A2 Refereed review article in a scientific journal

Tumor-on-chip platforms for transport phenotyping: decoding CAF-driven barriers to drug delivery




AuthorsLe Manach, Doriane; Senez, Vincent; Nees, Matthias

Publication year2026

Journal: Lab on a Chip

Volume26

First page 2415

Last page2438

ISSN1473-0197

eISSN1473-0189

DOIhttps://doi.org/10.1039/d5lc01131k

Publication's open availability at the time of reportingOpen Access

Publication channel's open availability Partially Open Access publication channel

Web address https://doi.org/10.1039/d5lc01131k

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/523039112

Self-archived copy's licenceCC BY NC

Self-archived copy's versionPublisher`s PDF


Abstract

Physical barriers within solid tumors constitute a fundamental but often overlooked mechanism of therapeutic resistance, contributing to the poor success rate of cancer drug translation. Therapeutic molecules often fail to reach their intended targets due to mass-transport limitations imposed by the remodeled, spatially heterogeneous tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) drive dynamic remodeling of the extracellular matrix (ECM), generating local variations in stiffness, porosity, and intrinsic permeability that, together, shape evolving transport phenotypes that govern drug accessibility. We focus on mechanical pathways of stromal mechanotransduction, tracing the sequence from CAF activation through ECM remodeling, to barrier formation, and show how these processes collectively govern therapeutic outcomes. We also evaluate advanced microfluidic and tumor-on-chip (ToC) platforms that reproduce stromal heterogeneity under controlled conditions, mimicking tissue architecture, transport behavior, and therapeutic response. By enabling patient-specific profiling of CAF-driven transport phenotypes, these systems demonstrate that transport barriers are not fixed obstacles but dynamically modifiable therapeutic targets. “Transport phenotyping” could complement genomic profiling in clinical oncology by integrating heterogeneity, biophysics, and precision medicine, potentially transforming personalized treatment strategies for patients whose tumors remain refractory to current therapies.


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Funding information in the publication
This work was supported by the Polish National Science Centre (NCN): UMO-2020/37/B/N24/03920, and UMO-2021/41/B/NZ7/03786, the Cancéropole Nord-Ouest, the Région Hauts-de-France, the Centre National de la Recherche Scientifique (CNRS), the Ligue Nationale Contre le Cancer (France).


Last updated on 30/04/2026 03:07:10 PM