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

Xiaodong Wang; Jing Qian; Ninghua Yao; Christine Pocha; Koo Jeong Kang; Roberta Angelico; Guodong Zhu

doi:10.21037/atm-22-2194

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

Ann Transl Med. 2022 May;10(10):595. doi: 10.21037/atm-22-2194.

Authors

Xiaodong Wang^#¹, Jing Qian^#², Ninghua Yao^#², Christine Pocha³, Koo Jeong Kang⁴, Roberta Angelico⁵, Guodong Zhu⁶

Affiliations

¹ Department of Interventional, the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
² Department of Cancer Center, Affiliated Hospital of Nantong University, Nantong, China.
³ Avera McKennnan Hospital and University Medical Center, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA.
⁴ Department of Surgery, Keimyung University School of Medicine, Dongsan Medical Center, Daegu, Republic of Korea.
⁵ HPB and Transplant Unit, Department of Surgical Sciences, University of Rome Tor Vergata, Rome, Italy.
⁶ Department of Hepatobiliary Surgery, Affiliated Nantong Hospital 3 of Nantong University, Nantong, China.

^# Contributed equally.

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.

Keywords: Hepatocellular carcinoma (HCC); The Cancer Genome Atlas (TCGA); cancer-related metabolic reprogramming; long non-coding RNA (lncRNA); tumor immune microenvironment (TIME).