Programmable proximal protein labeling of long non-coding RNAs in cancer

The human genome is estimated to contain approximately 20.000 to 25.000 genes, which accounts
for about 2% of the genomic DNA. Since the 1960s, the remaining 98% or non-coding DNA has
been referred to as “junk” DNA and was thought to have no molecular function in the cell.
Recently, however, it has been shown that this “junk” DNA has a prominent role in normal cellular
functioning. The bulk of “junk” DNA is being actively transcribed into long non-coding RNAs
(lncRNA). These lncRNAs exert their function through interaction with other molecules, and an
important mechanism underlying lncRNA function involves the interaction with proteins. Over the
last decennium, an increasing number of studies report the involvement of lncRNAs in human
diseases such as cancer. Due to their specific attributes, lncRNA-protein interactions are highly
suitable candidates as therapeutic targets. However, the study of lncRNA-protein interactions is
still in its infancy and robust methods to identify these proteins are still lacking. In this project
outline, we propose the development of a new and efficient method to identify lncRNA-interacting
proteins. In a second part, we will apply these methods on a set of cancer-specific lncRNAs. Finally,
we will elucidate and validate the molecular mechanisms behind the lncRNA in its relevant cancer
setting. At the end of this project, we expect to have a universal protein identification platform
that readily can be applied to any lncRNA.