Identification of potential hub-lncRNAs in ischemic stroke based on Subpathway-LNCE method

Ischemic stroke is a devastating condition with a high burden of neurological disability and death. The aim of this study was to explore the potential long noncoding RNA (lncRNA) biomarkers underlying the mechanism of stroke. The Subpathway-LNCE method, which was specifically designed to identify lncRNAs competitively regulated functions in diseases, was applied in ischemic stroke dataset to identify ischemic-stroke-associated dysfunctional subpathway that regulated by lncRNAs. At first, based on the shared microRNA (miRNA) between miRNA-messenger RNA (mRNA) and lncRNA-miRNA interactions, lncRNA-mRNA interactions were constructed. Then, the transcription profiling of 18 631 genes was downloaded from Array Express database and was preprocessed, including normalization and gene expression difference (DEG) analysis, to identify candidate differential pathways using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. Next, the pathway-lncRNA-mRNA networks were constructed by linking lncRNAs to candidate differential pathways. At last, there were 11 lncRNAs were identified in the top three subpathways as hub-lncRNAs totally, including LINC00240, LINC00472, LINC00265, LINC00473, MIR497HG, NEXN-AS1, HCG17, MEG8, EPB41L4A-AS1, SNHG7, and BCYRN1, five of which were validated to be very effective stroke biomarker by RT-PCR. In conclusion, we applied Subpathway-LNCE method and experimental verification to identify five lncRNAs, including LINC00265, LINC00473, NEXN-AS1, HCG17, and MEG8, which were considered as important lncRNAs biomarkers in ischemic stroke.