We are merging our knowledge of embryonic development with our knowledge of cancer to build the next generation of cancer diagnostics and identify new therapeutic targets in cancer. Our hypothesis is that many cancers are ultimately developmental diseases, with activation of normal embryonic programs in the wrong time and place. By leveraging existing datasets cataloging mammalian development with datasets cataloging cancer, we can build comprehensive developmental maps of human tumors. These maps can help us tell apart the differences between patients, or even between single tumor cells of the same patient. Using machine learning and data science approaches, we can construct models for better precision medicine.
