The GRHL2/ZEB Feedback Loop-A Key Axis in the Regulation of EMT in Breast Cancer

Abstract

More than 90% of cancer-related deaths are caused by metastasis. Epithelial-to-Mesenchymal Transition (EMT) causes tumor cell dissemination while the reverse process, Mesenchymal-to-Epithelial Transition (MET) allows cancer cells to grow and establish a potentially deadly metastatic lesion. Recent evidence indicates that in addition to E and M, cells can adopt a stable hybrid Epithelial/Mesenchymal (E/M) state where they can move collectively leading to clusters of Circulating Tumor Cells-the "bad actors" of metastasis. EMT is postulated to occur in all four major histological breast cancer subtypes. Here, we identify a set of genes strongly correlated with CDH1 in 877 cancer cell lines, and differentially expressed genes in cell lines overexpressing ZEB1, SNAIL, and TWIST. GRHL2 and ESRP1 appear in both these sets and also correlate with CDH1 at the protein level in 40 breast cancer specimens. Next, we find that GRHL2 and CD24 expression coincide with an epithelial character in human mammary epithelial cells. Further, we show that high GRHL2 expression is highly correlated with worse relapse-free survival in all four subtypes of breast cancer. Finally, we integrate CD24, GRHL2, and ESRP1 into a mathematical model of EMT regulation to validate the role of these players in EMT. Our data analysis and modeling results highlight the relationships among multiple crucial EMT/MET drivers including ZEB1, GRHL2, CD24, and ESRP1, particularly in basal-like breast cancers, which are most similar to triple-negative breast cancer (TNBC) and are considered the most dangerous subtype. J. Cell. Biochem. 118: 2559-2570, 2017. © 2017 Wiley Periodicals, Inc.

Interconnected feedback loops among ESRP1, HAS2, and CD44 regulate epithelial-mesenchymal plasticity in cancer

“…increased ESRP1 levels effectively). Finally, similar to the prognostic ability of GRHL2 and OVOL [27,39] -factors that can stabilize a hybrid E/M phenotype [25,27,37,38] -higher levels of ESRP1 have been associated with (a) poor OS in breast cancer, (b) poor 5-year progression-free survival (PFS) and OS in epithelial ovarian cancer samples [55,56], and (c) poor prognosis of distant metastasis in breast cancer samples [57]. Put together, these observations support a case for ESRP1 to be referred to as 'phenotypic stability factor' (PSF).…”

“…PSFs such as GRHL2 associate with poor prognosis in breast cancer [27,39], motivating us to investigate the correlation of ESRP1 with patient survival rates. Higher levels of ESRP1, and a higher ratio of ESRP1/HAS2 and ESRP1/ZEB1, correlate with poor relapse-free survival (RFS) and overall survival (OS) in multiple independent breast cancer datasets ( Figure 5A-C, S3).…”

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

“…GRLH2 and OVOL1/2 directly target the miR-200-ZEB axis regulating EMT [63,66], while NUMB/NUMBL modulates EMT via Notch-Jagged signaling [68]. Higher levels of these PSFs can also correlate with poor patient outcome [69]. Thus, future studies should investigate the effects of these and other PSFs in regulating cancer cell aggressiveness in vitro and in vivo to further elevate our understanding of the connection between EMT and stemness, and might potentially provide novel therapeutic targets to break the clusters of circulating tumor cells (CTCs) driving metastases.…”

Testing the Gene Expression Classification of the EMT Spectrum

“…We performed sample purification and isolated the purified epithelial samples that exhibit high expression of multiple E markers including CDH1, GRHL2, OVOL2, ∆Np63α and CLDN7. All of these players are known to be key regulators of epithelial phenotype [39][40][41][42]. Similarly, we performed sample purification to isolate the purified mesenchymal samples that have high expression of multiple M markers, including VIM, ZEB1, ZEB2, TGF-β and FOXC2.…”