Bioinformatic analysis and prediction of the function and regulatory network of long non-coding RNAs in hepatocellular carcinoma.

Bioinformatic analysis and prediction of the function and regulatory network of long non-coding RNAs in hepatocellular carcinoma. Oncol Lett. 2018 May;15(5):7783-7793 Authors: Cao MR, Han ZP, Liu JM, Li YG, Lv YB, Zhou JB, He JH Abstract Computational analysis and bioinformatics have significantly advanced the ability of researchers to process and analyze biological data. Molecular data from human and model organisms may facilitate drug target validation and identification of biomarkers with increased predictive accuracy. The aim of the present study was to investigate the function of long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) using online databases, and to predict their regulatory mechanism. HCC-associated lncRNAs, their downstream transcription factors and microRNAs (miRNAs/miRs), as well as the HCC-associated target genes, were identified using online databases. HCC-associated lncRNAs, including HOX antisense intergenic RNA (HOTAIR) and metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) were selected based on established databases of lncRNAs. The interaction between the HCC-associated lncRNAs and miRNAs (hsa-miR-1, hsa-miR-20a-5p) was predicted using starBase2.0. Signal transducer and activator of transcription 1, hepatocyte nuclear factor 4α (HNF4A), octamer-binding transcription factor 4, Nanog homeobox (NANOG), caudal type homeobox 2 (CDX2), DEAD-box helicase 5, brahma-related gene 1, MYC-ass...
Source: Oncology Letters - Category: Cancer & Oncology Tags: Oncol Lett Source Type: research