bioRxiv · 10.1101/508705
Identification of SNA-I-positive cells as stem-like cells in an established cell line using computerized single-cell lineage tracking
Abstract
To elucidate the dynamic evolution of cancer cell characteristics within the tumor microenvironment (TME), we developed an integrative method combining single-cell tracking, cell fate simulation, and three-dimensional (3D) TME modeling. We began our investigation by analyzing the spatiotemporal behavior of individual cancer cells in cultured pancreatic and cervical cancer cell lines, with a focus on the 2-6 sialic acid (2-6Sia) modification on glycans, which is associated with cell stemness. Our findings revealed that pancreatic cancer cells exhibited significantly higher levels of 2-6Sia modification, correlating with enhanced reproductive capabilities, whereas cervical cancer cells showed less prevalence of this modification. To accommodate the in vivo variability of 2-6Sia levels, we employed a cell fate simulation algorithm that digitally generates cell populations based on our observed data, simulating cell growth patterns. Subsequently, we constructed a 3D TME model incorporating these deduced cell populations along with specific immune cell landscapes derived from 193 cervical and 172 pancreatic cancer cases. Our analysis suggests that pancreatic cancer cells are less influenced by the immune cell landscape within the TME compared to cervical cancer cells, highlighting that the fate of cancer cells is shaped by both the surrounding immune landscape and the intrinsic characteristics of the cancer cells.
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Sato, S., Rancourt, A., Satoh, M. S.. 2018-12-31. Identification of SNA-I-positive cells as stem-like cells in an established cell line using computerized single-cell lineage tracking. https://doi.org/10.1101/508705
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