scholarly journals Identification and Validation of an 6-Metabolism-Related Gene Signature and Its Correlation With Immune Checkpoint in Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
He Ren ◽  
Wanjing Li ◽  
Xin Liu ◽  
Shuliang Li ◽  
Hao Guo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Clinicopathological Characteristics ◽  
Gene Set Enrichment Analysis ◽  
Operating Characteristics ◽  
Kaplan Meier ◽  
Characteristics Analysis

Hepatocellular carcinoma (HCC) is a common malignant tumor with relatively high malignancy and rapid disease progression. Metabolism-related genes (MRGs) are involved in the pathogenesis of HCC. This study explored potential key MRGs and their effect on T-cell immune function in the tumor immune microenvironment to provide new insight for the treatment of HCC. Of 456 differentially expressed MRGs identified from TCGA database, 21 were screened by MCODE and cytoHubba algorithms. From the key module, GAD1, SPP1, WFS1, GOT2, EHHADH, and APOA1 were selected for validation. The six MRGs were closely correlated with survival outcomes and clinicopathological characteristics in HCC. Receiver operating characteristics analysis and Kaplan-Meier plots showed that these genes had good prognostic value for HCC. Gene set enrichment analysis of the six MRGs indicated that they were associated with HCC development. TIMER and GEPIA databases revealed that WFS1 was significantly positively correlated and EHHADH was negatively correlated with tumor immune cell infiltration and immune checkpoint expression. Finally, quantificational real-time polymerase chain reaction (qRT-PCR) confirmed the expression of WFS1 and EHHADH mRNA in our own patients’ cohort samples and four HCC cell lines. Collectively, the present study identified six potential MRG biomarkers associated with the prognosis and tumor immune infiltration of HCC, thus providing new insight into the pathogenesis and treatment of HCC.

scholarly journals Comprehensive Analysis of the Expression, Prognosis and Immune Infiltration of KPNA Family in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Xiangyi Chen ◽  
Dechen Yu ◽  
Hai-Yu Zhou ◽  
XiaoBo Zhang ◽  
Yicun Hu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Tumor Grade ◽  
Mapk Signaling ◽  
Clinicopathological Characteristics ◽  
Expression Level ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Patient Prognosis

Abstract Background: The primary function of the Karyophorin alpha family (KPNAs) is to assist the transport of proteins from the cytoplasm to the nucleus. Studies have found that KPNAs are involved in the occurrence and development of a variety of tumors. However, the expression level of KPNAs family members in HCC, its influence on prognosis, its relationship with immune infiltration, and its clinical significance are still unclear.Methods: We used UALCAN, GEPIA, HPA, TIMER, Kaplan-Meier Plotter, CBioPortal, String and Metascape databases to analyze the expression and mutation of KPNAs in Hepatocellular carcinoma (HCC), the expression level of KPNAs and the prognosis of patients, tumor immune cell infiltration, HCC clinicopathological characteristics Relationship. Finally, the biological functions of KPNAs related genes are analyzed. Results: The protein and mRNA of KPNAs were significantly up-regulated in HCC, and their expression levels were closely related to the prognosis of patients and the clinical characteristics of the tumor (tumor grade, stage, etc.). In addition, KPNAs in HCC are prone to mutations, which are not conducive to the prognosis of patients. Moreover, the expression of HCC is positively correlated with the infiltration of immune cells. Enrichment analysis found that KPNAs-related genes are mainly related to biological processes such as nuclear and cytoplasmic signaling, protein chromosome localization, and their pathways mainly include cell cycle and MAPK signaling pathways. Conclusion: KPNAs are significantly related to the occurrence, development and patient prognosis of HCC and may become the target of HCC immunotherapy in the future.

scholarly journals Comprehensive Analysis of ESRRA in Endometrial Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382199208
Author(s):  
Shufang Wang ◽  
Xinlong Huo
Keyword(s):  
Endometrial Cancer ◽  
Protein Expression ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Operating Characteristics ◽  
Protein Expression Level ◽  
Normal Tissues

Background: Estrogen-related receptor alpha (ESRRA) was reported to play an important role in multiple biological processes of neoplastic diseases. The roles of ESRRA in endometrial cancer have not been fully investigated yet. Methods: Expression data and clinicopathological data of patients with uteri corpus endometrial carcinoma (UCEC) were obtained from The Cancer Genome Atlas (TCGA). Comprehensive bioinformatics analysis was performed, including receiver operating characteristics (ROC) curve analysis, Kaplan-Meier survival analysis, gene ontology (GO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA). Immunohistochemistry was used to detect the protein expression level of ESRRA and CCK-8 assay was performed to evaluate the effect of ESRRA on the proliferation ability. Results: A total of 552 UCEC tissues and 35 normal tissues were obtained from the TCGA database. The mRNA and protein expression level of ESRRA was highly elevated in UCEC compared with normal tissues, and was closely associated with poor prognosis. ROC analysis indicated a very high diagnostic value of ESRRA for patients with UCEC. GO and GSEA functional analysis showed that ESRRA might be mainly involved in cellular metabolism processes, in turn, tumorigenesis and progression of UCEC. Knockdown of ESRRA inhibited the proliferation of UCEC cells in vitro. Further immune cell infiltration demonstrated that ESRRA enhanced the infiltration level of neutrophil cell and reduced that of T cell (CD4+ naïve), NK cell, and cancer associated fibroblast (CAF). The alteration of immune microenvironment will greatly help in developing immune checkpoint therapy for UCEC. Conclusions: Our study comprehensively analyzed the expression level, clinical value, and possible mechanisms of action of ESRRA in UCEC. These findings showed that ESRRA might be a potential diagnostic and therapeutic target.

scholarly journals Cyclin B1 acts as a tumor microenvironment-related cancer promoter and prognostic biomarker in hepatocellular carcinoma

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110162
Author(s):  
Yangming Hou ◽  
Xin Wang ◽  
Junwei Wang ◽  
Xuemei Sun ◽  
Xinbo Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Proportional Hazards ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Cyclin B1 ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
Tumor Promoter ◽  
Protein Protein Interaction

Objectives The present study aimed to develop a gene signature based on the ESTIMATE algorithm in hepatocellular carcinoma (HCC) and explore possible cancer promoters. Methods The ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cells (TICs) in a cohort of HCC patients. The differentially expressed genes (DEGs) were screened by Cox proportional hazards regression analysis and protein–protein interaction (PPI) network construction. Cyclin B1 (CCNB1) function was verified using experiments. Results The stromal and immune scores were associated with clinicopathological factors and recurrence-free survival (RFS) in HCC patients. In total, 546 DEGs were up-regulated in low score groups, 127 of which were associated with RFS. CCNB1 was regarded as the most predictive factor closely related to prognosis of HCC and could be a cancer promoter. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analyses indicated that CCNB1 levels influenced HCC tumor microenvironment (TME) immune activity. Conclusions The ESTIMATE signature can be used as a prognosis tool in HCC. CCNB1 is a tumor promoter and contributes to TME status conversion.

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 an immune long non-coding RNA signature in liver hepatocellular carcinoma

2019 ◽  
Author(s):  
rui kong ◽  
Nan Wang ◽  
Wei Han ◽  
Yuejuan Zheng ◽  
Jie Lu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Liver Hepatocellular Carcinoma ◽  
Long Non Coding Rna

Abstract Background: In recent years, long non-coding RNAs (lncRNAs) are emerging as crucial regulators in the immunological process of liver hepatocellular carcinoma (LIHC). Increasing studies have found that some lncRNAs could be used as a diagnostic or therapeutic target for clinical management, but little research has investigated the role of immune-related lncRNA in tumor prognosis. In this study, we aimed to develop an immune lncRNA signature for the precise diagnosis and prognosis of liver hepatocellular carcinoma. Methods: Gene expression profiles of LIHC samples obtained from TCGA were screened for immune-related genes using two reference gene sets. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate cox analysis. Then the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were carried out to evaluate the capability of immune lncRNA signature as a prognostic indicator. Results: Six long non-coding RNA MSC−AS1, AC009005.1, AL117336.3, AL031985.3, AL365203.2, AC099850.3 were identified via correlation analysis and cox regression analysis considering their interactions with immune genes. Next, tumor samples were separated into two risk groups by the signature with different clinical outcomes. Stratification analysis showed the prognostic ability of this signature acted as an independent factor. The AUC value of ROC curve was 0.779. The Kaplan-Meier method was used in survival analysis and results showed a statistical difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Data from gene set enrichment analysis (GSEA) further unveiled several potential biological processes of these biomarkers may involve in. Conclusion: In summary, the study demonstrated the potential role of the six-lncRNA signature served as an independent prognostic factor for LIHC patients.

scholarly journals Decreased DHRS1 expression is a novel predictor of poor survival in patients with hepatocellular carcinoma

2021 ◽  
Vol 15 (15) ◽  
pp. 1319-1331
Author(s):  
Li Li ◽  
Hui-Jing Situ ◽  
Wen-Cheng Ma ◽  
Xuan Liu ◽  
Lu-Lu Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Aberrant Expression ◽  
Normal Tissues ◽  
Multiple Data ◽  
Kaplan Meier ◽  
Survival Gene ◽  
Mrna And Protein Expression

Aim: To investigate the effect of aberrant expression of DHRS1 on hepatocellular carcinoma (HCC). Materials & methods: Kaplan–Meier and Cox regression analyses were performed to evaluate the correlation between DHRS1 and overall survival. Gene set enrichment analysis was performed to explore the potential function of DHRS1 in HCC. Results: Multiple data analysis revealed that DHRS1 mRNA and protein expression level were remarkably lower in HCC than that in normal tissues. In survival analysis, patients with low DHRS1 expression presented a poorer prognosis, and was an independent risk factor for HCC. Conclusion: Decreased DHRS1 expression may be a potential predictor of poor prognosis in 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 ARID1A Is a Prognostic Biomarker and Associated with Immune Infiltrates in Hepatocellular Carcinoma

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Yuanyuan Feng ◽  
Xinfang Tang ◽  
Changcheng Li ◽  
Ying Su ◽  
Xiaoyu Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Migration And Invasion ◽  
Risk Indicator ◽  
Immune Cell Infiltration

Objective. ARID1A has been discovered as a potential cancer biomarker. But its role in hepatocellular carcinoma (HCC) is subject to considerable dispute. Methods. The relationship between ARID1A and clinical factors was investigated. Clinicopathological variables related to overall survival in HCC subjects were identified using Cox and Kaplan–Meier studies. The connection between immune infiltrating cells and ARID1A expression was investigated using the tumor Genome Atlas (TCGA) dataset for gene set enrichment analysis (GSEA). Finally, a cell experiment was used to confirm it. Results. The gender and cancer topography (T) categorization of HCC were linked to increased ARID1A expression. Participants with advanced levels of ARID1A expression had a worse prognosis than someone with lower levels. ARID1A was shown to be a risk indicator of overall survival on its own. ARID1A expression is inversely proportional to immune cell infiltration. In vitro, decreasing ARID1A expression substantially slowed the cell cycle and decreased HCC cell proliferation, migration, and invasion. Conclusion. The expression of ARID1A could be used to predict the outcome of HCC. It is closely related to tumor immune cell infiltration.

scholarly journals Identification of Potential Hub Genes Related to Diagnosis and Prognosis of Hepatitis B Virus-Related Hepatocellular Carcinoma via Integrated Bioinformatics Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Yuqin Tang ◽  
Yongqiang Zhang ◽  
Xun Hu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Diagnosis And Prognosis ◽  
Prognostic Analysis ◽  
B Virus

Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA–mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

scholarly journals Integrated Bioinformatics Analysis Identifies Heat Shock Factor 2 as a Prognostic Biomarker Associated With Immune Cell Infiltration in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yumei Fan ◽  
Jiajie Hou ◽  
Xiaopeng Liu ◽  
Bihui Han ◽  
Yanxiu Meng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Heat Shock ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Critical Role ◽  
Enrichment Analysis ◽  
Normal Liver ◽  
Heat Shock Factor ◽  
Gene Set Enrichment Analysis

Hepatocellular carcinoma (HCC) is one of the most common malignancies and ranks as the second leading cause of cancer-related mortality worldwide. Heat shock factor 2 (HSF2) is a transcription factor that plays a critical role in development, particularly corticogenesis and spermatogenesis. However, studies examining the expression and prognostic value of HSF2 and its association with tumor-infiltrating immune cells in HCC are still rare. In the present study, we found that HSF2 expression was significantly upregulated in HCC tissues compared with normal liver tissues using the TCGA, ICGC, GEO, UALCAN, HCCDB and HPA databases. High HSF2 expression was associated with shorter survival of patients with HCC. Cox regression analyses and nomogram were used to evaluate the association of HSF2 expression with the prognosis of patients with HCC. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and gene set enrichment analysis (GSEA) revealed that HSF2 was associated with various signaling pathways, including the immune response. Notably, HSF2 expression was significantly correlated with the infiltration levels of different immune cells using the TIMER database and CIBERSORT algorithm. HSF2 expression also displayed a significant correlation with multiple immune marker sets in HCC tissues. Knockdown of HSF2 significantly inhibited the proliferation, migration, invasion and colony formation ability of HCC cells. In summary, we explored the clinical significance of HSF2 and provided a therapeutic basis for the early diagnosis, prognostic judgment, and immunotherapy of HCC.

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