From cancer evolution to personalized therapies

Being able to predict the resistance or sensitivity of a tumour cell to a drug is a key success-factor of cancer precision therapy. But such a prediction is made difficult by the fact that genetic alterations in tumours change dynamically over time and are often interdependent, following a pattern that is poorly understood. A recent study led by researchers at the SIB Swiss Institute of Bioinformatics, University of Lausanne and EPFL provides a promising framework to anticipate drug resistance in cancer, by predicting the co-occurrence of about 500 known tumour alterations, as well as their response to over 200 common cancer drugs. The research, published in Cancer Cell, showed that while some co-occurrences between genomic alterations confer a resistance to tumour cells against particular drugs, they also make them sensitive to other unexpected drugs.

Mina M et al. Conditional selection of genomic alterations dictates cancer evolution and oncogenic dependencies. Cancer Cell, online on 27 July 2017. DOI:

Link to the highlight in Nature Reviews Clinical Oncology
Link to the highlight in Cancer Cell
Link to the data and software described in the paper
Link to the Ciriello Lab

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