TEAMSTER: End-to-end pipeline for generation, processing, and automated quantitative image analysis of 3D tumour spheroids for nanobiology

Three-dimensional (3D) tumour spheroids are widely used as physiologically relevant in vitro models to study tumour biology, therapeutic responses, and the distribution of drugs and nanomaterials. However, experimental workflows for spheroid-based studies remain highly heterogeneous, with limited standardization across spheroid generation, processing, and quantitative analysis, hindering reproducibility and accessibility. Here, we present TEAMSTER, an integrated, end-to-end pipeline for the generation, cryosectioning, immunostaining, and quantitative image analysis of tumour spheroids. The workflow combines optimized protocols for reproducible spheroid formation that minimize variability, a liquid nitrogen-free, colour-coded OCT embedding strategy improving spheroid localization during cryosectioning, standardized fixation and staining procedures compatible with multiplex fluorescence imaging, and a semi-automated, GUI-based CellProfiler pipeline enabling unbiased quantitative analysis without coding skills, machine learning, or dedicated computing hardware. TEAMSTER is experimentally validated in two distinct tumour spheroid models treated with fluorescently labelled nanoconjugates. Quantitative performance metrics for spheroid preparation (intraplate and interplate coefficients of variation) and image segmentation benchmarking (Dice and IoU coefficients) support the robustness of single-cell-resolved measurements across cryosectioned spheroid models and imaging conditions. By prioritizing experimental robustness, standardization, and usability, TEAMSTER provides a practical methodological resource for reproducible quantitative spheroid-based studies in cancer biology and nanomedicine.