Long non-coding RNAs and genes contributing to the generation of cancer stem cells in hepatocellular carcinoma identified by RNA sequencing analysis

Oncol Rep. 2016 Nov;36(5):2619-2624. doi: 10.3892/or.2016.5120. Epub 2016 Sep 22.

Abstract

Cancer stem cells (CSCs) play important roles in cancer initiation, progression and metastasis. The aim of the present study was to identify the potential targets that may contribute to the generation of hepatocellular carcinoma stem cells (HCSCs) from hepatocellular carcinoma (HCC) cells. The RNA sequencing (RNA‑Seq) dataset GSE70537 was downloaded from the Gene Expression Omnibus (GEO) database. Raw RNA sequences were mapped to the GRCh37/hg19 genome based on TopHat and assembled through Cufflinks. Cuffdiff of Cufflinks was used for the screening of differentially expressed genes (DEGs) in the two types of HCSCs (Hep3B‑C and Huh7‑C) compared with the two types of HCC cells (Hep3B and Huh7) which were satisfied by the criteria of |log2(RPKMHCSC/RPKMHCC)| >1 and p<0.05. In addition, based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID), we screened the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways which were enriched in the DEGs. For the DEGs with consistent differential expression in the two lists of DEGs, the LncRNA2Target database was used for the identification of long non‑coding RNA (lncRNA)‑gene pairs. A total of 218 and 591 DEGs were identified for the Hep3B‑C and Huh7‑C samples, respectively, and 22 overlaps were obtained. Biological processes and pathways related to steroid biosynthesis/metabolism or other substance transport were found to be enriched in the two lists of DEGs. Among the 22 overlaps, 16 were found to be consistently differentially expressed in the two HCSC samples, and the lncRNA‑gene regulatory network of these genes was constructed. Moreover, several potential biomarkers that may play important roles in the transformation of HCSCs were identified in the regulation network. Through the bioinformatics analysis of the RNA‑Seq dataset, several novel targets that were associated with the progression of HCC were obtained, and these targets may be valuable for the treatment and prognosis of HCC.

MeSH terms

  • Carcinoma, Hepatocellular / genetics*
  • Carcinoma, Hepatocellular / pathology
  • Computational Biology
  • Databases, Genetic
  • Gene Expression Regulation, Neoplastic / genetics*
  • Gene Ontology
  • Gene Regulatory Networks / genetics
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Liver Neoplasms / genetics*
  • Liver Neoplasms / pathology
  • Neoplastic Stem Cells / pathology
  • Oligonucleotide Array Sequence Analysis
  • RNA, Long Noncoding / biosynthesis*
  • RNA, Long Noncoding / genetics

Substances

  • RNA, Long Noncoding