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

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. [Display omitted] •Fate-seq links the drug response of a single cell to its own transcriptomic profile•Fate-seq recovers variable cell decision information from unstructured variability•It identifies molecular factors causing the intrinsic resistance to cancer drugs•A TRAIL therapeutic efficacy profile is performed in HeLa cells as proof of concept For most cancer drug treatments, a fraction of the clonal cell population can survive because of non-genetic cell-to-cell variability. We present fate-seq, a method to determine the molecular origins of this heterogeneous drug response, by comparing the transcriptomic profiles of predicted resistant versus predicted sensitive cells, before treatment induces confounding changes.