bioRxivBiophysicsPreprint
Cancer Phenotypic Plasticity Quantification using Morphology-Migration Coupled Metric in Live Label-Free Optical Microscopy
Abstract
Cancer phenotypic plasticity drives invasion, treatment resistance, and relapse. Quantifying how cells dynamically couple morphology and migration in real time, without molecular labels, remains unsolved. Static molecular markers report on protein expression state rather than functional migratory behavior. Existing image-based metrics treat shape and migration as independent features, missing the coordinated coupling that defines plastic migratory states. We introduce Directional Shape Coupling (DSC), a quantitative metric purpose-built for live label-free imaging. DSC integrates movement direction consistency, shape deformation, and directional-shape alignment into a single interpretable score. Component weights are derived from PCA, adapting automatically to any dataset without manual tuning. Applied to differential interference contrast imaging of pancreatic cancer cells on a tissue-mimicking substrate recapitulating desmoplastic tumor stroma, DSC exhibited a large phenotype-associated effect size,{varepsilon} 2 = 0.65, across five distinct migratory phenotypes within a genetically homogeneous population, demonstrating that behavioral heterogeneity is structured and non-genetic. DSC encodes information orthogonal to classical shape and motion descriptors. Critically, DSC reveals that dynamic shape adaptation to mechanical cues rather than directional commitment drives phenotypic identity in this system. DSC provides the label-free imaging community a transparent, generalizable framework for quantifying dynamic non-genetic plasticity directly from live imaging data.
- organism: human
- assay: imaging
- assay: fluorescence / live-cell microscopy
- research focus: cell signaling & trafficking
- research focus: cancer & tumor microenvironment
- research focus: cell type annotation
- research focus: clustering
- approach: deep learning
- approach: statistical model
- Citations
- 0
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