Abstract PO-100: Expressed molecular barcoding coupled with single cell RNAseq enables a high resolution investigation into the evolution of drug tolerance
Authors: Jennifer L. Cotton, Viveksagar Krisnamurthy Radhakrishna, Javier Estrada Diez, David A. Ruddy, Kathleen Sprouffske, Gaylor Boulay, Michelle Piquet, Joel Wagner, Youngchul Song, Xiaoyan Li, Katja Schumacher, Joshua Korn, Erick J. Morris, Peter S. Hammerman, Jeffrey A. Engelman, Matthew J. Niederst
Journal: Cancer Research (2020)

Abstract EGFR targeted kinase inhibitors (TKIs) are the standard of care in non-small cell lung cancer (NSCLC) patients with activating mutations in the epidermal growth factor receptor (EGFR). Patients initially respond well to EGFR inhibitors, although the majority only achieve a partial response and a subset of drug-tolerant persister cells remain at minimal residual disease (MRD). These drug-tolerant persister cells represent a cell reservoir from which de novo genetic mutations, such as EGFRT790M or MET amplification, can arise to render the tumor fully drug-resistant. Previous studies suggest that drug-tolerant cells rely on an altered chromatin state to survive EGFR-inhibition. However, it is still unclear whether the drug-tolerant cell population emerges through selection for cells that pre-existed in that state or through and adaptation in response to drug. It is also unknown if drug-tolerant persister cells rely on a single survival mechanism that could be exploited to more effectively target this population or if multiple independent mechanisms are being utilized and need to be targeted to fully suppress drug tolerance. Despite the urgent clinical need to answer these questions, we have lacked the techniques capable of the dynamic resolution necessary to investigate the emergence of drug tolerance throughout the course of treatment within individual cell lineages. Here we present a strategy to investigate the clonal evolution of drug tolerance in EGFRmut NSCLC using an expressed molecular barcoding library coupled with single cell RNAseq (scRNAseq). We found that the cell lineages that are destined to become drug-tolerant are pre-defined, although the epigenetic drug-tolerant state does not pre-exist. We observed multiple distinct heterogeneous classes of drug-tolerant cells with unique gene expression signatures as well as distinct trajectories in response to EGFRi. We observed evidence of putative mechanisms of drug tolerance, such as EMT and adaptive MAPK signaling, in parallel trajectory classes across cell lines. Finally, we compared EGFRi/TKI drug combinations versus EGFRi/chemotherapy combinations to investigate which therapeutic approach was more efficacious in targeting multiple trajectory classes of drug tolerant cells. Taken together, our work presents a new technology that enables a comprehensive interrogation of drug response over time and provides greater insight into how drug-tolerant cells evolve over the course of drug treatment, which ultimately can help inform combination treatment strategies for patients in the clinic. Citation Format: Jennifer L. Cotton, Viveksagar Krisnamurthy Radhakrishna, Javier Estrada Diez, David A. Ruddy, Kathleen Sprouffske, Gaylor Boulay, Michelle Piquet, Joel Wagner, Youngchul Song, Xiaoyan Li, Katja Schumacher, Joshua Korn, Erick J. Morris, Peter S. Hammerman, Jeffrey A. Engelman, Matthew J. Niederst. Expressed molecular barcoding coupled with single cell RNAseq enables a high resolution investigation into the evolution of drug tolerance [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-100.