Lung cancer intravasation-on-a-chip: Visualization and machine learning-assisted automatic quantification.

ABSTRACT: During lung cancer metastasis, tumor cells undergo epithelial-to-mesenchymal transition (EMT), enabling them to intravasate through the vascular barrier and enter the circulation before colonizing secondary sites. Here, a human in vitro microphysiological model of EMT-driven lung cancer intravasation-on-a-chip was developed and coupled with machine learning (ML)-assisted automatic identification and quantification of intravasation events. A robust EMT-inducing cocktail (EMT-IC) was formulated by augmenting macrophage-conditioned medium with transforming growth factor-β1. When introduced into microvascular networks (MVNs) in microfluidic devices, EMT-IC did not affect MVN stability and physiologically relevant barrier functions. To model lung cancer intravasation on-a-chip, EMT-IC wa

SUBMITTER: Wong CWT 

PROVIDER: S-EPMC12269418 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature