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

Science advances 2025 Vol.11(42) p. eadx0632

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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BibTeX ↓ RIS ↓
APA Gong D, Liu R, et al. (2025). Integrated spatial morpho-transcriptomics predicts functional traits in pancreatic cancer.. Science advances, 11(42), eadx0632. https://doi.org/10.1126/sciadv.adx0632
MLA Gong D, et al.. "Integrated spatial morpho-transcriptomics predicts functional traits in pancreatic cancer.." Science advances, vol. 11, no. 42, 2025, pp. eadx0632.
PMID 41105767

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 messenger RNA 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 and organizational subtypes and found differences in gene expression, therapeutic targeting potential, and metastatic proclivity. Patterns of cancer cell organization in human PDAC tissues stratified distinct gene expression signatures with clinical significance. 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.

MeSH Terms

Pancreatic Neoplasms; Gene Expression Regulation, Neoplastic; Carcinoma, Pancreatic Ductal; Drug Resistance, Neoplasm; Cell Line, Tumor; Proto-Oncogene Proteins p21(ras); Antineoplastic Agents; Transcriptome; Precision Medicine; Humans; Spatial Transcriptomics; Cost-Effectiveness Analysis; Single-Cell Analysis; Biomarkers, Tumor; Heterocyclic Compounds, 2-Ring; Naphthalenes; Piperazines

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