The Ki-67 labeling index (Ki-67 LI) and microvascular invasion (MVI) are critical prognostic biomarkers in hepatocellular carcinoma (HCC). Preoperative, noninvasive prediction of their dual positivity status remains challenging. This study aimed to develop and validate a combined model integrating radiomic features from gadoxetic acid disodium (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) with clinical data. It also aimed to assess the effectiveness of combining Gd-EOB-DTPA-enhanced MRI radiomics with clinical features for the preoperative prediction of Ki-67/MVI dual positivity in HCC. A total of 142 pathologically confirmed HCC patients were categorized into dual-positive (Ki-67 LI > 20% and MVI-positive) and non-dual-positive (Ki-67 LI ≤ 20% and/or MVI-negative) groups. Clinical variables (sex, age, hepatitis status, tumor diameter, alpha-fetoprotein [AFP], liver function, inflammatory indices, and tumor differentiation), along with MRI data, were analyzed. Radiomic features were extracted from hepatobiliary-phase regions of interest. Key predictors were selected using the least absolute shrinkage and selection operator and multivariate logistic regression to construct the nomogram. The model was evaluated using the receiver operating characteristic curves, calibration plots, and decision curve analysis. Tumor diameter, AFP, gamma-glutamyl transferase, and differentiation grade significantly differed between the groups ( P < .05), and 6 radiomic features were selected to generate a radiomics score. Multivariate analysis identified tumor diameter, AFP, and radiomics score as independent predictors of dual positivity for Ki-67/MVI. The combined model demonstrated excellent calibration and superior predictive performance, achieving an area under the curve of 0.879, sensitivity of 70.0%, specificity of 92.3%, accuracy of 78.8%, precision of 93.3%, and F1-score of 80%. Follow-up after surgery showed a significantly higher early recurrence rate in the dual-positive HCC (Ki-67/MVI) group than that in the non-dual-positive group ( P < .05). The Gd-EOB-DTPA-enhanced MRI radiomics-clinical nomogram effectively predicted preoperative Ki-67/MVI dual positivity in HCC. This combined method surpassed the individual-modality models, providing significant assistance in risk assessment and tailored treatment planning for patients with HCC.

The aim of this study is to evaluate the association between genes related to cellular senescence and ferroptosis and their relevance to hepatocellular carcinoma (HCC). Genes associated with senescence and ferroptosis in HCC were retrieved from public databases. A protein-protein interaction (PPI) network was constructed to identify for hub genes, and validate their expression. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis, while prognostic significance was determined through Kaplan-Meier analysis. A prognostic nomogram model was developed based on selected hub genes and Tumor Node Metastasis (TNM) staging. A total of 52 senescence-ferroptosis-related genes were identified in HCC. ROC analysis indicated moderate to high diagnostic efficacy for TP53 (AUC = 0.723, CI: 0.669-0.776), JUN (AUC = 0.733, CI: 0.659-0.806), RELA (AUC = 0.854, CI: 0.808-0.901), and CDKN2A (AUC = 0.953, CI: 0.932-0.974). Kaplan-Meier analysis revealed that TP53, HIF1A, and CDKN2A were significantly associated with overall survival (OS) in patients with HCC. A nomogram model incorporating these three genes and TNM staging achieved a concordance index (C-index) of 0.699. Calibration curves indicated concordance between the predicted and observed survival probabilities at 1-, 2-, and 3-year intervals. The senescence-ferroptosis-related genes TP53, HIF1A, and CDKN2A demonstrated potential as diagnostic and prognostic biomarkers in HCC. The developed nomogram may support individualized prognostic assessment and inform early diagnostic and therapeutic strategies in patients with HCC.

Endotrophin (ETP) is a cleavage fragment of collagen VI α3 (COL6A3) that functions as a potent fibrotic and pro-tumorigenic factor. ETP is a diagnostic and prognostic biomarker in hepatocellular carcinoma (HCC), continuously increasing throughout tumor development and promoting HCC progression. Elucidation of the underlying molecular mechanisms by which ETP exerts pro-tumorigenic effects in the liver could uncover potential therapeutic strategies. Using peroxidase-catalyzed proximity labeling, we identified CD44 as an ETP receptor. ETP binding to CD44 activated STAT3 signaling, promoting epithelial-mesenchymal transition (EMT), proliferation, and sorafenib resistance. Hepatic stellate cell-derived ETP targeted pericentral CD44+ tumor cells, inducing COL6A3 expression and sustaining ETP production via a STAT3-dependent feedback loop. Disruption of this axis by CD44 knockout, STAT3 inhibition, or CD44-binding-deficient ETP mutants suppressed malignant phenotypes in vitro. In metabolic dysfunction-associated HCC induced by diethylnitrosamine (DEN) plus high-fat diet (HFD), dual knockout of Col6a3 and Cd44 in mice markedly reduced tumor burden, restored sorafenib sensitivity, and attenuated EMT, fibrosis, and steatotic-fibrotic niche formation. These findings establish the ETP-CD44-STAT3 axis as a driver of tumor-stroma crosstalk linking fibro-inflammation to malignancy, highlighting it as a therapeutic target in obesity-associated liver cancer.

Tumor-derived ITIH2 activates PI3K\AKT pathway via THBS1 ubiquitination and promotes tumor angiogenesis in hepatocellular carcinoma.

BackgroundRNA modification enzymes (RMEs) are key post-transcriptional regulators that impact RNA stability, translation, and splicing. Dysregulation of RMEs is closely associated with tumor initiation and progression. However, their global regulatory patterns and clinical relevance across cancer types remain incompletely characterized.MethodsWe conducted an integrative multi-omics analysis of RME expression, copy number variation (CNV), and clinical outcomes across multiple cancers. Machine learning algorithms were employed to identify tumor-discriminating RME signatures. Single-cell RNA sequencing (scRNA-seq) characterized tumor microenvironmental heterogeneity. A LASSO-derived prognostic model was established and validated in independent cohorts. Drug sensitivity prediction and supportive functional assays (EdU assays, qRT-PCR, immunohistochemistry) were performed for representative RMEs.ResultsRMEs were broadly upregulated across cancers and showed strong associations with CNV gains. Machine learning identified 12 RMEs that reliably discriminated tumor from normal tissues. Single-cell transcriptomic analysis showed that 10 of the 12 selected RMEs (DKC1, METTL1, NAT10, TRMT1, RPUSD1, PUS1, WDR4, TRMU, ADAT2, GTPBP3) exhibited higher expression in tumor-infiltrating cells compared with adjacent normal tissues. T-cell subpopulations displayed marked heterogeneity, with ADAT2 preferentially enriched in regulatory T cells. CellChat analysis revealed T cell subsets as key mediators of intercellular communication via multiple immune-related pathways. A 6-gene prognostic model exhibited independent prognostic power and was integrated into a well-calibrated nomogram. Drug-response prediction revealed that high-risk patients exhibited enhanced sensitivity to microtubule-targeting agents and kinase inhibitors, whereas low-risk patients showed preferential response to epigenetic modulators. Importantly, supportive functional assays showed that NAT10 knockdown, validated by qRT-PCR, was associated with reduced proliferative activity in HCC cells as evidenced by EdU assays, and IHC validation further corroborated its overexpression in clinical tumor specimens compared to adjacent normal tissues.ConclusionsThis study delineates a CNV-associated landscape of RME dysregulation across cancers and establishes a 12-RME diagnostic signature and a 6-gene prognostic model with robust predictive performance. Single-cell analyses reveal tumor- and cell-type-specific expression patterns of RMEs, while supportive functional data suggest a potential biological relevance of NAT10 in HCC. Collectively, these findings provide an association-based framework for understanding the potential roles of RNA modification programs in cancer progression and clinical stratification.

Exosomal IGFALS as a prognostic biomarker in hepatocellular Carcinoma: Associations with immune infiltration and clinical outcomes.

RFXANK may serve as a prognostic biomarker in hepatocellular carcinoma

CDKN3 emerges as a promising diagnostic and prognostic biomarker in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors worldwide, and its occurrence and development are intricately associated with the abnormal regulation of various genes and signaling pathways. Exosome Component 3(EXOSC3) is involved in the occurrence and growth of tumors. However, the exact mechanisms by which EXOSC3 influences HCC remain to be elucidated. Bioinformatics analysis method was used to detect the expression of EXOSC3 in HCC, qRT-PCR and Western blot were used to verify EXOSC3 expression in HCC cell lines.CCK-8 and colony formation assay was used to evaluate the effect of EXOSC3 on tumor proliferation, and validate the impact on cell migration and invasion through Transwell and Wound healing assay. Flow cytometry and Hochest staining were used to investigate the effect of EXOSC3 knockdown on the cell cycle and apoptosis of HCC. Western blot method was used to detect proteins expression. In HCC tissues, EXOSC3 mRNA and protein expression levels were notably higher than those in normal liver tissues and these levels correlated with poor prognosis. After knocking down EXOSC3, cell proliferation, colony formation, and metastasis were significantly inhibited in HCC. Flow cytometry and Western blot analyses showed that knockdown EXOSC3 promoted HCC cell apoptosis and inhibited cell cycle progression with reduced G1/S checkpoint protein expression. Furthermore, knockdown EXOSC3 activated P53 and decreased retinoblastoma protein (RB1) phosphorylation, suggesting that EXOSC3 functions via the P53 pathway in HCC. EXOSC3 has potential as a prognostic biomarker in HCC. Knockdown EXOSC3 leads to cell cycle arrest and consequently inhibits the proliferation of liver cancer cells by activating the P53 signaling pathway and concomitantly suppressing the expression of crucial regulatory proteins. These results not only establish EXOSC3 as a clinically relevant prognostic indicator but also highlight its therapeutic potential as a molecular target for HCC intervention strategies.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-28270-5.

BackgroundThe heat shock protein (HSP)/albumin (ALB) ratio, which measures the levels of plasma Hsp90α to ALB, is believed to be a sensitive prognostic biomarker for hepatocellular carcinoma (HCC); however, its prognostic value has not been clearly confirmed. The aim of our study was to assess the role of HSP/ALB as a prognostic factor in patients with HCC and further establish an interpretable predictive model using least absolute shrinkage and selection operator (LASSO)-Cox regression and SHapley Additive exPlanations (SHAP) value.MethodsA total of 1,340 HCC patients were enrolled in this study. We measured the levels of HSP/ALB in HCC patients within a week before treatment. Then, we established the HSP/ALB ratio and assessed its correlation with prognosis. Finally, we use LASSO-Cox regression to incorporate HSP/ALB into the prediction model for visualization and risk stratification.ResultsThe best cut-off value for HSP/ALB was determined to be 3.77 using the X-tile software. It was found that the median overall survival (mOS) of patients with HSP/ALB ≥3.77 (high) [8.3 months, 95% confidence interval (CI): 7.6–9.3] was significantly lower than that of patients with HSP/ALB <3.77 (low) (38.7 months, 95% CI: 35.8–45). In the training cohort, the mOS of patients with HSP/ALB ≥3.77 was 7.3 months (95% CI: 5.8–8.9), and that of patients with HSP/ALB <3.77 was 36.1 months (95% CI: 28.4–39.8). In the validation cohort, the mOS of patients with HSP/ALB ≥3.77 was 7.1 months (95% CI: 4.9–9.0), and that of patients with HSP/ALB <3.77 was 36.2 months (95% CI: 31.6–43.7). The subgroup analysis included four groups: transarterial chemoembolization (TACE) alone, TACE combined with operation, and radiotherapy (RT) group. The results showed that the patients with HSP/ALB <3.77 had longer mOS. We integrated HSP/ALB into the LASSO-Cox prediction model. Our findings showed that using HSP/ALB alone, the area under the curve (AUC) values for predicting 1-, 2-, and 3-year overall survival (OS) were 0.757, 0.731, and 0.713, respectively. However, after incorporating HSP/ALB into the prediction model based on LASSO-Cox regression, the AUC values for predicting 1-, 2-, and 3-year OS were 0.850, 0.842, and 0.810, respectively. Additionally, a nomogram was created based on this improved prediction model. Meanwhile, it was observed that the OS of the low-risk group significantly outperformed that of the medium-risk and high-risk groups. Finally, we ranked the importance of variables according to the SHAP value.ConclusionsThe integration of HSP/ALB into the LASSO-Cox prediction model improves its predictive performance, indicating that HSP/ALB can serve as a reliable prognostic predictor.

BackgroundCytokeratin 19 (CK19), Ki67 antigen (Ki67), and β-catenin are abnormally overexpressed in hepatocellular carcinoma (HCC), but their diagnostic and prognostic value remains unclear. This study aims to investigate the predictive role of these three markers in post-operative survival of HCC patients.MethodsThe expression levels of CK19, Ki67, and β-catenin in HCC tumor tissues were determined through public datasets. Kaplan-Meier survival analysis and multivariate Cox regression were performed to evaluate their prognostic value. Immunohistochemistry and Western blotting were used to detect the expression levels of CK19, Ki67, and β-catenin in hepatocellular carcinoma tissues and adjacent non-cancerous tissues. Transcriptome sequencing was performed to analyze the differential transcriptional changes between HCC and adjacent non-cancerous tissues. A cohort of HCC post-operative patients was included to analyze the correlation between the three markers and clinical pathological features.ResultsCK19, Ki67, and β-catenin were highly expressed in HCC tissues and lowly expressed in adjacent non-cancerous tissues. High expression of CK19, Ki67, and β-catenin was closely associated with poor disease-free survival (DFS) and overall survival (OS) in HCC patients’ post-surgery. These three markers serve as independent prognostic factors for DFS and OS. Immunohistochemistry and Western blotting revealed upregulation of CK19, Ki67, and β-catenin in HCC tissues, while transcriptome sequencing indicated alterations related to metabolic reprogramming, immune evasion, and invasion/metastasis in HCC. Clinical data from HCC patients showed that CK19 expression correlated with tumor number and differentiation grade, Ki67 expression correlated with patient age, tumor size, tumor number, lymphatic metastasis, and tumor differentiation, while β-catenin expression was closely related to tumor diameter, number, and capsule status.ConclusionCK19, Ki67, and β-catenin are highly expressed in HCC and can serve as molecular markers for post-operative recurrence and poor survival in HCC patients, providing a basis for precise prognostic evaluation in HCC.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12885-025-15429-6.

BackgroundHepatocellular carcinoma (HCC) is a aggressive cancer associated with high morbidity and mortality globally. Reliable biomarkers are urgently needed to enhance diagnostic accuracy and survival outcomes in patients with HCC. This study aimed to evaluate the prognostic value of cleavage stimulation factor subunit 1 (CSTF1) in HCC.MethodsCSTF1 expression in different cancer types, including HCC, was analyzed using data from The Cancer Genome Atlas. Immunohistochemistry was performed to assess CSTF1 expression in clinical samples. Logistic regression analyses were used to evaluate associations between CSTF1 expression and the clinical characteristics of patients with HCC. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analysis (GSEA) were performed to identify signaling pathways and biological functions linked to differentially expressed genes. The prognostic significance of CSTF1 in HCC was assessed via the Kaplan-Meier method and Cox univariate and multivariate analyses. Immune cell infiltration was investigated through single-sample GSEA and the CIBERSORT algorithm. Three nomograms were constructed to predict overall survival (OS), disease-specific survival (DSS), and progression free interval (PFI) rates at 1, 3, and 5 years after diagnosis.ResultsCSTF1 expression was elevated in HCC cases and closely correlated with multiple clinical features. Elevated CSTF1 expression was strongly associated with various cancer-related pathways and the immune microenvironment. The Kaplan-Meier analysis revealed that elevated CSTF1 expression predicts poorer prognostic outcomes in individuals with HCC. CSTF1 hypermethylation was also related to poor patient outcomes. The constructed nomograms for OS, DSS, and PFI achieved concordance indices of 0.631, 0.719 and 0.787, respectively.ConclusionThese findings suggest that CSTF1 can serve as a novel prognostic biomarker for HCC. Evidence from immunohistochemistry and bioinformatics analyses supports CSTF1 as a prognostic indicator and a potential therapeutic target. This discovery could enhance diagnostic precision and improve survival outcomes for patients with HCC.

ObjectiveEarly diagnosis and prognostic evaluation of hepatocellular carcinoma (HCC) remain significant challenges in clinical management. This study aims to identify prognostic biomarkers in HCC and to explore their implications in immune microenvironment infiltration.MethodsIn this study, we constructed a single-cell transcriptomic atlas of HCC, focusing on the expression profiles of T cell-related genes. Analytical approaches included cell-cell communication analysis and pseudotime trajectory analysis. To further predict and validate T cell-associated prognostic genes, we integrated transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Patients were stratified into high- and low-risk groups based on a prognostic model derived from these biomarkers. Immune infiltration levels in the tumor microenvironment were then evaluated across risk groups.ResultsA total of eight primary tumor samples and seven normal tissue samples were included as raw data in this study. Following stringent quality control and filtering, 53,477 cells were retained for downstream analysis. From these, we isolated 12,333 T cells, which were subjected to further clustering and annotation. The T cell subpopulations identified included 6314 natural killer T cells (NK T cells), 5199 effector memory CD4+ T cells, and 820 central memory CD8+ T cells. By integrating transcriptomic data from TCGA-LIHC and GEO datasets, we identified six prognostic biomarkers: LYZ, SPP1, EGR1, MARCO, FCN3, and PTTG1. A prognostic model was developed based on these biomarkers, enabling risk stratification into high- and low-risk groups. The model demonstrated robust predictive performance in estimating patient survival rates and immune cell infiltration levels within the tumor microenvironment.ConclusionThis study identified and validated prognostic biomarkers in HCC that effectively predict patient survival rates and immune infiltration characteristics. These findings provide a potential foundation for precision medicine strategies in HCC, offering novel insights into the tumor-immune microenvironment and its clinical implications.

CD2-associated protein (CD2AP) is an adapter protein that stabilizes the actin cytoskeleton and is closely linked to disulfidptosis. However, its functional role in hepatocellular carcinoma (HCC) progression and disulfidptosis remains undefined. Herein, pan-cancer multiomics analyses were performed on 33 malignancies from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cohorts to evaluate CD2AP expression patterns, prognostic significance, and interactions with the tumor immune microenvironment. Clinical validation was performed using 70 HCC specimens, with qRT-PCR analysis and survival assessments. CD2AP expression was significantly elevated in tumor tissues across multiple cancer types and correlated with poor survival outcomes. In tumor tissues, high CD2AP expression positively correlated with the expression of immune checkpoints, including HAVCR2, CTLA4, CD274, TIGIT, and PDCD1. Additionally, qRT-PCR analysis of 70 HCC patients in our cohort confirmed a marked upregulation of CD2AP in HCC tumor tissues. Specifically, Kaplan–Meier analysis further revealed that high CD2AP expression was associated with reduced overall survival and recurrence-free survival in our HCC cohort. Functional experiments demonstrated that CD2AP silencing inhibited HCC cell proliferation and enhanced disulfidptosis susceptibility in SLC7A11-high cells, likely via NADPH depletion and actin network disruption. In conclusion, our findings indicate that CD2AP functions as an oncogene in HCC, promoting tumor progression by regulating disulfidptosis. This study provides novel insights into CD2AP as a potential prognostic biomarker and therapeutic target for HCC.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10238-025-01917-3.

FAM72B serves as a novel diagnostic and prognostic biomarker in hepatocellular carcinoma

Chronic hepatitis B (CHB) is a major risk factor for liver cirrhosis (LC) and hepatocellular carcinoma (HCC). Genes involved in the JAK/STAT signalling pathway play a critical role in the pathogenesis of HBV-related liver diseases, especially HCC. Although SOCS1 and SOCS3 have been extensively studied, the role of SOCS6 in HBV infection and disease progression remains unclear. This study aimed to investigate the association between SOCS6 gene polymorphisms and promoter methylation with HBV-related liver diseases. This study examined SOCS6 gene polymorphisms in a cohort of 335 patients with HBV-related liver diseases (120 with CHB, 100 with LC and 115 with HCC) and 120 healthy controls (HCs). In addition, SOCS6 promoter methylation was analysed in tumour and adjacent tissues from 41 HCC patients. We found that the rs2062345GA genotype and the dominant genetic model were associated with an increased risk of HBV infection and HCC. The rs7228049GA genotype increased the risk of LC and HCC. Conversely, the rs7228049AA genotype and the recessive model were associated with a reduced risk of CHB, LC and HCC. The SNPs rs2062345, rs7228049 and rs11151580 were related to several clinical parameters such as AST, albumin and prothrombin levels, platelet counts in LC and HCC patients. Promoter hypermethylation of SOCS6 was more prevalent in tumour tissues, especially in larger tumours with poorer histological differentiation (p<0.01 and p<0.05, respectively). SOCS6 gene variants and promoter methylation are associated with susceptibility and progression of HBV-related liver diseases. These findings suggest their potential utility as useful prognostic biomarkers for HCC.

An autophagy-related molecule reticulon 3 functions as a novel prognostic biomarker in hepatocellular carcinoma

Activating transcription factor 4-mediated upregulation of Heat Shock Protein Family A Member 4 promotes hepatocellular carcinoma progression through activation of Wnt/β-catenin/EMT signaling pathway.

Background/AimsCirculating exosomal microRNAs (miRNAs) can serve as diagnostic and prognostic biomarkers for cancer. This study aimed to identify specific miRNAs in serum exosomes of patients with hepatocellular carcinoma (HCC) and validate their biological functions as novel diagnostic and predictive biomarkers.MethodsSerum exosomal miRNAs in patients with HCC (n = 241) and without HCC (n = 45) were measured by qRT-PCR. The role of exosomal miRNAs in HCC was investigated through in vitro tests and verified in a clinical cohort of patients.ResultsIn vitro, we observed delivery of exosomal miRNA-720 (miR-720) to recipient cells. Exosome-mediated miR-720 promoted proliferation and inhibited apoptosis of recipient HCC cells. Exosomal miR-720 inhibited tumor suppressor StarD13 expression in recipient cells. Additionally, exosomal miR-720 promoted stemness in recipient cells by increasing protein expression of stemness-associated markers such as OCT4 and c-MYC. In our cohort, serum exosomal miR-720 was significantly upregulated in HCC patients than in non-HCC patients, showing an excellent diagnostic performance for HCC. Particularly, exosomal miR-720 exhibited superior performance in diagnosing small HCC (< 2 cm) compared to AFP or DCP. Exosomal miR-720 levels positively correlated with advancing tumor stage and size. Patients with high expression of exosomal miR-720 had significantly shorter time to progression than those with low expression of exosomal miR-720 during transarterial chemoembolization (TACE).ConclusionsOur results demonstrate that exosomal miR-720 plays an oncogenic role in HCC by targeting StarD13. Circulating exosomal miR-720 could be used as a novel diagnostic and therapeutic biomarker and serve as a guide for selecting treatment options including TACE for HCC.

Soluble programmed cell death-ligand 1 (sPD-L1) and soluble programmed cell death 1 (sPD-1) interact to promote tumor immune evasion and play important roles in the progression of hepatocellular carcinoma (HCC). Nevertheless, their clinical value in HCC patients remains controversial. Therefore, the present meta-analysis aimed to assess the diagnostic and prognostic value of sPD-L1 or sPD-1 for HCC comprehensively. A systematic search was performed in Web of Science, PubMed, Embase, and the Cochrane Library up to April 2025. Studies comparing sPD-1 or sPD-L1 levels between HCC patients and controls or assessing the associations of sPD-1 or sPD-L1 levels with prognosis in HCC patients were collected. Fourteen studies involving 1420 cases were included. Elevated sPD-L1 levels were observed in HCC patients compared with controls [standardized mean difference (SMD) (95% confidence interval (CI)): 2.655 (0.351, 4.959), P = 0.020]. A high sPD-L1 level was linked to reduced progression-free survival (PFS) [hazard ratio (HR) (95% CI): 2.807 (1.470, 5.361), P = 0.002], and it tended to be related to shortened overall survival (OS) in HCC patients, although the difference was not statistically significant [HR (95% CI): 1.817 (0.923, 3.576), P = 0.080]. Moreover, there was no association between sPD-1 levels and PFS [HR (95% CI): 1.028 (0.511, 2.069), P = 0.940] or OS [HR (95% CI): 1.017 (0.637, 1.624), P = 0.940)] in HCC patients. All included studies were of high quality. No publication bias was observed. sPD-L1, but not sPD-1, may be a diagnostic and prognostic biomarker that contributes to the management of HCC.