TRNP1 regulates tumorigenesis and enhances immunotherapy response via c-Kit/STAT3 signaling in hepatocellular carcinoma

Introduction

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, representing a significant global health burden due to its typically asymptomatic onset, poor prognosis, and high mortality rate (1-3). In addition to established risk factors such as viral hepatitis and chronic alcohol consumption, non-alcoholic fatty liver disease (NAFLD) is emerging as a major contributor to the global increase in HCC incidence (4). Current clinical treatments for HCC include surgical options such as liver transplantation and resection, locoregional therapies like radiofrequency ablation and transarterial approaches, as well as systemic therapies including chemotherapy, immunotherapy, targeted therapy and combination strategies (5-7). However, despite these therapeutic advances, the high recurrence rate, frequent metastasis, and prevalent chemoresistance result in an overall low survival rate for HCC patients (8,9). Therefore, there is an urgent need to explore novel molecular mechanisms involved in HCC development and progression to identify new therapeutic targets.

TMF1-regulated nuclear protein 1 (TRNP1) is a highly conserved nuclear protein encoded by a single exon on chromosome 1p36.11 in humans and chromosome 4 D3 in mice. The TRNP1 protein comprises 227 amino acids in humans and chimpanzees, while it consists of 223 amino acids in mice. Ectopic expression of TRNP1 in breast cancer cells, which do not typically express this protein, has promoted cell proliferation by accelerating the transition from the G0/G1 phase to the S phase of the cell cycle. Furthermore, TRNP1 is targeted for degradation via the proteasome, mediated by the TATA element regulator (TMF/ARA160) (10,11). Beyond its oncogenic role, TRNP1 is an important regulator of neural stem cell (NSC) dynamics, with high expression levels promoting NSC self-renewal and tangential expansion, while lower levels associated with radial expansion (12,13).

Importantly, recent studies have demonstrated that TRNP1 is upregulated in HCC, where its knockdown induces apoptosis in HCC cells and inhibits tumor growth. These findings suggest a potential role for TRNP1 in cellular senescence and tumor progression (14). Additionally, TRNP1 has been proposed as a diagnostic biomarker linked to mitochondrial autophagy, further underscoring its relevance to HCC prognosis (15). Given these observations, a deeper understanding of the molecular mechanisms regulated by TRNP1 is necessary to elucidate its role in HCC pathogenesis and to explore its potential as a therapeutic target.

In this study, we investigated the role of TRNP1 in HCC development and progression through in vivo and in vitro experiments, focusing on its involvement in tumorigenesis and immune evasion via the c-Kit/signal transducers and activators of transcription 3 (STAT3) signaling pathway. These findings provide insights into the molecular underpinnings of HCC and highlight TRNP1 as a promising target for future therapeutic interventions. We present this article in accordance with the ARRIVE and MDAR reporting checklists (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1084/rc).

Methods

Cell culture and transfection

In this study, the human HCC cell lines Sk-hep1, Hep3B, and HepG2 were obtained from the American Type Culture Collection (ATCC). Huh7, LM3 and the mouse HCC cell line Hepa 1–6 were obtained from the Cell Bank of Type Culture Collection of the Chinese Academy of Sciences. YY8103 was a gift from Dong Xie lab of Shanghai Institute of Nutrition and Health. All cells were cultured in their respective appropriate medium and environment. The lentiviral vector containing human TRNP1 was purchased from Hanbio (Shanghai, China). The siRNA sequence for TRNP1 is shown in Table 1. Subsequently, Sk-hep1, YY8103 and Huh7 cell densities reached about 50%, and 1 µg/mL of purinomycin was administered for 48 h, repeated 3 times. In addition, the transfection effect was verified by quantitative real-time polymerase chain reaction (q-PCR) and western blotting.

Cell proliferation assay

To perform cell proliferation tests, 2×10³ cells were seeded into 96-well plates and then incubated for 4, 24, 48, 72, 96 h respectively before adding 10 µL of Cell Counting Kit-8 (CCK-8, Hanbio, China). After 1 h incubation, the optical density was measured at 450 nm.

Colony formation assay

HCC cells were seeded in 6-well plates with 3×10³ cells/wells and incubated at 37 ℃ in 5% CO₂ for 8 days. Then washed once with PBS, fixed with 4% paraformaldehyde for 20 minutes, stained with 0.5% (w/v) crystal violet for 20 minutes, and counted the number of colonies.

Transwell cell migration and invasion assays

Using 24-well Transwell plates (8 µm; Corning, NY, USA) evaluated the migration and invasion capacity of HCC cells. For the migration test, 5×10⁴ cells suspended in serum-free medium were added to the upper chamber, and 600 µL of DMEM containing 20% FBS was added to the lower chamber. After incubation for 12 h, the cells were fixed with 4% paraformaldehyde for 20 min and stained with 0.5% (w/v) crystal violet for 20 min. At 10× magnification, the migration and invasion indices were calculated using the average number of cells in three random fields. To perform the invasion test, the Transwell chamber was coated with 50 µL diluted Matrigel (1:8, BD Biosciences) and hydrated for 2 hours. In addition to the cell incubation for 24 hours, the other steps were the same as the migration experiment.

q-PCR

According to the manufacturer’s protocol, total RNA was extracted using TRIzol reagent (Invitrogen, USA). q-PCR was performed using PrimeScript RT kit (TaKaRa, Tokyo, Japan) and SYBR Premix Ex Taq (TaKaRa, Tokyo, Japan). Target genes were quantified by 2^−ΔΔCt and normalized by glyceraldehyde 3-phosphate dehydrogenase (GAPDH). Then, select the primer sequences shown in Table 2.

Western blotting

Proteins were extracted from RIPA buffers (Sigma-Aldrich, USA) containing phosphatase inhibitors and protease inhibitors. The protein lysates were separated by sodium dodecyl sulfate polyacrylamide gels (SDS-PAGE) and then transferred to PVDF membrane. The membranes were blocked for 1 h and incubated overnight at 4 ℃ with the primary antibodies: TRNP1 (Abcam, 174303), c-Kit (CST, 3074S), STAT3 (CST, 9139S), phosphorylated STAT3 (Tyr705) (P-STAT3) (CST, 9145S), E-cadherin (CST, 14472S), N-cadherin (CST, 13116S), proliferating cell nuclear antigen (PCNA) (CST, 2586S), Caspase3 (Abmart, T40044S), Cleaved-caspase3 (Abmart, TA7022S), Bax (Abmart, T40051S), Bcl-2 (Abmart, T40056S) and β-Actin (Proteintech, 66009-1-Ig). The horseradish peroxidase (HRP)-conjugated secondary antibody was used at 1:2,000. Finally, the bands were visualized with ECL reagent (Shanghai, China).

Immunohistochemistry (IHC)

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The HCC tissues (TCGA database) were fixed with 4% paraformaldehyde and embedded in paraffin. After the sections were dewaxed and rehydrated, the peroxidase activity was blocked with hydrogen peroxide. The sections were incubated with primary antibody (TRNP1, PCNA, E-Cadherin, N-Cadherin, c-Kit, P-STAT3) at 4 ℃ overnight, and then treated with biotinylated secondary antibody for 30 min. In addition, the sections were treated with 3,3'-diaminobenzidine (DAB) antibodies.

Flow cytometric analysis for apoptosis

The cells were digested with trypsin solution (without EDTA) and centrifuged at 1,400 rpm, 5 min per session and washed 3 times with pre-cooled PBS buffer. After resuspension with 500 µL 1× binding buffer, apoptosis was analyzed with propyl iodide (PI)-Annexin V (APC) assay kit (MultiSciences, AT107, China). Treatment with 10 µL Annexin V-APC and 5 µL PI for 15 min (room temperature, away from light). The samples were loaded into flow cytometer (Beckman Coulter, Inc., Brea, CA, USA) for testing.

Animal experiments

The 6-week-old male BALB/c nude mice were purchased from Xi’an Jiaotong University (Xi’an, China). They were divided into 3 groups (n=6 per group) for the experiment. Sk-hep1 cells transfected with TRNP1 lentivirus or vector were used. 3×10⁶ cells were injected into the flank of mice. The tumor volumes were measured every 3 days, and the mice were killed and weighed at 15 days.

The 8-week-old male C57BL/6 mice were purchased from Xi’an Jiaotong University (Xi’an, China). They were divided into 4 groups (n=6 each). Hepa 1-6 cells (n=5×10⁶) containing TRNP1-NC and TRNP1-sh2 lentivirus were inoculated into the armpit. Among them, NC + anti-programmed cell death protein 1 (PD-1) and sh2 + anti-PD-1 groups were intraperitoneally injected with 0.2 mg of anti-mouse PD-1 (InVinoMAbTM) every 3 days, and the rest were injected with equal volume PBS for 3 times. The tumor volume was measured every 3 days, euthanized after 12 days, then resected and the tumor volume was calculated.

The mice were sacrificed via cervical dislocation after isofluorane (2%) anesthesia. All animal experiments were performed under a project license (No. XJTU1AF2024LSYY-382) granted by Ethics Committee of The First Affiliated Hospital of Xi’an Jiaotong University, in compliance with national or institutional guidelines for the care and use of animals.

Flow cytometry for macrophage analysis

The cells underwent digestion with DNAase I and collagenase were mechanically dissociated into single-cell suspensions, then they were resuspended in washing buffer. For extracellular staining, fluorochrome-labeled monoclonal antibodies or their isotype controls were applied at concentrations recommended by the manufacturer. After being incubated at room temperature in the dark for 15 minutes, the samples were washed and analyzed on a FACSCanto II flow cytometer. The data was processed using FACSDiva 6.1.3 software. The antibodies were APC-CY7 anti-mouse CD45 (BD Pharmingen, 557659), BV421 anti-mouse F4/80 (BD Pharmingen, 565411), APC anti-mouse CD206 (BD Pharmingen, 565250), BV786 anti-mouse CD86 (BD Pharmingen, 740900), FITC anti-mouse CD11b (BD Pharmingen, 557396).

Enzyme-linked immunosorbent assay (ELISA)

The frozen HCC tissue was thawed on ice, and a 20 mg portion was weighed and added to pre-chilled PBS. The tissue was sonicated until completely lysed, followed by centrifugation to collect the supernatant. The annexin A1 (ANXA1) content in the tumor tissue was then determined using an ELISA kit (ab264613, Abcam) according to the manufacturer’s instructions.

Statistical analysis

Each experiment was conducted using three biological replicates each including three technical replicates. GraphPad Prism software version 8.0 (GraphPad, USA) was used for statistical analysis and visualization. All experimental data were expressed as mean ± standard deviation (SD). P value <0.05 was considered statistically significant. We performed an independent T-test for continuous variable comparisons between the two groups and a one-way ANOVA analysis of variance for comparisons between multiple groups. *, P<0.05; **, P<0.01; ***, P<0.001; and ****, P<0.0001.

Results

TRNP1 is upregulated in HCC tissues

Using The Cancer Genome Atlas (TCGA) dataset, we analyzed TRNP1 expression in HCC tissues and observed a significant upregulation compared to adjacent normal tissues (Figure 1A,1B). Survival analysis revealed that patients with high TRNP1 expression exhibited significantly poorer overall survival (OS) and disease-free survival (DFS) compared to those with lower expression (OS: P<0.01, DFS: P<0.01) (Figure 1C,1D). To further explore the clinical relevance of TRNP1, we collected 19 pairs of HCC tissues and adjacent normal tissues to assess TRNP1 messenger RNA (mRNA) expression. The results demonstrated a significantly higher TRNP1 mRNA level in HCC tissues than in paracancerous tissues (Figure 1E). Additionally, protein expression analysis using western blotting and IHC confirmed the elevated TRNP1 levels in HCC tissues (Figure 1F,1G).

Figure 1 TRNP1 is up-regulated in HCC tissues. (A) The TCGA database revealed that TRNP1 expression was significantly upregulated in HCC patients. (B) For each patient, tumor tissues generally showed higher expression levels of TRNP1 compared to normal tissues. (C,D) The OS (C) and DFS (D) of the patients with HCC was computed with the GEPIA web tool. (E) TRNP1 mRNA expression in 19 paired HCC tissues and nontumoral liver tissues. (F) Images (left panel) and quantified analysis (right panel) of 9 paired HCC tissues and nontumoral liver tissues detected by western blot. (G) Representative images (left panel) and quantified analysis (right panel) of IHC staining of TRNP1 in HCC tissues and nontumoral liver tissues. Scale bar: 50 µm. **, P<0.01; ***, P<0.001; ****, P<0.0001. DFS, disease-free survival; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; GEPIA, Gene Expression Profiling Interactive Analysis; HCC, hepatocellular carcinoma; HR, mRNA, messenger RNA; N, OS, overall survival; T, TCGA, The Cancer Genome Atlas; TPM, TRNP1, TMF1-regulated nuclear protein 1.

TRNP1 promotes HCC proliferation, migration, invasion, and apoptosis

To determine the specific role of TRNP1 in HCC cells, we assessed its expression across various HCC cell lines, including HepG2, Hep3B, Huh7, Sk-hep1, YY8103, and HCC-LM3 (Figure 1A). TRNP1 was expressed at higher levels in Sk-hep1 and YY8103 cells compared to HepG2, Hep3B, Huh7, and HCC-LM3. Accordingly, Sk-hep1 and YY8103 cell lines were selected for further functional studies. Stable TRNP1 knockdown was achieved, as confirmed by western blot analysis (Figure 2B). Knockdown of TRNP1 led to significantly reduced cell viability, as shown by the CCK-8 assay and colony formation assay (Figure 2C,2D). Furthermore, migration and invasion assays revealed that TRNP1 knockdown notably impaired these capacities in Sk-hep1 and YY8103 cells (Figure 2E,2F). Apoptosis was significantly increased in TRNP1 knockdown cells compared to controls (Figure 2G).

Figure 2 TRNP1 knockdown affects the proliferation, invasion, migration and apoptosis of HCC. (A) The protein expression of TRNP1 in the HCC cell lines. (B) Images (left panel) and quantified analysis (right panel) of TRNP1 expression detected by western blot in Sk-hep1 and YY8103 cells. (C) Cell proliferation of TRNP1-NC, TRNP1-sh1, and TRNP1-sh2 groups in Sk-hep1 and YY8103 cells was evaluated by CCK-8 assay. (D) Images (left panel) and quantified analysis (right panel) of clone formation assays in Sk-hep1 and YY8103 cells with TRNP1-NC, TRNP1-sh1 and TRNP1-sh2. (E,F) Images (left panel) and quantified analysis (right panel) of transwell migration and invasion assays in Sk-hep1 and YY8103 cells with TRNP1-NC, TRNP1-sh1 and TRNP1-sh2. Scale bars: 100 µm. (G) Flow cytometric assays detecting the effects of TRNP1 knockdown on apoptosis in HCC cells (left panel) and statistical results (right panel). (H) Images (left panel) and quantified analysis (right panel) of apoptosis-related proteins expression detected by western blot in Sk-hep1 and YY8103 cells. (I) Expression of stem cell genes in Sk-hep1 and YY8103 cells with/without TRNP1 knockdown. CCK-8, Cell Counting Kit-8; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; HCC, hepatocellular carcinoma; NC, negative control; TRNP1, TMF1-regulated nuclear protein 1.

We assessed the expression of apoptosis-related proteins to investigate the underlying mechanism of increased apoptosis. TRNP1 knockdown cells displayed increased levels of pro-apoptotic Bax and cleaved-caspase3 and reduced levels of the anti-apoptotic protein Bcl-2 and stem cell genes (Figure 2H,2I). To further assess TRNP1’s role, a stable TRNP1 overexpression model was established in the Huh7 cell line, confirmed by western blotting (Figure 3A). Overexpression of TRNP1 promoted cell viability, colony formation, migration, and invasion in a series of assays (Figure 3B-3E).

Figure 3 Overexpression of TRNP1 affects the proliferation, invasion and migration of HCC cells. (A) Western blot images (left panel) and quantitative analysis (right panel) of TRNP1 expression in Huh7 cells. (B) Cell proliferation in the TRNP1-CON and TRNP1-OE groups in Huh7 cells was assessed by CCK-8 assays. (C) Images (left panel) and quantitative analyses (right panel) of clonal formation experiments in the TRNP1-CON and TRNP1-OE groups in Huh7 cells. (D,E) Images (left panel) and quantitative analysis (right panel) of Transwell migration and invasion experiments of TRNP1-CON and TRNP1-OE in Huh7 cells. Scale bars: 100 µm. CCK-8, Cell Counting Kit-8; CON; HCC, hepatocellular carcinoma; OE, TRNP1, TMF1-regulated nuclear protein 1.

TRNP1 promotes tumor growth in vivo

To validate the role of TRNP1 in vivo, we established a subcutaneous xenograft model using Sk-hep1 cells transfected with either TRNP1 knockdown or control vectors. Tumor growth was significantly reduced in the TRNP1 knockdown group compared to the control group, as evidenced by smaller tumor volumes and reduced growth rates (Figure 4A-4C). Furthermore, TRNP1 knockdown tumors exhibited reduced expression of PCNA, a marker of cell proliferation and a potential diagnostic biomarker for HCC (16,17), as confirmed by western blotting and IHC staining (Figure 4D,4E). These findings further support the role of TRNP1 in promoting tumorigenesis in HCC.

Figure 4 TRNP1 promotes HCC proliferation in vivo. The representative images (A), tumor weight (B) and tumor growth (C) of xenograft tumors from Sk-hep1 cells with TRNP1-NC, TRNP1-sh1 and TRNP1-sh2. (D) Western blot images (left) and quantitative analysis (right) of various markers in Sk-hep1 cells with/without TRNP1 knockdown. (E) Representative images (left panel) and quantitative analysis (right panel) of IHC staining of PCNA in xenografts of Sk-hep1 cells with TRNP1-NC, and TRNP1-sh2. Scale bars: 50 µm. HCC, hepatocellular carcinoma; IHC, immunohistochemistry; NC, negative control; PCNA, proliferating cell nuclear antigen; TRNP1, TMF1-regulated nuclear protein 1.

TRNP1 modulates malignant phenotype via the c-Kit/STAT3 signaling pathway

To elucidate the regulatory pathways influenced by TRNP1 in HCC, transcriptomic sequencing was performed. Differential gene expression analysis, visualized through a volcano plot, revealed significant alterations in gene expression in Sk-hep1 cells following TRNP1 knockdown compared to the negative control (NC) group (Figure 5A). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis highlighted the Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling pathway as one of the top 20 enriched pathways (Figure 5B). Specifically, the KIT mRNA expression was significantly reduced in TRNP1 knockdown cells (fold change =0.41), further confirmed through q-PCR (Figure 5C). Furthermore, western blot analysis revealed a notable decrease in both c-Kit and P-STAT3 levels in TRNP1 knockdown cells and subcutaneous tumors derived from these cells (Figure 5D-5F). These findings indicate that TRNP1 exerts its oncogenic effects in HCC by activating the c-Kit/STAT3 signaling pathway.

Figure 5 TRNP1 affects the malignant phenotype by targeting the c-Kit/STAT3 signaling pathway. (A) Volcano plot of differentially expressed genes in Sk-hep1 cells with/without TRNP1 knockdown. (B) KEGG enrichment analysis of differentially expressed genes. (C) Expression of relative KIT mRNA in Sk-hep1 cells with/without TRNP1 knockdown. (D) Western blot images (left) and quantitative analysis (right) of various markers in Sk-hep1 and YY8103 cells with/without TRNP1 knockdown. (E) Images (left panel) and quantified analysis (right panel) of EMT markers (E-cadherin, N-cadherin) detected by western blot in Sk-hep1 and YY8103 cells. (F,G) Representative images (left) and quantitative analysis (right) of IHC staining of c-Kit, P-STAT3 and E-cadherin, N-cadherin in xenografts of Sk-hep1 cells with/without TRNP1 knockdown. Scale bars: 50 µm. EMT, epithelial-mesenchymal transition; FC, fold change; FDR, false discovery rate; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; IHC, immunohistochemistry; KEGG, Kyoto Encyclopedia of Genes and Genomes; mRNA, messenger RNA; NC, negative control; STAT3, signal transducers and activators of transcription 3; TRNP1, TMF1-regulated nuclear protein 1.

Epithelial-mesenchymal transition (EMT) is a crucial mechanism in cancer cell migration and invasion, driving tumor progression and metastasis (18-20). To assess the influence of TRNP1 on EMT, we analyzed the expression of key EMT markers. Western blotting revealed that TRNP1 knockdown led to increased levels of the epithelial marker E-cadherin and decreased levels of the mesenchymal marker N-cadherin in Sk-hep1 and YY8103 cells (Figure 5E). These results were corroborated by IHC analysis (Figure 5G). Together, these findings suggest that TRNP1 facilitates EMT in HCC, promoting an aggressive malignant phenotype.

TRNP1 knockdown enhances therapeutic response to PD-1 blockade

PD-1, encoded by the PDCD1 gene, plays a critical role in immune suppression and has become a key target in immunotherapy for HCC (21-23). Using the Gene Expression Profiling Interactive Analysis (GEPIA) bioinformatics tool, we analyzed the correlation between TRNP1 and PDCD1 expression in HCC and found a significant positive correlation (Figure 6A). To further investigate this interaction, we established a mouse model in which C57BL/6 mice bearing Hepa 1-6 cells (transfected with either TRNP1 knockdown or NC vectors) were treated with anti-mouse PD-1 antibody (anti-PD-1) (Figure 6B,6C). Results showed that either TRNP1 knockdown or anti-PD-1 treatment significantly reduced tumor growth compared to the control group. Importantly, the combination of TRNP1 knockdown and anti-PD-1 therapy further reduced tumor weight and volume (Figure 6D,6E).

Figure 6 TRNP1 knockdown enhances the therapeutic response of HCC to PD-1 blockade. (A) The correlation between the gene expression of TRNP1 and PDCD1 in human HCC samples using the GEPIA web tool. (B) Western blot images (left) and quantitative analysis (right) of TRNP1 knocked down in Hepa 1-6 cells are shown below. The representative images (C), tumor weight (D) and tumor growth (E) of xenograft tumors from Hepa 1-6 cells with NC and shTRNP1 with/without anti-PD-1. (F) Lollipop graph illustrates the correlation between immune infiltration and TRNP1 expression. (G) The proportion of M1 and M2 macrophages in NC and TRNP1 knockeddown Hepa 1–6 subcutaneous tumors was detected by flow cytometry, along with statistical data. (H) Volcano plot of ANXA1 expression in Sk-hep1 cells with or without TRNP1 knockdown. q-PCR (I) and ELISA (J) analyze the expression of ANXA1 in mouse subcutaneous tumors tissues. ANXA1, annexin A1; ELISA, enzyme-linked immunosorbent assay; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; GEPIA, Gene Expression Profiling Interactive Analysis; HCC, hepatocellular carcinoma; NC, negative control; PD-1, programmed cell death protein 1; q-PCR, quantitative real-time polymerase chain reaction; TRNP1, TMF1-regulated nuclear protein 1.

According to TCGA database, TRNP1 expression was positively correlated with the presence of natural killer (NK) CD56bright cells, macrophages, Th2 cells, T follicular helper (TFH) cells, and T effector memory (Tem) cells, among others. Conversely, TRNP1 was negatively correlated with Th17 cells, neutrophils, gamma delta (Tgd) T cells, central memory T (TCM) cells, eosinophils, and CD8⁺ T cells (Figure 6F). Because macrophages play an important role in the tumor immune microenvironment, we analyzed the proportion of M1 and M2 macrophages in Hepa 1–6 subcutaneous tumors. When TRNP1 was knocked down, the proportion of M1 macrophages in tumor tissues increased significantly, while the proportion of M2 macrophages decreased, leading to a reduction in cancer-promoting M2 macrophages (Figure 6G). At the same time, based on transcriptome results, we identified the cytokine ANXA1 (Figure 6H). Studies have shown that ANXA1 promotes malignant growth and metastasis in mice by increasing the infiltration of tumor associated macrophages (TAMs) and M2 polarization in HCC (24). The results of q-PCR and ELISA demonstrated that compared with the NC group, the level of ANXA1 in the TRNP1 knockout group was significantly lower (Figure 6I,6J), thereby reducing macrophage M2 polarization and increasing M1 polarization. These data suggest that TRNP1 can modulate immune cell infiltration in the tumor microenvironment, especially the macrophages, influencing the response to PD-1 blockade therapy.

Discussion

HCC ranks as the fourth leading cause of cancer-related mortality worldwide despite advancements in diagnostic methods and treatment strategies over recent years (25,26). Unfortunately, effective therapeutic options for patients with intermediate and advanced HCC remain limited. In this study, we demonstrated that TRNP1 expression is significantly elevated in HCC and is associated with enhanced cell proliferation, migration, invasion, and inhibition of apoptosis. Our findings indicate that TRNP1 promotes HCC progression via activation of the c-Kit/STAT3 signaling pathway, establishing it as a tumor-promoting factor with the potential to serve as a clinical biomarker in HCC.

Beyond its known role in neural development and cell self-renewal, TRNP1 has garnered attention in cancer research due to its oncogenic potential. Initially identified in breast cancer, TRNP1 has been shown to enhance cell proliferation by facilitating progression through the G0/G1 to S phase transition, mediated by TMF1 and the E3 ubiquitin ligase (10). In HCC, TRNP1 has been implicated as a prognostic biomarker, with its expression correlating with immune cell infiltration and patient outcomes (27,28). Consistent with these reports, we observed that TRNP1 knockdown in highly metastatic HCC cell lines (Sk-hep1 and YY8103) led to reduced tumor growth, both in vitro and in vivo. In contrast, TRNP1 overexpression in Huh7 cells resulted in increased tumor growth. Importantly, EMT, a critical process in cancer metastasis, was shown to be influenced by TRNP1. Our results suggest that TRNP1 enhances the EMT process, facilitating the transformation of epithelial cells to a more mesenchymal, invasive phenotype, a key factor in HCC metastasis (29,30).

The c-Kit (CD117) receptor, a type III receptor tyrosine kinase family member, is a well-known regulator of cell proliferation and survival. Dysregulated c-Kit signaling has been implicated in various malignancies, including gastrointestinal stromal tumors, acute myeloid leukemia, and melanoma (31,32). The present study demonstrated that TRNP1 knockdown significantly reduced c-Kit expression, as confirmed by transcriptomic analysis, q-PCR, and western blotting. This reduction in c-Kit led to downstream inhibition of the JAK/STAT pathway, specifically reducing P-STAT3 levels. Given the established role of the c-Kit/STAT3 axis in cancer progression, these findings highlight the critical contribution of TRNP1 in promoting HCC growth through this pathway.

Moreover, our study explored the interaction between TRNP1 and immune modulation, particularly in PD-1 blockade therapy. PD-1 is a well-established immunosuppressive molecule, primarily expressed in T cells, B cells, and NK cells (33,34). Immunotherapies targeting the PD-1/programmed death ligand 1 (PD-L1) checkpoint have shown promise in treating HCC, particularly in combination with other therapies such as anti-angiogenic tyrosine kinase inhibitors (35,36). Our findings indicate that TRNP1 knockdown enhances the therapeutic efficacy of PD-1 blockade. Specifically, TRNP1 knockdown, in combination with anti-PD-1 therapy, significantly reduced tumor volume compared to either treatment alone. Furthermore, we identified correlations between TRNP1 expression and immune cell infiltration in the tumor microenvironment, including positive correlations with cells such as NK CD56bright cells, macrophages and Th2 cells and negative correlations with CD8⁺ T cells and Th17 cells (37,38). Specifically, the knockdown of TRNP1 leads to reduced ANXA1 levels, thereby shifting the balance of tumor-associated macrophages toward an increased proportion of the M1 subtype and a decreased proportion of the M2 subtype. These findings suggest that TRNP1-mediated modulation of ANXA1 expression in tumor cells may influence the polarization status of adjacent immune cells within the tumor microenvironment. The knockdown of TRNP1 led to an increase in the proportion of M1 macrophages and a decrease in M2 macrophages in tumor tissues. While these findings suggest that TRNP1 may modulate immune infiltration in HCC, the precise mechanisms underlying these effects warrant further investigation.

Despite the promising findings, our study has several limitations that warrant consideration. The research was conducted primarily using established HCC cell lines and xenograft mouse models. While these models are valuable, they may not fully recapitulate the heterogeneity and complex immune interplay of human HCC. Therefore, validation of our findings in patient-derived organoids or xenografts and analysis of TRNP1 expression in large clinical cohorts of ICI-treated patients are necessary next steps. Furthermore, the precise molecular mechanism by which TRNP1, a nuclear protein, regulates the expression or activity of the cell surface receptor c-Kit remains to be fully elucidated. Future studies should investigate whether TRNP1 acts as a transcription factor or co-factor for the KIT gene, or if it influences c-Kit through an indirect mechanism. Finally, while we focused on the c-Kit/STAT3 axis, it is plausible that TRNP1 may regulate other oncogenic pathways that contribute to its effects, which represents another avenue for future investigation.

Conclusions

In conclusion, this study establishes TRNP1 as a key oncogenic factor in HCC, driving tumor progression by activating the c-Kit/STAT3 signaling pathway. Our findings demonstrate that TRNP1 knockdown effectively inhibits HCC cell proliferation, migration, and invasion while enhancing apoptosis, thereby attenuating tumor growth. Furthermore, combining TRNP1 knockdown with anti-PD-1 immunotherapy represents a promising therapeutic strategy, as it significantly enhances the efficacy of immune checkpoint inhibition. These insights suggest that targeting TRNP1 may offer a novel approach to improving treatment outcomes for patients with HCC, particularly when integrated with immunotherapeutic interventions.

Acknowledgments

We thank all the authors for their contributions to this study.

Footnote

Reporting Checklist: The authors have completed the ARRIVE and MDAR reporting checklists. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1084/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1084/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1084/prf

Funding: This work was partially supported by grants from National Natural Science Foundation of China (No. 82002480) and the Key Research & Development Program of Shaanxi Province (General Project, Social Development Field) (No. 2024SF-YBXM-199).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1084/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 experiments were performed under a project license (No. XJTU1AF2024LSYY-382) granted by Ethics Committee of The First Affiliated Hospital of Xi’an Jiaotong University, in compliance with national or institutional guidelines for the care and use of animals.

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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