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Identification of metabolism-related long non-coding RNA (lncRNA) signature predicts prognosis and immune infiltrates in hepatocellular carcinoma

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Author(s)
Xiaodong WangJing QianNinghua YaoChristine PochaKoo Jeong KangRoberta AngelicoGuodong Zhu
Keimyung Author(s)
Kang, Koo Jeong
Department
Dept. of Surgery (외과학)
Journal Title
Ann Transl Med
Issued Date
2022
Volume
10
Issue
10
Keyword
Hepatocellular carcinoma (HCC)The Cancer Genome Atlas (TCGA)long non-coding RNA (lncRNA)cancer-related metabolic reprogrammingtumor immune microenvironment (TIME)
Abstract
Background:
Cancer-associated metabolic reprogramming promotes cancer cell differentiation, growth, and influences the tumor immune microenvironment (TIME) to promote hepatocellular carcinoma (HCC) progression. However, the clinical significance of metabolism-related lncRNA remains largely unexplored.

Methods:
Based on The Cancer Genome Atlas (TCGA) Liver hepatocellular carcinoma (LIHC) dataset, we identified characteristic prognostic long non-coding RNAs (lncRNAs) and construct metabolism-related lncRNA prognostic signature for HCC. Gender, age, grade, stage and TP53 status were used as covariates were used to assess the prognostic capacity of the characteristic lncRNA signature. Subsequently, the molecular and immune characteristics and drug sensitivity in metabolism-related lncRNA signature defined subgroups were analyzed.

Results:
We identified 34 metabolism-related lncRNAs significantly associated with the prognosis of HCC (P<0.05). Subsequently, we constructed a multigene signature based on 9 characteristics prognostic lncRNAs and classified HCC patients into high- and low-risk groups based on cutoff values. We found the lncRNA signature [hazard ratio (HR) =3.55 (2.44–5.15), P<0.001] to be significantly associated with survival. The receiver operating characteristic curve (ROC) curves area under the curve (AUC) values for 1-, 3-, and 5-year survival were 0.811, 0.773, and 0.753, respectively. In univariate and multivariate Cox regression analyses, prognostic characteristic lncRNAs were the most crucial prognostic factor besides the stage. The prognostic signature was subsequently validated in the test set. In addition, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) analyses revealed potential biological features and signaling pathways associated with the prognostic signature. We constructed a nomogram including risk groups and clinical parameters (age, gender, grade, and stage). Calibration plots and decision curve analysis (DCA) showed that our nomogram had a good predictive performance. Finally, we found reduced expression of immune-activated cells in the high-risk group.

Conclusions:
The metabolism-related lncRNA signature is a promising biomarker to distinguish the prognosis and an immune characteristic in HCC.
Keimyung Author(s)(Kor)
강구정
Publisher
School of Medicine (의과대학)
Citation
Xiaodong Wang et al. (2022). Identification of metabolism-related long non-coding RNA (lncRNA) signature predicts prognosis and immune infiltrates in hepatocellular carcinoma. Ann Transl Med, 10(10), 595. doi: 10.21037/atm-22-2194
Type
Article
ISSN
2305-5847
Source
https://atm.amegroups.com/article/view/95540/html
DOI
10.21037/atm-22-2194
URI
https://kumel.medlib.dsmc.or.kr/handle/2015.oak/44295
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Surgery (외과학)
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