Integrative analysis reveals the prognostic value and functions of splicing factors implicated in hepatocellular carcinoma.
Alternative Splicing
Biomarkers, Tumor
/ genetics
Carcinoma, Hepatocellular
/ genetics
DEAD-box RNA Helicases
/ genetics
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Humans
Liver Neoplasms
/ genetics
Models, Biological
Nuclear Proteins
/ genetics
Nucleocytoplasmic Transport Proteins
/ genetics
Prognosis
Protein Interaction Maps
/ genetics
RNA Splicing Factors
/ genetics
RNA-Binding Proteins
/ genetics
Risk Factors
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
26 07 2021
26 07 2021
Historique:
received:
10
04
2021
accepted:
15
07
2021
entrez:
27
7
2021
pubmed:
28
7
2021
medline:
4
11
2021
Statut:
epublish
Résumé
Splicing factors (SFs) play critical roles in the pathogenesis of various cancers through regulating tumor-associated alternative splicing (AS) events. However, the clinical value and biological functions of SFs in hepatocellular carcinoma (HCC) remain obscure. In this study, we identified 40 dysregulated SFs in HCC and established a prognostic model composed of four SFs (DNAJC6, ZC3H13, IGF2BP3, DDX19B). The predictive efficiency and independence of the prognostic model were confirmed to be satisfactory. Gene Set Enrichment Analysis (GSEA) illustrated the risk score calculated by our prognostic model was significantly associated with multiple cancer-related pathways and metabolic processes. Furthermore, we constructed the SFs-AS events regulatory network and extracted 108 protein-coding genes from the network for following functional explorations. Protein-protein interaction (PPI) network delineated the potential interactions among these 108 protein-coding genes. GO and KEGG pathway analyses investigated ontology gene sets and canonical pathways enriched by these 108 protein-coding genes. Overlapping the results of GSEA and KEGG, seven pathways were identified to be potential pathways regulated by our prognostic model through triggering aberrant AS events in HCC. In conclusion, the present study established an effective prognostic model based on SFs for HCC patients. Functional explorations of SFs and SFs-associated AS events provided directions to explore biological functions and mechanisms of SFs in HCC tumorigenesis.
Identifiants
pubmed: 34312475
doi: 10.1038/s41598-021-94701-8
pii: 10.1038/s41598-021-94701-8
pmc: PMC8313569
doi:
Substances chimiques
Biomarkers, Tumor
0
IGF2BP3 protein, human
0
Nuclear Proteins
0
Nucleocytoplasmic Transport Proteins
0
RNA Splicing Factors
0
RNA-Binding Proteins
0
ZC3H13 protein, human
0
DDX19B protein, human
EC 3.6.1.-
DEAD-box RNA Helicases
EC 3.6.4.13
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
15175Informations de copyright
© 2021. The Author(s).
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