Rosetta

The team set out to harness the power of cutting edge mass spectrometry imaging (MSI) techniques to create Google Earth-like views of a tumour in extraordinary detail. The team planned to apply highly-innovative metabolic mapping tools to measure a broad range of metabolites and map their spatial distribution within tumours more holistically than ever before. By creating a detailed atlas of cancer metabolism, Rosetta aimed to provide a whole new dimension to cancer diagnosis and treatment.

When the challenge was set, progress had been made in understanding specific metabolic hallmarks of cancer in vitro. However, there remained a considerable gap in understanding complete metabolic networks and their rewiring in relevant tumour models in vivo, and importantly, in patients. Spatial measurement technologies for MSI were still niche with limited applications. To properly understand cancer metabolism would involve developing multi-scale spatial techniques to detect proteins, amino acids, fatty acids, carbohydrates, vitamins and lipids simultaneously from complex samples.

The team set out to develop innovative approaches to measure and map hundreds or thousands of metabolites in a single experiment, in order to create a ‘Rosetta Stone’ for cancer metabolism.

Rosetta has helped lead the spatial biology revolution, developing new MSI methods, instruments and computational tools to map tumour metabolism at different scales. The team’s integrated imaging pipeline enables researchers to examine fixed and frozen tissue as well as real-time sampling during surgery, and to compare findings across laboratory models and patient tumours. By combining complementary measurements, the team can build detailed metabolic atlases, identify patterns associated with tumour biology and guide further imaging and molecular analysis.

Rosetta has demonstrated the value of applying a metabolomics lens to spatial biology, uncovering novel and functional insights into the molecular basis of cancer. The team has also conducted initial studies to showcase the potential power of its pipeline for clinical applications. Using the intelligent surgical knife (iKnife) previously developed by members of the team, they demonstrated a new method for real-time diagnosis and highlighted the potential of stratifying cancers into subtypes according to their metabolic phenotype to help guide treatment selection. By analysing breast cancer cell lines, patient-derived xenografts and primary tumours, the team identified that disruptions to the PIK3CA kinase pathway cause an increase in the metabolite arachidonic acid, which are detectable by the iKnife. Arachidonic acid also fuels the growth of these breast tumours – revealing a targetable metabolic vulnerability that largely depends on dietary fat restriction.

Using their correlative MSI approaches to explore metabolic differences within mammary tumours, the team demonstrated that pantothenic acid (also known as vitamin B5) is associated with areas of high MYC levels. This is driven by MYC upregulating the multivitamin transporter SLC5A6, responsible for pantothenic acid transport. This work went on to highlight dietary restriction of pantothenic acid, which was ultimately being used to fuel the Krebs cycle, as a potential option to restrain tumour growth. The team also identified potential new therapeutic targets in colorectal cancer- the glutamine antiporter SLC7A5 in KRAS-driven tumours, as well as the methionine cycle enzyme AHCY in APC-deficient tumours.

In 2025, Rosetta extended its metabolic mapping work in patients with glioblastoma, an aggressive type of brain cancer. By infusing patients with labelled glucose before surgery, the team traced how tumours process this nutrient. Combining MSI of surgically removed tissue with spatial measurements of gene activity in neighbouring tissue sections revealed three distinct metabolic subtypes. These findings highlight differences in tumour metabolism that could help inform treatment selection in the future.

The team also developed a new laser-based technique, LD-REIMS, for rapidly profiling metabolites and lipids in live or frozen cells with minimal sample preparation. Using an automated platform, the researchers demonstrated that the approach could distinguish metabolic differences between cancer cell lines and track changes in response to low oxygen levels. This expands the tools available to explore how cancer cells adapt to their surroundings.

Alongside these experimental advances, Rosetta developed a deep learning approach to integrate large, complex datasets, bringing together information from MSI, gene activity and the three-dimensional organisation of DNA. The team also developed a statistical framework that accounts for noise in Orbitrap-based MSI measurements, helping researchers distinguish meaningful molecular patterns from background variation. Together, these computational advances strengthen researchers’ ability to interpret metabolic maps and connect them with other layers of tumour biology.

Through collaboration between industry and academia, AstraZeneca has applied Rosetta’s MSI platform to investigate questions ranging from drug distribution to emerging resistance. The platform has now been integrated across AstraZeneca’s drug development pipeline in order to improve therapeutic outcomes for patients.

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Team Rosetta has pioneered MSI technologies and demonstrated their importance, applicability and relevance for cancer research. At the forefront of the field, the team has accelerated the development and wider adoption of these cutting-edge techniques across academia and industry. This underscores the importance of metabolism in cancer research and highlights the value of integrating this component into spatial biology. We can succesfully say tha Team Rosetta completed their challenge.

By applying these innovative metabolic mapping tools, the team has already uncovered metabolic complexities informing on tumour behaviour, prognosis and response to treatment. These novel insights have identified potentially new therapeutic interventions and could ultimately lead to more tailored and personalised treatments through metabolomic profiling of tumours. Team Rosetta has pioneered MSI technologies and accelerated their adoption across academia and industry, establishing metabolism as an important component of spatial cancer research. Its tools have revealed metabolic differences within and between tumours, uncovered potential therapeutic vulnerabilities and enabled detailed studies in patient tissue.

Building on this foundation, the team’s continued advances in imaging and data integration could help researchers understand tumour behaviour and response to treatment more fully. Translating these findings into clinical tools could ultimately support more personalised cancer diagnosis and treatment.