BEHAV3D Tumor Profiler to map heterogeneous cancer cell behavior in the tumor microenvironment
Journal Title
Elife
Abstract
Intravital microscopy (IVM) enables live imaging of animals at single-cell level, offering essential insights into cancer progression. This technique allows for the observation of single-cell behaviors within their natural 3D tissue environments, shedding light on how genetic and microenvironmental changes influence the complex dynamics of tumors. IVM generates highly complex datasets that often exceed the analytical capacity of traditional uni-parametric approaches, which can neglect single-cell heterogeneous in vivo behavior and limit insights into microenvironmental influences on cellular behavior. To overcome these limitations, we present BEHAV3D Tumor Profiler (BEHAV3D-TP), a computational framework that enables unbiased single-cell classification based on a range of morphological, environmental, and dynamic single-cell features. BEHAV3D-TP integrates with widely used 2D and 3D image processing pipelines, enabling researchers without advanced computational expertise to profile cancer and healthy cell dynamics in IVM data from mouse models. Here, we apply BEHAV3D-TP to study diffuse midline glioma (DMG), a highly aggressive pediatric brain tumor characterized by invasive progression. By extending BEHAV3D-TP to incorporate tumor microenvironment (TME) data from IVM or fixed correlative imaging, we demonstrate that distinct migratory behaviors of DMG cells are associated with specific TME components, including tumor-associated macrophages and vasculature. BEHAV3D-TP enhances the accessibility of computational tools for analyzing the complex behaviors of cancer cells and their interactions with the TME in IVM data.
Publisher
eLife
Keywords
*Tumor Microenvironment; Animals; Mice; *Intravital Microscopy/methods; Humans; *Glioma/pathology/diagnostic imaging; *Brain Neoplasms/pathology/diagnostic imaging; Imaging, Three-Dimensional/methods; *Single-Cell Analysis/methods; cancer biology; cell migration; computational biology; confocal microscopy; image analysis; mouse; systems biology
Research Division(s)
Cancer Biology and Stem Cells
PubMed ID
41091123
Publisher's Version
https://doi.org/0
Open Access at Publisher's Site
https://doi.org/10.7554/eLife.102097
Terms of Use/Rights Notice
Refer to copyright notice on published article.


Creation Date: 2025-10-20 01:57:47
Last Modified: 2025-10-20 01:57:58
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