Selection for targeted therapy resistance leads to an indirect selection for higher phenotypic plasticity and enhanced evolvability to orthogonal stressors

ABSTRACT Acquired resistance to targeted therapies is a primary barrier to durable cancer control. Resistance frequently coincides with stem-like features and EMT-associated cell-state changes (partial EMT), yet whether these programs directly cause resistance or instead enable escape by increasing phenotypic plasticity remains debated. Integrating computational modeling, functional experimental assays, and lineage tracing, we investigated how cell-state plasticity shapes acquired resistance to ALK inhibition in ALK+ lung cancer models. Our results support a model in which drug exposure selects for cells with higher phenotypic plasticity, progressively increasing their representation as resistance emerges. Consequently, resistant populations show enhanced capacity to adapt to orthogonal therapeutic and environmental stressors and exhibit heightened metastatic potential. Bulk ATAC-seq showed that highly plastic cells have increased chromatin accessibility at regulators of EMT and stemness. Consistent with this, boosting plasticity via Yamanaka-factor induction or EMT-factor expression reduced ALKi sensitivity over time. In contrast, constraining plasticity (SOX2 knockdown or epigenetic inhibition) reduced long-term resistance outgrowth and prolonged ALKi response. Together, our results indicate that targeted therapy indirectly selects for cells with increased phenotypic plasticity, providing the substrate from which multifactorial resistance and metastatic competence evolve. Further, it suggests that constraining plasticity could delay resistance and extend response durability. Competing Interest Statement The authors have declared no competing interest. Footnotes The authors declare no potential conflicts of interest. Text and figures have been revised for clarity. DATA AND CODE AVAILABILITY All simulation scripts, parameter files, and analysis notebooks are publicly available at https://github.com/mfroid/plasticityModels/. All ABM data is available upon request from the authors. ATAC-seq data is publicly available at https://www.ncbi.nlm.nih.gov/sra/PRJNA1400308. The previously established analysis pipeline can be found at https://github.com/GryderLab/gryderlab_pipeline. CloneTracer and CloneSweeper datasets can be found at https://www.ncbi.nlm.nih.gov/sra/PRJNA1400309. Single Cell RNA sequencing data was previously reported in (6) and can be found at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE144282. Bulk RNA sequencing data can be found at https://www.ncbi.nlm.nih.gov/sra/PRJNA1400309. All data reported in this paper are available from the corresponding author upon request.