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Cancers
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Dynamics of Cancer: Complexity and Hierarchy on Cancer Cells and...
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Dynamics of Cancer: Complexity and Hierarchy on Cancer Cells and Tissues

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Biomarkers".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4437

Special Issue Editors

Dr. Evangelia Sarantopoulou

E-Mail Website
Guest Editor
Theoretical and Physical Chemistry Institute, National Hellenic Research Foundation, 48 Vassileos Constantinou Avenue, 11635 Athens, Greece
Interests: biophysics; cancer cells; nanomedicine; complexity in biosystems; nanomechanics
Special Issues, Collections and Topics in MDPI journals
Dr. Angelo Ferraro

E-Mail Website
Co-Guest Editor
Laboratory of Electronic Sensors, National Technical University of Athens, Iroon Polytechniou 9, 15780 Zografou, Attiki, Greece
Interests: epigenetics; nucleosomes dynamics; chromatin dynamics; chromatin remodelling; cytoskeleton geometry; plasma membrane structure

Special Issue Information

Dear Colleagues,

Cancer is a complex disease, highly heterogeneous even for similar cells. Among other factors, tumor growth depends on dynamic interactions between cells and the continuously changing extracellular matrix microenvironment. It is still unknown why cancer therapies are more effective for some individuals and not for others. An interdisciplinary approach where physics, system dynamics, and biology will be integrated with traditional methods will tackle the challenge.

Generally, dynamical systems, such as cancerous ones, have structural (“hardware”) and functional (“software”) connotations that form ensembles of successfully interacting nested sets and subunits of variables and parameters forming different hierarchical dynamical states.

In the current Special Issue, novel topics, including cell and tissue biophysics and dynamics, biomechanics, nano-bio interactions, complexity, hierarchy, stability, chaos, the flow of information, cell memory, and novel cancer therapeutic and diagnostic methods at the nanoscale are welcome.

Dr. Evangelia Sarantopoulou
Dr. Angelo Ferraro
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cancer cells and tumors
  • cancer biophysics
  • cancer dynamics
  • cancer biomechanics
  • cancer nano-bio interactions
  • complexity and hierarchy in carcinomas
  • cancer fractality and chaos
  • cancer AFM diagnostic
  • cancer imaging
  • cancer therapeutics

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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18 pages, 7864 KiB  
Article
Nanoscale Prognosis of Colorectal Cancer Metastasis from AFM Image Processing of Histological Sections
by Vassilios Gavriil, Angelo Ferraro, Alkiviadis-Constantinos Cefalas, Zoe Kollia, Francesco Pepe, Umberto Malapelle, Caterina De Luca, Giancarlo Troncone and Evangelia Sarantopoulou
Cancers 2023, 15(4), 1220; https://doi.org/10.3390/cancers15041220 - 14 Feb 2023
Cited by 2 | Viewed by 1977
Abstract
Early ascertainment of metastatic tumour phases is crucial to improve cancer survival, formulate an accurate prognostic report of disease advancement, and, most importantly, quantify the metastatic progression and malignancy state of primary cancer cells with a universal numerical indexing system. This work proposes [...] Read more.
Early ascertainment of metastatic tumour phases is crucial to improve cancer survival, formulate an accurate prognostic report of disease advancement, and, most importantly, quantify the metastatic progression and malignancy state of primary cancer cells with a universal numerical indexing system. This work proposes an early improvement to metastatic cancer detection with 97.7 nm spatial resolution by indexing the metastatic cancer phases from the analysis of atomic force microscopy images of human colorectal cancer histological sections. The procedure applies variograms of residuals of Gaussian filtering and theta statistics of colorectal cancer tissue image settings. This methodology elucidates the early metastatic progression at the nanoscale level by setting metastatic indexes and critical thresholds based on relatively large histological sections and categorising the malignancy state of a few suspicious cells not identified with optical image analysis. In addition, we sought to detect early tiny morphological differentiations indicating potential cell transition from epithelial cell phenotypes of low metastatic potential to those of high metastatic potential. This metastatic differentiation, which is also identified in higher moments of variograms, sets different hierarchical levels for metastatic progression dynamics. Full article
(This article belongs to the Special Issue Dynamics of Cancer: Complexity and Hierarchy on Cancer Cells and Tissues)
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24 pages, 14463 KiB  
Article
Stochasticity and Drug Effects in Dynamical Model for Cancer Stem Cells
by Ludovico Mori and Martine Ben Amar
Cancers 2023, 15(3), 677; https://doi.org/10.3390/cancers15030677 - 21 Jan 2023
Cited by 2 | Viewed by 1852
Abstract
The Cancer Stem Model allows for a dynamical description of cancer colonies which accounts for the existence of different families of cells, namely stem cells, highly proliferating and quasi-immortal, and differentiated cells, both undergoing cellular processes under numerous activated pathways. In the present [...] Read more.
The Cancer Stem Model allows for a dynamical description of cancer colonies which accounts for the existence of different families of cells, namely stem cells, highly proliferating and quasi-immortal, and differentiated cells, both undergoing cellular processes under numerous activated pathways. In the present work, we investigate a dynamical model numerically, as a system of coupled differential equations, and include a plasticity mechanism, of differentiated cells turning into a stem state if the stem concentration drops low. We are particularly interested in the stability of the model once we introduce stochastically evolving parameters, associated with environmental and cellular intrinsic variabilities, as well as the response of the model after introducing a drug therapy. As long as we stay within the characteristic time scale of the system, defined on the base of the needed time for the trajectories to converge on stable states, we observe that the system remains stable for the main parameters evolving stochastically according to white noise. As for the drug treatments, we discuss a model both for the kinetics and the dynamics of the substance in the organism, and then consider the impact of different types of therapies in a few particular examples, outlining some interesting mechanisms, such as the tumor growth paradox, that possibly impact the outcome of therapy significantly. Full article
(This article belongs to the Special Issue Dynamics of Cancer: Complexity and Hierarchy on Cancer Cells and Tissues)
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