A Combined Bioinformatics and Literature Based Approach for Identification of Long Non-coding RNAs That Modulate Vitamin D Receptor Signaling in Breast Cancer.

BACKGROUND: Long non-coding RNAs (lncRNAs) as an important fraction of human transcriptome have been shown to exert fundamental role in regulation of signaling pathways implicated in carcinogenesis. Among them is vitamin D receptor (VDR) signaling whose participation in various cancers including breast cancer (BC) is evident. In spite of the presence of several evidences for participation of lncRNAs as well as VDR signaling in BC pathogenesis, no comprehensive study has evaluated the link between lncRNA dysregulation and VDR signaling in BC.

AIM: To introduce a bioinformatics approach for identification of lncRNAs that modulate VDR signaling in BC. This approach includes co-expression analysis, in silico identification of lncRNAs that target VDR and literature search.

CONCLUSIONS: Tens of lncRNAs are predicted to affect VDR signaling. Among them are some lncRNAs such as MALAT1 which has prominent role in BC pathogenesis. Identification of the lncRNAs that influence VDR gene expression is possible through in silico analysis. Considering the prominent role of VDR in BC pathogenesis as well as availability of VDR modulating agents, evaluation of VDR signaling pathway and related networks are of practical significance and bioinformatics tools are expected to facilitate such action. Key words: vitamin D receptor - long non-coding RNAs - co-expression - bioinformatics - calcitriol receptor - computational biology.