'Virtual' experiments could find cancer cure.
Using computer games technology, scientists at Abertay University have worked with the University of St Andrews Medical School to develop an interactive, animated simulation of cell signalling behaviour that has the potential to transform the way new, life-saving cancer treatments are developed.
Known as SiViT, the simulation tool converts existing models of cell behaviour into dynamic, colour-coded animations that enable researchers to conduct virtual experiments with anti-cancer drugs.
Drugs can be added to the animations from a drop-down menu, allowing for exploration of cell signalling pathway dynamics in a way that has never been possible before.
Signalling network response to 30 nM of pertuzumab
Time can be wound forwards and backwards to see how cells will be affected by different dosages of different drugs, including combinations of drugs, applied in different sequences and at different times.
Understanding the connections and interactions that have taken place within the modelled cells, and how they are affected by anti-cancer drugs, has until now only ever been possible through sophisticated model analysis, typically with the help of computational scientists.
Their vital role was to configure the models and act as interpreters of the data they generated each time the clinicians and biologists wished to carry out a new computer-based experiment.
These results were used to inform the clinicians’ next in vitro experiments, but the process was complicated by the different languages of the different disciplines which made it difficult for each to understand the other’s research and results.
Introduction of a mutation in the network
SiViT removes that complication: the clinicians interact with the model as if it were a computer game, while the model works away in the background, re-computing each of the complex mathematical equations the model is made up of every time they make a change to the experiment on screen.
The algorithm behind the animations uses the resulting data to optimise layout, automatically converting it into a graph of loops and rings that makes it possible for the clinicians to easily see the network of connections and interactions within a cell.
Through the interactive, animated graph, they can quickly and easily introduce a cancer-causing mutation into the network and then find ways to combat that mutation through combinations of anti-cancer drugs.
This aspect is of crucial importance in the design of combination therapies – an emerging form of personalised cancer treatment that offers a possible route to overcome anti-cancer drug resistance.
The challenge cancer scientists face is that different cell types contain pathways that can behave in different ways and react to drugs in different ways.
Response of mutated network to combination therapy
The beauty of SiViT in the face of this challenge is that it can run any model of cell behaviour – whether that is models of ovarian cell pathways, prostate cells, or breast cancer cells – so it can be adapted to suit the needs of any research team working on any cell type anywhere in the world.
Details of how SiViT works are published in the journal Oncotarget today (Friday 20 May).
Jim Bown – Professor of Systems Biology at Abertay University – who has led this project, explains why the development of SiViT is such a significant step forward for cancer research:
“Cell signalling networks are enormously complex systems and it’s this complexity that makes cancer research so incredibly difficult.
“These days, although it’s possible to determine whether an individual would be likely to benefit from a particular type of treatment or not – using what is called a disease specific biomarker – there are still no guarantees that the treatment will work.
“The patient might get an initial response, but after a while the drug will stop working because the cancer cell has found a way to overcome whatever the drug had managed to prevent it from doing.
“It’s enormously difficult to unravel all the mechanisms and complexities of network functioning to work out why cancer becomes resistant to drugs.
“When it comes to combination therapies, it isn’t just the types of drugs and the dosage that are important, but the order in which they are applied.
“Finding the right drugs that will work on the right part of the network and in the right way, without unexpected consequences, is a huge search problem for cancer scientists, and this tool can help them in that search so that they can develop new ways of treating cancer and, ultimately, increase survival rates.”
Professor David Harrison from the University of St Andrews, whose cancer research provided the data used to build and test SiViT, explains why this new tool is so important from his perspective:
“At the moment, the five-year cancer survival rate is at just 50 per cent. It is increasing, and further increases depend on us better understanding cancer. Part of that understanding comes from cancer cell experiments in the lab.
“Such in vitro experiments are time-consuming and expensive, so we have to be very careful in selecting which ones we do. But it’s extremely difficult because we have to try and predict how a change in one part of a cell’s pathway will have an impact on another.
“We can use computational models to help us understand the behaviour of the cell, and representing the important pathways in a cell can involve tens of interrelated equations.
“It’s easy enough to understand each equation locally and its nearest neighbour relationships, but understanding the system as a whole is hugely complex – the equation sets can be lengthy and intricate.
“The visualisation tool that Jim and his colleagues at Abertay have developed totally transforms this process though. It allows us to explore cell behaviour in a way that we just haven’t been able to do before: we’ve never had the ability to ‘see’ the numbers and figures we’re dealing with, to wind time backwards and forwards to see the effect of a drug on a certain part of the pathway. We’ve never been able to zoom in on a specific part of the pathway to examine an interaction more closely either.
“So it’s going to change the way we do things for the better. It’ll reduce the overall number of experiments we need to do, the huge cost involved and – most importantly – help us to develop new treatments that will save people’s lives.”
Abertay University is at the forefront of using computer games technology in both interactive media for entertainment and as a vehicle for exploring and understanding complex systems.
Interactive visualisation can be a valuable tool for gaining insights into complex systems, and can inform system management, plan for different scenarios and provoke informed discussion among multiple stakeholder groups.
Experts in computer graphics, computer science, mathematics and applied physics work together with biomedical scientists, epidemiologists, ecologists and engineers to develop interactive solutions to real world problems.
This interdisciplinary approach has already been used to develop an interactive, 3D computational modelling and visualisation tool that supported the planning process of the Dundee Waterfront project - a 30-year £1 billion investment into Dundee.
It has also been applied in relation to raising awareness of the issues faced in sustaining our environment. For example, a four-dimensional, realistic bird’s-eye view of the Fife coastline was created to help local people understand how to better protect a coastline that has already been affected by rising sea levels and severe storm events.
In addition to the work on cancer systems biology, the team are currently exploring how this technology can be used to help safeguard the future of the UK’s water, energy and food security.
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