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Updated: May 21, 2025
Author Spotlight: Tracing the Ferroptotic Signatures and Cell Death Dynamics in Medulloblastoma for Advanced Therapeutics
Published on: March 15, 2024
Deep transfer learning approach for automated cell death classification reveals novel ferroptosis-inducing agents in
Paweł Stachura1,2,3,4, Zhe Lu1,3,4, Raphael M Kronberg2,5,6
1Department of Pediatric Oncology, Hematology and Clinical Immunology, Medical Faculty, Heinrich-Heine-University, Moorenstrasse 5, 40225, Düsseldorf, Germany.
Abstract:
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.
Insights
Researchers identified volasertib as a novel ferroptosis inducer for hematological malignancies. Deep transfer learning and high-throughput screening revealed its potential against B-cell acute lymphoblastic leukemia (B-ALL) in vitro and in vivo.
Area of Science:
- Oncology
- Cell Death Research
- Computational Biology
Background:
- Ferroptosis, a regulated cell death, shows promise for treating hematological cancers.
- Discovering novel ferroptosis-inducing drugs has been challenging.
Purpose of the Study:
- To identify novel ferroptosis-inducing therapeutics using deep transfer learning and high-throughput screening.
- To investigate the efficacy of volasertib in inducing ferroptosis in B-cell acute lymphoblastic leukemia (B-ALL).
Main Methods:
- Classified cell death modes using deep transfer learning (DTL) on microscopy images.
- Employed high-throughput pharmacological screening with automated live-cell imaging.
- Validated volasertib's ferroptosis-inducing effects in B-ALL cell lines and patient samples.
Main Results:
- Identified volasertib as a novel ferroptosis inducer.
- Demonstrated volasertib's sensitivity in specific B-ALL cell lines and primary patient samples.
- Observed upregulation of ferroptosis-related genes and delayed tumor growth in vivo.
Conclusions:
- DTL combined with automated imaging effectively screens for ferroptosis inducers.
- Volasertib exhibits therapeutic potential against B-ALL by inducing ferroptosis.
- This approach accelerates the discovery of novel anti-cancer agents.
