Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours

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

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.

Developmental basis of SHH medulloblastoma heterogeneity

Many genes that drive normal cellular development also contribute to oncogenesis. Medulloblastoma (MB) tumors likely arise from neuronal progenitors in the cerebellum, and we hypothesized that the heterogeneity observed in MBs with sonic hedgehog (SHH) activation could be due to differences in developmental pathways. To investigate this question, here we perform single-nucleus RNA sequencing on highly differentiated SHH MBs with extensively nodular histology and observed malignant cells resembling each stage of canonical granule neuron development. Through innovative computational approaches, we connect these results to published datasets and find that some established molecular subtypes of SHH MB appear arrested at different developmental stages. Additionally, using multiplexed proteomic imaging and MALDI imaging mass spectrometry, we identify distinct histological and metabolic profiles for highly differentiated tumors. Our approaches are applicable to understanding the interplay between heterogeneity and differentiation in other cancers and can provide important insights for the design of targeted therapies.

miRNA-211 maintains metabolic homeostasis in medulloblastoma through its target gene long-chain acyl-CoA synthetase 4

The prognosis of childhood medulloblastoma (MB) is often poor, and it usually requires aggressive therapy that adversely affects quality of life. microRNA-211 (miR-211) was previously identified as an important regulator of cells that descend from neural cells. Since medulloblastomas primarily affect cells with similar ontogeny, we investigated the role and mechanism of miR-211 in MB. Here we showed that miR-211 expression was highly downregulated in cell lines, PDXs, and clinical samples of different MB subgroups (SHH, Group 3, and Group 4) compared to normal cerebellum. miR-211 gene was ectopically expressed in transgenic cells from MB subgroups, and they were subjected to molecular and phenotypic investigations. Monoclonal cells stably expressing miR-211 were injected into the mouse cerebellum. miR-211 forced expression acts as a tumor suppressor in MB both in vitro and in vivo, attenuating growth, promoting apoptosis, and inhibiting invasion. In support of emerging regulatory roles of metabolism in various forms of cancer, we identified the acyl-CoA synthetase long-chain family member (ACSL4) as a direct miR-211 target. Furthermore, lipid nanoparticle-coated, dendrimer-coated, and cerium oxide-coated miR-211 nanoparticles were applied to deliver synthetic miR-211 into MB cell lines and cellular responses were assayed. Synthesizing nanoparticle-miR-211 conjugates can suppress MB cell viability and invasion in vitro. Our findings reveal miR-211 as a tumor suppressor and a potential therapeutic agent in MB. This proof-of-concept paves the way for further pre-clinical and clinical development.

Surviving the hunger games: Metabolic reprogramming in medulloblastoma

Medulloblastoma is a highly malignant pediatric brain tumor characterized by its aggressive nature and limited treatment options. Metabolic changes have recently emerged as key factors in the development, progression, and response to therapy in various types of cancer. Cancer cells exhibit remarkable adaptability by modulating glucose, lipids, amino acids, and nucleotide metabolism to survive in nutrient- and oxygen-deprived environments. Although medulloblastoma has been extensively studied from a genomic perspective, leading to the identification of four subgroups and their respective subcategories, the investigation of its metabolic phenotype has remained relatively understudied. This review focus on the available literature, aiming to summarize the current knowledge about the main metabolic pathways that are deregulated in medulloblastoma tumors, while emphasizing the controversial aspects and the progress that is yet to be made. Furthermore, we underscored the insights gained so far regarding the impact of metabolism on the development of drug resistance in medulloblastoma and the therapeutic strategies employed to target specific metabolic pathways.

Global metabolomics study on the pathogenesis of pediatric medulloblastoma via UPLC- Q/E-MS/MS

Medulloblastoma is one of the most frequent malignant brain tumors in infancy and childhood. Early diagnosis and treatment are quite crucial for the prognosis. However, the pathogenesis of medulloblastoma is still not completely clarified. High-resolution mass spectrometry has enabled a comprehensive investigation on the mechanism of disease from the perspective of metabolism. Herein, we compared the difference of metabolic profiles of serum between medulloblastoma (n = 33) and healthy control (HC, n = 16) by using UPLC-Q/E-MS/MS. Principal component analysis and orthogonal projections to latent structures discriminant analysis (OPLS-DA) intuitively revealed the significantly distinct metabolic profiles between medulloblastoma and HC (p < 0.01 for permutation test on OPLS-DA model). Total of 25 significantly changed metabolites were identified. ROC analysis reported that six of them (Phosphatidic acid (8:0/15:0), 3'-Sialyllactose, Isocoproporphyrin, Acetylspermidine, Fructoseglycine and 3-Hydroxydodecanedioate) showed high specificity and precision to be potential diagnosis biomarkers (AUC > 0.98). Functional analysis discovered that there are four pathways notably perturbed for medulloblastoma. These pathways are related with the dysfunction of arachidonic acid metabolism, steroid hormone biosynthesis, and folate-related metabolism. The target intervention on these pathways may reduce the mortality of medulloblastoma.

Lipid Metabolic Reprogramming in Embryonal Neoplasms with MYCN Amplification

Tumor cells reprogram their metabolism, including glucose, glutamine, nucleotide, lipid, and amino acids to meet their enhanced energy demands, redox balance, and requirement of biosynthetic substrates for uncontrolled cell proliferation. Altered lipid metabolism in cancer provides lipids for rapid membrane biogenesis, generates the energy required for unrestricted cell proliferation, and some of the lipids act as signaling pathway mediators. In this review, we focus on the role of lipid metabolism in embryonal neoplasms with MYCN dysregulation. We specifically review lipid metabolic reactions in neuroblastoma, retinoblastoma, medulloblastoma, Wilms tumor, and rhabdomyosarcoma and the possibility of targeting lipid metabolism. Additionally, the regulation of lipid metabolism by the MYCN oncogene is discussed.

High-resolution magic angle spinning NMR for intact biological specimen analysis: Initial discovery, recent developments, and future directions

High-resolution magic angle spinning (HRMAS) NMR, an approach for intact biological material analysis discovered more than 25 years ago, has been advanced by many technical developments and applied to many biomedical uses. This article provides a history of its discovery, first by explaining the key scientific advances that paved the way for HRMAS NMR's invention, and then by turning to recent developments that have profited from applying and advancing the technique during the last 5 years. Developments aimed at directly impacting healthcare include HRMAS NMR metabolomics applications within studies of human disease states such as cancers, brain diseases, metabolic diseases, transplantation medicine, and adiposity. Here, the discussion describes recent HRMAS NMR metabolomics studies of breast cancer and prostate cancer, as well as of matching tissues with biofluids, multimodality studies, and mechanistic investigations, all conducted to better understand disease metabolic characteristics for diagnosis, opportune windows for treatment, and prognostication. In addition, HRMAS NMR metabolomics studies of plants, foods, and cell structures, along with longitudinal cell studies, are reviewed and discussed. Finally, inspired by the technique's history of discoveries and recent successes, future biomedical arenas that stand to benefit from HRMAS NMR-initiated scientific investigations are presented.

Exceptionally rare IDH1-mutant adult medulloblastoma with concurrent GNAS mutation revealed by in vivo magnetic resonance spectroscopy and deep sequencing

Medulloblastoma (MB) is the most common malignant brain tumor occurring in childhood and rarely found in adults. Based on transcriptome profile, MB are currently classified into four major molecular groups reflecting a considerable biological heterogeneity: WNT-activated, SHH-activated, group 3 and group 4. Recently, DNA methylation profiling allowed the identification of additional subgroups within the four major molecular groups associated with different clinic-pathological and molecular features. Isocitrate dehydrogenase-1 and 2 (IDH1 and IDH2) mutations have been described in several tumors, including gliomas, while in MB are rarely reported and not routinely investigated. By means of magnetic resonance spectroscopy (MRS), we unequivocally assessed the presence the oncometabolite D-2-hydroxyglutarate (2HG), a marker of IDH1 and IDH2 mutations, in a case of adult MB. Immunophenotypical work-up and methylation profiling assigned the diagnosis of MB, subclass SHH-A, and molecular testing revealed the presence of the non-canonical somatic IDH1(p.R132C) mutation and an additional GNAS mutation, also rarely described in MB. To the best of our knowledge, this is the first reported case of MB simultaneously harboring both mutations. Of note, tumor exhibited a heterogeneous phenotype with a tumor component displaying glial differentiation, with robust GFAP expression, and a component with conventional MB features and selective presence of GNAS mutation, suggesting co-existence of two different major tumor subclones. These findings drew attention to the need for a deeper genetic characterization of MB, in order to get insights into their biology and improve stratification and clinical management of the patients. Moreover, our results underlined the importance of performing MRS for the identification of IDH mutations in non-glial tumors. The use of throughput molecular profiling analysis and advanced medical imaging will certainly increase the frequency with which tumor entities with rare molecular alterations will be identified. Whether these findings have any specific therapeutic implications or prognostic relevance requires further investigations.

Identification of Therapeutic Targets for Medulloblastoma by Tissue-Specific Genome-Scale Metabolic Model

Medulloblastoma (MB), occurring in the cerebellum, is the most common childhood brain tumor. Because conventional methods decline life quality and endanger children with detrimental side effects, computer models are needed to imitate the characteristics of cancer cells and uncover effective therapeutic targets with minimum toxic effects on healthy cells. In this study, metabolic changes specific to MB were captured by the genome-scale metabolic brain model integrated with transcriptome data. To determine the roles of sphingolipid metabolism in proliferation and metastasis in the cancer cell, 79 reactions were incorporated into the MB model. The pathways employed by MB without a carbon source and the link between metastasis and the Warburg effect were examined in detail. To reveal therapeutic targets for MB, biomass-coupled reactions, the essential genes/gene products, and the antimetabolites, which might deplete the use of metabolites in cells by triggering competitive inhibition, were determined. As a result, interfering with the enzymes associated with fatty acid synthesis (FAs) and the mevalonate pathway in cholesterol synthesis, suppressing cardiolipin production, and tumor-supporting sphingolipid metabolites might be effective therapeutic approaches for MB. Moreover, decreasing the activity of succinate synthesis and GABA-catalyzing enzymes concurrently might be a promising strategy for metastatic MB.

LC–MS-Based Urine Metabolomics Analysis for the Diagnosis and Monitoring of Medulloblastoma

Medulloblastoma (MB) is the most common type of brain cancer in pediatric patients. Body fluid biomarkers will be helpful for clinical diagnosis and treatment. In this study, liquid chromatography–mass spectrometry (LC–MS)-based metabolomics was used to identify specific urine metabolites of MB in a cohort, including 118 healthy controls, 111 MB patients, 31 patients with malignant brain cancer, 51 patients with benign brain disease, 29 MB patients 1 week postsurgery and 80 MB patients 1 month postsurgery. The results showed an apparent separation for MB vs. healthy controls, MB vs. benign brain diseases, and MB vs. other malignant brain tumors, with AUCs values of 0.947/0.906, 0.900/0.873, and 0.842/0.885, respectively, in the discovery/validation group. Among all differentially identified metabolites, 4 metabolites (tetrahydrocortisone, cortolone, urothion and 20-oxo-leukotriene E4) were specific to MB. The analysis of these 4 metabolites in pre- and postoperative MB urine samples showed that their levels returned to a healthy state after the operation (especially after one month), showing the potential specificity of these metabolites for MB. Finally, the combination of two metabolites, tetrahydrocortisone and cortolone, showed diagnostic accuracy for distinguishing MB from non-MB, with an AUC value of 0.851. Our data showed that urine metabolomics might be used for MB diagnosis and monitoring.

Metabolite selection for machine learning in childhood brain tumour classification

MRS can provide high accuracy in the diagnosis of childhood brain tumours when combined with machine learning. A feature selection method such as principal component analysis is commonly used to reduce the dimensionality of metabolite profiles prior to classification. However, an alternative approach of identifying the optimal set of metabolites has not been fully evaluated, possibly due to the challenges of defining this for a multi-class problem. This study aims to investigate metabolite selection from in vivo MRS for childhood brain tumour classification. Multi-site 1.5 T and 3 T cohorts of patients with a brain tumour and histological diagnosis of ependymoma, medulloblastoma and pilocytic astrocytoma were retrospectively evaluated. Dimensionality reduction was undertaken by selecting metabolite concentrations through multi-class receiver operating characteristics and compared with principal component analysis. Classification accuracy was determined through leave-one-out and k-fold cross-validation. Metabolites identified as crucial in tumour classification include myo-inositol (P < 0.05, AUC = 0 . 81 ± 0 . 01 ), total lipids and macromolecules at 0.9 ppm (P < 0.05, AUC = 0 . 78 ± 0 . 01 ) and total creatine (P < 0.05, AUC = 0 . 77 ± 0 . 01 ) for the 1.5 T cohort, and glycine (P < 0.05, AUC = 0 . 79 ± 0 . 01 ), total N-acetylaspartate (P < 0.05, AUC = 0 . 79 ± 0 . 01 ) and total choline (P < 0.05, AUC = 0 . 75 ± 0 . 01 ) for the 3 T cohort. Compared with the principal components, the selected metabolites were able to provide significantly improved discrimination between the tumours through most classifiers (P < 0.05). The highest balanced classification accuracy determined through leave-one-out cross-validation was 85% for 1.5 T 1 H-MRS through support vector machine and 75% for 3 T 1 H-MRS through linear discriminant analysis after oversampling the minority. The study suggests that a group of crucial metabolites helps to achieve better discrimination between childhood brain tumours.

Risk factors for postresection shunting in children with suprasellar tumor: a retrospective analysis of 124 patients

OBJECTIVE

Hydrocephalus is one of the most significant comorbidities of pediatric suprasellar tumors. Up to 37.5-68.0% of patients were diagnosed with hydrocephalus at admission. However, after surgical resection of the tumor, 9.3-51.4% of the hydrocephalus will persist and require a ventriculoperitoneal shunt (VPS) surgery. The purpose of this study was to identify the risk factors associated with postresection shunting in children with suprasellar tumors.

METHODS

We conducted a retrospective analysis of children who underwent surgery for suprasellar tumors at our department from February 2011 to December 2020. We used univariate and multivariate analysis to screen the factors that might be correlated with postoperative shunt placement, taking into account patients' characteristics, tumor histology/size/calcification, the severity of preoperative hydrocephalus, the involvement of ventricles, external ventricular drainage (EVD) placement, postoperative intraventricular hematoma, the extent of resection, and other surgical details.

RESULTS

A total of 124 children who underwent surgery for suprasellar tumors were included in our study. Hydrocephalus was present in 55 patients (44.3%) at admission; 23 patients (18.5%) received VPS implantation after tumor removal. Univariate analysis showed that the involvement of ventricles (p = 0.002), moderate/severe preoperative hydrocephalus (p = 0.001), postoperative intraventricular hematoma (p = 0.005), and EVD implantation (p = 0.001) were significantly associated with postoperative VPS. Multivariate analysis confirmed that only ventricle involvement (p = 0.002; OR = 5.6; 95%CI 1.8-17.2) and intraventricular hematoma (p = 0.01; OR = 10.7; 95%CI 1.8-64.2) were independent risk factors for postresection shunting.

CONCLUSION

Ventricle involvement and intraventricular hematoma can be identified as independent predictors for postoperative shunting in pediatric suprasellar tumors.

Medulloblastoma cerebrospinal fluid reveals metabolites and lipids indicative of hypoxia and cancer-specific RNAs

Medulloblastoma (MB) is the most common malignant brain tumor in children. There remains an unmet need for diagnostics to sensitively detect the disease, particularly recurrences. Cerebrospinal fluid (CSF) provides a window into the central nervous system, and liquid biopsy of CSF could provide a relatively non-invasive means for disease diagnosis. There has yet to be an integrated analysis of the transcriptomic, metabolomic, and lipidomic changes occurring in the CSF of children with MB. CSF samples from patients with (n = 40) or without (n = 11; no cancer) MB were subjected to RNA-sequencing and high-resolution mass spectrometry to identify RNA, metabolite, and lipid profiles. Differentially expressed transcripts, metabolites, and lipids were identified and their biological significance assessed by pathway analysis. The DIABLO multivariate analysis package (R package mixOmics) was used to integrate the molecular changes characterizing the CSF of MB patients. Differentially expressed transcripts, metabolites, and lipids in CSF were discriminatory for the presence of MB but not the exact molecular subtype. One hundred and ten genes and ten circular RNAs were differentially expressed in MB CSF compared with normal, representing TGF-β signaling, TNF-α signaling via NF-kB, and adipogenesis pathways. Tricarboxylic acid cycle and other metabolites (malate, fumarate, succinate, α-ketoglutarate, hydroxypyruvate, N-acetyl-aspartate) and total triacylglycerols were significantly upregulated in MB CSF compared with normal CSF. Although separating MBs into subgroups using transcriptomic, metabolomic, and lipid signatures in CSF was challenging, we were able to identify a group of omics signatures that could separate cancer from normal CSF. Metabolic and lipidomic profiles both contained indicators of tumor hypoxia. Our approach provides several candidate signatures that deserve further validation, including the novel circular RNA circ_463, and insights into the impact of MB on the CSF microenvironment.

Magnetic Resonance Imaging in the Contemporary Management of Medulloblastoma: Current and Emerging Applications

Medulloblastoma, the most common malignant primary brain tumor in children, is now considered to comprise of four distinct molecular subgroups-wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4 medulloblastoma, each associated with distinct developmental origins, unique transcriptional profiles, diverse phenotypes, and variable clinical behavior. Due to its exquisite anatomic resolution, multiparametric nature, and ability to image the entire craniospinal axis, magnetic resonance imaging (MRI) is the preferred and recommended first-line imaging modality for suspected brain tumors including medulloblastoma. Preoperative MRI can reliably differentiate medulloblastoma from other common childhood posterior fossa masses such as ependymoma, pilocytic astrocytoma, and brainstem glioma. On T1-weighted images, medulloblastoma is generally iso- to hypointense, while on T2-weighted images, the densely packed cellular component of the tumor is significantly hypointense and displays restricted diffusion on diffusion-weighted imaging. Following intravenous gadolinium, medulloblastoma shows significant but variable and heterogeneous contrast enhancement. Given the propensity of neuraxial spread in medulloblastoma, sagittal fat-suppressed T1-postcontrast spinal MRI is recommended to rule out leptomeningeal metastases for accurate staging. Following neurosurgical excision, postoperative MRI done within 24-48 h confirms the extent of resection, accurately quantifying residual tumor burden imperative for risk assignment. Post-treatment MRI is needed to assess response and effectiveness of adjuvant radiotherapy and systemic chemotherapy. After completion of planned therapy, surveillance MRI is recommended periodically on follow-up for early detection of recurrence for timely institution of salvage therapy, as well as for monitoring treatment-related late complications. Recent studies suggest that preoperative MRI can reliably identify SHH and Group 4 medulloblastoma but has suboptimal predictive accuracy for WNT and Group 3 tumors. In this review, we focus on the role of MRI in the diagnosis, staging, and quantifying residual disease; post-treatment response assessment; and periodic surveillance, and provide a brief summary on radiogenomics in the contemporary management of medulloblastoma.

Sequential Orbitrap Secondary Ion Mass Spectrometry and Liquid Extraction Surface Analysis-Tandem Mass Spectrometry-Based Metabolomics for Prediction of Brain Tumor Relapse from Sample-Limited Primary Tissue Archives

We present here a novel surface mass spectrometry strategy to perform untargeted metabolite profiling of formalin-fixed paraffin-embedded pediatric ependymoma archives. Sequential Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) and liquid extraction surface analysis-tandem mass spectrometry (LESA-MS/MS) permitted the detection of 887 metabolites (163 chemical classes) from pediatric ependymoma tumor tissue microarrays (diameter: <1 mm; thickness: 4 μm). From these 163 classes, 60 classes were detected with both techniques, whilst LESA-MS/MS and 3D OrbiSIMS individually allowed the detection of another 83 and 20 unique metabolite classes, respectively. Through data fusion and multivariate analysis, we were able to identify key metabolites and corresponding pathways predictive of tumor relapse, which were retrospectively confirmed by gene expression analysis with publicly available data. Altogether, this sequential mass spectrometry strategy has shown to be a versatile tool to perform high-throughput metabolite profiling on sample-limited tissue archives.

Integrated Metabolomics and Transcriptomics Using an Optimised Dual Extraction Process to Study Human Brain Cancer Cells and Tissues

The integration of untargeted metabolomics and transcriptomics from the same population of cells or tissue enhances the confidence in the identified metabolic pathways and understanding of the enzyme–metabolite relationship. Here, we optimised a simultaneous extraction method of metabolites/lipids and RNA from ependymoma cells (BXD-1425). Relative to established RNA (mirVana kit) or metabolite (sequential solvent addition and shaking) single extraction methods, four dual-extraction techniques were evaluated and compared (methanol:water:chloroform ratios): cryomill/mirVana (1:1:2); cryomill-wash/Econospin (5:1:2); rotation/phenol-chloroform (9:10:1); Sequential/mirVana (1:1:3). All methods extracted the same metabolites, yet rotation/phenol-chloroform did not extract lipids. Cryomill/mirVana and sequential/mirVana recovered the highest amounts of RNA, at 70 and 68% of that recovered with mirVana kit alone. sequential/mirVana, involving RNA extraction from the interphase of our established sequential solvent addition and shaking metabolomics-lipidomics extraction method, was the most efficient approach overall. Sequential/mirVana was applied to study a) the biological effect caused by acute serum starvation in BXD-1425 cells and b) primary ependymoma tumour tissue. We found (a) 64 differentially abundant metabolites and 28 differentially expressed metabolic genes, discovering four gene-metabolite interactions, and (b) all metabolites and 62% lipids were above the limit of detection, and RNA yield was sufficient for transcriptomics, in just 10 mg of tissue.

Insights into the Chemical Biology of Childhood Embryonal Solid Tumors by NMR-Based Metabolomics

Most childhood cancers occur as isolated cases and show very different biological behavior when compared with cancers in adults. There are some solid tumors that occur almost exclusively in children among which stand out the embryonal solid tumors. These cancers main types are neuroblastoma, nephroblastoma (Wilms tumors), retinoblastoma and hepatoblastomas and tumors of the central nervous system (CNS). Embryonal solid tumors represent a heterogeneous group of cancers supposedly derived from undifferentiated cells, with histological features that resemble tissues of origin during embryogenesis. This key observation suggests that tumorigenesis might begin during early fetal or child life due to the errors in growth or pathways differentiation. There are not many literature data on genomic, transcriptomic, epigenetic, proteomic, or metabolomic differences in these types of cancers when compared to the omics- used in adult cancer research. Still, metabolomics by nuclear magnetic resonance (NMR) in childhood embryonal solid tumors research can contribute greatly to understand better metabolic pathways alterations and biology of the embryonal solid tumors and potential to be used in clinical applications. Different types of samples, such as tissues, cells, biofluids, mostly blood plasma and serum, can be analyzed by NMR to detect and identify cancer metabolic signatures and validated biomarkers using enlarged group of samples. The literature search for biomarkers points to around 20-30 compounds that could be associated with pediatric cancer as well as metastasis.