DANEELpath: Open-source Digital analysis tools for histopathological research. Applications in NEuroblastoma modELs

ABSTRACT Despite the considerable expansion of bioimage analysis as a subfield of biomedical sciences, there is an ongoing need for comprehensive image analysis pipelines to address specific biological inquiries. In the tumor microenvironment, the extracellular matrix (ECM) plays a pivotal role in cancer progression, promoting tumor cell adaptability, intratumor heterogeneity, and therapeutic resistance. In neuroblastoma (NB), the ECM glycoprotein vitronectin (VN) has been associated with more aggressive tumors. Three-dimensional (3D) hydrogels are an emerging biomimetic tool with significant potential for studying the role of ECM elements and testing new mechano-drugs such as cilengitide (CLG), a potential therapeutic agent to treat high-risk (HR) NB due to its ability to inhibit VN activity in cells. To gain a more detailed understanding of the effects of VN and CLG in 3D-grown NB cells, we developed DANEELpath, an open-source image analysis toolkit. DANEELpath integrates deep learning techniques, specific segmentation of individual and cluster cells through mathematical morphology pipelines, and extraction of spatial features within whole-slide images. Thanks to its versatility, DANEELpath is adaptable to address different biological questions and has significant potential for use in a variety of research fields and model systems, which could help advance biomedical discovery.