Title |
Current status and perspectives of patient-derived xenograft models in cancer research
|
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Published in |
Journal of Hematology & Oncology, May 2017
|
DOI | 10.1186/s13045-017-0470-7 |
Pubmed ID | |
Authors |
Yunxin Lai, Xinru Wei, Shouheng Lin, Le Qin, Lin Cheng, Peng Li |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Australia | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 383 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 63 | 16% |
Researcher | 62 | 16% |
Student > Master | 48 | 13% |
Student > Bachelor | 48 | 13% |
Student > Doctoral Student | 23 | 6% |
Other | 41 | 11% |
Unknown | 98 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 101 | 26% |
Medicine and Dentistry | 45 | 12% |
Agricultural and Biological Sciences | 41 | 11% |
Engineering | 18 | 5% |
Immunology and Microbiology | 16 | 4% |
Other | 45 | 12% |
Unknown | 117 | 31% |