Identification and validation of a tyrosine metabolism-related prognostic prediction model and characterization of the tumor microenvironment infiltration in hepatocellular carcinoma

Identification of molecular subtypes based on bile acid metabolism in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma is a highly heterogeneous tumor with bile acid metabolism involving in its development. The aim of this study was to characterize bile acid metabolism and identify specific subtypes to better stratify cholangiocarcinoma patients for individualized treatment and prognostic assessment.

METHODS

A total of 30 bile acids were quantified using the ultra-performance liquid chromatography tandem mass spectrometry. Using Consensus clustering, the molecular subtypes related to bile acid metabolism were identified. The prognosis, clinicopathologic characteristics, immune landscape, and therapeutic response were compared between these subtypes. The single-cell RNA sequencing (scRNA-seq) analysis and preliminary cell experiment were also conducted to verify our findings.

RESULTS

The altered bile acid profile and genetic variation of bile acid metabolism-related genes in cholangiocarcinoma were demonstrated. The cholangiocarcinoma was categorized into bile acid metabolism-active and -inactive subtypes with different prognoses, clinicopathologic characteristics, tumor microenvironments (TME) and therapeutic responses. This categorization was reproducible and predictable. Specifically, the bile acid metabolism-active subtype showed a poor prognosis with an immunosuppressive microenvironment and an inactive response to immunotherapy, while the bile acid metabolism-inactive subtype showed the opposite characteristics. Moreover, the scRNA-seq revealed that immunotherapy altered bile acid metabolism in TME of cholangiocarcinoma. Finally, a prognostic signature related to bile acid metabolism was developed, which exhibited strong power for prognostic assessment of cholangiocarcinoma. Consistently, these results were verified by immunohistochemistry, cell proliferation, migration, and apoptosis assays.

CONCLUSION

In conclusion, a novel cholangiocarcinoma classification based on bile acid metabolism was established. This classification was significant for the estimation of TME and prognosis.

Structural basis of tRNA recognition by the m3C RNA methyltransferase METTL6 in complex with SerRS seryl-tRNA synthetase

Methylation of cytosine 32 in the anticodon loop of tRNAs to 3-methylcytosine (m3C) is crucial for cellular translation fidelity. Misregulation of the RNA methyltransferases setting this modification can cause aggressive cancers and metabolic disturbances. Here, we report the cryo-electron microscopy structure of the human m3C tRNA methyltransferase METTL6 in complex with seryl-tRNA synthetase (SerRS) and their common substrate tRNASer. Through the complex structure, we identify the tRNA-binding domain of METTL6. We show that SerRS acts as the tRNASer substrate selection factor for METTL6. We demonstrate that SerRS augments the methylation activity of METTL6 and that direct contacts between METTL6 and SerRS are necessary for efficient tRNASer methylation. Finally, on the basis of the structure of METTL6 in complex with SerRS and tRNASer, we postulate a universal tRNA-binding mode for m3C RNA methyltransferases, including METTL2 and METTL8, suggesting that these mammalian paralogs use similar ways to engage their respective tRNA substrates and cofactors.

Identification of an Amino Acid Metabolism Reprogramming Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Colon Cancer

Colon cancer ranked third among the most frequently diagnosed cancers worldwide. Amino acid metabolic reprogramming was related to the occurrence and development of colon cancer. We looked for the amino acid metabolism genes (AMGs) associated with amino acid metabolism from molecular signatures database as prognostic markers and constructed amino acid metabolism scoring model (AMS). According to AMS, the patients were divided into high AMS and low AMS groups, and the prognostic characteristics, molecular phenotypes, somatic cell mutation characteristics, immune cell infiltration characteristics, and immunotherapy effect of the two groups were systematically analyzed. Finally, the compounds targeting AMGs were also screened. We screen out 6 prognostic AMGs (P < 0.05) and construct an AMS model based on them. K-M curve indicated that OS in low AMS group was significantly higher than that in high group (P < 0.05), which were validated in multiple datasets. And different AMS groups had different molecular phenotypes, somatic cell mutation characteristics and immune cell infiltration characteristics. Low AMS group had a better effect for immunotherapy. In addition, we predicted potential therapeutic compounds that could bind to AMGs target proteins. AMS model can be used as a hierarchical tool to evaluate the prognosis, immune infiltration characteristics and immunotherapy response ability of colon cancer. And the compounds screened based on AMGs may become new anti-tumor drugs.

TSA attenuates the progression of c-Myc-driven hepatocarcinogenesis by pAKT-ADH4 pathway

Hepatocellular carcinoma (HCC) is the primary malignant tumor of the liver. c-Myc is one of the most common oncogenes in clinical settings, and amplified levels of c-Myc are frequently found in HCC. Histone deacetylase inhibitors (HDACi), such as Trichostatin A (TSA), hold enormous promise for the treatment of HCC. However, the potential and mechanism of TSA in the treatment of c-Myc-induced HCC are unclear. In this study, we investigated the effects of TSA treatment on a c-Myc-induced HCC model in mice. TSA treatment delayed the development of HCC, and liver function indicators such as ALT, AST, liver weight ratio, and spleen weight ratio demonstrated the effectiveness of TSA treatment. Oil red staining further demonstrated that TSA attenuated lipid accumulation in the HCC tissues of mice. Through mRNA sequencing, we identified that TSA mainly affected cell cycle and fatty acid degradation genes, with alcohol dehydrogenase 4 (ADH4) potentially being the core molecular downstream target. QPCR, immunohistochemistry, and western blot analysis revealed that ADH4 expression was repressed by c-Myc and restored after TSA treatment both in vitro and in vivo. Furthermore, we observed that the levels of total NAD+ and NADH, NAD+, NAD+/NADH, and ATP concentration increased after c-Myc transfection in liver cells but decreased after TSA intervention. The levels of phosphorylated protein kinase B (p-AKT) and p-mTOR were identified as targets regulated by TSA, and they governed the ADH4 expression and the downstream regulation of total NAD+ and NADH, NAD+, NAD+/NADH, and ATP concentration. Overall, our study suggests that TSA has a therapeutic effect on c-Myc-induced HCC through the AKT-mTOR-ADH4 pathway. These findings provide valuable insights into the potential treatment of HCC using TSA and shed light on the underlying molecular mechanisms involved.

Integrated bioinformatics analysis and experimental validation to understand tryptophan metabolism-related genes in hepatocellular carcinoma

Background: Tryptophan (Trp) metabolism is closely related to tumor immunity, and its disorder can cause an immunosuppressive microenvironment, promoting the occurrence and development of hepatocellular carcinoma (HCC). The aim of this study is to explore and validate the independent prognostic genes in patients suffered from HCC. Methods: The transcriptome data of GSE87630 from GEO database were downloaded to analyze differentially expressed genes (DECs) which were intersected with the gene sets of Trp metabolism from MsigDB database. Univariate/multivariate COX regression was performed to identify the genes with independent prognostic significance. TCGA, GTEx, UALCAN, and GEPIA2 databases were applied to analyze DEGs for prognosis. RNA seq data of HCC from TCGA database were collected for Lasso regression analysis. The ssGSEA algorithm was used to perform the analysis of TCGA data. The effects of the candidate differential gene on HCC cells proliferation and migration were evaluated using EdU immunofluorescence and transwell assays. Results: Trp metabolism-related DECs for HCCs were obtained, including MAOB, CYP1A2, KYNU, CYP2E1, ALDH2, CYP2C18, TDO2, AOX1, CYP3A4 and INMT. Moreover, multivariate COX regression results showed that ALDH2 can serve as an independent prognostic molecule and its transcriptional and translational levels were significantly reduced in the tumor tissues. The low expression of ALDH2 was associated with poor prognosis. Overexpression of ALDH2 dramatically reduced the HCC cells proliferation and migration. Conclusion: ALDH2 is associated with Trp metabolism and its downregulation in HCC has a potential value on prognosis. Overexpression of ALDH2 can reduce the proliferation and migration of HCC cells.

Recent Advances in Biosensor Technology for Early-Stage Detection of Hepatocellular Carcinoma-Specific Biomarkers: An Overview

Hepatocellular carcinoma is currently the most common malignancy of the liver. It typically occurs due to a series of oncogenic mutations that lead to aberrant cell replication. Most commonly, hepatocellular carcinoma (HCC) occurs as a result of pre-occurring liver diseases, such as hepatitis and cirrhosis. Given its aggressive nature and poor prognosis, the early screening and diagnosis of HCC are crucial. However, due to its plethora of underlying risk factors and pathophysiologies, patient presentation often varies in the early stages, with many patients presenting with few, if any, specific symptoms in the early stages. Conventionally, screening and diagnosis are performed through radiological examination, with diagnosis confirmed by biopsy. Imaging modalities tend to be limited by their requirement of large, expensive equipment; time-consuming operation; and a lack of accurate diagnosis, whereas a biopsy's invasive nature makes it unappealing for repetitive use. Recently, biosensors have gained attention for their potential to detect numerous conditions rapidly, cheaply, accurately, and without complex equipment and training. Through their sensing platforms, they aim to detect various biomarkers, such as nucleic acids, proteins, and even whole cells extracted by a liquid biopsy. Numerous biosensors have been developed that may detect HCC in its early stages. We discuss the recent updates in biosensing technology, highlighting its competitive potential compared to conventional methodology and its prospects as a tool for screening and diagnosis.

Causal associations of BAFF-R on IgD+ CD24- B cell immune cell trait with hepatocellular carcinoma and the mediating role of phenylacetylglutamate levels: a Mendelian randomization study

We conducted a bi-directional two-sample Mendelian randomization (MR) analysis to investigate the causal associations between immune cell traits and hepatocellular carcinoma (HCC) and identified the mediating factor of metabolites. The exposure factors were immune cell traits, the mediators were metabolites, and the outcome variable was HCC. Inverse-variance weighted method (IVW) was the main method. Weighted median, MR-Egger regression, weighted mode, simple mode, and MR pleiotropy residual sum and outlier (MRPRESSO) methods were used as complementary methods. The results were tested by using the Bayesian weighted Mendelian randomization (BWMR) approach in our MR study. Subsequently, the potential mediating effect was investigated by conducting a two-step mediation analysis. We identified 26 traits with suggestive correlations between immune cell traits and HCC, with 4 immune cell traits among them having causal correlations with HCC. There were no causal correlations between HCC and immune cell traits in the reverse MR analysis. In the mediation analysis, we found a positive causal association between B cell-activating factor receptors (BAFF-R) on IgD+ CD24- B cell and HCC [IVW: odd ratio (OR), 0.845; 95% CI, 0.759-0.942; p = 0.002]. Phenylacetylglutamate (PAG) levels mediated 7.353% of the causal pathway from BAFF-R on IgD+ CD24- B cell and HCC. In conclusion, BAFF-R on IgD+ CD24- B cell lowers risk of HCC, with PAG levels playing a mediating role.

PD-1 Inhibitors Combined with Tyrosine Kinase Inhibitors with or without Hepatic Artery Infusion Chemotherapy for the First-Line Treatment of HBV-Related Advanced Hepatocellular Carcinoma: A Retrospective Study

Purpose

Comparing the efficacy and safety of programmed cell death protein-1 (PD-1) inhibitors combined with tyrosine kinase inhibitors (TKIs) with or without hepatic artery infusion chemotherapy (HAIC) in HBV-related advanced HCC and exploring prognostic predictors of the combined regimen.

Patients and Methods

A total of 194 patients diagnosed with HBV-related advanced HCC between 2020 and 2022 were included in the study, including 99 in the HAIC combined with PD-1 inhibitors plus TKIs (HPT group) and 95 in the PD-1 inhibitors plus TKIs (PT group). The efficacy was evaluated according to the tumor response rate and survival, and the safety was evaluated according to the adverse events.

Results

The HPT group showed higher overall response rate and disease control rate than the PT group. The median overall survival (OS) of the HPT group and the PT group were 18.10 months and 12.57 months, respectively, and the difference was statistically significant (hazard ratio (HR) = 0.519, 95% confidence interval (CI): 0.374-0.722, P < 0.001). The median progression-free survival (PFS) was 9.20 months in the HPT group and 6.33 months in the PT group (HR = 0.632, 95% CI: 0.470-0.851, P = 0.002). In addition, albumin bilirubin (ALBI) and systemic inflammatory response index (SIRI) are independent prognostic factors affecting HAIC combined with targeted immunotherapy and can be used as prognostic predictors. Almost all patients included in the study experienced treatment-related adverse events (TRAEs) of varying degrees of severity, with grade 1-2 adverse events predominating.

Conclusion

The HPT group had better OS and PFS than the PT group in patients with HBV-related advanced HCC. In addition, high ALBI and high SIRI were associated with poor prognosis in the HAIC combined group.

The biological behavior and clinical outcome of pituitary adenoma are affected by the microenvironment

BACKGROUND

Pituitary adenoma is one of the most common brain tumors. Most pituitary adenomas are benign and can be cured by surgery and/or medication. However, some pituitary adenomas show aggressive growth with a fast growth rate and are resistant to conventional treatments such as surgery, drug therapy, and radiation therapy. These tumors, referred to as refractory pituitary adenomas, often relapse or regrow in the early postoperative period. The tumor microenvironment (TME) has recently been identified as an important factor affecting the biological manifestations of tumors and acts as the main battlefield between the tumor and the host immune system.

MAIN BODY

In this review, we focus on describing TME in pituitary adenomas and refractory pituitary adenomas. Research on the immune microenvironment of pituitary adenomas is currently focused on immune cells such as macrophages and lymphocytes, and extensive research and experimental verifications are still required regarding other components of the TME. In particular, studies are needed to determine the role of the TME in the specific biological behaviors of refractory pituitary adenomas, such as high invasion, fast recurrence rate, and high tolerance to traditional treatments and to identify the mechanisms involved.

CONCLUSION

Overall, we summarize the similarities and differences between the TME of pituitary adenomas and refractory pituitary adenomas as well as the changes in the biological behavior of pituitary adenomas that may be caused by the microenvironment. These changes greatly affect the outcome of patients.

Identification of CD8+ T-cell exhaustion signatures for prognosis in HBV-related hepatocellular carcinoma patients by integrated analysis of single-cell and bulk RNA-sequencing

BACKGROUND

HBV infection is the leading risk factor for HCC. HBV infection has been confirmed to be associated with the exhaustion status of CD8+ T cells and immunotherapeutic efficacy in HCC. In this study, we aimed to investigate the prognostic value of the CD8+ T-cell exhaustion signature and immunotherapy response in patients with HBV-related HCC.

METHODS

We identified different clusters of HBV-related HCC cells by single-cell RNA sequencing (scRNA-seq) and identified CD8+ T-cell exhaustion-related genes (TERGs) by pseudotime analysis. We conducted differential expression analysis and LASSO Cox regression to detect genes and construct a CD8+ T-cell exhaustion index (TEI). We next combined the TEI with other clinicopathological factors to design a prognostic nomogram for HCC patients. We also analysed the difference in the TEI between the non-responder and responder groups during anti-PD-L1 therapy. In addition, we investigated how HBV induces CD8+ T lymphocyte exhaustion through the inhibition of tyrosine metabolism in HCC using gene set enrichment analysis and RT‒qPCR.

RESULTS

A CD8+ T-cell exhaustion index (TEI) was established with 5 TERGs (EEF1E1, GAGE1, CHORDC1, IKBIP and MAGOH). An AFP level > 500 ng, vascular invasion, histologic grade (G3-G4), advanced TNM stage and poor five-year prognosis were related to a higher TEI score, while HBV infection was related to a lower TEI score. Among those receiving anti-PD-L1 therapy, responders had lower TEIs than non-responders did. The TEI also serves as an independent prognostic factor for HCC, and the nomogram incorporating the TEI, TNM stage, and vascular invasion exhibited excellent predictive value for the prognosis in HCC patients. RT‒qPCR revealed that among the tyrosine metabolism-associated genes, TAT (tyrosine aminotransferase) and HGD (homogentisate 1,2 dioxygenase) were expressed at lower levels in HBV-HCC than in non-HBV HCC.

CONCLUSION

Generally, we established a novel TEI model by comprehensively analysing the progression of CD8+ T-cell exhaustion, which shows promise for predicting the clinical prognosis and potential immunotherapeutic efficacy in HBV-related HCC patients.

AP4M1 as a prognostic biomarker associated with cell proliferation, migration and immune regulation in hepatocellular carcinoma

BACKGROUND

AP4M1 is a protein-coding gene that plays a crucial role in transporter activity, recognition, and hereditary-associated diseases, but it's largely unknown in cancers.

METHODS

The expression level of AP4M1 in cancers was investigated by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and the correlation between AP4M1 and hepatocellular carcinoma (HCC) clinicopathological parameters were analyzed. Univariate and multifactorial COX regression analyses were performed to clarify the prognostic value of AP4M1 in HCC. The correlation between AP4M1 and immune cell infiltration was analyzed using single-sample Gene Set Enrichment Analysis (ssGSEA). Besides, we verified the biological function of AP4M1 by applying Cell Counting Kit-8 (CCK8), colony formation, and transwell assays.

RESULTS

The expression of AP4M1 was significantly elevated in HCC and was correlated with patients' pathological grades, AFP, and BMI. Kaplan-Meier survival curves indicated that patients with AP4M1 overexpression had worse overall survival. Univariate and multivariate COX regression analyses showed that AP4M1 was an independent risk factor affecting the prognosis of HCC. In addition, we observed that AP4M1 positively correlated with most immune checkpoint suppressor genes in HCC. Moreover, in vitro experiments further confirmed that AP4M1 could promote the proliferation and invasion of HCC.

CONCLUSIONS

AP4M1 is highly expressed and associated with poor prognosis in HCC. AP4M1 is closely related to cancer-immune regulation and could be a novel target for HCC, and guiding new strategies for the diagnosis and treatment of HCC patients.

A Novel Gene Pair CSTF2/DPE2A Impacts Prognosis and Cell Cycle of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC), one of the commonest cancers at present, possesses elevated mortality. This study explored the predictive value of CSTF2/PDE2A for HCC prognosis.

Methods

In this study, clinical information and RNA sequencing expression profiles of HCC patients were acquired from common databases. Kaplan-Meier curve compound with time-dependent ROC curve, nomogram model, and univariate/multivariate Cox analysis were carried out to access the prediction capacity of CSTF2/PDE2A. The immune status, tumor microenvironment, drug sensitivity, biological function and pathway between HCC and adjacent non-tumorous tissue were analyzed and compared. Finally, RT-qPCR, Western blot, and apoptosis assays were performed to verify the effect on HCC cells of CSTF2/PDE2A.

Results

The optimal cut-off value of CSTF2, PDE2A and CSTF2/PDE2A was 6.95, 0.95 and 3.63, respectively. In TCGA and ICGC cohorts, the high group of CSTF2/PDE2A presented higher OS compared to low group. The area under the curve (AUC) for OS at 1-, 2-, and 3-years predicted by CSTF2/PDE2A were 0.731/0.695, 0.713/0.732 and 0.689/0.755, higher than the counterparts of the single gene CSTF2 and PDE2A. Multivariate Cox analysis revealed that CSTF2/PDE2A (HR = 1.860/3.236, 95% CI = 1.265-2.733/1.575-6.645) was an independent prognostic factor for HCC. The OS nomogram model created according to five independent factors including CSTF2/PDE2A showed excellent capacity for HCC prognosis. Furthermore, the immune status of the CSTF2/PDE2A high group was deleted, cell cycle-related genes and chemotherapy resistance were increased. Finally, cell experiments revealed distinct differences in the proliferation, apoptosis, protein and mRNA expression of HCC cells after si-CSTF2 transfection compared with the negative control.

Conclusion

Taken together, the gene pair CSTF2/PDE2A is able to forecast the prognosis of HCC and regulates cell cycle, which is promising as a novel prognostic predictor of HCC.

Development of tryptophan metabolism patterns to predict prognosis and immunotherapeutic responses in hepatocellular carcinoma

Tryptophan metabolism is associated with tumorigenesis and tumor immune response in various cancers. Liver is the main place where tryptophan catabolism is performed. However, the role of tryptophan metabolism in hepatocellular carcinoma (HCC) has not been well clarified. In the present study, we described the mutations of 42 tryptophan metabolism-related genes (TRPGs) in HCC cohorts. Then, HCC patients were well distributed into two subtypes based on the expression profiles of the 42 TRPGs. The clinicopathological characteristics and tumor microenvironmental landscape of the two subtypes were profiled. We also established a TRPGs scoring system and identified four hallmark TRPGs, including ACSL3, ADH1B, ALDH2, and HADHA. Univariate and multivariate Cox regression analysis revealed that the TRPG signature was an independent prognostic indicator for HCC patients. Besides, the predictive accuracy of the TRPG signature was assessed by the receiver operating characteristic curve (ROC) analysis. These results showed that the TRPG risk model had an excellent capability in predicting survival in both TCGA and GEO HCC cohorts. Moreover, we discovered that the TRPG signature was significantly related to the different immune infiltration and therapeutic drug sensitivity. The functional experiments and immunohistochemistry staining analysis also validated the results above. Our comprehensive analysis enhanced our understanding of TRPGs in HCC. A novel predictive model based on TRPGs was built, which may be considered as a beneficial tool for predicting the clinical outcomes of HCC patients.

CD69 serves as a potential diagnostic and prognostic biomarker for hepatocellular carcinoma

The prevalence and mortality of hepatocellular carcinoma (HCC) are still increasing. This study aimed to identify potential therapeutic targets related to patient prognosis. Data were downloaded from TCGA, GSE25097, GSE36376, and GSE76427 datasets. Differential analysis and enrichment analysis were performed in HCC. Cell deaths were evaluated, and least absolute shrinkage and selection operator regression (LASSO) regression was analyzed to screen candidate genes. Additionally, immune cell infiltration in HCC was assessed. We identified 4088 common DEGs with the same direction of differential expression in all four datasets, they were mainly enriched in immunoinflammation and cell cycle pathways. Apoptosis was significantly suppressed in HCC in GSEA and GSVA. After LASSO regression analysis, we screened CD69, CDC25B, MGMT, TOP2A, and TXNIP as candidate genes. Among them, CD69 significantly influenced the overall survival of HCC patients in both TCGA and GSE76427. CD69 may be a protective factor for outcome of HCC patients. In addition, CD69 was positive correlation with T cells and CD3E. CD69, CDC25B, MGMT, TOP2A, and TXNIP were potential diagnostic and prognostic target for HCC, especially CD69.

Integrative Analysis of the Predictive Value of Perilipin Family on Clinical Significance, Prognosis and Immunotherapy of Glioma

Gliomas are common tumors of the central nervous system. The PLINs family is widely involved in the regulation of lipid metabolism and has been associated with the development and invasive metastasis of various malignancies. However, the biological role of the PLINs family in gliomas is still unclear. TIMER and UALCAN were used to assess PLINs mRNA expression in gliomas. “Survminer” and “Survival” were used to evaluate the connection between PLINs expression and glioma patients’ survival. cBioPortal was applied to assess PLINs’ genetic alterations in glioblastoma multiforme (GBM) and low-grade glioma (LGG). The correlation of PLINs expression with tumor immune cells was analyzed by TIMER. The expressions of PLIN1, PLIN4, and PLIN5 were decreased in GBM compared to normal tissues. However, PLIN2 and PLIN3 were significantly increased in GBM. Prognostic analysis showed that LGG patients with high PLIN1 expression had better overall survival (OS), and high expression of PLIN2/3/4/5 was associated with unfavorable OS. We further determined that the expression of PLINs members in gliomas was strongly related to tumor immune cells and immune checkpoint-associated genes. PLINS may be potential biomarkers for regulating the tumor microenvironment and predicting the efficacy of immunotherapy. In addition, we determined that PLIN1 may affect glioma patients’ therapeutic sensitivity to temozolomide. Our results demonstrated the biological significance and clinical values of PLINs in gliomas and provide a basis for future in-depth exploration of the specific mechanisms of each member of PLINs in gliomas.

Identification and validation of a novel cuproptosis-related genes signature associated with prognosis, clinical implications and immunotherapy of hepatocellular carcinoma

Background: Cuproptosis is a novel type of regulated cell death and is reported to promote tumor occurrence and progression. However, whether a cuproptosis-related signature has an impact on hepatocellular carcinoma (HCC) is still unclear. Materials and methods: We analyzed the transcriptome data of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database, and searched for tumor types with different cuproptosis patterns through consistent clustering of cuproptosis genes. We then constructed a Cuproptosis-Related Genes (CRGs)-based risk signature through LASSO COX regression, and further analyzed its impact on the prognosis, clinical characteristics, immune cell infiltration, and drug sensitivity of HCC. Results: We identified the expression changes of 10 cuproptosis-related genes in HCC, and all the patients can be divided into two subtypes with different prognosis by applying the consensus clustering algorithm. We then constructed a cuproptosis-related risk signature and identified five CRGs, which were highly correlated with prognosis and representative of this gene set, namely G6PD, PRR11, KIF20A, EZH2, and CDCA8. Patients in the low CRGs signature group had a favorable prognosis. We further validated the CRGs signature in ICGC cohorts and got consistent results. Besides, we also discovered that the CRGs signature was significantly associated with a variety of clinical characteristics, different immune landscapes and drug sensitivity. Moreover, we explored that the high CRGs signature group was more sensitive to immunotherapy. Conclusion: Our integrative analysis demonstrated the potential molecular signature and clinical applications of CRGs in HCC. The model based on CRGs can precisely predict the survival outcomes of HCC, and help better guide risk stratification and treatment strategy for HCC patients.