scholarly journals High SGO2 Expression Predicts Poor Overall Survival: A Potential Therapeutic Target for Hepatocellular Carcinoma

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 876
Author(s):  
Min Deng ◽  
Shaohua Li ◽  
Jie Mei ◽  
Wenping Lin ◽  
Jingwen Zou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Therapeutic Target ◽  
Tumor Grade ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Clinicopathological Parameters ◽  
Potential Therapeutic Target ◽  
Poor Overall Survival

Shugoshin2 (SGO2) may participate in the occurrence and development of tumors by regulating abnormal cell cycle division, but its prognostic value in hepatocellular carcinoma (HCC) remains unclear. In this study, we accessed The Cancer Genome Atlas (TCGA) database to get the clinical data and gene expression profile of HCC. The expression of SGO2 in HCC tissues and nontumor tissues and the relationship between SGO2 expression, survival, and clinicopathological parameters were analyzed. The SGO2 expression level was significantly higher in HCC tissues than in nontumor tissues (p < 0.001). An analysis from the Oncomine and Gene Expression Profiling Interactive Analysis 2 (GEPIA2) databases also demonstrated that SGO2 was upregulated in HCC (all p < 0.001). A logistic regression analysis revealed that the high expression of SGO2 was significantly correlated with gender, tumor grade, pathological stage, T classification, and Eastern Cancer Oncology Group (ECOG) score (all p < 0.05). The overall survival (OS) of HCC patients with higher SGO2 expression was significantly poor (p < 0.001). A multivariate analysis showed that age and high expression of SGO2 were independent predictors of poor overall survival (all p < 0.05). Twelve signaling pathways were significantly enriched in samples with the high-SGO2 expression phenotype. Ten proteins and 34 genes were significantly correlated with SGO2. In conclusion, the expression of SGO2 is closely related to the survival of HCC. It may be used as a potential therapeutic target and prognostic marker of HCC.

scholarly journals Identifies Oncogene PDRG1 as a Potential Prognostic Biomarker in Hepatocellular Carcinoma: A Study Based on Bioinformatics Analysis

2021 ◽  
Author(s):  
Jianyang Lin ◽  
Xin Ding ◽  
Zhihong Chen ◽  
Huiwen Pan ◽  
Yinyan Wu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Survival Rates ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Th2 Cells ◽  
Poor Overall Survival ◽  
Bioinformatics Analyses ◽  
Malignant Liver Tumor ◽  
Ppi Networks

Abstract Background: Hepatocellular carcinoma (HCC) is globally recognized as one of the most frequently occurring primary malignant liver tumor, making the identification of HCC biomarkers critically important. Methods: The gene expression and clinicopathology analysis, GO enrichment analysis (GSEA) and immune infiltration analysis are based on data obtained from The Cancer Genome Atlas (TCGA), with additional bioinformatics analyses performed. The statistical analysis was conducted in R. The protein-protein interaction (PPI) networks was constructed and the module analysis was performed using STRING and Cytoscape. Construction and evaluation of prognostic model based on PDRG1 and tumor status used nomogram and calibration.Results: The expression of PDRG1 was significantly higher in HCC tumor tissues. High expression of PDRG1 in HCC patients was significantly correlated with poor Overall Survival and adverse clinicopathological features including advanced T stage, residual tumor, histologic grade, vascular invasion, TP53 status and AFP level. GO, GSEA revealed that PDRG1 was closely correlated with DNA repair, DNA replication and cell cycle. Spearman correlation showed high expression of PDRG1 was significantly correlated with Th2 cells level in HCC patients. Nomograms based on PDRG1 and tumor stage had good predictive performance on overall survival rates of HCC patients.Conclusions: Our study demonstrated the potential significance of PDRG1 expression in the diagnosis and prognosis of HCC and further explored the function in HCC. Further study is still needed to confirm these results. The underlying mechanism revealed by these results provides a basis for PDRG1 as a new molecular target for the prevention and treatment of HCC.

scholarly journals Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Xiaofei Wang ◽  
Jie Qiao ◽  
Rongqi Wang
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Risk Score ◽  
Expression Profiles ◽  
Univariate Analysis ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Good Prediction ◽  
Expression Levels

Abstract The present study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.

scholarly journals Novel prognostic genes and subclasses of acute myeloid leukemia revealed by survival analysis of gene expression data

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yanli Lai ◽  
Guifang OuYang ◽  
Lixia Sheng ◽  
Yanli Zhang ◽  
Binbin Lai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Network Analysis ◽  
Risk Score ◽  
Myeloid Leukemia ◽  
The Cancer Genome Atlas ◽  
Prognostic Biomarkers ◽  
High Expression ◽  
Acute Myeloid

Abstract Background Acute myeloid leukemia (AML) is biologically heterogeneous diseases with adverse prognosis. This study was conducted to find prognostic biomarkers that could effectively classify AML patients and provide guidance for treatment decision making. Methods Weighted gene co-expression network analysis was applied to detect co-expression modules and analyze their relationship with clinicopathologic characteristics using RNA sequencing data from The Cancer Genome Atlas database. The associations of gene expression with patients’ mortality were investigated by a variety of statistical methods and validated in an independent dataset of 405 AML patients. A risk score formula was created based on a linear combination of five gene expression levels. Results The weighted gene co-expression network analysis detected 63 co-expression modules. The pink and darkred modules were negatively significantly correlated with overall survival of AML patients. High expression of FNDC3B, VSTM1 and CALR was associated with favourable overall survival, while high expression of PLA2G4A was associated with adverse overall survival. Hierarchical clustering analysis of FNDC3B, VSTM1, PLA2G4A, GOLGA3 and CALR uncovered four subgroups of AML patients. The cluster1 AML patients showed younger age, lower cytogenetics risk, higher frequency of NPM1 mutations and more favourable overall survival than cluster3 patients. The risk score was demonstrated to be an indicator of adverse prognosis in AML patients Conclusions The FNDC3B, VSTM1, PLA2G4A, GOLGA3, CALR and risk score may serve as key prognostic biomarkers for the stratification and ultimately guide rational treatment of AML patients.

scholarly journals CDKN3 expression predicates poor prognosis and regulates adriamycin sensitivity in hepatocellular carcinoma in vitro

2020 ◽  
Vol 48 (7) ◽  
pp. 030006052093687
Author(s):  
Wei Dai ◽  
Shuo Fang ◽  
Guanhe Cai ◽  
Jialiang Dai ◽  
Guotai Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Prognostic Factor ◽  
Therapeutic Target ◽  
Bioinformatics Analysis ◽  
Kinase Inhibitor ◽  
Disease Free Survival ◽  
The Cancer Genome Atlas ◽  
The Relationship

Objective Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related deaths worldwide. This study investigated the relationship between cyclin-dependent kinase inhibitor (CDKN)3 and prognosis and pathological characteristics in HCC patients to determine whether it could be used as a prognostic factor and/or therapeutic target for HCC drug development. Methods We previously showed that CDKN3 is deregulated in HCC tumor samples. Here, bioinformatics analysis was used to assess the relationship between CDKN3 gene expression and the characteristics of HCC patients from Gene Expression Omnibus and The Cancer Genome Atlas databases. Additionally, CDKN3 expression was silenced by small interfering RNA to determine its effect on HCC cell proliferation and on HCC cell sensitivity to adriamycin chemotherapy. Results Bioinformatics analysis showed a negative correlation between CDKN3 expression and both disease-free survival and overall survival. CDKN3 silencing did not significantly suppress the proliferation of HCC cells, but did decrease their sensitivity to adriamycin. Conclusions CDKN3 may have a dual role during the development of HCC, and could be used as an independent prognostic factor and therapeutic target for HCC treatment.

scholarly journals Prognostic roles of the transcriptional expression of exportins in hepatocellular carcinoma

2019 ◽  
Vol 39 (8) ◽  
Author(s):  
Lubiao Chen ◽  
Yanlin Huang ◽  
Liang Zhou ◽  
Yifan Lian ◽  
Jialiang Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Data ◽  
Disease Free Survival ◽  
Dna Amplification ◽  
Genetic Alterations ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
High Expression ◽  
Poor Overall Survival ◽  
Cancer Tissues

Abstract Aims: A large number of studies have suggested that exportins (XPOs) play a pivotal role in human cancers. In the present study, we analyzed XPO mRNA expression in cancer tissues and explored their prognostic value in hepatocellular carcinoma (HCC). Methods: Transcriptional and survival data related to XPO expression in HCC patients were obtained through the ONCOMINE and UALCAN databases. Survival analysis plots were drawn with Gene Expression Profiling Interactive Analysis (GEPIA). Sequence alteration data for XPOs were obtained from The Cancer Genome Atlas (TCGA) database and c-BioPortal. Gene functional enrichment analyses were performed with Database for Annotation, Visualization and Integrated Discovery (DAVID). Results: Compared with normal liver tissues, significant XPO mRNA overexpression was observed in HCC cancer tissues. There was a trend of higher XPO expression in more advanced clinical stages and lower differentiated pathological grades of HCC. In HCC patients, high expression of XPO1, CSE1L, XPOT, XPO4/5/6 was related to poor overall survival (OS), and XPO1, CSE1L and XPO5/6 were correlated with poor disease-free survival (DFS). The main genetic alterations in XPOs involved mRNA up-regulation, DNA amplification and deletion. General XPO mutations were remarkably associated with worse OS and mostly affected the pathways of RNA transport and oocyte meiosis. Conclusion: High expression of XPOs was associated with a poor prognosis in HCC patients. XPOs may be exploited as good prognostic biomarkers for survival in HCC patients.

scholarly journals Upregulated LINC01667 Expression Is Correlated With Poor Prognosis in Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Kainan Zhang ◽  
Hui Liu ◽  
Mengsi Yu ◽  
Hui Zhao ◽  
Ning Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Cancer Progression ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion ◽  
Poor Overall Survival ◽  
Expression Levels ◽  
Huh7 Cells ◽  
Gene Expression Levels

The development of hepatocellular carcinoma (HCC) is a complex pathological process. Long intergenic non–protein-coding RNA 1667 (LINC01667, also known as MGC38584) plays an oncogenic role in several human cancers; however, its functional role in HCC tumorigenesis remains unknown. Here, we first evaluated the gene expression levels of LINC01667 in HCC using data from The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis (GEPIA) databases. We then elucidated the association between LINC01667 gene expression levels and the survival rates of patients with HCC. We detected the effect of LINC01667 on the malignant phenotypes (cell proliferation, migration, invasion and apoptosis etc.) and the MAPK and PI3K/AKT/mTOR signaling pathways of HepG2, SMMC-7721 and HUH7 cells. We also analyzed the sensitivity of HepG2, SMMC-7721 and HUH7 with different expression levels of LINC01667 to anti-HCC drugs in vitro. Based on data from the aforementioned databases and our experiments in vitro, we found that LINC01667 was overexpressed in HCC, and that patients with high LINC01667 levels had a remarkably poor overall survival rate. In addition, inhibition of LINC01667 expression suppressed the proliferation, migration and invasion of HepG2 and SMMC-7721 cells and promoted their apoptosis in vitro. In contrast, overexpression of LINC01667 promoted the proliferation, migration and invasion of HUH7 cells and suppressed their apoptosis in vitro. ChIRP-seq (chromatin isolation by RNA purification) showed that LINC01667 bound to MEG3, and downregulated the expression of MEG3. In addition, western blotting showed that LINC01667 could activate the NF-κB pathway to promote cancer progression. In conclusion, we report that LINC01667 is an important oncogene in HCC and may be used as a potential diagnostic and prognostic biomarker of HCC.

scholarly journals Low APOA-1 Expression in Hepatocellular Carcinoma Patients Is Associated With DNA Methylation and Poor Overall Survival

2021 ◽  
Vol 12 ◽  
Author(s):  
Yingyun Guo ◽  
Binglu Huang ◽  
Ruixue Li ◽  
Jiao Li ◽  
Shan Tian ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Dna Methylation ◽  
Overall Survival ◽  
Survival Data ◽  
The Cancer Genome Atlas ◽  
High Density Lipoproteins ◽  
Healthy Individuals ◽  
Poor Overall Survival ◽  
Strong Negative Correlation ◽  
Free Survival

Background: Hepatocellular carcinoma (HCC) is the most frequent fatal malignancy, and it has a poor prognosis. Apolipoprotein 1 (APOA-1), the main protein component of high-density lipoproteins, is involved in numerous biological processes. Thus, this study was performed to detect the clinical significance of APOA-1 mRNA, APOA-1 expression, and APOA-1DNA methylation in patients with HCC.Methods: Data mining was performed using clinical and survival data from the Cancer Genome Atlas (TCGA) and Oncomine databases. The serum concentration of APOA-1 was measured in 316 patients with HCC and 100 healthy individuals at Renmin Hospital of Wuhan University, and the intact clinical information was reviewed and determined using univariate and multivariate Cox hazard models.Results: Bioinformatic analysis revealed that APOA-1 mRNA was present at lower levels in the serum of patients with HCC than in that of healthy individuals, and there was a strong negative correlation between levels of APOA-1 mRNA and APOA-1 DNA methylation. High expression of APOA-1 transcription correlated with better overall survival (p = 0.003), and APOA-1 hypermethylation correlated with progress-free survival (p = 0.045) in HCC sufferers. Next, the clinical data analysis demonstrated that APOA-1 protein levels in the serum were significantly lower in patients with HCC than in healthy controls. Furthermore, the expression of APOA-1 was significantly associated with some significant clinical indexes, and elevated APOA-1 expression was significantly associated with favorable (OS; HR:1.693, 95% CI: 1.194–2.401, p = 0.003) and better progression-free survival (PFS; HR = 1.33, 95% CI = 1.194–2.401, p = 0.045). Finally, enrichment analysis suggested that co-expressed genes of APOA-1 were involved in lipoprotein metabolism and FOXA2/3 transcription factor networks.Conclusion: APOA-1 mRNA expression is negatively regulated by DNA methylation in HCC. Low expression of APOA-1 might be a potential risk biomarker to predict survival in patients with HCC.

scholarly journals Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Junwei Liu ◽  
Fang Han ◽  
Jianyi Ding ◽  
Xiaodong Liang ◽  
Jie Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
Functional Study ◽  
Ppi Network ◽  
Hub Genes ◽  
Qrt Pcr

Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system, and its early asymptomatic characteristic increases the difficulty of diagnosis and treatment. This study is aimed at obtaining some novel biomarkers with diagnostic and prognostic meaning and may find out potential therapeutic targets for HCC. We screen differentially expressed genes (DEGs) from the HCC gene expression profile GSE14520 using GEO2R. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted by using the clusterProfiler software while a protein-protein interaction (PPI) network was performed based on the STRING database. Then, prognosis analysis of hub genes was conducted using The Cancer Genome Atlas (TCGA) database. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to further verify the expression of hub genes and explore the correlation between gene expression and clinicopathological parameters. A total of 1053 DEGs were captured, containing 497 upregulated genes and 556 downregulated genes. GO and KEGG analysis indicated that the downregulated DEGs were mainly enriched in the fatty acid catabolic process while upregulated DEGs were primarily enriched in the cell cycle. Simultaneously, ten hub genes (CYP3A4, UGT1A6, AOX1, UGT1A4, UGT2B15, CDK1, CCNB1, MAD2L1, CCNB2, and CDC20) were identified by the PPI network. Five prognosis-related hub genes (CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20) were uncovered by the survival analysis based on TCGA database. The ten hub genes were further validated by qRT-PCR using samples obtained from our hospital. The prognosis-related hub genes such as CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20 could be considered potential diagnosis biomarkers and prognosis targets for HCC. We also use Oncomine for further verification, and we found CCNB1, CCNB2, CDK1, and CYP3A4 which were highly expressed in HCC. Meanwhile, CCNB1, CCNB2, and CDK1 are highly expressed in almost all cancer types, which may play an important role in cancer. Still, further functional study should be conducted to explore the underlying mechanism and biological effect in the near future.

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