Epigenetic therapy is emerging as a potential therapy for solid tumors. To investigate its mechanism of action, we performed integrative expression and methylation analysis of 63 cancer cell lines (breast, colorectal, and ovarian) after treatment with the DNA methyltransferase inhibitor 5-azacitidine (AZA). Gene Set Enrichment Analysis demonstrated significant enrichment for immunomodulatory pathways in all three cancers (14.4-31.3%) including interferon signaling, antigen processing and presentation, and cytokines/chemokines. Strong upregulation of cancer testis antigens was also observed. An AZA IMmune gene set (AIMs) derived from the union of these immunomodulatory pathway genes classified primary tumors from all three types, into “high” and “low” AIM gene expression subsets in tumor expression data from both TCGA and GEO. Samples from selected patient biopsies showed upregulation of AIM genes after treatment with epigenetic therapy. These results point to a broad immune stimulatory role for DNA demethylating drugs in multiple cancers.
Summary: We here present BioCircos.js, an interactive and lightweight JavaScript library especially for biological data interactive visualization. BioCircos.js facilitates the development of web-based applications for circular visualization of various biological data, such as genomic features, genetic variations, gene expression and biomolecular interactions. Availability and implementation: BioCircos.js and its manual are freely available online at http://bioinfo.ibp.ac.cn/biocircos/. Contact:rschen@ibp.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.
Despite the fact that a large quantity of noncoding RNAs (ncRNAs) have been identified, their functions remain unclear. To enable researchers to have a better understanding of ncRNAs’ functions, we updated the NPInter database to version 3.0, which contains experimentally verified interactions between ncRNAs (excluding tRNAs and rRNAs), especially long noncoding RNAs (lncRNAs) and other biomolecules (proteins, mRNAs, miRNAs and genomic DNAs). In NPInter v3.0, interactions pertaining to ncRNAs are not only manually curated from scientific literature but also curated from high-throughput technologies. In addition, we also curated lncRNA–miRNA interactions from in silico predictions supported by AGO CLIP-seq data. When compared with NPInter v2.0, the interactions are more informative (with additional information on tissues or cell lines, binding sites, conservation, co-expression values and other features) and more organized (with divisions on data sets by data sources, tissues or cell lines, experiments and other criteria). NPInter v3.0 expands the data set to 491,416 interactions in 188 tissues (or cell lines) from 68 kinds of experimental technologies. NPInter v3.0 also improves the user interface and adds new web services, including a local UCSC Genome Browser to visualize binding sites. Additionally, NPInter v3.0 defined a high-confidence set of interactions and predicted the functions of lncRNAs in human and mouse based on the interactions curated in the database. NPInter v3.0 is available at http://www.bioinfo.org/NPInter/. Database URL: http://www.bioinfo.org/NPInter/