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. 2025 Mar 20;151(3):117. doi: 10.1007/s00432-025-06163-4

NSUN5 promotes cholangiocarcinoma progression by enhancing GLS mRNA stabilization

Ming Shu 1, Kunpeng Guo 2, Yikai Huang 2, Weishan Wang 2,✉
PMCID: PMC11926023  PMID: 40113612

Abstract

Background

NSUN5, also known as NOP2/Sun domain 5, is a pivotal RNA methyltransferase that catalyzes the formation of 5-methylcytosine (m5C). Cuproptosis, induced by elevated copper concentrations, is under investigation as a potential therapeutic strategy for cancer treatment. Despite this, the specific roles and the molecular mechanisms underlying Cuproptosis and NSUN5-mediated m5C modification in cholangiocarcinoma (CCA) remain to be fully elucidated.

Methods

Human tissue samples were collected to assess the expression levels of NSUN5 in CCA. In vitro functional assays were conducted to evaluate the biological function of NSUN5. The functional mechanism of NSUN5 on glutaminase (GLS) was investigated using RNA pull-down, RNA immunoprecipitation, molecular docking, and RNA stability assays.

Results

This study identified an upregulation of NSUN5 in CCA tissues. The knockdown of NSUN5 diminished the proliferation, migration, and invasion capabilities of CCA cells in vitro. In contrast, the overexpression of NSUN5 enhanced the growth and metastasis of CCA cells. Additionally, an increased copper content was detected in CCA tissues, which correlated with aggressive clinical features. CCA cells exhibited resistance to cuproptosis by upregulating GLS expression. Functionally, NSUN5 was found to positively modulate GLS expression. The NSUN5-mediated m5C modification at site 137 C on the GLS mRNA sequence stabilizes the GLS mRNA, leading to an accumulation of GLS within cells.

Conclusions

Our findings highlight the critical role of NSUN5 in CCA progression through m5C-dependent stabilization of the GLS transcript, suggesting a potential targeted therapeutic strategy for CCA.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00432-025-06163-4.

Keywords: Cholangiocarcinoma, 5-methylcytosine, NSUN5, Cuproptosis, GLS

Introduction

Cholangiocarcinoma (CCA) is a malignant tumor originating from hepatic and biliary epithelial cells, and its global incidence is increasing (Ilyas et al. 2023). The low five-year overall survival rate associated with CCA has garnered extensive scientific and clinical interest (Brindley et al. 2021). RNA modification, an epigenetic regulatory mechanism, has been garnering increasing attention in recent years (Barbieri and Kouzarides 2020). 5-methylcytosine (m5C), a critical post-transcriptional modification of mammalian mRNA, is catalyzed by the NOP2/Sun domain (NSUN) RNA methyltransferase family (Chen et al. 2021; Li et al. 2022). Recent studies suggest that aberrant m5C modification in mRNA is linked to the pathogenesis and progression of bladder and gastric cancers (Chen et al. 2019; Fang et al. 2023). However, the role of m5C modification in CCA remains to be elucidated. Consequently, in-depth studies on the regulation and function of m5C modification could potentially uncover the underlying mechanisms of CCA progression and pave the way for the development of novel therapeutic strategies.

Copper is an essential trace element that plays a critical role in cellular growth and metabolic processes (Bossak et al. 2018; Fukai et al. 2018). Dysregulation of copper homeostasis is closely associated with the initiation and progression of various malignancies, including breast and colorectal cancers (Stepien et al. 2017; Pavithra et al. 2015). Studies have demonstrated that elevated serum copper levels in cancer patients are correlated with tumor grading and resistance to chemotherapy (Majumder et al. 2009). When copper concentrations surpass a specific threshold, they exhibit toxicity and induce a distinct form of cell death termed cuproptosis (Tsvetkov et al. 2022). Cuproptosis is characterized by the direct interaction of copper with lipoylated components in the tricarboxylic acid cycle, resulting in copper accumulation, subsequent depletion of iron-sulfur cluster proteins, protein-induced cellular stress, and ultimately, cell death. Although evidence implicates copper ions in tumorigenesis, research into the specific role of copper ions in the pathogenesis of specific tumor types, such as CCA, remains limited. Therefore, further investigation is imperative to clarify the precise role of copper ions in tumor biology and to explore their potential therapeutic applications.

The study identified a significant upregulation of NSUN5 expression in CCA. NSUN5 mediates the enrichment of glutaminase (GLS) in CCA by introducing a m5C modification at the cytosine 137 site within the untranslated region of the GLS mRNA. This regulatory mechanism inhibits cuproptosis in CCA and promotes disease progression. Our findings establish a correlation between m5C modification and cuproptosis in CCA, shedding light on the underlying molecular mechanisms and indicating a potential therapeutic target for the treatment of CCA.

Materials and methods

Bioinformatic analysis

Microarray expression data (GSE107943) were retrieved from the Gene Expression Omnibus. Clinical information and bulk RNA-sequencing data for CCA were obtained from The Cancer Genome Atlas. Differential expression analysis was performed using the limma R package (Ritchie et al. 2015). Pearson correlation coefficients were calculated to assess the relationship between NSUN5 and GLS expression levels. A genetic association analysis of NSUN5 and GLS was conducted utilizing data from the FinnGen study (Kurki et al. 2023).

Human samples, cell culture and transfection

A total of four intrahepatic CCA tissues and four paracancerous tissues were collected from Shanghai Electric Power Hospital. Human samples were obtained with informed consent, and experiments involving human specimens were approved by our institution's research ethics committee.

Human intrahepatic CCA cells (HCCC-9810) were sourced from Procell Biotechnology Co., Ltd. (Wuhan, China) and cultured in DMEM supplemented with 10% fetal bovine serum (v/v), penicillin G (100 units/mL), and streptomycin (100 μg/mL). The cell line was identified by short tandem repeat analysis (Supplemental file 1). Lentiviral particles containing NSUN5 overexpression (OE), NSUN5 knockout (KO), GLS knockout (KO), and double mutants of NSUN5 were procured from Genechem (Shanghai, China). Transfections were carried out according to the manufacturer's protocol. In brief, cells were seeded at a density of 1 × 105 per well in a 24-well plate. Before transfection with lentivirus, the cell number was adjusted to approximately 2 × 105 per well. The frozen virus and its corresponding empty vector control were thawed on ice. The amount of virus was calculated based on the MOI value, and the virus solution along with Polybrene (5 µg/mL) was added to the culture medium. After mixing well, the culture system was incubated for 12 h. The cell status was observed, and if there was no significant change, the medium was replaced with fresh medium after 12 h. After 72 h of transfection, antibiotics were added to the culture medium for cell selection. Subsequently, the cells were observed regularly and the medium was changed until the cells with stable viral transfection were selected. For the transfection of NSUN5, puromycin (5 µg/mL) was used for selection. For the transfection of GLS, neomycin (500 µg/mL) was used for selection.

Polymerase reaction (PCR) and Western blot

Cells were lysed using TRIzol reagent, and PCR was conducted to assess mRNA expression levels as previously described (Li et al. 2024). GAPDH served as a control, and relative mRNA expression levels were quantified using the 2–ΔΔCt method. Primer sequences are provided in Supplemental Table 1.

RNA immunoprecipitation assays were performed following the manufacturer's instructions using the RNA Immunoprecipitation Kit (BersinBio, China). Briefly, 1 × 107 cells were collected and lysed in 0.9 mL polysome lysis buffer supplemented with protease inhibitor and RNase inhibitor. The lysates were treated with DNase to remove DNA contamination. For immunoprecipitation, the lysates were incubated with antibodies (1: 200) overnight at 4 °C using a vertical rotator mixer at 10 rpm to ensure thorough mixing. Protein A/G magnetic beads (20 µL) were then added to capture the antibody-RNA–protein complexes, and the mixture was incubated for an additional one hour at 4 °C with gentle rotation using the same vertical rotator mixer. The beads were washed sequentially with polysome washing buffer 1 and polysome washing buffer 2 to remove nonspecific binding. The RNA–protein complexes were eluted using polysome elution buffer. The immunoprecipitated RNA was purified by phenol–chloroform extraction and ethanol precipitation. The purified RNA was subsequently analyzed by PCR for downstream RNA detection.

For Western blot analysis, cells were lysed in a buffer containing proteinase and phosphatase inhibitors. Cell lysates were subjected to SDS-PAGE, transferred onto membranes, and incubated with specific antibodies for protein visualization. GAPDH served as a control, and the antibodies used are detailed in Supplemental Table 2.

RNA pull-down assays were conducted using the RNA pulldown Kit (BersinBio, China). Biotin-labeled mRNA or a random oligo probe was first denatured at 90 °C for 2 min and then cooled on ice for 2 min to form secondary structures. The probe was then incubated with 40 µL of streptavidin magnetic beads in a total volume of 300 µL containing 2 × TES buffer at room temperature for 30 min with gentle rotation. The cell lysates, prepared in RIP buffer supplemented with protease inhibitors and DNase, were incubated with the probe-beads complex at 4 °C overnight to allow RNA-associated proteins to bind to the RNA. After three washes with NT2 buffer at 4 °C, the RNA–protein complexes were eluted from the beads using protein elution buffer containing DTT at 37 °C for 2 h with intermittent mixing. The eluted complexes were analyzed by Western blot.

CCK-8 and flow cytometry

In CCK-8 assays, cells were seeded at a density of 1 × 102 cells per well in a 96-well plate. Subsequently, 10 µl of CCK-8 reagent was added at specific time points, and the optical density (OD) was measured at 450 nm after a one-hour incubation at 37 °C.

For apoptosis detection, cell suspensions were prepared in phosphate-buffered saline, and the Annexin V-FITC Apoptosis Detection Kit (Vazyme, China) along with flow cytometry were employed. Cells located in the right quadrants (Annexin V positive) were classified as apoptotic.

Cell migration and invasion assay

For the migration assay, 1 × 104 cells were seeded in the upper chamber and incubated with serum-free medium, while culture medium containing 10% FBS was added to the basolateral chamber. After 24 h, cells were fixed with 4% paraformaldehyde for 10 min, rinsed with PBS, and stained with 0.1% crystal violet for 10 min. Stained cells were photographed in three random visual fields and analyzed using ImageJ software.

For invasion assays, Matrigel from Corning (USA) was thawed at 4 °C overnight. A 100 µL Matrigel solution diluted in serum-free medium was applied to the upper chamber and allowed to solidify at 37 °C for 30 min. Subsequently, 1 × 104 cells were placed in the upper chamber for the invasion assay.

m5C quantification and Immunofluorescence

The global m5C level was assessed using the MethylFlash™ 5-mC RNA Methylation ELISA Easy Kit (Fluorometric) (EpiGentek, USA). In each well, 100 µl of binding solution and 200 ng of total RNA sample were added, followed by incubation at 37 °C for 90 min to allow RNA binding. Subsequently, 50 µl of m5C Detection Complex Solution, containing the m5C antibody, was added to each well after washing. After a 50-min incubation at room temperature, the diluted m5C antibody was removed. The wells were then incubated with Fluorescence Development Solution at room temperature for 2–4 min, away from direct light. The fluorescence signal was read by a microplate reader set at 530ex/590em nm within 2 to 10 min.

For immunofluorescence, cells were washed with phosphate-buffered saline and fixed with 4% paraformaldehyde for 10 min at room temperature. Subsequently, cells were permeabilized with 0.5% Triton X-100 for 20 min at room temperature, blocked, and incubated with the primary antibody overnight at 4 °C. Following this, cells underwent a washing step and were then incubated with a fluorochrome-conjugated secondary antibody for 1 h at room temperature, followed by DAPI staining. Image acquisition was performed using confocal microscopy.

RNA stability assays and molecular docking

For RNA stability assays, cells were plated in 6-well dishes and exposed to actinomycin D (5 μg/mL) (Sigma-Aldrich, USA) for 1, 3, and 6 h. In the negative control group, DMSO was added at 0 h. Subsequently, total RNA was extracted and analyzed via PCR.

The sequence of human NSUN5 was retrieved from the UniProt database and modeled through AlphaFold 3. The mRNA sequence of human GLS was obtained from the National Center for Biotechnology Information. The transcript analyzed in this study is NM_014905, with a length of 4840 bp. AlphaFold 3 was used to assess the interaction between NSUN5 and GLS mRNA (Abramson et al. 2024).

Xenograft tumor model in nude mice

Four-week-old male BALB/c nude mice were procured from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). These animals were housed in a temperature-controlled environment maintained at 23–25 °C with a 12-h light–dark cycle, and they had ad libitum access to both water and food. The nude mice were subcutaneously inoculated with 1 × 105 stably transfected HCCC-9810 cells or control cells. Two weeks post-inoculation, all mice were euthanized, and the xenografts were excised and weighed. Tumor volume was determined using the following formula: Volume (mm3) = length × width2 × 0.5. The animal experimentation was conducted with the approval of the research ethics committee of our institution (Approval No. 2024–008).

Statistical analysis

All analyses were conducted using R software (version 4.4.0). Data are presented as mean values ± standard deviation from three or more independent experiments. Group differences were evaluated using either a two-tailed Student’s t-test or a Mann–Whitney U test. Statistical significance was defined as P < 0.05.

Results

NSUN5 mediates m5C modification to promote the progression of CCA

We initially assessed the expression levels of the NSUN family members in CCA using publicly available databases. Analysis of data from The Cancer Genome Atlas (TCGA) revealed that, with the exception of NSUN6, the expression levels of other NSUN family members were significantly elevated in CCA (Fig. 1A). In the microarray dataset GSE107943, NSUN5 expression was found to be upregulated in CCA, while NSUN6 expression was downregulated (Fig. 1B). The expression patterns of NSUN family members were visualized in Fig. 1C, D. Furthermore, we examined the expression of the NSUN family in clinical samples, and the data indicated that only the mRNA expression of NSUN5 was significantly increased in CCA (n = 4) (Fig. 1E). Additionally, subsequent experimental results demonstrated a significant elevation in NSUN5 protein levels (n = 4) (Fig. 1F). Consequently, NSUN5 was identified as a key focus for subsequent investigations. Since the FinnGen study lacks CCA-specific data but includes information on cholangitis, a condition associated with a significantly increased risk of malignancy (Fung and Tabibian 2020), we performed a genetic association analysis. The findings revealed multiple single nucleotide polymorphisms in NSUN5 associated with cholangitis (Fig. 1G). These results suggest a potential role for NSUN5 in CCA development.

Fig. 1.

Fig. 1

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Oncogenic function of NSUN5 depends on its RNA 5-methylcytosine (m5C) methyltransferase activity. A, B Volcano map of m5C writers and cuproptosis inhibitors in TCGA-CHOL and GSE107943. C, D The expression profile of m5C writers and cuproptosis inhibitors in TCGA-CHOL and GSE107943. E The mRNA expression of m5C writers was quantified as relative (refer to GAPDH) level (n = 4). F The expression of NSUN5 was quantified as relative (refer to GAPDH) band density (n = 4). GAPDH was used as the loading control. G Genetic association analysis of NSUN5, data from the FinnGen study (SNP, single nucleotide polymorphism). H The protein expression of NSUN5 was quantified as relative (refer to GAPDH) level (n = 3). I M5C RNA methylation level of total RNA was measured by commercial kit and expressed as relative fluorescence units (n = 4). J Cell viability was detected by Cell Counting Kit-8 at specific time points (n = 4) and expressed as optical density in 450 nm (OD450). K The percentage of apoptotic cells was assessed using flow cytometry (n = 3). Cells located in the right quadrants (positive for FITC) were classified as apoptosis. L, M Transwell assays were conducted to evaluate the effect of the NSUN5 on the migration and invasion of cells (scale bars = 200 µm) (n = 3). Statistical data presented in this figure show mean values ± SD of three or more times of independent experiments. Statistical significance was evaluated by two-tailed unpaired Student’s t test (ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001)

We next explored the effects of NSUN5 on CCA cell behavior and whether these effects are contingent upon the m5C methyltransferase activity of NSUN5. An enzymatically inactive double-mutant of NSUN5 was created by introducing point mutations at cysteine residues 308 and 359 (King and Redman 2002). We then transfected NSUN5 wild-type (WT) and mutant (Mut) plasmids into NSUN5-knockout cells. Western blot analysis confirmed the successful establishment of the relevant cell lines (Fig. 1H). Following NSUN5 knockout, there was a significant decrease in the global RNA m5C modification level. Compared to the WT, the mutant NSUN5 also reduced the m5C modification level (Fig. 1I).

As depicted in Fig. 1J, NSUN5 knockout significantly impaired cell viability. The viability of cells expressing the mutant NSUN5 was even lower compared to the wild-type (WT). Additionally, both NSUN5 knockout and expression of the mutant NSUN5 led to an increase in the level of cell apoptosis (Fig. 1K). Furthermore, the number of migrating and invading cells was observed to decrease following NSUN5 knockout (Fig. 1L). Similar effects were noted in cells expressing the mutant NSUN5. In conclusion, these data confirm that NSUN5 promotes CCA progression through m5C modification.

GLS promotes the progression of CCA by alleviating cuproptosis

Cuproptosis, a form of programmed cell death induced by elevated copper concentrations, has not been extensively studied in the context of CCA. Given copper's essential role in liver metabolism (Liu et al. 2023), we quantified copper concentrations in CCA and adjacent tissues using the Copper Content Assay Kit (Solarbio, China). Our data revealed higher copper levels in CCA tissues compared to normal tissues (Fig. 2A). Further analysis demonstrated a positive correlation between copper content and the platelet/lymphocyte ratio and the neutrophil/lymphocyte ratio (Fig. 2B, C), both of which are established inflammatory biomarkers associated with the prognosis of invasive malignancies (Wu et al. 2019; Huang et al. 2019; Liu et al. 2022). These findings suggest a potential link between elevated copper content and CCA development, and imply the presence of factors in CCA that resist cuproptosis.

Fig. 2.

Fig. 2

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GLS promotes cholangiocarcinoma progression by inhibiting cuproptosis. A Paired line scatter plot showing Cu concentrations in cholangiocarcinoma (n = 4) and adjacent normal tissues (n = 4). B, C The Pearson tests were performed to calculate correlation coefficients between Cu concentrations and neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR). D, E The expression profile of cuproptosis inhibitors in TCGA-CHOL and GSE107943. F The mRNA expression of cuproptosis inhibitors was quantified as relative (refer to GAPDH) level (n = 4). G The expression of GLS was quantified as relative (refer to GAPDH) band density (n = 4). GAPDH was used as the loading control. H Genetic association analysis of GLS, data from the FinnGen study (SNP, single nucleotide polymorphism). I Construction of cell lines for knockout (KO) of GLS. The protein expression of GLS was quantified as relative (refer to GAPDH) level (n = 3). J Cell viability was detected by Cell Counting Kit-8 at specific time points (n = 4) and expressed as optical density in 450 nm (OD450). K The percentage of apoptotic cells was assessed using flow cytometry (n = 3). Cells located in the right quadrants (positive for FITC) were classified as apoptosis. L, M Transwell assays were conducted to evaluate the effect of the NSUN5 on the migration and invasion of cells (scale bars = 200 µm) (n = 3). N Western blot analysis of lipoylated DLAT expression in GLS-knockout cells (n = 3). GAPDH was used as the loading control. Statistical data presented in this figure show mean values ± SD of three or more times of independent experiments. Statistical significance was evaluated by two-tailed unpaired Student’s t test (ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001).

We subsequently investigated the expression levels of genes known to inhibit cuproptosis (Cyclin Dependent Kinase Inhibitor 2A/CDKN2, Glutaminase/GLS, and Metal Regulatory Transcription Factor 1/MTF1) in CCA (Tsvetkov et al. 2022). Figure 2D, E show that the expression of these genes was significantly upregulated in CCA. Analysis of clinical samples confirmed that only GLS mRNA expression was significantly increased in CCA (n = 4) (Fig. 2F). Further experiments also revealed a significant increase in GLS protein levels (n = 4) (Fig. 2G). Genetic correlation analysis identified associations between multiple single nucleotide polymorphisms of GLS and cholangitis (Fig. 2H). Therefore, GLS will be a focal point in our future studies.

Next, we knocked out GLS in cells (Fig. 2I) and treated them with CuSO4 (1 μM) and elesclomol (ELE) (100 nM) to induce cuproptosis. Experimental data indicated that GLS knockout significantly reduced cell viability (Fig. 2J), increased apoptosis (Fig. 2K), and decreased cell migration and invasion (Fig. 2L, M). Since protein lipoylation is a key component of cuproptosis (Tsvetkov et al. 2022), we assessed the impact of GLS knockdown on protein lipoylation by quantifying DLAT lipoylation using a lipoic acid-specific antibody through immunoblotting (Fig. 2N). The results indicated that GLS knockdown decreased DLAT lipoylation. These findings suggest that inhibiting GLS in CCA may suppress cuproptosis.

GLS is responsible for NSUN5-mediated tumor progression

Given the co-expression of NSUN5 and GLS in intrahepatic CCA, we hypothesize that NSUN5 may exert a tumorigenic effect by targeting GLS. Pearson correlation analysis revealed a strong positive correlation between NSUN5 and GLS expression levels (R > 0.7) (Fig. 3A, B). To investigate the functional role of the NSUN5-GLS axis, we initially stably overexpressed NSUN5 in intrahepatic CCA cells followed by the knockout of GLS.

Fig. 3.

Fig. 3

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NSUN5 promotes malignant phenotypes of cholangiocarcinoma cells via GLS. A, B The Pearson tests were performed to calculate correlation coefficients between NSUN5 and GLS in TCGA-CHOL and GSE107943. C Cell viability was detected by Cell Counting Kit-8 at specific time points (n = 4) and expressed as optical density in 450 nm (OD450). D The percentage of apoptotic cells was assessed using flow cytometry (n = 3). Cells located in the right quadrants (positive for FITC) were classified as apoptosis. E, F Transwell assays were conducted to evaluate the effect of the NSUN5 on the migration and invasion of cells (scale bars = 200 µm) (n = 3). G M5C RNA methylation level of total RNA was measured by commercial kit and expressed as relative fluorescence units (n = 4). H Western blot analysis of lipoylated DLAT expression (n = 3). GAPDH was used as the loading control. Statistical data presented in this figure show mean values ± SD of three or more times of independent experiments. Statistical significance was evaluated by two-tailed unpaired Student’s t test (ns not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001)

Figure 3C illustrates that NSUN5 overexpression significantly enhanced cell viability. This effect of NSUN5 was abrogated upon GLS knockout. Moreover, NSUN5 overexpression increased cellular resistance to copper-induced cell death, which was evidenced by a reduction in apoptosis levels. This effect was reversed by GLS knockout (Fig. 3D). Additionally, NSUN5 overexpression facilitated cell migration (Fig. 3E) and invasion (Fig. 3F), effects that were mitigated by GLS knockout. It was also observed that NSUN5 overexpression elevated the global m5C modification level of cellular RNA. Conversely, GLS knockout resulted in a decrease in the m5C modification level in cells (Fig. 3G). Western blot analysis demonstrated a decrease in the sulfur acylation level of DLAT in cells overexpressing NSUN5. In comparison, GLS knockout led to an increase in the sulfur acylation level of DLAT. These findings suggest that NSUN5 inhibits copper-induced cell death and promotes the progression of CCA by targeting GLS.

NSUN5 promotes GLS accumulation via m5C modification on GLS mRNA

We initially explored the influence of NSUN5 on GLS through the mechanism of m5C modification. Immunofluorescence analysis confirmed the predominant nuclear localization of NSUN5 (Fig. 4A). Correlative changes in GLS mRNA expression and protein levels were observed in response to alterations in NSUN5 levels. Specifically, the overexpression of NSUN5 led to increased GLS expression, while the knockout of NSUN5 resulted in decreased GLS levels (Fig. 4B, C). Given the role of m5C modification in regulating mRNA stability, cells were treated with actinomycin D to assess mRNA decay rates. Notably, cells overexpressing NSUN5 showed a reduced decay rate of GLS mRNA, as illustrated in Fig. 4D. In contrast, NSUN5 silencing accelerated the decay of GLS mRNA. Subsequent RNA immunoprecipitation (RIP) experiments (Fig. 4E) and RNA pull-down assays (Fig. 4F) definitively established a direct interaction between NSUN5 and GLS mRNA. Furthermore, we demonstrated the integrity of GLS mRNA by agarose gel electrophoresis (Supplemental file 2).

Fig. 4.

Fig. 4

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NSUN5 promotes GLS accumulation via m5C modification on GLS mRNA. A Representative immunofluorescent images of NSUN5 (red) in cell (scale bars, 5 μm). The nuclei were restained with DAPI. B, C The protein and mRNA expression of GLS was quantified as relative (refer to GAPDH) level (n = 3). D The relative (refer to GAPDH) mRNA expression of GLS in cells treated with 5 μg/ml actinomycin D for indicated times (n = 3). E. RIP assay for the binding of NSUN5 with mRNA of GLS. RIP was performed using NUSN5 antibody, followed by qRT-PCR assay for mRNA expression of GLS. F RNA pull-down assay followed by western blot for NSUN5 in cells. G Venn diagram showed the selection for the downstream target of m5C modification sites according to iRNA-m5C, RNA m5cfinder and Alphafold 3. H. Prediction of m5C modification sites. Prediction scores were obtained from RNA m5cfinder. I In silico modelling of NSUN5 (purple) bound to GLS mRNA (yellow). And molecular docking 3D map of NSUN5 with GLS mRNA. J The structure chart showing the predicted m5C motifs in the 5’UTR of GLS. K. MeRIP-qPCR assay validating that GLS-137 shows significant methylation activity compared to other sites (n = 3). Statistical data presented in this figure show mean values ± SD of three or more times of independent experiments. Statistical significance was evaluated by two-tailed unpaired Student’s t test (ns not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001)

To predict potential m5C modification sites on GLS mRNA that may be targeted by NSUN5, we employed iRNA-m5C, RNA m5Cfinder, and AlphaFold 3, with the prediction results and scores presented in Fig. 4G, H. Molecular docking details revealed that site 137 C on the GLS mRNA is in closest proximity to the two key amino acids of NSUN5 involved in m5C methyltransferase activity. Additionally, an interaction between site 137 C and Cys 359 was identified (Fig. 4I). Consequently, with high confidence, we identified a potential m5C modification site: site 137 C in the UTR region of the GLS transcript (Fig. 4J). Subsequent MeRIP-qPCR analysis using specific primers confirmed that site 137 on the GLS transcript is a direct substrate of NSUN5-mediated methylation (Fig. 4K). These data indicated that m5C modification of GLS mRNA by NSUN5 is achieved through site 137.

NSUN5 promotes CCA in vivo

Finally, we utilized a xenograft model to validate the in vivo functionality of the NSUN5-GLS axis. We inoculated CCA cells into nude mice. The data revealed that, compared to the control, overexpression of NSUN5 significantly promoted tumor growth, increasing both tumor mass and volume. The knockout of GLS blocked the promotional effects of NSUN5 (Fig. 5A–C). In conclusion, GLS is a key target through which NSUN5 facilitates the progression of CCA.

Fig. 5.

Fig. 5

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NSUN5-GLS axis promotes CCA progression in vivo. A CCA cells were stably infected with the indicated lentivirus and subcutaneously injected into nude mice (n = 4). About 2 weeks after injection, xenografts were removed. Representative images of xenografts were shown. B, C Tumor volume and tumor weight were determined (n = 4). Statistical data presented in this figure show mean values ± SD of three or more times of independent experiments. Statistical significance was evaluated by two-tailed unpaired Student’s t test (ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001)

Discussion

CCA stands as a significant contributor to cancer-related mortality on a global scale (Moris et al. 2023). Despite therapeutic advancements, the prognosis for CCA remains bleak, underscoring the critical imperative to investigate the underlying mechanisms driving CCA progression and to innovate new treatment modalities. Methylation modifications of mRNA play a pivotal role in regulating RNA stability, subcellular localization, and protein translation efficiency (Zhao et al. 2017). m5C methylation emerges as a prevalent modification on eukaryotic RNA, and recent research highlights its implications in various physiological and pathological processes (Bohnsack et al. 2019). Nevertheless, investigations regarding the functional implications of m5C modification in CCA remain substantially limited.

NSUN5 is a pivotal member of the NSUN family and functions as a ribosomal RNA methyltransferase, playing a key role in regulating overall protein synthesis and normal growth (Heissenberger et al. 2019). Limited reports currently exist regarding NSUN5’s m5C modification of mRNA. Our study highlights that the aberrant upregulation of NSUN5 leads to elevated m5C levels in CCA cells. Functional experiments unequivocally demonstrate that NSUN5 facilitates the growth and metastasis of CCA through m5C modification. These findings are corroborated by previous studies indicating NSUN5’s involvement in various tumor types, including prostate cancer and glioma (Zhang et al. 2023; Wu et al. 2024). Additionally, research conducted by Yibin Su et al. proposes that the NSUN5-FTH1 axis suppresses ferroptosis while promoting the proliferation of gastric cancer cells (Su et al. 2023). This work represents the first elucidation of the role of NUSN5-mediated m5C modification in CCA progression, shedding light on its underlying mechanism and further enhancing our comprehension of NSUN5’s oncogenic properties.

Copper homeostasis can impact tumor growth, invasion, and even confer resistance to chemotherapy. A surplus of copper, on the other hand, leads to cuproptosis. Our study revealed a significant increase in copper levels within CCA tissues, a finding positively associated with tumor invasiveness. CCA cells evade cuproptosis by upregulating GLS. GLS, a recently discovered inhibitor of cuproptosis, is commonly overexpressed in various cancers, thereby facilitating tumor advancement (Zhou et al. 2023; Xu et al. 2023; Chen et al. 2023). Studies have elucidated that GLS interacts with diverse cellular signaling pathways. For example, the succinylation of GLS by SUCLA2 has been linked to the augmentation of pancreatic cancer metastasis (Tong et al. 2021). This research focuses on delineating the role of GLS in CCA. Experimental evidence underscores that GLS enhances CCA progression by impeding copper-induced cell death mechanisms. The upregulation of GLS within cells can be attributed to the methylation modification catalyzed by NSUN5 at the GLS mRNA site 137 C.

Several limitations are evident in our study. Notably, the m5C methylation catalyzed by the NSUN family can be identified by ‘m5C readers’, potentially modulating the nuclear mRNA output (Yang et al. 2019). Thus, additional investigation is warranted to assess the involvement of m5C readers or m5C-associated enzymes in regulating GLS expression. Furthermore, constrained by laboratory constraints, the validation of our findings in animal models has not been achievable. Subsequent research endeavors should prioritize overcoming this challenge.

Conclusions

In summary, our study reveals heightened NSUN5 expression in CCA. NSUN5 facilitates GLS accumulation through a m5C-dependent mechanism, consequently suppressing cuproptosis and promoting tumor advancement in CCA. This investigation contributes to a more profound comprehension of CCA by examining RNA modification and copper balance. And NSUN5 may emerge as a potential target for CCA therapy.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (ZIP 921 KB) (921.2KB, zip)
Supplementary file2 (PDF 838 KB) (837.6KB, pdf)
Supplementary file3 (PDF 925 KB) (924.6KB, pdf)
Supplementary file4 (DOCX 19 KB) (19.3KB, docx)

Author contributions

Weishan Wang planned the study and supervised the analyses. Ming Shu performed the experiments and drafted the manuscript. Kunpeng Guo and Yikai Huang collected data and completed pictures and tables. All authors contributed to the interpretation of results and revision of the paper, and approved the final manuscript.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Conflict of interest

The authors declare no competing interests.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Shanghai electric power hospital (No. 2024-008).

Footnotes

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References

  1. Abramson J et al (2024) Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630(8016):493–500 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Barbieri I, Kouzarides T (2020) Role of RNA modifications in cancer. Nat Rev Cancer 20(6):303–322 [DOI] [PubMed] [Google Scholar]
  3. Bohnsack KE, Höbartner C, Bohnsack MT (2019) Eukaryotic 5-methylcytosine (m5C) RNA methyltransferases: mechanisms, cellular functions, and links to disease. Genes (Basel) 10(2):102 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bossak K et al (2018) The Cu(II) affinity of the N-terminus of human copper transporter CTR1: comparison of human and mouse sequences. J Inorg Biochem 182:230–237 [DOI] [PubMed] [Google Scholar]
  5. Brindley PJ et al (2021) Cholangiocarcinoma. Nat Rev Dis Primers 7(1):65 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chen X et al (2019) 5-methylcytosine promotes pathogenesis of bladder cancer through stabilizing mRNAs. Nat Cell Biol 21(8):978–990 [DOI] [PubMed] [Google Scholar]
  7. Chen YS et al (2021) Dynamic transcriptomic m(5) C and its regulatory role in RNA processing. Wiley Interdiscip Rev RNA 12(4):e1639 [DOI] [PubMed] [Google Scholar]
  8. Chen Z et al (2023) LncRNA PVT1 confers cisplatin resistance of esophageal cancer cells through modulating the miR-181a-5p-glutaminase (GLS) Axis. Nutr Cancer 75(8):1646–1657 [DOI] [PubMed] [Google Scholar]
  9. Fang L et al (2023) m5C-methylated lncRNA NR_033928 promotes gastric cancer proliferation by stabilizing GLS mRNA to promote glutamine metabolism reprogramming. Cell Death Dis 14(8):520 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Fukai T, Ushio-Fukai M, Kaplan JH (2018) Copper transporters and copper chaperones: roles in cardiovascular physiology and disease. Am J Physiol Cell Physiol 315(2):C186-c201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Fung BM, Tabibian JH (2020) Cholangiocarcinoma in patients with primary sclerosing cholangitis. Curr Opin Gastroenterol 36(2):77–84 [DOI] [PubMed] [Google Scholar]
  12. Heissenberger C et al (2019) Loss of the ribosomal RNA methyltransferase NSUN5 impairs global protein synthesis and normal growth. Nucleic Acids Res 47(22):11807–11825 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Huang H et al (2019) Preoperative neutrophil-lymphocyte and platelet-lymphocyte ratios as independent predictors of T stages in hilar cholangiocarcinoma. Cancer Manag Res 11:5157–5162 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Ilyas SI et al (2023) Cholangiocarcinoma - novel biological insights and therapeutic strategies. Nat Rev Clin Oncol 20(7):470–486 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. King MY, Redman KL (2002) RNA methyltransferases utilize two cysteine residues in the formation of 5-methylcytosine. Biochemistry 41(37):11218–11225 [DOI] [PubMed] [Google Scholar]
  16. Kurki MI et al (2023) FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 613(7944):508–518 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Li M et al (2022) 5-methylcytosine RNA methyltransferases and their potential roles in cancer. J Transl Med 20(1):214 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Li X et al (2024) Identification of TNFRSF21 as an inhibitory factor of osteosarcoma based on a necroptosis-related prognostic gene signature and molecular experiments. Cancer Cell Int 24(1):14 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Liu J et al (2022) Elevated serum neutrophil-lymphocyte ratio is associated with worse long-term survival in patients with HBV-related intrahepatic cholangiocarcinoma undergoing resection. Front Oncol 12:1012246 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Liu T et al (2023) Copper homeostasis dysregulation promoting cell damage and the association with liver diseases. Chin Med J (Engl) 136(14):1653–1662 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Majumder S et al (2009) The role of copper in drug-resistant murine and human tumors. Biometals 22(2):377–384 [DOI] [PubMed] [Google Scholar]
  22. Moris D et al (2023) Advances in the treatment of intrahepatic cholangiocarcinoma: an overview of the current and future therapeutic landscape for clinicians. CA Cancer J Clin 73(2):198–222 [DOI] [PubMed] [Google Scholar]
  23. Pavithra V et al (2015) Serum levels of metal ions in female patients with breast cancer. J Clin Diagn Res 9(1):BC25-c27 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Ritchie ME et al (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43(7):e47 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Stepien M et al (2017) Pre-diagnostic copper and zinc biomarkers and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort. Carcinogenesis 38(7):699–707 [DOI] [PubMed] [Google Scholar]
  26. Su Y et al (2023) NSUN5-FTH1 axis inhibits ferroptosis to promote the growth of gastric cancer cells. Cell Biochem Biophys 81(3):553–560 [DOI] [PubMed] [Google Scholar]
  27. Tong Y et al (2021) SUCLA2-coupled regulation of GLS succinylation and activity counteracts oxidative stress in tumor cells. Mol Cell 81(11):2303-2316.e8 [DOI] [PubMed] [Google Scholar]
  28. Tsvetkov P et al (2022) Copper induces cell death by targeting lipoylated TCA cycle proteins. Science 375(6586):1254–1261 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Wu Y et al (2019) Preoperative serum platelet-lymphocyte ratio as a prognostic factor in cholangiocarcinoma patients after radical resection: a retrospective analysis of 119 patients. Gastroenterol Res Pract 2019:8506967 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Wu R et al (2024) NSUN5/TET2-directed chromatin-associated RNA modification of 5-methylcytosine to 5-hydroxymethylcytosine governs glioma immune evasion. Proc Natl Acad Sci U S A 121(14):e2321611121 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Xu G, Qu J, Zhang M (2023) HDAC4-mediated deacetylation of glutaminase facilitates glioma stemness. Curr Cancer Drug Targets 23(9):742–750 [DOI] [PubMed] [Google Scholar]
  32. Yang Y et al (2019) RNA 5-methylcytosine facilitates the maternal-to-zygotic transition by preventing maternal mRNA decay. Mol Cell 75(6):1188-1202.e11 [DOI] [PubMed] [Google Scholar]
  33. Zhang Y et al (2023) CDK13 promotes lipid deposition and prostate cancer progression by stimulating NSUN5-mediated m5C modification of ACC1 mRNA. Cell Death Differ 30(12):2462–2476 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Zhao BS, Roundtree IA, He C (2017) Post-transcriptional gene regulation by mRNA modifications. Nat Rev Mol Cell Biol 18(1):31–42 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Zhou X et al (2023) miR-141-3p promotes the cisplatin sensitivity of osteosarcoma cell through targeting the glutaminase [GLS]-mediated glutamine metabolism. Curr Mol Med 23(2):177–184 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary file1 (ZIP 921 KB) (921.2KB, zip)
Supplementary file2 (PDF 838 KB) (837.6KB, pdf)
Supplementary file3 (PDF 925 KB) (924.6KB, pdf)
Supplementary file4 (DOCX 19 KB) (19.3KB, docx)

Data Availability Statement

No datasets were generated or analysed during the current study.

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