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Patient-derived tumor xenograft (PDX) models are frequently used to study cancer mechanisms and potential therapeutics, however, differences in tumor evolution between models and patients have called into question their clinical relevance. In this issue, Mer and colleagues describe the Xenograft Visualization and Analysis (Xeva) software tool that empowers pharmacogenomic analysis through integration of PDX model tumor-drug response with genetic data. By performing the largest PDX model meta-analysis of its kind, the authors demonstrate PDX models are robust platforms for cancer treatment studies. With a clear need for more integrative studies, Xeva is well placed to make more important contributions to pharmacogenomic discovery.
Keyword:
XENOGRAFTS
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期刊
IF:
16.6
论文数:
10.9W
被引数:
11.9W
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Systematic Review of Patient-Derived Xenograft Models for Preclinical Studies of Anti-Cancer Drugs in Solid Tumors.png)
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