Tumor metastasis is one of the major causes of high mortality in patients with hepatocellular carcinoma (HCC). Sustained activation of STAT3 signaling plays a critical role in HCC metastasis. RNA binding protein (RBP)–mediated posttranscriptional regulation is involved in the precise control of signal transduction, including STAT3 signaling. In this study, we investigated whether RBPs are important regulators of HCC metastasis. The RBP MEX3C was found to be significantly upregulated in highly metastatic HCC and correlated with poor prognosis in HCC. Mechanistically, MEX3C increased JAK2/STAT3 pathway activity by downregulating SOCS3, a major negative regulator of JAK2/STAT3 signaling. MEX3C interacted with the 3′UTR of SOCS3 and recruited CNOT7 to ubiquitinate and accelerate decay of SOCS3 mRNA. Treatment with MEX3C-specific antisense oligonucleotide significantly inhibited JAK2/STAT3 pathway activation, suppressing HCC migration in vitro and metastasis in vivo. These findings highlight a novel mRNA decay-mediated mechanism for the disruption of SOCS3-driven negative regulation of JAK2/STAT3 signaling, suggesting MEX3C may be a potential prognostic biomarker and promising therapeutic target in HCC.

Significance:

This study reveals that RNA-binding protein MEX3C induces SOCS3 mRNA decay to promote JAK2/STAT3 activation and tumor metastasis in hepatocellular carcinoma, identifying MEX3C targeting as a potential approach for treating metastatic disease.

Hepatocellular carcinoma (HCC) is one of the most common malignancies and is listed as the third leading cause of cancer-related death worldwide, with about 841,080 newly diagnosed cases and 781,631 deaths in 2018 (1, 2). Although major advances have been made in the prevention, detection, diagnosis, and treatment of HCC, the outcomes of patients with HCC are still unsatisfactory, with a postoperative 5-year survival rate of approximately 30% to 40% (3, 4). The uncontrolled occurrence of intrahepatic spread and extrahepatic metastasis result in the poor prognosis of patients with HCC (4). Therefore, uncovering the metastatic mechanism and exploring novel diagnostic markers and therapeutic targets are urgently required to improve HCC prognosis.

Sustained activation of STAT3 has been characterized as a central regulator of HCC metastasis (5–7). Inhibition of STAT3 signaling has been confirmed to suppress tumor growth and development, serving as a promising therapeutic strategy for cancers (5–7). Gain-of-function mutations of STAT3 are rare in solid cancers (7). Indeed, the sustained activation of STAT3 in various cancers is maintained by disabling negative regulators, including the interruption of suppressor of cytokine signaling (SOCS), protein inhibitor of activated STAT (PIAS), and protein tyrosine phosphatases (PTP) proteins (8). Cumulative evidence reveals that posttranscriptional regulation, such as mRNA decay, plays an important role in the activation of STAT3 signaling (9, 10). For instance, Y-box protein 1 (YB1) enhances phosphorylation of STAT3 protein by inducing PIAS3 mRNA decay (9). Unveiling the mechanisms of mRNA decay that activate STAT3 signaling is crucial for exploring targeted therapeutic strategies for HCC metastasis.

RNA-binding proteins (RBP) have emerged recently as key factors in regulating the abundance and translational potential of RNA transcripts through the posttranscriptional control, such as RNA decay (11, 12). There is a growing body of evidence demonstrated that RBPs and RBPs-controlled expression networks are critical in cancer metastasis (11–13). RNA interference-based approaches to modulate the expression of RBPs, such as antisense oligonucleotides (ASO), are under development as novel therapeutic avenues for cancer in preclinical models and in clinical trials (13, 14). Although several studies have revealed the importance of RBPs in HCC progression (15, 16), the explicit functions and the underlying mechanisms of RBPs in regulating HCC metastasis are largely unexplored. Recently, we performed RNA sequencing (RNA-seq) to screen the key RBPs that are potentially responsible for HCC metastasis. We found that the RBP Mex3 RNA-binding family member C (MEX3C) was significantly upregulated in metastatic HCC. RNA-binding proteins of the MEX3 family consist of two KH domains at the N-terminus with single-strand RNA binding activity, and a RING-finger domain at the C-terminus with ubiquitin E3 ligase activity, which have been recently identified as novel mediators of RNA decay (17–19). Intriguingly, MEX3C has been reported to involve in many pathophysiologic processes (20, 21). However, the role and mechanism of MEX3C in regulating HCC metastasis are unknown.

Here, we observed that upregulation of MEX3C was significantly correlated with tumor metastasis and poor prognosis in patients with HCC. MEX3C accelerate SOCS3 mRNA degradation via recruiting and ubiquitinating CNOT7, thereby maintains the activation of the JAK2/STAT3 pathway, inducing ECM degradation and promoting invasion and migration ability of HCC cells. More importantly, targeting MEX3C significantly inhibits the JAK2/STAT3 pathway activation and tumor metastasis. In general, our findings emphasize the importance of RNA metabolism in HCC progression and suggest a novel therapeutic strategy against tumor metastasis.

Patient information and tissue specimens

Tumor tissues were obtained from surgical specimen archives of 202 patients with HCC at Sun Yat‐sen University Cancer Center from 2008 to 2012. Frozen tissues were used for qRT-PCR and Western blotting analysis, and paraffin-embedded samples were used for IHC analysis. Tumor-node-metastasis (TNM) classification of HCC was based on the American Joint Commission on Cancer/International Union against Cancer Staging System (8th edition, 2017). The differentiation state was graded according to Edmondson and Steine method. Time to metastasis was defined as the time between surgery and the subsequent diagnosis of any type of metastasis, including intrahepatic metastasis and extrahepatic metastasis. The detailed clinicopathological characteristics are summarized was summarized in Supplementary Table S1. The study protocols were approved by the Institutional Research Ethics Committee of Sun Yat‐sen University for the use of these clinical materials for research purposes. All patients’ samples were obtained according to the Declaration of Helsinki and each patient signed written informed consent for the procedures.

Cells

HCC cell lines, including HCCLM6, Huh7, PLC/PRF/5, and the human normal liver cell line L-O2, were purchased from the ATCC. HCCLM3, MHCC97H, MHCC97L, and 293T cells were obtained from the Shanghai Cell Bank of the Chinese Academy of Sciences. All the cells were cultured in DMEM supplemented with 10% FBS (HyClone) at 37°C in a 5% CO2 incubator. The cell lines were authenticated using short tandem repeat (STR) fingerprinting and verified to be mycoplasma-free using the LookOut Mycoplasma PCR Detection Kit (#MP0035; Sigma-Aldrich). Cells were used within four to five passages from thawing of cryopreserved cells.

Transfection of ASOs

The ASOs were synthesized by RiboBio. All bases of ASOs were converted to thiooligonucleotides. By changing the 5 nt at the 5′ and 3′ ends into 2′-O-methyl ribonucleic acid, the second-generation ASOs are characterized by enhanced hybridization affinity for their RNA targets, increased nuclease stability, prolonged tissue half-life, and reduced immunostimulatory activity (22, 23). A universal nonsilencing ASO targeting no known sequence in human genome was used as the negative control (lnc6N0000001; ref. 24). Cells were transiently transfected with ASO-NC (100 nmol/L), MEX3C ASO-1 (100 nmol/L), or MEX3C ASO-2 (100 nmol/L) using Lipofectamine 3000 reagent (L3000001; Life Technologies) following manufacturer's protocol. The ASO target sequences are as following: ASO-1: ACATAGTAACTCCGAGCAGA; ASO-2: TGCTCAAACTATCTGGACTC.

IHC

IHC staining was performed on the 202 paraffin-embedded HCC tissues as described previously (25). Sections were incubated with anti-MEX3C antibodies (HPA040603; Sigma-Aldrich), anti-pSTAT3Y705 antibodies (#9145; Cell Signaling Technology), anti-p-JAK2Y1007 antibodies (ab195055; Abcam), and anti-SOCS3 antibodies (ab236519; Abcam) overnight at 4°C. IHC staining was scored separately by two independent pathologists who were blinded to the histopathologic features and patient data. Tumor cell proportions were scored as follows: 0, no positive tumor cells; 1, <10%; 2, 10% to 35%; 3, 35% to 75%; 4, >75%. Staining intensity was graded according to following standard: 1, no staining; 2, weak staining (light yellow); 3, moderate staining (yellow brown); 4, strong staining (brown). The staining index (SI) was calculated as the proportion of positive cells and the staining intensity score. Using this assessment method, we evaluated protein expression in HCC tissues by measuring SI, with possible scores of 0, 1, 2, 3, 4, 6, 8, 9, 12, and 16. The cutoff values to define the high and low MEX3C expression was derived from the highest combined sensitivity and specificity concerning patient survival. An optimal threshold of SI ≥8 was then determined to define samples with high MEX3C expression and samples with an SI < 8 were determined as low expression.

RNA immunoprecipitation assays

Cells at 80% confluency were fixed using 1% formaldehyde for 15 minutes, and 1 M glycine was added for 5 minutes to stop the fixation. For each immunoprecipitation reaction, a total of 1 × 107 cells is needed. After washing with PBS, the cells are collected by scraping and lysing in lysis buffer (20 mmol/L Tris-Cl, pH 8.0, 10 mmol/L NaCl, 1 mmol/L EDTA, 0.5% NP-40) supplemented with protease and RNasin (N2111; Promega). Samples were then immunoprecipitated using 5 μg anti-MEX3C (sc-398440; Santa Cruz Biotechnology), anti-Flag (#8146; Cell Signaling Technology), anti-HA (#3724; Cell Signaling Technology), or IgG (I5006; Sigma Aldrich) antibodies coupled to Dynabeads Protein A. The immunoprecipitates were extensively washed four to six times. The recovered sediments were then analyzed by qRT-PCR. ACTB was used as a negative control. The primers used were provided in the Supplementary Information. All experiments were performed in triplicate.

RNA decay and turnover experiment

The RNA decay and turnover assay was performed using the Click-iT Nascent RNA Capture Kit (#C10365; Thermo Fisher Scientific), according to a standard protocol (26). Briefly, cells (RNA) were labeled with 0.2 mmol/L 5-ethyluridine (EU) for 2 hours (pulse). Next, the cells were washed with normal growth medium and continued to grow in unlabeled medium for 2 hours (chase). The cells were harvested and used for the click reaction. At this stage, only EU-labeled RNAs were tagged with biotin. The biotinylated RNA was pulled down using streptavidin beads. Finally, the captured RNA was analyzed by qRT-PCR analysis. The primers used are provided in the Supplementary Information.

Deadenylation assays

The deadenylation activity assay of MEX3C complexes was performed according to a standard protocol (18). Briefly, 293T cells (1 × 106) were transfected with vector, HA-MEX3C, HA-MEX3C△KH, HA-MEX3C△RING, and Flag-CNOT7 constructs. After 48 hours, the cells were lysed using lysis buffer (150 mmol/L NaCl, 10 mmol/L HEPES, 1% NP-40) for 30 minutes at 4°C. The lysates were then incubated with HA affinity agarose (A2095; Sigma-Aldrich) at 4°C overnight. Beads containing affinity binding protein were washed with IP washing buffer (150 mmol/L NaCl, 10 mmol/L HEPES, pH 7.4, 0.1% NP-40) for six times, and then eluted with 1 M glycine (pH 3.0). The eluent and 5′-fluorescein labeling RNA substrates (Flc-5′-AAGAGCACUAUUUUUUAAUGAAAAA) were incubated for 1.5 hours. The reaction was stopped by adding TBE/Urea RNA sample buffer (#1610768; BioRad) and heated at 85°C for 3 minutes. The reaction products were separated by urea polyacrylamide gel electrophoresis and stained with SYBR Green-II RNA gel (S7568; Thermo Fisher Scientific). Residual RNA intensity was measured using ChemiDoc MP Gel System and ImageJ 1.42q software.

Gelatin degradation assay

Oregon Green 488-conjugated gelatin (G-13186; Life Technologies) was prepared according to a previously published protocol (27). Cells (1 × 104) were cultured overnight on the coverslips previously covered by the 488-gelatin substrate. The slides were treated with phalloidine to detect F-actin and DAPI to detect the nuclei for immunofluorescence analysis. Confocal microscopy analysis was performed using a 63× objective lens and five randomly selected fields were imaged. The degradation area was the area where the fluorescence signal was below the threshold and was assessed using ImageJ. The quantified area was then normalized to the number of cells.

In vivo assays

Male BALB/c-nude mice (6 weeks) were raised in specific pathogen-free conditions with a 12 hours light/dark schedule at 18 to 22°C and 50% to 60% humidity. The mice were randomly divided into the indicated groups (6 mice/group) before inoculation. For the orthotopic metastasis model, the indicated MHCC97L and MHCC97H cells (5 × 106) were injected into the left hepatic lobe of mice. The mice were sacrificed after 60 days, and their livers and lungs were removed. The metastases were detected using an in vivo imaging system (IVIS). Samples were paraffin-embedded and subjected to hematoxylin and eosin and IHC staining. All animal experimental procedures were approved by Institutional Animal Care and Use Committee of Sun Yat-sen University and performed following the Declaration of Helsinki.

RNA-seq data

RNA extraction and RNA-seq were performed on MHCC97H and MHCC97L cell lines. Differential expression analysis was performed using the DESeq2 software package. The RNA-seq data have been deposited in the Gene Expression Omnibus (GEO) database (No. GSE208148).

RNA immunoprecipitation sequencing

Cell lysates generated from MEX3C-Flag-overexpressing MHCC97H cells were used for RNA immunoprecipitation analysis as described previously (28). In brief, anti-MEX3C antibodies were conjugated to Dynabeads protein A for immunoprecipitation of MEX3C–RNA complexes. RNA was extracted using TRizol following the manufacturer's instructions. The RNA immunoprecipitation sequencing (RIP-seq) data have been deposited in the GEO database (No. GSE208371).

Statistical analysis

Statistical analyses were performed using the SPSS version 19.0 statistical software package and GraphPad Prism 8 version (GraphPad Software). Statistical tests for data analysis included the χ2 test (two-sided), Student t test (two-sided), and the log-rank test. Multivariate statistical analysis was performed using a Cox regression model. P < 0.05 was considered statistically significant. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Additional information is provided in Supplementary Materials and Methods.

Data availability

The sequence data generated in this study have been deposited in GEO at GSE208148 and GSE208371. Expression profile data analyzed in this study were obtained from The Cancer Genome Atlas (TCGA) liver HCC mRNA gene expression data and GEO at GSE15765 and GSE14323. All data supporting the findings of the study are available within the article and its Supplementary Information file.

MEX3C upregulation correlates with HCC metastasis

It has been recently reported that RBPs play a central role in controlling gene expression and function by directly regulating RNA metabolism, and dysregulated RBPs are considered pivotal factors in cancer metastasis and may be promising therapeutic targets (11–14). To identify the key RBPs involved in HCC metastasis, RNA-seq analysis was performed in the human HCC cell lines with high spontaneous metastatic potential (MHCC97H) and low potential (MHCC97L) to explore differentially expressed RBPs associated with HCC metastasis (29); differentially expressed genes were determined with P < 0.01 and a fold-change value ≥2. The result showed that 340 genes were differentially expressed in the two cell lines, among which, SOX17 (30), NLRP3 (31), and FBXO2 (32) have been reported to be closely associated with tumor metastasis, indicating the reliability of our results. We noted that four RBP genes were significantly upregulated in MHCC97H, among which, MEX3C was the most upregulated (Fig. 1A). We further validated the expression levels of these RBPs in various HCC cell lines. MEX3C, but not EXO1, BARD1, and THUMPD1, was significantly upregulated in HCC cell lines with high metastatic potential (MHCC97H, HCCLM6, and HCCLM3) compared with those with low metastatic potential (PLC, Huh7, and MHCC97L; Fig. 1B; Supplementary Fig. S1A; ref. 33). In addition, MEX3C level was significantly increased in HCC cells compared with that in normal liver cell line L-O2 (Fig. 1B). In accordance with the results detected in cell lines, MEX3C was elevated in metastatic HCC patient samples compared with those without metastasis (Fig. 1C). These findings reveal that MEX3C upregulation correlates with HCC metastasis.

Figure 1.

MEX3C upregulation correlates with HCC metastasis. A, Volcano plot for RBP expression in the RNA-seq analysis by comparing the low metastatic potential HCC cell line MHCC97L and high metastatic potential HCC cell line MHCC97H. The blue dots represent the downregulated RBP genes and red dots represent the upregulated RBP genes in MHCC97H cells compared with MHCC97L cells by RNA-seq. B, qRT-PCR and Western blotting analysis of MEX3C in a human normal liver cell line (L-O2) and six HCC cell lines with higher metastatic potential (red) or lower metastatic potential (black). GAPDH was used as an internal control. Immunoblots are representative of three independent experiments. C, qRT-PCR analysis of MEX3C in the hepatocellular tumor tissues from 20 patients with HCC with metastasis and 20 patients with HCC without metastasis. GAPDH was used as a loading control. D, Left, representative postoperative CT scan image of the liver and lung of patients with or without metastasis, and the corresponding images of MEX3C IHC staining in HCC specimens. Right, the distribution of MEX3C staining in patients with and without metastasis. Two-sided χ2 test and Cramer V were used to evaluate the correlation. Scale bars, 50 μm; insets, 20 μm. E, qRT-PCR analysis of MEX3C expression in eight pairs of primary and matched metastatic biopsies from patients with HCC. F and G, Kaplan–Meier analysis of metastasis-free survival (MFS) or overall survival (OS) curves for HCC patient stratified by low and high MEX3C expression (n = 202, log-rank test). H and I, Multivariate Cox regression analysis to assess the significance of the correlation between high MEX3C expression signature and MFS or OS in the presence of other important clinical variables. Each error bar in B represents the mean ± SD of three independent experiments. Two-sided Student t test was used for the statistical analysis. **, P < 0.01; ***, P < 0.001.

Figure 1.

MEX3C upregulation correlates with HCC metastasis. A, Volcano plot for RBP expression in the RNA-seq analysis by comparing the low metastatic potential HCC cell line MHCC97L and high metastatic potential HCC cell line MHCC97H. The blue dots represent the downregulated RBP genes and red dots represent the upregulated RBP genes in MHCC97H cells compared with MHCC97L cells by RNA-seq. B, qRT-PCR and Western blotting analysis of MEX3C in a human normal liver cell line (L-O2) and six HCC cell lines with higher metastatic potential (red) or lower metastatic potential (black). GAPDH was used as an internal control. Immunoblots are representative of three independent experiments. C, qRT-PCR analysis of MEX3C in the hepatocellular tumor tissues from 20 patients with HCC with metastasis and 20 patients with HCC without metastasis. GAPDH was used as a loading control. D, Left, representative postoperative CT scan image of the liver and lung of patients with or without metastasis, and the corresponding images of MEX3C IHC staining in HCC specimens. Right, the distribution of MEX3C staining in patients with and without metastasis. Two-sided χ2 test and Cramer V were used to evaluate the correlation. Scale bars, 50 μm; insets, 20 μm. E, qRT-PCR analysis of MEX3C expression in eight pairs of primary and matched metastatic biopsies from patients with HCC. F and G, Kaplan–Meier analysis of metastasis-free survival (MFS) or overall survival (OS) curves for HCC patient stratified by low and high MEX3C expression (n = 202, log-rank test). H and I, Multivariate Cox regression analysis to assess the significance of the correlation between high MEX3C expression signature and MFS or OS in the presence of other important clinical variables. Each error bar in B represents the mean ± SD of three independent experiments. Two-sided Student t test was used for the statistical analysis. **, P < 0.01; ***, P < 0.001.

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High MEX3C expression is associated with poor prognosis in patients with HCC

To further evaluate the clinical significance of MEX3C in HCC, we performed IHC to detect MEX3C expression in 202 paraffin-embedded HCC specimens (Supplementary Table S1). According to the staining index (SI), we divided the samples with SI < 8 into the MEX3C low expression group (82 cases) and the samples with SI ≥ 8 into the MEX3C high expression group (120 cases). MEX3C was remarkably upregulated in metastatic HCC tissues compared with that in non-metastatic tissues (Fig. 1D). Moreover, MEX3C expression was increased in the HCC metastases compared to paired primary tumors (Fig. 1E). High MEX3C expression was associated with tumor metastasis (P < 0.0001), advanced TNM stage (P < 0.0001), portal vein invasion (P = 0.0005), poor tumor differentiation (P = 0.0003), multiple tumor nodule (P = 0.0183), and large tumor size (P < 0.0001; Supplementary Table S2). Kaplan-Meier survival curves revealed shorter metastasis-free survival (MFS) and overall survival (OS) in patients with HCC with high level of MEX3C (Fig. 1F and G), which in accordance with the OS of patients with HCC from the TCGA (Supplementary Fig. S1B). Univariate and multivariate Cox regression analyses showed that high MEX3C expression was an independent prognostic factor for MFS and OS in patients with HCC (Fig. 1HI; Supplementary Tables S3 and S4). Collectively, these findings suggest that MEX3C serves as a novel predictive biomarker for HCC.

MEX3C activates the JAK2/STAT3 signaling pathway by downregulating SOCS3

Subsequently we explored the mechanisms by which MEX3C regulates HCC metastasis. It has been well-identified that JAK/STAT, TGFβ, WNT, mTOR, VEGF, MAPK, HEDGEHOG, and NOTCH signaling were pivotal pathways in driving tumor metastasis (34, 35). Our analysis of gene set enrichment analysis (GSEA) with TCGA Liver HCC (TCGA-LIHC) data revealed that the JAK/STAT, TGF-BETA, and other several metastasis-related signaling pathways were differentially enriched in HCC with high MEX3C expression (Fig. 2A). The normalized enrichment score (NES) of the JAK/STAT signaling pathway was the highest (Fig. 2A). Moreover, the GSEA plots showed that MEX3C expression positively correlated with JAK2-activated gene signatures (JAK2_DN.V1_DN) and STAT3-targeted gene signatures (AZARE_STAT3_TARGETS), suggesting that MEX3C might be involved in the activation of JAK2/STAT3 signaling in HCC (Supplementary Fig. S2A).

Figure 2.

MEX3C activates the JAK2/STAT3 signaling pathway by downregulating SOCS3. A, Signatures using the TCGA-LIHC dataset and displayed as a bubble plot. B, Western blotting analysis of p-JAK2, total JAK2, pSTAT3, and total STAT3 levels in the indicated cells. GAPDH was used as a loading control. C, STAT3 luciferase reporter activity was analyzed in the indicated cells. D, Representative images from cell immunofluorescence for pSTAT3. Nuclei were stained blue using DAPI. Scale bars, 15 μm. E, qRT-PCR analysis of MMP2, MMP9, IL6, CXCR4, and ICAM-1 in the indicated MHCC97H cells. F, Flowchart of RIP-seq analysis. G, Venn diagrams of MEX3C binding genes in the RIP-seq analysis (purple) and regulators of the JAK2/STAT3 pathway (blue) according to GSEA gene sets. H and I, qRT-PCR analysis (H) and Western blotting analysis (I) of TNFRSF1A, PPP2R1A, and SOCS3 in the indicated MHCC97H cell lines. J, Western blotting analysis of SOCS3 in the indicated cells. GAPDH was used as a loading control. K, STAT3 luciferase reporter activity was analyzed in the indicated HCC cells. Each error bar in C, E, H, and K represents the mean ± SD of three independent experiments. Two-sided Student t test was used for the statistical analysis. ***, P < 0.001.

Figure 2.

MEX3C activates the JAK2/STAT3 signaling pathway by downregulating SOCS3. A, Signatures using the TCGA-LIHC dataset and displayed as a bubble plot. B, Western blotting analysis of p-JAK2, total JAK2, pSTAT3, and total STAT3 levels in the indicated cells. GAPDH was used as a loading control. C, STAT3 luciferase reporter activity was analyzed in the indicated cells. D, Representative images from cell immunofluorescence for pSTAT3. Nuclei were stained blue using DAPI. Scale bars, 15 μm. E, qRT-PCR analysis of MMP2, MMP9, IL6, CXCR4, and ICAM-1 in the indicated MHCC97H cells. F, Flowchart of RIP-seq analysis. G, Venn diagrams of MEX3C binding genes in the RIP-seq analysis (purple) and regulators of the JAK2/STAT3 pathway (blue) according to GSEA gene sets. H and I, qRT-PCR analysis (H) and Western blotting analysis (I) of TNFRSF1A, PPP2R1A, and SOCS3 in the indicated MHCC97H cell lines. J, Western blotting analysis of SOCS3 in the indicated cells. GAPDH was used as a loading control. K, STAT3 luciferase reporter activity was analyzed in the indicated HCC cells. Each error bar in C, E, H, and K represents the mean ± SD of three independent experiments. Two-sided Student t test was used for the statistical analysis. ***, P < 0.001.

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To validate MEX3C's role in regulating JAK2/STAT3 signaling, we constructed MEX3C-silencing stable cell lines from MHCC97H cells, which initially expressed relatively high MEX3C and MEX3C-overexpressing stable cell lines from MHCC97L cells, which initially expressed relatively low MEX3C (Supplementary Fig. S2B). Western blotting analysis showed that MEX3C upregulation dramatically promoted, whereas MEX3C knockdown greatly inhibited the levels of p-JAK2 and pSTAT3 but had no obvious effects on total expression levels of JAK2 and STAT3 (Fig. 2B). Luciferase reporter assays indicated that overexpression of MEX3C significantly increased, whereas knockdown of MEX3C decreased STAT3 activity (Fig. 2C). Immunofluorescence staining further confirmed the activation of the STAT3 signaling by showing high levels of nuclear pSTAT3 in the cells (Fig. 2D). Consistently, the mRNA expression of STAT3 targets, such as MMP2, MMP9, IL6, CXCR4, and ICAM-1 (36–38), were increased in MEX3C-overexpressing cells but were reduced in MEX3C-silencing cells (Fig. 2E; Supplementary Fig. S2C). Collectively, these results indicate that MEX3C activates the JAK2/STAT3 signaling pathway in HCC.

MEX3C has been reported to control gene expression through direct binding target RNAs. To identify the interacting mRNAs of MEX3C, high-throughput sequencing followed RIP-seq was conducted (Fig. 2F). 505 mRNA targets of MEX3C were determined with the criteria of P < 0.05, a fold-change value >3. Strikingly, we noticed that TNFRSF1A, PPP2R1A, and SOCS3 mRNA might be the direct binding targets of MEX3C associated with the JAK/STAT pathway (Fig. 2G). Further validation through qRT-PCR and Western blotting assays showed that MEX3C slightly impacted the mRNA and protein levels of TNFRSF1A and PPP2R1A, while it evidently impaired the expression of SOCS3 (Fig. 2H and I; Supplementary Figs. S2D and S2E). These results indicate that MEX3C may activate the JAK2/STAT3 pathway by disrupting SOCS3 expression.

To verify the role of SOCS3 in MEX3C-induced JAK2/STAT3 activation, cell lines of ectopically-expressed SOCS3 in MEX3C-overexpressing MHCC97L cells and knocked-down SOCS3 in MEX3C-silenced MHCC97H cells were constructed, and the expression levels of SOCS3 were detected (Fig. 2J). Restoring SOCS3 expression significantly inhibited the activation of JAK2/STAT3 induced by MEX3C overexpression, while silencing SOCS3 reversed the inactivation of JAK2/STAT3 induced by MEX3C knockdown (Fig. 2K). Furthermore, the negative correlation of the mRNA expression of MEX3C and SOCS3 was demonstrated in human HCC tissues according to the online public datasets GSE15765 and GSE14323 (Supplementary Fig. S2F). Our findings show that MEX3C activates the JAK2/STAT3 signaling pathway by downregulating SOCS3 expression.

MEX3C interacts with SOCS3 3′UTR via the MEX3 recognition element

Subsequently, we further explored the binding relationship between MEX3C and SOCS3 mRNA. Endogenous RIP assays performed in MHCC97H cells with anti-MEX3C antibody and exogenous RIP assays performed with anti-HA antibody in 293T cells exogenously expressing HA-tagged MEX3C (HA-MEX3C) confirmed that MEX3C consistently interacted with SOCS3 transcripts (Fig. 3A and B). To detect the specific binding region, the SOCS3 mRNA were divided into different fragments and luciferase reporter plasmids containing the 5′UTR, CDS, and 3′UTR of SOCS3 mRNA were constructed, respectively. The results showed that MEX3C bound to the 3′UTR of SOCS3, but not the 5′UTR or CDS (Fig. 3C). Western blotting analysis followed biotinylated RNA pull-down assays (Fig. 3D and E) or MS2-based RIP assays (Fig. 3F) demonstrated that the 3′UTR was the binding region of SOCS3 mRNA with MEX3C. As shown in the pattern diagram, we found that the SOCS3 3′UTR contained a MEX3 recognition element (MRE; Fig. 3G), which was defined as (A/G/U)(G/U)AG(0–8)U(U/A/C)UA and was reported to interact with the RNA binding motif of MEX3 proteins (18). To test whether the MRE motif was crucial for the interaction between SOCS3 and MEX3C, we generated a mutation within this motif at SOCS3 3′UTR (Fig. 3G). Mutant SOCS3 3′UTR lost almost all of its ability to bind with MEX3C (Fig. 3H and I; Supplementary Fig. S3A). Taken together, these results suggest that the MRE motif at the 3′UTR is essential for the interaction of SOCS3 mRNA with MEX3C (Fig. 3J).

Figure 3.

MEX3C interacts with SOCS3 3′UTR via the MEX3 recognition element. A, RIP assays were performed in MHCC97H cells with anti-MEX3C antibodies. The extracted RNA was then subjected to qRT-PCR analysis of SOCS3, HLA-A2 (positive control), and ACTB (negative control). B, RIP assays followed by qRT-PCR analysis examining the interaction between MEX3C and SOCS3 mRNA in HA-MEX3C–overexpressing 293T cells using an anti-HA antibody. C, Luciferase reporter assays were performed to test the interaction of MEX3C and its targeting sequence (5′UTR, CDS, or 3′UTR) in the SOCS3 mRNA. D, Flowchart of the biotin-labeled RNA pull-down assay. Briefly, in vitro-transcribed and biotin-labeled SOCS3 RNA was incubated with purified MEX3C protein. Then, the biotin-labeled RNA complex was pulled down using streptavidin-conjugated magnetic beads. The RNA-bound protein complex was eluted and the retrieved MEX3C protein was detected using Western blotting assays. E, Western blotting analysis of MEX3C after biotin-labeled SOCS3 RNA pull-down. Dot blot indicates that the RNAs are biotin-labeled. Immunoblots are representative of three independent experiments. F, Top, flowchart of MS2-based RIP assay. Briefly, pcDNA3-MS2bp-Flag and pcDNA3–12*MS2bs conjugated with SOCS3 RNA or pcDNA3–12*MS2bs mock were cotransfected into the MHCC97H cells. The cells were lysed and the lysates were then pulled down using anti-Flag M2 affinity gel. The recovered precipitates were used for Western blotting detection. Bottom, Western blotting analysis of MEX3C after MS2bp-Flag-MS2bs–based pulldown of SOCS3 RNA in MHCC97H cells. G, The SOCS3-3′UTR contained a MEX3-recognition element (MRE). Schematic illustration showing the predicted binding site of MEX3C. Mutation of the binding site in the SOCS3-3′UTR is indicated. H, Western blotting analysis of MEX3C after the indicated biotin-labeled RNA pull-down. Dot blot indicates that the RNAs are biotin-labeled. I, Western blotting analysis of MEX3C after MS2bp-Flag-MS2bs–based pulldown of SOCS3 3′UTR or 3′UTR-Mut in MHCC97H cells. J, Working model showing that MEX3C bound to the MRE region of SOCS3 3′ UTR. Each error bar in A to C represents the mean ± SD of three independent experiments. Two-sided Student t test was used for the statistical analysis. ***, P < 0.001.

Figure 3.

MEX3C interacts with SOCS3 3′UTR via the MEX3 recognition element. A, RIP assays were performed in MHCC97H cells with anti-MEX3C antibodies. The extracted RNA was then subjected to qRT-PCR analysis of SOCS3, HLA-A2 (positive control), and ACTB (negative control). B, RIP assays followed by qRT-PCR analysis examining the interaction between MEX3C and SOCS3 mRNA in HA-MEX3C–overexpressing 293T cells using an anti-HA antibody. C, Luciferase reporter assays were performed to test the interaction of MEX3C and its targeting sequence (5′UTR, CDS, or 3′UTR) in the SOCS3 mRNA. D, Flowchart of the biotin-labeled RNA pull-down assay. Briefly, in vitro-transcribed and biotin-labeled SOCS3 RNA was incubated with purified MEX3C protein. Then, the biotin-labeled RNA complex was pulled down using streptavidin-conjugated magnetic beads. The RNA-bound protein complex was eluted and the retrieved MEX3C protein was detected using Western blotting assays. E, Western blotting analysis of MEX3C after biotin-labeled SOCS3 RNA pull-down. Dot blot indicates that the RNAs are biotin-labeled. Immunoblots are representative of three independent experiments. F, Top, flowchart of MS2-based RIP assay. Briefly, pcDNA3-MS2bp-Flag and pcDNA3–12*MS2bs conjugated with SOCS3 RNA or pcDNA3–12*MS2bs mock were cotransfected into the MHCC97H cells. The cells were lysed and the lysates were then pulled down using anti-Flag M2 affinity gel. The recovered precipitates were used for Western blotting detection. Bottom, Western blotting analysis of MEX3C after MS2bp-Flag-MS2bs–based pulldown of SOCS3 RNA in MHCC97H cells. G, The SOCS3-3′UTR contained a MEX3-recognition element (MRE). Schematic illustration showing the predicted binding site of MEX3C. Mutation of the binding site in the SOCS3-3′UTR is indicated. H, Western blotting analysis of MEX3C after the indicated biotin-labeled RNA pull-down. Dot blot indicates that the RNAs are biotin-labeled. I, Western blotting analysis of MEX3C after MS2bp-Flag-MS2bs–based pulldown of SOCS3 3′UTR or 3′UTR-Mut in MHCC97H cells. J, Working model showing that MEX3C bound to the MRE region of SOCS3 3′ UTR. Each error bar in A to C represents the mean ± SD of three independent experiments. Two-sided Student t test was used for the statistical analysis. ***, P < 0.001.

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MEX3C recruits CNOT7 to degrade SOCS3 mRNA

The mechanism of MEX3C-mediated SOCS3 downregulation was explored. It is notice that MEX3C has been identified to affect mRNA stability (17–19); thus, we proposed that MEX3C might regulate the abundance of SOCS3 by disrupting mRNA stability. By treating with a transcription inhibitor actinomycin D (5 μg/mL), SOCS3 mRNA was significantly degraded in MEX3C-overexpressing MHCC97L cells compared with control cells. The mRNA level of ACTB served as a negative control and was not affected by MEX3C expression (Fig. 4A). The opposite result was observed after silencing MEX3C in MHCC97H cells (Supplementary Fig. S4A). RNA decay analysis by chasing nascent RNA labeled with ethyluridine (EU) showed that MEX3C increased the degradation rate of SOCS3 (Fig. 4B and C; Supplementary Figs. S4B and S4C), suggesting that MEX3C accelerates SOCS3 mRNA decay.

Figure 4.

MEX3C recruits CNOT7 to degrade SOCS3 mRNA. A, Vector or MEX3C overexpressing MHCC97L cells were treated with actinomycin D (5 μg/mL). RNA was isolated at the specified time point and SOCS3 was subsequently analyzed by qRT-PCR analysis. The half-life of the mRNA was tracked by calculating its level relative to the untreated cell. ACTB was used as a negative control. B, Working model showing the pulse-chase analysis of SOCS3 mRNA in the indicated HCC cells. Briefly, cells (RNA) were labeled with 0.2 mmol/L 5-acetyluridine (EU) for 2 hours (pulse). Next, the cells were washed with normal growth medium and continued to grow in unlabeled medium for 2 hours (chase). Samples were harvested and used for the click reaction. At this stage, only EU-labeled RNAs were tagged with biotin. The biotinylated RNA was pulled down using streptavidin beads. Finally, the captured RNA was transformed into cDNA and was analyzed by qRT-PCR analysis. C, Pulse-chase analysis results of SOCS3 mRNA degradation in the indicated MHCC97L cells. D, Schematic illustrations of the MEX3C truncated constructs. E, RIP assays were used to detect whether the RING-finger and KH domains are necessary for MEX3C to bind with SOCS3 mRNA. F, Western blotting analysis of HA-MEX3C after biotin-labeled SOCS3 RNA pulldown in the indicated cells. Dot blot indicates that the RNAs have been biotin-labeled. G, Western blotting analysis of HA-MEX3C in the MHCC97L cells transfected with indicated truncations after MS2bp-Flag-MS2bs–based pulldown. H, The cells were transfected with the indicated HA-MEX3C plasmids together with Flag-CNOT7 plasmids. Cell lysates were immunoprecipitated using an anti-Flag antibody, followed by immunoblotting with anti-HA antibodies. I, RIP assays followed by qRT-PCR analysis examining the interaction between CNOT7 and SOCS3 mRNA in cells transfected with the indicated truncations. J, Vector or the indicated HA-MEX3C overexpressing MHCC97L cells were treated with MG132 (10 μmol/L) for 6 hours before harvest. The level of ubiquitinated CNOT7 was detected by immunoblotting with anti-Ub antibodies. WCL, whole cell lysate. K, Top, schematic diagram of the deadenylation assay. Bottom, the indicated HA-MEX3C pulldowns were cultured with a 5′-luciferin–labeled RNA substrate for 2 hours to observe the deadenylation activity of CNOT7. L, The half-life of SOCS3 mRNA was traced in the indicated MHCC97L cells. M, qRT-PCR and Western blotting analysis of SOCS3 in the indicated HCC cells. N, Western blotting of p-JAK2, total JAK2, pSTAT3, and total STAT3 levels in the indicated cells. GAPDH was used as a loading control. O, Working model showing that MEX3C degraded SOCS3 mRNA by recruiting CNOT7 to the SOCS3 mRNA. Each error bar in A, C, E, I, L, and M represents the mean ± SD of three independent experiments. ***, P < 0.001.

Figure 4.

MEX3C recruits CNOT7 to degrade SOCS3 mRNA. A, Vector or MEX3C overexpressing MHCC97L cells were treated with actinomycin D (5 μg/mL). RNA was isolated at the specified time point and SOCS3 was subsequently analyzed by qRT-PCR analysis. The half-life of the mRNA was tracked by calculating its level relative to the untreated cell. ACTB was used as a negative control. B, Working model showing the pulse-chase analysis of SOCS3 mRNA in the indicated HCC cells. Briefly, cells (RNA) were labeled with 0.2 mmol/L 5-acetyluridine (EU) for 2 hours (pulse). Next, the cells were washed with normal growth medium and continued to grow in unlabeled medium for 2 hours (chase). Samples were harvested and used for the click reaction. At this stage, only EU-labeled RNAs were tagged with biotin. The biotinylated RNA was pulled down using streptavidin beads. Finally, the captured RNA was transformed into cDNA and was analyzed by qRT-PCR analysis. C, Pulse-chase analysis results of SOCS3 mRNA degradation in the indicated MHCC97L cells. D, Schematic illustrations of the MEX3C truncated constructs. E, RIP assays were used to detect whether the RING-finger and KH domains are necessary for MEX3C to bind with SOCS3 mRNA. F, Western blotting analysis of HA-MEX3C after biotin-labeled SOCS3 RNA pulldown in the indicated cells. Dot blot indicates that the RNAs have been biotin-labeled. G, Western blotting analysis of HA-MEX3C in the MHCC97L cells transfected with indicated truncations after MS2bp-Flag-MS2bs–based pulldown. H, The cells were transfected with the indicated HA-MEX3C plasmids together with Flag-CNOT7 plasmids. Cell lysates were immunoprecipitated using an anti-Flag antibody, followed by immunoblotting with anti-HA antibodies. I, RIP assays followed by qRT-PCR analysis examining the interaction between CNOT7 and SOCS3 mRNA in cells transfected with the indicated truncations. J, Vector or the indicated HA-MEX3C overexpressing MHCC97L cells were treated with MG132 (10 μmol/L) for 6 hours before harvest. The level of ubiquitinated CNOT7 was detected by immunoblotting with anti-Ub antibodies. WCL, whole cell lysate. K, Top, schematic diagram of the deadenylation assay. Bottom, the indicated HA-MEX3C pulldowns were cultured with a 5′-luciferin–labeled RNA substrate for 2 hours to observe the deadenylation activity of CNOT7. L, The half-life of SOCS3 mRNA was traced in the indicated MHCC97L cells. M, qRT-PCR and Western blotting analysis of SOCS3 in the indicated HCC cells. N, Western blotting of p-JAK2, total JAK2, pSTAT3, and total STAT3 levels in the indicated cells. GAPDH was used as a loading control. O, Working model showing that MEX3C degraded SOCS3 mRNA by recruiting CNOT7 to the SOCS3 mRNA. Each error bar in A, C, E, I, L, and M represents the mean ± SD of three independent experiments. ***, P < 0.001.

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Similar to other members of MEX3 protein family, MEX3C contains two KH RNA-binding domains and a RING-finger domain with E3 ubiquitin ligase activity (18). To further determine whether these domains of MEX3C were critical in destabilizing SOCS3 mRNA, we evaluated the interaction between SOCS3 and the corresponding MEX3C deletion mutants (Fig. 4D). Compared with wild-type MEX3C, the KH domains (AA232–387) deletion mutant, rather than the RING-finger domain (AA608–652) deletion mutant, significantly lost its ability to pull down SOCS3, implying that the KH domains were required for SOCS3 mRNA-binding capacity (Fig. 4EG).

We further explored the mechanism by which MEX3C regulates SOCS3 mRNA degradation. The CCR4-NOT deadenylase complex is a major regulator of the cytoplasmic degradation of eukaryotic mRNAs (39). In addition, MEX3C has been reported to interact with CNOT7, the central catalytic component of the CCR4-NOT deadenylase complex (18). The immunoprecipitation (IP) assays demonstrated that MEX3C interacted with CNOT7 (Fig. 4H). We further revealed that the KH domains, but not the RING-finger region, of MEX3C protein were crucial for its interaction with CNOT7 (Fig. 4H). MEX3C enhanced the enrichment of CNOT7 on SOCS3 mRNA in a KH domain-dependent manner (Fig. 4I).

Ubiquitination of CNOT7 has been shown to modulate its deadenylation activity (18); we thus examined the effect of different MEX3C mutants on CNOT7 ubiquitination level. Wild-type MEX3C remarkably promoted CNOT7 ubiquitination, whereas Ringless MEX3C lost ubiquitin ligase activity and the KH domain deletion mutant failed to alter the ubiquitination level of CNOT7 (Fig. 4J), suggesting that MEX3C interacted with CNOT7 via the KH domains and ubiquitinate CNOT7 dependent on the RING-finger domain. Subsequently, in vitro deadenylation assays using a specific RNA substrate (fluorescein-labeled) for CNOT7 were performed to observe the deadenylation activity of CNOT7 (Fig. 4K). Deadenylation substrate tended to degrade after HA-MEX3C IP, whereas this effect was not seen for the KH domains deleted-MEX3C or Ringless MEX3C (Fig. 4K), suggesting that the integrity of MEX3C protein was required for the deadenylation of RNA substrates. Consistently, knockdown of MEX3C reversed the downregulation of SOCS3 caused by CNOT7 overexpression (Supplementary Fig. S4D), whereas the KH domains or RING-finger domain deletion abolished the downregulation of SOCS3 by MEX3C even in the presence of CNOT7 overexpression (Supplementary Fig. S4E), indicating the importance of the MEX3C/CNOT7 complex in regulating SOCS3.

As expected, KH or RING-finger domain-deficient MEX3C mutants failed to degrade SOCS3 (Fig. 4L; Supplementary Fig. S4F) and downregulate SOCS3 expression (Fig. 4M). We also demonstrated that both the KH domains and RING-finger domain were essential for MEX3C-mediated activation of the JAK2/STAT3 pathway (Fig. 4N). SOCS3 was reported to block the activity of JAK2 and the activation of STAT3 either through direct interaction with JAK2 or the activated receptor. Indeed, MEX3C inhibited the interaction of SOCS3 with JAK2 while enhancing STAT3 binding to JAK2 or the receptor GP130 (Supplementary Figs. S4G and S4H). In conclusion, MEX3C binds with the 3′UTR of SOCS3 and recruits CNOT7 via its KH domains, whereas ubiquitination of CNOT7 by MEX3C's RING-finger promotes SOCS3 mRNA decay, leading to the activation of the JAK2/STAT3 pathway (Fig. 4O).

MEX3C promotes HCC metastasis in vitro and in vivo

The JAK2/STAT3 signaling can promote the invasion and migration of cancer cells, which are considered prerequisite steps for metastasis (40); we thus further investigated whether MEX3C regulated the invasiveness and motility of HCC cells. Matrix degradation assays was performed to examine whether MEX3C was involved in the extracellular matrix (ECM) degradation. ECM degradation was significantly inhibited by MEX3C-silenced cells and enhanced by MEX3C overexpressing cells (Fig. 5A). The results of transwell invasion assays and wound healing assays indicated that the invasion capacities and motility of HCC cells was enhanced in the MEX3C-upregulated group and decreased in the MEX3C-downregulated group compared with that in the control group (Fig. 5B; Supplementary Figs. S5A and S5B). These data demonstrate that MEX3C is essential for ECM degradation, and enhance invasiveness and motility of HCC cells.

Figure 5.

MEX3C promotes HCC metastasis in vitro and in vivo. A, Representative images (left) and quantification (right) of gelatin matrix proteolysis after 24 hours of cultivation. Shown are the overlay of Alexa Fluor 488 fluorescent gelatin (green) with dark holes (degradation) and F-actin (red). Scale bar, 2.5 μm. B, Quantification of the invasiveness of the indicated cells after 24 hours of cultivation in transwell matrix penetration assays. C, Orthotopic metastasis model. The indicated HCC cells (5 × 106) were injected into the left hepatic lobe of BALB/c nude mice. D, Intrahepatic and lung metastasis rate in different groups of animals. E and F Representative bioluminescence images of liver (E) and lung (F) in mice. G, Intrahepatic metastases of mice and representative hematoxylin and eosin staining images are shown, as indicated by an arrow. Scale bars, 800 μm; insets, 100 μm. H, Lung metastases of mice and representative images of hematoxylin and eosin staining of metastatic nodules in lung from different groups of animals. Scale bars, 200 μm. I and J, Quantitative analysis of visible surface metastatic lesions on the liver (I) and lung (J) in each group. K, qRT-PCR analysis of SOCS3 mRNA of liver tumor foci in the indicated mice. Each error bar in A and B represents the mean ± SD of three independent experiments. Each error bar in K represent the mean ± SD of tumor mouse models (n = 6/group). ***, P < 0.001.

Figure 5.

MEX3C promotes HCC metastasis in vitro and in vivo. A, Representative images (left) and quantification (right) of gelatin matrix proteolysis after 24 hours of cultivation. Shown are the overlay of Alexa Fluor 488 fluorescent gelatin (green) with dark holes (degradation) and F-actin (red). Scale bar, 2.5 μm. B, Quantification of the invasiveness of the indicated cells after 24 hours of cultivation in transwell matrix penetration assays. C, Orthotopic metastasis model. The indicated HCC cells (5 × 106) were injected into the left hepatic lobe of BALB/c nude mice. D, Intrahepatic and lung metastasis rate in different groups of animals. E and F Representative bioluminescence images of liver (E) and lung (F) in mice. G, Intrahepatic metastases of mice and representative hematoxylin and eosin staining images are shown, as indicated by an arrow. Scale bars, 800 μm; insets, 100 μm. H, Lung metastases of mice and representative images of hematoxylin and eosin staining of metastatic nodules in lung from different groups of animals. Scale bars, 200 μm. I and J, Quantitative analysis of visible surface metastatic lesions on the liver (I) and lung (J) in each group. K, qRT-PCR analysis of SOCS3 mRNA of liver tumor foci in the indicated mice. Each error bar in A and B represents the mean ± SD of three independent experiments. Each error bar in K represent the mean ± SD of tumor mouse models (n = 6/group). ***, P < 0.001.

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Next, we investigated whether MEX3C promoted HCC metastasis in vivo. Orthotopic liver implantation was performed to examine the effects of MEX3C on intrahepatic and extrahepatic metastasis in the mouse model. The vector, wild-type MEX3C, or MEX3C△KH-overexpressed HCC cells were injected into the left hepatic lobe of BALB/c nude mice separately (Fig. 5C) and after 60 days, the mice were euthanized and subjected to intrahepatic and pulmonary metastases examination because the lung is the most common distant metastatic organ of HCC. Overexpression of wild-type MEX3C, but not the MEX3C△KH mutant, dramatically increased the intrahepatic and pulmonary metastasis rate of HCC (Fig. 5D). We also observed a significant increase in the number of metastatic nodules on the liver and lungs of mice bearing tumors that overexpressed MEX3C rather than MEX3C△KH (Fig. 5EJ). Consistently, SOCS3 mRNA level was significantly decreased in MEX3C/tumors but not in MEX3C△KH/tumors (Fig. 5K). However, the mRNA levels of STAT3 targets were increased in the MEX3C-overexpressing tumors but not in tumors formed by MEX3C△KH-overexpressing cells (Supplementary Fig. S5C). Taken together, these results indicate that MEX3C contributes to metastasis of HCC cells by counteracting the effectiveness of SOCS3.

The SOCS3/JAK2/STAT3 axis is essential for MEX3C-mediated metastasis

To further investigated whether the activation of the SOCS3/JAK2/STAT3 axis is indispensable for MEX3C-mediated HCC metastasis, we used SH-4–54, a specific and potent inhibitor of STAT3 (41), to block the STAT3 signaling pathway in MEX3C-overexpressing cells. SH-4–54 treatment significantly counteracted MEX3C-mediated ECM degradation (Fig. 6A), and inhibited invasiveness (Fig. 6B) and motility (Supplementary Fig. S6A) of MHCC97L cells that overexpressed MEX3C. Similar results were observed in MHCC97H cells (Fig. 6C and D; Supplementary Fig. S6B). Consistently, the expression of STAT3 targets were greatly reduced in MEX3C-overexpressing HCC cells treated with SH-4–54 (Supplementary Figs. S6C and S6D). In vivo experiments results showed that SH-4–54 treatment attenuated metastasis of HCC cells induced by MEX3C (Fig. 6E and F). These results indicate that the JAK2/STAT3 pathway is essential for MEX3C-mediated metastasis.

Figure 6.

The SOCS3/JAK2/STAT3 axis is essential for MEX3C-mediated metastasis. A, Representative images (left) and quantification (right) of gelatin matrix proteolysis in the indicated MHCC97L cells. Each group was treated with DMSO. Scale bar, 2.5 μm. B, SH-4–54 treatment (10 μmol/L) or restoring SOCS3 expression abolished MEX3C-mediated invasiveness of MEX3C-overexpressing MHCC97L cells. Each group was treated with DMSO. Scale bar, 100 μm. C, Representative images (left) and quantification (right) of gelatin matrix proteolysis in the indicated MHCC97H cells. Each group was treated with DMSO. Scale bar, 2.5 μm. D, SH-4–54 treatment (10 μmol/L) or restoring SOCS3 expression inhibited the invasiveness of MHCC97H cells. Each group was treated with DMSO. Scale bar, 100 μm. E and F, Mice were inoculated with vector, MEX3C-overexpressing, or MEX3C/SOCS3-overexpressing MHCC97L cells (5 × 106) in the left lobe of liver with or without intraperitoneal injection of SH-4–54 (10 mg/kg). Two months after inoculation, the number of metastases on the surface of the liver and lung was counted. G, qRT-PCR analysis of SOCS3 mRNA of liver tumor foci in the indicated mice. H, Representative images of MEX3C, SOCS3, and pSTAT3 IHC staining in HCC specimens in the indicated mice. Scale bars, 50 μm; insets, 20 μm. I and J, The number of metastases on the surface of the indicated liver and lung was counted. Each error bar in AD represents the mean ± SD of three independent experiments. Each error bar in G represents the mean ± SD of tumor mouse models (n = 6/group). ***, P < 0.001.

Figure 6.

The SOCS3/JAK2/STAT3 axis is essential for MEX3C-mediated metastasis. A, Representative images (left) and quantification (right) of gelatin matrix proteolysis in the indicated MHCC97L cells. Each group was treated with DMSO. Scale bar, 2.5 μm. B, SH-4–54 treatment (10 μmol/L) or restoring SOCS3 expression abolished MEX3C-mediated invasiveness of MEX3C-overexpressing MHCC97L cells. Each group was treated with DMSO. Scale bar, 100 μm. C, Representative images (left) and quantification (right) of gelatin matrix proteolysis in the indicated MHCC97H cells. Each group was treated with DMSO. Scale bar, 2.5 μm. D, SH-4–54 treatment (10 μmol/L) or restoring SOCS3 expression inhibited the invasiveness of MHCC97H cells. Each group was treated with DMSO. Scale bar, 100 μm. E and F, Mice were inoculated with vector, MEX3C-overexpressing, or MEX3C/SOCS3-overexpressing MHCC97L cells (5 × 106) in the left lobe of liver with or without intraperitoneal injection of SH-4–54 (10 mg/kg). Two months after inoculation, the number of metastases on the surface of the liver and lung was counted. G, qRT-PCR analysis of SOCS3 mRNA of liver tumor foci in the indicated mice. H, Representative images of MEX3C, SOCS3, and pSTAT3 IHC staining in HCC specimens in the indicated mice. Scale bars, 50 μm; insets, 20 μm. I and J, The number of metastases on the surface of the indicated liver and lung was counted. Each error bar in AD represents the mean ± SD of three independent experiments. Each error bar in G represents the mean ± SD of tumor mouse models (n = 6/group). ***, P < 0.001.

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Simultaneously, we found that restoring SOCS3 expression significantly reversed the ECM degradation, invasiveness, and motility abilities enhanced by MEX3C overexpression (Fig. 6AD; Supplementary Figs. S6A and S6B). STAT3 targets expression was significantly decreased after restoring SOCS3 expression (Supplementary Figs. S6C and S6D). In addition, restoration of SOCS3 expression attenuated MEX3C-induced tumor metastasis in vivo (Fig. 6E and F). We also detected SOCS3 levels in mouse tissues and found that SOCS3 expression restoration remarkably reduced pSTAT3 levels (Fig. 6G and H). Consistently, mRNA levels of STAT3 targets were decreased in HCC tissues with restored SOCS3 (Supplementary Fig. S6E).

Furthermore, we observed that SH-4–54 treatment alone or in combination with MEX3C inhibition resulted in significant decreased STAT3 activity in MHCC97H cells (Supplementary Fig. S6F). However, silencing MEX3C did not cause further inhibitory effects on ECM degradation, invasiveness, and motility in SH-4–54-treated cells (Supplementary Figs. S6G–S6I). In vivo experiments showed that either SH-4–54 treatment alone or in combination with MEX3C inhibition showed the similar effects on reduction of the number of liver and lung metastases and the expression of STAT3 targets in tumor tissues of mice (Fig. 6I and J; Supplementary Fig. S6J). These findings further supported the notion that MEX3C promoted HCC metastasis through activation of the JAK2/STAT3 pathway and suggest that targeting MEX3C or inhibiting the JAK2/STAT3 pathway may suppress HCC metastasis.

Clinical relevance of MEX3C

ASOs have recently been recognized as powerful therapeutic tools because of their target specificity (42, 43). ASOs are short (10–30bp) single-stranded nucleic acids that bind to RNA via Watson–Crick base pairing and perturb protein production by inducing the degradation of target RNAs or altering RNA metabolism (43). Currently, there are no direct, small molecule inhibitors of MEX3C for clinical application; we therefore developed MEX3C-specific second-generation ASOs to treat HCC metastasis. A universal nonsilencing ASO targeting no known sequence in human genome was used as the negative control (24). The results of qRT-PCR and Western blotting analysis showed that both ASO-1 and ASO-2 significantly decreased MEX3C mRNA and protein levels (Fig. 7A and B; Supplementary Figs. S7A and 7B).

Figure 7.

Clinical relevance of MEX3C. A,MEX3C mRNA expression was assessed by qRT-PCR analysis. MEX3C-overexpressing MHCC97L cells were transfected with the ASO negative control (ASO-NC), or MEX3C-specific ASOs at the indicated concentration. A universal nonsilencing ASO was used as ASO negative control (ASO-NC). B, Seventy-two hours after transfecting the indicated ASO, the MEX3C protein level of the indicated MEX3C-overexpressing MHCC97L cells was evaluated using Western blotting analysis. C, Western blotting analysis of SOCS3, p-JAK2, total JAK2, pSTAT3, and total STAT3 levels in MEX3C-overexpressing MHCC97L cells, with or without anti-MEX3C ASO-1 treatment (100 nmol/L). D, Representative images (left) and quantification (right) of gelatin matrix proteolysis in the MEX3C-overexpressing MHCC97L cells, with or without anti-MEX3C ASO-1 treatment. Scale bar, 2.5 μm. E, Anti-MEX3C ASO-1 treatment inhibited the invasiveness of MEX3C-overexpressing MHCC97L cells. Scale bar, 100 μm. F and G, Intravenously injected anti-MEX3C ASO-1 (50 mg/kg, 3 times/week) into MEX3C-overexpressing MHCC97L HCC xenografts. Two months after inoculation, the number of visible nodules on the liver and lung surface was counted. H, qRT-PCR analysis of SOCS3 mRNA of the indicated liver tumor tissues. I, Representative images of MEX3C, SOCS3, and pSTAT3 IHC staining in the indicated liver cancer tissues. Scale bars, 50 μm; insets, 20 μm. J, Representative images of MEX3C, SOCS3, p-JAK2, and pSTAT3 IHC staining in specimens from patients with HCC with or without metastasis. Scale bars, 50 μm; insets, 20 μm. K, The correlation between MEX3C and SOCS3, p-JAK2, or pSTAT3 expression was tested using two-sided χ2 test and Cramer V. Each error bar in A and D and E represents the mean ± SD of three independent experiments. Each error bar in H represents the mean ± SD of tumor mouse models (n = 6/group). ***, P < 0.001.

Figure 7.

Clinical relevance of MEX3C. A,MEX3C mRNA expression was assessed by qRT-PCR analysis. MEX3C-overexpressing MHCC97L cells were transfected with the ASO negative control (ASO-NC), or MEX3C-specific ASOs at the indicated concentration. A universal nonsilencing ASO was used as ASO negative control (ASO-NC). B, Seventy-two hours after transfecting the indicated ASO, the MEX3C protein level of the indicated MEX3C-overexpressing MHCC97L cells was evaluated using Western blotting analysis. C, Western blotting analysis of SOCS3, p-JAK2, total JAK2, pSTAT3, and total STAT3 levels in MEX3C-overexpressing MHCC97L cells, with or without anti-MEX3C ASO-1 treatment (100 nmol/L). D, Representative images (left) and quantification (right) of gelatin matrix proteolysis in the MEX3C-overexpressing MHCC97L cells, with or without anti-MEX3C ASO-1 treatment. Scale bar, 2.5 μm. E, Anti-MEX3C ASO-1 treatment inhibited the invasiveness of MEX3C-overexpressing MHCC97L cells. Scale bar, 100 μm. F and G, Intravenously injected anti-MEX3C ASO-1 (50 mg/kg, 3 times/week) into MEX3C-overexpressing MHCC97L HCC xenografts. Two months after inoculation, the number of visible nodules on the liver and lung surface was counted. H, qRT-PCR analysis of SOCS3 mRNA of the indicated liver tumor tissues. I, Representative images of MEX3C, SOCS3, and pSTAT3 IHC staining in the indicated liver cancer tissues. Scale bars, 50 μm; insets, 20 μm. J, Representative images of MEX3C, SOCS3, p-JAK2, and pSTAT3 IHC staining in specimens from patients with HCC with or without metastasis. Scale bars, 50 μm; insets, 20 μm. K, The correlation between MEX3C and SOCS3, p-JAK2, or pSTAT3 expression was tested using two-sided χ2 test and Cramer V. Each error bar in A and D and E represents the mean ± SD of three independent experiments. Each error bar in H represents the mean ± SD of tumor mouse models (n = 6/group). ***, P < 0.001.

Close modal

Next, we investigated whether ASOs-mediated MEX3C reduction could suppress HCC metastasis. The activation of the JAK2/STAT3 signaling was remarkably blocked in the MEX3C-overexpressing HCC cells when treated with anti-MEX3C ASO-1 (Fig. 7C; Supplementary Fig. S7C). Anti-MEX3C ASO-1 administration drastically reduced the ECM degradation, invasiveness, and motility abilities of MEX3C-overexpressing HCC cells (Fig. 7D and E; Supplementary Figs. S7D–S7F). The mRNA levels of STAT3 targets were significantly downregulated after anti-MEX3C ASO-1 treatment (Supplementary Figs. S7G and S7H). The therapeutic effect of anti-MEX3C ASO-1 against tumor metastasis was evaluated in MEX3C-overexpressing MHCC97L HCC xenografts. Anti-MEX3C ASO-1 was intravenously injected into the hepatic tumor bearing mice for 2 months at a dose of 50 mg/kg, three times a week. As shown in Fig. 7F and G, the burdens of intrahepatic and pulmonary metastasis were significantly alleviated by ASO-1 treatment. As expected, ASO-1 remarkably reversed the SCOS3 expression and pSTAT3 levels in mouse tumors (Fig. 7H and I). Similarly, STAT3 targets expression was decreased in tumor tissues treated with anti-MEX3C ASO-1 (Supplementary Fig. S7I). Collectively, these findings indicated the potential of anti-MEX3C ASO-1 in HCC treatment.

Finally, we assessed the MEX3C/SOCS3/JAK2/STAT3 axis's clinical relevance in HCC specimens. IHC staining was performed on 202 paraffin-embedded, archived HCC samples. The IHC staining and correlation analysis showed that MEX3C was inversely associated with SOCS3 expression levels but positively correlated with p-JAK2 and pSTAT3 levels in human tumor tissues, supporting the notion that MEX3C contributed to the JAK2/STAT3 activation by suppressing SOCS3 in HCC (Fig. 7J and K).

Taken together, MEX3C interacts with the SOCS3 3′UTR and recruits CNOT7 via MEX3C's KH domains and ubiquitinates CNOT7 via a RING finger to accelerate SOCS3 mRNA decay. Overexpression of MEX3C promotes ECM degradation, invasion, and migration of tumor cells, ultimately leading to HCC metastasis (Fig. 8). This study highlights that targeting MEX3C may be a promising strategy against HCC metastasis by blocking the activation of the JAK2/STAT3 signaling pathway.

Figure 8.

Study model. RNA-binding protein MEX3C binds with the SOCS3 3′UTR and recruits CNOT7 via MEX3C's KH domains to accelerate SOCS3 mRNA decay by ubiquitinating CNOT7 in a RING-finger dependent manner. Thus, the MEX3C/CNOT7 complex activates the JAK2/STAT3 signaling pathway by downregulating SOCS3. Overexpression of MEX3C promotes ECM degradation, invasion, and motility of tumor cells, ultimately leading to intrahepatic and pulmonary metastasis of HCC.

Figure 8.

Study model. RNA-binding protein MEX3C binds with the SOCS3 3′UTR and recruits CNOT7 via MEX3C's KH domains to accelerate SOCS3 mRNA decay by ubiquitinating CNOT7 in a RING-finger dependent manner. Thus, the MEX3C/CNOT7 complex activates the JAK2/STAT3 signaling pathway by downregulating SOCS3. Overexpression of MEX3C promotes ECM degradation, invasion, and motility of tumor cells, ultimately leading to intrahepatic and pulmonary metastasis of HCC.

Close modal

Tumor metastasis independently predicts poor prognosis and is one of the main causes of death in patients with HCC (1–4). It is in urgent need to identify the pivotal molecules that driving HCC metastasis and developing promising targeted therapies to improve the clinical outcome. In our study, we revealed that MEX3C was distinctly upregulated in metastatic HCC, predicting unfavorable outcomes in patients. Mechanistic analyses demonstrated that MEX3C facilitated SOCS3 mRNA degradation, resulting in constant activation of the JAK2/STAT3 signal pathway. Intravenous administration of a MEX3C-specific ASO evidently decreased tumor metastatic in vivo. Our findings highlight a novel mechanism of mRNA decay targeting SOCS3 to constantly activate the JAK2/STAT3 signaling, suggesting that MEX3C as a potent prognostic biomarker and a potential druggable target against progressive metastasis in HCC.

Activation of the JAK2/STAT3 signaling is closely associated with the development and progression of HCC, suggesting that perturbation of this signaling pathway might be a potential strategy (5–8). Activated-JAK2 kinase catalyzes phosphorylation of the GP130 receptor to recruit STAT3 and phosphorylate STAT3, and then phosphorylated STAT translocates into the nucleus (8). We previously reported that AGK interacts with the JH2 domain of JAK2 and blocks JH2-mediated self-inhibition to maintain sustained activation of the JAK2/STAT3 signaling (44). In addition to self-inhibition of JAK2, continuous activation of the JAK2/STAT3 signaling is controlled by negative regulators, mainly including PIAS, PTPs, and SOCS family member (8, 45). For instance, PIAS can block the DNA binding activity of STAT3 (8, 45); and PTPs dephosphorylate STAT3 in the cytoplasm and nucleus (8). Notably, SOCS3 has been identified as a major negative feedback regulator of the JAK2/STAT3 signaling, because it blocks the activity of JAK2 kinase and STAT3 protein, either by the direct interaction with JAK2 kinase or through the phosphorylated receptor (8). More importantly, our study showed that SOCS3 restoration reversed MEX3C-mediated constant activation of the JAK2/STAT3 signaling and HCC metastasis, suggesting the importance of SOCS3 in HCC progression. Therefore, further investigation of SOCS3’s regulatory mechanisms might provide a potentially effective target for HCC treatment.

SOCS3 protein can be detected in normal adult tissues, such as the spleen and liver, but it is frequently absent or inactivated, and generally functions as a tumor suppressor in various cancers, including HCC (46–48). Consistently, we confirmed that SOCS3 was downregulated in HCC cells and tissues. As a regulatory factor, SOCS3 expression is strictly controlled at multiple levels (47, 49, 50). For example, factors such as c-Fos, c-Jun, and FOXO3 have been reported to be responsible for SOCS3 transcriptional regulation (47, 50). At the protein level, SOCS3 can undergo non-proteasome and proteasome-mediated degradation (50, 51). However, posttranscriptional regulation of SOCS3 in HCC remains to be further explored. In this study, we demonstrated that the MEX3C/CNOT7 complex destabilizes SOCS3 mRNA to downregulate SOCS3 levels in HCC cells. Mechanistically, MEX3C binds to the MRE motif in the 3′UTR of SOCS3 and recruits CNOT7 to the SOCS3. Subsequently, MEX3C ubiquitinates CNOT7 to promote the deadenylation of the SOCS3. Our findings reveal a novel mRNA decay-mediated mechanism for the disruption of SOCS3 to activate the JAK2/STAT3 signaling.

However, no inhibitors directly targeting STAT3 have been approved by the FDA for clinical application so far, probably owing to a combination of low potency and poor specificity (52, 53). Intriguingly, RBPs have emerged recently as alternative therapeutic targets for cancer because of their critical role in regulating the activation of cancer-related pathways (11–13). Several clinical trials are underway evaluating the anti-tumor efficacy of RNA interference-based approaches, such as ASOs (14, 22, 43). Although ASOs targeting RBPs against tumors are not available in clinical practice, some ASOs targeting RBPs have been approved by the FDA to treat neurodegenerative diseases (42, 43); therefore, we anticipate ASOs targeting RBPs as promising therapeutic avenues in cancer therapy. In this study, we designed and developed a MEX3C-specific second-generation ASO that distinctly reduced MEX3C expression. Anti-MEX3C ASO-1 administration remarkably blocked the activation of the JAK2/STAT3 pathway. Intravenously injection of anti-MEX3C ASO-1 significantly impeded cancer metastasis in MEX3C-overexpressing MHCC97L HCC xenografts. Our study provides the basis for advancing MEX3C ASOs into clinical trials to treatment HCC metastasis.

MEX3C was recently identified as a novel RNA-binding ubiquitin E3 ligase, responsible for the posttranscriptional regulation of target genes (17–19). It has been reported that MEX3C is elevated in several cancer types and promotes the tumorigenesis and progression of cancer (20, 21). In our study, we found that MEX3C was upregulated in metastatic HCC and predicted unfavorable outcomes. By enhancing ECM degradation, invasiveness, and motility of HCC cells, MEX3C promoted the intrahepatic and lung metastasis of HCC. MEX3C reduced SOCS3 expression via a posttranscriptional mechanism to activate the JAK2/STAT3 signaling pathway. Specifically, MEX3C interacted with the MRE motif in the 3′UTR of SOCS mRNA via its KH domains, and accelerated SOCS3 mRNA decay by recruiting and ubiquitinating CNOT7. Previous evidence suggested that ubiquitination of the CNOT7 subunit enhanced its deadenylation activity (18). Indeed, we demonstrated that MEX3C interacted with CNOT7 via its KH domains and ubiquitinated CNOT7 in a RING-dependent manner, indicating that the integrity of MEX3C protein is necessary for CNOT7-mediated SOCS3 degradation. These pieces of evidence collectively indicated the importance of ubiquitin in regulating mRNA stability. Further research on the ubiquitin-dependent regulation of MEX3C and its mRNA substrate will provide insights into how ubiquitin controls mRNA degradation. In this study, apart from SOCS3, we also identified many other mRNAs that might interact with MEX3C. It would be of great value to further explore whether these genes contribute to the tumor-promoting effect of MEX3C in HCC.

To sum up, our study reveals that MEX3C acts as an oncogene to promote HCC metastasis by accelerating SOCS3 mRNA degradation via recruiting CNOT7 to the SOCS3 mRNA, thus leading to activation of the JAK2/STAT3 signaling pathway and enhancing tumor metastasis. Elucidating the precise role of MEX3C in SOCS3 mRNA decay and HCC metastasis will contribute to our deeper understanding of STAT3 sustained activation in cancer progression, and develop new therapeutic strategies against HCC metastasis.

No author disclosures were reported.

Y. Xiao: Data curation, software, validation, methodology. Y. Li: Data curation, software, validation, methodology. D. Shi: Data curation, software, validation, methodology. X. Wang: Data curation, validation. S. Dai: Data curation, validation. M. Yang: Data curation, validation. L. Kong: Data curation, validation. B. Chen: Data curation, validation. X. Huang: Data curation, validation. C. Lin: Data curation, validation. W. Liao: Data curation, validation. B. Xu: Data curation, validation. X. Chen: Data curation, validation. L. Wang: Data curation, validation. X. Chen: Data curation, validation. Y. Ouyang: Data curation, validation. G. Liu: Conceptualization, supervision, writing–original draft, project administration, writing–review and editing. H. Li: Conceptualization, supervision, writing–original draft, project administration, writing–review and editing. L. Song: Conceptualization, supervision, writing–original draft, project administration, writing–review and editing.

This work was supported by the National Key Research and Development Program of China (No. 2020YFA0509400 to J. Pan), National Natural Science Foundation of China (No. 82072609 to L. Song; 81602701 to H. Li; 81974443 to H. Li; 22174121 to G. Liu; 81872401 to W. Liao; and 82173289 to W. Liao), and the Natural Science Foundation of Guangdong Province (No. 2019A1515010298 to S. Dai).

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

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Supplementary data