Invited Guest Speaker: Mariaelena Pierobon, MD MPH
About the Speaker:
Dr. Pierobon is an Associate Professor at the School of Systems Biology and an affiliate faculty member of the Department of Bioengineering at George Mason University. She received a Medical Degree from the University of Padova, Italy, after which she began a surgical residency. Her work as a bench scientist began in 2005 when, sponsored by the Rotary Foundation, she joined the Center for Applied Proteomics and Molecular Medicine at George Mason University. Dr. Pierobon’s work has yielded more than 70 publications in peer-reviewed journals and is supported by U.S. federal and state funding sources as well as private foundations. Throughout her career Dr. Pierobon has mentored more than 30 students at different academic levels. In 2019, she was the recipient of a U.S. Fulbright Scholar award. Current research in Dr. Pierobon’s lab focuses on mapping and targeting signal transduction events to identify cancer vulnerabilities, uncover mechanisms of resistance, and devise multi-omic based strategies for treatment selection and response prediction.
Seminar Abstract:
The identification of genomic alterations that encode for druggable malfunctioning signaling molecules has revolutionized the field of oncology and paved the way for a major paradigm shift in cancer treatment. NGS-based molecular profiles have become an integral part of the therapeutic decision-making process in oncology. However, the relatively low matching rates to precision drugs has limited the number of patients who are eligible for personalized treatments. While genomic alterations are catalytic events for tumor initiation and progression, they phenotypically manifest as aberrantly activated signal transduction networks. From a functional perspective, these signaling networks regulate cellular activities in physiological and pathological conditions through spatial-temporal dynamic adaptations to incoming signals and endogenous or exogenous changes within the tumor microecology. Integration of signaling dynamics and functional proteomic data into translational studies and multi-omic-based treatment selection pipelines will be increasingly valuable for subclassifying tumors based on their true molecular drivers and for fine-tuning treatment selection for cancer patients.
