Special Issue "Networks in Cancer: From Symmetry Breaking to Targeted Therapy"

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Biology and Symmetry/Asymmetry".

Deadline for manuscript submissions: closed (15 November 2022) | Viewed by 5883

Special Issue Editors

Dr. Cristian Axenie
E-Mail Website
Guest Editor
Audi Konfuzius-Institut Ingolstadt Lab, Technische Hochschule Ingolstadt, Ingolstadt, Germany
Interests: research interest in developing novel machine learning tools for biomechanics and biomedical engineering, with a focus on integrative mathematical and computational oncology
Dr. María Rodríguez Martínez
E-Mail Website
Guest Editor
IBM Research Europe, 8803 Rüschlikon, Switzerland
Interests: machine learning; interpretable deep learning; multi-omics data integration; mechanistic models; cancer immunotherapies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Seen as a disease of the cell, cancer describes the symmetry breaking in a cell’s homeostasis and consequently its aberrant proliferation, differentiation, and death mechanisms. Beyond the cell, the tumor microenvironment describes the multi-variate phenotypic behavior of networks of cells and their interactions through different signaling pathways. Both cancer cells and host cells can display coupled phenotypic plasticity in response to these communicating signals. Such manifestations determine symmetry breaking in physical properties of their environment. This leads to complex spatiotemporal interaction patterns that impact therapeutic response that is aiming at restoring local symmetry and stability. Yet, driving the tumor-immune-host system to symmetric behavior under spatial and temporal constraints requires new analysis tools driving therapy. The emerging question about how to account for such spatiotemporal characteristics of these interaction networks, when analyzing cancer growth dynamics, is novel and largely unexplored by current standards. Mathematical and computational oncology can play an important role in extrapolating findings from in vitro experiments to in vivo conditions by means of in silico models. More precisely, such approaches allow for simulations of cancer therapies and can offer insights into their effects on the underlying symmetry breaking and symmetry preserving network-level interactions (e.g., tumor-immune interplay, gene regulatory networks, signal transduction networks, and proteolytic networks). Closing the loop, the captured insights can be used to make predictions about cancer progression and response to therapy on a patient-specific basis.

The aim of the present Special Issue is to gather the latest developments in mathematical and computational oncology tools for the mathematical modeling, analysis, and simulation of symmetry breaking and symmetry preserving network-level interactions used in therapy design.

We are soliciting contributions (research and review articles) covering a broad range of topics on Mathematical and Computational Oncology, including (though not limited to) the following:

  • Models and analysis of the symmetry breaking and symmetry preserving interplay between tumor and immune systems.
  • Models and analysis tools for symmetry breaking and symmetry preserving dynamics of signal transduction networks.
  • Models, analysis, and simulation of gene regulatory networks in cancer.
  • Models of proteolytic network interactions within cancer signaling pathways.
  • Finite element and continuum-based tools for modeling network interactions in cancer (e.g. tumor-immune, gene regulatory networks, etc.).
  • Agent-Based Modelling tools for symmetry breaking and symmetry preserving network interactions in cancer (e.g. tumor-immune, gene regulatory networks, etc.).
  • Machine Learning tools describing symmetry breaking and symmetry preserving spatiotemporal patterns of network interactions.
  • Hybrid modeling and simulation frameworks for cancer mechano-biology.

Submit your paper and select the Journal “Symmetry” and the Special Issue “Networks in Cancer: From Symmetry Breaking to Targeted Therapy” via: MDPI submission system. Our papers will be published on a rolling basis and we will be pleased to receive your submission once you have finished it.

Dr. Cristian Axenie
Dr. María Rodríguez Martínez
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 short 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. Symmetry is an international peer-reviewed open access monthly 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 1800 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

  • Mathematical Oncology
  • Cancer
  • Networks
  • Immune System
  • Genetics
  • Mechano-biology
  • Machine Learning

Published Papers (4 papers)

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Research

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Article
Antifragile Control Systems: The Case of an Anti-Symmetric Network Model of the Tumor-Immune-Drug Interactions
Symmetry 2022, 14(10), 2034; https://doi.org/10.3390/sym14102034 - 29 Sep 2022
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Abstract
A therapy’s outcome is determined by a tumor’s response to treatment which, in turn, depends on multiple factors such as the severity of the disease and the strength of the patient’s immune response. Gold standard cancer therapies are in most cases fragile when [...] Read more.
A therapy’s outcome is determined by a tumor’s response to treatment which, in turn, depends on multiple factors such as the severity of the disease and the strength of the patient’s immune response. Gold standard cancer therapies are in most cases fragile when sought to break the ties to either tumor kill ratio or patient toxicity. Lately, research has shown that cancer therapy can be at its most robust when handling adaptive drug resistance and immune escape patterns developed by evolving tumors. This is due to the stochastic and volatile nature of the interactions, at the tumor environment level, tissue vasculature, and immune landscape, induced by drugs. Herein, we explore the path toward antifragile therapy control, that generates treatment schemes that are not fragile but go beyond robustness. More precisely, we describe the first instantiation of a control-theoretic method to make therapy schemes cope with the systemic variability in the tumor-immune-drug interactions and gain more tumor kills with less patient toxicity. Considering the anti-symmetric interactions within a model of the tumor-immune-drug network, we introduce the antifragile control framework that demonstrates promising results in simulation. We evaluate our control strategy against state-of-the-art therapy schemes in various experiments and discuss the insights we gained on the potential that antifragile control could have in treatment design in clinical settings. Full article
(This article belongs to the Special Issue Networks in Cancer: From Symmetry Breaking to Targeted Therapy)
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Article
A Structural Characterisation of the Mitogen-Activated Protein Kinase Network in Cancer
Symmetry 2022, 14(5), 1009; https://doi.org/10.3390/sym14051009 - 16 May 2022
Viewed by 837
Abstract
Gene regulatory networks represent collections of regulators that interact with each other and with other molecules to govern gene expression. Biological signalling networks model how signals are transmitted and how activities are coordinated in the cell. The study of the structure of such [...] Read more.
Gene regulatory networks represent collections of regulators that interact with each other and with other molecules to govern gene expression. Biological signalling networks model how signals are transmitted and how activities are coordinated in the cell. The study of the structure of such networks in complex diseases such as cancer can provide insights into how they function, and consequently, suggest suitable treatment approaches. Here, we explored such topological characteristics in the example of a mitogen-activated protein kinase (MAPK) signalling network derived from published studies in cancer. We employed well-established techniques to conduct network analyses, and collected information on gene function as obtained from large-scale public databases. This allowed us to map topological and functional relationships, and build hypotheses on this network’s functional consequences. In particular, we find that the topology of this MAPK network is highly non-random, modular and robust. Moreover, analysis of the network’s structure indicates the presence of organisational features of cancer hallmarks, expressed in an asymmetrical manner across communities of the network. Finally, our results indicate that the organisation of this network renders it problematic to use treatment approaches that focus on a single target. Our analysis suggests that multi-target attacks in a well-orchestrated manner are required to alter how the network functions. Overall, we propose that complex network analyses combined with pharmacological insights will help inform on future treatment strategies, exploiting structural vulnerabilities of signalling and regulatory networks in cancer. Full article
(This article belongs to the Special Issue Networks in Cancer: From Symmetry Breaking to Targeted Therapy)
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Article
A 3D Agent-Based Model of Lung Fibrosis
Symmetry 2022, 14(1), 90; https://doi.org/10.3390/sym14010090 - 06 Jan 2022
Cited by 2 | Viewed by 1064
Abstract
Understanding the pathophysiology of lung fibrosis is of paramount importance to elaborate targeted and effective therapies. As it onsets, the randomly accumulating extracellular matrix (ECM) breaks the symmetry of the branching lung structure. Interestingly, similar pathways have been reported for both idiopathic pulmonary [...] Read more.
Understanding the pathophysiology of lung fibrosis is of paramount importance to elaborate targeted and effective therapies. As it onsets, the randomly accumulating extracellular matrix (ECM) breaks the symmetry of the branching lung structure. Interestingly, similar pathways have been reported for both idiopathic pulmonary fibrosis and radiation-induced lung fibrosis (RILF). Individuals suffering from the disease, the worldwide incidence of which is growing, have poor prognosis and a short mean survival time. In this context, mathematical and computational models have the potential to shed light on key underlying pathological mechanisms, shorten the time needed for clinical trials, parallelize hypotheses testing, and improve personalized drug development. Agent-based modeling (ABM) has proven to be a reliable and versatile simulation tool, whose features make it a good candidate for recapitulating emergent behaviors in heterogeneous systems, such as those found at multiple scales in the human body. In this paper, we detail the implementation of a 3D agent-based model of lung fibrosis using a novel simulation platform, namely, BioDynaMo, and prove that it can qualitatively and quantitatively reproduce published results. Furthermore, we provide additional insights on late-fibrosis patterns through ECM density distribution histograms. The model recapitulates key intercellular mechanisms, while cell numbers and types are embodied by alveolar segments that act as agents and are spatially arranged by a custom algorithm. Finally, our model may hold potential for future applications in the context of lung disorders, ranging from RILF (by implementing radiation-induced cell damage mechanisms) to COVID-19 and inflammatory diseases (such as asthma or chronic obstructive pulmonary disease). Full article
(This article belongs to the Special Issue Networks in Cancer: From Symmetry Breaking to Targeted Therapy)
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Perspective
The Multiple Dimensions of Networks in Cancer: A Perspective
Symmetry 2021, 13(9), 1559; https://doi.org/10.3390/sym13091559 - 25 Aug 2021
Cited by 3 | Viewed by 1728
Abstract
This perspective article gathers the latest developments in mathematical and computational oncology tools that exploit network approaches for the mathematical modelling, analysis, and simulation of cancer development and therapy design. It instigates the community to explore new paths and synergies under the umbrella [...] Read more.
This perspective article gathers the latest developments in mathematical and computational oncology tools that exploit network approaches for the mathematical modelling, analysis, and simulation of cancer development and therapy design. It instigates the community to explore new paths and synergies under the umbrella of the Special Issue “Networks in Cancer: From Symmetry Breaking to Targeted Therapy”. The focus of the perspective is to demonstrate how networks can model the physics, analyse the interactions, and predict the evolution of the multiple processes behind tumour-host encounters across multiple scales. From agent-based modelling and mechano-biology to machine learning and predictive modelling, the perspective motivates a methodology well suited to mathematical and computational oncology and suggests approaches that mark a viable path towards adoption in the clinic. Full article
(This article belongs to the Special Issue Networks in Cancer: From Symmetry Breaking to Targeted Therapy)
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