Technion researchers have developed a deep learning method for mapping critical receptors on cancer cells.
We have succeeded in showing that cancer has a unique signature in tissue morphology.
-Prof. Ron Kimmel
With over 20,000 scans from 5,356 breast cancer patients, Technion researchers have applied a groundbreaking method to map estrogen and progesterone receptors on cells. The research has implications for the treatment of all kinds of cancers.
“Computerized mapping of this morphology can give us tremendously relevant information on tumor characteristics,” said Prof. Ron Kimmel, of the Faculty of Computer Science. “In the first phase, we believe it will be a tool to help doctors make decisions and will later be developed as a real clinical tool.”
The technology extracts molecular information from biopsy images that underwent hematoxylin and eosin (H&E) staining. H&E is a common dye used to test tissue taken in a biopsy. The staining allows the pathologist to identify the type of cancer and its severity in the tissue under the microscope. But staining alone does not allow the identification of characteristics that are crucial in determining the appropriate treatment.
These include the molecular profile of the tumor, its biological pathways, the genetic code of the cancer cells, and the common receptors on the cell membrane. The mapping of receptors on the cell membrane is particularly relevant to personalized medicine, since it enables matching cancer patients with the treatment that will block the receptors and inhibit the development of the tumor.
“A human pathologist cannot infer the tumor features from its shape because of the sheer number of variables. The good news is that artificial intelligence technologies, and especially deep learning, are capable of doing so. The computer, unlike even the most skilled pathologist, can characterize the cancer with a complex analysis of its morphology,” says Prof. Kimmel.
Published in the prestigious JAMA journal, the research was conducted by doctoral students Gil Shamai and Ron Slossberg and Prof. Ron Kimmel of the Faculty of Computer Science, in collaboration with Dr. Yoav Binenbaum of Ichilov Hospital and Prof. Ziv Gil of Rambam Health Care Campus.
The research was supported by the Ministry of Science and Technology, the National Science Foundation, the Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering, and Schmidt Futures.
