MAGI3 inhibits renal clear cell carcinoma progression through the JAK-STAT3 pathway

Abstract

Background

Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer subtype. While localized disease is treated surgically, therapeutic options for advanced cases remain limited. This highlights an urgent need for reliable prognostic markers and novel therapeutic targets. Therefore, this study aimed to clarify the clinical significance and functional role of MAGI3 in ccRCC.

Methods

We analyzed MAGI3 expression in ccRCC and normal tissues using public datasets and clinical samples. Its correlation with clinicopathological features and patient survival was evaluated. The biological role of MAGI3 and its underlying mechanism were investigated through in vitro and in vivo functional assays.

Results

MAGI3 expression was significantly downregulated in tumor tissues compared with adjacent normal kidney specimens. Lower MAGI3 levels correlated positively with advanced tumor stage, higher Fuhrman nuclear grade, lymph node metastasis, increased infiltration of immunosuppressive cell populations, and poorer overall patient prognosis. Functional experiments further demonstrated that MAGI3 overexpression effectively suppressed ccRCC cell proliferation, migration, and invasion in vitro and in vivo by inhibiting STAT3 signaling phosphorylation and downstream transcriptional activity.

Conclusions

Our study identifies MAGI3 as a novel tumor suppressor in ccRCC that constrains cancer progression via the STAT3 pathway. These results firmly establish MAGI3 as a potential prognostic biomarker for ccRCC.

Highlight box.

Key findings

• MAGI3 is a novel tumor suppressor in clear cell renal cell carcinoma (ccRCC). Its expression is significantly downregulated in tumor tissues, and lower levels correlate with advanced tumor stage, lymph node metastasis, and poorer patient survival. Functionally, overexpression of MAGI3 inhibits ccRCC cell proliferation, migration, and invasion by suppressing the STAT3 signaling pathway.

What is known and what is new?

• Therapeutic options for advanced ccRCC remain limited, highlighting the need for reliable prognostic markers and novel targets.

• This study newly identifies MAGI3 as a key tumor suppressor in ccRCC. It demonstrates, for the first time, that low MAGI3 expression correlates with adverse clinicopathological features and prognosis, and elucidates its functional mechanism via the STAT3 pathway.

What is the implication, and what should change now?

• These findings position MAGI3 as a potential prognostic biomarker and the MAGI3-STAT3 axis as a promising therapeutic target for ccRCC. Future work should validate MAGI3’s prognostic value in larger independent cohorts and initiate preclinical studies targeting this pathway to advance toward clinical application.

Introduction

Renal cell carcinoma (RCC) ranks among the most prevalent malignancies affecting the urinary system. Recent years have witnessed a consistent annual rise in its incidence, comprising 3–5% of adult malignancies (1). Clear cell renal cell carcinoma (ccRCC) stands as the most common and aggressive pathological type, encompassing approximately 80% of RCCs (2,3). While surgery offers the mainstay of treatment for early-stage renal cancer, a substantial proportion of patients develop local recurrence or distant metastases post-operatively (4,5). Approximately 1/3 of patients present with advanced kidney cancer or metastasis. With advanced kidney cancer, the prognosis is unfavorable, with a 5-year survival rate below 11.2% (6). Delving into the molecular underpinnings of RCC occurrence and progression holds immense promise for uncovering novel therapeutic targets and establishing reliable markers to predict the efficacy and prognosis of kidney cancers.

MAGI3 (membrane-associated guanylate kinase, WW and PDZ domain containing 3) is a gene encoded by the human MAGI3 gene and belongs to the PDZ protein family (7). In most contexts, MAGI3 functions as a tumor suppressor. Upregulation of MAGI3 inhibits tumor growth, tumor metastasis, or enhances tumor cell chemoresistance, including glioma (8), cervical cancer (9) and colorectal cancer (10). For instance, it has been shown that MAGI3 inhibits the Wnt/β-catenin pathway by reducing β-catenin levels, thereby impeding the migration and invasion of cervical cancer cells (11). Additionally, MAGI3 degrades c-myc enzymes to improve the sensitivity of colorectal cancer to chemotherapeutic agents and enhance prognosis (10). In a minority of cases, MAGI3 has been reported to exert tumor-promoting effects. In breast cancer, polyadenylation of MAGI3 generates a truncated isoform that lacks full-length tumor-suppressive activity and exerts a dominant-negative effect, thereby relieving inhibition of YAP signaling and promoting oncogenic transformation (12). However, whether MAGI3 has an effect on the progression and invasion of RCC has not been studied.

In this study, we initially evaluated the expression of MAGI3 in a spectrum of prevalent malignancies and its correlation with patient prognosis using The Cancer Genome Atlas (TCGA). We confirmed that the levels of MAGI3 in kidney renal clear cell carcinoma (KIRC) tissues were significantly lower than those in normal and paraneoplastic tissues, thus further investigating the relationship between MAGI3 expression, invasion, prognosis, and molecular pathways in KIRC. Additionally, we investigated the potential association between MAGI3 expression and the tumor immune microenvironment. Finally, we observed the effect of MAGI3 overexpression on apoptosis and proliferation of renal clear cell carcinoma cells. Our results suggest that MAGI3 has an inhibitory effect on KIRC progression, emerging as a potential prognostic biomarker for assessing KIRC progression and prognosis. We present this article in accordance with the MDAR and ARRIVE reporting checklists (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0030/rc).

Methods

Data processing and screening for differentially expressed genes (DEGs)

RNA sequencing, somatic mutational data, single nucleotide polymorphisms (SNP), and related clinical data of 33 types of cancer were downloaded from TCGA KIRC (13) using University of California, Santa Cruz (UCSC) Xena (https://xena.ucsc.edu/). Fragments per kilobase million (FPKM) values were transformed into transcripts per kilobase million (TPM) values. Data from each tumor cell line was downloaded from the CCLE database (https://portals.broadinstitute.org/ccle/). The protein expression matrix was collected from Clinical Proteomic Tumor Analysis Consortium (CPTAC) (https://proteomics.cancer.gov/programs/cptac). Expression data from human tumor tissue and normal tissue were analyzed using the webserver GEPIA2 (http://gepia2.cancer-pku.cn/#index). The analysis of protein expression levels of MAGI3 in KIRC was performed by University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) database (https://ualcan.path.uab.edu/). The limma R package was used to screen for DEGs in the TCGA KIRC cohort, in which genes with P value <0.01 and |log₂ fold change (FC)| >1.5 were considered DEGs.

Analysis of the relationships between MAGI3, prognosis, and clinical phenotype

Survival and clinical phenotype data were obtained for each sample downloaded from TCGA KIRC. Two endpoints—overall survival (OS) and progression-free interval (PFI)—were selected to evaluate the association between MAGI3 expression and patient prognosis. A total of 528 patients with available survival data were included in the OS analysis, and 526 patients with PFI data were included in the PFI analysis. The Kaplan-Meier method and log-rank test (P<0.05) were applied for survival analysis in each cancer type. Survival curves were generated using the R package “survival”. Additionally, two clinical phenotypes—tumor stage and tumor grade—were selected to explore their relationship with MAGI3 expression.

Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs and gene set enrichment analysis (GSEA)

The Database for Annotation, Visualization, and Integrated Discovery (DAVID) (version 6.8) furnishes a comprehensive array of functional annotation tools, enabling investigators to discern the biological significance underlying an extensive gene inventory. The KEGG pathway of DEGs was analyzed and visualized by the clusterProfile R package. TCGA-KIRC patients were stratified into high- and low-MAGI3 phenotypes. GSEA based on KEGG was carried out using the ClusterProfiler R package.

Cell cultures

The human RCC cell lines Caki-1 and 786-O, obtained from the American Type Culture Collection (ATCC), were cultured at 37 ℃ in a humidified incubator with 5% CO₂. Caki-1 and 786-O cells were maintained in DMEM (Gibco, Grand Island, NY, USA; 31966021) and RPMI-1640 (Gibco, 61870010) media, respectively. Both media were supplemented with 10% fetal bovine serum (Biowest, Nuaillé, France; S1810-500) and 1% penicillin/streptomycin (Bioconcept, Allschwil, Switzerland; 4-01F00-H).

Cell transfection

The entire cDNA sequence of MAGI3 or STAT3 was prepared synthetically and incorporated into the pLVX-Puro lentiviral vector (sourced from GENERAY, Shanghai, China). Lentiviruses, designed to induce overexpression of MAGI3 or STAT3, were generated by simultaneously introducing the pLVX-MAGI3 construct and two assisting vectors, psPAX2 and pMD2G, into 293T cells, using PEI as the transfection medium (obtained from Roche, Switzerland). The virus was collected after 48 and 72 hours of transfection. To establish cell lines consistently overexpressing MAGI3 or STAT3, cells were subjected to puromycin (from Sigma-Aldrich, Missouri, USA) at 2 µg/mL for 1–2 weeks after the initial 24 hours of infection.

Cell Counting Kit-8 (CCK-8) assay

Cell viability of KIRC cells was determined with the CCK-8 (MedChemExpress, Monmouth Junction, NJ, USA) as per the manufacturer’s protocol. Cells were plated at 1,000 cells per well in a 96-well plate. At each designated time point, we added 10 µL of CCK-8 solution and measured the absorbance at 450 nm using a microplate reader.

Colony formation assay

A total of 1,000 cells were seeded onto 6 cm plates and allowed to proliferate for a duration of 7 days. Subsequently, we then dyed the colonies with crystal violet staining solution (Sangon Biotech, Shanghai, China) after fixing them with 4% paraformaldehyde for 21 days. The enumeration of colonies was then undertaken.

Flow cytometric analysis

Apoptosis was evaluated using an Annexin V-APC/7-AAD staining kit (BD Biosciences, San Jose, CA, USA) according to the manufacturer’s instructions. In brief, cells treated with respective agents for 48 hours were harvested and resuspended in 500 µL of binding buffer containing Annexin V-APC and 7-AAD. After incubation, the samples were analyzed on a Beckman Gallios flow cytometer, and the percentage of apoptotic cells was determined using FlowJo software.

Tumorigenesis assay in vivo

Six-week-old male BALB/c athymic nude mice (purchased from Risemice Biotechnology Co., Ltd., Guangdong, China) were housed under pathogen-free conditions. The mice were randomly divided into two groups (n=3 per group). Each mouse was subcutaneously inoculated in the right flank with 1×10⁶ Caki-1 cells (suspended in 200 µL PBS) stably transfected with either OE-MAGI3 or the empty vector control (OE-NC). Tumor growth was monitored weekly, and tumor volume was calculated using the formula: (length × width²)/2. At the end of the experiment, the mice were euthanized by cervical dislocation. Subsequently, the tumors were excised, photographed, and weighed. All animal experiments were performed under a project license (No. Rise-Mice-202301010001, approval date: January 1, 2023) granted by Ethics Committee of Affiliated Cancer Hospital and Institute of Guangzhou Medical University, in compliance with the NIH Guide for the Care and Use of Laboratory Animals.

Transwell assay

Cell migration was assessed using a 24-well Transwell chamber (Corning, Corning, NY, USA). Briefly, 30,000 KIRC cells were seeded into the upper chamber in serum-free medium. After 24 hours of incubation at 37 ℃, the non-migrated cells on the upper surface of the membrane were carefully removed by wiping with a cotton swab. The migrated cells on the lower surface were fixed with 4% paraformaldehyde for 10 minutes, stained with 0.1% crystal violet (Sangon Biotech) for 5 minutes, and then imaged. The number of migrated cells was counted from the captured images.

Wound-healing assay

A wound healing assay was performed to assess cell migration. Briefly, a confluent monolayer of cells in 6-well plates was scratched using a sterile 10 µL pipette tip to create a wound. The wound areas were photographed at 0, 24, and 48 hours post-scratching. The width of the wounds was measured using image analysis software (or a caliper tool). The percentage of wound closure was calculated as: [1 − (wound area at Tx/wound area at T0)] × 100%.

Western blot

Proteins were extracted using a lysis buffer, and their concentrations were determined via a BCA assay. Subsequently, 20 µg of protein underwent separation through sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), followed by transfer onto a polyvinylidene difluoride membrane (PVDF). Afterward, the membranes were immersed in TBS (150 mM NaCl, 20 mM Tris, pH 7.5, 0.05% Tween-20) containing 5% milk, undergoing a one-hour blocking step and a 1.5-hour incubation with specific antibodies at room temperature prior to detection. Immunoreactive proteins were visualized using an enhanced chemiluminescence system (Merck Millipore, Billerica, MA, USA).

The employed antibodies are as follows: STAT3 (ab119352, Abcam, Cambridge, UK), p-STAT3 (ab76315, Abcam), Ubiquitin (sc-53509, Santa Cruz Biotechnology, Dallas, TX, USA) and (3933, CST, Danvers, MA, USA), MAGI3 (sc-136471, Santa Cruz Biotechnology, Dallas, TX, USA), glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (ab76315, Abcam), and β-actin (ab8245, Abcam).

For secondary detection, the following antibodies were used: Peroxidase-Conjugated Goat Anti-Mouse IgG (H+L) (33201ES60, Yeasen, Shanghai, China), Peroxidase-Conjugated Rabbit Anti-Goat IgG (H+L) (33701ES60, Yeasen), PKCα (1:1,000, ab32376, Abcam), Bax (1:1,000, ab182734, Abcam), Mcl-1 (1:1,000, ab32087, Abcam), Bcl2 (1:1,000, ab59348, Abcam), c-Myc (1:1,000, ab32072, Abcam), MMP2 (1:1,000, ab92536, Abcam), MMP9 (1:1,000, ab76003, Abcam), Twist1 (1:50, ab50887, Abcam).

Immunofluorescence staining

The culture medium, which had been washed with phosphate-buffered saline (PBS), was aspirated, and the cultured cells were fixed with 4% paraformaldehyde for a duration of 30 minutes. Subsequently, the specimens underwent permeabilization with 0.5% Triton X-100 in PBS for 10 minutes, followed by blocking with 1% bovine serum albumin (BSA) in PBS at room temperature for 1 hour. Following this, the cells were subjected to an overnight incubation at 4 ℃ with primary antibodies, including STAT3 (ab119352, Abcam) and MAGI3 (NBP2-17210, Novus, Centennial, CO, USA).

Following three washes with PBS, the cells were incubated at room temperature for 1 hour with secondary antibodies: Goat anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 488 (A-11034, Thermo Fisher Scientific, Waltham, MA, USA), and Goat anti-Mouse IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 568 (A-11031, Thermo Fisher Scientific).

Ultimately, cell nuclei were rendered visible through staining with 4’,6-diamidine-2-phenylindole dihydrochloride (DAPI) (D3571, Thermo Fisher Scientific) for a duration of 10 minutes.

Kidney tissues underwent immunofluorescence staining using an optimized protocol adapted from established cell culture methods. Tissue sections were mounted, fixed (4% paraformaldehyde), and washed (PBS) to ensure antigen preservation. Permeabilization and blocking steps followed to optimize antibody penetration and specificity. Primary kidney antigen-specific antibodies were incubated overnight (4 ℃). After washes, fluorescent secondary antibodies were applied, followed by DAPI nuclear staining. This optimized protocol enabled precise visualization and localization of target antigens within the kidney sections.

Coimmunoprecipitation (CoIP)

For immunoprecipitation assays, cells were harvested and lysed in a buffer containing 10 mM Hepes, 1% deoxycholate, 5 mM ethylenediaminetetraacetic acid (EDTA), 1 mM benzamidine, and 1% Triton X-100, supplemented with protease inhibitors. The lysates were cleared by centrifugation and then incubated with 2 µL of the target antibody and Protein A/G-agarose beads for 2 hours at 4 ℃. The beads were subsequently washed three times with 1 mL of ice-cold PBS. Finally, the immunoprecipitated proteins were eluted by resuspending the beads in SDS-PAGE sample buffer, followed by detection via standard immunoblotting.

Immunostaining

Kidney tissues (normal and tumor) were dissected, fixed in 4% PFA at 4 ℃ overnight, and cryoprotected in 10% and 30% sucrose (48 hours each). After OCT embedding and sectioning (8 µm), tissue slides were post-fixed, permeabilized with 0.5% Triton X-100, and blocked with 5% fetal bovine serum (FBS)/3% BSA. Primary antibodies were applied overnight at 4 ℃, followed by fluorescent secondary antibody staining for 2 hours at RT.

For cultured Caki-1 and 786-O cells, fixation was done with 4% PFA. Cells were then washed with IF Wash Buffer and blocked in IF Blocking Buffer (containing 10% FBS) for 30 minutes. Immunostaining was performed by sequential incubation with primary antibodies (overnight, 4 ℃) and secondary antibodies (2 hours, RT), with thorough washing between steps, prior to mounting.

Quantitative real-time polymerase chain reaction RT-qPCR

Total RNA extraction was performed using TRIzol reagent (Thermo Fisher Scientific) following manufacturer’s stipulated protocols. Subsequently, cDNA synthesis was achieved using primeScript^TM RT reagent Kit with gDNA Eraser (RR047B, Takara, Dalian, China). The RNA levels were quantified using SYBR Green qPCR Mix (RR820B, Takara). Data normalization to GAPDH and calculations were executed employing the ΔΔCt method. The primer sequences were available in Table S1.

Chromatin immunoprecipitation (ChIP)-qPCR analysis

We used UCSC Genome Browser to search for the genomic sequence of MCL1 (ENST00000369026.3) and MMP2 (ENST00000219070.9) and the sequence between 2,000 bp upstream and 100 bp downstream of the transcription start site (TSS) of the gene was identified as the target sequence. Then we used Primer Premier 5 to design primers for every 300 bp of the target sequence. When we designed the primers, we set the PCR product size to 100–150 bp and others to the default. After that, the tool generated a list of potential primer pairs. We selected the primer pairs that meet our desired criteria for efficiency and specificity based on rating from high to low. Finally, we used the BLAST tool to search for potential off-target amplification to ensure that the primers are specific to the target sequence and do not amplify unintended regions. control group and various treated groups of Caki-1 cells (2×10⁷) underwent crosslinking, lysis, and shearing using a UCD-300 (Diagenode, Liège, Belgium) instrument, resulting in fragment lengths of approximately 200 to 700 base pairs. Subsequently, ChIP was executed employing an EZ ChIP kit (Millipore; 17–371) as per the manufacturer’s guidelines. The ChIP-enriched DNA was quantified through reverse transcription quantitative polymerase chain reaction (RT-qPCR). The primer sequences can be found in Table S1.

Human specimen analysis

Specimens were acquired from 3 patients [1 male (66 years old), 2 females (64 and 68 years old)] with kidney cancer: renal cancer tissues and paracancerous tissues, sourced post-surgical resection from patients diagnosed with renal clear cell carcinoma at Shenzhen Hospital, Southern Medical University, Shenzhen, China. The date range of specimen collection was June 1, 2020 to October 1, 2020. Notably, these patients underwent surgery without prior chemotherapy or radiotherapy. Subsequently, pathology sections were procured from the Department of Pathology for double immunofluorescence staining. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Shenzhen Hospital, Southern Medical University (No. NYSZYYEC20190018, approval date: December 9, 2019), and written informed consent was obtained from all patients.

Statistical analysis

Statistical analysis was performed by R (version 4.0.1). Comparison between groups was undertaken employing either Wilcoxon rank-sum test or the Kruskal-Wallis test followed by Dunn’s post hoc test. Spearman correlation analysis was employed for assessing correlations. Kaplan-Meier curves and the log-rank test were utilized to compare the OS between MAGI3 expression levels. P value <0.05 was set as the threshold.

Results

MAGI3 NR1B2 is downregulated in KIRC and correlates with poor survival

To investigate the roles of MAGI3 in KIRC pathogenesis, we firstly detected and analyzed MAGI3 expression in the in GAPIA2 databases across different cancers. Compared with normal tissues, MAGI3 was down-regulated in KIRC, kidney renal papillary cell carcinoma (KIRP), which suggested that MAGI3 might play a tumor suppressor role in the progression or development of urologic cancer (Figure 1A).

Figure 1.

MAGI3 expression profiles in human cancers and its association with KIRC prognosis. (A) Comparisons of MAGI3 expression levels between tumor tissues from the TCGA database and normal tissues from the GTEx database. (B) MAGI3 expression was detected in clear cell renal cell carcinoma and normal tissues using data from the CPTAC dataset. (C) Expression of MAGI3 in KIRC patients with different tumor grades. (D) Expression of MAGI3 in KIRC patients with different nodal metastasis status. (B-D) Data were analyzed using a t-test for 2 groups and Kruskal-Wallis test with multiple comparison. (E) Kaplan-Meier analysis of the association between MAGI3 expression and OS in TCGA-KIRC cohort. (F) Kaplan-Meier analysis of the association between MAGI3 expression and PFI in TCGA-KIRC cohort. T represents the tumor tissue and N represents the normal tissue. CI, confidence interval; CPTAC, Clinical Proteomic Tumor Analysis Consortium; HR, hazard ratio; KIRC, kidney renal clear cell carcinoma; OS, overall survival; PFI, progression-free interval; TCGA, The Tumor Genome Atlas; TPM, transcripts per kilobase million.

To scrutinize the clinical relevance of MAGI3 in KIRC, we examined the correlations of its expression with tumor grade and node metastasis. Evaluation of MAGI3 protein expression in KIRC was performed using the UALCAN database, revealing diminished expression levels in tumor tissues (Figure 1B). Furthermore, subsequent analysis indicated that reduced MAGI3 expression was associated with higher tumor grade (Figure 1C) and lymph node metastasis (Figure 1D) status in TCGA-KIRC patients. To further investigate the prognostic value of MAGI3 in KIRC, we analyzed RNA-seq and clinical data from the TCGA database (obtained via UCSC Xena). Patients in the TCGA-KIRC cohort were stratified into high- and low-expression groups based on the median MAGI3 expression level. The analysis demonstrated that patients with low MAGI3 expression had significantly worse OS and PFI than those in the high-expression group (Figure 1E,1F). Collectively, these data identify MAGI3 as a potential protective factor, as its expression was inversely correlated with tumor grade, stage, lymph node metastasis, and poor prognosis.

Overexpression of MAGI3 inhibits the growth and metastasis of kidney cancer cells both in vitro and in vivo

To comprehensively investigate the biological role of MAGI3 in renal cancer cells, we first examined MAGI3 expression in four kidney-associated cell lines, including two renal cancer cell lines, Caki-1 and 786-O, and two normal renal cell lines, HA1E and HEK-TE (Figure 2A,2B). MAGI3 expression was markedly lower in renal cancer cell lines than in normal renal cell lines (Figure S1A). To further determine the functional significance of MAGI3 in KIRC cells, Caki-1 and 786-O cells were selected for MAGI3 overexpression experiments, and the overexpression efficiency was confirmed (Figure 2C,2D, Figure S1B).

Figure 2.

MAGI3 inhibits the proliferation and tumorigenesis in kidney cancer cells. (A) The two renal cancer cell lines (Caki-1 and 786-O) with low expression levels of MAGI3. (B) MAGI3 protein levels were detected by western blot in four kidney cancer cell lines. (C) The RNA and protein (D) expression of MAGI3 in two types of kidney cancer cells. (E) In vitro growth of control and OE-MAGI3 in Caki-1 and 786-O cells as assessed by Cell Counting Kit-8 assay. (F,G) We evaluated the clone formation assay in renal cancer cells after overexpressing MAGI3. (H,I) Apoptosis assay suggested that the apoptosis rate of kidney cancer cells was significantly increased after overexpression of MAGI3. (J) Microscopic image of tumor size after mice were sacrificed. Tumor volume (K) and weight (L). n=6. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. GAPDH, glyceraldehyde-3-phosphate dehydrogenase; OE-NC, empty vector control; TPM, transcripts per kilobase million.

As shown in Figure 2E, the CCK-8 assay demonstrated that MAGI3 overexpression significantly inhibited the proliferation of Caki-1 and 786-O cells. This finding was further supported by the colony formation assay, which showed a reduced clonogenic capacity in MAGI3-overexpressing cells (Figure 2F,2G). In addition, Annexin V staining revealed that MAGI3 overexpression markedly increased apoptosis in KIRC cells (Figure 2H,2I).

To evaluate the effect of MAGI3 on renal cancer growth in vivo, we established a xenograft mouse model using Caki-1 cells with or without MAGI3 overexpression. Tumor volumes were measured on days 7, 14, and 21 after subcutaneous injection (Figure 2J,2K). Compared with the control group, mice injected with MAGI3-overexpressing cells developed significantly smaller tumors, as reflected by reduced tumor volume and tumor weight (Figure 2J-2L).

We next investigated whether MAGI3 affects the migratory and invasive abilities of RCC cells. Consistent with its tumor-suppressive function, MAGI3 overexpression significantly impaired the migration and invasion of Caki-1 and 786-O cells, as demonstrated by wound-healing and Transwell assays (Figure 3A-3C). Taken together, these results indicate that MAGI3 suppresses renal cancer cell proliferation, promotes apoptosis, inhibits migration and invasion, and restrains tumor growth in vivo.

Figure 3.

MAGI3 inhibits the metastasis and invasion of kidney cancer cells. (A,B) Representative light microscope images of Caki-1 and 786-O wound healing assays, used for evaluating migration rates at 24 and 48 h after OE-NC, OE-MAGI3-exposure. Scale bars: 500 μm. (C) The invasion of Caki-1 and 786-O were examined by transwell assay after OE-NC, OE-MAGI3-exposure. Scale bars: 200 μm. *, P<0.05; **, P<0.01; ***, P<0.001. OE-NC, empty vector control.

MAGI3 expression in KIRC is associated with alterations in immune-related pathways

To investigate the biological role of MAGI3 in KIRC, patients were stratified into high- and low-expression groups based on the median expression level. Using the limma package for differential expression analysis, we identified 3,991 DEGs between the low- and high-MAGI3 groups, with 198 upregulated and 3,793 downregulated genes (P value <0.01 and |log₂FC| >1.5; Figure 4A). KEGG pathway analysis indicated that the upregulated DEGs were significantly enriched in immune-related processes, including the PD-L1/PD-1 checkpoint pathway in cancer, IL-17 signaling pathway, and nuclear factor kappa-B (NF-κB) signaling pathway, among others (Figure 4B). Conversely, the downregulated DEGs were associated with pathways such as the Toll-like receptor signaling pathway, B cell receptor signaling pathway, and apoptosis (Figure 4C). These results suggest a strong link between MAGI3 expression and immune cell-related activities, particularly those involving B cells and T cells, as well as immune factor signaling. GSEA further corroborated these findings, showing significant enrichment in pathways including apoptosis, B and T cell receptor signaling, and leukocyte transendothelial migration (Figure 4D). In contrast, immune processes such as allograft rejection were not significantly enriched (Figure 4E). Overall, this integrative analysis underscores the potential role of MAGI3 in modulating immune-related pathways in KIRC, with notable involvement in both adaptive and innate immune signaling mechanisms.

Figure 4.

Functional enrichment analysis of DEGs. (A) Heat map of differentially expressed genes in MAGI3 low and high expression group of TCGA-KIRC cohort. Red represents up-regulated expression, blue represents down-regulated expression. (B) KEGG pathway enrichment analysis of upregulated DEGs and (C) downregulated DEGs. (D,E) GSEA results of immune-related pathways in the ranked gene dataset. DEG, differentially expressed gene; ES, enrichment score; GSEA, gene set enrichment analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes; KIRC, kidney renal clear cell carcinoma; NP, nominal P value; TCGA, The Tumor Genome Atlas.

MAGI3 modulates STAT3 degradation through ubiquitylation

To identify the underlying mechanisms of transcriptional dysregulation in MAGI3 low-expression KIRC, we performed upstream transcription factor prediction using the promoter sequences of the DEGs. As shown in Figure 5A, STAT3 was identified as a potential upstream regulator enriched among the up-regulated genes in MAGI3 low-expression KIRC.

Figure 5.

MAGI3 modulates STAT3 degradation through the ubiquitin pathway. (A) The promoter sequences of the differentially expressed genes. (B) qPCR analysis of overexpression as well as knockdown of MAGI3 in Caki-1 or 786-O cells was performed to analyse the levels of MAGI3 as well as STAT3 mRNA expression. (C) Overexpression of MAGI3 decreased, whereas knockdown of MAGI3 increased the protein levels of STAT3. STAT3 protein levels were detected by western blot in Caki-1 or 786-O cells overexpressed MAGI3 (left), and in Caki-1 or 786-O cells silenced MAGI3 (right). (D) MAGI3 manipulated ubiquitination assays of STAT3 in lysates from Caki-1 cell. Three independent experiments, data were presented as the mean ± standard deviation, unpaired t-test was used to determine statistical significance. ****, P<0.0001; ns, no significance. OE-NC, empty vector control.

To explore whether MAGI3 regulates STAT3 at the transcriptional level in RCC cells, we examined the mRNA levels of STAT3 in both Caki-1 and 786-O cell lines. Although STAT3 protein expression was markedly decreased after MAGI3 overexpression, no apparent change was observed at the mRNA level (Figure 5B), thereby excluding the possibility that MAGI3 regulates STAT3 through transcriptional regulation or mRNA stability.

Subsequent experiments revealed that MAGI3 possesses the capability to regulate STAT3 expression. Overexpression of MAGI3 in Caki-1 or 786-O cells led to a notable reduction in STAT3 and phosphorylated STAT3 (p-STAT3) protein levels, whereas the knockdown of MAGI3 significantly increased STAT3/p-STAT3 protein levels in Caki-1 or 786-O cells (Figure 5C, Figure S2).

Furthermore, to validate whether MAGI3 modulates STAT3 through protein posttranslational modifications, we examined the ubiquitination of STAT3 after MAGI3 overexpression. As shown in Figure 5D, enhanced ubiquitination was observed concomitant with MAGI3 manipulation, and a reduction in STAT3 protein levels was evident in Caki-1 cells overexpressing MAGI3. Collectively, these findings underscore the significance of the MAGI3/STAT3 interaction, elucidating its pivotal role in the MAGI3-mediated upregulation of STAT3 ubiquitination and subsequent degradation.

MAGI3 suppresses renal cancer growth and invasion by regulating STAT3 protein levels

To elucidate whether MAGI3 inhibits renal cancer growth through the modulation of STAT3 stability, we performed several overexpression experiments in two renal cancer cell lines. The cells were divided into four groups: control, STAT3 overexpression alone (pcDNA + STAT3), MAGI3 overexpression alone (MAGI3 + vector), and co-overexpression of both MAGI3 and STAT3 (MAGI3 + STAT3). To evaluate cell proliferation under different conditions, the viability of renal cancer cells was assessed using the CCK-8 assay. The results showed that MAGI3 overexpression suppressed renal cancer cell viability, whereas STAT3 overexpression promoted it (Figure 6A). Importantly, the anti-proliferative effect of MAGI3 was effectively reversed by concurrent STAT3 overexpression, suggesting that MAGI3 modulates cell viability through a STAT3-dependent mechanism.

Figure 6.

MAGI3 inhibited renal cancer growth by mediating STAT3 in vitro. (A) MAGI3 had less effect on the kidney cancer cells proliferation when STAT3 protein levels were overexpressed. Cell viability of Caki-1 and 786-O cells by CCK-8 assay. **, P<0.01, ***, P<0.001 vs. pcDNA3.0 + Vector; ^##, P<0.01, ^###, P<0.001 vs. MAGI3 + Vector. (B,C) STAT3 effectively restricted MAGI3-inhibition of transwell assay in renal cancer cells. (D) In normal or tumor tissue, MAGI3 and STAT3 were inversely related to each other. **, P<0.01; ***, P<0.001; ns, not significant. CCK-8, Cell Counting Kit-8.

We next examined whether this regulatory axis also influences invasive behavior. Transwell assays revealed that MAGI3 overexpression significantly attenuated the invasive capacity of renal cancer cells, and this suppression was similarly rescued by STAT3 co-expression (Figure 6B,6C).

To further investigate the relationship between MAGI3 and STAT3 in clinical contexts, we performed double immunofluorescence staining to determine their subcellular localization in paired paracancerous and kidney cancer tissues. An inverse correlation between STAT3 and MAGI3 expression is readily apparent. High levels of MAGI3 are observed in normal tissues, whereas tumor tissues display a marked loss of MAGI3 accompanied by a dramatic upregulation of STAT3 (Figure 6D).

MAGI3 suppresses the transcriptional output of STAT3 by downregulating its expression

Real-Time RNA validation was conducted to assess the expression of genes associated with apoptosis, proliferation, and tumor stemness in both the control and MAGI3 overexpression groups. We further analyzed the expression levels of several common oncogenes (PRKCA, MCL1, BCL2, MYC, MMP2, MMP9) and a tumor suppressor gene (Bax) associated with RCC. As shown in Figure 7A,7B, compared with the control group, the MAGI3 overexpression group exhibited significantly downregulated expression of the pro-tumor proliferation genes (PRKCA, MCL1) and the pro-tumor invasion and metastasis genes (MMP2, MMP9) (Figure 7A,7B). Western Blot analysis was conducted and quantified (Figure 7C), further confirming these findings at the protein level. To delve deeper into the mechanism by which MAGI3 regulates downstream genes, we investigated whether MAGI3 affects the transcription of these genes by modulating the degradation of STAT3 through ChIP. The results demonstrated that, compared to the group with overexpressed MAGI3, when cell lysates were subjected to immunoprecipitation with P-STAT3 antibody in the control group, a significant increase in the transcription of MCL1 and MMP2 genes was observed (Figure 7D,7E).

Figure 7.

MAGI3 suppresses the expression of tumor-associated genes by attenuating STAT3-mediated transcriptional activity. (A,B) RT-qPCR analysis of PRKCA, BAX, MCL1, BCL2, MYC, MMP2 and MMP9 expression. (C) Western blot analysis of PRKCA, BAX, MCL1, BCL2, MYC, MMP2 and MMP9 (GAPDH serves as the control). (D) ChIP-qPCR analysis of MAGI3 enrichment in the MCL1 and MMP2. (E) Gene promoters in control and differentially treated groups of renal cancer cells. *, P<0.05; **, P<0.01; ***, P<0.001. ChIP, chromatin immunoprecipitation; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; RT-qPCR, reverse transcription quantitative polymerase chain reaction; TSS, transcription start site.

Discussion

The dismal prognosis of malignant tumors is predominantly manifested by their pronounced aggressive and metastatic characteristics (14), and the etiology of metastatic and aggressive tumors remains inconclusive. Furthermore, there is a lack of definitive tumor markers for predicting the prognosis of patients with RCC (15). In this study, MAGI3 was identified as exerting an inhibitory role in the onset, metastasis and invasion of RCC.

MAGI3 is a protease encoded by the human MAGI3 gene (7,16), serving as a negative regulator of cell membrane receptors. It encompasses five PDZ domains capable of binding to target proteins through the PBM, thereby forming macromolecular complexes that govern the function of target proteins and their associated signaling pathways (9). Through interactions with a diverse array of molecules both inside and outside the cell, MAGI3 participates in various biological processes. Prior studies have unveiled that diminished levels of MAGI3 contribute to tumor development and progression in a variety of malignancies, including glioma (8), cervical cancer (9) and colorectal cancer (10). Nevertheless, the role of MAGI3 in RCC has yet to be elucidated.

MAGI3 exerts inhibitory effects on tumorigenesis and progression by modulating PI3K/AKT and Wnt signaling pathways (8,9,17). However, its role and associated pathways in kidney cancer remain unexplored. In this study, we analyzed RNA expression data from the TCGA dataset across 33 tumor types and found that MAGI3 expression was significantly reduced in renal clear cell carcinoma, renal papillary carcinoma, acute myeloid leukemia, and tenosynovial giant cell tumor tissues compared with normal tissues. Furthermore, analysis of MAGI3 in renal clear cell carcinoma using TCGA database unveiled a negative correlation between MAGI3 expression and tumor grade, stage and lymphatic metastasis, suggesting the possibility that the expression of MAGI3 may serve as a potential predictor of progression and prognosis of renal clear cell carcinoma. Bioinformatics analysis indicated that MAGI3 may inhibit the growth and invasive function of RCC through the jak-stat3 information pathway. Signal transducer and activator of transcription 3 (STAT3) is a transcription factor within the STAT protein family (18). Functioning as a key regulator of cell proliferation, survival and apoptosis (19), STAT3 plays a crucial role in the development and progression of various tumors (20,21). STAT3 orchestrates the crosstalk among inflammation, angiogenesis, and tumor immune escape, which are critical events in the progression of solid malignancies. Emerging evidence has highlighted that chemokines, particularly CXC and CC subfamilies, function as pivotal angiogenic regulators in non-hematological tumors. STAT3-dependent signaling cascades are closely intertwined with these chemokine-mediated angiogenic programs, thereby promoting tumor vascularization and malignant progression. Such regulatory networks are highly relevant to the pathogenesis and therapeutic resistance of urological malignancies, supporting the notion that targeting STAT-chemokine-angiogenesis axis may represent a promising strategy for cancer intervention (22). The JAK/STAT signaling pathway has been identified as a key driver in both leukemogenesis and colorectal cancer progression (23,24). Previous studies have demonstrated that in RCC, STAT3 enhances tumor pathological stage and promotes tumor progression, correlating with poor prognosis (19,25,26). Our results indicated that MAGI3 overexpression inhibited the growth and invasion of RCC. Moreover, it was further observed that MAGI3 overexpression hinders renal cell carcinogenesis or progression by suppressing the JAK-STAT3 signaling pathway.

In our study, q-PCR data revealed the involvement of MCL-1, MMP2 and other genes in this regulatory process. Notably, through Chip-qPCR analysis, we identified that MCL1 and MMP2 expression was directly regulated by p-STAT3. MCL 1, a member of BCL2 family, inhibits cell apoptosis (27,28). Additionally, MMP2 belongs to the matrix metalloproteinase (MMP) gene family, serving as a zinc-dependent enzyme associated with the regulation of vascularization and metastasis (29). Therefore, based on our findings, we posit that p-STAT3 can directly upregulate the transcription of MCL1 and MMP2, thereby promoting the growth, invasion and metastatic functions of tumor cells. Moreover, the up-regulated MAGI3 can facilitate Stat3 degradation through ubiquitination modification, thereby inhibiting the activation of Stat3 signaling pathway and subsequently leading to the down-regulated MCL1 and MMP2 transcription. The ubiquitination assay requires follow-up to evaluate key elements such as E3 ligases and ubiquitination sites for a more comprehensive exploration of regulation.

Immune checkpoint inhibitors (ICIs) are the mainstay of standard-of-care for advanced ccRCC. Our study identified MAGI3 as a potential prognostic biomarker and therapeutic target, but its association with ICIs and other standard treatments remains unclear. Notably, PD-1/PD-L1 signaling pathways are enriched in MAGI3-low tumors, implying that MAGI3 expression may regulate response to immunotherapy, either directly or indirectly through STAT3 modulation-an underexplored mechanism in our current work. A comprehensive summary of predictive and prognostic biomarkers for immunotherapy in advanced RCC has been provided by Rosellini et al. (30).

Conclusions

This study presents MAGI3 as a novel suppressor of RCC, illustrating its inhibitory impact on proliferation through the targeting STAT3. MAGI3 emerges as a potential predictive marker for patients with RCC.

Supplementary

The article’s supplementary files as

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Shenzhen Hospital, Southern Medical University (No. NYSZYYEC20190018, approval date: December 9, 2019), and written informed consent was obtained from all patients. All animal experiments were performed under a project license (No. Rise-Mice-202301010001, approval date: January 1, 2023) granted by Ethics Committee of Affiliated Cancer Hospital and Institute of Guangzhou Medical University, in compliance with the NIH Guide for the Care and Use of Laboratory Animals.

Data Sharing Statement

Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0030/dss

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DOI: 10.21037/tau-2026-1-0030