New Investigator Research Grant Program

Many leukemias, especially in children, are driven by “oncofusion” proteins. These abnormal proteins arise in cancer cells when DNA mutations cause two separate genes to mistakenly join together. Once generated, oncofusions help leukemia cells grow in an uncontrolled manner. Unfortunately, oncofusion proteins are difficult to target with existing drugs because they do not have obvious “on/off” switches. Instead, they rely on interactions with other proteins in the cancer cell to function. While some new drugs have begun to block these interactions, cancer cells can develop resistance, creating an urgent need for new treatment strategies.
Our project aims to find new targets and therapeutic strategies for these leukemia-driving oncofusion proteins using functional data and artificial intelligence (AI). We will combine large-scale genomic data with advanced computational models that predict how proteins interact in three dimensions. This will allow us to identify critical contact points between proteins that could be targeted by new drugs. We will first test and refine our approach in an aggressive form of acute leukemia driven by the KMT2A (MLL) oncofusion and then expand our approach to three other oncofusions to create a discovery resource for the research community.
By making these tools and data openly accessible, our work will help accelerate the discovery of new, more effective treatments for leukemias driven by oncofusions, ultimately improving outcomes for patients.