{"paper_id":"3c472bfa-2c33-41ac-88c5-0d6a3fa732fe","body_text":"Lowering of Cholesterol Hampers Glioblastoma Stem Cell Proliferation in Spheroids Through impaired Hh signaling: upregulation of epigenetic chromatin modifiers and down regulation CAV1 and Stem Cell markers | 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 Lowering of Cholesterol Hampers Glioblastoma Stem Cell Proliferation in Spheroids Through impaired Hh signaling: upregulation of epigenetic chromatin modifiers and down regulation CAV1 and Stem Cell markers Tirthankar Baral, Kirtana R, Soumen Manna, Jagdish Mishra, Subhajit Chakraborty, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8095695/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 Glioblastoma multiform (GBM) harbours tumor heterogeneity and shows little efficacy to the current treatment strategies. Persistence of glioma stem cells (GSCs) are the root cause of tumor recurrence and drug resistance. So, targeting GSCs can be a better therapeutic strategy to tackle GBM. To mimic the tumor microenvironment, we have developed tumor spheroids by hanging drop method using U87MG and Ln229 cells with an enriched GSC population. Compared to monolayer cells spheroids had higher expression of stemness markers like CD133, CD44, PAX6 and reduced expression of differentiation marker. Cancer cells rewire the metabolic pathways to sustain high proliferation. Among the metabolic pathways, cholesterol biosynthetic pathways are mostly dysregulated in cancers including GBM. The spheroids showed high expression of cholesterol biosynthetic gene (HMGCR, DHCR24), and Caveolin1 (Cav1). Targeting cholesterol metabolism by lovastatin resulted in depletion of cellular cholesterol levels, including in plasma membrane. Lowering of cholesterol affected membrane fluidity and hampered Hh signaling by lowering Gli1; consequently, causing downregulation of HMGCR, DHCR24, Cav1, and IDH3A, as well as loss of the stemness factors. However, there are enhanced expression of epigenetic chromatin modification enzymes, including DNMT1 and KDM5A. Tracking into the root cause of silencing of Cav1 gene, we found CAV1 gene promoter is methylated by DNMT1, and H3K4me3 level depleted due to enhanced KDM5A mediated demethylation. CAV1 gene silencing by siRNA validated its role in stemness maintenance and metabolic reprogramming of GSCs. Our findings suggest that, lovastatin has therapeutic potential and illustrates the importance of tumor spheroid models better understanding molecular mechanisms of GBM. Glioblastoma cholesterol biosynthesis stemness Caveolin1 DNMT1 KDM5A Gli1 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Glioblastoma multiform (GBM) is one of the most aggressive, infiltrative, adult brain tumors with minimal survival rate of 12–15 months. Current treatment strategies face clinical challenges due to high metastatic ability, tumor recurrence, multidrug resistance, reprogrammed metabolism, and presence of cancer stem cells [1–5]. Cancer stem cells (CSCs) are a subpopulation of cells within the tumor microenvironment that have the capability of self-renewal, differentiation, and can form tumors when transplanted to a new place in host. CSCs have high potential of initiating tumor growth, invasion, migration, and resistance to treatment strategies [6–10]. Glioblastoma stem cells (GSCs) were identified from GBM and play pivotal role in cancer recurrence and multidrug-resistance. GSCs are characterized by enhanced expression of stemness markers, such as; CD133, CD44, CD15, SOX2, SOX9 [11–13]. As, GSCs are root cause of cancer relapse, development of novel treatment strategies targeting GSCs is urgently required. Cholesterol metabolism and abundance have been associated with cancer progression, maintenance of stemness and considered as novel hallmark of various cancers including GBM. Key enzymes of cholesterol biosynthetic pathway (including SREBP-1, HMGCR) are upregulated and promote GBM metastasis [13–19]. Different cholesterol lowering drugs such as; lovastatin (HMGCR inhibitor) is used as current therapeutics to destroy cancer cells, but the underlying molecular mechanism remains unclear. Caveolin1 (Cav1) is an integral component of caveolae, plays significant role in maintaining cholesterol homeostasis, cholesterol transport, cholesterol signal transduction, and cholesterol metabolism [20–23]. Recent studies have showed the involvement of Cav1 in maintenance of CSCs, promotion of self-renewal and stemness marker expression, and resistance to chemotherapeutic agents [24–27]. Despite the emerging evidences suggesting the role of Cav1 in CSCs maintenance, the detailed molecular mechanism of its role in GSCs remains obscure. Epigenetic mechanisms like DNA methylation and histone modifications play crucial role in stem cell biology and epigenetic alterations may transform normal stem cell to cancer stem cells [28]. Mainly DNA methylation is associated with gene silencing, when placed within CpG islands, by inhibiting binding of transcription factors to DNA and histone modifications may either silence or activate genes depending on the type of modification and position where it is deposited [29–30]. Among histone modifiers, KDM5A catalyse the demethylation of methylated lysine 4 of histone 3 (H3K4me3) and is associated with gene repression [31]. Aberrant DNA methylation acts as drivers of CSC formation and plays crucial role in maintaining undifferentiated state of CSCs [32–33]. Several metabolic intermediates of lipid metabolism serve as co-factor for various chromatin modifiers and thus regulate histone modifications as well as DNA methylation [34]. Reprogrammed cholesterol metabolism is linked with altered DNA methylation and potentiates alteration of epigenomic landscape [35]. Thus, understanding the molecular cues regulating crosstalk between cholesterol biosynthesis and epigenetic modifications, may provide mechanistic insights into maintenance of GBM stemness. Through this study we have showed that targeting cholesterol metabolism by lovastatin affects the expression Cav1 by histone modification and DNA methylation and hampers GBM stemness. Aberrant Hedgehog (Hh) signaling is associated with tumorigenesis and maintenance of CSCs [36–37]. Cholesterol is essential for Hh signaling and cholesterol depletion hampers Hh signaling [38]. In this study we have shown that cholesterol depletion affects Hh signaling and regulates the expression of epigenetic modifiers KDM5A and DNMT1. Collectively this study shows that high cholesterol and Cav1 maintains GSCs. Reduction of cholesterol affects self-renewal properties of GSCs by downregulation of Cav1. The molecular mechanism of Cav1 downregulation is mediated by the upregulation of KDM5A and DNMT1. Additionally, this study shows that cholesterol depletion hampers Hh signaling and critically addresses the regulatory role of Hh signaling on KDM5A and DNMT1. This study links cholesterol metabolism to epigenomic changes in glioma spheroids. Materials and methods Cell culture conditions U87MG and Ln229 cells were cultured in DMEM media, with 10% FBS (Gibco − 10270106) and 1% anti-anti (Gibco − 15240-062) in a humidified incubator at 37°C and 5% CO 2 . Upon attaining 90% confluence, cells were trypsinized, centrifuged and washed with PBS, and re-suspended in complete media. After counting cells using hemacytometer, the concentration of cells was adjusted to 2.5*10 6 cells/ml and used to prepare the 3D spheroids as described below. Hanging Drop Cell Culture Protocol for Generation of 3D Spheroids A 100mm tissue culture dish was used to make spheroids. The lid of the dish was inverted and used as the base to deposit 10uL drops of suspended cells prepared above. PBS was added to the bottom of the dish to act as a hydration chamber. The lid with drops of cells was inverted onto the PBS-filled chamber and incubated at 37°C for 7 days, to allow formation of spheroids. The hanging drop method for spheroid generation was acquired from [39]. Drug treatments and MTT assay Cells were treated with HMGCR inhibitor Lovastatin (Sigma-PHR1285) and Hedgehog pathway inhibitor Erismodegib (further used as Erismo) for 48hrs. Cell viability changes following drug treatments were determined by measuring absorbance off MTT (Himedia-TC191) in living cells. In brief, 24 hrs prior to the drug administration, 10 3 to 3.5*10 3 cells were seeded into a 96-well plate, followed by replacing the normal media with drug dissolved media at required dilutions. The plate was then replaced into the incubator for 24hrs for the drug to be effective, followed by addition of MTT media, which was incubated for another 6hrs followed by DMSO (Himedia – AS121) mediated dissolution of the formazan crystals. A colorimetric analysis of the optical density at 570nm gave us the percentage of viable cells following treatment with different concentrations of a particular drug [40]. The percentage of cell viability was calculated as follows: % Viability = 100 * mean OD (drug)/mean OD (control) siRNA transfections and plasmid overexpression In U87MG spheroids, transfection was attained using lipofectamine 3000 (Invitrogen L3000-15) following manufacturer’s instructions. Caveolin siRNA (Santa cruz) (5’-CAUCUACAAGCCCAACAACTT-3’ (sense), 5’-GUUGUUGGGCUUGUAGAUGTT-3’ (antisense) was used for 48hrs. A negative control siRNA was used to determine the baseline changes induced by siRNA transfections. In U87MG spheroids overexpression (OE) was performed for 48 hours. Transfection was attained using lipofectamine 3000 (Invitrogen L3000-15) following manufacturer’s instructions [41]. Plasmid concentration varied from 6 well to 60mm plate and we used 5 or 10 µg respectively to induce KDM5A and DNMT1 overexpression. 10µg of plasmid concentration was used to overexpress. The pcDNA triple epitope SFB-tagged-RBP2 (KDM5A) overexpression construct was borrowed from Dr. Shweta Tyagi. The pcDNA3/Myc-DNMT1 overexpression plasmid was procured from Addgene (plasmid: #36939 pcDNA3/Myc-DNMT1). RNA isolation and quantitative real time PCR RNA isolation was performed by using TRIzol (Thermo − 15596018) method, using isopropanol (himedia-MB063) for RNA precipitation and 70% alcohol (Himedia-MB228) to wash off excess salts and contaminants, and the RNA was dissolved in DEPC water. Reverse transcriptase reaction with 1ug RNA was setup as per manufacturer’s instructions (Genesure – PGK163A) i.e., incubation at 42°C for 60min and 70°C for 5 min using a 20µL reaction mixture. Using this cDNA (1 µg) as template, and gene specific primers (300nM) respective to different physiological processes, RT-PCR was performed using SYBR-green technology (Thermo – A25742) with the following cycling conditions 50.0°C for 1:00; 96.0°C for 6:00 and [96.0°C for 0:10; 55.0°C for 0:30; 73.0°C for 1:00] for 40 cycles. The data was analysed according to Livak’s method (ddCT calculation) using either GAPDH or B-actin for normalization as described in [30]. For detection of transcript level expression, the following primers were designed and used: OCT4: FP-AGCAAAACCCGGAGGAGT: RP-CCACATCGGCCTGTGTATATC SOX2: FP-GGAAATGGAGGGGTGCAAAAGAGG: RP-TTGCGTGAGTGTGGATGGGATTGGTG NANOG: FP-TCCTCCTCTTCCTCTATACTAAC: RP-CCCACAATCACAGGCATAG KLF4: FP-CAGGGACTGTCACCCTGC: RP-GGCATGAGCTCTTGGTAATGG CD133: FP- ACACTACCAAGGACAAGGCG: RP- TCTCCAACGCCTCTTTGGTC CD44: FP- ACGGAAGAAACAGCTACCCAG: RP- TGTCCCTGTTGTCGAATGGG PAX6: FP- GAGAAGTGAGGAGTGGCTC: RP- GGATTGACTGTCTCCGACTT S100B: FP- GAAATCCGAACTGAAGGAGC: RP- CGTCTCCATCATTGTCCAGT PFKFB3: FP-AAAAGCCTCGCATCAACAGC: RP-TCCGGGAGCCTTTCATGTTT IDH3A: FP-CGCGTGGATCTCTAAGGTCT: RP-GGGCCAATACCATCTCCTGG G6PD: FP- TAGGCTGGAACCGCATCATC: RP-TGCGGTAGATCTGGTCCTCA HMGCR: FP- AGCTGTCATTCCAGCCAAGG: RP- CCATGGCAGAGCCCACTAAA DHCR24: FP- GACCTCCATTGGCTGGACTC: RP- GGCCGTACTTGTGGGATGAT CAV1: FP- ACCCACTCTTTGAAGCTGTTG: RP- GAACTTGAAATTGGCACCAGG Western blotting Spheroids were collected and whole cell lysate was prepared by RIPA lysis buffer (sigma –R0278-50ML), subjected to centrifugation at 10000 RPM for 15 minutes at 4°C, concentration was assessed by Bradford assay and immunoblotting was performed by following the protocol adapted from [42] In brief, the proteins were electrophoresed on 8–15% SDS-PAGE gels depending on target proteins analysed, resolved, and transferred to nitrocellulose membrane (Axiva – 160300RI), blocked with 5% skim milk for an hour. All primary antibodies were prepared in 1% BSA (Himedia-MB083) in PBST and the blots were probed with primary antibodies at 4 o C overnight. Following three washes with PBST, the blots were incubated with either anti-rabbit (Invitrogen-65-6120) or anti-mouse (Santa Cruz – SC516102) secondary antibody for an hour. The blots were then washed thrice using PBST, visualized using ECL chemiluminescence detection system (Thermo- 34580) and digitally captured using Bio-Rad Chemidoc instrument (ChemiDoc MP). Each experiment was performed in triplicate. The primary antibodies used in this study are: PFK-1 (G-11): sc-166722; IDH3A (A-10): sc-398021; G6PD (sc-373886); CD133 (NBP2-44247); CD44(NBP1-47386); PAX6 (DSHB); S100β (sc-393919); HMGCR (sc-271595); DHCR24 (sc-398938); CAVEOLIN-1 (sc-894); p53 (ABclonal- A0263); p21 (ABclonal- A1483), DNMT1 (ab13537), β-actin (abcam-ab8227), KDM5A (ab70892), and Gli-1 (ABclonal-A14675). Immunofluorescence Spheroids were cultured and treated as mentioned above, followed by fixation using 100% methanol for 5 minutes, permeabilized with PBST on ice for 10 minutes and blocked using 1% BSA in PBST for 1hr. The cells were incubated with primary antibodies - overnight at 4 o C in a humid chamber. Following 3 washes with PBS, the cells were incubated with Alexa488 (anti-rabbit-ab ab150077) Alexa647 (anti-mouse – ab150119), washed thrice and images were acquired using Leica microsystems. FACS assay Tumor spheres were collected in tubes and washed with ice cold PBS. Spheres were trypsinized and dissociated into single cells. These single cells were fixed using formaldehyde and permeabilized using 100% methanol. Fixed cells were washed by centrifugation with PBS. After washing cells were incubated with CD44 and CD133 primary antibodies at 4℃ overnight. Primary antibodies were removed and washed by centrifugation. After washing fluorescent tagged secondary antibodies (Alexa 448-anti rabbit antibody, and Alexa 647-anti mice antibody) were added and incubated at room temperature for 1hr. Cells were washed and dissolved in 500µl PBS and cell population distribution was measured by BD Accuri. Total Cholesterol estimation Total cholesterol from cells were extracted according to the protocol by Bittame et.al [43]. The relative cholesterol concentration in lovastatin, and Cav1 KD condition were measured by ZAK’s method [44]. Cholesterol standard graph was plotted by diluting various concentrations of cholesterol stock (ranging from 20–140µg) and OD was taken at 560nm. Equal volume (500µl) of cholesterol sample from different treatment conditions were taken in separate test tubes and in blank no cholesterol was added. The volume in all test tubes was made up to 5ml by addition of 0.5% ferric chloride acetic acid reagent. 3mL of conc. Sulphuric acid was added to each test tubes, mixed well and kept for 15mins at room temperature. Then OD was taken at 560nm. OD of all the tubes were normalized by subtracting OD of blank. The normalized OD values were plotted on the cholesterol standard graph and the concentration was measured against each OD. Then the cholesterol concentrations were normalized with protein concentrations. Methylation specific (MS)-PCR Genomic DNA was isolated from each treated cells by phenol chloroform method. Two micrograms of genomic DNA were bisulfite converted by EPIGENTEK Methylamp DNA Modification Kit (P-1001-2) according to the manufacturer’s instructions. Bisulfite-treated DNA was then used as template in PCR reactions for PCR analysis. For identifying the promotor following methylation specific primers were used. CAV1: FP(Methylated)-TGTTCGGGTGTGGAAATTC RP(Methylated)-ATCCTAAAACTCACCTACG FP(Unmethylated)-TTGTTTGGGTGTGGAAATTTTG RP(Unmethylated)-ATCCTAAACTCAATCTCACCTACA Chromatin immunoprecipitation Chromatin immunoprecipitation was performed after respective treatment in U87MG spheroid cells by using Imprint Chromatin Immunoprecipitation Kit (Sigma) according to the manufacturer instruction and the protocol standardized in our lab followed by qRT-PCR [31]. ChIP primer for CAV1 is 5’-CAGGATTGTGGATTGTTTCTGC-3’; 5’-GAGTGAGAACGTTTCTCCCG-3’. H3K4me3 (Invitrogen MA5-11199), IgG(M8695-Sigma) were used for ChIP assay. Statistical analysis The results are presented as mean ± SD. Each value represents mean calculated from 3 independent experiments and significant differences among experiments were assessed using Prism5. When 2 groups were tested - student’s ‘t’ test was employed and when multiple classes of data were analysed- either a one-way or two-way ANOVA were employed to test the significance. Results Glioblastoma spheroids show higher stemness properties As non-adherent conditions enhance self-renewal properties, spheroid cultures were generated using hanging drop method to mimic glioblastoma stem cells (GSCs). After 7 days, the spheroids formed (Fig. 1A) were assessed for stemness by quantifying pluripotency and surface marker expression in comparison to the monolayer cells. FACS assay results showed increase in CD133 + CD44 + double positive population from 0.5% (in monolayer) to 11.7% (in spheroids) (Fig. 1B). Thus, this method was used for generation of glioblastoma cell-line derived CSCs. RT-PCR was performed in both U87MG and Ln229 derived spheroids. An increase in OCT4, SOX2, NANOG and KLF4 as well as the universal stemness markers CD133, CD44 along with glial progenitor marker PAX6 was noted in spheroids derived from both cell lines (Fig. 1C, 1D). Further, CD133, CD44 and PAX6 were also upregulated at protein levels in U87MG Ln229 (Fig. 1E). The glial differentiation marker S100B was also quantified and a decrease in expression in spheroids when compared to monolayer was noted (Fig. 1E). Immunofluorescence staining also showed that the spheres developed by us are positive for CD133, CD44, PAX6, Cav1 but, negative for S100B in U87MG cells (Fig. 1F). Metabolic rewiring in GBM spheroids in comparison to monolayer culture: high expression of cholesterol biosynthesis gene, Cav1, and IDH3A support higher GSCs population in spheroids Total cholesterol content was increased in spheres compared to monolayer (Fig. 2A). The expression of HMGCR (the rate limiting enzyme of mevalonate pathway), DHCR24 (catalyzes the ultimate step of cholesterol synthesis) and cholesterol carrier-Cav1 was estimated in spheroids. In comparison to monolayer, GSC spheroids displayed enhanced expression of cholesterol biosynthetic genes and Cav1 at mRNA and protein level in U87MG and Ln229 (Fig. 2B-C). Confocal microscopy results also showed an increase in Cav1 in U87 spheroids compared to monolayer cells (Fig. 1F). As CSCs show dynamic plasticity to the environmental conditions, to understand the metabolic dependence of spheroids cultured by hanging drop method, we assessed the glycolytic marker PFK1, TCA protein IDH3A and PPP marker G6PD. From the RT-PCR and protein blots, it is apparent that PFK1 and G6PD were reduced in GSCs, but IDH3A was upregulated in U87MG and Ln229 (Fig. 2D-E) cell lines at both mRNA and protein level. Inhibition of cholesterol synthesis effectively reduces stemness and increased differentiation in U87MG spheroids As cholesterol synthesis and Cav1 were increased in spheroids, we targeted cellular cholesterol availability by inhibition of synthesis by lovastatin. Following cell viability test (Fig. 3A), a concentration of 2.5uM lovastatin was chosen for further experiments. It was seen that the relative cholesterol concentration was highly reduced in lovastatin (Fig. 3B). Lovastatin treatment was found to hinder cholesterol regulatory proteins (HMGCR and DHCR24) much effectively and Cav1 expression was reduced (Fig. 3C, 3D). In order to test whether lovastatin treatment affected stemness, we analysed stemness markers - CD133, CD44, PAX6 and differentiation marker S100B. RT-PCR and Western blot data depicts that lovastatin treatment inhibited stemness and promoted differentiation (Fig. 3E, 3F). Further, we tested if cholesterol inhibition altered IDH3A levels, and found that lovastatin treatments reduced IDH3A (Fig. 3G, 3H). Immunofluorescence data also showed lovastatin treatment reduced stem cell markers CD133, CD44 (Fig. 3I). Taken together, lovastatin inhibited Cav1 expression, reduced stemness in GSC and promoted its differentiation and hampered the metabolic adaptation of GSC. Cav1 knockdown reduces stemness in U87MG spheroids In line with inhibition of cholesterol, we determined if knockdown of Cav1 could inhibit the formation of spheroids. We utilized three different si-RNA concentrations, of which- 70nM si-RNA targeted towards Cav1, we could attain 90% knockdown of target protein compared to si-Control treated spheroids (Fig. 4A-B). Thus, 70nM of si-RNA was used for downstream experiments. As cholesterol and caveolin are interrelated and they regulate each other, we checked relative cholesterol content after Cav1 si-RNA transfection. Surprisingly, we found that the relative cholesterol content in Cav1 knockdown condition is effectively reduced (Fig. 4C). mRNA and protein analysis of siRNA treated cell lysates revealed a decrease in stemness markers CD133, CD44 and PAX6 (Fig. 4D-E). As IDH3A was increased in spheroids compared the GBM monolayers, we tested if Cav1 knockdown had any effect on its expression. From RT-PCR and western blots, we found that IDH3A expression was also reduced following Cav1 knockdown (Fig. 4F-G). Immunofluorescence results also showed Cav1 knockdown reduced expression of stem cell markers CD133 and CD44 (Fig. 4H). Cholesterol depletion upregulates KDM5A and DNMT1 in GSCs Since above results showed that high expression of Cav1 in glioma spheroids maintains GSCs, we investigated the mechanism of Cav1 expression in glioma spheroids. As Cav 1 is high in spheroids, we expected some epigenetic repressors to be down regulated. As expected, it was observed that two epigenetic repressors KDM5A (Fig. 5A) and DNMT1 (Fig. 5B) were downregulated in spheroids as compared to monolayers in both U87MG and Ln229 cell lines. As both KDM5A and DNMT1 were downregulated in spheroids, we individually overexpressed KDM5A and DNMT1 in U87 spheroids and checked the expression of Cav1. KDM5A was overexpressed (Fig. 5C) and the expression of Cav1 was significantly decreased in KDM5A OE condition (Fig. 5D). Similarly, DNMT1 OE also downregulated Cav1 expression (Fig. 5E-F). Since lovastatin treatment downregulates Cav1, we checked the expression of KDM5A and DNMT1 in lovastatin treatment in U87MG spheroids. Both KDM5A (Fig. 5G) and DNMT1 (Fig. 5H) expression were increased post lovastatin treatment. To investigate further the mechanism of Cav1 expression by lovastatin treatment, we performed ChIP to check the role of KDM5A and MS-PCR to check the role of DNMT1 in lovastatin treatment. ChIP results revealed that there was decrease in H3K4me3 mark in Cav1 promotor after lovastatin treatment (Fig. 5I). The reduction in H3K4me3 active mark is due to the increased occupancy of KDM5A in Cav1 promoter (Fig. 5I). MS-PCR results also showed that lovastatin treatment increased promotor methylation of Cav1 gene (Fig. 5J). Collectively, lovastatin treatment reduced Cav1 expression due to KDM5A mediated H3K4me3 demethylation and DNMT1 mediated promotor methylation of Cav1 gene. Tracing the mechanisms: how lowering of cholesterol enhances the expression of DNMT1 and KDM5A: To investigate how cholesterol depletion enhances the expression of KDM5A and DNMT1, we short if there could be involvement of Hh signaling. Since, Hh signaling largely depends on cholesterol abundance in plasma membrane. Along this line, firstly, we checked the expression of Hh signaling molecules SMO and Gli1 in spheroids. It was found that SMO and Gli1 expressions are increased at mRNA level in U87MG spheroids in comparison to monolayer (Fig. 6A). Gli1 protein expression in U87MG spheroids were also very high in comparison to monolayer cells (Fig. 6B). Then, we treated U87MG spheroids with lovastatin and traced that, there was reduction in transcripts of Gli1 and SMO (Fig. 6C) and reduced protein expression of Gli1 (Fig. 6D). As cholesterol depletion hampered Hh signaling, we hypothesized that Hh signaling might regulate the expression of KDM5A and DNMT1. Accordingly, we inhibited Hh signaling using a small molecule. Erismodegib (Erismo) treatment in U87MG spheroids. Following MTT assay result (Fig. 6E), we treated U87MG spheroids with 2.5µM of Erismo. There was reduction of Gli1 and SMO mRNA and Gli1 protein level in Erismo treatment (Fig. 6F-G). Then, we checked the expression of KDM5A and DNMT1 in Erismo treatment. As expected, we found Hh signaling inhibition by Erismo enhanced the expression of KDM5A and DNMT1 (Fig. 6H). Thus, it was confirmed that cholesterol depletion hampered Hh signaling and upregulated expression of KDM5A and DNMT1. Further the effect of Hh inhibition on downstream genes was evaluated. We found that the expression of Cav1 is downregulated in Erismo treatment in U87MG spheroids (Fig. 6I), which is in accordance with the upregulation of KDM5A and DNMT1 in Erismo treatment. Similarly, the expression of stemness markers CD133, CD44, Pax6 and the expression of TCA cycle gene IDH3A were downregulated in Erismo treatment (Fig. 6I). Discussion Glioblastoma stem cells (GSCs) have high proliferative and self-renewal capabilities and are the root cause of cancer recurrence and therapeutic resistance. Despite advances in GBM treatment, presence of GSCs pose a potential hindrance to current treatment strategies. So, understating the detailed molecular mechanism of GSCs proliferation and maintenance is essential to combat GMB. In this study, we used spheroid culture model that enriches for GSCs, validated by the significant upregulation of pluripotency and stemness markers (OCT4, SOX2, CD133, CD44, and PAX6) and the downregulation of the differentiation marker S100β. Using this model, we have uncovered a critical and previously uncharacterized signaling cascade that links cholesterol metabolism, Hedgehog (Hh) signaling, and epigenetic regulation in maintenance of GSCs. The spheroids developed by us showed distinct metabolic rewiring, characterized by high dependency on de novo cholesterol biosynthesis. GSC spheroid showed high expression of cholesterol biosynthesis genes like; HMGCR and DHCR24 and led to increased total cholesterol content. This metabolic shift is maintained by monitoring cholesterol localization inside a cell, and caveloin-1 possesses high binding affinity to cholesterol and thus partly contributes to the maintenance of cholesterol levels in a cell. Cholesterol metabolism and Cav1 plays significant role in maintenance of CSCs, including GBM. Studies have shown that targeting CSCs can be used as novel therapeutic approach in cancers [45]. Here we found that Cav1 is upregulated in GSCs, suggesting the role of Cav1 in GSCs maintenance. Some evidence suggests that slow-cycling quiescent CSCs originated from GBM tumors are less glycolytic and mainly rely on oxidative phosphorylation thereby show high ATP levels [46–48]. Further, to understand the metabolic adaptability of GSCs cultured by hanging drop method, we assessed PFK1, IDH3A and G6PD as markers of glycolysis, TCA cycle and PPP respectively. As only IDH3A was increased in spheroids, we concluded that GSCs derived energy by TCA cycle mediated OXPHOS and ATP generation. This suggests GSCs are not merely glycolytic but dependent on cholesterol metabolism and mitochondrial respiration to support their stem-like properties. The metabolic dependency towards cholesterol biosynthesis was targeted by reduction of cholesterol content using an inhibitor of cholesterol synthesis pathway. As lovastatin is a cholesterol lowering and a pharmacological modulator of Cav1 [49–50] and treatment with lovastatin inhibited mammosphere formation due to reduced Sox2 promoter transactivation [51], we challenged GSCs for depletion of both cholesterol and Cav1 protein. Treatment with lovastatin not only depleted cellular cholesterol but also triggered a collapse of the GSC phenotype. We observed a marked reduction in Cav1, a loss of stemness markers (CD133, CD44, PAX6), and an increase in the differentiation marker S100β. As cholesterol inhibition also reduced Cav1 levels, we further tested if this was responsible for altered stemness and metabolic inhibition in GSCs. Cav1 knockdown via siRNA phenocopied these effects, independently confirming Cav1 as a critical mediator of GSC stemness. Earlier studies have shown reduced invasiveness and colony formation when Cav1- knockdown was performed in U87MG cells [52]. Stabilization of Cav1 protein by Deubiquitination promotes stemness and drug resistance and it also promotes aggressiveness in GBM cells [53–54]. Mechanistically, we attempted to understand how this high-Cav1, cholesterol-rich state is maintained. We discovered a novel epigenetic basis for the regulation of Cav1 in GSCs. We found that GSCs maintain a state of distinct epigenetic landscape characterized by marked reduction of the histone H3K4 demethylase KDM5A and the DNA methyltransferase DNMT1. This downregulation of epigenetic repressors is required for GSC maintenance, given that forced overexpression of either KDM5A or DNMT1 was sufficient to markedly decrease Cav1 expression. This epigenetic state is dynamically regulated by cholesterol availability. Cholesterol depletion via lovastatin altered the epigenetic landscape, leading to a robust increase in both KDM5A and DNMT1 expression. This upregulation of epigenetic repressors had a direct, mechanistic consequence on Cav1 expression. ChIP-qPCR revealed that lovastatin treatment increased KDM5A occupancy at the Cav1 promoter, leading to a reduction in the active H3K4me3 mark. Concurrently, MS-PCR showed increased Cav1 promoter methylation. Thus, GSCs actively suppress KDM5A and DNMT1 to keep the Cav1 gene \"on\"; cholesterol inhibition breaks this cycle, restoring these repressors which then silence Cav1 through coordinated histone and DNA modification. Finally, we identified the key upstream regulator that links cholesterol to this epigenetic switch. The Hedgehog (Hh) signaling pathway was a prime regulator because of its dependency on cholesterol for activation of signaling pathway. We verified that Hh signaling (Gli1, SMO) is highly active in GSC spheroids but is significantly attenuated by cholesterol depletion with lovastatin. This places cholesterol as a critical fuel for Hh pathway activity in GSCs. Most importantly, direct pharmacological inhibition of the Hh pathway using Erismodegib perfectly mimicked the effects of lovastatin. Hh inhibition upregulated KDM5A and DNMT1, which in turn suppressed Cav1, reduced stemness markers, and decreased IDH3A. Conclusion Collectively, high cholesterol fuels Hh pathway in glioma spheroids. Hyperactivation of Hh pathway led to downregulation of KDM5A and DNMT1. Decreased expressed of KDM5A and DNMT1 failed to supress Cav1. High expression of Cav1 in glioma spheroids maintains stemness properties. Our study establishes the cholesterol-KDM5A/DNMT1-Cav1 axis in regulating stemness properties of GBM cells. Our findings strongly suggest that therapeutic strategies aimed at breaking this loop, such as cholesterol-lowering statins or Hh pathway inhibitors, could function as potent epigenetic and differentiation-inducing therapies, offering a promising new avenue to target the resilient GSC population in glioblastoma. Abbreviations GSCs -Glioma stem like cells CSCs -Cancer stem cells GBM -Glioblastoma multiform KMD5A - lysine demethylase 5A DNMT1 - DNA methyl transferase H3K4me3 - Histone 3 lysine 4 trimethylation HMGCR -3-hydroxy-3-methylglutaryl-CoA reductase DHCR24 - 24-dehydrocholesterol reductase IDH3A - Isocitrate dehydrogenase 3alpha PFK-1 - Phosphofructokinase-1 G6PD -Glucose-6-phosphate dehydrogenase Declarations Conflict of Interest: None Credit author statement SKP conceived the project, TB Conceptualize, Methodology, Software; TB, SM, JM & KR collected & curated data and wrote the manuscript. SC, PN, AR, Niharika, PM & BP information literature survey and curation of data. PD visualize the overall project, SKP edited the draft manuscript. Acknowledgement: TB, JM, SC, PN, PM are thankful to CSIR-UGC for fellowships, Govt. of India. R. Kirtana received and BP receives fellowship from CSIR, Govt. of India. SM & AR are thankful to NIT-Rourkela for Institute fellowship. 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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-8095695\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":550240389,\"identity\":\"09bb0369-e767-49cc-8ceb-0a3969b4cf7a\",\"order_by\":0,\"name\":\"Tirthankar Baral\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"National Institute of Technology Rourkela\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Tirthankar\",\"middleName\":\"\",\"lastName\":\"Baral\",\"suffix\":\"\"},{\"id\":550240390,\"identity\":\"e126ee9a-f40b-4571-90ae-42e1ff4f8e77\",\"order_by\":1,\"name\":\"Kirtana 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17:25:56\",\"extension\":\"html\",\"order_by\":22,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":98049,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"earlyproof.html\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8095695/v1/93e6903cc5be45780b74f02c.html\"},{\"id\":96915267,\"identity\":\"7988d375-1a46-4ce7-b648-0bd32007143a\",\"added_by\":\"auto\",\"created_at\":\"2025-11-27 14:07:03\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":801757,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eGlioblastoma sphere formation and characterization of stem cell properties:\\u003c/strong\\u003e Sphere formation from monolayer glioblastoma cell line U87MG by hanging drop (\\u003cstrong\\u003eA\\u003c/strong\\u003e). Stem cell population of spheres showing CD133 and CD44 marker expression were evaluated by FACS (\\u003cstrong\\u003eB\\u003c/strong\\u003e). Expression of pluripotency; Oct4, Sox2, Nanog, Klf4 \\u003cstrong\\u003e(C)\\u003c/strong\\u003e and stemness markers; CD133, CD44, PAX6 along with differentiation marker (S100B) \\u003cstrong\\u003e(D)\\u003c/strong\\u003e in glioblastoma spheroid compared to the monolayer cells by qRT-PCR in U87MG and Ln229 (C-D)\\u003cstrong\\u003e. \\u003c/strong\\u003eWestern blotting was performed to check protein level expression of stem cell markers CD133, CD44, PAX6, and differentiation marker S100β in U87MG and Ln229 \\u003cstrong\\u003e(E)\\u003c/strong\\u003e. Enrichment of stemness characterized by confocal microscopy. Stemness marker CD133 (green in colour) and differentiation marker S100B (red in colour) expression was assessed in spheroid (U87MG cell line)\\u003cstrong\\u003e (F)\\u003c/strong\\u003e. CD44 and Cav1 expression was assessed in spheres \\u003cstrong\\u003e(F\\u003c/strong\\u003e).\\u003cstrong\\u003e \\u003c/strong\\u003eAnother glial stem cell marker PAX6 expression was also checked in confocal microscopy in spheroid culture (U87MG cell line). Three or more independent experiments were performed for confirmation of the results (\\u003cstrong\\u003eF\\u003c/strong\\u003e). Data are representative of three independent experiments, values are expressed as the mean ± SD, and results are statistically significant when *p ≤ 0.05, **p ≤ 0.01 and ***p ≤ 0.001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8095695/v1/adddc2b286f07b540c74e7dc.png\"},{\"id\":96914178,\"identity\":\"320b73c1-bed6-4cff-871f-179cf9456eb7\",\"added_by\":\"auto\",\"created_at\":\"2025-11-27 14:05:33\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1033644,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eMetabolic rewiring of GBM spheroids:\\u003c/strong\\u003e Total cholesterol of monolayer and spheroid cells were estimated \\u003cstrong\\u003e(A). \\u003c/strong\\u003eCaveolin1 and key enzymes in cholesterol biosynthesis i.e., HMGCR and DHCR24 expression was analysed by qRT-PCR and western blotting in both cell line, U87MG and Ln229 \\u003cstrong\\u003e(B-C) \\u003c/strong\\u003eGlycolytic enzyme phosphofructokinase 1 (PFK1), TCA cycle enzyme Isocitrate dehydrogenases 3A (IDH3A) and pentose phosphate pathway enzyme i.e., glucose-6-phosphate dehydrogenase (G6PD) expressions were analysed by qRT-PCR and western blotting in both U87MG and Ln229 \\u003cstrong\\u003e(D-E)\\u003c/strong\\u003e cell line. Data are representative of three independent experiments, values are expressed as the mean ± SD, and results are statistically significant when *p ≤ 0.05, **p ≤ 0.01 and ***p ≤ 0.001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8095695/v1/11c28d78c8838445e10e8721.png\"},{\"id\":96753688,\"identity\":\"c18a97b0-d227-4bfd-9c36-acf1d9fcbd06\",\"added_by\":\"auto\",\"created_at\":\"2025-11-25 17:25:55\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":473510,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eLovastatin reduces GBM stemness:\\u003c/strong\\u003eLovastatin was used to deplete cholesterol. The graph represents cell viability assay in different concentration - The sub-lethal concentration of 2.5μM of lovastatin is used for downstream experiments (\\u003cstrong\\u003eA\\u003c/strong\\u003e). Total cholesterol content in lovastatin treatment was estimated \\u003cstrong\\u003e(B). \\u003c/strong\\u003eEffects of lovastatin on cholesterol biosynthesis genes and caveolin1 expression were analysed by qRT-PCR \\u003cstrong\\u003e(C)\\u003c/strong\\u003e and western blotting \\u003cstrong\\u003e(D)\\u003c/strong\\u003e. Further, effects on stemness markers and differentiation markers were also analysed by qRT-PCR (\\u003cstrong\\u003eE\\u003c/strong\\u003e) and western blotting (\\u003cstrong\\u003eF\\u003c/strong\\u003e). IDH3A expression was checked in lovastatin treatment in U87MG spheroid cells in transcription (\\u003cstrong\\u003eG\\u003c/strong\\u003e) and protein level (\\u003cstrong\\u003eH\\u003c/strong\\u003e). For further confirmation, confocal microscopy of the spheroid was performed in lovastatin treatment conditions (\\u003cstrong\\u003eI\\u003c/strong\\u003e). Data are representative of three independent experiments, values are expressed as the mean ± SD, and results are statistically significant when *p ≤ 0.05, **p ≤ 0.01 and ***p ≤ 0.001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8095695/v1/1f1a04ef946562dc2dcfeecf.png\"},{\"id\":96915318,\"identity\":\"6cca3545-dc74-4cda-92e7-8b55c7ded520\",\"added_by\":\"auto\",\"created_at\":\"2025-11-27 14:07:07\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":512427,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eCav1 knockdown reduces stemness in U87MG spheroids: \\u003c/strong\\u003eCav1 knockdown efficiency was checked in U87MG spheroid cells by qRT-PCR \\u003cstrong\\u003e(A)\\u003c/strong\\u003e and western blotting \\u003cstrong\\u003e(B\\u003c/strong\\u003e) using siRNA treatment. Cholesterol content was also checked after CAV-1 si-RNA transfection \\u003cstrong\\u003e(C).\\u003c/strong\\u003eUsing Cav1 siRNA, stemness markers expression was analysed in spheroids by qRT-PCR (\\u003cstrong\\u003eD\\u003c/strong\\u003e), western blotting (\\u003cstrong\\u003eE\\u003c/strong\\u003e). Further Cav1KD effects on IDH3A was analysed by qRT-PCR \\u003cstrong\\u003e(F)\\u003c/strong\\u003e and western blotting \\u003cstrong\\u003e(G)\\u003c/strong\\u003e. CD133, CD44 expression were checked in Cav1-KD condition \\u003cstrong\\u003e(H)\\u003c/strong\\u003e. Data are representative of three independent experiments, values are expressed as the mean ± SD, and results are statistically significant when *p ≤ 0.05, **p ≤ 0.01 and ***p ≤ 0.001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8095695/v1/265945e6fb7332b5f9dff3cc.png\"},{\"id\":96753695,\"identity\":\"33365fc0-1ffe-4d48-9a53-a69d856d3928\",\"added_by\":\"auto\",\"created_at\":\"2025-11-25 17:25:55\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1012937,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eCholesterol biosynthesis inhibition upregulates KDM5A and DNMT1 in GSCs:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWestern blotting was performed to check the expression of KDM5A (A) and DNMT1 (B) in spheroids compared to monolayer in U87MG and Ln229 cell lines. KDM5A was overexpressed in U87MG spheroids by plasmid transfection (C). Cav1 expression was checked in KDM5A OE condition in U87MG spheroids (D). DNMT1 was overexpressed in U87MG spheroids by plasmid transfection (E). Cav1 expression was checked in DNMT1 OE condition in U87MG spheroids (F). Protein expression of KDM5A (G) and DNMT1 (H) was checked by western blotting after lovastatin treatment. ChIP was performed in lovastatin treatment to analyse the enrichment of H3K4me3 and occupancy of KDM5A (I). MS-PCR was performed to check the methylation status of Cav1 promotor in lovastatin treatment (J). Data are representative of three independent experiments, values are expressed as the mean ± SD, and results are statistically significant when *p ≤ 0.05, **p ≤ 0.01 and ***p ≤ 0.001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8095695/v1/9fea3010e98f6e2d0520be65.png\"},{\"id\":96916051,\"identity\":\"6688e671-1172-4e2a-8ab4-a42902782ce6\",\"added_by\":\"auto\",\"created_at\":\"2025-11-27 14:07:54\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":902455,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eCholesterol depletion hampers Hh signaling and increases expression of KDM5A and DNMT1: \\u003c/strong\\u003eqRT-PCR was performed to check the m-RNA levels of Gli1 and SMO in spheroid compared to monolayer in U87MG cell line (A). Western blotting was performed to check the expression of Gli1 in U87MG spheroids compared to monolayer (B). Gli1 and SMO m-RNA levels were checked in U87MG spheroids after lovastatin treatment (C). Gli1 protein expression was analysed in U87MG spheroids after lovastatin treatment (D). MTT assay was performed in U87MG after Erismo treatment (E). Transcript levels of Gli1 and SMO were analysed after Erismo treatment in U87MG spheroids (F). Protein expression of Gli1 was checked after Erismo treatment in U87MG spheroids (G). The expression of KDM5A and DNMT1 were checked by western blotting after Erismo treatment (H). Protein expression of Cav1, CD133, CD44, Pax6, IDH3A were checked in Erismo treatment (I). Data are representative of three independent experiments, values are expressed as the mean ± SD, and results are statistically significant when *p ≤ 0.05, **p ≤ 0.01 and ***p ≤ 0.001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage7.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8095695/v1/751162bdbecf7dd1004296a1.png\"},{\"id\":97668299,\"identity\":\"a79c5ee1-a90c-430c-8b50-5ce31bb719f3\",\"added_by\":\"auto\",\"created_at\":\"2025-12-08 09:25:16\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":6112753,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8095695/v1/f162c4a0-6cc6-46d8-a892-bc009ccd7f39.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Lowering of Cholesterol Hampers Glioblastoma Stem Cell Proliferation in Spheroids Through impaired Hh signaling: upregulation of epigenetic chromatin modifiers and down regulation CAV1 and Stem Cell markers\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eGlioblastoma multiform (GBM) is one of the most aggressive, infiltrative, adult brain tumors with minimal survival rate of 12\\u0026ndash;15 months. Current treatment strategies face clinical challenges due to high metastatic ability, tumor recurrence, multidrug resistance, reprogrammed metabolism, and presence of cancer stem cells [1\\u0026ndash;5]. Cancer stem cells (CSCs) are a subpopulation of cells within the tumor microenvironment that have the capability of self-renewal, differentiation, and can form tumors when transplanted to a new place in host. CSCs have high potential of initiating tumor growth, invasion, migration, and resistance to treatment strategies [6\\u0026ndash;10]. Glioblastoma stem cells (GSCs) were identified from GBM and play pivotal role in cancer recurrence and multidrug-resistance. GSCs are characterized by enhanced expression of stemness markers, such as; CD133, CD44, CD15, SOX2, SOX9 [11\\u0026ndash;13]. As, GSCs are root cause of cancer relapse, development of novel treatment strategies targeting GSCs is urgently required.\\u003c/p\\u003e\\u003cp\\u003eCholesterol metabolism and abundance have been associated with cancer progression, maintenance of stemness and considered as novel hallmark of various cancers including GBM. Key enzymes of cholesterol biosynthetic pathway (including SREBP-1, HMGCR) are upregulated and promote GBM metastasis [13\\u0026ndash;19]. Different cholesterol lowering drugs such as; lovastatin (HMGCR inhibitor) is used as current therapeutics to destroy cancer cells, but the underlying molecular mechanism remains unclear. Caveolin1 (Cav1) is an integral component of caveolae, plays significant role in maintaining cholesterol homeostasis, cholesterol transport, cholesterol signal transduction, and cholesterol metabolism [20\\u0026ndash;23]. Recent studies have showed the involvement of Cav1 in maintenance of CSCs, promotion of self-renewal and stemness marker expression, and resistance to chemotherapeutic agents [24\\u0026ndash;27]. Despite the emerging evidences suggesting the role of Cav1 in CSCs maintenance, the detailed molecular mechanism of its role in GSCs remains obscure.\\u003c/p\\u003e\\u003cp\\u003eEpigenetic mechanisms like DNA methylation and histone modifications play crucial role in stem cell biology and epigenetic alterations may transform normal stem cell to cancer stem cells [28]. Mainly DNA methylation is associated with gene silencing, when placed within CpG islands, by inhibiting binding of transcription factors to DNA and histone modifications may either silence or activate genes depending on the type of modification and position where it is deposited [29\\u0026ndash;30]. Among histone modifiers, KDM5A catalyse the demethylation of methylated lysine 4 of histone 3 (H3K4me3) and is associated with gene repression [31]. Aberrant DNA methylation acts as drivers of CSC formation and plays crucial role in maintaining undifferentiated state of CSCs [32\\u0026ndash;33]. Several metabolic intermediates of lipid metabolism serve as co-factor for various chromatin modifiers and thus regulate histone modifications as well as DNA methylation [34]. Reprogrammed cholesterol metabolism is linked with altered DNA methylation and potentiates alteration of epigenomic landscape [35]. Thus, understanding the molecular cues regulating crosstalk between cholesterol biosynthesis and epigenetic modifications, may provide mechanistic insights into maintenance of GBM stemness. Through this study we have showed that targeting cholesterol metabolism by lovastatin affects the expression Cav1 by histone modification and DNA methylation and hampers GBM stemness.\\u003c/p\\u003e\\u003cp\\u003eAberrant Hedgehog (Hh) signaling is associated with tumorigenesis and maintenance of CSCs [36\\u0026ndash;37]. Cholesterol is essential for Hh signaling and cholesterol depletion hampers Hh signaling [38]. In this study we have shown that cholesterol depletion affects Hh signaling and regulates the expression of epigenetic modifiers KDM5A and DNMT1.\\u003c/p\\u003e\\u003cp\\u003eCollectively this study shows that high cholesterol and Cav1 maintains GSCs. Reduction of cholesterol affects self-renewal properties of GSCs by downregulation of Cav1. The molecular mechanism of Cav1 downregulation is mediated by the upregulation of KDM5A and DNMT1. Additionally, this study shows that cholesterol depletion hampers Hh signaling and critically addresses the regulatory role of Hh signaling on KDM5A and DNMT1. This study links cholesterol metabolism to epigenomic changes in glioma spheroids.\\u003c/p\\u003e\"},{\"header\":\"Materials and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eCell culture conditions\\u003c/h2\\u003e\\u003cp\\u003eU87MG and Ln229 cells were cultured in DMEM media, with 10% FBS (Gibco \\u0026minus;\\u0026thinsp;10270106) and 1% anti-anti (Gibco \\u0026minus;\\u0026thinsp;15240-062) in a humidified incubator at 37\\u0026deg;C and 5% CO\\u003csub\\u003e2\\u003c/sub\\u003e. Upon attaining 90% confluence, cells were trypsinized, centrifuged and washed with PBS, and re-suspended in complete media. After counting cells using hemacytometer, the concentration of cells was adjusted to 2.5*10\\u003csup\\u003e6\\u003c/sup\\u003e cells/ml and used to prepare the 3D spheroids as described below.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eHanging Drop Cell Culture Protocol for Generation of 3D Spheroids\\u003c/h3\\u003e\\n\\u003cp\\u003eA 100mm tissue culture dish was used to make spheroids. The lid of the dish was inverted and used as the base to deposit 10uL drops of suspended cells prepared above. PBS was added to the bottom of the dish to act as a hydration chamber. The lid with drops of cells was inverted onto the PBS-filled chamber and incubated at 37\\u0026deg;C for 7 days, to allow formation of spheroids. The hanging drop method for spheroid generation was acquired from [39].\\u003c/p\\u003e\\n\\u003ch3\\u003eDrug treatments and MTT assay\\u003c/h3\\u003e\\n\\u003cp\\u003eCells were treated with HMGCR inhibitor Lovastatin (Sigma-PHR1285) and Hedgehog pathway inhibitor Erismodegib (further used as Erismo) for 48hrs. Cell viability changes following drug treatments were determined by measuring absorbance off MTT (Himedia-TC191) in living cells. In brief, 24 hrs prior to the drug administration, 10\\u003csup\\u003e3\\u003c/sup\\u003e to 3.5*10\\u003csup\\u003e3\\u003c/sup\\u003e cells were seeded into a 96-well plate, followed by replacing the normal media with drug dissolved media at required dilutions. The plate was then replaced into the incubator for 24hrs for the drug to be effective, followed by addition of MTT media, which was incubated for another 6hrs followed by DMSO (Himedia \\u0026ndash; AS121) mediated dissolution of the formazan crystals. A colorimetric analysis of the optical density at 570nm gave us the percentage of viable cells following treatment with different concentrations of a particular drug [40].\\u003c/p\\u003e\\u003cp\\u003eThe percentage of cell viability was calculated as follows:\\u003c/p\\u003e\\u003cp\\u003e% Viability\\u0026thinsp;=\\u0026thinsp;100 * mean OD (drug)/mean OD (control)\\u003c/p\\u003e\\n\\u003ch3\\u003esiRNA transfections and plasmid overexpression\\u003c/h3\\u003e\\n\\u003cp\\u003eIn U87MG spheroids, transfection was attained using lipofectamine 3000 (Invitrogen L3000-15) following manufacturer\\u0026rsquo;s instructions. Caveolin siRNA (Santa cruz) (5\\u0026rsquo;-CAUCUACAAGCCCAACAACTT-3\\u0026rsquo; (sense), 5\\u0026rsquo;-GUUGUUGGGCUUGUAGAUGTT-3\\u0026rsquo; (antisense) was used for 48hrs. A negative control siRNA was used to determine the baseline changes induced by siRNA transfections. In U87MG spheroids overexpression (OE) was performed for 48 hours. Transfection was attained using lipofectamine 3000 (Invitrogen L3000-15) following manufacturer\\u0026rsquo;s instructions [41]. Plasmid concentration varied from 6 well to 60mm plate and we used 5 or 10 \\u0026micro;g respectively to induce KDM5A and DNMT1 overexpression. 10\\u0026micro;g of plasmid concentration was used to overexpress. The pcDNA triple epitope SFB-tagged-RBP2 (KDM5A) overexpression construct was borrowed from Dr. Shweta Tyagi. The pcDNA3/Myc-DNMT1 overexpression plasmid was procured from Addgene (plasmid: #36939 pcDNA3/Myc-DNMT1).\\u003c/p\\u003e\\n\\u003ch3\\u003eRNA isolation and quantitative real time PCR\\u003c/h3\\u003e\\n\\u003cp\\u003eRNA isolation was performed by using TRIzol (Thermo \\u0026minus;\\u0026thinsp;15596018) method, using isopropanol (himedia-MB063) for RNA precipitation and 70% alcohol (Himedia-MB228) to wash off excess salts and contaminants, and the RNA was dissolved in DEPC water. Reverse transcriptase reaction with 1ug RNA was setup as per manufacturer\\u0026rsquo;s instructions (Genesure \\u0026ndash; PGK163A) i.e., incubation at 42\\u0026deg;C for 60min and 70\\u0026deg;C for 5 min using a 20\\u0026micro;L reaction mixture. Using this cDNA (1 \\u0026micro;g) as template, and gene specific primers (300nM) respective to different physiological processes, RT-PCR was performed using SYBR-green technology (Thermo \\u0026ndash; A25742) with the following cycling conditions 50.0\\u0026deg;C for 1:00; 96.0\\u0026deg;C for 6:00 and [96.0\\u0026deg;C for 0:10; 55.0\\u0026deg;C for 0:30; 73.0\\u0026deg;C for 1:00] for 40 cycles. The data was analysed according to Livak\\u0026rsquo;s method (ddCT calculation) using either GAPDH or B-actin for normalization as described in [30].\\u003c/p\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eFor detection of transcript level expression, the following primers were designed and used:\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eOCT4: FP-AGCAAAACCCGGAGGAGT:\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section4\\\"\\u003e\\u003ch2\\u003eRP-CCACATCGGCCTGTGTATATC\\u003c/h2\\u003e\\u003cp\\u003eSOX2: FP-GGAAATGGAGGGGTGCAAAAGAGG:\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eRP-TTGCGTGAGTGTGGATGGGATTGGTG\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eNANOG: FP-TCCTCCTCTTCCTCTATACTAAC:\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section4\\\"\\u003e\\u003ch2\\u003eRP-CCCACAATCACAGGCATAG\\u003c/h2\\u003e\\u003cp\\u003eKLF4: FP-CAGGGACTGTCACCCTGC:\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eRP-GGCATGAGCTCTTGGTAATGG\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eCD133: FP- ACACTACCAAGGACAAGGCG:\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section4\\\"\\u003e\\u003ch2\\u003eRP- TCTCCAACGCCTCTTTGGTC\\u003c/h2\\u003e\\u003cp\\u003eCD44: FP- ACGGAAGAAACAGCTACCCAG:\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eRP- TGTCCCTGTTGTCGAATGGG\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec18\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003ePAX6: FP- GAGAAGTGAGGAGTGGCTC:\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec19\\\" class=\\\"Section4\\\"\\u003e\\u003ch2\\u003eRP- GGATTGACTGTCTCCGACTT\\u003c/h2\\u003e\\u003cp\\u003eS100B: FP- GAAATCCGAACTGAAGGAGC:\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eRP- CGTCTCCATCATTGTCCAGT\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec21\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003ePFKFB3: FP-AAAAGCCTCGCATCAACAGC:\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec22\\\" class=\\\"Section4\\\"\\u003e\\u003ch2\\u003eRP-TCCGGGAGCCTTTCATGTTT\\u003c/h2\\u003e\\u003cp\\u003eIDH3A: FP-CGCGTGGATCTCTAAGGTCT:\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec23\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eRP-GGGCCAATACCATCTCCTGG\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec24\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eG6PD: FP- TAGGCTGGAACCGCATCATC:\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec25\\\" class=\\\"Section4\\\"\\u003e\\u003ch2\\u003eRP-TGCGGTAGATCTGGTCCTCA\\u003c/h2\\u003e\\u003cp\\u003eHMGCR: FP- AGCTGTCATTCCAGCCAAGG:\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec26\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eRP- CCATGGCAGAGCCCACTAAA\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec27\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eDHCR24: FP- GACCTCCATTGGCTGGACTC:\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec28\\\" class=\\\"Section4\\\"\\u003e\\u003ch2\\u003eRP- GGCCGTACTTGTGGGATGAT\\u003c/h2\\u003e\\u003cp\\u003eCAV1: FP- ACCCACTCTTTGAAGCTGTTG:\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eRP- GAACTTGAAATTGGCACCAGG\\u003c/h3\\u003e\\n\\u003cdiv id=\\\"Sec30\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eWestern blotting\\u003c/h2\\u003e\\u003cp\\u003eSpheroids were collected and whole cell lysate was prepared by RIPA lysis buffer (sigma \\u0026ndash;R0278-50ML), subjected to centrifugation at 10000 RPM for 15 minutes at 4\\u0026deg;C, concentration was assessed by Bradford assay and immunoblotting was performed by following the protocol adapted from [42] In brief, the proteins were electrophoresed on 8\\u0026ndash;15% SDS-PAGE gels depending on target proteins analysed, resolved, and transferred to nitrocellulose membrane (Axiva \\u0026ndash; 160300RI), blocked with 5% skim milk for an hour. All primary antibodies were prepared in 1% BSA (Himedia-MB083) in PBST and the blots were probed with primary antibodies at 4\\u003csup\\u003eo\\u003c/sup\\u003eC overnight. Following three washes with PBST, the blots were incubated with either anti-rabbit (Invitrogen-65-6120) or anti-mouse (Santa Cruz \\u0026ndash; SC516102) secondary antibody for an hour. The blots were then washed thrice using PBST, visualized using ECL chemiluminescence detection system (Thermo- 34580) and digitally captured using Bio-Rad Chemidoc instrument (ChemiDoc MP). Each experiment was performed in triplicate.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec31\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eThe primary antibodies used in this study are:\\u003c/h2\\u003e\\u003cp\\u003ePFK-1 (G-11): sc-166722; IDH3A (A-10): sc-398021; G6PD (sc-373886); CD133 (NBP2-44247); CD44(NBP1-47386); PAX6 (DSHB); S100β (sc-393919); HMGCR (sc-271595); DHCR24 (sc-398938); CAVEOLIN-1 (sc-894); p53 (ABclonal- A0263); p21 (ABclonal- A1483), DNMT1 (ab13537), β-actin (abcam-ab8227), KDM5A (ab70892), and Gli-1 (ABclonal-A14675).\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec32\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eImmunofluorescence\\u003c/h2\\u003e\\u003cp\\u003eSpheroids were cultured and treated as mentioned above, followed by fixation using 100% methanol for 5 minutes, permeabilized with PBST on ice for 10 minutes and blocked using 1% BSA in PBST for 1hr. The cells were incubated with primary antibodies - overnight at 4\\u003csup\\u003eo\\u003c/sup\\u003eC in a humid chamber. Following 3 washes with PBS, the cells were incubated with Alexa488 (anti-rabbit-ab ab150077) Alexa647 (anti-mouse \\u0026ndash; ab150119), washed thrice and images were acquired using Leica microsystems.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec33\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eFACS assay\\u003c/h2\\u003e\\u003cp\\u003eTumor spheres were collected in tubes and washed with ice cold PBS. Spheres were trypsinized and dissociated into single cells. These single cells were fixed using formaldehyde and permeabilized using 100% methanol. Fixed cells were washed by centrifugation with PBS. After washing cells were incubated with CD44 and CD133 primary antibodies at 4℃ overnight. Primary antibodies were removed and washed by centrifugation. After washing fluorescent tagged secondary antibodies (Alexa 448-anti rabbit antibody, and Alexa 647-anti mice antibody) were added and incubated at room temperature for 1hr. Cells were washed and dissolved in 500\\u0026micro;l PBS and cell population distribution was measured by BD Accuri.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eTotal Cholesterol estimation\\u003c/h3\\u003e\\n\\u003cp\\u003eTotal cholesterol from cells were extracted according to the protocol by Bittame et.al [43]. The relative cholesterol concentration in lovastatin, and Cav1 KD condition were measured by ZAK\\u0026rsquo;s method [44]. Cholesterol standard graph was plotted by diluting various concentrations of cholesterol stock (ranging from 20\\u0026ndash;140\\u0026micro;g) and OD was taken at 560nm. Equal volume (500\\u0026micro;l) of cholesterol sample from different treatment conditions were taken in separate test tubes and in blank no cholesterol was added. The volume in all test tubes was made up to 5ml by addition of 0.5% ferric chloride acetic acid reagent. 3mL of conc. Sulphuric acid was added to each test tubes, mixed well and kept for 15mins at room temperature. Then OD was taken at 560nm. OD of all the tubes were normalized by subtracting OD of blank. The normalized OD values were plotted on the cholesterol standard graph and the concentration was measured against each OD. Then the cholesterol concentrations were normalized with protein concentrations.\\u003c/p\\u003e\\n\\u003ch3\\u003eMethylation specific (MS)-PCR\\u003c/h3\\u003e\\n\\u003cp\\u003eGenomic DNA was isolated from each treated cells by phenol chloroform method. Two micrograms of genomic DNA were bisulfite converted by EPIGENTEK Methylamp DNA Modification Kit (P-1001-2) according to the manufacturer\\u0026rsquo;s instructions. Bisulfite-treated DNA was then used as template in PCR reactions for PCR analysis. For identifying the promotor following methylation specific primers were used.\\u003c/p\\u003e\\u003cp\\u003eCAV1: FP(Methylated)-TGTTCGGGTGTGGAAATTC\\u003c/p\\u003e\\u003cp\\u003eRP(Methylated)-ATCCTAAAACTCACCTACG\\u003c/p\\u003e\\u003cp\\u003eFP(Unmethylated)-TTGTTTGGGTGTGGAAATTTTG\\u003c/p\\u003e\\u003cp\\u003eRP(Unmethylated)-ATCCTAAACTCAATCTCACCTACA\\u003c/p\\u003e\\n\\u003ch3\\u003eChromatin immunoprecipitation\\u003c/h3\\u003e\\n\\u003cp\\u003eChromatin immunoprecipitation was performed after respective treatment in U87MG spheroid cells by using Imprint Chromatin Immunoprecipitation Kit (Sigma) according to the manufacturer instruction and the protocol standardized in our lab followed by qRT-PCR [31]. ChIP primer for CAV1 is 5\\u0026rsquo;-CAGGATTGTGGATTGTTTCTGC-3\\u0026rsquo;; 5\\u0026rsquo;-GAGTGAGAACGTTTCTCCCG-3\\u0026rsquo;.\\u003c/p\\u003e\\u003cp\\u003eH3K4me3 (Invitrogen MA5-11199), IgG(M8695-Sigma) were used for ChIP assay.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec37\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e\\u003cp\\u003eThe results are presented as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD. Each value represents mean calculated from 3 independent experiments and significant differences among experiments were assessed using Prism5. When 2 groups were tested - student\\u0026rsquo;s \\u0026lsquo;t\\u0026rsquo; test was employed and when multiple classes of data were analysed- either a one-way or two-way ANOVA were employed to test the significance.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cb\\u003eGlioblastoma spheroids show higher stemness properties\\u003c/b\\u003e\\u003c/p\\u003e\\u003cp\\u003eAs non-adherent conditions enhance self-renewal properties, spheroid cultures were generated using hanging drop method to mimic glioblastoma stem cells (GSCs). After 7 days, the spheroids formed (Fig.\\u0026nbsp;1A) were assessed for stemness by quantifying pluripotency and surface marker expression in comparison to the monolayer cells. FACS assay results showed increase in CD133\\u0026thinsp;+\\u0026thinsp;CD44\\u0026thinsp;+\\u0026thinsp;double positive population from 0.5% (in monolayer) to 11.7% (in spheroids) (Fig.\\u0026nbsp;1B). Thus, this method was used for generation of glioblastoma cell-line derived CSCs.\\u003c/p\\u003e\\u003cp\\u003eRT-PCR was performed in both U87MG and Ln229 derived spheroids. An increase in OCT4, SOX2, NANOG and KLF4 as well as the universal stemness markers CD133, CD44 along with glial progenitor marker PAX6 was noted in spheroids derived from both cell lines (Fig.\\u0026nbsp;1C, 1D). Further, CD133, CD44 and PAX6 were also upregulated at protein levels in U87MG Ln229 (Fig.\\u0026nbsp;1E). The glial differentiation marker S100B was also quantified and a decrease in expression in spheroids when compared to monolayer was noted (Fig.\\u0026nbsp;1E). Immunofluorescence staining also showed that the spheres developed by us are positive for CD133, CD44, PAX6, Cav1 but, negative for S100B in U87MG cells (Fig.\\u0026nbsp;1F).\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eMetabolic rewiring in GBM spheroids in comparison to monolayer culture: high expression of cholesterol biosynthesis gene, Cav1, and IDH3A support higher GSCs population in spheroids\\u003c/b\\u003e\\u003c/p\\u003e\\u003cp\\u003eTotal cholesterol content was increased in spheres compared to monolayer (Fig.\\u0026nbsp;2A). The expression of HMGCR (the rate limiting enzyme of mevalonate pathway), DHCR24 (catalyzes the ultimate step of cholesterol synthesis) and cholesterol carrier-Cav1 was estimated in spheroids. In comparison to monolayer, GSC spheroids displayed enhanced expression of cholesterol biosynthetic genes and Cav1 at mRNA and protein level in U87MG and Ln229 (Fig.\\u0026nbsp;2B-C). Confocal microscopy results also showed an increase in Cav1 in U87 spheroids compared to monolayer cells (Fig.\\u0026nbsp;1F).\\u003c/p\\u003e\\u003cp\\u003eAs CSCs show dynamic plasticity to the environmental conditions, to understand the metabolic dependence of spheroids cultured by hanging drop method, we assessed the glycolytic marker PFK1, TCA protein IDH3A and PPP marker G6PD. From the RT-PCR and protein blots, it is apparent that PFK1 and G6PD were reduced in GSCs, but IDH3A was upregulated in U87MG and Ln229 (Fig.\\u0026nbsp;2D-E) cell lines at both mRNA and protein level.\\u003c/p\\u003e\\n\\u003ch3\\u003eInhibition of cholesterol synthesis effectively reduces stemness and increased differentiation in U87MG spheroids\\u003c/h3\\u003e\\n\\u003cp\\u003eAs cholesterol synthesis and Cav1 were increased in spheroids, we targeted cellular cholesterol availability by inhibition of synthesis by lovastatin. Following cell viability test (Fig.\\u0026nbsp;3A), a concentration of 2.5uM lovastatin was chosen for further experiments. It was seen that the relative cholesterol concentration was highly reduced in lovastatin (Fig.\\u0026nbsp;3B). Lovastatin treatment was found to hinder cholesterol regulatory proteins (HMGCR and DHCR24) much effectively and Cav1 expression was reduced (Fig.\\u0026nbsp;3C, 3D). In order to test whether lovastatin treatment affected stemness, we analysed stemness markers - CD133, CD44, PAX6 and differentiation marker S100B. RT-PCR and Western blot data depicts that lovastatin treatment inhibited stemness and promoted differentiation (Fig.\\u0026nbsp;3E, 3F). Further, we tested if cholesterol inhibition altered IDH3A levels, and found that lovastatin treatments reduced IDH3A (Fig.\\u0026nbsp;3G, 3H). Immunofluorescence data also showed lovastatin treatment reduced stem cell markers CD133, CD44 (Fig.\\u0026nbsp;3I). Taken together, lovastatin inhibited Cav1 expression, reduced stemness in GSC and promoted its differentiation and hampered the metabolic adaptation of GSC.\\u003c/p\\u003e\\n\\u003ch3\\u003eCav1 knockdown reduces stemness in U87MG spheroids\\u003c/h3\\u003e\\n\\u003cp\\u003eIn line with inhibition of cholesterol, we determined if knockdown of Cav1 could inhibit the formation of spheroids. We utilized three different si-RNA concentrations, of which- 70nM si-RNA targeted towards Cav1, we could attain 90% knockdown of target protein compared to si-Control treated spheroids (Fig.\\u0026nbsp;4A-B). Thus, 70nM of si-RNA was used for downstream experiments. As cholesterol and caveolin are interrelated and they regulate each other, we checked relative cholesterol content after Cav1 si-RNA transfection. Surprisingly, we found that the relative cholesterol content in Cav1 knockdown condition is effectively reduced (Fig.\\u0026nbsp;4C). mRNA and protein analysis of siRNA treated cell lysates revealed a decrease in stemness markers CD133, CD44 and PAX6 (Fig.\\u0026nbsp;4D-E). As IDH3A was increased in spheroids compared the GBM monolayers, we tested if Cav1 knockdown had any effect on its expression. From RT-PCR and western blots, we found that IDH3A expression was also reduced following Cav1 knockdown (Fig.\\u0026nbsp;4F-G). Immunofluorescence results also showed Cav1 knockdown reduced expression of stem cell markers CD133 and CD44 (Fig.\\u0026nbsp;4H).\\u003c/p\\u003e\\n\\u003ch3\\u003eCholesterol depletion upregulates KDM5A and DNMT1 in GSCs\\u003c/h3\\u003e\\n\\u003cp\\u003eSince above results showed that high expression of Cav1 in glioma spheroids maintains GSCs, we investigated the mechanism of Cav1 expression in glioma spheroids. As Cav 1 is high in spheroids, we expected some epigenetic repressors to be down regulated. As expected, it was observed that two epigenetic repressors KDM5A (Fig.\\u0026nbsp;5A) and DNMT1 (Fig.\\u0026nbsp;5B) were downregulated in spheroids as compared to monolayers in both U87MG and Ln229 cell lines. As both KDM5A and DNMT1 were downregulated in spheroids, we individually overexpressed KDM5A and DNMT1 in U87 spheroids and checked the expression of Cav1. KDM5A was overexpressed (Fig.\\u0026nbsp;5C) and the expression of Cav1 was significantly decreased in KDM5A OE condition (Fig.\\u0026nbsp;5D). Similarly, DNMT1 OE also downregulated Cav1 expression (Fig.\\u0026nbsp;5E-F). Since lovastatin treatment downregulates Cav1, we checked the expression of KDM5A and DNMT1 in lovastatin treatment in U87MG spheroids. Both KDM5A (Fig.\\u0026nbsp;5G) and DNMT1 (Fig.\\u0026nbsp;5H) expression were increased post lovastatin treatment. To investigate further the mechanism of Cav1 expression by lovastatin treatment, we performed ChIP to check the role of KDM5A and MS-PCR to check the role of DNMT1 in lovastatin treatment. ChIP results revealed that there was decrease in H3K4me3 mark in Cav1 promotor after lovastatin treatment (Fig.\\u0026nbsp;5I). The reduction in H3K4me3 active mark is due to the increased occupancy of KDM5A in Cav1 promoter (Fig.\\u0026nbsp;5I). MS-PCR results also showed that lovastatin treatment increased promotor methylation of Cav1 gene (Fig.\\u0026nbsp;5J). Collectively, lovastatin treatment reduced Cav1 expression due to KDM5A mediated H3K4me3 demethylation and DNMT1 mediated promotor methylation of Cav1 gene.\\u003c/p\\u003e\\n\\u003ch3\\u003eTracing the mechanisms: how lowering of cholesterol enhances the expression of DNMT1 and KDM5A:\\u003c/h3\\u003e\\n\\u003cp\\u003eTo investigate how cholesterol depletion enhances the expression of KDM5A and DNMT1, we short if there could be involvement of Hh signaling. Since, Hh signaling largely depends on cholesterol abundance in plasma membrane. Along this line, firstly, we checked the expression of Hh signaling molecules SMO and Gli1 in spheroids. It was found that SMO and Gli1 expressions are increased at mRNA level in U87MG spheroids in comparison to monolayer (Fig.\\u0026nbsp;6A). Gli1 protein expression in U87MG spheroids were also very high in comparison to monolayer cells (Fig.\\u0026nbsp;6B). Then, we treated U87MG spheroids with lovastatin and traced that, there was reduction in transcripts of Gli1 and SMO (Fig.\\u0026nbsp;6C) and reduced protein expression of Gli1 (Fig.\\u0026nbsp;6D). As cholesterol depletion hampered Hh signaling, we hypothesized that Hh signaling might regulate the expression of KDM5A and DNMT1. Accordingly, we inhibited Hh signaling using a small molecule. Erismodegib (Erismo) treatment in U87MG spheroids. Following MTT assay result (Fig.\\u0026nbsp;6E), we treated U87MG spheroids with 2.5\\u0026micro;M of Erismo. There was reduction of Gli1 and SMO mRNA and Gli1 protein level in Erismo treatment (Fig.\\u0026nbsp;6F-G). Then, we checked the expression of KDM5A and DNMT1 in Erismo treatment. As expected, we found Hh signaling inhibition by Erismo enhanced the expression of KDM5A and DNMT1 (Fig.\\u0026nbsp;6H). Thus, it was confirmed that cholesterol depletion hampered Hh signaling and upregulated expression of KDM5A and DNMT1. Further the effect of Hh inhibition on downstream genes was evaluated. We found that the expression of Cav1 is downregulated in Erismo treatment in U87MG spheroids (Fig.\\u0026nbsp;6I), which is in accordance with the upregulation of KDM5A and DNMT1 in Erismo treatment. Similarly, the expression of stemness markers CD133, CD44, Pax6 and the expression of TCA cycle gene IDH3A were downregulated in Erismo treatment (Fig.\\u0026nbsp;6I).\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eGlioblastoma stem cells (GSCs) have high proliferative and self-renewal capabilities and are the root cause of cancer recurrence and therapeutic resistance. Despite advances in GBM treatment, presence of GSCs pose a potential hindrance to current treatment strategies. So, understating the detailed molecular mechanism of GSCs proliferation and maintenance is essential to combat GMB. In this study, we used spheroid culture model that enriches for GSCs, validated by the significant upregulation of pluripotency and stemness markers (OCT4, SOX2, CD133, CD44, and PAX6) and the downregulation of the differentiation marker S100β. Using this model, we have uncovered a critical and previously uncharacterized signaling cascade that links cholesterol metabolism, Hedgehog (Hh) signaling, and epigenetic regulation in maintenance of GSCs.\\u003c/p\\u003e\\u003cp\\u003eThe spheroids developed by us showed distinct metabolic rewiring, characterized by high dependency on de novo cholesterol biosynthesis. GSC spheroid showed high expression of cholesterol biosynthesis genes like; HMGCR and DHCR24 and led to increased total cholesterol content. This metabolic shift is maintained by monitoring cholesterol localization inside a cell, and caveloin-1 possesses high binding affinity to cholesterol and thus partly contributes to the maintenance of cholesterol levels in a cell. Cholesterol metabolism and Cav1 plays significant role in maintenance of CSCs, including GBM. Studies have shown that targeting CSCs can be used as novel therapeutic approach in cancers [45]. Here we found that Cav1 is upregulated in GSCs, suggesting the role of Cav1 in GSCs maintenance. Some evidence suggests that slow-cycling quiescent CSCs originated from GBM tumors are less glycolytic and mainly rely on oxidative phosphorylation thereby show high ATP levels [46\\u0026ndash;48]. Further, to understand the metabolic adaptability of GSCs cultured by hanging drop method, we assessed PFK1, IDH3A and G6PD as markers of glycolysis, TCA cycle and PPP respectively. As only IDH3A was increased in spheroids, we concluded that GSCs derived energy by TCA cycle mediated OXPHOS and ATP generation. This suggests GSCs are not merely glycolytic but dependent on cholesterol metabolism and mitochondrial respiration to support their stem-like properties.\\u003c/p\\u003e\\u003cp\\u003eThe metabolic dependency towards cholesterol biosynthesis was targeted by reduction of cholesterol content using an inhibitor of cholesterol synthesis pathway. As lovastatin is a cholesterol lowering and a pharmacological modulator of Cav1 [49\\u0026ndash;50] and treatment with lovastatin inhibited mammosphere formation due to reduced Sox2 promoter transactivation [51], we challenged GSCs for depletion of both cholesterol and Cav1 protein. Treatment with lovastatin not only depleted cellular cholesterol but also triggered a collapse of the GSC phenotype. We observed a marked reduction in Cav1, a loss of stemness markers (CD133, CD44, PAX6), and an increase in the differentiation marker S100β. As cholesterol inhibition also reduced Cav1 levels, we further tested if this was responsible for altered stemness and metabolic inhibition in GSCs. Cav1 knockdown via siRNA phenocopied these effects, independently confirming Cav1 as a critical mediator of GSC stemness. Earlier studies have shown reduced invasiveness and colony formation when Cav1- knockdown was performed in U87MG cells [52]. Stabilization of Cav1 protein by Deubiquitination promotes stemness and drug resistance and it also promotes aggressiveness in GBM cells [53\\u0026ndash;54].\\u003c/p\\u003e\\u003cp\\u003eMechanistically, we attempted to understand how this high-Cav1, cholesterol-rich state is maintained. We discovered a novel epigenetic basis for the regulation of Cav1 in GSCs. We found that GSCs maintain a state of distinct epigenetic landscape characterized by marked reduction of the histone H3K4 demethylase KDM5A and the DNA methyltransferase DNMT1. This downregulation of epigenetic repressors is required for GSC maintenance, given that forced overexpression of either KDM5A or DNMT1 was sufficient to markedly decrease Cav1 expression.\\u003c/p\\u003e\\u003cp\\u003eThis epigenetic state is dynamically regulated by cholesterol availability. Cholesterol depletion via lovastatin altered the epigenetic landscape, leading to a robust increase in both KDM5A and DNMT1 expression. This upregulation of epigenetic repressors had a direct, mechanistic consequence on Cav1 expression. ChIP-qPCR revealed that lovastatin treatment increased KDM5A occupancy at the Cav1 promoter, leading to a reduction in the active H3K4me3 mark. Concurrently, MS-PCR showed increased Cav1 promoter methylation. Thus, GSCs actively suppress KDM5A and DNMT1 to keep the Cav1 gene \\\"on\\\"; cholesterol inhibition breaks this cycle, restoring these repressors which then silence Cav1 through coordinated histone and DNA modification.\\u003c/p\\u003e\\u003cp\\u003eFinally, we identified the key upstream regulator that links cholesterol to this epigenetic switch. The Hedgehog (Hh) signaling pathway was a prime regulator because of its dependency on cholesterol for activation of signaling pathway. We verified that Hh signaling (Gli1, SMO) is highly active in GSC spheroids but is significantly attenuated by cholesterol depletion with lovastatin. This places cholesterol as a critical fuel for Hh pathway activity in GSCs. Most importantly, direct pharmacological inhibition of the Hh pathway using Erismodegib perfectly mimicked the effects of lovastatin. Hh inhibition upregulated KDM5A and DNMT1, which in turn suppressed Cav1, reduced stemness markers, and decreased IDH3A.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eCollectively, high cholesterol fuels Hh pathway in glioma spheroids. Hyperactivation of Hh pathway led to downregulation of KDM5A and DNMT1. Decreased expressed of KDM5A and DNMT1 failed to supress Cav1. High expression of Cav1 in glioma spheroids maintains stemness properties. Our study establishes the cholesterol-KDM5A/DNMT1-Cav1 axis in regulating stemness properties of GBM cells. Our findings strongly suggest that therapeutic strategies aimed at breaking this loop, such as cholesterol-lowering statins or Hh pathway inhibitors, could function as potent epigenetic and differentiation-inducing therapies, offering a promising new avenue to target the resilient GSC population in glioblastoma.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eGSCs\\u003c/strong\\u003e-Glioma stem like cells\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCSCs\\u003c/strong\\u003e-Cancer stem cells\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eGBM\\u003c/strong\\u003e-Glioblastoma multiform\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eKMD5A\\u003c/strong\\u003e- lysine demethylase 5A\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDNMT1\\u003c/strong\\u003e- DNA methyl transferase\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eH3K4me3\\u003c/strong\\u003e- Histone 3 lysine 4 trimethylation\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eHMGCR\\u003c/strong\\u003e-3-hydroxy-3-methylglutaryl-CoA reductase\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDHCR24\\u003c/strong\\u003e- 24-dehydrocholesterol reductase\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eIDH3A\\u003c/strong\\u003e- Isocitrate dehydrogenase 3alpha\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePFK-1\\u003c/strong\\u003e- Phosphofructokinase-1\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eG6PD\\u003c/strong\\u003e-Glucose-6-phosphate dehydrogenase\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eConflict of Interest:\\u0026nbsp;\\u003c/strong\\u003eNone\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCredit author statement\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSKP conceived the project, TB Conceptualize, Methodology, Software; TB, SM, JM \\u0026amp; KR collected \\u0026amp; curated data and wrote the manuscript. SC, PN, AR, Niharika, PM \\u0026amp; BP information literature survey and curation of data. PD visualize the overall project, SKP edited the draft manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;Acknowledgement:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTB, JM, SC, PN, PM are thankful to CSIR-UGC for fellowships, Govt. of India. R. Kirtana received and BP receives fellowship from CSIR, Govt. of India. SM \\u0026amp; AR are thankful to NIT-Rourkela for Institute fellowship. This work is supported in part by the Department of Science and Technology- SERB (Government of India) project No.: EMR/2016/007034 to SKP, ICMR-grant no.: IIRP-2023-2134 to SKP and by a special grant from the then Director (Prof. Animesh Biswas) of the NIT-Rourkela to SKP.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eMyers BL, Brayer KJ, Paez-Beltran LE, Villicana E, Keith MS, Suzuki H, Newville J, Anderson RH, Lo Y, Mertz CM, Kollipara RK, Borromeo MD, Lu QR, Bachoo RM, Johnson JE, Vue TY. Transcription factors ASCL1 and OLIG2 drive glioblastoma initiation and co-regulate tumor cell types and migration. Nat Commun. 2024 Nov 28;15(1):10363\\u003c/li\\u003e\\n\\u003cli\\u003eLiu Y, Zhou F, Ali H, Lathia JD, Chen P. Immunotherapy for glioblastoma: current state, challenges, and future perspectives. 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Biochim Biophys Acta. 2009 Feb;1793(2):354-67.\\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\":\"info@researchsquare.com\",\"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\":\"Glioblastoma, cholesterol biosynthesis, stemness, Caveolin1, DNMT1, KDM5A, Gli1\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-8095695/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-8095695/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eGlioblastoma multiform (GBM) harbours tumor heterogeneity and shows little efficacy to the current treatment strategies. Persistence of glioma stem cells (GSCs) are the root cause of tumor recurrence and drug resistance. So, targeting GSCs can be a better therapeutic strategy to tackle GBM. To mimic the tumor microenvironment, we have developed tumor spheroids by hanging drop method using U87MG and Ln229 cells with an enriched GSC population. Compared to monolayer cells spheroids had higher expression of stemness markers like CD133, CD44, PAX6 and reduced expression of differentiation marker. Cancer cells rewire the metabolic pathways to sustain high proliferation. Among the metabolic pathways, cholesterol biosynthetic pathways are mostly dysregulated in cancers including GBM. The spheroids showed high expression of cholesterol biosynthetic gene (HMGCR, DHCR24), and Caveolin1 (Cav1). Targeting cholesterol metabolism by lovastatin resulted in depletion of cellular cholesterol levels, including in plasma membrane. Lowering of cholesterol affected membrane fluidity and hampered Hh signaling by lowering Gli1; consequently, causing downregulation of HMGCR, DHCR24, Cav1, and IDH3A, as well as loss of the stemness factors. However, there are enhanced expression of epigenetic chromatin modification enzymes, including DNMT1 and KDM5A. Tracking into the root cause of silencing of Cav1 gene, we found CAV1 gene promoter is methylated by DNMT1, and H3K4me3 level depleted due to enhanced KDM5A mediated demethylation. CAV1 gene silencing by siRNA validated its role in stemness maintenance and metabolic reprogramming of GSCs. Our findings suggest that, lovastatin has therapeutic potential and illustrates the importance of tumor spheroid models better understanding molecular mechanisms of GBM.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Lowering of Cholesterol Hampers Glioblastoma Stem Cell Proliferation in Spheroids Through impaired Hh signaling: upregulation of epigenetic chromatin modifiers and down regulation CAV1 and Stem Cell markers\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-11-25 17:25:51\",\"doi\":\"10.21203/rs.3.rs-8095695/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"3a2237c7-e7e7-4f83-9fe8-82c62c3de2ce\",\"owner\":[],\"postedDate\":\"November 25th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-12-04T16:08:35+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-11-25 17:25:51\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-8095695\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-8095695\",\"identity\":\"rs-8095695\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}