Characterization of patient-derived tumor xenografts (PDXs) as models for estrogen receptor positive (ER+HER2− and ER+HER2+) breast cancers

Noriko Kanaya, George Somlo, Jun Wu, Paul Frankel, Masaya Kai, Xueli Liu, Shang Victoria Wu, Duc Nguyen, Nymph Chan, Meng Yin Hsieh, Michele Kirschenbaum, Laura Kruper, Courtney Vito, Behnam Badie, John H. Yim, Yuan Yuan, Arti Hurria, Chu Peiguo, Joanne Mortimer, Shiuan Chen

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10 Citations (Scopus)

Abstract

The research was to appraise the utility of the patient-derived tumor xenografts (PDXs) as models of estrogen receptor positive (ER+HER2− and ER+HER2+) breast cancers. We compared protein expression profiles by Reverse Phase Protein Array (RPPA) in tumors that resulted in PDXs compared to those that did not. Our overall PDX intake rate for ER+ breast cancer was 9% (9/97). The intake rate for ER+HER2+ tumors (3/16, 19%) was higher than for ER+HER2− tumors (6/81, 7%). Heat map analyses of RPPA data showed that ER+HER2− tumors were divided into 2 groups by luminal A/B signature [protein expression of ER, AR, Bcl-2, Bim (BCL2L11), GATA3 and INPP4b], and this expression signature was also associated with the rate of PDX intake. Cell survival pathways such as the PI3K/AKT signaling and RAS/ERK pathways were more activated in the specimens that could be established as PDX in both classes. Expression of the ER protein itself may have a bearing on the potential success of an ER+ PDX model. In addition, HER2 and its downstream protein expressions were up-regulated in the ER+HER2+ patient tumors that were successfully established as PDX models. Moreover, the comparison of RPPA data between original and PDX tumors suggested that the selection/adaptation process required to grow the tumors in mice is unavoidable for generation of ER+ PDX models, and we identified differences between patient tumor samples and paired PDX tumors. A better understanding of the biological characteristics of ER + PDX would be the key to using PDX models in assessing treatment strategies in a preclinical setting.

Original languageEnglish
Pages (from-to)65-74
Number of pages10
JournalJournal of Steroid Biochemistry and Molecular Biology
Volume170
DOIs
Publication statusPublished - Jun 1 2017
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Molecular Medicine
  • Molecular Biology
  • Endocrinology
  • Clinical Biochemistry
  • Cell Biology

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