SERUM metabolomics of acute lymphoblastic leukaemia and acute myeloid leukaemia for probing biomarker molecules

Untargeted metabolomic and lipidomic analyses reveal lipid dysregulation in the plasma of acute leukemia patients

Acute leukemias (AL) are aggressive neoplasms with high mortality rates. Metabolomics and oxidative status have emerged as important tools to identify new biomarkers with clinical utility. To identify the metabolic differences between healthy individuals (HI) and patients with AL, a multiplatform untargeted metabolomic and lipidomic approach was conducted using liquid and gas chromatography coupled with quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS or GC-QTOF-MS). Additionally, the total antioxidant capacity (TAC) was measured. A total of 20 peripheral blood plasma samples were obtained from patients with AL and 18 samples from HI. Our analysis revealed 135 differentially altered metabolites in the patients belonging to 12 chemical classes; likewise, the metabolic pathways of glycerolipids and sphingolipids were the most affected in the patients. A decrease in the TAC of the patients with respect to the HI was evident. This study conducted with a cohort of Colombian patients is consistent with observations from other research studies that suggest dysregulation of lipid compounds. Furthermore, metabolic differences between patients and HI appear to be independent of lifestyle, race, or geographic location, providing valuable information for future advancements in understanding the disease and developing more global therapies.

Mass Spectrometry Analysis for Clinical Applications: A Review

Mass spectrometry (MS) has become an attractive analytical method in clinical analysis due to its comprehensive advantages of high sensitivity, high specificity and high throughput. Separation techniques coupled MS detection (e.g., LC-MS/MS) have shown unique advantages over immunoassay and have developed as golden criterion for many clinical applications. This review summarizes the characteristics and applications of MS, and emphasizes the high efficiency of MS in clinical research. In addition, this review also put forward further prospects for the future of mass spectrometry technology, including the introduction of miniature MS instruments, point-of-care detection and high-throughput analysis, to achieve better development of MS technology in various fields of clinical application. Moreover, as ambient ionization mass spectrometry (AIMS) requires little or no sample pretreatment and improves the flux of MS, this review also summarizes its potential applications in clinic.

Association of lipid metabolism-related metabolites with overweight/obesity based on the FTO rs1421085

Globally, obesity is a severe health issue. A more precise and practical approach is required to enhance clinical care and drug development. The FTO (fat mass and obesity-associated) gene variant rs1421085 is strongly associated with an increased susceptibility to obesity in numerous populations; however, the precise mechanism behind this association concerning metabolomics is still not understood. This study aims to examine the association between metabolites and obesity-related anthropometric traits based on the variant FTO rs1421085. This study was based on a case-control design involving a total of 542 participants including overweight/obese cases and healthy controls. The blood samples were collected from all the participants. The isolated serum samples were subjected to untargeted metabolomics using GC-MS. The isolated DNA samples were genotyped for the FTO rs1421085 variant. Initially, a total of 42 metabolites were identified on GC-MS, which were subjected to further association analyses. The study observed a significant association of two metabolites, glycerol and 2,3-dihydroxypropyl stearate with FTO gene variant rs1421085 and obesity-related anthropometric traits including % BF, WHtR, WC, and HC. The CT genotype of FTO rs1421085 may greatly increase the risk of overweight/obesity by changing the lipid metabolism-related metabolites. Therefore, this study highlights the significance of biochemical networks in the progression of obesity in carriers of the FTO rs1421085 risk genotype.

Metabolomic Study of Urine from Workers Exposed to Low Concentrations of Benzene by UHPLC-ESI-QToF-MS Reveals Potential Biomarkers Associated with Oxidative Stress and Genotoxicity

Benzene is a human carcinogen whose exposure to concentrations below 1 ppm (3.19 mg·m^-3) is associated with myelotoxic effects. The determination of biomarkers such as trans-trans muconic acid (AttM) and S-phenylmercapturic acid (SPMA) show exposure without reflecting the toxic effects of benzene. For this reason, in this study, the urinary metabolome of individuals exposed to low concentrations of benzene was investigated, with the aim of understanding the biological response to exposure to this xenobiotic and identifying metabolites correlated with the toxic effects induced by it. Ultra-efficient liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer (UHPLC-ESI-Q-ToF-MS) was used to identify metabolites in the urine of environmentally (n = 28) and occupationally exposed (n = 32) to benzene (mean of 22.1 μg·m^-3 and 31.8 μg·m^-3, respectively). Non-targeted metabolomics analysis by PLS-DA revealed nine urinary metabolites discriminating between groups and statistically correlated with oxidative damage (MDA, thiol) and genetic material (chromosomal aberrations) induced by the hydrocarbon. The analysis of metabolic pathways revealed important alterations in lipid metabolism. These results point to the involvement of alterations in lipid metabolism in the mechanisms of cytotoxic and genotoxic action of benzene. Furthermore, this study proves the potential of metabolomics to provide relevant information to understand the biological response to exposure to xenobiotics and identify early effect biomarkers.

Lipids and the cancer stemness regulatory system in acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous disease of impaired myeloid differentiation and a caricature of normal hematopoiesis. Leukemic stem cells (LSCs) are responsible for long-term clonal propagation in AML just as hematopoietic stem cells (HSCs) sustain lifelong hematopoiesis. LSCs are often resistant to standard chemotherapy and are responsible for clinical relapse. Although AML is highly heterogeneous, determinants of stemness are prognostic for AML patient survival and can predict AML drug sensitivity. Therefore, one way to overcome challenges preventing efficacious treatment outcomes is to target LSC stemness. Metabolomic and lipidomic studies of serum and cells from AML patients are emerging to complement genomic, transcriptomic, epigenetic, and proteomic data sets to characterize and stratify AML. Recent studies have shown the value of fractionating LSCs versus blasts when characterizing metabolic pathways and implicate the importance of lipid balance to LSCs function. As more extensive metabolic studies coupled to functional in vivo assays are conducted on highly purified HSCs, bulk AML, and LSCs, the similarities and differences in lipid homeostasis in stem-like versus more mature AML subtypes as well as from normal HSCs are emerging. Here, we discuss the latest findings from studies of lipid function in LSCs, with a focus on sphingolipids (SLs) as stemness/lineage fate mediators in AML, and the balance of fatty acid anabolism and catabolism fueling metabolic flexibility and drug resistance in AML. We also discuss how designing successful strategies to target lipid vulnerabilities and improve AML patient survival should take into consideration the hierarchical nature of AML.

Differentiation and prognostic stratification of acute myeloid leukemia by serum-based spectroscopy coupling with metabolic fingerprints

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by complex molecular and cytogenetic abnormalities. New approaches to predict the prognosis of AML have increasingly attracted attention. There were 98 non-M3 AML cases and 48 healthy controls were enrolled in the current work. Clinically routine assays for cytogenetic and molecular genetic analyses were performed on the bone marrow samples of patients with AML. Meanwhile, metabolic profiling of these AML subjects was also performed on the serum samples by combining Ag nanoparticle-based surface-enhanced Raman spectroscopy (SERS) with proton nuclear magnetic resonance (NMR) spectroscopy. Although most of the routine biochemical test showed no significant differences between the M0-M2 and M5 groups, the metabolic profiles were significantly different either between AML subtypes or between prognostic risk subgroups. Specific SERS bands were screened to serve as potential markers for AML subtypes. The results demonstrated that the classification models for M0-M2 and M5 shared two bands (i.e., 1328 and 741 cm^-1 ), all came from nucleic acid signals. Furthermore, Metabolic profiles provided various differential metabolites responsible for different AML subtypes, and we found altered pathways mainly included energy metabolism like glycolysis, pyruvate metabolism, and metabolisms of nucleic acid bases as well as specific amino acid metabolisms. It is concluded that integration of SERS and NMR provides the rational and could be reliable to reveal AML differentiation, and meanwhile lay the basis for experimental and clinical practice to monitor disease progression and prognostic evaluation.

Serum Metabolomics Coupling With Clinical Laboratory Indicators Reveal Taxonomic Features of Leukemia

Metabolic abnormality has been considered to be the seventh characteristic in cancer cells. The potential prospect of using serum biomarkers metabolites to differentiate ALL from AML remains unclear. The purpose of our study is to probe whether the differences in metabolomics are related to clinical laboratory-related indicators. We used LC-MS-based metabolomics analysis to study 50 peripheral blood samples of leukemia patients from a single center. Then Chi-square test and T test were used to analyze the clinical characteristics, laboratory indicators and cytokines of 50 patients with leukemia. Correlation analysis was used to explore the relationship between them and the differential metabolites of different types of leukemia. Our study shows that it is feasible to better identify serum metabolic differences in different types and states of leukemia by metabolomic analysis on existing clinical diagnostic techniques. The metabolism of choline and betaine may also be significantly related to the patient’s blood lipid profile. The main enrichment pathways for distinguishing differential metabolites in different types of leukemia are amino acid metabolism and fatty acid metabolism. All these findings suggested that differential metabolites and lipid profiles might identify different types of leukemia based on existing clinical diagnostic techniques, and their rich metabolic pathways help us to better understand the physiological characteristics of leukemia.

Plasma lipidome acts as diagnostic marker and predictor for cyclosporin response in patients with aplastic anemia

The lipid metabolomic profile has been well defined in the pathogenesis and differential diagnosis in patients with different myeloid diseases. We assumed that the serum lipid metabolites could also help the diagnosis and prognostic prediction of aplastic anemia (AA). In this study, serum lipid profiles were explored in AA patients before and after cyclosporin (CsA) treatment. Meanwhile, hypocellular myelodysplastic syndrome (h-MDS) patients and the healthy volunteers were compared as controls. 15 AA patients, 11 h-MDS patients and 20 age and sex matched health controls were enrolled. All the AA patients were diagnosed to be non-severe aplastic anemia with transfusion dependency and were treated by CsA 3-5 mg/kg/d for at least 6 months. AA patients had decreased arachidonic acid pathway metabolites and retinol metabolism-related metabolites as compared with h-MDS and the health (P < 0.05), whereas h-MDS patients had increased metabolism of proline and threonine and abnormal sphingolipid metabolism compared with AA patients and the normal controls. After 6 month of CsA treatment, serum arachidonic acid, PGE2, PGJ2, 15(S)-HETE, leukotriene B4 and Protectin D1 decreased significantly. Patients who had response to CsA had higher levels of baseline protectin D1 (P = 0.011), leukotriene B4 (P = 0.011), 15(S)-HETE (P = 0.004) and all-trans-retinal (P = 0.000) than those who had no response.

Metabolic Reprogramming and Cell Adhesion in Acute Leukemia Adaptation to the CNS Niche

Involvement of the Central Nervous System (CNS) in acute leukemia confers poor prognosis and lower overall survival. Existing CNS-directed therapies are associated with a significant risk of short- or long-term toxicities. Leukemic cells can metabolically adapt and survive in the microenvironment of the CNS. The supporting role of the CNS microenvironment in leukemia progression and dissemination has not received sufficient attention. Understanding the mechanism by which leukemic cells survive in the nutrient-poor and oxygen-deprived CNS microenvironment will lead to the development of more specific and less toxic therapies. Here, we review the current literature regarding the roles of metabolic reprogramming in leukemic cell adhesion and survival in the CNS.

Integrated genomic-metabolic classification of acute myeloid leukemia defines a subgroup with NPM1 and cohesin/DNA damage mutations

Although targeting of cell metabolism is a promising therapeutic strategy in acute myeloid leukemia (AML), metabolic dependencies are largely unexplored. We aimed to classify AML patients based on their metabolic landscape and map connections between metabolic and genomic profiles. Combined serum and urine metabolomics improved AML characterization compared with individual biofluid analysis. At intracellular level, AML displayed dysregulated amino acid, nucleotide, lipid, and bioenergetic metabolism. The integration of intracellular and biofluid metabolomics provided a map of alterations in the metabolism of polyamine, purine, keton bodies and polyunsaturated fatty acids and tricarboxylic acid cycle. The intracellular metabolome distinguished three AML clusters, correlating with distinct genomic profiles: NPM1-mutated(mut), chromatin/spliceosome-mut and TP53-mut/aneuploid AML that were confirmed by biofluid analysis. Interestingly, integrated genomic-metabolic profiles defined two subgroups of NPM1-mut AML. One was enriched for mutations in cohesin/DNA damage-related genes (NPM1/cohesin-mut AML) and showed increased serum choline + trimethylamine-N-oxide and leucine, higher mutation load, transcriptomic signatures of reduced inflammatory status and better ex-vivo response to EGFR and MET inhibition. The transcriptional differences of enzyme-encoding genes between NPM1/cohesin-mut and NPM1-mut allowed in silico modeling of intracellular metabolic perturbations. This approach predicted alterations in NAD and purine metabolism in NPM1/cohesin-mut AML that suggest potential vulnerabilities, worthy of being therapeutically explored.

Impact of acute lymphoblastic leukemia induction therapy: findings from metabolomics on non-fasted plasma samples from a biorepository

INTRODUCTION

Acute lymphoblastic leukemia (ALL) is among the most common cancers in children. With improvements in combination chemotherapy regimens, the overall survival has increased to over 90%. However, the current challenge is to mitigate adverse events resulting from the complex therapy. Several chemotherapies intercept cancer metabolism, but little is known about their collective role in altering host metabolism.

OBJECTIVES

We profiled the metabolomic changes in plasma of ALL patients initial- and post- induction therapy.

METHODS

We exploited a biorepository of non-fasted plasma samples derived from the Dana Farber Cancer Institute ALL Consortium; these samples were obtained from 50 ALL patients initial- and post-induction therapy. Plasma metabolites and complex lipids were analyzed by high resolution tandem mass spectrometry and differential mobility tandem mass spectrometry. Data were analyzed using a covariate-adjusted regression model with multiplicity adjustment. Pathway enrichment analysis and co-expression network analysis were performed to identify unique clusters of molecules.

RESULTS

More than 1200 metabolites and complex lipids were identified in the total of global metabolomics and lipidomics platforms. Over 20% of those molecules were significantly altered. In the pathway enrichment analysis, lipids, particularly phosphatidylethanolamines (PEs), were identified. Network analysis indicated that the bioactive fatty acids, docosahexaenoic acid (DHA)-containing (22:6) triacylglycerols (TAGs), were decreased in the post-induction therapy.

CONCLUSION

Metabolomic profiling in ALL patients revealed a large number of alterations following induction chemotherapy. In particular, lipid metabolism was substantially altered. The changes in metabolites and complex lipids following induction therapy could provide insight into the adverse events experienced by ALL patients.

Cellular Metabolomics Profiles Associated With Drug Chemosensitivity in AML

Background

Acute myeloid leukemia (AML) is a hematological malignancy with a dismal prognosis. For over four decades, AML has primarily been treated by cytarabine combined with an anthracycline. Although a significant proportion of patients achieve remission with this regimen, roughly 40% of children and 70% of adults relapse. Over 90% of patients with resistant or relapsed AML die within 3 years. Thus, relapsed and resistant disease following treatment with standard therapy are the most common clinical failures that occur in treating this disease. In this study, we evaluated the relationship between AML cell line global metabolomes and variation in chemosensitivity.

Methods

We performed global metabolomics on seven AML cell lines with varying chemosensitivity to cytarabine and the anthracycline doxorubicin (MV4.11, KG-1, HL-60, Kasumi-1, AML-193, ME1, THP-1) using ultra-high performance liquid chromatography - mass spectrometry (UHPLC-MS). Univariate and multivariate analyses were performed on the metabolite peak intensity values from UHPLC-MS using MetaboAnalyst to identify cellular metabolites associated with drug chemosensitivity.

Results

A total of 1,624 metabolic features were detected across the leukemic cell lines. Of these, 187 were annotated to known metabolites. With respect to doxorubicin, we observed significantly greater abundance of a carboxylic acid (1-aminocyclopropane-1-carboxylate) and several amino acids in resistant cell lines. Pathway analysis found enrichment of several amino acid biosynthesis and metabolic pathways. For cytarabine resistance, nine annotated metabolites were significantly different in resistance vs. sensitive cell lines, including D-raffinose, guanosine, inosine, guanine, aldopentose, two xenobiotics (allopurinol and 4-hydroxy-L-phenylglycine) and glucosamine/mannosamine. Pathway analysis associated these metabolites with the purine metabolic pathway.

Conclusion

Overall, our results demonstrate that metabolomics differences contribute toward drug resistance. In addition, it could potentially identify predictive biomarkers for chemosensitivity to various anti-leukemic drugs. Our results provide opportunity to further explore these metabolites in patient samples for association with clinical response.

Investigation of pathogenesis and therapeutic targets of acute myeloid leukemia based on untargeted plasma metabolomics and network pharmacology approach

Acute myeloid leukemia (AML) is a malignant disease originating from bone marrow hematopoietic stem cells, characterized by anemia, hemorrhage, fever, and infection, with low survival rate. However, the pathogenesis of AML is not fully understood at present. In this work, an integrated approach based untargeted metabolomics and network pharmacology was adopted to elucidate the pathogenesis of AML. Metabolic profiling of plasma samples from 14 patients and 16 healthy individuals were performed based on UHPLC-MS platform. As a result, 23 metabolites were identified by using the human metabolite database based on PLS-DA (partial least squares discriminant analysis) and independent sample test. And metabolic pathways related to AML mainly included fatty acid metabolism, amino acid metabolism, energy metabolism and lipid metabolism. Meanwhile, biomarkers-targets-pathways-disease network was constructed, 75 biomarker targets and 122 disease targets were identified. Furthermore, 30 pathways were predicted, some of which were consistent with these in metabolomics. This is the first time that metabolomics and network pharmacology approach have been combined to investigate the pathogenesis and therapeutic targets of AML. ALDH, CYP2E1 and CYP3A4 were potential therapeutic targets for AML, which provide available way to elucidate the pathogenesis and treatment of AML.

(2R,3S)-Dihydroxybutanoic Acid Synthesis as a Novel Metabolic Function of Mutant Isocitrate Dehydrogenase 1 and 2 in Acute Myeloid Leukemia

Simple Summary

Acute myeloid leukemia (AML) is one of several cancers where cancer proliferation occurs under the influence of an aberrant metabolite known as an oncometabolite produced by a mutated enzyme in the cancer cell. In AML, mutant isocitrate dehydrogenases produce the oncometabolite 2-hydroxyglutarate. We screened AML patients with and without mutant isocitrate dehydrogenases by using a technique known as metabolomics, which measures many different metabolites in patient plasma. It was observed that another metabolite, 2,3-dihydroxybutyrate, was produced in larger amounts in patients with mutated isocitrate dehydrogenase and correlated strongly with 2-hydroxyglutarate levels. Moreover, 2,3-dihydroxybutyrate was a better indicator of the presence of mutated isocitrate dehydrogenase in the cancer than the known oncometabolite 2-hydroxyglutarate. These findings may lead to the characterization of 2,3-dihydroxybutyrate as a novel oncometabolite in AML, which would bring a fuller understanding of the etiology of this disease and offer opportunities for the development of novel therapeutic agents.

Abstract

Acute myeloid leukemia (AML) frequently harbors mutations in isocitrate 1 (IDH1) and 2 (IDH2) genes, leading to the formation of the oncometabolite (2R)-hydroxyglutaric acid (2R-HG) with epigenetic consequences for AML proliferation and differentiation. To investigate if broad metabolic aberrations may result from IDH1 and IDH2 mutations in AML, plasma metabolomics was conducted by gas chromatography–mass spectrometry (GC–MS) on 51 AML patients, 29 IDH1/2 wild-type (WT), 9 with IDH1R132, 12 with IDH2R140 and one with IDH2R172 mutations. Distinct metabolic differences were observed between IDH1/2 WT, IDH1R132 and IDH2R140 patients that comprised 22 plasma metabolites that were mainly amino acids. Only two plasma metabolites were statistically significantly different (p < 0.0001) between both IDH1R132 and WT IDH1/2 and IDH2R140 and WT IDH1/2, specifically (2R)-hydroxyglutaric acid (2R-HG) and the threonine metabolite (2R,3S)-dihydroxybutanoic acid (2,3-DHBA). Moreover, 2R-HG correlated strongly (p < 0.0001) with 2,3-DHBA in plasma. One WT patient was discovered to have a D-2-hydroxyglutarate dehydrogenase (D2HGDH) A426T inactivating mutation but this had little influence on 2R-HG and 2,3-DHBA plasma concentrations. Expression of transporter genes SLC16A1 and SLC16A3 displayed a weak correlation with 2R-HG but not 2,3-DHBA plasma concentrations. Receiver operating characteristic (ROC) analysis demonstrated that 2,3-DHBA was a better biomarker for IDH mutation than 2R-HG (Area under the curve (AUC) 0.861; p < 0.0001; 80% specificity; 87.3% sensitivity). It was concluded that 2,3-DHBA and 2R-HG are both formed by mutant IDH1R132, IDH2R140 and IDH2R172, suggesting a potential role of 2,3-DHBA in AML pathogenesis.

Metabolomics in acute myeloid leukemia

Acute myeloid leukemia (AML) is a complex, heterogenous hematological malignancy caused by mutations in myeloid differentiation and proliferation. Response to therapy and long-term outcomes vary widely based on chromosomal and molecular aberrations. Many platforms have been used to characterize and stratify AML. Metabolomics, the global profiling of small molecules in a biological sample, has emerged in the last decade as an important tool for studying the metabolic dependency of cancer cells. Metabolic reprogramming is not only an important manifestation of AML but clinically relevant for diagnosis, risk stratification and targeted drug development. In this review, we discuss notable metabolic studies of the last decade and their application to novel therapies.

Metabolomics analysis identifies lysine and taurine as candidate prognostic biomarkers for AML-M2 patients

There is an ongoing search for potential biomarkers for acute myeloid leukemia (AML) patients using metabolic analysis. However, only few studies to date have focused on bone marrow samples or a specific subtype of AML. In the present study, we used gas chromatography time-of-flight mass spectrometry of plasma and bone marrow supernatants to compare the metabolic characteristics of patients with AML with maturation (AML-M2). This approach identified significantly altered metabolites. We next performed pathway analysis and determined relative mRNA expression by qRT-PCR. Our results show that lysine, methionine and serine were significantly decreased in AML-M2 patients compared with healthy control. Moreover, plasma abundance of lysine was negatively associated with patients' risk stratification. Taurine had higher plasma abundance in AML-M2 patients and plasma level of taurine was positively related with AML-M2 risk status, while the expression level of taurine transporter showed a negative correlation. Receiver operating characteristic curve analysis showed these four metabolites had high diagnostic value with lysine showing the highest sensitivity and specificity. These results suggest that plasma abundances of lysine and taurine may serve as potential metabolic biomarkers for the prognosis of patients with AML-M2.

Mass spectrometry based proteomics and metabolomics in personalized oncology

Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.

Metabolomic profiling identifies pathways associated with minimal residual disease in childhood acute lymphoblastic leukaemia

Background

End-induction minimal residual disease (MRD) is the strongest predictor of relapse in paediatric acute lymphoblastic leukaemia (ALL), but an understanding of the biological pathways underlying early treatment response remains elusive. We hypothesized that metabolomic profiling of diagnostic bone marrow plasma could provide insights into the underlying biology of early treatment response and inform treatment strategies for high-risk patients.

Methods

We performed global metabolomic profiling of samples from discovery (N = 93) and replication (N = 62) cohorts treated at Texas Children's Hospital. Next, we tested the cytotoxicity of drugs targeting central carbon metabolism in cell lines and patient-derived xenograft (PDX) cells.

Findings

Metabolite set enrichment analysis identified altered central carbon and amino acid metabolism in MRD-positive patients from both cohorts at a 5% false discovery rate. Metabolites from these pathways were used as inputs for unsupervised hierarchical clustering. Two distinct clusters were identified, which were independently associated with MRD after adjustment for immunophenotype, cytogenetics, and NCI risk group. Three nicotinamide phosphoribosyltransferase (NAMPT) inhibitors, which reduce glycolytic/TCA cycle activities, demonstrated nanomolar-range cytotoxicity in B- and T-ALL cell lines and PDX cells.

Interpretation

This study provides new insights into the role of central carbon metabolism in early treatment response and as a potential targetable pathway in high-risk disease.

Funding

American Society of Hematology; Baylor College of Medicine Department of Paediatrics; Cancer Prevention and Research Institute of Texas; the Lynch family; St. Baldrick's Foundation with support from the Micaela's Army Foundation; United States National Institutes of Health.

Rationale for Targeting Deregulated Metabolic Pathways as a Therapeutic Strategy in Acute Myeloid Leukemia

Metabolic reprogramming is a common cancer cell phenotype as it sustains growth and proliferation. Targeting metabolic activities offers a wide range of therapeutic possibilities which are applicable to acute myeloid leukemia (AML). Indeed, in addition to the IDH1/2-mutated AML model which established the proof-of-concept for specifically targeting metabolic adaptations in AML, several recent reports have expanded the scope of such strategies in these diseases. This review highlights recent findings on metabolic deregulation in AML and summarizes their implications in leukemogenesis.

Metabolomics of neonatal blood spots reveal distinct phenotypes of pediatric acute lymphoblastic leukemia and potential effects of early-life nutrition

Early-life exposures are believed to influence the incidence of pediatric acute lymphoblastic leukemia (ALL). Archived neonatal blood spots (NBS), collected within the first days of life, offer a means to investigate small molecules that reflect early-life exposures. Using untargeted metabolomics, we compared abundances of small-molecule features in extracts of NBS punches from 332 children that later developed ALL and 324 healthy controls. Subjects were stratified by early (1-5 y) and late (6-14 y) diagnosis. Mutually-exclusive sets of metabolic features - representing putative lipids and fatty acids - were associated with ALL, including 9 and 19 metabolites in the early- and late-diagnosis groups, respectively. In the late-diagnosis group, a prominent cluster of features with apparent 18:2 fatty-acid chains suggested that newborn exposure to the essential nutrient, linoleic acid, increased ALL risk. Interestingly, abundances of these putative 18:2 lipids were greater in infants who were fed formula rather than breast milk (colostrum) and increased with the mother's pre-pregnancy body mass index. These results suggest possible etiologic roles of newborn nutrition in late-diagnosis ALL.

Mathematical models of amino acid panel for assisting diagnosis of children acute leukemia

BACKGROUND

The altered concentrations of amino acids were found in the bone marrow or blood of leukemia patients. Metabolomics technology combining mathematical model of biomarkers could be used for assisting the diagnosis of pediatric acute leukemia (AL).

METHODS

The concentrations of 17 amino acids was measured by targeted liquid chromatograph-tandem mass spectrometry in periphery blood collected using dried blood spots. After evaluation, the mathematical models were further evaluated by prospective clinical validation cohort for AL diagnosis.

RESULTS

The concentrations of 13 in 17 amino acids were statistically different between the periphery blood dried serum dots measured by targeted LC-MS/MS. The receiver operating characteristic analysis for the models of amino acid panel showed that the area under curve for AL diagnosis were 0.848, 0.834 and 0.856 by SVM, RF and XGBoost. The Kappa values in further prospectively evaluated clinical cohort were 0.697, 0.703 and 0.789 (p > 0.05) respectively, and the accuracies for the models were 84.86%, 85.20% and 89.46% respectively with further clinical validation.

CONCLUSIONS

The established mathematical model is a faster, cheaper and more convenient way than conventional methods, and no significant difference on the effect of diagnosis comparing with conventional methods. The mathematical model can be clinically useful for assisting pediatric AL diagnosis.

Identification of novel serum biomarker for the detection of acute myeloid leukemia based on liquid chromatography-mass spectrometry

Acute myeloid leukemia (AML) is a life-threatening hematological malignancy. Traditional diagnosis of AML depends on invasive bone marrow biopsies. To recognize the metabolic characteristics related with AML and search for early non-invasive biomarkers of AML, in this work we applied ultra-high performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOFMS)-based metabolomoc method to profile serum metabolites from 55 de novo AML patients and 45 age- and gender-matched healthy subjects and to screen and validate AML biomarkers. We observed AML-related metabolic differences mainly involved in alanine, aspartate and glutamate metabolism; d-Glutamine and d-glutamate metabolism; tryptophan metabolism; taurine and hypotaurine metabolism; and phenylalanine metabolism as well as fatty acid metabolism. A serum metabolite biomarker panel consisting of glutamic acid, kynurenine and oleic acid was defined and validated based on binary logistic regression analysis and receiver operating characteristic curves (ROC) analysis, yielding an area under the ROC curve (AUC) of 0.981 with 0.975 sensitivity and 0.933 specificity in the discovery set and an AUC of 0.973 with 0.933 sensitivity and 0.933 specificity in the validation set. This work demonstrated the UHPLC- MS-based metabolomics as a low invasive potential tool for the detection of AML, and this composite serum metabolite panel exhibited good diagnostic performance for AML in this case-control study and deserved further validation in a large-scale clinical trial. The identified metabolic pathways were also potentially worthy of further studying the pathogenesis of AML.

Alteration of Serum Free Fatty Acids are Indicators for Progression of Pre-leukaemia Diseases to Leukaemia

Acute Leukaemia (AL) is a neoplasm of WBCs (white blood cells). Being an important class of metabolites, alteration in free fatty acids (FFAs) levels play a key role in cancer development and progression. As they involve in cell signaling, maintain membrane integrity, regulate homeostasis and effect cell and tissue functions. Considering this fact, a comprehensive analysis of FFAs was conducted to monitor their alteration in AL, pre-leukaemic diseases and healthy control. Fifteen FFAs were analyzed in 179 serum samples of myelodysplastic syndrome (MDS), aplastic anemia (APA), acute lymphoblastic leukaemia (ALL), acute myeloid leukaemia (AML) and healthy control using gas chromatography-multiple reaction monitoring-mass spectrometry (GC-MRM-MS). A multivariate statistical method of random forest (RF) was employed for chemometric analysis. Serum level of two FFAs including C18:0 and C14:0 were found discriminative among all five groups, and between ALL and AML, respectively. Moreover, C14:0 was identified as differentiated FFAs for systematic progression of pre-leukaemic conditions towards AML. C16:0 came as discriminated FFAs between APA and MDS/AML. Over all it was identified that FFAs profile not only become altered in leukaemia but also in pre-leukaemic diseases.

Endogenous volatile organic compounds in acute myeloid leukemia: origins and potential clinical applications

Not unlike many cancer types, acute myeloid leukemia (AML) exhibits many metabolic changes and reprogramming, causing changes in lipid metabolism. Some of the distinct molecular abnormalities associated with AML also modify the metabolic changes. Both processes result in changes in the production of endogenous volatile organic compounds (VOCs). The increasing availability of highly sensitive methods for detecting trace chemicals provides the opportunity to investigate the role of patient-specific VOC finger-prints as biomarkers for detecting early relapse or minimal residual disease in AML. Since VOC production is reliant on metabolic activities, when combined with currently available methods, VOC analysis may identify within a group of patients with flow cytometric or molecular evidence of residual disease those most at risk for disease relapse.

Pharmacometabolomics identifies dodecanamide and leukotriene B4 dimethylamide as a predictor of chemosensitivity for patients with acute myeloid leukemia treated with cytarabine and anthracycline

Clinical responses to standard cytarabine plus anthracycline regimen in acute myeloid leukemia (AML) are heterogeneous and there is an unmet need for biological predictors of response to this regimen. Here, we applied a pharmacometabolomics approach to identify potential biomarkers associated with response to this regimen in AML patients. Based on clinical response the enrolled 82 patients were subdivided into two groups: complete remission(CR) responders (n=42) and non-responders (n=40). Metabolic profiles of pre-treatment serum from patients were analyzed by ultra-high performance liquid chromatography coupled with mass spectrometry and the metabolic differences between the two groups were investigated by multivariate statistical analysis. A metabolite panel containing dodecanamide and leukotriene B4 dimethylamide (LTB4-DMA) had the power capacity to differentiate the two groups of patients, yielding an area under the receiver operating characteristic of 0.945 (85.2% sensitivity and 88.9% specificity) in the training set and 0.944(84.6% sensitivity and 80.0% specificity) in the test set. The patients with high levels of LTB4-DMA and low amounts of dodecanamide had good sensitivity to chemotherapeutic agents. The possible reasons were that dodecanamide was produced by leukemic cells as a lipolytic factor to fuel their growth with a potential role in drug resistance and LTB4-DMA was a potent leukotriene B4 antagonist that could be applicable in the treatment of AML. These preliminary results demonstrates the feasibility of relating chemotherapy responses with pre-treatment metabolic profiles of AML patients, and pharmacometabolomics may be a useful tool to select patients that are more likely to benefit from cytarabine plus anthracycline chemotherapy.

Emerging role and recent applications of metabolomics biomarkers in obesity disease research

Metabolomics is a promising approach for the identification of metabolites which serve for early diagnosis, prediction of therapeutic response and prognosis of disease.