Identification of key pathways and potential biomarkers for intrahepatic cholangiocarcinoma based on integrated bioinformatics and evaluation of their diagnostic value
- Journal of Third Military Medical University Vol. 43, Issue 10, Pages: 915-922(2021)
- 作者机构：
- 作者简介：
- 基金信息：the Popularization and Application Project of Scientific Research Program of Sichuan Provincial Health Commission(18PJ568)
DOI：10.16016/j.1000-5404.202011021
CLC：Received：04 November 2020，
Published：30 May 2021
- 稿件说明：
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Bo LIU, Tingting FU, Xiaodong GUO, et al. Identification of key pathways and potential biomarkers for intrahepatic cholangiocarcinoma based on integrated bioinformatics and evaluation of their diagnostic value[J]. Journal of Third Military Medical University, 2021, 43(10): 915-922.
Bo LIU, Tingting FU, Xiaodong GUO, et al. Identification of key pathways and potential biomarkers for intrahepatic cholangiocarcinoma based on integrated bioinformatics and evaluation of their diagnostic value[J]. Journal of Third Military Medical University, 2021, 43(10): 915-922. DOI： 10.16016/j.1000-5404.202011021.
摘要
Abstract
Objective
2
To identify the key pathways and potential biomarkers with diagnotic value for the development of intrahepatic cholangiocarcinoma (ICC) by integrating bioinformatics analysis.
Methods
2
We downloaded 3 high-quality datasets of ICC gene microarray (GSE26566
GSE32879 and GSE45001) from Gene Expression Omnibus (GEO) and the high-throughput sequencing data of cholangiocarcinoma (CCA) from the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened using the Limma package in R software; Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed with Cluster Profiler package. Protein-protein interaction (PPI) network analysis of DEGs was subsequently carried out using the Search Tool for the Retrieval of Interacting Genes (STRING) database and subsequently visualized with Cytoscape. In addition
the transcriptional expression of hub genes was further verified by Gene Expression Profiling Interactive Analysis (GEPIA)
and their diagnostic value was assessed by receiver operating characteristic (ROC) curve. Finally
the methylation level of the hub genes was determined using Diseasemeth 2.0.
Results
2
In total
382 DEGs were screened and validated
including 90 up-regulated and 292 down-regulated genes. The up-regulated genes were noticeably enriched in PI3K-Akt signaling pathway
while the down-regulated in the carbon metabolism pathway. A PPI network was constructed with 289 nodes
and 6 hub genes were identified by PPI analysis: PRSS23
LGALS1
VCAN
COL5A1
ITGB1 and EHHADH. ROC curve results showed that all the hub genes distinguished tumor tissues from non-tumorous tissues.
Conclusion
2
Six hub genes are identified by integrative bioinformatics analysis
which may be potential molecular biomarkers for early diagnosis of ICC.
关键词
Keywords
references
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