Integrative analysis of layers of data in hepatocellular carcinoma reveals pathway dependencies.
Gene expression
Hepatocellular carcinoma
High throughput data
Methylation
Proteomics
miRNA
Journal
World journal of hepatology
ISSN: 1948-5182
Titre abrégé: World J Hepatol
Pays: United States
ID NLM: 101532469
Informations de publication
Date de publication:
27 Jan 2021
27 Jan 2021
Historique:
received:
06
08
2020
revised:
19
11
2020
accepted:
04
12
2020
entrez:
15
2
2021
pubmed:
16
2
2021
medline:
16
2
2021
Statut:
ppublish
Résumé
The broader use of high-throughput technologies has led to improved molecular characterization of hepatocellular carcinoma (HCC). To comprehensively analyze and characterize all publicly available genomic, gene expression, methylation, miRNA and proteomic data in HCC, covering 85 studies and 3355 patient sample profiles, to identify the key dysregulated genes and pathways they affect. We collected and curated all well-annotated and publicly available high-throughput datasets from PubMed and Gene Expression Omnibus derived from human HCC tissue. Comprehensive pathway enrichment analysis was performed using pathDIP for each data type (genomic, gene expression, methylation, miRNA and proteomic), and the overlap of pathways was assessed to elucidate pathway dependencies in HCC. We identified a total of 8733 abstracts retrieved by the search on PubMed on HCC for the different layers of data on human HCC samples, published until December 2016. The common key dysregulated pathways in HCC tissue across different layers of data included epidermal growth factor (EGFR) and β1-integrin pathways. Genes along these pathways were significantly and consistently dysregulated across the different types of high-throughput data and had prognostic value with respect to overall survival. Using CTD database, estradiol would best modulate and revert these genes appropriately. By analyzing and integrating all available high-throughput genomic, transcriptomic, miRNA, methylation and proteomic data from human HCC tissue, we identified EGFR, β1-integrin and axon guidance as pathway dependencies in HCC. These are master regulators of key pathways in HCC, such as the mTOR, Ras/Raf/MAPK and p53 pathways. The genes implicated in these pathways had prognostic value in HCC, with Netrin and Slit3 being novel proteins of prognostic importance to HCC. Based on this integrative analysis, EGFR, and β1-integrin are master regulators that could serve as potential therapeutic targets in HCC.
Sections du résumé
BACKGROUND
BACKGROUND
The broader use of high-throughput technologies has led to improved molecular characterization of hepatocellular carcinoma (HCC).
AIM
OBJECTIVE
To comprehensively analyze and characterize all publicly available genomic, gene expression, methylation, miRNA and proteomic data in HCC, covering 85 studies and 3355 patient sample profiles, to identify the key dysregulated genes and pathways they affect.
METHODS
METHODS
We collected and curated all well-annotated and publicly available high-throughput datasets from PubMed and Gene Expression Omnibus derived from human HCC tissue. Comprehensive pathway enrichment analysis was performed using pathDIP for each data type (genomic, gene expression, methylation, miRNA and proteomic), and the overlap of pathways was assessed to elucidate pathway dependencies in HCC.
RESULTS
RESULTS
We identified a total of 8733 abstracts retrieved by the search on PubMed on HCC for the different layers of data on human HCC samples, published until December 2016. The common key dysregulated pathways in HCC tissue across different layers of data included epidermal growth factor (EGFR) and β1-integrin pathways. Genes along these pathways were significantly and consistently dysregulated across the different types of high-throughput data and had prognostic value with respect to overall survival. Using CTD database, estradiol would best modulate and revert these genes appropriately.
CONCLUSION
CONCLUSIONS
By analyzing and integrating all available high-throughput genomic, transcriptomic, miRNA, methylation and proteomic data from human HCC tissue, we identified EGFR, β1-integrin and axon guidance as pathway dependencies in HCC. These are master regulators of key pathways in HCC, such as the mTOR, Ras/Raf/MAPK and p53 pathways. The genes implicated in these pathways had prognostic value in HCC, with Netrin and Slit3 being novel proteins of prognostic importance to HCC. Based on this integrative analysis, EGFR, and β1-integrin are master regulators that could serve as potential therapeutic targets in HCC.
Identifiants
pubmed: 33584989
doi: 10.4254/wjh.v13.i1.94
pmc: PMC7856865
doi:
Types de publication
Journal Article
Langues
eng
Pagination
94-108Informations de copyright
©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
Déclaration de conflit d'intérêts
Conflict-of-interest statement: The authors do not have any conflict of interest to declare.
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