Peng Jiang, PhD

Stadtman Investigator
Cancer Data Science Laboratory

My research focuses on developing big-data mining and artificial intelligence frameworks to study cancer immunotherapy resistance and tumor immune evasion. For example, we have released the CytoSig platform (Jiang et al., Nature Methods 2021), providing both a database of target genes modulated by cytokines and a predictive model of cytokine signaling cascades from transcriptomic profiles, based on 20,591 transcriptome profiles for human cytokine, chemokine, and growth factor responses. Previously, we have developed a data integration platform, TIDE (Jiang et al., Nature Medicine 2018), hosting data from large-scale immuno-oncology studies, functional genomics screens, and non-immunotherapy datasets repurposed to study tumor immune evasion. TIDE enables the robustness evaluation of immune checkpoint blockade response biomarkers and the candidate immunotherapy resistance regulators across many studies. Currently, we are developing computational models to evaluate the T-cell efficacies and recognition specificities in cell therapies in solid tumors. My current team has members from both computational and wet-lab backgrounds. Thus, students from diverse backgrounds can find a good fit in our Lab.

Suggested Penn mentors: Jenny Jiang, Michael Millone, John Wherry, Robert Vonderheide, Carl June