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

Jolly, Mohit Kumar; Preca, Bogdan‐Tiberius; Tripathi, Satyendra Chandra; Jia, Dongya; Hanash, Samir M.; Brabletz, Thomas; Stemmler, Marc P.; Maurer, Jochen; Levine, Herbert

doi:10.1101/260349

Cited by 4 publications

(2 citation statements)

References 67 publications

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“…The expression of zeb1b/zeb2a was highest in cluster 5. Consistent with the notion that ZEB drives a mesenchymal identity partly by repressing ESRP [43], we found strongest expression of the zeb1b/zeb2a paralogs in cluster 5, where there is weakest esrp1 expression. These data indicate that canonical MET and EMT components are expressed in osteoblastic cells.…”

Section: Osteoblastic Cells Differentially Express Met-and Emt-associated Genessupporting

confidence: 88%

Single-cell resolution of MET- and EMT-like programs in osteoblasts during zebrafish fin regeneration

Cj²,

Olmstead³

et al. 2021

Preprint

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While humans have limited potential for limb regeneration, some vertebrates can regenerate bony appendages following amputation. During zebrafish fin regeneration, mature osteoblasts at the amputation stump dedifferentiate and migrate to the blastema, where they re-enter the cell cycle and then re-differentiate to form new bone. Osteoblastic cells exhibit dual mesenchymal and epithelial characteristics during fin regeneration, however little is known about why or how this occurs. Using single-cell RNA-sequencing, we found osteoprogenitors are enriched with components associated with the epithelial-to-mesenchymal transition (EMT) and its reverse, mesenchymal-to-epithelial transition (MET). In trajectory analyses, osteoblastic cells solely expressed EMT components, or transiently expressed MET components prior to expressing those for EMT. We found that cdh11, a cancer EMT marker, is expressed during osteoblast dedifferentiation. We also found that esrp1, a regulator of alternative splicing in epithelial cells whose expression is important for MET, is expressed in a subset of osteoprogenitors during outgrowth. This study provides a valuable single cell resource for the study of osteoblast differentiation during zebrafish fin regeneration, and identifies MET- and EMT-associated components which may be important for successful appendage regeneration.

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Section: Osteoblastic Cells Differentially Express Met-and Emt-associated Genessupporting

confidence: 88%

Single-cell resolution of MET- and EMT-like programs in osteoblasts during zebrafish fin regeneration

Cj²,

Olmstead³

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…Local methods employ a one-at-a-time approach in which model responses are analyzed while one parameter at a time is varied (Chen et al, 2018;Jolly et al, 2018;Faro et al, 2019;Storey et al, 2020;Subbalakshmi et al, 2021;Dela et al, 2022;Ryan et al, 2022). In contrast, global methods explore model responses by varying all the parameters at the same time within a range of uncertainty (Dela et al, 2022).…”

Section: Sensitivity Analysis Identifies Key Influencers Of Emtmentioning

confidence: 99%

Network motifs and hypermotifs in TGFβ-induced epithelial to mesenchymal transition and metastasis

Bhavani

Palanisamy

2023

Front. Syst. Biol.

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Epithelial to mesenchymal transition (EMT) is a complex, non-linear, dynamic multistep process that plays an integral role in the development of metastatic cancers. A diverse range of signaling molecules, along with their associated pathways, were observed to be involved in promoting EMT and cancer metastasis. Transforming growth factor–β (TGFβ), through its SMAD-dependent and SMAD-independent signaling, orchestrates numerous regulators that converge on key EMT transcription factors (TFs). These TFs further govern the phenotypic transition of cancer cells from epithelial to mesenchymal states. This study explores the TGFβ signaling pathway and its unique network architecture to understand their information processing roles in EMT. Two coherent type 1 feed forward network motifs regulating the expression of SNAIL and N-cadherin were observed. SNAIL, which is one of the crucial regulators of EMT, links both the coherent type 1 feed forward loops (C1FFLs) leading to hypermotif-like structure (Adler and Medzhitov, 2022). Systems modeling and analysis of these motifs and hypermotifs illustrated several interesting emergent information processing roles of the regulators involved. The known roles of these regulators, as described in the literature, were highly correlated with the emergent properties observed. The motifs illustrated persistence detection and noise filtration in regulating the expression of SNAIL and N-cadherin. Along with these system-level properties, the hypermotif architecture also exhibited temporal expression of GLI, SNAIL, ZEB, and N-cadherin. Furthermore, a hypothetical three-layered C1FFL hypermotif was postulated and analyzed. The analysis revealed various interesting system-level properties. However, possible existence of such real biological networks needs further exploration both theoretically and experimentally. Deciphering these network motifs and hypermotifs has provided an additional understanding of the complex biological phenomenon, such as EMT in cancer metastasis.

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Multistability and consequent phenotypic plasticity in AMPK-Akt double negative feedback loop in cancer cells

Chedere

Hari

Kumar

et al. 2020

Preprint

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Adaptation and survival of cancer cells to various stress and growth factor conditions is crucial for successful metastasis. A double-negative feedback loop between two serine/threonine kinases AMPK and Akt can regulate the adaptation of breast cancer cells to matrix-deprivation stress. This feedback loop can generate majorly two phenotypes or cell states: matrix detachment-triggered pAMPKhigh/ pAktlow state, and matrix (re)attachment-triggered pAkthigh/ pAMPKlow state. However, whether these two cell states can exhibit phenotypic plasticity and heterogeneity in a given cell population, i.e., whether they can co-exist and undergo spontaneous switching to generate the other subpopulation, remains unclear. Here, we develop a mechanism-based mathematical model that captures the set of experimentally reported interactions among AMPK and Akt. Our simulations suggest that the AMPK-Akt feedback loop can give rise to two co-existing phenotypes (pAkthigh/ pAMPKlow and pAMPKhigh/pAktlow) in specific parameter regimes. Next, to test the model predictions, we segregated these two subpopulations in MDA-MB-231 cells and observed that each of them was capable of switching to another in adherent conditions. Finally, the predicted trends are supported by clinical data analysis of TCGA breast cancer and pan-cancer cohorts that revealed negatively correlated pAMPK and pAkt protein levels. Overall, our integrated computational-experimental approach unravels that AMPK-Akt feedback loop can generate multistability and drive phenotypic switching and heterogeneity in a cancer cell population.

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

Cited by 4 publications

References 67 publications

Single-cell resolution of MET- and EMT-like programs in osteoblasts during zebrafish fin regeneration

Single-cell resolution of MET- and EMT-like programs in osteoblasts during zebrafish fin regeneration

Network motifs and hypermotifs in TGFβ-induced epithelial to mesenchymal transition and metastasis

Multistability and consequent phenotypic plasticity in AMPK-Akt double negative feedback loop in cancer cells

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