Stem Cells: The Good, the Bad and the Ugly

TL;DR

This paper explores the network-based mechanisms differentiating normal and cancer stem cells, emphasizing the importance of spatial-temporal gene activation and proposing targeted therapies based on stem cell hierarchy.

Contribution

It introduces a stem cell network theory that predicts stem cell behavior and suggests new diagnostic and therapeutic strategies for cancer treatment.

Findings

Cancer stem cells and normal stem cells share network architecture.

Metastatic potential is driven by genetic changes, not network divergence.

Targeting highest order stem cells may improve cancer therapy outcomes.

Abstract

Cancer stem cells are controlled by developmental networks that are often topologically indistinguishable from normal, healthy stem cells. The question is why cancer stem cells can be both phenotypically distinct and have morphological effects so different from normal stem cells. The difference between cancer stem cells and normal stem cells lies not in differences their network architecture, but rather in the spatial-temporal locality of their activation in the genome and the resulting expression in the body. The metastatic potential cancer stem cells is not based primarily on their network divergence from normal stem cells, but on non-network based genetic changes that enable the evolution of gene-based phenotypic properties of the cell that permit its escape and travel to other parts of the body. Stem cell network theory allows the precise prediction of stem cell behavioral dynamics and a mathematical description of stem cell proliferation for both normal and cancer stem cells. It indicates that the best therapeutic approach is to tackle the highest order stem cells first, otherwise spontaneous remission of so called cured cancers will always be a danger. Stem cell networks point to a pathway to new methods to diagnose and cure not only stem cell cancers but cancers generally.