Canine glioma stem-like cells demonstrate DNA methylation-dependent enhancement of cellular respiration following low oxygen tension

Canine glioma stem-like cells demonstrate DNA methylation-dependent enhancement of cellular respiration following low oxygen tension | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Canine glioma stem-like cells demonstrate DNA methylation-dependent enhancement of cellular respiration following low oxygen tension Ryan Toedebusch, Chang-il Hwang, Shafee Syed-Quadri, Orwa Aboud, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4600799/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Glioma stem cells (GSCs) have been implicated in radio- and chemotherapeutic resistance of glioblastoma (GBM). Therapeutic targeting of GSCs has shown promise in immunocompromised rodent models but have not been translated into effective therapies for human patients. The limited success of translating therapies from rodent models to GBM patients may be attributed, in part, to the lack of co-evolution between tumors and the tumor microenvironment in immunocompromised rodent models. Thus, spontaneous canine high-grade gliomas (HGGs) may provide a complementary translational model for human therapeutic development. While described in canine HGGs, little is known about canine glioma stem cell biology. In this study, we evaluatedcellular metabolism, DNA methylation, gene expression, and functional tests of malignancy to interrogate differences between canine glioma stem-cell like (GSLC) lines and a traditional serum grown glioma cell line following exposure to hypoxia. Hypoxia increased oxygen consumption rates in GSLCs, which correlated with hypoxia-induced hypomethylation and increased mRNA levels of genes important in cellular metabolism and stemness (e.g., KCNN3, KDM4B, TCF7L2) , as well as augmented features of malignancy in GSLCs. Importantly, we were able to demonstrate a positive correlation between up-regulated genes in human GBM GSCs and hypomethylation of orthologous canine genes following hypoxia. Together, these data highlight similarities between canine and human GBM GSC cellular metabolism and their epigenetic regulation. hypoxia metabolism mitochondria cancer epigenetic glioblastoma Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The concept of cancer stem cells originated in 1937 when a mouse injected with a single leukemia cell developed a rapidly lethal leukemia 1 . Over the past several decades of research, cancer stem cells are now defined as a subpopulation of tumor cells that have characteristics of sustained self-renewal, persistent proliferation, and tumor initiation. Stem cells have been identified in several cancers, including high-grade glioma (HGG) 2,3 . HGGs are uniformly lethal primary brain tumors of children and adults 4 , and are the leading cause of cancer-related death in children 5 . Glioma stem cells (GSCs) have been implicated in resistance to radiotherapy 3 and chemotherapy 6 , leading to tumor recurrence and poor median survival times in both pediatric (14–20 months 7 ) and adult (e.g., glioblastoma (GBM), 18 months 8 ) HGG. Mechanisms underlying GSC malignancy have been extensively studied; however, targeted therapies for this specific cell population are still lacking. Metabolic flexibility plays a crucial role in regulating GSC function 9 . Following Dr. Otto Warburg’s 1956 observation that cancer cells favor glycolytic metabolism, it has long been assumed that glioma cells, including GSCs, relied upon glycolysis for energy production. However, recent evidence indicates that GSCs readily switch between oxidative and non-oxidative glucose metabolism depending on nutrient availability. For example, pyruvate is utilized by GSCs for non-oxidative metabolism through lactate production, as well as oxidative metabolism by contributing a significant number of glucose carbons to the tricarboxylic (TCA) cycle 10 . Moreover, GSCs up-regulate the pentose phosphate pathway for self-renewal during periods of prolonged hypoxia 11 . In addition to cellular respiration, mitochondria regulate several cellular processes including DNA repair 12 , and cell cycle control 13 . In contrast to many non-cancer stem cells that have underdeveloped mitochondria 14 , GSCs heavily depend on mitochondrial function for metabolic plasticity, cytoprotection to sustain stemness, and resistance to radiotherapy and chemotherapy. Epigenetic regulation has been strongly associated with the key features of GSCs, such as metabolic flexibility and stemness. For example, nicotinamide-N-methyltransferase (NNMT) has emerged as a link between cellular metabolism and epigenetic regulation. Catalyzing the methylation of nicotinamide, NNMT maintains cellular dependency on oxidative phosphorylation 15 and is ranked among the most consistently overexpressed metabolic genes in GBM 16 . Similarly, epigenetic regulation can promote GSC maintenance. For example, Enhancer of Zeste Homolog 2 (EZH2) is a potent epigenetic modulator across pediatric and adult HGG and is necessary to maintain GSC stemness 17 . These examples support that the malignancy of HGG rests, in part, on the intersection of epigenetics, metabolism, and GSC maintenance. Therapeutic targeting of GSCs has shown promising preclinical efficacy, but they have not successfully been applied to human HGG patients. Many of these studies were conducted in immunocompromised rodent models. As tissue context and the tumor microenvironment influence tumorigenesis and tumor progression, the absence of a host response precludes accurate prediction of a therapeutic response in human patients. Thus, spontaneous canine high-grade glioma may offer a complementary model for therapeutic translation from rodent models to human patients. Spontaneous canine high-grade gliomas (HGGs), including both astrocytoma and oligodendroglioma tumors, have historically been utilized as a model for HGG. Like human HGG, canine HGGs harbor a stem cell population 18,19 , yet their metabolic plasticity and epigenetic regulation remains unknown. The objectives of this study were to investigate a) the metabolic flexibility of canine astrocytoma derived glioma stem-like cells (GSLCs), b) the associated epigenetic changes under hypoxic conditions, and c) the correlation of these findings with human pediatric and adult HGG, aiming to enhance the translational relevance of spontaneous canine glioma as a model for human patients. We found that hypoxia increased oxygen consumption rates in canine GSLCs, which corresponded with hypoxia-induced hypomethylation and increased mRNA levels of genes important in cellular metabolism and stemness (e.g., KCNN3, KDM4B, TCF7L2) , as well as augmented features of malignancy in GSLCs. Importantly, we were able to demonstrate a positive correlation between up-regulated genes in GBM GSCs and hypomethylation of orthologous canine genes. Together, these data highlight similarities between canine astrocytoma and GBM GSC cellular metabolism and (epi)genetic regulation. Materials and Methods Canine glioma cell lines We utilized three patient-derived canine astrocytoma cell lines in this study (G06A 20 , 1110 21 , and 0514 21 ). G06A is a traditional serum grown canine glioma cell line. 0514 and 1110 are considered canine GSLCs, which have been verified to express neural progenitor cell markers (SOX2, OLIG2, GFAP, NES) 22 . Genomic integrity of each cell line was verified by comparison of copy number alterations with parental tumor DNA using Illumina CanineHD SNP array and sequenced to confirm canine origin. All cell lines were routinely tested and confirmed to be mycoplasma free by PCR. Prior to endpoint assays, cells were cultured under normoxic (21% O 2 ) or hypoxic (1% O 2 ) conditions for 72 hours. To achieve hypoxia, cells were incubated in 1% O 2 using the Hypoxia Incubator Chamber (#27310; STEMCELL Technologies, Vancouver, British Columbia, Canada). Detailed culture conditions are further described in Supplementary Methods. Whole Genome Sequencing Genomic DNA was isolated from each cell line (DNeasy Blood & Tissue Kit #69504, Qiagen, Valencia, CA, USA) and quantified using Qubit fluorometer (ThermoFisher Scientific, Waltham, MA, USA). Libraries were prepared using TruSeq DNA PCR Free Kit (Illumina Inc., San Diego, CA, USA). The library was subsequently sequenced to an average depth of 60x using Illumina NovaSeq platform for paired-end sequencing with a 150 base pair read length. Whole genome sequence reads were trimmed, aligned and copy number and variants called using the canFam6 canine genome (GCF_000002285.5, Dog10K_Boxer_Tasha; Dog Genome Sequencing Consortium) with the addition of the ROS_Cfam_1.0 23,24 canine chromosome Y on an Illumina DRAGEN (Dynamic Read Analysis for Genomics) Ultra-Rapid Next Generation Sequencing Data Analysis Platform. Q30 bases were greater than 92%, with median genome coverage of 89- to 95-fold across the 3 genomes. Copy number analysis utilized the segmentation files derived from the DRAGEN analysis as well as the R packages BSgenome v1.68.0, QDNAseq v1.36.0 25 , and ACE v1.18.0 0 26 within RStudio. The required CanFam6 BSgenome package was forged using BSgenome with the canine genome plus chr Y described above. A mappability file was generated using GenMap v1.3.0 27 and converted with the UCSC genome browser tools ‘wigToBigWig’, ‘bigWigToBedGraph’ and ‘bigWigAverageOverBed’. Variant calls in vcf format were annotated using Annovar v2020-06-08 28 with purpose built CanFam6 annotation files generated using the UCSC genome browser ‘liftover’ tool. Variants were filtered using a map quality of 40 and a minimal read depth of 10. Synonymous variants were not considered, and all others were filtered for inclusion as Intogen cancer driver genes, release 2023.05.31 29 . All variants in cancer driver genes were manually reviewed using the Integrated Genome Viewer (IGV v2.15.4) 30 . Normal polymorphic loci were determined by comparison to other normal canine exomes. Whole cell mitochondrial oxygen consumption Cells (1.2 × 10 5 ) were seeded on 24-well Seahorse plates. Oxygen consumption rates (OCR) were measured in real-time with Seahorse XF Mitochondria Stress Test Kit (Agilent Technologies, Santa Clara, CA, USA) using the Seahorse XF24 Analyzer (Seahorse Biosciences, Agilent, United States) per manufacturers protocol. Assay conditions are described in Supplementary Methods. Upon assay completion a BCA (ThermoFisher, Waltham, MA, USA) protein assay was performed to normalize OCR to the cell protein content in each well. Three independent experiments with five technical replicates per condition were performed. Reduced Representation Bisulfide Sequencing library construction and sequencing Genomic DNA was isolated from three replicates per cell line, per condition using Zymo Research DNA isolation kit per the manufacturer’s instruction (Zymo Research, Irvine, CA, USA). Reduced representation bisulfide sequencing (RRBS) libraries were constructed using 40ng input DNA per sample. Complete details of library construction are included in Supplementary Methods. Libraries were sequenced using the Illumine NovaSeq 6000 platform for paired-end sequencing with a 150 bp read length. Read alignment and bioinformatic analysis Sequence reads from bisulfite-treated Classic RRBS libraries were identified using the standard Illumina base-calling pipeline. Fastq files were trimmed using TrimGalore version 0.6.4 to remove low quality bases. FastQC 0.11.9 was used to assess the quality redistributions of the data. Reads were aligned to the canine reference genome ROS_Cfam_1.0 23,24 using Bismark 0.22.3. Methylated and unmethylated read totals for each CpG site were called using MethylDackel 0.5.0. The DNA methylation (DNAme) level of each sampled cytosine was estimated as the number of reads reporting a C, divided by the total number of reads reporting a C or T. Differential methylation was detected using the Bioconductor package Dispersion Shrinkage for Sequencing (DSS). Differentially methylated regions (DMRs) in the canine genome were converted to human genome (hg38) using the UCSC genome browser ‘liftover’ tool. Using the GREAT (Genomic Regions Enrichment of Annotations), the genes associated with the DMRs were identified. Differentially methylated genes across cell lines were imported into Panther 17.0 (pantherdb.org) and DAVID (David.ncifcrf.gov) for gene ontology identification. Two gene sets for hypermethylated DMRs and hypomethylated DMRs were used for the Gene Set Enrichment Analysis (GSEA) with the transcriptome data from human glioma stem-like cell lines upon hypoxia (GBM, GSE45117) and pediatric DIPG samples (GSE26576) with a hypoxia gene signature. The enrichment of the hypoxia signature in these patient samples was confirmed by the Hallmark Hypoxia gene set curated by the GSEA. Quantitative Real Time PCR Targeted gene mRNA expression was performed on cell lines cultured under normoxic (21% O 2 ) or hypoxic (1% O 2 ) conditions for 72 hours. Total RNA isolation and cDNA synthesis were performed as described in Supplementary Methods. Primer sets (Supplementary Table 1) were designed using NCBI primer design ( https://www.ncbi.nlm.nih.gov/tools/primer-blast/index.cgi ). Primer validation and qPCR reactions were carried out as described in Supplementary Methods. Fold difference in expression between normal brain and tumor samples was calculated and plotted using the double delta Ct analysis with β-actin as the control gene for normalization and relative expression. Cell-based functional assays Cell viability was determined using the Cell Titer Glo® 2.0 Assay (Promega, Madison, WI, USA) according to the manufacturers protocol. Cellular migration was assessed using transwell migration assays. Detailed experimental conditions are described in Supplementary Methods. Statistical Analysis Statistical analysis for oxygen consumption rate assays, qRT-PCR, and GSLC functional experiments were performed with Prism GraphPad V9.0.2 software. Data were tested for normality via the Shapiro-Wilks test. Data are presented as the mean ± SEM. Statistical significance was assessed via unpaired two-tailed Student’s t -test. Results were regarded as statistically significant for p < 0.05. Results Canine glioma cell lines have few non-polymorphic variants in known oncogenes WGS analysis revealed that the three cell lines had few non-polymorphic, presumably somatic, variants in known cancer driver genes. All were determined to have a low probability of phenotypic effect or “Tolerated” by the Sorting Intolerant From Tolerant (SIFT 31 ) with one exception; a homozygous PARP4 truncating variant observed in the GSLC 1110 cell line (NM_001145980:exon30:c.4107delT:p.F1369Lfs*10). ( Table 1 ). Table 1. Cancer driver gene variants across canine cell lines. Copy number analysis showed 2N ploidy for cell lines G06A and GSLC 0514, the latter harboring a large chromosome 1 deletion (chr1:28,809,718 – 527,795,402) and trisomy chromosome 13 ( Supplementary Figures 1 and 2 ). Cell line GSLC 1110 appears to have had a genome duplication event with 3.8N ploidy ( Supplementary Figure 1 ). Multiple chromosomes have lost one or two copies with chromosome 31 at 6 copies. Multiple chromosomes show more complex etiology such as chromosome 1 with 4N and 2N segments, proximal and distal, respectively. These likely represent translocation events and attempts to resolve this complexity was not undertaken. Gains of canine chromosomes 13 and 31 are frequently observed in canine carcinomas 32,33 . Cellular bioenergetics differ between canine GSLCs and differentiated glioma cells To ascertain how hypoxia alters mitochondrial function across cell lines, cells were exposed to normoxia (21% FIO 2 ) and hypoxia (1% FIO 2 ) for 72 hours and oxygen consumption rates (OCR) were measured. Basal OCR, the net sum of all cellular processes consuming oxygen, was not affected by hypoxia in either GSLC line (0514: 154.0 +/- 18.3 vs. 175.2 +/- 11.7, p=0.1749, Figure 1A, B ); (1110: 175.2 +/- 4.46 vs. 159.8 +/- 8.2, p=0.3668, Figure 1F, 1G ). Similarly, G06A basal OCR was not affected by hypoxia (130.3 +/- 15.9 vs. 176.6 +/- 18.7, p=0.1255, Figure 1K, L ). To assess the specific contribution of ATP-linked respiration to OCR, ATP synthase (Complex V) was inhibited via oligomycin. ATP-linked OCR was not altered by hypoxia in any cell line (0514: 105.5 +/- 4.6 vs. 106.0 +/- 10.4, p=0.9670, Figure 1A, C ; 1110: 105.7 +/- 6.9 vs. 92.9 +/- 13.3 p=0.4238, Figure 1F, H ; G06A: 91.3 +/- 8.8 vs. 124.2 +/- 14.5 p=0.1248, Figure 1K, M ). Next, carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone (FCCP) was administered to determine maximal cellular OCR. Hypoxia increased maximal OCR by ≥2-fold in both GSLC lines (0514: 672.4 +/- 17.8 vs. 265.9 +/- 26.2, p=0.0002, Fig. 1A, D ; 1110: 762.4 +/- 51.7 vs 333.3 +/- 45.7, p=0.0008, Figure 1F, I ), but attenuated maximal OCR in G06A cells (274.2 +/- 29.9 vs 637.2 +/- 83.8, p=0.0151, Figure 1K, N ). Lastly, mitochondrial spare respiratory capacity (SRC) was assessed following injection of a mixture of rotenone, a complex I inhibitor, and antimycin A, a complex III inhibitor. SRC increased ≥3-fold following hypoxia treatment in GSLCs (0514: 512.5 +/- 12.9 vs 90.7 +/- 29.1, p=0.0002, Figure 1A, E ; 1110: 587.2 +/- 39.9 vs 179.3 +/- 30.4, p=0.0002, Figure 1F, J ), but was attenuated in G06A cells (90.7 +/- 29.1 vs. 512.5 +/- 12.9, p=0.0092, Figure 1K, O ). To compare the magnitude of change in OCR throughout the mitochondrial stress test within and across cell lines, the OCR at each timepoint was normalized to the basal OCR for each condition. Under normoxic conditions, relative ATP-linked OCR was decreased from basal OCR in GSLC 1110 cells (60.3 +/- 8.6 vs. 100.1 +/- 11.9; p=0.0108) and G06A cells (69.9 +/- 8.1 vs. 100.0 +/- 10.5; p=0.0357), but not GSLC 0514 cells (p=0.0714) ( Figure 1P ). G06A cells had the largest relative increase in maximal (358.7 +/- 47.2) and SRC (258.7 +/- 36.8), with a significantly increased SRC compared GSLC 0514 cells (51.8 +/- 16.6; p = 0.0342) ( Figure 1P ). Following exposure to hypoxia, relative ATP-linked OCR was decreased from basal OCR in both GSLC cell lines (0514: 66.0 +/- 5.0 vs. 100.0 +/- 8.0, p=0.0265; 1110: 60.3 +/- 7.9 vs. 100.0 +/- 13.4, p=0.0066), but not G06A cells (p=0.1636) ( Figure 1Q ). However, relative maximal OCR and SRC following hypoxia was robust in both GSLC lines. The relative maximal OCR was markedly increased in GSLC 1110 cells (435.0 +/- 59.0, p=0.0297) with a similar, non-significant rise in GSLC 0514 cells (420.6 +/- 19.2, p=0.0530) ( Figure 1Q ). Relative SRC was also significantly increased in both GSLCs (GSLC 110 cells: 3352 +/- 45.6, p=0.0016; GSLC 0514 cells: 320.6 +/- 14.0, p = 0.0004. However, neither relative maximal OCR (110.4 +/- 18.7; p=0.4671) ( Figure 1Q ), nor SRC (110.4 +/- 18.7; p=0.1434) were increased in G06A cells. Hypoxia-induced methylation alterations were cell line specific Given their differential OCR across conditions, we hypothesized that hypoxia treatment reduced methylation of nuclear-encoded mitochondrial genes in canine GSLCs relative to traditional serum grown glioma cells. We performed reduced representation bisulfite sequencing (RRBS) to generate genome-wide single-nucleotide resolution DNA methylation profiles across cell lines following normoxia and hypoxia treatment. On average, >35 million bisulfite sequencing reads were generated per sample, with >98% bisulfite conversion efficiency ( Supplementary Table 2 ). At least 53% of CpG dinucleotides in the canine genome (ROS_Cfam_1.0) were covered with at least one read. (ROS_Cfam_1.0). The average methylation values were similarly distributed across groups ( Figure 2A ). GSLC 0514 had the largest number of differentially methylated cytosines (DMCs; n=307), with the majority of cytosines hypomethylated following hypoxia (n=254; Figure 2B ). G06A cells followed a similar pattern, with 190/266 DMCs exhibiting hypomethylation ( Figure 2D ). GSLC 1110 cells had the fewest DMCs (n=209) with an equal distribution between hypo- and hypermethylated cytosines (107 vs. 102; Figure 2C ). Next, we identified the regions of the nuclear genome with one or more DMC. Differentially methylated regions (DMRs) were calculated as read-depth weighted average over all included cytosines. Despite having the fewest DMCs, GSLC 1110 cells had the most differentially methylated regions (DMRs; n=43; Figure 3B, 3D ) following hypoxia treatment, with an equal distribution between hypo- and hypermethylated regions. G06A cells had 33 DMRs resulting in hypomethylation of most regions following hypoxia treatment (n=24/33; Figure 3C, D ). GSLC 0514 cells had the fewest DMRs (n=25), most of which were hypomethylated following hypoxia treatment (n=20; Figure 3A, D ). We utilized Integrative Genomics Viewer to identify specific genes mapping to the DMRs. Hypoxia treatment induced hypomethylation of 39 identifiable genes in GSLC 0514 cells, 31 genes in GSLC 1110 cells, and 26 genes in G06A cells. Three hypomethylated genes were shared between GSLC 0514 and GSLC 1110 cells ( CDH4, KCNN3, STK32C ), with a single gene shared between GSLC 1110 and G06A cells ( HDAC4 ) ( Figure 3E ). Hypoxia treatment induced hypermethylation of 37 genes in GSLC 0514 cells, 30 genes in GSLC 1110 cells, and 39 genes in G06A cells ( Figure 3F ). Two hypermethylated genes were shared between GSLC 0514 and GSLC 1110 cells ( ARHGEF28, FOXN3 ) ( Figure 3F ). Genes with the molecular function associated with ‘binding’ were commonly differentially methylated across cell lines ( Supplemental Figure 3A, B ). Commonly hypomethylated genes following hypoxia were associated with DNA binding and bone morphogenetic protein (BMP) receptor binding function in both GSLC 1110 and 0514 cell lines . However, the most commonly hypomethylated genes following hypoxia in G06A cells were associated with zinc ion binding and sequence-specific DNA binding (e.g., RNA poly II core promoter proximal region). Genes associated with metal ion binding function were commonly hypermethylated following hypoxia in all three cell lines. Genes with the biological process associated with ‘cellular process’ (GO 009987) were the most differentially methylated across cell lines ( Supplemental Table 2 ). All three cell lines had multiple hypo- and hypermethylated genes associated with ‘cellular metabolic process’ (GO 0044237) and ‘regulation of biological process’ (GO 0060789). Both GSLC lines, but not G06A, had multiple hypomethylated genes associated with ‘cellular component organization or biogenesis’ (GO 007165). However, hypoxia also had differential effects on methylation between GSLC lines. Several genes associated with ‘signal transduction’ (GO 007165) and ‘cellular communication’ (GO 0044237) were hypomethylated in GSLC 0514s. Genes associated with ‘cellular response to stimulus’ (GO 0051716) and ‘cellular communication’ (GO 007154) were hypermethylated in GSLC 1110s. G06A cells also had several hypermethylated genes associated with ‘cellular response to stimulus’ (GO 0051716) and ‘cellular communication’ (GO 007154) ( Supplemental Table 2 ). Differential methylation was associated with altered gene expression following hypoxia We next sought to determine the effect of methylation on gene expression of several DMGs. CDH4, KCNN3, and STK32C were hypomethylated following hypoxia in both GSLC lines. STK32C , but not KCNN3 , mRNA levels were increased following hypoxia (GSLC 1110: 4-fold, p<0.05; GSLC 0514: 5-fold, p<0.001) ( Figure 4A ). CDH4 was below the limit of detection in both cell lines. mRNA levels of hypermethylated FOXN3 were increased following hypoxia in GSLC 0514 cells (3-fold; p<0.05) but were unchanged in GSLC 1110s (p= 0.3981) ( Figure 4A ). mRNA levels of hypermethylated ARHGEF28 were unchanged in both GSLC 0514 (p=0.1659) and 1110 lines (p=0.1182) ( Figure 4A ). Hypoxia induced hypomethylation of ALDH9A1, HT2RC, and TCF7L2 corresponded with increased mRNA levels in GSLC 0514 cells ( ALDH9A1 : 2.5-fold, p<0.001; HT2RC : 1.5-fold, p<0.05; TCF7L2 : 4-fold, p<0.0001) ( Figure 4C ). mRNA levels of hypermethylated CABLES1 (2-fold; p<0.001), but not ARID5B (p=0.1362) were decreased following hypoxia in GSLC 0514 cells ( Figure 4C ). Hypoxia induced hypomethylation of CLOCK and KDM4B in GSLC 1110 cells corresponded with increased mRNA levels ( CLOCK : 3-fold, p<0.001; KDM4B : 5-fold, p<0.0001) ( Fig. 4D ). Moreover, hypermethylation of NOX5 was associated with increased mRNA levels (12-fold; p<0.0001) ( Figure 4D ). Hypoxia-induced hypomethylation was not associated with changes in mRNA expression of FLNA2, nor TGFB3 , in G06A cells ( Figure 4E ). Hypermethylation of ENO1 (10-fold, p<0.0001 ), but not RFN6 (p=0.6183), was associated with decreased mRNA levels in G06A cells ( Figure 4E ). Hypoxia differentially augmented malignant features of canine glioma cell lines Given the up regulation of metabolic and cancer stemness genes in GSLCs following hypoxia, we hypothesized that hypoxia would alter functional properties of GSLCs, but not traditional serum grown glioma cells. Indeed, relative viability increased more than 50% in GSLC 0514 cells following hypoxia (100.0 +/- 3.6; p<0.0001) ( Figure 5A ). However, viability was unaffected by hypoxia in GSLC 1110 cells (p=0.0848) and G06A cells (p=0.1762) ( Figure 5B, C ). Strikingly, relative cellular migration was increased more than 100% in GSLC 1110 cells following hypoxia (100.0 +/- 12.3 vs. 236.3 +/- 8.2; p=0.0016) ( Fig. 5E ). However, neither GSLC 0514 (p=0.1258), nor G06A (p=0.1534) migration was altered by hypoxia ( Figure 5D, F ). Hypomethylated genes in canine GSLCs correlated with increased expression of orthologous genes in human adult GSCs following hypoxia To evaluate similarities between canine and human GSC biology under hypoxic stress, we compared genes that were differentially methylated in our canine cell lines to genes that were differentially expressed in human adult (GBM) and pediatric (DIPG) glioma. Utilizing publicly available microarray datasets 11,34 , Gene Set Enrichment Analysis (GSEA) demonstrated a positive correlation between genes that were significantly hypomethylated in canine GSLCs and orthologous genes with increased mRNA expression in GBM GSCs ( Figure 6A ; normalized enrichment score (NES) = 1.87, p<0.01). There was no correlation between significantly hypermethylated canine genes and orthologous genes in human GBM GSCs ( Figure 6B ; NES: 1.04, p=0.35). We next performed GSEA of 35 pediatric diffuse intrinsic pontine glioma (DIPG) patient samples (GSE26576) stratified by a hypoxic signature. We observed a negative correlation between genes that were significantly hypomethylated in canine GSLCs and orthologous genes with differential expression in DIPG ( Figure 6C ; NES: -1.51, p=0.02). Similar to human GBM, there was no correlation between hypermethylated canine genes and orthologous genes with differential expression in DIPG ( Figure 6D ; NES: -0.99, p=0.47). Discussion In this study, we integrated cellular metabolism, DNA methylation, and gene expression patterns to interrogate differences between canine GSLC and traditional serum grown glioma cell lines. Following 72 hours of hypoxia, oxygen consumption rates increased in GSLCs, but not traditional serum grown glioma cell lines. However, there were few similarities in DNA methylation patterns between GSLC lines, which suggests that canine GSLCs are heterogeneous across canine patients, like GBM. Notably, hypoxia induced expression of several genes associated with mitochondrial activity, cancer stemness, and decreased GBM patient survival in canine GSLCs. Moreover, GSLCs, but not traditional serum grown glioma cell lines, had increased features of malignancy following exposure to hypoxia (e.g., proliferation and migration). Finally, we were able to demonstrate a positive correlation between hypomethylated canine GSLC genes and up-regulated orthologous genes in GBM GSC following hypoxia. Taken together, this study supports shared stem cell features between GBM and canine astrocytomas, further strengthening the rationale for the use of dogs with naturally occurring canine astrocytoma as a therapeutic translational model for GBM. A major finding of this study was the differential effects of hypoxia on the parameters of OCR between canine GSLCs and traditional serum grown glioma cell line. Under normal oxygen tension, canine GSLCs exhibited a quiescent phenotype with smaller changes in OCR, consistent with GBM GSCs 35 . Conversely, canine GSLCs exhibited greater oxygen consumption rates in the presence of low oxygen tension. Maximal and spare respiratory capacity were increased in both GSLC lines, highlighting their metabolic plasticity and ability to overcome the stress of hypoxia and produce ATP 36 . This metabolic plasticity, specifically an increased mitochondrial reserve capacity, may contribute to GSLC derived treatment-resistance in canine glioma patients 37-39 , similar to what has been observed in human GBM GSCs 40 . Cellular respiratory capacity over changing oxygen tension can be influenced through a variety of ways, including altered methylation of nuclear-encoded mitochondrial genes 41 . Few hypo- and hypermethylated genes were shared across GSLC cell lines in this study. Of the shared differentially methylated genes in this study ( CDH4, KCNN3, STK32C, ARHGEF28, FOXN3 ), only KCNN3 is a known nuclear encoded mitochondrial gene 42 . KCNN3 encodes a small conductance calcium-activated potassium channel and has been identified in mitochondria of human, rat, and guinea pig ventricular myocytes. While its cellular localization has not been confirmed in the brain, it is one of 16 genes encoding ion channels downregulated in adult high-grade glioma patients 43 . In fact, decreased KCNN3 mRNA levels have been postulated as a negative prognostic indicator in GBM 43 . It is also worthwhile to note that hypoxia resulted in hypomethylation and an associated robust increase in mRNA levels of STK32C in both canine GSLC lines. While less is known about STK32C , it’s expression is a negative prognostic indicator in several cancers. STK32C has not been linked to cancer stem cells or stemness, but it has been shown to augment proliferation, migration, and invasion in human bladder cancer 44 . Importantly, approximately 90% of adult gliomas express this protein (proteinatlas.org). Thus, STK32C inhibition may be a shared therapeutic target across species and should be further investigated. Canine HGG is increasingly recognized as a relevant model for human glioma, but it remains to be determined if canine HGG is best suited as a model for pediatric or adult disease. Going forward, it is imperative to consider canine high-grade astrocytoma and oligodendroglioma as distinct and separate tumors before comparison to pediatric and/or adult HGG. This will inform appropriate translational application of canine glioma clinical trials. Canine cell lines used in this study were patient-derived lines from astrocytic tumors. Our GSEA found a significant positive correlation between hypomethylated genes in canine GSLCs and up-regulated orthologous genes in GBM GSCs following hypoxia. This suggests robust similarities in the hypoxic gene response between canine GSLCs and GBM GSCs. Conversely, hypomethylated genes in canine GSLCs were negatively correlated with up-regulated genes in DIPG patient samples when stratified by their hypoxic signature. Therefore, these results support the hypothesis that canine astrocytoma stem cell function and response to hypoxia is more like GBM than pediatric HGGs. We have previously hypothesized this linkage, as we have shown that the glioma-associated microglia and macrophage response in canine astrocytoma closely aligns with GBM 21,45 . Future canine studies should continue to investigate this important question. Our study had several limitations. Comparisons to normal astrocytic canine cell lines were not performed. While we were unable to evaluate methylation changes induced by neoplastic transformation, our primary objective was to evaluate the hypoxic response (OCR, methylation, functional analysis) of canine GSLCs relative to traditional serum grown glioma cell lines. Moreover, mRNA expression was evaluated on a small subset of candidate genes, precluding a global view of the relationship between methylation and gene expression in canine glioma cell lines. To address these limitations, future studies should consider coupling methylation with single cell RNA sequencing on patient-derived canine glioma samples. This approach would allow for a comprehensive analysis of the effects of DNA methylation on gene expression across GSLCs and differentiated glioma cells. Our data highlight that canine GSLCs are metabolically adaptable like human GBM stem cells. Moreover, the epigenetic regulation of gene expression associated with metabolic plasticity and stemness is heterogenous across canine GSLCs, further recapitulating the heterogeneity observed in GBM and strengthening the use of canine astrocytoma as comparative disease model for GBM. Declarations Author’s Disclosure: None. Author Contributions: Conceptualization, R.G.T, C.M.T.; methodology, R.G.T, C-I.H, O. A, K.D.W, M.P, J.D.M, C.M.T; formal analysis, R.G.T, C-I.H, J.D.M; investigation, R.G.T, S.S-Q, J.D.M; resources, K.D.W, D.Y, M.P, P.J.D.; data curation, R.G.T, C-I.H, M.P, J.D.M; writing—original draft preparation, R.G.T, C.M.T; writing—review and editing, R.G.T, C-I.H, S.S-Q, O. A, K.D.W, D.Y, M.P, P.J.D., F.J.M, J.D.M, C.M.T; funding acquisition, R.G.T, C.M.T. All authors have read and agreed to the published version of the manuscript. Acknowledgments: First and foremost, the authors thank all the companion canines and their owners for donation of their tissues to this work. We also thank the Cortopassi Laboratory and Alexey Tomilov for assistance with all Seahorse experiments. Funding: This research was supported in part by the UC Davis Paul Calabresi Career Development Award for Clinical Oncology as funded by the National Cancer Institute/National Institutes of Health through grant #2K12CA138464-11 (C.M.T, O.A), The Center for Companion Animal Health (CCAH) within the School of Veterinary Medicine at University of California, Davis through grant #2019-5F, and the Paul C. and Borghild T. Petersen Brain Tumor Foundation (R.G.T, P.J.D., C.M.T). Data Availability Statement: The data discussed in this publication have been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession number GSE223852 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE223852). References Furth J, Kahn MC, Breedis C. The Transmission of Leukemia of Mice with a Single Cell1. The American Journal of Cancer. 1937; 31(2):276-282. 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Biochim Biophys Acta Bioenerg. 2017; 1858(6):442-458. Wang R, Gurguis CI, Gu W, et al. Ion channel gene expression predicts survival in glioma patients. Sci Rep. 2015; 5:11593. Sun E, Liu K, Zhao K, Wang L. Serine/threonine kinase 32C is overexpressed in bladder cancer and contributes to tumor progression. Cancer Biol Ther. 2019; 20(3):307-320. Toedebusch RG, Wei N-W, Simafranca KT, et al. Intra- and Intertumoral Microglia/Macrophage Infiltration and Their Associated Molecular Signature Is Highly Variable in Canine Oligodendroglioma: A Preliminary Evaluation. Veterinary Sciences. 2023; 10(6):403. Additional Declarations No competing interests reported. Supplementary Files CanineGSLCMetabolismSuppMethods.docx CanineGSLCSupplementFigsTables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4600799","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":319704349,"identity":"9aeb95f5-eff3-45af-aa99-11d1798046c7","order_by":0,"name":"Ryan Toedebusch","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"Ryan","middleName":"","lastName":"Toedebusch","suffix":""},{"id":319704351,"identity":"738b42da-bc51-410d-a31d-20fb722f896a","order_by":1,"name":"Chang-il Hwang","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"Chang-il","middleName":"","lastName":"Hwang","suffix":""},{"id":319704352,"identity":"50998b19-3bfc-42eb-b89a-6597c5a8cfca","order_by":2,"name":"Shafee Syed-Quadri","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"Shafee","middleName":"","lastName":"Syed-Quadri","suffix":""},{"id":319704353,"identity":"5a872570-d488-447c-ab8c-a8f400126d0d","order_by":3,"name":"Orwa Aboud","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"Orwa","middleName":"","lastName":"Aboud","suffix":""},{"id":319704354,"identity":"96e9af6d-4e5f-482e-a953-0226f79c7c61","order_by":4,"name":"Kevin Woolard","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"","lastName":"Woolard","suffix":""},{"id":319704355,"identity":"5f0d117e-ec7d-4e62-9b24-02679f35e8e6","order_by":5,"name":"Daniel York","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"York","suffix":""},{"id":319704359,"identity":"f809f52b-74ea-43e4-a73f-914957a61d66","order_by":6,"name":"Maciej Parys","email":"","orcid":"","institution":"University of Edinburgh","correspondingAuthor":false,"prefix":"","firstName":"Maciej","middleName":"","lastName":"Parys","suffix":""},{"id":319704361,"identity":"3e3e309a-342c-4050-a5fb-5f5b0f130b6e","order_by":7,"name":"Peter Dickinson","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Dickinson","suffix":""},{"id":319704362,"identity":"8e2b479c-7aec-4134-a237-70d815cce150","order_by":8,"name":"Frederick Meyers","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"Frederick","middleName":"","lastName":"Meyers","suffix":""},{"id":319704363,"identity":"453583d9-98cc-4846-956d-3d5e67cb014e","order_by":9,"name":"John McPherson","email":"","orcid":"","institution":"University of California, Davis","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"McPherson","suffix":""},{"id":319704364,"identity":"e05c68eb-e860-44d4-aada-7db3cb92b301","order_by":10,"name":"Christine Toedebusch","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYNACNoYEMPmBgYGxAYQYGJjxKGdGaGGcQbIWZh4GiHq8WvinnT/44EOZTZ7B+cPPHtu22cn2z0hu/sBQYZ3YgEOLxO1kZsMZ59KKDW6kmRvntiUbz7iR2CbBcCYdpxYD6WQ2ad62w4kbbvCwSee2HUhsOHOwjYERKIJXy9+2/4kbzp9hk7YEapl/5mDzB8Z/BLQwAlVuOJADZRxvbJBgbMCtBegXY8Oec8nFkjfSzCSBDOONxxvbJBKOpRvj0sI/O/Hhgx9ldnl8wBCTADJk5x1mf/zhQ421LC4tOEACacpHwSgYBaNgFKABAITPXx6gFXh9AAAAAElFTkSuQmCC","orcid":"","institution":"University of California, Davis","correspondingAuthor":true,"prefix":"","firstName":"Christine","middleName":"","lastName":"Toedebusch","suffix":""}],"badges":[],"createdAt":"2024-06-18 14:47:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4600799/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4600799/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60623917,"identity":"996d6e96-7864-4ead-a4ee-5a2989acad26","added_by":"auto","created_at":"2024-07-18 21:59:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":97260,"visible":true,"origin":"","legend":"\u003cp\u003eCanine glioma stem-like cells (GSLCs) increased cellular respiration following hypoxia. Oxygen consumption (OCR, pmol/min/µg protein) profile of (\u003cstrong\u003eA\u003c/strong\u003e) GSLC 0514, during the mitochondrial stress test following normoxia and hypoxia (1% FIO\u003csub\u003e2\u003c/sub\u003e) treatment. (\u003cstrong\u003eB – E) \u003c/strong\u003eare calculated values from A for basal, ATP-linked, Maximal, and spare capacity, respectively. These values are empirically determined using calculations from Agilent. \u003cstrong\u003e(F\u003c/strong\u003e) OCR profile from mitochondrial stress test assay of GSLC 1110 cells after hypoxia. (\u003cstrong\u003eG – J\u003c/strong\u003e) Calculated values from F for basal, ATP-linked, Maximal, and spare capacity, respectively.\u0026nbsp; \u003cstrong\u003e(K\u003c/strong\u003e) OCR profile from mitochondrial stress test assay of G06A cells after hypoxia. (\u003cstrong\u003eL – O\u003c/strong\u003e) Calculated values from K for basal, ATP-linked, Maximal, and spare capacity, respectively. Comparisons based on unpaired t­-test; *p\u0026lt;0.05; **p\u0026lt;0.01, ***p\u0026lt;0.001. Scatter dot plot with bar at the group mean; lines represent the standard error of the meanm (SEM). (\u003cstrong\u003eP\u003c/strong\u003e) Normoxia: ATP-linked relative OCR was attenuated from basal OCR in GSLC 1110 (\u003csup\u003eb\u003c/sup\u003ep=0.0108) and G06A cells (\u003csup\u003ea\u003c/sup\u003ep=0.0357). (\u003cstrong\u003eQ\u003c/strong\u003e) Hypoxia: Relative ATP-linked OCR was decreased from basal OCR in both GSLC cell lines (0514: \u003csup\u003ec\u003c/sup\u003ep=0.0265; 1110: \u003csup\u003eb\u003c/sup\u003ep=0.0066). Relative maximum OCR was lower in G06A cells compared to GSC 1110 cells (\u003csup\u003e#\u003c/sup\u003ep = 0.0297). Relative spare OCR was attenuated in G06A cells compared to 1110 cells (\u003csup\u003e#\u003c/sup\u003ep = 0.0016) and 0514 cells (\u003csup\u003e#\u003c/sup\u003ep = 0.0004). Comparisons based on 2-way repeated measures analysis of variance with post hoc Sidak’s multiple comparison test; bars represent group mean and SEM. Data represent one of three independent experiments.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/0e4a16f89739bc48c2b8ce2e.jpg"},{"id":60623685,"identity":"72d0a274-4b70-4bd1-984d-7c6e4555b8e6","added_by":"auto","created_at":"2024-07-18 21:51:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53818,"visible":true,"origin":"","legend":"\u003cp\u003eHypoxia-induced cytosine methylation is similar across canine glioma cell lines.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Density plot depicting average cytosine methylation values for each group. Heatmap of methylation values of significant DMCs between normoxia and hypoxia of (\u003cstrong\u003eB\u003c/strong\u003e) GSLC 0514, (\u003cstrong\u003eC\u003c/strong\u003e) GSLC 1110, and (\u003cstrong\u003eD\u003c/strong\u003e) G06A cell lines. Blue equals 1.0, or 100%, methylation at indicated cytosine; yellow equals 0.0, or 0%, methylation at indicated cytosine.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/45fe198cdd684282e3e990ec.jpg"},{"id":60623688,"identity":"7d51652c-3517-40aa-ba9e-ef9dc0451645","added_by":"auto","created_at":"2024-07-18 21:51:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":112256,"visible":true,"origin":"","legend":"\u003cp\u003eDifferentially methylated regions were cell line specific. Heatmap of methylation values of significant differentially methylated regions (DMRs) between normoxia and hypoxia of (\u003cstrong\u003eA\u003c/strong\u003e) GSLC 0514, (\u003cstrong\u003eB\u003c/strong\u003e) GSLC 1110, and (\u003cstrong\u003eC\u003c/strong\u003e) G06A cell lines. Blue equals 1.0, or 100%, methylation at indicated region; yellow equals 0.0, or 0%, methylation at indicated region. (\u003cstrong\u003eD\u003c/strong\u003e) Table displaying quantification of hypo- and hypermethylated regions across cell lines. Venn diagrams demonstrating little overlap between cell lines of hypoxia-induced (\u003cstrong\u003eE\u003c/strong\u003e) hypomethylation and (\u003cstrong\u003eF\u003c/strong\u003e) hypermethylation of specific genes mapped to DMRs.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/3884c76b7c92337d9f5af26c.jpg"},{"id":60623916,"identity":"91dcf453-6796-431d-a154-a77ebe604770","added_by":"auto","created_at":"2024-07-18 21:59:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":80696,"visible":true,"origin":"","legend":"\u003cp\u003eHypoxia-induced hypomethylation correlated with increased mRNA levels of genes regulating cellular metabolism and cancer stemness. (\u003cstrong\u003eA\u003c/strong\u003e) \u003cem\u003eSTK32C \u003c/em\u003emRNA levels were increased following hypoxia in both GSLCs. (\u003cstrong\u003eB\u003c/strong\u003e) mRNA levels of hypomethhlated \u003cem\u003eHDAC4 \u003c/em\u003ewere uncharged following hypoxia in GSLC 1110 and G06A cell lines. (\u003cstrong\u003eC\u003c/strong\u003e) Hypomethylation was associated with Increased mRNA levels of multiple genes in GSLC 1110s. (\u003cstrong\u003eC\u003c/strong\u003e) mRNA levels of multiple genes were increased following hypoxia in GSC 0514 cells. (\u003cstrong\u003eD\u003c/strong\u003e) Hypomethylation was associated with Increased mRNA levels of multiple genes in GSLC 1110s. (\u003cstrong\u003eE\u003c/strong\u003e) mRNA levels of \u003cem\u003eENO1 \u003c/em\u003ewere increased in G06A cells following hypoxia. Comparisons based on unpaired t­-test;*p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001, ****p\u0026lt;0.0001. Bars represent group mean and standard error of the mean. Data represent one of three independent experiments.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/fca48f97f13f4d95812d8e47.jpg"},{"id":60623919,"identity":"d7e75961-e427-459a-815b-42e448f27aa9","added_by":"auto","created_at":"2024-07-18 21:59:22","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":47305,"visible":true,"origin":"","legend":"\u003cp\u003eHypoxia differentially augmented malignant features of canine glioma cell lines. (\u003cstrong\u003eA\u003c/strong\u003e) Relative cellular viability was increased in GSLC 0514 cells following hypoxia (p\u0026lt;0.0001), but not (\u003cstrong\u003eB\u003c/strong\u003e) GSLC 1110 (p=0.0848), nor (\u003cstrong\u003eC\u003c/strong\u003e) G06A cells (p=0.1762). Relative cellular migration was increased in (\u003cstrong\u003eE\u003c/strong\u003e) GSLC 1110 cells (p=0.0016), but not (\u003cstrong\u003eD\u003c/strong\u003e) GSLC 0514 cells (p=0.1258) nor (\u003cstrong\u003eF\u003c/strong\u003e) G06A cells (p=0.0014), . Comparisons based on unpaired t­-test; **p\u0026lt;0.01, ****p\u0026lt;0.0001. Bars represent group mean and standard error of the mean. Data represent one of three independent experiments.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/bcd60ad97569f3a736de073b.jpg"},{"id":60623920,"identity":"99dd17e5-85d6-46b2-b54b-1e50f94cc83a","added_by":"auto","created_at":"2024-07-18 21:59:23","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":129516,"visible":true,"origin":"","legend":"\u003cp\u003eThe hypomethylated gene signature following hypoxia in canine astrocytoma GSLCs positively correlated with increased mRNA levels of orthologous genes in adult GBM GSCs. \u0026nbsp;(\u003cstrong\u003eA\u003c/strong\u003e) Gene Set Enrichment Analysis between genes that were hypomethylated following hypoxia in canine GSLCs and orthologous genes in adult GBM GSCs with increased mRNA expression following hypoxia (normalized enrichment score (NES) = 1.87, p\u0026lt;0.01). (\u003cstrong\u003eB\u003c/strong\u003e) There was no correlation between hypermethylated genes in canine GSLCs and expression of orthologous genes in adult GBM GSCs (NES: 1.04, p=0.35). (\u003cstrong\u003eC\u003c/strong\u003e) Gene Set Enrichment Analysis between genes that were hypomethylated following hypoxia in canine GSLCs and orthologous genes in diffuse intrinsic pontine glioma (DIPG) patient samples stratified by a hypoxic signature. There was a negative correlation between hypomethylated genes in canine GSLCs and differentially expressed orthologous genes in DIPG (NES = -1.51, p=0.02). (\u003cstrong\u003eD\u003c/strong\u003e) There was no correlation between hypermethylated genes in canine GSLCs and differentially expressed orthologous genes in DIPG (NES: -0.99, p=0.47).\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/3596fed5219e1f1e6ad7e9b9.jpg"},{"id":89260410,"identity":"a71c9ae2-fc2f-4101-8ddb-e99e77aebb33","added_by":"auto","created_at":"2025-08-18 06:47:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1820291,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/834643ac-1a4a-4981-adda-27690e64595c.pdf"},{"id":60623691,"identity":"ecf90764-a8e2-46f0-8bf0-c6621bd19cf5","added_by":"auto","created_at":"2024-07-18 21:51:22","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":20720,"visible":true,"origin":"","legend":"","description":"","filename":"CanineGSLCMetabolismSuppMethods.docx","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/1cded50d77af53544a37572f.docx"},{"id":60623693,"identity":"c87f2c81-abae-4ed7-a4af-a5a2c1bd3984","added_by":"auto","created_at":"2024-07-18 21:51:23","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":31152612,"visible":true,"origin":"","legend":"","description":"","filename":"CanineGSLCSupplementFigsTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4600799/v1/dcfa4f0787ddda86a12c6c99.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Canine glioma stem-like cells demonstrate DNA methylation-dependent enhancement of cellular respiration following low oxygen tension","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe concept of cancer stem cells originated in 1937 when a mouse injected with a single leukemia cell developed a rapidly lethal leukemia \u003csup\u003e1\u003c/sup\u003e. Over the past several decades of research, cancer stem cells are now defined as a subpopulation of tumor cells that have characteristics of sustained self-renewal, persistent proliferation, and tumor initiation. Stem cells have been identified in several cancers, including high-grade glioma (HGG)\u003csup\u003e2,3\u003c/sup\u003e. HGGs are uniformly lethal primary brain tumors of children and adults\u003csup\u003e4\u003c/sup\u003e, and are the leading cause of cancer-related death in children\u003csup\u003e5\u003c/sup\u003e. Glioma stem cells (GSCs) have been implicated in resistance to radiotherapy\u003csup\u003e3\u003c/sup\u003e and chemotherapy\u003csup\u003e6\u003c/sup\u003e, leading to tumor recurrence and poor median survival times in both pediatric (14\u0026ndash;20 months\u003csup\u003e7\u003c/sup\u003e) and adult (e.g., glioblastoma (GBM), 18 months\u003csup\u003e8\u003c/sup\u003e) HGG. Mechanisms underlying GSC malignancy have been extensively studied; however, targeted therapies for this specific cell population are still lacking.\u003c/p\u003e \u003cp\u003eMetabolic flexibility plays a crucial role in regulating GSC function\u003csup\u003e9\u003c/sup\u003e. Following Dr. Otto Warburg\u0026rsquo;s 1956 observation that cancer cells favor glycolytic metabolism, it has long been assumed that glioma cells, including GSCs, relied upon glycolysis for energy production. However, recent evidence indicates that GSCs readily switch between oxidative and non-oxidative glucose metabolism depending on nutrient availability. For example, pyruvate is utilized by GSCs for non-oxidative metabolism through lactate production, as well as oxidative metabolism by contributing a significant number of glucose carbons to the tricarboxylic (TCA) cycle \u003csup\u003e10\u003c/sup\u003e. Moreover, GSCs up-regulate the pentose phosphate pathway for self-renewal during periods of prolonged hypoxia \u003csup\u003e11\u003c/sup\u003e. In addition to cellular respiration, mitochondria regulate several cellular processes including DNA repair \u003csup\u003e12\u003c/sup\u003e, and cell cycle control \u003csup\u003e13\u003c/sup\u003e. In contrast to many non-cancer stem cells that have underdeveloped mitochondria \u003csup\u003e14\u003c/sup\u003e, GSCs heavily depend on mitochondrial function for metabolic plasticity, cytoprotection to sustain stemness, and resistance to radiotherapy and chemotherapy.\u003c/p\u003e \u003cp\u003eEpigenetic regulation has been strongly associated with the key features of GSCs, such as metabolic flexibility and stemness. For example, nicotinamide-N-methyltransferase (NNMT) has emerged as a link between cellular metabolism and epigenetic regulation. Catalyzing the methylation of nicotinamide, NNMT maintains cellular dependency on oxidative phosphorylation \u003csup\u003e15\u003c/sup\u003e and is ranked among the most consistently overexpressed metabolic genes in GBM \u003csup\u003e16\u003c/sup\u003e. Similarly, epigenetic regulation can promote GSC maintenance. For example, Enhancer of Zeste Homolog 2 (EZH2) is a potent epigenetic modulator across pediatric and adult HGG and is necessary to maintain GSC stemness\u003csup\u003e17\u003c/sup\u003e. These examples support that the malignancy of HGG rests, in part, on the intersection of epigenetics, metabolism, and GSC maintenance.\u003c/p\u003e \u003cp\u003eTherapeutic targeting of GSCs has shown promising preclinical efficacy, but they have not successfully been applied to human HGG patients. Many of these studies were conducted in immunocompromised rodent models. As tissue context and the tumor microenvironment influence tumorigenesis and tumor progression, the absence of a host response precludes accurate prediction of a therapeutic response in human patients. Thus, spontaneous canine high-grade glioma may offer a complementary model for therapeutic translation from rodent models to human patients. Spontaneous canine high-grade gliomas (HGGs), including both astrocytoma and oligodendroglioma tumors, have historically been utilized as a model for HGG. Like human HGG, canine HGGs harbor a stem cell population\u003csup\u003e18,19\u003c/sup\u003e, yet their metabolic plasticity and epigenetic regulation remains unknown.\u003c/p\u003e \u003cp\u003eThe objectives of this study were to investigate a) the metabolic flexibility of canine astrocytoma derived glioma stem-like cells (GSLCs), b) the associated epigenetic changes under hypoxic conditions, and c) the correlation of these findings with human pediatric and adult HGG, aiming to enhance the translational relevance of spontaneous canine glioma as a model for human patients. We found that hypoxia increased oxygen consumption rates in canine GSLCs, which corresponded with hypoxia-induced hypomethylation and increased mRNA levels of genes important in cellular metabolism and stemness (e.g., \u003cem\u003eKCNN3, KDM4B, TCF7L2)\u003c/em\u003e, as well as augmented features of malignancy in GSLCs. Importantly, we were able to demonstrate a positive correlation between up-regulated genes in GBM GSCs and hypomethylation of orthologous canine genes. Together, these data highlight similarities between canine astrocytoma and GBM GSC cellular metabolism and (epi)genetic regulation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCanine glioma cell lines\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe utilized three patient-derived canine astrocytoma cell lines in this study (G06A \u003csup\u003e20\u003c/sup\u003e, 1110 \u003csup\u003e21\u003c/sup\u003e, and 0514 \u003csup\u003e21\u003c/sup\u003e). G06A is a traditional serum grown canine glioma cell line. 0514 and 1110 are considered canine GSLCs, which have been verified to express neural progenitor cell markers (SOX2, OLIG2, GFAP, NES) \u003csup\u003e22\u003c/sup\u003e. Genomic integrity of each cell line was verified by comparison of copy number alterations with parental tumor DNA using Illumina CanineHD SNP array and sequenced to confirm canine origin. All cell lines were routinely tested and confirmed to be mycoplasma free by PCR. Prior to endpoint assays, cells were cultured under normoxic (21% O\u003csub\u003e2\u003c/sub\u003e) or hypoxic (1% O\u003csub\u003e2\u003c/sub\u003e) conditions for 72 hours. To achieve hypoxia, cells were incubated in 1% O\u003csub\u003e2\u003c/sub\u003e using the Hypoxia Incubator Chamber (#27310; STEMCELL Technologies, Vancouver, British Columbia, Canada). Detailed culture conditions are further described in Supplementary Methods.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eWhole Genome Sequencing\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eGenomic DNA was isolated from each cell line (DNeasy Blood \u0026amp; Tissue Kit #69504, Qiagen, Valencia, CA, USA) and quantified using Qubit fluorometer (ThermoFisher Scientific, Waltham, MA, USA). Libraries were prepared using TruSeq DNA PCR Free Kit (Illumina Inc., San Diego, CA, USA). The library was subsequently sequenced to an average depth of 60x using Illumina NovaSeq platform for paired-end sequencing with a 150 base pair read length.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhole genome sequence reads were trimmed, aligned and copy number and variants called using the canFam6 canine genome (GCF_000002285.5, Dog10K_Boxer_Tasha; Dog Genome Sequencing Consortium) with the addition of the ROS_Cfam_1.0 \u003csup\u003e23,24\u003c/sup\u003e canine chromosome Y on an Illumina DRAGEN (Dynamic Read Analysis for Genomics) Ultra-Rapid Next Generation Sequencing Data Analysis Platform. Q30 bases were greater than 92%, with median genome coverage of 89- to 95-fold across the 3 genomes. Copy number analysis utilized the segmentation files derived from the DRAGEN analysis as well as the R packages BSgenome v1.68.0, QDNAseq v1.36.0\u003csup\u003e25\u003c/sup\u003e, and ACE v1.18.0 0\u003csup\u003e26\u003c/sup\u003e within RStudio. The required CanFam6 BSgenome package was forged using BSgenome with the canine genome plus chr Y described above. A mappability file was generated using GenMap v1.3.0\u003csup\u003e27\u003c/sup\u003e and converted with the UCSC genome browser tools \u0026lsquo;wigToBigWig\u0026rsquo;, \u0026lsquo;bigWigToBedGraph\u0026rsquo; and \u0026lsquo;bigWigAverageOverBed\u0026rsquo;.\u003c/p\u003e \u003cp\u003eVariant calls in vcf format were annotated using Annovar v2020-06-08\u003csup\u003e28\u003c/sup\u003e with purpose built CanFam6 annotation files generated using the UCSC genome browser \u0026lsquo;liftover\u0026rsquo; tool. Variants were filtered using a map quality of 40 and a minimal read depth of 10. Synonymous variants were not considered, and all others were filtered for inclusion as Intogen cancer driver genes, release 2023.05.31\u003csup\u003e29\u003c/sup\u003e. All variants in cancer driver genes were manually reviewed using the Integrated Genome Viewer (IGV v2.15.4)\u003csup\u003e30\u003c/sup\u003e. Normal polymorphic loci were determined by comparison to other normal canine exomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eWhole cell mitochondrial oxygen consumption\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eCells (1.2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e) were seeded on 24-well Seahorse plates. Oxygen consumption rates (OCR) were measured in real-time with Seahorse XF Mitochondria Stress Test Kit (Agilent Technologies, Santa Clara, CA, USA) using the Seahorse XF24 Analyzer (Seahorse Biosciences, Agilent, United States) per manufacturers protocol. Assay conditions are described in Supplementary Methods. Upon assay completion a BCA (ThermoFisher, Waltham, MA, USA) protein assay was performed to normalize OCR to the cell protein content in each well. Three independent experiments with five technical replicates per condition were performed.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eReduced Representation Bisulfide Sequencing library construction and sequencing\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eGenomic DNA was isolated from three replicates per cell line, per condition using Zymo Research DNA isolation kit per the manufacturer\u0026rsquo;s instruction (Zymo Research, Irvine, CA, USA). Reduced representation bisulfide sequencing (RRBS) libraries were constructed using 40ng input DNA per sample. Complete details of library construction are included in Supplementary Methods. Libraries were sequenced using the Illumine NovaSeq 6000 platform for paired-end sequencing with a 150 bp read length.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eRead alignment and bioinformatic analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSequence reads from bisulfite-treated Classic RRBS libraries were identified using the standard Illumina base-calling pipeline. Fastq files were trimmed using TrimGalore version 0.6.4 to remove low quality bases. FastQC 0.11.9 was used to assess the quality redistributions of the data. Reads were aligned to the canine reference genome ROS_Cfam_1.0\u003csup\u003e23,24\u003c/sup\u003e using Bismark 0.22.3. Methylated and unmethylated read totals for each CpG site were called using MethylDackel 0.5.0. The DNA methylation (DNAme) level of each sampled cytosine was estimated as the number of reads reporting a C, divided by the total number of reads reporting a C or T. Differential methylation was detected using the Bioconductor package Dispersion Shrinkage for Sequencing (DSS). Differentially methylated regions (DMRs) in the canine genome were converted to human genome (hg38) using the UCSC genome browser \u0026lsquo;liftover\u0026rsquo; tool. Using the GREAT (Genomic Regions Enrichment of Annotations), the genes associated with the DMRs were identified. Differentially methylated genes across cell lines were imported into Panther 17.0 (pantherdb.org) and DAVID (David.ncifcrf.gov) for gene ontology identification. Two gene sets for hypermethylated DMRs and hypomethylated DMRs were used for the Gene Set Enrichment Analysis (GSEA) with the transcriptome data from human glioma stem-like cell lines upon hypoxia (GBM, GSE45117) and pediatric DIPG samples (GSE26576) with a hypoxia gene signature. The enrichment of the hypoxia signature in these patient samples was confirmed by the Hallmark Hypoxia gene set curated by the GSEA.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative Real Time PCR\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTargeted gene mRNA expression was performed on cell lines cultured under normoxic (21% O\u003csub\u003e2\u003c/sub\u003e) or hypoxic (1% O\u003csub\u003e2\u003c/sub\u003e) conditions for 72 hours. Total RNA isolation and cDNA synthesis were performed as described in Supplementary Methods. Primer sets (Supplementary Table\u0026nbsp;1) were designed using NCBI primer design (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/tools/primer-blast/index.cgi\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/tools/primer-blast/index.cgi\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Primer validation and qPCR reactions were carried out as described in Supplementary Methods. Fold difference in expression between normal brain and tumor samples was calculated and plotted using the double delta Ct analysis with β-actin as the control gene for normalization and relative expression.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCell-based functional assays\u003c/h2\u003e \u003cp\u003eCell viability was determined using the Cell Titer Glo\u0026reg; 2.0 Assay (Promega, Madison, WI, USA) according to the manufacturers protocol. Cellular migration was assessed using transwell migration assays. Detailed experimental conditions are described in Supplementary Methods.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eStatistical analysis for oxygen consumption rate assays, qRT-PCR, and GSLC functional experiments were performed with Prism GraphPad V9.0.2 software. Data were tested for normality via the Shapiro-Wilks test. Data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. Statistical significance was assessed via unpaired two-tailed Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test. Results were regarded as statistically significant for \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eCanine glioma cell lines have few non-polymorphic variants in known oncogenes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWGS analysis revealed that the three cell lines had few non-polymorphic, presumably somatic, variants in known cancer driver genes. All were determined to have a low probability of phenotypic effect or \u0026ldquo;Tolerated\u0026rdquo; by the Sorting Intolerant From Tolerant (SIFT\u003csup\u003e31\u003c/sup\u003e) with one exception; a homozygous PARP4 truncating variant observed in the GSLC 1110 cell line (NM_001145980:exon30:c.4107delT:p.F1369Lfs*10). (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eCancer driver gene variants across canine cell lines. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" style=\"width: 712px; height: 347.179px;\" width=\"712\" height=\"347.179\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eCopy number analysis showed 2N ploidy for cell lines G06A and GSLC 0514, the latter harboring a large chromosome 1 deletion (chr1:28,809,718 \u0026ndash; 527,795,402) and trisomy chromosome 13 (\u003cstrong\u003eSupplementary Figures 1 and 2\u003c/strong\u003e). Cell line GSLC 1110 appears to have had a genome duplication event with 3.8N ploidy (\u003cstrong\u003eSupplementary Figure 1\u003c/strong\u003e). Multiple chromosomes have lost one or two copies with chromosome 31 at 6 copies. Multiple chromosomes show more complex etiology such as chromosome 1 with 4N and 2N segments, proximal and distal, respectively. These likely represent translocation events and attempts to resolve this complexity was not undertaken. Gains of canine chromosomes 13 and 31 are frequently observed in canine carcinomas\u003csup\u003e32,33\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCellular bioenergetics differ between canine GSLCs and differentiated glioma cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo ascertain how hypoxia alters mitochondrial function across cell lines, cells were exposed to normoxia (21% FIO\u003csub\u003e2\u003c/sub\u003e) and hypoxia (1% FIO\u003csub\u003e2\u003c/sub\u003e) for 72 hours and oxygen consumption rates (OCR) were measured. Basal OCR,\u0026nbsp;the net sum of all cellular processes consuming oxygen, was not affected by hypoxia\u0026nbsp;in either GSLC line (0514: 154.0 +/- 18.3 vs. 175.2 +/- 11.7, p=0.1749, \u003cstrong\u003eFigure 1A, B\u003c/strong\u003e); (1110: 175.2 +/- 4.46 vs. 159.8 +/- 8.2, p=0.3668, \u003cstrong\u003eFigure 1F, 1G\u003c/strong\u003e). Similarly, G06A basal OCR was not affected by hypoxia (130.3 +/- 15.9 vs. 176.6 +/- 18.7,\u0026nbsp;p=0.1255, \u003cstrong\u003eFigure 1K, L\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo assess the specific contribution of ATP-linked respiration to OCR, ATP synthase (Complex V) was inhibited via oligomycin. ATP-linked OCR was not altered by hypoxia in any cell line (0514: 105.5 +/- 4.6 vs. 106.0 +/- 10.4, p=0.9670, \u003cstrong\u003eFigure 1A, C\u003c/strong\u003e; 1110: 105.7 +/- 6.9 vs. 92.9 +/- 13.3 p=0.4238, \u003cstrong\u003eFigure 1F, H\u003c/strong\u003e; G06A:\u0026nbsp;91.3 +/- 8.8 vs. 124.2 +/- 14.5\u0026nbsp;p=0.1248, \u003cstrong\u003eFigure 1K, M\u003c/strong\u003e). Next, carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone (FCCP) was administered to determine maximal cellular OCR. Hypoxia increased maximal OCR by \u0026ge;2-fold in both GSLC lines (0514: 672.4 +/- 17.8 vs. 265.9 +/- 26.2, p=0.0002, \u003cstrong\u003eFig. 1A, D\u003c/strong\u003e; 1110: 762.4 +/- 51.7 vs 333.3 +/- 45.7,\u0026nbsp;p=0.0008, \u003cstrong\u003eFigure 1F, I\u003c/strong\u003e), but attenuated maximal OCR in G06A cells (274.2 +/- 29.9 vs 637.2 +/- 83.8, p=0.0151, \u003cstrong\u003eFigure 1K, N\u003c/strong\u003e). Lastly, mitochondrial spare respiratory capacity (SRC) was assessed following injection of a mixture of rotenone, a complex I inhibitor, and antimycin A, a complex III inhibitor. SRC increased \u0026ge;3-fold following hypoxia treatment in GSLCs (0514: 512.5 +/- 12.9 vs 90.7 +/- 29.1, p=0.0002, \u003cstrong\u003eFigure 1A, E\u003c/strong\u003e; 1110: 587.2 +/- 39.9 vs 179.3 +/- 30.4,\u0026nbsp;p=0.0002, \u003cstrong\u003eFigure 1F, J\u003c/strong\u003e), but was attenuated in G06A cells (90.7 +/- 29.1 vs. 512.5 +/- 12.9,\u0026nbsp;p=0.0092, \u003cstrong\u003eFigure 1K, O\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTo compare the magnitude of change in OCR throughout the mitochondrial stress test within and across cell lines, the OCR at each timepoint was normalized to the basal OCR for each condition. Under normoxic conditions, relative ATP-linked OCR was decreased from basal OCR in GSLC 1110 cells (60.3 +/- 8.6 vs. 100.1 +/- 11.9; p=0.0108) and G06A cells (69.9 +/- 8.1 vs. 100.0 +/- 10.5; p=0.0357), but not GSLC 0514 cells (p=0.0714) (\u003cstrong\u003eFigure 1P\u003c/strong\u003e). G06A cells had the largest relative increase in maximal (358.7 +/- 47.2) and SRC (258.7 +/- 36.8), with a significantly increased SRC compared GSLC 0514 cells (51.8 +/- 16.6; p = 0.0342) (\u003cstrong\u003eFigure 1P\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFollowing exposure to hypoxia, relative ATP-linked OCR was decreased from basal OCR in both GSLC cell lines (0514: 66.0 +/- 5.0 vs. 100.0 +/- 8.0, p=0.0265; 1110: 60.3 +/- 7.9 vs. 100.0 +/- 13.4, p=0.0066), but not G06A cells (p=0.1636) (\u003cstrong\u003eFigure 1Q\u003c/strong\u003e). However, relative maximal OCR and SRC following hypoxia was robust in both GSLC lines. The relative maximal OCR was markedly increased in GSLC 1110 cells (435.0 +/- 59.0, p=0.0297) with a similar, non-significant rise in GSLC 0514 cells (420.6 +/- 19.2, p=0.0530) (\u003cstrong\u003eFigure 1Q\u003c/strong\u003e). Relative SRC was also significantly increased in both GSLCs (GSLC 110 cells: 3352 +/- 45.6, p=0.0016; GSLC 0514 cells: 320.6 +/- 14.0, p = 0.0004. However, neither relative maximal OCR (110.4 +/- 18.7; p=0.4671) (\u003cstrong\u003eFigure 1Q\u003c/strong\u003e), nor SRC (110.4 +/- 18.7; p=0.1434) were increased in G06A cells. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypoxia-induced methylation alterations were cell line specific\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven their differential OCR across conditions, we hypothesized that hypoxia treatment reduced methylation of nuclear-encoded mitochondrial genes in canine GSLCs relative to traditional serum grown glioma cells. \u0026nbsp;We performed reduced representation bisulfite sequencing (RRBS) to generate genome-wide single-nucleotide resolution DNA methylation profiles across cell lines following normoxia and hypoxia treatment. On average, \u0026gt;35 million bisulfite sequencing reads were generated per sample, with \u0026gt;98% bisulfite conversion efficiency (\u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e). At least 53% of CpG dinucleotides in the canine genome (ROS_Cfam_1.0) were covered with at least one read. (ROS_Cfam_1.0). The average methylation values were similarly distributed across groups (\u003cstrong\u003eFigure 2A\u003c/strong\u003e). GSLC 0514 had the largest number of differentially methylated cytosines (DMCs; n=307), with the majority of cytosines hypomethylated following hypoxia (n=254; \u003cstrong\u003eFigure 2B\u003c/strong\u003e). G06A cells followed a similar pattern, with 190/266 DMCs exhibiting hypomethylation (\u003cstrong\u003eFigure\u003c/strong\u003e \u003cstrong\u003e2D\u003c/strong\u003e). GSLC 1110 cells had the fewest DMCs (n=209) with an equal distribution between hypo- and hypermethylated cytosines (107 vs. 102; \u003cstrong\u003eFigure 2C\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNext, we identified the regions of the nuclear genome with one or more DMC. Differentially methylated regions (DMRs) were calculated as read-depth weighted average over all included cytosines. Despite having the fewest DMCs, GSLC 1110 cells had the most differentially methylated regions (DMRs; n=43; \u003cstrong\u003eFigure 3B, 3D\u003c/strong\u003e) following hypoxia treatment, with an equal distribution between hypo- and hypermethylated regions. G06A cells had 33 DMRs resulting in hypomethylation of most regions following hypoxia treatment (n=24/33; \u003cstrong\u003eFigure 3C, D\u003c/strong\u003e). GSLC 0514 cells had the fewest DMRs (n=25), most of which were hypomethylated following hypoxia treatment (n=20;\u0026nbsp;\u003cstrong\u003eFigure 3A, D\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eWe utilized Integrative Genomics Viewer to identify specific genes mapping to the DMRs. Hypoxia treatment induced hypomethylation of 39 identifiable genes in GSLC 0514 cells, 31 genes in GSLC 1110 cells, and 26 genes in G06A cells. Three hypomethylated genes were shared between GSLC 0514 and GSLC 1110 cells (\u003cem\u003eCDH4, KCNN3, STK32C\u003c/em\u003e), with a single gene shared between GSLC 1110 and G06A cells (\u003cem\u003eHDAC4\u003c/em\u003e) (\u003cstrong\u003eFigure 3E\u003c/strong\u003e). Hypoxia treatment induced hypermethylation of 37 genes in GSLC 0514 cells, 30 genes in GSLC 1110 cells, and 39 genes in G06A cells (\u003cstrong\u003eFigure 3F\u003c/strong\u003e). Two hypermethylated genes were shared between GSLC 0514 and GSLC 1110 cells (\u003cem\u003eARHGEF28, FOXN3\u003c/em\u003e)\u0026nbsp;(\u003cstrong\u003eFigure 3F\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGenes with the molecular function associated with \u0026lsquo;binding\u0026rsquo; were commonly differentially methylated across cell lines (\u003cstrong\u003eSupplemental\u003c/strong\u003e \u003cstrong\u003eFigure 3A, B\u003c/strong\u003e). Commonly hypomethylated genes following hypoxia were associated with DNA binding and bone morphogenetic protein (BMP) receptor binding function in both GSLC 1110 and 0514 cell lines\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eHowever, the most commonly hypomethylated genes following hypoxia in G06A cells were associated with zinc ion binding and sequence-specific DNA binding (e.g., RNA poly II core promoter proximal region). Genes associated with metal ion binding function were commonly hypermethylated following hypoxia in all three cell lines.\u003c/p\u003e\n\u003cp\u003eGenes with the biological process associated with \u0026lsquo;cellular process\u0026rsquo; (GO 009987) were the most differentially methylated across cell lines (\u003cstrong\u003eSupplemental\u003c/strong\u003e \u003cstrong\u003eTable 2\u003c/strong\u003e). All three cell lines had multiple hypo- and hypermethylated genes associated with \u0026lsquo;cellular metabolic process\u0026rsquo; (GO 0044237) and \u0026lsquo;regulation of biological process\u0026rsquo; (GO 0060789). Both GSLC lines, but not G06A, had multiple hypomethylated genes associated with \u0026lsquo;cellular component organization or biogenesis\u0026rsquo; (GO 007165). However, hypoxia also had differential effects on methylation between GSLC lines. Several genes associated with \u0026lsquo;signal transduction\u0026rsquo; (GO 007165) and \u0026lsquo;cellular communication\u0026rsquo; (GO 0044237) were hypomethylated in GSLC 0514s. Genes associated with \u0026lsquo;cellular response to stimulus\u0026rsquo; (GO 0051716) and \u0026lsquo;cellular communication\u0026rsquo; (GO 007154) were hypermethylated in GSLC 1110s. G06A cells also had several hypermethylated genes associated with \u0026lsquo;cellular response to stimulus\u0026rsquo; (GO 0051716) and \u0026lsquo;cellular communication\u0026rsquo; (GO 007154) (\u003cstrong\u003eSupplemental\u003c/strong\u003e \u003cstrong\u003eTable 2\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDifferential methylation was associated with altered gene expression following hypoxia\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe next sought to determine the effect of methylation on gene expression of several DMGs. \u003cem\u003eCDH4, KCNN3,\u0026nbsp;\u003c/em\u003eand \u003cem\u003eSTK32C\u003c/em\u003e were hypomethylated following hypoxia in both GSLC lines. \u003cem\u003eSTK32C\u003c/em\u003e, but not \u003cem\u003eKCNN3\u003c/em\u003e, mRNA levels were increased following hypoxia (GSLC 1110: 4-fold, p\u0026lt;0.05; GSLC 0514: 5-fold, p\u0026lt;0.001) (\u003cstrong\u003eFigure 4A\u003c/strong\u003e). \u003cem\u003eCDH4\u003c/em\u003e was below the limit of detection in both cell lines. mRNA levels of hypermethylated \u003cem\u003eFOXN3\u0026nbsp;\u003c/em\u003ewere increased following hypoxia in GSLC 0514 cells (3-fold; p\u0026lt;0.05) but were unchanged in GSLC 1110s (p= 0.3981) (\u003cstrong\u003eFigure 4A\u003c/strong\u003e). mRNA levels of hypermethylated \u003cem\u003eARHGEF28\u0026nbsp;\u003c/em\u003ewere unchanged in both GSLC 0514 (p=0.1659) and 1110 lines (p=0.1182) (\u003cstrong\u003eFigure 4A\u003c/strong\u003e). Hypoxia induced hypomethylation of \u003cem\u003eALDH9A1, HT2RC,\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;TCF7L2\u0026nbsp;\u003c/em\u003ecorresponded with increased mRNA levels in GSLC 0514 cells (\u003cem\u003eALDH9A1\u003c/em\u003e: 2.5-fold, p\u0026lt;0.001; \u003cem\u003eHT2RC\u003c/em\u003e: 1.5-fold, p\u0026lt;0.05; \u003cem\u003eTCF7L2\u003c/em\u003e: 4-fold, p\u0026lt;0.0001) (\u003cstrong\u003eFigure 4C\u003c/strong\u003e). mRNA levels of hypermethylated \u003cem\u003eCABLES1\u003c/em\u003e (2-fold; p\u0026lt;0.001), but not \u003cem\u003eARID5B\u0026nbsp;\u003c/em\u003e(p=0.1362) were decreased following hypoxia in GSLC 0514 cells (\u003cstrong\u003eFigure 4C\u003c/strong\u003e). Hypoxia induced hypomethylation of \u003cem\u003eCLOCK\u0026nbsp;\u003c/em\u003eand \u003cem\u003eKDM4B\u0026nbsp;\u003c/em\u003ein GSLC 1110 cells\u003cem\u003e\u0026nbsp;\u003c/em\u003ecorresponded with increased mRNA levels (\u003cem\u003eCLOCK\u003c/em\u003e: 3-fold, p\u0026lt;0.001; \u003cem\u003eKDM4B\u003c/em\u003e: 5-fold, p\u0026lt;0.0001) (\u003cstrong\u003eFig. 4D\u003c/strong\u003e). Moreover, hypermethylation of \u003cem\u003eNOX5\u0026nbsp;\u003c/em\u003ewas associated with increased mRNA levels (12-fold; p\u0026lt;0.0001) (\u003cstrong\u003eFigure 4D\u003c/strong\u003e). Hypoxia-induced hypomethylation was not associated with changes in mRNA expression of \u003cem\u003eFLNA2,\u0026nbsp;\u003c/em\u003enor\u003cem\u003e\u0026nbsp;TGFB3\u003c/em\u003e,\u003cem\u003e\u0026nbsp;\u003c/em\u003ein G06A cells (\u003cstrong\u003eFigure 4E\u003c/strong\u003e).\u003cem\u003e\u0026nbsp;\u003c/em\u003eHypermethylation of \u003cem\u003eENO1\u0026nbsp;\u003c/em\u003e(10-fold, p\u0026lt;0.0001\u003cem\u003e),\u0026nbsp;\u003c/em\u003ebut not\u003cem\u003e\u0026nbsp;RFN6\u0026nbsp;\u003c/em\u003e(p=0.6183), was associated with decreased mRNA levels in G06A cells (\u003cstrong\u003eFigure 4E\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypoxia differentially augmented malignant features of canine glioma cell lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the up regulation of metabolic and cancer stemness genes in GSLCs following hypoxia, we hypothesized that hypoxia would alter functional properties of GSLCs, but not traditional serum grown glioma cells. Indeed, relative viability increased more than 50% in GSLC 0514 cells following hypoxia (100.0 +/- 3.6; p\u0026lt;0.0001) (\u003cstrong\u003eFigure 5A\u003c/strong\u003e). However, viability was unaffected by hypoxia in GSLC 1110 cells (p=0.0848) and G06A cells (p=0.1762) (\u003cstrong\u003eFigure 5B, C\u003c/strong\u003e). Strikingly, relative cellular migration was increased more than 100% in GSLC 1110 cells following hypoxia (100.0 +/- 12.3 vs. 236.3 +/- 8.2; p=0.0016) (\u003cstrong\u003eFig. 5E\u003c/strong\u003e). However, neither GSLC 0514 (p=0.1258), nor G06A (p=0.1534) migration was altered by hypoxia (\u003cstrong\u003eFigure 5D, F\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypomethylated genes in canine GSLCs correlated with increased expression of orthologous genes in human adult GSCs following hypoxia\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate similarities between canine and human GSC biology under hypoxic stress, we compared genes that were differentially methylated in our canine cell lines to genes that were differentially expressed in human adult (GBM) and pediatric (DIPG) glioma. Utilizing publicly available microarray datasets\u0026nbsp;\u003csup\u003e11,34\u003c/sup\u003e, Gene Set Enrichment Analysis (GSEA) demonstrated a positive correlation between genes that were\u0026nbsp;significantly\u0026nbsp;hypomethylated in canine GSLCs and orthologous genes with increased mRNA expression in GBM GSCs (\u003cstrong\u003eFigure 6A\u003c/strong\u003e; normalized enrichment score (NES) = 1.87, p\u0026lt;0.01). There was no correlation between significantly hypermethylated canine genes and orthologous genes in human GBM GSCs (\u003cstrong\u003eFigure 6B\u003c/strong\u003e; NES: 1.04, p=0.35). We next performed GSEA of\u0026nbsp;35 pediatric diffuse intrinsic pontine glioma (DIPG) patient samples (GSE26576) stratified by a hypoxic signature. We observed a negative correlation between\u0026nbsp;genes that were\u0026nbsp;significantly\u0026nbsp;hypomethylated in canine GSLCs and orthologous genes with differential expression in DIPG (\u003cstrong\u003eFigure 6C\u003c/strong\u003e; NES: -1.51, p=0.02). Similar to human GBM, there was no correlation between hypermethylated canine genes and orthologous genes with differential expression in DIPG (\u003cstrong\u003eFigure 6D\u003c/strong\u003e; NES: -0.99, p=0.47).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we integrated cellular metabolism, DNA methylation, and gene expression patterns to interrogate differences between canine GSLC and traditional serum grown glioma cell lines. Following 72 hours of hypoxia, oxygen consumption rates increased in GSLCs, but not traditional serum grown glioma cell lines. However, there were few similarities in DNA methylation patterns between GSLC lines, which suggests that canine GSLCs are heterogeneous across canine patients, like GBM. Notably, hypoxia induced expression of several genes associated with mitochondrial activity, cancer stemness, and decreased GBM patient survival in canine GSLCs. Moreover, GSLCs, but not traditional serum grown glioma cell lines, had increased features of malignancy following exposure to hypoxia (e.g., proliferation and migration). Finally, we were able to demonstrate a positive correlation between hypomethylated canine GSLC genes and up-regulated orthologous genes in GBM GSC following hypoxia. Taken together, this study supports shared stem cell features between GBM and canine astrocytomas, further strengthening the rationale for the use of dogs with naturally occurring canine astrocytoma as a therapeutic translational model for GBM.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA major finding of this study was the differential effects of hypoxia on the parameters of OCR between canine GSLCs and traditional serum grown glioma cell line. Under normal oxygen tension, canine GSLCs exhibited a quiescent phenotype with smaller changes in OCR, consistent with GBM GSCs \u003csup\u003e35\u003c/sup\u003e. Conversely, canine GSLCs exhibited greater oxygen consumption rates in the presence of low oxygen tension. Maximal and spare respiratory capacity were increased in both GSLC lines, highlighting their metabolic plasticity and ability to overcome the stress of hypoxia and produce ATP \u003csup\u003e36\u003c/sup\u003e. This metabolic plasticity, specifically an increased mitochondrial reserve capacity, may contribute to GSLC derived treatment-resistance in canine glioma patients \u003csup\u003e37-39\u003c/sup\u003e, similar to what has been observed in human GBM GSCs \u003csup\u003e40\u003c/sup\u003e. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCellular respiratory capacity over changing oxygen tension can be influenced through a variety of ways, including altered methylation of nuclear-encoded mitochondrial genes \u003csup\u003e41\u003c/sup\u003e.\u0026nbsp;Few hypo- and hypermethylated genes were shared across GSLC cell lines in this study. Of the shared differentially methylated genes in this study (\u003cem\u003eCDH4, KCNN3, STK32C, ARHGEF28, FOXN3\u003c/em\u003e), only \u003cem\u003eKCNN3\u003c/em\u003e is a known nuclear encoded mitochondrial gene \u003csup\u003e42\u003c/sup\u003e. \u003cem\u003eKCNN3\u003c/em\u003e encodes a small conductance calcium-activated potassium channel and has been identified in mitochondria of human, rat, and guinea pig ventricular myocytes. While its cellular localization has not been confirmed in the brain, it is one of 16 genes encoding ion channels downregulated in adult high-grade glioma patients \u003csup\u003e43\u003c/sup\u003e. In fact, decreased \u003cem\u003eKCNN3\u0026nbsp;\u003c/em\u003emRNA levels have been postulated as a negative prognostic indicator in GBM \u003csup\u003e43\u003c/sup\u003e. It is also worthwhile to note that hypoxia resulted in hypomethylation and an associated robust increase in mRNA levels of \u003cem\u003eSTK32C\u0026nbsp;\u003c/em\u003ein both canine GSLC lines. While less is known about \u003cem\u003eSTK32C\u003c/em\u003e, it\u0026rsquo;s expression is a negative prognostic indicator in several cancers. \u003cem\u003eSTK32C\u0026nbsp;\u003c/em\u003ehas not been linked to cancer stem cells or stemness, but it has been shown to augment proliferation, migration, and invasion in human bladder cancer \u003csup\u003e44\u003c/sup\u003e. Importantly, approximately 90% of adult gliomas express this protein (proteinatlas.org). Thus, \u003cem\u003eSTK32C\u0026nbsp;\u003c/em\u003einhibition may be a shared therapeutic target across species and should be further investigated.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Canine HGG is increasingly recognized as a relevant model for human glioma, but it remains to be determined if canine HGG is best suited as a model for pediatric or adult disease. Going forward, it is imperative to consider canine high-grade astrocytoma and oligodendroglioma as distinct and separate tumors before comparison to pediatric and/or adult HGG. This will inform appropriate translational application of canine glioma clinical trials. Canine cell lines used in this study were patient-derived lines from astrocytic tumors. Our GSEA found a significant positive correlation between hypomethylated genes in canine GSLCs and up-regulated orthologous genes in GBM GSCs following hypoxia. This suggests robust similarities in the hypoxic gene response between canine GSLCs and GBM GSCs. Conversely, hypomethylated genes in canine GSLCs were negatively correlated with up-regulated genes in DIPG patient samples when stratified by their hypoxic signature. Therefore, these results support the hypothesis that canine astrocytoma stem cell function and response to hypoxia is more like GBM than pediatric HGGs. We have previously hypothesized this linkage, as we have shown that the glioma-associated microglia and macrophage response in canine astrocytoma closely aligns with GBM \u003csup\u003e21,45\u003c/sup\u003e. Future canine studies should continue to investigate this important question.\u003c/p\u003e\n\u003cp\u003eOur study had several limitations. Comparisons to normal astrocytic canine cell lines were not performed. While we were unable to evaluate methylation changes induced by neoplastic transformation, our primary objective was to evaluate the hypoxic response (OCR, methylation, functional analysis) of canine GSLCs relative to traditional serum grown glioma cell lines. Moreover, mRNA expression was evaluated on a small subset of candidate genes, precluding a global view of the relationship between methylation and gene expression in canine glioma cell lines. To address these limitations, future studies should consider coupling methylation with single cell RNA sequencing on patient-derived canine glioma samples. This approach would allow for a comprehensive analysis of the effects of DNA methylation on gene expression across GSLCs and differentiated glioma cells. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur data highlight that canine GSLCs are metabolically adaptable like human GBM stem cells. Moreover, the epigenetic regulation of gene expression associated with metabolic plasticity and stemness is heterogenous across canine GSLCs, further recapitulating the heterogeneity observed in GBM and strengthening the use of canine astrocytoma as comparative disease model for GBM.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor\u0026rsquo;s Disclosure:\u0026nbsp;None.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions:\u0026nbsp;Conceptualization, R.G.T, C.M.T.; methodology, R.G.T, C-I.H, O. A, K.D.W, M.P, J.D.M, C.M.T; formal analysis, R.G.T, C-I.H, J.D.M; investigation, R.G.T, S.S-Q, J.D.M; resources, K.D.W, D.Y, M.P, P.J.D.; data curation, R.G.T, C-I.H, M.P, J.D.M; writing\u0026mdash;original draft preparation, R.G.T, C.M.T; writing\u0026mdash;review and editing, R.G.T, C-I.H, S.S-Q, O. A, K.D.W, D.Y, M.P, P.J.D., F.J.M, J.D.M, C.M.T; funding acquisition, R.G.T, C.M.T. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e First and foremost, the authors thank all the companion canines and their owners for donation of their tissues to this work. We also thank the Cortopassi Laboratory and Alexey Tomilov for assistance with all Seahorse experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was supported in part by the UC Davis Paul Calabresi Career Development Award for Clinical Oncology as funded by the National Cancer Institute/National Institutes of Health through grant #2K12CA138464-11 (C.M.T, O.A), The\u0026nbsp;Center for Companion Animal Health (CCAH) within the School of Veterinary Medicine at University of California, Davis through grant #2019-5F, and\u0026nbsp;the Paul C. and Borghild T. Petersen Brain Tumor Foundation (R.G.T, P.J.D., C.M.T).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e\u0026nbsp; The data discussed in this publication have been deposited in NCBI\u0026rsquo;s Gene Expression Omnibus and are accessible through GEO Series accession number GSE223852 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE223852).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFurth J, Kahn MC, Breedis C. The Transmission of Leukemia of Mice with a Single Cell1. \u003cem\u003eThe American Journal of Cancer. \u003c/em\u003e1937; 31(2):276-282.\u003c/li\u003e\n\u003cli\u003eChen J, Li Y, Yu TS, et al. A restricted cell population propagates glioblastoma growth after chemotherapy. \u003cem\u003eNature. \u003c/em\u003e2012; 488(7412):522-526.\u003c/li\u003e\n\u003cli\u003eBao S, Wu Q, McLendon RE, et al. 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Intra- and Intertumoral Microglia/Macrophage Infiltration and Their Associated Molecular Signature Is Highly Variable in Canine Oligodendroglioma: A Preliminary Evaluation. \u003cem\u003eVeterinary Sciences. \u003c/em\u003e2023; 10(6):403.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"hypoxia, metabolism, mitochondria, cancer, epigenetic, glioblastoma","lastPublishedDoi":"10.21203/rs.3.rs-4600799/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4600799/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGlioma stem cells (GSCs) have been implicated in radio- and chemotherapeutic resistance of glioblastoma (GBM). Therapeutic targeting of GSCs has shown promise in immunocompromised rodent models but have not been translated into effective therapies for human patients. The limited success of translating therapies from rodent models to GBM patients may be attributed, in part, to the lack of co-evolution between tumors and the tumor microenvironment in immunocompromised rodent models. Thus, spontaneous canine high-grade gliomas (HGGs) may provide a complementary translational model for human therapeutic development. While described in canine HGGs, little is known about canine glioma stem cell biology. In this study, we evaluatedcellular metabolism, DNA methylation, gene expression, and functional tests of malignancy to interrogate differences between canine glioma stem-cell like (GSLC) lines and a traditional serum grown glioma cell line following exposure to hypoxia. Hypoxia increased oxygen consumption rates in GSLCs, which correlated with hypoxia-induced hypomethylation and increased mRNA levels of genes important in cellular metabolism and stemness (e.g., \u003cem\u003eKCNN3, KDM4B, TCF7L2)\u003c/em\u003e, as well as augmented features of malignancy in GSLCs. Importantly, we were able to demonstrate a positive correlation between up-regulated genes in human GBM GSCs and hypomethylation of orthologous canine genes following hypoxia. Together, these data highlight similarities between canine and human GBM GSC cellular metabolism and their epigenetic regulation.\u003c/p\u003e","manuscriptTitle":"Canine glioma stem-like cells demonstrate DNA methylation-dependent enhancement of cellular respiration following low oxygen tension","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 21:51:17","doi":"10.21203/rs.3.rs-4600799/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"af62ba87-cdd3-4a3b-a155-28e8fc370501","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-18T06:38:51+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-18 21:51:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4600799","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4600799","identity":"rs-4600799","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}