Microfluidics-based, Functional Vascularized Cancer Intravasation-on-a-Chip Platform
Year: 2026
Type: dissertation
Abstract: Cancer metastasis remains the principal cause of cancer mortality, yet how tumor cells negotiate vascular barriers under physiological flow and mechanical constraints is incompletely understood. This thesis develops and applies microfluidic, vascularized cancer-on-chip platforms, termed INVADE, that engineer dynamic vascular interfaces and tunable extracellular matrices to interrogate key steps of the metastatic cascade. First, we show that endothelial remodeling under shear critically governs tumor–endothelium encounters. Using an endothelialized, perfused microchannel, we demonstrate that shear-dependent vascular dynamics and junctional reorganization determine how tumor spheroids dock, spread, and penetrate the endothelium. Second, we establish an integrated intravasation platform that resolves bidirectional tumor–endothelial crosstalk: tumor–vascular interactions drive cancer cell entry into circulation and involve EMT/MET processes, revealing dynamic and reversible phenotypic changes at the vascular interface. Third, we delineate mechanobiological regulation of invasion by ECM stiffness and architecture; in confined 3D matrices, the mechanosensitive ion channel PIEZO1 emerges as a central regulator that negatively modulates migration and EMT marker expression, linking matrix mechanics to metastatic potential. Methodologically, the platforms combine endothelialized perfusion channels, ECM-confined tumor niches with controlled geometry, and on-chip mechanical actuation to enable high-content, time-lapse quantification of invasion and transendothelial migration under well-defined biochemical and biomechanical contexts. Collectively, these studies demonstrate that metastatic dissemination is governed by an integrated triad of vascular, cellular, and mechanical factors. The presented platforms bridge the gap between simplified in vitro assays and animal models, providing a robust foundation for mechanistic discovery and future translational applications.
Author: Jiang, Fengtao
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7161100802