Metabolomics in paediatric oncology: a potential still to be exploited

Noninvasive testing for mycophenolate exposure in children with renal transplant using urinary metabolomics

BACKGROUND

Despite the common use of mycophenolate in pediatric renal transplantation, lack of effective therapeuic drug monitoring increases uncertainty over optimal drug exposure and risk for adverse reactions. This study aims to develop a novel urine test to estimate MPA exposure based using metabolomics.

METHODS

Urine samples obtained on the same day of MPA pharmacokinetic testing from two prospective cohorts of pediatric kidney transplant recipients were assayed for 133 unique metabolites by mass spectrometry. Partial least squares (PLS) discriminate analysis was used to develop a top 10 urinary metabolite classifier that estimates MPA exposure. An independent cohort was used to test pharmacodynamic validity for allograft inflammation (urinary CXCL10 levels) and eGFR ratio (12mo/1mo eGFR) at 1 year.

RESULTS

Fifty-two urine samples from separate children (36.5% female, 12.0 ± 5.3 years at transplant) were evaluated at 1.6 ± 2.5 years post-transplant. Using all detected metabolites (n = 90), the classifier exhibited strong association with MPA AUC by principal component regression (r = 0.56, p < .001) and PLS (r = 0.75, p < .001). A practical classifier (top 10 metabolites; r = 0.64, p < .001) retained similar accuracy after cross-validation (LOOCV; r = 0.52, p < .001). When applied to an independent cohort (n = 97 patients, 1053 samples), estimated mean MPA exposure over Year 1 was inversely associated with mean urinary CXCL10:Cr (r = -0.28, 95% CI -0.45, -0.08) and exhibited a trend for association with eGFR ratio (r = 0.35, p = .07), over the same time period.

CONCLUSIONS

This urinary metabolite classifier can estimate MPA exposure and correlates with allograft inflammation. Future studies with larger samples are required to validate and evaluate its clinical application.

Metabolic Pathways Associated With Psychoneurological Symptoms in Children With Cancer Receiving Chemotherapy

CONTEXT

Children with cancer undergoing chemotherapy experience a cluster of psychoneurological symptoms (PNS), including pain, fatigue, anxiety, and depressive symptoms. Metabolomics is promising to differentiate metabolic pathways associated with the PNS cluster.

OBJECTIVES

Identify metabolic pathways associated with the PNS cluster in children with cancer before and after chemotherapy.

METHODS

Pain, fatigue, anxiety, and depressive symptoms were assessed using the Pediatric PROMIS scales. T-scores were computed and divided dichotomously by a cutoff point of 50; the PNS cluster was a sum of the four symptoms ranging from 0 (all T-scores <50) to 4 (all T-scores ≥50). Serum metabolites were processed using liquid chromatography mass-spectrometry untargeted metabolomics approach. Linear regression models examined metabolites associated with the PNS cluster. Metabolic pathway enrichment analysis was performed.

RESULTS

Participant demographics (n = 40) were 55% female, 60% white, 62.5% aged 13-19 years, and 62.5% diagnoses of Hodgkin's lymphoma and B-cell acute lymphocytic leukemia. Among 9276 unique metabolic features, 454 were associated with pain, 281 with fatigue, 596 with anxiety, 551 with depressive symptoms, and 300 with the PNS cluster across one chemotherapy cycle. Fatty acids pathways were associated with pain: de novo fatty acid biosynthesis (p < .001), fatty acid metabolism (p = .001), fatty acid activation (p = .004), and omega-3 fatty acid metabolism (p = .009). Tryptophan amino acid pathway was associated with fatigue (p < .001), anxiety (p = .015), and the PNS cluster (p = .037). Carnitine shuttle was associated with the PNS cluster (p = .015).

CONCLUSION

Fatty acids and amino acids pathways were associated with PNS in children undergoing chemotherapy. These findings require further investigation in a larger sample.

How could metabolomics change pediatric health?

In the last years, 'omics' technologies, and especially metabolomics, emerged as expanding scientific disciplines and promising technologies in the characterization of several pathophysiological processes.In detail, metabolomics, able to detect in a dynamic way the whole set of molecules of low molecular weight in cells, tissues, organs, and biological fluids, can provide a detailed phenotypic portray, representing a metabolic "snapshot."Thanks to its numerous strength points, metabolomics could become a fundamental tool in human health, allowing the exact evaluation of individual metabolic responses to pathophysiological stimuli including drugs, environmental changes, lifestyle, a great number of diseases and other epigenetics factors.Moreover, if current metabolomics data will be confirmed on larger samples, such technology could become useful in the early diagnosis of diseases, maybe even before the clinical onset, allowing a clinical monitoring of disease progression and helping in performing the best therapeutic approach, potentially predicting the therapy response and avoiding overtreatments. Moreover, the application of metabolomics in nutrition could provide significant information on the best nutrition regimen, optimal infantile growth and even in the characterization and improvement of commercial products' composition.These are only some of the fields in which metabolomics was applied, in the perspective of a precision-based, personalized care of human health.In this review, we discuss the available literature on such topic and provide some evidence regarding clinical application of metabolomics in heart diseases, auditory disturbance, nephrouropathies, adult and pediatric cancer, obstetrics, perinatal conditions like asphyxia, neonatal nutrition, neonatal sepsis and even some neuropsychiatric disorders, including autism.Our research group has been interested in metabolomics since several years, performing a wide spectrum of experimental and clinical studies, including the first metabolomics analysis of human breast milk. In the future, it is reasonable to predict that the current knowledge could be applied in daily clinical practice, and that sensible metabolomics biomarkers could be easily detected through cheap and accurate sticks, evaluating biofluids at the patient's bed, improving diagnosis, management and prognosis of sick patients and allowing a personalized medicine. A dream? May be I am a dreamer, but I am not the only one.

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.

Metabolic changes in the midgut of Eri silkworm after Oral administration of 1-deoxynojirimycin: A 1H-NMR-based metabonomic study

1-deoxynojirimycin (DNJ) is a natural D-glucose analogue and has a strong physiological activity in inhibiting α-glucosidase in vivo. The antidiabetic effects of DNJ in mice or other mammals were extensively explored, but the physiological and toxic roles of DNJ in insects was seldom reported. In this study, the biological effects of DNJ were examined in midgut extracts of fourth-instar larvae of Eri silkworm (Samia cynthia ricini, Saturniidae). Based on nuclear magnetic resonance (NMR) metabonomics technology, we analyzed the alterations of glycometabolism, lipids, and energy metabolism pathways in the midgut of S. cynthia ricini caused by DNJ. Pattern recognition analysis (partial least square-discriminant analysis, PLS-DA) showed that four groups of latex, 0.25% DNJ, 0.5% DNJ and the mixture of 0.5% DNJ and latex (1:1) were distinctly different from the control group. Moreover, several metabolic pathways of DNJ-mediated modulation in the midgut were identified. Compared with the control group, alanine, succinate, glutamate, and fumarate concentrations decreased in three groups of 0.5% DNJ, latex, and the mixture, choline levels increased in two DNJ groups, and trehalose levels increased in all experimental groups. Therefore, these results suggest that DNJ modulated lipid metabolism by limiting the hydrolysis pathways of phospholipids metabolism. Additionally, DNJ has a potent negative effect on energy metabolism by inhibiting the hydrolysis of trehalose, glycolysis and the tricarboxylic acid (TCA) cycle. Overall, DNJ, as a single-ingredient, is an efficient substance for modulating lipid metabolism and inhibiting energy metabolism.

A 1H-NMR Based Study on Hemolymph Metabolomics in Eri Silkworm after Oral Administration of 1-Deoxynojirimycin

We aimed to investigate whether 1-deoxynojirimycin (DNJ) modulates glycometabolism and has toxicity in Eri silkworm (Samia cynthia ricini, Saturniidae). In this paper, hemolymph metabolites were used to explore metabolic changes after oral administration of DNJ or mulberry latex and to characterize the biological function of DNJ at the metabolic and systemic levels. Hemolymph samples were collected from fourth-instar larvae of Eri silkworm and ex-vivo high-resolution 1H nuclear magnetic resonance (NMR) spectra were acquired from the collected hemolymph samples. Then the obtained spectra were analyzed by principal component analysis (PCA) and independent-samples t-test. Metabolic pattern recognition analysis of hemolymph samples indicated that the groups of 0.25% DNJ, latex, and the mixture of 0.5% DNJ and latex (1:1) were significantly different from the control group. Moreover, compared to the control group, the groups of 0.25% DNJ, latex, and the mixture of 0.5% DNJ and latex (1:1) showed the decreased levels of citrate, succinate, fumarate, malate, and glutamine in hemolymph, the groups of 0.25% DNJ and the mixture of 0.5% DNJ and latex (1:1) showed the increased levels of trehalose and lactate. In addition, mulberry leaves exude latex was highly toxic to Eri silkworm because rich unidentified high-molecular-weight factor (s) acted as toxic substances. In our results, latex caused 20 deaths among 50 fourth-instar larvae of Eri silkmoth, but DNJ or the mixture did not caused death. All these results suggest that DNJ has a positive impact on the reverse glycometabolism by modulating glycometabolism and inhibiting glucogenesis and energy metabolism. DNJ is a secure substance as a single-ingredient antidiabetic medicine due to its nontoxicity and bioactivity.