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Spatial transcriptomic analysis drives PET imaging of tight junction protein expression in pancreatic cancer theranostics

Author

Listed:
  • James Wang

    (Stanford University)

  • Jai Woong Seo

    (Stanford University)

  • Aris J. Kare

    (Stanford University
    Stanford University)

  • Martin Schneider

    (Stanford University)

  • Mallesh Pandrala

    (Stanford University)

  • Spencer K. Tumbale

    (Stanford University)

  • Marina N. Raie

    (Stanford University)

  • Gokce Engudar

    (Stanford University)

  • Nisi Zhang

    (Stanford University)

  • Yutong Guo

    (Stanford University)

  • Xiaoxu Zhong

    (Stanford University)

  • Sofia Ferreira

    (Stanford University)

  • Bo Wu

    (Stanford University)

  • Laura D. Attardi

    (Stanford University
    Stanford University)

  • Guillem Pratx

    (Stanford University)

  • Andrei Iagaru

    (Stanford University)

  • Ryan L. Brunsing

    (Stanford University)

  • Gregory W. Charville

    (Stanford University)

  • Walter G. Park

    (Stanford University)

  • Katherine W. Ferrara

    (Stanford University)

Abstract

Molecular imaging using positron emission tomography (PET) provides sensitive detection and mapping of molecular targets. While cancer-associated fibroblasts and integrins have been proposed as targets for imaging of pancreatic ductal adenocarcinoma (PDAC), herein, spatial transcriptomics and proteomics of human surgical samples are applied to select PDAC targets. We find that selected cancer cell surface markers are spatially correlated and provide specific cancer localization, whereas the spatial correlation between cancer markers and immune-related or fibroblast markers is low. Claudin-4 expression increases ~16 fold in cancer as compared with normal pancreas, and tight junction localization confers low background for imaging in normal tissue. We develop a peptide-based molecular imaging agent targeted to claudin-4 with accumulation to ~25% injected activity per cubic centimeter (IA/cc) in metastases and ~18% IA/cc in tumors. Our work motivates a data-driven approach to selection of molecular targets.

Suggested Citation

  • James Wang & Jai Woong Seo & Aris J. Kare & Martin Schneider & Mallesh Pandrala & Spencer K. Tumbale & Marina N. Raie & Gokce Engudar & Nisi Zhang & Yutong Guo & Xiaoxu Zhong & Sofia Ferreira & Bo Wu , 2024. "Spatial transcriptomic analysis drives PET imaging of tight junction protein expression in pancreatic cancer theranostics," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-54761-6
    DOI: 10.1038/s41467-024-54761-6
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