Cancer in 3-D,
One Cell at a Time
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BERKELEY, CA — Hoping to track cancer as it spreads cell-by-cell through the body, Lawrence Berkeley National Laboratory researchers have developed a way to shape high-resolution microscopy images into three-dimensional renditions of tissue such as mammary ducts.
The result is a microscopic look at the molecular and genetic underpinnings of cancer on a glandular scale. The system, which couples a computer-assisted microscope to powerful visualization programs, stacks two-dimensional microscopy images into a lifelike structure packed with genes, hormone receptors, and proteins. It could ultimately portray how cancer spreads from a few anomalous cells to millions of cancerous cells radiating throughout a gland. It could also map the cellular degeneration of diseases such as Alzheimer's and Parkinson's as they ravage surrounding tissue.
"In the future, we could analyze any three-dimensional tissue sample for its genetic and cellular activity," says Carlos Ortiz de Solorzano, a staff scientist in Berkeley Lab's Life Sciences Division who helped develop the technique. "We'll more easily relate morphology with molecular events."
In conventional microscopy, tissue is sectioned into ultra-thin segments, and stained with a chemical marker that highlights a genetic phenomenon indicative of a specific pathology. To image a type of breast cancer called ductal carcinoma in situ, for example, breast tissue is stained with a marker that only adheres to the amplified form of a gene called Her2 -- an indication of cancer.
Researchers then search for this chemical marker under a microscope, which allows them to see which cells in each two-dimensional section are potentially cancerous. But if they want a broader picture, such as the extent to which cancerous cells have wormed throughout the tissue, they must mentally stack several microscopy images together. Complicating matters, tissue samples are often stained with a palette of chemical markers to accentuate different cells. Mentally keeping track of each color in a series of microscopy images is difficult. Now, a computer does it for them.
"We've streamlined the acquisition, reconstruction, and analysis of large tissue samples," says Ortiz de Solorzano. "It's far better than mentally reconstructing images, which is nearly impossible."
There are other ways to map the three-dimensional spread of disease, such as the medical imaging technologies magnetic resonance imaging and positron emission tomography. Although highly accurate, and the only way to non-invasively image disease in patients, these techniques only capture blood flow and metabolic changes that indicate disease. Changes to individual cells go unnoticed. Another method, called confocal laser scanning microscopy, can track the genetic activity of individual cells, but only in relatively thin tissue samples. Berkeley Lab's system encompasses cellular resolution, three-dimensional reconstruction, and multicolor display of thick tissue in a single, computer-automated process.
So far, Ortiz de Solorzano's team has used the technique to map the distribution of amplified Her2 genes in a tissue biopsy of ductal carcinoma in situ, which invades mammary ducts. They're searching for cells with pronounced Her2 genes that somehow sprout far from the tumor in otherwise healthy tissue. Finding these isolated, abnormal cells, and determining the pattern by which they spread, could offer the earliest indication that a tumor may be invasive.
"The question is: is the tumor emitting some kind of field effect and influencing cells far way, or has a cell broken off from the main tumor?" Ortiz de Solorzano says.
To answer this question, researchers must cast a wide net. The carcinoma must be microscopically imaged, as well as the surrounding tissue in all directions. The trick is to capture a breast tumor and these lone, abnormal cells in the same image, which could offer a window into their poorly understood relationship. Unfortunately, conventional microscopy only images a two-dimensional slice of tissue, and only the luckiest slice harbors both carcinoma and abnormal cell.
"If cells have broken from the main tumor and invaded the ducts, there's a good chance you won't capture them," Ortiz de Solorzano says. "You're ignoring the tissue's 3-D structure."
But if a series of images are digitally stacked into a gland-size shape, the carcinoma and its widely scattered orbit of abnormal cells takes shape. In this manner, a computer, not a brain, does the heavy work and makes sense of cancer's heterogeneous sprawl of cells.
Ortiz de Solorzano's team is also using their technique to model the activation of estrogen and progesterone hormone receptors throughout the development of a mammary gland. They're examining chemically labeled mouse tissue samples at several week intervals, and asking key questions: Do progesterone-positive cells usually appear next to estrogen-positive cells? Do they appear first in large ducts, or small ducts? They hope to learn how these receptors, which are critical to normal breast tissue function, are distributed throughout tissue. And they're interested in how these receptors express differently in cancerous tissue. With conventional microscopy, such an inquiry requires taking flat sections and extrapolating how they appear in three dimensions -- possible, but very time consuming.
"With our technique, however, we can more quickly look at receptor development in entire glands," says Ortiz de Solorzano. "And cancer is fundamentally a cellular and tissue disease, so it must be examined in three dimensions. The more quickly we can do this, the faster we'll understand it."
Their technique is described in the paper "A system for combined three-dimensional morphological and molecular analysis of thick tissue specimens," which appeared in the December 15, 2002 issue of Microscopy Research and Technique. Computer scientists Enrique García Rodriguez and Arthur Jones, and graduate student Rodrigo Fernández-González, contributed to the research.
Berkeley Lab is a U.S. Department of Energy national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California.