Metastasis is a significant contributor to morbidity and mortality for many cancer patients and remains a major obstacle for effective treatment. In many tissue types, metastasis is fueled by the epithelial-to-mesenchymal transition (EMT)—a dynamic process characterized by phenotypic and morphologic changes concomitant with increased migratory and invasive potential. Recent experimental and theoretical evidence suggests that cells can be stably halted en route to EMT in a hybrid E/M phenotype. Cells in this phenotype tend to move collectively, forming clusters of circulating tumor cells that are key tumor-initiating agents. Here, we developed an inferential model built on the gene expression of multiple cancer subtypes to devise an EMT metric that characterizes the degree to which a given cell line exhibits hybrid E/M features. Our model identified drivers and fine-tuners of epithelial–mesenchymal plasticity and recapitulated the behavior observed in multiple in vitro experiments across cancer types. We also predicted and experimentally validated the hybrid E/M status of certain cancer cell lines, including DU145 and A549. Finally, we demonstrated the relevance of predicted EMT scores to patient survival and observed that the role of the hybrid E/M phenotype in characterizing tumor aggressiveness is tissue and subtype specific. Our algorithm is a promising tool to quantify the EMT spectrum, to investigate the correlation of EMT score with cancer treatment response and survival, and to provide an important metric for systematic clinical risk stratification and treatment. Cancer Res; 77(22); 6415–28. ©2017 AACR.

The epithelial-mesenchymal transition (EMT) is a key process implicated in cancer metastasis and therapy resistance. Recent studies have emphasized that cells can undergo partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype – a cornerstone of tumour aggressiveness and poor prognosis. These cells can have enhanced tumour-initiation potential as compared to purely epithelial or mesenchymal ones and can integrate the properties of cell-cell adhesion and motility that facilitates collective cell migration leading to clusters of circulating tumour cells (CTCs) – the prevalent mode of metastasis. Thus, identifying the molecular players that can enable cells to maintain a hybrid E/M phenotype is crucial to curb the metastatic load. Using an integrated computational-experimental approach, we show that the transcription factor NRF2 can prevent a complete EMT and instead stabilize a hybrid E/M phenotype. Knockdown of NRF2 in hybrid E/M non-small cell lung cancer cells H1975 and bladder cancer cells RT4 destabilized a hybrid E/M phenotype and compromised the ability to collectively migrate to close a wound in vitro. Notably, while NRF2 knockout simultaneously downregulated E-cadherin and ZEB-1, overexpression of NRF2 enriched for a hybrid E/M phenotype by simultaneously upregulating both E-cadherin and ZEB-1 in individual RT4 cells. Further, we predict that NRF2 is maximally expressed in hybrid E/M phenotype(s) and demonstrate that this biphasic dynamic arises from the interconnections among NRF2 and the EMT regulatory circuit. Finally, clinical records from multiple datasets suggest a correlation between a hybrid E/M phenotype, high levels of NRF2 and its targets and poor survival, further strengthening the emerging notion that hybrid E/M phenotype(s) may occupy the ‘metastatic sweet spot’.

The ability of breast cancer cells to transiently transition between epithelial and mesenchymal states contributes to their metastatic potential. Therefore, driving tumor cells into a stable mesenchymal state, as opposed to complete tumor cell eradication, presents an opportunity to pharmacologically limit disease progression by promoting an asymptomatic state of dormancy. Here, we compare a reversible model of epithelial–mesenchymal transition (EMT) induced by TGFβ to a stable mesenchymal phenotype induced by chronic exposure to the ErbB kinase inhibitor lapatinib. Only cells capable of returning to an epithelial phenotype resulted in skeletal metastasis. Gene expression analyses of the two mesenchymal states indicated similar transition expression profiles. A potently downregulated gene in both datasets was spleen tyrosine kinase (SYK). In contrast to this similar diminution in mRNA, kinome analyses using a peptide array and DNA-conjugated peptide substrates showed a robust increase in SYK activity upon TGFβ-induced EMT only. SYK was present in cytoplasmic RNA processing depots known as P-bodies formed during the onset of EMT, and SYK activity was required for autophagy-mediated clearance of P-bodies during mesenchymal–epithelial transition (MET). Genetic knockout of autophagy-related 7 (ATG7) or pharmacologic inhibition of SYK activity with fostamatinib, a clinically approved inhibitor of SYK, prevented P-body clearance and MET, inhibiting metastatic tumor outgrowth. Overall, this study suggests assessment of SYK activity as a biomarker for metastatic disease and the use of fostamatinib as a means to stabilize the latency of disseminated tumor cells. Significance: These findings present inhibition of spleen tyrosine kinase as a therapeutic option to limit breast cancer metastasis by promoting systemic tumor dormancy. Graphical http://cancerres.aacrjournals.org/content/canres/79/8/1831/F1.large.jpg. See related commentary by Farrington and Narla, p. 1756 Graphical Abstract

Aberrant activation of epithelial-mesenchymal transition (EMT) in carcinoma cells contributes to increased migration and invasion, metastasis, drug resistance, and tumor-initiating capacity. EMT is not always a binary process; rather, cells may exhibit a hybrid epithelial/mesenchymal (E/M) phenotype. ZEB1—a key transcription factor driving EMT—can both induce and maintain a mesenchymal phenotype. Recent studies have identified two novel autocrine feedback loops utilizing epithelial splicing regulatory protein 1 (ESRP1), hyaluronic acid synthase 2 (HAS2), and CD44 which maintain high levels of ZEB1. However, how the crosstalk between these feedback loops alters the dynamics of epithelial-hybrid-mesenchymal transition remains elusive. Here, using an integrated theoretical-experimental framework, we identify that these feedback loops can enable cells to stably maintain a hybrid E/M phenotype. Moreover, computational analysis identifies the regulation of ESRP1 as a crucial node, a prediction that is validated by experiments showing that knockdown of ESRP1 in stable hybrid E/M H1975 cells drives EMT. Finally, in multiple breast cancer datasets, high levels of ESRP1, ESRP1/HAS2, and ESRP1/ZEB1 correlate with poor prognosis, supporting the relevance of ZEB1/ESRP1 and ZEB1/HAS2 axes in tumor progression. Together, our results unravel how these interconnected feedback loops act in concert to regulate ZEB1 levels and to drive the dynamics of epithelial-hybrid-mesenchymal transition.

Thermoresponsive poly(N-isopropylacrylamide) (PNIPAAm) hydrogels are widely studied smart materials, particularly for biomedical applications, but are limited by their mechanical strength. In this study, double network (DN) hydrogels were prepared with an asymmetric crosslink design and inclusion of an electrostatic co-monomer, 2-acrylamido-2-methylpropane sulfonic acid (AMPS). These P(NIPAAm-co-AMPS)/PNIPAAm DN hydrogels were sequentially formed with a tightly crosslinked 1^st network comprised of variable levels of AMPS (100 : 0 to 25 : 75 wt% ratio of NIPAAm:AMPS) and a loosely crosslinked 2^nd network comprised of PNIPAAm. The impact of AMPS content in the 1^st network on the volume phase transition temperature (VPTT), morphology, deswelling–reswelling kinetics and mechanical properties was evaluated. Without substantially altering the VPTT of conventional PNIPAAm hydrogels but with improving thermosensitivity, the DN hydrogel formed with 25 : 75 wt% of NIPAAm:AMPS achieved exceptional strength, high modulus and high %strain at break.

A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling