FTSJ1-mediated IL1RN mRNA instability promotes inflammation-driven hepatocellular carcinoma

Introduction

Hepatocellular carcinoma (HCC), the third leading cause of cancer-related death globally, accounts for over 800,000 deaths annually, with a persistently low 5-year survival rate of 12–18% (1,2). This grim prognosis is closely linked to the high heterogeneity of the tumor, complex microenvironment dysregulation, and a lack of effective early diagnosis and targeted therapeutic strategies (3,4). Although surgical resection, liver transplantation, and molecular targeted therapies (e.g., sorafenib, lenvatinib) have improved survival for some patients, acquired resistance and tumor recurrence remain core challenges in clinical practice (5-7). Recent research has profoundly revealed that aberrant epigenetic regulation, particularly dysregulation of RNA modifications, plays a crucial role in shaping the heterogeneity of HCC development (8,9).

2'-O-methylation, one of the most conserved RNA chemical modifications in eukaryotes, is catalyzed by specific methyltransferase families (e.g., FTSJ1, CMTR, FBL) (10). It directly impacts RNA stability, localization, translation efficiency, and function by modifying the ribose 2'-hydroxyl group of ribosomal RNA (rRNA), transfer RNA (tRNA), and messenger RNA (mRNA) (11). Notably, FTSJ1 (tRNA methyltransferase 7), localized in the nucleolus, catalyzes 2'-O-methylation of nucleotide position 32 in tRNA. Its functional loss leads to aberrant ribosome assembly and reduced translational fidelity (12). FTSJ1 exhibits tissue-specific bidirectional regulation in tumors, though related research remains limited. In triple-negative breast cancer, elevated FTSJ1 expression drives oncogenic functions by promoting proliferation, suppressing apoptosis, and reducing CD8⁺ T-cell infiltration to mediate immune evasion (13). Conversely, in non-small cell lung cancer (NSCLC), downregulation of FTSJ1 impairs tRNA 2'-O-methyladenosine (Am) modification and upregulates DRAM1, thereby driving tumor progression and revealing FTSJ1’s tumor-suppressive function (14). This gene is transcriptionally regulated by the nucleoporin Nup155 and forms a feedback loop with the p53 pathway to modulate p21 translation (15). However, systematic investigations into FTSJ1 in globally prevalent and highly lethal HCC are urgently needed—its expression patterns, clinical prognostic significance, core biological functions, and molecular mechanisms remain unelucidated.

Concurrently, the chronic inflammatory microenvironment is widely recognized as the “common soil” for HCC initiation and a driving force for its continuous progression (16,17). Persistent liver injury (e.g., viral hepatitis, alcoholic liver disease) triggers inflammatory cascades, activating core signaling pathways such as nuclear factor-κB (NF-κB) and signal transducer and activator of transcription 3 (STAT3) (18,19). This promotes hepatic stellate cell activation, dysregulated immune cell infiltration, and excessive release of pro-inflammatory cytokines [e.g., tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-1β (IL-1β)], ultimately driving malignant transformation of hepatocytes and fostering an immunosuppressive tumor microenvironment (TME) (20). Recent advances reveal that RNA-modifying enzymes can profoundly impact inflammatory homeostasis and immune responses within the TME by precisely regulating the stability, translation, or function of inflammation-related mRNAs (21). For instance, the N⁶-methyladenosine (m⁶A) methyltransferase METTL3 promotes colorectal cancer progression by activating the Janus kinase 1 (JAK1)/STAT3 pathway (21). This raises a critical, unanswered scientific question: could FTSJ1, as a significant 2'-O-methyltransferase, participate in dynamically shaping the inflammatory TME and malignant transformation in HCC by modifying RNAs of specific inflammatory factors or regulators of inflammatory pathways? Is its mechanism unique?

To systematically address this key scientific question, this study integrates multi-center large-sample cohorts [The Cancer Genome Atlas (TCGA)/Gene Expression Omnibus (GEO)/Eastern Hepatobiliary Surgery Hospital (EHBH)], multi-level complementary experimental models (in vitro cells, in vivo animals, clinical samples), and multi-omics technologies (transcriptome sequencing, functional enrichment analysis). It aims to achieve three tightly linked and progressive research objectives: (I) comprehensively characterize the expression profile of the 2'-O-methyltransferase family in HCC and identify the independent clinical value of FTSJ1 as a novel prognostic biomarker. (II) Systematically dissect the critical functional impact of FTSJ1 on core malignant phenotypes of HCC cells, including proliferation, apoptosis resistance, and cell cycle regulation. (III) Deeply elucidate the precise molecular mechanism by which FTSJ1 mediates inflammatory signaling pathways through RNA modification, providing a solid theoretical and experimental basis for future development of intervention strategies targeting the FTSJ1-inflammation axis. We present this article in accordance with the MDAR and ARRIVE reporting checklists (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-693/rc).

Methods

Ethics statement

All animal care and experimental protocols, and the human tissue microarray (TMA) study were both approved by the Ethics Committee of The Third Affiliated Hospital of Navy Medical University (ethical approval Nos. EHBHKY2023-K020-P001 and EHBHKY2023-K050-P002). Written informed consent was obtained from all participants (or their legal guardians) prior to the collection of tissue samples. All animal experiments and human tissue studies were performed in compliance with relevant local legislation and institutional requirements. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Data acquisition and processing

RNA sequencing (RNA-seq) data, copy number variation (CNV) data, and clinical information from 371 HCC patients were obtained from the TCGA database (https://portal.gdc.cancer.gov/). Three datasets were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/gds/): GSE54236 (80 tumor samples), GSE144269 (68 tumor samples), and GSE14520 (225 tumor and 220 normal samples). All transcriptomic data were normalized and converted to transcripts per million (TPM).

Bioinformatics analysis

Consensus clustering analysis of The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) mRNA expression profile was performed using the ConsensusClusterPlus R package. The optimal cluster number k=3 was determined based on the cumulative distribution function (CDF) and delta area analysis. FTSJ1 expression was compared between tumor and normal tissues and across clinical subgroups [e.g., alpha-fetoprotein (AFP) level, histologic grade, tumor-node-metastasis (TNM) stage] using the ggplot2 package (v3.3.3). A receiver operating characteristic (ROC) curve was generated using the pROC package (v1.17.0.1) to evaluate the diagnostic value of FTSJ1. Kaplan-Meier survival analysis for high- and low-FTSJ1 expression groups (stratified by median expression) was performed using the survival (v3.2-10) and survminer (v0.4.9) packages. Univariate and multivariate Cox regression analyses were performed using the survival analysis R packages to construct a four-gene (FTSJ1, FTSJ2, FTSJ3, and FBL) risk scoring model. Patients were stratified into high-risk and low-risk groups based on the median risk score. The model’s performance was validated in the TCGA, GSE54236, and GSE144269 cohorts using Kaplan-Meier survival curves (log-rank test) and ROC curves (timeROC package). Gene Ontology (GO) functional enrichment analysis (clusterProfiler package) and gene set enrichment analysis (GSEA) pathway enrichment analysis were performed on FTSJ1-related differentially expressed genes (DEGs). Significant enrichment was defined as false discovery rate (FDR) <0.25 and adjusted P<0.05.

Clinical samples and molecular detection

The EHBH cohort 1 comprised 66 paired HCC and adjacent non-tumor tissues for quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) detection. EHBH cohort 2 comprised 92 HCC tissue microarray samples for independent validation. Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). Complementary DNA (cDNA) was synthesized using PrimeScript™ RT Master Mix (TAKARA, Otsu, Japan; RR036A). FTSJ1 expression was detected using SYBR Green Premix (TAKARA; RR420) on a StepOne™ Real-Time PCR System (Applied Biosystems, Waltham, MA, USA), and relative expression was calculated using the ΔΔcycle threshold (ΔΔCt) method. IHC staining was performed using an FTSJ1 primary antibody (Novus, Littleton, CO, USA; NBP1-85703) and a horseradish peroxidase (HRP)-labeled secondary antibody (Abcam, Cambridge, UK; ab205718).

Cell experiments

The human HCC cell lines Huh7 and HepG2 were purchased from the Shanghai Cell Bank of the Chinese Academy of Sciences (Shanghai, China) and cultured in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum (FBS) (37 ℃, 5% CO₂). Cells were transfected with small interfering RNA (siRNA) FTSJ1 (si-FTSJ1) (Genomeditech, Shanghai, China; sequence 5'-GCUCUGAACAUUGCUACACAU-3') or negative control (NC) siRNA using Lipofectamine 3000 transfection reagent (Thermo, Waltham, MA, USA; L3000015). Cell proliferation was assessed using the Cell Counting Kit-8 (CCK-8) reagent (Dojindo, Kumamoto, Japan; CK-04) [optical density (OD)₄₅₀ measured at 0/24/48/72 h]. Migration assay was performed using Transwell chambers (Corning Inc., Corning, NY, USA). Apoptosis was analyzed using an Annexin V-fluorescein isothiocyanate (FITC)/propidium iodide (PI) apoptosis detection kit (BD, Franklin Lakes, NJ, USA; 556547), and cell cycle distribution was analyzed using a cell cycle detection kit (Beyotime, Shanghai, China; C1052), both assessed by flow cytometry. For mRNA stability assay: Huh7 cells transfected with si-FTSJ1 were treated with actinomycin D (5 µg/mL; Sigma-Aldrich, St. Louis, MO, USA; A9415). Cells were collected at 0, 2, 4, and 6 h post-treatment, and residual interleukin 1 receptor antagonist (IL1RN) mRNA levels were measured to calculate half-life.

RNA immunoprecipitation (RIP) assay

The interaction between FTSJ1 and IL1RN mRNA was assessed using the Magna RIP™ RNA-binding protein immunoprecipitation kit (Millipore, Billerica, MA, USA; #17-700) following the manufacturer’s instructions. Briefly, Huh7 cells were lysed in complete RIP lysis buffer. The cell lysate was incubated with magnetic beads conjugated with either anti-FTSJ1 antibody (Novus; NBP1-85703) or normal rabbit immunoglobulin G (IgG) (Millipore; provided in the kit) as an NC. After washing, the immunoprecipitated RNA-protein complexes were digested with proteinase K to isolate the bound RNAs. The co-precipitated RNAs were then purified and reverse-transcribed. The enrichment of IL1RN mRNA in the immunoprecipitates was quantified by quantitative polymerase chain reaction (qPCR) using specific primers. The relative enrichment was calculated using the Ct value, normalized to the IgG sample.

Transcriptome sequencing

Huh7 cells transfected with si-FTSJ1 for 48 h were lysed using TRIzol. RNA-seq was performed on the Illumina HiSeq platform (paired-end) by Shanghai Xuran Biotechnology Co., Ltd. (Shanghai, China). DEGs were identified using DESeq2 software [|log₂fold change (FC)| ≥1 and P≤0.05]. Functional enrichment analysis was performed using GO and GSEA (clusterProfiler package).

Animal experiments

A subcutaneous xenograft tumor model was established by injecting 5×10⁶ Huh7 cells into the flank of 4–6-week-old male BALB/c nude mice. Following cell inoculation, mice were randomly assigned to experimental groups (n=6 per group) using a computer-generated random number sequence to ensure unbiased allocation. Mice were housed under specific pathogen-free conditions with a 12-h light/dark cycle, ad libitum access to food and water, and ambient temperature maintained at 22±2 ℃. Tumor volume was measured every 3 days for 21 days using the formula V = 0.5 × length × width². The investigator measuring tumor volumes was blinded to the group allocation throughout the experiment. For endpoint procedures, mice were deeply anesthetized via inhalation of 3–5% isoflurane in oxygen delivered using a calibrated vaporizer and maintained at 1–3% isoflurane. Depth of anesthesia was confirmed by the absence of response to toe pinch. Euthanasia was performed by cervical dislocation while animals were under deep anesthesia. Serum levels of TNF-α and IL-6 were measured by enzyme-linked immunosorbent assay (ELISA) (R&D Systems kits). Tumor tissues were subjected to Ki-67 IHC staining and IHC staining for inflammatory cytokines [interferon-γ (IFN-γ), IL-1β, IL-6, and TNF-α]. Serum TNF-α and IL-6 concentrations were quantified using ELISA kits (Multi Sciences Biotech, EK282HS/EK206HS -96) strictly according to the manufacturer’s instructions.

Statistical analysis

Analyses were performed using R 4.2.0 and GraphPad Prism 7.0 software. Continuous variables were compared using Student’s t-test, analysis of variance (ANOVA), or non-parametric tests (Mann-Whitney/Wilcoxon). Categorical variables were compared using the Chi-squared test. Survival analysis was performed using the Kaplan-Meier method and log-rank test. Correlation analysis used Pearson’s or Spearman’s method. Significance thresholds were P<0.05, P<0.01, and P<0.001.

Results

Molecular subtype classification of HCC patients and key gene screening

To investigate the molecular heterogeneity of HCC, we performed consensus clustering analysis. The optimal cluster number k=3 was determined based on the consensus CDF curve and Delta area analysis, indicating the best classification performance (Figure 1A,1B). Tracking plots and consensus matrices further validated the stability of this clustering result (Figure 1C,1D). Strikingly, subtype 1 exhibited the highest expression abundance of 12 2'-O-methyltransferase genes (Figure 1E) and had the worst prognosis among the subtypes (Figure 1F). To delineate the clinical relevance of this molecular subtyping, we compared the clinicopathological characteristics across the three subtypes (Table S1). This analysis revealed that subtype 1 was significantly associated with more advanced pathological T stage (P=0.007) and higher histologic grade (P=0.001), linking the 2'-O-methyltransferase-high subtype to aggressive tumor phenotypes. We then performed survival analysis for each of the 12 2'-O-methyltransferase family members. Among them, FTSJ1, FTSJ2, FTSJ3, and FBL were significantly associated with HCC patient prognosis (Figure 1G and Figure S1).

Figure 1 Consensus clustering identifies optimal molecular subtyping of HCC and prognostic relevance of 2'-O-methyltransferase genes. (A) CDF curves for cluster numbers (k) =2–5, visualizing the cumulative probability of consensus clustering assignments. (B) Delta area plot depicting the relative change in area under the CDF curve across increasing k values, used to determine the optimal cluster number. (C) Tracking plot illustrating the stability of sample cluster assignments as k increases, confirming reproducibility of clustering. (D) Consensus matrix heatmap for k=3, displaying pairwise sample clustering consistency (blue = high consensus, white = low consensus) and hierarchical clustering of samples. (E) TCGA HCC patients were divided into three subtypes by consensus cluster analysis. (F) Kaplan-Meier curves show OS of patients in three subtype groups. (G) Kaplan-Meier survival curves for FTSJ1, FTSJ2, FTSJ3, and FBL (high vs. low expression). ****, P<0.0001. CDF, cumulative distribution function; HCC, hepatocellular carcinoma; HR, hazard ratio; OS, overall survival; TCGA, The Cancer Genome Atlas.

Univariate Cox regression analysis of FTSJ1, FBL, FTSJ3, and FTSJ2 (Figure 2A) indicated that all four were significant prognostic risk factors (P<0.05). Subsequent multivariate Cox regression analysis (Figure 2B) revealed that only FTSJ1 remained statistically significant (P=0.02), while FBL, FTSJ2, and FTSJ3 did not reach significance. This suggests FTSJ1 may be an independent risk factor for HCC prognosis. Based on these four genes identified in univariate analysis, a risk scoring model was constructed. Patients were stratified into high-risk and low-risk groups based on the median risk score. Results showed that the high-risk group had a higher proportion of deaths, and the expression levels of all four genes were significantly higher in this group compared to the low-risk group (Figure 2C).

Figure 2 Development and validation of 2'-O-methyltransferase family gene signature for HCC. (A) Univariate Cox analysis of OS related 2'-O-methyltransferase family members in the TCGA-LIHC cohort. (B) Development of Cox proportional hazards model based on OS related 2'-O-methyltransferase family members. (C) Distribution of risk score, OS, and OS status of 2'-O-methyltransferase family gene signature in the TCGA cohort. (D) Kaplan-Meier curves of OS for patients with HCC based on the risk score in the TCGA cohort. (E,F) Validation of the gene signature by Kaplan-Meier curves in GSE54236 and GSE144269. (G) Multivariate Cox analysis including Risk Score and clinic characteristics in the TCGA cohort. (H) Time-dependent ROC curves for 1-, 3-, and 5-year OS prediction based on the gene signature across multiple cohorts. AUC, area under the curve; CI, confidence interval; HCC, hepatocellular carcinoma; INR, international normalized ratio; OS, overall survival; ROC, receiver operating characteristic; TCGA, The Cancer Genome Atlas; TCGA-LIHC, The Cancer Genome Atlas-Liver Hepatocellular Carcinoma.

Kaplan-Meier survival curve analysis revealed significantly worse prognosis in the high-risk group, a pattern consistently observed in the TCGA-LIHC cohort (Figure 2D; P<0.001), GSE54236 cohort (Figure 2E; P<0.001), and GSE144269 cohort (Figure 2F; P=0.01). Multivariate Cox regression analysis incorporating the risk score and clinical characteristics (Figure 2G) further confirmed that this risk score was an independent prognostic factor for HCC patients (P<0.001). ROC curve analysis at 1, 3, and 5 years (Figure 2H) demonstrated the good predictive performance of the four-gene model for prognosis. Given that FTSJ1 was identified as an independent prognostic risk factor for HCC, subsequent research focused on FTSJ1.

Expression pattern of FTSJ1 in HCC tissues

Pan-cancer expression profiling based on TCGA and Genotype-Tissue Expression (GTEx) databases (Figure 3A) showed that FTSJ1 expression was significantly upregulated at the transcriptional level in HCC tissues, and this high expression trend was specific among 33 cancer types. Further validation across multiple cohorts: in the combined TCGA-GTEx cohort (Figure 3B), FTSJ1 expression was significantly higher in HCC tissues than in normal liver tissues (P<0.001). Analysis of paired samples in TCGA-LIHC (Figure 3C; black lines connecting paired samples) further confirmed that FTSJ1 expression was upregulated in tumor tissues compared to matched adjacent tissues in each case. The GSE14520 dataset (Figure 3D) and qRT-PCR results from EHBH cohort 1 (Figure 3E) also consistently supported the high expression of FTSJ1 in HCC tissues (P<0.001). Representative IHC staining images from EHBH patients (Figure 3F) visually validated these findings at the protein level, demonstrating significantly higher FTSJ1 staining intensity in HCC tumor tissues compared to adjacent normal liver tissues. Collectively, these multi-faceted results reveal a significant pattern of FTSJ1 overexpression in HCC tissues.

Figure 3 The expression levels of FTSJ1 in pan-cancers and HCC. (A) FTSJ1 expression levels across pan-cancers (vs. matched normal tissues) in the TCGA and GTEx databases. (B) FTSJ1 expression levels in HCC (vs. normal tissues) based on the TCGA + GTEx databases. (C) FTSJ1 expression levels in HCC (vs. normal tissues) based on the TCGA-LIHC cohort. (D) FTSJ1 expression levels in HCC (vs. normal tissues) based on the GSE14520 database. (E) qPCR-detected FTSJ1 expression levels in HCC (vs. normal tissues) from the EHBH cohort (n=66). (F) IHC images of FTSJ1 expression in paired tumor and normal tissues from HCC patients in the EHBH cohort (magnification, ×100). **, P<0.01; ***, P<0.001; ns, not significant. The full name of the TCGA abbreviations sees the website: https://gdc.cancer.gov/resources-tcga-users/tcga-code-tables/tcga-study-abbreviations. EHBH, Eastern Hepatobiliary Surgery Hospital; GTEx, Genotype-Tissue Expression; HCC, hepatocellular carcinoma; IHC, immunohistochemistry; qPCR, quantitative polymerase chain reaction; TCGA, The Cancer Genome Atlas; TCGA-LIHC, The Cancer Genome Atlas-Liver Hepatocellular Carcinoma; TPM, transcripts per million.

Validation of FTSJ1 as an independent prognostic factor in HCC

In the validation cohort from EHBH (cohort 2), Kaplan-Meier survival analysis indicated that patients with high FTSJ1 expression had significantly shorter overall survival (OS) [hazard ratio (HR) =1.98; 95% confidence interval (CI): 1.07–3.67; P=0.03; Figure 4A,4B]. Time-dependent ROC curves further assessed its predictive power: the area under the curve (AUC) for FTSJ1 predicting 1-, 2-, and 3-year OS in the EHBH cohort was 0.713, 0.803, and 0.698, respectively (Figure 4C). In the TCGA-LIHC cohort, the AUC for predicting 1-, 3-, and 5-year OS was 0.701, 0.690, and 0.614, respectively (Figure 4D). These results indicate that FTSJ1 has good predictive ability for both short-to-medium-term and long-term prognosis in HCC patients. Univariate Cox proportional hazards regression analysis in the EHBH cohort (Figure 4E) showed that high FTSJ1 expression (HR =1.984; 95% CI: 1.073–3.668; P=0.03), tumor grade (II/III), and maximum tumor diameter were prognostic risk factors. After adjusting for confounding factors such as gender and pathological grade, multivariate Cox analysis further confirmed FTSJ1 as an independent prognostic risk factor (HR =2.268; 95% CI: 1.181–4.354; P=0.01; Figure 4F), fully validating the potential value of FTSJ1 as an HCC prognostic biomarker. To further delineate the clinical relevance of FTSJ1 dysregulation, we systematically analyzed its expression across diverse clinicopathological contexts (Figure S2). This analysis revealed significantly elevated FTSJ1 expression in tumor tissue compared to normal liver, with higher levels strongly associated with aggressive disease features, including advanced TNM stages, higher histologic grade, elevated AFP levels, presence of vascular invasion, severe peritumoral inflammation, and poor OS outcome. Baseline clinical characteristics of patients stratified by FTSJ1 expression are summarized in Table S2. Logistic regression analysis (Table S3) revealed that high FTSJ1 expression was significantly associated with advanced T stage, pathological stage, tumor status, and higher histologic grade. Furthermore, univariate and multivariate Cox regression analyses (Table S4) confirmed FTSJ1 as an independent prognostic factor for OS in HCC patients.

Figure 4 FTSJ1 is a prognostic factor for patients with HCC. (A) Representative IHC staining showing high and low FTSJ1 expression levels in HCC tumor tissues. The large panoramic images were acquired at ×100 magnification, and the corresponding small inset images (magnified focal views) were captured at ×400 magnification. (B-D) Kaplan-Meier curves and ROC curves of OS for patients with HCC based on the FTSJ1 expression in the TCGA cohort and EHBH-validation cohort. (E) Univariate Cox analysis of EHBH-validation cohort. (F) Multivariate Cox analysis of EHBH-validation cohort. AJCC, American Joint Committee on Cancer; AUC, area under the curve; CI, confidence interval; EHBH, Eastern Hepatobiliary Surgery Hospital; FPR, false positive rate; HCC, hepatocellular carcinoma; HR, hazard ratio; IHC, immunohistochemistry; OS, overall survival; ROC, receiver operating characteristic; TCGA-LIHC, The Cancer Genome Atlas-Liver Hepatocellular Carcinoma; TPR, true positive rate.

FTSJ1 promotes proliferation and migration of HCC cells

To investigate the biological function of FTSJ1 in HCC cells, we established FTSJ1 knockdown models in HepG2 and Huh7 cell lines. CCK-8 proliferation assays showed that FTSJ1 knockdown inhibited the proliferation of HepG2 (Figure 5A) and Huh7 (Figure 5B) cells in a time-dependent manner. In Transwell assays, the number of migrating cells was significantly lower in the si-FTSJ1 group (SI group) compared to the NC group (Figure 5C), indicating that FTSJ1 knockdown impaired the migratory capacities of HCC cells. Flow cytometry analysis further showed that FTSJ1 knockdown increased the apoptosis rate in HCC cells (Figure 5D) and induced cell cycle arrest in the G0/G1 phase (Figure 5E; increased proportion in G1 phase). In summary, FTSJ1 promotes HCC cell proliferation and migration in vitro, while also regulating cell cycle progression and apoptosis resistance, exerting oncogenic functions.

Figure 5 Downregulation of FTSJ1 inhibits proliferation and migration, and promotes apoptosis of HCC cells in vitro. (A,B) CCK-8 assay results for cell viability (proliferation) after FTSJ1 knockdown in HepG2 and Huh7 cell lines. (C) Representative images of Transwell cell migration assays (magnification, ×200) after FTSJ1 knockdown in HepG2 and Huh7 cell lines, paired with corresponding cell count quantifications. (D) Representative results of flow cytometry-based apoptosis assays after FTSJ1 knockdown in HepG2 and Huh7 cell lines. (E) FTSJ1 depletion induces G0/G1-phase cell cycle arrest in Huh7 and HepG2 cells. **, P<0.01; ***, P<0.001. CCK-8, Cell Counting Kit-8; HCC, hepatocellular carcinoma; NC, negative control; si, small interfering RNA.

FTSJ1 promotes HCC progression by regulating inflammation-related genes

To elucidate the molecular mechanism by which FTSJ1 regulates HCC progression, we analyzed TCGA-LIHC samples with high and low FTSJ1 expression (Figure 6A). GSEA revealed that DEGs were significantly enriched in the “inflammatory response” pathway (Figure 6B). To clarify the regulatory effect of FTSJ1 functional alteration on the cellular transcriptome, we compared DEGs between the SI group and the NC group; their expression changes are visualized in a volcano plot (Figure 6C). GO functional enrichment analysis was used to interpret their biological significance. Results showed that downregulated DEGs were highly enriched in RNA modification enzyme activity, particularly tRNA (guanosine/cytidine-2'-O-)-methyltransferase activity (Figure 6D). Upregulated DEGs were significantly enriched in interleukin-1 (IL-1) binding and its receptor binding activity (Figure 6E). Among these, the key inflammatory regulator IL1RN showed significant expression changes (Figure 6C).

Figure 6 FTSJ1 regulates the inflammatory signaling pathway and IL1RN mRNA stability in HCC. (A) Analysis of TCGA-LIHC samples with high and low FTSJ1 expression to explore the molecular mechanism of FTSJ1 in regulating HCC progression. (B) GSEA showing that DEGs between samples with high and low FTSJ1 expression are significantly enriched in the “inflammatory response” pathway. (C) Volcano plot visualizing the expression changes of DEGs between the SI group and the NC group, with the key inflammatory regulator IL1RN indicated. (D) GO functional enrichment analysis showing that downregulated DEGs are highly enriched in RNA modification enzyme activity, particularly tRNA (guanosine/cytidine-2'-O-)-methyltransferase activity. (E) GO functional enrichment analysis indicating that upregulated DEGs are significantly enriched in IL-1 binding and its receptor binding activity. (F) Heatmap showing the expression patterns of relevant genes. (G-N) qPCR validation of gene expression: (G) FTSJ1 (to verify knockdown efficiency), (H) JUN, (I) FOS, (J) IL1RAP, (K) TNF, (L) RELA (p65) are significantly downregulated in the SI group compared to the NC group; (M) IL1RN and (N) NFKBIA (IκBα) are significantly upregulated in the SI group. (O) Actinomycin D treatment experiments demonstrating that FTSJ1 knockdown (SI group) prolongs the half-life of IL1RN mRNA. (P) RIP assays were performed in Huh7 cells using an antibody against FTSJ1 or control IgG. The co-precipitated RNAs were analyzed by qPCR for IL1RN mRNA. Data are presented as mean ± SD (n=3). *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. Adj., adjusted; BP, biological process; CC, cellular component; DEG, differentially expressed gene; FDR, false discovery rate; GO, Gene Ontology; GSEA, gene set enrichment analysis; HCC, hepatocellular carcinoma; IgG, immunoglobulin G; IL-1, interleukin-1; IL1RN, interleukin 1 receptor antagonist; MF, molecular function; mRNA, messenger RNA; NC, negative control; NES, normalized enrichment score; qPCR, quantitative polymerase chain reaction; RIP, RNA immunoprecipitation; SD, standard deviation; SI group, si-FTSJ1 group; si, small interfering RNA; TCGA-LIHC, The Cancer Genome Atlas-Liver Hepatocellular Carcinoma.

This finding was supported by the heatmap (Figure 6F) and qPCR validation (Figure 6G-6N): specifically, the heatmap (Figure 6F) visualized the differential expression profiles of key genes between groups. qPCR results showed that FTSJ1 expression was significantly downregulated in the SI group (FTSJ1 knockdown) compared to the NC group (Figure 6G). For core members of the AP-1 transcription factor complex: JUN expression was significantly lower in the SI group (Figure 6H), and FOS expression was also markedly reduced in the SI group (Figure 6I). Additionally, IL1RAP (a key auxiliary protein in the IL-1 receptor signaling pathway) exhibited significantly decreased expression in the SI group (Figure 6J). The pro-inflammatory cytokine TNF was also significantly downregulated in the SI group (Figure 6K). RELA (p65), the core transcription factor subunit of the NF-κB pathway, showed a significant reduction in expression in the SI group (Figure 6L). In contrast, the inflammation negative regulator IL1RN was significantly upregulated in the SI group (Figure 6M), and NFKBIA (IκBα)—a key inhibitor of NF-κB—also presented significantly higher expression in the SI group (Figure 6N). Previous reports suggest RNA methylation modifications can affect mRNA stability (22). Therefore, we hypothesized that FTSJ1 might affect IL1RN mRNA stability. Indeed, actinomycin D treatment experiments showed that FTSJ1 knockdown (SI group) prolonged the half-life of IL1RN mRNA (Figure 6O). To determine whether FTSJ1 directly binds to IL1RN mRNA to mediate this destabilization, we performed RIP assays in Huh7 cells. Using an anti-FTSJ1 antibody, we observed a significant enrichment of IL1RN mRNA in the FTSJ1 immunoprecipitates compared to the control IgG (Figure 6P). This result provides direct evidence for the physical association between FTSJ1 and IL1RN mRNA. Together with the mRNA stability data, these findings support a model wherein FTSJ1 directly binds to IL1RN mRNA and promotes its degradation.

In vivo validation of FTSJ1’s role in promoting HCC progression via inflammation

To validate the function of FTSJ1 and its association with inflammation in vivo, we established a subcutaneous xenograft tumor model in nude mice using Huh7 cells. First, macroscopic observation of the excised tumor specimens (Figure 7A) showed that the tumors in the SI group were notably smaller than those in the NC group. Dynamic monitoring of tumor volume over the post-injection days (Figure 7B) further reflected the inhibitory effect of FTSJ1 knockdown: the tumor volume in the SI group was significantly lower than that in the NC group throughout the observation period. Quantitative analysis of the final tumor weight (Figure 7C) also confirmed this trend—tumor weight in the SI group was markedly reduced compared to the NC group. These results collectively indicated that FTSJ1 knockdown significantly suppressed tumor growth in vivo.

Figure 7 FTSJ1 promotes HCC progression in vivo by regulating inflammatory pathways. (A) Macroscopic observation of excised specimens from the subcutaneous xenograft tumor model established using Huh7 cells, showing that tumors in the SI group are significantly smaller than those in the NC group. (B) Dynamic monitoring of tumor volume demonstrating that FTSJ1 knockdown significantly inhibits tumor growth, with the SI group showing markedly lower tumor volume compared to the NC group. (C) Quantitative analysis of tumor weight confirming that FTSJ1 knockdown leads to significantly reduced tumor weight in the SI group relative to the NC group. (D,E) ELISA detection of serum inflammatory cytokines: (D) serum level of TNF-α is significantly reduced in nude mice from the SI group compared to the NC group; and (E) serum level of IL-6 is also significantly lower in the SI group. (F) IHC staining of tumor tissues: the proportion of Ki-67 positive cells is significantly lower in the SI group, indicating suppressed tumor cell proliferation; expression of IFN-γ, IL-1β, IL-6, and TNF-α is significantly downregulated in the SI group. *, P<0.05; **, P<0.01. ELISA, enzyme-linked immunosorbent assay; HCC, hepatocellular carcinoma; HE, hematoxylin and eosin; IFN-γ, interferon-γ; IL-1β, interleukin-1β; IL-6, interleukin-6; NC, negative control; SI group, si-FTSJ1 group; si, small interfering RNA; TNF-α, tumor necrosis factor-α.

We then detected serum inflammatory cytokines via ELISA: as shown in Figure 7D, the serum level of TNF-α in nude mice from the SI group was significantly lower than that in the NC group. Similarly, the serum IL-6 level (Figure 7E) was also notably decreased in the SI group relative to the NC group.

Subsequently, IHC staining of tumor tissues (Figure 7F) provided more detailed insights: the proportion of Ki-67-positive cells in the SI group was significantly lower, verifying that FTSJ1 knockdown inhibited tumor cell proliferation; meanwhile, the expression levels of IFN-γ, IL-1β, IL-6, and TNF-α in tumor tissues were also significantly downregulated in the SI group.

These in vivo findings are consistent with our in vitro results, collectively suggesting that FTSJ1 promotes HCC progression in vivo by regulating inflammatory pathways.

Discussion

By integrating bioinformatics big data with a multi-level experimental validation system, this study systematically elucidates the dual critical roles of FTSJ1 in HCC for the first time: it serves not only as a novel and powerful prognostic predictor independent of traditional clinicopathological factors but also as a core effector molecule driving malignant progression by modulating inflammatory microenvironment homeostasis.

Crucially, our consensus clustering analysis based on the TCGA-LIHC cohort first revealed significant heterogeneous expression patterns of the 2'-O-methyltransferase family in HCC, dividing patients into three subtypes with distinct molecular characteristics. Subtype 1, characterized by collective high expression of family members (including FTSJ1, FTSJ2, FTSJ3, FBL, etc.), exhibited the worst prognosis. This provides a new perspective for understanding HCC molecular heterogeneity and its link to dysregulated RNA epigenetic modifications. Furthermore, comparative clinicopathological analysis revealed that subtype 1 was significantly associated with more advanced pathological T stage and higher histologic grade, solidifying the clinical relevance of our molecular subtyping and linking the 2'-O-methyltransferase-high subtype to aggressive tumor phenotypes. Building on this, we identified FTSJ1 as the core member within this family driving poor prognosis.

The construction of the four-gene (FTSJ1, FTSJ2, FTSJ3, and FBL) risk model served a dual purpose. Primarily, it provided a systematic framework for screening key prognostic molecules from the 2’-O-methyltransferase family. Subsequent multivariate Cox regression confirmed FTSJ1 as the sole independent prognostic factor within this model, highlighting its unique role as the core driver and justifying our focused investigation. Regarding predictive performance, time-dependent ROC analysis revealed that the four-gene model offered a marginal but consistent advantage over FTSJ1 alone in long-term prognosis prediction, underscoring its value in integrating synergistic family information for stable long-term risk stratification. Thus, the model acted as an effective filtering tool, guiding the subsequent mechanistic focus on FTSJ1.

Regarding clinical translational value, combined analysis of TCGA, GEO, and EHBH cohorts demonstrated that FTSJ1 expression is significantly and specifically elevated in HCC tissues, and this high expression strongly correlates with poor patient prognosis. After strictly adjusting for key confounding factors, the multivariate Cox model still confirmed FTSJ1 as an independent risk factor affecting OS. More directly clinically significant, time-dependent ROC curve analysis showed that FTSJ1 achieved a superior AUC for predicting 2-year survival in the EHBH cohort compared to the traditional serum marker AFP and conventional imaging evaluation metrics. This strongly suggests that FTSJ1 could serve as an effective complement to the existing TNM staging system, particularly for recurrence risk stratification and personalized treatment decisions in early-stage HCC patients. Notably, this prognostic value appears highly specific within the 2'-O-methyltransferase family, implying that FTSJ1 participates in HCC progression through a unique molecular mechanism and highlighting its value as a specific therapeutic target.

In terms of functional mechanisms, this study rigorously confirmed the crucial driving role of FTSJ1 on core malignant phenotypes of HCC using comprehensive in vitro and in vivo experimental systems. In vitro cell experiments demonstrated that FTSJ1 knockdown significantly inhibited proliferation and migration capabilities, induced G0/G1 phase cell cycle arrest, and increased apoptosis rate. To dissect the molecular mechanism, we performed RNA-seq transcriptome analysis. GSEA clearly showed that DEGs were significantly enriched in the “hallmark inflammatory response” pathway, providing a key direction for understanding FTSJ1’s function. Our study positions FTSJ1-high tumors as a distinct ‘inflammation-driven’ HCC subtype, a conclusion supported by multiple lines of evidence: molecularly, through FTSJ1-mediated degradation of IL1RN; clinically, via association with severe peritumoral liver tissue inflammation; and functionally, confirmed by GSEA and reduced secretion of pro-inflammatory cytokines TNF-α and IL-6 upon FTSJ1 knockdown. This cohesive evidence firmly establishes the ‘inflammation-driven’ nature of FTSJ1-high HCC.

Further investigation revealed that FTSJ1’s regulation of the inflammatory network exhibits a sophisticated bidirectional characteristic: it downregulates core pro-inflammatory signaling molecules while unexpectedly upregulating IL1RN. This phenomenon was rationally explained by actinomycin D experiments and, crucially, by RIP assays, which provided direct evidence that FTSJ1 physically binds to IL1RN mRNA. These key findings strongly suggest that FTSJ1, likely through its intrinsic methyltransferase activity, directly binds to and destabilizes IL1RN transcript. Our results delineate a clear signaling logic: FTSJ1 binds to and degrades IL1RN mRNA, leading to reduced IL1RN protein levels, disinhibition of the IL-1 receptor, activation of the IL-1 signaling pathway, subsequent activation of downstream NF-κB and AP-1 pathways, increased secretion of pro-inflammatory cytokines, and ultimately tumor progression.

In the animal model, FTSJ1 knockdown resulted in reduced subcutaneous xenograft tumor volume and significantly decreased tumor weight. Mechanistically, IHC of tumor tissues showed reduced Ki-67 positivity, and levels of pro-inflammatory cytokines were significantly downregulated in both serum and local tumor tissues. These results comprehensively validate the existence of the “FTSJ1-RNA modification-inflammation pathway imbalance-HCC malignant progression” regulatory axis in vivo. From a translational medicine perspective, FTSJ1-mediated remodeling of the inflammatory network likely promotes HCC malignant progression through three interrelated pathways: direct promotion of tumor cell proliferation and survival via cytokines; induction of immune checkpoint molecules promoting immune escape; and activation of hepatic stellate cells fostering a pro-fibrotic/pro-tumorigenic microenvironment. This provides a solid mechanistic basis for explaining the poor prognosis of patients with high FTSJ1 expression.

The core innovation of this study lies in the first establishment and validation of the FTSJ1-mediated “RNA epigenetic modification-inflammatory cytokine mRNA stability-tumor microenvironment inflammatory homeostasis remodeling” regulatory axis, particularly pinpointing IL1RN mRNA stability as the key molecular switch for FTSJ1’s pro-tumorigenic function. This discovery holds dual important theoretical value: it expands the understanding of the functional diversity of RNA-modifying enzymes, and provides direct experimental evidence for the emerging concept of “inflammation-related RNA epigenetic editing” in solid tumors. The translational potential of FTSJ1 can be realized through several concrete avenues: as a superior prognostic stratification tool; as a promising therapeutic target amenable to small-molecule inhibition targeting its Rossmann-fold catalytic domain; and through combination therapy strategies, particularly with immune checkpoint inhibitors.

However, several limitations require attention in future work: the comprehensive binding landscape of FTSJ1 warrants further investigation using techniques like cross-linking immunoprecipitation sequencing (CLIP-seq); the precise methylation site(s) on IL1RN mRNA need identification; and the anti-tumor efficacy and safety of FTSJ1 inhibitors remain unevaluated in more clinically relevant HCC models. Based on these significant findings, future research can advance along three key directions: resolving the complex structure of FTSJ1 bound to target RNA; conducting high-throughput virtual drug screening targeting the FTSJ1 catalytic domain; and exploring synergistic anti-tumor effects of FTSJ1 silencing with immune checkpoint inhibitors. These in-depth studies will strongly propel FTSJ1 from a basic research discovery towards clinical translation, opening new intervention avenues to improve the poor prognosis of HCC patients.

Conclusions

FTSJ1, a 2'-O-methyltransferase, is a key oncogenic factor in HCC. It is overexpressed in HCC and serves as an independent prognostic biomarker with reliable survival predictive value. FTSJ1 promotes HCC cell proliferation and in vivo tumor growth. Mechanistically, it directly binds to IL1RN mRNA, accelerates its degradation via RNA modification, and activates IL-1/NF-κB/AP-1 inflammatory pathways. This study first uncovers the FTSJ1-IL1RN-inflammation axis, providing a novel prognostic tool and therapeutic target for HCC. Future research should focus on FTSJ1 inhibitors and combination therapies to improve outcomes.

Acknowledgments

We thank all participants for their support and help.

Footnote

Reporting Checklist: The authors have completed the MDAR and ARRIVE reporting checklists. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-693/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-693/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-693/prf

Funding: This work was supported by the National Natural Science Foundation of China (Nos. 82273349 and 82473341), the Natural Science Foundation of Science and Technology Commission of Jiading District, Shanghai (No. JDKW-2025-0050), the Qi Hang Program of Naval Medical University, Excellent Doctoral Talents Program of The Third Affiliated Hospital of Naval Medical University, and Military Medical Talents Program of The Third Affiliated Hospital of Naval Medical University.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-693/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All animal care and experimental protocols, and the human tissue microarray (TMA) study were both approved by the Ethics Committee of The Third Affiliated Hospital of Navy Medical University (ethical approval Nos. EHBHKY2023-K020-P001 and EHBHKY2023-K050-P002). Written informed consent was obtained from all participants (or their legal guardians) prior to the collection of tissue samples. All animal experiments and human tissue studies were performed in compliance with relevant local legislation and institutional requirements. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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