In
the fight against cancer, knowing the enemy’s exact identity is crucial
for diagnosis and treatment, especially in metastatic cancers, those
that spread between organs and tissues. Now chemists led by Vincent
Rotello at the University of Massachusetts Amherst have developed a
rapid, sensitive way to detect microscopic levels of many different
metastatic cell types in living tissue. Findings appear in the current
issue of the journal ACS Nano.

In
a pre-clinical non-small-cell lung cancer metastasis model in mice
developed by Frank Jirik and colleagues at the University of Calgary,
Rotello’s team at UMass Amherst use a sensor array system of gold
nanoparticles and proteins to “smell” different cancer types in much the
same way our noses identify and remember different odors. The new work
builds on Rotello and colleagues’ earlier development of a “chemical
nose” array of nanoparticles and polymers able to differentiate between
normal cells and cancerous ones.

Rotello
explains, “With this tool, we can now actually detect and identify
metastasized tumor cells in living animal tissue rapidly and effectively
using the ‘nose’ strategy. We were the first group to use this approach
in cells, which is relatively straightforward. Now we’ve done it in
tissues and organs, which are very much more complex. With this advance,
we’re much closer to the promise of a general diagnostic test.”

Until
now the standard method for precisely identifying cancer cells used a
biological receptor approach, a protein binding to a cancer cell wall.
Its major drawback is that one must know the appropriate receptor
beforehand. Rotello and colleagues’ breakthrough is to use an array of
gold nanoparticle sensors plus green fluorescent protein (GFP) that
activates in response to patterns in the proteins found in cancer cells
within minutes, assigning a unique signature to each cancer.

The
chemist says, “Smell ‘A’ generates a pattern in the nose, a unique set
of activated receptors, and these are different for every smell we
encounter. Smell ‘B’ has a different pattern. Your brain will instantly
recognize each, even if the only time you ever smelled it was 40 years
ago. In the same way, we can tune or teach our nanoparticle array to
recognize many healthy tissues, so it can immediately recognize
something that’s even a little bit ‘off,’ that is, very subtly different
from normal. It’s like a ‘check engine’ light, and assigns a different
pattern to each ‘wrong’ tissue. The sensitivity is exquisite, and very
powerful.”

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 new sensor
array method in human tissue samples, the researchers say.

Source: University of Massachusetts Amherst