DANEELpath open source digital analysis tools for histopathological research in neuroblastoma models.

Area of Science:

• Biomedical Sciences
• Bioimage Analysis
• Cancer Research

Background:

• The tumor microenvironment's extracellular matrix (ECM) influences cancer progression and therapeutic resistance.
• Vitronectin (VN), an ECM glycoprotein, is linked to aggressive neuroblastoma (NB).
• Three-dimensional (3D) hydrogels offer biomimetic models for studying ECM roles and potential mechano-drugs like cilengitide.

Purpose of the Study:

• To develop an advanced image analysis pipeline for studying 3D-cultured neuroblastoma cells.
• To provide a versatile tool for investigating the extracellular matrix's role in cancer progression.
• To facilitate the study of mechano-drugs targeting VN in high-risk neuroblastoma.

Main Methods:

• Development of DANEELpath, an open-source bioimage analysis toolkit.
• Integration of deep learning for cell segmentation and spatial feature extraction.
• Application of mathematical morphology pipelines for individual and cluster cell analysis within whole-slide images.

Main Results:

• DANEELpath enables detailed analysis of 3D-grown neuroblastoma cell dynamics.
• The toolkit facilitates the extraction of spatial features crucial for understanding tumor behavior.
• Demonstrated versatility of DANEELpath for diverse biological questions and model systems.

Conclusions:

• DANEELpath is a valuable open-source resource for bioimage analysis in cancer research.
• The toolkit can advance the understanding of ECM contributions to tumor aggressiveness and therapeutic resistance.
• DANEELpath has the potential to accelerate biomedical discovery across various research fields.