hnRNPC Promotes Oral Squamous Cell Carcinoma Progression via m6A-Dependent Stabilization of BCAT1 to Enhance Branched-Chain Amino Acid Metabolism

hnRNPC Promotes Oral Squamous Cell Carcinoma Progression via m6A-Dependent Stabilization of BCAT1 to Enhance Branched-Chain Amino Acid Metabolism | 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 hnRNPC Promotes Oral Squamous Cell Carcinoma Progression via m6A-Dependent Stabilization of BCAT1 to Enhance Branched-Chain Amino Acid Metabolism Zhixin Zhang, Xiao Gao, Ting Han, Fei Chai, Menghui Gao, Yulin An This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8676944/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 Oral squamous cell carcinoma (OSCC) remains a major cause of cancer-related mortality worldwide, with current treatments limited by chemoresistance and long-term toxicities. N6-methyladenosine (m6A) modification regulates mRNA fate to drive cancer progression. However, how m6A modification regulates OSCC progression remains uncharacterized. In this study, we integrated bioinformatics analysis of The Cancer Genome Atlas (TCGA) datasets and experimental validation to explore the role of heterogeneous nuclear ribonucleoprotein C (hnRNPC), an m6A-related RNA-binding protein, in OSCC. Bioinformatics analysis of 515 HNSCC patients identified hnRNPC as a novel independent prognostic biomarker. High hnRNPC expression correlated with advanced pathological stages, poor overall survival, and served as a risk factor for HNSCC. Functional experiments demonstrated that hnRNPC knockdown in OSCC cell lines inhibited cell proliferation, colony formation, tumorsphere formation, and in vivo tumor growth, while downregulating stemness-related genes (OCT4, SOX2, Nanog). Mechanistically, hnRNPC promoted BCAA metabolism in OSCC. High hnRNPC expression was associated with activated BCAA metabolic pathways, and hnRNPC knockdown reduced BCAA uptake, glutamate levels, oxygen consumption rate (OCR), and glutathione (GSH) levels. Further, hnRNPC stabilized BCAT1 mRNA in an m6A-dependent manner. BCAT1 inhibition via EGR240 enhanced the tumor-suppressive effects of hnRNPC knockdown. Exogenous supplementation of α-ketoglutarate (α-KG) rescued energy deficiency and functional defects in hnRNPC-knockdown OSCC cells. Collectively, our findings identify a novel hnRNPC/m6A/BCAT1/BCAA metabolism axis driving OSCC progression. This axis not only explains hnRNPC’s prognostic value but also provides a potential therapeutic target for improving OSCC treatment outcomes by disrupting tumor-specific metabolic and epigenetic adaptations. Oral squamous cell carcinoma hnRNPC BCAT1 m6A modification Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Oral squamous cell carcinoma (OSCC) is a heterogeneous malignant neoplasm originating from the epithelial tissue of the oral mucosa, which remains one of the leading causes of cancer death worldwide[ 1 ]. It accounts for 90% of all malignant tumors in the oral cavity and serves as the most common subtype of head and neck squamous cell carcinoma (HNSCC) [ 2 , 3 ]. Clinically, drug resistance, significantly reducing the efficacy of traditional chemotherapeutics such as cisplatin, fluorouracil, and paclitaxel[ 4 , 5 ]. Additionally, while high-dose radiotherapy is often combined with drug therapy, it causes acute toxicities that develop into long-term sequelae, further compromising treatment tolerance and patients’ quality of life[ 6 ]. Thus, current OSCC drug-based treatments are far from optimal, calling for more effective and tailored solutions. Branched-chain amino acids (BCAAs, including leucine, isoleucine, and valine) are essential amino acids that require catabolism. Branched-chain amino acid transaminase (BCAT) is the rate-limiting enzyme driving BCAA transamination, a reaction that transfers the amino group of BCAAs (leucine, isoleucine, valine) to α-ketoglutarate (α-KG), generating branched-chain α-ketoacids (BCKAs) and glutamate[ 7 ]. BCKAs enter the TCA cycle to produce ATP for tumor energy needs, while glutamate acts as a key precursor for glutathione (GSH) synthesis: it fuels GSH production (supporting the first rate-limiting step via glutamate-cysteine ligase), scavenges ROS to protect tumors from oxidative stress, and even contributes to chemoresistance [ 8 – 10 ]. This BCAT-mediated metabolism (energy supply via BCKAs, antioxidant defense via glutamate-GSH) is a tumor-specific adaptation, making BCAT1 a potential therapeutic target [ 11 ]. N6-methyladenosine (m6A) modification is the most abundant epigenetic modification in eukaryotic mRNA, which is co-regulated by methyltransferase complexes ("writers"), demethylases ("erasers"), and m6A-binding proteins ("readers") [ 12 , 13 ]. By influencing mRNA splicing, transport, translation, and degradation, it plays a central role in physiological processes such as cell proliferation and differentiation [ 14 ]. Heterogeneous nuclear ribonucleoprotein C (hnRNPC) is a classic RNA-binding protein that mainly recognizes uracil-rich sequences in precursor mRNA (pre-mRNA) to participate in RNA splicing, stability maintenance, and nucleocytoplasmic transport, serving as a key regulatory factor in the RNA metabolic network [ 15 , 16 ]. Previous studies have demonstrated that hnRNPC consistently exerts oncogenic functions. It promotes tumor progression through multiple mechanisms, such as regulating the stability of mRNA or miRNA and mediating alternative splicing, with well-documented roles in glioma, acute myeloid leukemia (AML), breast cancer, and other malignancies [ 17 – 20 ]. However, the function of hnRNPC in OSCC remains largely unknown and requires further in-depth investigation. In this study, we utilized The Cancer Genome Atlas (TCGA) datasets to conduct an integrated bioinformatics analysis, systematically exploring the relationship between m6A modification patterns and OSCC malignancy. Through rigorous screening and functional validation of m6A regulatory proteins involved in OSCC progression, we identified that hnRNPC is highly associated with the prognosis of OSCC, showing a positive correlation with poor clinical outcomes. Mechanistically, our findings revealed that hnRNPC can induce the expression of BCAT1 in an m6A modification-dependent manner. This, in turn, promotes BCAA metabolism in OSCC cells, supporting BCAT1-dependent energy production and the maintenance of redox homeostasis. Collectively, these results suggest that hnRNPC may serve as a potential therapeutic target in OSCC progression and holds significant implications for the diagnosis and prognosis of OSCC. Materials and methods Collection of m6A transcriptome data and expression profiling Transcriptome datasets, comprising 515 head and neck squamous cell carcinoma (HNSCC) samples and 44 normal tissue samples, were retrieved from The Cancer Genome Atlas (TCGA). A total of 23 m6A-associated genes were selected from the dataset based on findings from prior studies [ 15 , 16 ]. Specifically, the cohort GDC TCGA Head and Neck Cancer (HNSC) was retrieved from the UCSC Xena database, and the STAR-FPKM data under the gene expression RNAseq module were downloaded ( https://portal.gdc.cancer.gov ). To visualize gene expression patterns, heatmaps and boxplots were constructed using the ggplot2 and boxplot packages in R. Development of Cox risk regression model Study samples were randomly allocated into a training cohort and a validation cohort at a 3:7 ratio. Univariate and multivariate Cox regression analyses were applied to pinpoint independent prognostic factors for HNSCC patients. The robustness of these factors was further assessed using the validation cohort. Ultimately, three genes—IGF2BP2, hnRNPC, and YTHDC2—were incorporated into the final Cox risk regression model. Cell culture and lentivirus preparation The human HNSCC cell lines CAL-27 and SCC-15 were acquired from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). These cell lines were maintained in Dulbecco's modified Eagle's medium (DMEM) containing 10% fetal bovine serum. For stem cell induction, oral squamous cell carcinoma cells were cultured in DMEM/F12 medium supplemented with basic fibroblast growth factor (bFGF) and epidermal growth factor (EGF). These induced stem cells were grown as tumor spheres in DMEM/F12 medium with 20 ng/ml each of bFGF (#HY-P7331, MedChemExpress) and EGF (#AF-100-15-100, Peprotech). Lentivirus targeting hnRNPC for knockdown was produced by Hanheng Biotechnology (Shanghai, China), with the corresponding shRNA sequences provided in Supplementary Table 1. Subcutaneous tumor xenograft model The nude mice were purchased from CYAGEN company (Suzhou, China). This study was approved by the ethics committee of Zhen Jiang Stomatological Hospital (PJ(m)2023-08-23). Tumor cells were collected and resuspended in a 1:1 mixture of PBS and Matrigel at a density of 1×10 7 cells per 100 µL. This cell suspension was injected subcutaneously into the right flank of 6-week-old BALB/c nude mice. Tumor growth was assessed every 48 hours using calipers to measure tumor size, and volume was calculated with the formula: Volume = (Length × Width 2 )/2. After 21 days, the mice were euthanized, and the tumors were dissected, weighed, and processed for subsequent analyses. Reagent For reagent treatment, the indicated cells were treated with various concentrations of ERG240 (#HY-W193545A, MedChemExpress) (5µM, 10µM, 20µM, 30µM). Dimethyl 2-oxoglutarate were purchased from MedChemExpress (HY-44134). The m6A RNA methylation assay kit were purchased from Abcam (#ab185912) and the assays were conducted following the instructions provided by the manufacturer. RNA extraction and quantitative real-time PCR (q-PCR) Total RNA was isolated from cultured cells with the AXYGEN RNA Extraction Kit (catalog number: #AP-MN-MS-RNA-250). Subsequent to extraction, the RNA samples were converted into complementary DNA (cDNA) via reverse transcription, a process carried out using the Takara PrimeScript™ RT Master Mix Kit (#RR036A). For the analysis of gene expression, reactions were run in triplicate using the Takara SYBR® Premix Ex Taq™ II kit (#RR036A) on an Applied Biosystems™ 7500 instrument (Thermo). The 2 − ΔΔCt algorithm was employed to determine the relative expression levels of each target gene. β-actin served as the endogenous reference gene to normalize the data. Detailed information regarding the primers utilized in the q-PCR assays is provided in Supplementary Table 2. Western blotting SDS-PAGE and western blotting procedures were conducted as outlined in previous reports[ 21 ]. For cell lysis, RIPA buffer (#P0013D, Beyotime) was used, supplemented with both protease inhibitors (#43002700, Roche) and phosphatase inhibitors (#43002700, Roche). Protein concentrations was determined using the BCA Protein Assay kit (#K813-2500, BioVision) according to the manufacturer's protocol. Equal protein aliquots were separated by SDS-PAGE and transferred to 0.45µm PVDF membranes (#IPVH00010, Merck Millipore). Following membranes were blocked with skim milk before incubation with primary antibodies, followed by a 1-hour incubation with horseradish peroxidase (HRP)-conjugated secondary antibodies (ZSGB-BIO, Beijing, China). Immunoreactive bands were visualized using an ECL detection kit (Merck Millipore, Billerica, MA, USA), with β-actin serving as the loading control. Primary antibodies included: rabbit anti-hnRNPC (#ab133607, 1:1000, Abcam), rabbit anti-BCAT1 (#ab197941, 1:1000, Abcam), and mouse anti-β-actin (#sc58673, 1:10000, Santa Cruz Biotechnology). Colony formation assay Cells were seeded in 6-well plates at a density of 3000 cells per well and maintained in a 5% CO₂ atmosphere at 37°C for 17 days. Following PBS washes, cells were fixed with 4% paraformaldehyde for 15 minutes and stained with crystal violet at room temperature for 15 minutes. Colony images were captured using a Nikon bright-field microscope, and colony counts were analyzed quantitatively. Cell proliferation assay Relative cell proliferation was evaluated through viability measurements using the Cell Counting Kit-8 (#CK04, Dojindo) and 5-ethynyl-20-deoxyuridine (EdU) incorporation assays with the EdU Cell Proliferation Assay Kit (Ribobio, Guangzhou, China), following previously described methods [ 22 ]. Limiting dilution assay Isolated stem cells were plated in 96-well plates at varying densities: 5, 10, 20, 50, 100, or 200 cells per well. After an 8-day incubation period, tumor sphere formation in each well was examined. Stem cell frequency was calculated using the limit dilution analysis software (ELDA), accessible at http://bioinf.wehi.edu.au/ . Seahorse-based bioenergetic analysis. OCR was assessed using the Seahorse XFe24 extracellular flux analyzer (Agilent Technologies) following the manufacturer's protocol. Cells were seeded onto collagen-coated 24-well Seahorse plates at a density of 1 × 10 5 cells per well and allowed to adhere overnight. OCR measurements were performed in basal assay medium containing 1 mM pyruvate, 10 mM glucose, and 2 mM glutamine. This was followed by sequential injections of 1 µM oligomycin, 2 µM FCCP, and 0.5 µM rotenone/antimycin A.. Glutamine uptake and glutamate production quantification Glutamine uptake/consumption and glutamate production were measured using the Glutamine Assay Kit (Abcam, #ab83374) and Glutamate Assay Kit (Sigma, MAK004-1KT), respectively, following the manufacturers' instructions. Branched-chain amino acid (BCAA) uptake/consumption was determined by subtracting the measured BCAA concentration in the medium from the initial concentration. All results were normalized to cell number. Metabolite level detection ATP levels were quantified using the ATP Assay Kit (Colorimetric/Fluorometric) (ab83355). This kit employs a standard protocol for fluorometric and colorimetric ATP determination involving three key reactions: glycerol phosphorylation by glycerol kinase (ATP-dependent) to form glycerol 3-phosphate; conversion of glycerol 3-phosphate to glycerone phosphate and hydrogen peroxide by glycerol phosphate oxidase; and peroxidase-mediated reaction of hydrogen peroxide with a probe to generate a red color (λmax = 570 nm) and fluorescence (Ex/Em = 535/587 nm). Succinate levels were measured using the Succinate Assay Kit (Colorimetric) (#ab204718) following the manufacturer's instructions. This assay detects succinate through its conversion (along with ATP and CoA) to succinyl-CoA, ADP, and Pi by succinyl-CoA synthase, with colorimetric detection at 450 nm. Fumarate concentrations were determined using the Fumarate Assay Kit (ab102516), which utilizes a colorimetric method (λ = 450 nm) for quantification. Glutathione (GSH) levels were measured with the GSH Assay Kit (Colorimetric) (ab239709), where GSH concentration is determined by absorbance readings at 412 nm. RNA stability assay Cells (4 × 10 5 ) were seeded in 6-well plates and treated with 5µg/ml actinomycin D (#HY-17559, MedChemExpress) for specified time periods. At each designated time point, cells were harvested for RNA isolation and subsequent RT-qPCR analysis. RNA immunoprecipitation (RIP) RIP assays were performed using the PureBinding® RNA Immunoprecipitation Kit (Geneseed) according to the manufacturer's protocol. Briefly, 5µg of hnRNPC antibody (#ab133607, 1:1000, Abcam) was bound to protein A/G magnetic beads at room temperature for 30 minutes, followed by three washes. The antibody-conjugated beads were then incubated with pre-cleared nuclear extracts in RIP buffer. Total RNA served as the input control, and extracted RNA was analyzed by RT-qPCR, which included U1 as a negative control. All RIP experiments were conducted in triplicate using three biological replicates. Primer sequences are provided in Supplementary Table 3. Methylated RNA immunoprecipitation (MeRIP)-qPCR The m6A modification status of a specific gene was analyzed using the MeRIP Kit (Millipore) following previously described procedures [ 2 ]. Briefly, 5 µg of either anti-m6A antibody (#CS220007, Millipore) or normal mouse IgG (#CS200621, Millipore) was prewashed and then incubated with Magna ChIP protein A/G magnetic beads (#CS203152, Millipore) for 30 minutes at room temperature. This antibody-bead complex was then incubated with purified poly-(A) RNA. The degree of enrichment of m⁶A-containing mRNA was subsequently quantified using RT-qPCR, with the relevant primer sequences listed in Supplementary Table 3. Results hnRNPC represents a novel independent prognostic biomarker in HNSCC To investigate the impact of m6A regulatory genes on HNSCC, we analyzed transcriptome data from 515 HNSCC patients and 44 normal tissues from TCGA. Expression profiles of 23 m6A-related genes were extracted, among which 18 showed aberrant expression in HNSCC (Fig. 1 A), suggesting a close association between m6A modification and HNSCC development. Feature selection of m6A regulators was performed using univariate Cox regression analysis (Fig. 1 B), identifying five genes (hnRNPC, ALKBH5, IGF2BP1, IGF2BP2, and YTHDC2) significantly associated with HNSCC survival. Subsequent multivariate Cox regression analysis of these candidates revealed that three genes (hnRNPC, IGF2BP2, and YTHDC2) remained significantly correlated with survival (Fig. 1 C). Univariate analysis (Fig. 1 D) was also conducted on clinical variables from HNSCC samples and significant clinical factors along with the three candidate genes were incorporated into a multifactorial Cox model (Fig. 1 E). The results indicated that hnRNPC, IGF2BP2, and YTHDC2 could serve as independent prognostic factors for HNSCC. Specifically, YTHDC2 was identified as a protective factor, while IGF2BP2 and hnRNPC were risk factors. Patients were stratified into high- and low-risk groups based on a RiskScore derived from the model (Figure S1 ). Survival analysis demonstrated that patients in the high-risk group had significantly shorter overall survival (OS; Fig. 1 F), a finding consistent in the test set (Fig. 1 G- 1 H). A nomogram and calibration curves based on the final multivariate Cox model further supported these results (Fig. 1 I-J). Although the roles of YTHDC2 and IGF2BP2 in HNSCC have been previously reported, we focused on hnRNPC. Survival analysis based on hnRNPC expression alone indicated that high expression was associated with poorer prognosis (Fig. 1 K). Moreover, hnRNPC expression was positively correlated with advanced pathological stage and T category (Fig. 1 L- 1 M). In summary, we successfully constructed an m6A-related risk regression model for HNSCC and identified hnRNPC as a novel independent prognostic biomarker in this malignancy. hnRNPC exerts oncogenic functions in oral squamous cell carcinoma To verify the potential role of hnRNPC in the progression of OSCC, we knocked down hnRNPC expression in OSCC cell lines CAL-27 and SCC-15 using two distinct shRNA sequences (Fig. 2 A- 2 B). Results from CCK-8 and colony formation assays demonstrated that hnRNPC knockdown significantly inhibited the proliferative capacity of OSCC cells compared to the negative control (NC) group, confirming the oncogenic function of hnRNPC (Fig. 2 C- 2 F). Further, EdU incorporation assay indicated that hnRNPC knockdown suppressed the proliferation rate of OSCC cells (Fig. 2 G- 2 H). Consistently, nude mouse subcutaneous xenograft experiments showed that hnRNPC silencing led to a significant reduction in both volume and weight of subcutaneously formed OSCC tumors (Fig. 2 I- 2 K). Furthermore, hnRNPC knockdown significantly decreased the frequency of tumorsphere formation by CAL-27-derived stem cells, as determined by an in vitro limiting dilution assay (Fig. 2 L). We analyzed the expressions of key stemness genes, including OCT4, SOX2, and Nanog, which are well-known for endowing tumor cells with self-renewal capabilities, using qPCR. hnRNPC knockdown resulted in a significant downregulation of these genes (Fig. 2 M). Therefore, hnRNPC emerges as a crucial regulator of OSCC cell growth and the maintenance of stem-like properties. hnRNPC promotes energy production and antioxidant capacity in OSCC via BCAA metabolism To investigate the mechanism underlying hnRNPC-mediated regulation of OSCC progression, we analyzed transcriptomic data of HNSC from TCGA. Results revealed that the BCAA metabolic pathway was active in HNSC tissues with high hnRNPC expression (Fig. 3 A). Since the BCAA metabolic pathway is involved in energy production and redox homeostasis, we also observed changes in pathways related to oxidative phosphorylation and oxidative stress (Fig. 3 B- 3 C). Consistently, BCAA uptake capacity was significantly impaired in OSCC cell lines with hnRNPC knockdown (Fig. 3 D). Since BCAAs generate large amounts of glutamate and BCKAs through catabolic pathways—where glutamate contributes to the synthesis of reduced glutathione (GSH) for antioxidant defense, and BCKAs promote the tricarboxylic acid (TCA) cycle and oxidative phosphorylation via acetyl-CoA production—we examined these indicators in OSCC cells[ 23 , 24 ]. Our findings showed that hnRNPC knockdown led to decreased glutamate levels, reduced oxygen consumption rate (OCR), and lower GSH levels in OSCC cells (Fig. 3 E- 3 L). In accordance, GESA analysis based on the TCGA data also revealed a dramatical enrichment of glutathione metabolism pathway in hnRNPC highly expressed OSCC tissues (Fig. 3 M- 3 N). These results indicate that hnRNPC can enhance tumor energy production and antioxidant capacity by promoting the BCAA metabolic pathway, thereby facilitating oxidative phosphorylation and increasing GSH levels, which likely represents a key mechanism underlying its tumor-promoting effects. hnRNPC regulates BCAT1 mRNA stability in an m6A modification-dependent manner To explore the specific mechanism by which hnRNPC promotes tumor progression through regulating BCAA metabolism, we analyzed differentially expressed genes between hnRNPC-high and hnRNPC-low expressing samples from the HNSC transcriptome database. We found that BCAT1 was significantly upregulated in OSCC tissues with high hnRNPC expression, suggesting that hnRNPC may regulate BCAA metabolism by promoting BCAT1 expression (Fig. 4 A- 4 B). Consistent with this observation, Western blotting and qPCR results showed that BCAT1 expression was significantly suppressed in OSCC cells following hnRNPC knockdown (Fig. 4 C- 4 D). Notably, treatment with the BCAT1 inhibitor EGR240 further enhanced the tumor-suppressive effects of hnRNPC knockdown (Fig. 4 E- 4 F), indicating that combined targeting of hnRNPC and BCAT1 to interfere with BCAA metabolism could represent a promising therapeutic strategy for OSCC. Given that hnRNPC functions as an m6A modification reader protein to regulate mRNA stability of downstream genes, we further investigated whether hnRNPC-mediated regulation of BCAT1 is dependent on m6A modification. mRNA stability assays demonstrated that BCAT1 mRNA stability was significantly reduced after hnRNPC knockdown (Fig. 4 G- 4 H). Using the SRAMP algorithm, we predicted the top five m6A modification sites in BCAT1 mRNA (Fig. 4 I). Further MeRIP-qPCR experiments identified the most prominent m6A peak at position + 8438 within the BCAT1 3'-UTR (Fig. 4 J- 4 K). RIP assays confirmed the direct binding of hnRNPC to BCAT1 mRNA (Fig. 4 L), while MeRIP analysis revealed that METTL3 knockdown reduced m6A methylation on BCAT1 transcripts (Fig. 4 M). Importantly, METTL3 silencing also diminished the association between hnRNPC and BCAT1 mRNA, demonstrating that m6A marks are required for hnRNPC recognition (Fig. 4 N). Moreover, transcriptomic analysis of TCGA database showed a significant positive correlation between hnRNPC and BCAT1 expression in HNSC tissues (Fig. 4 O). Consistent with this finding, pan-cancer transcriptomic data from the TCGA data and pan-tissue transcriptomic data from the GTEx database also revealed the significant positive correlation between hnRNPC and BCAT1 expression (Fig. 4 P- 4 Q). Therefore, hnRNPC may promote BCAT1 expression in an m6A-dependent manner during OSCC progression, thereby driving the malignant evolution of OSCC dependent on BCAA metabolism. α-ketoglutarate rescues hnRNPC-mediated BCAA-dependent energy deficiency Since α-ketoglutarate (α-KG) serves as a key donor for BCAT1-catalyzed glutamate generation in the BCAA metabolic pathway and functions as a critical intermediate in mitochondrial TCA cycle, we investigated whether exogenous supplementation of α-KG could reverse the hnRNPC-induced suppression of BCAA metabolism and subsequent energy deficiency. Results from CCK-8 and colony formation assays demonstrated that α-KG supplementation significantly restored cell viability in hnRNPC-knockdown OSCC cells (Fig. 5 A- 5 D). Stem cell viability experiments revealed that α-KG supplementation notably increased the frequency of tumorsphere formation by CAL-27-derived stem cells with hnRNPC knockdown (Fig. 5 E), accompanied by significant recovery of OCT4, SOX2, and Nanog expression levels which were downregulated by hnRNPC silencing (Fig. 5 F). Furthermore, Seahorse assay results showed that α-KG supplementation led to significant restoration of OCR and increased ATP levels in OSCC cells (Fig. 5 G- 5 K). These findings confirm that BCAT1-mediated BCAA metabolic pathway for energy production represents one of the important mechanisms underlying hnRNPC-promoted tumor progression. Discussion This study systematically explored the role and mechanism of hnRNPC in OSCC by integrating bioinformatics analysis and experimental validation. Through mining TCGA datasets of HNSCC, with OSCC as the predominant subtype, we first identified hnRNPC as a novel independent prognostic biomarker for HNSCC. The high expression of hnRNPC correlated with advanced pathological stages, poor overall survival, and served as a risk factor for clinical outcomes. Functional experiments further confirmed the oncogenic role of hnRNPC in OSCC. Knockdown of hnRNPC inhibited cell proliferation, colony formation, and tumorsphere formation in vitro, and reduced tumor growth in nude mouse xenografts, while also downregulating stemness-related genes (OCT4, SOX2, Nanog). Mechanistically, we revealed that hnRNPC promotes OSCC progression by regulating BCAA metabolism. hnRNPC enhances BCAA uptake, supports BCAT1-dependent energy production (via branched-chain α-ketoacids, BCKAs, entering the TCA cycle) and redox homeostasis (via glutamate-mediated glutathione, GSH, synthesis). Critically, this regulation of BCAT1 by hnRNPC is dependent on m6A modification—hnRNPC binds to m6A-modified BCAT1 mRNA (predominantly at the + 8438 site in the 3'-UTR) to maintain its stability, and METTL3 is required for this recognition. Finally, exogenous supplementation of α-KG, a key metabolite in TCA cylce, rescued the energy deficiency and functional impairment of OSCC cells caused by hnRNPC knockdown, further validating the BCAA metabolic pathway as a downstream effector of hnRNPC. A major innovation of this study lies in establishing a novel regulatory axis—hnRNPC/m6A/BCAT1/BCAA metabolism—that drives OSCC progression, filling critical gaps in current knowledge. Previous studies have separately highlighted the roles of m6A modification (e.g., METTL3, IGF2BP2) and BCAA metabolism (e.g., BCAT1) in OSCC, but their functional connection remained uncharacterized [ 25 – 27 ]. Our findings demonstrate that hnRNPC, a classic RNA-binding protein with established oncogenic roles in numorous types of cancer[ 28 , 29 ], acts as an m6A reader in OSCC to stabilize BCAT1 mRNA. This not only expands the functional spectrum of hnRNPC, beyond mRNA splicing and stability regulation to m6A-dependent metabolic control, but also reveals a unique epigenetic-metabolic crosstalk in OSCC. Specifically, m6A modification, by marking BCAT1 mRNA, enables hnRNPC to fine-tune BCAA metabolism—an adaptation that supports tumor energy demands (via BCKA-driven oxidative phosphorylation) and antioxidant defense (via glutamate-GSH axis). Notably, this axis also explains the clinical challenge of chemoresistance in OSCC. Previous work has shown that BCAT1-mediated GSH synthesis reduces drug-induced ROS and DNA damage [ 9 , 30 ]. Our study extends this by showing that hnRNPC upregulation enhances this pathway, providing a molecular basis for why high hnRNPC expression correlates with poor prognosis. This mechanistic link offers a new perspective for overcoming chemoresistance, that targeting hnRNPC or BCAT1 could disrupt the BCAA-GSH antioxidant system, sensitizing OSCC cells to cisplatin and other ROS-inducing therapies. The hnRNPC/m6A/BCAT1 axis identified in this study has significant clinical potential for the management of OSCC. From a prognostic perspective, hnRNPC could act as a prognostic biomarker. As hnRNPC expression level is combined with pathological stage, it may improve the risk stratification of OSCC patients, which in turn helps clinicians identify patients who are at high risk of recurrence or disease progression. In terms of treatment, targeting this axis provides a new therapeutic strategy. Combined inhibition of hnRNPC (such as through small interfering RNAs or small-molecule inhibitors) and BCAT1 (like using EGR240) can synergistically disrupt BCAA metabolism. This disruption not only reduces the energy supply available to tumor cells and impairs their antioxidant capacity but also makes the cells more sensitive to chemotherapy. Besides, METTL3 inhibitors can block the m6A modification of BCAT1 mRNA, thereby eliminating the stabilization of BCAT1 mRNA mediated by hnRNPC. This approach may help avoid the off-target effects that are often associated with direct inhibition of hnRNPC. Despite its contributions, this study has several limitations. First, while TCGA datasets provided robust clinical correlation data, the functional experiments were primarily conducted in two OSCC cell lines (CAL-27, SCC-15) and nude mouse xenografts. Validation in additional OSCC cell lines and patient-derived xenograft (PDX) models, which better recapitulate the heterogeneity of clinical OSCC, would strengthen the translational relevance of our findings. Second, while α-KG supplementation rescued hnRNPC knockdown-induced defects, the in vivo efficacy of targeting the hnRNPC/m6A/BCAT1 axis (e.g., using BCAT1 inhibitors like EGR240 or m6A methyltransferase inhibitors) was not evaluated; future studies should test these combination therapies in preclinical models. Finally, the correlation between hnRNPC expression and clinical chemoresistance was not validated using patient samples, which is critical for translating our findings to clinical practice. In conclusion, this study reveals a novel epigenetic-metabolic axis in OSCC, demonstrating that hnRNPC promotes BCAA metabolism via m6A-dependent stabilization of BCAT1. These findings not only enhance our understanding of OSCC progression but also provide potential biomarkers and therapeutic targets for improving OSCC patient outcomes. Declarations Competing interests The authors declare that they have no competing interests. Ethics approval and consent to participate The animal experiments were approved by the ethics committee of ZhenJiang Stomatological Hospital (PJm-20230823) and complied with the National Institutes of Health guide for the care and use of Laboratory animals (NIH Publications No. 8023, revised 1978). Consent for publication Not applicable. Supplementary Fig. 1. The appropriate cutoff value based on risk score in the training set Funding This study was supported by the Guidance Program of the Jiangsu Provincial Health Commission (Grant No. Z2022002). Author Contribution YA designed research. ZZ, XG, TH and FC performed research. ZZ, XG and TH analyzed data. YA wrote the paper. Acknowledgements Not applicable. Data Availability The TCGA data used in this study are from the cohort GDC TCGA Head and Neck Cancer (HNSC), the relevant gene expression RNAseq data (STAR – FPKM) can be directly download from the link:https://xenabrowser.net/datapages/?cohort=GDC%20TCGA%20Head%20and%20Neck%20Cancer%20(HNSC)&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443.All data that support the findings of this study are available from the corresponding authors upon reasonable request. References Hsu CW, et al. Integrated analyses utilizing metabolomics and transcriptomics reveal perturbation of the polyamine pathway in oral cavity squamous cell carcinoma. Anal Chim Acta. 2019;1050:113–22. Chamoli A, et al. Overview of oral cavity squamous cell carcinoma: Risk factors, mechanisms, and diagnostics. Oral Oncol. 2021;121:105451. Tan Y, et al. Oral squamous cell carcinomas: state of the field and emerging directions. Int J Oral Sci. 2023;15(1):44. Patil VM, et al. Beyond conventional chemotherapy, targeted therapy and immunotherapy in squamous cell cancer of the oral cavity. Oral Oncol. 2020;105:104673. Parmar A, et al. Interventions for the treatment of oral cavity and oropharyngeal cancer: chemotherapy. Cochrane Database Syst Rev. 2021;12(12):CD006386. Zhou Y, et al. Oral squamous cell carcinoma: Insights into cellular heterogeneity, drug resistance, and evolutionary trajectories. Cell Biol Toxicol. 2025;41(1):101. Choi BH, Hyun S, Koo SH. The role of BCAA metabolism in metabolic health and disease. Exp Mol Med. 2024;56(7):1552–9. Qian L, et al. Enhanced BCAT1 activity and BCAA metabolism promotes RhoC activity in cancer progression. Nat Metab. 2023;5(7):1159–73. McBrayer SK, et al. Transaminase Inhibition by 2-Hydroxyglutarate Impairs Glutamate Biosynthesis and Redox Homeostasis in Glioma. Cell. 2018;175(1):101–e11625. Xu E, et al. Branched-chain amino acids catabolism and cancer progression: focus on therapeutic interventions. Front Oncol. 2023;13:1220638. Ananieva EA, Wilkinson AC. Branched-chain amino acid metabolism in cancer. Curr Opin Clin Nutr Metab Care. 2018;21(1):64–70. Deng X, et al. The roles and implications of RNA m(6)A modification in cancer. Nat Rev Clin Oncol. 2023;20(8):507–26. Hong J, Xu K, Lee JH. Biological roles of the RNA m(6)A modification and its implications in cancer. Exp Mol Med. 2022;54(11):1822–32. Jiang X, et al. The role of m6A modification in the biological functions and diseases. Signal Transduct Target Ther. 2021;6(1):74. De Kesel J, et al. HNRNPC and m6A RNA methylation control oncogenic transcription and metabolism in T-cell leukemia. Blood. 2025;146(3):275–90. Bi Z, et al. A dynamic reversible RNA N(6) -methyladenosine modification: current status and perspectives. J Cell Physiol. 2019;234(6):7948–56. Navickas A, et al. An mRNA processing pathway suppresses metastasis by governing translational control from the nucleus. Nat Cell Biol. 2023;25(6):892–903. Wu Y et al. Function of HNRNPC in breast cancer cells by controlling the dsRNA-induced interferon response. EMBO J, 2018. 37(23). Su Z, et al. Novel reciprocal fusion genes involving HNRNPC and RARG in acute promyelocytic leukemia lacking RARA rearrangement. Haematologica. 2020;105(7):e376–8. Chen JJ, et al. The m6A reader HNRNPC promotes glioma progression by enhancing the stability of IRAK1 mRNA through the MAPK pathway. Cell Death Dis. 2024;15(6):390. Shen L et al. NDRG2 facilitates colorectal cancer differentiation through the regulation of Skp2-p21/p27 axis. Oncogene, 2018. 37(13): pp. 1759–1774. Liu H, et al. Interaction of lncRNA MIR100HG with hnRNPA2B1 facilitates m(6)A-dependent stabilization of TCF7L2 mRNA and colorectal cancer progression. Mol Cancer. 2022;21(1):74. Nie C et al. Branched Chain Amino Acids: Beyond Nutrition Metabolism. Int J Mol Sci, 2018. 19(4). Duan Y, et al. The role of leucine and its metabolites in protein and energy metabolism. Amino Acids. 2016;48(1):41–51. Su Y, et al. METTL3 Promotes OSCC Progression by Down-Regulating WEE1 in a m6A-YTHDF2-Dependent Manner. Mol Biotechnol. 2025;67(5):1867–79. Zhang D, et al. The m6A Reader IGF2BP2 Promotes Oral Squamous Cell Carcinoma Progression by Maintaining UCA1 Stability. Recent Pat Anticancer Drug Discov; 2024. Yuan Z, Li M, Tang Z. BCAT1 promotes cell proliferation, migration, and invasion via the PI3K-Akt signaling pathway in oral squamous cell carcinoma. Oral Dis. 2025;31(2):364–75. Liu YY, et al. HNRNPC mediates lymphatic metastasis of cervical cancer through m6A-dependent alternative splicing of FOXM1. Cell Death Dis. 2024;15(10):732. Yang N et al. hnRNPC Promotes Malignancy in Pancreatic Cancer through Stabilization of IQGAP3. Biomed Res Int, 2022. 2022: p. 6319685. Wang Y, et al. Branched-Chain Amino Acid Metabolic Reprogramming Orchestrates Drug Resistance to EGFR Tyrosine Kinase Inhibitors. Cell Rep. 2019;28(2):512–e5256. Additional Declarations No competing interests reported. Supplementary Files Supplementarytable13.docx Supplementaryfigure1.tif Supplementary Figure1. The appropriate cutoff value based on risk score in the training set Originaldata.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8676944","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588419947,"identity":"ee4914bb-d274-44a4-8e60-c5854504f59d","order_by":0,"name":"Zhixin Zhang","email":"","orcid":"","institution":"Zhen Jiang Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhixin","middleName":"","lastName":"Zhang","suffix":""},{"id":588419948,"identity":"40901066-ac7b-4d84-aa97-4c3591c89503","order_by":1,"name":"Xiao Gao","email":"","orcid":"","institution":"Zhen Jiang Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Gao","suffix":""},{"id":588419949,"identity":"df299721-e07e-4fc4-88bb-0975addb1c14","order_by":2,"name":"Ting Han","email":"","orcid":"","institution":"Zhen Jiang Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Han","suffix":""},{"id":588419950,"identity":"140bdc9a-be47-4a19-8f39-40c44902ce64","order_by":3,"name":"Fei Chai","email":"","orcid":"","institution":"Zhen Jiang Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Chai","suffix":""},{"id":588419951,"identity":"1c1463e6-4374-451f-ba70-bebf89691129","order_by":4,"name":"Menghui Gao","email":"","orcid":"","institution":"Zhen Jiang Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Menghui","middleName":"","lastName":"Gao","suffix":""},{"id":588419952,"identity":"5e69fbf3-1171-4ce9-bd82-4cf38357167e","order_by":5,"name":"Yulin An","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBAC9gYog4+ZgfFBQkUNYS08B6AMNmYGZoMHZ46RogWIJB+2MBOhRex0msTPHYcT29h5j1UkNrAx8Ld3J+DXIp27TbL3DFALM1/ajcQdMgwSZ85uwKvFHqhFgrcNpIXH7EbiGTYGA4lc/FrAtvyFaikAksRpkYbZwkCsls3Wsm3pxkAtxhIJZ47xEPQLUMvGm2/brGX7+c8YfvxRUSPH396LXwsUNCPMIEY5CNQRq3AUjIJRMApGIgAAmblDGqrSsCYAAAAASUVORK5CYII=","orcid":"","institution":"Zhen Jiang Stomatological Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yulin","middleName":"","lastName":"An","suffix":""}],"badges":[],"createdAt":"2026-01-23 08:40:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8676944/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8676944/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102745815,"identity":"f5a87c7d-f7cd-48d2-a09c-df81975a69d8","added_by":"auto","created_at":"2026-02-16 08:54:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10539358,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ehnRNPC represents a novel independent prognostic biomarker in HNSCC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Boxplot visualizing the expression of 23 m6A-related genes in 515 HNSCC and 44 normal tissues. (B) Heatmap (left) of the 23 m6A-related genes and Univariate cox regression analysis (right) based on m6A-related genes associated with the overall survival of HNSCC. (C) Heatmap (left) of the significant genes (HNRNPC, ALKBH5, IGF2BP1, IGF2BP2, YTHDC2) in the univariate Cox regression analysis and Multivariate cox regression analysis (right) based on candidate genes with the overall survival of HNSCC. (D) Forest plot presents the univariate Cox regression analysis of the clinical information of the training set. (E) The forest plot presents the multivariate regression analysis of the candidate genes in the training set and clinical information. Pink: HR \u0026lt; 1, Green: HR \u0026gt; 1. (F) Kaplan–Meier OS curves for the training set patients assigned to high- and low-risk groups. (G)The forest plot presents the results of a multivariate regression analysis of candidate genes in the test set and clinical information. Red: HR \u0026gt; 1, Blue: HR \u0026lt; 1. (H) Kaplan–Meier OS curves for the test set patients assigned to high- and low-risk groups. (I) Nomogram integrating the HNSCC risk score with age, gender, and expression levels of HNRNPC, IGF2BP2, and YTHDC2 to predict 3- and 5-year overall survival. (J) Calibration curves confirming good agreement between nomogram-predicted and observed survival probabilities. (K) Kaplan–Meier curves depicting OS according to the expression hnRNPC based on TCGA data. (L) Box-and-whisker plots comparing hnRNPC expression across pathological stages (stage I vs. II) and (M) T classifications (T3–T4 vs. T1–T2); Boxes represent median and interquartile range; whiskers indicate 1.5× IQR. NS, not significant. Unless otherwise stated, data are expressed as mean ± SD, *P \u0026lt; .05, **P \u0026lt; .01, ***P \u0026lt; .001.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/e264cfc3c7be20302a73bae2.png"},{"id":102746129,"identity":"26ccbf6e-6955-43d1-bf1a-46f425b1c6ef","added_by":"auto","created_at":"2026-02-16 08:55:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":9583296,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ehnRNPC exerts oncogenic functions in OSCC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) Western blotting (A) and qPCR (B) was used to detect protein expression after stable knockdown expression of hnRNPC in CAL-27 and SCC-15 cell lines. (C-D) CCK8 assay was used to detect the effect of hnRNPC knockdown on the viability of CAL-27 (C) and (D) SCC-15 cells. (E-F) Representative images (E) and relative quantifications (F) of colony formation assays of indicated cells. (G-H) EdU solution was incorporated for 2 h to evaluate the proliferation in indicated cells (G). The percentage of positive cells was quantified (H). (I-K) Knockdown of hnRNPC can inhibit the growth of subcutaneous tumor tumors. Cells with empty vector or CAL-27 knockdown vectors were subcutaneously injected into nude mice. Tumor size was measured every 3 days and growth curves were plotted. Tumors were dissected from the nude mice of each group and photographed at 21 days after the weight of tumors was measured. (L) Sphere formation frequency of GSCs (27-CSC) with or without hnRNPC knockdown was calculated with extreme limiting dilution assay analysis (left panel). Stem cell frequencies from 27-CSC cells with or without hnRNPC knockdown were estimated as the ratio 1/x with the upper and lower 95% confidence intervals, where 1 = stem cell and x = all cells (right panel). (M) qPCR was used to detect the Sox2, Nanog and Oct4 mRNA. For A–H and L-M, n = 3 biologically independent experiments. For I-K, n = 5 mice per group. Unless otherwise stated, data are expressed as mean ± SD, *P \u0026lt; .05, **P \u0026lt; .01, ***P \u0026lt; .001.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/cd429648ed22375d46ec6378.png"},{"id":102440538,"identity":"c52f52e3-9808-4d3f-917f-e51eeecf70c9","added_by":"auto","created_at":"2026-02-11 16:49:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4713219,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ehnRNPC promotes energy production and antioxidant capacity in OSCC via BCAA metabolism\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-C) GO enrichment analysis of 1.5FC DEGs. Present separately the metabolism of amino acids (BCAA), energy metabolism (B), and pathway of oxidative stress (C). (D-E) The BCAA uptake rate (D) and internal glutamate levels (E) were determined in CAL-27, SCC-15 and 27-CSC cells with or without hnRNPC Knockdown. (F-I) Analysis of OCR measurement of one representative experiment in indicated cells after 4 h culture in basal condition and after sequential addition of oligomycin, FCCP and antimycin/rotenone (A/R) (F,H). Quantification of Basal respiration, ATP-production-coupled respiration, Maximal respiration and Spars capacity in CAL-27 and SCC-15 cells with or without HRNPC Knockdown (G,I); Box-and-whisker plots show median and minimum to maximum; data in dot and bar plots are mean ± standard deviation. (L) The GSH level was determined in CAL-27, SCC-15 and 27-CSC cells with or without hnRNPC Knockdown. (M-N) GSEA enrichment analysis glutathione metabolism pathway. Unless otherwise stated, data are expressed as mean ± sd, *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/169ba7e659eb43d8c291946d.png"},{"id":102745770,"identity":"f470cc5b-7242-44d8-aa41-4a0c712bbd9b","added_by":"auto","created_at":"2026-02-16 08:53:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":8742223,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ehnRNPC regulates BCAT1 mRNA stability in an m6A modification-dependent manner\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) The volcano plot shows the expression of BCAT1 in hnRNPC with low expression versus high expression based on TCGA-seq data. (B) The Sankey diagram chart shows the expression levels of genes in different amino acid metabolic pathways. BCAT1: Pink (C-D) Western blotting (C) and qPCR (D) analysis of BCAT1 protein and Mrna expressions in in CAL-27, SCC-15 with or without hnRNPC expression. (E-F) Detect the growth conditions of CAL-27 (E) and SCC-15 (F) cells with or without hnRNPC knockdown after adding the BCAT1 inhibitor ERG240. (G-H) Detection of the stability of BCAT1 mRNA in CAL-27 (G) and SCC-15 (H) cells after knockdown of hnRNPC. (I) The position map shows the prediction of the top five m6A modification sites in the BCAT1 mRNA using the SRAMP algorithm. (J-K) Analysis of MeRIP assays detecting BCAT1 retrieved by a m6A antibody around the high‑confidence m6A sites in CAL-27 (J) and SCC-15 cells (K). (L) Assessment of RIP assays detecting BCAT1 mRNA +8438 site retrieved by a hnRNPC antibody or by IgG in CAL-27 and SCC-15 cells. (M) Analysis of MeRIP assays detecting BCAT1 mRNA +8438 site site recovered with m6A antibody in METTL3 knockdown in CAL-27 and SCC-15 cells. (N) Assessment of RIP assays by a hnRNPC antibody or by IgG in CAL-27 and SCC-15 cells after METTL3 knockdown. (O) Transcriptomic analysis of TCGA database showed a significant positive correlation between hnRNPC and BCAT1 expression in HNSC tissues. (P-Q) GTEx database also revealed the significant positive correlation between hnRNPC and BCAT1 expression. Unless otherwise stated, data are expressed as mean ± SD, *P \u0026lt; .05, **P \u0026lt; .01, ***P \u0026lt; .001.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/a0aa72fb2a453dc5f0a619e6.png"},{"id":102440536,"identity":"7ceb013f-ced7-49d7-9f60-2839b6a00b6e","added_by":"auto","created_at":"2026-02-11 16:49:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":7550909,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eα-ketoglutarate rescues hnRNPC-mediated BCAA-dependent energy deficiency\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) The CCK8 assay was used to investigate the growth conditions of α-KG in CAL-27 (A) and SCC-15 (B) cells with knocked-down hnRNPC. (C-D) Representative images (C) and relative quantifications (D) of colony formation assays of indicated cells (E) Sphere formation frequency in 27-CSC of knocked-down hnRNPC with conditions of α-KG was calculated with extreme limiting dilution assay analysis (top panel). Stem cell frequencies from 27-CSC cells were estimated as the ratio 1/x with the upper and lower 95% confidence intervals, where 1 = stem cell and x = all cells (bottom panel). (F) qPCR was used to detect the Sox2, Nanog and Oct4 mRNA. (G-J) Analysis of OCR measurement of one representative experiment in indicated cells after 4 h culture in basal condition and after sequential addition of oligomycin, FCCP and antimycin/rotenone (A/R) (G,I). Quantification of Basal respiration, ATP-production-coupled respiration, Maximal respiration and Spars capacity in CAL-27 and SCC-15 of knocked-down hnRNPC with conditions of α-KG (H,J). Box-and-whisker plots show median and minimum to maximum; data in dot and bar plots are mean ± standard deviation. (K) The ATP level was determined in CAL-27 and SCC-15 of knocked-down hnRNPC with conditions of α-KG. Unless otherwise stated, data are expressed as mean ± SD, *P \u0026lt; .05, **P \u0026lt; .01, ***P \u0026lt; .001.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/d7ffab61008bbc156f3d6cd4.png"},{"id":102440531,"identity":"cb8a0d34-1266-486b-bdee-698273cfe856","added_by":"auto","created_at":"2026-02-11 16:49:33","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":692252,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe proposed mechanism of hnRNPC action in regulation of BCAT1 stabilization in m6A-dependent manner during OSCC progression.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/826c45f9630ac71ded891243.png"},{"id":106404791,"identity":"793c6811-65e6-4af0-a591-b229ea148a68","added_by":"auto","created_at":"2026-04-08 09:17:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":42973693,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/3bfc7390-8483-4deb-85e1-439b7d27dbc1.pdf"},{"id":102440530,"identity":"68c72407-5240-454b-b17a-b4db6134f47c","added_by":"auto","created_at":"2026-02-11 16:49:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18285,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable13.docx","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/d2a7e30b19b01420a7d163df.docx"},{"id":102440535,"identity":"bb5689ae-4e5e-41d3-8521-6fbc91d6e8a4","added_by":"auto","created_at":"2026-02-11 16:49:33","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2093752,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe appropriate cutoff value based on risk score in the training set\u003c/p\u003e","description":"","filename":"Supplementaryfigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/8a0fbf3866a80ee3cbf5af56.tif"},{"id":102440534,"identity":"1bae846f-c3d6-4ec0-8322-e8c820b4d585","added_by":"auto","created_at":"2026-02-11 16:49:33","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1616598,"visible":true,"origin":"","legend":"","description":"","filename":"Originaldata.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8676944/v1/926c6b081fb93d9f8996c923.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"hnRNPC Promotes Oral Squamous Cell Carcinoma Progression via m6A-Dependent Stabilization of BCAT1 to Enhance Branched-Chain Amino Acid Metabolism","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOral squamous cell carcinoma (OSCC) is a heterogeneous malignant neoplasm originating from the epithelial tissue of the oral mucosa, which remains one of the leading causes of cancer death worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It accounts for 90% of all malignant tumors in the oral cavity and serves as the most common subtype of head and neck squamous cell carcinoma (HNSCC) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Clinically, drug resistance, significantly reducing the efficacy of traditional chemotherapeutics such as cisplatin, fluorouracil, and paclitaxel[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Additionally, while high-dose radiotherapy is often combined with drug therapy, it causes acute toxicities that develop into long-term sequelae, further compromising treatment tolerance and patients\u0026rsquo; quality of life[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Thus, current OSCC drug-based treatments are far from optimal, calling for more effective and tailored solutions.\u003c/p\u003e \u003cp\u003eBranched-chain amino acids (BCAAs, including leucine, isoleucine, and valine) are essential amino acids that require catabolism. Branched-chain amino acid transaminase (BCAT) is the rate-limiting enzyme driving BCAA transamination, a reaction that transfers the amino group of BCAAs (leucine, isoleucine, valine) to α-ketoglutarate (α-KG), generating branched-chain α-ketoacids (BCKAs) and glutamate[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. BCKAs enter the TCA cycle to produce ATP for tumor energy needs, while glutamate acts as a key precursor for glutathione (GSH) synthesis: it fuels GSH production (supporting the first rate-limiting step via glutamate-cysteine ligase), scavenges ROS to protect tumors from oxidative stress, and even contributes to chemoresistance [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This BCAT-mediated metabolism (energy supply via BCKAs, antioxidant defense via glutamate-GSH) is a tumor-specific adaptation, making BCAT1 a potential therapeutic target [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eN6-methyladenosine (m6A) modification is the most abundant epigenetic modification in eukaryotic mRNA, which is co-regulated by methyltransferase complexes (\"writers\"), demethylases (\"erasers\"), and m6A-binding proteins (\"readers\") [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. By influencing mRNA splicing, transport, translation, and degradation, it plays a central role in physiological processes such as cell proliferation and differentiation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Heterogeneous nuclear ribonucleoprotein C (hnRNPC) is a classic RNA-binding protein that mainly recognizes uracil-rich sequences in precursor mRNA (pre-mRNA) to participate in RNA splicing, stability maintenance, and nucleocytoplasmic transport, serving as a key regulatory factor in the RNA metabolic network [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Previous studies have demonstrated that hnRNPC consistently exerts oncogenic functions. It promotes tumor progression through multiple mechanisms, such as regulating the stability of mRNA or miRNA and mediating alternative splicing, with well-documented roles in glioma, acute myeloid leukemia (AML), breast cancer, and other malignancies [\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, the function of hnRNPC in OSCC remains largely unknown and requires further in-depth investigation.\u003c/p\u003e \u003cp\u003eIn this study, we utilized The Cancer Genome Atlas (TCGA) datasets to conduct an integrated bioinformatics analysis, systematically exploring the relationship between m6A modification patterns and OSCC malignancy. Through rigorous screening and functional validation of m6A regulatory proteins involved in OSCC progression, we identified that hnRNPC is highly associated with the prognosis of OSCC, showing a positive correlation with poor clinical outcomes. Mechanistically, our findings revealed that hnRNPC can induce the expression of BCAT1 in an m6A modification-dependent manner. This, in turn, promotes BCAA metabolism in OSCC cells, supporting BCAT1-dependent energy production and the maintenance of redox homeostasis. Collectively, these results suggest that hnRNPC may serve as a potential therapeutic target in OSCC progression and holds significant implications for the diagnosis and prognosis of OSCC.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCollection of m6A transcriptome data and expression profiling\u003c/h2\u003e \u003cp\u003eTranscriptome datasets, comprising 515 head and neck squamous cell carcinoma (HNSCC) samples and 44 normal tissue samples, were retrieved from The Cancer Genome Atlas (TCGA). A total of 23 m6A-associated genes were selected from the dataset based on findings from prior studies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Specifically, the cohort GDC TCGA Head and Neck Cancer (HNSC) was retrieved from the UCSC Xena database, and the STAR-FPKM data under the gene expression RNAseq module were downloaded (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov\u003c/span\u003e\u003cspan address=\"https://portal.gdc.cancer.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To visualize gene expression patterns, heatmaps and boxplots were constructed using the ggplot2 and boxplot packages in R.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDevelopment of Cox risk regression model\u003c/h3\u003e\n\u003cp\u003eStudy samples were randomly allocated into a training cohort and a validation cohort at a 3:7 ratio. Univariate and multivariate Cox regression analyses were applied to pinpoint independent prognostic factors for HNSCC patients. The robustness of these factors was further assessed using the validation cohort. Ultimately, three genes\u0026mdash;IGF2BP2, hnRNPC, and YTHDC2\u0026mdash;were incorporated into the final Cox risk regression model.\u003c/p\u003e\n\u003ch3\u003eCell culture and lentivirus preparation\u003c/h3\u003e\n\u003cp\u003eThe human HNSCC cell lines CAL-27 and SCC-15 were acquired from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). These cell lines were maintained in Dulbecco's modified Eagle's medium (DMEM) containing 10% fetal bovine serum. For stem cell induction, oral squamous cell carcinoma cells were cultured in DMEM/F12 medium supplemented with basic fibroblast growth factor (bFGF) and epidermal growth factor (EGF). These induced stem cells were grown as tumor spheres in DMEM/F12 medium with 20 ng/ml each of bFGF (#HY-P7331, MedChemExpress) and EGF (#AF-100-15-100, Peprotech). Lentivirus targeting hnRNPC for knockdown was produced by Hanheng Biotechnology (Shanghai, China), with the corresponding shRNA sequences provided in Supplementary Table\u0026nbsp;1.\u003c/p\u003e\n\u003ch3\u003eSubcutaneous tumor xenograft model\u003c/h3\u003e\n\u003cp\u003eThe nude mice were purchased from CYAGEN company (Suzhou, China). This study was approved by the ethics committee of Zhen Jiang Stomatological Hospital (PJ(m)2023-08-23). Tumor cells were collected and resuspended in a 1:1 mixture of PBS and Matrigel at a density of 1\u0026times;10\u003csup\u003e7\u003c/sup\u003e cells per 100 \u0026micro;L. This cell suspension was injected subcutaneously into the right flank of 6-week-old BALB/c nude mice. Tumor growth was assessed every 48 hours using calipers to measure tumor size, and volume was calculated with the formula: Volume = (Length \u0026times; Width\u003csup\u003e2\u003c/sup\u003e)/2. After 21 days, the mice were euthanized, and the tumors were dissected, weighed, and processed for subsequent analyses.\u003c/p\u003e\n\u003ch3\u003eReagent\u003c/h3\u003e\n\u003cp\u003eFor reagent treatment, the indicated cells were treated with various concentrations of ERG240 (#HY-W193545A, MedChemExpress) (5\u0026micro;M, 10\u0026micro;M, 20\u0026micro;M, 30\u0026micro;M). Dimethyl 2-oxoglutarate were purchased from MedChemExpress (HY-44134). The m6A RNA methylation assay kit were purchased from Abcam (#ab185912) and the assays were conducted following the instructions provided by the manufacturer.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction and quantitative real-time PCR (q-PCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was isolated from cultured cells with the AXYGEN RNA Extraction Kit (catalog number: #AP-MN-MS-RNA-250). Subsequent to extraction, the RNA samples were converted into complementary DNA (cDNA) via reverse transcription, a process carried out using the Takara PrimeScript\u0026trade; RT Master Mix Kit (#RR036A). For the analysis of gene expression, reactions were run in triplicate using the Takara SYBR\u0026reg; Premix Ex Taq\u0026trade; II kit (#RR036A) on an Applied Biosystems\u0026trade; 7500 instrument (Thermo). The 2\u0026thinsp;\u0026minus;\u0026thinsp;ΔΔCt algorithm was employed to determine the relative expression levels of each target gene. β-actin served as the endogenous reference gene to normalize the data. Detailed information regarding the primers utilized in the q-PCR assays is provided in Supplementary Table\u0026nbsp;2.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eWestern blotting\u003c/h3\u003e\u003cp\u003eSDS-PAGE and western blotting procedures were conducted as outlined in previous reports[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For cell lysis, RIPA buffer (#P0013D, Beyotime) was used, supplemented with both protease inhibitors (#43002700, Roche) and phosphatase inhibitors (#43002700, Roche). Protein concentrations was determined using the BCA Protein Assay kit (#K813-2500, BioVision) according to the manufacturer's protocol. Equal protein aliquots were separated by SDS-PAGE and transferred to 0.45\u0026micro;m PVDF membranes (#IPVH00010, Merck Millipore). Following membranes were blocked with skim milk before incubation with primary antibodies, followed by a 1-hour incubation with horseradish peroxidase (HRP)-conjugated secondary antibodies (ZSGB-BIO, Beijing, China). Immunoreactive bands were visualized using an ECL detection kit (Merck Millipore, Billerica, MA, USA), with β-actin serving as the loading control. Primary antibodies included: rabbit anti-hnRNPC (#ab133607, 1:1000, Abcam), rabbit anti-BCAT1 (#ab197941, 1:1000, Abcam), and mouse anti-β-actin (#sc58673, 1:10000, Santa Cruz Biotechnology).\u003c/p\u003e\n\u003ch3\u003eColony formation assay\u003c/h3\u003e\n\u003cp\u003eCells were seeded in 6-well plates at a density of 3000 cells per well and maintained in a 5% CO₂ atmosphere at 37\u0026deg;C for 17 days. Following PBS washes, cells were fixed with 4% paraformaldehyde for 15 minutes and stained with crystal violet at room temperature for 15 minutes. Colony images were captured using a Nikon bright-field microscope, and colony counts were analyzed quantitatively.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCell proliferation assay\u003c/h2\u003e \u003cp\u003eRelative cell proliferation was evaluated through viability measurements using the Cell Counting Kit-8 (#CK04, Dojindo) and 5-ethynyl-20-deoxyuridine (EdU) incorporation assays with the EdU Cell Proliferation Assay Kit (Ribobio, Guangzhou, China), following previously described methods [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimiting dilution assay\u003c/h2\u003e \u003cp\u003eIsolated stem cells were plated in 96-well plates at varying densities: 5, 10, 20, 50, 100, or 200 cells per well. After an 8-day incubation period, tumor sphere formation in each well was examined. Stem cell frequency was calculated using the limit dilution analysis software (ELDA), accessible at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinf.wehi.edu.au/\u003c/span\u003e\u003cspan address=\"http://bioinf.wehi.edu.au/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSeahorse-based bioenergetic analysis.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOCR was assessed using the Seahorse XFe24 extracellular flux analyzer (Agilent Technologies) following the manufacturer's protocol. Cells were seeded onto collagen-coated 24-well Seahorse plates at a density of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells per well and allowed to adhere overnight. OCR measurements were performed in basal assay medium containing 1 mM pyruvate, 10 mM glucose, and 2 mM glutamine. This was followed by sequential injections of 1 \u0026micro;M oligomycin, 2 \u0026micro;M FCCP, and 0.5 \u0026micro;M rotenone/antimycin A..\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGlutamine uptake and glutamate production quantification\u003c/h2\u003e \u003cp\u003eGlutamine uptake/consumption and glutamate production were measured using the Glutamine Assay Kit (Abcam, #ab83374) and Glutamate Assay Kit (Sigma, MAK004-1KT), respectively, following the manufacturers' instructions. Branched-chain amino acid (BCAA) uptake/consumption was determined by subtracting the measured BCAA concentration in the medium from the initial concentration. All results were normalized to cell number.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMetabolite level detection\u003c/h2\u003e \u003cp\u003eATP levels were quantified using the ATP Assay Kit (Colorimetric/Fluorometric) (ab83355). This kit employs a standard protocol for fluorometric and colorimetric ATP determination involving three key reactions: glycerol phosphorylation by glycerol kinase (ATP-dependent) to form glycerol 3-phosphate; conversion of glycerol 3-phosphate to glycerone phosphate and hydrogen peroxide by glycerol phosphate oxidase; and peroxidase-mediated reaction of hydrogen peroxide with a probe to generate a red color (λmax\u0026thinsp;=\u0026thinsp;570 nm) and fluorescence (Ex/Em\u0026thinsp;=\u0026thinsp;535/587 nm). Succinate levels were measured using the Succinate Assay Kit (Colorimetric) (#ab204718) following the manufacturer's instructions. This assay detects succinate through its conversion (along with ATP and CoA) to succinyl-CoA, ADP, and Pi by succinyl-CoA synthase, with colorimetric detection at 450 nm. Fumarate concentrations were determined using the Fumarate Assay Kit (ab102516), which utilizes a colorimetric method (λ\u0026thinsp;=\u0026thinsp;450 nm) for quantification. Glutathione (GSH) levels were measured with the GSH Assay Kit (Colorimetric) (ab239709), where GSH concentration is determined by absorbance readings at 412 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRNA stability assay\u003c/h2\u003e \u003cp\u003eCells (4 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e) were seeded in 6-well plates and treated with 5\u0026micro;g/ml actinomycin D (#HY-17559, MedChemExpress) for specified time periods. At each designated time point, cells were harvested for RNA isolation and subsequent RT-qPCR analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRNA immunoprecipitation (RIP)\u003c/h2\u003e \u003cp\u003eRIP assays were performed using the PureBinding\u0026reg; RNA Immunoprecipitation Kit (Geneseed) according to the manufacturer's protocol. Briefly, 5\u0026micro;g of hnRNPC antibody (#ab133607, 1:1000, Abcam) was bound to protein A/G magnetic beads at room temperature for 30 minutes, followed by three washes. The antibody-conjugated beads were then incubated with pre-cleared nuclear extracts in RIP buffer. Total RNA served as the input control, and extracted RNA was analyzed by RT-qPCR, which included U1 as a negative control. All RIP experiments were conducted in triplicate using three biological replicates. Primer sequences are provided in Supplementary Table\u0026nbsp;3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMethylated RNA immunoprecipitation (MeRIP)-qPCR\u003c/h2\u003e \u003cp\u003eThe m6A modification status of a specific gene was analyzed using the MeRIP Kit (Millipore) following previously described procedures [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Briefly, 5 \u0026micro;g of either anti-m6A antibody (#CS220007, Millipore) or normal mouse IgG (#CS200621, Millipore) was prewashed and then incubated with Magna ChIP protein A/G magnetic beads (#CS203152, Millipore) for 30 minutes at room temperature. This antibody-bead complex was then incubated with purified poly-(A) RNA. The degree of enrichment of m⁶A-containing mRNA was subsequently quantified using RT-qPCR, with the relevant primer sequences listed in Supplementary Table\u0026nbsp;3.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ehnRNPC represents a novel independent prognostic biomarker in HNSCC\u003c/h2\u003e \u003cp\u003eTo investigate the impact of m6A regulatory genes on HNSCC, we analyzed transcriptome data from 515 HNSCC patients and 44 normal tissues from TCGA. Expression profiles of 23 m6A-related genes were extracted, among which 18 showed aberrant expression in HNSCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), suggesting a close association between m6A modification and HNSCC development. Feature selection of m6A regulators was performed using univariate Cox regression analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), identifying five genes (hnRNPC, ALKBH5, IGF2BP1, IGF2BP2, and YTHDC2) significantly associated with HNSCC survival. Subsequent multivariate Cox regression analysis of these candidates revealed that three genes (hnRNPC, IGF2BP2, and YTHDC2) remained significantly correlated with survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Univariate analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) was also conducted on clinical variables from HNSCC samples and significant clinical factors along with the three candidate genes were incorporated into a multifactorial Cox model (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). The results indicated that hnRNPC, IGF2BP2, and YTHDC2 could serve as independent prognostic factors for HNSCC. Specifically, YTHDC2 was identified as a protective factor, while IGF2BP2 and hnRNPC were risk factors. Patients were stratified into high- and low-risk groups based on a RiskScore derived from the model (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Survival analysis demonstrated that patients in the high-risk group had significantly shorter overall survival (OS; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), a finding consistent in the test set (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). A nomogram and calibration curves based on the final multivariate Cox model further supported these results (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI-J). Although the roles of YTHDC2 and IGF2BP2 in HNSCC have been previously reported, we focused on hnRNPC. Survival analysis based on hnRNPC expression alone indicated that high expression was associated with poorer prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eK). Moreover, hnRNPC expression was positively correlated with advanced pathological stage and T category (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eL-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eM). In summary, we successfully constructed an m6A-related risk regression model for HNSCC and identified hnRNPC as a novel independent prognostic biomarker in this malignancy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003ehnRNPC exerts oncogenic functions in oral squamous cell carcinoma\u003c/h2\u003e \u003cp\u003eTo verify the potential role of hnRNPC in the progression of OSCC, we knocked down hnRNPC expression in OSCC cell lines CAL-27 and SCC-15 using two distinct shRNA sequences (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Results from CCK-8 and colony formation assays demonstrated that hnRNPC knockdown significantly inhibited the proliferative capacity of OSCC cells compared to the negative control (NC) group, confirming the oncogenic function of hnRNPC (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Further, EdU incorporation assay indicated that hnRNPC knockdown suppressed the proliferation rate of OSCC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH). Consistently, nude mouse subcutaneous xenograft experiments showed that hnRNPC silencing led to a significant reduction in both volume and weight of subcutaneously formed OSCC tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eK). Furthermore, hnRNPC knockdown significantly decreased the frequency of tumorsphere formation by CAL-27-derived stem cells, as determined by an in vitro limiting dilution assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eL). We analyzed the expressions of key stemness genes, including OCT4, SOX2, and Nanog, which are well-known for endowing tumor cells with self-renewal capabilities, using qPCR. hnRNPC knockdown resulted in a significant downregulation of these genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eM). Therefore, hnRNPC emerges as a crucial regulator of OSCC cell growth and the maintenance of stem-like properties.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ehnRNPC promotes energy production and antioxidant capacity in OSCC via BCAA metabolism\u003c/h2\u003e \u003cp\u003eTo investigate the mechanism underlying hnRNPC-mediated regulation of OSCC progression, we analyzed transcriptomic data of HNSC from TCGA. Results revealed that the BCAA metabolic pathway was active in HNSC tissues with high hnRNPC expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Since the BCAA metabolic pathway is involved in energy production and redox homeostasis, we also observed changes in pathways related to oxidative phosphorylation and oxidative stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Consistently, BCAA uptake capacity was significantly impaired in OSCC cell lines with hnRNPC knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Since BCAAs generate large amounts of glutamate and BCKAs through catabolic pathways\u0026mdash;where glutamate contributes to the synthesis of reduced glutathione (GSH) for antioxidant defense, and BCKAs promote the tricarboxylic acid (TCA) cycle and oxidative phosphorylation via acetyl-CoA production\u0026mdash;we examined these indicators in OSCC cells[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Our findings showed that hnRNPC knockdown led to decreased glutamate levels, reduced oxygen consumption rate (OCR), and lower GSH levels in OSCC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL). In accordance, GESA analysis based on the TCGA data also revealed a dramatical enrichment of glutathione metabolism pathway in hnRNPC highly expressed OSCC tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eM-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eN). These results indicate that hnRNPC can enhance tumor energy production and antioxidant capacity by promoting the BCAA metabolic pathway, thereby facilitating oxidative phosphorylation and increasing GSH levels, which likely represents a key mechanism underlying its tumor-promoting effects.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ehnRNPC regulates BCAT1 mRNA stability in an m6A modification-dependent manner\u003c/h2\u003e \u003cp\u003eTo explore the specific mechanism by which hnRNPC promotes tumor progression through regulating BCAA metabolism, we analyzed differentially expressed genes between hnRNPC-high and hnRNPC-low expressing samples from the HNSC transcriptome database. We found that BCAT1 was significantly upregulated in OSCC tissues with high hnRNPC expression, suggesting that hnRNPC may regulate BCAA metabolism by promoting BCAT1 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Consistent with this observation, Western blotting and qPCR results showed that BCAT1 expression was significantly suppressed in OSCC cells following hnRNPC knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Notably, treatment with the BCAT1 inhibitor EGR240 further enhanced the tumor-suppressive effects of hnRNPC knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF), indicating that combined targeting of hnRNPC and BCAT1 to interfere with BCAA metabolism could represent a promising therapeutic strategy for OSCC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGiven that hnRNPC functions as an m6A modification reader protein to regulate mRNA stability of downstream genes, we further investigated whether hnRNPC-mediated regulation of BCAT1 is dependent on m6A modification. mRNA stability assays demonstrated that BCAT1 mRNA stability was significantly reduced after hnRNPC knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH). Using the SRAMP algorithm, we predicted the top five m6A modification sites in BCAT1 mRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI). Further MeRIP-qPCR experiments identified the most prominent m6A peak at position\u0026thinsp;+\u0026thinsp;8438 within the BCAT1 3'-UTR (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK). RIP assays confirmed the direct binding of hnRNPC to BCAT1 mRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eL), while MeRIP analysis revealed that METTL3 knockdown reduced m6A methylation on BCAT1 transcripts (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eM). Importantly, METTL3 silencing also diminished the association between hnRNPC and BCAT1 mRNA, demonstrating that m6A marks are required for hnRNPC recognition (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eN). Moreover, transcriptomic analysis of TCGA database showed a significant positive correlation between hnRNPC and BCAT1 expression in HNSC tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eO). Consistent with this finding, pan-cancer transcriptomic data from the TCGA data and pan-tissue transcriptomic data from the GTEx database also revealed the significant positive correlation between hnRNPC and BCAT1 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eP-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eQ). Therefore, hnRNPC may promote BCAT1 expression in an m6A-dependent manner during OSCC progression, thereby driving the malignant evolution of OSCC dependent on BCAA metabolism.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eα-ketoglutarate rescues hnRNPC-mediated BCAA-dependent energy deficiency\u003c/h2\u003e \u003cp\u003eSince α-ketoglutarate (α-KG) serves as a key donor for BCAT1-catalyzed glutamate generation in the BCAA metabolic pathway and functions as a critical intermediate in mitochondrial TCA cycle, we investigated whether exogenous supplementation of α-KG could reverse the hnRNPC-induced suppression of BCAA metabolism and subsequent energy deficiency. Results from CCK-8 and colony formation assays demonstrated that α-KG supplementation significantly restored cell viability in hnRNPC-knockdown OSCC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Stem cell viability experiments revealed that α-KG supplementation notably increased the frequency of tumorsphere formation by CAL-27-derived stem cells with hnRNPC knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE), accompanied by significant recovery of OCT4, SOX2, and Nanog expression levels which were downregulated by hnRNPC silencing (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). Furthermore, Seahorse assay results showed that α-KG supplementation led to significant restoration of OCR and increased ATP levels in OSCC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK). These findings confirm that BCAT1-mediated BCAA metabolic pathway for energy production represents one of the important mechanisms underlying hnRNPC-promoted tumor progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study systematically explored the role and mechanism of hnRNPC in OSCC by integrating bioinformatics analysis and experimental validation. Through mining TCGA datasets of HNSCC, with OSCC as the predominant subtype, we first identified hnRNPC as a novel independent prognostic biomarker for HNSCC. The high expression of hnRNPC correlated with advanced pathological stages, poor overall survival, and served as a risk factor for clinical outcomes. Functional experiments further confirmed the oncogenic role of hnRNPC in OSCC. Knockdown of hnRNPC inhibited cell proliferation, colony formation, and tumorsphere formation in vitro, and reduced tumor growth in nude mouse xenografts, while also downregulating stemness-related genes (OCT4, SOX2, Nanog). Mechanistically, we revealed that hnRNPC promotes OSCC progression by regulating BCAA metabolism. hnRNPC enhances BCAA uptake, supports BCAT1-dependent energy production (via branched-chain α-ketoacids, BCKAs, entering the TCA cycle) and redox homeostasis (via glutamate-mediated glutathione, GSH, synthesis). Critically, this regulation of BCAT1 by hnRNPC is dependent on m6A modification\u0026mdash;hnRNPC binds to m6A-modified BCAT1 mRNA (predominantly at the +\u0026thinsp;8438 site in the 3'-UTR) to maintain its stability, and METTL3 is required for this recognition. Finally, exogenous supplementation of α-KG, a key metabolite in TCA cylce, rescued the energy deficiency and functional impairment of OSCC cells caused by hnRNPC knockdown, further validating the BCAA metabolic pathway as a downstream effector of hnRNPC.\u003c/p\u003e \u003cp\u003eA major innovation of this study lies in establishing a novel regulatory axis\u0026mdash;hnRNPC/m6A/BCAT1/BCAA metabolism\u0026mdash;that drives OSCC progression, filling critical gaps in current knowledge. Previous studies have separately highlighted the roles of m6A modification (e.g., METTL3, IGF2BP2) and BCAA metabolism (e.g., BCAT1) in OSCC, but their functional connection remained uncharacterized [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Our findings demonstrate that hnRNPC, a classic RNA-binding protein with established oncogenic roles in numorous types of cancer[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], acts as an m6A reader in OSCC to stabilize BCAT1 mRNA. This not only expands the functional spectrum of hnRNPC, beyond mRNA splicing and stability regulation to m6A-dependent metabolic control, but also reveals a unique epigenetic-metabolic crosstalk in OSCC. Specifically, m6A modification, by marking BCAT1 mRNA, enables hnRNPC to fine-tune BCAA metabolism\u0026mdash;an adaptation that supports tumor energy demands (via BCKA-driven oxidative phosphorylation) and antioxidant defense (via glutamate-GSH axis).\u003c/p\u003e \u003cp\u003eNotably, this axis also explains the clinical challenge of chemoresistance in OSCC. Previous work has shown that BCAT1-mediated GSH synthesis reduces drug-induced ROS and DNA damage [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Our study extends this by showing that hnRNPC upregulation enhances this pathway, providing a molecular basis for why high hnRNPC expression correlates with poor prognosis. This mechanistic link offers a new perspective for overcoming chemoresistance, that targeting hnRNPC or BCAT1 could disrupt the BCAA-GSH antioxidant system, sensitizing OSCC cells to cisplatin and other ROS-inducing therapies.\u003c/p\u003e \u003cp\u003eThe hnRNPC/m6A/BCAT1 axis identified in this study has significant clinical potential for the management of OSCC. From a prognostic perspective, hnRNPC could act as a prognostic biomarker. As hnRNPC expression level is combined with pathological stage, it may improve the risk stratification of OSCC patients, which in turn helps clinicians identify patients who are at high risk of recurrence or disease progression. In terms of treatment, targeting this axis provides a new therapeutic strategy. Combined inhibition of hnRNPC (such as through small interfering RNAs or small-molecule inhibitors) and BCAT1 (like using EGR240) can synergistically disrupt BCAA metabolism. This disruption not only reduces the energy supply available to tumor cells and impairs their antioxidant capacity but also makes the cells more sensitive to chemotherapy. Besides, METTL3 inhibitors can block the m6A modification of BCAT1 mRNA, thereby eliminating the stabilization of BCAT1 mRNA mediated by hnRNPC. This approach may help avoid the off-target effects that are often associated with direct inhibition of hnRNPC.\u003c/p\u003e \u003cp\u003eDespite its contributions, this study has several limitations. First, while TCGA datasets provided robust clinical correlation data, the functional experiments were primarily conducted in two OSCC cell lines (CAL-27, SCC-15) and nude mouse xenografts. Validation in additional OSCC cell lines and patient-derived xenograft (PDX) models, which better recapitulate the heterogeneity of clinical OSCC, would strengthen the translational relevance of our findings. Second, while α-KG supplementation rescued hnRNPC knockdown-induced defects, the in vivo efficacy of targeting the hnRNPC/m6A/BCAT1 axis (e.g., using BCAT1 inhibitors like EGR240 or m6A methyltransferase inhibitors) was not evaluated; future studies should test these combination therapies in preclinical models. Finally, the correlation between hnRNPC expression and clinical chemoresistance was not validated using patient samples, which is critical for translating our findings to clinical practice.\u003c/p\u003e \u003cp\u003eIn conclusion, this study reveals a novel epigenetic-metabolic axis in OSCC, demonstrating that hnRNPC promotes BCAA metabolism via m6A-dependent stabilization of BCAT1. These findings not only enhance our understanding of OSCC progression but also provide potential biomarkers and therapeutic targets for improving OSCC patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eThe animal experiments were approved by the ethics committee of ZhenJiang Stomatological Hospital (PJm-20230823) and complied with the National Institutes of Health guide for the care and use of Laboratory animals (NIH Publications No. 8023, revised 1978).\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eSupplementary Fig.\u0026nbsp;1.\u003c/h2\u003e \u003cp\u003eThe appropriate cutoff value based on risk score in the training set\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was supported by the Guidance Program of the Jiangsu Provincial Health Commission (Grant No. Z2022002).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYA designed research. ZZ, XG, TH and FC performed research. ZZ, XG and TH analyzed data. YA wrote the paper.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe TCGA data used in this study are from the cohort GDC TCGA Head and Neck Cancer (HNSC), the relevant gene expression RNAseq data (STAR \u0026ndash; FPKM) can be directly download from the link:https://xenabrowser.net/datapages/?cohort=GDC%20TCGA%20Head%20and%20Neck%20Cancer%20(HNSC)\u0026amp;amp;removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443.All data that support the findings of this study are available from the corresponding authors upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHsu CW, et al. Integrated analyses utilizing metabolomics and transcriptomics reveal perturbation of the polyamine pathway in oral cavity squamous cell carcinoma. Anal Chim Acta. 2019;1050:113\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChamoli A, et al. Overview of oral cavity squamous cell carcinoma: Risk factors, mechanisms, and diagnostics. Oral Oncol. 2021;121:105451.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan Y, et al. Oral squamous cell carcinomas: state of the field and emerging directions. Int J Oral Sci. 2023;15(1):44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatil VM, et al. Beyond conventional chemotherapy, targeted therapy and immunotherapy in squamous cell cancer of the oral cavity. Oral Oncol. 2020;105:104673.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParmar A, et al. Interventions for the treatment of oral cavity and oropharyngeal cancer: chemotherapy. Cochrane Database Syst Rev. 2021;12(12):CD006386.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou Y, et al. Oral squamous cell carcinoma: Insights into cellular heterogeneity, drug resistance, and evolutionary trajectories. Cell Biol Toxicol. 2025;41(1):101.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi BH, Hyun S, Koo SH. The role of BCAA metabolism in metabolic health and disease. Exp Mol Med. 2024;56(7):1552\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQian L, et al. Enhanced BCAT1 activity and BCAA metabolism promotes RhoC activity in cancer progression. Nat Metab. 2023;5(7):1159\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcBrayer SK, et al. Transaminase Inhibition by 2-Hydroxyglutarate Impairs Glutamate Biosynthesis and Redox Homeostasis in Glioma. Cell. 2018;175(1):101\u0026ndash;e11625.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu E, et al. Branched-chain amino acids catabolism and cancer progression: focus on therapeutic interventions. Front Oncol. 2023;13:1220638.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnanieva EA, Wilkinson AC. Branched-chain amino acid metabolism in cancer. Curr Opin Clin Nutr Metab Care. 2018;21(1):64\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeng X, et al. The roles and implications of RNA m(6)A modification in cancer. Nat Rev Clin Oncol. 2023;20(8):507\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong J, Xu K, Lee JH. Biological roles of the RNA m(6)A modification and its implications in cancer. Exp Mol Med. 2022;54(11):1822\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang X, et al. The role of m6A modification in the biological functions and diseases. Signal Transduct Target Ther. 2021;6(1):74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Kesel J, et al. HNRNPC and m6A RNA methylation control oncogenic transcription and metabolism in T-cell leukemia. Blood. 2025;146(3):275\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBi Z, et al. A dynamic reversible RNA N(6) -methyladenosine modification: current status and perspectives. J Cell Physiol. 2019;234(6):7948\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavickas A, et al. An mRNA processing pathway suppresses metastasis by governing translational control from the nucleus. Nat Cell Biol. 2023;25(6):892\u0026ndash;903.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y et al. Function of HNRNPC in breast cancer cells by controlling the dsRNA-induced interferon response. EMBO J, 2018. 37(23).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu Z, et al. Novel reciprocal fusion genes involving HNRNPC and RARG in acute promyelocytic leukemia lacking RARA rearrangement. Haematologica. 2020;105(7):e376\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen JJ, et al. The m6A reader HNRNPC promotes glioma progression by enhancing the stability of IRAK1 mRNA through the MAPK pathway. Cell Death Dis. 2024;15(6):390.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShen L et al. \u003cem\u003eNDRG2 facilitates colorectal cancer differentiation through the regulation of Skp2-p21/p27 axis.\u003c/em\u003e Oncogene, 2018. 37(13): pp. 1759\u0026ndash;1774.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu H, et al. Interaction of lncRNA MIR100HG with hnRNPA2B1 facilitates m(6)A-dependent stabilization of TCF7L2 mRNA and colorectal cancer progression. Mol Cancer. 2022;21(1):74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNie C et al. Branched Chain Amino Acids: Beyond Nutrition Metabolism. Int J Mol Sci, 2018. 19(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuan Y, et al. The role of leucine and its metabolites in protein and energy metabolism. Amino Acids. 2016;48(1):41\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu Y, et al. METTL3 Promotes OSCC Progression by Down-Regulating WEE1 in a m6A-YTHDF2-Dependent Manner. Mol Biotechnol. 2025;67(5):1867\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang D, et al. The m6A Reader IGF2BP2 Promotes Oral Squamous Cell Carcinoma Progression by Maintaining UCA1 Stability. Recent Pat Anticancer Drug Discov; 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan Z, Li M, Tang Z. BCAT1 promotes cell proliferation, migration, and invasion via the PI3K-Akt signaling pathway in oral squamous cell carcinoma. Oral Dis. 2025;31(2):364\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu YY, et al. HNRNPC mediates lymphatic metastasis of cervical cancer through m6A-dependent alternative splicing of FOXM1. Cell Death Dis. 2024;15(10):732.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang N et al. \u003cem\u003ehnRNPC Promotes Malignancy in Pancreatic Cancer through Stabilization of IQGAP3.\u003c/em\u003e Biomed Res Int, 2022. 2022: p. 6319685.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, et al. Branched-Chain Amino Acid Metabolic Reprogramming Orchestrates Drug Resistance to EGFR Tyrosine Kinase Inhibitors. Cell Rep. 2019;28(2):512\u0026ndash;e5256.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Oral squamous cell carcinoma, hnRNPC, BCAT1, m6A modification","lastPublishedDoi":"10.21203/rs.3.rs-8676944/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8676944/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOral squamous cell carcinoma (OSCC) remains a major cause of cancer-related mortality worldwide, with current treatments limited by chemoresistance and long-term toxicities. N6-methyladenosine (m6A) modification regulates mRNA fate to drive cancer progression. However, how m6A modification regulates OSCC progression remains uncharacterized. In this study, we integrated bioinformatics analysis of The Cancer Genome Atlas (TCGA) datasets and experimental validation to explore the role of heterogeneous nuclear ribonucleoprotein C (hnRNPC), an m6A-related RNA-binding protein, in OSCC. Bioinformatics analysis of 515 HNSCC patients identified hnRNPC as a novel independent prognostic biomarker. High hnRNPC expression correlated with advanced pathological stages, poor overall survival, and served as a risk factor for HNSCC. Functional experiments demonstrated that hnRNPC knockdown in OSCC cell lines inhibited cell proliferation, colony formation, tumorsphere formation, and in vivo tumor growth, while downregulating stemness-related genes (OCT4, SOX2, Nanog). Mechanistically, hnRNPC promoted BCAA metabolism in OSCC. High hnRNPC expression was associated with activated BCAA metabolic pathways, and hnRNPC knockdown reduced BCAA uptake, glutamate levels, oxygen consumption rate (OCR), and glutathione (GSH) levels. Further, hnRNPC stabilized BCAT1 mRNA in an m6A-dependent manner. BCAT1 inhibition via EGR240 enhanced the tumor-suppressive effects of hnRNPC knockdown. Exogenous supplementation of α-ketoglutarate (α-KG) rescued energy deficiency and functional defects in hnRNPC-knockdown OSCC cells. Collectively, our findings identify a novel hnRNPC/m6A/BCAT1/BCAA metabolism axis driving OSCC progression. This axis not only explains hnRNPC\u0026rsquo;s prognostic value but also provides a potential therapeutic target for improving OSCC treatment outcomes by disrupting tumor-specific metabolic and epigenetic adaptations.\u003c/p\u003e","manuscriptTitle":"hnRNPC Promotes Oral Squamous Cell Carcinoma Progression via m6A-Dependent Stabilization of BCAT1 to Enhance Branched-Chain Amino Acid Metabolism","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 16:49:08","doi":"10.21203/rs.3.rs-8676944/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0ab51ed7-6b02-4a45-8c91-777244766c57","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T08:29:13+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-11 16:49:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8676944","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8676944","identity":"rs-8676944","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}