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Tumor Progression02:07

Tumor Progression

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Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
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Cancer02:18

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Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.
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Under normal conditions, most adult cells remain in a non-proliferative state unless stimulated by internal or external factors to replace lost cells. Abnormal cell proliferation is a condition in which the cell's growth exceeds and is uncoordinated with normal cells. In such situations, cell division persists in the same excessive manner even after cessation of the stimuli, leading to persistent tumors. The tumor arises from the damaged cells that replicate to pass the damage to the...
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Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...
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Induction and Diagnosis of Tumors in Drosophila Imaginal Disc Epithelia
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Tumors as chaotic attractors.

Svetoslav Nikolov1, Olaf Wolkenhauer, Julio Vera

  • 1Department of Systems Biology and Bioinformatics, Institute for Informatics, University of Rostock, 18051 Rostock, Germany.

Molecular Biosystems
|November 22, 2013
PubMed
Summary

Tumors exhibit complex dynamics akin to strange attractors, featuring local instability and global stability. This characteristic explains tumor robustness, plasticity, and resistance to anti-cancer therapies.

Area of Science:

  • Complex Systems Biology
  • Cancer Research
  • Non-linear Dynamics

Background:

  • Malignant tumor growth, progression, and evolution share characteristics with strange attractors, a type of non-linear dynamical system behavior.
  • Genetic instability drives tumor evolution, while selective pressures promote stability and robustness against perturbations.
  • This interplay of local instability and global stability contributes to tumor robustness, plasticity, and resistance to therapies.

Purpose of the Study:

  • To conceptualize tumors as dynamical systems exhibiting strange attractor properties.
  • To investigate key features of tumors as dynamical systems, including local instability, global stability, self-similarity, and sensitivity to initial conditions.
  • To provide a framework for developing experimental and computational tools linking micro- and mesoscopic tumor biology.

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Main Methods:

  • Conceptual framework development: viewing tumors as dynamical systems with strange attractor characteristics.
  • Investigation of inherent system features: local instability, global stability, self-similarity, and sensitivity to initial conditions.
  • Focus on non-linear dynamics within tumor biochemical regulatory circuits and cell interactions.

Main Results:

  • Tumors demonstrate local instability coupled with global stability, a hallmark of strange attractors.
  • Self-similarity across different biological levels and strong sensitivity to initial conditions were identified as key features.
  • The dynamical system perspective offers insights into tumor robustness and therapeutic resistance.

Conclusions:

  • Tumors can be effectively modeled as dynamical systems exhibiting strange attractor behaviors.
  • Understanding tumors as strange attractors elucidates their inherent robustness, plasticity, and resistance to anti-cancer treatments.
  • This paradigm necessitates integrated experimental and computational approaches for a comprehensive view of tumor biology.