Quantification of Tumor and Angiogenesis-Related Markers in Ovarian Cancer Models by a Digital Pathology Approach

Methods Mol Biol. 2023:2572:81-89. doi: 10.1007/978-1-0716-2703-7_6.

Abstract

Digital pathology has the potential to quantify tumor markers accurately and reproducibly with various cellular and subcellular localizations in tissues, thus filling a need in cancer research. As a case study, we quantified the percentage of necrosis, microvessels density, and monocarboxylate transporter 4 (MCT4) expression in two ovarian cancer patient-derived xenograft (PDX) models subcutaneously injected in NOD/SCID mice. PDX models were treated with bevacizumab, an antiangiogenic drug, that targets vascular endothelial growth factor A (VEGF-A). Specific signal analysis algorithms allowed us to study morphologic, vascular, and metabolic modifications induced by antiangiogenic therapy by a quantitative, reproducible, and reliable approach.

Keywords: Angiogenesis; Digital pathology; Glycolysis; Ovarian cancer; Tumor xenografts.

MeSH terms

  • Angiogenesis Inhibitors / pharmacology
  • Animals
  • Bevacizumab
  • Biomarkers, Tumor / metabolism
  • Carcinoma, Ovarian Epithelial
  • Cell Line, Tumor
  • Female
  • Humans
  • Mice
  • Mice, Inbred NOD
  • Mice, SCID
  • Neovascularization, Pathologic / pathology
  • Ovarian Neoplasms* / drug therapy
  • Ovarian Neoplasms* / metabolism
  • Vascular Endothelial Growth Factor A* / metabolism
  • Xenograft Model Antitumor Assays

Substances

  • Angiogenesis Inhibitors
  • Biomarkers, Tumor
  • Vascular Endothelial Growth Factor A
  • Bevacizumab