Failure of a patient-derived xenograft for brain tumor model prepared by implantation of tissue fragments

Kyung Min Kim, Jin Kyoung Shim, Jong Hee Chang, Ji Hyun Lee, Se Hoon Kim, Junjeong Choi, Junseong Park, Eui Hyun Kim, Sun Ho Kim, Yong Min Huh, Su Jae Lee, Jae Ho Cheong, Seok Gu Kang

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6 Citations (Scopus)

Abstract

Background: With the continuing development of new anti-cancer drugs comes a need for preclinical experimental models capable of predicting the clinical activity of these novel agents in cancer patients. However existing models have a limited ability to recapitulate the clinical characteristics and associated drug sensitivity of tumors. Among the more promising approaches for improving preclinical models is direct implantation of patient-derived tumor tissue into immunocompromised mice, such as athymic nude or non-obese diabetic/severe combined immunodeficient (NOD/SCID) mice. In the current study, we attempted to develop patient-derived xenograft (PDX) models using tissue fragments from surgical samples of brain tumors. Methods: In this approach, tiny tissue fragments of tumors were biopsied from eight brain tumor patients-seven glioblastoma patients and one primitive neuroectodermal tumor patient. Two administration methods-a cut-down syringe and a pipette-were used to implant tissue fragments from each patient into the brains of athymic nude mice. Results: In contrast to previous reports, and contrary to our expectations, we found that none of these fragments from brain tumor biopsies resulted in the successful establishment of xenograft tumors. Conclusions: These results suggest that fragments of surgical specimens from brain tumor patients are unsuitable for implementation of brain tumor PDX models, and instead recommend other in vivo testing platforms for brain tumors, such as cell-based brain tumor models.

Original languageEnglish
Article number43
JournalCancer Cell International
Volume16
Issue number1
DOIs
Publication statusPublished - 2016 Jun 10

All Science Journal Classification (ASJC) codes

  • Oncology
  • Genetics
  • Cancer Research

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