Machine learning technique helps identify cancer cell types

Brown University researchers have developed a new image analysis technique to distinguish two key cancer cell types associated with tumor progression. The approach could help in pre-clinical screening of cancer drugs and shed light on a cellular metamorphosis that is associated with more malignant and drug-resistant cancers. The epithelial-mesenchymal transition, or EMT, is a process by which more docile epithelial cells transform into more aggressive mesenchymal cells. Tumors with higher numbers of mesenchymal cells are often more malignant and more resistant to drug therapies. The new technique combines microscopic imaging with a machine learning algorithm to better identify and distinguish between the two cell types in laboratory samples.