For this work, the researchers took healthy tissue and mouse tumor samples and trained the nanoparticle-GFP sensor array to recognize them and the GFP to fluoresce in the presence of metastatic tissue. Metastases are differentiated from healthy tissue in a matter of minutes, providing a rapid and very general means of detecting and identifying cancer and potentially other diseases using minimally invasive microbiopsies.
"It's sensitive to really subtle differences," says Rotello. "Even though two cheeses may look the same, our noses can tell a nicely ripe one from a cheese that's a few days past tasting good. In the same way, once we train the sensor array we can identify whether a tissue sample is healthy or not and what kind of cancer it is with very high accuracy. The sensitivity is impressive from a sample of only about 2,000 cells, a microbiopsy that's less invasive for patients."
In addition to the high sensitivity, the authors point out, their sensor is able to differentiate between low (parental) and high (bone, adrenal, and ovary) metastases, as well as between site-specific cells such as breast, liver, lung and prostate cancers.
"Overall, this array-based sensing strategy presents the prospect of unbiased phenotype screening of tissue states arising from genetic variations and differentiation state." Their next step will be to test the ne
|Contact: Janet Lathrop|
University of Massachusetts at Amherst