Abstract 2859: High-resolution lineage tracing for the study of cancer drug persistence at the single-cell level
Authors: Zhitomirsky Benny , Ezike Jideofor , Hopkins Elizabeth , Danysh Brian P. , Parida Laxmi , Oren Yaara , Getz Gad 
Published: June 2023

Cancer drug persistence allows small fractions of otherwise drug-sensitive populations of cancer cells to survive treatment with anti-cancer drugs. Unlike drug resistance, persistence mechanisms are not driven by genetic mutations, and are thus considered reversible after a ‘drug holiday’ period. While most persistent cells remain in cell cycle arrest under drug treatment, recent work with EGFR-mutant Non-Small Cell Lung Cancer (NSCLC) cell lines has demonstrated that a small fraction of persister cells continue to undergo cell divisions under treatment with EGFR inhibitors. Thus, persister cells have a two-fold potential clinical significance: (i) they can serve as an intermediate state, allowing a non-resistant cancer cell to survive long enough and continue to divide under drug treatment to acquire a resistance mutation; and (ii) cycling persister cells might directly contribute to relapse, without a secondary resistance-driving mutation. Despite this, little is known about the underlying mechanisms by which affect the potential of a given cell to persist, or about the epigenetic traits that govern the distribution of persistence potential in a cell population. In this work, we use high-resolution lineage tracing to study lineages of drug persistent cells within a cancer cell population. Using the PC9 NSCLC cell line as a model, we demonstrate that while most lineages within the PC9 cell population can generate persisters, certain branches within the lineage tree have significantly higher persistence potentials than other branches, suggesting that inherited events determine the probability of a cell to persist under treatment. Moreover, we analyze the rate of change of the potential to persist within a single-cell-derived lineage of NSCLC cells and assess which branches within the lineage tree generate cycling persisters. Furthermore, we couple single-cell RNAseq data with lineage tracing information to identify gene expression patterns that correlate with the probability of drug-naïve cells to persist under drug treatment, allowing for insight into the cellular and molecular mechanisms underlying the continuum of the probability to persist. Finally, we demonstrate that while persistent-derived PC9 cells are indeed resensitized after a drug holiday, they give rise to a significantly higher proportion of cycling persister cells upon resumption of drug treatment, allowing for a rapid repopulation of the cell culture by cycling persisters. These results suggest that lineage tracing is a powerful tool to study drug-induced persistence and resistance and we will apply it to multiple other cell lines and tumor types.

Citation Format: Benny Zhitomirsky, Jideofor Ezike, Elizabeth Hopkins, Brian P. Danysh, Laxmi Parida, Yaara Oren, Gad Getz. High-resolution lineage tracing for the study of cancer drug persistence at the single-cell level [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2859.