AI-powered single-cell imaging and morphology-guided label-free enrichment reveal tumor heterogeneity, genomic relatedness, and divergence in malignant effusions

ABSTRACT Background: Malignant effusions are clinically accessible yet underutilized sources of metastatic tumor cells. However, abundant background immune cells complicate tumor cell isolation and molecular characterization. We integrate AI-powered single-cell imaging and morphology-guided label-free tumor cell enrichment with genomic profiling to characterize phenotypic and genomic heterogeneity in malignant effusions. Methods: We applied a pre-trained deep learning model to brightfield images of single cells from malignant effusions of 10 patients with metastatic breast cancer to extract mo

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