Gfeller lab

Tumors form highly complex structures comprising many different cell types like cancer and immune cells. In our research, we use and develop computational biology and immuno-informatics to better understand and predict the interactions between immune and cancer cells. Our lab is affiliated to the Department of Oncology at the University of Lausanne (UNIL), the Ludwig Institute for Cancer Research (LICR) and the Swiss Institute of Bioinformatics (SIB). ...

Research projects

Analysis and predictions of antigen presentation and TCR recognition

The diversity of T-cell epitopes in cancer is overwhelming due the heterogeneity of genetic alterations and the polymorphism of HLA genes. To narrow down the most promising candidates, our lab has developed state-of-the-art predictors of HLA-I [Gfeller et al. J Immunol 2018, Gfeller et al. Cell Systems 2023] and HLA-II ligands [Racle et al. Nature Biotech 2019, Racle et al. Immunity 2023], as well as predictors of neo-epitope TCR recognition [Schmidt et al. Cell Rep Med 2021, Gfeller et al. Cell Systems 2023]. These predictions are largely based on high-quality HLA peptidomics data and machine learning algorithms for motif deconvolution [Bassani-Sternberg and Gfeller J Immunol 2016 , Racle et al. Nature Biotech 2019 ]. Our findings also revealed alternative binding modes of HLA ligands [Guillaume et al. PNAS 2018, Racle et al. Immunity 2023],  and enabled us to better understand the properties of the antigen presentation pathways.

Modelling TCR repertoire and specificity

T cells have the ability to generate billions of T-Cell Receptors (TCRs) that can recognize various epitopes displayed on HLA molecules. While information about the presence of specific T cells in a tumor can be obtained with TCR-sequencing technologies, a major challenge remains to know which T cells recognize which epitopes. Together with several experimental collaborators, we are developing machine learning algorithms both for understanding and modelling the properties of the TCR repertoire and unraveling the determinants of TCR specificity for their cognate epitopes.


David Gfeller

PhD Computational cancer biology, Associate Professor, Department of Oncology UNIL & CHUV, Ludwig adjunct scientist, Ludwig Institute for Cancer Research Lausanne GfellerLab

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