scholarly journals Upregulation of PTGFRN in Hepatocellular Carcinoma Predicts Poor Prognosis: A Study Based on the TCGA Database

2021 ◽  
Author(s):  
Yanlin Tan ◽  
Fan Wu ◽  
Wenzhen Lin ◽  
Yuqin Wei ◽  
Yitong Lin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Enrichment Analysis ◽  
Cox Proportional Hazards Model ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Rank Test ◽  
Expression Data ◽  
Clinical Prognosis ◽  
Mesenchymal Transition

Abstract Background. The importance of prostaglandin F2 receptor inhibitors (PTGFRN) in the progression of a variety of malignant tumors has been recognized in recent years. So far, no role of PTGFRN in hepatocellular carcinoma (HCC) has been reported. In this study, we focused on the possible mechanisms of PTGFRN in HCC based on the Cancer Genome Atlas (TCGA) data. Methods. The mRNA gene expression data of PTGFRN were downloaded from TCGA database to analyze the expression level of PTGFRN in HCC. According to the human protein atlas database, the expression difference of PTGFRN protein between HCC and adjacent tissues was verified. Wilcoxon signed-rank test and logistic regression were used to analyze the relationship between PTGFRN and clinicopathological characteristics. Kaplan Meier method and Cox proportional hazards model were used to explore the prognostic role of PTGFRN in HCC. The ROC curve was used to evaluate the diagnostic value of PTGFRN in HCC. Gene Set Enrichment Analysis (GSEA) was used to investigate the function of PTGFRN related Gene sets. Finally, obtain the co-expressed genes of PTGFRN through the cBioPortal database, and use the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) function enrichment analysis to further explore the role of PTGFRN in HCC regulated related pathways.Results. Analysis of mRNA expression data of 377 HCC patients showed that the expression of PTGFRN was up-regulated in HCC, which was confirmed by immunohistochemistry. The overexpression of PTGFRN was significantly correlated with clinical stage (P = 0.028) and histological grade (P = 0.027). High expression of PTGFRN was associated with poorer overall survival.. Meanwhile, multivariate Cox analysis showed that PTGFRN may be a potential independent risk factor for HCC. GSEA enrichment results showed that the up-regulated PTGFRN phenotype was concentrated in "endocytosis", "oocyte meiosis" and "ERBB signaling pathway". In addition, through the analysis of KEGG and GO pathways, we found that PTGFRN co-expressed genes are mainly involved in extracellular matrix tissue, epithelial-mesenchymal transition, cell adhesion and cell cycle, and PI3K-Akt/NF-kB signaling pathways.Conclusions. PTGFRN is highly expressed in HCC and can be used as an independent predictor of the clinical prognosis of HCC.

scholarly journals Novel Biomarker NEDD1 and Its Analysis in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Xiaopeng Ding ◽  
Jiahao Yu ◽  
Xin Shi ◽  
Kangwei Li ◽  
Shuoyi Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
External Validation ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Related Data ◽  
Significant Difference

Abstract Background: NEDD1 (NEDD1 Gamma-Tubulin Ring Complex Targeting Factor) plays a crucial impact in regulating cell cycle and the development of scirrhous gastric cancer. However, the role of NEDD1 hasn’t been reported in hepatocellular carcinoma (HCC) so far. The aim of this research is to explore the role of NEDD1 on the development and prognosis of HCC. Methods: HCC-related data were download from The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene set enrichment analysis (GSEA) were conducted by the LinkedOmics database. Results: The expression of NEDD1 has significant difference between tumor and adjacent normal tissues in HCC (P＜0.01). We also found that NEDD1 was an independent risk factor in HCC patients (HR 1.643, 95%CI 1.125–2.398; P = 0.01). The study also demonstrated that NEDD1 expression was significantly relevant to the expression of several immune checkpoint genes, including CTLA-4, PD-L1 and PD-1. GSEA revealed that Cell cycle, MicroRNAs in cancer and Ribosome pathways were significantly enriched in NEDD1 overexpression phenotype. By integrating NEDD1 with other relevant factors, we constructed the prognostic nomogram to help the improvement of the prognosis for patients with HCC. The data from the International Cancer Genome Consortium (ICGC) database were used as an independent external validation of our prognostic model. Conclusion: The expression level of NEDD1 was negatively correlated to the prognosis of HCC patients and it may be a promising therapeutic target of HCC, which probably be able to predict the efficacy of immunotherapy for HCC patients.

scholarly journals Gene signatures and prognostic values of m1A-related regulatory genes in hepatocellular carcinoma

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Qingmiao Shi ◽  
Chen Xue ◽  
Xin Yuan ◽  
Yuting He ◽  
Zujiang Yu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Regulatory Genes ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Clinical Prognosis ◽  
Cox Regression Analysis ◽  
Genes Expression

Abstract Hepatocellular carcinoma (HCC) ranks fourth in cancer-related mortality worldwide. N1-methyladenosine (m1A), a methylation modification on RNA, is gaining attention for its role across diverse biological processes. However, m1A-related regulatory genes expression, its relationship with clinical prognosis, and its role in HCC remain unclear. In this study, we utilized The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) database to investigate alterations within 10 m1A-related regulatory genes and observed a high mutation frequency (23/363). Cox regression analysis and least absolute shrinkage and selection operator were used to explore the association between m1A-related regulatory genes expression and HCC patient survival and identified four regulators that were remarkably associated with HCC patient prognosis. Additionally, an independent cohort from International Cancer Genome Consortium was studied to validate our discoveries and found to be consistent with those in the TCGA dataset. In terms of mechanism, gene set enrichment analysis linked these four genes with various physiological roles in cell division, the MYC pathway, protein metabolism, and mitosis. Kyoto Encyclopedia of Genes and Genomes analysis revealed that PI3K/Akt signaling pathway had potential relevance to m1A-related regulatory genes in HCC. These findings indicate that m1A-related regulatory genes may play crucial roles in regulating HCC progression and be exploited for diagnostic and prognostic purposes.

scholarly journals HAMP Downregulation Contributes to Aggressive Hepatocellular Carcinoma via Mechanism Mediated by Cyclin4-Dependent Kinase-1/STAT3 Pathway

Diagnostics ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 48 ◽  
Author(s):  
Ying Shen ◽  
Xin Li ◽  
Yanwei Su ◽  
Shaikh Atik Badshah ◽  
Bin Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Cellular Proliferation ◽  
Flow Cytometric Analysis ◽  
Enrichment Analysis ◽  
Cell Cycle Checkpoints ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Cycle Gene

Background: Hepcidin encoded by HAMP is vital to regulating proliferation, metastasis, and migration. Hepcidin is secreted specifically by the liver. This study sought to examine the functional role of hepcidin in hepatocellular carcinoma (HCC). Methods: Data in the Cancer Genome Atlas database was used to analyze HAMP expression as it relates to HCC prognosis. We then used the 5-ethynyl-20-deoxyuridine (EdU) incorporation assay, transwell assay, and flow cytometric analysis, respectively, to assess proliferation, migration, and the cell cycle. Gene set enrichment analysis (GSEA) was used to find pathways affected by HAMP. Results: HAMP expression was lower in hepatocellular carcinoma samples compared with adjacent normal tissue controls. Low HAMP expression was linked with a higher rate of metastasis and poor disease-free status. Downregulation of HAMP induced SMMC-7721 and HepG-2 cell proliferation and promoted their migration. HAMP could affect the cell cycle pathway and Western blotting, confirming that reduced HAMP levels activated cyclin-dependent kinase-1/stat 3 pathway. Conclusion: Our findings indicate that HAMP functions as a tumor suppressor gene. The role of HAMP in cellular proliferation and metastasis is related to cell cycle checkpoints. HAMP could be considered as a diagnostic biomarker and targeted therapy in HCC.

scholarly journals Enolase 1 Correlated With Cancer Progression and Immune-Infiltrating in Multiple Cancer Types: A Pan-Cancer Analysis

2021 ◽  
Vol 10 ◽  
Author(s):  
Wenhua Xu ◽  
Wenna Yang ◽  
Chunfeng Wu ◽  
Xiaocong Ma ◽  
Haoyu Li ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Stress Protein ◽  
Enrichment Analysis ◽  
Tumor Stage ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Multiple Cancer ◽  
Clinical Prognosis ◽  
Multiple Tumor ◽  
Normal Tissues

Enolase 1 (ENO1) is an oxidative stress protein expressed in endothelial cells. This study aimed to investigate the correlation of ENO1 with prognosis, tumor stage, and levels of tumor-infiltrating immune cells in multiple cancers. ENO1 expression and its influence on tumor stage and clinical prognosis were analyzed by UCSC Xena browser, Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), and GTEx Portal. The ENO1 mutation analysis was performed by cBio Portal, and demonstrated ENO1 mutation (1.8%) did not impact on tumor prognosis. The relationship between ENO1 expression and tumor immunity was analyzed by Tumor Immune Estimation Resource (TIMER) and GEPIA. The potential functions of ENO1 in pathways were investigated by Gene Set Enrichment Analysis. ENO1 expression was significantly different in tumor and corresponding normal tissues. ENO1 expression in multiple tumor tissues correlated with prognosis and stage. ENO1 showed correlation with immune infiltrates including B cells, CD8+ and CD4+ T cells, macrophages, neutrophils, and dendritic cells, and tumor purity. ENO1 was proved to be involved in DNA replication, cell cycle, apoptosis, glycolysis process, and other processes. These findings indicate that ENO1 is a potential prognostic biomarker that correlates with cancer progression immune infiltration.

scholarly journals An angiogenesis-related long noncoding RNA signature correlates with prognosis in patients with hepatocellular carcinoma

2021 ◽  
Vol 41 (4) ◽  
Author(s):  
Dengliang Lei ◽  
Yue Chen ◽  
Yang Zhou ◽  
Gangli Hu ◽  
Fang Luo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Roc Curves ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Highly Correlated

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal cancers worldwide. Neovascularization is closely related to the malignancy of tumors. We constructed a signature of angiogenesis-related long noncoding RNA (lncRNA) to predict the prognosis of patients with HCC. The lncRNA expression matrix of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA). First, gene set enrichment analysis (GSEA) was used to distinguish the differentially expressed genes of the angiogenesis genes in liver cancer and adjacent tissues. Next, a signature of angiogenesis-related lncRNAs was constructed using univariate and multivariate analyses, and receiver operating characteristic (ROC) curves were used to assess the accuracy. The signature and relevant clinical information were used to construct the nomogram. A 5-lncRNA signature was highly correlated with overall survival (OS) in HCC patients and performed well in evaluations using the C-index, areas under the curve, and calibration curves. In summary, the 5-lncRNA model can serve as an accurate signature to predict the prognosis of patients with liver cancer, but its mechanism of action must be further elucidated by experiments.

scholarly journals Identification of a Novel Epithelial-Mesenchymal Transition Gene Signature Regulated by KEAP1-NRF2 Pathway in Esophageal Carcinoma

2020 ◽  
Author(s):  
Mohamed Elshaer ◽  
Ahmed Hammad ◽  
Xiu Jun Wang ◽  
Xiuwen Tang
Keyword(s):  
Cell Lines ◽  
Epithelial Mesenchymal Transition ◽  
Cancer Cell Line ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Mesenchymal Transition ◽  
Gene Set ◽  
Over Expression

Abstract BackgroundKEAP1-NRF2 pathway alterations were identified in many cancers including, esophageal cancer (ESCA). Identifying biomarkers that are associated with mutations in this pathway will aid in defining this cancer subset; and hence in supporting precision and personalized medicine. MethodsIn this study, 182 tumor samples from the Cancer Genome Atlas (TCGA)-ESCA RNA-Seq V2 level 3 data were segregated into two groups KEAP1-NRF2-mutated (22) and wild-type (160).The two groups were subjected to differential gene expression analysis, and we performed Gene Set Enrichment Analysis (GSEA) to determine all significantly affected biological pathways. Then, the enriched gene set was integrated with the differentially expressed genes (DEGs) to identify a gene signature regulated by the KEAP1-NRF2 pathway in ESCA. Furthermore, we validated the gene signature using mRNA expression data of ESCA cell lines provided by the Cancer Cell Line Encyclopedia (CCLE). The identified signature was tested in 3 independent ESCA datasets to assess its prognostic value.ResultsWe identified 11 epithelial-mesenchymal transition (EMT) genes regulated by the KEAP1-NRF2 pathway in ESCA patients. Five of the 11 genes showed significant over-expression in KEAP1-NRF2-mutated ESCA cell lines. In addition, the over-expression of these five genes was significantly associated with poor survival in 3 independent ESCA datasets, including the TCGA-ESCA dataset.ConclusionAltogether, we identified a novel EMT 5-gene signature regulated by the KEAP1-NRF2 axis and this signature is strongly associated with metastasis and drug resistance in ESCA. These 5-genes are potential biomarkers and therapeutic targets for ESCA patients in whom the KEAP1-NRF2 pathway is altered.

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 Identification and Validation of the N6-Methyladenosine RNA Methylation Regulator YTHDF1 as a Novel Prognostic Marker and Potential Target for Hepatocellular Carcinoma

2020 ◽  
Vol 7 ◽  
Author(s):  
Saiyan Bian ◽  
Wenkai Ni ◽  
Mengqi Zhu ◽  
Qianqian Song ◽  
Jianping Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Biological Activities ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
Cell Counting ◽  
Migration And Invasion ◽  
Mesenchymal Transition ◽  
Rna Methylation ◽  
Hcc Cells

Purpose: N6-methyladenosine (m6A) RNA methylation has been implicated in various malignancies. This study aimed to identify the m6A methylation regulator-based prognostic signature for hepatocellular carcinoma (HCC) as well as provide candidate targets for HCC treatment.Methods: The least absolute shrinkage and selection operator (LASSO) analyses were performed to identify a risk signature in The Cancer Genome Atlas (TCGA) datasets. The risk signature was further validated in International Cancer Genome Consortium (ICGC) and Pan-Cancer Analysis of Whole Genomes (PCAWG) datasets. Following transfection of short hairpin RNA (shRNA) targeting YTHDF1, the biological activities of HCC cells were evaluated by Cell Counting Kit-8 (CCK-8), wound-healing, Transwell, flow cytometry, and xenograft tumor assays, respectively. The potential mechanisms mediated by YTHDF1 were predicted by overrepresentation enrichment analysis (ORA)/gene set enrichment analysis (GSEA) and validated by Western blotting.Results: Overexpression of m6A RNA methylation regulators was correlated with malignant clinicopathological characteristics of HCC patients. The Cox regression and LASSO analyses identified a risk signature with five m6A methylation regulators (KIAA1429, ZC3H13, YTHDF1, YTHDF2, and METTL3). In accordance with HCC cases in TCGA, the prognostic value of risk signature was also determined in ICGC and PCAWG datasets. Following analyzing the expression and clinical implications in TCGA and Gene Expression Omnibus (GEO), YTHDF1 was chosen for further experimental validation. Knockdown of YTHDF1 significantly inhibited the proliferation, migration, and invasion of HCC cells, as well as enhanced the apoptosis in vitro. Moreover, silencing YTHDF1 repressed the growth of xenograft tumors in vivo. Mechanism investigation indicated that YTHDF1 might promote the aggressive phenotypes by facilitating epithelial–mesenchymal transition (EMT) and activating AKT/glycogen synthase kinase (GSK)-3β/β-catenin signaling.Conclusion: The current study identified a robust risk signature consisting of m6A RNA methylation regulators for HCC prognosis. In addition, YTHDF1 was a potential molecular target for HCC treatment.

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

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

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

scholarly journals CXCL5 Has Potential to Be a Marker for Hepatocellular Carcinoma Prognosis and Was Correlating With Immune Infiltrates

2021 ◽  
Vol 11 ◽  
Author(s):  
Yuan Nie ◽  
Mei-chun Jiang ◽  
Cong Liu ◽  
Qi Liu ◽  
Xuan Zhu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Hospital Data ◽  
Gene Set Enrichment ◽  
Local Hospital ◽  
High Expression Group ◽  
Cancer Genome Atlas

BackgroundsTumor microenvironment (TME) plays a crucial role in the initiation and progression of Hepatocellular Carcinoma (HCC), especially immune infiltrates. However, there is still a challenge in understanding the modulation of the immune and stromal components in TME, especially TME related genes.MethodsThe proportion of tumor-infiltrating immune cells (TICs) and the immune and stromal scores in 374 HCC patients from The Cancer Genome Atlas (TCGA) database were determined using CIBERSORT and ESTIMATE computational methods. The final screened genes were confirmed by the PPI network and univariate Cox regression of the differentially expressed genes based on different immune or stromal scores. The correlation between the expression levels of the final gene interactions and the clinical characteristics was based on TCGA database and local hospital data. Gene set enrichment analysis (GSEA) and the effect of CXCL5 expression on TICs were conducted.ResultsThere were correlations between the expression of CXCL5 and survival of HCC patients and TMN classification both in TCGA database and local hospital data. The immune-related activities were enriched in the high-expression group; however, the metabolic pathways were enriched in the low-expression group. The result of CIBERSORT analyzing had indicated that CXCL5 expression were correlated with the proportion of NK cells activated, macrophages M0, Mast cells resting, Neutrophils.ConclusionsCXCL5 was a potential prognostic marker for HCC and provides clues regarding immune infiltrates, which offers extra insight for therapeutics of HCC, however, more independent cohorts and functional experiments of CXCL5 are warranted.

Sign in / Sign up

Export Citation Format

Share Document