Work

Identification of Long Noncoding RNA Biomarkers for Hepatocellular Carcinoma Using Single‐Sample Networks

Year: 2020

Type: article

Abstract: OBJECTIVE: Many studies have found that long noncoding RNAs (lncRNAs) are differentially expressed in hepatocellular carcinoma (HCC) and closely associated with the occurrence and prognosis of HCC. Since patients with HCC are usually diagnosed in late stages, more effective biomarkers for early diagnosis and prognostic prediction are in urgent need. METHODS: The RNA-seq data of liver hepatocellular carcinoma (LIHC) were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs and mRNAs were obtained using the edgeR package. The single-sample networks of the 371 tumor samples were constructed to identify the candidate lncRNA biomarkers. Univariate Cox regression analysis was performed to further select the potential lncRNA biomarkers. By multivariate Cox regression analysis, a 3-lncRNA-based risk score model was established on the training set. Then, the survival prediction ability of the 3-lncRNA-based risk score model was evaluated on the testing set and the entire set. Function enrichment analyses were performed using Metascape. RESULTS: Three lncRNAs (RP11-150O12.3, RP11-187E13.1, and RP13-143G15.4) were identified as the potential lncRNA biomarkers for LIHC. The 3-lncRNA-based risk model had a good survival prediction ability for the patients with LIHC. Multivariate Cox regression analysis proved that the 3-lncRNA-based risk score was an independent predictor for the survival prediction of patients with LIHC. Function enrichment analysis indicated that the three lncRNAs may be associated with LIHC via their involvement in many known cancer-associated biological functions. CONCLUSION: This study could provide novel insights to identify lncRNA biomarkers for LIHC at a molecular network level.

Source: BioMed Research International

DOI: 10.1155/2020/8579651

Authors: Xiaoqing Yu, Jingsong Zhang, Rui Yang, Chun Li

Institutions: Shanghai Institute of Technology, Chinese Academy of Sciences, Center for Excellence in Molecular Cell Science, State Key Laboratory of Cell Biology, Hainan Normal University

Language: English

Topic: Cancer-related molecular mechanisms research

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $2,680