Cisplatin Resistant Spheroids Model Clinically Relevant Survival Mechanisms in Ovarian Tumors

Winyoo Chowanadisai1,2, Shanta M Messerli2, Daniel H Miller3,4

  • 1Department of Nutritional Sciences, Oklahoma State University, Stillwater, Oklahoma, United States of America, 74078.

Plos One
|March 18, 2016
PubMed

Insights

Drug-resistant ovarian cancer spheroids reveal new insights into treatment failure. A 17-gene signature predicts shorter survival in ovarian cancer patients, highlighting the epithelial-to-mesenchymal transition in resistance.

Area of Science:

  • Oncology
  • Genomics
  • Drug Resistance

Background:

  • Ovarian tumors frequently recur as drug-resistant forms, posing a significant clinical challenge.
  • Understanding the molecular mechanisms underlying cisplatin resistance is crucial for improving patient outcomes.

Purpose of the Study:

  • To investigate gene expression profiles in cisplatin-sensitive and resistant ovarian cancer spheroids.
  • To identify molecular pathways and develop predictive biomarkers associated with cisplatin resistance in ovarian cancer.

Main Methods:

  • Generation of a cisplatin-resistant ovarian cancer cell line (OVCAR-8R) from sensitive cells (OVCAR-8).
  • Utilized 3D spheroid models to mimic in vivo tumor microenvironments.
  • Performed genome-wide gene expression profiling to compare sensitive and resistant cell lines.

Main Results:

  • Identified 3,139 differentially expressed genes between sensitive and resistant ovarian cancer spheroids.
  • Cisplatin resistance was not linked to altered intracellular drug concentration but showed enrichment for a mesenchymal gene signature.
  • A 17-gene signature derived from resistant cells accurately predicted shorter overall survival in independent patient datasets.

Conclusions:

  • 3D spheroid models of cisplatin-resistant ovarian cancer are effective for studying resistance mechanisms.
  • The epithelial-to-mesenchymal transition is implicated in the acquisition of cisplatin resistance in ovarian cancer.
  • The identified 17-gene signature serves as a potential prognostic biomarker for ovarian cancer patients.

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