Long Non-coding RNA Expression Profiles Of Hepatitis C Virus-related Dysplasia And Hepatocellular Carcinoma

BackgroundHepatocellular carcinoma (HCC) is one of the most frequently diagnosed cancers in the world and is the second leading cause of cancer-related deaths worldwide. The major risk factors for the development of HCC include chronic liver disease as a result of infection with either the hepatitis B virus (HBV) or the hepatitis C virus (HCV) and exposure to carcinogens, such as aflatoxin Bl. Recently, long non-coding RNAs (lncRNAs) were recognized as key regulators of gene expression and found to be implicated in cancer progression. Many studies have highlighted the role of lncRNAs in Hepatitis B Virus-related HCC. However, the contributions of lncRNAs to Hepatitis C virus-related hepatocellular carcinoma (HCC) remain largely unknown. Here, we characterized lncRNAs expression in 75 tissue samples from several different developmental stages of HCV-related hepatocarcinogenesis by repurposing microarray data sets. Material and MethodThe microarray data used in this study were generated using the Affymetrix platform HG-U133A Plus 2.0. The microarray data assessed the gene expression profiles of 75 samples consisting of 10 normal liver tissue samples,13 cirrhotic liver tissue samples,17 dysplastic nodules, and 35 HCCs. Sixty-five frozen HCC tissues and matched adjacent normal liver tissues were randomly obtained from sixty-five patients who underwent hepatectomy at Peking Union Medical College Hospital (Beijing, China). This patient cohort consisted of fifty patients who were infected with HBV and fifteen patients who were infected with HCV. We used these samples to perform quantitative real-time polymerase chain reaction (qRT-PCR) analysis. Non-coding RNA Function Annotation Server (ncFANs) can be used to quantify the levels of messenger RNAs and long non-coding RNAs depending on the re-annotation of Affymetrix microarray probes. The relative expression levels of the lncRNAs were calculated using the comparative Ct method. The DAVID Bioinformatics Tool was used to identify functional enrichment of target protein coding genes. Gene expression data for 75 tissue samples was submitted to ncFANs to generate a coding-non-coding co-expression network.ResultWe found that the expression of 7 IncRNAs in preneoplastic lesions and HCC was significantly different. Among these significantly differently expressed lncRNAs, the lncRNA LINC01419 transcripts were expressed at higher levels in early stage HCC compared to dysplasia and as compared with early stage HCC, IncRNA AK021443 level increase in advanced stage HCC while lncRNA AF070632 level decrease in advanced stage HCC. Using quantitative real-time reverse-transcription PCR, we validated that LINC01419 was significantly overexpressed in HBV-related and HCV-related HCC when compared with matched non-tumor liver tissues. Moreover, functional predictions suggested that LINC01419 and AK021443 regulate cell cycle genes, whereas AF070632 is associated with cofactor binding, oxidation-reduction and carboxylic acid catabolic process.ConclusionThese findings provide the first large-scale survey of lncRNAs associated with the development of hepatocarcinogenesis and may offer new diagnostic biomarkers and therapeutic targets for HCV-related HCC.