Insulin-Like Growth Factors and Their Binding Proteins in Tumors and Ascites of Ovarian Cancer Patients: Association With Response To Neoadjuvant Chemotherapy

Document Type : Research Articles

Authors

Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia

Abstract

 
Purpose: Tumor cell growth and sensitivity to chemotherapy depend on many factors, among which insulin-like growth factors (IGFs) may play important roles. The aim of the present study was to evaluate the levels of insulin-like growth factors (IGFs) and IGF binding proteins (IGFBPs) in primary tumors and ascites as predictors of response to neoadjuvant chemotherapy in ovarian cancer (OC) patients. Materials and Methods: Tumor tissue samples and ascitic fluid were obtained from 59 patients with advanced OC. The levels of IGF-I, IGF-II, IGFBP-3, IGFBP-4 and PAPP-A were determined using ELISA kits. Taking into account the data on expression of these IGF-related proteins and outcome, logistic regression was performed to identify predictors of response to neoajuvant chemotherapy. Results: Human ovarian tumors expressed IGFs, IGFBP-3, IGFBP-4 and PAPP-A and these proteins were also present in ascites fluid and associated with its volume. IGFs and IGFBPs in ascites and soluble PAPP-A might play a key role in ovarian cancer progression . However, levels of proteins of the IGF system in tumors were not significant predictors of objective clinical response (oCR). Univariate analysis showed that the level of IGF-I in ascites was the only independent predictor for oCR. Conclusion: The level of IGF-I in ascites was shown to be an independent predictor of objective clinical response to chemotherapy for OC patients treated with neoadjuvant chemotherapy and debulking surgery.

Keywords

Asian Pacific Journal of Cancer Prevention
Volume 17, Issue 12
December 2016
Pages 5315-5320

Files

History

  • Receive Date: 30 November 2016
  • Revise Date: 21 December 2016
  • Accept Date: 27 January 2017
  • First Publish Date: 27 January 2017

Share

How to cite

Statistics