Emergence of heterogeneity in triple negative breast cancer resulting from stochastic loss of information at the single-cell level
Meyer CT1, Tyson DR2, Quaranta V2
1Chemical and Physical Biology; 2Cancer Biology, Vanderbilt University
The dynamic of diversification undergirding the emergence of heterogeneity in triple negative breast cancer (TNBC) has previously been proposed to result from state transitions, but this model paradigm lacks direct experimental observation and relies on cell states segregated by binning. To address these problems, we developed an information theory framework to quantify diversification at single-cell resolution. This approach, based on recent advances in particle-tracking algorithms, enabled us to track temporal fluctuations of cell-surface markers EpCAM/CD44 in several thousand single-cells of H2B-RFP tagged TNBC cell lines SUM14PT and MDA-MB468. Comparing a cell’s EpCAM/CD44 median expression to its progeny revealed only a moderate correlation (r<0.7 for both cell lines) suggesting an unexpectedly high rate of information decay in cell-identity specification between generations. Under the assumption cell divisions are a Markovian process, we fit the decrease in mutual information between generations to an exponential decay. This fit predicts regardless of initial expression profile, the progeny of a single cell can reposition itself anywhere in the original state space in as few as ten generations. Preliminary experimental results indicate a mutagen (cisplatin) and an epigenetic modifier (valproic acid) increase the rate of information decay, implying that compounds targeting mechanism preserving information transfer may accelerate the pace tumor heterogeneity emerges.
Our results indicate changes in cell-identity do not occur discretely during the lifetime of a cell, as postulated by previous theoretical models of diversification dynamics. Rather, we posit the diversification dynamics are the outcome of progressive loss of information across cell generations. Looking forward, the next challenge is stratifying the contribution of different molecular mechanisms to the integrity of information transfer between generations.