A2 Refereed review article in a scientific journal
Tumor-on-chip platforms for transport phenotyping: decoding CAF-driven barriers to drug delivery
Authors: Le Manach, Doriane; Senez, Vincent; Nees, Matthias
Publication year: 2026
Journal: Lab on a Chip
Volume: 26
First page : 2415
Last page: 2438
ISSN: 1473-0197
eISSN: 1473-0189
DOI: https://doi.org/10.1039/d5lc01131k
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Partially Open Access publication channel
Web address : https://doi.org/10.1039/d5lc01131k
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/523039112
Self-archived copy's licence: CC BY NC
Self-archived copy's version: Publisher`s PDF
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.
Downloadable publication This is an electronic reprint of the original article. |
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).