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Current and Future Horizons of Patient-Derived Xenograft Models in Colorectal Cancer Translational Research.
- Source :
- Cancers; Sep2019, Vol. 11 Issue 9, p1321-1321, 1p
- Publication Year :
- 2019
-
Abstract
- Our poor understanding of the intricate biology of cancer and the limited availability of preclinical models that faithfully recapitulate the complexity of tumors are primary contributors to the high failure rate of novel therapeutics in oncology clinical studies. To address this need, patient-derived xenograft (PDX) platforms have been widely deployed and have reached a point of development where we can critically review their utility to model and interrogate relevant clinical scenarios, including tumor heterogeneity and clonal evolution, contributions of the tumor microenvironment, identification of novel drugs and biomarkers, and mechanisms of drug resistance. Colorectal cancer (CRC) constitutes a unique case to illustrate clinical perspectives revealed by PDX studies, as they overcome limitations intrinsic to conventional ex vivo models. Furthermore, the success of molecularly annotated "Avatar" models for co-clinical trials in other diseases suggests that this approach may provide an additional opportunity to improve clinical decisions, including opportunities for precision targeted therapeutics, for patients with CRC in real time. Although critical weaknesses have been identified with regard to the ability of PDX models to predict clinical outcomes, for now, they are certainly the model of choice for preclinical studies in CRC. Ongoing multi-institutional efforts to develop and share large-scale, well-annotated PDX resources aim to maximize their translational potential. This review comprehensively surveys the current status of PDX models in translational CRC research and discusses the opportunities and considerations for future PDX development. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20726694
- Volume :
- 11
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- Cancers
- Publication Type :
- Academic Journal
- Accession number :
- 138961516
- Full Text :
- https://doi.org/10.3390/cancers11091321