Deep learning-based method for mapping critical receptors on cancer cells. Using digital images of biopsies taken from breast cancer patients, the new technology is expected to significantly improve personalized cancer treatments.
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. The Technion researchers’ conceptual innovation is in extracting molecular information from the cell shape and the environment (the morphology of the tissue) as reflected in the H&E scans. The study examined more than 20,000 scans from 5,356 breast cancer patients. Using the new technology, the researchers were able to map estrogen and progesterone receptors, among other molecular biomarkers, from the scans alone and based on cell morphology.
- Showing that cancer has a unique signature in tissue morphology and that computerized mapping of this morphology can provide tremendously relevant information on tumor characteristics
Applications and Opportunities
- Decision making tool for doctors for cancer diagnosis and better treatment