Peer-review started: September 3, 2014
First decision: October 14, 2014
Revised: November 18, 2014
Accepted: January 15, 2015
Article in press: January 19, 2015
Published online: March 9, 2015
Processing time: 193 Days and 16.5 Hours
The majority of cancer drugs entering clinical trials fail to reach the market due to poor efficacy. Preclinical efficacy has been traditionally tested using subcutaneous xenograft models that are cheap, fast and easy to perform. However, these models lack the correct tumor microenvironment, leading to poor clinical predictivity. Selecting compounds for clinical trials based on efficacy results obtained from subcutaneous xenograft models may therefore be one important reason for the high failure rates. In this review we concentrate in describing the role and importance of the tumor microenvironment in progression of breast and prostate cancer, and describe some breast and prostate cancer cell lines that are widely used in preclinical studies. We go through different preclinical efficacy models that incorporate the tissue microenvironment and should therefore be clinically more predictive than subcutaneous xenografts. These include three-dimensional cell culture models, orthotopic and metastasis models, humanized and transgenic mouse models, and patient-derived xenografts. Different endpoint measurements and applicable imaging techniques are also discussed. We conclude that models that incorporate the tissue microenvironment should be increasingly used in preclinical efficacy studies to reduce the current high attrition rates of cancer drugs in clinical trials.
Core tip: It is today a recognized major problem in cancer drug development that the vast majority of drugs entering clinical trials fail to reach the market due to poor efficacy. One important reason for this is the wide use of subcutaneous xenograft models that are cheap, fast and easy to perform, but lack tumor microenvironment. Concentrating on breast and prostate cancer, we explain why the presence of tumor microenvironment is important, and describe different types of preclinical efficacy models that incorporate tumor microenvironment. We state the importance of using these models to reduce the high failure rates in clinical trials.