Transcriptional and post-transcriptional control of epithelial-mesenchymal plasticity: why so many regulators?

Migault, Mélodie; Sapkota, Sunil; Bracken, Cameron P.

doi:10.1007/s00018-022-04199-0

Cited by 24 publications

(17 citation statements)

References 264 publications

(243 reference statements)

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“…Next, candidate gene expression profiles were evaluated following differential expression analysis between clusters to further contextualize cluster specific gene expression patterns. Immediately apparent and consistent with previous work were hallmark gene signatures of the Epithelial-Mesenchymal Transition (EMT) characterized by high levels of TWIST, VIM, PDGFRA/B, SNAI1, CYR61 (Figure 2B; Supplemental Figure 4) (37)(38)(39)(40). These signals localize predominantly in cluster 9, and to a lesser extent cluster 1, in agreement with a split in EMT signal previously reported between LUSC and HNSC (Figure 2B; Supplemental Figure 4) (31).…”

Section: Spectral Cluster Analysis Reveals Hallmarks Of Mesenchymal T...supporting

confidence: 89%

Multimodal Dimension Reduction and Subtype Classification of Head and Neck Squamous Cell Tumors

et al. 2022

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Traditional analysis of genomic data from bulk sequencing experiments seek to group and compare sample cohorts into biologically meaningful groups. To accomplish this task, large scale databases of patient-derived samples, like that of TCGA, have been established, giving the ability to interrogate multiple data modalities per tumor. We have developed a computational strategy employing multimodal integration paired with spectral clustering and modern dimension reduction techniques such as PHATE to provide a more robust method for cancer sub-type classification. Using this integrated approach, we have examined 514 Head and Neck Squamous Carcinoma (HNSC) tumor samples from TCGA across gene-expression, DNA-methylation, and microbiome data modalities. We show that these approaches, primarily developed for single-cell sequencing can be efficiently applied to bulk tumor sequencing data. Our multimodal analysis captures the dynamic heterogeneity, identifies new and refines subtypes of HNSC, and orders tumor samples along well-defined cellular trajectories. Collectively, these results showcase the inherent molecular complexity of tumors and offer insights into carcinogenesis and importance of targeted therapy. Computational techniques as highlighted in our study provide an organic and powerful approach to identify granular patterns in large and noisy datasets that may otherwise be overlooked.

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Section: Spectral Cluster Analysis Reveals Hallmarks Of Mesenchymal T...supporting

confidence: 89%

Multimodal Dimension Reduction and Subtype Classification of Head and Neck Squamous Cell Tumors

et al. 2022

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“…However, in human cancer, EMT is not complete in the tumors, but cancer cells are entrapped in an intermediate state when epithelial and mesenchymal markers co-exist in the cancer cells. This is called partial EMT (p-EMT) [22]. EMT is regulated by the wild-type forms of tissue specific EMT-transcription factors (TF).…”

Section: Epithelial-mesenchymal Transition (Emt)mentioning

confidence: 99%

“…The functional role of EMT in cancer is the close association with motility, invasiveness, and metastatic potential, in addition to chemoresistance [19]. EMT-TFs are SNAIL, SLUG, TWIST1/2, and ZEB1/2 [19,22]. However, besides these core EMT-TFs, there are many other TFs which can promote EMT, like TBXT, E47, KLF4, PPRX1, GSC, RUNX1, TCF4, SIX1, FOXC2, or SOX4, and can be expressed in a tissue or cancer type specific manner [22].…”

Section: Epithelial-mesenchymal Transition (Emt)mentioning

confidence: 99%

“…EMT-TFs are SNAIL, SLUG, TWIST1/2, and ZEB1/2 [19,22]. However, besides these core EMT-TFs, there are many other TFs which can promote EMT, like TBXT, E47, KLF4, PPRX1, GSC, RUNX1, TCF4, SIX1, FOXC2, or SOX4, and can be expressed in a tissue or cancer type specific manner [22]. There is an additional level of EMT regulation by miRs.…”

Section: Epithelial-mesenchymal Transition (Emt)mentioning

confidence: 99%

“…There is an additional level of EMT regulation by miRs. MiR-200 is a direct repressor of ZEB-TFs; miR-34 and miR-200 are SNAI2/SLUG repressors, while miR-203 is a SNAI1 repressor [22].…”

Section: Epithelial-mesenchymal Transition (Emt)mentioning

confidence: 99%

See 2 more Smart Citations

Newly identified form of phenotypic plasticity of cancer: immunogenic mimicry

Tı́már

Honn

Hendrix

et al. 2023

Cancer Metastasis Rev

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Cancer plasticity is now a recognized new hallmark of cancer which is due to disturbances of cell differentiation programs. It is manifested not only in various forms like the best-known epithelial-mesenchymal transition (EMT) but also in vasculogenic and megakaryocytic mimicries regulated by EMT-specific or less-specific transcription factors such as HIF1a or STAT1/2. Studies in the past decades provided ample data that cancer plasticity can be manifested also in the expression of a vast array of immune cell genes; best-known examples are PDL1/CD274, CD47, or IDO, and we termed it immunogenic mimicry (IGM). However, unlike other types of plasticities which are epigenetically regulated, expression of IGM genes are frequently due to gene amplifications. It is important that the majority of the IGM genes are regulated by interferons (IFNs) suggesting that their protein expressions are regulated by the immune microenvironment. Most of the IGM genes have been shown to be involved in immune escape of cancers broadening the repertoire of these mechanisms and offering novel targets for immunotherapeutics.

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Epithelial–mesenchymal plasticity in cancer: signaling pathways and therapeutic targets

Wang,

Xue,

Pang

et al. 2024

MedComm

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Currently, cancer is still a leading cause of human death globally. Tumor deterioration comprises multiple events including metastasis, therapeutic resistance and immune evasion, all of which are tightly related to the phenotypic plasticity especially epithelial–mesenchymal plasticity (EMP). Tumor cells with EMP are manifest in three states as epithelial–mesenchymal transition (EMT), partial EMT, and mesenchymal–epithelial transition, which orchestrate the phenotypic switch and heterogeneity of tumor cells via transcriptional regulation and a series of signaling pathways, including transforming growth factor‐β, Wnt/β‐catenin, and Notch. However, due to the complicated nature of EMP, the diverse process of EMP is still not fully understood. In this review, we systematically conclude the biological background, regulating mechanisms of EMP as well as the role of EMP in therapy response. We also summarize a range of small molecule inhibitors, immune‐related therapeutic approaches, and combination therapies that have been developed to target EMP for the outstanding role of EMP‐driven tumor deterioration. Additionally, we explore the potential technique for EMP‐based tumor mechanistic investigation and therapeutic research, which may burst vigorous prospects. Overall, we elucidate the multifaceted aspects of EMP in tumor progression and suggest a promising direction of cancer treatment based on targeting EMP.

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Transcriptional and post-transcriptional control of epithelial-mesenchymal plasticity: why so many regulators?

Cited by 24 publications

References 264 publications

Multimodal Dimension Reduction and Subtype Classification of Head and Neck Squamous Cell Tumors

Multimodal Dimension Reduction and Subtype Classification of Head and Neck Squamous Cell Tumors

Newly identified form of phenotypic plasticity of cancer: immunogenic mimicry

Epithelial–mesenchymal plasticity in cancer: signaling pathways and therapeutic targets

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