Even the new revolution of single-cell sequencing leaves researchers with no context as to what cells were adjacent to the individual diseased cells they analyze.
"The resolution of MRI can't 'see' individual cell differences. But we were able to find evidence for correlations between genetic and cellular changes. We can see the consequences of specific genetic changes in brain cancer tumors that show up on a medical image," Dr. Berens said.
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This type of information could potentially help surgeons decide how much tissue must be removed to extract the cancer, the dosage and frequency a radiologist might use to treat the cancer, and what specific drugs might be best suited for each patient at differing points in time.
It could help answer other questions. For example: How is the tumor infiltrating adjacent tissue? How is it interfering with the body's immune system? How is it generating new adjacent blood vessels to obtain a surge of nutrients to keep it growing?
Using fluorescent tags to identify biomarkers
To help answer these questions, TGen's partnering investigators at General Electric Global Research Center deployed a novel imaging tool, which they developed over the past decade together with GE Healthcare, called "Cell DIVE™," or Multiplexed immunofluorescence imaging (MxIF), which is used to repeatedly stain tumor samples with antibodies attached to fluorescent dyes. In an iterative process of staining and imaging, the method allows cell level quantification of over 60 cell biomarkers in a single sample.
In this study, researchers analyzed more than 100,000 cells in brain tumor cases, using MxIF to uncover differences between two types of brain tumors based on mutations in the gene IDH1.
"Using this platform, we can visualize and analyze various cell types and cell states present in the tumor tissue as well as how they interact with each other and their microenvironment," said Dr. Anup Sood, a senior scientist at GE Global Research, and also a lead author of the study.
"Visualizing the microenvironment, especially, is key to understanding tumor behavior and the response to therapy, which has been difficult to analyze with conventional methods," Dr. Sood said. "The platform's unique capabilities, which allows deeper insights into cancer, were the result of a more than decade's long effort by a multidisciplinary team of more than 50 chemists, biologists, software and hardware engineers, computer scientists, statisticians with key industrial and academic partners."
