Translational Tools and Resources to Advance MHC (HLA) Cancer Genetics

The Cieslik Lab develops computational and statistical approaches to characterize and understand cancer genomes. Our overarching goal is to discover the genomic underpinnings of cancer and translate clinically relevant findings into diagnostic tools. Currently, the key objective of the lab is to understand how cancer genetics shapes anti-tumor immunity and response to immunotherapy. We are also working to understand the evolutionary and selective role of structural and copy-number variation in cancer metastasis and progression. Finally, we are studying how germline variation contributes to the somatic evolution of tumors. A significant focus is on developing applied bioinformatics methods to improve and enhance precision oncology. These analytical approaches, tools, and pipelines are being used within MI-OncoSeq, our institutional precision oncology program.