Predicting Response to Standard First-line Treatment in High-grade Serous Ovarian Carcinoma by Angiogenesis-related Genes

Anticancer Res. 2018 Sep;38(9):5393-5400. doi: 10.21873/anticanres.12869.

Abstract

Background/aim: Predicting response to treatment in high-grade serous ovarian carcinoma (HGSOC) still remains a clinical challenge. The standard-of-care for first-line chemotherapy, based on a combination of carboplatin and paclitaxel, achieves a high response rate. However, the development of drug resistance is one of the major limitations to efficacy. Therefore, identification of biomarkers able to predict response to chemotherapy in patients with HGSOC is a critical step for prognosis and treatment of the disease. Several studies suggest that angiogenesis is an important process in the development of ovarian carcinoma and chemoresistance. The aim of this study was to identify a profile of angiogenesis-related genes as a biomarker for response to first-line chemotherapy in HGSOC.

Materials and methods: Formalin-fixed paraffin-embedded samples from 39 patients with HGSOC who underwent surgical cytoreduction and received a first-line chemotherapy with carboplatin and paclitaxel were included in this study. Expression levels of 82 angiogenesis-related genes were measured by quantitative real-time polymerase chain reaction using TaqMan low-density arrays.

Results: Univariate analysis identified five genes [angiopoietin 1 (ANGPT1), aryl hydrocarbon receptor nuclear translocator (ARNT), CD34, epidermal growth factor (EGF) and matrix metallopeptidase 3 (MMP3)] as being statistically associated with response to treatment. Multivariable analysis by Lasso-penalized Cox regression generated a model with the combined expression of seven genes [angiotensinogen (AGT), CD34, EGF, erythropoietin receptor (EPOR), interleukin 8 (IL8), MMP3 and MMP7)]. The area under the receiver operating characteristics curve (0.679) and cross-validated Kaplan-Meier survival curves were used to estimate the accuracy of these predictors.

Conclusion: An angiogenesis-related gene expression profile useful for response prediction in HGSOC was identified, supporting the important role of angiogenesis in HGSOC.

Keywords: Ovarian cancer; angiogenesis; chemotherapy; gene-expression profile; high-grade serous carcinoma; response prediction.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Angiogenic Proteins / genetics*
  • Antineoplastic Combined Chemotherapy Protocols / therapeutic use*
  • Area Under Curve
  • Biomarkers, Tumor / genetics*
  • Carboplatin / administration & dosage
  • Clinical Decision-Making
  • Cytoreduction Surgical Procedures
  • Female
  • Gene Expression Profiling / methods*
  • Humans
  • Kaplan-Meier Estimate
  • Middle Aged
  • Multivariate Analysis
  • Neoplasm Grading
  • Neoplasms, Cystic, Mucinous, and Serous / drug therapy*
  • Neoplasms, Cystic, Mucinous, and Serous / genetics*
  • Neoplasms, Cystic, Mucinous, and Serous / pathology
  • Neovascularization, Pathologic / genetics*
  • Ovarian Neoplasms / drug therapy*
  • Ovarian Neoplasms / genetics*
  • Ovarian Neoplasms / pathology
  • Paclitaxel / administration & dosage
  • Patient Selection
  • Precision Medicine / methods*
  • Predictive Value of Tests
  • Proportional Hazards Models
  • ROC Curve
  • Risk Factors
  • Transcriptome

Substances

  • Angiogenic Proteins
  • Biomarkers, Tumor
  • Carboplatin
  • Paclitaxel