scholarly journals Identification of key genes and pathways by�bioinformatics analysis with TCGA RNA sequencing data in hepatocellular carcinoma

2018 ◽  
Author(s):  
Qiandong Zhu ◽  
Yunpeng Sun ◽  
Qingqing Zhou ◽  
Qikuan He ◽  
Haixin Qian
Keyword(s):  
Hepatocellular Carcinoma ◽  
Rna Sequencing ◽  
Bioinformatics Analysis ◽  
Sequencing Data ◽  
Key Genes

scholarly journals Identifying key genes associated with Hirschsprung’s disease based on bioinformatics analysis of RNA-sequencing data

2017 ◽  
Vol 13 (3) ◽  
pp. 267-273 ◽  
Author(s):  
Wei-Kang Pan ◽  
Ya-Fei Zhang ◽  
Hui Yu ◽  
Ya Gao ◽  
Bai-Jun Zheng ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Hirschsprung's Disease ◽  
Hirschsprung’S Disease ◽  
Bioinformatics Analysis ◽  
Sequencing Data ◽  
Key Genes

scholarly journals Bioinformatics Analysis and RNA-Sequencing of SCAMP3 Expression and Correlated Gene Regulation in Hepatocellular Carcinoma

2020 ◽  
Vol Volume 13 ◽  
pp. 1047-1057
Author(s):  
Shan-shan Han ◽  
Zhi-qiang Feng ◽  
Rui Liu ◽  
Jun Ye ◽  
Wei-wei Cheng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Gene Regulation ◽  
Rna Sequencing ◽  
Bioinformatics Analysis

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.

scholarly journals Identification of Key Genes and Potential New Biomarkers for Ovarian Aging: A Study Based on RNA-Sequencing Data

2020 ◽  
Vol 11 ◽  
Author(s):  
Lingwei Ma ◽  
Huan Lu ◽  
Runhua Chen ◽  
Meng Wu ◽  
Yan Jin ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Sequencing Data ◽  
Ovarian Aging ◽  
Key Genes ◽  
New Biomarkers
Sign in / Sign up

Export Citation Format

Share Document