Researchers at Vanderbilt University have combined molecular imaging with mass spectrometry to improve their ability to identify and quantify the production of proteins in potentially cancerous tissue. By pinpointing the precise location of cells that are producing high levels of a protein thought to allow tumors to grow, the laser-based technique, matrix-assisted laser desorption ionization, is expected to lead to improvements in both the diagnosis and treatment of cancer.
While traditional mass spectrometry can generate a spectrum of proteins based on molecular weight or mass, imaging mass spectrometry takes this one step further by determining the location of specific proteins in tissue and creating molecular photographs of these proteins. The result is a chemically based means of imaging that shows the distribution of individual proteins and can distinguish between normal and disease states. The technique could one day benefit intraoperative assessment of the surgical margins of tumors, replacing conventional light microscopy.
“Mass spectrometry with a laser already exists commercially,” says Richard Caprioli, director of the Mass Spectrometry Research Center at Vanderbilt University School of Medicine (Nashville, TN). “But it is not made to do imaging. What we did was devise hardware and software that would allow you to take a piece of human or animal tissue and put it inside this instrument. Maintaining the integrity of the tissue is no easy trick.”
No easy trick indeed. A frozen tissue sample from a tumor is mounted on a stainless-steel plate, coated with a matrix solution (such as sinapinic acid), then dried, and introduced into the vacuum inlet of the mass spectrometer (the Voyager Elite DE, Applied Biosystems; Framingham, MA). The instrument is controlled by imaging software written at the Mass Spectrometry Research Center. Images are created from a raster over the surface of the sample with consecutive laser spots (25 mm in diameter). The 337-nm laser remains fixed, and the plate is moved to obtain the spots.
The tissue sample is riddled with tens of thousands of shots from the laser, one spot at a time; as the protein molecules fly off (each spot produces 200 to 300 protein signals), the spectrometer measures their respective molecular weights based upon the speed with which they travel through the time-of-flight analyzer. The spectrometer then locates each protein within this array of pixels. The computer software can then isolate a protein of a specific molecular weight and, within minutes, produce a color image of the location of a specific protein in the tissue.
“This is a new concept for using laser-based mass-spectrometry instrumentation. We produce an image one pixel at a time," Caprioli says. "The advantage is that each pixel has a wealth of information. We can look at our image in any one of the thousands of [protein] signals, and each signal represents a particular molecular weight. Everything a cell does is controlled by the proteins, and how they interact is critical to health and disease.”
Initially Caprioli and his colleagues are focusing on molecular analysis and imaging of peptides and proteins in brain tumors. Such analysis would be an important part of strategies designed to locate specific proteins that are more highly expressed in tumors, according to Caprioli. In early experiments, the Vanderbilt researchers looked at tumor-bearing tissues generated by subcutaneous implantation of human glioblastoma cells into the hind limb of a nude mouse. After tumors grew to about 1 cm in diameter, they were removed and frozen. Samples measuring 12 mm thick were cut and processed, then imaged in the modified mass spectrometer.
Using this approach, Caprioli and his colleagues were able to detect more than 150 different proteins in the tissue samples, many present in all parts of the tissue. But the proliferating areas of the tumor tissue contained many proteins that were expressed at higher levels than in the normal tissue.
In addition to brain tumors, Caprioli and his colleagues are using this technique to study prostate and colon cancer development and progression and are working with Applied Biosystems to take this technology out of the lab and eventually put it into the medical mainstream. But their biggest job is still ahead of them, Caprioli says.
“One image might have 30,000 pixels, and each pixel contains 100,000 data points. How does a human being sift through all this data?” he says. “The idea is to employ artificial intelligence and teach the computer to use the protein patterns to classify the tumors and develop molecular information for pathologists. And down the road after many hundreds of samples, the computers would learn, and we would be able to look at protein patterns and identify the kind of cancer and where it is located.”
Kathy Kincade, contributing editor, Laser Focus World
Source: Medical Laser Report, July 2001