Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours
Abstract Paediatric brain tumors are becoming well characterized due to large genomic and epigenomic studies. Metabolomics is a powerful analytical approach aiding in the characterization of tumors. This study shows that common cerebellar tumors have metabolite profiles sufficiently different to bui...
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| Autores principales: | , , , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/a7d2970fe73a49548b25fcf0b28229c9 |
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| Sumario: | Abstract Paediatric brain tumors are becoming well characterized due to large genomic and epigenomic studies. Metabolomics is a powerful analytical approach aiding in the characterization of tumors. This study shows that common cerebellar tumors have metabolite profiles sufficiently different to build accurate, robust diagnostic classifiers, and that the metabolite profiles can be used to assess differences in metabolism between the tumors. Tissue metabolite profiles were obtained from cerebellar ependymoma (n = 18), medulloblastoma (n = 36), pilocytic astrocytoma (n = 24) and atypical teratoid/rhabdoid tumors (n = 5) samples using HR-MAS. Quantified metabolites accurately discriminated the tumors; classification accuracies were 94% for ependymoma and medulloblastoma and 92% for pilocytic astrocytoma. Using current intraoperative examination the diagnostic accuracy was 72% for ependymoma, 90% for medulloblastoma and 89% for pilocytic astrocytoma. Elevated myo-inositol was characteristic of ependymoma whilst high taurine, phosphocholine and glycine distinguished medulloblastoma. Glutamine, hypotaurine and N-acetylaspartate (NAA) were increased in pilocytic astrocytoma. High lipids, phosphocholine and glutathione were important for separating ATRTs from medulloblastomas. This study demonstrates the ability of metabolic profiling by HR-MAS on small biopsy tissue samples to characterize these tumors. Analysis of tissue metabolite profiles has advantages in terms of minimal tissue pre-processing, short data acquisition time giving the potential to be used as part of a rapid diagnostic work-up. |
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