Abstract Relapses in cancer therapy occur due to the presence of sub-populations that exhibit intrinsic or acquired resistance to treatment. Acquired resistance can arise via non-mutational adaptive mechanisms in response to a perturbation. Identification of these heterogenous mechanisms mediated via stochastic changes in cellular signaling is challenging using traditional bulk methods that average signals at a cellular population level. We harnessed the power of single-cell RNA sequencing (scRNA-seq) to identify the adaptive resistance mechanisms to regorafenib, a clinically approved multi-tyrosine kinase inhibitor, in a colon cancer model. HCT116 cells were treated with an IC50 dose of regorafenib or vehicle control for 1 hour, 3 days, 7 days or 12 days and subjected to scRNA-seq using the 10X Genomics platform. Cells were sequenced at an average depth of 50000 reads/cell using Illumina sequencing. We controlled for batch effects by incorporating independent biological replicates and multiplexing using cell “hashing” with barcoded antibodies (BD Biosciences). Graph-based clustering, differential expression analysis and cell cycle phase assignment was performed using the Seurat algorithm. Proliferation was assessed using PI staining for cell cycle status, CellTiter Blue viability assay and clonogenic assays. We analyzed a total of 19,879 single cells following a time-course of regorafenib or vehicle treatment. Regorafenib treatment at one hour resulted in no significant transcriptional changes. At all further time points, we could confirm the down-regulation of MAPK signaling, reflecting the mechanism of action of regorafenib. At 72 hours, we detected sub-populations with varying activation levels of ER stress response and increased lipid metabolism, together with upregulation of transcription factors SOX4 and ID3. These features continued to be detected till 7 and 12 days after treatment. By 12 days, we observed upregulation of keratins 7, 8, 10, 18, 19 together with markers of G2M/S phase progression. Survival of clonal cell populations at 12 days was confirmed by crystal violet staining. Small molecule-based inhibition of ER stress (azoramide) and lipid synthesis (fatostain) was synergistic with regorafenib at day 3 and successfully inhibited the emergence of these resistant clones by day 12. Our results reveal multiple signaling events that lead to a resistance phenotype characterized by increased proliferation and keratin upregulation that can be counteracted by combination therapies. For future studies we will continue to dissect the molecular networks underlying these events by gene silencing and protein over-expression studies. Citation Format: Anuja Sathe, Billy T. Lau, Sue Grimes, Stephanie Greer, Hanlee Ji. Single cell RNA sequencing reveals multiple adaptive resistance mechanisms to regorafenib in colon cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2105.