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Adrian Godlewski, MSc, from the Metabolomics and Proteomics Laboratory, operating within the Clinical Research Centre of the Medical University of Bialystok, received PLN 209,814 in funding for a research project entitled ‘Estimating the probability of glioma recurrence and its timing using metabolomics, proteomics and machine learning tools’. The funds were awarded as part of the PRELUDIUM 24 competition organised by the National Science Centre. The scientific supervisor of the project is Prof. Michał Ciborowski.

The aim of the research is to identify metabolites, lipids and proteins that will allow the risk of glioma recurrence to be assessed and the time of its occurrence to be predicted. Glioma is one of the most aggressive and deadly brain tumours, and the main cause of therapeutic failure is recurrence of the disease after surgical and adjuvant treatment. Currently, the diagnosis of recurrence is based primarily on imaging methods such as computed tomography or magnetic resonance imaging, but due to technical limitations, it is often difficult to clearly distinguish tumour recurrence from natural postoperative changes.

The project plans comprehensive metabolomic, lipidomic and proteomic analyses of plasma and tumour tissue collected from patients undergoing surgery for glioma. The idea for the research is the result of cooperation between the Metabolomics and Proteomics Laboratory and the MUB Department of Neurosurgery headed by Dr Tomasz Łysoń. The MUB Biobank also plays a key role, with its staff ensuring the high quality and reliability of the biological material used in the analyses.

Combining metabolomic and lipidomic data with proteomic research results increases the chance of identifying specific markers of recurrence. Proteins, especially enzymes and transporters, are often responsible for metabolic changes in cancer cells, so their analysis can help to better understand the mechanisms of glioma progression. The research will be complemented by machine learning tools that will enable the development of predictive models to estimate both the risk of recurrence and the time of its occurrence.

The project has the potential to provide important information on the mechanisms of glioma recurrence and lay the groundwork for the development of a minimally invasive method for early detection of recurrence. The model developed may in the future provide real support for doctors, facilitating the planning of follow-up visits and therapeutic decisions, and thus contribute to prolonging the lives of patients.

The results of the research may also pave the way for further, larger projects and become an important step in the development of precision medicine in neurosurgery, particularly in the area of diagnosis, monitoring and prognosis of brain tumours.

Project title: ‘Estimating the probability of glioma recurrence and its timing using metabolomics, proteomics and machine learning tools.’

Grant amount: PLN 209,814

The grant is administered by the Department of Development and Evaluation at the Medical University of Bialystok.