Cell communication with Rune Linding

Understanding communication between cells is crucial because many forms of cancer and other diseases are caused by the breakdown of communications systems. A cutting edge technique that enables scientists to monitor communication between cells could transform the way medical experiments are formed

Scientists at the Institute of Cancer Research have developed a method to make laboratory studies of cancers and other human diseases – and assessment of drugs to treat them – more accurate. Their method accurately mimics what happens in the body and allows them to monitor the Eph communication system. Many types of cancer, including colorectal cancer, lung, prostate and breast cancer and glioma have an abnormality in the Eph system.

Dr Rune Linding is head of the Cellular and Molecular Logic Team at ICR and developed this new method with colleagues in the UK and Canada.

Why is it necessary to understand how cells communicate?

All multi-cellular organisms depend on their cells communicating. The communication is key for the development of tissues and organs but this communication can also be hijacked by diseases - for example in cancer.

Cells communicate using EphB2 – could you explain how and when?

The EphB2/ephrinB1 system is a pair of proteins that reside in the cell membrane, often they are expressed at different levels so one population of cells will have the EphB2 receptor and another population the EphrinB1 ligand. Once cells get in close proximity the two molecules can bind together, and this results in signals being propagated in the two cells. This happens for example in the colon, and results in tissue boundary formation and organisation of the colon tissues. The gene encoding for the EphB2 protein if often mutated in colon cancer and many other cancers.

How were you able to ‘hear’ the cell communicate? We took an integrative network biology approach. By quantifying signalling events (phosphorylation) in the EphB2 system using mass-spectrometry and genetic perturbations using siRNA, we could construct network models of each cell population. This is the first time we have been able to systematically listen in on the interpretation of the conversation in both the EphB2 and ephrinB1 cells. That is, we could not only hear the conversation, we could also to some extent see how each cell type responded to the conversation.

How does this differ from previous methods used and what were their shortcomings?

It's dramatically different. Classical biochemical approaches using, for example, phospho-specific antibodies cannot distinguish which signals come from each cell type. In addition, such approaches do not give the same quantification possible with mass-spectrometry. Most important is that we could trace the signalling events back to each cell type due to labelling of their proteomes - all proteins within the cell - using modified amino acids; in addition we integrated the data from siRNA screening and our algorithms NetworKIN and NetPhorest to provide integrated network models.

What is the importance of this research – what will it mean for laboratory testing?

The importance of this work is that for the first time have we been able to systematically assess and model the communication between two cell populations. In many ways this is similar to when astronomers first observed collisions between galaxies, a lot of new knowledge can be derived from studying such phenomena.

A key outcome is that using traditional artificial ligands like EGF or TNF in high concentration results in networks and cell behaviour that are highly distorted. It is crucial to do experiments at physiological relevant settings, for example by mixing cells instead of using synthesised ligands.

[caption id="attachment_23464" align="alignright" width="150" caption="Rune Linding"][/caption]

What is the next stage of your research?

We will perform studies in time and evolution and importantly also look at such systems in vivo. We work as part of the Integrative Network Biology initiative (INBi) at the ICR which is a large-scale multi-diciplinary and highly collaborative new research focus for the ICR aiming to target metastatic progression through high-dimensional signalling network modelling.