Future cancer care will use mutation analysis of tumour DNA as a tool to match each patient with the best possible treatment. To do this we must improve our understanding of the importance of different mutations. Today, analyses completely focus on mutations that are relatively easy to interpret, while so-called "silent" or synonymous mutations, which do not directly alter a protein, are filtered out. However, also synonymous mutations can be functional through effects on e.g. mRNA splicing or the speed of translation. We study synonymous mutations in breast cancers from several thousand Swedish women to investigate their effects on tumour behaviour with a combination of bioinformatic analyses and functional studies. Through this research we wish to demonstrate that also "silent" mutations are important so that more patients can receive targeted treatment. Hopefully, our work will also lead to identification of new therapeutical targets and a reevaluation of the standard analysis of sequencing data.
