Chebulagic acid limits mTOR activity leading to TFEB-driven autophagy and lysosomal biogenesis to suppress the arecoline-induced NLRP3-mediated inflammasome axis in OSCC

Chebulagic acid limits mTOR activity leading to TFEB-driven autophagy and lysosomal biogenesis to suppress the arecoline-induced NLRP3-mediated inflammasome axis in OSCC | 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 Chebulagic acid limits mTOR activity leading to TFEB-driven autophagy and lysosomal biogenesis to suppress the arecoline-induced NLRP3-mediated inflammasome axis in OSCC Prakash Kumar Senapati, Amruta Singh, Rakesh Kumar Kar, Kewal Kumar Mahapatra, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9058916/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Chebulagic acid (CA), a primary compound found in the Indian traditional medicinal plant Terminalia bellirica (TB) (Gaertn.) Roxb. (Bahera) is an important constituent present in the Ayurvedic formulation Triphala churn. CA, a hydrolysable tannin, is known for its anti-inflammatory and antioxidant properties. Chronic exposure to areca nut leads to the development of oral squamous cell carcinoma (OSCC) via activation of the NLRP3-mediated inflammasome axis, driven by the presence of Aricolin. The primary objective of our study is to investigate the role of chebulagic acid in mitigating the arecoline-induced NLRP3-mediated inflammasome via modulation of the mTOR-autophagy-lysosomal biogenesis axis in oral squamous cell carcinoma (OSCC). CAL33 cells were treated with chebulagic acid to study mTOR activities, autophagy, lysosomal biogenesis using western blotting, immunofluorescence, LysoTracker/LysoSensor staining, and molecular docking. Moreover, we used LLOMe to induce lysosomal damage and stress. We find that chebulagic acid inhibits mTORC1 signaling by limiting mTOR lysosomal localization and reducing the phosphorylation of mTOR and p-p70S6K in CAL33 cells. The inhibition of mTOR leads to activation of BECN1-dependent autophagy and TFEB-mediated lysosomal biogenesis. In addition, chebulagic acid reduced the expression of NLRP3, IL-18, and reduced ASC puncta in the arecoline-induced NLRP3-mediated inflammasome condition. Chebulagic acid acts as a key bioactive compound with the potential to limit arecoline-induced NLRP3-mediated inflammasome activation by inhibiting mTOR, followed by the induction of BECN1-dependent autophagy and TFEB-driven lysosomal biogenesis. Autophagy Chebulagic acid Inflammasome Lysosomal biogenesis mTOR NLRP3 TFEB Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Oral squamous cell carcinoma (OSCC) is one of the common cancer burdens globally. OSCC makes up more than 90% of all oral cancer, and there are around 450000 new cases each year across the world [ 1 ]. The overall survival rate of OSCC is still low, even though there is an advancement in therapy and improvement in diagnosis techniques [ 2 ]. However, dysregulation of various cellular signalling pathways, such as autophagy, the mechanistic target of rapamycin (mTOR), lysosomal biogenesis, and the NLRP3-mediated inflammasome axis, serves a vital role in promoting OSCC (Tan et al., 2019; Shi et al., 2025). Therefore, a therapeutic strategy for managing OSCC, based on understanding the above key deregulatory pathways and modulating them with potential natural bioactive compounds, is the major focus. mTOR acts as a key player involved in metabolic signalling pathways, which play a crucial role in maintaining cancer cell progression. mTORC1 signalling integrates with both anabolic and catabolic pathways, which are associated with cancer progression [ 5 ]. In OSCC, the upregulation of mTOR activity serves as a hallmark of cancer [ 6 ]. The lysosomal membrane serves as a signaling platform for regulating metabolic signaling pathways, such as mTORC1 signaling [ 7 ]. Lysosomal activities are essential for regulating the metabolic signalling, cellular clearance, and nutrient recycling. However, dysfunction in the lysosomal activities is also a key reason for cancer progression and survival [ 8 ]. The key regulator of lysosomal biogenesis is TFEB, which is mainly regulated by mTOR signalling. When mTOR is in the active state, it limits TFEB-mediated lysosomal biogenesis by limiting their nuclear localization via phosphorylation. However, when mTOR activity is inhibited, it promotes the TFEB-mediated lysosomal biogenesis and autophagy (Martina et al., 2012; Diez-Roux and Ballabio, 2016). Targeting mTOR activities to regulate lysosomal biogenesis is a novel approach to inhibiting cancer progression. The autophagy events in the cells act as an antagonistic process to the mTOR activities [ 11 ]. The cytoprotective mechanism of autophagy plays a crucial role in regulating cancer progression due to its dual function. Autophagy acts as a cancer-promoting event by providing essential nutrients through the degradation of cargo. At the same time, autophagy acts as a tumor suppressor by removing misfolded, nonfunctional organelles and harmful cargo [ 12 ]. Moreover, excessive autophagy can lead to autosis or, in some cases, autophagic cell death, a type of cell death known as type-II cell death, which acts as a tumor-limiting event [ 13 ]. Arecoline, a primary alkaloid present in areca nuts, is primarily responsible for inducing oral cancer [ 14 ]. A major consequence of arecoline is activation of NLRP3-mediated inflammasome signalling [ 15 ]. However, arecoline not only activates the NLRP3-mediated inflammasome axis but also alters the mTOR signalling pathway, which is associated with cancer progression [ 16 ]. Chebulagic acid (CA), a primary compound found in the Terminalia bellirica (TB) (Gaertn.) Roxb. (Bahera) belongs to the group of hydrolyzable tannins [ 17 ]. Chebulagic acid (CA) is an important constituent present in the Ayurvedic formulation Triphala churn. Continuing exposure to areca nut leads to the development of oral squamous cell carcinoma (OSCC) via activation of the NLRP3-mediated inflammasome axis, driven by the presence of Aricolin. CA is known for its anti-inflammatory and antioxidant nature, but the roles in mTOR inhibition, autophagy induction, lysosomal biogenesis, and inhibition of arecoline-induced NLRP3-mediated inflammasome are yet to be well defined. We aim to examine the role of CA in mitigating the arecoline-induced NLRP3-mediated inflammasome via modulation of the mTOR-autophagy-lysosomal biogenesis axis in OSCC. 2. Materials and Methods 2.1 Reagents Quinic acid (TCI chemicals, Q0009), Gallic acid (TCI chemicals, G0011), Ellagic acid dihydrate (TCI chemicals, E0375), Chebulagic acid (Natural Remedies Pvt Ltd, C004), Chebulinic acid (Natural Remedies Pvt Ltd, C005), MTT (Tokyo Chemical Industry, M3297), DAPI (Sigma-Aldrich, D9542), Hoechst 33342 (Sigma-Aldrich, B2261), LysoTracker Red DND-99 (Invitrogen, L7528), LysoTracker Green DND-26 (Invitrogen, L7526), LysoSensor Yellow/Blue DND-160 (Invitrogen, L7545), L-Leucyl-L-Leucine methyl ester hydrobromide (Sigma, L7393), MHY1485 (MedChemExpress, HY-B0795), Chloroquine (Sigma-Aldrich, C6628), Dimethyl sulfoxide (Sigma-Aldrich, D4540), arecoline (Sigma-Aldrich, TA9H9A1760B0), phosphate buffered saline (PBS 1X for washing; Himedia, M1866-100G), Dulbecco's Modified Eagle Medium (DMEM) (Gibco, Catalog number-12800082), Bovin Serum Albumin (BSA; Himedia, MB083), Triton X-100 (Sigma-Aldrich, X100), formaldehyde solution (4% for fixing; Sigma-Aldrich, 252549), cell lysis buffer (10X; Cell Signaling Technology, 9803), phosphatase inhibitor (Sigma-Aldrich, P0044), protease inhibitor (Sigma-Aldrich, P7626), Lipofectamine 3000 (Invitrogen, L3000015). Antibodies such as Anti-mouse IgG (1:5000; Biobharti, BB-SAB 02 C), Anti-rabbit IgG (1:5000; Biobharti, BB-SAB 01 C), Anti-mouse IgG Alexa Fluor 488 (1:500; Invitrogen, A11001), and Anti-mouse IgG Alexa Fluor 568 (1:500; Invitrogen, A11004), Anti-LC3 (1:1000 for WB and 1:500 for IF; CST, 83506S), Anti-LAMP1 (1:500 for IF; CST, 9091S), Anti-BECN1 (1:1000 for WB; Abclonal, A7353), Anti p62(1:1000, CST-5114), Anti-TFEB(1:1000, Abclonal, A21928), Anti-Actin (1: 100000; Abclonal, AC026), Anti-ATG-5 (1:1000 for WB, Abcam Ab109490), Anti-AMPK1(1:1000 for WB, CST, 2532), Anti-p-AMPK1 (1:1000, CST, 2535), Anti-Ulk1 (1:1000, CST, 8054), Anti-mTOR (1:1000, CST, 2972), Anti-p-mTOR (1:1000 for WB, 1: 200 for IF, CST, 2971), Anti-p70S6K (1:1000 for WB; 1: 200 for IF, Abclonal, A4898), Anti-p-p70S6K (1:1000; Abclonal, AP0564), Anti-NLRP3 (1:1000 for WB; Abclonal, A5652), Anti-IL-1β (1:1000 for WB; Abclonal, A16737), Anti-ASC(1:1000 for WB, 1: 200 for IF, sc-514414), Anti-NRF2 (1:1000 for WB; Abclonal, A0674), and Anti-SOD (1:1000 for WB, sc-137254). 2.2 Cell culture CAL33, a human oral squamous cell carcinoma, from the American Type Culture Collection (ATCC, USA) was maintained using Dulbecco’s Modified Eagle Medium (Himedia, AL151A), with 10% fetal bovine serum albumin (Gibco, 10270106) along with 1% Plasmocin™ prophylactic (ant-mpp) and 5% of antibiotic and antimycotic (Himedia, A002A) in an incubator with 5% CO₂. 2.3 Plasmid and shRNAs To generate stable cell lines, we used shRNAs specific for BECN1 ( shBECN1 , Sigma-Aldrich, TRCN0000299864) and TFEB ( shTFEB , Sigma-Aldrich, TRCN0000437246). For lentivirus production, we used the packaging vector plasmid psPAX2 (Addgene, #12260, from Dr. Didier Trono) and the envelope plasmid pMD2.G (Addgene, #12259, from Dr. Didier Trono). 2.4 Transfection and generation of stable cell lines To perform a knockdown experiment, the shRNAs specific for BECN1 ( shBECN1 ; Sigma-Aldrich, TRCN0000299864) and TFEB ( shTFEB ; Sigma-Aldrich, TRCN0000437246) from Sigma-Aldrich were used for the lentiviral method of stable cell generation. The lentivirus production takes place in the HEK293FT cells using the lentiviral packaging vector plasmid psPAX2 and the envelope plasmid pMD2.G using Lipofectamine® 3000 reagent (Thermo Fisher Scientific, L3000015). Following the manufacturers' instructions, viral particles were harvested at 48 h and 72 h post-treatment. Then, the viral mixture, combined with culture media at a 1:1 ratio and polybrene, was added to CAL33 cells. For stable cell selection, we used puromycin (Sigma-Aldrich, P8833) at a concentration of 500 ng/mL. 2.5 MTT To study the cytotoxicity of the bioactive compounds of TB, CAL33 cells were first seeded at approximately 5000 cells per well in 96-well plates and allowed to attach. After the cells were attached, we administered the treatment for 48 hours. Then, an MTT solution of 5 mg/mL concentration was added to each well, and the incubation lasted for 4 hours. The formazan crystals were formed within the live cells through the reduction of MTT. Then, with Dimethyl sulfoxide (DMSO), the formazan crystals were dissolved, and the absorbance was measured at 570 nm using a BMG LABTECH created FLUOstar Omega microplate reader. Based on the absorbance reading, the % of cell viability was calculated relative to the control. 2.6 Immunofluorescence study Approximately 25,000 CAL33 cells were seeded in the confocal well and allowed to adhere overnight. Then, the cells are treated according to the experimental condition for 24 hours. After the treatment period, the cells were washed with PBS, followed by fixation with 4% formaldehyde for 15 minutes. To reduce nonspecific binding, cells were blocked with 3% BSA in PBS for 1 hour at room temperature. Followed by incubation of the specific primary antibody with the desired dilution with BSA overnight at 4° C. After incubation of the primary antibodies, washing with PBS followed by incubation with appropriate Alexa Fluor conjugated secondary antibodies for 1 h at room temperature in dark conditions. DAPI was used as a counterstain for nuclei. Images were acquired using a Leica STELLARIS 5 confocal microscope (Wetzlar, Germany, Leica Microsystems). For each experimental condition, 15–20 cells from at least three independent setups were analyzed. 2.7 LysoTracker staining To assess lysosomal mass and integrity, LysoTracker Red DND-99 (50 nM, 30 min incubation time; Invitrogen, L7528) was used. Approximately 25,000 CAL33 cells were seeded in the confocal well and allowed to adhere overnight. Then, the cells are treated according to the experimental condition for 24 hours. After the experimental condition, the cells were incubated with LysoTracker Red DND-99 for 30 min at 37°C in the dark. Followed by washing with PBS, the cells were immediately subjected to live cell imaging (for each experimental condition, 15–20 cells from at least three independent setups were analyzed) at the desired laser filter to acquire the images. The acquired images are quantified based on the intensity of red fluorescence using ImageJ (Fiji) software. 2.8 LysoSensor staining To access lysosomal pH, LysoSensor Yellow/Blue DND-160 (50 nM, 5 min incubation time; Invitrogen, L7545) was used. Approximately 25,000 CAL33 cells were seeded in the confocal well and allowed to adhere overnight. Then, the cells are treated according to the experimental condition for 24 hours. After the experimental condition, the cells were incubated with LysoSensor Yellow/Blue DND-160 for 5 min at 37°C in the dark. Followed by washing with PBS, the cells were immediately subjected to live cell imaging (for each experimental condition, 15–20 cells from at least three independent setups were analyzed) at the desired laser filter to acquire the images. The acquired images are quantified based on the intensity of yellow/blue fluorescence using ImageJ (Fiji) software. 2.9 Western blotting To assess protein expression after treatment, approximately 7 × 10⁵ cells were seeded in a 60 mm cell culture plate according to the experimental setup. After 24 hours of treatment, the whole-cell lysates were collected and subjected to lysis using the lysis buffer. The lysate was subjected to protein estimation via following Bradford protocol. In the SDS-PAGE gels, 40 µg of protein was loaded in each well. The gel was then transferred to nitrocellulose membranes, followed by blocking with skim milk for about 2–3 hrs. After blocking, the primary antibody was incubated overnight (12–16 hours) at 4°C with the recommended specific dilution. Then, the washing step was carried out three times, with 10-minute intervals between each wash. The secondary antibody, conjugated with HRP, was used for incubation at room temperature for 2 hours. Following the PBST wash, western blot images were developed using enhanced chemiluminescence (ECL) with the ImageQuant LAS 500 system (GE Healthcare, USA). 2.10 Flow cytometry analysis To evaluate lysosomal content change or to study lysosomal biogenesis, flow cytometry analysis was carried out using LysoTracker Green DND-26 (50 nM incubation time-30 min; Invitrogen, L7526). First, approximately 1 × 10⁵ CAL33 cells were seeded in the 12-well plates and allowed to adhere overnight. Followed by treatment with CA (50,100, and 150 µM) for 24 h. After the experimental condition, the cells were incubated with LysoTracker Green DND-26 for 30 min at 37°C in the dark. Then, followed by PBS wash, the cells were detached from the plate with trypsin and collected by centrifugation. The collected cells were suspended in PBS and subjected to flow cytometry analysis by acquiring 10,000 events with the help of the BD LSRFortessa™ flow cytometer. 2.11 LLOMe washout experiment To study the effect of our bioactive compound on lysosomal recovery after acute damage, we used L-Leucyl-L-Leucine methyl ester hydrobromide (LLOMe, 1000 µM, incubation for 2 h, Sigma, L7393). Approximately 25,000 CAL33 cells were seeded in the confocal well and allowed to adhere overnight. Pre-treatment of LLOMe for 1 h at 37°C induces lysosomal membrane permeabilization. Following three PBS washes to remove the LLOMe, the cells were incubated in fresh media under the desired experimental conditions and treated with CA for 24 hours. After treatment, condition cells were incubated with LysoTracker Red DND-99 (50 nM, 30 min incubation time; Invitrogen, L7528). After a 30-minute incubation period with PBS, the cells are subjected to live cell imaging (for each experimental condition, 15–20 cells from at least three independent setups were analyzed) at the desired filter to acquire images. The acquired images are quantified based on the intensity of red fluorescence using ImageJ (Fiji) software. 2.12 Molecular docking by using PyRx To predict the interaction of CA with key target proteins involved in autophagy, lysosomal biogenesis, mTOR activity, and inflammation signaling, we performed molecular docking using AutoDock Tools integrated within PyRx 0.9.8. The 3D structures of mTOR and NLRP3 were downloaded from the Protein Data Bank (PDB). Similarly, the structure of CA was retrieved from the PubChem database. After preparing the protein ligand, molecular docking was carried out. The top-ranked docked complex with lower binding energy is subjected to protein ligand interaction using PyMOL and BIOVIA Discovery Studio Visualizer. 2.13 UCSC Xena and R language We utilized publicly available transcriptomic and clinical datasets from the UCSC Xena platform ( https://xena.ucsc.edu/ ) to study mTOR and NLRP3 signaling in HNSCC. At the same time, for bioinformatics and statistical analysis, we used the R programming environment (version 4.2.0). The Gene expression matrices were filtered to retain genes of interest, and Z-score normalization was applied for heatmap generation and comparative visualization for our study. 2.14 Statistical analysis For statistical quantification of the experimental data, we used Student’s t-test and one-way ANOVA using GraphPad Prism 9 software. Statistical significance was decided based on p-value, which is represented as: p > 0.05, i.e., ns, not significant; whereas *p < 0.05; **p < 0.01; ***p < 0.001; and ****p < 0.0001. Results 1. screening of the mTOR-inhibiting potential of (TB)-derived bioactive compounds 1. In silico screening of the mTOR-inhibiting potential of Terminalia bellerica (TB)-derived bioactive compounds We performed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to establish the significance of screening mTOR inhibitors in head and neck squamous cell carcinoma (HNSCC). We used the UCSC Xena ( https://xena.ucsc.edu/ ) platform to obtain the TCGA transcriptomic data for HNSCC and analyzed them using the R language to generate KEGG pathway analysis in a bubble plot. The KEGG analysis revealed that the mTOR signaling pathway was the most significantly enriched pathway, characterized by a high gene ratio and a low p-value, in HNSCC. In addition to mTOR Signaling, autophagy, AMPK, and PI3K-Akt signaling were also significantly enriched in the case of HNSCC (Fig. 1 A). Following KEGG pathway enrichment analysis, we performed a heatmap analysis of the overall elevated expression of core mTOR pathway genes across the HNSCC tumor samples (Fig. 1 B). Hierarchical clustering of core mTOR pathway genes in the heatmap revealed that the coordinated upregulation of both mTORC1 and mTORC2-associated genes was widely activated in HNSCC. Then, to further assess whether mTOR signalling was activated in tumor tissue versus normal tissue, hierarchical clustering of HNSCC was performed. The clustering analysis revealed that the majority of tumor samples exhibited mTOR signaling, with a small clustering of normal tissues (Fig. 1 C). Collectively, the above analysis strongly suggests a reasonable target of mTOR signalling using an mTOR inhibitor. Terminalia bellirica (Gaertn.) Roxb. is readily known for its common names, such as Baheda, Bibhitaki, Belleric Myrobalan, Kalidruma, Bhutavasa, and Kaliyugalaya. TB plants have various medicinal properties and are used to cure or alleviate fear associated with various diseases; therefore, in Sanskrit, it's known as “vibheetaki”, which means fearless [ 18 ]. Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMMPAT, https://cb.imsc.res.in/imppat/ ) is a database that provides systematic details about various Indian medicinal plants, their derived bioactive compounds, and their sources, along with their therapeutic applications. According to the IMMPAT platform, TB is reported to contain 54 bioactive compounds. However, Singh et al. (2016) reported the major bioactive compounds present in the TB, which were subjected to screening for mTOR inhibitors in our study (Fig. S1 ). However, based on the literature, we identified five major compounds, including quinic acid, gallic acid, ellagic acid, chebulagic acid, and chebulinic acid, which are mostly found in higher amounts in the TB fruits. These five major compounds found in the TB fruits were then screened for their potential to induce autophagy and inhibit mTOR activity. We performed molecular docking using AutoDock Tools integrated within PyRx 0.9.8. to evaluate the binding affinity of TB fruit-derived bioactive compounds towards the mTOR kinase domain (PDB ID-4JSV, Chain-AC). The molecular docking result shows that quinic acid exhibited the highest binding affinity with a binding energy score of -9.3 kcal/mol, followed by ellagic acid (-9.2 kcal/mol), chebulinic acid (-8.8 kcal/mol), gallic acid (-8.7 kcal/mol), and chebulagic acid (-8.3 kcal/mol) (Fig. S1 ). However, although quinic acid shows a positive binding score, it exhibits a comparatively weaker and less stable interaction. We find that ellagic acid, chebulinic acid, and gallic acid have slightly stronger binding energy than chebulagic acid, but the chebulagic acid displayed a favorable binding orientation within the mTOR active site and formed a stable interaction with key catalytic residues (Fig. 2 A-E). The key bioactive compounds present in various parts of TB are listed in the supplementary information, along with their binding scores when docked with the mTOR kinase (Fig. S1 ). 2. Chebulagic acid inhibits mTOR activities and limits mTORC1 lysosomal membrane localization in a dose-dependent manner After molecular docking, we performed a two-dimensional interaction analysis of CA with the mTOR kinase domain using LigPlot, which revealed that CA formed multiple hydrogen bonds with key amino acid residues, including Gln225, Cys226, His177, Glu49, Leu48, Ser90, and Ala89, indicating stable polar interactions within the active site pocket. In addition to hydrogen bonding, several hydrophobic interactions we observed with residues such as Arg227, Ser175, Trp274, Gly275, Val316, Asn46, and Cys133, which contributed to the overall stabilization of the ligand-protein complex (Fig. 2 E). As CA has a favorable binding orientation within the mTOR active site and forms a stable interaction with key catalytic residues, we selected CA for a detailed investigation of its mTOR inhibitory action. To study the cytotoxicity of the selected five major bioactive compounds of TB, CAL33 cells were first seeded at approximately 5,000 cells per well in the 96-well plates, and the selected compounds, including quinic acid, gallic acid, ellagic acid, chebulagic acid, and chebulinic acid, were administered for 48 hours at varying concentrations. We find that all five bioactive compounds show cytotoxic effects in a dose-dependent manner (Fig. S2 ). Based on the MTT results, we identified five distinct IC50 values, which were subsequently screened for their potential to induce autophagy and inhibit mTOR activity. Next, CAL33 cells were treated with three different doses (50, 100, and 150 µM) of CA, then subjected to western blot and immunofluorescence-based study to evaluate mTOR activity and localization. The immunofluorescence study of p-mTOR revealed a dose-dependent reduction in fluorescence intensity with treatment of CA, confirming the mTOR inhibition potential of CA (Fig. 3 A-D). To further validate this, we examined the expression of the mTOR downstream target p-p70S6K, which also shows a dose-dependent reduction in expression in both the western blot and immunofluorescence studies with CA treatment (Fig. 3 E-H). The above results collectively confirmed the potential of CA to inhibit mTOR and mTORC1 signalling. Moreover, as mTORC1 activation requires the lysosomal membrane localization, we further examined the mTOR-lysosome interaction via mTOR-LAMP1 colocalization using confocal microscopy. The mTOR-LAMP1 colocalization result showed a gradual reduction in colocalization with the treatment of CA, indicating that CA limits mTORC1 activities and signaling via its inhibition of lysosomal membrane localization (Fig. 3 I). 3. Chebulagic acid promotes TFEB-mediated lysosomal biogenesis To examine the role of CA in maintaining the lysosomal pool and biogenesis, we first checked the lysosomal mass using LysoTracker red staining. The dose-dependent treatment with CA results in an increase in the mean LysoTracker red intensity, which was further validated by flow cytometry analysis using LysoTracker green (Fig. 3 C-E). Then, to assess the effect of CA on altering lysosomal acidity, which is crucial for lysosomal function, we used LysoSensor Yellow/Blue. The LysoSensor Yellow/Blue exhibits a yellow color in acidic environments, whereas it emits a blue color in less acidic or neutral environments. We find that with CA treatment, the yellow/blue fluorescence intensity ratio increases dose dependently, suggesting that CA enhances lysosomal acidity to improve lysosomal function (Fig. 3 F, G). Moreover, to understand whether the induced lysosomal activities are due to the upregulation of TFEB, we found that with dose-dependent treatment of CA, the TFEB expression was higher in the western blot (Fig. 3 A, B). Then we genetically knocked out TFEB and performed LysoTracker red and LysoSensor Yellow/Blue staining. Under shTFEB conditions, CA is unable to induce higher LysoTracker red and LysoSensor Yellow fluorescence, indicating that increased lysosomal activity is due to TFEB (Fig. 3 H-K). To check the effect of CA under stress conditions, we used LLOMe, a compound that disrupts the lysosomal membrane and induces lysosomal stress. We find that with LLOMe treatment, the mean LysoTracker red intensity sharply reduces, indicating lysosomal damage. Notably, we find that after pretreatment of CA, the mean LysoTracker intensity recovers, indicating that CA has the potential to protect lysosomes from LLOMe-induced lysosomal damage (Fig. 3 L, M). Next, we examined the lysosomal activity in the presence of MHY1485, a potent cell-permeable mTOR activator that targets the ATP domain of mTOR in CAL33 cells. Our data showed that CA in MHY1485-pretreated cells markedly reduces the LysoTracker intensity, suggesting that CA counteracts mTOR-driven TFEB suppression and promotes lysosomal biogenesis (Fig. 3 N, O). 4. Chebulagic acid induces BECN1-dependent autophagy and induces autophagic flux dose dependently To screen out compounds with autophagy-inducing potential, LC3 puncta formation was assessed by confocal microscopy for all five selected bioactive compounds found in the TB fruits. Among the five major bioactive compounds derived from TB fruits, gallic acid, ellagic acid, chebulagic acid (CA), and chebulinic acid have been shown to have the potential to induce autophagy (Fig. S3). Our group also previously worked on gallic acid derived from TB-derived fruit. We showed that gallic acid induces autophagy and alters the NRF2 signalling pathway [ 19 ]. Similarly, various studies related to autophagy have already been explored on ellagic acid and chebulinic acid. The LC3 puncta analysis result indicates that among the five compounds in TB fruits, CA exhibits a higher number of LC3 puncta in CAL33 cells (Fig. S3C). Moreover, the accumulation of LC3 II was assessed using western blotting, which showed that gallic acid, ellagic acid, chebulagic acid (CA), and chebulinic acid have higher LC3 accumulation compared to the known mTOR inhibitor, rapamycin (Fig. S3A, B). Furthermore, to investigate the role of CA on autophagy, CAL33 cells were treated with 50, 100, and 150 µM of CA and analyzed via immunofluorescence and western blot analysis. The LC3 puncta analysis revealed a dose-dependent increase in the number of LC3 puncta per cell as compared to the control (Fig. 5 C, D). The western blot analysis also showed a gradual increase in the LC3-II/LC3-I ratio in CAL33 cells. In parallel, the expression of other autophagy markers, such as ATG5, ULK1, and p-AMPK, was increased with decreased p62 expression, indicating active autophagic degradation (Fig. 5 A, 5 B, S4). To study the role of autophagy in autophagosome and lysosome fusion, LC3 and LAMP1 colocalization study was performed. The LC3-LAMP1 colocalization study shows that with an increase in the dose of CA, the colocalization increased (Fig. 5 G, H). The increased colocalization of LC3-LAMP1 indicates the efficient fusion of autophagosomes and lysosomes induced by CA. Autophagic flux-inducing potential of CA was analyzed using chloroquine (CQ) with the help of LC3 puncta analysis. The LC3 puncta in the case of co-treatment with CA and CQ were higher compared to treatment conditions with CA or CQ alone, which indicates that CA induces autophagic flux (Fig. 5 I, J). Furthermore, to investigate the role of CA in the genetic regulation of autophagy, LC3 puncta analysis was performed under the shBECN1 condition. The LC3 puncta study revealed that under shBECN1 conditions, CA is unable to induce higher LC3 puncta per cell, indicating that it induces BECN1-dependent autophagy (Fig. 5 E, F). Moreover, to understand whether the induced autophagy is due to the upregulation of TFEB, we genetically knocked out TFEB and performed LC3 puncta analysis. We find that under shTFEB conditions, CA is unable to induce higher LC3 puncta, indicating that it induces autophagy through TFEB activation (Fig. 5 K, L). Lastly, to assess the potential of CA in overcoming the mTOR activation condition, we used MHY1485, which is known to suppress autophagy. As expected, CA showed a marked reduction in LC3 puncta in exposure to MHY1485 as compared to only CA treatment, indicating that CA has the potential to counteract mTOR activation and induce autophagy (Fig. 5 M, N). 5. Chebulagic acid limits the arecoline-induced NLRP3-mediated inflammasome axis Next, we investigated the activation of NLRP3 signaling in tumor tissue versus normal tissue using hierarchical clustering of HNSCC TCGA data from the UCSC Xena platform ( https://xena.ucsc.edu/ ) and the R language. The clustering analysis revealed that the majority of tumor samples exhibited NLRP3 signaling with a small clustering of normal tissues. We then performed a heatmap analysis of the overall elevated expression of core NLRP3 pathway-related genes across HNSCC tumor samples using TCGA data from the UCSC Xena platform and the R language. Hierarchical clustering of core NLRP3 signalling pathway-related genes in the heatmap revealed that the upregulation of NLRP3 signaling-associated genes was widely activated in HNSCC (Fig. 6 A, B). Furthermore, to investigate the direct interaction of CA with the NLRP3 inflammasome complex, we performed molecular docking using Autodock with the crystal structure of NLRP3 (PDB ID: 8RI2). We find that CA exhibits a favorable and stable interaction with NLRP3, with a docking score of -7.4 kcal/mol (Fig. 6 C). Then, to assess the role of CA in modulating the NLRP3-mediated inflammasome axis, we first performed western blot analysis of the inflammasome signaling player NLRP3 and IL-18. To evaluate the effect of CA under proinflammatory conditions, we used arecoline to induce the NLRP3-mediated inflammasome. The western blot analysis showed that the expression of NLRP3 and IL-18 was increased with arecoline treatment (100 µM, 24 h, Sigma-Aldrich, TA9H9A1760B0). However, CA treatment marked reduced of arecoline-induced NLRP3 and IL-18 expression, which depicts the potential of CA in limiting the NLRP3-mediated inflammasome axis (Fig. 6 D, E). Since ASC speck formation is a characteristic event of NLRP3 inflammasome activation, we next checked ASC puncta formation using confocal microscopy during the CA treatment condition. The results showed a marked reduction in ASC puncta with dose-dependent treatment of CA (Fig. 6 F, G). To understand the role of CA-induced TFEB in limiting the NLRP3-mediated inflammasome axis, we checked the ASC puncta in shTFEB cells under arecoline pretreatment conditions. Our data showed that TFEB knockdown markedly increased the ASC puncta during CA treatment under arecoline-induced NLRP3 inflammasome activation in CAL33 cells (Fig. 6 H, I). Based on the above data, we concluded that CA induces TFEB, which plays an essential role in limiting the NLRP3-mediated inflammasome axis. Discussion The mTOR signalling is a central regulatory pathway that plays a crucial role in maintaining cellular metabolic status, which is often altered in various cancers. In HNSCC, the mTOR pathways are most commonly upregulated and represent as a major molecular hallmark [ 3 ]. It showed that Triphala inhibits the mTOR/PI3K/Akt signaling pathways in oral cancer [ 20 ]. To dissect the bioactive natural mTOR inhibitor from Triphala, our study investigated the role of TB fruit-derived bioactive compounds in inhibiting mTOR activity. Singh et al. (2016) study reported the major bioactive compounds present in the TB, which were subsequently used for screening of mTOR inhibitors in our study [ 21 ]. A study reported that the bioactive compound CA, primarily found in the TB fruits, exhibits neuroprotective effects in the SHSY5Y cell line, with limited mTOR activity [ 22 ]. Our results reveal that treatment with CA in oral cancer cells markedly inhibits mTOR activity. Moreover, it has been reported that mTORC1 activation requires localization to the lysosomal membrane [ 7 ]. Our mTOR-LAMP1 colocalization data also support that treatment with CA significantly reduces the lysosomal localization of mTOR, indicating that CA limits mTORC1 activities and signaling by inhibiting lysosomal membrane localization in OSCC. TFEB acts as a master regulator of lysosomal biogenesis [ 23 ]. A previous study reported that mTORC1 acts as a transcriptional regulator of lysosomal biogenesis and autophagy via regulating TFEB activities [ 9 ]. The study also indicates that the overexpression of TFEB leads to an increase in lysosomes within the cells [ 10 ]. We find that CA treatment increases the lysosomal mass and lysosomal acidity, as demonstrated by LysoTracker red and LysoSensor Yellow/Blue staining, through TFEB activation. LLOMe inactivates the lysosomal cysteine cathepsins by transiently permeabilizing the lysosomal membrane [ 24 ]. We find that after pretreatment of CA, the mean LysoTracker intensity recovers, indicating that CA has the potential to protect lysosomes from LLOMe-induced inactivation of lysosomal cysteine cathepsins and maintain lysosomal biogenesis in oral cancer cells. Previous reports showed that CA induces autophagy in SHSY5Y cells, leading to neuroprotective effects [ 22 ]. We find that CA also promotes autophagy and maintains autophagic flux in a BECN1-dependent way. Arecoline, the principal alkaloid of areca nut, is known as an inducer of oxidative stress and the NLRP3-mediated inflammasome axis. A recent study also reported that CA is involved in improving oxidative stress and the inflammasome in diabetic rats [ 25 ]. Triphala-loaded nanoparticles inhibit the NLRP3-mediated inflammasome in Lung cells [ 26 ]. Our hierarchical clustering of studies on NLRP3 signaling in the context of HNSCC, along with a comparison of normal versus tumor samples, suggests that NLRP3 signaling is most prevalent in HNSCC. We found that with the treatment of CA in the arecoline pretreatment condition, the expression of NLRP3 and IL-1β is markedly reduced, supporting that CA limits arecoline-induced inflammasome signaling. Various studies reported that TFEB attenuates NLRP3 signalling and promotes autophagic degradation of NLRP3. Our result also shows that TFEB knockdown markedly increased the ASC puncta during CA treatment under arecoline-induced NLRP3 inflammasome activation. From our data, we concluded that CA induces TFEB, which plays a crucial role in limiting the NLRP3-mediated inflammasome axis. Collectively, our findings highlight the therapeutic applications of CA, a major bioactive compound of TB fruits, which limits arecoline-induced NLRP3 signalling in OSCC. CA markedly suppressed mTOR activities by limiting lysosomal localization, which in turn facilitates TFEB-driven lysosomal biogenesis and autophagy. Our data suggest that CA can be used as a target against oncogenic mTOR signalling and arecoline-induced NLRP3-mediated inflammation in OSCC, which needs further exploration in an in vivo model. Abbreviations BECN1 Beclin1 CA chebulagic acid mTOR Mechanistic Target of Rapamycin NLRP3 NOD-like Receptor Family Pyrin Domain Containing 3 LLOMe L-Leucyl-L-Leucine methyl ester hydrobromide TB Terminalia bellirica and TFEB Transcription Factor EB Declarations Authors’ Contributions Prakash Kumar Senapati: Conceptualization , Writing original draft, Validation, Methodology, Visualization, Investigation, Amruta Singh : Formal analysis, Conceptualization, Methodology, Writing review and editing, Rakesh Kumar Kar: Experimental execution and data analysis, Kewal Kumar Mahapatra: Investigation, Validation, Formal analysis, Writing Review and editing Mrutyunjay Jena and Swatilekha Maiti: provided technical inputs and assisted with manuscript refinement, Sujit Kumar Bhutia: Conceptualization, Writing original draft, validation, Methodology, Visualization, Investigation, Formal analysis and editing, Funding acquisition, Supervision. Funding This work was supported by the Department of Biotechnology (DBT), Government of India (Grant No. BT/PR42013/TRM/120/508/2021). Prakash Kumar Senapati gratefully acknowledges financial support from the Department of Science and Technology (DST), Government of India, through the INSPIRE Fellowship (No. DST/INSPIRE Fellowship/2022/IF220331). Data Availability The datasets generated or analyzed during the study are available from the corresponding author upon reasonable request. Competing Interests All the authors declared they have no competing interests Disclosure Statement All authors declared no conflict of interest . Ethical approval and consent to participate: NA Acknowledgements Prakash Kumar Senapati (PKS) gratefully acknowledges the Government of India, Ministry of Science and Technology, Department of Science and Technology (DST) for financial support through the INSPIRE Fellowship (No. DST/INSPIRE Fellowship/2022/IF220331). Partial research funding was also provided by the Department of Biotechnology (DBT), Government of India (Grant No. BT/PR42013/TRM/120/508/2021). The authors sincerely regret any inadvertent omission of relevant original contributions and note that priority has been given to citing recent publications that comprehensively document earlier work. References Tan, Y., Wang, Z., Xu, M., Li, B., Huang, Z., Qin, S., & Huang, C. (2023). Oral squamous cell carcinomas: state of the field and emerging directions. International Journal of Oral Science , 15 (1), 44. https://doi.org/10.1038/s41368-023-00249-w Dong, L., Xue, L., Cheng, W., Tang, J., Ran, J., & Li, Y. (2024). Comprehensive survival analysis of oral squamous cell carcinoma patients undergoing initial radical surgery. BMC oral health , 24 (1), 919. https://doi.org/10.1186/s12903-024-04690-z Tan, F. H., Bai, Y., Saintigny, P., & Darido, C. (2019). mTOR Signalling in Head and Neck Cancer: Heads Up. Cells , 8 (4). https://doi.org/10.3390/cells8040333 Shi, R., Zhuang, X., Liu, T., Yao, S. N., & Xue, F. S. (2025). The Role of NLRP3 Inflammasome in Oral Squamous Cell Carcinoma. Journal of inflammation research , 18 , 5601–5609. https://doi.org/10.2147/JIR.S512770 Ben-Sahra, I., & Manning, B. D. (2017). mTORC1 signaling and the metabolic control of cell growth. Current opinion in cell biology , 45 , 72–82. https://doi.org/10.1016/j.ceb.2017.02.012 Harsha, C., Banik, K., Ang, H. L., Girisa, S., Vikkurthi, R., Parama, D., & Kunnumakkara, A. B. (2020). Targeting AKT/mTOR in Oral Cancer: Mechanisms and Advances in Clinical Trials. International journal of molecular sciences , 21 (9). https://doi.org/10.3390/ijms21093285 Cui, Z., Esposito, A., Napolitano, G., Ballabio, A., & Hurley, J. H. (2025). Structural basis for mTORC1 activation on the lysosomal membrane. Nature , 647 (8089), 536–543. https://doi.org/10.1038/s41586-025-09545-3 Zhu, S., Yao, R., Li, Y., Zhao, P., Ren, C., Du, X., & Yao, Y. (2020). Lysosomal quality control of cell fate: a novel therapeutic target for human diseases. Cell Death & Disease , 11 (9), 817. https://doi.org/10.1038/s41419-020-03032-5 Martina, J. A., Chen, Y., Gucek, M., & Puertollano, R. (2012). MTORC1 functions as a transcriptional regulator of autophagy by preventing nuclear transport of TFEB. Autophagy , 8 (6), 903–914. https://doi.org/10.4161/auto.19653 Diez-Roux, G., & Ballabio, A. (2016). TFEB, Master Regulator of Cellular Clearance. In Lysosomes: Biology, Diseases, and Therapeutics (pp. 101–114). https://doi.org/https://doi.org/10.1002/9781118978320.ch7 Kim, Y. C., & Guan, K. L. (2015). mTOR: a pharmacologic target for autophagy regulation. The Journal of clinical investigation , 125 (1), 25–32. https://doi.org/10.1172/JCI73939 Patergnani, S., Missiroli, S., Morciano, G., Perrone, M., Mantovani, C. M., Anania, G., & Giorgi, C. (2021). Understanding the Role of Autophagy in Cancer Formation and Progression Is a Real Opportunity to Treat and Cure Human Cancers. Cancers , 13 (22). https://doi.org/10.3390/cancers13225622 Senapati, P. K., Mahapatra, K. K., Singh, A., & Bhutia, S. K. (2025). mTOR inhibitors in targeting autophagy and autophagy-associated signaling for cancer cell death and therapy. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer , 1880 (3), 189342. https://doi.org/https://doi.org/10.1016/j.bbcan.2025.189342 Leng, L., Wang, X., Wang, H., Hu, Y., Deng, Y., & Wang, C. (2025). Molecular mechanisms of arecoline-induced oral cancer: a network toxicology and molecular docking techniques integrated analysis. Discover oncology , 16 (1), 842. https://doi.org/10.1007/s12672-025-02659-0 You, Y., Huang, Y., Wang, D., Li, Y., Wang, G., Jin, S., & Li, X. (2019). Angiotensin (1–7) inhibits arecoline-induced migration and collagen synthesis in human oral myofibroblasts via inhibiting NLRP3 inflammasome activation. Journal of Cellular Physiology , 234 (4), 4668–4680. https://doi.org/https://doi.org/10.1002/jcp.27267 Gu, L., Xie, C., Peng, Q., Zhang, J., Li, J., & Tang, Z. (2019). Arecoline suppresses epithelial cell viability through the Akt/mTOR signaling pathway via upregulation of PHLPP2. Toxicology , 419 , 32–39. https://doi.org/10.1016/j.tox.2019.03.006 Guggilla, M., Chow, S., & Siow, L. (2022). Supercritical Fluid Extraction of Chebulagic acid from Terminalia Bellirica Fruits (Baheda). Journal of Food Processing and Preservation , 46 . https://doi.org/10.1111/jfpp.16455 Gupta, A., Kumar, R., Bhattacharyya, P., Bishayee, A., & Pandey, A. K. (2020). Terminalia bellirica (Gaertn.) roxb. (Bahera) in health and disease: A systematic and comprehensive review. Phytomedicine , 77 , 153278. https://doi.org/https://doi.org/10.1016/j.phymed.2020.153278 Patra, S., Bhol, C. S., Panigrahi, D. P., Praharaj, P. P., Pradhan, B., Jena, M., & Bhutia, S. K. (2020). Gamma irradiation promotes chemo-sensitization potential of gallic acid through attenuation of autophagic flux to trigger apoptosis in an NRF2 inactivation signalling pathway. Free radical biology & medicine , 160 , 111–124. https://doi.org/10.1016/j.freeradbiomed.2020.06.022 Hu, S., Li, S., Xu, Y., Huang, X., Mai, Z., Chen, Y., … Hu, X. (2024). The antitumor effects of herbal medicine Triphala on oral cancer by inactivating PI3K/Akt signaling pathway: based on the network pharmacology, molecular docking, in vitro and in vivo experimental validation. Phytomedicine: international journal of phytotherapy and phytopharmacology , 128 , 155488. https://doi.org/10.1016/j.phymed.2024.155488. Singh, A., Bajpai, V., Kumar, S., Kumar, B., Srivastava, M., & Rameshkumar, K. B. (2016). Comparative profiling of phenolic compounds from different plant parts of six Terminalia species by liquid chromatography–tandem mass spectrometry with chemometric analysis. Industrial Crops and Products , 87 , 236–246. https://doi.org/https://doi.org/10.1016/j.indcrop.2016.04.048 Kim, H. J., Kim, J., Kang, K. S., Lee, K. T., & Yang, H. O. (2014). Neuroprotective Effect of Chebulagic Acid via Autophagy Induction in SH-SY5Y Cells. Biomolecules & therapeutics , 22 (4), 275–281. https://doi.org/10.4062/biomolther.2014.068 Bala, S., & Szabo, G. (2018). TFEB, a master regulator of lysosome biogenesis and autophagy, is a new player in alcoholic liver disease. Digestive medicine research , 1 . https://doi.org/10.21037/dmr.2018.09.03 Repnik, U., Borg Distefano, M., Speth, M. T., Ng, M. Y. W., Progida, C., Hoflack,B., … Griffiths, G. (2017). L-leucyl-L-leucine methyl ester does not release cysteine cathepsins to the cytosol but inactivates them in transiently permeabilized lysosomes. Journal of cell science , 130 (18), 3124–3140. https://doi.org/10.1242/jcs.204529. Sundaram, R., Karuppiah, M., Almansour, A., Natarajan, A., & Perumal, K. (2024). Chebulagic Acid Ameliorates Oxidative Stress and Inflammation via Regulation of Insulin Signaling Pathway in High-Fat Diet/Streptozotocin-Induced Diabetic Rats. Revista Brasileira de Farmacognosia , 35 . https://doi.org/10.1007/s43450-024-00600-0 Chittasupho, C., Umsumarng, S., Srisawad, K., Arjsri, P., Phongpradist, R., Samee,W., … Dejkriengkraikul, P. (2024). Inhibition of SARS-CoV-2-Induced NLRP3 Inflammasome-Mediated Lung Cell Inflammation by Triphala-Loaded Nanoparticle Targeting Spike Glycoprotein S1. Pharmaceutics , 16 (6). https://doi.org/10.3390/pharmaceutics16060751. Supplementary Files Supplementarywesternblotuncropeddata.docx Supplementary.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 20 Apr, 2026 Reviewers invited by journal 19 Apr, 2026 Editor invited by journal 15 Mar, 2026 Editor assigned by journal 10 Mar, 2026 First submitted to journal 09 Mar, 2026 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-9058916","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":625927290,"identity":"8d1f35d6-ad1f-45a2-b93d-0b7bc3557f24","order_by":0,"name":"Prakash Kumar Senapati","email":"","orcid":"","institution":"NIT Rourkela: National Institute of Technology Rourkela","correspondingAuthor":false,"prefix":"","firstName":"Prakash","middleName":"Kumar","lastName":"Senapati","suffix":""},{"id":625927291,"identity":"297c271f-2700-41ad-8502-8f90347c3281","order_by":1,"name":"Amruta Singh","email":"","orcid":"","institution":"NIT Rourkela: National Institute of Technology Rourkela","correspondingAuthor":false,"prefix":"","firstName":"Amruta","middleName":"","lastName":"Singh","suffix":""},{"id":625927292,"identity":"8d616eed-17c7-4791-af0c-aea188a35516","order_by":2,"name":"Rakesh Kumar Kar","email":"","orcid":"","institution":"NIT Rourkela: National Institute of Technology Rourkela","correspondingAuthor":false,"prefix":"","firstName":"Rakesh","middleName":"Kumar","lastName":"Kar","suffix":""},{"id":625927293,"identity":"6ba29318-6695-4662-b90f-e8c78991d68b","order_by":3,"name":"Kewal Kumar Mahapatra","email":"","orcid":"","institution":"C V Raman Global University","correspondingAuthor":false,"prefix":"","firstName":"Kewal","middleName":"Kumar","lastName":"Mahapatra","suffix":""},{"id":625927294,"identity":"72af1a47-2be5-426f-bd1b-efce07cd3812","order_by":4,"name":"Swatilekha Maiti","email":"","orcid":"","institution":"Garhbeta College","correspondingAuthor":false,"prefix":"","firstName":"Swatilekha","middleName":"","lastName":"Maiti","suffix":""},{"id":625927295,"identity":"ac88eb57-8f22-494e-b197-004305cf4c63","order_by":5,"name":"Mrutyunjay Jena","email":"","orcid":"","institution":"Berhampur University","correspondingAuthor":false,"prefix":"","firstName":"Mrutyunjay","middleName":"","lastName":"Jena","suffix":""},{"id":625927296,"identity":"2e4f2741-fa2e-4bc9-aafe-3e64f7dd8976","order_by":6,"name":"Sujit K Bhutia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIie2RMQrCMBSGfwmki9bVLVdIcZWe5ZWCk7i4KA4WhDq5u3mNjikFXaqugkvFC9QbmAiKU+MomI8sgffxPniAw/GbkGolA3CAoTJ/9o2SJ0NwrmfpSwXIkwJ4KzbEhq7FPTuNfbG+SUIo4HVUoyLPpMPKy4Rzr0+EOEiY37xM9oySXqKUc6YITL+2tIUZ5fhSFnYFz7BUPRUdVtgVWVakDmWslSGTJPdBag1bjeJ6loXRdrljvXo6F91uaQlDmz6XmvtY8ZR9xuFwOP6bB5snQn64aYOJAAAAAElFTkSuQmCC","orcid":"","institution":"NIT Rourkela: National Institute of Technology Rourkela","correspondingAuthor":true,"prefix":"","firstName":"Sujit","middleName":"K","lastName":"Bhutia","suffix":""}],"badges":[],"createdAt":"2026-03-07 13:54:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9058916/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9058916/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108012177,"identity":"0884045a-6e02-4609-8622-43a0cc6589c6","added_by":"auto","created_at":"2026-04-28 13:15:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":7711586,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emTOR signaling is dysregulated in head and neck squamous cell carcinoma (HNSCC). \u003c/strong\u003e(A) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified the mTOR signaling pathway as the most significantly enriched pathway in HNSCC, characterized by a high gene ratio and low p-value. (B) Heatmap analysis of the mTOR signaling pathway gene expression. (C) Hierarchical clustering of mTOR signaling in the case of HNSCC and comparison of normal vs tumor samples.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/b88cfd983d0fdfc8ee0786cc.png"},{"id":108012220,"identity":"280961ec-28a3-4b25-bf04-b67969012076","added_by":"auto","created_at":"2026-04-28 13:15:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":39490465,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMolecular docking of TB fruit-derived five major bioactive compounds. \u003c/strong\u003e(A) Molecular docking of Quinic acid with mTOR kinase domain (PDB ID-4JSV, Chain-AC), (B) Molecular docking of Gallic acid with mTOR kinase domain, (C) Molecular docking of Ellagic acid with mTOR kinase domain, (D) Molecular docking of Chebulinic acid with mTOR kinase domain, (E) Molecular docking of Chebulagic acid with mTOR kinase domain, and (F) Two-dimensional interaction of CA with the mTOR kinase domain using LigPlot. Molecular docking was performed using AutoDock Tools, integrated within PyRx 0.9.8, and the interactions were visualized by using PyMOL.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/51745bdac4af7f72efd89db3.png"},{"id":108012195,"identity":"3aa51013-3f1d-419e-bfac-35271b015992","added_by":"auto","created_at":"2026-04-28 13:15:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26586913,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChebulagic acid hinders mTOR activities and limits mTORC1 lysosomal membrane localization in a dose-dependent manner. \u003c/strong\u003e(A) Western blot analysis of p-mTOR and total mTOR during CA (50μM,100μM, and 150μM concentrations) treatment condition, (B) Normalized p-mTOR/mTOR expression (C) Immunofluorescence staining of p-mTOR during treatment of CA, (D) Quantification of p-mTOR fluorescence intensity, (E) Western blot analysis of p-p70S6K and total p70S6K, (F) Normalized p-p70S6K and p70S6K expression, (G) Immunofluorescence staining of p-p70S6K during treatment of CA, (H) Quantification of p-p70S6K fluorescence intensity, (I) p-mTOR-LAMP1 colocalization study. For statistical quantification of the experimental data, we used Student’s t-test and one-way ANOVA using GraphPad Prism 9 software. Statistical significance was decided based on p-value, which is represented as: p \u0026gt; 0.05, i.e., ns, not significant; whereas *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; and ****p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/706ffdaf7d88ff1bd14bc7a9.png"},{"id":108012535,"identity":"43f7535c-2b46-4340-87c6-834964345cc6","added_by":"auto","created_at":"2026-04-28 13:15:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":25541492,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChebulagic acid promotes TFEB-mediated lysosomal biogenesis. \u003c/strong\u003e(A) Western blot analysis of TFEB during CA (50μM,100μM, and 150μM concentrations) treatment condition, (B) Western blot quantification of TFEB, (C) Flow cytometry analysis to assess lysosomal quantity LysoTracker green, (D) LysoTracker red staining during CA treatment condition, (E) Quantification of LysoTracker red staining, (F) LysoSensor Yellow/Blue staining during CA (50,100, and 150 μM concentrations) treatment condition, (G) Quantification of LysoSensor Yellow/Blue staining during CA treatment condition, (H) LysoTracker red staining during \u003cem\u003eshTFEB\u003c/em\u003econdition, (I) Quantification of LysoTracker red staining during shTFEB condition, (J) LysoSensor Yellow/Blue staining during \u003cem\u003eshTFEB\u003c/em\u003e condition, (K) Quantification of LysoSensor Yellow/Blue staining during \u003cem\u003eshTFEB \u003c/em\u003econdition, (L) LysoTracker red staining during LLOMe\u003cem\u003e \u003c/em\u003etreatment condition, (M) Quantification of LysoTracker red staining during LLOMe\u003cem\u003e \u003c/em\u003etreatment condition, (N) LysoTracker red staining during MHY1485\u003cem\u003e \u003c/em\u003etreatment condition, and (O) Quantification of LysoTracker red staining during MHY1485\u003cem\u003e \u003c/em\u003etreatment condition. For statistical quantification of the experimental data, we used Student’s t-test and one-way ANOVA using GraphPad Prism 9 software. Statistical significance was decided based on p-value, which is represented as: p \u0026gt; 0.05, i.e., ns, not significant; whereas *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; and ****p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/cf819544eb33e3ce6a1db29c.png"},{"id":108012445,"identity":"d5821759-b3f1-45f8-92ba-d84f2090dba7","added_by":"auto","created_at":"2026-04-28 13:15:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":31254706,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChebulagic acid promotes BECN1-dependent autophagy and induces autophagic flux in a dose-dependent manner. \u003c/strong\u003e(A) Western blot analysis of autophagy markers ULK1, p-AMPK, and AMPK, (B) Western blot analysis of autophagy markers p62, ATG5, and LC3, (C) LC3 puncta analysis during CA (50, 100, and 150 μM concentrations) treatment condition, (D) Quantification of LC3 puncta, (E) LC3 puncta analysis during \u003cem\u003eshBECN1\u003c/em\u003econdition, (F) Quantification of LC3 puncta during \u003cem\u003eshBECN1\u003c/em\u003e condition, (G) LC3-LAMP1 colocalization study during CA treatment condition, (H) Quantification of LC3-LAMP1 colocalization, (I) LC3 puncta analysis during CQ treatment condition, (J) Quantification of LC3 puncta during CQ treatment condition, (K) LC3 puncta analysis during \u003cem\u003eshTFEB\u003c/em\u003e condition, (L) Quantification of LC3 puncta during \u003cem\u003eshTFEB\u003c/em\u003e condition, (M) LC3 puncta analysis during MHY1485 treatment condition, and (N) Quantification of LC3 puncta during MHY1485 treatment condition. For statistical quantification of the experimental data, we used Student’s t-test and one-way ANOVA using GraphPad Prism 9 software. Statistical significance was decided based on p-value, which is represented as: p \u0026gt; 0.05, i.e., ns, not significant; whereas *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; and ****p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/d316379a8cace9ab6b46ba8a.png"},{"id":108012713,"identity":"7851b925-4682-43c0-861e-ab3d65f6361a","added_by":"auto","created_at":"2026-04-28 13:16:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":26362142,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChebulagic acid limits the arecoline-induced NLRP3-mediated inflammasome axis. \u003c/strong\u003e(A) Hierarchical clustering of NLRP3 signaling in the case of HNSCC and comparison of normal vs tumor samples, (B) Heatmap analysis of the NLRP3 signaling pathway gene expression, (C) Molecular docking of CA with NLRP3 (PDB ID: 8RI2) and their 2D interaction study using LigPlot, (D) Western blot analysis of NLRP3 and IL-1β, (E) Normalized expression of IL-1β, (F) ASC puncta analysis during CA treatment condition, (G) Quantification ASC puncta during CA treatment condition, (H) ASC puncta analysis during \u003cem\u003eshTFEB\u003c/em\u003e condition, and (I) Quantification ASC puncta during \u003cem\u003eshTFEB\u003c/em\u003econdition. For statistical quantification of the experimental data, we used Student’s t-test and one-way ANOVA using GraphPad Prism 9 software. Statistical significance was decided based on p-value, which is represented as: p \u0026gt; 0.05, i.e., ns, not significant; whereas *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; and ****p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/c14491162a28a45078e7560a.png"},{"id":108013368,"identity":"f0000f98-b33f-4c2f-807a-8dcd79f89afc","added_by":"auto","created_at":"2026-04-28 13:18:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":140983182,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/3a78b57c-16f4-4c70-bdd7-eaba2b275fb2.pdf"},{"id":108012427,"identity":"a23c944e-c213-4f40-865e-b032f8478aef","added_by":"auto","created_at":"2026-04-28 13:15:40","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":708050,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarywesternblotuncropeddata.docx","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/5bb3a93cd52ff9db895cfd0e.docx"},{"id":108012810,"identity":"16092a35-8e68-4a1a-bf8c-d18f4557930d","added_by":"auto","created_at":"2026-04-28 13:16:26","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":1558966,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-9058916/v1/906272deb08e1feb5785a99f.docx"}],"financialInterests":"","formattedTitle":"Chebulagic acid limits mTOR activity leading to TFEB-driven autophagy and lysosomal biogenesis to suppress the arecoline-induced NLRP3-mediated inflammasome axis in OSCC","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOral squamous cell carcinoma (OSCC) is one of the common cancer burdens globally. OSCC makes up more than 90% of all oral cancer, and there are around 450000 new cases each year across the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The overall survival rate of OSCC is still low, even though there is an advancement in therapy and improvement in diagnosis techniques [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, dysregulation of various cellular signalling pathways, such as autophagy, the mechanistic target of rapamycin (mTOR), lysosomal biogenesis, and the NLRP3-mediated inflammasome axis, serves a vital role in promoting OSCC (Tan et al., 2019; Shi et al., 2025). Therefore, a therapeutic strategy for managing OSCC, based on understanding the above key deregulatory pathways and modulating them with potential natural bioactive compounds, is the major focus. mTOR acts as a key player involved in metabolic signalling pathways, which play a crucial role in maintaining cancer cell progression. mTORC1 signalling integrates with both anabolic and catabolic pathways, which are associated with cancer progression [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In OSCC, the upregulation of mTOR activity serves as a hallmark of cancer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The lysosomal membrane serves as a signaling platform for regulating metabolic signaling pathways, such as mTORC1 signaling [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Lysosomal activities are essential for regulating the metabolic signalling, cellular clearance, and nutrient recycling. However, dysfunction in the lysosomal activities is also a key reason for cancer progression and survival [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The key regulator of lysosomal biogenesis is TFEB, which is mainly regulated by mTOR signalling. When mTOR is in the active state, it limits TFEB-mediated lysosomal biogenesis by limiting their nuclear localization via phosphorylation. However, when mTOR activity is inhibited, it promotes the TFEB-mediated lysosomal biogenesis and autophagy (Martina et al., 2012; Diez-Roux and Ballabio, 2016). Targeting mTOR activities to regulate lysosomal biogenesis is a novel approach to inhibiting cancer progression.\u003c/p\u003e \u003cp\u003eThe autophagy events in the cells act as an antagonistic process to the mTOR activities [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The cytoprotective mechanism of autophagy plays a crucial role in regulating cancer progression due to its dual function. Autophagy acts as a cancer-promoting event by providing essential nutrients through the degradation of cargo. At the same time, autophagy acts as a tumor suppressor by removing misfolded, nonfunctional organelles and harmful cargo [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Moreover, excessive autophagy can lead to autosis or, in some cases, autophagic cell death, a type of cell death known as type-II cell death, which acts as a tumor-limiting event [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eArecoline, a primary alkaloid present in areca nuts, is primarily responsible for inducing oral cancer [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A major consequence of arecoline is activation of NLRP3-mediated inflammasome signalling [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, arecoline not only activates the NLRP3-mediated inflammasome axis but also alters the mTOR signalling pathway, which is associated with cancer progression [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Chebulagic acid (CA), a primary compound found in the \u003cem\u003eTerminalia bellirica\u003c/em\u003e (TB) (Gaertn.) Roxb. (Bahera) belongs to the group of hydrolyzable tannins [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Chebulagic acid (CA) is an important constituent present in the Ayurvedic formulation Triphala churn. Continuing exposure to areca nut leads to the development of oral squamous cell carcinoma (OSCC) via activation of the NLRP3-mediated inflammasome axis, driven by the presence of Aricolin. CA is known for its anti-inflammatory and antioxidant nature, but the roles in mTOR inhibition, autophagy induction, lysosomal biogenesis, and inhibition of arecoline-induced NLRP3-mediated inflammasome are yet to be well defined. We aim to examine the role of CA in mitigating the arecoline-induced NLRP3-mediated inflammasome via modulation of the mTOR-autophagy-lysosomal biogenesis axis in OSCC.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Reagents\u003c/h2\u003e \u003cp\u003eQuinic acid (TCI chemicals, Q0009), Gallic acid (TCI chemicals, G0011), Ellagic acid dihydrate (TCI chemicals, E0375), Chebulagic acid (Natural Remedies Pvt Ltd, C004), Chebulinic acid (Natural Remedies Pvt Ltd, C005), MTT (Tokyo Chemical Industry, M3297), DAPI (Sigma-Aldrich, D9542), Hoechst 33342 (Sigma-Aldrich, B2261), LysoTracker Red DND-99 (Invitrogen, L7528), LysoTracker Green DND-26 (Invitrogen, L7526), LysoSensor Yellow/Blue DND-160 (Invitrogen, L7545), L-Leucyl-L-Leucine methyl ester hydrobromide (Sigma, L7393), MHY1485 (MedChemExpress, HY-B0795), Chloroquine (Sigma-Aldrich, C6628), Dimethyl sulfoxide (Sigma-Aldrich, D4540), arecoline (Sigma-Aldrich, TA9H9A1760B0), phosphate buffered saline (PBS 1X for washing; Himedia, M1866-100G), Dulbecco's Modified Eagle Medium (DMEM) (Gibco, Catalog number-12800082), Bovin Serum Albumin (BSA; Himedia, MB083), Triton X-100 (Sigma-Aldrich, X100), formaldehyde solution (4% for fixing; Sigma-Aldrich, 252549), cell lysis buffer (10X; Cell Signaling Technology, 9803), phosphatase inhibitor (Sigma-Aldrich, P0044), protease inhibitor (Sigma-Aldrich, P7626), Lipofectamine 3000 (Invitrogen, L3000015). Antibodies such as Anti-mouse IgG (1:5000; Biobharti, BB-SAB 02 C), Anti-rabbit IgG (1:5000; Biobharti, BB-SAB 01 C), Anti-mouse IgG Alexa Fluor 488 (1:500; Invitrogen, A11001), and Anti-mouse IgG Alexa Fluor 568 (1:500; Invitrogen, A11004), Anti-LC3 (1:1000 for WB and 1:500 for IF; CST, 83506S), Anti-LAMP1 (1:500 for IF; CST, 9091S), Anti-BECN1 (1:1000 for WB; Abclonal, A7353), Anti p62(1:1000, CST-5114), Anti-TFEB(1:1000, Abclonal, A21928), Anti-Actin (1: 100000; Abclonal, AC026), Anti-ATG-5 (1:1000 for WB, Abcam Ab109490), Anti-AMPK1(1:1000 for WB, CST, 2532), Anti-p-AMPK1 (1:1000, CST, 2535), Anti-Ulk1 (1:1000, CST, 8054), Anti-mTOR (1:1000, CST, 2972), Anti-p-mTOR (1:1000 for WB, 1: 200 for IF, CST, 2971), Anti-p70S6K (1:1000 for WB; 1: 200 for IF, Abclonal, A4898), Anti-p-p70S6K (1:1000; Abclonal, AP0564), Anti-NLRP3 (1:1000 for WB; Abclonal, A5652), Anti-IL-1β (1:1000 for WB; Abclonal, A16737), Anti-ASC(1:1000 for WB, 1: 200 for IF, sc-514414), Anti-NRF2 (1:1000 for WB; Abclonal, A0674), and Anti-SOD (1:1000 for WB, sc-137254).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Cell culture\u003c/h2\u003e \u003cp\u003eCAL33, a human oral squamous cell carcinoma, from the American Type Culture Collection (ATCC, USA) was maintained using Dulbecco\u0026rsquo;s Modified Eagle Medium (Himedia, AL151A), with 10% fetal bovine serum albumin (Gibco, 10270106) along with 1% Plasmocin\u0026trade; prophylactic (ant-mpp) and 5% of antibiotic and antimycotic (Himedia, A002A) in an incubator with 5% CO₂.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Plasmid and shRNAs\u003c/h2\u003e \u003cp\u003eTo generate stable cell lines, we used shRNAs specific for BECN1 (\u003cem\u003eshBECN1\u003c/em\u003e, Sigma-Aldrich, TRCN0000299864) and TFEB (\u003cem\u003eshTFEB\u003c/em\u003e, Sigma-Aldrich, TRCN0000437246). For lentivirus production, we used the packaging vector plasmid psPAX2 (Addgene, #12260, from Dr. Didier Trono) and the envelope plasmid pMD2.G (Addgene, #12259, from Dr. Didier Trono).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Transfection and generation of stable cell lines\u003c/h2\u003e \u003cp\u003eTo perform a knockdown experiment, the shRNAs specific for BECN1 (\u003cem\u003eshBECN1\u003c/em\u003e; Sigma-Aldrich, TRCN0000299864) and TFEB (\u003cem\u003eshTFEB\u003c/em\u003e; Sigma-Aldrich, TRCN0000437246) from Sigma-Aldrich were used for the lentiviral method of stable cell generation. The lentivirus production takes place in the HEK293FT cells using the lentiviral packaging vector plasmid psPAX2 and the envelope plasmid pMD2.G using Lipofectamine\u0026reg; 3000 reagent (Thermo Fisher Scientific, L3000015). Following the manufacturers' instructions, viral particles were harvested at 48 h and 72 h post-treatment. Then, the viral mixture, combined with culture media at a 1:1 ratio and polybrene, was added to CAL33 cells. For stable cell selection, we used puromycin (Sigma-Aldrich, P8833) at a concentration of 500 ng/mL.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 MTT\u003c/h2\u003e \u003cp\u003eTo study the cytotoxicity of the bioactive compounds of TB, CAL33 cells were first seeded at approximately 5000 cells per well in 96-well plates and allowed to attach. After the cells were attached, we administered the treatment for 48 hours. Then, an MTT solution of 5 mg/mL concentration was added to each well, and the incubation lasted for 4 hours. The formazan crystals were formed within the live cells through the reduction of MTT. Then, with Dimethyl sulfoxide (DMSO), the formazan crystals were dissolved, and the absorbance was measured at 570 nm using a BMG LABTECH created FLUOstar Omega microplate reader. Based on the absorbance reading, the % of cell viability was calculated relative to the control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Immunofluorescence study\u003c/h2\u003e \u003cp\u003eApproximately 25,000 CAL33 cells were seeded in the confocal well and allowed to adhere overnight. Then, the cells are treated according to the experimental condition for 24 hours. After the treatment period, the cells were washed with PBS, followed by fixation with 4% formaldehyde for 15 minutes. To reduce nonspecific binding, cells were blocked with 3% BSA in PBS for 1 hour at room temperature. Followed by incubation of the specific primary antibody with the desired dilution with BSA overnight at 4\u0026deg; C. After incubation of the primary antibodies, washing with PBS followed by incubation with appropriate Alexa Fluor conjugated secondary antibodies for 1 h at room temperature in dark conditions. DAPI was used as a counterstain for nuclei. Images were acquired using a Leica STELLARIS 5 confocal microscope (Wetzlar, Germany, Leica Microsystems). For each experimental condition, 15\u0026ndash;20 cells from at least three independent setups were analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 LysoTracker staining\u003c/h2\u003e \u003cp\u003eTo assess lysosomal mass and integrity, LysoTracker Red DND-99 (50 nM, 30 min incubation time; Invitrogen, L7528) was used. Approximately 25,000 CAL33 cells were seeded in the confocal well and allowed to adhere overnight. Then, the cells are treated according to the experimental condition for 24 hours. After the experimental condition, the cells were incubated with LysoTracker Red DND-99 for 30 min at 37\u0026deg;C in the dark. Followed by washing with PBS, the cells were immediately subjected to live cell imaging (for each experimental condition, 15\u0026ndash;20 cells from at least three independent setups were analyzed) at the desired laser filter to acquire the images. The acquired images are quantified based on the intensity of red fluorescence using ImageJ (Fiji) software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 LysoSensor staining\u003c/h2\u003e \u003cp\u003eTo access lysosomal pH, LysoSensor Yellow/Blue DND-160 (50 nM, 5 min incubation time; Invitrogen, L7545) was used. Approximately 25,000 CAL33 cells were seeded in the confocal well and allowed to adhere overnight. Then, the cells are treated according to the experimental condition for 24 hours. After the experimental condition, the cells were incubated with LysoSensor Yellow/Blue DND-160 for 5 min at 37\u0026deg;C in the dark. Followed by washing with PBS, the cells were immediately subjected to live cell imaging (for each experimental condition, 15\u0026ndash;20 cells from at least three independent setups were analyzed) at the desired laser filter to acquire the images. The acquired images are quantified based on the intensity of yellow/blue fluorescence using ImageJ (Fiji) software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Western blotting\u003c/h2\u003e \u003cp\u003eTo assess protein expression after treatment, approximately 7 \u0026times; 10⁵ cells were seeded in a 60 mm cell culture plate according to the experimental setup. After 24 hours of treatment, the whole-cell lysates were collected and subjected to lysis using the lysis buffer. The lysate was subjected to protein estimation via following Bradford protocol. In the SDS-PAGE gels, 40 \u0026micro;g of protein was loaded in each well. The gel was then transferred to nitrocellulose membranes, followed by blocking with skim milk for about 2\u0026ndash;3 hrs. After blocking, the primary antibody was incubated overnight (12\u0026ndash;16 hours) at 4\u0026deg;C with the recommended specific dilution. Then, the washing step was carried out three times, with 10-minute intervals between each wash. The secondary antibody, conjugated with HRP, was used for incubation at room temperature for 2 hours. Following the PBST wash, western blot images were developed using enhanced chemiluminescence (ECL) with the ImageQuant LAS 500 system (GE Healthcare, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Flow cytometry analysis\u003c/h2\u003e \u003cp\u003eTo evaluate lysosomal content change or to study lysosomal biogenesis, flow cytometry analysis was carried out using LysoTracker Green DND-26 (50 nM incubation time-30 min; Invitrogen, L7526). First, approximately 1 \u0026times; 10⁵ CAL33 cells were seeded in the 12-well plates and allowed to adhere overnight. Followed by treatment with CA (50,100, and 150 \u0026micro;M) for 24 h. After the experimental condition, the cells were incubated with LysoTracker Green DND-26 for 30 min at 37\u0026deg;C in the dark. Then, followed by PBS wash, the cells were detached from the plate with trypsin and collected by centrifugation. The collected cells were suspended in PBS and subjected to flow cytometry analysis by acquiring 10,000 events with the help of the BD LSRFortessa\u0026trade; flow cytometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 LLOMe washout experiment\u003c/h2\u003e \u003cp\u003eTo study the effect of our bioactive compound on lysosomal recovery after acute damage, we used L-Leucyl-L-Leucine methyl ester hydrobromide (LLOMe, 1000 \u0026micro;M, incubation for 2 h, Sigma, L7393). Approximately 25,000 CAL33 cells were seeded in the confocal well and allowed to adhere overnight. Pre-treatment of LLOMe for 1 h at 37\u0026deg;C induces lysosomal membrane permeabilization. Following three PBS washes to remove the LLOMe, the cells were incubated in fresh media under the desired experimental conditions and treated with CA for 24 hours. After treatment, condition cells were incubated with LysoTracker Red DND-99 (50 nM, 30 min incubation time; Invitrogen, L7528). After a 30-minute incubation period with PBS, the cells are subjected to live cell imaging (for each experimental condition, 15\u0026ndash;20 cells from at least three independent setups were analyzed) at the desired filter to acquire images. The acquired images are quantified based on the intensity of red fluorescence using ImageJ (Fiji) software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.12 Molecular docking by using PyRx\u003c/h2\u003e \u003cp\u003eTo predict the interaction of CA with key target proteins involved in autophagy, lysosomal biogenesis, mTOR activity, and inflammation signaling, we performed molecular docking using AutoDock Tools integrated within PyRx 0.9.8. The 3D structures of mTOR and NLRP3 were downloaded from the Protein Data Bank (PDB). Similarly, the structure of CA was retrieved from the PubChem database. After preparing the protein ligand, molecular docking was carried out. The top-ranked docked complex with lower binding energy is subjected to protein ligand interaction using PyMOL and BIOVIA Discovery Studio Visualizer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.13 UCSC Xena and R language\u003c/h2\u003e \u003cp\u003eWe utilized publicly available transcriptomic and clinical datasets from the UCSC Xena platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://xena.ucsc.edu/\u003c/span\u003e\u003cspan address=\"https://xena.ucsc.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to study mTOR and NLRP3 signaling in HNSCC. At the same time, for bioinformatics and statistical analysis, we used the R programming environment (version 4.2.0). The Gene expression matrices were filtered to retain genes of interest, and Z-score normalization was applied for heatmap generation and comparative visualization for our study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e2.14 Statistical analysis\u003c/h2\u003e \u003cp\u003eFor statistical quantification of the experimental data, we used Student\u0026rsquo;s t-test and one-way ANOVA using GraphPad Prism 9 software. Statistical significance was decided based on p-value, which is represented as: p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, i.e., ns, not significant; whereas *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; and ****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\n\u003ch3\u003e1. screening of the mTOR-inhibiting potential of (TB)-derived bioactive compounds\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003e1. \u003cem\u003eIn silico\u003c/em\u003e screening of the mTOR-inhibiting potential of \u003cem\u003eTerminalia bellerica\u003c/em\u003e (TB)-derived bioactive compounds\u003c/div\u003e \u003cp\u003eWe performed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to establish the significance of screening mTOR inhibitors in head and neck squamous cell carcinoma (HNSCC). We used the UCSC Xena (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://xena.ucsc.edu/\u003c/span\u003e\u003cspan address=\"https://xena.ucsc.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) platform to obtain the TCGA transcriptomic data for HNSCC and analyzed them using the R language to generate KEGG pathway analysis in a bubble plot. The KEGG analysis revealed that the mTOR signaling pathway was the most significantly enriched pathway, characterized by a high gene ratio and a low p-value, in HNSCC. In addition to mTOR Signaling, autophagy, AMPK, and PI3K-Akt signaling were also significantly enriched in the case of HNSCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Following KEGG pathway enrichment analysis, we performed a heatmap analysis of the overall elevated expression of core mTOR pathway genes across the HNSCC tumor samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Hierarchical clustering of core mTOR pathway genes in the heatmap revealed that the coordinated upregulation of both mTORC1 and mTORC2-associated genes was widely activated in HNSCC. Then, to further assess whether mTOR signalling was activated in tumor tissue versus normal tissue, hierarchical clustering of HNSCC was performed. The clustering analysis revealed that the majority of tumor samples exhibited mTOR signaling, with a small clustering of normal tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Collectively, the above analysis strongly suggests a reasonable target of mTOR signalling using an mTOR inhibitor.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eTerminalia bellirica\u003c/em\u003e (Gaertn.) Roxb. is readily known for its common names, such as Baheda, Bibhitaki, Belleric Myrobalan, Kalidruma, Bhutavasa, and Kaliyugalaya. TB plants have various medicinal properties and are used to cure or alleviate fear associated with various diseases; therefore, in Sanskrit, it's known as \u0026ldquo;vibheetaki\u0026rdquo;, which means fearless [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMMPAT, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cb.imsc.res.in/imppat/\u003c/span\u003e\u003cspan address=\"https://cb.imsc.res.in/imppat/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a database that provides systematic details about various Indian medicinal plants, their derived bioactive compounds, and their sources, along with their therapeutic applications. According to the IMMPAT platform, TB is reported to contain 54 bioactive compounds. However, Singh et al. (2016) reported the major bioactive compounds present in the TB, which were subjected to screening for mTOR inhibitors in our study (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). However, based on the literature, we identified five major compounds, including quinic acid, gallic acid, ellagic acid, chebulagic acid, and chebulinic acid, which are mostly found in higher amounts in the TB fruits. These five major compounds found in the TB fruits were then screened for their potential to induce autophagy and inhibit mTOR activity. We performed molecular docking using AutoDock Tools integrated within PyRx 0.9.8. to evaluate the binding affinity of TB fruit-derived bioactive compounds towards the mTOR kinase domain (PDB ID-4JSV, Chain-AC). The molecular docking result shows that quinic acid exhibited the highest binding affinity with a binding energy score of -9.3 kcal/mol, followed by ellagic acid (-9.2 kcal/mol), chebulinic acid (-8.8 kcal/mol), gallic acid (-8.7 kcal/mol), and chebulagic acid (-8.3 kcal/mol) (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). However, although quinic acid shows a positive binding score, it exhibits a comparatively weaker and less stable interaction. We find that ellagic acid, chebulinic acid, and gallic acid have slightly stronger binding energy than chebulagic acid, but the chebulagic acid displayed a favorable binding orientation within the mTOR active site and formed a stable interaction with key catalytic residues (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-E). The key bioactive compounds present in various parts of TB are listed in the supplementary information, along with their binding scores when docked with the mTOR kinase (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003e2. Chebulagic acid inhibits mTOR activities and limits mTORC1 lysosomal membrane localization in a dose-dependent manner\u003c/h3\u003e\n\u003cp\u003eAfter molecular docking, we performed a two-dimensional interaction analysis of CA with the mTOR kinase domain using LigPlot, which revealed that CA formed multiple hydrogen bonds with key amino acid residues, including Gln225, Cys226, His177, Glu49, Leu48, Ser90, and Ala89, indicating stable polar interactions within the active site pocket. In addition to hydrogen bonding, several hydrophobic interactions we observed with residues such as Arg227, Ser175, Trp274, Gly275, Val316, Asn46, and Cys133, which contributed to the overall stabilization of the ligand-protein complex (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). As CA has a favorable binding orientation within the mTOR active site and forms a stable interaction with key catalytic residues, we selected CA for a detailed investigation of its mTOR inhibitory action. To study the cytotoxicity of the selected five major bioactive compounds of TB, CAL33 cells were first seeded at approximately 5,000 cells per well in the 96-well plates, and the selected compounds, including quinic acid, gallic acid, ellagic acid, chebulagic acid, and chebulinic acid, were administered for 48 hours at varying concentrations. We find that all five bioactive compounds show cytotoxic effects in a dose-dependent manner (Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Based on the MTT results, we identified five distinct IC50 values, which were subsequently screened for their potential to induce autophagy and inhibit mTOR activity. Next, CAL33 cells were treated with three different doses (50, 100, and 150 \u0026micro;M) of CA, then subjected to western blot and immunofluorescence-based study to evaluate mTOR activity and localization. The immunofluorescence study of p-mTOR revealed a dose-dependent reduction in fluorescence intensity with treatment of CA, confirming the mTOR inhibition potential of CA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-D). To further validate this, we examined the expression of the mTOR downstream target p-p70S6K, which also shows a dose-dependent reduction in expression in both the western blot and immunofluorescence studies with CA treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-H). The above results collectively confirmed the potential of CA to inhibit mTOR and mTORC1 signalling. Moreover, as mTORC1 activation requires the lysosomal membrane localization, we further examined the mTOR-lysosome interaction via mTOR-LAMP1 colocalization using confocal microscopy. The mTOR-LAMP1 colocalization result showed a gradual reduction in colocalization with the treatment of CA, indicating that CA limits mTORC1 activities and signaling via its inhibition of lysosomal membrane localization (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003e3. Chebulagic acid promotes TFEB-mediated lysosomal biogenesis\u003c/h3\u003e\n\u003cp\u003eTo examine the role of CA in maintaining the lysosomal pool and biogenesis, we first checked the lysosomal mass using LysoTracker red staining. The dose-dependent treatment with CA results in an increase in the mean LysoTracker red intensity, which was further validated by flow cytometry analysis using LysoTracker green (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-E). Then, to assess the effect of CA on altering lysosomal acidity, which is crucial for lysosomal function, we used LysoSensor Yellow/Blue. The LysoSensor Yellow/Blue exhibits a yellow color in acidic environments, whereas it emits a blue color in less acidic or neutral environments. We find that with CA treatment, the yellow/blue fluorescence intensity ratio increases dose dependently, suggesting that CA enhances lysosomal acidity to improve lysosomal function (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF, G). Moreover, to understand whether the induced lysosomal activities are due to the upregulation of TFEB, we found that with dose-dependent treatment of CA, the TFEB expression was higher in the western blot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B). Then we genetically knocked out TFEB and performed LysoTracker red and LysoSensor Yellow/Blue staining. Under \u003cem\u003eshTFEB\u003c/em\u003e conditions, CA is unable to induce higher LysoTracker red and LysoSensor Yellow fluorescence, indicating that increased lysosomal activity is due to TFEB (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH-K).\u003c/p\u003e \u003cp\u003eTo check the effect of CA under stress conditions, we used LLOMe, a compound that disrupts the lysosomal membrane and induces lysosomal stress. We find that with LLOMe treatment, the mean LysoTracker red intensity sharply reduces, indicating lysosomal damage. Notably, we find that after pretreatment of CA, the mean LysoTracker intensity recovers, indicating that CA has the potential to protect lysosomes from LLOMe-induced lysosomal damage (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL, M). Next, we examined the lysosomal activity in the presence of MHY1485, a potent cell-permeable mTOR activator that targets the ATP domain of mTOR in CAL33 cells. Our data showed that CA in MHY1485-pretreated cells markedly reduces the LysoTracker intensity, suggesting that CA counteracts mTOR-driven TFEB suppression and promotes lysosomal biogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eN, O).\u003c/p\u003e\n\u003ch3\u003e4. Chebulagic acid induces BECN1-dependent autophagy and induces autophagic flux dose dependently\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo screen out compounds with autophagy-inducing potential, LC3 puncta formation was assessed by confocal microscopy for all five selected bioactive compounds found in the TB fruits. Among the five major bioactive compounds derived from TB fruits, gallic acid, ellagic acid, chebulagic acid (CA), and chebulinic acid have been shown to have the potential to induce autophagy (Fig. S3). Our group also previously worked on gallic acid derived from TB-derived fruit. We showed that gallic acid induces autophagy and alters the NRF2 signalling pathway [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Similarly, various studies related to autophagy have already been explored on ellagic acid and chebulinic acid. The LC3 puncta analysis result indicates that among the five compounds in TB fruits, CA exhibits a higher number of LC3 puncta in CAL33 cells (Fig. S3C). Moreover, the accumulation of LC3 II was assessed using western blotting, which showed that gallic acid, ellagic acid, chebulagic acid (CA), and chebulinic acid have higher LC3 accumulation compared to the known mTOR inhibitor, rapamycin (Fig. S3A, B). Furthermore, to investigate the role of CA on autophagy, CAL33 cells were treated with 50, 100, and 150 \u0026micro;M of CA and analyzed via immunofluorescence and western blot analysis. The LC3 puncta analysis revealed a dose-dependent increase in the number of LC3 puncta per cell as compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, D). The western blot analysis also showed a gradual increase in the LC3-II/LC3-I ratio in CAL33 cells. In parallel, the expression of other autophagy markers, such as ATG5, ULK1, and p-AMPK, was increased with decreased p62 expression, indicating active autophagic degradation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, S4). To study the role of autophagy in autophagosome and lysosome fusion, LC3 and LAMP1 colocalization study was performed. The LC3-LAMP1 colocalization study shows that with an increase in the dose of CA, the colocalization increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG, H). The increased colocalization of LC3-LAMP1 indicates the efficient fusion of autophagosomes and lysosomes induced by CA. Autophagic flux-inducing potential of CA was analyzed using chloroquine (CQ) with the help of LC3 puncta analysis. The LC3 puncta in the case of co-treatment with CA and CQ were higher compared to treatment conditions with CA or CQ alone, which indicates that CA induces autophagic flux (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI, J). Furthermore, to investigate the role of CA in the genetic regulation of autophagy, LC3 puncta analysis was performed under the \u003cem\u003eshBECN1\u003c/em\u003e condition. The LC3 puncta study revealed that under \u003cem\u003eshBECN1\u003c/em\u003e conditions, CA is unable to induce higher LC3 puncta per cell, indicating that it induces BECN1-dependent autophagy (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE, F). Moreover, to understand whether the induced autophagy is due to the upregulation of TFEB, we genetically knocked out TFEB and performed LC3 puncta analysis. We find that under \u003cem\u003eshTFEB\u003c/em\u003e conditions, CA is unable to induce higher LC3 puncta, indicating that it induces autophagy through TFEB activation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK, L). Lastly, to assess the potential of CA in overcoming the mTOR activation condition, we used MHY1485, which is known to suppress autophagy. As expected, CA showed a marked reduction in LC3 puncta in exposure to MHY1485 as compared to only CA treatment, indicating that CA has the potential to counteract mTOR activation and induce autophagy (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eM, N).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003e5. Chebulagic acid limits the arecoline-induced NLRP3-mediated inflammasome axis\u003c/h3\u003e\n\u003cp\u003eNext, we investigated the activation of NLRP3 signaling in tumor tissue versus normal tissue using hierarchical clustering of HNSCC TCGA data from the UCSC Xena platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://xena.ucsc.edu/\u003c/span\u003e\u003cspan address=\"https://xena.ucsc.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the R language. The clustering analysis revealed that the majority of tumor samples exhibited NLRP3 signaling with a small clustering of normal tissues. We then performed a heatmap analysis of the overall elevated expression of core NLRP3 pathway-related genes across HNSCC tumor samples using TCGA data from the UCSC Xena platform and the R language. Hierarchical clustering of core NLRP3 signalling pathway-related genes in the heatmap revealed that the upregulation of NLRP3 signaling-associated genes was widely activated in HNSCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, B). Furthermore, to investigate the direct interaction of CA with the NLRP3 inflammasome complex, we performed molecular docking using Autodock with the crystal structure of NLRP3 (PDB ID: 8RI2). We find that CA exhibits a favorable and stable interaction with NLRP3, with a docking score of -7.4 kcal/mol (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Then, to assess the role of CA in modulating the NLRP3-mediated inflammasome axis, we first performed western blot analysis of the inflammasome signaling player NLRP3 and IL-18. To evaluate the effect of CA under proinflammatory conditions, we used arecoline to induce the NLRP3-mediated inflammasome. The western blot analysis showed that the expression of NLRP3 and IL-18 was increased with arecoline treatment (100 \u0026micro;M, 24 h, Sigma-Aldrich, TA9H9A1760B0). However, CA treatment marked reduced of arecoline-induced NLRP3 and IL-18 expression, which depicts the potential of CA in limiting the NLRP3-mediated inflammasome axis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD, E). Since ASC speck formation is a characteristic event of NLRP3 inflammasome activation, we next checked ASC puncta formation using confocal microscopy during the CA treatment condition. The results showed a marked reduction in ASC puncta with dose-dependent treatment of CA (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF, G). To understand the role of CA-induced TFEB in limiting the NLRP3-mediated inflammasome axis, we checked the ASC puncta in \u003cem\u003eshTFEB\u003c/em\u003e cells under arecoline pretreatment conditions. Our data showed that TFEB knockdown markedly increased the ASC puncta during CA treatment under arecoline-induced NLRP3 inflammasome activation in CAL33 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH, I). Based on the above data, we concluded that CA induces TFEB, which plays an essential role in limiting the NLRP3-mediated inflammasome axis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe mTOR signalling is a central regulatory pathway that plays a crucial role in maintaining cellular metabolic status, which is often altered in various cancers. In HNSCC, the mTOR pathways are most commonly upregulated and represent as a major molecular hallmark [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It showed that Triphala inhibits the mTOR/PI3K/Akt signaling pathways in oral cancer [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. To dissect the bioactive natural mTOR inhibitor from Triphala, our study investigated the role of TB fruit-derived bioactive compounds in inhibiting mTOR activity. Singh et al. (2016) study reported the major bioactive compounds present in the TB, which were subsequently used for screening of mTOR inhibitors in our study [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. A study reported that the bioactive compound CA, primarily found in the TB fruits, exhibits neuroprotective effects in the SHSY5Y cell line, with limited mTOR activity [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Our results reveal that treatment with CA in oral cancer cells markedly inhibits mTOR activity. Moreover, it has been reported that mTORC1 activation requires localization to the lysosomal membrane [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Our mTOR-LAMP1 colocalization data also support that treatment with CA significantly reduces the lysosomal localization of mTOR, indicating that CA limits mTORC1 activities and signaling by inhibiting lysosomal membrane localization in OSCC.\u003c/p\u003e \u003cp\u003eTFEB acts as a master regulator of lysosomal biogenesis [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A previous study reported that mTORC1 acts as a transcriptional regulator of lysosomal biogenesis and autophagy via regulating TFEB activities [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The study also indicates that the overexpression of TFEB leads to an increase in lysosomes within the cells [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. We find that CA treatment increases the lysosomal mass and lysosomal acidity, as demonstrated by LysoTracker red and LysoSensor Yellow/Blue staining, through TFEB activation. LLOMe inactivates the lysosomal cysteine cathepsins by transiently permeabilizing the lysosomal membrane [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. We find that after pretreatment of CA, the mean LysoTracker intensity recovers, indicating that CA has the potential to protect lysosomes from LLOMe-induced inactivation of lysosomal cysteine cathepsins and maintain lysosomal biogenesis in oral cancer cells. Previous reports showed that CA induces autophagy in SHSY5Y cells, leading to neuroprotective effects [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. We find that CA also promotes autophagy and maintains autophagic flux in a BECN1-dependent way.\u003c/p\u003e \u003cp\u003eArecoline, the principal alkaloid of areca nut, is known as an inducer of oxidative stress and the NLRP3-mediated inflammasome axis. A recent study also reported that CA is involved in improving oxidative stress and the inflammasome in diabetic rats [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Triphala-loaded nanoparticles inhibit the NLRP3-mediated inflammasome in Lung cells [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our hierarchical clustering of studies on NLRP3 signaling in the context of HNSCC, along with a comparison of normal versus tumor samples, suggests that NLRP3 signaling is most prevalent in HNSCC. We found that with the treatment of CA in the arecoline pretreatment condition, the expression of NLRP3 and IL-1β is markedly reduced, supporting that CA limits arecoline-induced inflammasome signaling. Various studies reported that TFEB attenuates NLRP3 signalling and promotes autophagic degradation of NLRP3. Our result also shows that TFEB knockdown markedly increased the ASC puncta during CA treatment under arecoline-induced NLRP3 inflammasome activation. From our data, we concluded that CA induces TFEB, which plays a crucial role in limiting the NLRP3-mediated inflammasome axis.\u003c/p\u003e \u003cp\u003eCollectively, our findings highlight the therapeutic applications of CA, a major bioactive compound of TB fruits, which limits arecoline-induced NLRP3 signalling in OSCC. CA markedly suppressed mTOR activities by limiting lysosomal localization, which in turn facilitates TFEB-driven lysosomal biogenesis and autophagy. Our data suggest that CA can be used as a target against oncogenic mTOR signalling and arecoline-induced NLRP3-mediated inflammation in OSCC, which needs further exploration in an in vivo model.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBECN1\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBeclin1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003echebulagic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003emTOR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMechanistic Target of Rapamycin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNLRP3\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNOD-like Receptor Family Pyrin Domain Containing 3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLLOMe\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eL-Leucyl-L-Leucine methyl ester hydrobromide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTB\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eTerminalia bellirica\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eand \u003cb\u003eTFEB\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTranscription Factor EB\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthors\u0026rsquo; Contributions\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePrakash Kumar Senapati:\u0026nbsp;\u003c/strong\u003eConceptualization\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eWriting original draft, \u0026nbsp;Validation, \u0026nbsp; Methodology, Visualization, Investigation, \u003cstrong\u003eAmruta Singh\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eFormal analysis, Conceptualization, Methodology, Writing review and editing, \u003cstrong\u003eRakesh Kumar Kar:\u0026nbsp;\u003c/strong\u003eExperimental execution and data analysis, \u003cstrong\u003eKewal Kumar Mahapatra:\u0026nbsp;\u003c/strong\u003eInvestigation, Validation, Formal analysis, Writing Review and editing \u003cstrong\u003e\u0026nbsp;Mrutyunjay Jena and Swatilekha Maiti:\u0026nbsp;\u003c/strong\u003eprovided technical inputs and assisted with manuscript refinement, \u003cstrong\u003eSujit Kumar Bhutia:\u0026nbsp;\u003c/strong\u003eConceptualization, Writing original draft, validation, Methodology, Visualization, Investigation, Formal analysis and editing, Funding acquisition, Supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Department of Biotechnology (DBT), Government of India (Grant No. BT/PR42013/TRM/120/508/2021). Prakash Kumar Senapati gratefully acknowledges financial support from the Department of Science and Technology (DST), Government of India, through the INSPIRE Fellowship (No. DST/INSPIRE Fellowship/2022/IF220331).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated or analyzed during the study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors declared they have no competing interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declared no conflict of interest\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNA\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrakash Kumar Senapati (PKS) gratefully acknowledges the Government of India, Ministry of Science and Technology, Department of Science and Technology (DST) for financial support through the INSPIRE Fellowship (No. DST/INSPIRE Fellowship/2022/IF220331). Partial research funding was also provided by the Department of Biotechnology (DBT), Government of India (Grant No. BT/PR42013/TRM/120/508/2021). The authors sincerely regret any inadvertent omission of relevant original contributions and note that priority has been given to citing recent publications that comprehensively document earlier work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTan, Y., Wang, Z., Xu, M., Li, B., Huang, Z., Qin, S., \u0026amp; Huang, C. (2023). Oral squamous cell carcinomas: state of the field and emerging directions. \u003cem\u003eInternational Journal of Oral Science\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(1), 44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41368-023-00249-w\u003c/span\u003e\u003cspan address=\"10.1038/s41368-023-00249-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong, L., Xue, L., Cheng, W., Tang, J., Ran, J., \u0026amp; Li, Y. (2024). Comprehensive survival analysis of oral squamous cell carcinoma patients undergoing initial radical surgery. \u003cem\u003eBMC oral health\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(1), 919. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12903-024-04690-z\u003c/span\u003e\u003cspan address=\"10.1186/s12903-024-04690-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan, F. H., Bai, Y., Saintigny, P., \u0026amp; Darido, C. (2019). mTOR Signalling in Head and Neck Cancer: Heads Up. \u003cem\u003eCells\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/cells8040333\u003c/span\u003e\u003cspan address=\"10.3390/cells8040333\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi, R., Zhuang, X., Liu, T., Yao, S. N., \u0026amp; Xue, F. S. (2025). The Role of NLRP3 Inflammasome in Oral Squamous Cell Carcinoma. \u003cem\u003eJournal of inflammation research\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e, 5601\u0026ndash;5609. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2147/JIR.S512770\u003c/span\u003e\u003cspan address=\"10.2147/JIR.S512770\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBen-Sahra, I., \u0026amp; Manning, B. D. (2017). mTORC1 signaling and the metabolic control of cell growth. \u003cem\u003eCurrent opinion in cell biology\u003c/em\u003e, \u003cem\u003e45\u003c/em\u003e, 72\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ceb.2017.02.012\u003c/span\u003e\u003cspan address=\"10.1016/j.ceb.2017.02.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarsha, C., Banik, K., Ang, H. L., Girisa, S., Vikkurthi, R., Parama, D., \u0026amp; Kunnumakkara, A. B. (2020). Targeting AKT/mTOR in Oral Cancer: Mechanisms and Advances in Clinical Trials. \u003cem\u003eInternational journal of molecular sciences\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(9). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijms21093285\u003c/span\u003e\u003cspan address=\"10.3390/ijms21093285\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCui, Z., Esposito, A., Napolitano, G., Ballabio, A., \u0026amp; Hurley, J. H. (2025). Structural basis for mTORC1 activation on the lysosomal membrane. \u003cem\u003eNature\u003c/em\u003e, \u003cem\u003e647\u003c/em\u003e(8089), 536\u0026ndash;543. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41586-025-09545-3\u003c/span\u003e\u003cspan address=\"10.1038/s41586-025-09545-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu, S., Yao, R., Li, Y., Zhao, P., Ren, C., Du, X., \u0026amp; Yao, Y. (2020). Lysosomal quality control of cell fate: a novel therapeutic target for human diseases. \u003cem\u003eCell Death \u0026amp; Disease\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(9), 817. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41419-020-03032-5\u003c/span\u003e\u003cspan address=\"10.1038/s41419-020-03032-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartina, J. A., Chen, Y., Gucek, M., \u0026amp; Puertollano, R. (2012). MTORC1 functions as a transcriptional regulator of autophagy by preventing nuclear transport of TFEB. \u003cem\u003eAutophagy\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(6), 903\u0026ndash;914. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4161/auto.19653\u003c/span\u003e\u003cspan address=\"10.4161/auto.19653\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiez-Roux, G., \u0026amp; Ballabio, A. (2016). TFEB, Master Regulator of Cellular Clearance. In \u003cem\u003eLysosomes: Biology, Diseases, and Therapeutics\u003c/em\u003e (pp. 101\u0026ndash;114). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1002/9781118978320.ch7\u003c/span\u003e\u003cspan address=\"10.1002/9781118978320.ch7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim, Y. C., \u0026amp; Guan, K. L. (2015). mTOR: a pharmacologic target for autophagy regulation. \u003cem\u003eThe Journal of clinical investigation\u003c/em\u003e, \u003cem\u003e125\u003c/em\u003e(1), 25\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1172/JCI73939\u003c/span\u003e\u003cspan address=\"10.1172/JCI73939\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatergnani, S., Missiroli, S., Morciano, G., Perrone, M., Mantovani, C. M., Anania, G., \u0026amp; Giorgi, C. (2021). Understanding the Role of Autophagy in Cancer Formation and Progression Is a Real Opportunity to Treat and Cure Human Cancers. \u003cem\u003eCancers\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(22). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/cancers13225622\u003c/span\u003e\u003cspan address=\"10.3390/cancers13225622\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSenapati, P. K., Mahapatra, K. K., Singh, A., \u0026amp; Bhutia, S. K. (2025). mTOR inhibitors in targeting autophagy and autophagy-associated signaling for cancer cell death and therapy. \u003cem\u003eBiochimica et Biophysica Acta (BBA) - Reviews on Cancer\u003c/em\u003e, \u003cem\u003e1880\u003c/em\u003e(3), 189342. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1016/j.bbcan.2025.189342\u003c/span\u003e\u003cspan address=\"10.1016/j.bbcan.2025.189342\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeng, L., Wang, X., Wang, H., Hu, Y., Deng, Y., \u0026amp; Wang, C. (2025). Molecular mechanisms of arecoline-induced oral cancer: a network toxicology and molecular docking techniques integrated analysis. \u003cem\u003eDiscover oncology\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(1), 842. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12672-025-02659-0\u003c/span\u003e\u003cspan address=\"10.1007/s12672-025-02659-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYou, Y., Huang, Y., Wang, D., Li, Y., Wang, G., Jin, S., \u0026amp; Li, X. (2019). Angiotensin (1\u0026ndash;7) inhibits arecoline-induced migration and collagen synthesis in human oral myofibroblasts via inhibiting NLRP3 inflammasome activation. \u003cem\u003eJournal of Cellular Physiology\u003c/em\u003e, \u003cem\u003e234\u003c/em\u003e(4), 4668\u0026ndash;4680. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1002/jcp.27267\u003c/span\u003e\u003cspan address=\"10.1002/jcp.27267\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu, L., Xie, C., Peng, Q., Zhang, J., Li, J., \u0026amp; Tang, Z. (2019). Arecoline suppresses epithelial cell viability through the Akt/mTOR signaling pathway via upregulation of PHLPP2. \u003cem\u003eToxicology\u003c/em\u003e, \u003cem\u003e419\u003c/em\u003e, 32\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tox.2019.03.006\u003c/span\u003e\u003cspan address=\"10.1016/j.tox.2019.03.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuggilla, M., Chow, S., \u0026amp; Siow, L. (2022). Supercritical Fluid Extraction of Chebulagic acid from Terminalia Bellirica Fruits (Baheda). \u003cem\u003eJournal of Food Processing and Preservation\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jfpp.16455\u003c/span\u003e\u003cspan address=\"10.1111/jfpp.16455\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta, A., Kumar, R., Bhattacharyya, P., Bishayee, A., \u0026amp; Pandey, A. K. (2020). Terminalia bellirica (Gaertn.) roxb. (Bahera) in health and disease: A systematic and comprehensive review. \u003cem\u003ePhytomedicine\u003c/em\u003e, \u003cem\u003e77\u003c/em\u003e, 153278. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1016/j.phymed.2020.153278\u003c/span\u003e\u003cspan address=\"10.1016/j.phymed.2020.153278\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatra, S., Bhol, C. S., Panigrahi, D. P., Praharaj, P. P., Pradhan, B., Jena, M., \u0026amp; Bhutia, S. K. (2020). Gamma irradiation promotes chemo-sensitization potential of gallic acid through attenuation of autophagic flux to trigger apoptosis in an NRF2 inactivation signalling pathway. \u003cem\u003eFree radical biology \u0026amp; medicine\u003c/em\u003e, \u003cem\u003e160\u003c/em\u003e, 111\u0026ndash;124. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.freeradbiomed.2020.06.022\u003c/span\u003e\u003cspan address=\"10.1016/j.freeradbiomed.2020.06.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu, S., Li, S., Xu, Y., Huang, X., Mai, Z., Chen, Y., \u0026hellip; Hu, X. (2024). The antitumor effects of herbal medicine Triphala on oral cancer by inactivating PI3K/Akt signaling pathway: based on the network pharmacology, molecular docking, in vitro and in vivo experimental validation. \u003cem\u003ePhytomedicine: international journal of phytotherapy and phytopharmacology\u003c/em\u003e, \u003cem\u003e128\u003c/em\u003e, 155488. https://doi.org/10.1016/j.phymed.2024.155488.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh, A., Bajpai, V., Kumar, S., Kumar, B., Srivastava, M., \u0026amp; Rameshkumar, K. B. (2016). Comparative profiling of phenolic compounds from different plant parts of six Terminalia species by liquid chromatography\u0026ndash;tandem mass spectrometry with chemometric analysis. \u003cem\u003eIndustrial Crops and Products\u003c/em\u003e, \u003cem\u003e87\u003c/em\u003e, 236\u0026ndash;246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1016/j.indcrop.2016.04.048\u003c/span\u003e\u003cspan address=\"10.1016/j.indcrop.2016.04.048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim, H. J., Kim, J., Kang, K. S., Lee, K. T., \u0026amp; Yang, H. O. (2014). Neuroprotective Effect of Chebulagic Acid via Autophagy Induction in SH-SY5Y Cells. \u003cem\u003eBiomolecules \u0026amp; therapeutics\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(4), 275\u0026ndash;281. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4062/biomolther.2014.068\u003c/span\u003e\u003cspan address=\"10.4062/biomolther.2014.068\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBala, S., \u0026amp; Szabo, G. (2018). TFEB, a master regulator of lysosome biogenesis and autophagy, is a new player in alcoholic liver disease. \u003cem\u003eDigestive medicine research\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21037/dmr.2018.09.03\u003c/span\u003e\u003cspan address=\"10.21037/dmr.2018.09.03\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRepnik, U., Borg Distefano, M., Speth, M. T., Ng, M. Y. W., Progida, C., Hoflack,B., \u0026hellip; Griffiths, G. (2017). L-leucyl-L-leucine methyl ester does not release cysteine cathepsins to the cytosol but inactivates them in transiently permeabilized lysosomes.\u003cem\u003eJournal of cell science\u003c/em\u003e, \u003cem\u003e130\u003c/em\u003e(18), 3124\u0026ndash;3140. https://doi.org/10.1242/jcs.204529.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSundaram, R., Karuppiah, M., Almansour, A., Natarajan, A., \u0026amp; Perumal, K. (2024). Chebulagic Acid Ameliorates Oxidative Stress and Inflammation via Regulation of Insulin Signaling Pathway in High-Fat Diet/Streptozotocin-Induced Diabetic Rats. \u003cem\u003eRevista Brasileira de Farmacognosia\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s43450-024-00600-0\u003c/span\u003e\u003cspan address=\"10.1007/s43450-024-00600-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChittasupho, C., Umsumarng, S., Srisawad, K., Arjsri, P., Phongpradist, R., Samee,W., \u0026hellip; Dejkriengkraikul, P. (2024). Inhibition of SARS-CoV-2-Induced NLRP3 Inflammasome-Mediated Lung Cell Inflammation by Triphala-Loaded Nanoparticle Targeting Spike Glycoprotein S1. \u003cem\u003ePharmaceutics\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(6). https://doi.org/10.3390/pharmaceutics16060751.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"applied-biochemistry-and-biotechnology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"abab","sideBox":"Learn more about [Applied Biochemistry and Biotechnology](https://www.springer.com/journal/12010)","snPcode":"12010","submissionUrl":"https://submission.nature.com/new-submission/12010/3","title":"Applied Biochemistry and Biotechnology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Autophagy, Chebulagic acid, Inflammasome, Lysosomal biogenesis, mTOR, NLRP3, TFEB","lastPublishedDoi":"10.21203/rs.3.rs-9058916/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9058916/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChebulagic acid (CA), a primary compound found in the Indian traditional medicinal plant \u003cem\u003eTerminalia bellirica\u003c/em\u003e (TB) \u003cem\u003e(Gaertn.) Roxb. (Bahera)\u003c/em\u003e is an important constituent present in the Ayurvedic formulation Triphala churn. CA, a hydrolysable tannin, is known for its anti-inflammatory and antioxidant properties. Chronic exposure to areca nut leads to the development of oral squamous cell carcinoma (OSCC) via activation of the NLRP3-mediated inflammasome axis, driven by the presence of Aricolin. The primary objective of our study is to investigate the role of chebulagic acid in mitigating the arecoline-induced NLRP3-mediated inflammasome via modulation of the mTOR-autophagy-lysosomal biogenesis axis in oral squamous cell carcinoma (OSCC). CAL33 cells were treated with chebulagic acid to study mTOR activities, autophagy, lysosomal biogenesis using western blotting, immunofluorescence, LysoTracker/LysoSensor staining, and molecular docking. Moreover, we used LLOMe to induce lysosomal damage and stress. We find that chebulagic acid inhibits mTORC1 signaling by limiting mTOR lysosomal localization and reducing the phosphorylation of mTOR and p-p70S6K in CAL33 cells. The inhibition of mTOR leads to activation of BECN1-dependent autophagy and TFEB-mediated lysosomal biogenesis. In addition, chebulagic acid reduced the expression of NLRP3, IL-18, and reduced ASC puncta in the arecoline-induced NLRP3-mediated inflammasome condition. Chebulagic acid acts as a key bioactive compound with the potential to limit arecoline-induced NLRP3-mediated inflammasome activation by inhibiting mTOR, followed by the induction of BECN1-dependent autophagy and TFEB-driven lysosomal biogenesis.\u003c/p\u003e","manuscriptTitle":"Chebulagic acid limits mTOR activity leading to TFEB-driven autophagy and lysosomal biogenesis to suppress the arecoline-induced NLRP3-mediated inflammasome axis in OSCC","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 13:04:50","doi":"10.21203/rs.3.rs-9058916/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-04-20T04:03:10+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T03:09:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Applied Biochemistry and Biotechnology","date":"2026-03-15T19:40:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-10T23:17:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Applied Biochemistry and Biotechnology","date":"2026-03-10T00:51:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"applied-biochemistry-and-biotechnology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"abab","sideBox":"Learn more about [Applied Biochemistry and Biotechnology](https://www.springer.com/journal/12010)","snPcode":"12010","submissionUrl":"https://submission.nature.com/new-submission/12010/3","title":"Applied Biochemistry and Biotechnology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c871c1ec-ab5f-4051-a3f0-7206e19a8aed","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T13:04:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 13:04:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9058916","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9058916","identity":"rs-9058916","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}