scholarly journals In Silico Identification of Contradictory Role of ADAMTS5 in Hepatocellular Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382098682
Author(s):  
Zhipeng Zhu ◽  
Jiuhua Xu ◽  
Xiaofang Wu ◽  
Sihao Lin ◽  
Lulu Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Subgroup Analysis ◽  
Prognostic Value ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Clinicopathological Parameters ◽  
Free Survival ◽  
Cox Regression Analysis ◽  
The Impact

Background: ADAMTS5 has different roles in multiple types of cancers and participates in various molecular mechanisms. However, the prognostic value of ADAMTS5 in patients with hepatocellular carcinoma (HCC) still remains unclear. We carried the study to evaluate the prognostic value and identified underlying molecular mechanisms in HCC. Methods: Firstly, the association of ADAMTS5 expression and clinicopathological parameters was evaluated by in GSE14520. Next, ADAMTS5 expression in HCC was performed using GSE14520, GSE36376, GSE76427 and The Cancer Genome Atlas (TCGA) profile. Furthermore, Kaplan-Meier analysis, Univariate and Multivariate Cox regression analysis, subgroup analysis was performed to evaluate the prognostic value of ADAMTS5 in HCC. Finally, GO enrichment analysis, gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis (WGCNA) were performed to revealed underlying molecular mechanisms. Result: The expression of ADAMTS5 was positively correlated with the development of HCC. Next, high ADAMTS5 expression was significantly associated with poorer survival (all P < 0.05) and the impact of ADAMTS5 on all overall survival (OS), disease-free survival (DFS), relapse-free survival (RFS), disease specific survival (DSS) and progression free interval (PFI) was specific for HCC among other 29 cancer types. Subgroup analysis showed that ADAMTS5 overexpression was significantly associated with poorer OS in patients with HCC. Finally, ADAMTS5 might participate in the status conversion from metabolic-dominant to extracellular matrix-dominant, and the activation of ECM-related biological process might contribute to high higher mortality risk for patients with HCC. Conclusion: ADAMTS5 may play an important role in the progression of HCC, and may be considered as a novel and effective biomarker for predicting prognosis for patients with HCC.

scholarly journals Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11273
Author(s):  
Lei Yang ◽  
Weilong Yin ◽  
Xuechen Liu ◽  
Fangcun Li ◽  
Li Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Overall Survival ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Hub Genes ◽  
Cox Regression Analysis

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

scholarly journals Prognostic Value of Lactate Dehydrogenase in Patients with Hepatocellular Carcinoma: A Meta-Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Weihao Kong ◽  
Xiaomin Zuo ◽  
Hao Liang ◽  
Jingxiong Hu ◽  
Huabing Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Sensitivity Analysis ◽  
Lactate Dehydrogenase ◽  
Publication Bias ◽  
Subgroup Analysis ◽  
Prognostic Value ◽  
Meta Analysis ◽  
Progression Free Survival ◽  
Cochrane Library ◽  
Free Survival

Background. Previous studies have shown the prognostic value of lactate dehydrogenase (LDH) in hepatocellular carcinoma (HCC), but the results are not persuasive. Therefore, the purpose of our study was to quantitatively explore the prognostic value of LDH in hepatocellular carcinoma.Methods. We searched the Web of Science, Embase, PubMed, and the Cochrane Library for literature published before October 2018 on the prognostic value of LDH in patients with hepatocellular carcinoma. The combined hazard ratios (HRs) and 95% confidence intervals (CIs) were utilized to assess the prognostic value of LDH in overall survival (OS), recurrence-free survival (RFS), and progression-free survival (PFS) of HCC. Subgroup analysis, sensitivity analysis, and metaregression were used to explore the source of heterogeneity. Funnel plots with Begg’s test and Egger’s test were used to detect potential publication biases. Furthermore, combined odds ratios (ORs) were utilized to assess the correlation between LDH and clinicopathological features.Results. A total of 10 nonrandomized controlled studies were included in this meta-analysis. The combined effects of LDH on HCC patients’ OS, RFS/DFS, and PFS were HR = 2.07, 95% CI: 1.63-2.62, P < 0.001; HR = 1.62, 95% CI: 1.37-1.90, P < 0.001; and HR = 1.96, 95% CI: 1.14-3.36, P = 0.014, respectively. Subgroup analysis and sensitivity analysis showed that the outcome was stable, and the results of the metaregression also identified statistical models as an important source of heterogeneity. Potential publication bias was detected in the OS studies, so the trim-and-fill method was used to explore publication bias, and the results showed stability. Furthermore, the combined OR suggests that LDH was significantly correlated with gender, Child-Pugh grade, alpha-fetoprotein, vascular invasion, and tumor size.Conclusions. Preoperative LDH elevation is significantly associated with poor prognosis in patients with HCC, which may be a promising factor in assessing the prognosis of patients with HCC.

scholarly journals Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Honglan Guo ◽  
Qinqiao Fan
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Normal Tissues

Background. We aimed to investigate the expression of the hyaluronan-mediated motility receptor (HMMR) gene in hepatocellular carcinoma (HCC) and nonneoplastic tissues and to investigate the diagnostic and prognostic value of HMMR. Method. With the reuse of the publicly available The Cancer Genome Atlas (TCGA) data, 374 HCC patients and 50 nonneoplastic tissues were used to investigate the diagnostic and prognostic values of HMMR genes by receiver operating characteristic (ROC) curve analysis and survival analysis. All patients were divided into low- and high-expression groups based on the median value of HMMR expression level. Univariate and multivariate Cox regression analysis were used to identify prognostic factors. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanism of the HMMR genes involved in HCC. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC). Results. HMMR mRNA expression was significantly elevated in HCC tissues compared with that in normal tissues from both TCGA and the ICGC cohorts (all P values <0.001). Increased HMMR expression was significantly associated with histologic grade, pathological stage, and survival status (all P values <0.05). The area under the ROC curve for HMMR expression in HCC and normal tissues was 0.969 (95% CI: 0.948–0.983) in the TCGA cohort and 0.956 (95% CI: 0.932–0.973) in the ICGC cohort. Patients with high HMMR expression had a poor prognosis than patients with low expression group in both cohorts (all P < 0.001 ). Univariate and multivariate analysis also showed that HMMR is an independent predictor factor associated with overall survival in both cohorts (all P values <0.001). GSEA showed that genes upregulated in the high-HMMR HCC subgroup were mainly significantly enriched in the cell cycle pathway, pathways in cancer, and P53 signaling pathway. Conclusion. HMMR is expressed at high levels in HCC. HMMR overexpression may be an unfavorable prognostic factor for HCC.

scholarly journals Identification and Validation of Tumour Microenvironment-Based Immune Related Signature for Hepatocellular Carcioma: Immunotherapeutic Implications

2021 ◽  
Author(s):  
Hong Yu ◽  
Shao Wang ◽  
Tao Zhou ◽  
Jia Sun ◽  
Tian Qi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Treatment Outcomes ◽  
Predictive Model ◽  
Cox Regression ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Patient Treatment ◽  
Cox Regression Analysis

Abstract Background: Even though treatment outcomes for hepatocellular carcinoma patients have significantly improved, prognostic clinical evaluation remains a substantial challenge due to the heterogeneity and complexity of cancer. Accumulating evidence has revealed that the tumor immune microenvironment is critical for progression and prognosis of hepatocellular carcinoma. A powerful predictive model could assist physicians to better monitor patient treatment outcomes and improve overall survival rates. Therefore, we introduced tumor immune-related genes into a model that could be used for patient risk classification. Results: First, the Single-sample gene set enrichment analysis (ssGSEA) and Weighted gene co-expression networks construction (WGCNA) methods were applied to identify highly associated immunity genes. Following this, a multi-immune-related gene-based signature determined by The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to determine risk stratification. In addition, this predictive model was evaluated according to its performance as a prognostic model in the training and testing datasets. Furthermore, tumor mutation burden and biological enrichment analysis were applied to reveal the potential mechanisms through which the gene signature functions. Conclusion: In conclusion, our four-gene signature model may be clinically applied in hepatocellular carcinoma patients at high risk of mortality for personalized therapy.

scholarly journals Diagnostic significance and carcinogenic mechanism of pan-cancer gene POU5F1 in liver hepatocellular carcinoma

2020 ◽  
Author(s):  
Dingdong He ◽  
Xiaokang Zhang ◽  
Jiancheng Tu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Meta Analysis ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
Clinicopathological Parameters ◽  
Cancer Gene ◽  
Hub Genes ◽  
Liver Hepatocellular Carcinoma ◽  
The Impact ◽  
Pan Cancer

Abstract Background The prognostic and clinicopathological significance of POU Class 5 Homeobox 1 (POU5F1) among various cancers is disputable heretofore. The diagnostic value and function mechanism of POU5F1 in liver hepatocellular carcinoma (LIHC) have not been studied thoroughly. Methods An integrative strategy of meta-analysis, bioinformatics and wet-lab approach was used to explore the diagnostic and prognostic significance of POU5F1 in various types of tumors, especially in LIHC. Meta-analysis was utilized to investigate the impact of POU5F1 on prognosis and clinicopathological parameters in various cancers. The expression level and diagnostic value of POU5F1 were assessed by qPCR in plasma collected from LIHC patients and controls. The correlation between POU5F1 and tumor infiltrating immune cells (TIICs) in LIHC was evaluated by CIBERSORT. Gene set enrichment analysis (GSEA) was performed based on TCGA. Hub genes and related pathways were identified on the basis of co-expression genes of POU5F1. Results Elevated POU5F1 was associated with poor OS, DFS, RFS and DSS in various cancers. POU5F1 was confirmed as an independent risk factor for LIHC and correlated with tumor occurrence, stage and invasion depth. The combination of POU5F1 and AFP in plasma was with high diagnostic validity (AUC = 0.902, P < 0.001). Specifically, the level of POU5F1 was correlated with infiltrating levels of B cells, T cells, dendritic cells and monocytes in LIHC. GSEA indicated POU5F1 participated in multiple cancer related pathways and cell proliferation pathways. Moreover, CBX3, CCHCR1 and NFYC were filtered as the central hub genes of POU5F1. Conclusions Our study identified POU5F1 as a pan-cancer gene could not only be a prognostic and diagnostic biomarker in various cancers, especially in LIHC, but functionally carcinogenic in LIHC.

scholarly journals eIF6 Promotes the Malignant Progression of Human Hepatocellular Carcinoma via the mTOR Signaling Pathway

2020 ◽  
Author(s):  
Liping Sun ◽  
Shuguang Liu ◽  
Xiaopai Wang ◽  
Xuefeng Zheng ◽  
Ya Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Signaling Pathway ◽  
Prognostic Value ◽  
Molecular Mechanisms ◽  
Protein Translation ◽  
Translation Initiation Factor ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Initiation Factor ◽  
Hcc Cells

Abstract Background Eukaryotic translation initiation factor 6 (eIF6) has a crucial function in the maturation of 60S ribosomal subunits, and it controls the initiation of protein translation. Although emerging studies indicate that eIF6 is aberrantly expressed in various types of cancers, the functions and underlying molecular mechanisms of eIF6 in the pathological progression of hepatocellular carcinoma (HCC) remain unclear. This study aimed to evaluate the potential diagnostic and prognostic value of eIF6 in patients with HCC. Methods HCC samples enrolled from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and our cohort were used to explore the role and mechanism of eIF6 in HCC. The diagnostic power of eIF6 was verified by receiver operating characteristic curve (ROC) analysis and its prognostic value was assessed by Kaplan-Meier analysis, and then related biological functions of eIF6 were determined in vitro and in vivo cancer models. In addition, potential molecular mechanism of eIF6 in HCC was unveiled by the gene set enrichment analysis and western blot assay. Results We demonstrated that eIF6 expression was markedly increased in HCC, and elevated eIF6 expression correlated with pathological progression of HCC. Besides, eIF6 served as not only a new diagnostic biomarker but also an independent risk factor for OS in HCC patients. Functional studies indicated that the deletion of eIF6 displayed tumor-suppressor activity in HCC cells. Furthermore, we found that eIF6 could activate the mTOR-related signaling pathway and regulate the expression level of its target genes, such as CCND1, CDK4, CDK6, MYC, CASP3 and CTNNBL1, and these activities promoted proliferation and invasion of HCC cells. Conclusions The findings of this study provided a novel basis for understanding the potential role of eIF6 in promoting tumor growth and invasion, and exploited a promising strategy for improving diagnosis and prognosis of HCC.

scholarly journals Prognostic Value of BTNL9 Combined with Genes of Proteasome and Ubiquitin System in Pancreatic Cancer

2021 ◽  
Author(s):  
Ke Xu ◽  
Qingfan Mo ◽  
Bo Liu ◽  
Rongfei Huang ◽  
Wei Zhou ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Prognostic Factors ◽  
Prognostic Value ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Immune Checkpoints ◽  
Prognostic Prediction ◽  
The Relationship

Abstract Background: An accurate prognostic prediction can improve the individualized management of patients with pancreatic cancer (PC), and the exploration of biomarkers with prognostic value for clinical practice is the prerequisite of the work. Butyrophilin-Like 9 (BTNL9) has recently been found to function as a tumor suppressor gene in a variety of malignancies and has the potency to serve as a prognostic biomarker. Our aim was to explore the relationship between BTNL9 expression and the prognosis of PC, and to unearth its upstream and downstream molecular mechanisms. Methods: The RNA expression of BTNL9 was analyzed in 5 datasets from Gene Expression Omnibus (GEO) database. The protein expression of BTNL9 was detected by immunohistochemistry in a cohort including 42 PC patients. The relationship between BTNL9 expression and prognosis was analyzed by survival and prognostic factors analysis. Online database and Gene Set Enrichment Analysis (GSEA) were used to explore the upstream and downstream molecular mechanisms of BTNL9. Correlation analysis and CIBERSORT were applied to investigate the relationship between BTNL9 and tumor immunology.Results: In multiple datasets and our cohort, BTNL9 expression was decreased in PC tissues. Patients with high expression of BTNL9 had a better prognosis. BTNL9, age and N stage were identified as the independent prognostic factors of PC. BTNL9 was predicted to be down-regulated by hsa-miR-1910-5p, and it may be involved in the proteasome and PC signaling pathway. Interestingly, genes of proteasome (PSMD2, PSMD7 and PMSD14) and deubiquitin system (USP20, USP27X and USP30) combined BTNL9 could improve the prognostic prediction of PC. In addition, the expression of BTNL9 correlates with the expression of immune checkpoints and influences the infiltration of tumor immune cells. Conclusions: BTNL9 can serve as a prognostic marker of PC, and high expression of BTNL9 was generally associated with better prognosis. Combined the expression of BTNL9 and the expression of PSMD2, PSMD7, PMSD14, USP20, USP27X and USP30 can more accurately analyze the prognosis of patients with PC.

scholarly journals Distant Survival for Patients Undergoing Surgery Using Volatile versus IV Anesthesia for Hepatocellular Carcinoma with Portal Vein Tumor Thrombus:A Retrospective study.

2020 ◽  
Author(s):  
Xiao-Yan Meng ◽  
Xiu-Ping Zhang ◽  
Hong-Qian Wang ◽  
Weifeng Yu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Portal Vein ◽  
Cox Regression ◽  
Cancer Recurrence ◽  
Survival Outcomes ◽  
Free Survival ◽  
Cox Regression Analysis ◽  
Underlying Causes ◽  
The Impact

Abstract Background Whether anesthesia type is associate with the surgical outcome of Hepatocellular carcinoma (HCC) patients with portal vein tumor thrombus (PVTT) remains to be determined. This study aims to investigate the impact of volatile inhalational anesthesia (INHA) versus total IV anesthesia (TIVA) on the survival outcomes in HCC patients with PVTT. Methods A cohort of in-patients whom were diagnosed of HCC with PVTT in Eastern Hepatobiliary Surgery Hospital, Shanghai, China, from January 1, 2008 to December 24, 2012 were identified. Surgical patients receiving the INHA and TIVA were screened out. The overall survival (OS), recurrence-free survival (RFS) and several postoperative adverse events were compared according to anesthesia types. Results A total of 1513 patients were included in this study. After exclusions are applied, 263 patients remain in the INHA group and 208 in the TIVA group. Patients receiving INHA have a lower 5-year overall survival rate than that of patients receiving TIVA [12.6% (95% CI, 9.0 to 17.3) vs. 17.7% (95% CI, 11.3 to 20.8), P=0.024]. Results of multivariable Cox-regression analysis also identify that INHA anesthesia is significantly associated with mortality and cancer recurrence after surgery compare to TIVA, with HR (95%CI) of 1.303 (1.065, 1.595) and 1.265 (1.040, 1.539), respectively. Subgroup analysis suggested that in more severe cancer patients, the worse outcome related to INHA might be more significant. Conclusion This retrospective analysis identifies that TIVA has better survival outcomes compare to INHA in HCC patients with PVTT. Future prospective researches are urgent to verify this difference and figure out underlying causes of it.

scholarly journals Development of a prognostic signature based on six immune related lncRNAs for hepatocellular carcinoma.

2020 ◽  
Author(s):  
Ze-bing Song ◽  
Guo-pei Zhang ◽  
shaoqiang li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Cerna Network

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumor in the world which prognosis is poor. Therefore, a precise biomarker is needed to guide treatment and improve prognosis. More and more studies have shown that lncRNAs and immune response are closely related to the prognosis of hepatocellular carcinoma. The aim of this study was to establish a prognostic signature based on immune related lncRNAs for HCC.Methods: Univariate cox regression analysis was performed to identify immune related lncRNAs, which had negative correlation with overall survival (OS) of 370 HCC patients from The Cancer Genome Atlas (TCGA). A prognostic signature based on OS related lncRNAs was identified by using multivariate cox regression analysis. Gene set enrichment analysis (GSEA) and a competing endogenous RNA (ceRNA) network were performed to clarify the potential mechanism of lncRNAs included in prognostic signature. Results: A prognostic signature based on OS related lncRNAs (AC145207.5, AL365203.2, AC009779.2, ZFPM2-AS1, PCAT6, LINC00942) showed moderately in prognosis prediction, and related with pathologic stage (Stage I&II VS Stage III&IV), distant metastasis status (M0 VS M1) and tumor stage (T1-2 VS T3-4). CeRNA network constructed 15 aixs among differentially expressed immune related genes, lncRNAs included in prognostic signature and differentially expressed miRNA. GSEA indicated that these lncRNAs were involved in cancer-related pathways. Conclusion: We constructed a prognostic signature based on immune related lncRNAs which can predict prognosis and guide therapies for HCC.

scholarly journals Construction and Validation of a Reliable Six-Gene Prognostic Signature Based on the TP53 Alteration for Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Junyu Huo ◽  
Liqun Wu ◽  
Yunjin Zang
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Gene Set Enrichment ◽  
Cox Regression Analysis ◽  
Gene Set

BackgroundThe high mutation rate of TP53 in hepatocellular carcinoma (HCC) makes it an attractive potential therapeutic target. However, the mechanism by which TP53 mutation affects the prognosis of HCC is not fully understood.Material and ApproachThis study downloaded a gene expression profile and clinical-related information from The Cancer Genome Atlas (TCGA) database and the international genome consortium (ICGC) database. We used Gene Set Enrichment Analysis (GSEA) to determine the difference in gene expression patterns between HCC samples with wild-type TP53 (n=258) and mutant TP53 (n=116) in the TCGA cohort. We screened prognosis-related genes by univariate Cox regression analysis and Kaplan–Meier (KM) survival analysis. We constructed a six-gene prognostic signature in the TCGA training group (n=184) by Lasso and multivariate Cox regression analysis. To assess the predictive capability and applicability of the signature in HCC, we conducted internal validation, external validation, integrated analysis and subgroup analysis.ResultsA prognostic signature consisting of six genes (EIF2S1, SEC61A1, CDC42EP2, SRM, GRM8, and TBCD) showed good performance in predicting the prognosis of HCC. The area under the curve (AUC) values of the ROC curve of 1-, 2-, and 3-year survival of the model were all greater than 0.7 in each independent cohort (internal testing cohort, n = 181; TCGA cohort, n = 365; ICGC cohort, n = 229; whole cohort, n = 594; subgroup, n = 9). Importantly, by gene set variation analysis (GSVA) and the single sample gene set enrichment analysis (ssGSEA) method, we found three possible causes that may lead to poor prognosis of HCC: high proliferative activity, low metabolic activity and immunosuppression.ConclusionOur study provides a reliable method for the prognostic risk assessment of HCC and has great potential for clinical transformation.

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