Cancer: A turbulence problem

Uthamacumaran, Abicumaran

doi:10.1016/j.neo.2020.09.008

Cited by 22 publications

(3 citation statements)

References 77 publications

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“…For instance, further exploration of biological systems could reveal more instances where diffusiophoresis contributes to pattern formation such as embryo morphogenesis ( 1 ) and early life ( 34 ), which could subsequently lead to a better understanding of how these patterns emerge, evolve, and adapt in different species. In recent years, an embryonic framework has gained attention for understanding cancer ecosystems as chaotic expressions of the complex interactions between cellular and chemical components ( 49 ), and Turing patterns are theorized to play an important role in tumorigenesis ( 50 ). Unveiling diffusiophoresis as a mechanism in cellular organization processes can be crucial to future cancer research.…”

Section: Discussionmentioning

confidence: 99%

Diffusiophoresis-enhanced Turing patterns

Alessio,

Gupta

2023

Sci. Adv.

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Turing patterns are fundamental in biophysics, emerging from short-range activation and long-range inhibition processes. However, their paradigm is based on diffusive transport processes that yield patterns with shallower gradients than those observed in nature. A complete physical description of this discrepancy remains unknown. We propose a solution to this phenomenon by investigating the role of diffusiophoresis, which is the propulsion of colloids by a chemical gradient, in Turing patterns. Diffusiophoresis enables robust patterning of colloidal particles with substantially finer length scales than the accompanying chemical Turing patterns. A scaling analysis and a comparison to recent experiments indicate that chromatophores, ubiquitous in biological pattern formation, are likely diffusiophoretic and the colloidal Péclet number controls the pattern enhancement. This discovery suggests that important features of biological pattern formation can be explained with a universal mechanism that is quantified straightforwardly from the fundamental physics of colloids.

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Section: Discussionmentioning

confidence: 99%

Diffusiophoresis-enhanced Turing patterns

Alessio,

Gupta

2023

Sci. Adv.

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“…Macrophages are related to various inflammatory respiratory illnesses, including acute lung injury (ALI) [ 7 ], asthma [ 8 ], and pulmonary fibrosis [ 9 ]. Currently, cancer ranks as the primary cause of disease-related deaths throughout the world [ 10 ]. The tumor microenvironment (TME), which drives the development of cancer, is complex and contains stromal cells, fibroblasts, endothelial cells, and immune cells [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Exosomal Non-Coding RNAs: Novel Regulators of Macrophage-Linked Intercellular Communication in Lung Cancer and Inflammatory Lung Diseases

et al. 2023

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Macrophages are innate immune cells and often classified as M1 macrophages (pro-inflammatory states) and M2 macrophages (anti-inflammatory states). Exosomes are cell-derived nanovesicles that range in diameter from 30 to 150 nm. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), are abundant in exosomes and exosomal ncRNAs influence immune responses. Exosomal ncRNAs control macrophage-linked intercellular communication via their targets or signaling pathways, which can play positive or negative roles in lung cancer and inflammatory lung disorders, including acute lung injury (ALI), asthma, and pulmonary fibrosis. In lung cancer, exosomal ncRNAs mediated intercellular communication between lung tumor cells and tumor-associated macrophages (TAMs), coordinating cancer proliferation, migration, invasion, metastasis, immune evasion, and therapy resistance. In inflammatory lung illnesses, exosomal ncRNAs mediate macrophage activation and inflammation to promote or inhibit lung damage. Furthermore, we also discussed the possible applications of exosomal ncRNA-based therapies for lung disorders.

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“…The other cell-centered, ‘cancer attractor’ theory suggests that oncogenesis is caused by a shift in cellular program activity towards a cancer attractor (stable state of cellular systems), which is achieved mostly via epigenetic mechanisms [ 29 , 41 , 42 ]. However, with a minor exception of transmissible tumors, cancers are not inheritable and reduce the fitness of a host organism.…”

Section: Introductionmentioning

confidence: 99%

Systemic Alterations of Cancer Cells and Their Boost by Polyploidization: Unicellular Attractor (UCA) Model

Vinogradov

Anatskaya

2023

IJMS

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Using meta-analyses, we introduce a unicellular attractor (UCA) model integrating essential features of the ‘atavistic reversal’, ‘cancer attractor’, ‘somatic mutation’, ‘genome chaos’, and ‘tissue organization field’ theories. The ‘atavistic reversal’ theory is taken as a keystone. We propose a possible mechanism of this reversal, its refinement called ‘gradual atavism’, and evidence for the ‘serial atavism’ model. We showed the gradual core-to-periphery evolutionary growth of the human interactome resulting in the higher protein interaction density and global interactome centrality in the UC center. In addition, we revealed that UC genes are more actively expressed even in normal cells. The modeling of random walk along protein interaction trajectories demonstrated that random alterations in cellular networks, caused by genetic and epigenetic changes, can result in a further gradual activation of the UC center. These changes can be induced and accelerated by cellular stress that additionally activates UC genes (especially during cell proliferation), because the genes involved in cellular stress response and cell cycle are mostly of UC origin. The functional enrichment analysis showed that cancer cells demonstrate the hyperactivation of energetics and the suppression of multicellular genes involved in communication with the extracellular environment (especially immune surveillance). Collectively, these events can unleash selfish cell behavior aimed at survival at all means. All these changes are boosted by polyploidization. The UCA model may facilitate an understanding of oncogenesis and promote the development of therapeutic strategies.

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Cancer: A turbulence problem

Cited by 22 publications

References 77 publications

Diffusiophoresis-enhanced Turing patterns

Diffusiophoresis-enhanced Turing patterns

Exosomal Non-Coding RNAs: Novel Regulators of Macrophage-Linked Intercellular Communication in Lung Cancer and Inflammatory Lung Diseases

Systemic Alterations of Cancer Cells and Their Boost by Polyploidization: Unicellular Attractor (UCA) Model

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