Researchers have long lacked an approach to determine exactly how a drug works in human cells — until now.
A team of researchers from Weill Cornell Medical College and The Rockefeller University has pioneered a new method for determining exactly how a drug works, including identifying a drug's mechanism of action and its molecular targets. But how?
"We have developed a groundbreaking genomic technique method to identify the target of a drug in human cells by examining drug resistance mechanisms first," said the study's senior author Dr. Olivier Elemento, an assistant professor in the Department of Physiology and Biophysics and assistant professor of computational genomics in the Institute for Computational at Weill Cornell Medical College. "This novel method allows us to show exactly how drugs work in human cells and the mechanisms by which cells acquire resistance to these drugs."
The study's new approach, highlighted in the journal Nature Chemical Biology, makes use of high-throughput RNA sequencing and computational biology techniques to examine all of the differences between drug-resistant cells and normal cells. This helped the study researchers pinpoint the mutations most likely to cause drug resistance, which then in turn suggest the drug's target.
Drug-resistant cells are used in this approach to determine how a drug works. The underlying idea is that if a cell is resistant to a drug, it's often because a mutation has occurred that affects the drug's binding site on its target — a protein. In current practice, if researchers suspect which protein might be the drug's target, they can determine if the gene that codes for the protein carries a mutation and confirm that that protein is the drug's target. The problem is there are thousands of possibilities when it comes to which protein has the mutation, so the method would rely on trial and error. This makes for a biased analysis, because there are other potential molecular targets that aren't being tested.
Enter high-throughput RNA sequencing. It's a technology that reads a cell's RNA — the molecules that direct the synthesis of proteins. Using this sequencing technique, the research team was able to look at all of the expressed genes in drug-resistant cells, look for mutations in each of these genes and narrow down the possibilities, ultimately identifying the gene most likely to encode the target of the studied drug. This new method is made possible thanks to advances in technology and bioinformatics, a new field that applies computer science to biology — in this case, reading and interpreting the RNA data.
In the study, the scientists looked at two cytotoxic anticancer drugs, one of which was BI 2536, a drug recently tested in clinical trials. The drug has a generally-accepted molecular target, the PLK1 protein, and the researchers wanted to test their new method by seeing if it came to the same conclusion. They used RNA sequencing on human cells that were resistant to the drug and located mutations in those cells' RNA. Mutations from distinct and independent resistant cells were compared, and one emerged as common among more than one of the resistant cells: PLK1.
Next, the researchers created cells with the PLK1 mutation and compared them to cells without it when put in the presence of the anti-cancer drug. As they suspected, only the cells with the mutation were drug-resistant, suggesting that the PLK1 protein is the major physiological target of BI 2536. The researchers then went on to show that their approach also accurately re-discovered the target and binding pocket of bortezomib, an FDA-approved drug used to treat multiple myeloma and mantle cell lymphoma.
"Our genomic approach, combining RNA sequencing, bioinformatics, cell biology and biochemistry accurately identified the known targets of the two anti-cancer molecules BI 2536 and bortezomib," said Dr. Elemento. "This is extremely important since most patients treated with targeted anticancer drugs develop resistance at one point. Being able to predict ahead of time how and why patients will become resistant to a drug would help guide the development of future therapeutic strategies to delay or eliminate resistance."
According to researchers, the new approach has the potential to be applied wider for the identification of mechanisms of action for all drugs in human cells, their direct targets and locating their resistance mutations.
"The research has the potential to be an extremely valuable component of the drug development process especially in pre-clinical phases. Plus, knowledge gained using our novel approach may guide improvement in drug efficacy and decrease toxic side effects in the future," said Dr. Elemento.
This study was a collaboration between Dr. Elemento's lab at Weill Cornell and the lab of Dr. Tarun Kapoor's at The Rockefeller University.