Engineered polymeric systems suppress breast cancer metastasis by manipulating the clustering states of cell surface C-X-C chemokine receptor 4.

Authors

Chendong Liu, Junzhu Shi, Likai Shi, Qingrui Jia, Jiaqi Liu, Yue Yan, Minglu Zhou, Zhou Zhou, Yuan Huang, Lian Li

Published in

Journal of controlled release : official journal of the Controlled Release Society. Pages 115383. Sep 20, 2026. Epub Sep 20, 2026.

Abstract

The clustering states of cell surface C-X-C chemokine receptor 4 (CXCR4) play a critical role in cancer metastasis. We previously reported a "Pro-Clustering Polymers (PCP)" system, P-BS-CM1 → P-CM2, for the treatment of metastatic triple-negative breast cancer (TNBC). Subsequent studies demonstrated that PCP enhanced CXCR4 blockade and metastasis suppression by disrupting CXCR4 association-disassociation dynamic equilibrium and shifting the receptor toward a hyper-clustered state. As an alternative strategy to disrupt this equilibrium, shifting CXCR4 toward a less clustered, more dispersed state, i.e., inhibiting CXCR4 clustering, remains largely underexplored. Herein, we developed a "De-Clustering Polymer (DCP)" system, P-BS-pHLIP, which introduces steric hindrance to block receptor-receptor interactions and thereby inhibits CXCR4 clustering. Side-by-side comparisons of DCP with our previously developed PCP system revealed that different modes of CXCR4 manipulation dictate divergent downstream biological outcomes. PCP preferentially impaired tumor cell motility by inducing mitochondrial dysfunction and energy depletion, whereas DCP preferentially reduced tumor cell adhesiveness by downregulating multiple adhesion molecules. Both PCP and DCP exert potent anti-metastatic efficacy in multiple TNBC metastatic models. Collectively, this study demonstrates that engineered polymeric systems that biophysically manipulate receptor clustering states, via either pro-clustering or de-clustering, represent promising therapeutic strategies for suppressing cancer metastasis.

PMID:
42764094
Bibliographic data and abstract were imported from PubMed on 21 Sep 2026.

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