English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

MicroRNAs (miRNAs) inhibit expression of target genes by binding to their RNA transcripts. It has been recently shown that RNA transcripts targeted by the same miRNA could “compete” for the miRNA molecules and thereby indirectly regulate each other. Experimental evidence has suggested that the aberration of such miRNA-mediated interaction between RNAs—called competing endogenous RNA (ceRNA) interaction—can play important roles in tumorigenesis. Given the difficulty of deciphering context-specific miRNA binding, and the existence of various gene regulatory factors such as DNA methylation and copy number alteration, inferring context-specific ceRNA interactions accurately is a computationally challenging task. Here we propose a computational method called Cancerin to identify cancer-associated ceRNA interactions. Cancerin incorporates DNA methylation, copy number alteration, gene and miRNA expression datasets to construct cancer-specific ceRNA networks. We applied Cancerin to three cancer datasets from the Cancer Genome Atlas (TCGA) project. Our results indicated that ceRNAs were enriched with cancer-related genes, and ceRNA modules in the inferred ceRNA networks were involved in cancer-associated biological processes. Using LINCS-L1000 shRNA-mediated gene knockdown experiment in breast cancer cell line to assess accuracy, Cancerin was able to predict expression outcome of ceRNA genes with high accuracy.

Cancerin: A computational pipeline to infer cancer-associated ceRNA interaction networks