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April 3rd, 2025
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Pathology Department, Medical School, University of Valencia-INCLIVA-CIBERONC
cancer biology
biorxiv

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

Vieco-Marti, I.Open in Google Scholar•Lopez-Carrasco, A.Open in Google Scholar•Navarro, S.Open in Google Scholar•Granados-Aparici, S.Open in Google Scholar•Noguera, R.Open in Google Scholar

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.

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