Cancer is one of the most pressing, and prominent, public health concerns. Cancer Research UK reports that cancer caused more than a quarter of all deaths in the UK in 2016. One of the barriers for researchers looking to treat cancers is a lack of knowledge of the composition of tumours. Detail is particularly lacking on the molecular level, detail that intricately describes the behaviour and development of the tumour. This is what informs drug development strategy; the better we understand the molecular detail, the more drug targets will be revealed, and the more effectively we can target them.
At the National Physical Laboratory this picture is starting to emerge. The Rosetta team – named after the Rosetta stone, a vital reference point for the deciphering of Egyptian hieroglyphs – is developing a standardised, reproducible method of ‘mapping’ tumours; that is, pinning down the location of the components that support the growth of a tumour.
Previously, our work has been described as building a ‘Google Earth’ of cancer, and there are a lot of similarities behind this comparison. Cancer researchers build maps of tumours in the same way that mapping technology builds maps of locations, only instead of helping people to get from A to B, they contribute to a better understanding of the inner workings of a tumour.
Currently, the team’s focus is on a small number of tumours, including breast, bowel, and pancreatic tumours, as well as glioblastoma, a particularly aggressive type of brain tumour. The reasoning behind these tumours is that, through our partners, we have access to ‘state-of-the-art’ models of cancer that recapitulate the human disease, in addition to well-curated human samples. This provides maximum opportunity for addressing major questions, like what mutational drivers lie within tumours.
The importance of imaging
Key to unlocking this detail are imaging techniques, particularly mass spectrometry. NPL is home to the National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), which is a fantastic source of equipment and expertise in everything from Secondary Ion Mass Spectrometry (SIMS), to Matrix Assisted Laser Desorption/Ionisation Mass Spectrometry (MALDI-MS), as well as a host of other imaging techniques, including DESI and REIMS.
Mass spectrometry is a brilliant investigative tool; we can use MS methods to identify (based on the mass of molecules) chemicals in tissue, and to image lots of molecules in single experiments. In a tumour section, we can generate data on the molecules produced as a result of chemical reactions in cells, known as metabolites. These indicate the state of growth of the cell, and how it is developing. There is huge potential insight from this data; for example how tumours develop and respond to treatments.
A variety of mass spectrometry techniques can be used in combination to plot the 3D position of cells and molecules within tumours extremely precisely. This includes the complete tumour microenvironment, from the whole tumour down to monitoring fats and other molecules inside cells. We can combine this data with maps that reveal information about the underlying genetics of tumours to deliver a completely new review of tumour biology.
MALDI and DESI platforms both allow spatially resolved detection of metabolites from the surface of a section of thin tissue. In both cases, the molecules on the surface are ionised – with DESI, via a focused electrospray of a volatile solvent, and with MALDI, via the assistance of a ‘matrix’ compound applied to the tissue, which is then irradiated with a laser. Both enable relatively high-throughput of samples, rapid sample analysis and are unlabelled. Each is more suitable for analysis of different metabolites within a sample, meaning that they complement each other nicely. All the time, we are realising which is the best platform for different experiments, depending on the metabolites involved.
These platforms are powerful tools for our research as they lead us to particular areas of interest – for instance an area of drug resistance. Here, we can use higher resolution methods, such as SIMS and NanoSIMS, which offer the highest lateral resolution possible, and allow us to visualise metabolites or labels at an intracellular level of detail.
Alternatively, we can use imaging mass cytometry, which images mass tagged proteins with high special resolution. Both this and NanoSIMS can reveal unprecedented levels of detail within a tumour. In our programme we apply these techniques to carefully selected targets. The pipeline enables us to harness their capabilities, while addressing their shortcomings.
Results so far
To date, the team has seen remarkable results from its work. The first year saw the development of a pipeline for imaging tumours, which produces an ultra-high-resolution picture of their metabolism. We validated the pipeline, with major support from project partner AstraZeneca, by analysing preclinical tumours that had been treated with different cancer drugs. This work provided valuable insight into the distribution within tumours, highlighting hot-spots of drug resistance. Once this is known, it can be linked to the biological consequences, and this leads to improved efficiency within pharmaceutical studies, which we hope can be used in the future to develop new drugs more effectively, and with a greater rate of success.
Furthermore, we’ve been making great progress on our investigations of the mutational drivers for cancer, and we’re ready to take this to the next level; realising how preclinical model data translates into human samples.
The promising future
Our research relies on state-of-the-art measurements and instrumentation based at NPL and with our collaborators at Imperial College London, AstraZeneca, Barts Cancer Institute, and the University of Cambridge. We are studying cancer models from cancer biology experts at The Francis Crick Institute, The Institute for Cancer Research and the CRUK Beatson Institute. Importantly, all of our data will be freely available to the research community, removing the barriers to supercharging the discovery of drugs to treat cancers.
Our consortium has established an impressive pipeline to study precisely how tumour metabolism relates to the activation of key pathways, and now we can start to understand the mutational drivers of cancer. In the future this will support the lessons learned from preclinical models, and ultimately the research has the potential to accelerate novel strategies of treatment, as well as the biomarkers to develop them.
In addition to this, the imaging pipeline we have validated in our research will hopefully, in the future, be capable of effectively identifying previously undiscovered targets for drug development and accurate methods for diagnosing, and monitoring the treatment of, disease. This means that one day we may be able to predict therapeutic responses in cancers as a result of this research.
