Research Paper Volume 11, Issue 22 pp 10422—10453

Large-scale analyses identify a cluster of novel long noncoding RNAs as potential competitive endogenous RNAs in progression of hepatocellular carcinoma

Mengjia Song 1, 2, *, , Ailin Zhong 4, *, , Jieying Yang 1, 2, *, , Junyi He 1, 2, *, , Shaoyan Cheng 3, , Jianxiong Zeng 1, 2, , Yue Huang 1, 2, , Qiuzhong Pan 1, 2, , Jingjing Zhao 1, 2, , Ziqi Zhou 1, 2, , Qian Zhu 1, 2, , Yan Tang 1, 2, , Hao Chen 1, 2, , Chaopin Yang 1, 2, , Yuan Liu 1, 2, , Xiaocong Mo 1, 2, , Desheng Weng 1, 2, , Jian-Chuan Xia 1, 2, ,

  • 1 Department of Biotherapy, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
  • 2 Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, China
  • 3 Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
  • 4 Office of International Exchange and Cooperation, Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
* Equal contribution

received: July 23, 2019 ; accepted: November 8, 2019 ; published: November 23, 2019 ;
How to Cite

Copyright © 2019 Song et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


The abnormal expression of noncoding RNAs has attracted increasing interest in the field of hepatocellular carcinoma progression. However, the underlying molecular mechanisms mediated by noncoding RNAs in these processes are unclear. Here, we obtained the expression profiles of long noncoding RNAs, microRNAs, and mRNAs from the Gene Expression Omnibus database and identified hepatocarcinogenesis-specific differentially expressed transcripts. Next, we identified significant Gene Ontology and pathway terms that the differentially expressed transcripts involved in. Using functional analysis and target prediction, we constructed a hepatocellular carcinoma-associated deregulated competitive endogenous RNA network to reveal the potential mechanisms underlying tumor progression. By analyzing The Cancer Genome Atlas dataset, six key long noncoding RNAs showed significant association with overall survival as well as strong correlation with some microRNAs and mRNAs in the competitive endogenous RNA network. We further validated the above results and determined their diagnostic and prognostic value in clinical samples. Importantly, by large-scale analyses, we identified a cluster of long noncoding RNAs, GBAP1, MCM3AP-AS1, SLC16A1-AS1, C3P1, DIO3OS, and HNF4A-AS1 as candidate biomarkers for the diagnosis and prognosis of hepatocellular carcinoma, which will improve our understanding of competitive endogenous RNA-mediated regulatory mechanisms underlying hepatocellular carcinoma development and will provide novel therapeutic targets in the future.


AUC: area under the curve; ceRNA: competitive endogenous RNA; DEGs: differentially expressed genes; DELs: differentially expressed lncRNAs; DEMs: differentially expressed miRNAs; EMT: epithelial-mesenchymal transition; FC: Fold Change; FDR: false discovery rate; GEO: Gene Expression Omnibus; GO: Gene Ontology; HCC: hepatocellular carcinoma; KEGG: Kyoto Encyclopedia of Genes and Genomes; lncRNA: long noncoding RNA; miRNA: microRNAs; MRE: miRNA response elements; OS: overall survival; PFS: progression-free survival; qRT-PCR: quantitative reverse transcriptase-polymerase chain reaction; ROC: Receiver operating characteristic; signal-net: signal regulation network; TCGA: the Cancer Genome Atlas; TGF-β: transforming growth factor-beta.