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Background <p>Pancreatic neuroendocrine tumors (PNETs) are rare malignancies with limited treatment options beyond surgery, particularly in advanced stages, highlighting the need for novel therapeutic strategies. Featured by pronounced biologic heterogeneity, PNETs are driven by dysregulation of complex molecular-signaling pathways during tumor progression. This underscores the importance of biologically relevant and cost-effective preclinical models that allow convenient real-time monitoring of tumor progression and tracking of individual tumor cells, a current gap in the field.</p> Methods <p>To address this challenge, the authors engineered a novel enteroendocrine tumor-derived STC-1 murine cell line that stably co-expresses firefly luciferase (F-Luc) and enhanced green fluorescent protein (EGFP). These dual-labeled cells were implanted into immunocompromised mice via three different routes: subcutaneous (SubQ), renal capsule (RC), and orthotopic pancreatic (OP) injections. Tumor growth was tracked using bioluminescence in vivo imaging, and PNET characteristics were assessed by histologic, immunohistochemical (IHC) and co-immunofluorescence analyses.</p> Results <p>Tumors formed in all three models. The SubQ model showed rapid tumor growth but lacked key PNET features based on hematoxylin and eosin (H&amp;E) and IHC staining. The RC model exhibited moderate growth but limited expression of PNET-specific markers. In contrast, the OP model demonstrated robust tumor growth and most closely resembled well-differentiated, grade 1 human PNETs. Lineage-tracing experiments further exhibited clonal architecture and dynamic progression within the OP model.</p> Conclusions <p>Orthotopic pancreatic implantation of dual-labeled STC-1 cells provides a biologically relevant and pragmatic preclinical platform that closely resembles human PNETs. This model offers valuable utility for investigating PNET biology and evaluating novel therapeutic strategies.</p>

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Lighting up PNETs: Creating Murine Models with a Novel Bioluminescent Cell Line

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月3日

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  • Matthew C. Moccia,
  • Rachel Nation,
  • T. Hess,
  • Gena V. Topper,
  • Ami Kalola,
  • Michael Wang,
  • Hannah Sofield,
  • Zena Saleh,
  • Xiaofeng Zhao,
  • Yahui Li,
  • Francis Spitz,
  • Tao Gao,
  • Young Ki Hong

摘要

Background

Pancreatic neuroendocrine tumors (PNETs) are rare malignancies with limited treatment options beyond surgery, particularly in advanced stages, highlighting the need for novel therapeutic strategies. Featured by pronounced biologic heterogeneity, PNETs are driven by dysregulation of complex molecular-signaling pathways during tumor progression. This underscores the importance of biologically relevant and cost-effective preclinical models that allow convenient real-time monitoring of tumor progression and tracking of individual tumor cells, a current gap in the field.

Methods

To address this challenge, the authors engineered a novel enteroendocrine tumor-derived STC-1 murine cell line that stably co-expresses firefly luciferase (F-Luc) and enhanced green fluorescent protein (EGFP). These dual-labeled cells were implanted into immunocompromised mice via three different routes: subcutaneous (SubQ), renal capsule (RC), and orthotopic pancreatic (OP) injections. Tumor growth was tracked using bioluminescence in vivo imaging, and PNET characteristics were assessed by histologic, immunohistochemical (IHC) and co-immunofluorescence analyses.

Results

Tumors formed in all three models. The SubQ model showed rapid tumor growth but lacked key PNET features based on hematoxylin and eosin (H&E) and IHC staining. The RC model exhibited moderate growth but limited expression of PNET-specific markers. In contrast, the OP model demonstrated robust tumor growth and most closely resembled well-differentiated, grade 1 human PNETs. Lineage-tracing experiments further exhibited clonal architecture and dynamic progression within the OP model.

Conclusions

Orthotopic pancreatic implantation of dual-labeled STC-1 cells provides a biologically relevant and pragmatic preclinical platform that closely resembles human PNETs. This model offers valuable utility for investigating PNET biology and evaluating novel therapeutic strategies.