scholarly journals Upregulated expression of MTFR2 as a novel biomarker predicts poor prognosis in hepatocellular carcinoma by bioinformatics analysis

2021 ◽  
Author(s):  
Dan Li ◽  
YanMei Ji ◽  
JiaLong Guo ◽  
Qiang Guo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Independent Predictor ◽  
Cancer Stage ◽  
Clinical Role ◽  
P53 Signaling ◽  
Dismal Prognosis ◽  
P53 Signaling Pathway

Aim: The authors investigated the clinical role of MTFR2 in hepatocellular carcinoma (HCC) progression. Results: MTFR2 expression and methylation were abnormal in HCC tissues, and HCC patients with increased MTFR2 expression or methylation had poor or better overall survival, respectively. In addition, increased MTFR2 expression was correlated with age, grade, cancer stage and T stage. MTFR2 was an independent predictor of dismal prognosis in HCC patients. MTFR2 was involved in HCC progression by modulating the cell cycle, homologous recombination, DNA replication, p53 signaling pathway, etc. The ten hub genes were overexpressed in HCC tissues and were linked to cancer stage and dismal prognosis in HCC patients. Conclusion: MTFR2 could be a prospective biomarker of poor prognosis in individuals with HCC.

scholarly journals Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Shui Liu ◽  
Xiaoxiao Yao ◽  
Dan Zhang ◽  
Jiyao Sheng ◽  
Xin Wen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Signaling Pathway ◽  
Gene Network ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Mrna Levels ◽  
Qrt Pcr ◽  
P53 Signaling ◽  
Tf Gene ◽  
P53 Signaling Pathway

Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR were performed. We found 237 differentially expressed genes (DEGs) including EGR1, FOS, and FOSB, which were three cancer-related transcription factors. Subsequently, we constructed TF-gene network and miRNA-TF-mRNA network based on data obtained from mRNA and miRNA expression profiles for analysis of HCC. We found that 42 key genes from the TF-gene network including EGR1, FOS, and FOSB were most enriched in the p53 signaling pathway. The qRT-PCR data confirmed that mRNA levels of EGR1, FOS, and FOSB all were decreased in HCC tissues. In addition, we confirmed that the mRNA levels of CCNB1, CCNB2, and CHEK1, three key markers of the p53 signaling pathway, were all increased in HCC tissues by bioinformatics analysis and qRT-PCR validation. Therefore, we speculated that miR-181a-5p, which was upregulated in HCC tissues, could regulate FOS and EGR1 to promote the invasion and progression of HCC by p53 signaling pathway. Overall, the study provides support for the possible mechanisms of progression in HCC.

scholarly journals Role of the Mitochondrial Citrate-malate Shuttle in Hras12V-Induced Hepatocarcinogenesis: A Metabolomics-Based Analysis

Metabolites ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 193
Author(s):  
Chuanyi Lei ◽  
Jun Chen ◽  
Huiling Li ◽  
Tingting Fan ◽  
Xu Zheng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Bioinformatics Analysis ◽  
Lipid Biosynthesis ◽  
Pentose Phosphate ◽  
Glutathione Metabolism ◽  
Ras Signaling ◽  
Significant Finding ◽  
Ras Oncogene

The activation of the Ras signaling pathway is a crucial process in hepatocarcinogenesis. Till now, no reports have scrutinized the role of dynamic metabolic changes in Ras oncogene-induced transition of the normal and precancerous liver cells to hepatocellular carcinoma in vivo. In the current study, we attempted a comprehensive investigation of Hras12V transgenic mice (Ras-Tg) by concatenating nontargeted metabolomics, transcriptomics analysis, and targeted-metabolomics incorporating [U-13C] glucose. A total of 631 peaks were detected, out of which 555 metabolites were screened. Besides, a total of 122 differently expressed metabolites (DEMs) were identified, and they were categorized and subtyped with the help of variation tendency analysis of the normal (W), precancerous (P), and hepatocellular carcinoma (T) liver tissues. Thus, the positive or negative association between metabolites and the hepatocellular carcinoma and Ras oncogene were identified. The bioinformatics analysis elucidated the hepatocarcinogenesis-associated significant metabolic pathways: glycolysis, mitochondrial citrate-malate shuttle, lipid biosynthesis, pentose phosphate pathway (PPP), cholesterol and bile acid biosynthesis, and glutathione metabolism. The key metabolites and enzymes identified in this analysis were further validated. Moreover, we confirmed the PPP, glycolysis, and conversion of pyruvate to cytosol acetyl-CoA by mitochondrial citrate-malate shuttle, in vivo, by incorporating [U-13C] glucose. In summary, the current study presented the comprehensive bioinformatics analysis, depicting the Ras oncogene-induced dynamic metabolite variations in hepatocarcinogenesis. A significant finding of our study was that the mitochondrial citrate-malate shuttle plays a crucial role in detoxification of lactic acid, maintenance of mitochondrial integrity, and enhancement of lipid biosynthesis, which, in turn, promotes hepatocarcinogenesis.

scholarly journals Paired box gene 5is a novel tumor suppressor in hepatocellular carcinoma through interaction with p53 signaling pathway

Hepatology ◽  
2011 ◽  
Vol 53 (3) ◽  
pp. 843-853 ◽  
Author(s):  
Weili Liu ◽  
Xiaoxing Li ◽  
Eagle S.H. Chu ◽  
Minnie Y.Y. Go ◽  
Lixia Xu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Suppressor ◽  
Signaling Pathway ◽  
P53 Signaling ◽  
P53 Signaling Pathway

Clinical role of MMP-2/TIMP-2 imbalance in hepatocellular carcinoma

2002 ◽  
Vol 97 (4) ◽  
pp. 425-431 ◽  
Author(s):  
Gianluigi Giannelli ◽  
Carlo Bergamini ◽  
Felice Marinosci ◽  
Emilia Fransvea ◽  
Michele Quaranta ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Clinical Role

scholarly journals Increased IGFBP7 Expression Correlates with Poor Prognosis and Immune Infiltration in Gastric Cancer: An Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Qiaoyun Zhao ◽  
Rulin Zhao ◽  
Conghua Song ◽  
Huan Wang ◽  
Jianfang Rong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Biological Processes ◽  
Coexpressed Genes

Abstract Background Insulin-like growth factor binding protein-7 (IGFBP7) contributes to multiple biological processes in various tumors. However, the role of IGFBP7 in gastric cancer (GC) is still undetermined. The study aims to explore the role of IGFBP7 in GC via an integrated bioinformatics analysis.Methods IGFBP7 expression levels in GC and its normal gastric tissues were analyzed using multiple databases, including the Tumor Immune Estimation Resource (TIMER), Oncomine, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The methylation analysis was conducted with MEXPRESS, UALCAN and Xena online tools. The survival analysis was conducted using the Kaplan-Meier Plotter and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Coexpressed genes of IGFBP7 were selected with the cBioPortal tool and enrichment analysis was conducted with the clusterProfiler package in R software. Gene set enrichment analysis (GSEA) was performed to explore the IGFBP7-related biological processes involved in GC. Correlations between IGFBP7 and immune cell infiltrates were analyzed using the TIMER database.Results IGFBP7 expression was significantly upregulated in GC and correlated with stage, grade, tumor status and Helicobacter pylori infection. High IGFBP7 expression and low IGFBP7 methylation levels were significantly associated with short survival of patients with GC. Univariate and multivariate analyses revealed that IGFBP7 was an independent risk factor for GC. The coexpressed genes LHFPL6, SEPTIN4, HSPB2, LAYN and GGT5 predicted unfavorable outcomes of GC. Enrichment analysis showed that the coexpressed genes were involved in extracellular matrix (ECM)-related processes. GSEA indicated that IGFBP7 was positively related to ECM and inflammation-related pathways. TIMER analysis indicated that the IGFBP7 expression level was strongly correlated with genes related to various infiltrating immune cells in GC, especially with gene markers of tumor associated macrophages (TAMs).Conclusions We demonstrate that increased IGFBP7 expression correlates with poor prognosis and immune cell infiltration in GC. IGFBP7 might be a potential biomarker for the diagnosis and targeted therapy for GC.

scholarly journals Bioinformatics Analysis and Insights for The Role of COMMD7 in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Xuehui Peng ◽  
Yonggang He ◽  
Xiaobing Huang ◽  
Nan You ◽  
Huiying Gu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Bioinformatics Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Research Progress ◽  
Kaplan Meier ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Kaplan Meier Plotter

Abstract Background: The tumorigenesis and development of hepatocellular carcinoma (HCC) is a process involving multiple factors. The COMMDs family proteins were reported to play important roles in various disease and cancers including HCC. We previously found COMMD7 acted as a HCC-promotion factor; however, further understanding on COMMD7 was needed. We conducted these bioinformatics analysis for the purpose of comprehensive understanding of the functional role of COMMD7 in HCC.Methods: The bioinformatics analysis of COMMD7 were launched by online platforms including KEGG, GEPIA, cBioportal, Gene Ontology and The Kaplan-Meier plotter. Data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were downloaded, and the data analysis and processing were conducted by RStudio (version 1.3.959) software.Results: The expression profile results of COMMD7 in TCGA and GTEx database suggested that COMMD7 expressed highly in liver tumor tissues and positively related with poorer prognosis (p<0.01); COMMD7 also contributed to the early development of HCC as its higher expression resulted in progression from stage I to stage III (p<0.01). Based on our previous studies, COMMD7 may target NF-κB signaling and CXCL10 to enhance the proliferation of hepatoma cells so that promoting the development of HCC. Conclusions：This study updates the current studies about the newly recognized roles of COMMD7 in the progression of HCC, summarizing the research progress and prospects of COMMD7 comprehensively, offering an outlook for the future investigation and targeted therapy of HCC.

scholarly journals Transcriptome analysis revealed key prognostic genes and microRNAs in hepatocellular carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8930 ◽  
Author(s):  
Xi Ma ◽  
Lin Zhou ◽  
Shusen Zheng
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Survival Analysis ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Pathway Enrichment Analysis ◽  
Cox Regression Analysis ◽  
Key Genes ◽  
Overall Survival Analysis

Background Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. However, the molecular mechanisms involved in HCC remain unclear and are in urgent need of elucidation. Therefore, we sought to identify biomarkers in the prognosis of HCC through an integrated bioinformatics analysis. Methods Messenger RNA (mRNA) expression profiles were obtained from the Gene Expression Omnibus database and The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) for the screening of common differentially expressed genes (DEGs). Function and pathway enrichment analysis, protein-protein interaction network construction and key gene identification were performed. The significance of key genes in HCC was validated by overall survival analysis and immunohistochemistry. Meanwhile, based on TCGA data, prognostic microRNAs (miRNAs) were decoded using univariable and multivariable Cox regression analysis, and their target genes were predicted by miRWalk. Results Eleven hub genes (upregulated ASPM, AURKA, CCNB2, CDC20, PRC1 and TOP2A and downregulated AOX1, CAT, CYP2E1, CYP3A4 and HP) with the most interactions were considered as potential biomarkers in HCC and confirmed by overall survival analysis. Moreover, AURKA, PRC1, TOP2A, AOX1, CYP2E1, and CYP3A4 were considered candidate liver-biopsy markers for high risk of developing HCC and poor prognosis in HCC. Upregulation of hsa-mir-1269b, hsa-mir-518d, hsa-mir-548aq, hsa-mir-548f-1, and hsa-mir-6728, and downregulation of hsa-mir-139 and hsa-mir-4800 were determined to be risk factors of poor prognosis, and most of these miRNAs have strong potential to help regulate the expression of key genes. Conclusions This study undertook the first large-scale integrated bioinformatics analysis of the data from Illumina BeadArray platforms and the TCGA database. With a comprehensive analysis of transcriptional alterations, including mRNAs and miRNAs, in HCC, our study presented candidate biomarkers for the surveillance and prognosis of the disease, and also identified novel therapeutic targets at the molecular and pathway levels.

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