A Computational Cancer & Immunology lab at the McArdle Laboratory for Cancer Research


Diseases like cancer are heterogeneous, complicating how we understand them and, therefore, treatment. Immunotherapy has revolutionized cancer treatment, but many patients still face little or no clinical benefit with the same treatment. Recent high-dimensional technologies have allowed us the ability to understand the tissue ecosystem and its impact on treatment response. We are motivated by the questions of how the tissue microenvironment changes upon disease progression, before and after treatment, and if we can predict treatment responses based on blood immune cell signatures, with a special focus on neutrophils. Another strong focus of the lab is characterizing and understanding neutrophils in the wound-healing context. We wish to identify severe human burn trauma biomarkers by looking at human samples and model organisms like zebrafish and mice and to compare neutrophils with cancers – the wounds that do not heal.


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, we aim to understand how the immune tissue microenvironment changes toward finding immunotherapeutic biomarkers and targets.

Although our central questions focus on the biomedical context, we are open to the collaborative environment in Madison to explore similar questions in other exciting areas.

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