LncRNA and mRNA integration network reconstruction reveals novel key regulators in esophageal squamous-cell carcinoma.
Esophageal Neoplasms
/ diagnosis
Esophageal Squamous Cell Carcinoma
/ diagnosis
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Ontology
Gene Regulatory Networks
Humans
Open Reading Frames
/ genetics
Prognosis
RNA, Long Noncoding
/ genetics
RNA, Messenger
/ genetics
Survival Analysis
ESCC
Esophageal squamous cell carcinoma
Gene co-expression network
LncRNA and systems biology
Long non-coding RNA
Journal
Genomics
ISSN: 1089-8646
Titre abrégé: Genomics
Pays: United States
ID NLM: 8800135
Informations de publication
Date de publication:
01 2019
01 2019
Historique:
received:
16
09
2017
revised:
05
01
2018
accepted:
05
01
2018
pubmed:
11
1
2018
medline:
18
4
2019
entrez:
11
1
2018
Statut:
ppublish
Résumé
Many experimental and computational studies have identified key protein coding genes in initiation and progression of esophageal squamous cell carcinoma (ESCC). However, the number of researches that tried to reveal the role of long non-coding RNAs (lncRNAs) in ESCC has been limited. LncRNAs are one of the important regulators of cancers which are transcribed dominantly in the genome and in various conditions. The main goal of this study was to use a systems biology approach to predict novel lncRNAs as well as protein coding genes associated with ESCC and assess their prognostic values. By using microarray expression data for mRNAs and lncRNAs from a large number of ESCC patients, we utilized "Weighted Gene Co-expression Network Analysis" (WGCNA) method to make a big coding-non-coding gene co-expression network, and discovered important functional modules. Gene set enrichment and pathway analysis revealed major biological processes and pathways involved in these modules. After selecting some protein coding genes involved in biological processes and pathways related to cancer, we used "LncTar", a computational tool to predict potential interactions between these genes and lncRNAs. By combining interaction results with Pearson correlations, we introduced some novel lncRNAs with putative key regulatory roles in the network. Survival analysis with Kaplan-Meier estimator and Log-rank test statistic confirmed that most of the introduced genes are associated with poor prognosis in ESCC. Overall, our study reveals novel protein coding genes and lncRNAs associated with ESCC, along with their predicted interactions. Based on the promising results of survival analysis, these genes can be used as good estimators of patients' survival, or even can be analyzed further as new potential signatures or targets for the therapy of ESCC disease.
Identifiants
pubmed: 29317304
pii: S0888-7543(18)30007-7
doi: 10.1016/j.ygeno.2018.01.003
pii:
doi:
Substances chimiques
RNA, Long Noncoding
0
RNA, Messenger
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
76-89Informations de copyright
Copyright © 2018 Elsevier Inc. All rights reserved.