Determination of a Tumor-Promoting Microenvironment in Recurrent Medulloblastoma: A Multi-Omics Study of Cerebrospinal Fluid

REST-dependent downregulation of von Hippel-Lindau tumor suppressor promotes autophagy in SHH-medulloblastoma

The RE1 silencing transcription factor (REST) is a driver of sonic hedgehog (SHH) medulloblastoma genesis. Our previous studies showed that REST enhances cell proliferation, metastasis and vascular growth and blocks neuronal differentiation to drive progression of SHH medulloblastoma tumors. Here, we demonstrate that REST promotes autophagy, a pathway that is found to be significantly enriched in human medulloblastoma tumors relative to normal cerebella. In SHH medulloblastoma tumor xenografts, REST elevation is strongly correlated with increased expression of the hypoxia-inducible factor 1-alpha (HIF1α)-a positive regulator of autophagy, and with reduced expression of the von Hippel-Lindau (VHL) tumor suppressor protein - a component of an E3 ligase complex that ubiquitinates HIF1α. Human SHH-medulloblastoma tumors with higher REST expression exhibit nuclear localization of HIF1α, in contrast to its cytoplasmic localization in low-REST tumors. In vitro, REST knockdown promotes an increase in VHL levels and a decrease in cytoplasmic HIF1α protein levels, and autophagy flux. In contrast, REST elevation causes a decline in VHL levels, as well as its interaction with HIF1α, resulting in a reduction in HIF1α ubiquitination and an increase in autophagy flux. These data suggest that REST elevation promotes autophagy in SHH medulloblastoma cells by modulating HIF1α ubiquitination and stability in a VHL-dependent manner. Thus, our study is one of the first to connect VHL to REST-dependent control of autophagy in a subset of medulloblastomas.

Cellular metabolism regulates the differentiation and function of T-cell subsets

T cells are an important component of adaptive immunity and protect the host from infectious diseases and cancers. However, uncontrolled T cell immunity may cause autoimmune disorders. In both situations, antigen-specific T cells undergo clonal expansion upon the engagement and activation of antigens. Cellular metabolism is reprogrammed to meet the increase in bioenergetic and biosynthetic demands associated with effector T cell expansion. Metabolites not only serve as building blocks or energy sources to fuel cell growth and expansion but also regulate a broad spectrum of cellular signals that instruct the differentiation of multiple T cell subsets. The realm of immunometabolism research is undergoing swift advancements. Encapsulating all the recent progress within this concise review in not possible. Instead, our objective is to provide a succinct introduction to this swiftly progressing research, concentrating on the metabolic intricacies of three pivotal nutrient classes-lipids, glucose, and amino acids-in T cells. We shed light on recent investigations elucidating the roles of these three groups of metabolites in mediating the metabolic and immune functions of T cells. Moreover, we delve into the prospect of "editing" metabolic pathways within T cells using pharmacological or genetic approaches, with the aim of synergizing this approach with existing immunotherapies and enhancing the efficacy of antitumor and antiinfection immune responses.

Influence of maternal folate depletion on Art3 DNA methylation in the murine adult brain; potential consequences for brain and neurocognitive health

The developmental origins of health and disease hypothesis suggest early-life environment impacts health outcomes throughout the life course. In particular, epigenetic marks, including DNA methylation, are thought to be key mechanisms through which environmental exposures programme later-life health. Adequate maternal folate status before and during pregnancy is essential in the protection against neural tube defects, but data are emerging that suggest early-life folate exposures may also influence neurocognitive outcomes in childhood and, potentially, thereafter. Since folate is key to the supply of methyl donors for DNA methylation, we hypothesize that DNA methylation may be a mediating mechanism through which maternal folate influences neurocognitive outcomes. Using bisulphite sequencing, we measured DNA methylation of five genes (Art3, Rsp16, Tspo, Wnt16, and Pcdhb6) in the brain tissue of adult offspring of dams who were depleted of folate (n = 5, 0.4 mg folic acid/kg diet) during pregnancy (~19-21 days) and lactation (mean 22 days) compared with controls (n = 6, 2 mg folic acid/kg diet). Genes were selected as methylation of their promoters had previously been found to be altered by maternal folate intake in mice and humans across the life course, and because they have potential associations with neurocognitive outcomes. Maternal folate depletion was significantly associated with Art3 gene hypomethylation in subcortical brain tissue of adult mice at 28 weeks of age (mean decrease 6.2%, P = .03). For the other genes, no statistically significant differences were found between folate depleted and control groups. Given its association with neurocognitive outcomes, we suggest Art3 warrants further study in the context of lifecourse brain health. We have uncovered a potential biomarker that, once validated in accessible biospecimens and human context, may be useful to track the impact of early-life folate exposure on later-life neurocognitive health, and potentially be used to develop and monitor the effects of interventions.

Serine enrichment in tumors promotes regulatory T cell accumulation through sphinganine-mediated regulation of c-Fos

CD4+ regulatory T (Treg) cells accumulate in the tumor microenvironment (TME) and suppress the immune system. Whether and how metabolite availability in the TME influences Treg cell differentiation is not understood. Here, we measured 630 metabolites in the TME and found that serine and palmitic acid, substrates required for the synthesis of sphingolipids, were enriched. A serine-free diet or a deficiency in Sptlc2, the rate-limiting enzyme catalyzing sphingolipid synthesis, suppressed Treg cell accumulation and inhibited tumor growth. Sphinganine, an intermediate metabolite in sphingolipid synthesis, physically interacted with the transcription factor c-Fos. Sphinganine c-Fos interactions enhanced the genome-wide recruitment of c-Fos to regions near the transcription start sites of target genes including Pdcd1 (encoding PD-1), which promoted Pdcd1 transcription and increased inducible Treg cell differentiation in vitro in a PD-1-dependent manner. Thus, Sptlc2-mediated sphingolipid synthesis translates the extracellular information of metabolite availability into nuclear signals for Treg cell differentiation and limits antitumor immunity.

Mass spectrometry-based proteomics of cerebrospinal fluid in pediatric central nervous system malignancies: a systematic review with meta-analysis of individual patient data

BACKGROUND

The cerebrospinal fluid (CSF) proteome could offer important insights into central nervous system (CNS) malignancies. To advance proteomic research in pediatric CNS cancer, the current study aims to (1) evaluate past mass spectrometry-based workflows and (2) synthesize previous CSF proteomic data, focusing on both qualitative summaries and quantitative re-analysis. MAIN: In our analysis of 11 studies investigating the CSF proteome in pediatric patients with acute lymphoblastic leukemia (ALL) or primary brain tumors, we observed significant methodological variability. This variability negatively affects comparative analysis of the included studies, as per GRADE criteria for quality of evidence. The qualitative summaries covered 161 patients and 134 non-tumor controls, while the application of validation cohort varied among the studies. The quantitative re-analysis comprised 15 B-ALL vs 6 "healthy" controls and 15 medulloblastoma patients vs 22 non-tumor controls. Certain CSF proteins were identified as potential indicators of specific malignancies or stages of neurotoxicity during chemotherapy, yet definitive conclusions were impeded by inconsistent data. There were no proteins with statistically significant differences when comparing cases versus controls that were corroborated across studies where quantitative reanalysis was feasible. From a gene ontology enrichment, we observed that age disparities between unmatched case and controls may mislead to protein correlations more indicative of age-related CNS developmental stages rather than neuro-oncological disease. Despite efforts to batch correct (HarmonizR) and impute missing values, merging of dataset proved unfeasible and thereby limited meaningful data integration across different studies.

CONCLUSION

Infrequent publications on rare pediatric cancer entities, which often involve small sample sizes, are inherently prone to result in heterogeneous studies-particularly when conducted within a rapidly evolving field like proteomics. As a result, obtaining clear evidence, such as CSF proteome biomarkers for CNS dissemination or early-stage neurotoxicity, is currently impractical. Our general recommendations comprise the need for standardized methodologies, collaborative efforts, and improved data sharing in pediatric CNS malignancy research. We specifically emphasize the possible importance of considering natural age-related variations in CSF due to different CNS development stages when matching cases and controls in future studies.

Liquid Biopsies for Monitoring Medulloblastoma: Circulating Tumor DNA as a Biomarker for Disease Progression and Treatment Response

Pediatric brain tumors, including medulloblastoma (MB), represent a significant challenge in clinical oncology. Early diagnosis, accurate monitoring of therapeutic response, and the detection of minimal residual disease (MRD) are crucial for improving outcomes in these patients. This review aims to explore recent advancements in liquid biopsy techniques for monitoring pediatric brain tumors, with a specific focus on medulloblastoma. The primary research question is how liquid biopsy techniques can be effectively utilized for these purposes. Liquid biopsies, particularly the analysis of circulating tumor DNA (ctDNA) in cerebrospinal fluid (CSF), are investigated as promising noninvasive tools. This comprehensive review examines the components of liquid biopsies, including ctDNA, cell-free DNA (cfDNA), and microRNA (miRNA). Their applications in diagnosis, prognosis, and MRD assessment are critically assessed. The review also discusses the role of liquid biopsies in categorizing medulloblastoma subgroups, risk stratification, and the identification of therapeutic targets. Liquid biopsies have shown promising applications in the pediatric brain tumor field, particularly in medulloblastoma. They offer noninvasive means of diagnosis, monitoring treatment response, and detecting MRD. These biopsies have played a pivotal role in subgroup classification and risk stratification of medulloblastoma patients, aiding in the identification of therapeutic targets. However, challenges related to sensitivity and specificity are noted. In conclusion, this review highlights the growing importance of liquid biopsies, specifically ctDNA analysis in CSF, in pediatric brain tumor management, with a primary focus on medulloblastoma. Liquid biopsies have the potential to revolutionize patient care by enabling early diagnosis, accurate monitoring, and MRD detection. Nevertheless, further research is essential to validate their clinical utility fully. The evolving landscape of liquid biopsy applications underscores their promise in improving outcomes for pediatric brain tumor patients.

GPR37 expression as a prognostic marker in gliomas: a bioinformatics-based analysis

BACKGROUND

Gliomas are the most frequently diagnosed primary brain tumors, and are associated with multiple molecular aberrations during their development and progression. GPR37 is an orphan G protein-coupled receptor (GPCR) that is implicated in different physiological pathways in the brain, and has been linked to various malignancies. The aim of this study was to explore the relationship between GPR37 gene expression and the clinicopathological factors, patient prognosis, tumor-infiltrating immune cell signature GSEA and methylation levels in glioma.

METHODS

We explored the diagnostic value, clinical relevance, and molecular function of GPR37 in glioma using TCGA, STRING, cBioPortal, Tumor Immunity Estimation Resource (TIMER) database and MethSurv databases. Besides, the "ssGSEA" algorithm was conducted to estimate immune cells infiltration abundance, with 'ggplot2' package visualizing the results. Immunohistochemical staining of clinical samples were used to verify the speculations of bioinformatics analysis.

RESULTS

GPR37 expression was significantly higher in the glioma tissues compared to the normal brain tissues, and was linked to poor prognosis. Functional annotation of GPR37 showed enrichment of ether lipid metabolism, fat digestion and absorption, and histidine metabolism. In addition, GSEA showed that GPR37 was positively correlated to the positive regulation of macrophage derived foam cell differentiation, negative regulation of T cell receptor signaling pathway, neuroactive ligand receptor interaction, calcium signaling pathway, and negatively associated with immunoglobulin complex, immunoglobulin complex circulating, ribosome and spliceosome mediated by circulating immunoglobulin etc. TIMER2.0 and ssGSEA showed that GPR37 expression was significantly associated with the infiltration of T cells, CD8 T cell, eosinophils, macrophages, neutrophils, NK CD56dim cells, NK cells, plasmacytoid DCs (pDCs), T helper cells and T effector memory (Tem) cells. In addition, high GPR37 expression was positively correlated with increased infiltration of M2 macrophages, which in turn was associated with poor prognosis. Furthermore, GPR37 was positively correlated with various immune checkpoints (ICPs). Finally, hypomethylation of the GPR37 promoter was associated with its high expression levels and poor prognosis in glioma.

CONCLUSION

GPR37 had diagnostic and prognostic value in glioma. The possible biological mechanisms of GPR37 provide novel insights into the clinical diagnosis and treatment of glioma.

Orphan G Protein-Coupled Receptor GPR37 as an Emerging Therapeutic Target

G protein-coupled receptors (GPCRs) are successful druggable targets, making up around 35% of all FDA-approved medications. However, a large number of receptors remain orphaned, with no known endogenous ligand, representing a challenging but untapped area to discover new therapeutic targets. Among orphan GPCRs (oGPCRs) of interest, G protein-coupled receptor 37 (GPR37) is highly expressed in the central nervous system (CNS), particularly in the spinal cord and oligodendrocytes. While its cellular signaling mechanisms and endogenous receptor ligands remain elusive, GPR37 has been implicated in several important neurological conditions, including Parkinson's disease (PD), inflammation, pain, autism, and brain tumors. GPR37 structure, signaling, emerging physiology, and pharmacology are reviewed while integrating a discussion on potential therapeutic indications and opportunities.

A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy

INTRODUCTION

Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation.

AREAS COVERED

This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches.

EXPERT OPINION

Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.

Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma

BACKGROUND

Dysregulation of lipid metabolism is closely associated with cancer progression. The study aimed to establish a prognostic model to predict distant metastasis-free survival (DMFS) in patients with nasopharyngeal carcinoma (NPC), based on lipidomics.

METHODS

The plasma lipid profiles of 179 patients with locoregionally advanced NPC (LANPC) were measured and quantified using widely targeted quantitative lipidomics. Then, patients were randomly split into the training (125 patients, 69.8%) and validation (54 patients, 30.2%) sets. To identify distant metastasis-associated lipids, univariate Cox regression was applied to the training set (P < 0.05). A deep survival method called DeepSurv was employed to develop a proposed model based on significant lipid species (P < 0.01) and clinical biomarkers to predict DMFS. Concordance index and receiver operating curve analyses were performed to assess model effectiveness. The study also explored the potential role of lipid alterations in the prognosis of NPC.

RESULTS

Forty lipids were recognized as distant metastasis-associated (P < 0.05) by univariate Cox regression. The concordance indices of the proposed model were 0.764 (95% confidence interval (CI), 0.682-0.846) and 0.760 (95% CI, 0.649-0.871) in the training and validation sets, respectively. High-risk patients had poorer 5-year DMFS compared with low-risk patients (Hazard ratio, 26.18; 95% CI, 3.52-194.80; P < 0.0001). Moreover, the six lipids were significantly correlated with immunity- and inflammation-associated biomarkers and were mainly enriched in metabolic pathways.

CONCLUSIONS

Widely targeted quantitative lipidomics reveals plasma lipid predictors for LANPC, the prognostic model based on that demonstrated superior performance in predicting metastasis in LANPC patients.

Phosphoproteomic and proteomic profiling in post-infarction chronic heart failure

Background: Post-infarction chronic heart failure is the most common type of heart failure. Patients with chronic heart failure show elevated morbidity and mortality with limited evidence-based therapies. Phosphoproteomic and proteomic analysis can provide insights regarding molecular mechanisms underlying post-infarction chronic heart failure and explore new therapeutic approaches. Methods and results: Global quantitative phosphoproteomic and proteomic analysis of left ventricular tissues from post-infarction chronic heart failure rats were performed. A total of 33 differentially expressed phosphorylated proteins (DPPs) and 129 differentially expressed proteins were identified. Bioinformatic analysis indicated that DPPs were enriched mostly in nucleocytoplasmic transport and mRNA surveillance pathway. Bclaf1 Ser658 was identified after construction of Protein-Protein Interaction Network and intersection with Thanatos Apoptosis Database. Predicted Upstream Kinases of DPPs based on kinase-substrate enrichment analysis (KSEA) app showed 13 kinases enhanced in heart failure. Proteomic analysis showed marked changes in protein expression related to cardiac contractility and metabolism. Conclusion: The present study marked phosphoproteomics and proteomics changes in post-infarction chronic heart failure. Bclaf1 Ser658 might play a critical role in apoptosis in heart failure. PRKAA1, PRKACA, and PAK1 might serve as potential therapeutic targets for post-infarction chronic heart failure.

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.

To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

Metabolomics in oncology

BACKGROUND

Oncogenic transformation alters intracellular metabolism and contributes to the growth of malignant cells. Metabolomics, or the study of small molecules, can reveal insight about cancer progression that other biomarker studies cannot. Number of metabolites involved in this process have been in spotlight for cancer detection, monitoring, and therapy.

RECENT FINDINGS

In this review, the "Metabolomics" is defined in terms of current technology having both clinical and translational applications. Researchers have shown metabolomics can be used to discern metabolic indicators non-invasively using different analytical methods like positron emission tomography, magnetic resonance spectroscopic imaging etc. Metabolomic profiling is a powerful and technically feasible way to track changes in tumor metabolism and gauge treatment response across time. Recent studies have shown metabolomics can also predict individual metabolic changes in response to cancer treatment, measure medication efficacy, and monitor drug resistance. Its significance in cancer development and treatment is summarized in this review.

CONCLUSION

Although in infancy, metabolomics can be used to identify treatment options and/or predict responsiveness to cancer treatments. Technical challenges like database management, cost and methodical knowhow still persist. Overcoming these challenges in near further can help in designing new treatment régimes with increased sensitivity and specificity.

Pathological implications of metabolic reprogramming and its therapeutic potential in medulloblastoma

Tumor-specific alterations in metabolism have been recognized to sustain the production of ATP and macromolecules needed for cell growth, division and survival in many cancer types. However, metabolic heterogeneity poses a challenge for the establishment of effective anticancer therapies that exploit metabolic vulnerabilities. Medulloblastoma (MB) is one of the most heterogeneous malignant pediatric brain tumors, divided into four molecular subgroups (Wingless, Sonic Hedgehog, Group 3 and Group 4). Recent progresses in genomics, single-cell sequencing, and novel tumor models have updated the classification and stratification of MB, highlighting the complex intratumoral cellular diversity of this cancer. In this review, we emphasize the mechanisms through which MB cells rewire their metabolism and energy production networks to support and empower rapid growth, survival under stressful conditions, invasion, metastasis, and resistance to therapy. Additionally, we discuss the potential clinical benefits of currently available drugs that could target energy metabolism to suppress MB progression and increase the efficacy of the current MB therapies.

The Tumor Microenvironment of Medulloblastoma: An Intricate Multicellular Network with Therapeutic Potential

Simple Summary

The current treatment options for medulloblastoma, the most common malignant childhood brain cancer, are associated with many negative side effects and toxicities. Therefore, novel treatment options are needed that target the tumor without affecting the healthy tissue. Medulloblastoma tumors consist of a wide variety of cell types and extracellular components that make up the microenvironment of the tumor. This tumor microenvironment influences the development, progression, and relapse of medulloblastoma through different cell–cell and cell–extracellular matrix interactions. Obtaining insights into these interactions will help with gaining a better understanding of this malignancy. Additionally, it could support the search for new targets of treatments directed at components of the tumor microenvironment.

Abstract

Medulloblastoma (MB) is a heterogeneous disease in which survival is highly affected by the underlying subgroup-specific characteristics. Although the current treatment modalities have increased the overall survival rates of MB up to 70–80%, MB remains a major cause of cancer-related mortality among children. This indicates that novel therapeutic approaches against MB are needed. New promising treatment options comprise the targeting of cells and components of the tumor microenvironment (TME). The TME of MB consists of an intricate multicellular network of tumor cells, progenitor cells, astrocytes, neurons, supporting stromal cells, microglia, immune cells, extracellular matrix components, and vasculature systems. In this review, we will discuss all the different components of the MB TME and their role in MB initiation, progression, metastasis, and relapse. Additionally, we briefly introduce the effect that age plays on the TME of brain malignancies and discuss the MB subgroup-specific differences in TME components and how all of these variations could affect the progression of MB. Finally, we highlight the TME-directed treatments, in which we will focus on therapies that are being evaluated in clinical trials.

Cellular Immunotherapy for Medulloblastoma

Medulloblastoma (MB) is the most common malignant brain tumor in children, making up ~20% of all primary pediatric brain tumors. Current therapies consist of maximal surgical resection and aggressive radio- and chemotherapy. A third of the treated patients cannot be cured and survivors are often left with devastating long-term side effects. Novel efficient and targeted treatment is desperately needed for this patient population. Cellular immunotherapy aims to enhance and utilize immune cells to target tumors, and has been proven successful in various cancers. However, for MB, the knowledge and possibilities of cellular immunotherapy are limited. In this review, we provide a comprehensive overview of the current status of cellular immunotherapy for MB, from fundamental in vitro research to in vivo models and (ongoing) clinical trials. In addition, we compare our findings to cellular immunotherapy in glioma, an MB-like intracranial tumor. Finally, future possibilities for MB are discussed to improve efficacy and safety.

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.

Retinoid Drugs Improve Autophagy of Medulloblastoma Cells via Hedgehog-Gli Signaling Pathway

Our study aims to discuss the effect of retinoid drug on autophagy of medulloblastoma cells. Targeted ferrocenoretinoic acid was prepared and identified. The MB cells were assigned into blank group, control group and transfection group followed by analysis of cell survival rate and expression of Rack1, Hedgehog-Gli, Beclin1 and LC3. The size and form of prepared ferrocenoretinoic acid was uniform. There was positive charge which can bind target. Ferrocenoretinoic acid treatment declined cell survival rate and increased cell apoptotic rate. The level of Rack1 and Hedgehog-Gli in transfection group was lower than other two group. The tendency in expression of Beclin1 and LC3 was reversed. In conclusion, the expression of Rack1 is restrained by nano-retinoid drug so as to restrain the Hedgehog-Gli signal activity. Therefore, the survival rate of medulloblastoma cells could be restrained and apoptotic rate could be prompted.

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.

A hypoxia-linked gene signature for prognosis prediction and evaluating the immune microenvironment in patients with hepatocellular carcinoma

Background

Previous research indicates that hypoxia critically affects the initiation and progression of hepatocellular carcinoma (HCC). Nevertheless, the molecular mechanisms responsible for HCC development are poorly understood. Herein, we purposed to build a prognostic model using hypoxia-linked genes to predict patient prognosis and investigate the relationship of hypoxia with immune status in the tumor microenvironment (TME).

Methods

The training cohort included transcriptome along with clinical data abstracted from The Cancer Genome Atlas (TCGA). The validation cohort was abstracted from Gene Expression Omnibus (GEO). Univariate along with multivariate Cox regression were adopted to create the prediction model. We divided all patients into low- and high-risk groups using median risk scores. The estimation power of the prediction model was determined with bioinformatic tools.

Results

Six hypoxia-linked genes, HMOX1, TKTL1, TPI1, ENO2, LDHA, and SLC2A1, were employed to create an estimation model. Kaplan-Meier, ROC curve, and risk plot analyses demonstrated that the estimation potential of the risk model was satisfactory. Univariate along with multivariate regression data illustrated that the risk model could independently predict the overall survival (OS). A nomogram integrating the risk signature and clinicopathological characteristics showed a good potential to estimate HCC prognosis. Gene set enrichment analysis (GSEA) revealed that genes associated with cell proliferation and metabolism cascades were abundant in high-risk group. Furthermore, the signature showed a strong ability to distinguish the two groups in terms of immune status.

Conclusions

A prediction model for predicting HCC prognosis using six hypoxia-linked genes was designed in this study, facilitating the diagnosis and treatment of HCC.

Recent Metabolomics Analysis in Tumor Metabolism Reprogramming

Metabolic reprogramming has been suggested as a hallmark of cancer progression. Metabolomic analysis of various metabolic profiles represents a powerful and technically feasible method to monitor dynamic changes in tumor metabolism and response to treatment over the course of the disease. To date, numerous original studies have highlighted the application of metabolomics to various aspects of tumor metabolic reprogramming research. In this review, we summarize how metabolomics techniques can help understand the effects that changes in the metabolic profile of the tumor microenvironment on the three major metabolic pathways of tumors. Various non-invasive biofluids are available that produce accurate and useful clinical information on tumor metabolism to identify early biomarkers of tumor development. Similarly, metabolomics can predict individual metabolic differences in response to tumor drugs, assess drug efficacy, and monitor drug resistance. On this basis, we also discuss the application of stable isotope tracer technology as a method for the study of tumor metabolism, which enables the tracking of metabolite activity in the body and deep metabolic pathways. We summarize the multifaceted application of metabolomics in cancer metabolic reprogramming to reveal its important role in cancer development and treatment.

Multi-Omics Analysis of Mammary Metabolic Changes in Dairy Cows Exposed to Hypoxia

Hypoxia exposure can cause a series of physiological and biochemical reactions in the organism and cells. Our previous studies found the milk fat rate increased significantly in hypoxic dairy cows, however, its specific metabolic mechanism is unclear. In this experiment, we explored and verified the mechanism of hypoxia adaptation based on the apparent and omics results of animal experiments and in vitro cell model. The results revealed that hypoxia exposure was associated with the elevation of AGPAT2-mediated glycerophospholipid metabolism. These intracellular metabolic disorders consequently led to the lipid disorders associated with apoptosis. Our findings update the existing understanding of increased adaptability of dairy cows exposure to hypoxia at the metabolic level.

Cytotoxic effects and tolerability of gemcitabine and axitinib in a xenograft model for c-myc amplified medulloblastoma

Medulloblastoma is the most common high-grade brain tumor in childhood. Medulloblastomas with c-myc amplification, classified as group 3, are the most aggressive among the four disease subtypes resulting in a 5-year overall survival of just above 50%. Despite current intensive therapy regimens, patients suffering from group 3 medulloblastoma urgently require new therapeutic options. Using a recently established c-myc amplified human medulloblastoma cell line, we performed an in-vitro-drug screen with single and combinatorial drugs that are either already clinically approved or agents in the advanced stage of clinical development. Candidate drugs were identified in vitro and then evaluated in vivo. Tumor growth was closely monitored by BLI. Vessel development was assessed by 3D light-sheet-fluorescence-microscopy. We identified the combination of gemcitabine and axitinib to be highly cytotoxic, requiring only low picomolar concentrations when used in combination. In the orthotopic model, gemcitabine and axitinib showed efficacy in terms of tumor control and survival. In both models, gemcitabine and axitinib were better tolerated than the standard regimen comprising of cisplatin and etoposide phosphate. 3D light-sheet-fluorescence-microscopy of intact tumors revealed thinning and rarefication of tumor vessels, providing one explanation for reduced tumor growth. Thus, the combination of the two drugs gemcitabine and axitinib has favorable effects on preventing tumor progression in an orthotopic group 3 medulloblastoma xenograft model while exhibiting a favorable toxicity profile. The combination merits further exploration as a new approach to treat high-risk group 3 medulloblastoma.

Molecular Mechanisms of Fetal Tendon Regeneration Versus Adult Fibrous Repair

Tendinopathies are painful, disabling conditions that afflict 25% of the adult human population. Filling an unmet need for realistic large-animal models, we here present an ovine model of tendon injury for the comparative study of adult scarring repair and fetal regeneration. Complete regeneration of the fetal tendon within 28 days is demonstrated, while adult tendon defects remained macroscopically and histologically evident five months post-injury. In addition to a comprehensive histological assessment, proteome analyses of secretomes were performed. Confirming histological data, a specific and pronounced inflammation accompanied by activation of neutrophils in adult tendon defects was observed, corroborated by the significant up-regulation of pro-inflammatory factors, neutrophil attracting chemokines, the release of potentially tissue-damaging antimicrobial and extracellular matrix-degrading enzymes, and a response to oxidative stress. In contrast, secreted proteins of injured fetal tendons included proteins initiating the resolution of inflammation or promoting functional extracellular matrix production. These results demonstrate the power and relevance of our novel ovine fetal tendon regeneration model, which thus promises to accelerate research in the field. First insights from the model already support our molecular understanding of successful fetal tendon healing processes and may guide improved therapeutic strategies.

Recent Advances in Understanding the Role of Autophagy in Paediatric Brain Tumours

Autophagy is a degradative process occurring in eukaryotic cells to maintain homeostasis and cell survival. After stressful conditions including nutrient deprivation, hypoxia or drugs administration, autophagy is induced to counteract pathways that could lead to cell death. In cancer, autophagy plays a paradoxical role, acting both as tumour suppressor—by cleaning cells from damaged organelles and inhibiting inflammation or, alternatively, by promoting genomic stability and tumour adaptive response—or as a pro-survival mechanism to protect cells from stresses such as chemotherapy. Neural-derived paediatric solid tumours represent a variety of childhood cancers with unique anatomical location, cellular origins, and clinical presentation. These tumours are a leading cause of morbidity and mortality among children and new molecular diagnostics and therapies are necessary for longer survival and reduced morbidity. Here, we review advances in our understanding of how autophagy modulation exhibits antitumor properties in experimental models of paediatric brain tumours, i.e., medulloblastoma (MB), ependymoma (EPN), paediatric low-grade and high-grade gliomas (LGGs, HGGs), atypical teratoid/rhabdoid tumours (ATRTs), and retinoblastoma (RB). We also discuss clinical perspectives to consider how targeting autophagy may be relevant in these specific paediatric tumours.

A systematic view of pediatric medulloblastoma proteomics-current state of the field and future directions

Quantitative mass spectrometry (MS)-based approaches have allowed further characterization of medulloblastoma (MB) classification and clinical/biological behavior. By investigating protein expression, as well as the role of post-translational modifications in shaping cellular activity, novel avenues of research will clarify the current subgrouping, providing elements for tumor treatment-new molecular targets and signaling cascades-and introducing serum, urinary, and CSF markers of tumor growth and recurrence. We systematically searched and reviewed original research articles treating MB proteomics on PubMed. Reviews, opinion papers, and abstracts were excluded from the final work. A total of 30 novel articles treating the proteomic characterization of MB were included in our review. Research conducted on tissue samples, cell lines, CSF, and urine, as well as exosome and medullospheres, was considered, to picture a broad view of the different directions MS-based proteomic analysis is moving toward. In this review, we collect, summarize, and interpret the current literature on this topic. Significant progress has been achieved in the last decade in MB characterization, paving the way for further exploration of large biobanks of MB and other tissues that will allow a more systematic understanding of MB functioning and clinical progression.

Eicosanoid Content in Fetal Calf Serum Accounts for Reproducibility Challenges in Cell Culture

Reproducibility issues regarding in vitro cell culture experiments are related to genetic fluctuations and batch-wise variations of biological materials such as fetal calf serum (FCS). Genome sequencing may control the former, while the latter may remain unrecognized. Using a U937 macrophage model for cell differentiation and inflammation, we investigated whether the formation of effector molecules was dependent on the FCS batch used for cultivation. High resolution mass spectrometry (HRMS) was used to identify FCS constituents and to explore their effects on cultured cells evaluating secreted cytokines, eicosanoids, and other inflammatory mediators. Remarkably, the FCS eicosanoid composition showed more batch-dependent variations than the protein composition. Efficient uptake of fatty acids from the medium by U937 macrophages and inflammation-induced release thereof was evidenced using C13-labelled arachidonic acid, highlighting rapid lipid metabolism. For functional testing, FCS batch-dependent nanomolar concentration differences of two selected eicosanoids, 5-HETE and 15-HETE, were balanced out by spiking. Culturing U937 cells at these defined conditions indeed resulted in significant proteome alterations indicating HETE-induced PPARγ activation, independently corroborated by HETE-induced formation of peroxisomes observed by high-resolution microscopy. In conclusion, the present data demonstrate that FCS-contained eicosanoids, subject to substantial batch-wise variation, may modulate cellular effector functions in cell culture experiments.

Liquid Biomarkers for Pediatric Brain Tumors: Biological Features, Advantages and Perspectives

Tumors of the central nervous system are the most frequent solid tumor type and the major cause for cancer-related mortality in children and adolescents. These tumors are biologically highly heterogeneous and comprise various different entities. Molecular diagnostics are already well-established for pediatric brain tumors and have facilitated a more accurate patient stratification. The availability of targeted, biomarker-driven therapies has increased the necessity of longitudinal monitoring of molecular alterations within tumors for precision medicine-guided therapy. Nevertheless, diagnosis is still primarily based on analyses of the primary tumor and follow-up is usually performed by imaging techniques which lack important information on tumor biology possibly changing the course of the disease. To overcome this shortage of longitudinal information, liquid biopsy has emerged as a promising diagnostic tool representing a less-invasive source of biomarkers for tumor monitoring and therapeutic decision making. Novel ultrasensitive methods for detection of allele variants, genetic alterations with low abundance, have been developed and are promising tools for establishing and integrating liquid biopsy techniques into clinical routine. Pediatric brain tumors harbor multiple molecular alterations with the potential to be used as liquid biomarkers. Consequently, studies have already investigated different types of biomarker in diverse entities of pediatric brain tumors. However, there are still certain pitfalls until liquid biomarkers can be unleashed and implemented into routine clinical care. Within this review, we summarize current knowledge on liquid biopsy markers and technologies in pediatric brain tumors, their advantages and drawbacks, as well as future potential biomarkers and perspectives with respect to clinical implementation in patient care.