Metabolomics for mitochondrial and cancer studies

Mitofusin-2 Regulates Platelet Mitochondria and Function

BACKGROUND

Single-nucleotide polymorphisms linked with the rs1474868 T allele (MFN2 [mitofusin-2] T/T) in the human mitochondrial fusion protein MFN2 gene are associated with reduced platelet MFN2 RNA expression and platelet counts. This study investigates the impact of MFN2 on megakaryocyte and platelet biology.

METHODS

Mice with megakaryocyte/platelet deletion of Mfn2 (Mfn2-/- [Mfn2 conditional knockout]) were generated using Pf4-Cre crossed with floxed Mfn2 mice. Human megakaryocytes were generated from cord blood and platelets isolated from healthy subjects genotyped for rs1474868. Ex vivo approaches assessed mitochondrial morphology, function, and platelet activation responses. In vivo measurements included endogenous/transfused platelet life span, tail bleed time, transient middle cerebral artery occlusion, and pulmonary vascular permeability/hemorrhage following lipopolysaccharide-induced acute lung injury.

RESULTS

Mitochondria was more fragmented in megakaryocytes derived from Mfn2-/- mice and from human cord blood with MFN2 T/T genotype compared with control megakaryocytes. Human resting platelets of MFN2 T/T genotype had reduced MFN2 protein, diminished mitochondrial membrane potential, and an increased rate of phosphatidylserine exposure during ex vivo culture. Platelet counts and platelet life span were reduced in Mfn2-/- mice accompanied by an increased rate of phosphatidylserine exposure in resting platelets, especially aged platelets, during ex vivo culture. Mfn2-/- also decreased platelet mitochondrial membrane potential (basal) and activated mitochondrial oxygen consumption rate, reactive oxygen species generation, calcium flux, platelet-neutrophil aggregate formation, and phosphatidylserine exposure following dual agonist activation. Ultimately, Mfn2-/- mice showed prolonged tail bleed times, decreased ischemic stroke infarct size after cerebral ischemia-reperfusion, and exacerbated pulmonary inflammatory hemorrhage following lipopolysaccharide-induced acute lung injury. Analysis of MFN2 SNPs in the iSPAAR study (Identification of SNPs Predisposing to Altered ALI Risk) identified a significant association between MFN2 and 28-day mortality in patients with acute respiratory distress syndrome.

CONCLUSIONS

Mfn2 preserves mitochondrial phenotypes in megakaryocytes and platelets and influences platelet life span, function, and outcomes of stroke and lung injury.

Metabolic reprogramming enables the auxiliary diagnosis of breast cancer by automated breast volume scanner

Breast cancer is the leading cause of female cancer-related deaths worldwide. New technologies with enhanced sensitivity and specificity for early diagnosis and monitoring of postoperative recurrence are in critical demand. Automatic breast full volume scanning system (ABVS) is an emerging technology used as an alternative imaging method for breast cancer screening. Despite its improved detection rate of malignant tumors, ABVS cannot accurately stage breast cancer preoperatively in 30–40% of cases. As a major hallmark of breast cancer, the characteristic metabolic reprogramming may provide potential biomarkers as an auxiliary method for ABVS.

Objective

The objective of this study was to identify differential metabolomic signatures between benign and malignant breast tumors and among different subtypes of breast cancer patients based on untargeted metabolomics and improve breast cancer detection rate by combining key metabolites and ABVS.

Methods

Untargeted metabolomics approach was used to profile serum samples from 70 patients with different subtypes of breast cancer and benign breast tumor to determine specific metabolomic profiles through univariate and multivariate statistical data analysis.

Results

Metabolic profiles correctly distinguished benign and malignant breast tumors patients, and a total of 791 metabolites were identified. There were 54 different metabolites between benign and malignant breast tumors and 17 different metabolites between invasive and non-invasive breast cancer. Notably, the missed diagnosis rate of ABVS could be reduced by differential metabolite analysis. Moreover, the diagnostic performance analyses of combined metabolites (pelargonic acid, N-acetylasparagine, and cysteine-S-sulfate) with ABVS performance gave a ROC area under the curve of 0.967 (95% CI: 0.926, 0.993).

Conclusions

Our study identified metabolic features both in benign and malignant breast tumors and in invasive and non-invasive breast cancer. Combined ultrasound ABVS and a panel of differential serum metabolites could further improve the accuracy of preoperative diagnosis of breast cancer and guide surgical therapy.

Blood biomarkers for assessment of mitochondrial dysfunction: An expert review

Although mitochondrial dysfunction is the known cause of primary mitochondrial disease, mitochondrial dysfunction is often difficult to measure and prove, especially when biopsies of affected tissue are not available. In order to identify blood biomarkers of mitochondrial dysfunction, we reviewed studies that measured blood biomarkers in genetically, clinically or biochemically confirmed primary mitochondrial disease patients. In this way, we were certain that there was an underlying mitochondrial dysfunction which could validate the biomarker. We found biomarkers of three classes: 1) functional markers measured in blood cells, 2) biochemical markers of serum/plasma and 3) DNA markers. While none of the reviewed single biomarkers may perfectly reveal all underlying mitochondrial dysfunction, combining biomarkers that cover different aspects of mitochondrial impairment probably is a good strategy. This biomarker panel may assist in the diagnosis of primary mitochondrial disease patients. As mitochondrial dysfunction may also play a significant role in the pathophysiology of multifactorial disorders such as Alzheimer's disease and glaucoma, the panel may serve to assess mitochondrial dysfunction in complex multifactorial diseases as well and enable selection of patients who could benefit from therapies targeting mitochondria.

Sub-Cellular Metabolomics Contributes Mitochondria-Specific Metabolic Insights to a Mouse Model of Leigh Syndrome

Direct injury of mitochondrial respiratory chain (RC) complex I by Ndufs4 subunit mutations results in complex I deficiency (CID) and a progressive encephalomyopathy, known as Leigh syndrome. While mitochondrial, cytosolic and multi-organelle pathways are known to be involved in the neuromuscular LS pathogenesis, compartment-specific metabolomics has, to date, not been applied to murine models of CID. We thus hypothesized that sub-cellular metabolomics would be able to contribute organelle-specific insights to known Ndufs4 metabolic perturbations. To that end, whole brains and skeletal muscle from late-stage Ndufs4 mice and age/sex-matched controls were harvested for mitochondrial and cytosolic isolation. Untargeted ¹H-NMR and semi-targeted LC-MS/MS metabolomics was applied to the resulting cell fractions, whereafter important variables (VIPs) were selected by univariate statistics. A predominant increase in multiple targeted amino acids was observed in whole-brain samples, with a more prominent effect at the mitochondrial level. Similar pathways were implicated in the muscle tissue, showing a greater depletion of core metabolites with a compartment-specific distribution, however. The altered metabolites expectedly implicate altered redox homeostasis, alternate RC fueling, one-carbon metabolism, urea cycling and dysregulated proteostasis to different degrees in the analyzed tissues. A first application of EDTA-chelated magnesium and calcium measurement by NMR also revealed tissue- and compartment-specific alterations, implicating stress response-related calcium redistribution between neural cell compartments, as well as whole-cell muscle magnesium depletion. Altogether, these results confirm the ability of compartment-specific metabolomics to capture known alterations related to Ndufs4 KO and CID while proving its worth in elucidating metabolic compartmentalization in said pathways that went undetected in the diluted whole-cell samples previously studied.

Mass Spectrometry-Based Targeted Serum Monomethylated Ribonucleosides Profiling for Early Detection of Breast Cancer

RNA methylation plays a significant regulatory role in various of physiological activities and it has gradually become a hotspot of epigenetics in the past decade. 2′-O-methyladenosine (Am), 2′-O-methylguanosine (Gm), 2′-O-methylcytidine (Cm), 2′-O-methyluridine (Um), N⁶-methyladenosine (m⁶A), N¹-methylguanosine (m¹G), 5-methylcytidine (m⁵C), and 5-methyluridine (m⁵U) are representative 2′-O-methylation and base-methylation modified epigenetic marks of RNA. Abnormal levels of these ribonucleosides were found to be related to various diseases including cancer. Serum is an important source of biofluid for the discovery of biomarkers, and novel tumor biomarkers can be explored by measuring these ribonucleoside modifications in human serum. Herein, we developed and applied a hydrophilic interaction liquid chromatography tandem mass spectrometry (HILIC-MS/MS) method to determine the content of monomethylated ribonucleosides in human serum. The developed method enabled sensitive and accurate determination of these monomethylated ribonucleosides. By applying this robust method, we demonstrated the presence of Gm and Um in human serum for the first time, and we successfully quantified m⁶A, Gm, m¹G, Cm, Um and m⁵U in serum samples collected from 61 patients with breast cancer and 69 healthy controls. We discovered that the levels of Gm, m¹G, Cm, Um and m⁵U in serum were all significantly decreased in breast cancer patients whereas m⁶A was increased. We performed receiver operating characteristic (ROC) curve analysis, and obtained highest area under curve (AUC) value when combining these six monomethylated ribonucleosides together. These results suggest that m⁶A, Gm, m¹G, Cm, Um and m⁵U might have great potential to be novel biomarkers for detection of breast cancer in the early stage. In addition, this study may stimulate future investigations about the regulatory roles of monomethylated ribonucleosides on the initiation and development of breast cancer.

The Inside-Out of End-Stage Liver Disease: Hepatocytes are the Keystone

Chronic liver injury results in cirrhosis and end-stage liver disease (ESLD) which represents a leading cause of death worldwide, affecting people in their most productive years of life. Medical therapy can extend life, but the only definitive treatment is liver transplantation (LT). However, LT remains limited by access to quality donor organs and suboptimal long-term outcomes. The degeneration from healthy-functioning livers to cirrhosis and ESLD involves a dynamic process of hepatocyte damage, diminished hepatic function, and adaptation. However, the mechanisms responsible for deterioration of hepatocyte function and ultimately hepatic failure in man are poorly understood. We review the current understanding of cirrhosis and ESLD as a dynamic process and outline the current mechanisms associated with the development of hepatic failure from the clinical manifestations to energy adaptations, regeneration, and regulation of nuclear transcription factors. A new generation of therapeutics could target stabilization of hepatocyte differentiation and function to avoid the need for transplantation in patients with cirrhosis and ESLD.

Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics

Prostate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.

Isolation and Metabolic Assessment of Cancer Cell Mitochondria

Mitochondrial metabolism plays an essential role in various biological processes of cancer cells. Herein, we established an experimental procedure for the metabolic assessment of mitochondria in cancer cells. We examined procedures for mitochondrial isolation coupled with various mitochondrial extraction buffers in three major cancer cell lines (PANC1, A549, and MDA-MB-231) and identified a potentially optimal and generalized approach. The purity of the mitochondrial fraction isolated by the selected protocol was verified using specific protein markers of cellular components, and the ultrastructure of the isolated mitochondria was also analyzed by transmission electron microscopy. The isolation procedure, involving a bead beater for cell lysis, a modified sucrose buffer, and differential centrifugation, appeared to be a suitable method for the extraction of mitochondria from cancer cells. Electron micrographs indicated an intact two-layer membrane and inner structures of mitochondria isolated by this procedure. Metabolomic and lipidomic analyses were conducted to examine the metabolic phenotypes of the mitochondria-enriched fractions and associated bulk cancer cells. A total of 44 metabolites, including malate and succinate, occurred at significantly higher levels in the mitochondrial fractions, whereas 51 metabolites, including citrate, oxaloacetate, and fumarate of the Krebs cycle and the oncometabolites glutamine and glutamate, were reduced in mitochondria compared to that in the corresponding bulk cells of PANC1. Similar patterns were observed in mitochondria and bulk cells of MDA-MB-231 and A549 cell lines. A clear difference between the lipid profiles of bulk PANC1, MDA-MB-231, and A549 and corresponding mitochondrial fractions of these cell lines was detected by principal component analysis. In conclusion, we developed an experimental procedure for a large-scale metabolic assessment for suborganelle metabolic profiling and multiple omics data integration in cancer cells with broad applications.

Study on Urinary Candidate Metabolome for the Early Detection of Breast Cancer

A metabolomic study for determination of certain urinary metabolomes, 1-methyladenosine (1-MA), 1-methylguanosine (1-MG), and 8-hydroxy-2' deoxyguanosine (8-OHdG) in urine specimens of breast cancer patients. The accuracy of these metabolites and their combined score with cancer antigen 15-3 (CA15-3) was developed to improve the early detection of breast cancer. This study recruited 52 healthy individuals, 47 benign breast tumors, and 167 malignant breast tumor patients. Urine samples were handled to adjust the creatinine concentrations to 8 mg/dL (0.7 mmol/L) and analyzed using GC-MS to detect and quantify the selected urinary metabolomes in urine samples of all participants. The accuracy of individual urinary metabolomes and their combination with CA15-3 were evaluated using multivariate statistical analysis. The cutoff value of CA15-3 was 32.5 U/mL. Cutoff values of 1-MA, 1-MG, and 8-OHdG were 2.19, 2.1, and 7.3 µmol/mmol creatinine, respectively. The concentrations of 1-MA, 1-MG, and 8-OHdG were significantly higher in breast cancer patients, especially in the early-stage. The combination of three urinary metabolomes with CA15-3 improves the diagnostic sensitivity of breast cancer. For the combined score, the area under the curve (AUC) value of combined score ranged from 0.820 to 0.950, with high accuracy, ranged from 77.0 to 95.5%. The most significant AUC (0.973), sensitivity (90.1%), selectivity (94.0%) was recorded at comparing the healthy control with the early-stage of malignant breast cancer. In conclusion, the combination of three urinary metabolomes with serum CA15-3 improves the diagnostic sensitivity of breast cancer.

Novel mitochondrial and cytosolic purification pipeline for compartment-specific metabolomics in mammalian disease model tissues

INTRODUCTION

Mitochondria represent an important milieu for studying the pathogenesis of several major diseases. The need for organelle-level metabolic resolution exists, as mitochondrial/cytosolic metabolites are often diluted beyond detection limits in complex samples. Compartment-specific studies are still hindered by the lack of efficient, cost-effective fractioning methods-applicable to laboratories of all financial/analytical standing.

OBJECTIVES

We established a novel mitochondrial/cytosolic purification pipeline for complimentary GC-TOF-MS and ¹H-NMR metabolomics using robust, commercially available fractionation strategies.

METHODS

Magnetic based mitochondria isolation kits (MACS) were adapted for this purpose, accompanied by cytosolic filtering. Yield was assessed through the percentage recovery of citrate synthase (CS; a mitochondrial marker), purity by immunoblotting against compartment-specific proteins and integrity interrogated through the respiratory coupling ratio (RCR). The effects of the kit-based buffers on MS/NMR analyses of pure metabolite standards were evaluated. Finally, biological applicability to mammalian disease models was shown using Ndufs4 mouse brain tissue.

RESULTS

With minor modifications, MACS produced around 60% more mitochondria compared to a differential centrifugation method. Less than 15% of lysosomal LAMP-2 protein was found in the MACS isolates, confirming relative purity-while RCR's above 6 indicate sufficient mitochondrial integrity. The filtering approach effectively depleted mitochondria from the cytosolic fraction, as indicated by negligible Hsp60 and CS levels. Our GC-MS pilot yielded 60-70 features per fraction, while NMR analyses could quantify 6-10 of the most abundant compounds in each fraction.

CONCLUSION

This study provides a simple and flexible solution for mitochondrial and cytosolic metabolomics in animal model tissues, towards large-scale application of such methodologies in disease research.

Preclinical studies on metal based anticancer drugs as enabled by integrated metallomics and metabolomics

Resistance development is a major obstacle for platinum-based chemotherapy, with the anticancer drug oxaliplatin being no exception. Acquired resistance is often associated with altered drug accumulation. In this work we introduce a novel -omics workflow enabling the parallel study of platinum drug uptake and its distribution between nucleus/protein and small molecule fraction along with metabolic changes after different treatment time points. This integrated metallomics/metabolomics approach is facilitated by a tailored sample preparation workflow suitable for preclinical studies on adherent cancer cell models. Inductively coupled plasma mass spectrometry monitors the platinum drug, while the metabolomics tool-set is provided by hydrophilic interaction liquid chromatography combined with high-resolution Orbitrap mass spectrometry. The implemented method covers biochemical key pathways of cancer cell metabolism as shown by a panel of >130 metabolite standards. Furthermore, the addition of yeast-based 13C-enriched internal standards upon extraction enabled a novel targeted/untargeted analysis strategy. In this study we used our method to compare an oxaliplatin sensitive human colon cancer cell line (HCT116) and its corresponding resistant model. In the acquired oxaliplatin resistant cells distinct differences in oxaliplatin accumulation correlated with differences in metabolomic rearrangements. Using this multi-omics approach for platinum-treated samples facilitates the generation of novel hypotheses regarding the susceptibility and resistance towards oxaliplatin.

Development of a gas chromatography-mass spectrometry method for breast cancer diagnosis based on nucleoside metabolomes 1-methyl adenosine, 1-methylguanosine and 8-hydroxy-2'-deoxyguanosine

Metabolomes are small molecule metabolites (<1000 Da) produced by cellular processes. Metabolomes are close counterparts to the genome, transcriptome and proteome. The aim of this study was to develop a method to detect and quantify candidate nucleoside metabolomes 1-methyl adenosine (1-MA), 1-methylguanosine (1-MG) and 8-hydroxy-2'-deoxyguanosine (8-OHdG) in the urine of patients with breast cancer using gas chromatography-mass spectrometry (GC-MS). The method was applied to urine specimens from patients with breast cancer (n = 56) and benign breast tumors (n = 22), as well as from healthy females (n = 20). The relative standard deviations of precision and repeatability analysis were <10%, and recoveries ranged from 88.5 to 105.6%. Limits of detection were 0.014, 0.012, and 0.018 mg/L for 1-MA, 1-MG and 8-OHdG, respectively. The lower limits of quantitation were 0.056, 0.048 and 0.072 mg/L, respectively. There were significant differences in concentrations of candidate metabolomes between patients with cancer and the healthy individuals, especially for those in the early stages of the disease (p < 0.001). No significant differences were observed between the benign and healthy groups. In conclusion, a reliable GC-MS method for the detection and quantification of 1-MA, 1-MG, and 8-OHdG metabolomes in urine has been developed.

Emerging Therapies for Acute Myelogenus Leukemia Patients Targeting Apoptosis and Mitochondrial Metabolism

Acute Myelogenous Leukemia (AML) is a malignant disease of the hematopoietic cells, characterized by impaired differentiation and uncontrolled clonal expansion of myeloid progenitors/precursors, resulting in bone marrow failure and impaired normal hematopoiesis. AML comprises a heterogeneous group of malignancies, characterized by a combination of different somatic genetic abnormalities, some of which act as events driving leukemic development. Studies carried out in the last years have shown that AML cells invariably have abnormalities in one or more apoptotic pathways and have identified some components of the apoptotic pathway that can be targeted by specific drugs. Clinical results deriving from studies using B-cell lymphoma 2 (BCL-2) inhibitors in combination with standard AML agents, such as azacytidine, decitabine, low-dose cytarabine, provided promising results and strongly support the use of these agents in the treatment of AML patients, particularly of elderly patients. TNF-related apoptosis-inducing ligand (TRAIL) and its receptors are frequently deregulated in AML patients and their targeting may represent a promising strategy for development of new treatments. Altered mitochondrial metabolism is a common feature of AML cells, as supported through the discovery of mutations in the isocitrate dehydrogenase gene and in mitochondrial electron transport chain and of numerous abnormalities of oxidative metabolism existing in AML subgroups. Overall, these observations strongly support the view that the targeting of mitochondrial apoptotic or metabolic machinery is an appealing new therapeutic perspective in AML.

Metabolomics Biomarkers for Detection of Colorectal Neoplasms: A Systematic Review

BACKGROUND

Several approaches have been suggested to be useful in the early detection of colorectal neoplasms. Since metabolites are closely related to the phenotype and are available from different human bio-fluids, metabolomics are candidates for non-invasive early detection of colorectal neoplasms.

OBJECTIVES

We aimed to summarize current knowledge on performance characteristics of metabolomics biomarkers that are potentially applicable in a screening setting for the early detection of colorectal neoplasms.

DESIGN

We conducted a systematic literature search in PubMed and Web of Science and searched for biomarkers for the early detection of colorectal neoplasms in easy-to-collect human bio-fluids. Information on study design and performance characteristics for diagnostic accuracy was extracted.

RESULTS

Finally, we included 41 studies in our analysis investigating biomarkers in different bio-fluids (blood, urine, and feces). Although single metabolites mostly had limited ability to distinguish people with and without colorectal neoplasms, promising results were reported for metabolite panels, especially amino acid panels in blood samples, as well as nucleosides in urine samples in several studies. However, validation of the results is limited.

CONCLUSIONS

Panels of metabolites consisting of amino acids in blood and nucleosides in urinary samples might be useful biomarkers for early detection of advanced colorectal neoplasms. However, to make metabolomic biomarkers clinically applicable, future research in larger studies and external validation of the results is required.

Metabolomic and BH3 profiling of esophageal cancers: novel assessment methods for precision therapy

BACKGROUND

Esophageal cancers accounted for nearly 16,000 deaths in 2016. The number of patients with esophageal cancers increases every year. Neoadjuvant chemoradiotherapy (nCRT) prior to esophagectomy is a standard treatment for esophageal cancers. The patients who have no residual tumor (pathological complete response (pCR)) at surgery are the most likely to experience long term survival. Accurately determining which patients will have a pCR will improve prognostic information for patients and families, confirm lack of response to nCRT, or avoid surgery if no residual tumor is present. Imaging, endoscopy, and liquid biomarkers have all failed to detect pCR without performing an esophagectomy.

METHODS

In this study, we are enrolling patients with esophageal adenocarcinoma and squamous cell carcinoma. Patients will undergo standard evaluation including CT scans, laboratory tests, endoscopy with biopsies, and evaluation by a thoracic surgeon. Tissue biopsy is required for enrollment that will be sent for BH3 profiling and metabolomics. Patients will be treated with standard nCRT followed by surgery. Patients with metastatic disease are not eligible. Surgery at the National Cancer Institute will be minimally-invasive robotic surgery. Patients will remain on study indefinitely with regular clinic visits and imaging tests.

DISCUSSION

The mitochondria are critically involved in the intrinsic pathway apoptosis. Bcl-2 homology domain 3 (BH3) profiling is a technique to measure a cell's susceptibility to apoptosis. BH3 profiling measures the relative interactions of proteins that induce or block apoptosis. The collective balance of these proteins determines whether a cell is near the threshold to undergo apoptosis. If the cell is near this threshold, then the tumor may be more likely to die when treated with nCRT. The mitochondria secrete metabolites that may be detectable as biomarkers. Metabolomics is a global assessment of all metabolite changes that has been performed for detection, monitoring, prognosis, and treatment response in cancers. Stratification of patients based on whether pCR occurs or not may elucidate metabolomic signatures that may be associated with response. We are asking whether BH3 profiling or a metabolomic signature will correlate with tumor death after nCRT for esophageal cancer.

TRIAL REGISTRATION

NCT03223662 ; Clinicaltrials.gov. July 21, 2017.

Tsumura-Suzuki obese diabetic mice-derived hepatic tumors closely resemble human hepatocellular carcinomas in metabolism-related genes expression and bile acid accumulation

BACKGROUND AND AIMS

Tsumura-Suzuki obese diabetic (TSOD) is a good model of metabolic syndrome showing typical lesions found in nonalcoholic fatty liver disease and nonalcoholic steatohepatitis, and develops spontaneous hepatic tumors with a high frequency. Majority of the developing tumors overexpress glutamine synthetase (GS), which is used as a marker of hepatocellular carcinoma (HCC). The aim of this study is to assess the status of expression of metabolism-related genes and the level of bile acids in the TSOD mice-derived tumors and to determine the association with metabolic dysregulation between human HCC and TSOD mice-derived tumors.

METHODS

GS-positive hepatic tumors or adjacent normal tissues from 71-week-old male TSOD mice were subjected to immunohistochemical staining, quantitative RT-PCR (qRT-PCR), quantitation of cholic acid and taurocholic acid.

RESULTS

We found that downregulation of the rate-limiting enzyme for betaine synthesis (BADH), at both mRNA and protein levels in GS-positive TSOD mice-derived tumors. Furthermore, the bile acid receptor FXR and the bile acid excretion pump BSEP (Abcb11) were found to be downregulated, whereas BAAT and Akr1c14, involved in primary bile acid synthesis and bile acid conjugation, were found to be upregulated at mRNA level in GS-positive TSOD mice-derived tumors. BAAT and Akr1c14 were also overexpressed at protein levels. Total cholic acid was found to be increased in GS-positive TSOD mice-derived tumors.

CONCLUSION

Our results strongly support the significance of TSOD mice as a model of spontaneously developing HCC.

A window into extreme longevity; the circulating metabolomic signature of the naked mole-rat, a mammal that shows negligible senescence

Mouse-sized naked mole-rats (Heterocephalus glaber), unlike other mammals, do not conform to Gompertzian laws of age-related mortality; adults show no age-related change in mortality risk. Moreover, we observe negligible hallmarks of aging with well-maintained physiological and molecular functions, commonly altered with age in other species. We questioned whether naked mole-rats, living an order of magnitude longer than laboratory mice, exhibit different plasma metabolite profiles, which could then highlight novel mechanisms or targets involved in disease and longevity. Using a comprehensive, unbiased metabolomics screen, we observe striking inter-species differences in amino acid, peptide, and lipid metabolites. Low circulating levels of specific amino acids, particularly those linked to the methionine pathway, resemble those observed during the fasting period at late torpor in hibernating ground squirrels and those seen in longer-lived methionine-restricted rats. These data also concur with metabolome reports on long-lived mutant mice, including the Ames dwarf mice and calorically restricted mice, as well as fruit flies, and even show similarities to circulating metabolite differences observed in young human adults when compared to older humans. During evolution, some of these beneficial nutrient/stress response pathways may have been positively selected in the naked mole-rat. These observations suggest that interventions that modify the aging metabolomic profile to a more youthful one may enable people to lead healthier and longer lives.

Recent advances in using mass spectrometry for mitochondrial metabolomics and lipidomics - A review

Metabolomics and lipidomics generally targets a huge number of intermediate and end products of cellular metabolism in body fluids, tissues, and cells etc. At present, mass spectrometry (MS) based metabolic or lipid profiling of routine biological specimens including the whole cells, tissues, plasma, serum and urine etc., can cover hundreds of metabolites or lipid species in one analysis, which has qualified deep elucidation of global metabolic and lipid networks. Mitochondria are important intracellular organelles and many critical biochemical reactions occur here, they provide building block for new cells, control redox balance, participate in apoptosis and behave as a signalling platform. Evidence suggests high prevalence of mitochondrial dysfunction occurs in a variety of cancers and other diseases, thus there is an urgent demand for investigating and clarifying mitochondrial metabolic and lipid alterations induced by diseases. Nevertheless, mitochondria contribute a small fraction to cellular contents, profiling of whole cell is probably unsuitable for monitoring alterations in mitochondria. Therefore, metabolomics and lipidomics analyses specially for mitochondria are necessary to understand disturbed metabolic and lipid pathways induced by environment and diseases. However, methods for comprehensively profiling metabolites and lipids in mitochondria have been limited at present. This review summarizes the current states and progress of MS-based mitochondrial metabolomics and lipidomics study. Details of mitochondrial isolation procedure, analytical methods and their applications are described. The challenges and opportunities are also given.

Metabolomic prediction of endometrial cancer

INTRODUCTION

Endometrial cancer (EC) is associated with metabolic disturbances including obesity, diabetes and metabolic syndrome. Identifying metabolite biomarkers for EC detection has a crucial role in reducing morbidity and mortality.

OBJECTIVE

To determine whether metabolomic based biomarkers can detect EC overall and early-stage EC.

METHODS

We performed NMR and mass spectrometry based metabolomic analyses of serum in EC cases versus controls. A total of 46 early-stage (FIGO stages I-II) and 10 late-stage (FIGO stages III-IV) EC cases constituted the study group. A total of 60 unaffected control samples were used. Patients and controls were divided randomly into a discovery group (n = 69) and an independent validation group (n = 47). Predictive algorithms based on biomarkers and demographic characteristics were generated using logistic regression analysis.

RESULTS

A total of 181 metabolites were evaluated. Extensive changes in metabolite levels were noted in the EC versus the control group. The combination of C14:2, phosphatidylcholine with acyl-alkyl residue sum C38:1 (PCae C38:1) and 3-hydroxybutyric acid had an area under the receiver operating characteristics curve (AUC) (95% CI) = 0.826 (0.706-0.946) and a sensitivity = 82.6%, and specificity = 70.8% for EC overall. For early EC prediction: BMI, C14:2 and PC ae C40:1 had an AUC (95% CI) = 0.819 (0.689-0.95) and a sensitivity = 72.2% and specificity = 79.2% in the validation group.

CONCLUSIONS

EC is characterized by significant perturbations in important cellular metabolites. Metabolites accurately detected early-stage EC cases and EC overall which could lead to the development of non-invasive biomarkers for earlier detection of EC and for monitoring disease recurrence.

Unravelling the complexity of signalling networks in cancer: A review of the increasing role for computational modelling

Cancer induction is a highly complex process involving hundreds of different inducers but whose eventual outcome is the same. Clearly, it is essential to understand how signalling pathways and networks generated by these inducers interact to regulate cell behaviour and create the cancer phenotype. While enormous strides have been made in identifying key networking profiles, the amount of data generated far exceeds our ability to understand how it all "fits together". The number of potential interactions is astronomically large and requires novel approaches and extreme computation methods to dissect them out. However, such methodologies have high intrinsic mathematical and conceptual content which is difficult to follow. This review explains how computation modelling is progressively finding solutions and also revealing unexpected and unpredictable nano-scale molecular behaviours extremely relevant to how signalling and networking are coherently integrated. It is divided into linked sections illustrated by numerous figures from the literature describing different approaches and offering visual portrayals of networking and major conceptual advances in the field. First, the problem of signalling complexity and data collection is illustrated for only a small selection of known oncogenes. Next, new concepts from biophysics, molecular behaviours, kinetics, organisation at the nano level and predictive models are presented. These areas include: visual representations of networking, Energy Landscapes and energy transfer/dissemination (entropy); diffusion, percolation; molecular crowding; protein allostery; quinary structure and fractal distributions; energy management, metabolism and re-examination of the Warburg effect. The importance of unravelling complex network interactions is then illustrated for some widely-used drugs in cancer therapy whose interactions are very extensive. Finally, use of computational modelling to develop micro- and nano- functional models ("bottom-up" research) is highlighted. The review concludes that computational modelling is an essential part of cancer research and is vital to understanding network formation and molecular behaviours that are associated with it. Its role is increasingly essential because it is unravelling the huge complexity of cancer induction otherwise unattainable by any other approach.

Application of metabolomics: Focus on the quantification of organic acids in healthy adults

Metabolomics, a 'budding' discipline, may accurately reflect a specific phenotype which is sensitive to genetic and epigenetic interactions. This rapidly evolving field in science has been proposed as a tool for the evaluation of the effects of epigenetic factors, such as nutrition, environment, drug and lifestyle on phenotype. Urine, being sterile, is easy to obtain and as it contains metabolized or non-metabolized products, is a favored study material in the field of metabolomics. Urine organic acids (OAs) reflect the activity of main metabolic pathways and have been used to assess health status, nutritional status, vitamin deficiencies and response to xenobiotics. To date, a limited number of studies have been performed which actually define reference OA values in a healthy population and as reference range for epigenetic influences, and not as a reference to congenital metabolic diseases. The aim of the present study was thus the determination of reference values (RVs) for urine OA in a healthy adult population. Targeted metabolomics analysis of 22 OAs in the urine of 122 healthy adults by gas chromatography-mass spectrometry, was conducted. Percentile distributions of the OA concentrations in urine, as a base for determining the RVs in the respective population sample, were used. No significant differences were detected between female and male individuals. These findings can facilitate the more sensitive determination of OAs in pathological conditions. Therefore, the findings of this study may contribute or add to the information already available on urine metabolite databases, and may thus promote the use of targeted metabolomics for the evaluation of OAs in a clinical setting and for pathophysiological evaluation. However, further studies with well-defined patients groups exhibiting specific symptoms or diseases are warranted in order to discern between normal and pathological values.

Correlation-Based Network Generation, Visualization, and Analysis as a Powerful Tool in Biological Studies: A Case Study in Cancer Cell Metabolism

In the last decade vast data sets are being generated in biological and medical studies. The challenge lies in their summary, complexity reduction, and interpretation. Correlation-based networks and graph-theory based properties of this type of networks can be successfully used during this process. However, the procedure has its pitfalls and requires specific knowledge that often lays beyond classical biology and includes many computational tools and software. Here we introduce one of a series of methods for correlation-based network generation and analysis using freely available software. The pipeline allows the user to control each step of the network generation and provides flexibility in selection of correlation methods and thresholds. The pipeline was implemented on published metabolomics data of a population of human breast carcinoma cell lines MDA-MB-231 under two conditions: normal and hypoxia. The analysis revealed significant differences between the metabolic networks in response to the tested conditions. The network under hypoxia had 1.7 times more significant correlations between metabolites, compared to normal conditions. Unique metabolic interactions were identified which could lead to the identification of improved markers or aid in elucidating the mechanism of regulation between distantly related metabolites induced by the cancer growth.

HSulf-1 deficiency dictates a metabolic reprograming of glycolysis and TCA cycle in ovarian cancer

Warburg effect has emerged as a potential hallmark of many cancers. However, the molecular mechanisms that led to this metabolic state of aerobic glycolysis, particularly in ovarian cancer (OVCA) have not been completely elucidated. HSulf-1 predominantly functions by limiting the bioavailability of heparan binding growth factors and hence their downstream signaling. Here we report that HSulf-1, a known putative tumor suppressor, is a negative regulator of glycolysis. Silencing of HSulf-1 expression in OV202 cell line increased glucose uptake and lactate production by upregulating glycolytic genes such as Glut1, HKII, LDHA, as well as metabolites. Conversely, HSulf-1 overexpression in TOV21G cells resulted in the down regulation of glycolytic enzymes and reduced glycolytic phenotype, supporting the role of HSulf-1 loss in enhanced aerobic glycolysis. HSulf-1 deficiency mediated glycolytic enhancement also resulted in increased inhibitory phosphorylation of pyruvate dehydrogenase (PDH) thus blocking the entry of glucose flux into TCA cycle. Consistent with this, metabolomic and isotope tracer analysis showed reduced glucose flux into TCA cycle. Moreover, HSulf-1 loss is associated with lower oxygen consumption rate (OCR) and impaired mitochondrial function. Mechanistically, lack of HSulf-1 promotes c-Myc induction through HB-EGF-mediated p-ERK activation. Pharmacological inhibition of c-Myc reduced HB-EGF induced glycolytic enzymes implicating a major role of c-Myc in loss of HSulf-1 mediated altered glycolytic pathway in OVCA. Similarly, PG545 treatment, an agent that binds to heparan binding growth factors and sequesters growth factors away from their ligand also blocked HB-EGF signaling and reduced glucose uptake in vivo in HSulf-1 deficient cells.

Sequential Serum Metabolomic Profiling after Radiofrequency Ablation of Hepatocellular Carcinoma Reveals Different Response Patterns According to Etiology

Radiofrequency ablation (RFA) is commonly performed as a curative approach in patients with hepatocellular carcinoma (HCC); however, the risk of tumor recurrence is difficult to predict due to a lack of reliable clinical and biological markers, and identification of new biomarkers poses a major challenge for improving prognoses. Metabolomics is a promising technique that may lead to the identification and characterization of new disease fingerprints. The objective of the present study was to explore, preoperatively and at various time points post-RFA, the metabolic profile of serum samples from HCC patients to identify factors associated with treatment response and recurrence. Sequential sera obtained before and after RFA procedures for 120 patients with HCC due to cirrhosis were investigated using nuclear magnetic resonance metabolomics. A multilevel orthogonal projection to latent structure analysis was used to discriminate intraindividual metabolic changes in response to RFA treatment. Recurrence-free survival differed depending on the underlying cause of cirrhosis. The statistical model showed significant differences depending on whether the liver disease had a viral or nonviral etiology before RFA intervention (explained variance of R(2)Y = 0.89 and predictability of Q(2)Y = 0.34). These profiles were also associated with specific and distinct metabolic responses after RFA.

Biomarkers in bladder cancer: A metabolomic approach using in vitro and ex vivo model systems

Metabolomics has recently proved to be useful in the area of biomarker discovery for cancers in which early diagnostic and prognostic biomarkers are urgently needed, as is the case of bladder cancer (BC). This article presents a comprehensive review of the literature on the metabolomic studies on BC, highlighting metabolic pathways perturbed in this disease and the altered metabolites as potential biomarkers for BC detection. Current disease model systems used in the study of BC metabolome include in vitro-cultured cancer cells, ex vivo neoplastic bladder tissues and biological fluids, mainly urine but also blood serum/plasma, from BC patients. The major advantages and drawbacks of each model system are discussed. Based on available data, it seems that BC metabolic signature is mainly characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid metabolism, known to be crucial for cell proliferation, as well as glutathione metabolism, known to be determinant in maintaining cellular redox balance. In addition, purine and pyrimidine metabolism as well as carnitine species were found to be altered in BC. Finally, it is emphasized that, despite the progress made in respect to novel biomarkers for BC diagnosis, there are still some challenges and limitations that should be addressed in future metabolomic studies to ensure their translatability to clinical practice.

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

Structure-function analysis of NEET proteins uncovers their role as key regulators of iron and ROS homeostasis in health and disease

A novel family of 2Fe-2S proteins, the NEET family, was discovered during the last decade in numerous organisms, including archea, bacteria, algae, plant and human; suggesting an evolutionary-conserved function, potentially mediated by their CDGSH Iron-Sulfur Domain. In human, three NEET members encoded by the CISD1-3 genes were identified. The structures of CISD1 (mitoNEET, mNT), CISD2 (NAF-1), and the plant At-NEET uncovered a homodimer with a unique "NEET fold", as well as two distinct domains: a beta-cap and a 2Fe-2S cluster-binding domain. The 2Fe-2S clusters of NEET proteins were found to be coordinated by a novel 3Cys:1His structure that is relatively labile compared to other 2Fe-2S proteins and is the reason of the NEETs' clusters could be transferred to apo-acceptor protein(s) or mitochondria. Positioned at the protein surface, the NEET's 2Fe-2S's coordinating His is exposed to protonation upon changes in its environment, potentially suggesting a sensing function for this residue. Studies in different model systems demonstrated a role for NAF-1 and mNT in the regulation of cellular iron, calcium and ROS homeostasis, and uncovered a key role for NEET proteins in critical processes, such as cancer cell proliferation and tumor growth, lipid and glucose homeostasis in obesity and diabetes, control of autophagy, longevity in mice, and senescence in plants. Abnormal regulation of NEET proteins was consequently found to result in multiple health conditions, and aberrant splicing of NAF-1 was found to be a causative of the neurological genetic disorder Wolfram Syndrome 2. Here we review the discovery of NEET proteins, their structural, biochemical and biophysical characterization, and their most recent structure-function analyses. We additionally highlight future avenues of research focused on NEET proteins and propose an essential role for NEETs in health and disease. This article is part of a Special Issue entitled: Fe/S proteins: Analysis, structure, function, biogenesis and diseases.

Nitric oxide is a positive regulator of the Warburg effect in ovarian cancer cells

Ovarian cancer (OVCA) is among the most lethal gynecological cancers leading to high mortality rates among women. Increasing evidence indicate that cancer cells undergo metabolic transformation during tumorigenesis and growth through nutrients and growth factors available in tumor microenvironment. This altered metabolic rewiring further enhances tumor progression. Recent studies have begun to unravel the role of amino acids in the tumor microenvironment on the proliferation of cancer cells. One critically important, yet often overlooked, component to tumor growth is the metabolic reprogramming of nitric oxide (NO) pathways in cancer cells. Multiple lines of evidence support the link between NO and tumor growth in some cancers, including pancreas, breast and ovarian. However, the multifaceted role of NO in the metabolism of OVCA is unclear and direct demonstration of NO's role in modulating OVCA cells' metabolism is lacking. This study aims at indentifying the mechanistic links between NO and OVCA metabolism. We uncover a role of NO in modulating OVCA metabolism: NO positively regulates the Warburg effect, which postulates increased glycolysis along with reduced mitochondrial activity under aerobic conditions in cancer cells. Through both NO synthesis inhibition (using L-arginine deprivation, arginine is a substrate for NO synthase (NOS), which catalyzes NO synthesis; using L-Name, a NOS inhibitor) and NO donor (using DETA-NONOate) analysis, we show that NO not only positively regulates tumor growth but also inhibits mitochondrial respiration in OVCA cells, shifting these cells towards glycolysis to maintain their ATP production. Additionally, NO led to an increase in TCA cycle flux and glutaminolysis, suggesting that NO decreases ROS levels by increasing NADPH and glutathione levels. Our results place NO as a central player in the metabolism of OVCA cells. Understanding the effects of NO on cancer cell metabolism can lead to the development of NO targeting drugs for OVCAs.

A switch in the source of ATP production and a loss in capacity to perform glycolysis are hallmarks of hepatocyte failure in advance liver disease

BACKGROUND & AIMS

The cause of hepatic failure in the terminal stages of chronic injury is unknown. Cellular metabolic adaptations in response to the microenvironment have been implicated in cellular breakdown.

METHODS

To address the role of energy metabolism in this process we studied mitochondrial number, respiration, and functional reserve, as well as cellular adenosine-5'-triphosphate (ATP) production, glycolytic flux, and expression of glycolysis related genes in isolated hepatocytes from early and terminal stages of cirrhosis using a model that produces hepatic failure from irreversible cirrhosis in rats. To study the clinical relevance of energy metabolism in terminal stages of chronic liver failure, we analyzed glycolysis and energy metabolism related gene expression in liver tissue from patients at different stages of chronic liver failure according to Child-Pugh classification. Additionally, to determine whether the expression of these genes in early-stage cirrhosis (Child-Pugh Class A) is related to patient outcome, we performed network analysis of publicly available microarray data obtained from biopsies of 216 patients with hepatitis C-related Child-Pugh A cirrhosis who were prospectively followed up for a median of 10years.

RESULTS

In the early phase of cirrhosis, mitochondrial function and ATP generation are maintained by increasing energy production from glycolytic flux as production from oxidative phosphorylation falls. At the terminal stage of hepatic injury, mitochondria respiration and ATP production are significantly compromised, as the hepatocytes are unable to sustain the increased demand for high levels of ATP generation from glycolysis. This impairment corresponds to a decrease in glucose-6-phosphatase catalytic subunit and phosphoglucomutase 1. Similar decreased gene expression was observed in liver tissue from patients at different stages of chronic liver injury. Further, unbiased network analysis of microarray data revealed that expression of these genes was down regulated in the group of patients with poor outcome.

CONCLUSIONS

An adaptive metabolic shift, from generating energy predominantly from oxidative phosphorylation to glycolysis, allows maintenance of energy homeostasis during early stages of liver injury, but leads to hepatocyte dysfunction during terminal stages of chronic liver disease because hepatocytes are unable to sustain high levels of energy production from glycolysis.

Cell culture metabolomics in the diagnosis of lung cancer-the influence of cell culture conditions

Lung cancer is the leading cause of cancer deaths. Unfortunately, lung cancer is often diagnosed only when it becomes symptomatic or at an advanced stage when few treatment options are available. Hence, a diagnostic test suitable for screening widespread populations is required to enable earlier diagnosis. Analysis of exhaled breath provides a non-invasive method for early detection of lung cancer. Analysis of volatile organic compounds (VOCs) by various mass spectral techniques has identified potential biomarkers of disease. Nevertheless, the metabolic origins and the disease specificity of VOCs need further elucidation. Cell culture metabolomics can be used as a bottom-up approach to identify biomarkers of pathological conditions and can also be used to study the metabolic pathways that produce such compounds. This paper summarizes the current knowledge of lung cancer biomarkers in exhaled breath and emphasizes the critical role of cell culture conditions in determining the VOCs produced in vitro. Hypoxic culture conditions more closely mimic the conditions of cancer cell growth in vivo. We propose that since hypoxia influences cell metabolism and so potentially the VOCs that the cancer cells produce, the cell culture metabolomics projects should consider culturing cancer cells in hypoxic conditions.

Signal intensities derived from different NMR probes and parameters contribute to variations in quantification of metabolites

We discovered that serious issues could arise that may complicate interpretation of metabolomic data when identical samples are analyzed at more than one NMR facility, or using slightly different NMR parameters on the same instrument. This is important because cross-center validation metabolomics studies are essential for the reliable application of metabolomics to clinical biomarker discovery. To test the reproducibility of quantified metabolite data at multiple sites, technical replicates of urine samples were assayed by 1D-¹H-NMR at the University of Alberta and the University of Michigan. Urine samples were obtained from healthy controls under a standard operating procedure for collection and processing. Subsequent analysis using standard statistical techniques revealed that quantitative data across sites can be achieved, but also that previously unrecognized NMR parameter differences can dramatically and widely perturb results. We present here a confirmed validation of NMR analysis at two sites, and report the range and magnitude that common NMR parameters involved in solvent suppression can have on quantitated metabolomics data. Specifically, saturation power levels greatly influenced peak height intensities in a frequency-dependent manner for a number of metabolites, which markedly impacted the quantification of metabolites. We also investigated other NMR parameters to determine their effects on further quantitative accuracy and precision. Collectively, these findings highlight the importance of and need for consistent use of NMR parameter settings within and across centers in order to generate reliable, reproducible quantified NMR metabolomics data.

Sampling and analysis of metabolomes in biological fluids

Metabolome analysis involves the study of small molecules that are involved in the metabolic responses that occur through patho-physiological changes caused by genetic stimuli or chemical agents.

Chronic caloric restriction partially protects against age-related alteration in serum metabolome

Calorie restriction (CR) remains the most robust metabolic intervention to extend lifespan and improve healthspan in several species. Using global and targeted mass spectrometry-based metabolomics approaches, here we show that chronic CR prevents age-related changes in specific metabolic signatures. Global metabolomic analysis using ultra-performance liquid chromatography-tandem mass spectrometry detected more than 7,000 metabolites in sera from ad-libitum-fed young, aged, and aged C57BL/6 mice maintained on 40 % CR. Multivariate statistical analysis of mass spectrometry data revealed a clear separation among the young, aged, and aged-CR mice demonstrating the potential of this approach for producing reliable metabolic profiles that discriminate based on age and diet. We have identified 168 discriminating features with high statistical significance (p ≤ 0.001) and validated and quantified three of these metabolites using targeted metabolite analysis. Calorie restriction prevented the age-related alteration in specific metabolites, namely lysophosphatidylcholines (16:1 and 18:4), sphingomyelin (d18:1/12:0), tetracosahexaenoic acid, and 7α-dihydroxy-4-cholesten-3-one, in the serum. Pathway analysis revealed that CR impacted the age-related changes in metabolic byproducts of lipid metabolism, fatty acid metabolism, and bile acid biosynthesis. Our data suggest that metabolomics approach has the potential to elucidate the metabolic mechanism of CR's potential anti-aging effects in larger-scale investigations.

Targeting proteomics to investigate metastasis-associated mitochondrial proteins

Mitochondria are essential organelles in eukaryotic cells and are responsible for regulating energy metabolism, ROS production, and cell survival. Recently, various cellular pathogeneses, including tumorigenesis and metastasis, have been reported to be associated with mitochondrial homeostasis. Consequently, exploiting the correlation between dysfunctional mitochondria and tumor progression has been implicated in the understanding of tumorigenesis, tumor metastasis, and chemoresistance, along with novel strategies to develop cancer therapeutics. To comprehensively understand the role of the mitochondria in cancer metastasis, it is necessary to resolve thousands of mitochondrial proteins and their post-translational modifications with high-throughput global assessments. We introduce mitochondrial proteomic strategies in this review and a discussion on their recent findings related to cancer metastasis. Additionally, the mitochondrial respiratory chain is believed to be a major site for ROS production, and elevated ROS is likely a key source to trigger dysfunctional mitochondria and impaired mitochondrial metabolism that subsequently contribute to the development of cancer progression. Equipment-based metabolomic analysis now allows the monitoring of disease progression and diagnosis. These newly emerging techniques, including proteomics, redox-proteomics, and metabolomics, are described in this review.

Pyruvate uptake is increased in highly invasive ovarian cancer cells under anoikis conditions for anaplerosis, mitochondrial function, and migration

Anoikis resistance, or the ability for cells to live detached from the extracellular matrix, is a property of epithelial cancers. The "Warburg effect," or the preference of cancer cells for glycolysis for their energy production even in the presence of oxygen, has been shown to be evident in various tumors. Since a cancer cell's metastatic ability depends on microenvironmental conditions (nutrients, stromal cells, and vascularization) and is highly variable for different organs, their cellular metabolic fluxes and nutrient demand may show considerable differences. Moreover, a cancer cell's metastatic ability, which is dependent on the stage of cancer, may further create metabolic alterations depending on its microenvironment. Although recent studies have aimed to elucidate cancer cell metabolism under detached conditions, the nutrient demand and metabolic activity of cancer cells under nonadherent conditions remain poorly understood. Additionally, less is known about metabolic alterations in ovarian cancer cells with varying invasive capability under anoikis conditions. We hypothesized that the metabolism of highly invasive ovarian cancer cells in detachment would differ from less invasive ovarian cancer cells and that ovarian cancer cells will have altered metabolism in detached vs. attached conditions. To assess these metabolic differences, we integrated a secretomics-based metabolic footprinting (MFP) approach with mitochondrial bioenergetics. Interestingly, MFP revealed higher pyruvate uptake and oxygen consumption in more invasive ovarian cancer cells than their less invasive counterparts. Furthermore, ATP production was higher in more invasive vs. less invasive ovarian cancer cells in detachment. We found that pyruvate has an effect on highly invasive ovarian cancer cells' migration ability. Our results are the first to demonstrate that higher mitochondrial activity is related to higher ovarian cancer invasiveness under detached conditions. Importantly, our results bring insights regarding the metabolism of cancer cells under nonadherent conditions and could lead to the development of therapies for modulating cancer cell invasiveness.

Untargeted plasma metabolite profiling reveals the broad systemic consequences of xanthine oxidoreductase inactivation in mice

A major challenge in systems biology is integration of molecular findings for individual enzyme activities into a cohesive high-level understanding of cellular metabolism and physiology/pathophysiology. However, meaningful prediction for how a perturbed enzyme activity will globally impact metabolism in a cell, tissue or intact organisms is precluded by multiple unknowns, including in vivo enzymatic rates, subcellular distribution and pathway interactions. To address this challenge, metabolomics offers the potential to simultaneously survey changes in thousands of structurally diverse metabolites within complex biological matrices. The present study assessed the capability of untargeted plasma metabolite profiling to discover systemic changes arising from inactivation of xanthine oxidoreductase (XOR), an enzyme that catalyzes the final steps in purine degradation. Using LC-MS coupled with a multivariate statistical data analysis platform, we confidently surveyed >3,700 plasma metabolites (50-1,000 Da) for differential expression in XOR wildtype vs. mice with inactivated XOR, arising from gene deletion or pharmacological inhibition. Results confirmed the predicted derangements in purine metabolism, but also revealed unanticipated perturbations in metabolism of pyrimidines, nicotinamides, tryptophan, phospholipids, Krebs and urea cycles, and revealed kidney dysfunction biomarkers. Histochemical studies confirmed and characterized kidney failure in xor-nullizygous mice. These findings provide new insight into XOR functions and demonstrate the power of untargeted metabolite profiling for systemic discovery of direct and indirect consequences of gene mutations and drug treatments.

Detailed mitochondrial phenotyping by high resolution metabolomics

Mitochondrial phenotype is complex and difficult to define at the level of individual cell types. Newer metabolic profiling methods provide information on dozens of metabolic pathways from a relatively small sample. This pilot study used “top-down” metabolic profiling to determine the spectrum of metabolites present in liver mitochondria. High resolution mass spectral analyses and multivariate statistical tests provided global metabolic information about mitochondria and showed that liver mitochondria possess a significant phenotype based on gender and genotype. The data also show that mitochondria contain a large number of unidentified chemicals.

pH-titratable superparamagnetic iron oxide for improved nanoparticle accumulation in acidic tumor microenvironments

A wide variety of nanoparticle platforms are being developed for the diagnosis and treatment of malignancy. While many of these are passively targeted or rely on receptor-ligand interactions, metabolically directed nanoparticles provide a complementary approach. It is known that both primary and secondary events in tumorigenesis alter the metabolic profile of developing and metastatic cancers. One highly conserved metabolic phenotype is a state of up-regulated glycolysis and reduced use of oxidative phosphorylation, even when oxygen tension is not limiting. This metabolic shift, termed the Warburg effect, creates a "hostile" tumor microenvironment with increased levels of lactic acid and low extracellular pH. In order to exploit this phenomenon and improve the delivery of nanoparticle platforms to a wide variety of tumors, a pH-responsive iron oxide nanoparticle was designed. Specifically, glycol chitosan (GC), a water-soluble polymer with pH-titratable charge, was conjugated to the surface of superparamagnetic iron oxide nanoparticles (SPIO) to generate a T(2)*-weighted MR contrast agent that responds to alterations in its surrounding pH. Compared to control nanoparticles that lack pH sensitivity, these GC-SPIO nanoparticles demonstrated potent pH-dependent cellular association and MR contrast in vitro. In murine tumor models, GC-SPIO also generated robust T(2)*-weighted contrast, which correlated with increased delivery of the agent to the tumor site, measured quantitatively by inductively coupled plasma mass spectrometry. Importantly, the increased delivery of GC-SPIO nanoparticles cannot be solely attributed to the commonly observed enhanced permeability and retention effect since these nanoparticles have similar physical properties and blood circulation times as control agents.

Metabolomics of oxidative stress in recent studies of endogenous and exogenously administered intermediate metabolites

Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS) that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case) greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites—pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate—whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately developing “omics”-based, diagnostic tests to help influence therapies.

Long-lasting supersensitivity of the rat vas deferens to norepinephrine after chronic guanethidine administration

Metabolic alterations, driven by genetic and epigenetic factors, have long been known to be associated with the etiology of cancer. Furthermore, accumulating evidence suggest that cancer metabolism is intimately linked to drug resistance, which is currently one of the most important challenges in cancer treatment. Altered metabolic pathways help cancer cells to proliferate at a rate higher than normal, adapt to nutrient limited conditions, and develop drug resistance phenotypes. Application of systems biology, boosted by recent advancement of novel high-throughput technologies to obtain cancer-associated, transcriptomic, proteomic and metabolomic data, is expected to make a significant contribution to our understanding of metabolic properties related to malignancy. Indeed, despite being at a very early stage, quantitative data obtained from the omics platforms and through applications of ¹³C metabolic flux analysis (MFA) in in vitro studies, researchers have already began to gain insight into the complex metabolic mechanisms of cancer, paving the way for selection of molecular targets for therapeutic interventions. In this review, we discuss some of the major findings associated with the metabolic pathways in cancer cells and also discuss new evidences and achievements on specific metabolic enzyme targets and target-directed small molecules that can potentially be used as anti-cancer drugs.