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 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 Up-regulated Expression and Related Gene Regulatory Networks of ANLN Predict Poor Prognosis and Correlate with Immune Infiltration in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Bo Hu ◽  
Xiao-Bo Yang ◽  
Xinting Sang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Immune Infiltration ◽  
Dismal Prognosis ◽  
Mrna Binding

Abstract Background: The aberrant Anillin (ANLN) expression is reported to be associated with carcinogenesis. In this study, sequencing data collected from the Cancer Genome Atlas database were utilized to analyze ANLN expression in hepatocellular carcinoma (HCC).Methods: The relationships of clinicopathological features with ANLN were investigated, and gene set enrichment analysis (GSEA) was performed to reveal the ANLN-related functions. LinkedOmics was employed to identify the co-expressed genes of ANLN and to examine the target networks of kinases, microRNAs (miRNAs) and transcription factors (TFs). Besides, the correlation of ANLN expression with cancer immune infiltrates was analyzed by TIMER. Results: ANLN over-expression predicted dismal prognosis, and GESA results revealed several functions that were related to cell cycle and mRNA binding. Moreover, functional network analysis indicated that, ANLN might regulate DNA replication and cell cycle signaling through pathways that involved several cancer-related kinases, miRNAs and E2F1. Additionally, ANLN was suggested to be associated with the infiltration of several immune cells, which was proved to be upregulated in both HCC cells and tissues. Conclusion: Those efficiently mined data reveal information regarding ANLN expression, the potential regulatory networks and the relationship with immune infiltration in HCC, which lay a foundation for further study on the role of ANLN in carcinogenesis.

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 CSIG-03. RECONCILING TUMOR HETEROGENEITY IN GLIOBLASTOMA USING A PATHWAY-BASED APPROACH

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii28-ii28
Author(s):  
Alvaro Alvarado ◽  
Kaleab Tessema ◽  
Kunal Patel ◽  
Riki Kawaguchi ◽  
Richard Everson ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Patient Survival ◽  
Molecular Subtype ◽  
Gene List ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Molecular Architecture ◽  
Survival Pathways ◽  
Cancer Genome Atlas

Abstract Despite efforts to gain a deeper understanding of its molecular architecture, glioblastoma (GBM) remains uniformly fatal. While genome-based molecular subtyping has revealed that GBMs may be parsed into several molecularly distinct categories, this insight has yielded little progress towards extending patient survival. In particular, the great phenotypic heterogeneity of GBM – both inter and intratumorally – has hindered therapeutic efforts. To this end, we interrogated tumor samples using a pathway-based approach to resolve tumoral heterogeneity. Gene set enrichment analysis (GSEA) was applied to gene expression data and used to provide an overview of each sample that can be compared to other samples by generating sample clusters based on overall patterns of enrichment. The Cancer Genome Atlas (TCGA) samples were clustered using the canonical and oncogenic signatures and in both cases the clustering was distinct from the molecular subtype previously reported and clusters were informative of patient survival. We also analyzed single cell RNA sequencing datasets and uniformly found two clusters of cells enriched for cell cycle regulation and survival pathways. We have validated our approach by generating gene lists from common elements found in the top contributing genesets for a particular cluster and testing the top targets in appropriate gliomasphere patient-derived lines. Samples enriched for cell cycle related genesets showed a decrease in sphere formation capacity when E2F1, out top target, was silenced and when treated with fulvestrant and calcitriol, which were identified as potential drugs targeting this genelist. Conversely, no changes were observed in samples not enriched for this gene list. Finally, we interrogated spatial heterogeneity and found higher enrichment of the proliferative signature in contrast enhancing compared with non-enhancing regions. Our studies relate inter- and intratumoral heterogeneity to critical cellular pathways dysregulated in GBM, with the ultimate goal of establishing a pipeline for patient- and tumor-specific precision medicine.

scholarly journals Integrative and Comprehensive Pancancer Analysis of Regulator of Chromatin Condensation 1 (RCC1)

2021 ◽  
Vol 22 (14) ◽  
pp. 7374
Author(s):  
Changwu Wu ◽  
Yingjuan Duan ◽  
Siming Gong ◽  
Sonja Kallendrusch ◽  
Nikolas Schopow ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Chromatin Condensation ◽  
Treatment Strategies ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Malignant Neoplasms ◽  
Nucleotide Exchange ◽  
Genome Database

Regulator of Chromatin Condensation 1 (RCC1) is the only known guanine nucleotide exchange factor that acts on the Ras-like G protein Ran and plays a key role in cell cycle regulation. Although there is growing evidence to support the relationship between RCC1 and cancer, detailed pancancer analyses have not yet been performed. In this genome database study, based on The Cancer Genome Atlas, Genotype-Tissue Expression and Gene Expression Omnibus databases, the potential role of RCC1 in 33 tumors’ entities was explored. The results show that RCC1 is highly expressed in most human malignant neoplasms in contrast to healthy tissues. RCC1 expression is closely related to the prognosis of a broad variety of tumor patients. Enrichment analysis showed that some tumor-related pathways such as “cell cycle” and “RNA transport” were involved in the functional mechanism of RCC1. In particular, the conducted analysis reveals the relation of RCC1 to multiple immune checkpoint genes and suggests that the regulation of RCC1 is closely related to tumor infiltration of cancer-associated fibroblasts and CD8+ T cells. Coherent data demonstrate the association of RCC1 with the tumor mutation burden and microsatellite instability in various tumors. These findings provide new insights into the role of RCC1 in oncogenesis and tumor immunology in various tumors and indicate its potential as marker for therapy prognosis and targeted treatment strategies.

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 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 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 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 Pan-cancer analysis of the oncogenic role of discs large homolog associated protein 5 (DLGAP5) in human tumors

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Neng Tang ◽  
Xiaolin Dou ◽  
Xing You ◽  
Qiman Shi ◽  
Mujing Ke ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Carcinoma ◽  
Cell Lines ◽  
Cellular Proliferation ◽  
Germ Cell Tumors ◽  
Enrichment Analysis ◽  
Human Tumors ◽  
Testicular Germ Cell ◽  
Pan Cancer

Abstract Background In recent years, there have been many studies on the relationship between DLGAP5 and different types of cancers, yet there is no pan-cancer analysis of DLGAP5. Therefore, this study aims to analyze the roles of DLGAP5 in human tumors. Methods Firstly, we evaluated the expression level of DLGAP5 in 33 types of tumors throughout the datasets of TCGA (Cancer Genome Atlas) and GEO (Gene Expression Synthesis). Secondly, we used the GEPIA2 and Kaplan-Meier plotter to conduct Survival prognosis analysis. Additionally, cBioPortal web was utilized to analyze the genetic alteration of DLGAP5, after which we selected hepatocellular carcinoma (HCC) cell lines to define the function of DLGAP5. Last but not least, we performed immune infiltration analysis and DLGAP5-related gene enrichment analysis. Results DLGAP5 is highly expressed in most type of cancers, and there is a significant correlation between the expression of DLGAP5 and the prognosis of cancer patients. We have observed that DLGAP5 promotes the proliferation and invasion of hepatocellular carcinoma (HCC) cell lines. We also found that DLGAP5 expression was related with the CD8+ T-cell infiltration status in kidney renal clear cell carcinoma, uveal melanoma, and thymoma, and cancer-associated fibroblast infiltration was observed in breast invasive carcinoma, kidney renal papillary cell carcinoma and testicular germ cell tumors. In addition, enrichment analysis revealed that cell cycle- and oocyte meiosis-associated functions were involved in the functional mechanism of DLGAP5. Conclusions Taken together, our unpresented pan-cancer analysis of DLGAP5 provides a relatively integrative understanding of the oncogenic role of DLGAP5 in various tumors. DLGAP5 may prompt HCC cellular proliferation, invasion and metastasis. All of these provides solid basement and will promote more advanced understanding the role of DLGAP5 in tumorigenesis and development from the perspective of clinical tumor samples and cells.

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