scholarly journals Prognostic Values of Stabilin-2 in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Zhicheng Du ◽  
Pengfei Zhu ◽  
Long Yu ◽  
Kunlun Chen ◽  
Janwen Ye ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Survival Time ◽  
Cox Regression ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Primary Malignancy ◽  
Diagnosis And Prognosis ◽  
Kaplan Meier ◽  
Potential Biomarker

Abstract Background: Hepatocellular carcinoma (HCC) is the primary malignancy of the liver. However, biomarkers for early HCC diagnosis are not available. Stabilin (STAB) proteins are scavenger receptors involved in apoptosis and clearance of hyaluronic acid .The role of STAB in HCC has not been previously explored; therefore, the aim of this study was to assess whether STAB gene expression can be used as a novel HCC biomarker.Materials and Methods: Data on 370 HCC patients in the Cancer Genome Atlas database and 221 patients in the Gene Expression Comprehensive Database were retrieved and analyzed. Kaplan–Meier analysis and Cox regression model were used to calculate median survival time using hazard ratio (HR) and 95% confidence interval (CI). Results: The Gene Expression Omnibus dataset showed that high Stabilin-2（STAB2） expression implies longer overall survival (HR after correction = 0.541; 95% CI, 0.339–0.865; p = 0.0182, after correction p = 0.010) and longer recurrence-free survival time (adjusted HR = 0.554; 95% CI, 0.376-0.816; p = 0.0085, adjusted p = 0.003). Conclusions: STAB2 is a potential biomarker for the diagnosis and prognosis of HCC.

scholarly journals Identification and Validation of a Novel Immune-Related Four-lncRNA Signature for Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Jixin Wang ◽  
Xiangjun Yin ◽  
Yin-Qiang Zhang ◽  
Xuming Ji
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Lasso Regression ◽  
Kaplan Meier

Lung adenocarcinoma (LUAD) is a major subtype of lung cancer, the prognosis of patients with which is associated with both lncRNAs and cancer immunity. In this study, we collected gene expression data of 585 LUAD patients from The Cancer Genome Atlas (TCGA) database and 605 subjects from the Gene Expression Omnibus (GEO) database. LUAD patients were divided into high and low immune-cell-infiltrated groups according to the single sample gene set enrichment analysis (ssGSEA) algorithm to identify differentially expressed genes (DEGs). Based on the 49 immune-related DE lncRNAs, a four-lncRNA prognostic signature was constructed by applying least absolute shrinkage and selection operator (LASSO) regression, univariate Cox regression, and stepwise multivariate Cox regression in sequence. Kaplan–Meier curve, ROC analysis, and the testing GEO datasets verified the effectiveness of the signature in predicting overall survival (OS). Univariate Cox regression and multivariate Cox regression suggested that the signature was an independent prognostic factor. The correlation analysis revealed that the infiltration immune cell subtypes were related to these lncRNAs.

scholarly journals Construction of a Pseudogene‐associated ceRNA Network and Identification of Prognostic Pseudogene Biomarkers for Colorectal Cancer

2021 ◽  
Author(s):  
Zhuoqi Li ◽  
Jing Zhou ◽  
Liankun Gu ◽  
Baozhen Zhang
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Cox Regression ◽  
Expression Profiles ◽  
Colon Adenocarcinoma ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Cerna Network ◽  
Kaplan Meier

Abstract Colorectal cancer (CRC) is one of the most common and deadly malignant carcinomas. Many long noncoding RNAs (lncRNA) have been reported to play an important role in the tumorigenesis of CRC by interacting with miRNAs and influencing the expression of some mRNAs through a competing endogenous RNA (ceRNA) network. Pseudogenes are one kind of lncRNA and can act as RNA sponges for miRNAs and regulate gene expression via ceRNA networks, but there are few studies about pseudogenes in CRC. In this study, total of 31 differentially expressed (DE) pseudogenes, 17 DE miRNAs and 152 DE mRNAs were identified by analyzing the expression profiles of colon adenocarcinoma (COAD) obtained from The Cancer Genome Atlas (TCGA). And a ceRNA network was constructed based on these RNAs. Kaplan–Meier analysis showed that 7 pseudogenes, 4 miRNAs and 30 mRNAs were significantly associated with overall survival. Then multivariate Cox regression analysis on the ceRNA-related DE pseudogenes was performed and a 5-pseudogene signature with the greatest prognostic value for CRC was identified. What’s more, the results were validated by the Gene Expression Omnibus (GEO) database, and quantitative real‐time PCR (qRT‐PCR) in 113 pairs of CRC tissues. In conclusion, this study provides a pseudogene-associated ceRNA network and 7 prognostic pseudogene biomarkers, and a 5-pseudogene prognostic risk signature that may be useful to predict the survival of CRC patients.

scholarly journals Screening the genome for HCC-specific CpG methylation signatures as biomarkers for diagnosis and prognosis evaluation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Rui-kun Zhang ◽  
Jia-lin Liu
Keyword(s):  
Cox Regression ◽  
Malignant Tumors ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Training Set ◽  
Cpg Sites ◽  
Diagnosis And Prognosis ◽  
Patient Prognosis ◽  
Prognosis Evaluation

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and invasive malignant tumors in the world. The change in DNA methylation is a key event in HCC. Methods Methylation datasets for HCC and 17 other types of cancer were downloaded from The Cancer Genome Atlas (TCGA). The CpG sites with large differences in methylation between tumor tissues and paracancerous tissues were identified. We used the HCC methylation dataset downloaded from the TCGA as the training set and removed the overlapping sites among all cancer datasets to ensure that only CpG sites specific to HCC remained. Logistic regression analysis was performed to select specific biomarkers that can be used to diagnose HCC, and two datasets—GSE157341 and GSE54503—downloaded from GEO as validation sets were used to validate our model. We also used a Cox regression model to select CpG sites related to patient prognosis. Results We identified 6 HCC-specific methylated CpG sites as biomarkers for HCC diagnosis. In the training set, the area under the receiver operating characteristic (ROC) curve (AUC) for the model containing all these sites was 0.971. The AUCs were 0.8802 and 0.9711 for the two validation sets from the GEO database. In addition, 3 other CpG sites were analyzed and used to create a risk scoring model for patient prognosis and survival prediction. Conclusions Through the analysis of HCC methylation datasets from the TCGA and Gene Expression Omnibus (GEO) databases, potential biomarkers for HCC diagnosis and prognosis evaluation were ascertained.

scholarly journals Down-Regulation of LncRNA DGCR5 Correlates with Poor Prognosis in Hepatocellular Carcinoma

2016 ◽  
Vol 40 (3-4) ◽  
pp. 707-715 ◽  
Author(s):  
Ruyi Huang ◽  
Xiaochen Wang ◽  
Wenjie Zhang ◽  
Guangyan Zhangyuan ◽  
Kangpeng Jin ◽  
...  
Keyword(s):  
Roc Curve ◽  
Cox Regression ◽  
Cancer Specific Survival ◽  
Term Survival ◽  
Diagnosis And Prognosis ◽  
Kaplan Meier ◽  
High Expression Group ◽  
Negative Prognostic Factor ◽  
Potential Biomarker ◽  
Low Expression

Background/Aims: Long non-coding RNAs (lncRNAs) have been reported to play pivotal roles in multiple tumors and can act as tumor biomarkers. In this study, we explored the association of the expression of an lncRNA, DGCR5 with clinicopathological features and prognosis in HCC. Methods: Expression levels of DGCR5 were detected by quantitative real-time PCR (qRT-PCR) and the clinical data was obtained, including basic information, data of clinicopathology and cancer specific survival rate. Receiver operating characteristic (ROC) curve, Kaplan-Meier methods and multivariable Cox regression models were used to analyze predictive efficiency, long-term survival outcomes and risk factors. Results: DGCR5 was found down-regulated in HCC tissues (P<0.001) and serum (P = 0.0035) and low expression of DGCR5 was correlated with a poor cancer specific survival (CSS) (P = 0.0019), as the overall 5-year CSS rates were 10.3% (low expression group) and 36.6% (high expression group), respectively. A stratified analysis demonstrated that low DGCR5 expression was an independent negative prognostic factor for HCC. In addition, the area under the ROC curve was 0.782 with a sensitivity of 0.633 and a specificity of 0.833. Conclusions: Our results suggest that DGCR5 may be a participator in HCC and can serve as potential biomarker for the diagnosis and prognosis in HCC.

scholarly journals High Squalene Epoxidase in Tumors Predicts Worse Survival in Patients With Hepatocellular Carcinoma: Integrated Bioinformatic Analysis on NAFLD and HCC

2020 ◽  
Vol 27 (1) ◽  
pp. 107327482091466
Author(s):  
Tingting Shen ◽  
Yunfei Lu ◽  
Qin Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Messenger Rna ◽  
Disease Free Survival ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Squalene Epoxidase ◽  
Nonalcoholic Fatty Liver ◽  
Kaplan Meier ◽  
High Level

This study aimed to identify candidate biomarkers for predicting outcomes in nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC). Using Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) databases, we identified common upregulated differential expressed genes (DEGs) in patients with NAFLD/nonalcoholic steatohepatitis (NASH) and HCC and conducted survival analysis of these upregulated DEGs with HCC outcomes. Two common upregulated DEGs including squalene epoxidase (SQLE) and EPPK1 messenger RNA (mRNA) were significantly upregulated in NAFLD, NASH, and HCC tissues, both in GSE45436 ( P < .001) and TCGA profile ( P < .001). Both SQLE and EPPK1 mRNA were upregulated in 15.56% and 8.06% patients with HCC in TCGA profile. Overexpression of SQLE in tumors was significantly associated with worse overall survival (OS) and disease-free survival (DFS) in patients with HCC (log-rank P = .027 and log-rank P = .048, respectively), while no statistical significances of OS and DFS were found in EPPK1 groups (both log-rank P > .05). For validation, SQLE upregulation contributed to significantly worse OS in patients wih HCC using Kaplan-Meier plotter analysis (hazard ratio = 1.43, 95% confidence interval: 1.01-2.02, log-rank P = .043). In addition, high level of SQLE significantly associated with advanced neoplasm histologic grade, advanced AJCC stage, and α-fetoprotein elevation ( P = .036, .045, and .029, respectively). Squalene epoxidase is associated with OS and DFS and serves as a novel prognostic biomarker for patients with HCC.

scholarly journals OSmfs: An Online Interactive Tool to Evaluate Prognostic Markers for Myxofibrosarcoma

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1523
Author(s):  
Huimin Li ◽  
Longxiang Xie ◽  
Qiang Wang ◽  
Yifang Dang ◽  
Xiaoxiao Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Poor Prognosis ◽  
Analysis Data ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Prognostic Biomarkers ◽  
Rank Test ◽  
Web Tool ◽  
Kaplan Meier ◽  
Cox Analysis

Myxofibrosarcoma is a complex genetic disease with poor prognosis. However, more effective biomarkers that forebode poor prognosis in Myxofibrosarcoma remain to be determined. Herein, utilizing gene expression profiling data and clinical follow-up data of Myxofibrosarcoma cases in three independent cohorts with a total of 128 Myxofibrosarcoma samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we constructed an easy-to-use web tool, named Online consensus Survival analysis for Myxofibrosarcoma (OSmfs) to analyze the prognostic value of certain genes. Through retrieving the database, users generate a Kaplan–Meier plot with log-rank test and hazard ratio (HR) to assess prognostic-related genes or discover novel Myxofibrosarcoma prognostic biomarkers. The effectiveness and availability of OSmfs were validated using genes in ever reports predicting the prognosis of Myxofibrosarcoma patients. Furthermore, utilizing the cox analysis data and transcriptome data establishing OSmfs, seven genes were selected and considered as more potentially prognostic biomarkers through overlapping and ROC analysis. In conclusion, OSmfs is a promising web tool to evaluate the prognostic potency and reliability of genes in Myxofibrosarcoma, which may significantly contribute to the enrichment of novelly potential prognostic biomarkers and therapeutic targets for Myxofibrosarcoma.

scholarly journals Based on Integrated Bioinformatics Analysis Identification of Biomarkers in Hepatocellular Carcinoma Patients from Different Regions

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Linxin Teng ◽  
Kaiyuan Wang ◽  
Yu Liu ◽  
Yanxia Ma ◽  
Weiping Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Predictive Biomarkers ◽  
Principal Component ◽  
Roc Curves ◽  
Core Gene ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
The Core ◽  
Kaplan Meier

Accumulating statistics have shown that liver cancer causes the second highest mortality rate of cancer-related deaths worldwide, of which 80% is hepatocellular carcinoma (HCC). Given the underlying molecular mechanism of HCC pathology is not fully understood yet, identification of reliable predictive biomarkers is more applicable to improve patients’ outcomes. The results of principal component analysis (PCA) showed that the grouped data from 1557 samples in Gene Expression Omnibus (GEO) came from different populations, and the mean tumor purity of tumor tissues was 0.765 through the estimate package in R software. After integrating the differentially expressed genes (DEGs), we finally got 266 genes. Then, the protein-protein interaction (PPI) network was established based on these DEGs, which contained 240 nodes and 1747 edges. FOXM1 was the core gene in module 1 and highly associated with FOXM1 transcription factor network pathway, while FTCD was the core gene in module 2 and was enriched in the metabolism of amino acids and derivatives. The expression levels of hub genes were in line with The Cancer Genome Atlas (TCGA) database. Meanwhile, there were certain correlations among the top ten genes in the up- and downregulated DEGs. Finally, Kaplan–Meier curves and receiver operating characteristic (ROC) curves were plotted for the top five genes in PPI. Apart from CDKN3, the others were closely concerned with overall survival. In this study, we detected the potential biomarkers and their involved biological processes, which would provide a new train of thought for clinical diagnosis and treatment.

scholarly journals PDK2: a novel diagnostic and prognostic biomarker for liver cancer

2020 ◽  
Author(s):  
Zhi-Cheng Liu ◽  
Yan-Qing Li ◽  
Yan Jiao ◽  
Yue-Chen Zhao
Keyword(s):  
Liver Cancer ◽  
Pyruvate Dehydrogenase ◽  
Cox Regression ◽  
Area Under The Curve ◽  
Normal Liver ◽  
The Cancer Genome Atlas ◽  
High Morbidity ◽  
Cox Regression Analysis ◽  
Diagnosis And Prognosis ◽  
Potential Biomarker

Abstract Background: Liver cancer (LC) is a common malignancy with very high morbidity. Pyruvate dehydrogenase kinases (PDKs) are regulators of mitochondrial pyruvate dehydrogenase complexes (PDCs) and play an important role in regulating cellular energy metabolism. In this study, The Cancer Genome Atlas (TCGA) database was used to analyze the expression of PDK2 mRNA in LC, and to explore the value of PDK2 in the diagnosis and prognosis of LC.Methods: The TCGA database, containing the clinical data of 373 LC patients, includes information on PDK2 expression values. The receiver operating characteristic (ROC) curve of PDK2 was drawn to evaluate its diagnostic ability. Patients were divided into PDK2 high- and low-expressing groups by threshold levels. The Chi-square test was used to evaluate the correlation between PDK2 levels and clinicopathological characteristics. The Kaplan-Meier estimator and Cox regression analysis were performed to assess the effect of PDK2 levels on survival outcomes.Results: PDK2 expression in LC tissue was lower than that in normal liver tissues. According to the area under the curve (AUC) value calculated by ROC, PDK2 has a considerable diagnostic value for LC prognosis. The decreased expression of PDK2 is associated with clinical parameters, such as histologic grade ( P =0.0001), radiation therapy ( P =0.0490), vital status ( P =0.0240), and overall survival (OS) ( P =0.0222). Multivariate analysis shows that decreased PDK2 level is an independent risk factor for predicting poor prognosis in LC.Conclusions: PDK2 has a significant impact on the prognosis of LC and is a potential biomarker for the diagnosis and prognosis of LC.

scholarly journals Unveiling Prognostics Biomarkers of Tyrosine Metabolism Reprogramming in Liver Cancer by Cross-platform Gene Expression Analyses

2020 ◽  
Author(s):  
Tran Ngoc Nguyen ◽  
Ha Quy Nguyen ◽  
Duc-Hau Le
Keyword(s):  
Gene Expression ◽  
Normal Liver ◽  
Tyrosine Aminotransferase ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Enzymatic Reactions ◽  
Kaplan Meier ◽  
Catabolic Genes ◽  
Tyrosine Metabolism ◽  
Cross Platform

AbstractTyrosine is mainly degraded in the liver by a series of enzymatic reactions. Abnormal expression of the tyrosine catabolic enzyme tyrosine aminotransferase (TAT) has been reported in patients with hepatocellular carcinoma (HCC). Despite this, aberration in tyrosine metabolism has not been investigated in cancer development. In this work, we conduct comprehensive cross-platform study to obtain foundation for discoveries of potential therapeutics and preventative biomarkers of HCC. We explore data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine and Kaplan Meier plotter (KM plotter) and performed integrated analyses to evaluate the clinical significance and prognostic values of the tyrosine catabolic genes in HCC. We find that five tyrosine catabolic enzymes are downregulated in HCC compared to normal liver at mRNA and protein level. Moreover, low expression of these enzymes correlates with poorer survival in patients with HCC. Notably, we identify pathways and upstream regulators that might involve in tyrosine catabolic reprogramming and further drive HCC development. In total, our results underscore tyrosine metabolism alteration in HCC and lay foundation for incorporating these pathway components in therapeutics and preventative strategies.

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