Long non-coding RNAs (lncRNAs) have been proven to be implicated in the pathogenesis of various diseases. Multiple studies have demonstrated that small molecule drugs can modify lncRNA expression, which suggests a promising therapy for human diseases. Here, we constructed a comprehensive query and analytical platform D-lnc to dissect the influence of drugs on lncRNA expression. Firstly, we manually curated the experimentally validated regulations of drugs on lncRNA expression and recorded 7,825 entries between 59 drugs and 7,538 lncRNAs across five species from nearly 1,000 published papers. Secondly, we comprehensively screened the Connectivity Map (cMap) and the Gene Expression Omnibus (GEO) databases to obtain the drug-perturbed gene expression profiles. Through probe re-annotation of microarray data, we identified 19,946 putative associations between 1,279 drugs and 129 lncRNAs in cMap and 36,210 entries between 115 drugs and 2,360 lncRNAs in GEO. Finally, we developed an online analytical platform to predict the potential acting drugs or modified lncRNAs based on user input lncRNA sequence or drug structure through computing the similarities of lncRNA sequences or drug structures. In a word, D-lnc provides a comprehensive platform to detect the modification of drugs on lncRNA expression, which would facilitate the development of lncRNA-targeted therapeutics. D-lnc is freely available at http://www.jianglab.cn/D-lnc/ .
Keywords: Drug; IncRNA-targeted therapy; gene expression profile; lncRNA; probe re-annotation.