| Literature DB >> 27154416 |
Noriko Kanaya1, George Somlo2, Jun Wu3, Paul Frankel4, Masaya Kai1, Xueli Liu4, Shang Victoria Wu1, Duc Nguyen1, Nymph Chan1, Meng-Yin Hsieh3, Michele Kirschenbaum5, Laura Kruper6, Courtney Vito6, Behnam Badie6, John H Yim6, Yuan Yuan2, Arti Hurria2, Chu Peiguo7, Joanne Mortimer2, Shiuan Chen8.
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.Entities:
Keywords: Breast cancer; ER+HER2+; ER+HER2−; Luminal A/B; Patient-derived tumor xenografts (PDXs)
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Year: 2016 PMID: 27154416 PMCID: PMC5094906 DOI: 10.1016/j.jsbmb.2016.05.001
Source DB: PubMed Journal: J Steroid Biochem Mol Biol ISSN: 0960-0760 Impact factor: 4.292