Mechanosensitive (de)regulation of exosome production in tumors.

Abstract

Cells release membrane-bound nanovesicles (extracellular vesicles) as efficient modes for cell-to-cell communication. Exosomes are nanovesicles produced through the endocytic pathway (involving inwards budding of the endosomal membrane to form multivesicular endosomes, MVEs) and secreted via exocytosis. Tumor-derived exosomes (TEXs) have been implicated in cancer progression and metastasis, with studies showing their role in promoting tumor cell invasion, immune evasion, and pre-metastatic niches. Tumors also leverage dysregulated extracellular matrix (ECM) remodeling mechanisms to create a conducive microenvironment. One such essential mechanical alteration is the stiffening of ECM, which enhances oncogenic signaling pathways leading to tumor progression. Recent experiments have demonstrated ECM stiffness-dependent exosome secretion in various cancer cell lines with higher exosome release on stiff matrix. To capture this mechanobiology-based regulatory axis hijacked by tumors, we suggest a two-pronged mechanosensitive modulation of TEXs. First, using a mesoscale membrane model evolved with Monte Carlo techniques based on the Helfrich Hamiltonian, we show that stiff ECM modulates exosome formation through its effect on cortical tension. Our results suggest an ultrasensitive response of vesicle nucleation induced by curvature-inducing proteins to changes in cortical tension. Second, experimental collaborators have observed Akt-dependent activation of Rabin8 (Guanine Exchange Factor (GEF) of Rab8) along with increased Rab8-mediated exosome secretion on a stiff matrix for transformed cell lines. We capture this mechanosensitive signaling pathway, involved in directing MVE transport to the cellular membrane for exosome release, using an ODE model. Exosome secretion can then be quantified as the combination of formation and trafficking of MVEs. These coarse-grain predictions agree with the experimentally observed change in exosome amount as the matrix stiffens.