2.1. Patient Selection and Tumor Specimens

Paired normal and HCC tissues were obtained from 124 HCC patients who underwent tumor resection surgery at the Second Affiliated Hospital of Xi’an Jiaotong University. All patients had not received systemic anticancer or immunosuppressive therapy for at least 3 months before surgery. This study was approved by the Ethics Committee of Xi’an Jiaotong University (XJTU-2021045) and adhered to the standards set in the Declaration of Helsinki.

2.2. CD8⁺ T Cells Isolation

The EasySep Direct Human CD8⁺ T-Cell Isolation Kit (StemCell Technologies, Canada) was used for CD8⁺ T cell isolation from peripheral blood mononuclear cells (PBMCs) of HCC patients. CD8⁺ T cells were incubated with anti-CD3/CD28 antibodies for 2 days to activate T cells.

2.3. Cell Culture and Transfection

HCC cell lines (HCCLM3 and MHCC97H) were purchased from SUNNCELL (Wuhan, Hubei, China). DMEM (Gibco, Rockville, MD, USA) medium supplemented with FBS (10%, Gibco) and P/S (1%, 100 μL/mL) was used for cell culture at 37°C in a 5% CO₂ atmosphere.

WTAP overexpression vector (pcDNA3.1-WTAP) was obtained from Sangon Biotech (Shanghai, China). GenePharma (Shanghai, China) synthesized WTAP siRNA, YTHDF1 siRNA and NC siRNA. Lentivirus-mediated WTAP short hairpin RNA (sh-WTAP) vectors were constructed by GeneChem (Shanghai, China). Anti-PD-1 (#BE0188) and control IgG (#BE0297) were purchased from BioXcell (NH, USA). Lipofectamine 3000 (Invitrogen Corporation, CA, USA) was used for cell transfection.

2.4. Flow Cytometry Analysis

Normal liver tissue and HCC tumor-infiltrating T cells were stained with anti-TCF1, anti-CD4, anti-CD8a, and anti-PD1 antibodies. Flow cytometry data were acquired with an LSR-II instrument, and cells were sorted on an Aria II sorter. FlowJo software (TreeStar) was used for data analysis.

2.5. Western Blot Analysis

Total protein extraction was conducted using RIPA (Beyotime, Shanghai, China), and protein concentration was determined using a Pierce BCA Protein Assay Kit (Thermo). Approximately 50 μg of protein samples were separated by SDS-PAGE and was transferred onto PVDF membranes. Membranes were then incubated with primary antibodies against WTAP (#56501, Cell Signaling Technology [CST], Boston, MA, USA); PD1 (ab52587, Abcam, Cambridge, UK); YTHDF1 (ab290749, ab52587); and YTHDF2 (ab220163, ab52587) after blocking with nonfat milk (5%). Secondary antibodies were applied for membrane incubation, and band visualization was performed using an enhanced chemiluminescence kit (Beyotime). Band intensities were analyzed using ImageJ software.

2.6. RT-qPCR

Total RNA extraction was performed using TRIzol reagent (Takara, Dalian, China). cDNA was obtained using a PrimeScript RT reagent Kit (Takara). RT-qPCR was carried out using a TB Green Premix Ex Taq kit (TaKaRa). The primers used were as follows: WTAP-F-5^′-TTC CCA AGA AGG TTC GAT TG-3^′, WTAP-R-5^′-TGC AGA CTC CTG CTG TTG TT-3^′; PD1-F-5^′-ACC TGG GTG TTG GGA GGG CA-3^′, PD1-R-5^′-GGA GTG GAT AGG CCA CGG CG-3^′; GAPDH-F-5^′-GGA GCG AGA TCC CTC CAA AAT-3^′, GAPDH-R-5^′- GGC TGT TGT CAT ACT TCT CAT GG-3^′. GAPDH served as the internal control. Gene expressions were calculated using the 2^−ΔΔct method.

2.7. ELISA

The levels of perforin, IFN-γ, granzyme-B, and TNF-α produced by CD8⁺ T cells were determined using corresponding commercial ELISA kits (eBioscience, CA, USA) following the manufacturer’s guidelines.

2.8. Methylated RNA Immune-Precipitation (MeRIP)-qPCR Assay

Fragmented RNA samples from CD8⁺ T cells were immunoprecipitated using the Magna MeRIP m6A Kit (Millipore, Boston, MA, USA) and anti-m6A antibody (ab286164, Abcam) following the instructions of the manufacturer. The level of m6A-modified PD1 was detected by RT-qPCR.

2.9. Cell Apoptosis

An Annexin V-FITC/PI apoptosis detection kit (Beyotime) was used for cell apoptosis detection. HCCLM3 and MHCC97H cells were collected, washed with PBS, and sequentially incubated with Annexin V (5 μL) and PI (1 μL) for 10 min. Apoptotic cells were measured using a flow cytometer (Becton Dickinson, San Jose, CA, USA).

2.10. Transwell Assay

Cell invasion of HCCLM3 and MHCC97H cells was assessed using 8 μm microporous filters coated with Matrigel (Becton, Bedford, MA, USA). 1 × 10⁴ cells were added to the upper chamber with 200 μL of serum-free DMEM medium, and the bottom chamber was supplemented with DMEM medium containing 10% FBS. After 24 h, cells on the lower surface of the filter were fixed with formaldehyde and stained with hematoxylin for 20 min. Finally, cells in five randomized regions were photographed and counted.

2.11. Colony Formation Assay

HCCLM3 or MHCC97H cells (5 × 10⁴) were seeded in 6-well plates. After treatment, cells were fixed in paraformaldehyde (4%) for 20 min at 4°C, followed by staining with crystal violet (0.25%) for 20 min at room temperature. Cells were then washed with ddH₂O to remove excess staining solution. Colony formation was observed using a light microscope, and images were captured. A colony was defined as consisting of at least 50 cells.

2.12. RNA Immunoprecipitation (RIP)

RIP assay was performed using the Magna RIP Kit (17–700, Millipore, MA) following the manufacturer’s instructions. Briefly, anti-WTAP, anti-YTHDF1, anti-YTHDF2, and IgG antibodies were incubated with protein A/G magnetic beads for 30 min at room temperature. Cell lysates (more than 2 × 10⁷ cells per sample) were collected and incubated with the bead-antibody conjugates at 4°C overnight. The beads were then treated with proteinase K for 30 min to remove proteins. The RNA in the immune complexes was detected using RT-qPCR.

2.13. EdU Assay

HCCLM3 or MHCC97H cells (6 × 10³/well) were seeded in a 96-well plate for 24 h, and EdU reagent (50 μM, 100 μL) was added. Two hours later, cells were sequentially treated with paraformaldehyde (4%, 30 min), Triton X-100 (0.5%, 10 min), and 1x Apollo Stain Buffer (0.5 h). After staining with DAPI, cells were photographed under a fluorescence microscope (Nikon, Japan).

2.14. Humanized Mouse Generation

NSG mice were purchased from VITALSTAR (Beijing, China) and raised under SPF conditions. CD34⁺ hematopoietic stem cells were obtained from the human fetal liver tissues as previously described [25]. NSG mice (1–3 day old) were irradiated (1 Gy) and injected intravenously with CD34⁺ human hematopoietic stem cells (2 × 10⁵ cells/mouse). The reconstitution of the human immune system was analyzed using peripheral blood from humanized NSG (HuNSG) mice 3 months after injection and before the start of the experiment.

2.15. In Vivo Tumor Growth

This study was approved by the Animal Care and Use Committee of the Xi’an Jiaotong University. HuNSG mice were randomly divided into 5 groups (n = 8): (1) control group: 100 μL of PBS containing 2 × 10⁵ HCCLM3 cells were injected into the right flank of the mice; (2) NC shRNA group: 100 μL of PBS containing 2 × 10⁵ HCCLM3 cells infected with Lv-sh-NC were injected into the right flank of the mice; (3) sh-WTAP group: 100 μL of PBS containing 2 × 10⁵ HCCLM3 cells infected with Lv-sh-WTAP were injected into the right flank of the mice; (4) anti-PD1 group: 100 μL of PBS containing 2 × 10⁵ HCCLM3 cells were injected into the right flank of the mice, followed by Opdivo (100 μg) injection through the tail vein for 2 weeks (three times a week); and (5) combination group: 100 μL of PBS containing 2 × 10⁵ HCCLM3 cells infected with Lv-sh-WTAP were injected into the right flank of the mice, followed by Opdivo (100 μg) injection through the tail vein for 2 weeks (three times a week). Twenty-eight days after injection, tumor tissues and spleen tissues were isolated for subsequent studies.

2.16. scRNA-Seq Data Processing and Analysis

The single-cell RNA sequencing data comprising CD45⁺ immune cells isolated from five distinct immune-related anatomical sites in HCC patients were obtained from the GEO dataset GSE140228. Single-cell RNA sequencing data were processed using the Seurat package. Initial quality control removed cells with fewer than 3 detected genes (minimum cells = 3), UMI counts below 500, gene counts under 250 (n gene > 250), or mitochondrial content exceeding 10% (mitoratio < 0.1). The SCTransform normalization and integration workflow was applied, followed by UMAP dimensionality reduction. Cell clusters were annotated via singleR to characterize CD8⁺ T cell heterogeneity.

2.17. Statistical Analysis

SPSS 22.0 was used for statistical analyses, and data were presented as mean ± SD. Each experiment was independently repeated at least three times. Statistical significance was assessed using Student’s t-test and one-way ANOVA, followed by Tukey’s post hoc test. p < 0.05 indicated statistically significant.

3.1. High Levels of WTAP Were Associated With Shorter Survival in HCC Patients

The GEPIA online database was used to analyze the expression pattern of WTAP in liver cancer and normal tissues, as well as its correlation with the overall survival rate and clinical stage of liver cancer patients. The data showed that WTAP levels did not differ significantly between liver cancer and para-carcinoma tissues (Figure 1A). Moreover, no prominent difference was observed in WTAP expression among liver cancer specimens of different stages (Figure 1B). However, higher levels of WTAP predicted a shorter median survival time (MST) in liver cancer patients (<50 vs. >80 months, p = 0.0053) (Figure 1C).

3.2. WTAP Was Upregulated in Tumor-Infiltrating Exhausted CD8⁺ T Cells

It has been reported that co-expression of PD1 and TCF1 by CD8⁺ T cells is indicative of T cell exhaustion. We first screened for tissue-infiltrating T cells from adjacent and tumor tissues, and further isolated CD8⁺ T cells (Figure 2A). Subsequently, the proportion of PD1^highTCF1⁺ T cells in the para-cancer and tumor groups was analyzed. The proportion of PD1^highTCF1⁺ CD8⁺ T cells was significantly higher in tumor tissues compared to the para-cancer group (Figure 2B). Based on the median proportion of tumor-infiltrating PD1^highTCF1⁺ CD8⁺ T cells, 124 HCC patients were divided into low-ratio and high-ratio groups. The Kaplan–Meier curve showed a significantly higher 3-year survival rate among patients in the low-ratio group compared to the high-ratio group (Figure 2C). Moreover, PD1 protein levels and WTAP mRNA levels in tissue-infiltrating CD8⁺ T cells were increased in the HCC group compared to the para-cancer group (Figure 2D,E). Table 1 lists the relationships between the expression levels of WTAP in tissue-infiltrating CD8⁺ T cells and the clinicopathologic characteristics of 124 HCC patients. High expression of WTAP and PD1 was associated with advanced pathological stage in HCC, while elevated PD1 expression additionally correlated with higher histological grade (Figure 2F–I). However, neither WTAP nor PD1 expression levels showed significant associations with patient age or gender (Figure S1A–D). ROC curve analysis was used to evaluate the predictive value of WTAP in the diagnosis of liver cancer. The area under the curve (AUC) of the WTAP was 0.98 (Figure 2J). Pearson’s correlation analysis indicated a strong positive correlation between PD1 and WTAP levels (Figure 2K). Furthermore, analysis of the TISIDB database revealed that the expression levels of both WTAP and PD-1 showed significant positive correlations with the abundance of activated CD8⁺ T cells (Figure S1E,F). Additionally, scRNA-seq data comprising CD45⁺ immune cells isolated from five distinct immune-related anatomical sites in HCC patients were downloaded from the GSE140228 dataset. Figure S1G,H illustrates the differential distribution patterns of TCF1 and WTAP among distinct CD8⁺ T cell subsets within the tumor immune microenvironment of HCC. Quantitative analysis revealed that TCF1⁺ and WTAP⁺ cells accounted for 11.8% and 31.6% of PD-1⁺ CD8⁺ T cell subpopulations, respectively (Figure S1I,J).

3.3. WTAP Overexpression Suppressed CD8⁺ T Cell Function and Upregulated PD1 Expression

To explore the role of WTAP in CD8⁺ T cell function, different concentrations of WTAP overexpression vectors were transfected into CD8⁺ T cells, which were then activated by anti-CD3/anti-CD28 stimulation. After transfection with pcDNA-WTAP, WTAP expression was notably elevated in a concentration-dependent manner (Figure 3A–C). Some cytokines, including TNF-α, IFN-γ, perforin, and granzyme-B, play key roles in antitumor response. Overexpression of WTAP significantly suppressed CD8⁺ T cell proliferation and cytokine secretion (including perforin, IFN-γ, granzyme-B, and TNF-α) (Figure 3D–I). Additionally, ectopic expression of WTAP notably increased PD1 expression at both the transcription and translation levels (Figure 3J–L).

3.4. Silencing WTAP Promoted CD8⁺ T Cell Function and Suppressed PD1 Expression

Next, 30 nM or 60 nM WTAP siRNA was used to inhibit WTAP expression in CD8⁺ T cells. Treatment with WTAP siRNA significantly reduced WTAP expression in a dose-dependent manner (Figure 4A–C). Moreover, CD8⁺ T cells treated with 60 nM WTAP siRNA, but not 30 nM, showed significantly increased cell proliferation and cytokine secretion levels (Figure 4D–I). Furthermore, silencing WTAP markedly decreased PD1 expression in CD8⁺ T cells (Figure 4J–L).

3.5. WTAP Overexpression in CD8⁺ T Cells Promoted Malignant Progression of HCC Cells

To explore the effect of CD8⁺ T cells overexpressing or silencing WTAP on the behavior of HCC cells, pcDNA-WTAP, or WTAP siRNA was transfected into CD8⁺ T cells, which were then co-cultured with HCCLM3 or MHCC97H cells. Compared to the vector group, overexpressing WTAP in CD8⁺ T cells significantly facilitated cell proliferation, invasion, and colony formation, while inhibiting apoptosis in HCC cells (Figure 5A–G and S2A-D). Conversely, knockdown of WTAP in CD8⁺ T cells hindered cell proliferation, invasion, and clone formation, while promoting apoptosis (Figure 5A–G).

3.6. WTAP Regulated PD1 Expression in an m6A-Dependent Manner

We first examined whether the key m6A-modifying enzymes bind to PD1 mRNA. The data showed that the m6A methyltransferases WTAP and the m6A “reader” YTHDF1, but not YTHDF2, bound to PD1 mRNA (Figure 6A). Next, we investigated whether WTAP regulates PD1 expression by modulating its m6A level. The findings indicated that overexpression of WTAP in CD8⁺ T cells increased the m6A level of PD1, whereas knockdown of WTAP had the opposite effect (Figure 6B). To determine whether YTHDF1 is involved in regulating the m6A level of PD1, we transfected pcDNA-WTAP into CD8⁺ T cells either alone or in combination with YTHDF1 siRNA. Overexpression of WTAP did not affect the protein level of YTHDF1, while transfection with YTHDF1 siRNA markedly reduced YTHDF1 expression (Figure 6C,D). Knockdown of YTHDF1 reversed the increase in the protein levels of PD1 (Figure 6C,E). Analysis of the GEPIA database and validation in HCC samples revealed that WTAP expression was significantly positively correlated with TIM3 and CTLA4, but not with LAG3 (Figure S3A-F). Overexpression of WTAP markedly increased TIM3 and CTLA4 protein levels, while leaving LAG3 unaffected (Figure S3G, H). Notably, WTAP exhibited the most pronounced upregulatory effect on PD1. Additionally, silencing YTHDF1 effectively abolished the inhibitory effect of WTAP overexpression on IFN-γ, granzyme-B, and perforin secretion levels (Figure 6G–I).

3.7. WTAP and YTHDF1 in CD8⁺ T Cells Synergistically Regulate the Malignant Behavior of HCC Cells

To further explore the effects of WTAP and YTHDF1 in CD8⁺ T cells on the behavior of HCC cells, we transfected pcDNA-WTAP either alone or together with YTHDF1 siRNA into CD8⁺ T cells, which were then co-cultured with HCCLM3 or MHCC97H cells. The data showed that silencing YTHDF1 reversed the increased cell proliferation, invasion, and clone formation, as well as the decreased apoptosis caused by WTAP overexpression in HCC cells (Figure 7A–F and Figure S4A-F).

3.8. WTAP Silencing Enhanced the Promotion of Anti-PD1 on the Activity and Anti-Tumor Capacity of CD8⁺ T Cells

We explored whether silencing WTAP affects the ability of anti-PD1 to enhance the activity of CD8⁺ T cells. Compared to the control group, anti-PD1 treatment significantly reduced the PD1 protein level, without altering the expression of WTAP (Figure S5A–C). In contrast, WTAP knockdown decreased the expression of both PD1 and WTAP (Figure S5A–C). Anti-PD1 treatment notably promoted CD8⁺ T cell proliferation (Figure S5D,E) and the secretion of IFN-γ, perforin, granzyme-B, and TNF-α, compared to the control group (Figure S5F–I). Interestingly, WTAP knockdown further enhanced CD8⁺ T cell proliferation and the secretion of IFN-γ and perforin, compared to the anti-PD1 group (Figure S5D–G). Next, CD8⁺ T cells treated with anti-PD1 alone or in combination with WTAP siRNA were co-cultured with HCC cells. The results showed that silencing PD1 in CD8⁺ T cells significantly inhibited cell invasion (Figure S6A–D) of HCCLM3 and MHCC97H cells, while promoting apoptosis (Figure S6E–H). Co-silencing of WTAP and PD1 in CD8⁺ T cells led to a more pronounced inhibitory effect on the malignant progression of HCC cells compared to the anti-PD1 treatment alone (Figure S6A–H).

3.9. Downregulation of WTAP Enhanced Anti-PD1 Mediated Tumor Inhibition in a HuNSG Mouse Model

To further investigate the effect of WTAP on liver cancer progression, a humanized immune system was used to establish a HuNSG mouse model. Our data showed that silencing WTAP or treatment with anti-PD1 significantly inhibited the tumor cell proliferation and tumor growth (Figure 8A–D). The combination of WTAP silencing and anti-PD1 treatment resulted in more effective tumor growth suppression than anti-PD1 treatment alone (Figure 8A–D). WTAP knockdown or anti-PD1 treatment also reduced the proportion of PD1^highTCF1⁺ CD8⁺ T cells in the spleen of the mice (Figure 8E). Notably, the proportion of PD1^highTCF1⁺ CD8⁺ T cells in the WTAP silencing combined with anti-PD1 treatment group was lower than in the anti-PD1 treatment group (Figure 8E). Additionally, WTAP knockdown downregulated both WTAP and PD1 expression, as well as the PD1 m6A level in CD8⁺ T cells from the mouse spleen (Figure 8F–I). Anti-PD1 treatment significantly reduced PD1 protein levels without altering WTAP protein levels or PD1 m6A levels (Figure 8F–I). When combined, WTAP silencing and anti-PD1 treatment further reduced WTAP and PD1 expressions and PD1 m6A levels in CD8⁺ T cells from the spleen (Figure 8F–I).