Researchers led by Tarun Kapoor at The Rockefeller University, in collaboration with Olivier Elemento at Weill Cornell Medical College, have hit on a new method for determining a drug’s molecular target that takes the guesswork out of the equation. The approach makes use of RNA sequencing and advances in data processing technologies to examine all of the differences between a drug-resistant cell and a normal cell and pinpoint the change most likely to cause resistance, which may suggest the drug’s target.
“Knowing a drug’s target can give us insight into why someone might develop resistance to the drug, and can help scientists discover other diseases that the drug may treat,” says Sarah Wacker, a former graduate student in Kapoor’s Laboratory of Chemistry and Cell Biology and first author in the study, which was recently published in Nature Chemical Biology. “It can also be helpful in improving the efficacy of a drug during the drug development process.”
Drug-resistant cells are used as one method for determining where a drug works in the body. If an organism 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 is involved, they can determine if it carries a mutation and infer 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 relies on trial and error. It makes for a biased experiment, because there are other potential molecular targets that aren’t being tested.
Enter RNA sequencing. It’s a technology that reads a cell’s RNA — the molecules that direct the synthesis of proteins. Using the sequencing technique, Kapoor and colleagues were able to look at all of the potential receptors and narrow down the possibilities, ultimately identifying the one most likely to be the binding site of the 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.
“RNA sequencing is a fairly recent technology and it’s continuously advancing, so it’s becoming cheaper to get more data for less money,” says Wacker.
The scientists looked at two cytotoxic anticancer drugs, one of which was BI 2536, which was 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 resisted the drug and located mutations in those cells’ RNA. The mutations 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.
“Our method is an improvement over other target identification strategies because it lets us establish a genetic proof of a target in human cells in an unbiased manner,” says Wacker.
In future research, the Kapoor laboratory will examine a drug for which no target site is established, testing the strength of their method with complete objectivity.
|Nature Chemical Biology 8: 235–237 (February 12, 2012)
Using transcriptome sequencing to identify mechanisms of drug action and resistance
Sarah A. Wacker, Benjamin R. Houghtaling, Olivier Elemento and Tarun M. Kapoor