Background: The efficacy of immune checkpoint blockade therapy in patients with hepatocellular carcinoma (HCC) remains poor. Although serine‐ and arginine‐rich splicing factor (SRSF) family members play crucial roles in tumors, their impact on tumor immunology remains unclear. This study aimed to elucidate the role of SRSF10 in HCC immunotherapy. Methods: To identify the key genes associated with immunotherapy resistance, we conducted single‐nuclear RNA sequencing, multiplex immunofluorescence, and The Cancer Genome Atlas and Gene Expression Omnibus database analyses. We investigated the biological functions of SRSF10 in immune evasion using in vitro co‐culture systems, flow cytometry, various tumor‐bearing mouse models, and patient‐derived organotypic tumor spheroids. Results: SRSF10 was upregulated in various tumors and associated with poor prognosis. Moreover, SRSF10 positively regulated lactate production, and SRSF10/glycolysis/ histone H3 lysine 18 lactylation (H3K18la) formed a positive feedback loop in tumor cells. Increased lactate levels promoted M2 macrophage polarization, thereby inhibiting CD8 ⁺ T cell activity. Mechanistically, SRSF10 interacted with the 3′‐untranslated region of MYB , enhancing MYB RNA stability, and subsequently upregulating key glycolysis‐related enzymes including glucose transporter 1 ( GLUT1 ), hexokinase 1 ( HK1 ), lactate dehydrogenase A ( LDHA ), resulting in elevated intracellular and extracellular lactate levels. Lactate accumulation induced histone lactylation, which further upregulated SRSF10 expression. Additionally, lactate produced by tumors induced lactylation of the histone H3K18la site upon transport into macrophages, thereby activating transcription and enhancing pro‐tumor macrophage activity. M2 macrophages, in turn, inhibited the enrichment of CD8 ⁺ T cells and the proportion of interferon‐γ ⁺ CD8 ⁺ T cells in the tumor microenvironment (TME), thus creating an immunosuppressive TME. Clinically, SRSF10 could serve as a biomarker for assessing immunotherapy resistance in various solid tumors. Pharmacological targeting of SRSF10 with a selective inhibitor 1C8 enhanced the efficacy of programmed cell death 1 (PD‐1) monoclonal antibodies (mAbs) in both murine and human preclinical models. Conclusions: The SRSF10/MYB/glycolysis/lactate axis is critical for triggering immune evasion and anti‐PD‐1 resistance. Inhibiting SRSF10 by 1C8 may overcome anti‐PD‐1 tolerance in HCC.

The efficacy of immunotherapy targeting the PD-1/PD-L1 pathway in hepatocellular carcinoma (HCC) is limited. NOD-like receptors (NLRs) comprise a highly evolutionarily conserved family of cytosolic bacterial sensors, yet their impact on antitumor immunity against HCC remains unclear. In this study, we uncovered that NOD1, a well-studied member of NLR family, exhibits predominant expression in tumor-associated macrophages (TAMs) and correlates positively with improved prognosis and responses to anti–PD-1 treatments in patients with HCC. Activation of NOD1 in vivo augments antitumor immunity and enhances the effectiveness of anti–PD-1 therapy. Mechanistically, NOD1 activation resulted in diminished expression of perilipin 5, thereby hindering fatty acid oxidation and inducing free fatty acid accumulation in TAMs. This metabolic alteration promoted membrane localization of the costimulatory molecule OX40L in a lipid modification–dependent manner, thereby activating CD8⁺T cells. These findings unveil a previously unrecognized role for NOD1 in fortifying antitumor T cell immunity in HCC, potentially advancing cancer immunotherapy.

Albumin-to-alkaline phosphatase ratio (AAPR), a newly developed blood biomarker, has been reported to have prognostic value in several types of cancer. This study aimed to investigate the predictiv...

The poliovirus receptor (PVR) is a member of the immunoglobulin superfamily (Ig SF) and is essential for the promotion of cancer cell proliferation and invasion. However, the correlation between PVR expression and prognosis as well as immune infiltration in hepatocellular carcinoma (HCC) remains unclear. The expression level of PVR was quantified using the Tumor and Tumor Immunity Evaluation Resource (TIMER) and Sangerbox. The Gene Expression Omnibus (GEO) database was used to validate the PVR expression. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of using PVR as a differentiating factor according to the area under curve (AUC) score. A PVR binding protein network was built using the STRING tool. An enrichment analysis using the R package clusterProfiler was used to explore the potential function of PVR. Immune infiltration analysis was calculated with ESTIMATE algorithms. We also assessed the correlation between PVR expression and immune infiltration by the single-sample Gene Set Enrichment Analysis (ssGSEA) method from the R package GSVA and TIMER database. The results showed that PVR was commonly overexpressed in multiple types of tumors including HCC. The data of GSE64041 confirmed the same result. The ROC curve suggested that PVR could be a potential diagnostic biomarker. Additionally, high mRNA expression of PVR in HCC was significantly correlated with poor overall survival (OS) and relapse free survival (RFS). Results also indicated correlations between PVR mRNA expression with the level of infiltration immune cells including B cells, CD8+ T cells, cytotoxic cells, DCs, CD56dim NK cells, pDCs, and Th2 cells. Furthermore, the PVR level was significantly correlated with immune markers for immunosuppressive cells in HCC. In conclusion, PVR might be an important regulator of tumor immune cell infiltration and a valuable prognostic biomarker in HCC. However, additional work is needed to fully elucidate the underlying mechanisms.

Background: CD276 is an emerging immune checkpoint molecule that has been implicated in various cancers. However, its specific role in hepatocellular carcinoma (HCC) remains unclear. This study examined the impact of CD276 on patient prognosis and the tumor microenvironment (TME). Methods: The Cancer Genome Atlas (TCGA) database was utilized to evaluate CD276 expression in HCC and the association between CD276 and immune indicators was also analyzed. The signaling pathways correlated with CD276 expression were identified by gene set enrichment analysis (GSEA). Different algorithms were used to assess immune cell infiltration. The effect of CD276 knockdown on HCC cell phenotypes and its relationship with macrophage polarization was examined using the cell counting kit 8 (CCK-8) assay and co-culture system. Results: CD276 was upregulated in HCC and associated with unfavorable clinical outcomes. Hgh CD276 expression was associated with enrichment of the G2/M checkpoint, E2F targets, and mitotic spindles. CD276 expression was correlated with the infiltration of immune cells, including high level of tumor-associated macrophages and low levels of CD8⁺ T cells. Knockdown of CD276 decreased HCC cell proliferation and increased apoptosis. CD276 silencing in HCC cells and co-culture with THP-1–derived macrophages had a regulatory effect on macrophage polarization and macrophage-mediated cell proliferation and migration. Conclusion: CD276 expression in HCC is associated with unfavorable clinical outcomes and may contribute to the development of an immunosuppressive microenvironment. Specifically, CD276 was associated with alterations in immune cell infiltration, immune marker expression, and macrophage polarization during HCC progression, suggesting its potential as a prognostic indicator and promising target for immunotherapeutic intervention in HCC.

Albumin to gamma-glutamyltransferase ratio (AGR) is a newly developed biomarker for the prediction of patients’ prognosis in solid tumors. The purpose of the study was to establish a novel AGR-based nomogram to predict tumor prognosis in patients with early-stage HCC undergoing radiofrequency ablation (RFA). 394 hepatocellular carcinoma (HCC) patients who had received RFA as initial treatment were classified into the training cohort and validation cohort. Independent prognostic factors were identified by univariate and multivariate analyses. The value of AGR was evaluated by the concordance index (-index), receiver operating characteristic (ROC) curves, and likelihood ratio tests (LAT). Logistic regression and nomogram were performed to establish the pretreatment scoring model based on the clinical variables. As a result, was identified as the best cutoff value to predict overall survival (OS) in the training cohort. According to the results of multivariate analysis, AGR was an independent indicator for OS and recurrence-free survival (RFS). In both training cohort and validation cohort, the high-AGR group showed better RFS and OS than the low-AGR group. What is more, the -index, area under the ROC curves, and LAT values suggested that AGR outperformed the Child-Pugh (CP) grade and albumin-bilirubin (ALBI) grade in terms of predicting OS. The AGR, AKP, and tumor size were used to establish the OS nomogram. Besides, the results of Hosmer-Lemeshow test and calibration curve analysis displayed that both nomograms in the training and validation cohorts performed well in terms of calibration. Therefore, the AGR-based nomogram can predict the postoperative prognosis of early HCC patients undergoing RFA.