Proteomic maps of breast cancer subtypes

Stefka Tyanova, Reidar Albrechtsen, Pauliina Kronqvist, Juergen Cox (), Matthias Mann () and Tamar Geiger ()
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Stefka Tyanova: Max Planck Institute of Biochemistry
Reidar Albrechtsen: University of Copenhagen
Pauliina Kronqvist: University of Turku
Juergen Cox: Max Planck Institute of Biochemistry
Matthias Mann: Max Planck Institute of Biochemistry
Tamar Geiger: Max Planck Institute of Biochemistry

Nature Communications, 2016, vol. 7, issue 1, 1-11

Abstract: Abstract Systems-wide profiling of breast cancer has almost always entailed RNA and DNA analysis by microarray and sequencing techniques. Marked developments in proteomic technologies now enable very deep profiling of clinical samples, with high identification and quantification accuracy. We analysed 40 oestrogen receptor positive (luminal), Her2 positive and triple negative breast tumours and reached a quantitative depth of >10,000 proteins. These proteomic profiles identified functional differences between breast cancer subtypes, related to energy metabolism, cell growth, mRNA translation and cell–cell communication. Furthermore, we derived a signature of 19 proteins, which differ between the breast cancer subtypes, through support vector machine (SVM)-based classification and feature selection. Remarkably, only three proteins of the signature were associated with gene copy number variations and eleven were also reflected on the mRNA level. These breast cancer features revealed by our work provide novel insights that may ultimately translate to development of subtype-specific therapeutics.

Date: 2016
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DOI: 10.1038/ncomms10259

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