Regulated cell death modalities such as apoptosis and necroptosis play an important role in regulating different cellular processes. Currently, regulated cell death is identified using the golden standard techniques such as fluorescence microscopy and flow cytometry. However, they require fluorescent labels, which are potentially phototoxic. Therefore, there is a need for the development of new label-free methods. In this work, we apply Digital Holographic Microscopy (DHM) coupled with a deep learning algorithm to distinguish between alive, apoptotic and necroptotic cells in murine cancer cells. This method is solely based on label-free quantitative phase images, where the phase delay of light by cells is quantified and is used to calculate their topography. We show that a combination of label-free DHM in a high-throughput set-up (~10,000 cells per condition) can discriminate between apoptosis, necroptosis and alive cells in the L929sAhFas cell line with a precision of over 85%. To the best of our knowledge, this is the first time deep learning in the form of convolutional neural networks is applied to distinguish—with a high accuracy—apoptosis and necroptosis and alive cancer cells from each other in a label-free manner. It is expected that the approach described here will have a profound impact on research in regulated cell death, biomedicine and the field of (cancer) cell biology in general.

Regulated cell death (RCD) has a fundamental role in development, pathology, and tissue homeostasis. In order to understand the RCD mechanisms, it is essential to follow these processes in real time. Here, atomic force microscopy (AFM) is applied to morphologically and mechanically characterize four RCD modalities (intrinsic and extrinsic apoptosis, necroptosis, and ferroptosis) in murine tumor cell lines. The nano-topographical analysis revealed a distinct surface morphology in case of necroptosis, ∼ 200 nm membrane disruptions are observed. Using mechanical measurements, it is possible to detect the early onset of RCD. Combined elasticity and microrheology analysis allowed for a clear distinction between apoptotic and regulated necrotic cell death. Finally, immunofluorescence analysis of the cytoskeleton structure during the RCD processes confirm the measured mechanical changes. The results of this study not only demonstrate the possibility of early real-time cell death detection but also reveal important differences in the cytoskeletal dynamics between multiple RCD modalities.