Work

DLBCL cells with ferroptosis morphology can be detected with a deep convolutional neural network

Year: 2024

Type: article

Abstract: It has been demonstrated that diffuse large B-cell lymphoma (DLBCL) is especially sensitive to ferroptosis. Currently, confirming the presence of ferroptosis requires flow cytometry, which is a time consuming and labor-intensive task. Blistering of the cell membrane has been shown to be a ferroptosis-specific morphological change. In this study we developed a deep convolutional neural network to detect the blistering of cell membrane. Buthionine sulfoximine treatment increased the percentage of blistering cells from 2 % to 38 % (p < 0.001) when glutathione was deprived from the culture media. Ferrostatin-1 treatment completely reversed the effect. Imidazole ketone erastin (IKE) and auranofin treatment increased blistering cells gradually in dose response manner from 5.4 % to 18.1 % (p < 0.05) and 6.1–50.1 % (p < 0.0001) respectively. We also tested malignant melanoma and breast cancer cell lines to confirm that the blistering phenomena can also be observed in adherent cell lines. We used fluorescence-activated cell sorting to measure the lipid peroxidation associated with ferroptosis and found a significant increase of bodiby-C11 oxidized mean compared to DMSO controls for IKE (345 vs 462, p < 0.01) and auranofin (345 vs 686.5, p < 0.05). • Cell wall blistering can be detected using with convolutional neural network based image detection model. • Cell wall blistering is associated with ferroptotic cell death. • AI-based detection enables high-throughput assays for screening drugs for ferroptotic activity.

Source: Biomedicine & Pharmacotherapy

DOI: 10.1016/j.biopha.2024.117785