Intra-tumoral nerve-tracing in a novel syngeneic model of high-grade serous ovarian carcinoma

Jeffrey L. Barr, Allison Kruse, Anthony C. Restaino, Natalia Tulina, Sarah Stuckelberger, Samuel J. Vermeer, Caitlin S. Williamson, Daniel W. Vermeer, Marianna Madeo, Jillian Stamp, Maria Bell, Mark Morgan, Ju Yoon Yoon, Marilyn A. Mitchell, Anna Budina, Dalia K. Omran, Lauren E. Schwartz, Ronny Drapkin, Paola D. Vermeer

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Dense tumor innervation is associated with enhanced cancer progression and poor progno-sis. We observed innervation in breast, prostate, pancreatic, lung, liver, ovarian, and colon cancers. Defining innervation in high-grade serous ovarian carcinoma (HGSOC) was a focus since sensory innervation was observed whereas the normal tissue contains predominantly sympathetic input. The origin, specific nerve type, and the mechanisms promoting innervation and driving nerve-cancer cell communications in ovarian cancer remain largely unknown. The technique of neuro-tracing enhances the study of tumor innervation by offering a means for identification and mapping of nerve sources that may directly and indirectly affect the tumor microenvironment. Here, we establish a murine model of HGSOC and utilize image-guided microinjections of retrograde neuro-tracer to label tumor-infiltrating peripheral neurons, mapping their source and circuitry. We show that regional sensory neurons innervate HGSOC tumors. Interestingly, the axons within the tumor trace back to local dorsal root ganglia as well as jugular–nodose ganglia. Further manipulations of these tumor projecting neurons may define the neuronal contributions in tumor growth, invasion, metastasis, and responses to therapeutics.

Original languageEnglish (US)
Article number3491
Issue number12
StatePublished - Dec 2021
Externally publishedYes


  • Innervation
  • Nerve-tracing
  • Ovarian cancer
  • Ultrasound

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology


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