Metabolite profiles of medulloblastoma for rapid and non-invasive detection of molecular disease groups.

Autor:	Kohe S; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Birmingham Children's Hospital, Birmingham, UK., Bennett C; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Birmingham Children's Hospital, Birmingham, UK., Burté F; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK., Adiamah M; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK., Rose H; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Birmingham Children's Hospital, Birmingham, UK., Worthington L; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Birmingham Children's Hospital, Birmingham, UK; RRPPS, University Hospital Birmingham, Birmingham, UK., Scerif F; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK., MacPherson L; Birmingham Children's Hospital, Birmingham, UK., Gill S; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Birmingham Children's Hospital, Birmingham, UK., Hicks D; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK., Schwalbe EC; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK; Department of Applied Sciences, Northumbria University, Newcastle upon Tyne, UK., Crosier S; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK., Storer L; Children's Brain Tumour Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK., Lourdusamy A; Children's Brain Tumour Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK., Mitra D; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK., Morgan PS; Children's Brain Tumour Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK., Dineen RA; Radiological Sciences, Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK; Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, UK., Avula S; Alder Hey Children's Hospital, Liverpool, UK., Pizer B; University of Liverpool, Liverpool, UK., Wilson M; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Birmingham Children's Hospital, Birmingham, UK., Davies N; RRPPS, University Hospital Birmingham, Birmingham, UK., Tennant D; Institute of Metabolism and Systems Research, University of Birmingham, UK., Bailey S; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK., Williamson D; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK., Arvanitis TN; Department of Electronic, Electrical and Systems Engineering, University of Birmingham, UK., Grundy RG; Children's Brain Tumour Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK., Clifford SC; Wolfson Childhood Cancer Research Centre, Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK. Electronic address: steve.clifford@ncl.ac.uk., Peet AC; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Birmingham Children's Hospital, Birmingham, UK. Electronic address: a.peet@bham.ac.uk.
Jazyk:	angličtina
Zdroj:	EBioMedicine [EBioMedicine] 2024 Feb; Vol. 100, pp. 104958. Date of Electronic Publication: 2024 Jan 06.
DOI:	10.1016/j.ebiom.2023.104958
Abstrakt:	Background: The malignant childhood brain tumour, medulloblastoma, is classified clinically into molecular groups which guide therapy. DNA-methylation profiling is the current classification 'gold-standard', typically delivered 3-4 weeks post-surgery. Pre-surgery non-invasive diagnostics thus offer significant potential to improve early diagnosis and clinical management. Here, we determine tumour metabolite profiles of the four medulloblastoma groups, assess their diagnostic utility using tumour tissue and potential for non-invasive diagnosis using in vivo magnetic resonance spectroscopy (MRS). Methods: Metabolite profiles were acquired by high-resolution magic-angle spinning NMR spectroscopy (MAS) from 86 medulloblastomas (from 59 male and 27 female patients), previously classified by DNA-methylation array (WNT (n = 9), SHH (n = 22), Group3 (n = 21), Group4 (n = 34)); RNA-seq data was available for sixty. Unsupervised class-discovery was performed and a support vector machine (SVM) constructed to assess diagnostic performance. The SVM classifier was adapted to use only metabolites (n = 10) routinely quantified from in vivo MRS data, and re-tested. Glutamate was assessed as a predictor of overall survival. Findings: Group-specific metabolite profiles were identified; tumours clustered with good concordance to their reference molecular group (93%). GABA was only detected in WNT, taurine was low in SHH and lipids were high in Group3. The tissue-based metabolite SVM classifier had a cross-validated accuracy of 89% (100% for WNT) and, adapted to use metabolites routinely quantified in vivo, gave a combined classification accuracy of 90% for SHH, Group3 and Group4. Glutamate predicted survival after incorporating known risk-factors (HR = 3.39, 95% CI 1.4-8.1, p = 0.025). Interpretation: Tissue metabolite profiles characterise medulloblastoma molecular groups. Their combination with machine learning can aid rapid diagnosis from tissue and potentially in vivo. Specific metabolites provide important information; GABA identifying WNT and glutamate conferring poor prognosis. Funding: Children with Cancer UK, Cancer Research UK, Children's Cancer North and a Newcastle University PhD studentship. Competing Interests: Declaration of interests HR holds stock options in Healx (AI drug discovery in rare diseases). PSM is unpaid co-chair of SIOP-Europe Brain Tumour Group Imaging Group. We declare no other competing interests. (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu