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

Dennis Gong1,2,3, Rachel Liu4, Yi Cui4

  • 1Division of Health Sciences and Technology, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.

Science Advances
|October 17, 2025
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Summary
This summary is machine-generated.

Cell morphology in pancreatic cancer models reveals drug resistance patterns and subtypes, aiding precision oncology. This study links cell shape and organization to gene expression and therapeutic potential in patient-derived models and tissues.

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Area of Science:

  • Oncology
  • Cell Biology
  • Genomics

Background:

  • Patient-derived cell lines are crucial for identifying biomarkers and therapeutic targets in pancreatic adenocarcinoma (PDAC).
  • Characterization of cellular morphology in PDAC models is currently limited.
  • Understanding morphological properties can offer new insights into cancer biology and treatment response.

Purpose of the Study:

  • To investigate the association between cell morphologies of human pancreatic adenocarcinoma (PDAC) cell lines and their drug sensitivity, gene expression, and functional properties.
  • To identify KRAS inhibitor-induced morphological changes in drug-resistant PDAC cells.
  • To categorize PDAC cell lines into subtypes based on morphology and organization and assess their clinical relevance.

Main Methods:

  • Integrated live cell imaging with spatial messenger RNA (mRNA) imaging.
  • Analyzed morphological changes in response to KRAS inhibitors.
  • Categorized a large panel of patient-derived PDAC cell lines into distinct morphological and organizational subtypes.
  • Correlated morphological features with gene expression patterns and clinical data from PDAC tissues.

Main Results:

  • Identified specific KRAS inhibitor-induced morphological changes in drug-resistant PDAC cells that correlated with gene expression alterations.
  • Discovered distinct morphological and organizational subtypes within PDAC cell lines, showing differences in gene expression, therapeutic targeting potential, and metastatic proclivity.
  • Observed that cancer cell organization patterns in human PDAC tissues stratified distinct gene expression signatures with clinical significance.

Conclusions:

  • Cell morphological information can be leveraged in rapid, cost-effective assays for precision oncology.
  • Patient-derived in vitro models and tissues, when analyzed for morphology, can significantly aid in understanding PDAC and guiding treatment strategies.
  • Morphological characterization provides a valuable, underutilized dimension for PDAC research and clinical applications.