Drug-discovery method shows promise against aggressive breast cancer
By Doug Bennett
Photo on right by Scott Wiseman: Beads coated with hundreds of thousands of drug-like molecules encoded with DNA barcodes are sorted with a laser. They were tested for their affinity to an RNA target involved in the progression of triple-negative breast cancer. Good hits are moved into a group for retrieval, study and further refinement for their potential as anti-cancer, RNA-modifying medications.
Gainesville, Florida - UF Scripps Biomedical Research scientist Matthew Disney, Ph.D. has found yet another groundbreaking approach to a problem that has long vexed scientists: How to cure diseases by targeting key RNA. Until now, RNA has been an elusive target for drug discovery. Discoveries made by Disney and his collaborators have rewritten that dogma.
The group’s recent discoveries have important, broader implications for possibly treating many now-incurable diseases. For now, most drugs work by targeting proteins from humans or infectious organisms. Developing the ability to modulate RNA, as Disney’s inventions do, potentially increases the number of diseases that can be targeted with pharmaceuticals.
By targeting RNA — the middleman between gene and protein — factors that cause disease never get built in the first place. Disney’s latest discovery capitalizes on work by his longtime collaborator, Brian Paegel, Ph.D., of the University of California, Irvine, to bring new efficiency to the drug-discovery process. Their approach makes it possible to screen hundreds of millions of drug-RNA interactions for effectiveness. The results were published recently in the Proceedings of the National Academy of Sciences.
The new findings were enabled by Paegel’s technique, which involves encoding small, drug-like molecules in DNA or using DNA-encoded “libraries” of compounds. These libraries allowed the researchers to use DNA sequencing to identify viable medicines that bind with RNA targets.
In recent proof-of-principle experiments involving triple-negative breast cancer RNA targets, Disney and his colleagues combined Paegel’s system with compounds discovered and built in Disney’s lab to screen hundreds of millions of drug-RNA interactions for effectiveness. Disney ultimately identified a highly potent inhibitor that stopped the cancer’s progression in preclinical models.
The findings show it is possible to substantially accelerate the drug discovery process. The technique opens new doors to treating diseases by targeting their RNA processes, said Disney, chair of the department of chemistry at UF Scripps.
Drug discovery is a time-consuming, tedious process. Scientists typically investigate one or a few targets at a time to determine if the respective drug and cell molecules bind correctly to treat disease. The new method leverages a simple-but-challenging concept: Every disease process is influenced by RNA. Targeting the right RNA with the right drug could represent a new route to a potential treatment or cure.
Disney and Paegel’s approach enables drug discovery to be done more quickly and on a massive scale. In the case of triple-negative breast cancer, it evaluated a library of more than 73,000 molecules, known as ligands, against some 4,000 RNA targets. In total, the screening parsed approximately 300 million interactions and ultimately identified numerous candidate drug-RNA pairs to target.
One of the newly discovered compounds potently and selectively inhibited the advance of triple-negative breast cancer by “reprogramming” genetic activity, the researchers found.
Triple-negative breast cancer accounts for only about 20% of all breast cancer cases but carries the highest mortality rate. It disproportionately affects younger and Black women in the United States, according to the American Cancer Society. Its name also belies its stubbornness: Triple-negative breast cancer cells lack crucial receptors that might otherwise allow hormonal and other treatments to work.
Disney likened the screening process to pulling a needle out of a 300 million-piece haystack.