scholarly journals Effects of miRNA-140 on the Growth and Clinical Prognosis of SMMC-7721 Hepatocellular Carcinoma Cell Line

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Cun-qing Kong ◽  
Xing-cai Chen ◽  
Guan-hua Qiu ◽  
Jing-chen Liang ◽  
Duo Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Cox Regression ◽  
Expression Level ◽  
Migration And Invasion ◽  
Clinical Prognosis ◽  
Cox Regression Analysis ◽  
Qrt Pcr ◽  
Kaplan Meier ◽  
Hcc Cells

Background. A growing number of studies have suggested that microRNAs exert an essential role in the development and occurrence of multiple tumours and act as crucial regulators in various biological processes. However, the expression and function of miRNA-140 in hepatocellular carcinoma (HCC) cells are not yet adequately identified and manifested. Methods. The expression of miRNA-140 was determined in HCC tissues and adjacent nontumour tissues by quantitative real-time polymerase chain reaction (qRT-PCR). Kaplan–Meier survival analysis and Cox regression analysis were performed to explore the correlation between miRNA-140 expression level and the survival rate of patients with HCC. Additionally, overexpression experiments were conducted to investigate the biological role of miRNA-140 in HCC cells. Bioinformatics was used to predict the related target genes and pathways of miRNA-140. Results. QRT-PCR results signified that the expression level of miRNA-140 in HCC was lower than that of adjacent normal tissues ( P < 0.0001 ). Compared with the control group, the SMMC-7721 HCC cells in the miRNA-140 mimic group had a decrease in proliferation, migration, and invasion ( P < 0.05 ), whereas those in the miRNA-140 inhibitor group had an increase in proliferation, migration, and invasion ( P < 0.05 ). Cell cycle arrest occurred in the G0/1 phase. Prognosis analysis showed that the expression level of miRNA-140 was not related to the prognosis of HCC. Furthermore, the Kaplan–Meier test revealed that patients with lower miRNA-140 expression levels in liver cancer tissue had significantly shorter disease-free survival (DFS, P = 0.004 ) and overall survival (OS) times ( P = 0.010 ) after hepatectomy. Cox regression analysis further indicated that miRNA-140 was an independent risk factor that may affect the DFS ( P = 0.004 ) and OS times ( P = 0.014 ) of patients after hepatectomy. Our results suggested that miRNA-140 might be a crucial regulator involved in the HCC progression and is thus considered a potential prognostic biomarker and therapeutic target for HCC.

scholarly journals Screening Prognosis-Related lncRNAs Based on WGCNA to Establish a New Risk Score for Predicting Prognosis in Patients with Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Xueliang Zhou ◽  
Mengmeng Dou ◽  
Zaoqu Liu ◽  
Dechao Jiao ◽  
Zhaonan Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Scoring System ◽  
Normal Tissue ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Risk Scoring ◽  
Risk Scoring System

Background. Hepatocellular carcinoma (HCC) remains an important cause of cancer death. The molecular mechanism of hepatocarcinogenesis and prognostic factors of HCC have not been completely uncovered. Methods. In this study, we screened out differentially expressed lncRNAs (DE lncRNAs), miRNAs (DE miRNAs), and mRNAs (DE mRNAs) by comparing the gene expression of HCC and normal tissue in The Cancer Genome Atlas (TCGA) database. DE mRNAs were used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the miRNA and lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a competitive endogenous RNA (ceRNA) network by weighted gene coexpression network analysis (WGCNA). Moreover, univariable Cox regression and Kaplan-Meier curve analyses of DE lncRNAs and DE mRNAs were conducted. Finally, the lasso-penalized Cox regression analysis and nomogram model were used to establish a new risk scoring system and predict the prognosis of patients with liver cancer. The expression of survival-related DE lncRNAs was verified by qRT-PCR. Results. A total of 1896 DEmRNAs, 330 DElncRNAs, and 76 DEmiRNAs were identified in HCC and normal tissue samples. Then, the turquoise miRNA and turquoise lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a ceRNA network by WGCNA. In this ceRNA network, there were 566 lncRNA-miRNA-mRNA regulatory pairs, including 30 upregulated lncRNAs, 16 downregulated miRNAs, and 75 upregulated mRNAs. Moreover, we screened out 19 lncRNAs and 14 hub mRNAs related to prognosis from this ceRNA network by univariable Cox regression and Kaplan-Meier curve analyses. Finally, a new risk scoring system was established by selecting the optimal risk lncRNAs from the 19 prognosis-related lncRNAs through lasso-penalized Cox regression analysis. In addition, we established a nomogram model consisting of independent prognostic factors to predict the survival rate of HCC patients. Finally, the correlation between the risk score and immune cell infiltration and gene set enrichment analysis were determined. Conclusions. In conclusion, the results may provide potential biomarkers or therapeutic targets for HCC and the establishment of the new risk scoring system and nomogram model provides the new perspective for predicting the prognosis of HCC.

scholarly journals Integrated Analysis of lncRNA-Mediated ceRNA Network Reveals a Prognostic Signature for Hepatocellular Carcinoma

2020 ◽  
Vol 11 ◽  
Author(s):  
Jian-Rong Sun ◽  
Chen-Fan Kong ◽  
Kun-Min Xiao ◽  
Jia-Lu Yang ◽  
Xiang-Ke Qu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Cox Regression ◽  
Tnm Stage ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Cox Regression Analysis ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Risk Patients

Hepatocellular carcinoma (HCC) is one of the most common types of malignancy and is associated with high mortality. Prior research suggests that long non-coding RNAs (lncRNAs) play a crucial role in the development of HCC. Therefore, it is necessary to identify lncRNA-associated therapeutic biomarkers to improve the accuracy of HCC prognosis. Transcriptomic data of HCC obtained from The Cancer Genome Atlas (TCGA) database were used in the present study. Differentially expressed RNAs (DERNAs), including 74 lncRNAs, 16 miRNAs, and 35 mRNAs, were identified using bioinformatics analysis. The DERNAs were subsequently used to reconstruct a competing endogenous RNA (ceRNA) network. A lncRNA signature was revealed using Cox regression analysis, including LINC00200, MIR137HG, LINC00462, AP002478.1, and HTR2A-AS1. Kaplan-Meier plot demonstrated that the lncRNA signature is highly accurate in discriminating high- and low-risk patients (P &lt; 0.05). The area under curve (AUC) value exceeded 0.7 in both training and validation cohort, suggesting a high prognostic potential of the signature. Furthermore, multivariate Cox regression analysis indicated that both the TNM stage and the lncRNA signature could serve as independent prognostic factors for HCC (P &lt; 0.05). Then, a nomogram comprising the TNM stage and the lncRNA signature was determined to raise the accuracy in predicting the survival of HCC patients. In the present study, we have introduced a ceRNA network that could contribute to provide a new insight into the identification of potential regulation mechanisms for the development of HCC. The five-lncRNA signature could serve as a reliable biosignature for HCC prognosis, while the nomogram possesses strong potential in clinical applications.

scholarly journals Expression of Long Non-Coding RNA PANDAR and its Prognostic Value in Colorectal Cancer Patients

2017 ◽  
Vol 32 (2) ◽  
pp. 218-223 ◽  
Author(s):  
Xiangke Li ◽  
Feng Wang ◽  
Yan Sun ◽  
Qingxia Fan ◽  
Guangfei Cui
Keyword(s):  
Colorectal Cancer ◽  
Cox Regression ◽  
Human Cancer ◽  
Expression Level ◽  
Migration And Invasion ◽  
Cox Regression Analysis ◽  
Relative Expression Level ◽  
Kaplan Meier ◽  
Colorectal Cancer Patients

Background Long noncoding RNAs (lncRNAs) are emerging as key molecules in human cancer. In the present study, we explored the role of the lncRNA PANDAR in colorectal cancer (CRC). Methods The relative expression level of lncRNA PANDAR in CRC tissues and cell lines was determined by quantitative real-time polymerase chain reaction (qRT-PCR). The associations between PANDAR expression and clinicopathological features of CRC patients were further analyzed. Kaplan-Meier survival analysis was performed to evaluate the value of PANDAR in the prognosis of CRC patients. Furthermore, the biological function of PANDAR on CRC cell growth, apoptosis and mobility was investigated through MTT, flow cytometry, transwell migration and invasion assays in vitro. Results The expression level of PANDAR was higher in CRC tissues and cells compared with adjacent nontumor tissues and normal colonic cell line NCM460. PANDAR expression was significantly correlated with local invasion, lymph node metastasis and TNM stage. Kaplan-Meier analysis showed that patients with high PANDAR expression had poorer overall survival than patients with low PANDAR expression. Multivariate Cox regression analysis indicated that PANDAR might be an independent prognostic factor for CRC patients. Furthermore, PANDAR knockdown significantly inhibited cell proliferation, cycle progression, migration and invasion of CRC in vitro. Conclusions Our results suggest that high expression of PANDAR was involved in CRC progression and could act as an independent biomarker for prognosis of CRC patients.

scholarly journals Microtubule-Associated Protein 4 Is a Prognostic Factor and Promotes Tumor Progression in Lung Adenocarcinoma

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaochun Xia ◽  
Chao He ◽  
Anqing Wu ◽  
Jundong Zhou ◽  
Jinchang Wu
Keyword(s):  
Regression Analysis ◽  
Prognostic Factor ◽  
Lung Adenocarcinoma ◽  
Cancer Progression ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Microtubule Assembly ◽  
Migration And Invasion ◽  
Cox Regression Analysis ◽  
Kaplan Meier

Microtubule-associated protein 4 (MAP4) plays an important role in microtubule assembly and stabilization. The purpose of this study was to investigate the level of expression of MAP4 in lung adenocarcinoma (LADC) samples and to evaluate its prognostic value and the influence on cancer progression in LADC patients. The expression of MAP4 protein was analyzed using immunohistochemistry. The clinical significance and the prognostic significance of MAP4 expression were assessed by Kaplan-Meier analysis and Cox regression analysis. The roles of MAP4 in the migration and invasion of LADC cells were detected by wound-healing assays and transwell assays, respectively. We found the expression levels of MAP4 protein in LADC tissues to be significantly higher than those in noncancerous tissues. MAP4 expression was significantly correlated with differentiation, pathological T stage, and TNM stage. Kaplan-Meier survival analysis indicated that patients with high MAP4 expression had significantly poorer overall survival (OS). Cox regression analysis revealed that MAP4 expression level was an independent prognostic factor for OS. Functionally, in vitro studies showed that MAP4 knockdown efficiently suppressed the migration and invasion of LADC cells. Our data indicated that MAP4 protein may represent a novel prognostic biomarker and a potential therapeutic target for LADC.

scholarly journals Increased Expression of miR-487b Is Associated With Poor Prognosis and Tumor Progression of HBV-Related Hepatocellular Carcinoma

2020 ◽  
Vol 7 (12) ◽  
Author(s):  
Xiangang Cao ◽  
Qian Yang ◽  
Qing Yu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Hepatitis B ◽  
Roc Curve ◽  
Cox Regression ◽  
Migration And Invasion ◽  
Healthy Controls ◽  
Cox Regression Analysis ◽  
Specificity And Sensitivity ◽  
Tumor Node Metastasis Stage

Abstract Background Increasing evidence has demonstrated the involvement of microRNAs in the pathogenesis of hepatitis B virus (HBV)–related hepatocellular carcinoma (HCC). The aims of this study were to analyze whether miR-487b can be used as a diagnostic and prognostic biomarker for HBV-related HCC and to explore its effect on the biological function of HCC. Methods The expression levels of miR-487b in the serum of all subjects were measured by real-time quantitative fluorescence polymerase chain reaction. The diagnostic value of miR-487b in serum was assessed using the receiver operating characteristic (ROC) curve. The relationship between miR-487b and the clinical data of patients was analyzed using the chi-square test. The prognostic value of miR-487b in HCC was assessed by Cox regression analysis and Kaplan-Meier survival. Moreover, CCK-8 and Transwell assays were performed to investigate the effect of miR-487b on HBV-related HCC function. Results Our data indicated that miR-487b in HCC patients was significantly higher than in chronic hepatitis B (CHB) patients and healthy controls. Meanwhile, the ROC curve showed that miR-487b had high specificity and sensitivity in the diagnosis of HBV-related HCC. MiR-487b can significantly distinguish between HCC patients and healthy controls and can differentiate HCC patients from CHB patients. Cox regression analysis showed that miR-487b was an independent risk factor. Overexpression of miR-487b was associated with Tumor Node Metastasis stage stage and Barcelona Clinic Liver Cancer stage in HCC patients. Cell function experiments demonstrated that upregulated miR-487b promoted cell proliferation, migration, and invasion. Conclusions Combined the results of the current study demonstrate that the upregulation of serum miR-487b may serve as a promising noninvasive diagnostic biomarker for HBV-related HCC.

scholarly journals Screening prognosis-related lncRNAs based on WGCNA to establish a new risk score for predicting prognosis in patients with hepatocellular carcinoma

2020 ◽  
Author(s):  
Xueliang Zhou ◽  
Mengmeng Dou ◽  
Zaoqu Liu ◽  
Dechao Jiao ◽  
Zhaonan Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Scoring System ◽  
Normal Tissue ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Background: Hepatocellular carcinoma (HCC) remains an important cause of cancer death. The molecular mechanism of hepatocarcinogenesis and prognostic factors of HCC have not been completely uncovered. Methods: In this study, we screened out differentially expressed lncRNAs (DE lncRNAs), miRNAs (DE miRNAs), and mRNAs (DE mRNAs) by comparing the gene expression of HCC and normal tissue in the The Cancer Genome Atlas (TCGA) database. DE mRNAs were used to perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the miRNA and lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a competitive endogenous RNA (ceRNA) network by weighted gene coexpression network analysis (WGCNA). Moreover, univariable Cox regression and Kaplan-Meier curve analyses of DE lncRNAs and DE mRNAs were conducted. Finally, the lasso‐penalized Cox regression analysis and nomogram model were used to establish new risk scoring system and predict the prognosis of patients with liver cancer. Results: A total of 1896 DEmRNAs, 330 DElncRNAs, and 76 DEmiRNAs were identified in HCC and normal tissue samples. Then, the turquoise miRNA and turquoise lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a ceRNA network by WGCNA. In this ceRNA network, there were 566 lncRNA-miRNA-mRNA regulatory pairs, including 30 upregulated lncRNAs, 16 downregulated miRNAs and 75 upregulated mRNAs. Moreover, we screened out 19 lncRNAs and 14 hub mRNAs related to prognosis from this ceRNA network by univariable Cox regression and Kaplan-Meier curve analyses. Finally, a new risk scoring system was established by selecting the optimal risk lncRNAs from the 19 prognosis-related lncRNAs through lasso‐penalized Cox regression analysis. In addition, we established a nomogram model consisting of independent prognostic factors to predict the survival rate of HCC patients. Conclusions: In conclusion, the results may provide potential biomarkers or therapeutic targets for HCC, and the establishment of new risk scoring system and nomogram model provide the new perspective for predicting the prognosis of HCC.

scholarly journals Construction and Comprehensive Analysis of a Stratification System Based on AGTRAP in Patients with Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Li Wang ◽  
Wenjun Zhang ◽  
Tao Yang ◽  
Le He ◽  
Yunmei Liao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Differential Expression ◽  
Topological Degree ◽  
Cox Regression ◽  
Ppi Network ◽  
Hub Gene ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Stratification System

Background. With the development of sequencing technology, several signatures have been reported for the prediction of prognosis in patients with hepatocellular carcinoma (HCC). However, the above signatures are characterized by cumbersome application. Therefore, the study is aimed at screening out a robust stratification system based on only one gene to guide treatment. Methods. Firstly, we used the limma package for performing differential expression analysis on 374 HCC samples, followed by Cox regression analysis on overall survival (OS) and disease-free interval (PFI). Subsequently, hub prognostic genes were found at the intersection of the above three groups. In addition, the topological degree inside the PPI network was used to screen for a unique hub gene. The rms package was used to construct two visual stratification systems for OS and PFI, and Kaplan-Meier analysis was utilized to investigate survival differences in clinical subgroups. The ssGSEA algorithm was then used to reveal the relationship between the hub gene and immune cells, immunological function, and checkpoints. In addition, we also used function annotation to explore into putative biological functions. Finally, for preliminary validation, the hub gene was knocked down in the HCC cell line. Results. We discovered 6 prognostic genes (SKA1, CDC20, AGTRAP, BIRC5, NEIL3, and CDC25C) for constructing a PPI network after investigating survival and differential expression genes. According to the topological degree, AGTRAP was chosen as the basis for the stratification system, and it was revealed to be a risk factor with an independent prognostic value in Kaplan-Meier analysis and Cox regression analysis ( P < 0.05 ). In addition, we constructed two visualized nomograms based on AGTRAP. The novel stratification system had a robust predictive value for PFI and OS in ROC analysis and calibration curve ( P < 0.05 ). Meanwhile, AGTRAP upregulation was associated with T staging, N staging, M staging, pathological stage, grade, and vascular invasion ( P < 0.05 ). Notably, AGTRAP was overexpressed in tumor tissues in all pancancers with paired samples ( P < 0.05 ). Furthermore, AGTRAP was associated with immune response and may change immune microenvironment in HCC ( P < 0.05 ). Next, gene enrichment analysis suggested that AGTRAP may be involved in the biological process, such as cotranslational protein targeting to the membrane. Finally, we identified the oncogenic effect of AGTRAP by qRT-PCR, colony formation, western blot, and CCK-8 assay ( P < 0.05 ). Conclusion. We provided robust evidences that a stratification system based on AGTRAP can guide survival prediction for HCC patients.

scholarly journals Predictive Value of F-SIRI in Prognosis of Patients with Hepatocellular Carcinoma after Radical Hepatectomy

2021 ◽  
Author(s):  
hu panyi ◽  
Yongwei Zhang ◽  
yeben qian
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Predictive Value ◽  
Cox Regression ◽  
Clinicopathological Characteristics ◽  
Tumor Diameter ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
High Level ◽  
The Relationship

Abstract Background: Objective to evaluate the predictive value of preoperative fibrinogen and systemic inflammatory response index (F-SIRI) in the prognosis of patients with hepatocellular carcinoma after radical hepatectomy. Methods: the clinical data of 298 patients with hepatocellular carcinoma who underwent surgery and confirmed by postoperative pathology in our hospital from January 2015 to December 2017 were retrospectively analyzed. The F-SIRI score was calculated according to FIB and SIRI data of peripheral blood. The relationship between F-SIRI score and clinicopathological characteristics was analyzed. The survival analysis was performed by Kaplan Meier method, Cox regression analysis was used to analyze the prognostic factors. Results: preoperative F-SIRI score was correlated with tumor diameter, FIB and SIRI (P<0.05), but not with age, gender, TNM stage and other clinical features (P>0.05). There were significant differences in the 5-year DFS rate and OS rate among patients with different preoperative F-SIRI scores(P<0.05); Cox regression analysis showed that preoperative tumor diameter, alpha fetoprotein level and F-SIRI score were independent predictors of DFS in patients with HCC (P< 0.05), while preoperative tumor diameter, ALB and F-SIRI score as independent predictors of OS (P<0.05). Conclusion: preoperative F-SIRI is an independent prognostic factor in patients with HCC after radical hepatectomy, with poor prognosis in patients with high level of F-SIRI.

scholarly journals WAITING DAAS LIST MORTALITY IMPACT IN HCV CIRRHOTIC PATIENTS

2018 ◽  
Vol 55 (4) ◽  
pp. 343-345 ◽  
Author(s):  
Giovanni Faria SILVA ◽  
Vanessa Gutierrez de ANDRADE ◽  
Alecsandro MOREIRA
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Cox Regression ◽  
Antiviral Agents ◽  
Meld Score ◽  
New Drugs ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Cirrhotic Patients ◽  
Direct Antiviral Agents

ABSTRACT BACKGROUND: The infection for the hepatitis C virus (HCV) is a leading cause of liver-related morbidity and mortality through its evolution to liver cirrhosis, end-stage liver complications and hepatocellular carcinoma. Currently, the new drugs for the HCV infection, based on direct antiviral agents, have changed the outcomes in this setting. OBJECTIVE: To assess death incidence, during the wait for the treatment with the new drugs, and to analyze which independent variable (age, sex, ascite, HDA, albumin, α-fetoprotein, platelets and Meld score) had relation with death. METHODS: Prospective study with cirrhotic patients by HCV. Inclusion: cirrhotic patients by hepatic biopsy (METAVIR), clinic or image, detectable RNA (HCV). Exclusion: Other stages of hepatic fibrosis and hepatocellular carcinoma. Descriptive statistic in continue variables. Fisher Exact and Kaplan Meier and Cox Regression Analysis to assess the association of variables studied with death. P<0.05. RESULTS: A total of 129 patients were included. Of this, 73% were men. Mean age was 57.8±12.1, albumin of 3.5±0.6 mg/dL, platelets of 123.4±59.6 and Meld score of 10.59±3.56. The time of observation was 11.2±3.26 months, and the number of death 9/129 (6,9%). The Kaplan-Meier showed association between death with albumin lower than 2.9 (0.0006), MELD score higher than 15 (0.007) and α-fetoprotein higher than 40 ng/mL (<0.0001). Adjusted Cox Regression Analysis showed that α-fetoprotein higher than 40 ng/ml could be considered an independent risk for death. CONCLUSION: We conclude that, patients with advanced cirrhosis should be prioritized for treatment with direct antiviral agents.

scholarly journals Identification and Validation a Costimulatory Molecule Gene Signature to Predict the Prognosis and Immunotherapy Response for Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Yinan Hu ◽  
Jingyi Liu ◽  
Jiahao Yu ◽  
Fangfang Yang ◽  
Miao Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Immune Cells ◽  
Cox Regression ◽  
Costimulatory Molecule ◽  
Gene Signature ◽  
Consensus Clustering ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Qrt Pcr

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Costimulatory molecules have been proven to be the foundation of immunotherapy. However, the potential roles of costimulatory molecule genes (CMGs) in HCC remain unclear. Our study is aimed to develop a costimulatory molecule-related gene signature that could evaluate the prognosis of HCC patients.Methods: Based on The Cancer Gene Atlas (TCGA) database, univariate Cox regression analysis was applied in CMGs to identify prognosis-related CMGs. Consensus clustering analysis was performed to stratify HCC patients into different subtypes and compared them in OS. Subsequently, the LASSO Cox regression analysis was performed to construct the CMGs-related prognostic signature and Kaplan–Meier survival curves as well as ROC curve were used to validate the predictive capability. Then we explored the correlations of the risk signature with tumor-infiltrating immune cells, tumor mutation burden (TMB) and response to immunotherapy. The expression levels of prognosis-related CMGs were validated in HCC using qRT-PCR method.Results: All HCC patients were classified into two clusters based on 11 CMGs with prognosis values and cluster 2 correlated with a poorer prognosis. Next, a prognostic signature of six CMGs was constructed, which was an independent risk factor for HCC patients. Patients with low-risk score were associated with better prognosis. The correlation analysis showed that the risk signature could predict the infiltration of immune cells and immune status of the immune microenvironment in HCC. The qRT-PCR indicated six CMGs with significantly differential expression in HCC tissues and normal tissues.Conclusion: In conclusion, our CMGs-related risk signature could be used as a prediction tool in survival assessment and immunotherapy for HCC patients.

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