| Literature DB >> 32109311 |
Maiko Okano1,2, Masanori Oshi1, Ali Butash1, Ichiro Okano1, Katsuharu Saito3, Tsutomu Kawaguchi1, Masayuki Nagahashi4, Koji Kono3, Toru Ohtake2, Kazuaki Takabe5,6,7,8,9,10.
Abstract
Patient-Derived Xenograft (PDX) is now accepted as a murine model that better mimics human cancer when compared to a conventional cancer cell-line inoculation model. Some claim the advantage of orthotopic site implantation of patient tumor (OS) over ectopic implantation into the subcutaneous space (SQ); however, there has been no study that describes a head-to-head comparison of oncological differences between these two models to date. We hypothesize that OS tumors re-transplant and grow better than SQ tumors and are therefore a better model to evaluate tumor aggressiveness. Breast cancer PDXs were generated using the tumors derived from 11 patients into NOD scid gamma (NSG) mice. We used six ER(+)HER2(-) tumors and five triple negative (TN) tumors for a total of 11 tumors. Five PDX lines grew for an overall engraftment rate of 45%. We present our OS implantation method in detail. The re-transplantation rate of TN tumors in each transplant site was significantly higher in OS when compared to SQ tumors (70.1% vs. 32.1%, p < 0.01). OS tumors grow significantly faster than SQ tumors. Similarly, OS tumors demonstrated significantly more mitotic figures and Ki-67 positive cells than SQ tumors. The tumor re-transplantation rate significantly increased by the second and third generations with the OS method. The time from implantation to development of a palpable tumor dramatically decreased after the first passage. PDX of ER(+) tumors demonstrated significantly lower engraftment rates and slower tumor growth than TN tumors, which remarkably improved by the first passage. Orthotopically implanted PDX tumors showed better re-transplantation rates, greater tumor size, and more significant growth compared to the subcutaneously implanted model.Entities:
Keywords: Breast Cancer; Orthotopic; PDX; Patient-Derived Xenografts; Pre-clinical model
Mesh:
Year: 2020 PMID: 32109311 PMCID: PMC7141774 DOI: 10.1007/s10911-020-09442-7
Source DB: PubMed Journal: J Mammary Gland Biol Neoplasia ISSN: 1083-3021 Impact factor: 2.673