Cancer is a difficult disease to treat because it's a personal disease. Each case is unique and based on a combination of environmental and genetic factors. Conventional chemotherapy employs treatment with one or more drugs, assuming that these medicines are able to both "diagnose" and "treat" the affected cells. Many of the side effects experienced by chemotherapy patients are due to the fact that the drugs they are taking aren't selective enough. For instance, taking a drug that targets fast-growing tumor cells frequently results in hair loss, because cells in the hair follicle are among some of the fastest growing in the body. When it comes down to it, these drugs get the diagnosis wrong.
But what if we had cancer treatments that worked more like a computer program, which can perform actions based on conditional statements? Then, a treatment would kill a cell if --and only if-- the cell had been diagnosed with a mutation. Only the defective cells would be destroyed, virtually eliminating unwanted side effects.
With support from the National Science Foundation (NSF), researchers at the California Institute of Technology have created conditional small RNA molecules to perform this task. Their strategy uses characteristics that are built into our DNA and RNA to separate the diagnosis and treatment steps.
"The molecules are able to detect a mutation within a cancer cell, and then change conformation to activate a therapeutic response in the cancer cell, while remaining inactive in cells that lack the cancer mutation," claims Niles Pierce, co-author of a recent study which appears in the September 6 issue of Proceedings of the National Academy of Sciences (PNAS).
This work is part of the Molecular Programming Project, funded by NSF's Directorate for Computer & Information Science & Engineering. One of the goals of the project is to increase understanding of how information can be stored and processed by
|Contact: Lisa Van Pay|
National Science Foundation