Abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is a common cancer with high morbidity and mortality, especially in East Asia. Reliable biomarkers for HCC are indispensible given the absence of capable prediction of prognosis. Long non-coding RNAs (lncRNAs) are the most abundant products of transcription, which might serve as robust markers for diagnosis or treatment. METHODS: Multiple bioinformatics tools were utilized to screen indicative lncRNAs for HCC concurrently with the underlying mechanism of its role in tumorigenesis and development. We analyzed the genome-wide alterations and transcriptomics profiles of HCC and non-tumor samples from The Cancer Genome Atlas (TCGA). Survival analyses were also applied. Integrated bioinformatics analyses were applied to identify co-expressed genes along with chromosome loci, predictive RNA binding proteins (RBPs) and co-expressed miRNAs. RESULTS: Combining copy number variations (CNVs) with expressions of lncRNAs, 20 most aberrant lncRNAs were identified. MAFA-AS1 was identified as a prognostic indicator of HCC poor overall survival (OS) and disease-free survival (DFS). Multiple bioinformatics analyses suggest that MAFA-AS1 is involved in HCC progression via interacting with SRSF1/SRSF9 and coordinating with miR210. CONCLUSIONS: MAFA-AS1is a prognostic biomarker for poor OS and DFS of patients with HCC. It is involved in HCC progression.