Identification of modules and novel prognostic biomarkers in liver cancer through integrated bioinformatics analysis

• Main Authors: Bo Shen, Kun Li, Yuting Zhang
• Format: Article
• Language: English
• Published: Wiley 2020-11-01
• Series: FEBS Open Bio
• Subjects: competitive endogenous RNAs; liver cancer; microRNA; prognosis; weighted gene coexpression network analysis
• Online Access: https://doi.org/10.1002/2211-5463.12983

Liver cancer is a common malignant tumor with poor prognosis. Due to the lack of specific clinical manifestations at early stages, most patients are already at advanced stages of the disease by the time of diagnosis. Identification of novel biomarkers for liver cancer may thus enable earlier detection, improving outcome. MicroRNAs (miRNAs) are small endogenous noncoding RNAs of 18–22 nucleotides in length, which have a regulatory role in the expression of target proteins. Increased evidence suggests that miRNAs are abnormally expressed in a variety of cancer malignancies. Here, we combined RNA sequencing data and clinical information from The Cancer Genome Atlas Liver Hepatocellular Carcinoma database for weighted gene coexpression network analysis to identify potential miRNA prognostic biomarkers. We constructed nine coexpression modules, allowing us to identify that miR‐105‐5p, miR‐767‐5p, miR‐1266‐5p, miR‐4746‐5p, miR‐500a‐3p, miR‐1180‐3p and miR‐139‐5p are significantly associated with liver cancer prognosis. We found that these miRNAs exhibit significant association with prognosis of patients with liver cancer and confirmed the expression of these miRNAs in liver cancer tissues. Multivariate Cox regression analysis showed that miR‐105‐5p and miR‐139‐5p may be considered as independent factors. In summary, here we report that seven miRNAs have potential value as prognostic biomarkers of liver cancer.