Dynamic network and epigenetic landscape model of a regulatory core underlying spontaneous immortalization and epithelial carcinogenesis

TL;DR

This paper develops a minimal gene regulatory network model that captures the key cell state transitions during epithelial cell transformation and carcinogenesis, integrating molecular data and epigenetic landscape analysis.

Contribution

It introduces a reduced regulatory core model that explains cell state transitions and tumorigenic progression in epithelial cells, linking molecular interactions to observed phenotypes.

Findings

The network has three stable states corresponding to normal, senescent, and mesenchymal stem-like cells.

The model reproduces the time-ordered cell state transitions during tumorigenic transformation.

Epigenetic landscape analysis aligns with in vitro and in vivo epithelial carcinogenesis patterns.

Abstract

Tumorigenic transformation of human epithelial cells in vitro has been described experimentally as the potential result of a process known as spontaneous immortalization. In this process a generic series of cell state transitions occur in which normal epithelial cells acquire a senescent state, later surpassed to attain first a mesenchymal state and then a final mesenchymal stem-like phenotype, with potential tumorigenic behavior. In this paper we integrate published data on the molecular components and interactions that have been described as key regulators of such cell states and transitions. A large network, that is provided, is constructed and then reduced with the aim of recovering a minimal regulatory core incorporating the necessary and sufficient restrictions to recover the observed cell states and their generic progression patterns in epithelial-mesenchymal transition. Data is formalized into logical regulatory rules that govern the dynamics of each of the network's components as a function of the states of its regulators. The proposed core gene regulatory network attains only three steady-state gene expression configurations that correspond to the profiles characteristic of normal epithelial, senescent, and mesenchymal stem-like cells. Interestingly, epigenetic landscape analyses of the uncovered network shows that it also recovers the generic time-ordered transitions documented during tumorigenic transformation in vitro of epithelial cells. The latter strongly correlate with the patterns observed during the progressive pathological description of epithelial carcinogenesis in vivo.