Grupo de Genómica Computacional del Cáncer

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Becarios Pre-Doctorales

  • Jaejun Lee

Técnicos de Laboratorio

  • Adrián Maqueda
  • Manuel Moradiellos

Cancer is a complex disease whereby cells grow and reproduce uncontrollably. One important feature necessary to understand cancer is its heterogeneity, which indicates that the effect of alterations could be different depending on the cellular context. In the Computational Cancer Genomics (CCG) Lab, we aim to understand the context-dependent cancer fitness landscape both by applying a computational approach and by setting up experimental collaborations. For example, we are specifically interested in changing the cancer fitness landscape depending on time, by analysing the associations between germline variants and somatic alterations, or by comparing the differences between the primary tumour and metastasis. In addition, we aim to further pursue how protein-protein interaction networks of cancer driver genes can be perturbed by their somatic or germline variants. We expect that our context-dependent cancer fitness landscape will provide a crucial direction for personalised medicine, since we are aiming to address the heterogeneity across patients, conditions, and cellular contexts.