The p63 Gene Is Regulated by Grainyhead-like 2 (GRHL2) through Reciprocal Feedback and Determines the Epithelial Phenotype in Human Keratinocytes

Mehrazarin, Shebli; Chen, Wei; Oh, Joo Hyun; Liu, Zi X.; Kang, Kyung Lhi; Yi, Jin Woong; Kim, Reuben H.; Shin, Kihyuk; Park, No‐Hee; Kang, Mo K.

doi:10.1074/jbc.m115.659144

Cited by 40 publications

(30 citation statements)

References 28 publications

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“…single-cell migration and/or invasion) Additionally, ΔNp63α can trigger the secretion of matrix metalloproteinases (MMPs) to drive the invasive program 39 . Pcadherin is a downstream target of ΔNp63α 35 , and p63 gene can be activated by GRHL2 40 , another PSF 29 .…”

Section: Clusters Of Ctcs and A Hybrid Epithelial/mesenchymal Phenotymentioning

confidence: 99%

Inflammatory Breast Cancer: a model for investigating cluster-based dissemination

Jolly

Boareto

Debeb³

et al. 2017

Preprint

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Metastases claim more than 90% of cancer-related patient deaths and are usually seeded by a subset of circulating tumor cells (CTCs) shed off from the primary tumor. In circulation, CTCs are found both as single cells and as clusters of cells. The clusters of CTCs, although many fewer in number, possess much higher metastatic potential as compared to that of individual CTCs. In this review, we highlight recent insights into molecular mechanisms that can enable the formation of these clusters -(a) hybrid epithelial/mesenchymal (E/M) phenotype of cells that couples their ability to migrate and adhere, and (b) intercellular communication that can spatially coordinate the cluster formation and provide survival signals to cancer cells. Building upon these molecular mechanisms, we also offer a possible mechanistic understanding of why clusters are endowed with a higher metastatic potential. Finally, we discuss the highly aggressive Inflammatory Breast Cancer (IBC) as an example of a carcinoma that can metastasize via clusters and corroborates the proposed molecular mechanisms.

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Section: Clusters Of Ctcs and A Hybrid Epithelial/mesenchymal Phenotymentioning

confidence: 99%

Inflammatory Breast Cancer: a model for investigating cluster-based dissemination

Jolly

Boareto

Debeb³

et al. 2017

Preprint

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“…Specifically, overexpression of GRHL2 has been shown to induce epithelial gene expression, inhibit mesenchymal gene expression, restore metabolic reprogramming caused by EMT, and suppress tumor cell migration/invasion, at least in breast and ovarian cancer cell lines [46]. It can also activate directly or indirectly other drivers of an epithelial phenotype such as p63 [57,58], OVOL2 [59,60], and miR-200 [38,61]. While epigenetic changes induced by EMT-TFs have been reported extensively [62], recent studies have pointed out the possibility of GRHL2 contributing to epigenetic control of genes involved in EMT/MET [39].…”

Section: Discussionmentioning

confidence: 99%

Epigenetic feedback and stochastic partitioning during cell division can drive resistance to EMT

Jia

Tripathi

Chakraborty

et al. 2020

Preprint

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Epithelial-mesenchymal transition (EMT) and its reverse process mesenchymal-epithelial transition (MET) are central to metastatic aggressiveness and therapy resistance in solid tumors. While molecular determinants of both processes have been extensively characterized, the heterogeneity in the response of tumor cells to EMT and MET inducers has come into focus recently, and has been implicated in the failure of anti-cancer therapies. Recent experimental studies have shown that some cells can undergo an irreversible EMT depending on the duration of exposure to EMT-inducing signals. While the irreversibility of MET, or equivalently, resistance to EMT, has not been studied in as much detail, evidence supporting such behavior is slowly emerging. Here, we identify two possible mechanisms that can underlie resistance of cells to undergo EMT: epigenetic feedback in ZEB1/GRHL2 feedback loop and stochastic partitioning of biomolecules during cell division. Identifying the ZEB1/GRHL2 axis as a key determinant of epithelial-mesenchymal plasticity across many cancer types, we use mechanistic mathematical models to show how GRHL2 can be involved in both the abovementioned processes, thus driving an irreversible MET. Our study highlights how an isogenic population may contain subpopulation with varying degrees of susceptibility or resistance to EMT, and proposes a next set of questions for detailed experimental studies characterizing the irreversibility of MET/resistance to EMT.

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“…6 Paradoxically, ΔNp63 can also (a) synergize with Notch to induce Keratin 1 (K1) expression 7 and (b) directly induce p57Kip2, a cyclin-dependent kinase inhibitor associated with terminal differentiation of keratinocytes. 16 We showed a relationship between p63 expression and factor inhibiting HIF-1 (FIH-1) where FIH-1 null (FIH-1 −/− ) mice displayed a significant decrease in p63 expression in the limbal epithelium when compared with littermate controls. 6 Although much is known about the genes regulated by p63 in keratinocytes and the epidermis, [9][10][11] how p63 is regulated is less clear.…”

Section: Introductionmentioning

confidence: 99%

FIH‐1 engages novel binding partners to positively influence epithelial proliferation via p63

et al. 2019

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Whereas much is known about the genes regulated by ΔNp63α in keratinocytes, how ΔNp63α is regulated is less clear. During studies with the hydroxylase, factor inhibiting hypoxia‐inducible factor 1 (FIH‐1), we observed increases in epidermal ΔNp63α expression along with proliferative capacity in a conditional FIH‐1 transgenic mouse. Conversely, loss of FIH‐1 in vivo and in vitro attenuated ΔNp63α expression. To elucidate the FIH‐1/p63 relationship, BioID proteomics assays identified FIH‐1 binding partners that had the potential to regulate p63 expression. FIH‐1 interacts with two previously unknown partners, Plectin1 and signal transducer and activator of transcription 1 (STAT1) leading to the regulation of ΔNp63α expression. Two known interactors of FIH‐1, apoptosis‐stimulating of P53 protein 2 (ASPP2) and histone deacetylase 1 (HDAC1), were also identified. Knockdown of ASPP2 upregulated ΔNp63α and reversed the decrease in ΔNp63α by FIH‐1 depletion. Additionally, FIH‐1 regulates growth arrest and DNA damage‐45 alpha (GADD45α), a negative regulator of ΔNp63α by interacting with HDAC1. GADD45α knockdown rescued reduction in ΔNp63α by FIH‐1 depletion. Collectively, our data reveal that FIH‐1 positively regulates ΔNp63α in keratinocytes via variety of signaling partners: (a) Plectin1/STAT1, (b) ASPP2, and (c) HDAC1/GADD45α signaling pathways.

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The p63 Gene Is Regulated by Grainyhead-like 2 (GRHL2) through Reciprocal Feedback and Determines the Epithelial Phenotype in Human Keratinocytes

Cited by 40 publications

References 28 publications

Inflammatory Breast Cancer: a model for investigating cluster-based dissemination

Inflammatory Breast Cancer: a model for investigating cluster-based dissemination

Epigenetic feedback and stochastic partitioning during cell division can drive resistance to EMT

FIH‐1 engages novel binding partners to positively influence epithelial proliferation via p63

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