Computacional Cancer Genomics Group

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Technicians

  • Luis García

Cancer is one of the most complex human diseases, involving genetic, environmental and even unknown factors. Over the past several decades, large-scale genomics analyses of cancer patients have been made in order to understand this complex disease. One of the most striking findings of large-scale cancer genomics is the remarkable heterogeneity in cancer driver (oncogene or tumour suppressor gene) alterations across different patients and cancer types. However, even though various important biological characteristics are commonly measured in cancer patients, little is currently known about the cancer type- or context-specific tumour progression for each gene in each cancer type. Furthermore, by analysing large-scale cancer genomics data, many exceptions have been observed, including haploinsufficiency in tumour suppressor genes, or amplification-linked mutations in oncogenes and even in dual-functional genes. Clearly, activity levels of genomic alterations in cancer genes are disparate across cancer types, and their optimal models for tumour progression may also vary depending on contexts or cancer types.

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