2013/01/16 by Jacob G. Scott, Scott, Jacob G., Prakash Chinnaiyan +9
Biochemistry, Genetics and Molecular Biology · Computer Science · Medicine · Pharmacology, Toxicology and Pharmaceutics · #Cancer Cells and Metastasis #Chemical Reactions and Isotopes #Computational Engineering #FOS: Biological sciences #FOS: Computer and information sciences #FOXO transcription factor regulation #Finance #Tissues and Organs (q-bio.TO) #and Science (cs.CE) #cs.CE #q-bio.TO
paper · pdf · doi:10.48550/arxiv.1301.3934
8 pages, 4 figures
openalex publication_date 2013/01/16 · arxiv created 2013/08/20 · arxiv updated 2013/08/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Since the discovery of a cancer initiating side population in solid tumours, studies focussing on the role of so-called cancer stem cells in cancer initiation and progression have abounded. The biological interrogation of these cells has yielded volumes of information about their behaviour, but there has, as of yet, not been many actionable generalised theoretical conclusions. To address this point, we have created a hybrid, discrete/continuous computational cellular automaton model of a generalised stem-cell driven tissue and explored the phenotypic traits inherent in the inciting cell and the resultant tissue growth. We identify the regions in phenotype parameter space where these initiating cells are able to cause a disruption in homeostasis, leading to tissue overgrowth and tumour formation. As our parameters and model are non-specific, they could apply to any tissue cancer stem-cell and do not assume specific genetic mutations. In this way, our model suggests that targeting these phenotypic traits could represent generalizable strategies across cancer types and represents a first attempt to identify the hallmarks of cancer stem cells.