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
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