Prognostic and predictive significance of the tumor microenvironment in hepatocellular carcinoma

2021 ◽  
pp. 1-12
Author(s):  
Jibing Liu ◽  
Shuwen Kuang ◽  
Yiling Zheng ◽  
Mei Liu ◽  
Liming Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Roc Curve ◽  
Cox Regression ◽  
Predictive Biomarker ◽  
Foxp3 Expression ◽  
Tissue Samples ◽  
Logistic Analysis ◽  
Kaplan Meier ◽  
Tumor Number

BACKGROUND: Identification of molecular markers that reflect the characteristics of the tumor microenvironment (TME) may be beneficial to predict the prognosis of post-operative hepatocellular carcinoma (HCC) patients. OBJECTIVE AND METHODS: A total of 100 tissue samples from HCC patients were separately stained by immunohistochemistry to examine the expression levels of CD56, CD8α, CD68, FoxP3, CD31 and pan-Keratin. The prognostic values were analyzed by Cox regression and the Kaplan-Meier method. RESULTS: Univariate and multivariate logistic analysis showed that FoxP3 was the independent factor associated with microvascular invasion (MVI), tumor size and envelop invasion; CD68 was associated with envelope invasion and AFP. Kaplan-Meier survival curves revealed that CD68 and FoxP3 expression were significantly associated with relapse free survival (RFS) of HCC patients (P< 0.05). The ROC curve indicated that the combination of tumor number, MVI present and CD68 expression yielded a ROC curve area of 82.3% (86.36% specificity, 68.75% sensitivity) to evaluate the prognosis of HCC patients, which was higher than the classifier established by the combination of tumor number and MVI (78.8% probability, 63.64% specificity and 85.42% sensitivity). CONCLUSIONS: Our study indicated that CD68 and FoxP3 are associated with prognosis of HCC patients, and CD68 can be considered as a potential prognostic and predictive biomarker.

Identification of Novel Tumor Microenvironment-Related Long Non-coding RNAs to Predict the Prognosis for Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Shenglan Huang ◽  
Jian Zhang ◽  
Dan Li ◽  
Xiaolan Lai ◽  
Lingling Zhuang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Clinicopathological Parameters ◽  
Kaplan Meier ◽  
The Impact

Abstract Introduction: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with poor prognosis. Tumor microenvironment (TME) plays a vital role in the tumor progression of HCC. Thus, we aimed to analyze the association of TME with HCC prognosis, and construct an TME-related lncRNAs signature for predicting the prognosis of HCC patients.Methods: We firstly assessed the stromal/immune /Estimate scores within the HCC microenvironment using the ESTIMATE algorithm based on TCGA database, and its associations with survival and clinicopathological parameters were also analyzed. Then, different expression lncRNAs were filtered out according to immune/stromal scores. Cox regression was performed to built an TME-related lncRNAs risk signature. Kaplan–Meier analysis was carried out to explored the prognostic values of the risk signature. Furthermore, we explored the biological functions and immune microenvironment feathers in high- and low risk groups. Lastly, we probed the association of the risk signature with the treatment responses to immune checkpoint inhibitors (ICIs) in HCC by comparing the immunophenoscore (IPS).Results: Stromal/immune /Estimate scores of HCC patients were obtained based on the ESTIMATE algorithm. The Kaplan-Meier curve analysis showed the high stromal/immune/ Estimate scores were significantly associated with better prognosis of the HCC patients. Then, six TME-related lncRNAs were screened for constructing the prognosis model. Kaplan-Meier survival curves suggested that HCC patients in high-risk group had worse prognosis than those with low-risk. ROC curve and Cox regression analyses demonstrated the signature could predict HCC survival exactly and independently. Function enrichment analysis revealed that some tumor- and immune-related pathways associated with HCC tumorigenesis and progression might be activated in high-risk group. We also discovered that some immune cells, which were beneficial to enhance immune responses towards cancer, were remarkably upregulated in low-risk group. Besides, there was closely correlation of immune checkmate inhibitors (ICIs) with the risk signature and the signature can be used to predict treatment response of ICIs.Conclusions: We analyzed the impact of the tumor microenvironment scores on the prognosis of patients with HCC. A novel TME-related prognostic risk signature was established, which may improve prognostic predictive accuracy and guide individualized immunotherapy for HCC patients.

scholarly journals Identification of Novel Tumor Microenvironment-Related Long Noncoding RNAs to Determine the Prognosis and Response to Immunotherapy of Hepatocellular Carcinoma Patients

2021 ◽  
Vol 8 ◽  
Author(s):  
Shenglan Huang ◽  
Jian Zhang ◽  
Xiaolan Lai ◽  
Lingling Zhuang ◽  
Jianbing Wu
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Risk Model ◽  
Cox Regression ◽  
Risk Group ◽  
Low Risk ◽  
Kaplan Meier ◽  
Treatment Responses

Introduction: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with poor prognosis. The tumor microenvironment (TME) plays a vital role in HCC progression. Thus, this research was designed to analyze the correlation between the TME and the prognosis of HCC patients and to construct a TME-related long noncoding RNA (lncRNA) signature to determine HCC patients’ prognosis and response to immunotherapy.Methods: We assessed the stromal–immune–estimate scores within the HCC microenvironment using the ESTIMATE (Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data) algorithm based on The Cancer Genome Atlas database, and their associations with survival and clinicopathological parameters were also analyzed. Thereafter, differentially expressed lncRNAs were filtered out according to the immune and stromal scores. Cox regression analysis was performed to build a TME-related lncRNA risk signature. Kaplan–Meier analysis was used to explore the prognostic value of the risk signature. Furthermore, we explored the biological functions and immune microenvironment features in the high- and low-risk groups. Lastly, we probed the association of the risk model with treatment responses to immune checkpoint inhibitors (ICIs) in HCC.Results: The stromal, immune, and estimate scores were obtained utilizing the ESTIMATE algorithm for patients with HCC. Kaplan–Meier analysis showed that high scores were significantly correlated with better prognosis in HCC patients. Six TME-related lncRNAs were screened to construct the prognostic model. The Kaplan–Meier curves suggested that HCC patients with low risk had better prognosis than those with high risk. Receiver operating characteristic (ROC) curve and Cox regression analyses indicated that the risk model could predict HCC survival exactly and independently. Functional enrichment analysis revealed that some tumor- and immune-related pathways were activated in the high-risk group. We also revealed that some immune cells, which were important in enhancing immune responses toward cancer, were significantly increased in the low-risk group. In addition, there was a close correlation between ICIs and the risk signature, which can be used to predict the treatment responses of HCC patients.Conclusion: We analyzed the influence of the stromal, immune, and estimate scores on the prognosis of HCC patients. A novel TME-related lncRNA risk model was established, which could be effectively applied as an independent prognostic biomarker and predictor of ICIs for HCC patients.

scholarly journals Eg5 Overexpression Is Predictive of Poor Prognosis in Hepatocellular Carcinoma Patients

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Can Liu ◽  
Nan Zhou ◽  
Jieying Li ◽  
Jun Kong ◽  
Xi Guan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cirrhosis ◽  
Protein Expression ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Tnm Stage ◽  
Tissue Samples ◽  
Cycle Arrest ◽  
Kaplan Meier

Eg5 (kinesin spindle protein) plays an essential role in mitosis. Inhibition of Eg5 function results in cell cycle arrest at mitosis, which leads to cell death. To date, Eg5 expression and its prognostic significance have not been studied in hepatocellular carcinoma (HCC). In this study, 26 freshly frozen HCC tissue samples and matched peritumoral tissue samples were evaluated with a one-step qPCR test and immunohistochemical (IHC) analysis was conducted on 156 HCC samples to investigate the relationships among Eg5 expression, clinicopathological factors, and prognosis. Eg5 mRNA and protein expression levels were significantly higher in HCC tissues relative to matched noncancerous tissues (p<0.05). High Eg5 protein expression was significantly related to liver cirrhosis (p=0.038) and TNM stage (p=0.008). Kaplan-Meier survival and Cox regression analyses revealed that Eg5 overexpression (p=0.001), liver cirrhosis (p=0.009), and TNM stage (p=0.025) were independent prognostic factors for overall survival. These findings indicate that Eg5 expression can be used as a biomarker of poor prognosis and as a novel therapeutic target for HCC.

scholarly journals CELSR3 mRNA expression is increased in hepatocellular carcinoma and indicates poor prognosis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7816 ◽  
Author(s):  
Xuefeng Gu ◽  
Hongbo Li ◽  
Ling Sha ◽  
Yuan Mao ◽  
Chuanbing Shi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mrna Expression ◽  
Cell Line ◽  
Roc Curve ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Dna Recombination ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier

Objective Hepatocellular carcinoma (HCC) is a disease that is associated with high mortality; currently, there is no curative and reliable treatment. Cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) is the key signaling molecule in the wingless and INT-1/planar cell polarity (WNT/PCP) pathway. This study aimed to elucidate the prognostic significance of CELSR3 in HCC patients. Methods The Cancer Genome Atlas (TCGA) database, the Cancer Cell Line Encyclopedia (CCLE) database and the Gene Expression Omnibus (GEO) database were used to analyze the expression of CELSR3 mRNA in HCC samples and cells. The relationship between CELSR3 mRNA and clinical features was assessed by the chi-square test. the diagnostic and predictive value of CELSR3 mRNA expression were analyzed using the receiver operating characteristic (ROC) curve. Kaplan–Meier curve and Cox regression analyses were performed to assess the prognostic value of CELSR3 mRNA in HCC patients. Finally, all three cohorts database was used for gene set enrichment analysis(GSEA) and the identification of CELSR3-related signal transduction pathways. Results The expression of CELSR3 mRNA was upregulated in HCC, and its expression was correlated with age (P = 0.025), tumor status (P = 0.022), clinical stage (P = 0.003), T classification (P = 0.010), vital status (P = 0.001), and relapse (P = 0.005). The ROC curve assessment indicated that CELSR3 mRNA expression has high diagnostic value in HCC and in the subgroup analysis of stage. In addition, the Kaplan-Meier curve and Cox analyses suggested that patients with high CELSR3 mRNA expression have a poor prognosis, indicating that CELSR3 mRNA is an independent prognostic factor for the overall survival of HCC patients. GSEA showed that GO somatic diversification of immune receptors, GO endonuclease activity, GO DNA repair complex and GO somatic cell DNA recombination, were differentially enriched in the meta-GEO cohort, the HCC cell line cohort and the TCGA cohort of the high CELSR3 mRNA expression phenotype. Conclusion Our results indicate that CELSR3 mRNA is involved in the progression of cancer and can be used as a biomarker for the prognosis of HCC patients.

scholarly journals GNAO1 as a Novel Predictive Biomarker for Late Relapse in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Meiling Du ◽  
Jie Feng ◽  
Yiran Tao ◽  
Qincong Pan ◽  
Fengyuan Chen
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Predictive Biomarker ◽  
High Expression ◽  
Late Relapse ◽  
Kaplan Meier ◽  
Good Ability ◽  
Relapse Prediction ◽  
Kaplan Meier Plotter

GNAO1, the alpha O1 subunit of G protein, was reported to be significantly downregulated in hepatocellular carcinoma (HCC), as well as being implicated in a variety of intracellular biological events; findings suggest that it may act as a tumor suppressor. Our goal was to further explore the expression of GNAO1 in HCC patients and its potential clinical significance. Oncomine and Kaplan–Meier plotter databases were used to assess the mRNA expression of GNAO1 in HCC tissues and patient survival time. Subsequently, immunohistochemistry (IHC) was used to measure GNAO1 protein level in tissue from 79 cases of HCC and paired adjacent tissues. The Kaplan–Meier survival analysis, Cox regression model, and prognostic nomogram were used to evaluate the prognostic role of GNAO1 in HCC. Results demonstrated that mRNA and protein expressions of GNAO1 were both lower in HCC tissues than in adjacent tissues (all p < 0.01 ). HCC patients with high expression of GNAO1 had better relapse-free survival (RFS) than those with low GNAO1 expression (all p < 0.05 ). A high expression of GNAO1, meanwhile, functioned as a good predictor of late relapse for HCC ( p < 0.05 ). The nomogram consisting of GNAO1 expression and the tumor-node-metastasis (TNM) model presented good ability in predicting the 3-year relapse for HCC (C-index = 0.614). In conclusion, GNAO1 was a reliable biomarker of relapse prediction for HCC.

scholarly journals Mining prognostic markers of Asian hepatocellular carcinoma patients based on the apoptosis-related genes

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Junbin Yan ◽  
Jielu Cao ◽  
Zhiyun Chen
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Risk Score ◽  
Roc Curve ◽  
Prognostic Model ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Cox Analysis ◽  
Kaplan Meier Plotter

Abstract Background Apoptosis-related genes(Args)play an essential role in the occurrence and progression of hepatocellular carcinoma(HCC). However, few studies have focused on the prognostic significance of Args in HCC. In the study, we aim to explore an efficient prognostic model of Asian HCC patients based on the Args. Methods We downloaded mRNA expression profiles and corresponding clinical data of Asian HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The Args were collected from Deathbase, a database related to cell death, combined with the research results of GeneCards、National Center for Biotechnology Information (NCBI) databases and a lot of literature. We used Wilcoxon-test and univariate Cox analysis to screen the differential expressed genes (DEGs) and the prognostic related genes (PRGs) of HCC. The intersection genes of DEGs and PGGs were seen as crucial Args of HCC. The prognostic model of Asian HCC patients was constructed by least absolute shrinkage and selection operator (lasso)- proportional hazards model (Cox) regression analysis. Kaplan-Meier curve, Principal Component Analysis (PCA) analysis, t-distributed Stochastic Neighbor Embedding (t-SNE) analysis, risk score curve, receiver operating characteristic (ROC) curve, and the HCC data of ICGC database and the data of Asian HCC patients of Kaplan-Meier plotter database were used to verify the model. Results A total of 20 of 56 Args were differentially expressed between HCC and adjacent normal tissues (p < 0.05). Univariate Cox regression analysis showed that 10 of 56 Args were associated with survival time and survival status of HCC patients (p < 0.05). There are seven overlapping genes of these 20 and 10 genes, including BAK1, BAX, BNIP3, CRADD, CSE1L, FAS, and SH3GLB1. Through Lasso-Cox analysis, an HCC prognostic model composed of BAK1, BNIP3, CSE1L, and FAS was constructed. Kaplan-Meier curve, PCA, t-SNE analysis, risk score curve, ROC curve, and secondary verification of ICGC database and Kaplan-Meier plotter database all support the reliability of the model. Conclusions Lasso-Cox regression analysis identified a 4-gene prognostic model, which integrates clinical and gene expression and has a good effect. The expression of Args is related to the prognosis of HCC patients, but the specific mechanism remains to be further verified.

scholarly journals Expression and clinical significance of miR-3615 in hepatocellular carcinoma

2021 ◽  
Vol 49 (1) ◽  
pp. 030006052098154
Author(s):  
Xin Yuan ◽  
Yize Zhang ◽  
Zujiang Yu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Curve ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
Prognostic Information ◽  
Ki 67 ◽  
Tissue Samples ◽  
Expression Levels ◽  
Kaplan Meier ◽  
Serum Alpha Fetoprotein

Objective To investigate the association between microRNA-3615 (miR-3615) expression and the prognosis and clinicopathological features in patients with hepatocellular carcinoma (HCC). Methods We obtained clinicopathological and genomic data and prognostic information on HCC patients from The Cancer Genome Atlas (TCGA) database. We then analyzed differences in miR-3615 expression levels between HCC and adjacent tissues using SPSS software, and examined the relationships between miR-3615 expression levels and clinicopathological characteristics. We also explored the influence of miR-3615 expression levels on the prognosis of HCC patients using Kaplan–Meier survival curve analysis. Results Based on data for 345 HCC and 50 adjacent normal tissue samples, expression levels of miR-3615 were significantly higher in HCC tissues compared with adjacent tissues. MiR-3615 expression levels in HCC patients were negatively correlated with overall survival time and positively correlated with high TNM stage, serum Ki-67 expression level, and serum alpha-fetoprotein level. There were no significant correlations between miR-3615 expression and age, sex, and pathological grade. Conclusion MiR-3615 may be a promising new biomarker and prognostic factor for HCC.

Baseline apparent diffusion coefficients: Validation study of new predictor of survival in patients with unresectable hepatocellular carcinoma following chemoembolization

2021 ◽  
pp. 1-10
Author(s):  
Lichao Xu ◽  
Shiqin Wang ◽  
Shengping Wang ◽  
Ying Wang ◽  
Wentao Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Response To Treatment ◽  
Roc Curve Analysis ◽  
Adc Value ◽  
Apparent Diffusion Coefficients ◽  
Apparent Diffusion ◽  
Response Biomarker ◽  
The Difference

OBJECTIVES: To investigate whether the baseline apparent diffusion coefficient (ADC) can predict survival in the hepatocellular carcinoma (HCC) patients receiving chemoembolization. MATERIALS AND METHODS: Diffusion-weighted MR imaging of HCC patients is performed within 2 weeks before chemoembolization. The ADC of the largest index lesion is recorded. Responses are assessed by mRECIST after the start of the second course of chemoembolization. Receiver operating characteristic (ROC) curve analysis is performed to evaluate the diagnostic performance and determine optimal cut-off values. Cox regression and Kaplan–Meier survival analyses are used to explore the differences in overall survival (OS) between the responders and non-responders. RESULTS: The difference is statistically significant in the baseline ADC between the responders and non-responders (P <  0.001). ROC analyses indicate that the baseline ADC value is a good predictor of response to treatment with an area under the ROC curve (AUC) of 0.744 and the optimal cut-off value of 1.22×10–3 mm2/s. The Cox regression model shows that the baseline ADC is an independent predictor of OS, with a 57.2% reduction in risk. CONCLUSION: An optimal baseline ADC value is a functional imaging response biomarker that has higher discriminatory power to predict tumor response and prolonged survival following chemoembolization in HCC patients.

scholarly journals NDRG3 overexpression is associated with a poor prognosis in patients with hepatocellular carcinoma

2018 ◽  
Vol 38 (6) ◽  
Author(s):  
Ji-sheng Jing ◽  
Hongbo Li ◽  
Shun-cai Wang ◽  
Jiu-ming Ma ◽  
La-qing Yu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Survival Curve ◽  
Disease Free Survival ◽  
Prognostic Indicator ◽  
Clinicopathological Characteristics ◽  
Pcr Analysis ◽  
Kaplan Meier ◽  
Tumor Tissues ◽  
The Relationship

N-myc downstream-regulated gene 3 (NDRG3), an important member of the NDRG family, is involved in cell proliferation, differentiation, and other biological processes. The present study analyzed NDRG3 expression in hepatocellular carcinoma (HCC) and explored the relationship between expression of NDRG3 in HCC patients and their clinicopathological characteristics. We performed quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry (IHC) analyses on HCC tissues to elucidate NDRG3 expression characteristics in HCC patients. Kaplan–Meier survival curve and Cox regression analyses were used to evaluate the prognoses of 102 patients with HCC. The results revealed that compared with non-tumor tissues, HCC tissues showed significantly higher NDRG3 expression. In addition, our analyses showed that NDRG3 expression was statistically associated with tumor size (P=0.048) and pathological grade (P=0.001). Survival analysis and Kaplan–Meier curves revealed that NDRG3 expression is an independent prognostic indicator for disease-free survival (P=0.002) and overall survival (P=0.005) in HCC patients. The data indicate that NDRG3 expression may be considered as a oncogenic biomarker and a novel predictor for HCC prognosis.

scholarly journals Glucose-6-Phosphate Dehydrogenase is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma

2022 ◽  
Author(s):  
Yang Bu ◽  
Kejun Liu ◽  
Yiming Niu ◽  
Ji Hao ◽  
Lei Cui ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Liver Cancer ◽  
Immune Cell ◽  
Cox Regression ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Potential Biomarker ◽  
Glucose 6 Phosphate Dehydrogenase

Abstract Background: Glucose-6-phosphate dehydrogenase (G6PD) plays an important role in the metabolic and immunological aspects of tumors. In hepatocellular carcinoma (HCC), the alteration of tumor microenvironment influences recurrence and metastasis. We extracted G6PD-related data from public databases of HCC tissues and used a bioinformatics approach to explore the correlation between G6PD expression and clinicopathological features and prognosis of immune cell infiltration in HCC.Methods: We extract G6PD expression information from TCGA and GEO databases in liver cancer tissues and normal tissues, validated by immunohistochemistry, and the correlation between G6PD expression and clinical features is analyzed, and the clinical significance of G6PD in liver cancer is assessed by Kaplan-Meier, Cox regression and prognostic line graph models. Functional enrichment analysis is performed by protein-protein interaction (PPI) network, GO/KEGG, GSEA and G6PD-associated differentially expressed genes (DEGs). TIMER and ssGSEA packages are used to assess the correlation between expression and the level of immune cell infiltration.Results: Our results show that G6PD expression is significantly upregulated in hepatocellular carcinoma tissues (P < 0.001). G6PD expression is associated with histological grade, pathological stage, T-stage, vascular infiltration and AFP level (P < 0.05); HCC patients in the low G6PD expression group had longer overall survival and better prognosis compared with the high G6PD expression group (P < 0.05). The level of G6PD expression also affects the levels of macrophages, unactivated dendritic cells, B cells, and follicular helper T cells in the tumor microenvironment.Conclusion: High expression of G6PD is a potential biomarker for poor prognosis of hepatocellular carcinoma, and G6PD may be a target for immunotherapy of HCC.

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