Abstract

To screen out copy number variation (CNV)-driven differentially expressed genes (DEGs) in liver cancer and advance our understanding of the pathogenesis, an integrated analysis of liver cancer-related CNV data from The Cancer Genome Atlas (TCGA) and gene expression data from EBI Array Express database were performed. The DEGs were identified by package limma based on the cut-off of |log2 (fold-change)|>0.585 and adjusted p-value<0.05. Using hg19 annotation information provided by UCSC, liver cancer-related CNVs were then screened out. TF-target gene interactions were also predicted with information from UCSC using DAVID online tools. As a result, 25 CNV-driven genes were obtained, including tripartite motif containing 28 (TRIM28) and RanBP-type and C3HC4-type zinc finger containing 1 (RBCK1). In the transcriptional regulatory network, 8 known cancer-related transcription factors (TFs) interacted with 21 CNV-driven genes, suggesting that the other 8 TFs may be involved in liver cancer. These genes may be potential biomarkers for early detection and prevention of liver cancer. These findings may improve our knowledge of the pathogenesis of liver cancer. Nevertheless, further experiments are still needed to confirm our findings.

Highlights

  • Primary liver cancer is the fifth most frequently diagnosed cancer globally and the second leading cause of cancer-related mortality

  • Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on differentially expressed genes (DEGs) and copy number variation (CNV)-driven genes using Database for Annotation, Visualization, and Integrated Discovery (DAVID) [16] online tools

  • A total of 19,944 gene expression values were obtained in normal liver tissue samples and liver cancer samples

Read more

Summary

Introduction

Primary liver cancer is the fifth most frequently diagnosed cancer globally and the second leading cause of cancer-related mortality. We carried out an integrated analysis of liver cancer CNV data from The Cancer Genome Atlas (TCGA) and liver cancer expression profile data from the EBI Array Express database using bioinformatic tools, aiming to identify CNV-driven genes. These CNV-related differentially expressed genes (DEGs) may be potential biomarkers for early diagnosis or treatment. They may aid in identifying underlying mechanisms of liver cancer

Materials and methods
Results
Discussion
28. Tsai RY and Reed RR
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call