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Greta Guarda


Greta Guarda studied Molecular Biology at the University of Zurich and performed her diploma work at the Swiss Federal Institute of Technology, Zurich. From 2004 to 2007, she carried out her PhD work on T cell-mediated immunity at the Institute for Research in Biomedicine (IRB), Bellinzona. In 2007, she joined as post-doctoral fellow the University of Lausanne, where she became senior lecturer in 2010. During these years, she focused her research on NOD-like receptors and inflammasome function. She established her independent research group in 2012 thanks to the award of a Swiss National Science Foundation professorship and a European Research Council starting grant. Greta Guarda joined the IRB as Group Leader in 2018 and is Full Professor at the Università della Svizzera italiana, where she became Vice-Dean of Research in 2021. Since 2016, she is member of the Federal Ethics Committee on Non-Human Biotechnology and since 2020 she has been elected member of the Swiss Academy of Sciences, Forum for Genetic Research. For her scientific contributions, she was awarded the Premio Fondazione Dr. Ettore Balli 2018, the Pfizer Research Prize 2019, and the Friedrich Miescher Award 2020.



Our research focuses on the interplay between major histocompatibility complex (MHC) class I, cytotoxic T cells, and natural killer (NK) cells in the context of infection and cancer. In fact, recognition of infected or transformed cells by cytotoxic T lymphocytes requires MHC class I molecules. NK cells, using a complementary strategy, eliminate hazardous cellular targets lacking MHC class I expression. These molecules are therefore central players in immunity and we study novel mechanisms – relevant for innate and adaptive cytotoxic responses – regulating their levels. Further, we investigate new molecular pathways controlling function and metabolic fitness of lymphocytes in health and disease. To achieve these goals, we use a variety of approaches, including genetic, genomic, biochemical, and molecular techniques, as well as translational models.

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