Innovative metabolic mapping to predict and enhance the response of targeted anti-cancer therapies
Lead Research Organisation:
Institute of Cancer Research
Abstract
Evidence suggests that the way cells consume and process nutrients, collectively known as metabolism, differs between healthy and tumour cells and can even change the way they communicate with adjacent cells, grow, and importantly, respond to therapy. Nutrient availability in the environment where the tumour is growing can also have a fundamental impact on the effectiveness of anti-cancer therapies. This project will draw on the strengths of innovative tools and methods to track the metabolism of breast cancer tumours and pre-clinical models, and identify the metabolic determinants that guide the response to anti-cancer therapies. In this context, it will assist with gaining insight into how certain drugs affect tumour metabolism, and ultimately, how the metabolism of a tumour and its surrounding affect its response to therapy. In the longer term this knowledge will expose weaknesses in the tumour's armour and unveil more effective therapeutic strategies where diet and metabolic targets could help circumvent drug resistance and slow down tumour growth.
People |
ORCID iD |
| George Poulogiannis (Principal Investigator / Fellow) |
Publications
Dexter A
(2025)
A New Approach to Large Multiomics Data Integration.
in Analytical chemistry
Leslie TK
(2024)
A novel Nav1.5-dependent feedback mechanism driving glycolytic acidification in breast cancer metastasis.
in Oncogene
Tripp A
(2022)
Banking on metabolomics for novel therapies in TNBC.
in Cell research
Perry NJS
(2025)
Cancer Biology and the Perioperative Period: Opportunities for Disease Evolution and Challenges for Perioperative Care.
in Anesthesia and analgesia
Metodiev M
(2026)
Evaluating Batch Correction Methods for Large-Scale Mass Spectrometry Imaging of Heterogeneous Tissues.
in Analytical chemistry
Maneta-Stavrakaki S
(2025)
Laser Desorption-Rapid Evaporative Ionization Mass Spectrometry (LD-REIMS): A New Tool for the High-Throughput Metabolomic and Lipidomic Profiling of Live Cells.
in Analytical chemistry
Dannhorn A
(2024)
Morphological and molecular preservation through universal preparation of fresh-frozen tissue samples for multimodal imaging workflows.
in Nature protocols
Graziani V
(2025)
SLC7A11 protects amoeboid-disseminating cancer cells from oxidative stress
in Cell Reports
Kaufmann M
(2024)
Testing of rapid evaporative mass spectrometry for histological tissue classification and molecular diagnostics in a multi-site study
in British Journal of Cancer
Karalis T
(2024)
The Emerging Role of LPA as an Oncometabolite.
in Cells
Ling S
(2025)
Use of metabolic imaging to monitor heterogeneity of tumour response following therapeutic mTORC1/2 pathway inhibition.
in Disease models & mechanisms
Goodwin RJA
(2025)
Visualizing Cancer Heterogeneity at the Molecular and Cellular Levels: Lessons from Rosetta.
in Cancer discovery
Kreuzaler P
(2023)
Vitamin B5 supports MYC oncogenic metabolism and tumor progression in breast cancer.
in Nature metabolism
Duan S
(2025)
WNK1 signalling regulates amino acid transport and mTORC1 activity to sustain acute myeloid leukaemia growth.
in Nature communications
| Description | That is strong already-clear, accessible, and appropriate for a non-specialist audience. I would just make a few light edits for flow and concision: The research funded through this award has already produced important advances in understanding how cancers respond to treatment and why some tumours become resistant. A major achievement has been the identification of previously unrecognised links between specific cancer-causing genetic changes and the way tumours use nutrients and energy. This helps to explain why cancers that may look similar under the microscope can behave very differently in patients. The work has also shown that advanced metabolic imaging can be used to track differences in how distinct parts of a tumour respond to targeted therapies. This is important because tumours are often made up of a mixture of cell populations, and some regions may respond to treatment while others survive and drive relapse. By revealing this hidden variation, the project is helping to build a more accurate picture of tumour behaviour. Another key finding has been the discovery of a potentially actionable weakness in breast cancers carrying mutations in the PIK3CA gene. Building on earlier work, my team found that a cancer-related enzyme called cPLA2 can be inhibited indirectly by aspirin, and that this effect is influenced by the balance of omega-6 and omega-3 fats in the diet. This raises the possibility that a widely used drug, combined with dietary intervention, could become part of a more effective treatment strategy for this subtype of breast cancer. |
| Exploitation Route | The outcomes of this funding could be taken forward by other researchers and clinicians in several ways. The identification of links between specific genetic alterations and tumour metabolism could help others better understand why apparently similar cancers respond differently to treatment, and could guide the development of more biologically informed treatment strategies. The use of advanced metabolic imaging to track how different regions of a tumour respond to therapy could also be adopted more widely by others studying tumour heterogeneity and drug resistance. This approach has the potential to support the discovery of new biomarkers of response and relapse, and to improve how patients are stratified for targeted therapies. The findings in PIK3CA-mutant breast cancer may also have translational value for other groups. In particular, the discovery that cPLA2 can be inhibited indirectly by aspirin, and that this response is influenced by the balance of omega-6 and omega-3 fats in the diet, could be taken forward in future preclinical and clinical studies exploring combination treatment strategies. |
| Sectors | Pharmaceuticals and Medical Biotechnology |
| Description | Tracking metabolic reprogramming through stable isotope-resolved metabolomics |
| Amount | £497,353 (GBP) |
| Funding ID | MC_PC_ MR/X013715/1 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2023 |
| End | 03/2023 |