Stanford University
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Raya Saab
Lindhard Family Professor of Pediatric Cancer Biology
BioOur laboratory focuses on investigating molecular mechanisms of oncogene-induced tumorigenesis and tumor suppressor pathways, and oncogenic signaling in the pediatric solid tumor rhabdomyosarcoma. Our earlier work identified the tumor suppressors p53 and p18Ink4c as inhibitors of Cyclin D1-driven tumorigenesis in a pineoblastoma model, through senescence induction, and highlighted distinct roles for the the RB and p53 pathways in induction and maintenance of oncogene-induced senescence. We also identified CDK2 as a potential target for inducing senescence in premalignant lesions to inhibit tumor progression.
Our current focus is on studying oncogenic signaling and tumor suppression in the childhood tumor rhabdomyosarcoma, to identify key mediators of invasion and metastasis, which is the most common cause of treatment failure clinically. We use preclinical in vitro and in vivo models, including murine and human cell lines, and mouse models of disease.
We have recently uncovered a paracrine role for rhabdomyosarcoma-secreted exosomes in impacting biology of stromal cells. Rhabdomyosarcoma-derived exosomes carry specific miRNA cargo that imparts an invasive and migratory phenotype on normal recipient fibroblasts, and proteomic analysis revealed specific and unique pathways relevant to the two different molecular rhabdomyosarcoma subtypes that are driven by distinct oncogenic pathways. We identified that the driver oncogene in fusion-positive rhabdomyosarcoma, PAX3-FOXO1, modulates exosome cargo to promote invasion, migration, and angiogenic properties, and identified specific microRNA and protein cargo acting as effectors of PAX3-FOXO1 exosome-mediated signaling, including modulation of oxidative stress response and cell survival signaling.
Our ongoing work is focused on interrogating specific paracrine signaling pathways and molecular mechanisms of metastatic disease progression in rhabdomyosarcoma, for potential therapeutic targeting. -
Chiara Sabatti
Professor of Biomedical Data Science and of Statistics
Current Research and Scholarly InterestsStatistical models and reasoning are key to our understanding of the genetic basis of human traits. Modern high-throughput technology presents us with new opportunities and challenges. We develop statistical approaches for high dimensional data in the attempt of improving our understanding of the molecular basis of health related traits.
