scholarly journals A novel prognostic target-gene signature and nomogram based on an integrated bioinformatics analysis in hepatocellular carcinoma

BIOCELL ◽  
2022 ◽  
Vol 46 (5) ◽  
pp. 1261-1288
Author(s):  
RUI XU ◽  
QIBIAO WU ◽  
YUHAN GONG ◽  
YONGZHE WU ◽  
QINGJIA CHI ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Target Gene ◽  
Bioinformatics Analysis ◽  
Gene Signature

scholarly journals Identification of an eight-gene signature for survival prediction for patients with hepatocellular carcinoma based on integrated bioinformatics analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6548 ◽  
Author(s):  
Guo-jie Qiao ◽  
Liang Chen ◽  
Jin-cai Wu ◽  
Zhou-ri Li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Bioinformatics Analysis ◽  
Gene Signature ◽  
Training Dataset ◽  
Rank Test ◽  
Survival Prediction ◽  
Gene Model ◽  
Cox Regression Analysis ◽  
Log Rank Test

Background Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related death worldwide. Despite recent advances in imaging techniques and therapeutic intervention for HCC, the low overall 5-year survival rate of HCC patients remains unsatisfactory. This study aims to find a gene signature to predict clinical outcomes in HCC. Methods Bioinformatics analysis including Cox’s regression analysis, Kaplan-Meier (KM) and receiver operating characteristic curve (ROC) analysis and the random survival forest algorithm were performed to mine the expression profiles of 553 hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public database. Results We selected a signature comprising eight protein-coding genes (DCAF13, FAM163A, GPR18, LRP10, PVRIG, S100A9, SGCB, and TNNI3K) in the training dataset (AUC = 0.77 at five years, n = 332). The signature stratified patients into high- and low-risk groups with significantly different survival in the training dataset (median 2.20 vs. 8.93 years, log-rank test P < 0.001) and in the test dataset (median 2.68 vs. 4.24 years, log-rank test P = 0.004, n = 221, GSE14520). Further multivariate Cox regression analysis showed that the signature was an independent prognostic factor for patients with HCC. Compared with TNM stage and another reported three-gene model, the signature displayed improved survival prediction power in entire dataset (AUC signature = 0.66 vs. AUC TNM = 0.64 vs. AUC gene model = 0.60, n = 553). Stratification analysis shows that it can be used as an auxiliary marker for many traditional staging models. Conclusions We constructed an eight-gene signature that can be a novel prognostic marker to predict the survival of HCC patients.

scholarly journals Analysis of microarrays of miR-34a and its identification of prospective target gene signature in hepatocellular carcinoma

BMC Cancer ◽  
2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Fang-Hui Ren ◽  
Hong Yang ◽  
Rong-quan He ◽  
Jing-ning Lu ◽  
Xing-gu Lin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Target Gene ◽  
Gene Signature

The p53 family target gene signature is of prognostic relevance in hepatocellular carcinoma

2010 ◽  
Vol 48 (01) ◽  
Author(s):  
F Staib ◽  
H Mundt ◽  
A Koch ◽  
M Krupp ◽  
PR Galle ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Target Gene ◽  
Gene Signature ◽  
P53 Family ◽  
Prognostic Relevance

902 THE P53 FAMILY TARGET GENE SIGNATURE IS OF PROGNOSTIC RELEVANCE IN HEPATOCELLULAR CARCINOMA

2010 ◽  
Vol 52 ◽  
pp. S350-S351
Author(s):  
F. Staib ◽  
H. Mundt ◽  
A. Koch ◽  
M. Krupp ◽  
P.R. Galle ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Target Gene ◽  
Gene Signature ◽  
P53 Family ◽  
Prognostic Relevance

scholarly journals Identifying a Six-Gene Signature Predicting Response to TACE in Hepatocellular Carcinoma by Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xin Yao ◽  
Xin Yin ◽  
Wei Lu ◽  
Leitao Cao
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Cytochrome P450 ◽  
Predictive Value ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Gene Signature ◽  
Metabolic Process ◽  
Training Set ◽  
Validation Set

Background and Aim. With regard to patients with intermediate-stage, irresectable hepatocellular carcinoma (HCC), transcatheter arterial chemoembolization (TACE) is the mainstay of treatment. There is an urgent clinical requirement to identify reliable biomarkers to predict the response of HCC patients to TACE treatment. We aimed to identify a gene signature for predicting TACE response in HCC patients based on bioinformatics analysis. Methods. We downloaded the gene expression profile GSE104580 based on 147 tumor samples from 81 responders to TACE and 66 nonresponders from the Gene Expression Omnibus (GEO) database. Then, we randomly divided the 147 tumor samples into a training set ( n = 89 ) and a validation set ( n = 58 ) and screened differentially expressed genes (DEGs) in the training set. Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to annotate functions of the DEGs. The DEGs were mapped into the STRING website for constructing protein-protein interaction (PPI). The predictive value of the candidate genes by receiver-operating characteristic (ROC) curves was further verified in the validation set. Results. We totally found 158 DEGs (92 upregulated genes and 66 downregulated genes) in the training set. The GO enrichment analysis revealed that DEGs were significantly enriched in metabolic and catabolic processes, such as drug metabolic process, fatty acid metabolic process, and small molecule catabolic process. The KEGG pathway analysis revealed that the DEGs were mainly concentrated in drug metabolism-cytochrome P450, metabolism of xenobiotics by cytochrome P450, and chemical carcinogenesis. We identified 6 candidate genes (CXCL8, AFP, CYP1A1, MMP9, CYP3A4, and SERPINC1) based on the PPI network of the DEGs, which had high predictive value in HCC response to TACE with an area under the curve (AUC) value of 0.875 and 0.897 for the training set and validation set, respectively. Conclusion. We identified a six-gene signature which might be biomarkers for predicting HCC response to TACE by a comprehensive bioinformatics analysis. However, the actual functions of these genes required verification.

scholarly journals Identification and Validation of New Cancer Stem Cell-Related Genes and Their Regulatory microRNAs in Colorectal Cancerogenesis

Biomedicines ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 179
Author(s):  
Kristian Urh ◽  
Margareta Žlajpah ◽  
Nina Zidar ◽  
Emanuela Boštjančič
Keyword(s):  
Experimental Validation ◽  
Target Gene ◽  
Bioinformatics Analysis ◽  
Early Carcinoma ◽  
Significant Progress ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Node Metastases ◽  
Formalin Fixed ◽  
Made In

Significant progress has been made in the last decade in our understanding of the pathogenetic mechanisms of colorectal cancer (CRC). Cancer stem cells (CSC) have gained much attention and are now believed to play a crucial role in the pathogenesis of various cancers, including CRC. In the current study, we validated gene expression of four genes related to CSC, L1TD1, SLITRK6, ST6GALNAC1 and TCEA3, identified in a previous bioinformatics analysis. Using bioinformatics, potential miRNA-target gene correlations were prioritized. In total, 70 formalin-fixed paraffin-embedded biopsy samples from 47 patients with adenoma, adenoma with early carcinoma and CRC without and with lymph node metastases were included. The expression of selected genes and microRNAs (miRNAs) was evaluated using quantitative PCR. Differential expression of all investigated genes and four of six prioritized miRNAs (hsa-miR-199a-3p, hsa-miR-335-5p, hsa-miR-425-5p, hsa-miR-1225-3p, hsa-miR-1233-3p and hsa-miR-1303) was found in at least one group of CRC cancerogenesis. L1TD1, SLITRK6, miR-1233-3p and miR-1225-3p were correlated to the level of malignancy. A negative correlation between miR-199a-3p and its predicted target SLITRK6 was observed, showing potential for further experimental validation in CRC. Our results provide further evidence that CSC-related genes and their regulatory miRNAs are involved in CRC development and progression and suggest that some them, particularly miR-199a-3p and its SLITRK6 target gene, are promising for further validation in CRC.

scholarly journals Distinct diagnostic and prognostic values of Glypicans gene expression in patients with hepatocellular carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jian-Yao Wang ◽  
Xiang-Kun Wang ◽  
Guang-Zhi Zhu ◽  
Xin Zhou ◽  
Jun Yao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Tumor Tissue ◽  
Bioinformatics Analysis ◽  
Mrna Level ◽  
Normal Liver ◽  
Predictive Index ◽  
Expression Levels ◽  
Interactive Analysis ◽  
Diagnostic Values

Abstract Backgroud In our current work, we aimed to investigate the expressions of glypican (GPC) family genes at the mRNA level and assess their prognostic significances in patients with hepatocellular carcinoma (HCC). Methods The pathological roles of GPC family genes were examined using bioinformatics analysis. The diagnostic values of GPC genes were explored with the Gene Expression Profiling Interactive Analysis. Moreover, the mRNA expression and prognostic values of GPC genes were assessed via the KM plotter database. Results Our data showed that the expression of GPC-3 was dramatically increased in the liver tumor tissue. Moreover, the expressions of the other five GPC family members were not significantly different between the tumor and normal liver tissues (P > 0.05). Furthermore, the up-regulation of GPC-1 at the mRNA level was dramatically correlated to the reduced overall survival (OS) for all HCC patients (hazard ratio = 2.03, 95% confidence intervals =1.44–2.87, P = 4.1e-05) compared with its low-expression group. Besides, the prognosis of the Caucasians was related to most GPC family genes, while the prognosis of the Asian race was only related to the expression of GPC-2. Besides, for pathological factors, including stage, grade, AJCC, and vascular invasion, the higher the pathological grade and vascular invasiveness, the lower the expression levels of GPC family genes (P < 0.05). Finally, the expression levels of GPC-1, 2, and 3 in the hepatitis group were related to the poor prognosis of HCC in the risk factor (alcohol consumption and hepatitis) subgroup (P < 0.05). Conclusions Our findings indicated that GPC-3 was dysregulated in HCC compared with paracancerous tissues. The expression of GPC-1 could be used as a potent predictive index for the general prognosis of HCC. The pathology, patients, and risk factors might affect the prognostic value of GPC family genes in HCC.

scholarly journals A Bioinformatics Analysis Identifies the Telomerase Inhibitor MST-312 for Treating High-STMN1-Expressing Hepatocellular Carcinoma

2021 ◽  
Vol 11 (5) ◽  
pp. 332
Author(s):  
Szu-Jen Wang ◽  
Pei-Ming Yang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Kinase Inhibitors ◽  
Cancer Genomics ◽  
Gene Signature ◽  
Migration And Invasion ◽  
Advanced Hcc ◽  
Telomerase Inhibitor ◽  
Cell Cycle Related Gene ◽  
Hcc Cells

Hepatocellular carcinoma (HCC) is a relatively chemo-resistant tumor. Several multi-kinase inhibitors have been approved for treating advanced HCC. However, most HCC patients are highly refractory to these drugs. Therefore, the development of more effective therapies for advanced HCC patients is urgently needed. Stathmin 1 (STMN1) is an oncoprotein that destabilizes microtubules and promotes cancer cell migration and invasion. In this study, cancer genomics data mining identified STMN1 as a prognosis biomarker and a therapeutic target for HCC. Co-expressed gene analysis indicated that STMN1 expression was positively associated with cell-cycle-related gene expression. Chemical sensitivity profiling of HCC cell lines suggested that High-STMN1-expressing HCC cells were the most sensitive to MST-312 (a telomerase inhibitor). Drug–gene connectivity mapping supported that MST-312 reversed the STMN1-co-expressed gene signature (especially BUB1B, MCM2/5/6, and TTK genes). In vitro experiments validated that MST-312 inhibited HCC cell viability and related protein expression (STMN1, BUB1B, and MCM5). In addition, overexpression of STMN1 enhanced the anticancer activity of MST-312 in HCC cells. Therefore, MST-312 can be used for treating STMN1-high expression HCC.

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