Abstract
Patient-derived xenografts (PDXs) are powerful tools for translational cancer research. Here, we established PDX models from different molecular subtypes of breast cancer for in vivo drug tests and compared the histopathologic features of PDX model tumors with those of patient tumors. Predictive biomarkers were identified by gene expression analysis of PDX samples using Nanostring nCount cancer panels. Validation of predictive biomarkers for treatment response was conducted in established PDX models by in vivo drug testing. Twenty breast cancer PDX models were generated from different molecular subtypes (overall success rate, 17.5%; 3.6% for HR+/HER2−, 21.4% for HR+/HER2+, 21.9% for HR−/HER2+ and 22.5% for triple-negative breast cancer (TNBC)). The histopathologic features of original tumors were retained in the PDX models. We detected upregulated HIF1A, RAF1, AKT2 and VEGFA in TNBC cases and demonstrated the efficacy of combined treatment with sorafenib and everolimus or docetaxel and bevacizumab in each TNBC model. Additionally, we identified upregulated HIF1A in two cases of trastuzumab-exposed HR−/HER2+ PDX models and validated the efficacy of the HIF1A inhibitor, PX-478, alone or in combination with neratinib. Our results demonstrate that PDX models can be used as effective tools for predicting therapeutic markers and evaluating personalized treatment strategies in breast cancer patients with resistance to standard chemotherapy regimens.
Highlights
Developing models that mimic human cancer is a long-standing goal in cancer research [1].By testing treatments in a model similar to a given patient’s condition, it should be possible to identify personalized, effective treatment options that avoid unnecessary therapeutic interventions.Cancers 2019, 11, 574; doi:10.3390/cancers11040574 www.mdpi.com/journal/cancersCancer cell lines are among the most popular tools for drug testing and molecular research because of their ease of handling and rapid proliferation
An analysis of Patient-derived xenografts (PDXs) engraftment according to survival showed that tumors derived from patients with poor disease-free and overall survival showed a tendency towards good engraftment (Figure 1D)
An IHC analysis of markers revealed that Ki-67, VEGFA and HIF1A expression were decreased in the corresponding tumors in tumor-bearing mice treated with bevacizumab, docetaxel, or their combination (Figure 3). These results suggest that direct targeting of VEGFA using bevacizumab in PDX tumors from PT12 is a better treatment strategy than sorafenib-mediated inhibition of VEGF receptor (VEGFR)-2 and-3 tyrosine kinases
Summary
Cancer cell lines are among the most popular tools for drug testing and molecular research because of their ease of handling and rapid proliferation. Such cell lines are in vitro models that have a limited ability to recapitulate the features of actual cancers. A xenograft model generated by injection of a cancer cell line into immunodeficient mice is a widely used model for preclinical drug studies [2]. Xenograft models created using cancer cell lines do not reflect the heterogeneity of complex tumors and often do not reproduce the microenvironment of tumor cells in vivo, including accessory cell components such as fibroblasts, blood vessel cells and immune cells [3,4]
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