Profiling the Non-genetic Origins of Cancer Drug Resistance with a Single-Cell Functional Genomics Approach Using Predictive Cell Dynamics

Abstract

Non-genetic heterogeneity observed in clonal cell populations is an immediate cause of drug resistance that remains challenging to profile because of its transient nature. Here, we coupled three single-cell technologies to link the predicted drug response of a cell to its own genome-wide transcriptomic profile. As a proof of principle, we analyzed the response to tumor-necrosis-factor-related apoptosis-inducing ligand (TRAIL) in HeLa cells to demonstrate that cell dynamics can discriminate the transient transcriptional states at the origin of cell decisions such as sensitivity and resistance. Our same-cell approach, named fate-seq, can reveal the molecular factors regulating the efficacy of a drug in clonal cells, providing therapeutic targets of non-genetic drug resistance otherwise confounded in gene expression noise. A record of this paper's transparent peer review process is included in the Supplemental Information.

Keywords: cancer drug resistance; cell-to-cell variability; laser-capture microdissection; live-cell microscopy; pharmacogenomics; single-cell; systems biology; transcriptomics.