Publication: Digital ‘Rosetta Stone’ able to decipher how genetic mutations rewire signalling in cancer cells

Thomas R. Cox, Sep 2015

Linding Lab publishes back-to-back papers in Cell explaining how genetic cancer mutations systematically attack the networks controlling human cells

Today Professor Rune Linding at the Biotech Research & Innovation Centre (BRIC), University of Copenhagen (UCPH) along with collaborators at BRIC UCPH, Yale, University of Zurich (UZH), University of Rome and University of Tottori, have published back-to-back papers in Cell unravelling how disease mutations target and damage the protein signalling networks within human cells.

doi:10.1016/j.cell.2015.08.056 and doi:10.1016/j.cell.2015.08.057

doi:10.1016/j.cell.2015.08.056 and doi:10.1016/j.cell.2015.08.057

In these two papers, both first authored by Pau Creixell (formerly Linding Lab, but now a Postdoctoral Research Associate at Massachusetts Institute of Technology (MIT)), researchers have developed a novel platform that allows them to computationally translate the effects of DNA mutations on the function of translated proteins.

Network attacking mutations

Types of network attacking mutations

The studies demonstrate that kinases are not only simply switched ‘on’ or ‘off’ by cancer mutations, but that their behaviour can be drastically modulated to disrupt other proteins and protein networks thereby pushing normal cells toward a more cancerous state.

The researchers have created two pieces of software;
1. KINspect which is designed to predict the specific parts of a kinase which are essential for its activity
2. ReKINect which predicts the functional impact of genetic mutations on the activity of the kinase

How do they work?

The first of the two programs, KINspect is a computational algorithm that works out which amino acid residues within the kinase sequence are important for determining the specificity of the kinase in selecting (and phosphorylating) a substrate. These so-called ‘Determinants of Specificity’ (DoS) are the residues which are critical to kinase specificity. The algorithm was validated on a set of kinases with known, published DoS, but the new tool can go beyond what is known and predict DoS not previously reported.

The predictions from KINspect then form the basis of the second tool, ReKINect. This tool is used to predict whether a mutation in one or more of these DoS would have an effect on the specificity of the kinase. Such a mutation might activate or deactivate the kinase, change the specificity of the kinase or create/destroy phosphorylation sites. All of these events would lead to changes in protein signalling networks within cells and are termed network-attacking mutations (NAMs). ReKINect was used to classifiy known cancer mutations and predict their ability to perturb cellular signalling, although the tool could be applied to any biological system or disease.

Using these two tools together, it means that we can now take patient-specific mutation data and predict not only the rewiring that has occurred in the cells, but also which drugs will be most effective in treating a specific patient.


Kinome-wide Decoding of Network Attacking Mutations Rewiring Cancer
Creixell P, Schoof EM, Simpson CD, Longden J, Miller CJ, Lou HJ, Perryman L, Cox TR, Zivanovic N, Palmeri A, Wesolowska-Andersen A, Helmer-Citterich M, Ferkinghoff-Borg J, Itamochi H, Bodenmiller B, Erler JT, Turk BE, Linding R
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Unmasking Determinants of Specificity in the Human Kinome
Creixell P, Palmeri A, Miller CJ, Lou HJ, Santini CC, Nielsen M, Turk BE, Linding R

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Read more about the Linding Lab here

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Biotech Research & Innovation Centre (BRIC)
European Research Council (ERC)

The work was supported by the European Research Council (ERC), the Lundbeck Foundation and Human Frontier Science Program.