Cancer is a heterogeneous disease that complicates its study and therefore treatment. Immunotherapy has revolutionized cancer treatment but many patients still are facing with little or no clinical benefit with the same treatment. Recent high-dimensional technologies have allowed us the ability to understand the tumor ecosystem and its impact on treatment response. We are motivated by the questions of how the tumor microenvironment changes upon cancer progression, before and after treatment, and if we can predict treatment responses based on blood immune cell signatures.


We follow where science takes us. Currently, we leverage computational biology approaches, using high-dimensional data from multi-omics genome-wide (genomics and epigenomics) and single-cell assays, data mining, and bioinformatics. We develop and employ computational biology methods to mine publicly available data and in-house generated data for the specific questions we ask. We validate what we found in human data using independent data cohort, in vitro and in vivo approaches.

Ultimately, our goal is to understand how tumor immune microenvironment changes toward finding immunotherapeutic biomarkers and targets.

Although our central questions focus on cancer, we are open to the collaborative environment in Madison to explore similar questions in other diseases.

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