Spatial self-organization of cancer stem cell niches revealed by live single-cell imaging

Abstract

Background: Phenotypic plasticity is a major factor in tumor heterogeneity and treatment resistance. In particular, cancer stem cells (CSCs) represent a small subpopulation within tumors that possesses self-renewal and tumor-forming capabilities. Understanding reprogramming, maintenance, and lineage properties of CSCs requires dedicated tools to disentangle the respective influences of phenotypic inheritance and cell-cell interactions. Methods: Here, we set up ultra-wide field microscopy to image breast cancer cell lines expressing a stemness fluorescent reporter over several days. The fluorescent reporter distinguishes three phenotypes: CSCs, cancer differentiated cells (CDCs), and intermediate/transiting cancer cells (iCCs). Results: Spatial statistics indicate significant zonation in which CSCs cluster together and are spatially separated from CDCs, forming patterns resembling niches. Surprisingly, single-cell time series reveal spontaneous reprogramming events from CDC to CSC even in unperturbed populations. We identify that such transitions are prone to arise during the cell cycle. Moreover, lineage analysis shows that the phenotype is partially inherited from ancestor cells. However, such heredity is not sufficient to explain the spatial properties of the cell population, which also depend on cell-cell interactions. Indeed, we find that phenotypic transitions of cancer cells are influenced by the phenotypic state of neighboring cells. Reprogramming into CSCs is respectively promoted and inhibited by the presence of CSCs and CDCs in the neighborhood. Conclusions: Altogether, our results disentangle how phenotypic inheritance and intercellular interactions orchestrate the spatio-temporal self-organization of cancer cell heterogeneity, maintaining a subpopulation of CSCs within niches.

1. Introduction

Tumors consist of multiple sub-populations of cells, each differing in their response to drugs and ability to adapt to environmental changes. This variability between cells significantly influences therapeutic outcomes and affects disease progression [1, 2]. While part of this variability in treatment response can be attributed to the presence of distinct genetic and epigenetic profiles [1, 3–5], the existence of multiple phenotypic states, resembling the hierarchical organization of normal tissues, plays a crucial role in tumorigenesis and treatment resistance [6–8]. At the apex of this hierarchy, Cancer Stem Cells (CSCs) generate cellular diversity by differentiation within the tumor [8, 9].

This process is not strictly unidirectional, as cells can switch between states in response to specific conditions, a phenomenon known as cell plasticity [10–14]. This ability of cells to transition between states enables them to evade selective pressures during tumor progression, metastasis, and resistance to treatment [14, 15]. For instance, phenotypic plasticity was shown to be triggered during tumor progression, such as epithelial-to-mesenchymal transition [14, 16] or immune escape [17, 18]. Consequently, cellular plasticity, which enables dynamic transitions between CSCs and non-CSCs, may undermine therapeutic strategies aimed solely at eliminating CSCs [9, 13, 19, 20]. A deeper understanding of phenotypic plasticity is essential for developing effective treatments that can target and deplete the CSC population [9].

Under homeostatic conditions, a complex network maintains a balance between stem-like and differentiated cells. This equilibrium is critical for tissue integrity and is often disrupted in cancer, leading to uncontrolled growth and therapy resistance. The mechanisms that govern this balance, including the role of the microenvironment and cell-cell communication, remain incompletely understood. In this study, we employ advanced live-cell imaging to investigate the spatiotemporal dynamics of CSC and non-CSC populations, aiming to uncover the principles that drive the self-organization of tumor heterogeneity.