Identifying transcriptional programs underlying cancer drug response with TraCe-seq

Abstract

Genetic and non-genetic heterogeneity within cancer cell populations represent major challenges to anticancer therapies. We currently lack robust methods to determine how preexisting and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA sequencing (scRNA-seq), we have developed tracking differential clonal response by scRNA-seq (TraCe-seq). TraCe-seq is a method that captures at clonal resolution the origin, fate and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual epidermal growth factor receptor (EGFR) inhibitor-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. We identified a loss of antigrowth activity associated with targeted degradation of EGFR protein and an essential role of the endoplasmic reticulum (ER) protein processing pathway in anti-EGFR therapeutic efficacy. Our results suggest that targeted degradation is not always superior to enzymatic inhibition and establish TraCe-seq as an approach to study how preexisting transcriptional programs affect treatment responses.