Abstract
Simple SummaryEpithelial-mesenchymal transition (EMT) is a key process in cancer progression through which cells weaken their cell-cell adhesion and gain mobility and invasive traits. Besides chemical signaling, recent studies have established the connection of EMT to mechanical microenvironment, such as the stiffness of extracellular matrix (ECM). LOXL2 is representative of a family of enzymes that promotes fiber cross-linking in ECM. With increased cross-linking comes increased stiffness, which induces EMT that can, in turn, elevate LOXL2 levels. As such, a positive feedback loop among EMT, LOXL2, and ECM stiffness can be formed. We built a mathematical model on a core biochemical reaction network featuring this feedback loop, and showed how strongly it drives EMT. We also illustrated mechanistically how cross-linking connects with stiffness, using a mechanical model of collagen (a major component of ECM). Using this theoretical framework, we demonstrated the heterogeneity of LOXL2/stiffness and its implications on migrating cancer cells that could seed metastasis, the growth of secondary malignant tumors. This framework can inspire experimental studies of more fine-grained mechanotransduction and biomechanical heterogeneity in cancers.The epithelial-mesenchymal transition (EMT) plays a critical role in cancer progression, being responsible in many cases for the onset of the metastatic cascade and being integral in the ability of cells to resist drug treatment. Most studies of EMT focus on its induction via chemical signals such as TGF-β or Notch ligands, but it has become increasingly clear that biomechanical features of the microenvironment such as extracellular matrix (ECM) stiffness can be equally important. Here, we introduce a coupled feedback loop connecting stiffness to the EMT transcription factor ZEB1, which acts via increasing the secretion of LOXL2 that leads to increased cross-linking of collagen fibers in the ECM. This increased cross-linking can effectively increase ECM stiffness and increase ZEB1 levels, thus setting a positive feedback loop between ZEB1 and ECM stiffness. To investigate the impact of this non-cell-autonomous effect, we introduce a computational approach capable of connecting LOXL2 concentration to increased stiffness and thereby to higher ZEB1 levels. Our results indicate that this positive feedback loop, once activated, can effectively lock the cells in a mesenchymal state. The spatial-temporal heterogeneity of the LOXL2 concentration and thus the mechanical stiffness also has direct implications for migrating cells that attempt to escape the primary tumor.
Highlights
Metastasis remains the most lethal aspect of cancer progression
We investigated the correlation between the expression levels of LOXL2 and that of key epithelial-mesenchymal transition (EMT) markers for tumor samples, using various TCGA datasets (BRCA, COAD, COADREAD, OV), and for cancer cell lines using the Cancer Cell Line Encyclopedia (CCLE) dataset
The 76GS score showed a negative correlation with LOXL2 and as expected, the other two scores (KS, MLR) showed a positive correlation with LOXL2 across all tumor datasets (Figure S1)
Summary
Metastasis remains the most lethal aspect of cancer progression. Various steps of the metastatic cascade have been intensely investigated from a biochemical signaling perspective. Intracellular processes as well as cell-cell communication signaling networks underlying EMT dynamics have been mapped out extensively through the latest advances in high-throughput data acquisition such as RNA-seq, ATAC-seq, ChIP-seq and mass cytometry [7,8,9,10,11] This data deluge has led to novel mechanism-based and data-based computational models to decode the underlying principles underlying the nonlinear dynamics of EMT [12,13,14,15,16,17,18,19,20]. We use the aforementioned couplings to devise a circuit model which incorporates the ZEB1-LOXL2 mutual activation loop into existing systems biology treatments of EMT Results from this augmented model indicate how the ECM feedback enhances the stability of more mesenchymal states in a cell density dependent manner and makes more difficult the reversion back to epithelial phenotypes. FFiigguurree 22.. ((AA)) AA llooccaall rreeggiioonnoofftthheeddiilluutteeddtrtriaianngguulalarrlalatttitciec.e.TThheererdedcicricrlcelererperperseesnetnstasnanemembebdeddeddebdebaedaudsuedsefdorfomremaseuarsiunrglioncgalosctaiflfsnteifsfsn.es(sB.)(BL)inLeianreasrhsehaeramr modoudluulsusfofrorddififfefreernent tppphan anadndpbpond, b,labclakckbabrasrsrerperperseesnent tththeeppooininttwwhheerree aavverage connectivity equals to 4
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.