Deep transfer learning approach for automated cell death classification reveals novel ferroptosis-inducing agents in subsets of B-ALL.

Ferroptosis is a recently described type of regulated necrotic cell death whose induction has anti-cancer therapeutic potential, especially in hematological malignancies. However, efforts to uncover novel ferroptosis-inducing therapeutics have been largely unsuccessful. In the current investigation, we classified brightfield microscopy images of tumor cells undergoing defined modes of cell death using deep transfer learning (DTL). The trained DTL network was subsequently combined with high-throughput pharmacological screening approaches using automated live cell imaging to identify novel ferroptosis-inducing functions of the polo-like kinase inhibitor volasertib. Secondary validation showed that subsets of B-cell acute lymphoblastic leukemia (B-ALL) cell lines, namely 697, NALM6, HAL01, REH and primary patient B-ALL samples were sensitive to ferroptosis induction by volasertib. This was accompanied by an upregulation of ferroptosis-related genes post-volasertib treatment in cell lines and patient samples. Importantly, using several leukemia models, we determined that volasertib delayed tumor growth and induced ferroptosis in vivo. Taken together, we have applied DTL to automated live-cell imaging in pharmacological screening to identify novel ferroptosis-inducing functions of a clinically relevant anti-cancer therapeutic.