LongTx · Targeting long non-coding RNAs for novel treatment strategies in vascular diseases

The perception that RNAs are passive carriers of genetic information has been overturned. Due to the diverse targeting abilities and extensive research in RNA modification and delivery systems, nucleic acid-based therapies have emerged as suitable treatment options for many diseases. Targeting RNAs offers opportunities to modulate numerous cellular processes, including those linked to the large portion of ‘undruggable’ proteins. Currently approved protein-targeted therapies interact with <700 gene products, meaning that only 0.05% of the human genome is presently utilized for treatment. On the contrary, a large fraction of the human genome (>70%) is transcribed into non-coding RNAs. Humans produce more than 15.000 long non-coding RNAs (lncRNA), with a substantial subset of these likely being ‘druggable’ via RNA interference strategies, such as antisense oligonucleotides and siRNAs. In my current LongTx proposal, we aim at identifying suitable lncRNAs with relevance to vascular disease development and progression. To be successful, we made sure that we have identified suitable lncRNAs by profiling diseased human tissue from patients with carotid artery disease and stroke, as well as abdominal aortic aneurysms. Both diseases are currently being treated with suboptimal surgical interventions, and the growing affected patient population would tremendously benefit from novel treatment strategies that enable stabilization of advanced vulnerable atherosclerotic lesions, and also limit the risk for acute aortic ruptures and dissections. The two lncRNAs we have identified in preliminary studies using single-cell, bulk, and spatial transcriptomics are called CRNDE and NKILA. We propose to study these lncRNAs in disease-relevant preclinical in vitro (arteries-on-chips) and in vivo (genetically mutated mice and mini-pigs) models, with a strong focus on novel local delivery concepts for antisense oligonucleotide inhibitors that site-specifically target both transcripts.