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The DOI matches its Crossref record; 162 of the 162 references it cites were found in a registry or an index.

Current status and perspectives of patient-derived xenograft models in cancer research

Open access
Lai, Yunxin, Wei, Xinru, Lin, Shouheng, Qin, Le, Cheng, Lin, Li, Peng·2017·Journal of Hematology & Oncology

Abstract

Cancers remain a major public health problem worldwide, which still require profound research in both the basic and preclinical fields. Patient-derived xenograft (PDX) models are created when cancerous cells or tissues from patients' primary tumors are implanted into immunodeficient mice to simulate human tumor biology in vivo, which have been extensively used in cancer research. The routes of implantation appeared to affect the outcome of PDX research, and there has been increasing applications of patient-derived orthotopic xenograft (PDOX) models. In this review, we firstly summarize the methodology to establish PDX models and then go over recent application and function of PDX models in basic cancer research on the areas of cancer characterization, initiation, proliferation, metastasis, and tumor microenvironment and in preclinical explorations of anti-cancer targets, drugs, and therapeutic strategies and finally give our perspectives on the future prospects of PDX models.

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Metadata

Authors
Lai, Y., Wei, X., Lin, S., Qin, L., Cheng, L., & Li, P.
Venue
Journal of Hematology & Oncology
Published
2017-05-12
Volume
10
Issue
1
Pages
106-106
ISSN
1756-8722 (ISSN-L)
OpenAlex
W2612901302
Cited by
295
References
162
FWCI
13.36
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Current status and perspectives of patient-derived xenograft models in cancer research. https://app.cochat.ai/papers/10.1186/s13045-017-0470-7
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Lai, Y., Wei, X., Lin, S., Qin, L., Cheng, L., & Li, P. (2017). Current status and perspectives of patient-derived xenograft models in cancer research. Journal of Hematology & Oncology. https://doi.org/10.1186/s13045-017-0470-7

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.