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Can a 'systems' view help 'understand' cancer?
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Classroom Contents
Dynamical Systems Biology of Cancer Metastasis by Mohit Kumar Jolly
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- 1 Dynamical systems biology of cancer metastasis
- 2 uncontrolled growth of abnormal cells
- 3 Stages of cancer progression
- 4 Metastasis : the cause of 90 percent of all cancer deaths
- 5 What traits cells need to successfully metastasize?
- 6 Is genetics the answer? Not always
- 7 Can cancer proceed without mutations? Perhaps!
- 8 Can a 'systems' view help 'understand' cancer?
- 9 Example of 'systems' approach
- 10 We are...
- 11 EMT/MET: The engine of metastasis
- 12 Metastasis: a journey taken in groups
- 13 How do clusters reconcile with binary EMT?
- 14 Systems biology model for EMT/MET
- 15 Toggle switch: A systems biology model
- 16 Theoretical framework for miRNA-based circuits
- 17 Tristability in the underlying EMT network
- 18 Hybrid E/M can be a stable phenotype
- 19 Co-existence of phenotypes seen experimentally
- 20 Quantifying the EMT spectrum of states
- 21 Identifying 'phenotypic stability factors' PSFs
- 22 Knockdown of PSFs can drive a complete EMT
- 23 Spontaneous switching among phenotypes
- 24 Is EMT always reversible?
- 25 How EMT alters tumor-initiation ability stemness?
- 26 Hybrid E/M cells can form many more tumors
- 27 In vivo spontaneous EMT model highlights the aggressive behavior of hybrid E/M phenotypes
- 28 Hybrid E/M phenotype may form CTC clusters
- 29 How are CTC clusters formed?
- 30 Crosstalk between EMT and Notch pathways
- 31 Notch-Jagged signaling can form CTC clusters
- 32 JAG1 knockdown diminishes emboli formation
- 33 Why do hybrid E/M cells matter in the clinic?
- 34 Hybrid E/M: the 'fittest' for metastasis?
- 35 Conclusion
- 36 Ongoing questions/debate
- 37 Fifty or more shades of cellular plasticity
- 38 Acknowledgements
