A mouse model repository for cancer biomarker discovery.

Early detection of cancer using biomarkers obtained from blood or other easily accessible tissues would have a significant impact on reducing cancer mortality. However, identifying new blood-based biomarkers has been hindered by the dynamic complexity of the human plasma proteome, confounded by genetic and environmental variability, and the scarcity of high quality controlled samples. In this report, we discuss a new paradigm for biomarker discovery through the use of mouse models.

Plasma proteome profiling of a mouse model of breast cancer identifies a set of up-regulated proteins in common with human breast cancer cells.

We have applied an in-depth quantitative proteomic approach, combining isotopic labeling extensive intact protein separation and mass spectrometry, for high confidence identification of protein changes in plasmas from a mouse model of breast cancer. We hypothesized that a wide spectrum of proteins may be up-regulated in plasma with tumor development and that comparisons with proteins expressed in human breast cancer cell lines may identify a subset of up-regulated proteins in common with proteins expressed in breast cancer cell lines that may represent candidate biomarkers for breast cancer. Plasma from PyMT transgenic tumor-bearing mice and matched controls were obtained at two time points during tumor growth.

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery.