Cancers are a diverse collection of diseases that are caused by distinct gene mutations. Effective cancer treatment has to be tailored for these patient-specific aberrations. To this end, the cancer genome project has systematically identified mutations in various cancer types and provided a foundation for personalized cancer medicine. However, the cancer genome can be littered with mutations simply due to the fact that cancer cells are highly unstable. Therefore, it is critical to understand which mutations play a causal role in driving cancer progression, i.e. acting as drivers, and which mutations are merely bystanders.
To address this question, we have developed a novel technology for generating personalized breast cancer models that contain mutations found in human patients. Using these models, we will decipher which mutations are functional important, and thus can be useful therapeutic targets. Our work is like to identify novel breast cancer genes and provide new therapeutic targets and biomarkers for selecting most effective treatment.
Successful outcomes of our study will pave the way for developing therapeutic agents for targeting these new breast cancer genes. In addition, the technology perfected through this study will be highly valuable for investigating mutations of other cancer types to identify a catalog of cancer targets that can be tailored for personalized medicine.