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Purpose: Medulloblastoma is the most common malignant brain tumor occurring in childhood and is a significant cause of morbidity and mortality in pediatric oncology. More intense treatment strategies are recommended for patients displaying high-risk factors; however, considerable variation in outcome remains, indicating a need for improved predictive markers. In this study, 1H magnetic resonance spectroscopy (MRS) was used to investigate noninvasive molecular biomarkers of survival in medulloblastoma.Experimental Design: MRS was performed on a series of 35 biopsy-confirmed medulloblastoma cases. One case was excluded because of poor quality MRS. The prognostic value of MRS detectable biomarkers was investigated using Cox regression, retrospectively (N = 15). A subsequent validation analysis (N = 19) was also performed to reduce the chance of type I errors. Where available, high-resolution ex vivo MRS of biopsy tissue was used to confirm biomarker assignments.Results: The retrospective analysis revealed that creatine, glutamate, and glycine were markers of survival (P < 0.01). The validation analysis showed that glutamate was a robust marker, with a hazard ration (HR) of 8.0 for the full dataset (P = 0.0003, N = 34). A good correlation between in vivo and ex vivo MRS glutamate/total-choline was found (P = 0.001), validating the in vivo assignment. Ex vivo glutamate/total-choline was also associated with survival (P < 0.01).Conclusion: The identification of glutamate as a predictive biomarker of survival in pediatric medulloblastoma provides a clinically viable risk factor and highlights the importance of more detailed studies into the metabolism of this disease. Noninvasive biomarker detection using MRS may offer improved disease monitoring and potential for widespread use following multicenter validation. Clin Cancer Res; 20(17); 4532–9. ©2014 AACR.

Supplementary Methods (Text 1). A description of the treatment protocols used during the study period. Supplementary Figure 1. Example medulloblastoma fits where the lowest smooth black line is the baseline; the middle black line represents the acquired spectrum following pre-processing; the red line shows the spectral fit and the top black line shows the residual between the fit and acquired spectrum. A) shows a distorted baseline leading to qc failure whereas B) is an example of an ideal smooth baseline.

Brain tumours are the most common cause of cancer death in children. Molecular studies have greatly improved our understanding of these tumours but tumour metabolism is underexplored. Metabolites measured in vivo have been reported as prognostic biomarkers of these tumours but analysis of surgically resected tumour tissue allows a more extensive set of metabolites to be measured aiding biomarker discovery and providing validation of in vivo findings. In this study, metabolites were quantified across a range of paediatric brain tumours using 1H-High-Resolution Magic Angle Spinning nuclear magnetic resonance spectroscopy (HR-MAS) and their prognostic potential investigated. HR-MAS was performed on pre-treatment frozen tumour tissue from a single centre. Univariate and multivariate Cox regression was used to examine the ability of metabolites to predict survival. The models were cross validated using C-indices and further validated by splitting the cohort into two. Higher concentrations of glutamine were predictive of a longer overall survival, whilst higher concentrations of lipids were predictive of a shorter overall survival. These metabolites were predictive independent of diagnosis, as demonstrated in multivariate Cox regression models. Whilst accurate quantification of metabolites such as glutamine in vivo is challenging, metabolites show promise as prognostic markers due to development of optimised detection methods and increasing use of 3 T clinical scanners.

Background 1H-magnetic resonance spectroscopy (MRS) facilitates noninvasive diagnosis of pediatric brain tumors by providing metabolite profiles. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. We aimed to evaluate diagnostic accuracy of MRS for childhood brain tumors and determine added clinical value compared with conventional MRI. Methods Children presenting to a tertiary pediatric center with brain lesions from December 2015 through 2017 were included. MRI and single-voxel MRS were acquired on 52 tumors and sequentially interpreted by 3 radiologists, blinded to histopathology. Proportions of correct diagnoses and interrater agreement at each stage were compared. Cases were reviewed to determine added value of qualitative radiological review of MRS through increased certainty of correct diagnosis, reduced number of differentials, or diagnosis following spectroscopist evaluation. Final diagnosis was agreed by the tumor board at study end. Results Radiologists’ principal MRI diagnosis was correct in 69%, increasing to 77% with MRS. MRI + MRS resulted in significantly more additional correct diagnoses than MRI alone (P = .035). There was a significant increase in interrater agreement when correct with MRS (P = .046). Added value following radiologist interpretation of MRS occurred in 73% of cases, increasing to 83% with additional spectroscopist review. First histopathological diagnosis was available a median of 9.5 days following imaging, with 25% of all patients managed without conclusive histopathology. Conclusions MRS can improve the accuracy of noninvasive diagnosis of pediatric brain tumors and add value in the diagnostic pathway. Incorporation into practice has the potential to facilitate early diagnosis, guide treatment planning, and improve patient care.

The rare pediatric embryonal tumors retinoblastoma, medulloblastoma and neuroblastoma derive from neuroectodermal tissue and share similar histopathological features despite different anatomical locations and diverse clinical outcomes. As metabolism can reflect genetic and histological features, we investigated whether the metabolism of embryonal tumors reflects their similar histology, shared developmental and neural origins, or tumor location. We undertook metabolic profiling on 50 retinoblastoma, 39 medulloblastoma and 70 neuroblastoma using high resolution magic angle spinning magnetic resonance spectroscopy (1H-MRS). Mean metabolite concentrations identified several metabolites that were significantly different between the tumor groups including taurine, hypotaurine, glutamate, glutamine, GABA, phosphocholine, N-acetylaspartate, creatine, glycine and myoinositol, p < 0.0017. Unsupervised multivariate analysis found that each tumor group clustered separately, with a unique metabolic profile, influenced by their underlying clinical diversity. Taurine was notably high in all tumors consistent with prior evidence from embryonal tumors. Retinoblastoma and medulloblastoma were more metabolically similar, sharing features associated with the central nervous system (CNS). Neuroblastoma had features consistent with neural tissue, but also contained significantly higher myoinositol and altered glutamate-glutamine ratio, suggestive of differences in the underlying metabolism of embryonal tumors located outside of the CNS. Despite the histological similarities and shared neural metabolic features, we show that individual neuroectodermal derived embryonal tumors can be distinguished by tissue metabolic profile. Pathway analysis suggests the alanine-aspartate-glutamate and taurine-hypotaurine metabolic pathways may be the most pertinent pathways to investigate for novel therapeutic strategies. This work strengthens our understanding of the biology and metabolic pathways underlying neuroectodermal derived embryonal tumors of childhood.

Background Magnetic resonance spectroscopy (MRS) aids noninvasive diagnosis of pediatric brain tumors, but use in clinical practice is not well documented. We aimed to review clinical use of MRS, establish added value in noninvasive diagnosis, and investigate potential impact on patient care. Methods Sixty-nine children with lesions imaged using MRS and reviewed by the tumor board from 2014 to 2016 met inclusion criteria. Contemporaneous MRI diagnosis, spectroscopy analysis, histopathology, and clinical information were reviewed. Final diagnosis was agreed on by the tumor board at study end. Results Five cases were excluded for lack of documented MRI diagnosis. The principal MRI diagnosis by pediatric radiologists was correct in 59%, increasing to 73% with addition of MRS. Of the 73%, 19.1% (95% CI, 9.1%-33.3%) were incorrectly diagnosed with MRI alone. MRS led to a significant improvement in correct diagnosis over all tumor types (P = .012). Of diagnoses correctly made with MRI, confidence increased by 37% when adding MRS, with no patients incorrectly re-diagnosed. Indolent lesions were diagnosed noninvasively in 85% of cases, with MRS a major contributor to 91% of these diagnoses. Of all patients, 39% were managed without histopathological diagnosis. MRS contributed to diagnosis in 68% of this group, modifying it in 12%. MRS influenced management in 33% of cases, mainly through avoiding and guiding biopsy and aiding tumor characterization. Conclusion MRS can improve accuracy and confidence in noninvasive diagnosis of pediatric brain lesions in clinical practice. There is potential to improve outcomes through avoiding biopsy of indolent lesions, aiding tumor characterization, and facilitating earlier family discussions and treatment planning.

BACKGROUND: (1)H-magnetic resonance spectroscopy (MRS) facilitates noninvasive diagnosis of pediatric brain tumors by providing metabolite profiles. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. We aimed to evaluate diagnostic accuracy of MRS for childhood brain tumors and determine added clinical value compared with conventional MRI. METHODS: Children presenting to a tertiary pediatric center with brain lesions from December 2015 through 2017 were included. MRI and single-voxel MRS were acquired on 52 tumors and sequentially interpreted by 3 radiologists, blinded to histopathology. Proportions of correct diagnoses and interrater agreement at each stage were compared. Cases were reviewed to determine added value of qualitative radiological review of MRS through increased certainty of correct diagnosis, reduced number of differentials, or diagnosis following spectroscopist evaluation. Final diagnosis was agreed by the tumor board at study end. RESULTS: Radiologists’ principal MRI diagnosis was correct in 69%, increasing to 77% with MRS. MRI + MRS resulted in significantly more additional correct diagnoses than MRI alone (P = .035). There was a significant increase in interrater agreement when correct with MRS (P = .046). Added value following radiologist interpretation of MRS occurred in 73% of cases, increasing to 83% with additional spectroscopist review. First histopathological diagnosis was available a median of 9.5 days following imaging, with 25% of all patients managed without conclusive histopathology. CONCLUSIONS: MRS can improve the accuracy of noninvasive diagnosis of pediatric brain tumors and add value in the diagnostic pathway. Incorporation into practice has the potential to facilitate early diagnosis, guide treatment planning, and improve patient care.

Metabolic profiling by Magnetic Resonance Spectroscopy has shown the three most common paediatric cerebellar tumours are metabolically distinct; however, these techniques are limited by their sensitivity. Mass spectrometry is more sensitive and able to detect many more metabolites. In this study, metabolic phenotyping was performed to investigate the water-soluble metabolome and the lipidome of the three most common paediatric cerebellar tumours with the aim of informing a detailed metabolic pathway analysis. A discovery based experiment was performed on 60 surgically resected snap frozen pilocytic astrocytomas, ependymomas and medulloblastomas using UPLC-MS assays to detect water soluble and lipid metabolites. Principal component analysis demonstrates separation of the tumours based on the relative concentration of thousands of detected metabolites. The relative concentrations of glucose and glycolytic intermediates varied between the tumour types, as did metabolites involved in purine and pyrimidine metabolism. Key metabolites within the taurine metabolism pathway were found to be higher in medulloblastoma. Alterations were observed in lipid metabolism, with a wide range of relative concentration differences in di- and triacylglycerides, sphingolipids, ceramides, cardiolipins and glycerophospholipids. This study has shown that these tumours are metabolically distinct and offer the opportunities for stratified diagnosis and treatment. Some of the observed changes in relative concentration between the tumours reflect findings from spectroscopic studies, particularly with regards to taurine which is known to be higher in medulloblastoma. The ability of mass spectrometry to identify and measure lipid species and low concentration metabolites from tissue could allow targetable metabolic differences to be characterised and exploited.

MB-84. IDENTIFICATION OF MEDULLOBLASTOMA MOLECULAR SUBGROUPS USING METABOLITE PROFILES Sarah Kohe1,2, Simrandip K. Gill1,2, Debbie Hicks3, Ed C. Schwalbe3, Stephen Crosier3, Lisa Storer4, Anbarasu Lourdusamy4, Christopher D. Bennett1,2, Martin Wilson1,2, Simon Bailey3, Daniel Williamson3, Richard G. Grundy4, Steven C. Clifford3, and Andrew C. Peet1,2; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Birmingham Childrens Hospital, Birmingham, UK; Northern Institute for Cancer Research, Newcastle University, Newcastle, UK; Childrens Brain Tumour Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, UK Identification of the four consensus molecular subgroups of medulloblastoma is becoming increasingly important for determining risk-based treatment strategies. Metabolite profiles can distinguish between brain tumour types, therefore we investigated whether profiling can discriminate the molecular subgroups within medulloblastoma. Metabolite concentrations were determined using high resolution magnetic resonance spectroscopy (MRS) on biopsied tissue from 29 medulloblastomas. Molecular subgroup was determined by Illumina 450K DNA methylation array and consensus clustering. Mean metabolite concentrations showed taurine, characteristic of PNETs, was prominent in all subgroups. Lipid was significantly elevated in high-risk Group 3 tumours (n 1⁄4 5, p , 0.0002) consistent with it being a marker of poor prognosis. The ratio of glutamate to glutamine was significantly higher in SHH (n 1⁄4 6), and lower in Group 4 (n 1⁄4 15), p , 0.03. Decreased creatine was detected in SHH tumours, p , 0.002. Only low risk WNT tumours (n 1⁄4 3) contained GABA suggesting it may be a subgroup specific marker, supported by links between GABA and WNT signalling in the developing cerebellum. Glycine, typically associated with poor prognosis, was also significantly lower in WNT tumours (p , 0.003). Multivariate PLS discriminant analysis found metabolite profiles could discriminate subgroup with a classification accuracy of 85% in this pilot set. Lipid, glutamate, glutamine, taurine, hypotaurine, GABA, myoinositol, glycine and creatine were most discriminatory. Matched 1.5T in-vivo MRS concentrations (n 1⁄4 19) found significant correlations with ex-vivo values for taurine, glutamate, glutamine, glycine, creatine, and myoinositol (Pearson’s r range:0.61-0.67, p , 0.05). Identified profiles will inform non-invasive MRS methods for pre-operative subgroup identification, with potential to guide extent of surgical resection and enhanced disease monitoring. Neuro-Oncology 18:iii97–iii122, 2016. doi:10.1093/neuonc/now076.80 #The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Molecular subgroup is now influencing risk stratification and disease management in medulloblastoma. Tissue metabolite profiles have shown promise in identifying the four consensus subgroups. A smaller number of metabolites can be measured non-invasively in patients using magnetic resonance spectroscopy (MRS). We investigated if a classifier constructed from tissue metabolites could be applied to in-vivo metabolite profiles to accurately predict subgroup non-invasively. Machine learning was used to construct a classifier with tissue concentrations from 10 metabolites reliably detected in-vivo. Retrospectively acquired diagnostic in-vivo MRS was available for 37 cases from four treatment centres. Although we identified WNT tumours by the presence of GABA with 100% accuracy in tissue, GABA was not reliability quantified in this in-vivo dataset. Therefore the classifier was developed using tissue profiles of known molecular subgroup (determined using DNA methylation array) from group 3(n=20), group 4(n=34) and SHH(n=23). The cross-validated accuracy of the tissue classifier was 86%. When applied to in-vivo metabolite profiles, subgroup was predicted non-invasively with an overall accuracy of 76%. Group 3 had the highest proportion of incorrectly classified cases (4/11), followed by SHH (2/10), and group 4 (3/16), largely due to differences in measuring lipids, glutamate, glutamine and hypotaurine in-vivo. We have established the feasibility of non-invasive metabolite profiling to identify medulloblastoma subgroups. With the ongoing optimization of MRS to target specific metabolites including GABA, we can further improve accuracy. Rapid, non-invasive preoperative diagnosis of subgroup will offer opportunities to stratify early therapeutic intervention especially surgery, avoiding long-term sequalae and improving quality of survival.

Pilocytic astrocytomas are the most common brain tumours arising in children, accounting for ~18% of primary brain tumours. 42% are cerebellar in origin and, whilst they have an excellent 10-year overall survival rate of >90%, progression-free survival for these tumours is variable. Identifying tumours more likely to progress will help determine those requiring more aggressive treatment. Metabolite profiles were obtained from 23 cerebellar pilocytic astrocytomas using High Resolution Magic Angle Spinning NMR (HR-MAS). Cox regression tested the ability of individual metabolites to predict progression-free survival. Progression was defined as the time point at which the local multi-disciplinary team decided to further treat the tumour. Low normalised tissue glutamine concentration was found to be associated with a worse progression-free survival (HR=4.58; P

Purpose: Medulloblastoma is the most common malignant brain tumor occurring in childhood and is a significant cause of morbidity and mortality in pediatric oncology. More intense treatment strategies are recommended for patients displaying high-risk factors; however, considerable variation in outcome remains, indicating a need for improved predictive markers. In this study, 1H magnetic resonance spectroscopy (MRS) was used to investigate noninvasive molecular biomarkers of survival in medulloblastoma. Experimental Design: MRS was performed on a series of 35 biopsy-confirmed medulloblastoma cases. One case was excluded because of poor quality MRS. The prognostic value of MRS detectable biomarkers was investigated using Cox regression, retrospectively (N = 15). A subsequent validation analysis (N = 19) was also performed to reduce the chance of type I errors. Where available, high-resolution ex vivo MRS of biopsy tissue was used to confirm biomarker assignments. Results: The retrospective analysis revealed that creatine, glutamate, and glycine were markers of survival (P < 0.01). The validation analysis showed that glutamate was a robust marker, with a hazard ration (HR) of 8.0 for the full dataset (P = 0.0003, N = 34). A good correlation between in vivo and ex vivo MRS glutamate/total-choline was found (P = 0.001), validating the in vivo assignment. Ex vivo glutamate/total-choline was also associated with survival (P < 0.01). Conclusion: The identification of glutamate as a predictive biomarker of survival in pediatric medulloblastoma provides a clinically viable risk factor and highlights the importance of more detailed studies into the metabolism of this disease. Noninvasive biomarker detection using MRS may offer improved disease monitoring and potential for widespread use following multicenter validation. Clin Cancer Res; 20(17); 4532–9. ©2014 AACR.

Background: Malignant brain tumors in children generally have a very poor prognosis when they relapse and improvements are required in their management. It can be difficult to accurately diagnose abnormalities detected during tumor surveillance, and new techniques are required to aid this process. This study investigates how metabolite profiles measured noninvasively by 1H magnetic resonance spectroscopy (MRS) at relapse reflect those at diagnosis and may be used in this monitoring process. Methods: Single-voxel MRS (1.5 T, point-resolved spectroscopy, echo time 30 ms, repetition time 1500 ms was performed on 19 children with grades II–IV brain tumors during routine MRI scans prior to treatment for a suspected brain tumor and at suspected first relapse. MRS was analyzed using TARQUIN software to provide metabolite concentrations. Paired Student's t-tests were performed between metabolite profiles at diagnosis and at first relapse. Results: There was no significant difference (P > .05) in the level of any metabolite, lipid, or macromolecule from tumors prior to treatment and at first relapse. This was true for the whole group (n = 19), those with a local relapse (n = 12), and those with a distant relapse (n = 7). Lipids at 1.3 ppm were close to significance when comparing the level at diagnosis with that at distant first relapse (P = .07, 6.5 vs 12.9). In 5 cases the MRS indicative of tumor preceded a formal diagnosis of relapse. Conclusions: Tumor metabolite profiles, measured by MRS, do not change greatly from diagnosis to first relapse, and this can aid the confirmation of the presence of tumor.

Magnetic resonance spectroscopy can provide noninvasive metabolite profiles of childhood brain tumors and these are highly characteristic for tumor type. This information is increasingly being used to provide a noninvasive diagnostic aid but since tumor pathologies differ in children to adults, child specific classifiers are required. Despite the strong dependence of the MRS metabolite profile on tumor type, some metabolites are also biomarkers of prognosis both within and across tumor groups. Some evidence is also emerging that MRS can also provide biomarkers of treatment response where prior to changes on conventional MRI.