UC San Diego

Tumors evolve from normal cells due to aberrant activation or repression of cell signaling. Our understanding of how these signaling pathways affect the phenotype of the malignant cells themselves, as well as the surrounding microenvironment, is lacking. As the era of precision medicine approaches, a more holistic understanding of cancer intrinsic signaling and its effect on the epigenome of tumor cells, as well as how these tumor cells interact with surrounding normal cells, is key to unlocking novel therapeutic targets and biomarkers. Through three examples of cancer evolution and signaling I will show the value of integrative data modeling to better understand the biology of this disease.First, in the context of breast cancer progression, I developed a microenvironment modeling approach to identify several novel intercellular signaling pathways that are altered in the transition from in situ to invasive disease. Second, in uveal melanoma, a cancer caused by aberrant GNAQ signaling, I generated and integrated transcriptional and protein level datasets together to nominate p53, and other pathways, as novel downstream targets of GNAQ. And third, in the context of head and neck cancer progression, I characterized the role of YAP activation in malignant transformation and cell signaling through EGFR and mTOR.