Jul 21 2009
Using a "chemical nose" array of nanoparticles and polymers, researchers at the University of Massachusetts Amherst have developed a fundamentally new, more effective way to differentiate not only between healthy and cancerous cells but also between metastatic and nonmetastatic cancer cells. It is a tool that could revolutionize cancer detection and treatment, according to Vincent M. Rotello, Ph.D., M.Phil., and D. Joseph Jerry, Ph.D., M.S., the investigators who led the study.
Currently, detecting cancer via cell surface biomarkers has taken what is known as the "lock and key" approach. Drawbacks of this method include that foreknowledge of the biomarker is required. Also, as Dr. Rotello explained, a cancer cell often has the same biomarkers on its surface as a healthy cell but in different concentrations—a maddeningly small difference that can be difficult to detect. "You often don’t get a big signal for the presence of cancer," he noted. "It’s a subtle thing."
He added, "Our new method uses an array of sensors not only to recognize known cancer types but also to signal that abnormal cells are present. That is, the chemical nose can simply tell us something isn’t right, like a "check engine" indicator on one’s car, although it may never have encountered that type before." Furthermore, the chemical nose can be designed to alert doctors of the most invasive cancer types, those for which early treatment is crucial.
In blinded experiments using four human cancer cell lines (cervical, liver, testes, breast), as well as in three metastatic breast cell lines and normal cells, the new detection technique not only correctly indicated the presence of cancer cells in a sample but also identified primary cancer vs. metastatic disease. An article describing this new chemical nose method of cancer detection appears in the Proceedings of the National Academy of Sciences of the United States of America.
In additional experiments to rule out the possibility that the chemical nose had simply detected individual differences in cells from different donors, the researchers repeated the experiments in skin cells from three groups of cloned BALB/c mice: healthy animals, those with primary cancer, and those with metastatic disease. Once again, it worked. "This result is key," says Dr. Rotello. "It shows that we can differentiate among the three cell types in a single individual using the chemical nose approach."
The investigators designed the new detection system by combining three gold nanoparticles that have special affinity for the surface of chemically abnormal cells plus the polymer para-phenyleneethynylene (PPE). As the check-engine indicator, PPE fluoresces or glows when displaced from the nanoparticle surface.
By adding the PPE-gold nanoparticle construct to human cells incubating in wells on a culture plate, the researchers induced a response called "competitive binding." Cell surfaces bind the nanoparticles, displacing PPE from the surface. This turns on PPE’s fluorescent switch. Cells then are identified from the patterns generated by different particle-PPE systems.
Dr. Rotello says the chemical nose approach is so named because it works like a human nose, which is arrayed with hundreds of very selective chemical receptors. These bind with thousands of different chemicals in the air, some more strongly than others, in the endless combinations we encounter. The receptors report instantly to the brain, which recognizes patterns such as, for example, "french fries," or it creates a new smell pattern.
Chemical receptors in the nose and the brain’s pattern recognition skills together are incredibly sensitive at detecting subtly different combinations, Dr. Rotello noted. Like a human nose, the chemical version being developed for use in cancer also remembers the patterns experienced, even if only once, and creates a new one when needed.
This work, which was supported in part by the National Cancer Institute, is detailed in the paper "Detection and differentiation of normal, cancerous, and metastatic cells using nanoparticle-polymer sensor arrays." Investigators from the Georgia Institute of Technology also participated in this study. An abstract of the paper is available at the journal’s Web site.