Review Volume 13, Issue 8 pp 12273—12293
Patient-derived xenograft: a developing tool for screening biomarkers and potential therapeutic targets for human esophageal cancers
- 1 Sino-British Research Center for Molecular Oncology, National Center for the International Research in Cell and Gene Therapy, School of Basic Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, P.R. China
- 2 The Academy of Medical Science, Precision Medicine Center of the Second Affiliated Hospital of Zhengzhou University, Zhengzhou University, Henan, P.R. China
- 3 Centre for Cancer Biomarkers and Biotherapeuitcs, Barts Cancer Institute, Queen Mary University of London, London, UK
- 4 Academy of Chinese Medicine Science, Henan University of Chinese Medicine, Zhengzhou, Henan, P.R. China
Received: September 4, 2020 Accepted: March 23, 2021 Published: April 26, 2021https://doi.org/10.18632/aging.202934
How to Cite
Copyright: © 2021 Lan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Esophageal cancer (EC) represents a human malignancy, diagnosed often at the advanced stage of cancer and resulting in high morbidity and mortality. The development of precision medicine allows for the identification of more personalized therapeutic strategies to improve cancer treatment. By implanting primary cancer tissues into immunodeficient mice for expansion, patient-derived xenograft (PDX) models largely maintain similar histological and genetic representations naturally found in patients’ tumor cells. PDX models of EC (EC-PDX) provide fine platforms to investigate the tumor microenvironment, tumor genomic heterogeneity, and tumor response to chemoradiotherapy, which are necessary for new drug discovery to combat EC in addition to optimization of current therapeutic strategies for EC. In this review, we summarize the methods used for establishing EC-PDX models and investigate the utilities of EC-PDX in screening predictive biomarkers and potential therapeutic targets. The challenge of this promising research tool is also discussed.