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Integrated spatial morpho-transcriptomics predicts functional traits in pancreatic cancer.

bioRxiv : the preprint server for biology 2025

Gong D, Liu R, Cui Y, Rhodes M, Bae JW, Beechem JM, Hwang WL

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Analyses of patient-derived cell lines have greatly enhanced discovery of molecular biomarkers and therapeutic targets.

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APA Gong D, Liu R, et al. (2025). Integrated spatial morpho-transcriptomics predicts functional traits in pancreatic cancer.. bioRxiv : the preprint server for biology. https://doi.org/10.1101/2025.03.12.642933
MLA Gong D, et al.. "Integrated spatial morpho-transcriptomics predicts functional traits in pancreatic cancer.." bioRxiv : the preprint server for biology, 2025.
PMID 40161804

Abstract

Analyses of patient-derived cell lines have greatly enhanced discovery of molecular biomarkers and therapeutic targets. However, characterization of cellular morphological properties is limited. We studied cell morphologies of human pancreatic adenocarcinoma (PDAC) cell lines and their associations with drug sensitivity, gene expression, and functional properties. By integrating live cell and spatial mRNA imaging, we identified KRAS inhibitor-induced morphological changes specific for drug-resistant cells that correlated with gene expression changes. We then categorized a large panel of patient-derived PDAC cell lines into morphological (e.g., polygonal, irregular, spheroid) and organizational (e.g., tightly aggregated, multilayered, dispersed) subtypes and found differences in gene expression, therapeutic targeting potential, and metastatic proclivity. In human PDAC tissues, we identified prognostic expression signatures associated with distinct cancer cell organization patterns. In summary, we highlight the potential of cell morphological information in rapid, cost-effective assays to aid precision oncology efforts leveraging patient-derived in vitro models and tissues.

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