Abeloff V Scholar* (Tied for Top Rank)
The term “metastasis” describes the spread of cancer cells from their original location in the body to nearby or distant organs. Almost 90% of all cancer deaths are because of metastasis. Unfortunately, this estimate has not changed in the last 50 years and our understanding of metastasis is limited. In order to effectively treat metastasis, we need to first understand them.
Both cancers and their metastasis contain mutations in their DNA. Using our advanced algorithms, we can utilize these mutations to generate a tree that shows the evolution of a cancer in an individual cancer patient. On this tree, we can map the most important changes that can be used by doctors for making treatment decisions. In addition to using individual mutations, we can also use the patterns of all mutations in a cancer patient to pinpoint the processes that were active during evolution of the cancer. Some of these processes can be used as clocks to time the important changes found on the tree.
Overall, we will create a high-definition timeline of the molecular events in the metastatic cancer of each individual cancer patient. The project will examine almost 2,000 cancer patients and increase our understanding of the events needed to transform a cancer to a metastasis. This knowledge is an essential step in providing patients with metastatic cancer with an informed and optimal cancer treatment.
