Calcium Dysregulation Promotes Glioma Progression by Inhibiting STAT3 Degradation Through Blocking Chaperone‐Mediated Autophagy
Jialong Chen, Yixi Lai, Mingque Li, ZiWei Cai, Renjian Lu, Linhua Liu, Yongming Peng, Chunlai Fu, Zhefan Xie, Xueqion Zhou, Jiaxian Liu, He Zhang
TL;DR
Calcium imbalance in brain tumors promotes cancer growth by preventing the breakdown of a key protein called STAT3 through a specific cellular process.
Contribution
The study identifies TRPC1 as a novel regulator of STAT3 stability via chaperone-mediated autophagy in gliomas.
Findings
TRPC1 increases STAT3 protein levels, promoting glioma cell migration.
TRPC1 inhibits chaperone-mediated autophagy, preventing STAT3 degradation.
TRPC1 modulates the interaction between HDAC6 and HSC70, affecting CMA activity.
Abstract
Calcium dysregulation is closely associated with cancer cell proliferation, migration, and invasion. Transient receptor potential canonical 1 (TRPC1) plays an essential role in regulating calcium homeostasis. However, the role of TRPC1 in calcium dysregulation in gliomas remains incompletely understood. In this study, we demonstrate that TRPC1 promotes glioma cell migration by increasing Signal transduction and transcription activator 3 (STAT3) protein levels. Furthermore, we show that TRPC1 modulates STAT3 stability by inhibiting chaperone‐mediated autophagy (CMA), and we identify STAT3 as a novel substrate of CMA. Additionally, TRPC1 modulates the interaction between HDAC6 and Heat Shock Cognate 70 through intracellular Ca2+ homeostasis, which is associated with changes in CMA activity. These changes prevent STAT3 degradation, highlighting the TRPC1‐HDAC6 axis as a regulator of glioma…
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FIGURE 8- —Basic and Applied Basic Research Foundation of Guangdong Province10.13039/501100021171
- —National Natural Science Foundation of China10.13039/501100001809
- —Dongguan Social Development Science and Technology (Key) Project
- —Guangdong Medical University Clinical + Basic Medical Science and Technology Innovation Special Program
- —Science Foundation of traditional Chinese medicine administration of Guangdong Province
- —Discipline Construction Project of Guangdong Medical University
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Taxonomy
TopicsIon Channels and Receptors · Endoplasmic Reticulum Stress and Disease · Cytokine Signaling Pathways and Interactions
Introduction
1
Gliomas are the most common primary tumors of the central nervous system, with patients facing a poor prognosis due to their highly invasive nature [1, 2]. Specifically, the median survival time for patients with glioblastoma (GBM), the most malignant subtype of glioma, is approximately 15 months [2, 3, 4]. Despite extensive research into gene therapy and molecular signaling pathways to improve treatment outcomes for glioma, the molecular mechanisms underlying its development remain poorly understood [5]. Therefore, elucidating the pathogenesis and identifying therapeutic targets are crucial for advancing glioma treatment.
Calcium ions (Ca^2+^) are essential second messengers in cells, vital for the survival and function of all higher organisms. Disruptions in Ca^2+^ homeostasis and signaling are frequently associated with pathological conditions, such as cancer. Transmembrane ion channels play a critical role in tumor proliferation and invasion [6]. Furthermore, ion channels are potential biomarkers and therapeutic targets for GBM because of their role in promoting glioma malignancy [7]. Transient receptor potential canonical 1 (TRPC1), the first identified member of the mammalian transient receptor potential canonical (TRPC) family, is a non‐selective cation channel ubiquitously expressed in human tissues, involved in cell migration and proliferation [8]. Studies have demonstrated that TRPC1 mediates Ca^2+^ influx in response to endoplasmic reticulum Ca^2+^ store depletion, thereby influencing cell invasion and migration [9]. Additionally, TRPC1 plays a significant role in chemotaxis, migration, and cytokinesis in glioma cells by regulating calcium homeostasis [10, 11, 12]. However, the precise functions, clinical implications, and molecular mechanisms of TRPC1 in glioma progression remain to be fully elucidated.
Signal Transducer and Activator of Transcription 3 (STAT3) is constitutively activated in gliomas and has been established as both a prognostic marker and a therapeutic target, influencing glioma cell proliferation, survival, migration, invasion, and angiogenesis [9]. STAT3 promotes the malignant progression of glioma cells, and its activity is regulated by the Ca^2+^/calpain signaling axis [13, 14]. Research indicates that STAT3 activation depends on TRPC1 channel‐mediated calcium signals [15], suggesting that TRPC1 may enhance glioma cell migration by modulating STAT3 activation. Nevertheless, the exact molecular mechanisms and the interplay between TRPC1 and STAT3 in glioma development are not yet fully understood.
High‐grade glioma cells, such as those from anaplastic astrocytomas and glioblastomas, exhibit lower levels of autophagy‐associated proteins compared to low‐grade gliomas [16, 17, 18]. Notably, inducing autophagy in GL15 and U87 glioma cell lines can reverse epithelial‐mesenchymal transition, migration, and invasion [17]. While autophagy has been extensively studied for its role in regulating cancer cell death and survival, and modulating autophagy is being explored as a potential therapy for malignant gliomas, research on chaperone‐mediated autophagy (CMA) is still limited. CMA selectively degrades specific intracellular proteins [19, 20]. As more CMA substrates and regulators are identified, targeting CMA may offer new avenues for cancer treatment. However, the role of CMA in glioma pathogenesis remains unclear.
CMA relies on lysosome‐associated membrane protein type 2A (LAMP2A) and heat shock proteins (HSPs). Histone deacetylase 6 (HDAC6) regulates autophagy and interacts with HSPs to promote tumor development and progression. The precise mechanisms by which HDAC6 influences autophagy are not fully understood, and its specific role in gliomas is still unclear.
In this study, we demonstrate that TRPC1‐mediated calcium dysregulation impairs CMA‐dependent STAT3 degradation, thereby promoting glioma cell migration and tumor progression. Mechanistically, TRPC1 suppresses CMA activity by modulating HDAC6‐mediated deacetylation of Heat Shock Cognate 70 (HSC70), which prevents recognition and lysosomal degradation of STAT3—a protein we identify here as a novel CMA substrate. Furthermore, both pharmacological inhibition of TRPC1 and activation of CMA attenuate glioma progression. These findings establish the TRPC1‐HDAC6‐CMA‐STAT3 axis as a central mechanism driving glioma malignancy and highlight potential therapeutic targets for intervention.
Materials and Methods
2
Data Mining From Public Databases
2.1
The expression levels of TRPC1 and STAT3 were analyzed using the Cancer Cell Line Encyclopedia (CCLE; https://portals.broadinstitute.org/ccle), The Human Protein Atlas (https://www.proteinatlas.org/), and Gene Expression Profiling Interactive Analysis (GEPIA; http://gepia.cancer‐pku.cn/index.html) databases. Additionally, the correlation between TRPC1 and STAT3 expression across different stages of glioma was investigated using GEPIA and the Chinese Glioma Genome Atlas (CGGA; http://www.cgga.org.cn/index.jsp).
Cell Cultures and Treatments
2.2
U87 human GBM cells (Shanghai, China) and U251 human GBM cells (Shanghai, China) were cultured in Dulbecco's Modified Eagle's Medium (DMEM) supplemented with 10% fetal bovine serum (Sangon Biotech; Uruguay, South America) and penicillin/streptomycin (Beyotime, China), at 37°C in a humidified atmosphere of 5% CO_2_. Cells were treated with the following agents for 48 h: 100 μM 2‐Aminoethyl diphenylborinate (2‐APB), 20 μM QX77, 20 μM Chloroquine (CQ), 1 μM mg132. For each treatment, the cells were divided into separate wells to account for biological variability, with three independent replicates per condition.
Cells Transfection, Plasmids, and siRNA‐Mediated Knockdown
2.3
Cell transfection was achieved by using Lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA) for plasmid and siRNA following the manufacturer's protocols. The overexpression plasmid‐CV702 TRPC1 (CV702‐TRPC1) was constructed by Genechem Biotechnology (Shanghai, China). The TRPC1 siRNA (siTRPC1), LAMP2A siRNA (siLAMP2A) and STAT3 siRNA (siSTAT3) were purchased from GenePharma Biotechnology (Suzhou, China). Lentiviruses knocking down TRPC1 were purchased from Hanbio (Shanghai, China). A stable shTRPC1 cell line was achieved by lentivirus transduction according to manufacturer's protocols. And U251 cells were similarly subjected to TRPC1 knockdown using the same siRNA and lentiviral approaches for parallel validation experiments. Nucleotide sequences were shown in the Table S1. The transfection efficiency was confirmed by quantitative real‐time PCR and Western blotting.
Quantitative Real‐Time PCR
2.4
Total RNA was extracted from U87 cells using TRIzol reagent (thermo, New York, USA), and then reverse transcribed into cDNA using qScript reverse transcriptase (Takara, Kyoto, Japan). Primers were purchased from Generay. TRPC1:F,5‐AGTGACGAGCCTCTTGACAAAC‐3 and R,5‐GGGCTTGCGTCGGTAAC‐3; STAT3:F,5‐CAGCAGCTTGACACACGGTA‐3 and R,5‐AAACACCAAAGTGGCATGTGA‐3; LAMP2A:F,5‐GCCGTTCTCACACTGCTCTA‐3 and R,5‐CCGCTATGGGCACAAGGAA‐3; β‐Actin:F,5‐ATTGGCAATGAGCGGTTCC‐3 and R,5‐GGTAGTTTCGTGGATGCCACA‐3.
Quantitative Real‐Time PCR was performed using 0.8 μL of cDNA, 5 μL of TB Green (Takara, Japan) and 10 μM of each primer in a total reaction volume of 10 μL. The reaction was initiated at 95°C for 30 s, and followed by 40 cycles of denaturation at 95°C for 5 s, annealing at 60°C for 1 min and extension at 60°C for 30 s. Data were recorded on a Thermal Cycler Dice Real‐Time System and cycle threshold values for each reaction were determined using analytical software from the same manufacturer.
Migration Assay
2.5
Wound healing assay: Constructed cells were seed in a 24‐well culture plate (1 × 10^5^ cells/well), and placed at 37°C, 5% CO_2_ for 24 h. Remove the medium and scratch the surface of the inoculated cells with a 10 μl pipette tip and mark it. Wash gently twice with phosphate‐buffered saline (PBS). Add 1 mL of the medium containing 10% serum. Photograph the scratches at 0 h and 24 h. The experiment was conducted in three sessions and repeated five times. The distance that the cells migrated to the wounded area during this time was measured. The results are expressed as migration index (the migration distance of cells in the experimental group relative to the migration distance of cells in the NC group).
Transwell cell migration assay: Constructed cells were seeded in the wells of a Matrigel plate containing serum‐free and high‐glucose DMEM medium (1 × 10^5^ cells/well). The lower well contains 500 μL of complete medium (DMEM and 10% fetal bovine serum). After incubation at 37°C for 48 h, gently remove cells that have not migrated through the well with a cotton swab. The cells in the lower chamber were fixed with 5% glutaraldehyde for 10 min and stained with 1% crystal violet in 2% ethanol at room temperature for 20 min, photographed, and counted.
Establishment of Tumor‐Bearing Nude Mouse Model
2.6
Cells in the logarithmic growth phase were digested with 0.25% trypsin, centrifuged at 1000 rpm for 3 min, and the supernatant was discarded to collect the cells. Count the cells after resuspending them in PBS, and adjust the cell concentration to about 6 × 10^7^ cells/ml, put on ice for use.
Prepare 36 male and female BALB/c nude mice (purchased from Guangdong Experimental Animal Center) of 3–5 weeks of age with no specific pathogens and an average weight of 17 ± 2 g. Mice were randomly assigned to four groups (six mice per group) using a random number generator and inoculated with U87 cells in overexpression (OE), normal control (NC), TRPC1 siRNA interfering (TRPC1), TRPC1 + STAT3 siRNA interfering (TRPC1 + STAT3), and TRPC1 + LAMP2A siRNA interfering (TRPC1 + LAMP2A) groups. We aspirated the cell suspension with a 1 mL syringe (shake the cell suspension before mixing) and slowly injected 150 μL suspension into the subcutaneous area of the axilla of nude mice. After the tumor cells were inoculated, the general condition and growth of the nude mice were closely observed. The nude mice were housed in separate cages in the specific pathogen‐free‐grade animal room of the Animal Experiment Center of Guang dong Medical University. Tumor volume was measured weekly, and the general health status of the animals was monitored throughout the experiment. After 6 weeks, the nude mice were euthanized (Chloral hydrate injection, Shanghai, China). The tumors were carefully peeled off and removed. The tumors were placed neatly and photographed. The tumor volume was measured with a ruler and weighed on the scales. Volume formula: volume = long diameter × short diameter2 × 1/2. All experiments were conducted under the guidelines outlined by the committee of Guangdong Medical University on the use and care of animals.
Proteomic Analysis (TMT/iTRAQ Scan)
2.7
Cell samples from three groups of shTRPC1 and three groups of control cells were used for proteomic analysis. Metware Biotechnology Co. Ltd. (Wuhan, China) performed lysis of the samples, protein precipitation, digestion and labeling with a TMT Mass Tag Labeling kit. Peptide samples were reconstructed, fractionated, and disposed to LC–MS/MS analysis. Raw MS data were analyzed in MaxQuant (V1.6.6) using the Andromeda algorithm. Annotate the identified protein with Gene Ontology, Kyoto Encyclopedia of Genes and Genomes and Clusters of Orthologous Groups of proteins databases to explore the function of protein.
Lysosomal Isolation and Protein Uptake Assay
2.8
U87 cells (density: 1–3 × 10^8^) were washed twice with 5 mL PBS, and collected by centrifugation 500 g for 5 min at 4°C. After suspending the cells, the cells were homogenated 20–30 times in a homogenizer. Then, lysosomes were attained through high‐speed centrifugation and flotation in a discontinuous metrizamide gradient. Following isolation, the integrity of lysosomes was verified by measuring the activity of β‐hexosaminidase. The preparations with lysosomes' damage rate more than 10% after separation were scrapped. Total proteins were incubated with freshly isolated U87 cells' lysosomes for 30 min at 37°C with or without protease inhibitor cocktails (10 mM leupeptin, 10 mM 4‐(2‐aminoethyl)benzenesulfonyl fluoride hydrochloride, 1 mM pepstatin, and ethylenediaminetetraacetic acid (EDTA)). At the end of the incubation, lysosomes were collected and subjected to SDS‐PAGE.
Western Blotting and Co‐Immunoprecipitation
2.9
U87 cells were lysed in RIPA buffer (Beyotime, Shanghai, China) supplemented with 1:100 phenylmethylsulfonyl fluoride (PMSF; Beyotime, Shanghai, China). Lysates were centrifuged to remove debris, and the supernatant was collected. Protein concentration was determined using the BCA Protein Assay Kit (Beyotime, Shanghai, China). For Western blotting (WB), 20 μg of protein per sample was mixed with 5 × SDS‐PAGE loading buffer (Beyotime, Shanghai, China) at a 4:1 ratio (sample:buffer) and boiled at 100°C for 5 min. Proteins were separated by SDS‐PAGE and transferred to polyvinylidene fluoride (PVDF) membranes. Membranes were blocked with 5% bovine serum albumin (BSA) in Tris‐buffered saline with Tween 20 (TBST) for 1 h at room temperature and incubated overnight at 4°C with primary antibodies: rabbit anti‐TRPC1 (1:1500, Abcam, Cambridge, UK), mouse anti‐STAT3 (1:1500, Cell Signaling Technology, Danvers, MA, USA), rabbit anti‐phospho‐STAT3 (1:1500, Cell Signaling Technology), rabbit anti‐HSC70 (1:1000, Proteintech, Rosemont, IL, USA), rabbit anti‐LAMP2A (1:1000, Proteintech), mouse anti‐vimentin (1:1000, Santa Cruz Biotechnology, Dallas, TX, USA), mouse anti‐tubulin (1:1000, Proteintech), and mouse anti‐GAPDH (1:1000, Beyotime). Membranes were then incubated with horseradish peroxidase (HRP)‐conjugated secondary antibodies (1:1000) for 1 h at room temperature. Protein bands were visualized using an enhanced chemiluminescence (ECL) detection system and quantified with ImageJ software.
For co‐immunoprecipitation (co‐IP), cell lysates were incubated overnight at 4°C with the appropriate primary antibody. The following day, 70 μL of protein A/G agarose beads (Bioworld, Bloomington, IN, USA) was added and incubated for 2 h at 4°C with rotation. Beads were washed three times with lysis buffer, and immunoprecipitated proteins were eluted by boiling in 2 × SDS‐PAGE sample buffer for 5 min before WB.
Immunofluorescence Assay
2.10
Cells were washed twice in PBS, fixed in 4% paraformaldehyde for 15 min and permeabilized with Precooled methanol for 10 min. Then incubated in 5% BSA blocking buffer for 30 min. STAT3 and LAMP2A were detected in a confocal microscope by incubating the cells with anti‐STAT3 (1: 200, Cell signaling) and anti‐LAMP2A (1: 100, Proteintech) antibodies, followed by anti‐rabbit CoraLite488‐conjugated (1: 100, Proteintech) and anti‐mouse CoraLite594‐conjugated (1: 100, Proteintech) secondary antibody.
Tissue samples: paraffin sections were dewaxed to water and placed in a repair box filled with EDTA antigen repair buffer (PH8.0) for antigen repair in a microwave oven. Using a histochemical pen to draw a circle around the tissue to prevent the flow of antibodies, the sections were sealed with 3% hydrogen peroxide. BSA was added to block for 30 min, washed three times with PBS, and the first antibody was added to incubate at 4°C in the wet box overnight. Next day, the corresponding Horseradish Peroxidase labelled second antibody was added to incubate 50 min at room temperature, then washed three times, and Cy3‐tyramide (or Fluorescein isothiocyanate‐tyramide) was added to incubate at room temperature for 10 min in dark. Another first antibody was incubated by repeating the above steps, and the nucleus was re‐stained with 4′,6‐diamidino‐2‐phenylindole. Sections were sealed with an anti‐fluorescence quenching agent and observed under a confocal microscope.
Immunohistochemistry
2.11
The surgically resected glioma tissues were harvested from 15 patients (grade 2: five cases, grade 3: five cases, grade 4: five cases) at Shenzhen People's Hospital, China, after having obtained informed consent from the patients and in line with the guidelines of the Research Ethics Committee. All samples were preserved in formalin or expeditiously frozen and stored at −80°C after surgery. Demographic data of the patients were shown in Table S2.
Paraffin embedded tissue sections were de‐paraffinized with xylene and endogenous peroxidase activity was quenched with 3% H_2_O_2_ in methanol for 25 min in the dark. Tissue sections were dehydrated through graded alcohols and subjected to antigen retrieval using sodium citrate. After PBS wash three times and blocked with 3% BSA for 30 min, sections were incubated sequentially with the primary antibodies at 4°C overnight. The next day, sections were then washed for 5 min in PBS and incubated for 1 h with the respective secondary antibody (Servicebio, Wuhan, China). After washing, sections were incubated with 3,3′‐diaminobenzidine tetrahydrochloride (Servicebio, Wuhan, China) and immediately washed under tap water after color development. Sections were then counter stained with haematoxylin. Slides were mounted with dibutyl phthalate xylene and were then observed under a light microscope.
Statistical Analyses
2.12
All data are presented as the Mean ± Standard Deviation (SD) from at least three independent biological replicates (n ≥ 3), unless otherwise specified in individual figure legends. The unpaired/paired Student's t‐test was used to determine statistical significance between two groups, while one‐way ANOVA followed by Dunnett's multiple comparisons test was used for comparisons involving more than two groups. All statistical analyses were performed using GraphPad Prism version 8. Statistical significance was defined as *p < 0.05, **p < 0.01, ***p < 0.001. Results were mirrored in each figure legend for transparency, specifying the statistical test, data presentation format (mean ± SD), and significance threshold (p < 0.05). The specific statistical approaches for each assay type are detailed below:
- Western blot quantification: Band intensities were quantified using ImageJ software and normalized to loading controls (β‐tubulin). Data from n = 3 independent experiments are presented as mean ± standard deviation (SD).
- Wound‐healing assays: Migration distance was measured at 0 h and 24 h (or 48 h as indicated) using ImageJ. Five independent measurements per condition from n = 3 biological replicates were quantified. Data are expressed as migration index (experimental group migration distance relative to control group).
- Transwell migration assays: Migrated cells were counted in five random fields per membrane from n = 3 independent experiments. Data are presented as mean ± SD.
- Immunofluorescence colocalization: Colocalization was quantified using Pearson's correlation coefficient calculated from at least 10 cells per condition across n = 3 independent experiments.
Results
3
TRPC1 Promotes Tumor Progression in Glioma Cells
3.1
To investigate the functional role of TRPC1 in glioma progression, we first characterized TRPC1 expression patterns across glioma grades and examined its effects on glioma cell migration and tumor growth. According to the CCLE (https://portals.broadinstitute.org/ccle/page?gene=TRPC1) and The Human Protein Atlas (https://www.proteinatlas.org/ENSG00000144935‐TRPC1/celltype), the expression of TRPC1 in gliomas was relatively higher than that in other tumor (Figure S1A,B). Additionally, immunohistochemistry (IHC) analysis of gliomas from grades 2 to 4 demonstrated a progressive increase in TRPC1 expression with increasing tumor grade (Figure S1C,D). To investigate the role of TRPC1 in the development of glioma, wound‐healing and transwell assays were performed to elucidate the effect of TRPC1 on the migration of U87 cells. Treatment with 100 μM 2‐APB, a specific TRPC inhibitor, significantly reduced the number of migratory U87 cells at 48 h compared to control cells (Figure S1E–G). WB analysis showed a corresponding decrease in Vimentin levels, a protein involved in cell migration, following 2‐APB treatment (Figure S1H,I).
Sin U87 cells using siRNA (siTRPC1) to knock down TRPC1 or a plasmid (CV702‐TRPC1) to overexpress TRPC1. Wound‐healing and transwell assays revealed that siTRPC1 treatment significantly decreased U87 cell migration, whereas CV702‐TRPC1 treatment enhanced migration (Figure 1A–E). Consistently, Vimentin expression was increased in U87 cells overexpressing TRPC1 (Figure 1F,G). To assess the role of TRPC1 in calcium influx, U87 cells were treated with siTRPC1 or CV702‐TRPC1 and loaded with Fluo‐4 AM to measure intracellular Ca^2+^ levels. Thapsigargin (Tg, 1 μM), a SERCA pump inhibitor, was used to deplete endoplasmic reticulum (ER) Ca^2+^ stores and induce Ca^2+^ entry. The Tg‐induced increase in intracellular Ca^2+^ was significantly reduced in siTRPC1‐treated cells but enhanced in cells overexpressing TRPC1 (Figure 1H) [21]. To validate these findings in vivo, nude mice were subcutaneously injected with 1 × 10^6^ U87 cells stably expressing shTRPC1 (knockdown) or CV702‐TRPC1 (overexpression). Mice injected with shTRPC1 U87 cells developed smaller tumor and exhibited reduced tumor weight compared to controls (Figure 1I–K). Collectively, these data demonstrate that TRPC1 promotes glioma cell migration and tumor progression by regulating calcium influx.
*TRPC1 facilitates the migration of glioma cells. (A‐E): Wound‐healing assay (scale bar: 250 μm, 48 h) and transwell assay (scale bar: 50 μm, 48 h) evaluating cell migratory capacity in U87 cells treated with siTRPC1 or CV702‐TRPC1. (F‐G): Western blot analysis of Vimentin expression in U87 cells treated with siTRPC1 or CV702‐TRPC1. (H): Ca2+ tracing in U87 cells following treatment with siTRPC1 or CV702‐TRPC1. (I‐K): Tumor weight and size changes in nude mice xenograft model (n = 6 mice per group). All in vitro data represent n = 3 independent biological replicates. Data are presented as mean ± SD (*p < 0.05, **p < 0.01, **p < 0.001).
TRPC1 Facilitates Glioma Migration via Up‐Regulating the Expression of STAT3
3.2
Having established that TRPC1 promotes glioma cell migration (Figure 1), we next sought to identify the downstream effectors mediating this effect. Given the known involvement of STAT3 in glioma malignancy and its reported regulation by calcium signaling, we investigated whether TRPC1 influences glioma progression through modulation of STAT3. To explore potential mechanisms, we analyzed STAT3 expression in gliomas using the GEPIA (http://gepia.cancer‐pku.cn/detail.php?gene=STAT3). GEPIA analysis revealed significantly higher STAT3 expression in low‐grade gliomas and glioblastoma multiforme compared to normal brain tissues (Figure 2A) [14]. Furthermore, a positive correlation between TRPC1 and STAT3 expression was observed across different glioma grades using GEPIA (http://gepia.cancer‐pku.cn/detail.php?clicktag=correlation) and CGGA (http://www.cgga.org.cn/analyse/RNA‐data‐expression‐correlation‐result.jsp) (Figure 2B). IHC analysis of human glioma samples from grades 2 to 4 demonstrated that both TRPC1 and STAT3 expression levels increase with tumor malignancy (Figure 2C,D).
*TRPC1 facilitates glioma migration via upregulating STAT3 expression. (A): STAT3 expression in normal brain tissue and GBM from GEPIA database. (B): Positive correlation between TRPC1 and STAT3 in primary and recurrent gliomas from CGGA datasets. (C‐D): Representative IHC images of TRPC1 and STAT3 in glioma tissues (scale bar: 100 μm; n = 5 patients per grade). (E‐F): Proteomic analysis showing STAT3 expression (n = 3 biological replicates per group). (G): RT‐qPCR analysis of STAT3 mRNA levels after TRPC1 knockdown (n = 3 biological replicates). (H‐I): Western blot analysis of STAT3 expression in U87 cells (n = 3 biological replicates). (J‐L): Migration analysis of U87 cells transfected with CV702‐TRPC1 and/or siSTAT3 (n = 3 biological replicates). Data are presented as mean ± SD (*p < 0.05, **p < 0.01, **p < 0.001).
To further verify the effect of TRPC1 on STAT3, proteomic analysis was performed and the results showed that TRPC1 knockdown could down‐regulate the level of STAT3 protein (Figure 2E,F). Notably, the proteomic volcano plot (Figure 2F) highlighted STAT3 as one of the most significantly downregulated proteins in TRPC1‐knockdown cells, indicating that loss of TRPC1 leads to a pronounced reduction in STAT3 protein abundance. This unbiased finding strongly suggests a post‐transcriptional mechanism for STAT3 regulation by TRPC1, since STAT3 mRNA levels remained unchanged in these conditions (Figure 2G). Consequently, we hypothesized that TRPC1 stabilizes STAT3 via inhibiting its degradation rather than enhancing STAT3 gene expression. Guided by this proteomics insight, we began to explore whether STAT3 undergoes CMA and found evidence supporting STAT3 as a CMA substrate whose degradation is impeded by TRPC1. To determine whether the expression of STAT3 was regulated by TRPC1, we detected that the mRNA level of STAT3 had not significantly changed after treating U87 cells with siTRPC1 and CV702‐TRPC1 (Figure 2G). In contrast, WB analysis showed a marked decrease in STAT3 protein levels upon TRPC1 knockdown (Figure 2H,I). To confirm that TRPC1‐mediated glioma migration involves STAT3 activation [22], we evaluated the migration of U87 cells with manipulated STAT3 expression. Knockdown STAT3 diminished the migration ability by wound‐healing assay and transwell experiment (Figure 2J–L). Besides, the U87 cells' migration was also reduced after siSTAT3 treatment in TRPC1‐overexpressing U87 cells compared with CV702‐TRPC1 U87 cells (Figure 2J–L). Similarly, Vimentin expression decreased following siSTAT3 treatment in U87 cells, and this reduction was also observed in TRPC1‐overexpressing U87 cells treated with siSTAT3 (Figure S2A,B). In summary, as a key molecular determinant of glioma migration, STAT3 was regulated by TRPC1.
TRPC1 Activates STAT3 via Blocking CMA
3.3
Given that TRPC1 affects STAT3 protein levels without altering its mRNA, we hypothesized that TRPC1 might influence STAT3 degradation. The ubiquitin‐proteasomal system (UPS) and the autophagy‐lysosomal system (ALS), as the main cellular proteolytic systems, serve in maintaining proteostasis and strongly influence cellular fate [23]. To investigate this, we used the proteasome inhibitor MG132 and autophagy inhibitor CQ. Treatment with CQ (lysosome inhibitor, 20 μM), but not MG132 (proteasome inhibitor, 1 μM), prevented the decrease in STAT3 levels induced by TRPC1 inhibition, suggesting that STAT3 degradation is mediated by the autophagy‐lysosome pathway rather than the proteasome (Figure 3A–C).
*TRPC1 regulates STAT3 protein levels via CMA. (A‐C): Western blot analysis of STAT3 in U87 cells treated with proteasome inhibitor MG132 (1 μM) or autophagy inhibitor CQ (20 μM) combined with TRPC1 inhibition or knockdown (n = 3 biological replicates). (D‐E): Western blot analysis of STAT3 in U87 cells with siLC3, siATG5, siHSC70, or siLAMP2A combined with TRPC1 knockdown (n = 3 biological replicates). (F‐G): Western blot analysis of LAMP2A after TRPC1 knockdown or overexpression (n = 3 biological replicates). (H‐I): Western blot analysis of STAT3 and LAMP2A in U87 cells treated with QX77 (20 μM) combined with TRPC1 overexpression (n = 3 biological replicates). (J‐L): Migration analysis of U87 cells transfected with CV702‐TRPC1 and/or QX77 treatment (48 h; n = 3 biological replicates). Data are presented as mean ± SD. (*p < 0.05, **p < 0.01, **p < 0.001).
To further explore whether TRPC1 inhibits the degradation of STAT3 through macroautophagy, we knocked down the LC3 and ATG5, key mediators of macroautophagy. However, knockdown of LC3 or ATG5 did not prevent STAT3 degradation induced by TRPC1 inhibition (Figure 3D), indicating that macroautophagy is not responsible. We then investigated whether STAT3 is degraded via CMA by knocking down LAMP2A and HSC70, essential components of CMA. Notably, in TRPC1‐knockdown cells, additional knockdown of LAMP2A or HSC70 prevented the degradation of STAT3 (Figure 3D,E), suggesting that CMA is involved in STAT3 degradation. Furthermore, TRPC1 knockdown increased LAMP2A protein levels, whereas TRPC1 overexpression decreased them (Figure 3F,G).
To evaluate the effect of CMA on glioma cell migration that was effectively promoted by TRPC1 in the following work. The expression of TRPC1 and LAMP2A in U87 cells treated with QX77 (CMA agonist) and TRPC1 were measured. Those results revealed that CMA receptor LAMP2A level was decreased in the overexpression of TRPC1 U87 cells, which was rescued by QX77 (Figure 3H,I). Next, QX77 (20 μM) could not only inhibit the migration of U87 cells but also eliminate the migration effect of TRPC1 overexpression (Figure 3J–L). In summary, TRPC1 stabilizes STAT3 by inhibiting CMA, thereby promoting glioma cell migration.
To further validate the generality of the TRPC1‐HDAC6‐CMA‐STAT3 pathway, we extended our experiments to another glioma cell line, U251. In this parallel experiment, we silenced TRPC1 expression in U251 cells and analyzed the levels of STAT3, LAMP2A and Vimentin by WB. The results were consistent with our findings in the U87 cell line, showing that TRPC1 knockdown in U251 cells led to decreased STAT3 levels, increased LAMP2A levels, and decreased Vimentin expression, indicating enhanced CMA activity. This supports the hypothesis that the TRPC1‐HDAC6‐CMA‐STAT3 pathway is not specific to U87 cells but may function similarly across different glioblastoma cell lines (Figure S4).
STAT3 Is a Direct Substrate of CMA
3.4
The preceding results demonstrate that TRPC1 stabilizes STAT3 by inhibiting CMA; however, whether STAT3 serves as a direct CMA substrate remained to be established. To address this question, we examined the molecular requirements for CMA‐mediated STAT3 degradation, including the presence of KFERQ‐like motifs and direct interactions with CMA machinery components. Importantly, CMA substrates typically contain a KFERQ‐like pentapeptide sequence recognized by HSC70. By analyzing the human STAT3 amino acid sequence, we identified five such KFERQ‐like motifs in STAT3: 69SRFLQ73, 113SRLLQ117, 149QDVRK153, 322VVERQ326, and 570DLVKK574 (Figure S3A).This indicates that STAT3 possesses the requisite CMA‐targeting motif, supporting its identification as a novel CMA substrate. Using the STRING (https://string‐db.org/cgi/network?taskId=bcclJyXmo2GQandsessionId=bGiwdEBidVOG), we found potential functional associations between TRPC1, HSPA8 (HSC70), LAMP2A and STAT3, suggesting a regulatory network involving CMA (Figure S3B).
To confirm that STAT3 is a CMA substrate, we performed co‐IP assays in human glioma tissues, nude mouse tumor tissues, and U87 cells, demonstrating an interaction between LAMP2A and STAT3 (Figure 4A). Furthermore, inhibition of TRPC1 increased the interaction between STAT3 and LAMP2A, as well as between STAT3 and HSC70, in U87 cells (Figure 4B,C). Immunofluorescence (IF) analysis revealed that colocalization STAT3 with HSC70 and LAMP2A was reduced in cells overexpressing TRPC1 and increased in cells with TRPC1 knockdown (Figure 4D–G). Notably, preliminary findings from IF analysis suggest that TRPC1 knockdown may promote HSC70 translocation from the cytoplasm to the nucleus (Figure 4D), a phenomenon that could potentially influence CMA activity or STAT3 degradation. However, the specific mechanisms underlying this translocation remain unclear and require detailed investigations, such as subcellular fractionation and mutational analysis, to validate its functional significance in glioma progression. In vivo, IF analysis of nude mouse tumors showed that siTRPC1 treatment enhanced the colocalization LAMP2A and STAT3 (Figure 4H,I). Additionally, in human glioma samples, the colocalization decreased with increasing tumor grade (Figure 4J,K).
*TRPC1 regulates the interaction between STAT3 and LAMP2A/HSC70. (A): Co‐IP confirming STAT3‐LAMP2A interaction using anti‐LAMP2A antibodies in glioma tissues, nude mice tumor tissues, and U87 cells (n = 3 biological replicates). Input shows total protein before immunoprecipitation. (B‐C): Co‐IP with anti‐STAT3 antibodies in siTRPC1‐transfected U87 cells, immunoblotted for HSC70 and LAMP2A (n = 3 biological replicates). (D‐G): Immunofluorescence colocalization analysis of STAT3 with HSC70 or LAMP2A (scale bar: 50 μm; n = 3 biological replicates, ≥ 10 cells analyzed per condition). (H‐I): Immunofluorescence colocalization of LAMP2A and STAT3 in control, shTRPC1, and CV702‐TRPC1 groups in xenograft tumor tissue (scale bar: 50 μm). Pearson's coefficients: Control = 0.68, shTRPC1 = 0.75, CV702‐TRPC1 = 0.59. (J‐K): Immunofluorescence colocalization of LAMP2A and STAT3 in human glioma samples from grades 2, 3, and 4 (scale bar: 50 μm; n = 5 patients per grade). Pearson's coefficients: Grade 2 = 0.90, grade 3 = 0.74, grade 4 = 0.69. Data are presented as mean ± SD (*p < 0.05, **p < 0.01, **p < 0.001).
To further assess whether CMA is involved in the regulation of STAT3 degradation, U87 cells were subjected to serum deprivation or treated with QX77 (20 μM), both known to activate CMA. Both treatments increased LAMP2A protein levels and decreased STAT3 protein levels (Figure 5A–D). In order to demonstrate that STAT3 is targeted to CMA‐active lysosomes, we isolated lysosomes enriched with HSC70. Then, the addition of total proteins to isolated lysosomes showed that STAT3 was degraded, whereas the increased levels of recombinant STAT3 were present in the lysosomes following the addition of protease inhibitors cocktail (Figure S3C). Meanwhile, the expression of GAPDH, a common CMA substrate, showed that GAPDH was degraded in CMA‐active lysosomes, but not in lysosomes with protease inhibitors cocktail (Figure 5E,F), which strongly proves that the experiment of lysosome binding and uptake in vitro was feasible.
*STAT3 is a novel substrate of CMA. (A‐B): Western blot analysis of STAT3 and LAMP2A in U87 cells subjected to serum starvation (n = 3 biological replicates). (C‐D): Western blot analysis of STAT3 and LAMP2A in U87 cells treated with QX77 (20 μM; n = 3 biological replicates). (E‐F): In vitro lysosomal binding and uptake assay showing protein levels following incubation with isolated lysosomes ± protease inhibitors (n = 3 biological replicates). (G‐H): Western blot analysis of STAT3 in U87 cells treated with siLAMP2A and/or QX77 (n = 3 biological replicates). (I‐J): Western blot analysis of STAT3 in U87 cells treated with siLAMP2A and/or siTRPC1 (n = 3 biological replicates). (K‐L): Migration analysis of U87 cells treated with siTRPC1 and/or siLAMP2A (48 h; n = 3 biological replicates). Data are presented as mean ± SD (*p < 0.05, **p < 0.01, **p < 0.001).
To confirm STAT3 was degraded through CMA, we treated U87 cells with LAMP2A siRNA. As Figure shown, LAMP2A siRNA effectively blocked STAT3 degradation caused by QX77 (Figure 5G,H). To investigate whether siLAMP2A could block the STAT3 degradation regulated by TRPC1, siLAMP2A was transfected in knockdown TRPC1 U87 cell lines and normal U87 cells. The results revealed that siLAMP2A can effectively eliminate the decrease of STAT3 caused by siTRPC1, while LAMP2A level was increased in shTRPC1‐U87 cells (Figure 5I,J). The migration of U87 cells ability attenuated by shTRPC1 was significantly enhanced after siLAMP2A treatment (Figure 5K,L). All these data suggested that STAT3 localized in CMA‐active lysosomes was degraded through CMA, involved in glioma migration.
TRPC1 Activates CMA via Inhibiting HDAC6‐Mediated HSC70 Deacetylation
3.5
While our findings established that TRPC1 inhibits CMA‐dependent STAT3 degradation (Figures 3, 4, 5), the mechanism by which TRPC1 suppresses CMA activity remained unclear. To elucidate this regulatory mechanism, we performed proteomic analysis to identify proteins differentially expressed upon TRPC1 knockdown that might link TRPC1 to CMA regulation. Proteomic data revealed that HDAC6 expression was elevated in TRPC1‐knockdown cells compared to controls (Figure 6A). In particular, the proteomic analysis (Figure 6A) identified HDAC6 as a significantly upregulated protein upon TRPC1 silencing, underscoring a potential link between TRPC1 loss and increased HDAC6 activity. This finding provides strong support for the TRPC1‐HDAC6‐CMA regulatory hypothesis: normally, TRPC1 appears to restrain HDAC6, so without TRPC1, HDAC6 levels rise and likely lead to excessive deacetylation of HSC70. Such deacetylation would impair CMA activity, since acetylated HSC70 is required for efficient substrate delivery to lysosomes. Thus, the proteomics result revealing HDAC6 upregulation in TRPC1‐knockdown cells was pivotal, as it connects TRPC1 depletion to reduced CMA activity and helps explain how TRPC1 keeps CMA active by holding HDAC6‐mediated inhibition in check. IHC analysis of human glioma samples showed an inverse correlation between HDAC6 and TRPC1 expression across grades 2 to 4 (Figure 6B,C). Moreover, the protein levels of HDAC6 were increased after TRPC1 knockdown and declined after TRPC1 overexpression both in U87 cells and nude mice tumor (Figure 6D–G). To investigate if HDAC6 affects CMA activity, we manipulated HDAC6 expression in TRPC1‐knockdown U87 cells. Knockdown of HDAC6 increased LAMP2A levels, while overexpression of HDAC6 decreased LAMP2A levels (Figure 6H,I), suggesting that HDAC6 negatively regulates LAMP2A and thus CMA activity.
*TRPC1 activates CMA via inhibiting HDAC6‐mediated HSC70 deacetylation. (A): Proteomic analysis showing HDAC6 expression (n = 3 biological replicates per group). (B‐C): Representative IHC images of TRPC1 and HDAC6 in glioma tissues (scale bar: 100 μm; n = 5 patients per grade). (D‐E): Western blot analysis of HDAC6 in U87 cells treated with siTRPC1 or CV702‐TRPC1 (n = 3 biological replicates). (F‐G): Representative IHC images of HDAC6 in nude mice xenograft tumors (scale bar: 100 μm; n = 6 mice per group). (H‐I): Western blot analysis of LAMP2A in U87 cells treated with siTRPC1 combined with HDAC6 overexpression or siHDAC6 (n = 3 biological replicates). (J): Immunofluorescence colocalization HSC70 and HDAC6 in control, shTRPC1, and CV702‐TRPC1 groups (scale bar: 50 μm; n = 3 biological replicates). Pearson's coefficients: Control = 0.78, shTRPC1 = 0.89, CV702‐TRPC1 = 0.70. (K): Immunofluorescence colocalization of HSC70 and HDAC6 in human glioma samples from grades 2, 3, and 4 (scale bar: 50 μm; n = 5 patients per grade). Pearson's coefficients: Grade 2 = 0.87, grade 3 = 0.72, grade 4 = 0.65. (L‐N): Co‐IP with anti‐HSC70 antibodies assessing HDAC6‐HSC70 interaction and HSC70 acetylation in siTRPC1‐transfected U87 cells (n = 3 biological replicates). Data are presented as mean ± SD (*p < 0.05, **p < 0.01, **p < 0.001).
These results prompted us to speculate whether HDAC6 directly regulates HSC70, the core molecule of CMA, through deacetylation. Therefore, the interaction between HDAC6 and HSC70 was further analyzed. IF analysis of nude mice tumors showed that siTRPC1 enhanced the colocalization HDAC6 and HSC70 (Figure 6J). What's more, it was also found that the colocalization HDAC6 and HSC70 became weaker with the increase of malignancy in human glioma (Figure 6K). To test whether HDAC6 directly regulates HSC70, the interaction of HDAC6 and HSC70 as well as the acetylation level of HSC70 were measured by co‐IP after TRPC1 knockdown. Co‐IP assays in U87 cells showed that TRPC1 knockdown enhanced the interaction between HDAC6 and HSC70 (Figure 6L–N). Therefore, TRPC1 activates CMA via inhibiting HDAC6‐mediated HSC70 deacetylation.
TRPC1‐CMA‐STAT3 Pathway Contributes to Glioma Tumor Progression
3.6
To investigate the role of the TRPC1‐CMA‐STAT3 pathway in glioma tumor progression, we established subcutaneous xenograft models in nude mice using U87 cells with stable knockdown of TRPC1 alone, or in combination with STAT3 or LAMP2A. Specifically, mice were injected with 1 × 10^6^ U87 cells expressing shTRPC1, shTRPC1 + shSTAT3, or shTRPC1 + shLAMP2A. TRPC1 knockdown significantly reduced both tumor size and weight. However, concurrent knockdown of STAT3 or LAMP2A with TRPC1 reversed this effect, resulting in larger and heavier tumors (Figure 7A,B).
*TRPC1‐CMA‐STAT3 pathway is involved in glioma tumor progression. (A‐B): Tumor size changes in nude mice xenograft model (n = 6 mice per group). (C‐D): Western blot analysis of protein levels in tumors from TRPC1 knockdown or overexpression groups (n = 3 representative samples per group). (E): Western blot analysis of protein levels in human glioma tissues (n = 3 representative samples per group). (F‐H): Representative IHC images of TRPC1, LAMP2A, and STAT3 in human glioma tissues (scale bar: 100 μm; n = 5 patients per grade). Data are presented as mean ± SD (*p < 0.05, **p < 0.01, **p < 0.001).
Further analysis of tumor tissues revealed that TRPC1 knockdown decreased the protein levels of TRPC1, STAT3, and Vimentin, while increasing LAMP2A expression (Figure 7C,D). Additionally, WB and IHC analyses of human glioma samples demonstrated that the expression of TRPC1, STAT3, and Vimentin increase with glioma grade, whereas LAMP2A expression decreases (Figure 7E–H). These findings confirm that TRPC1 promotes glioma progression by inhibiting CMA‐dependent STAT3 degradation in vivo.
To determine the effects of TRPC1‐CMA‐STAT3 on tumor progression, nude mice were injected with 1 × 10^6^ inducible TRPC1 knockdown, TRPC1 knockdown STAT3 knockdown or TRPC1 knockdown + LAMP2A knockdown U87 cells in the Cervico dorsal. We found that TRPC1 knockdown decreased the size and weight of tumor, while the STAT3 knockdown or LAMP2A knockdown can eliminate the effect of siTRPC1(Figure 7A,B). Furthermore, we found that the expression levels of TRPC1, STAT3 and Vimentin decreased, while the expression levels of LAMP2A increased in TRPC1 knockdown nude mice tumor (Figure 7C,D). Likewise, WB and IHC were performed to observe protein expression; the results showed that the expression of TRPC1, STAT3 and Vimentin increased with the increase of malignant degree of glioma, while LAMP2A showed the opposite trend (Figure 7E–H). In all, the mechanism of TRPC1 blocking CMA‐dependent STAT3 degradation had been verified again in vivo.
Discussion
4
In this study, we provide compelling evidence that TRPC1‐mediated calcium dysregulation enhances STAT3 protein levels by inhibiting HDAC6‐dependent CMA, a key mechanism driving glioma onset and progression. Our findings demonstrate that both TRPC1 and STAT3 are significantly upregulated in high‐grade gliomas compared to lower‐grade tumors (grade 2). Furthermore, we show that TRPC1 suppresses CMA through the modulation of HDAC6‐mediated HSC70 deacetylation, thereby preventing the degradation of STAT3, which we have identified as a novel CMA substrate. Importantly, inhibition of STAT3 or LAMP2A abrogates TRPC1‐induced glioma progression both in vitro and in vivo, underscoring the therapeutic potential of targeting this pathway. Preliminary experiments in the U251 glioma cell line show similar effects, suggesting broad applicability across glioma models. The proteomic approach in our study was instrumental in uncovering this mechanism. By analyzing global protein changes upon TRPC1 knockdown, we identified STAT3 and HDAC6 as critical nodes dysregulated in the absence of TRPC1. Specifically, the unbiased proteomics data revealed a significant decrease in STAT3 and a concurrent increase in HDAC6 (Figures 2F and 6A), directly pointing to a TRPC1‐HDAC6‐HSC70‐CMA axis affecting STAT3 stability.
TRPC1 has been implicated in various cancers, including pancreatic, breast, and brain tumors [24]. Previous work demonstrated that TRPC1/4/5 channel complexes promote cancer progression [24, 25, 26], and functional TRPC1 inhibition induces multinucleated cell formation in gliomas [10]. Our results found that TRPC1 expression was closely related to the grade of glioma and the grade of glioma was positively associated with poor prognosis(Figure S1). Notably, our results from clinical specimens differ somewhat from database predictions, possibly due to ethnic variations in patient populations. As a non‐selective calcium channel critical for cytoplasmic calcium homeostasis, TRPC1's biological role in glioma was examined. Our results showed that TRPC1 depletion decreased the concentration of intracellular Ca^2+^ in the cytoplasm of tumor cells, while high TRPC1 level was the opposite (Figure 1H). Moreover, TRPC1 knockdown inhibited cell growth and migration in glioma cells and tumor xenografts in nude mice. Thus, we consider that TRPC1 promotes calcium influx, which in turn facilitates the migration of gliomas.
Bioinformatics analysis revealed a potential association between TRPC1 and STAT3 in glioma migration, which was further supported by our findings in human brain tissues showing a strong correlation between TRPC1 and STAT3 expression. Since elevated cytosolic Ca2+ regulates cancer‐promoting signaling pathways [27, 28] and STAT3 is ubiquitously activated in gliomas [14, 29], we investigated this relationship. Interestingly, while we did not observe a direct correlation at the gene expression level, knocking down TRPC1 significantly reduced STAT3 protein levels, indicating post‐transcriptional regulation.
Given that the major proteolytic systems—UPS and ALS—are dysregulated in tumor cells [23, 30], we hypothesized that TRPC1 knockdown enhances STAT3 degradation through these pathways. And our data demonstrated that STAT3 degradation occurs primarily through the ALS pathway. CMA, one of the lysosomal proteolysis pathways of ALS, can selectively degrade substrate proteins via HSC70 recognition of KFERQ‐like motifs and LAMP2A‐mediated lysosomal translocation [29, 31, 32, 33]. We found that knockdown of TRPC1 not only decreased the expression of STAT3, but also increased the expression of LAMP2A, while the higher STAT3 and lower LAMP2A expressions were induced by overexpressing TRPC1. Importantly, we identified that human STAT3 contains five conserved KFERQ‐like motifs, which are well‐ distinguished requirements for a protein to bind to HSC70 and therefore to be a substrate for CMA [32, 33, 34]. In addition, we observed that TRPC1 significantly decreased the amount of STAT3 associated with HSC70 and LAMP2A. Previous reports showed that substrate bound to LAMP2A represents the rate‐limiting step of CMA activity, and variation in abundance of active LAMP2A and translocation of CMA‐active lysosomes can affect CMA activity [32, 35]. After silencing LAMP2A, we found that siTRPC1 induced STAT3 degradation was significantly reversed in glioma cells. These results suggested that STAT3 could be a CMA substrate and decreased degradation by TRPC1 in a dysregulated CMA fashion in glioma.
However, how TRPC1 mediates the decrease of CMA activity and thus reduces the degradation of STAT3 remains unclear. Noteworthy reports showed that lysine acetylation level affects the activity of HSC70, and the deacetylation of HSC70 was mediated by the interaction with HDAC6 [36, 37]. Our proteomics data revealed increased HDAC6 expression following TRPC1 silencing, consistent with previous reports demonstrating HDAC6's role in regulating CMA activity through HSC70 deacetylation in neurodegenerative disease models [38, 39]. Furthermore, we observed that TRPC1 significantly decreased the amount of HDAC6 interaction with HSC70. Besides, the degradation of STAT3 through binding to HSC70 and then directly to CMA was decreased after inhibiting the expression of HDAC6 with WT161. These findings raised the intriguing possibility that TRPC1 facilitates glioma migration by inhibiting HDAC6 and thus reducing the degradation of CMA‐dependent STAT3.
Our data showed that TRPC1 silencing decreased LAMP2A expression, though the specific regulatory mechanism requires further investigation. Additionally, while we demonstrate HDAC6‐mediated HSC70 deacetylation regulates CMA, the precise acetylation sites involved warrant mutational analysis.
In conclusion, we describe a novel mechanism by which TRPC1 inhibits CMA‐dependent STAT3 degradation via HDAC6, providing insights into glioma progression (Figure 8). Silencing TRPC1 enhances HDAC6‐mediated CMA and reduces STAT3‐induced glioma migration. Given that cell migration is critical for tumor proliferation, this mechanism offers new avenues for controlling tumor development. Minor variability between experiments notwithstanding, the consistent trends across multiple approaches support the validity of our findings.
Schematic model illustrating the proposed mechanism.
Our findings carry important therapeutic implications for glioma treatment. Pharmacological targeting of TRPC channels has shown promise in preclinical cancer models. The TRPC inhibitor SKF96365 has demonstrated antitumor effects in various cancer cell lines, including glioblastoma, where it induces cell cycle arrest at the G2/M phase and impairs cytokinesis [21, 40]. Additionally, 2‐aminoethoxydiphenylborane (2‐APB), another TRPC channel blocker, inhibits glioma cell proliferation by disrupting calcium signaling [21]. These findings suggest that TRPC1 inhibition could be a viable therapeutic strategy for glioma patients.
Equally compelling is the potential for targeting HDAC6 in glioma therapy. Selective HDAC6 inhibitors, including ricolinostat (ACY‐1215), have demonstrated anticancer activity in multiple tumor types and are currently being evaluated in clinical trials for breast cancer and hematologic malignancies [41, 42]. Ricolinostat inhibits glioma cell growth through the MKK7/JNK/c‐Jun signaling pathway [43], supporting its therapeutic relevance in brain tumors. Furthermore, WT161, another HDAC6‐selective inhibitor, has shown potent anti‐tumor activity in preclinical models [44]. Given our finding that HDAC6 activation promotes CMA‐dependent STAT3 degradation, HDAC6 activators—or alternatively, compounds that enhance the HDAC6‐HSC70 interaction—may represent a novel therapeutic approach specifically for gliomas with elevated TRPC1/STAT3 expression.
Importantly, targeting the CMA pathway directly also offers therapeutic potential. Approaches that enhance LAMP2A expression or HSC70 chaperone activity could promote STAT3 degradation and inhibit glioma progression [19]. Combinatorial strategies targeting multiple nodes of the TRPC1‐HDAC6‐CMA‐STAT3 axis may provide synergistic anti‐tumor effects while minimizing resistance development [45]. Future studies should evaluate these therapeutic strategies in patient‐derived glioma models and explore biomarkers that predict sensitivity to TRPC1 or HDAC6‐targeted therapies.
Author Contributions
Jialong Chen: writing – original draft (equal). Yixi Lai: writing – review and editing (equal). Mingque Li: conceptualization (equal), methodology (equal), writing – original draft (equal). ZiWei Cai: validation (equal). Renjian Lu: validation (equal). Linhua Liu: software (equal). Yongming Peng: validation (equal). Chunlai Fu: funding acquisition (equal). Zhefan Xie: visualization (equal). Xueqion Zhou: visualization (equal). Jiaxian Liu: software (equal). He Zhang: writing – review and editing (equal).
Funding
This work was supported by the National Natural Science Foundation of China (82103879), Guangdong Basic and Applied Basic Research Foundation (2021B1515140032 2022A1515110272 2022A1515140173 2023A1515140164 2024A1515140191), Guangdong Medical University Clinical + Basic Medical Science and Technology Innovation Special Program (GDMULCJC2024152 GDMULCJC2024153 GDMULCJC2024140), Dongguan Social Development Science and Technology (Key) Project (20211800905332), Discipline Construction Project of Guangdong Medical University (4SG21021G), Science Foundation of traditional Chinese medicine administration of Guangdong Province (20222104).
Ethics Statement
This study was approved by the ethics committee of Guangdong Medical University. This study had received approval of the research protocol by an Institutional Reviewer Board, Informed Consent and Animal Studies.
Consent
All authors have approved the contents of this manuscript and provided consent for publication.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Figure S1: jcmm71062‐sup‐0001‐FigureS1.tif.
Figure S2: jcmm71062‐sup‐0002‐FigureS2.tif.
Figure S3: jcmm71062‐sup‐0003‐FigureS3.tif.
Figure S4: jcmm71062‐sup‐0004‐FigureS4.tif.
Table S1: Nucleotide sequence of siTRPC1、siLamp2A and siSTAT3.
Table S2: Demographic data of the patients.
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