Quantitative High-Throughput Screening Using an Organotypic Model Identifies Compounds that Inhibit Ovarian Cancer

Hilary A Kenny1, Madhu Lal-Nag2, Min Shen2

  • 1Department of Obstetrics and Gynecology/Section of Gynecologic Oncology, University of Chicago, Chicago, Illinois. hkenny@uchicago.edu.

Insights

Researchers screened thousands of compounds to find new ovarian cancer metastasis inhibitors. Three promising drugs, including NCGC00117362, were identified that block cancer spread and improve survival in preclinical models.

Area of Science:

  • Oncology
  • Drug Discovery
  • Tumor Microenvironment Research

Background:

  • The tumor microenvironment (TME) critically influences cancer metastasis.
  • Developing effective ovarian cancer metastasis therapies requires understanding TME interactions.
  • Quantitative high-throughput screening (qHTS) offers a scalable approach to identify novel therapeutic agents.

Purpose of the Study:

  • To identify small molecules that inhibit ovarian cancer metastasis using a 3D organotypic TME model.
  • To validate potential therapeutic candidates through in vitro and in vivo assays.
  • To explore the therapeutic potential of novel compounds for ovarian cancer prevention and treatment.

Main Methods:

  • A quantitative high-throughput screen (qHTS) of 44,420 diverse compounds and 386 pharmacologically active molecules.
  • Utilized a layered organotypic 3D assay mimicking the ovarian cancer metastatic TME with primary human cells and extracellular matrix.
  • Secondary in vitro and in vivo assays, including kinase profiling and structure-activity relationship studies, were performed for validation.

Main Results:

  • Identified 100 compounds inhibiting ovarian cancer adhesion/invasion; eight were confirmed active in cell lines.
  • Three compounds, PP-121, milciclib, and NCGC00117362, showed potent inhibition of ovarian cancer aggressiveness at 1 μmol/L.
  • In vivo studies demonstrated that these compounds prevented metastasis, prolonged survival, and reduced tumor growth.

Conclusions:

  • A complex 3D TME model is effective for qHTS drug discovery.
  • PP-121, milciclib, and NCGC00117362 show significant promise as therapeutics for ovarian cancer metastasis.
  • Further development of NCGC00117362 and its analogues could lead to novel clinical treatments.

Related Concept Videos