A2 Vertaisarvioitu katsausartikkeli tieteellisessä lehdessä

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




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

Julkaisuvuosi2026

Lehti: Lab on a Chip

Vuosikerta26

Aloitussivu2415

Lopetussivu2438

ISSN1473-0197

eISSN1473-0189

DOIhttps://doi.org/10.1039/d5lc01131k

Julkaisun avoimuus kirjaamishetkelläAvoimesti saatavilla

Julkaisukanavan avoimuus Osittain avoin julkaisukanava

Verkko-osoitehttps://doi.org/10.1039/d5lc01131k

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/523039112

Rinnakkaistallenteen lisenssiCC BY NC

Rinnakkaistallennetun julkaisun versioKustantajan versio


Tiivistelmä

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.


Ladattava julkaisu

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Julkaisussa olevat rahoitustiedot
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).


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