A Voxel Model to Decipher the Role of Molecular Communication in the Growth of Glioblastoma Multiforme

Awan, Hamdan and Balasubramaniam, Sasitharan and Odysseos, Andreani (2021) A Voxel Model to Decipher the Role of Molecular Communication in the Growth of Glioblastoma Multiforme. IEEE Transactions on Nanobioscience, 20 (3). pp. 296-310. ISSN 1536-1241

Full text not available from this repository. (Request a copy)

Abstract

Glioblastoma Multiforme (GBM), the most malignant human tumour, can be defined by the evolution of growing bio-nanomachine networks within an interplay between self-renewal (Grow) and invasion (Go) potential of mutually exclusive phenotypes of transmitter and receiver cells. Herein, we present a mathematical model for the growth of GBM tumour driven by molecule-mediated inter-cellular communication between two populations of evolutionary bio-nanomachines representing the Glioma Stem Cells (GSCs) and Glioma Cells (GCs). The contribution of each subpopulation to tumour growth is quantified by a voxel model representing the end to end inter-cellular communication models for GSCs and progressively evolving invasiveness levels of glioma cells within a network of diverse cell configurations. Mutual information, information propagation speed and the impact of cell numbers and phenotypes on the communication output and GBM growth are studied by using analysis from information theory. The numerical simulations show that the progression of GBM is directly related to higher mutual information and higher input information flow of molecules between the GSCs and GCs, resulting in an increased tumour growth rate. These fundamental findings contribute to deciphering the mechanisms of tumour growth and are expected to provide new knowledge towards the development of future bio-nanomachine-based therapeutic approaches for GBM.

Item Type:	Article
Additional Information:	Funding Information: Manuscript received November 26, 2020; revised February 22, 2021; accepted March 30, 2021. Date of publication April 8, 2021; date of current version July 1, 2021. This work was supported by the European Union EU-FET-Open H2020 Gladiator Project under Grant 828837. The work of Sasitharan Balasubramaniam was supported in part by the FutureNeuro from Science Foundation Ireland (SFI) under Grant 16/RC/3948, in part by the European Regional Development Fund, and in part by FutureNeuro Industry Partners. (Corresponding author: Hamdan Awan.) Hamdan Awan is with the Walton Institute for Information and Communication Systems Science, Waterford Institute of Technology, Waterford, X91 P20H Ireland (e-mail: hamdan.awan@waltoninstitute.ie). Publisher Copyright: © 2002-2011 IEEE.
Uncontrolled Keywords:	/dk/atira/pure/subjectarea/asjc/1300/1305
Departments or Groups:
Depositing User:	Admin SSL
Date Deposited:	19 Oct 2022 23:06
Last Modified:	01 Aug 2023 16:05
URI:	http://repository-testing.wit.ie/id/eprint/4083

Actions (login required)

View Item