and beta 3-Tubulin suggested the multilineage
   potential of both models. 403H was more prompt to cell invasion and
   developed infiltrative HGG in vivo. The differentially expressed genes
   (DEGs) from the RNA sequencing analysis revealed the tumor invasion and
   aggressiveness related genes exclusively upregulated in the 403H model.
   Pathway analysis showcased an enrichment of genes associated with
   epithelial-mesenchymal transition (EMT) and Notch signaling pathways in
   403H and 403L, respectively. Mass spectrometry-based targeted
   metabolomics and hyperpolarized (HP) 1-^13C pyruvate in-cell NMR
   analyses demonstrated significant alterations in the TCA cycle and
   fatty acid metabolism. Citrate, glutamine, and 2-HG levels were
   significantly higher in 403H. To our knowledge, this is the first
   report describing the development of a matched pair of 3D
   patient-derived cell models representative of MT and temozolomide
   (TMZ)-induced hypermutator phenotype (HMP) in IDH-mutant glioma,
   providing insights into genetic and metabolic changes during MT/HMP.
   This novel in vitro model allows further investigation of the
   mechanisms of MT at the cellular level.

Graphic Abstract

   [66]graphic file with name 40478_2024_1860_Figa_HTML.jpg

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s40478-024-01860-6.

   Keywords: Malignant transformation (MT), IDH-mutant glioma, Low-grade
   glioma (LGG), High-grade glioma (HGG), Tumor mutational burden (TMB),
   Hypermutator phenotype (HMP), 3D cell model, Matched patient-derived
   cells

Introduction

   Diffuse low-grade gliomas (LGG) harboring IDH1 R132H mutations are
   primary brain tumors most commonly diagnosed in patients under 50 years
   of age [[67]1]. The World Health Organization (WHO) Classification of
   Tumors of the Central Nervous System (CNS) classifies IDH-mutant
   gliomas based on histological and molecular features. These tumors can
   be grade 2, 3, or 4 astrocytomas with intact 1p and 19q chromosomal
   arms, or grade 2 or 3 oligodendrogliomas with chromosome 1p and 19q
   codeletion [[68]2]. While IDH-mutant gliomas have a more favorable
   prognosis compared to IDH-wildtype (IDH-wt), they remain incurable.
   Additionally, a small subset of progressed tumors accumulates
   significantly more mutations compared to their parental tumors and
   develop hypermutator phenotype (HMP) [[69]3]. Most grade 2 or 3
   patients undergo disease progression to high-grade (grade 4) tumors
   over time through a process known as malignant transformation (MT). MT
   significantly reduces overall survival (OS), with patients experiencing
   a much poorer prognosis after transformation [[70]4]. Although MT is
   commonly observed clinically, its mechanisms are not completely
   understood. Furthermore, non-invasive detection of the MT process
   remains challenging, hindering timely detection and intervention before
   the late stage of the process when patients are clinically
   deteriorating.

   Magnetic resonance imaging (MRI) has been associated with less than 80%
   accuracy in identifying MT; therefore, molecular and pathologic
   analyses have been applied to define MT [[71]5–[72]7]. There has been
   an increasing interest in studying MT in IDH-mutant gliomas. A recent
   retrospective study examined MT in 193 IDH-mutant LGG patients based on
   pathologic definition of MT by an increase in tumor grade between
   initial and subsequent surgeries. The study revealed that time to MT is
   longer in grade 2 oligodendroglioma than grade 2 astrocytoma, and
   initial gross total resection is associated with delayed MT and
   improved OS in astrocytoma [[73]4, [74]8, [75]9]. Chemotherapy and/or
   radiation was found to delay MT and prolong MT-free survival in grade 2
   oligodendroglioma but may contribute to accelerated MT in grade 2
   astrocytoma [[76]4, [77]10, [78]11], suggesting a subtype-specific role
   of treatment in relation to MT and survival. Importantly, a proportion
   of patients previously treated with temozolomide (TMZ) undergo MT with
   the development of a HMP characterized by a specific mutational
   signature [[79]12] and linked to a poor outcome [[80]13], indicating
   that TMZ-induced HMP is an important prognostic factor and feature of
   MT.

   To gain a better understanding of the genomic landscape dynamics and
   molecular mechanisms of MT, Bai et al. analyzed fixed tumor samples,
   comparing higher-grade, progressed samples to their lower-grade
   IDH-mutant counterparts. Activation of the MYC and RTK-RAS-PI3K
   pathways and upregulation of the FOXM1 and E2F2 networks and EZH2 were
   among the oncogenic pathways driving disease progression [[81]14].
   However, a pairwise rather than bulk group comparison of the matched
   samples would be desirable for dissecting case-specific alterations.
   Jones et al. attempted to model MT and HMP in vitro by establishing
   IDH1-mutant astrocytoma and IDH1-mutant oligodendroglioma
   patient-derived cells obtained from surgical tissues of patients at
   recurrence with chemotherapy-induced hypermutation [[82]15]. However,
   only tumor tissues at recurrence were characterized and lacked matched
   tumor samples before MT. Developing experimental models that include
   matched low-grade and high-grade counterparts that faithfully
   recapitulate the disease evolution is indispensable in advancing the
   understanding of the MT process.

   Metabolic reprogramming has been recognized as one of the cancer
   hallmarks required for tumor development and MT in parallel with
   changes in the genomic landscape [[83]16]. Different metabolic profiles
   have been reported in different types of gliomas as well as gliomas of
   different grades, reflecting a complex and dynamic metabolic
   reprogramming during MT [[84]17, [85]18]. Unbiased metabolomics flux
   experiments using a panel of isogenic cell lines containing
   heterozygous IDH1/2 mutations revealed elevated glucose turnover in
   IDH-wt glioma cells and increased dependence on mitochondrial oxidative
   phosphorylation (OxPhos) in IDH-mutant cells [[86]19]. Yu et al. found
   that short-chain acylcarnitines and N-methyl-glutamic acid were
   elevated, whereas lysophosphatidylethanolamines (LPEs),
   phosphatidylserines (PSs), and phosphatidylinositols (PIs) were
   decreased in high-grade gliomas compared with grade 2 glioma tissues
   and para-tumor tissues [[87]17]. However, metabolic shifts specific to
   IDH1 mutation associated with MT remain poorly characterized,
   particularly in the context of the same patient.

   Therefore, in this study, we aimed to develop preclinical 3D cell
   models derived from the same patient before and after MT to facilitate
   the investigation of the mechanisms of MT and HMP in IDH-mutant glioma
   at the genetic and epigenetic levels. Importantly, the established cell
   models are a powerful tool for exploring the key components of
   metabolic reprogramming at the cellular level, highlighting the
   advantages of versatility and replicability over single-use fixed tumor
   tissues.

Materials and methods

Generation of patient-derived 3D cell line models

   Fresh surgical specimens were obtained from the patient undergoing
   surgical resection of the tumor at the Surgical Neurology Branch (SNB)
   at National Institutes of Health (NIH). 403L tumor tissue sample was
   obtained when the patient’s tumor was diagnosed as WHO grade 2, while
   403H sample was obtained from the same patient when the tumor
   transformed to WHO grade 4.

   403L and 403H cell lines were cultured from the 403L and 403H tumor
   tissues, respectively. The cell lines were generated by the
   Neuro-Oncology Branch laboratory at the National Cancer Institute
   (NCI), NIH. Tumor tissues were chopped into small pieces and
   non-enzymatically dissociated. Both cell lines were grown as 3D tumor
   spheroids in the NBE medium, composed of Neurobasal -A medium (Thermo
   Fisher Scientific, Waltham, MA), N2 and B27 supplements (Invitrogen,
   Carlsbad, CA) and recombinant human basic fibroblast growth factor
   (bFGF), epidermal growth factor (EGF), and 1 mmol/L of L-Glutamine
   (Thermo Fisher Scientific). Accutase (Sigma-Aldrich, St. Louis, MO) was
   used to dissociate 3D tumor spheroids into single cells. GSC923 cells
   were generated from a tumor tissue of a glioblastoma patient, as
   described previously [[88]20].

   All cells were cultured at 37 °C in 5% CO[2] and routinely checked for
   Mycoplasma contamination using MycoAlert Mycoplasma kit (#LT07-318,
   Lonza).

Cell line authentication

   Cell line authentication was performed using short tandem repeat (STR)
   profiling. DNAs from cell lines were prepared from 2 × 10^6 cell
   pellets for each cell line using DNeasy Blood & Tissue Kit (Qiagen,
   Germantown, MD), according to manufacturer’s instructions. Germline DNA
   was extracted from the patient’s blood and served as a reference
   sample. Each cell line’s STR profile was compared to the patient’s
   reference sample and the percent match was calculated by adding
   together the total number of alleles that were identical between the
   cell line and reference profiles and dividing that number by the total
   number of total alleles in the cell line profile only; homozygous (one
   peak at that site) alleles were counted as one. Sample was considered
   “authenticated”, if the sample had a percent match ≥ 80% when compared
   to the reference STR profile.

Droplet digital PCR (ddPCR) mutation detection assay

   ddPCR mutation detection assay was used to detect IDH1 p.R132H mutation
   in the cell lines. DNA was extracted using DNeasy Blood & Tissue Kit
   (Qiagen), according to manufacturer’s instructions. The IDH1 p.R132H
   c.395_396inv probe was purchased from Bio-Rad (Bio-Rad Laboratories,
   Hercules, CA).

3D tumor spheroid invasion assay

   The cells were seeded at 5 × 10^3 cells/well in ultra-low attachment
   96-well plates and allowed to naturally form 3D tumor spheroids for
   3 days. After confirming formation of one single tumor spheroid in each
   well, 100 µL of Matrigel (Corning, NY) was gently dispensed per well.
   The 3D tumor spheroid invasion was monitored using Celigo image
   cytometer (Nexcelom Bioscience, Lawrence, MA), as described previously
   [[89]21].

Western blotting

   Tumor spheroids were lysed using RIPA buffer, and the protein
   concentration of the tumor spheroids was measured using DC (detergent
   compatible) protein assay. Western blot analysis was performed as
   described previously [[90]22]. Briefly, protein lysates were resolved
   on gradient 4–20% gels (Bio-rad) transferred to nitrocellulose
   membranes and blocked with 5% bovine serum albumin (BSA) in TBS with
   0.1% Tween 20 (TBST) for 1 h. Membranes were probed with primary
   antibodies overnight at 1:5000 dilution for ACTIN and 1:1000 dilution
   for the rest antibodies used. The next day, membranes were washed with
   TBST and then probed with secondary antibodies (1:5000 dilution) for
   1 h at room temperature. Membranes were visualized by adding Clarity
   Max Western ECL Substrate (Bio-Rad) and imaged via ChemiDoc Touch
   imaging system (Bio-Rad). The following antibodies were used: IDH1
   R132H (Millipore Sigma, clone HMab-1, #MABC171), SOX2 (Cell Signaling,
   #3579), GFAP (Cell Signaling, #3670), OLIG2 (Abcam, #ab109186), NESTIN
   (Millipore Sigma, #MAB5326), beta 3-Tubulin (Cell Signaling, #5568),
   LDHA (Cell Signaling, #3582), LDHB (Santa-Cruz Biotechnology,
   sc-100775), and ACTIN (Cell Signaling, #4970).

Immunofluorescent analysis

   Glass slides with removable silicone chambers (ibidi) were pre-coated
   with Geltrex one hour before cell seeding. The next day after seeding,
   the NBE culture media was changed to NBE media + 1% FBS to induce
   differentiation. After 3 days, the cells were washed with PBS and fixed
   using 4% PFA in PBS for 20 min at room temperature. Following
   permeabilization using Triton X-100, the cells were incubated with the
   following primary antibodies: GFAP (Cell Signaling, #3670, 1:1000),
   beta 3-Tubulin (Cell Signaling, #5568, 1:250), and O4 ((Millipore
   Sigma, #MAB345M, 1:500). The next day, anti-mouse Alexa Fluor™ 488
   (Invitrogen, A-11029, 1:1000) and anti-rabbit Alexa Fluor™ 594
   (Invitrogen, A-11012, 1:1000) secondary antibodies were added, and the
   slides were mounted using DAPI Fluoroshield (Sigma).

Orthotopic xenograft mouse glioma model using 403L/H cell lines

   Eight-week-old female NSG mice were anesthetized with a combination of
   xylazine (20 mg/ml) and ketamine (100 mg/ml) diluted in 0.9% injection
   NaCl at a 1:1:4 volume ratios for a total dose of 0.1 ml per 20 g body
   weight. After the animals were fully anesthetized, they were placed and
   immobilized in a small animal stereotactic frame fitted with a
   mouse-specific headpiece using lidocaine gel pre-treated ear bars. All
   surgery procedures were done under sterile condition. 403L and 403H
   cells (1 × 10^6 cells/4µL) resuspended in serum-free Neurobasal -A
   medium were slowly injected intracranially (2 mm anterior and 2 mm
   lateral to bregma; 2.5 mm deep from the dura). The burr hole was closed
   with bone wax, and the scalp closed with Vetbond, or one to two staples
   or sutures. Five mice were injected with each cell line. Animals were
   observed frequently while they recover from the anesthesia in a warm,
   draft-free area. All animal experiments were approved by the National
   Cancer Institute Animal Care and Use Committee (NCI ACUC) and conducted
   in accordance with NCI ACUC guidelines under the authority of the
   animal protocol (NOB-023). Animal behavior and body weight were
   monitored constantly. Animals were euthanized when they reached the
   endpoints. The experimental endpoint criteria for intracranial tumors
   include symptoms of increased intracranial pressure such as less moving
   around the cage and appearing drowsy with less response to stimuli;
   signs of neurological impairment such as paralysis, circling, head
   tilting and conclusion; swollen/domed cranium; swelling subcutaneously
   at injection site > 1 cm diameter or that adversely affects the general
   well-being of the mouse. Additional humane endpoint criteria include
   body weight loss (> 15%), rough hair coat, hunched posture, rapid or
   labored breathing, debilitating diarrhea, dehydration, lethargy,
   jaundice, pallor or cyanosis, anemia, bleeding from any orifice,
   self-induced trauma, impaired mobility affecting the ability to reach
   food or water.

Magnetic resonance imaging (MRI)

   Mice were anesthetized prior to MRI imaging with isoflurane inhalation
   (4% for induction and 1%–2% for maintenance) and placed in a prone
   position. Axial and coronal images were acquired using a Rapid
   Acquisition with Relaxation Enhancement (RARE) sequence on a Bruker
   BioSpec 3T scanner. The acquisition parameters included a matrix size
   of 128 × 128, a field of view of 20 mm × 20 mm, a slice thickness of
   0.5 mm, a repetition time of 2367 ms, and an echo time of 48 ms.
   Throughout the MRI procedure, the mice's breathing rate was monitored
   with a pressure transducer (SA Instruments, Inc.) and maintained at
   60 ± 20 breaths per minute. The core body temperature was kept at
   36 °C ± 1 °C using warm air flow. MRI procedures were approved by the
   NCI ACUC and in accordance with federal regulatory requirements and
   standards.

Histology and immunohistochemistry (IHC)

   Patient’s surgical specimens and whole brains from the mouse xenograft
   models containing non-tumor and tumor regions were fixed in 10%
   formalin, embedded in paraffin, sectioned at 4 μm, and mounted on
   slides. Hematoxylin and eosin (H&E) staining was performed per standard
   protocol. All slides were stained on the Ventana Benchmark Ultra
   automated immunostainer using a standard DAB protocol. The following
   antibodies were used for the IHC analysis: IDH1 R132H (Dianova, clone
   H09, DIA-H09; 1:100), ATRX (Sigma, #HPA001906, 1:200), and Ki-67 (Dako,
   clone MIB-1, M7240; 1:200).

Whole exome sequencing (WES) and tumor mutational burden (TMB) of tumors

   Whole exome sequencing (WES) was carried out on paired tumor and
   germline DNA, which was extracted from formalin fixed paraffin embedded
   (FFPE) tumor tissue and peripheral blood mononuclear cells (PBMC),
   respectively. Exome libraries were prepared using Agilent SureSelect
   Clinical Research Exome kits (Agilent, Santa Clara, CA) and sequenced
   using paired-end method on Illumina NextSeq500 sequencers (Illumina,
   San Diego, CA). Germline and somatic mutations were called as described
   previously [[91]23]. Tumor mutational burden (TMB) was calculated as
   number of somatic mutations per megabase (Mb) of sequenced genomic
   region. The somatic mutations variants tier system was used as it was
   detailed previously [[92]24].

DNA methylation analysis of tumors and cell lines

   Genomic DNA (250 ng as the standard) was extracted from FFPE tissue
   sections using the AllPrep DNA/RNA FFPE kit (Qiagen, Hilden, Germany)
   and bisulfite-converted (EZ DNA Methylation Kit, Zymo Research D5001).
   Bisulfite-converted FFPE DNA was processed with the Infinium FFPE DNA
   Restore kit (Illumina) and assayed on Infinium MethylationEPIC kit
   (Illumina), according to the Infinium HD FFPE Methylation Assay
   automated protocol (Illumina). Methylation data was processed using
   versions 11.b4 and 12.5 of the DKFZ classifiers and NCI-Bethesda
   classifier [[93]25]. For clustering and dimensionality reduction,
   feature selection was performed by reducing the beta value matrix to
   the most variable probes by standard deviation (> 0.21). The number of
   principal components (PC) used for dimensionality reduction were 40.
   Dimensionality reduction on the PC matrix was then performed using the
   uniform manifold approximation and projection (UMAP) method (uwot R
   package) with the following non-default parameters: n_neighbors = 10,
   spread = 2, min_dist = 0.2.

   Genomic DNA from cell models was prepared from 2 × 10^6 cell pellets.
   DNA was extracted using DNeasy Blood & Tissue Kit (Qiagen), according
   to manufacturer’s instructions. EPIC 850 k array was used for
   methylation profiling of the samples. The array data was run through
   the ChAMP package’s EPIC pipeline resulting in a matrix of normalized
   beta values for further analysis [[94]26]. The CpG sites of interest
   were categorized into four groups: Both Methylated (Beta > 0.75 in both
   cell lines), Both Unmethylated (Beta < 0.25 in both cell lines), 403H
   Methylated Only, and 403L Methylated Only [[95]26]. CpG sites were
   mapped to CpG islands and gene regions using the publicly available
   EPIC manifest file.

RNA sequencing and Gene set enrichment analysis (GSEA) of cell models

   RNA from cell models was extracted using PureLink RNA Mini Kit
   (#12183018A, Thermo Fisher Scientific) following manufacturer’s
   instructions, including on-column DNase treatment to remove
   contaminating DNA (#12185010, PureLink DNase Set, Invitrogen). First,
   raw RNA-Seq data was filtered via the filter by expression function
   from the Edger package. Next, the counts were normalized and
   statistically compared with the DESeq, results (lfcThreshold = 0.58,
   alpha = 0.05), and lfcShrink functions from the DESeq2 package. Pathway
   enrichment analysis was performed using Gene Set Enrichment Analysis
   (GSEA) on DESeq2 rlog transformed counts with the Signal2Noise ranking
   metric. The Hallmark collection within the Molecular Signatures
   Database (MSigDB) was analyzed for enrichment with the GSEA algorithm.
   Only enriched gene sets with an FDR value less than 0.05 were
   considered for further analysis.

Liquid chromatography–mass spectrometry (LC–MS) measurements of cell
metabolites

   Cells were seeded at 2 × 10^6 cells in T25 flasks in two cell culture
   media conditions: (1) regular NBE medium and (2) NBE medium without
   L-glutamine. The cells were cultured in suspension as 3D tumor
   spheroids for 3 days and four replicates were collected for each cell
   line and growth condition.

   Isotope dilution liquid chromatography-mass spectrometry was performed
   to measure the concentrations of metabolites in several key cellular
   metabolic pathways. In brief, all reference target compounds, and
   isotopic standards were purchased from Sigma-Aldrich, Cambridge Isotope
   Laboratory, Medical Isotopes, Inc. and CDN Isotopes Inc. Cell pellets
   were extracted by chilled 80% methanol in water supplemented with
   appropriate isotopic standards. Reversed-phase LC-MS2 analysis was
   performed using Thermo TSQ™ triple quadrupole mass spectrometers
   (Thermo Fisher Scientific) coupled to either Shimadzu 20AC-XR or
   Vanquish (Thermo Fisher Scientific) liquid chromatographic system for
   the measurements of central carbon metabolites including R and S forms
   of 2-hydroxyglutaric acids, free fatty acids, acylcarnitines, and
   cholesterol, respectively. The mass spectrometers were operated in
   either negative or positive ion mode and set to monitor parent-product
   ion transitions using Selected Reaction Monitoring (SRM). Quantitation
   of targeted metabolites was carried out using Xcalibur™ Quan Browser
   (Thermo Fisher Scientific). Calibration curves for each metabolite were
   constructed by plotting reference compound/isotopic peak area ratios
   obtained from the calibration standards curve and fitting the data
   using linear regression with 1/X weighting. The analyte concentrations
   in samples were then interpolated using the linear function obtained
   from the calibration curve.

Real-time mito stress assay

   The cells were seeded into 96-well Seahorse microplate (Agilent, Santa
   Clara, CA) at 0.04 × 10^6 cells/well density. Sensory cartridge was
   hydrated in a non-CO[2], 37 °C incubator for 12–18 h prior to analysis.
   Next day, the cells were analyzed real-time on a Seahorse XFe96
   Analyzer using a Seahorse XF96 Cell Mito Stress Test Kit (Agilent),
   according to the manufacturer’s instructions. The data were normalized
   to protein content measured by the DC protein assay (Bio-Rad).

Hyperpolarized 1-^13C pyruvate nuclear magnetic resonance (NMR) of cell
models

   Accutase was applied in cells cultured in 2D (80% confluence), washed
   twice in high glucose Hans Clever media, and resuspended in high
   glucose Hans Clever media lacking sodium pyruvate media. A total of 400
   μL of the cell solution (2.0 × 10^7–5.0 × 10^7 cells per sample) was
   transferred to a 5-mm NMR tube. This sample was incubated in a 37 °C
   water bath for 5 min. 150 μL of 94.6 mM hyperpolarized 1-^13C pyruvate
   solution was added to the cell mixture, resulting in a final pyruvate
   concentration of 25.8 mM and pH of 7.5. 150 scans of one dimensional
   ^13C NMR spectra were acquired immediately after the addition of the
   hyperpolarized 1-^13C pyruvate solution. NMR measurements were
   conducted on a 1 T Magritek bench top NMR, using a pulse length of 5
   degree and repetition time of 2 s.

Lactate dehydrogenase (LDH) assay

   LDH activity was examined in 2 × 10^6 cell pellets using quantitative
   LDH enzyme assay kit (Abcam, ab102526), according to manufacturer’s
   instructions. The data were normalized to the protein content measured
   by the DC protein assay.

Statistical analysis

   Statistical analyses were performed using GraphPad Prism software
   (version 9.3.1, San Diego, CA). Orthogonal partial least
   squares-discriminant analysis was performed on the log transformed,
   mean centered concentrations normalized to total metabolites using
   MetaboAnalyst 6.0 [[96]27]. The data is expressed as mean ± SEM. A
   2-tailed t-test was used to evaluate a difference between experimental
   groups. P < 0.05 was considered statistically significant.

Results

Patient’s clinical history and characteristics

   The patient was a woman in her 30 s with a right frontal astrocytoma,
   biopsied as WHO grade 2. She was subsequently followed with serial
   imaging until she became symptomatic, and brain MRI suggested disease
   progression with a large non-enhancing lesion in the right cerebral
   hemisphere causing a mass effect with a midline shift (Fig. [97]1A).
   She underwent a gross total resection (Fig. [98]1A), and pathology was
   notable for LGG with IDH1 mutation, WHO grade 2 (403L, Fig. [99]1B).
   Before she was able to get the tumor treatment, she had a second tumor
   resection. Results of the WES of tumor tissue were compatible with
   astrocytoma (ATRX loss and TP53 mutation). She then received concurrent
   radiation and TMZ followed by twelve cycles of adjuvant TMZ.
   Unfortunately, tumor progression was observed again, and a third tumor
   resection was performed eleven years after the initial diagnosis.
   Pathological examination along with DNA methylation suggested
   high-grade astrocytoma, IDH-mutant, WHO grade 4 (403H, Fig. [100]1B).
   IHC staining detected a strong expression of the IDH1 R132H mutant and
   loss of ATRX in the nuclei of both 403L and 403H surgical tumors.
   Ki-67, a proliferative marker, showed a moderate-to-strong expression
   in the 403H tumor only (Fig. [101]1B). In addition, WES demonstrated
   TMB of 3.96/Mb and 70.07/Mb at grades 2 and 4, respectively
   (Fig. [102]1C). MT was diagnosed based on the clinical,
   histopathological, and genomic evaluation of the initial (grade 2) and
   recurrent (grade 4) surgical tumors. In addition to the TMB and high
   confidence mutations in tumor samples from all three surgical
   resections in the reported time frame, WES analysis of 403H revealed
   mutational signature 11, suggesting TMZ-induced HMP (Suppl. Fig.
   [103]S1, Table [104]S1) [[105]12].

Fig. 1.

   [106]Fig. 1
   [107]Open in a new tab

   Case presentation. A Left panel: patient’s MRI obtained before (pre-op)
   and after (post-op) resection #1, when the tumor was low-grade
   astrocytoma (403L). Right panel: The same patient’s MRI obtained before
   (pre-op) and after (post-op) resection #3, when the tumor was
   transformed to high-grade astrocytoma (403H). B H&E staining showing
   tumor pathology and IHC analysis demonstrating Ki-67 expression, IDH1
   R132H mutation, and ATRX loss (10 × magnification) in 403L and 403H
   patient’s tissues following 1st and 3rd resections, respectively. C.
   Timeline of disease diagnosis and treatment. Red arrows indicate that
   403L and 403H patient-derived cell lines were cultured from the freshly
   resected tumors at resections #1 and #3, respectively

Patient-derived cell models express mutant IDH and possess invasive and
stem-like properties

   As shown in the Fig. [108]1C, the 403L (low-grade) and 403H
   (high-grade) patient-derived cell lines were cultured from the freshly
   resected tumor tissues obtained from the same patient when they were
   diagnosed as grades 2 and 4, respectively. STR analysis using gDNA
   obtained from both cell lines confirmed a match to the patient’s
   germline (100% in 403L and 93.33% in 403H) (Table [109]1).
   Additionally, ddPCR using the specific IDH1 R132H probe detected that
   the mutation fraction abundance in 403L and 403H cells were 45.56 and
   41.92, respectively (Suppl. Fig. [110]S2A). Western blot analysis
   verified expression of IDH1 R132H in both cells (Suppl. Fig. [111]S2B).
   These results verified the authentication of the cell models generated
   from the tumors of the same patient harboring the IDH1 R132H mutation.

Table 1.

   Short tandem repeat (STR) analysis of cell models versus patient’s
   sample
   STR loci tested Reference (Patient's sample) 403L cells sample 403H
   cells sample
   D3S1358 14, 15 14, 15 14, 15
   D7S820 9, 11 9, 11 9, 11
   vWA 15, 17 15, 17 15, 17
   FGA 19, 21 19, 21 18, 19, 21
   D8S1179 10, 13 10, 13 10, 13
   D21S11 27, 32.2 27, 32.2 27, 32.2
   D18S51 13, 19 13, 19 13, 18, 19
   D5S818 10, 13 10, 13 10, 13
   D13S317 11, 12 12 12
   D16S539 12, 13 12, 13 12, 13
   TH01 9, 9.3 9 9
   TPOX 11 11 11
   CSF1PO 10, 11 11 10, 11
   AMEL X X X
   Penta D 9, 13 9, 13 9, 13
   Penta E 7, 14 7, 14 7, 14
   Mouse NA NA NA
   [112]Open in a new tab

   NA Allele information not available

   No mouse DNA was detected for both cell samples

   As shown in Fig. [113]2A, the 403L and 403H cell models were able to
   grow in 2D culture on the pre-coated surface as well as to form 3D
   tumor spheroids in suspension. As the ability for cell migration and
   invasion are among the key characteristics of the malignant phenotype,
   we examined 403L and 403H cell models in 3D tumor spheroid invasion
   assay. At 24 h, 403H spheroids showed a marked increase in the area
   invaded by cells around the spheroid compared to 403L (p < 0.0001)
   (Fig. [114]2B, C). These results indicated that 403H has a higher
   potential to invade and spread into nearby areas as compared to 403L.

Fig. 2.

   [115]Fig. 2
   [116]Open in a new tab

   In vitro characterization of the established LGG and HGG models. A 403L
   and 403H cell growth in 2D monolayer and 3D spheroid cultures (scale
   bar 400 µm). B 3D spheroid invasion assay in 403L and 403H measured by
   Celigo Image Cytometer over 24 h of 3D culture (scale bar 500 µm). C
   Invasion area measured by ImageJ in 403L and 403H at 0 h and 24 h. D
   Western blot analysis of 403L and 403H spheroids showing expression of
   IDH1 R132H, stem cell and lineage markers. E Immunofluorescent analysis
   of beta3-Tubulin (neuronal), O4 (oligodendroglial), and GFAP
   (astrocytic) lineage markers in 403L and 403H cells cultured as 2D
   monolayers in the culture media containing 1% FBS for 3 days. F MRI of
   the 403H orthotopic mouse model suggesting tumor growth. G H&E staining
   of the 403H murine tumors displaying tumor infiltration (left; scale
   bar 200 µm), polymorphic and bizarre cells (middle; scale bar 100 µm)
   as well as multiple atypic mitoses (right; scale bar 50 µm). H H&E
   (left), IHC staining of IDH1 R132H (middle) and ATRX (right) in 403H
   xenografts (top—scale bar 100 µm; bottom—scale bar 50 µm)

   Next, we explored the expression of stem cell markers in 3D spheroids.
   The levels of stem cell marker SOX2 and neuronal marker beta3-Tubulin
   were nearly equal. Interestingly, 403H had a higher expression of
   NESTIN, which is known as a neural stem/progenitor cell marker. We
   found that both models had OLIG2-expressing cells with higher levels in
   403L and GFAP-positive astrocytic cells mostly in 403H (Fig. [117]2D).
   In order to explore the multilineage potential, 1% FBS was introduced
   to the culture medium, as described previously [[118]28]. When both
   cells were cultured in the media containing FBS to induce
   differentiation, we observed the expression of all three lineage
   markers using immunofluorescent staining (Fig. [119]2E). Overall, these
   results suggest that the established cell models possess stem cell-like
   traits and a multilineage potential. Collectively, 403L and 403H cells
   cultured from the patient’s tumors were established as stable 3D
   neurospheres retaining mutant IDH and displaying hallmarks of
   invasiveness, self-renewal, and multipotency.

403H develops HGG tumors in an orthotopic mouse xenograft model

   Next, we injected 403L and 403H cells intracranially into NSG mice to
   test their tumor formation capacity in vivo. An MRI scan was performed
   at 14.5 months post-injection with 403H cells and demonstrated a large
   area of T2 hyperintensity in mouse brain suggesting tumor growth
   (Fig. [120]2F). Histologically, the 403H tumors were infiltrative HGG
   tumors (Fig. [121]2G), demonstrating tumor infiltration (left),
   polymorphic and bizarre cells (middle) as well as multiple mitotic
   figures (right). IHC analysis confirmed IDH1 R132H expression and ATRX
   loss in the nuclei of tumor cells (Fig. [122]2H). 4 out of 5 mice
   injected with 403H cells developed tumors with a median survival of
   13.5 months. No tumor development was observed in mice injected with
   403L cells within 18 months of observation. These results suggest that
   403H cells can form aggressive high-grade tumors in brain
   microenvironment that resembles human HGG. Consistent with previous
   reports, it remains challenging to establish a low-grade IDH-mutant
   orthotopic glioma mouse model [[123]15, [124]29].

DNA Methylation analysis of LGG and HGG models

   UMAP analysis was employed to investigate DNA methylation profiling of
   the tumors using methylation-based classifiers of the CNS tumors. As
   expected, the parental tumors 403L and 403H were clustered together
   under the IDH-mutant glioma category in IDH_LGG and IDH_HGG subclasses,
   respectively (Fig. [125]3A). Next, we conducted a comprehensive
   examination of DNA methylation patterns of 742,000 CpG sites across the
   genomes of the two cell lines, 403L and 403H. To assess the presence of
   methylation at each CpG site, beta values were employed, as described
   previously [[126]26]. Notably, we observed that 60% of the CpG sites
   displayed methylation in both cell lines (top right quadrant in green).
   Additionally, 18% of the CpG sites showed a consistent absence of
   methylation in both cell lines (bottom left quadrant in green).
   Conversely, a subset of CpG sites amounting to < 1% emerged as
   exclusively methylated in each respective cell line (top left and
   bottom right quadrants in red) (Fig. [127]3B). Further analysis of the
   methylated regions showed an inverse enrichment of CpG islands (CGI)
   and open sea probes (interCGI) among both methylated and both
   unmethylated groups (Fig. [128]3C). Analysis of gene regulatory regions
   similarly showed inverse patterns of methylation in coding sequence
   (cds) and in promoter regions (Fig. [129]3D). The 403L methylated sites
   showed an enrichment for CGIs and promoter regions compared to 403H
   methylated sites (Fig. [130]3C, D). Overall, the high percentage of
   consistency in DNA methylation profiles between the established cell
   lines support their identity and a common cell of origin.

Fig. 3.

   [131]Fig. 3
   [132]Open in a new tab

   DNA methylation and RNAseq analyses of the LGG and HGG parental tumors
   and cell models. A UMAP demonstrating DNA methylation-based clustering
   of the parental 403L and 403H surgical tissues. B DNA methylation
   patterns across the genomes of 403L and 403H cells based on normalized
   beta values. Red and green boxes represent areas of CpG sites
   methylated in both cell lines or specific to either 403L or 403H. C
   Distribution of CpG regions across grouped CpG sites. D Distribution of
   gene regions across grouped CpG sites. E PCA plot comparing RNAseq
   samples for 403L, 403H, and GSC923 cells. F Volcano plot of the DEGs in
   403H versus 403L comparison based on p-value and log[2]FC. G Notch
   signaling heatmap and enrichment plot in 403L and 403H. H EMT signaling
   heatmap and enrichment plot in 403L and 403H

Notch signaling and epithelial-mesenchymal transition (EMT) are important
during MT

   To gain insight into the underlying biological distinctions between
   403L and 403H at the gene expression level, RNAseq analysis was
   performed using 403L, 403H, and a patient-derived IDH-wt cell line
   GSC923. Each cell line showed a distinct separation on the principal
   component analysis (PCA) plot. The first component PC1, accounting for
   64% of the variance, separated the IDH-wt GSC923 cell line from the
   IDH-mutant cell lines. The second component PC2, accounting for 32% of
   the variance, distinguished the 403L and 403H cell lines within the IDH
   mutants (Fig. [133]3E). Top differentially suppressed genes as the
   tumor transformed included SMOC1, BCAN, NES, AIF1L, ENC1, and IGF2
   (p < 0.01). In contrast, the expression of NRP1, POSTN, CALCRL, PRUNE2,
   COL12A1, ADNP2, EPB41L3, PCDH11X, and MGST1 was significantly higher in
   HGG than LGG model (Fig. [134]3F, p  < 0.01). When we performed a
   pathway analysis of DEGs using GSEA, Notch signaling and
   epithelial-mesenchymal transition (EMT) emerged as statistically
   significant when compared to one another. As shown in heatmaps and
   enrichment plots in Fig. [135]3G and H, the 403L cell line showed an
   enrichment of genes related to the Notch signaling pathway, such as
   NOTCH1 and NOTCH3, while the 403H cell line exhibited a vast
   upregulation and enrichment of EMT genes, such as NRP1, POSTN, CALCRL,
   COL12A, ADNP2, PCDH11X, and MGST1.

The cell models provide insight into metabolic reprogramming during MT in
IDH-mutant gliomas

   Since IDH mutation leads to metabolic reprogramming that affects
   various cellular processes including energy production and redox
   regulation [[136]30, [137]31], we utilized LC–MS based metabolites
   profiling of in vitro 3D cell cultures of 403L, 403H, and GSC923 to
   identify distinct metabolic signatures associated with IDH mutation
   status, MT, and glutamine dependency. We also explored the effects of
   glutamine supplementation on the metabolic profiles in the cell lines.
   PCA of the metabolites revealed that all samples clustered by cell line
   (Fig. [138]4A). The first component, accounting for 42.2% of the
   variance, separated the IDH-wt GSC923 cell line from the IDH-mutant
   cell lines. The second component, accounting for 31.3% of the variance,
   distinguished the 403L and 403H cell lines within the IDH mutants. The
   third minor component, accounting for 8% of the variance, was largely
   associated with the presence or absence of glutamine in the culture
   medium. As the contribution of culture medium was minor, we only
   considered cells cultured in the presence of glutamine in subsequent
   analysis.

Fig. 4.

   [139]Fig. 4
   [140]Open in a new tab

   Metabolic characterization of the established models. A PCA plot of the
   three cell cell lines and two media conditions (Blue = GSC923,
   Red = 403L, Green = 403H, Circles = Media with 1 mM glutamine,
   Triangles = Media without glutamine). B Bar graph showing a total
   concentration of tested metabolites normalized to cell count in each
   cell line. C Statistically significant metabolites for the 403H vs 403L
   comparison plotted on the major metabolite pathways. D Energy map
   showing real-time measurement of maximal OCR and ECAR levels in live
   403L and 403H cells. E Hyperpolarized ^13C pyruvate NMR spectroscopy
   measuring Lac/Pyr ratio in 403L and 403H. F Western blot of LDHA and
   LDHB expression in 403L and 403H. G LDH activity in both cell lines

   Total metabolite concentrations are shown in Fig. [141]4B. All tested
   metabolites, except for succinate and AMP, had a higher absolute
   concentration in the 403H cell line compared to 403L cells (Suppl. Fig.
   [142]S3). To adjust for the difference in the metabolic activity and to
   reveal significantly altered metabolites in each cell line, metabolite
   levels were normalized to the total sum of the metabolites within each
   cell line. Compared to the 403L cell line, 403H is characterized by a
   relative accumulation of intermediates in the first half of the TCA
   cycle and a relative depletion of TCA cycle intermediates after the
   second half (Fig. [143]4C). There was a relative increase in the
   production of early glycolytic intermediates and decrease in lactate
   when compared to their levels across all metabolites in the 403H vs
   403L. When comparing the normalized metabolite levels between 403H and
   403L, fatty acid metabolism, including the synthesis of palmitic and
   myristic acids and the FAO of acetyl-, butyryl-, and
   valeryl-carnitines, was relatively more pronounced in 403H.
   Importantly, glutamine and D-2HG levels were significantly higher in
   403H compared to 403L, when normalized to cell count and total sum of
   metabolites within each cell line (Fig. [144]4C and Suppl. Fig.
   [145]S3). In addition, OPLS-DA analysis revealed that the IDH-mutant
   cell lines are primarily separated from the IDH-wt cell line by
   elevated 2-HG, an increase in early glycolytic intermediates such as
   fructose biphosphate and fructose 6-phosphate, as well as decreased
   fatty acid synthesis (Suppl. Figs. [146]S4 & [147]S5). Overall, the
   normalized metabolite profiles are consistent with a metabolic shift in
   the 403H cell line, characterized by a relative decrease in production
   of late glycolytic intermediates and a corresponding relative
   upregulation of fatty acid metabolism and glutamine synthesis.

   To assess the glycolytic and mitochondrial respiration potential in
   live 403L and 403H cells, we performed the Seahorse mito stress assay.
   As shown in Fig. [148]4D, the maximal respiratory capacity, measured by
   the oxygen consumption rate (OCR) levels after adding carbonyl
   cyanide-p-trifluoromethoxyphenylhydrazon (FCCP), was slightly higher in
   403L compared to 403H cells, but this difference was not statistically
   significant (p = 0.2182). The extracellular acidification rate (ECAR),
   which represents glycolytic flux, was significantly higher in 403H
   cells (p = 0.0139). These findings suggest that both IDH-mutant models
   have comparable levels of OxPhos, but the 403H cells exhibit a slightly
   higher glycolytic capacity (Fig. [149]4D).

   To better understand the metabolic flux through lactate dehydrogenase
   (LDH) and to complement our previous measurements of steady-state
   lactate concentrations, we performed hyperpolarized 1-^13C pyruvate
   in-cell NMR spectroscopy on 403L and 403H cell models. This technique
   allows for the real-time observation of metabolic flux, providing
   insights into the dynamic processes that steady-state measurements
   cannot capture as they depend on the activity of multiple pathways.
   Hyperpolarized measurements, by contrast, are a transient phenomenon
   that measures the metabolic conversion through a single reaction with
   the product to substrate ratio being proportional to the metabolic flux
   through that reaction. The analysis demonstrated that 403H cells had a
   higher lactate/pyruvate (Lac/Pyr) ratio compared to 403L, with mean
   (Lac/Pyr)AUC/million cells being 1.667 × 10^–4 and 3.251 × 10^–4 in
   403L and 403H cells, respectively (p < 0.01) (Fig. [150]4E).

   To further investigate the mechanisms behind these differences, we
   examined lactate dehydrogenase A (LDHA) and B (LDHB) expression levels
   and LDH activity in both cell models. Our analysis revealed that while
   LDHB levels were similar between the two models, LDHA expression was
   significantly higher in 403H cells (Fig. [151]4F). A quantitative LDH
   assay confirmed increased LDH activity in the 403H model
   (Fig. [152]4G), supporting the elevated Lac/Pyr ratio observed in the
   hyperpolarized 1-^13C pyruvate measurements (Fig. [153]4E). These
   results suggest enhanced glycolytic capacity in 403H cells, driven by
   higher LDHA expression and LDH activity, compared to 403L cells. In
   summary, analysis of metabolic profiles of the established 403L and
   403H cells revealed alterations in the fatty acid metabolism, TCA
   cycle, glutamine synthesis, and glycolysis in MT similar to those
   associated with the IDH mutation [[154]32].

Discussion

   Despite an overall better prognosis in IDH-mutant gliomas, which often
   present as LGGs, most tumors recur, leading to relentless MT and
   hypermutation in a subset of transformed tumors. The development of
   preclinical models that closely resemble tumor biology changes during
   MT as well as HMP induced by TMZ in IDH-mutant glioma are crucial in
   advancing understanding of the underlying mechanisms and discovering
   new targets and factors of the disease. Preclinical models are also of
   great importance as a tool to test the efficacy of novel therapeutics
   and discovering causes of drug response or resistance. For the first
   time, we developed a preclinical model of MT with TMZ-induced HMP by
   establishing matched patient-derived 3D cell lines of LGG and HGG that
   were established from the same patient at grades 2 and 4, respectively.
   Both models recapitulated the main characteristics of the parental
   tumors at genetic and epigenetic levels. HGG model demonstrated a
   superior capacity for cell invasion evidenced in 3D invasion assay and
   upregulation of the EMT pathway in the RNAseq analysis. Importantly,
   the cell models allow the investigation of the metabolites at the
   cellular level, which can be challenging in the in vivo setting. The
   LC–MS based metabolite profiling revealed alterations in TCA cycle,
   glycolysis, glutamine and fatty acid metabolism and observed an overall
   higher metabolic activity in the HGG model compared to LGG. Utilizing
   hyperpolarized 1-^13C pyruvate in-cell NMR spectroscopy, we were able
   to detect the metabolic flux suggesting an increasing lactate/pyruvate
   ratio when the MT occurs in the cell model. To our knowledge, this is
   the first study reporting the development of the matched
   patient-derived 3D models of MT with HMP, offering new insights into
   better understanding of the MT process in IDH-mutant glioma. This novel
   in vitro 3D model presents opportunities to be used as a tool for
   further elucidation of the mechanisms of MT.

   Developing models of MT in IDH-mutant glioma has been challenging due
   to various reasons. Firstly, HGG models are easier to develop because
   of the fast-growing nature. In contrast, it has proved to be
   challenging to establish a truly LGG glioma cell lines from patients’
   tissues. Verheul et al. have attempted to establish cell cultures from
   over 275 LGGs and HGGs, of which only 12 cultures were successfully
   established. All the 12 cell lines appear to represent a more advanced
   stages of astrocytomas, even when derived from LGG tumors [[155]29].
   Secondly, since the development of patient-derived cell lines with
   endogenous mutations has been a challenge, introducing IDH mutation and
   other genetic alterations to the IDH-wt HGG models has frequently been
   used as an approach to investigate associations between IDH-mutant and
   IDH-wt tumors as well as LGG and HGG [[156]33, [157]34]. However, the
   intrinsic genetic background of IDH-wt HGG tumors, which harbor
   abnormalities rarely found in LGG tumors, may lead to a distorted
   interpretation of the findings. Thirdly, since the timing of MT is
   unpredictable, it is challenging to capture the opportunity for tumor
   sample collection from the same patients to make the ideal paired
   comparisons. Among prominent advantages of the 3D models established in
   this study are that they were derived from the same patient before and
   after MT, express endogenous IDH mutation and share genetic and
   epigenetic similarities with their parental tumors. Additionally, it is
   important to highlight the ability of our cell models to grow in 3D
   spheroids, conferring specific advantages over 2D models. Since 3D
   spheroids grow at a slower rate than 2D cell culture that grows at an
   unnaturally rapid pace, this makes 3D spheroids more suitable for
   testing long-term effects of drugs since they can remain stable for a
   prolonged period. Moreover, 3D spheroids can replicate more natural
   tumor architecture by comprising of an external proliferating zone, an
   internal quiescent zone with limited oxygen, nutrient and growth factor
   distribution, and a necrotic and hypoxic core [[158]35]. Importantly,
   all these aspects affect drug response and make 3D spheroids extremely
   useful in drug discovery.

   Conversely, one of the limitations of this paired model and other tumor
   models is that since they are comprised of the tumor cells, they
   represent only a monotypic tumor cell population that lacks tumor
   microenvironment (TME). To model TME and enhance the complexity of such
   models, the cells could be co-cultured with stromal cells, such as
   immune cells, endothelial cells, and fibroblasts. Such approach may
   lead to a closer resemblance to the real tissue and offer new insights
   into the impact of non-tumor cell types on MT process and drug
   response. Additionally, as the tumor developed HMP, the biological,
   genomic, and metabolic changes between our cell line models may not
   reflect those in MT without HMP.

   Our observation that only HGG model was able to grow tumors in vivo,
   when the cell cultures were injected intracranially points to the
   aggressiveness of the HGG model which can grow and expand effectively
   in a xenograft model. The challenge of developing LGG models that grow
   tumors in vivo is in line with the previous study where researchers
   established 12 IDH-mutant cell cultures derived from patients’ tumors,
   yet none of them formed tumors in vivo [[159]29]. However, it was
   reported previously that even if xenografted human cancer cells grow in
   vivo, the paracrine interaction of xenografted human cancer cells with
   the surrounding mouse tissues may not be complete and highly
   tumor-stromal relevant cross talk may be missing [[160]36, [161]37].
   These are some of the aspects of the cross-species incompatibility
   observed in xenograft models that ultimately points to a consideration
   that different methodologies should be used to complement each other
   for a rigorous research and preclinical testing.

   Pathway analysis of the RNAseq data helps to infer biological meaning
   and functions affected in LGG and HGG models. In our study, the EMT
   pathway was found to be significantly upregulated during MT/HMP.
   Neuropilin-1 (NRP1) was detected among top statistically significant
   DEGs to be highly expressed in HGG vs LGG model. NRP1 acts as a
   co-receptor for the class 3 semaphorins (SEMA3) and vascular
   endothelial growth factor (VEGF) [[162]38–[163]40]. Recent studies
   revealed that NRP1 can actively bind several other growth factors, such
   as transforming growth factor β1 (TGF-β1) and its receptors, hepatocyte
   growth factor (HGF) and its receptor cMet, platelet derived growth
   factor (PDGF) and its receptors, fibroblast growth factors (FGFs), and
   integrins, which are relevant to angiogenesis, cell proliferation,
   survival, and wound healing [[164]41, [165]42]. NRP1 depletion
   attenuated proliferation and migration ability of cancer cells in vitro
   and in vivo in multiple cancer models [[166]43, [167]44]. Overall,
   studies suggested that in cancer, increased expression of NRP1 has been
   linked to a poor prognosis and low responsiveness and resistance to
   radiotherapy and chemotherapy in various cancer types through
   facilitating aberrant growth factor signaling during EMT-associated
   drug resistance and metastasis [[168]42, [169]45]. Another gene found
   among top significant DEGs between LGG and HGG was periostin (POSTN),
   which interacts with multiple integrins to coordinate a variety of
   cellular processes, including EMT and cell migration. Several studies
   report its important role in tumor invasion and resistance to therapy
   in glioma, breast, lung cancers, renal cell carcinoma
   [[170]46–[171]49]. Additionally, ADNP2, PCDH11X, and MGST1 detected to
   be highly expressed in the transformed HGG model have been associated
   with EMT and treatment resistance in various cancer types
   [[172]50–[173]53]. Collectively, EMT pathway appears to be an important
   component driving MT with the development of HMP in IDH-mutant glioma.
   On the other hand, secreted modular calcium-binding protein 1 (SMOC1)
   was found to be decreased in HGG vs LGG comparison. It appears to be
   consistent with the report by Wang et al. showing that SMOC1 expression
   is increased in LGG and significantly correlates with better survival
   of LGG [[174]54]. In addition, we checked the mRNA expression of DEGs
   found in our cell models using the TCGA_GBMLGG dataset within GlioVis
   ([175]http://gliovis.bioinfo.cnio.es), a publicly available web-based
   portal of brain tumor samples [[176]55]. Upregulation of NRP1, POSTN,
   ADNP2 and downregulation of SMOC1, NOTCH1, and BCAN in the grade 2 vs
   grade 4 sample comparison were consistent with our findings in LGG and
   HGG cell models (Suppl. Fig. [177]S6). Given that the models
   established in this study are representative of the matched tumor
   samples before and after MT with the development of HMP, it is possible
   that different sets of DEGs would be present when compared to the
   matched tumors without the development of HMP. Additional studies
   analyzing matched tumors of MT without HMP would bring new insights and
   expand our understanding on the role of HMP during MT.

   Additionally, reflecting on the study by Bai et al. [[178]14], we
   acknowledge that the pathway analysis using fixed tumor tissues may
   better represent the multicellular complexity and heterogeneity of the
   primary bulk samples, when compared to monotypic cancer cell
   populations used in cell models. Despite this limitation, the developed
   3D cell lines confer a significant advantage over the fixed single-use
   tissue analysis as they can be utilized under experimental conditions
   to further elucidate contributing factors and the biology of the MT
   process at the cellular level, such as the metabolic reprogramming.

   Metabolic rewiring is recognized as a key adaptation for cell survival
   in IDH-mutant tumors, similar to how genetic and epigenetic changes
   contribute to tumorigenesis [[179]30, [180]31, [181]56]. However, the
   specific metabolic changes that occur during MT, particularly at the
   cellular level, are still not well-understood [[182]57, [183]58]. To
   address this, we performed metabolic profiling on our established
   paired model system to explore metabolites within major metabolic
   pathways. The analysis revealed several prominent metabolic differences
   between IDH-wt and LGG/HGG IDH-mutant cell lines including accumulation
   of 2-HG, alterations in the TCA cycle, and suppression of fatty acid
   synthesis. These findings are consistent with the known effects of IDH
   mutation on the TCA cycle, where mutant IDH leads to the accumulation
   of the oncometabolite 2-HG from alpha-ketoglutarate (α-KG) and disrupts
   normal TCA cycle function [[184]30]. Importantly, when we directly
   compared LGG and HGG metabolite levels normalized to cell number, we
   observed elevated glutamine and 2-HG at the cellular level. This aligns
   with the previous study reporting increased 2-HG levels in higher grade
   clinical tumor samples compared to lower grade tumors [[185]31],
   however, our study indicates that the overall increase in 2-HG during
   MT is due to the changes in the intrinsic metabolism of the tumors and
   not the increased cellularity which also occurs with MT. In addition,
   relatively increased acetyl-CoA could be sourced from FAO contributing
   to elevated citrate to boost TCA cycle and stimulate fatty acid
   synthesis in 403H.

   Glutaminolysis, the conversion of glutamine to glutamate by glutaminase
   (GLS), serves as a key source for replenishing the TCA cycle
   intermediate α-KG via anaplerosis [[186]59]. Glutamine also provides
   essential nitrogen for the synthesis of amino acids and nucleotides,
   which are crucial for rapid cell proliferation. Consequently, glutamine
   metabolism is linked to tumor cell survival, maintenance, and
   antioxidative defense through glutathione (GSH) synthesis. Glutamate
   and GSH levels were lower in the HGG 403H model while an α-KG was
   higher, suggesting an increased consumption of glutamate for α-KG
   production to support TCA cycle and increase 2-HG production as well as
   reduced antioxidant activity during MT from LGG. These data corroborate
   previous reports demonstrating that glutamine deprivation and GLS gene
   silencing reduces glioma cell proliferation, with IDH-mutant glioma
   cells exhibiting particular sensitivity to GLS inhibitors/glutamine
   antagonists or GLS gene silencing [[187]60, [188]61]. As increased
   glutamine appears to be a major contributor to 2-HG elevation during
   MT, it is likely that as IDH-mutant LGG transforms to HGG, it becomes
   even more highly dependent on glutamine metabolism as a critical source
   of energy for cell growth and survival. However, while removing
   glutamine from the culture media of LGG and HGG tumors reduced cell
   viability in our models (data not shown), it didn’t produce a
   significant shift in the metabolic profiles in both models
   (Fig. [189]4A) suggesting that availability of exogenous glutamine may
   not be the only mechanism driving glutamine dependency during MT.

   Reports on the role of glycolysis and lactate production in MT have
   been complex and somewhat contradictory. Expression of LDHA, which
   catalyzes oxidation of pyruvate to lactate and other genes involved in
   glycolysis has been reported to be epigenetically silenced in
   IDH-mutant compared to IDH-wt cells [[190]62], suggesting that
   IDH-mutant tumors may be less glycolytic and rely more on mitochondrial
   metabolism. In contrast, the expression of LDHB, which converts
   primarily lactate to pyruvate through the reverse reaction, was
   reported to be increased in IDH-mutant vs IDH-wt models [[191]56,
   [192]63, [193]64]. The hypermethylation of glycolytic enzymes can be
   lost in IDH-mutant cell models of [[194]65] and ex vivo analysis of
   patients’ samples has generally shown an increase in lactate upon MT
   and a negative correlation of LDHA expression with patient survival
   [[195]58].

   Steady state lactate concentrations were lower in our HGG IDH-mutant
   glioma model and steady state lactate concentrations were lower in both
   LGG and HGG IDH-mutant models than in IDH-wt model (Fig. [196]4C and
   Suppl. Fig. [197]S5). This measurement may depend on the specific
   metabolic context, however. The LDHA expression was markedly higher in
   HGG 403H compared to LGG 403L, while the expression of LDHB was at a
   similarly high level in both. Similarly, when the metabolic flux
   specifically through the pyruvate to lactate conversion was measured by
   hyperpolarized MRI, HGG 403H converted significantly more pyruvate to
   lactate (Fig. [198]4E), suggesting relative depletion of glycolytic
   intermediates may be limiting lactate production. Interestingly, we
   also found that the expression of monocarboxylate transporter 2 (MCT2),
   which has a high affinity for lactate and is responsible to the uptake
   of lactate into cells [[199]66], was found to be expressed in much
   higher levels in 403H than 403L cells (Suppl. Fig. [200]S7).
   Indirectly, these data implies that HGG tumors may also import lactate
   via the MCT2 transporter from the TME: astrocytes, neurons, and other
   cells that produce lactate, and use it, and not glucose, as a direct
   source of energy [[201]67]. It is possible that such interaction with
   the TME contributed to the invasiveness and aggressiveness of the HGG
   403H tumor growth in vivo. Overall, IDH-mutant gliomas rely on
   lactate/pyruvate and glutamine/glutamate as anaplerotic substances to
   support TCA cycle activity, facilitate fatty acid metabolism, and
   increase 2-HG accumulation during MT.

Conclusions

   We present the first report, to our knowledge, of a 3D model of MT with
   HMP in IDH-mutant glioma by establishing LGG and HGG stable cell lines
   derived from the same patient before and after MT. Extensive
   characterization of the cell line models displayed a close resemblance
   to the parental tumors and revealed EMT and notch signaling as
   important pathways altered during MT/HMP. Steady-state metabolic
   profiling and metabolic flux experiments uncovered increased 2-HG and
   glutamine levels per cell and enhanced fatty acid metabolism and
   glycolytic capacity as major metabolic factors of MT/HMP.

Supplementary Information

   [202]Supplementary Material 1.^ (3.5MB, pdf)
   [203]Supplementary Material 2.^ (21KB, docx)

Acknowledgements