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  4. Modular signature of long non-coding RNA association networks as a prognostic biomarker in lung cancer
 
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Modular signature of long non-coding RNA association networks as a prognostic biomarker in lung cancer

Journal
BMC Medical Genomics
Journal Volume
14
Journal Issue
Art. No.290
Date Issued
2021-11-01
Author(s)
Li, Albert
Yu, Wen Hsuan
CHIA-LANG HSU
Huang, Hsuan Cheng
HSUEH-FEN JUAN  
DOI
10.1186/s12920-021-01137-0
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/592523
URL
https://api.elsevier.com/content/abstract/scopus_id/85120779997
Abstract
Background: Increasing amount of long non-coding RNAs (lncRNAs) have been found involving in many biological processes and played salient roles in cancers. However, up until recently, functions of most lncRNAs in lung cancer have not been fully discovered, particularly in the co-regulated lncRNAs. Thus, this study aims to investigate roles of lncRNA modules and uncover a module-based biomarker in lung adenocarcinoma (LUAD). Results: We used gene expression profiles from The Cancer Genome Atlas (TCGA) to construct the lncRNA association networks, from which the highly-associated lncRNAs are connected as modules. It was found that the expression of some modules is significantly associated with patient’s survival, including module N1 (HR = 0.62, 95% CI = 0.46–0.84, p = 0.00189); N2 (HR = 0.68, CI = 0.50–0.93, p = 0.00159); N4 (HR = 0.70, CI = 0.52–0.95, p = 0.0205) and P3 (HR = 0.68, CI = 0.50–0.92, p = 0.0123). The lncRNA signature consisting of these four prognosis-related modules, a 4-modular lncRNA signature, is associated with favourable prognosis in TCGA-LUAD (HR = 0.51, CI = 0.37–0.69, p value = 2.00e−05). Afterwards, to assess the performance of the generic modular signature as a prognostic biomarker, we computed the time-dependent area under the receiver operating characteristics (AUC) of this 4-modular lncRNA signature, which showed AUC equals 68.44% on 336th day. In terms of biological functions, these modules are correlated with several cancer hallmarks and pathways, including Myc targets, E2F targets, cell cycle, inflammation/immunity-related pathways, androgen/oestrogen response, KRAS signalling, DNA repair and epithelial-mesenchymal transition (EMT). Conclusion: Taken together, we identified four novel LUAD prognosis-related lncRNA modules, and assessed the performance of the 4-modular lncRNA signature being a prognostic biomarker. Functionally speaking, these modules involve in oncogenic hallmarks as well as pathways. The results unveiled the co-regulated lncRNAs in LUAD and may provide a framework for further lncRNA studies in lung cancer.
Subjects
LncRNA association networks | lncRNA modular prognostic biomarkers | Lung cancer
SDGs

[SDGs]SDG3

Publisher
BioMed Central Ltd
Type
journal article

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