Latest information on COVID-19
Support teaching, research, and patient care.
I am passionate about translational research and how single cell technologies could open up new avenues for better and more accurate predictive models. Currently, I am focus on integrating single cell RNA and protein expression data to develop models to predict patient at risk for Antigen Loss relapse after CAR T cells immunotherapy.
CD19-directed chimeric antigen receptor T cell (CAR-T) therapy has shown impressive results in children and adults with relapsed or refractory (r/r) B-ALL or non-Hodgkin lymphoma. However, 30 – 70% of initial responders will eventually relapse with CD19 antigen loss (CD19Neg). The development of tools to accurately predict which patients are at risk for CD19Neg relapse would guide treatment decisions regarding alternative therapies. <br/>The goal of my research is to develop a model to predict which patients are at risk for CD19Neg relapse.<br/>I hypothesize that resistant tumor cells, and their features associated with CD19Neg relapse, are present before CAR-T administration and can be detected and used to build a model to predict which patients are at risk for CD19Neg relapse. To that end, I used a combination of single cell mass cytometry (CyTOF) and simultaneous whole transcriptome analysis and antibodies sequencing (WTA-AbSeq) data from B-ALL patient samples collected before or after CD19-directed CAR-T administration. Through these analyses I expect to identify and deeply characterize those tumor populations present before CAR-T administration responsible for CD19Neg relapse.