Reyes Hueros, R. A. | Search bioRxiv

bioRxiv2023

Non-genetic differences underlie variability in proliferation among esophageal epithelial clones

The growth potential of individual epithelial cells is a key determinant of tissue development, homeostasis, and disease progression. Although it is known that epithelial progenitor cells vary in their proliferative capacity, the cell states underlying these differences are yet to be uncovered. Here we performed clonal tracing through imaging and cellular barcoding of an in vitro model of esophageal epithelial cells (EPC2-hTERT). We found that individual clones possess unique growth and differentiation capacities, with a subset of clones growing exponentially. Further, we discovered that this proliferative potential for a clone is heritable through cell division and can be influenced by extrinsic cues from neighboring cells. Combining barcoding with single-cell RNA-sequencing (scRNA-seq), we identified the cellular states associated with the highly proliferative clones, which include genes in the WNT and PI3K pathways. Importantly, we also identified a subset of cells resembling the highly proliferative cell state in the healthy human esophageal epithelium and, to a greater extent, in esophageal squamous cell carcinoma (ESCC). These findings highlight the physiological relevance of our cell line model, providing insights into the behavior of esophageal epithelial cells during homeostasis and disease.

systems biology↗

bioRxiv2022

Disrupting cellular memory to overcome drug resistance

Plasticity enables cells to change their gene expression state in the absence of a genetic change. At the single-cell level, these gene expression states can persist for different lengths of time which is a quantitative measurement referred to as gene expression memory. Because plasticity is not encoded by genetic changes, these cell states can be reversible, and therefore, are amenable to modulation by disrupting gene expression memory. However, we currently do not have robust methods to find the regulators of memory or to track state switching in plastic cell populations. Here, we developed a lineage tracing-based technique to quantify gene expression memory and to identify single cells as they undergo cell state transitions. Applied to human melanoma cells, we quantified long-lived fluctuations in gene expression that underlie resistance to targeted therapy. Further, we identified the PI3K and TGF-{beta} pathways as modulators of these state dynamics. Applying the gene expression signatures derived from this technique, we find that these expression states are generalizable to in vivo models and present in scRNA-seq from patient tumors. Leveraging the PI3K and TGF-{beta} pathways as dials on memory between plastic states, we propose a " pretreatment" model in which we first use a PI3K inhibitor to modulate the expression states of the cell population and then apply targeted therapy. This plasticity informed dosing scheme ultimately yields fewer resistant colonies than targeted therapy alone. Taken together, we describe a technique to find modulators of gene expression memory and then apply this knowledge to alter plastic cell states and their connected cell fates.

systems biology↗