Clonal morphology-guided combination therapies overcome heterogeneity-driven drug tolerance
Abstract
Abstract Tumor heterogeneity plays a critical role in tumor relapse and the development of drug resistance. Current personalized strategies, based on genetic profiling or bulk tumor drug sensitivity testing, offer limited clinical value as they overlook clonal heterogeneity. Here, through establishing primary tumor cell cultures from multiple metastatic sites, we observed that tumor cells exhibit high morphological plasticity and readily form distinct clonal morphologies during monoclonal expansion. Moreover, these heterogeneous clones displayed distinct tumorigenic and histological traits in orthotopic models, which may imply their differing clinical relevance in tumor progression. We also found that clonal morphological heterogeneity was exhibited by both established cell lines and primary lines derived from chemically induced tumor models. Subsequently, we analyzed the drug sensitivity profiles of tumor clones and identified clone-specific sensitive drugs. Despite limited in vitro synergy in pairwise combinations, both in vitro and in vivo assays confirmed their potent, clone-selective inhibition, suggesting rational drug combinations can precisely target distinct clonal populations. Taken together, Collectively, our findings propose that a heterogeneity-informed drug selection paradigm, enabled by rapid clonal morphology analysis of patient-derived cells, can be used to prevent recurrence and overcome resistance. Graphic Abstract Highlights Tumor cells develop distinct morphologies during clonal expansion. Distinct morphologies serve as simple markers of tumor heterogeneity. Distinct clonal morphology defines a unique drug-response profile. Clone-selective drug combinations combat heterogeneity-driven resistance.
Fields of Study & Subjects
Cancer Cells and Metastasis
3D Printing in Biomedical Research
Mathematical Biology Tumor Growth
Publication details
- Journal / source
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Publication date
- 3 February 2026
- Document type
- Preprint