Colorectal cancer models for novel drug discovery
Name
Yilmaz_Review US spelling.pdf
Size
1.51 MB
Format
Adobe PDF
Checksum (MD5)
4761f9d61d127756edd5a506e2f84c47
Author(s)
Golovko, Daniel
Kedrin, Dmitriy
Yilmaz, Omer
Roper, Jatin
Date Issued
August 2015
Journal
Expert Opinion on Drug Discovery
Publisher
Informa Healthcare
Citation
Golovko, Daniel et al. “Colorectal Cancer Models for Novel Drug Discovery.” Expert Opinion on Drug Discovery 10.11 (2015): 1217–1229.
Version
Author's final manuscript
Abstract
Introduction: Despite increased screening rates and advances in targeted therapy, colorectal cancer (CRC) remains the third leading cause of cancer-related mortality. CRC models that recapitulate key features of human disease are essential to the development of novel and effective
therapeutics. Classic methods of modeling CRC such as human cell lines and xenograft mice, while useful for many applications, carry significant limitations. Recently developed in vitro and in vivo models overcome some of these deficiencies and thus can be utilized to better model CRC
for mechanistic and translational research.
Areas Covered; The authors review established models of in vitro cell culture and describe advances in organoid culture for studying normal and malignant intestine. They also discuss key features of classic xenograft models and describe other approaches for in vivo CRC research,
including patient-derived xenograft, carcinogen-induced, orthotopic transplantation, and transgenic mouse models. We also describe mouse models of metastatic CRC.
Expert opinion: No single model is optimal for drug discovery in CRC. Genetically engineered models overcome many limitations of xenograft models. Three-dimensional organoids can be efficiently derived from both normal and malignant tissue for large-scale in vitro and in vivo
(transplantation) studies, and are thus a significant advance in CRC drug discovery.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Koch Institute for Integrative Cancer Research at MIT
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1517/17460441.2015.1079618
