scholarly journals Learning Edge Rewiring in EMT From Single Cell Data

2017 ◽  
Author(s):  
Smita Krishnaswamy ◽  
Nevena Zivanovic ◽  
Roshan Sharma ◽  
Dana Pe’er ◽  
Bernd Bodenmiller
Keyword(s):  
Single Cell ◽  
Breast Cancer Cells ◽  
Regulatory Networks ◽  
Epithelial To Mesenchymal Transition ◽  
Mass Cytometry ◽  
Mesenchymal Transition ◽  
Dynamic Modulation ◽  
Static Interaction ◽  
Cell Data ◽  
Time Point

AbstractCellular regulatory networks are not static, but continuously reconfigure in response to stimuli via alterations in gene expression and protein confirmations. However, typical computational approaches treat them as static interaction networks derived from a single experimental time point. Here, we provide a method for learning the dynamic modulation, or rewiring of pairwise relationships (edges) from a static single-cell data. We use the epithelial-to-mesenchymal transition (EMT) in murine breast cancer cells as a model system, and measure mass cytometry data three days after induction of the transition by TGFβ. We take advantage of transitional rate variability between cells in the data by deriving a pseudo-time EMT trajectory. Then we propose methods for visualizing and quantifying time-varying edge behavior over the trajectory and use these methods: TIDES (Trajectory Imputed DREMI scores), and measure of edge dynamism (3DDREMI) to predict and validate the effect of drug perturbations on EMT.

scholarly journals The Role of Autophagy and lncRNAs in the Maintenance of Cancer Stem Cells

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1239
Author(s):  
Leila Jahangiri ◽  
Tala Ishola ◽  
Perla Pucci ◽  
Ricky M. Trigg ◽  
Joao Pereira ◽  
...  
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Cancer Progression ◽  
Regulatory Networks ◽  
Epithelial To Mesenchymal Transition ◽  
Tumour Microenvironment ◽  
Repair Capacity ◽  
Mesenchymal Transition ◽  
Cellular Processes

Cancer stem cells (CSCs) possess properties such as self-renewal, resistance to apoptotic cues, quiescence, and DNA-damage repair capacity. Moreover, CSCs strongly influence the tumour microenvironment (TME) and may account for cancer progression, recurrence, and relapse. CSCs represent a distinct subpopulation in tumours and the detection, characterisation, and understanding of the regulatory landscape and cellular processes that govern their maintenance may pave the way to improving prognosis, selective targeted therapy, and therapy outcomes. In this review, we have discussed the characteristics of CSCs identified in various cancer types and the role of autophagy and long noncoding RNAs (lncRNAs) in maintaining the homeostasis of CSCs. Further, we have discussed methods to detect CSCs and strategies for treatment and relapse, taking into account the requirement to inhibit CSC growth and survival within the complex backdrop of cellular processes, microenvironmental interactions, and regulatory networks associated with cancer. Finally, we critique the computationally reinforced triangle of factors inclusive of CSC properties, the process of autophagy, and lncRNA and their associated networks with respect to hypoxia, epithelial-to-mesenchymal transition (EMT), and signalling pathways.

scholarly journals Metadherin enhances the invasiveness of breast cancer cells by inducing epithelial to mesenchymal transition

2011 ◽  
Vol 102 (6) ◽  
pp. 1151-1157 ◽  
Author(s):  
Xiaoyan Li ◽  
Xiaoli Kong ◽  
Qiang Huo ◽  
Haiyang Guo ◽  
Shi Yan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Epithelial To Mesenchymal Transition ◽  
Mesenchymal Transition

scholarly journals Global and gene specific DNA methylation in breast cancer cells was not affected during epithelial-to-mesenchymal transition in vitro

Neoplasma ◽  
2016 ◽  
Vol 63 (06) ◽  
pp. 901-910 ◽  
Author(s):  
B. SMOLKOVA ◽  
S. MIKLIKOVA ◽  
V. HORVATHOVA KAJABOVA ◽  
A. BABELOVA ◽  
N. EL YAMANI ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Epithelial To Mesenchymal Transition ◽  
Mesenchymal Transition

scholarly journals Fluid flow exposure promotes Epithelial-to-Mesenchymal Transition and adhesion of breast cancer cells to endothelial cells

2020 ◽  
Author(s):  
Kenneth F. Fuh ◽  
Robert D. Shepherd ◽  
Jessica S. Withell ◽  
Brayden K. Kooistra ◽  
Kristina D Rinker
Keyword(s):  
Breast Cancer ◽  
Endothelial Cells ◽  
Fluid Flow ◽  
Network Analysis ◽  
Protein Expression ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Epithelial To Mesenchymal Transition ◽  
Endothelial Monolayer ◽  
Mesenchymal Transition

Abstract Background: Fluid forces are an integral part of the tumor microenvironment through all phases of development and progression. However, it is not well understood how these forces affect key steps in the progression of breast cancer of Epithelial-to-Mesenchymal Transition (EMT) and adhesion to vascular wall endothelial cells. EMT is associated with the progression of most carcinomas through induction of new transcriptional programs within affected epithelial cells, resulting in cells becoming more motile and adhesive to endothelial cells.Methods: MDA-MB-231, SK-BR-3, BT-474, and MCF-7 cells and normal Human Mammary Epithelial Cells (HMECs) were exposed to fluid flow in a parallel-plate bioreactor system. Changes in gene expression were quantified using microarrays and qPCR, gene-gene interactions were elucidated using network analysis, and key modified genes were examined in clinical datasets. Changes in protein expression of key EMT markers between chemically induced EMT and flow-exposed cells were compared in immunocytochemistry assays. Finally, the ability of flow-stimulated and unstimulated cancer cells to adhere to an endothelial monolayer was evaluated in flow and static adhesion experiments.Results: Fluid flow stimulation resulted in upregulation of EMT inducers and downregulation of repressors. Specifically, Vimentin and Snail were upregulated both at the gene and protein expression levels in flow stimulated HMECs, suggesting progression towards an EMT phenotype. Flow-induced overexpression of a panel of cell adhesion genes was also observed. Network analysis revealed genes involved in cell flow responses including FN1, PLAU, and ALCAM. When evaluated in clinical datasets, overexpression of FN1, PLAU, and ALCAM was observed in patients with most subtypes of breast cancer. We also observed increased adhesion of flow-stimulated breast cancer cells compared to unstimulated controls, suggesting an increased potential to form secondary tumors at metastatic sites. Conclusions: This study shows that prolonged fluid force exposure on the order of 1 Pa promotes EMT and adhesion of breast cancer cells to an endothelial monolayer. Further, identified biomarkers were distinctly expressed in patient populations. A better understanding of how biophysical forces such as shear stress affect cellular processes involved in metastatic progression of breast cancer is important for identifying new molecular markers for disease progression, and for predicting metastatic risk.

scholarly journals Consensus transcriptional regulatory networks of coronavirus-infected human cells

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Scott A. Ochsner ◽  
Rudolf T. Pillich ◽  
Neil J. McKenna
Keyword(s):  
Signaling Pathways ◽  
Regulatory Networks ◽  
Data Exchange ◽  
Epithelial To Mesenchymal Transition ◽  
Transcriptional Regulatory Networks ◽  
Mesenchymal Transition ◽  
Human Genes ◽  
Transcriptional Regulatory ◽  
Infected Cells ◽  
Key Drivers

Abstract Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of MERS, SARS1 and SARS2 infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family HCTs encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.

scholarly journals Learning time-varying information flow from single-cell epithelial to mesenchymal transition data

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0203389 ◽  
Author(s):  
Smita Krishnaswamy ◽  
Nevena Zivanovic ◽  
Roshan Sharma ◽  
Dana Pe’er ◽  
Bernd Bodenmiller
Keyword(s):  
Single Cell ◽  
Information Flow ◽  
Epithelial To Mesenchymal Transition ◽  
Time Varying ◽  
Mesenchymal Transition ◽  
Learning Time
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