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IJMSInternational Journal of Molecular Sciences
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18 February 2026

18 Pages

m6A RNA Methylation Is Increased in Tumour Invasive Regions and Influences Invasive Capability and Chemotherapeutic Sensitivity in Adult Glioblastoma

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1
Children’s Brain Tumour Research Centre, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, UK
2
Queen’s Medical Centre, Nottingham University Hospitals NHS Trust, Nottingham NG7 2UH, UK
3
School of Life Sciences, University of Nottingham, Nottingham NG7 2UH, UK
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci.2026, 27(4), 1967;https://doi.org/10.3390/ijms27041967
This article belongs to the Special Issue Updates and Advances in the Field of Glioblastomas: Mechanisms, Microenvironment and Treatments
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Abstract

Adult glioblastoma multiforme (GBM) is the most common primary malignant brain tumour caused by multiple molecular factors. N6-methyl-adenosine (m6A) is an abundant RNA modification that governs cellular RNA metabolism. We hypothesise that changes in m6A-modified RNA and regulatory machinery such as the writer proteins, Methyltransferase 3 (METTL3) and WT1-associating protein (WTAP), the demethyltransferase protein, and Alpha-ketoglutarate dependent dioxygenase (FTO), are driving factors of GBM development and treatment resistance. Here, we investigated m6A-RNA spatial and quantitative abundance and expression of m6A effector proteins directly in GBM tissue and patient-derived low-passage primary adult GBM and low-grade glioma (LGG) cells, and explored the consequences of m6A-RNA disruption on GBM invasive capabilities, self-renewal and responsiveness to temozolomide (TMZ). We observed that METTL3, WTAP and FTO transcript and protein expression were significantly increased in cells derived from invasive regions of GBM tumours, and elevated WTAP and FTO expression significantly correlated with poor GBM patient survival. We further found that the abundance of m6A-modified RNA in GBM tumours was significant higher in rim and invasive tissue, as well as significantly higher in patient-derived cells from GBM tumour invasive regions. Functional depletion of these effector proteins significantly altered m6A levels on and the expression of the pluripotency stem cell marker SOX2 while also impairing self-renewal and cell invasion behaviour and increasing sensitivity to TMZ. The targeting of RNA modification regulatory mechanisms reveals novel therapeutic strategies aimed at improving clinical outcomes for GBM patients.

1. Introduction

Glioblastoma (GBM; World Health Organization WHO grade IV IDH wild type astrocytoma) is the most common and lethal primary malignant brain tumour [1]. The median survival duration of radically treated GBM patients is approximately 14.6 months, despite surgical and oncological interventions [2]. This limitation is attributed to the following: intra- and intertumoral heterogeneity and the existence of stem-like properties in cells that confers self-renewal and resistance to conventional alkylating agents [3]. With the lack of preventative treatment and common occurrence of recurrence, there is a pressing need to develop new therapeutic strategies.
Modification of RNA by N6-methyl-adenosine was first reported in 1974 [4] and has recently received significant interest as a post-transcriptional process controlling cellular metabolism which may contribute to disease mechanisms [5]. The co-transcriptional deposition of m6A modification on nuclear mRNA is mediated by the writer METTL3-METTL14 effector protein heterodimer [6] and a third effector protein, WTAP, anchoring the METTL3-METTL14 complex in the nuclear compartment [7,8]. m6A RNA modification is a reversible process as modification is performed in a signal-dependent manner by two ‘eraser’ effector demethylases, FTO and ALKBH5 [9,10]. Furthermore, groups of specific proteins, known as reader effector proteins, facilitate the reading of methyl groups onto all forms of RNA species. The molecular consequences of m6A RNA modification affect multiple RNA characteristics such as base pairing, secondary structure and protein binding which, in turn, fine-tune gene expression by regulating RNA metabolism processes such as degradation, splicing, alternative polyadenylation, translation efficiency and subcellular localization [11,12,13,14,15].
Studies suggest that m6A RNA modification is an important functional modulator in a variety of malignant cancers. For instance, the m6A eraser FTO is found to control the sensitivity of leukaemia cells to oncometabolites [16], whereas the second eraser protein ALKBH5 suppresses the proliferation of patient-derived glioma stem-like cells [17]. Likewise, WTAP, a writer complex protein, is overexpressed in glioblastoma tissue and may regulate the migration and proliferation of glioblastoma cells via an epidermal growth factor-dependent mechanism [18]. Furthermore, depletion of METTL3, a second writer complex protein, is reported to both impair [19] and promote [20] self-renewal in glioblastoma stem cells (GSCs). Despite previous studies indicating the involvement of m6A RNA methylation regulatory machinery in different types of cancers and tumours, there is a need for a deeper understanding of disrupted processes and their clinical relevance. Here, we aimed to directly examine m6A-RNA abundance and changes in effector protein machinery in GBM pathology and etiological mechanisms using patient GBM tumour tissue and patient-derived primary GBM cells. We first characterised expression of METTL3, WTAP and FTO in GBM patient tissue and low-passage LGG and glioblastoma cells derived from patient tumour subregions and subsequently examined expression profiles as a predictor of GBM patient survival. We investigated the abundance of m6A-modified RNAs across subregions of tumour tissue and patient-derived primary GBM cells and m6A enrichment within transcripts involved in stem-cell differentiation. Finally, we explored whether depletion of effector proteins changed GBM cell invasion activity and sensitivity to chemotherapeutic agents. Our findings highlight that m6A-RNA-dependent RNA processes significantly influence GBM tumour invasive behaviour.

2. Results

2.1. Increased METTL3, WTAP and FTO Expression in GBM Invasive Tumour Patient-Derived Cell Lines and Correlation with Poor Patient Survival

To explore m6A-RNA methylation writer complex and FTO expression profiles, we first measured basal expression of METTL3, WTAP and FTO mRNA in primary cell culture derived from LGG (LGG38 and LGG41) and both core (GCE28 and GCE40) and invasive (GIN5, GIN8, GIN28 and GIN40) regions of GBM tumour specimens. We found that METTL3, WTAP and FTO transcripts are highly increased in cells derived from the invasive regions (GIN28 and GIN40) compared to primary astrocytes (METTL3: GIN28 9.195 ± 0.289, p = 0.0273, GIN40 23.888 ± 8.833, p < 0.0001; WTAP: GIN40 2.837 ± 0.777, p = 0.0006; FTO GIN28 1.824 ± 0.180, p = 0.010, GIN40 2.384 ± 0.631, p < 0.0001) (Figure 1(a(i)–a(iii))). However, no significant alteration of METTL3 and WTAP was seen in any of the cells derived from LGG and the core region of GBM tissues. In contrast, FTO expression was significantly lower in cells derived from low-grade (LGG38 and LGG41) and core region tissue (GCE28, GCE40) (Figure 1(a(iii))). At the protein level, GIN28 and GIN40 cells also showed the highest expression of METTL3, WTAP and FTO (METTL3: GIN28 3.3160 ± 0.694, p = 0.0003, GIN40 2.642 ± 0.412 p = 0.0024; WTAP: GIN28 2.930 ± 0.779, p = 0.0260; FTO: GIN28 1.982 ± 0.162, p = 0.0316, GIN40 4.043 ± 0.613, p < 0.0001) compared to primary astrocytes (Figure 1(b(i)–b(iii)),(c(i)–c(iii))).
Figure 1. METTL3, WTAP and FTO m6A effector protein expression is increased in adult GBM cells and predicts poor survival of GBM patients. (a(i)–a(iii)) RT-qPCR expression profiles of METTL3, WTAP and FTO in GIN5, GIN8, GIN28, GIN40, GCE28, GCE40, LGG38 and LGG41 GBM cell lines. (b(i)–b(iii)) Representative IF images of METTL3, WTAP and FTO proteins within GIN GBM cell lines. Scale bar, 20 µM. (c(i)–c(iii)) Quantification of METTL3, WTAP and FTO IF abundance in GIN GBM cells compared to human astrocytes. (d(i)–d(iii)) The correlation between m6A effectors’ expression over time and the survival of GBM patients using the TCGA dataset. Error bars in a and c represent standard deviation across three independent replicates. * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. Abbreviations: HA, human astrocyte; IF, immunofluorescence; TCGA, The Cancer Genome Atlas.
Invasive regions of GBM tumours have been proposed to be more similar to residual tumour left behind after surgery, which can cause recurrence and hence shortened patient survival times. As our findings indicated increased expression of the m6A methylation effector protein in patient-derived cells from invasive regions of tumour, we next investigated whether m6A effectors’ transcript levels could be used as prognostic factors for GBM patient survival. We therefore assessed METTL3, WTAP and FTO gene expression with patient survival using the ‘The Cancer Genome Atlas’, Tumour Glisblastoma TCGA-540-MAS5.0-u133a, and mRNA affymetrix chip generated dataset. The results presented as Kaplan–Meier survival curves in Figure 1(d(i)–d(iii)) indicate that elevated WTAP and FTO, but not METTL3, correlates with poor GBM patient survival (METTL3, p = 0.296; WTAP, p = 0.034; and FTO, p = 0.019). These findings add support for the proposal that changes in mRNA and protein levels of m6A effector proteins in derived cells from invasive regions of GBM tumours could be moderating detrimental tumour behaviour and thereby reducing patients’ survival.

2.2. Higher m6A-Modified RNA Abundance in Patient Tissue from Rim and Invasive Regions of Glioblastoma Multiforme

The different subregions of GBM tumours, e.g., core, rim and invasive regions, display variation in cellular phenotype and genotype and, as discussed above, can lead to differential propensity for aggressive invasion or tumour recurrence [21]. To examine variability in METTL3, WTAP and FTO protein abundance between the tumour subregions in situ, DAB immunohistochemistry was conducted on patient tissue from core, rim and invasive regions of GMB tumours and non-tumour temporal lobe tissue.
The results showed no significant differences in protein abundance of METTL3, WTAP and FTO across the different regions of GBM tumours (Figure 2a–c). Furthermore, RT-qPCR analysis indicated no significant change in the expression of these and showed additional writer, reader and eraser m6A effector transcripts across the tissue subregions (Figure 2d). However, IHC staining using an antibody which specifically binds to m6A-modified RNA revealed significantly higher abundance of m6A-modified RNA in the rim and invasive regions (rim 17,612.512 ± 8677.248, p = 0.0001; invasive: 12,829.465 ± 5245.169, p = 0.0056) of GBM tumours compared with normal temporal lobe brain tissue (Figure 2e,f). This finding is consistent with changes in m6A-RNA regulation contributing to the GBM tissue rim/invasive tissue phenotype, which might involve changes in expression or cellular sub-compartment localisation of alterative ‘writer’, ‘reader’ or ‘eraser’ RNA-binding effector proteins.
Figure 2. m6A effector protein abundance shows regional topological variation within adult GBM patient tissue. Immunohistochemical protein staining of (a) METTL3, (b) WTAP and (c) FTO protein abundance within core, rim and invasive regions of GBM compared to non-tumour temporal lobe (TL). Scale bar, 20 µM. Quantification of METTL3, WTAP and FTO protein abundance across tumour regions is plotted on far-right column. (d) RT-qPCR of m6A effector protein mRNA within core, rim and invasive regions of GBM tissue. Error bars represent standard error across three independent replicates. (e) IHC images of m6A-RNA distribution and abundance within TL, core, rim and invasive regions of GBM. (f) Quantification of m6A-RNA abundance across different regions of GBM tumour tissue. Scale bar, 20 µM. Error bars represent standard deviation across three independent replicates. ** p < 0.01, *** p < 0.001. Abbreviation GBM, glioblastoma multiforme.

2.3. m6A-RNA Abundance Is Significantly Higher in Invasive Region Patient-Derived GBM Cells and Loss of FTO Increases m6A-RNA Abundance

Given our observation of increased abundance of m6A-modified RNA in invasive and rim subregions of GBM patient tumours, and having the capacity to perform functional studies on cell cultures, we next sought to examine if there are differences in the amount and distribution of m6A-modified RNAs directly within patient-derived GBM cells. We performed immunofluorescence and confocal microscopy on patient-derived cell lines from invasive regions of tumours, namely GIN5, GIN8, GIN28 and GIN40. m6A-modified RNAs were predominately observed in the cytoplasmic compartments of GBM-derived GIN cells, and, once again, we found a significant increase in m6A-RNA abundance in the GIN28 cell line (GIN28: 3.653 ± 1.781, p =0.0021) compared to human astrocytes (Figure 3a,b).
Figure 3. Modified m6A-RNA abundance is altered in wild type and METTL3, WTAP and FTO knockdown patient GBM cells. (a) Representative IF images of m6A-modified RNA abundance in human astrocyte and GIN5, GIN8, GIN28 and GIN40 GBM cells. Scale bar, 20 µM. (b) Quantification of m6A-modified RNA in GIN5, GIN8, GIN28 and GIN40 GBM cells relative to HAs. (c) Representative IF images of m6A-modified RNA abundance in GIN28 and GIN40 in control cells and upon siRNA-mediated knockdown of METTL3, WTAP and FTO. Scale bar, 20 µM. Bottom row plots quantification of m6A-modified RNA abundance in control and KD cells. Error bars represent standard deviation across three independent replicates. * p < 0.05, ** p < 0.01, and **** p < 0.0001. Abbreviations: HA, human astrocyte.
siRNA-mediated knockdown of METTL3, WTAP and FTO was performed to assess their impact on m6A RNA modification levels in two of the invasive tumour region-derived cells, GIN28 and GIN40 cells. Immunofluorescence analysis revealed that depletion of FTO resulted in a significant increase in m6A levels in both cell lines examined (Figure 3c(i),c(ii)). As demethylases remove m6A-modification from RNA, a loss of FTO activity is consistent with FTO functioning as the key RNA demethylase in these cells, leading to an increase in the number of m6A-modified transcripts. However, knockdown of METTL3 and WTAP did not result in a detectable change in m6A levels. This raises the possibility that the basal m6A methylation state in these cells is maintained by other effector protein compensatory mechanisms. Alternatively, since the anti-m6A antibody can detect m6A modifications on rRNA, tRNA, mt-RNA and mRNA, it is possible that the potential lack of change upon METTL3 and WTAP inhibition depends on METTL3 and WTAP functional involvement with the different types of modified RNA within these cells and METTL3/WTAP sub-compartment expression.

2.4. Knockdown of METTL3, WTAP and FTO Affects m6A Modification and Gene Expression of SOX2, And Self-Renewal and Cellular Invasion Behaviour

To explore the potential functional consequences of aberrant m6A regulation, which may drive tumour progression, we analysed the consequences of depletion of these effector proteins on the expression of and m6A abundance on genes involved in cell self-renewal; we also assessed the derived cells’ ability to form neurospheres and undergo cellular invasion. We first examined the transcripts FOXM1, Nestin (NES) and SOX2 that are involved in stemness and stem cell differentiation. Using methylated RNA immunoprecipitation, we assessed whether FOXM1, NES and SOX2 were enriched in the pull-down of the m6A antibody lysate compared to m6A-deficient lysate mRNA. We found that only SOX2 mRNA, a transcription factor regulating stem cell self-renewal, is enriched in the abundance of m6A modification in invasive region patient-derived cell lines GIN28 and GIN40 (Figure 4a).
Figure 4. Enrichment of m6A-RNA in transcripts involved in stemness and disrupted self-renewal behaviour in KD GBM patient cells. (a) Enrichment of m6A modification in FOXM1, NES and SOX2 transcripts as detected by (MeRIP)-qPCR in GIN28 and GIN40 compared to HA cells. (b) Relative m6A abundance across SOX2 transcript in GIN28 and GIN40 GBM patient cells and upon siRNA-mediated KD of METTL3, WTAP and FTO. (c) RT-qPCR expression profiles of SOX2 in GIN5, GIN8, GIN28 and GIN40 in the control and upon siRNA-mediated KD of METTL3 (c(i)), WTAP (c(ii)) and FTO (c(iii)), respectively. (d) Quantification of sphere formation assays in GIN GBM cells and following knockdown of METTL3 (d(i)), WTAP (d(ii)) and FTO (d(iii)). Error bars represent standard deviation across three independent replicates. * p < 0.05, ** p < 0.01. Abbreviations: MeRIP, Methylated RNA ImmunoPrecipitation; HA, human astrocyte.
To ascertain if m6A methylation of the SOX2 transcript is altered by changes in m6A effector protein machinery, we performed MeRIP-qPCR of SOX2 on siRNA-mediated knockdown of METTL3, WTAP and FTO in GIN28 and GIN40 GBM cells. Our results showed that METLL3 knockdown significantly reduced m6A modification levels on SOX2 in both GIN28 and GIN40 cells (Figure 4b), while WTAP knockdown significantly decreased SOX2 m6A modification levels in the GIN28 cell line only. Conversely, FTO knockdown significantly increased the degree of m6A modification along SOX2 mRNA in GIN28 cells, and a similar pattern was observed for GIN40 cells, although this increase did not reach statistical significance (Figure 4b). Subsequently, we knocked down METTL3, WTAP and FTO in the four GBM low-passage invasive region-derived cell lines (GIN5, GIN8, GIN28 and GIN40) to assess SOX2 expression. Upon knockdown of METTL3 and WTAP, signification downregulation in the expression of SOX2 was found in GIN8, GIN28 and GIN40 cells. (Figure 4c(i),c(ii)). In contrast, upon FTO knockdown, only one cell line, GIN40, showed a significant decrease in SOX2 expression (Figure 4c(iii)).
Next, by using a sphere formation assay and the same GBM patient-derived cell lines, we assessed whether disruption of writer effectors modified the cells’ self-renewal capacity. We found that depletion of METTL3 and WTAP significantly reduced the ability of GIN8 and GIN5 cells to form neurospheres (Figure 4d(i),d(ii)). In addition, knockdown of FTO reduced the ability of GIN8 and GIN40 cells to form spheroids compared with the non-targeting scramble siRNA (Figure 4d(iii)). Likewise, when assessing the effect of knockdown of METTL3, WTAP and FTO using siRNA on cell invasion behaviour in GIN8, GIN28 and GIN40 cells, we observed significantly reduced invasion (Figure 5a,b). Collectively, these results suggest that m6A effector machinery is critically required for GBM cell self-renewal and invasion behaviour.
Figure 5. m6A effector proteins regulate cellular invasive behaviour and contribute to the sensitivity of patient-derived invasive GBM cells to temozolomide. (a) Representative images of the invasion behaviour assay in GIN8, GIN28 and GIN40 GBM cells of the control and after siRNA-mediated knockdown of METTL3, WTAP and FTO. Scale bar, 100 µM. (b) Plots presenting the quantification of the cell invasion assay. (c) Viability analysis of (c(i)) GIN5, (c(ii)) GIN8, (c(iii)) GIN28 and (c(iv)) GIN40 treated with a combined regime of temozolomide and siRNA against METTL3, WTAP and FTO compared to temozolomide only. Error bars represent the standard deviation across three independent replicates. * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001.

2.5. Impaired Function of m6A Effectors Improves Temozolomide (TMZ) Sensitivity in GIN Cells

Temozolomide, a drug that targets tumour cell growth through DNA methylation mechanisms, is used to treat brain tumours such as glioblastoma to improve patient survival. We aimed to assess whether m6A effector proteins may be contributing to temozolomide efficacy and resistance in GBM cells. Functional depletion of METTL3, WTAP and FTO was found to improve the sensitivity of GIN5 and GIN40 cells to low doses of temozolomide (Figure 5c(i),c(iv)). Further, siRNA-mediated knockdown of WTAP and FTO significantly reduced the viability of GIN8 cells compared to temozolomide-only-treated cells (Figure 5c(ii)). However, no significant change was observed in GIN28 cells (Figure 5c(iii)) upon silencing, whereas knockdown of METTL3, WTAP and FTO improved temozolomide efficacy in affecting cell viability (Figure 5c(iv)). This finding may be attributed to the genotypic heterogeneity of GBMs. These results suggest that silencing of m6A effector proteins METLL3, WTAP and FTO increases the sensitivity of invasive region GBM cells to the beneficial effect of temozolomide.

3. Discussion

Recent studies have implicated m6A RNA modification machinery to be involved in the progression of different types of cancer [19,22,23]. However, our understanding of the mechanisms by which m6A writer complex and demethylation proteins may influence adult glioblastoma phenotypes remains limited. Here, we aimed to identify the clinical relevance and functional consequences of three m6A effectors, METTL3, WTAP and FTO, in GBM primary tumour tissue and patient-derived cell lines by examining m6A modification profiles, transcriptomic expression, invasive capability and chemotherapeutic sensitivity. Of importance, we first noted that elevated WTAP and FTO expression correlated with poor adult patient survival, providing evidence that regulation of m6A effector proteins is involved in GBM prognosis.
We, and others, have previously observed phenotypic and genotypic variation within different GBM tumour regions [21]. For example, tumour core regions display high cellularity and vascularity, while the invasive area consists of neurons and other non-neoplastic cells [24]. The majority of the core region is removed during surgical resection, while the invasive region that penetrates the brain parenchyma is left behind and can gives rise to tumour recurrence.
Interestingly, gene expression of m6A effector proteins was significantly higher in cell cultures derived from the invasive region of GBM specimens compared with the core of the tumour. This finding is consistent with previous studies [18,19,25] which report that the expression of WTAP, FTO and METTL3 is are significantly higher in GBM cell lines compared to control non-cancer cells. However, we also observed that m6A effector proteins either remained unchanged (METTL3 and WTAP) or were significantly downregulated, e.g., FTO, in cells derived from LGG, suggesting that the m6A machinery could play distinct roles in tumours of different grades or with phenotypic properties. Upon direct assessment of the different subregions of GBM tumour tissue, however, we did not find significant differences in METTL3, WTAP and FTO transcript or protein expression. These inconsistencies may be due to the high degree of inter- and intra- tumour heterogeneity and heterogeneous cellular composition and highlight the complexities of comparing molecular differences between primary tumour subregions with cells derived from different tumour regions.
Nevertheless, quantification of m6A-modified RNA abundance also demonstrated a higher abundance of m6A-RNAs in the invasive and rim regions compared to both the tumour core and non-tumour tissue, as well in patient-derived cell lines from invasive tumour regions. m6A modification has been commonly reported to be dynamically regulated in response to environmental cues [26]. The invasive region of GBM tumours is subjected to microenvironmental stressors, such as hypoxia, metabolic changes and extracellular matrix interactions [27,28,29,30]. This may be one explanation as to why modified m6A-RNAs are more abundant in the invasive region, even if the total expression of METTL3, WTAP, and FTO remain unchanged. Furthermore, as rRNA is m6A-modified and highly abundant in cells, it is likely that the increase in m6A-modifed RNA in tumour invasive regions may be due to changes in rRNA. Indeed, METTL5, a methyltransferase which installs m6A onto rRNA, is reported to contribute to different forms cancer such as gastric, breast and liver cancers [31,32,33]. Further studies using high-throughput m6A-RNA-sequencing or ONT native RNA-sequencing approaches to comprehensively profile differences in modification sites and abundance on mRNA and rRNA across different GBM subregions of tumour tissue will provide insight into why there are discrepancies in findings and will further our understanding of molecular pathways which are region- or cell-specifically m6A-RNA-governed.
Given the potential role of m6A RNA modification in stemness [17,34] and tumorigenesis in GSC [20], we examined markers of stem cell pluripotency and the effects on the expression and transcription of m6A abundance when depleting m6A effector proteins. The transcription factor SOX2 is critically important in the development of the brain and implicated in the self-renewal and propagating potential of GBM [35,36]. We found that the SOX2 transcript was enriched for m6A modification in patient-derived cell lines from invasive regions of tumours, and depletion of METTL3, WTAP and FTO resulted in a reduction in m6A abundance on SOX2 and in the expression of SOX2 in invasive cells. These results are consistent with reports of m6A-RNA modification of SOX2 in neurospheres derived from the U87-GBM-1 glioblastoma cell line [31].
The mechanisms which may underlie these SOX2 changes, and indeed may directly influence the processing of other transcripts and proteins, may be centred around transcriptional control, e.g., modification status on splicing or the regulation of protein synthesis or protein degradation. For example, METTL3 is reported to promote breast cancer progression by catalysing m6A modification on SOX2 mRNA, thereby stabilizing the transcript and preventing degradation [37]. Alternatively, METTL3 is also indicated to enhance mRNA translation though a process whereby METTL3 interacts with eIF3h, a translation initiation factor, to promote mRNA circularization, facilitating efficient translation and oncogenesis in lung cancer cells [38]. Changes in m6A methylation status acting upon co-transcriptional feedback loops involving local antisense, long intergenic non-coding RNAs have also been indicated to be relevant to cell proliferation. For instance, the transcription factor FOXM1 is m6A-demethylated by ALKBH5, which increases FOXM1 expression. However, this process is facilitated by the action of an overlapping antisense long intergenic non-coding RNA to FOXM1, known as ‘FOXM1-AS’, and knocking down ALKBH5 or FOXM1-AS disrupts GSC oncogenesis [17]. Of note, a long non-coding interacting RNA which overlaps with SOX2, known as SOX2 Overlapping Transcript (SOX2 OT), is transcribed in the same direction as SOX2 and shows a transcriptional regulatory relationship, namely when one is transcribed, it actively inhibits the expression of the other [39]. As SOX2 OT has also been suggested as a modulator of cell proliferation in forms of cancer [40,41], it is therefore possible that SOX2 OT, similar to the ALKBH5/FOXM1-AS mechanism, has a role in an m6A-regulated transcriptional feedback loop in GBM tumorigenesis.
A limitation of this study, as is a limitation of many studies that have, to date, investigated RNA modifications and their role in malignant cancers, is that it focuses on a few effector proteins and specific transcripts or pre-selected biologically relevant or known oncogenic processes. However, individual m6A effector proteins are involved in many cellular functions which may be cell sub-compartment- or nanodomain-dependent. For example, by examining global mass spectrometry proteomic data generated after biological perturbation in cell culture [42] to identify proteins which change in abundance with effector proteins, we discovered that proteins that are co-regulated with WTAP are enriched for involvement in spliceosome regulation, mRNA export from nucleus, co-translational protein targeting, mRNA surveillance and ubiquitination/phosphorylation [43]. METTL 3-co-regulated protein processes showed some overlap in biological function such as spliceosome regulation and phosphorylation, but some enriched processes differed from those of WTAP, such as acetylation and cell-to-cell adhesion. Similarly, FTO had enriched co-regulatory processes of acetylation and phosphorylation and the regulation of splicing, common to WTAP or METLL3, but also DNA repair, chromatin remodelling and cell division. Furthermore, it has been found that m6A and a second mRNA modification system, m5C, showed global cross-regulatory and functional interactions, a finding also indicated by two studies which examined changes in effector protein gene expression as a means of predicting cancer prognosis [44,45]. Such regulatory cross-talk across RNA modification systems adds further complexity to how changes in effector protein abundance or location, or indeed RNA methylation abundance, may be inducing pathological processes. Further mechanistic work is clearly warranted including novel methods to dissect RNA methylation co-regulated pathways which may act as a switch driving tumorigenesis.
GBM is one of the most malignant brain tumours against which chemotherapies, including the drug temozolomide, are commonly limited in effectiveness [46]. Therefore, one concerted goal in GBM research is to develop new effective therapeutic approaches. In the current study, we found that depletion of METTL3, WTAP and FTO improved the sensitivity of invasive glioblastoma cells to low doses of temozolomide, whereas combined treatment of depletion of WTAP and FTO and TMZ significantly reduced glioblastoma cell viability. Our findings are consistent with reports using alternative methods; for example, knockdown of METTL3 reduced self-renewal, proliferation and TMZ resistance in GSCs [19]. Furthermore, novel small molecules or repurposing drugs which activate, inhibit or interact with m6A effector proteins with high specificity have recently shown some success in cancer cells. For example, inhibitors of FTO, MA2 [20] and Diacerein [47] have shown beneficial effects of suppressing tumour progression in GSC-grafted mice and breast cancer tumour-grafted mice, respectively. Likewise, STM2457, a catalytic inhibitor of METTL3, leads to reduced AML growth and an increase in differentiation and apoptosis [48]. These findings bring promise that small-molecule compounds which target m6A effector processes may have significant tumour suppressor properties, which will represent an advanced step in GBM therapy.

4. Materials and Methods

4.1. Human Tissues and Derived Primary Cell Culture

Glioma brain tumour specimens were taken from adult patients who underwent craniotomy, whereas control brain tissues were taken from epileptic patients undergoing functional resections. Tumour specimens were collected at the UK East Midlands Regional Neurosurgical Centre during standard neurosurgical tumour resection procedures under the approval of the Nottingham REC ethics application 11/EM/0076. The specimens were either immediately frozen for the purpose of RNA extraction and subsequent molecular analysis or fixed and embedded in paraffin for immunohistochemistry analysis. Primary cells used in this study were derived from fresh surgical specimens of LGG (WHO grade 2 astrocytoma) and GBM, which were from either peripheral invasive and core regions, as defined by image guidance intra-operatively. The characteristics of these cells, including their genotype for known pathological variants within the gene isocitrate dehydrogenase (NADP(+)) 1 (IDH1), are presented in Supplementary Table S1. The cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% foetal bovine serum at 370C in 5% CO2. Human primary astrocytes from the cerebral cortex were obtained from Sciencell (Human astrocytes; catalog number 1800) and maintained according to the manufacturer’s instructions. All cells were routinely tested for mycoplasma contamination.

4.2. siRNA-Mediated Knockdown of Effector Proteins

Functional depletion of METTL3, WTAP and FTO in glioblastoma cells was achieved using ON-TARGETplus siRNA SMARTpool against METTL3, WTAP and FTO. The ON-TARGETplus non-targeting siRNA was used as a negative control. The reagents were prepared and the transfection was performed according to the manufacturer’s instructions (Horizon Discovery, Cambridge, UK). Transfection was performed using Lipofectamine RNAiMAX (Invitrogen, Life Technologies, Carlsbad, CA, USA).

4.3. RNA Isolation and Gene Expression Analysis

RNA was isolated from brain tumour cells using the mirVana miRNA Isolation Kit (ambion, Life Technologies) with on-column DNase treatment. The yield and purity were assessed using nanodrops. Reverse transcription was carried out using RevertAid Reverse Transcriptase (Thermo Scientific, Waltham, MA, USA) following the manufacturer’s instructions. Real-time quantitative polymerase chain reaction (RTqPCR) was conducted to validate the relative expression of specific mRNAs using CFX384 Touch Real-Time PCR Detection System (BIO-RAD). The Livak method (2−∆∆Ct) was used to analyse qPCR data [49]. Supplementary Table S2 presents the sequences of the primers used in this study.

4.4. Methylated RNA Immunoprecipitation–Quantitative Polymerase Chain Reaction

The MeRIPqPCR assay was adapted from a published protocol [50]. Briefly, RNA samples were incubated with anti-m6A antibody (Abcam, Cambridge, UK) in 1ml buffer containing RNasin Plus RNase inhibitor (Promega, Madison, WI, USA) and Ribonucleoside vanadyl complexes (Merck, Darmstadt, Germany) for 2 h at 4 °C. Recombinant protein A bead slurry was washed, added to the previous mixture and incubated for 2 h at 4 °C in a head-over-tail rotator. m6A RNA was eluted with an elution buffer containing N6-methyladenosine 5′-monophosphate sodium salt at 4 °C for an hour with continuous shaking. m6A RNA was precipitated with glycogen and one-tenth volumes of 3 M sodium acetate in 2.5 volumes of 100% ethanol at −80 °C overnight. m6A enrichment was assessed by RTqPCR analysis.

4.5. Immunohistochemistry

Immunohistochemistry was performed as described in [21]. To removal paraffin wax, the slides were placed in Xylene for 15 min, followed by absolute ethanol for 10 min and 95% ethanol for 10 min, and then washed. The samples were placed in a microwave with sodium citrate buffer (pH 6) for 20 min at 90 °C. Slides were subsequently washed with phosphate-buffered solution (PBS) for 2 min. Peroxidase blocking solution was applied for 5 min. Primary antibodies were applied after dilution in antibody diluent (Supplementary Table S3) and incubated overnight at 4 °C. A secondary antibody (DAKO) was applied to cover the specimen and incubated at room temperature for 30 min. The substrate–chromogen solution (DAB) was applied to cover the specimen and incubated for 5 min. Harris haematoxylin was used as a nuclear counterstain. Slides were placed in Lithium carbonate, then dehydrated and mounted with DePeX medium. Light microscopy was used to acquire the images. Three representative images were taken per slide and image analysis quantification was performed using ImageJ 1.45.

4.6. Immunofluorescence

Cells were seeded in 8-well chamber slides (ibidi, Gräfelfing, Germany) and fixed with 4% paraformaldehyde for 10 min before washing three times with PBS, permeabilized with 0.1% Triton-X-100 for 10 min and incubated with 5% bovine serum albumin for an hour at room temperature. Primary antibodies were prepared and diluted following the manufacturer’s recommendations (Table S2). Cells were incubated with primary antibodies overnight at 4 °C. After washing, Alexa-fluor-conjugated secondary antibodies (Invitrogen) were diluted 1:300 in 5% bovine serum albumin for an hour at room temperature. Phalloidin was added to the cells for an hour at room temperature. Dapi (Thermo Scientific) was used to counterstain nuclei, and the slides were mounted with Fluoromount aqueous mounting medium (Merck). The images were acquired using the Leica TCS SPE confocal microscope (Leica, Wetzlar, Germany) equipped with LAS X software (4.7.0) using ×63 oil immersion objective and were analysed with ImageJ.

4.7. Sphere Formation Assay

Cells were resuspended in neurosphere medium comprising Dulbecco’s Modified Eagle Medium/F12 supplemented with L-glutamine, B27 (Gibco, Waltham, MA, USA), N2 (Gibco), heparin (2 µg/mL, Stem Cell Technologies, Vancouver, BC, Canada), epidermal growth factor (20 ng/mL, Gibco) and fibroblast growth factor (10 ng/mL, Gibco). Cells were seeded in ultra-low-attachment 96-well plates (Corning Incorporated, Corning, NY, USA) and spheroids were allowed to grow for 4 days in a humidified incubator at 37 °C and 5% CO2. ImageJ was used to measure the size of spheroids.

4.8. Invasion and Viability Assays

Thincert cell culture inserts for 24 well plates (Greiner, Kremsmunster, Austria) were coated with 30 µg of mouse collagen IV (bio-techne R&D systems, Minneapolis, MN, USA) and left in a shaker incubator at 37 °C overnight. Coated inserts were soaked in 100 µL serum-free Dulbecco’s Modified Eagle Medium for an hour. Cells were resuspended in serum-free medium and 200 µL of cell suspension was added to each insert. Dulbecco’s Modified Eagle Medium supplemented with 10% foetal bovine serum was added to the lower chamber of the inserts and the cells were allowed to invade for 3 days. Invaded cells were fixed with methanol for an hour at room temperature and stained with 0.2% crystal violet. Cells were imaged using the Nikon ECLIPSE Ti2 microscope (Nikon Corporation, Tokyo, Japan). Four images were taken per insert, and they were manually analysed.

4.9. Viability Assay

For the viability and TMZ assay, cells were seeded into 96-well plates in medium supplemented with 10% foetal bovine serum. On day 2, siRNA-mediated knockdown of METTL3, WTAP or FTO was performed using Lipofectamine RNAiMAX (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. On day 4, cells were treated with 0–400 μM temozolomide (Thermo Fisher Scientific) for 24 h. Cell viability was measured using the PrestoBlue Cell Viability Reagent (Invitrogen, Thermo Fisher Scientific, Carlsbad, CA, USA) following the manufacturer’s protocol. Fluorescence was detected with a microplate reader and viability was normalized to untreated controls.

4.10. Statistical Analysis

Statistical analyses were performed using the two-tailed Student’s t test and values are represented as either the means ± standard deviation or the means ± standard error, as indicated in each experiment. Statistical significance was set at p ≤ 0.05. Figures were generated using GraphPad Prism 9.4.1. Kaplan–Meier survival curves were generated using R2 genomic analysis and visualization platform.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/ijms27041967/s1.

Author Contributions

M.R. designed and performed the experiments, analysed data and wrote the original draft. J.R. designed and performed the experiments, analysed data and contributed to reviewing of the manuscript. L.W. and S.D. designed and performed the experiments and contributed to reviewing the manuscript. H.M.K. contributed to the supervision, reviewing and editing of the manuscript. S.S. contributed to funding acquisition, supervision, reviewing and editing the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by funds gifted by the Stoneygate Trust.

Institutional Review Board Statement

This study was performed under the approval of East Midlands NRES 2 11/EM/0076 (12/August/2025). This study was performed in accordance with the Declaration of Helsinki.

Data Availability Statement

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors gratefully acknowledge the financial support of the Stoneygate Foundation.

Conflicts of Interest

The authors have no relevant financial or non-financial interests to disclose.

Abbreviations

ALKBH5AlkB Homolog 5
DMEMDulbecco’s Modified Eagle Medium
eIF3hEukaryotic Translation Initiation Factor 3 Subunit H
FOXM1Forkhead Box M1
FOXM1-ASFOXM1 anti sense
FTOFat Mass and Obesity-Associated Protein
GBMGlioblastoma Multiforme
HAKAIE3 Ubiquitin Ligase CBLL1
IDH1Isocitrate Dehydrogenase 1
IHCImmunohistochemistry
KIAA1429Also known as VIRMA (Vir-Like M6A Methyltransferase Associated)
LGGLower-Grade Glioma
LncrsLong non-coding RNAs
m6AN6-methyladenosine
MeRIPqPCRMethylated RNA Immunoprecipitation Quantitative PCR
METTL14Methyltransferase 14
METTL16Methyltransferase 16
METTL3Methyltransferase 3
mRNAMessenger RNA
mtRNAMitochondrial RNA
NESNestin
PBSPhosphate-Buffered Saline
RBM15RNA-Binding Motif Protein 15
RNARibonucleic Acid
RTqPCRReverse Transcription Quantitative Polymerase Chain Reaction
siRNASmall Interfering RNA
SOX2SRY-Box Transcription Factor 2
SOX2-OTSOX2 overlapping transcript
TCGAThe Cancer Genome Atlas
TMZTemozolomide
WHOWorld Health Organization
WTAPWT1-associating protein
ZC3H13Zinc Finger CCCH-Type Containing 13

References

  1. Ostrom, Q.T.; Gittleman, H.; de Blank, P.M.; Finlay, J.L.; Gurney, J.G.; McKean-Cowdin, R.; Stearns, D.S.; Wolff, J.E.; Liu, M.; Wolinsky, Y.; et al. Adolescent and young adult primary brain and central nervous system tumors diagnosed in the United States in 2008–2012. Neuro Oncol. 2015, 18, i1–i50. [Google Scholar] [CrossRef] [Scilit]
  2. Omuro, A.; DeAngelis, L.M. Glioblastoma and other malignant gliomas: A clinical review. JAMA 2013, 310, 1842–1850. [Google Scholar] [CrossRef] [Scilit]
  3. Silver, A.; Feier, D.; Ghosh, T.; Rahman, M.; Huang, J.; Sarkisian, M.R.; Deleyrolle, L.P. Heterogeneity of glioblastoma stem cells in the context of the immune microenvironment and geospatial organization. Front. Oncol. 2022, 12, 1022716. [Google Scholar] [CrossRef] [Scilit]
  4. Desrosiers, R.; Friderici, K.; Rottman, F. Identification of methylated nucleosides in messenger RNA from Novikoff hepatoma cells. Proc. Natl. Acad. Sci. USA 1974, 71, 3971–3975. [Google Scholar] [CrossRef] [Scilit]
  5. Dominissini, D.; Moshitch-Moshkovitz, S.; Schwartz, S.; Salmon-Divon, M.; Ungar, L.; Osenberg, S.; Cesarkas, K.; Jacob-Hirsch, J.; Amariglio, N.; Kupiec, M.; et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 2012, 485, 201–206. [Google Scholar] [CrossRef] [Scilit]
  6. Liu, J.; Yue, Y.; Han, D.; Wang, X.; Fu, Y.; Zhang, L.; Jia, G.; Yu, M.; Lu, Z.; Deng, X.; et al. A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat. Chem. Biol. 2014, 10, 93–95. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  7. Nishikura, K. A-to-I editing of coding and non-coding RNAs by ADARs. Nat. Rev. Mol. Cell Biol. 2016, 17, 83–96. [Google Scholar] [CrossRef] [Scilit]
  8. Scholler, E.; Weichmann, F.; Treiber, T.; Ringle, S.; Treiber, N.; Flatley, A.; Feederle, R.; Bruckmann, A.; Meister, G. Interactions, localization, and phosphorylation of the m(6)A generating METTL3-METTL14-WTAP complex. RNA 2018, 24, 499–512. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  9. Jia, G.; Fu, Y.; Zhao, X.; Dai, Q.; Zheng, G.; Yang, Y.; Yi, C.; Lindahl, T.; Pan, T.; Yang, Y.-G.; et al. N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat. Chem. Biol. 2011, 7, 885–887, Erratum in Nat. Chem. Biol. 2012, 8, 1008. [Google Scholar] [CrossRef] [Scilit]
  10. Zheng, G.; Dahl, J.A.; Niu, Y.; Fedorcsak, P.; Huang, C.M.; Li, C.J.; Vågbø, C.B.; Shi, Y.; Wang, W.-L.; Song, S.-H.; et al. ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol. Cell 2013, 49, 18–29. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  11. Liu, N.; Zhou, K.I.; Parisien, M.; Dai, Q.; Diatchenko, L.; Pan, T. N6-methyladenosine alters RNA structure to regulate binding of a low-complexity protein. Nucleic Acids Res. 2017, 45, 6051–6063. [Google Scholar] [CrossRef] [Scilit]
  12. Liu, N. N6-Methyladenosine-Dependent RNA Structural Switches Modulate RNA-Protein Interactions. Ph.D. Thesis, University of Chicago, Chicago, IL, USA, 2015. [Google Scholar]
  13. Roundtree, I.A.; Luo, G.-Z.; Zhang, Z.; Wang, X.; Zhou, T.; Cui, Y.; Sha, J.; Huang, X.; Guerrero, L.; Xie, P.; et al. YTHDC1 mediates nuclear export of N6-methyladenosine methylated mRNAs. eLife 2017, 6, e31311. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  14. Du, H.; Zhao, Y.; He, J.; Zhang, Y.; Xi, H.; Liu, M.; Ma, J.; Wu, L. YTHDF2 destabilizes m6A-containing RNA through direct recruitment of the CCR4-NOT deadenylase complex. Nat. Commun. 2016, 7, 12626. [Google Scholar] [CrossRef] [Scilit]
  15. Shi, H.; Wang, X.; Lu, Z.; Zhao, B.S.; Ma, H.; Hsu, P.J.; Liu, C.; He, C. YTHDF3 facilitates translation and decay of N(6)-methyladenosine-modified RNA. Cell Res. 2017, 27, 315–328. [Google Scholar] [CrossRef] [Scilit]
  16. Su, R.; Dong, L.; Li, C.; Nachtergaele, S.; Wunderlich, M.; Qing, Y.; Deng, X.; Wang, Y.; Weng, X.; Hu, C.; et al. R-2HG Exhibits Anti-tumor Activity by Targeting FTO/m(6)A/MYC/CEBPA Signaling. Cell 2018, 172, 90–105 e23. [Google Scholar] [CrossRef] [Scilit]
  17. Zhang, S.; Zhao, B.S.; Zhou, A.; Lin, K.; Zheng, S.; Lu, Z.; Chen, Y.; Sulman, E.P.; Xie, K.; Bögler, O.; et al. m(6)A Demethylase ALKBH5 Maintains Tumorigenicity of Glioblastoma Stem-like Cells by Sustaining FOXM1 Expression and Cell Proliferation Program. Cancer Cell 2017, 31, 591–606 e6. [Google Scholar] [CrossRef] [Scilit]
  18. Jin, D.I.; Lee, S.W.; Han, M.E.; Kim, H.J.; Seo, S.A.; Hur, G.Y.; Jung, S.; Kim, B.; Oh, S. Expression and roles of Wilms’ tumor 1-associating protein in glioblastoma. Cancer Sci. 2012, 103, 2102–2109. [Google Scholar] [CrossRef] [Scilit]
  19. Shi, J.; Zhang, P.; Dong, X.; Yuan, J.; Li, Y.; Li, S.; Cheng, S.; Ping, Y.; Dai, X.; Dong, J. METTL3 knockdown promotes temozolomide sensitivity of glioma stem cells via decreasing MGMT and APNG mRNA stability. Cell Death Discov. 2023, 9, 22. [Google Scholar] [CrossRef] [Scilit]
  20. Cui, Q.; Shi, H.; Ye, P.; Li, L.; Qu, Q.; Sun, G.; Sun, G.; Lu, Z.; Huang, Y.; Yang, C.-G.; et al. m(6)A RNA Methylation Regulates the Self-Renewal and Tumorigenesis of Glioblastoma Stem Cells. Cell Rep. 2017, 18, 2622–2634. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  21. Smith, S.J.; Diksin, M.; Chhaya, S.; Sairam, S.; Estevez-Cebrero, M.A.; Rahman, R. The Invasive Region of Glioblastoma Defined by 5ALA Guided Surgery Has an Altered Cancer Stem Cell Marker Profile Compared to Central Tumour. Int. J. Mol. Sci. 2017, 18, 2452. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  22. Sharma, A.; Wang, Y.; Ge, F.; Chen, P.; Dakal, T.C.; Carro, M.S.; Schmidt-Wolf, I.G.H.; Maciaczyk, J. Systematic integration of m6A regulators and autophagy-related genes in combination with long non-coding RNAs predicts survival in glioblastoma multiforme. Sci. Rep. 2023, 13, 17232. [Google Scholar] [CrossRef] [Scilit]
  23. Deng, X.; Sun, X.; Hu, Z.; Wu, Y.; Zhou, C.; Sun, J.; Gao, X.; Huang, Y. Exploring the role of m6A methylation regulators in glioblastoma multiforme and their impact on the tumor immune microenvironment. FASEB J. 2023, 37, e23155. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  24. Gill, B.J.; Pisapia, D.J.; Malone, H.R.; Goldstein, H.; Lei, L.; Sonabend, A.; Yun, J.; Samanamud, J.; Sims, J.S.; Banu, M.; et al. MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma. Proc. Natl. Acad. Sci. USA 2014, 111, 12550–12555. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  25. Li, F.; Yi, Y.; Miao, Y.; Long, W.; Long, T.; Chen, S.; Cheng, W.; Zou, C.; Zheng, Y.; Wu, X.; et al. N(6)-Methyladenosine Modulates Nonsense-Mediated mRNA Decay in Human Glioblastoma. Cancer Res. 2019, 79, 5785–5798. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  26. Zhou, J.; Wan, J.; Gao, X.; Zhang, X.; Jaffrey, S.R.; Qian, S.B. Dynamic m(6)A mRNA methylation directs translational control of heat shock response. Nature 2015, 526, 591–594. [Google Scholar] [CrossRef] [Scilit]
  27. Bilston, L.E. Soft tissue rheology and its implications for elastography: Challenges and opportunities. NMR Biomed. 2017, 31, e3832. [Google Scholar] [CrossRef] [Scilit]
  28. Gatenby, R.A.; Gawlinski, E.T.; Gmitro, A.F.; Kaylor, B.; Gillies, R.J. Acid-mediated tumor invasion: A multidisciplinary study. Cancer Res. 2006, 66, 5216–5223. [Google Scholar] [CrossRef] [Scilit]
  29. Colwell, N.; Larion, M.; Giles, A.J.; Seldomridge, A.N.; Sizdahkhani, S.; Gilbert, M.R.; Park, D.M. Hypoxia in the glioblastoma microenvironment: Shaping the phenotype of cancer stem-like cells. Neuro Oncol. 2017, 19, 887–896. [Google Scholar] [CrossRef] [Scilit]
  30. Semenza, G.L. Hypoxia-inducible factors in physiology and medicine. Cell 2012, 148, 399–408. [Google Scholar] [CrossRef] [Scilit]
  31. Xia, P.; Zhang, H.; Lu, H.; Xu, K.; Jiang, X.; Jiang, Y.; Gongye, X.; Chen, Z.; Liu, J.; Chen, X.; et al. METTL5 stabilizes c-Myc by facilitating USP5 translation to reprogram glucose metabolism and promote hepatocellular carcinoma progression. Cancer Commun. 2023, 43, 338–364. [Google Scholar] [CrossRef] [Scilit]
  32. Wang, Z.; Liu, J.; Yang, Y.; Xing, C.; Jing, J.; Yuan, Y. Expression and prognostic potential of ribosome 18S RNA m6A methyltransferase METTL5 in gastric cancer. Cancer Cell Int. 2021, 21, 569. [Google Scholar] [CrossRef] [Scilit]
  33. Rong, B.; Zhang, Q.; Wan, J.; Xing, S.; Dai, R.; Li, Y.; Cai, J.; Xie, J.; Song, Y.; Chen, J.; et al. Ribosome 18S m6A methyltransferase METTL5 promotes translation initiation and breast cancer cell growth. Cell Rep. 2020, 33, 108498. [Google Scholar] [CrossRef] [Scilit]
  34. Visvanathan, A.; Patil, V.; Arora, A.; Hegde, A.S.; Arivazhagan, A.; Santosh, V.; Somasundaram, K. Essential role of METTL3-mediated m(6)A modification in glioma stem-like cells maintenance and radioresistance. Oncogene 2018, 37, 522–533. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  35. Pagin, M.; Pernebrink, M.; Giubbolini, S.; Barone, C.; Sambruni, G.; Zhu, Y.; Chiara, M.; Ottolenghi, S.; Pavesi, G.; Wei, C.-L.; et al. Sox2 controls neural stem cell self-renewal through a Fos-centered gene regulatory network. Stem Cells 2021, 39, 1107–1119. [Google Scholar] [CrossRef] [Scilit]
  36. Lopez-Bertoni, H.; Johnson, A.; Rui, Y.; Lal, B.; Sall, S.; Malloy, M.; Coulter, J.B.; Lugo-Fagundo, M.; Shudir, S.; Khela, H.; et al. Sox2 induces glioblastoma cell stemness and tumor propagation by repressing TET2 and deregulating 5hmC and 5mC DNA modifications. Signal Transduct. Target. Ther. 2022, 7, 37. [Google Scholar] [CrossRef] [Scilit]
  37. Xie, J.; Ba, J.; Zhang, M.; Wan, Y.; Jin, Z.; Yao, Y. The m6A methyltransferase METTL3 promotes the stemness and malignant progression of breast cancer by mediating m6A modification on SOX2. J. BUON 2021, 26, 444–449. [Google Scholar]
  38. Choe, J.; Lin, S.; Zhang, W.; Liu, Q.; Wang, L.; Ramirez-Moya, J.; Du, P.; Kim, W.; Tang, S.; Sliz, P.; et al. mRNA circularization by METTL3-eIF3h enhances translation and promotes oncogenesis. Nature 2018, 561, 556–560. [Google Scholar] [CrossRef] [Scilit]
  39. Messemaker, T.C.; van Leeuwen, S.M.; van den Berg, P.R.; ’t Jong, A.E.J.; Palstra, R.J.; Hoeben, R.C.; Semrau, S.; Mikkers, H.M.M. Allele-specific repression of Sox2 through the long non-coding RNA Sox2ot. Sci. Rep. 2018, 8, 386. [Google Scholar] [CrossRef] [Scilit]
  40. Wang, Z.; Tan, M.; Chen, G.; Li, Z.; Lu, X. LncRNA SOX2-OT is a novel prognostic biomarker for osteosarcoma patients and regulates osteosarcoma cells proliferation and motility through modulating SOX2. IUBMB Life 2017, 69, 867–876. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  41. Wei, C.X.; Wong, H.; Xu, F.; Liu, Z.; Ran, L.; Jiang, R.D. IRF4-induced upregulation of lncRNA SOX2-OT promotes cell proliferation and metastasis in cholangiocarcinoma by regulating SOX2 and PI3K/AKT signaling. Eur. Rev. Med. Pharmacol. Sci. 2018, 22, 8169–8178. [Google Scholar] [PubMed]
  42. Kustatscher, G.; Grabowski, P.; Schrader, T.A.; Passmore, J.B.; Schrader, M.; Rappsilber, J. Co-regulation map of the human proteome enables identification of protein functions. Nat. Biotechnol. 2019, 37, 1361–1371. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  43. Orji, O.C.; Stones, J.; Rajani, S.; Markus, R.; Öz, M.D.; Knight, H.M. Global Co-regulatory Cross Talk Between m6A and m5C RNA Methylation Systems Coordinate Cellular Responses and Brain Disease Pathways. Mol. Neurobiol. 2025, 62, 5006–5021. [Google Scholar] [CrossRef] [Scilit] [PubMed] [PubMed Central]
  44. Chen, H.; Yao, J.; Bao, R.; Dong, Y.; Zhang, T.; Du, Y.; Wang, G.; Ni, D.; Xun, Z.; Niu, X.; et al. Cross-talk of four types of RNA modification writers defines tumor microenvironment and pharmacogenomic landscape in colorectal cancer. Mol Cancer 2021, 20, 29. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  45. Qi, L.; Zhang, W.; Ren, X.; Xu, R.; Yang, Z.; Chen, R.; Tu, C.; Li, Z. Cross-Talk of Multiple Types of RNA Modification Regulators Uncovers the Tumor Microenvironment and Immune Infiltrates in Soft Tissue Sarcoma. Front. Immunol. 2022, 3, 921223. [Google Scholar] [CrossRef] [Scilit]
  46. Stupp, R.; Mason, W.P.; van den Bent, M.J.; Weller, M.; Fisher, B.; Taphoorn, M.J.B.; Belanger, K.; Brandes, A.A.; Marosi, C.; Bogdahn, U.; et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N. Engl. J. Med. 2005, 352, 987–996. [Google Scholar] [CrossRef] [Scilit]
  47. Bharti, R.; Dey, G.; Ojha, P.K.; Rajput, S.; Jaganathan, S.K.; Sen, R.; Mandal, M. Diacerein-mediated inhibition of IL-6/IL-6R signaling induces apoptotic effects on breast cancer. Oncogene 2016, 35, 3965–3975. [Google Scholar] [CrossRef] [Scilit]
  48. Yankova, E.; Blackaby, W.; Albertella, M.; Rak, J.; De Braekeleer, E.; Tsagkogeorga, G.; Pilka, E.S.; Aspris, D.; Leggate, D.; Hendrick, A.G.; et al. Small-molecule inhibition of METTL3 as a strategy against myeloid leukaemia. Nature 2021, 593, 597–601. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  49. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [Scilit]
  50. Dominissini, D.; Moshitch-Moshkovitz, S.; Salmon-Divon, M.; Amariglio, N.; Rechavi, G. Transcriptome-wide mapping of N(6)-methyladenosine by m(6)A-seq based on immunocapturing and massively parallel sequencing. Nat. Protoc. 2013, 8, 176–189. [Google Scholar] [CrossRef] [Scilit]
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