Comparison of clinical features and outcomes in epithelial ovarian cancer according to tumorigenicity in patient-derived xenograft models

Kyung Jin Eoh, Young Shin Chung, So Hyun Lee, Sun Ae Park, Hee Jung Kim, Wookyeom Yang, In Ok Lee, Jung Yun Lee, Hanbyoul Cho, Doo Byung Chay, Sunghoon Kim, Sang Wun Kim, Jae Hoon Kim, Young Tae Kim, Eun Ji Nam

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7 Citations (Scopus)

Abstract

Purpose Although the use of xenograft models is increasing, few studies have compared the clinical features or outcomes of epithelial ovarian cancer (EOC) patients according to the tumorigenicity of engrafted specimens. The purpose of this study was to evaluate whether tumorigenicity was associated with the clinical features and outcomes of EOC patients. Materials and Methods Eighty-eight EOC patients who underwent primary or interval debulking surgery from June 2014 to December 2015 were included. Fresh tumor specimens were implanted subcutaneously on each flank of immunodeficient mice. Patient characteristics, progression-free survival (PFS), and germline mutation spectra were compared according to tumorigenicity. Results Xenografts were established successfully from 49 of 88 specimens. Tumorigenicity was associated with lymphovascular invasion and there was a propensity to engraft successfully with high-grade tumors. Tumors from patients who underwent non-optimal (residual disease ≥ 1 cm) primary or interval debulking surgery had a significantly greater propensity to achieve tumorigenicity than those who received optimal surgery. In addition, patients whose tumors became engrafted seemed to have a shorter PFS and more frequent germline mutations than patients whose tumors failed to engraft. Tumorigenicity was a significant factor for predicting PFS with advanced International Federation of Gynecology and Obstetrics stage and high-grade cancers. Conclusion Tumorigenicity in a xenograft model was a strong prognostic factor and was associated with more aggressive tumors in EOC patients. Xenograft models can be useful as a preclinical tool to predict prognosis and could be applied to further pharmacologic and genomic studies on personalized treatments.

Original languageEnglish
Pages (from-to)956-963
Number of pages8
JournalCancer Research and Treatment
Volume50
Issue number3
DOIs
Publication statusPublished - 2018 Jul 1

Bibliographical note

Funding Information:
This work was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (2014R1A1A1A05002-926; 2015R1A2A2A01008162; 2015R1C1A2A01053516), a faculty research grant of Yonsei University College of Medicine (6-2016-0088), and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (2016-31-0454, HI13-C2162), funded by the Ministry of Health & Welfare, Republic of Korea. Partial funding was provided by the Korea Gynecologic Cancer Bank through the Bio & Medical Technology Development Program of the MSIP, Korea.

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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