Large-scale profiling of serum metabolites in African American and European American patients with bladder cancer reveals metabolic pathways associated with patient survival

Enzymatic depletion of circulating glutamine is immunosuppressive in cancers

Although glutamine addiction in cancer cells is extensively reported, there is controversy on the impact of glutamine metabolism on the immune cells within the tumor microenvironment (TME). To address the role of extracellular glutamine, we enzymatically depleted circulating glutamine using PEGylated Helicobacter pylori gamma-glutamyl transferase (PEG-GGT) in syngeneic mouse models of breast and colon cancers. PEG-GGT treatment inhibits growth of cancer cells in vitro, but in vivo it increases myeloid-derived suppressor cells (MDSCs) and has no significant impact on tumor growth. By deriving a glutamine depletion signature, we analyze diverse human cancers within the TCGA and illustrate that glutamine depletion is not associated with favorable clinical outcomes and correlates with accumulation of MDSC. Broadly, our results help clarify the integrated impact of glutamine depletion within the TME and advance PEG-GGT as an enzymatic tool for the systemic and selective depletion (no asparaginase activity) of circulating glutamine in live animals.

A panel of four plasma amino acids is a promising biomarker for newly diagnosed bladder cancer

BACKGROUND

Metastasis and recurrence are the main causes of death in post-operative bladder cancer (BC), emphasizing the importance of exploring early-stage diagnostic markers. Serum biomarkers constitute a promising diagnostic approach for asymptomatic stage cancer as they are non-invasive, have high accuracy and low cost.

AIMS

To correlate concentrations of plasma amino acids with BC progression to assess their utility as an early-stage diagnostic.

METHODS

Newly diagnosed BC patients (n = 95) and normal controls (n = 96) were recruited during the period from 1 December 2018 to 30 December 2020. General and food frequency questionnaires established their basic information and dietary intake data. Venous blood samples were collected from fasting subjects and used to detect levels of plasma amino acids by liquid chromatography-mass spectrometry. Verification was performed on the GSE13507 transcriptome gene expression matrix of BC from Gene Expression Omnibus (GEO) database.

RESULTS

Eleven amino acids have been identified as altered in the plasma of newly diagnosed BC patients compared to controls (P < 0.05). Adjusted by gender, education, smoking and other factors, plasma ornithine level (OR = 0.256, 95% CI: 0.104-0.630) is a protective factor for BC, plasma levels of methionine (OR = 3.460, 95% CI: 1.384-8.651), arginine (OR = 3.851, 95% CI: 1.542-9.616), and glutamate (OR = 3.813, 95% CI: 1.543-9.419) are all risk factors for BC. ROC analysis demonstrated that the combination of plasma ornithine, methionine, arginine and glutamate could accurately diagnose BC (AUC = 0.84, 95% CI: 0.747-0.833). In addition, the mRNA level of arginase 1 was decreased (P < 0.05), while the inducible nitric oxide synthase was increased significantly, which may be linked with the disturbance of arginine metabolism in BC patients. Further analysis of GEO database confirmed the role of arginine metabolism.

CONCLUSION

A biomarker panel containing four amino acids may provide a feasible strategy for the early diagnosis of BC. However, further validation is required through prospective studies.

Differences in metabolomic profiles between Black and White women in the U.S.: Analyses from two prospective cohorts

There is growing interest in incorporating metabolomics into public health practice. However, Black women are under-represented in many metabolomics studies. If metabolomic profiles differ between Black and White women, this under-representation may exacerbate existing Black-White health disparities. We therefore aimed to estimate metabolomic differences between Black and White women in the U.S. We leveraged data from two prospective cohorts: the Nurses' Health Study (NHS; n = 2077) and Women's Health Initiative (WHI; n = 2128). The WHI served as the replication cohort. Plasma metabolites (n = 334) were measured via liquid chromatography-tandem mass spectrometry. Observed metabolomic differences were estimated using linear regression and metabolite set enrichment analyses. Residual metabolomic differences in a hypothetical population in which the distributions of 14 risk factors were equalized across racial groups were estimated using inverse odds ratio weighting. In the NHS, Black-White differences were observed for most metabolites (75 metabolites with observed differences ≥ |0.50| standard deviations). Black women had lower average levels than White women for most metabolites (e.g., for N6, N6-dimethlylysine, mean Black-White difference = - 0.98 standard deviations; 95% CI: - 1.11, - 0.84). In metabolite set enrichment analyses, Black women had lower levels of triglycerides, phosphatidylcholines, lysophosphatidylethanolamines, phosphatidylethanolamines, and organoheterocyclic compounds, but higher levels of phosphatidylethanolamine plasmalogens, phosphatidylcholine plasmalogens, cholesteryl esters, and carnitines. In a hypothetical population in which distributions of 14 risk factors were equalized, Black-White metabolomic differences persisted. Most results replicated in the WHI (88% of 272 metabolites available for replication). Substantial differences in metabolomic profiles exist between Black and White women. Future studies should prioritize racial representation.

Racial disparities in stage at bladder cancer diagnosis in the US Veterans Affairs healthcare system

OBJECTIVE

To describe patient characteristics and pathological stage at bladder cancer (BCa) diagnosis in a diverse population within a national, equal-access healthcare system.

METHODS

This retrospective cohort study identified 15 966 men diagnosed with BCa in the Veterans Affairs (VA) healthcare system from 2000 to 2020. The primary outcome was pathological stage at diagnosis, determined by index transurethral resection of bladder tumour. Logistic regression was used to assess the relationship between race and stage. Competing risk models tested the association between race and BCa-specific mortality with cumulative incidence estimates.

RESULTS

Of 15 966 BCa patients, 12 868 (81%), 1726 (11%), 493 (3%) and 879 (6%) were White, Black, Hispanic and Other race, respectively. Black patients had significantly higher muscle-invasive bladder cancer (MIBC) rates than White patients (35% vs 32%; P = 0.009). In multivariable analysis, the odds of presenting with MIBC did not differ significantly between Black and White patients (odds ratio [OR] 1.10, 95% confidence interval [CI] 0.98-1.22) or between Hispanic patients (OR 0.82, 95% CI 0.67-1.01) and White patients. Compared to White patients, Black patients had a similar risk of BCa-specific mortality (hazard ratio [HR] 0.89, 95% CI 0.75-1.06), whereas Hispanic patients had a lower risk (HR 0.56, 95% CI 0.38-0.82).

CONCLUSIONS

Black patients presented with the highest rates of de novo MIBC. However, in a large, equal-access healthcare system, this did not result in a difference in BCa-specific mortality. In contrast, Hispanic patients had lower risks of MIBC and BCa-specific mortality.

Metabolomic profiles in Jamaican children with and without autism spectrum disorder

Background

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a wide range of behavioral and cognitive impairments. While genetic and environmental factors are known to contribute to its etiology, the underlying metabolic perturbations associated with ASD which can potentially connect genetic and environmental factors, remain poorly understood. Therefore, we conducted a metabolomic case-control study and performed a comprehensive analysis to identify significant alterations in metabolite profiles between children with ASD and typically developing (TD) controls.

Objective

To elucidate potential metabolomic signatures associated with ASD in children and identify specific metabolites that may serve as biomarkers for the disorder.

Methods

We conducted metabolomic profiling on plasma samples from participants in the second phase of Epidemiological Research on Autism in Jamaica (ERAJ-2), which was a 1:1 age (±6 months)-and sex-matched cohort of 200 children with ASD and 200 TD controls (2-8 years old). Using high-throughput liquid chromatography-mass spectrometry techniques, we performed a targeted metabolite analysis, encompassing amino acids, lipids, carbohydrates, and other key metabolic compounds. After quality control and imputation of missing values, we performed univariable and multivariable analysis using normalized metabolites while adjusting for covariates, age, sex, socioeconomic status, and child's parish of birth.

Results

Our findings revealed unique metabolic patterns in children with ASD for four metabolites compared to TD controls. Notably, three of these metabolites were fatty acids, including myristoleic acid, eicosatetraenoic acid, and octadecenoic acid. Additionally, the amino acid sarcosine exhibited a significant association with ASD.

Conclusions

These findings highlight the role of metabolites in the etiology of ASD and suggest opportunities for the development of targeted interventions.

Exploration of potential biomarkers for early bladder cancer based on urine proteomics

Background

Bladder cancer is a common malignant tumor of the urinary system. The progression of the condition is associated with a poor prognosis, so it is necessary to identify new biomarkers to improve the diagnostic rate of bladder cancer.

Methods

In this study, 338 urine samples (144 bladder cancer, 123 healthy control, 32 cystitis, and 39 upper urinary tract cancer samples) were collected, among which 238 samples (discovery group) were analyzed by LC-MS. The urinary proteome characteristics of each group were compared with those of bladder cancer, and the differential proteins were defined by bioinformatics analysis. The pathways and functional enrichments were annotated. The selected proteins with the highest AUC score were used to construct a diagnostic panel. One hundred samples (validation group) were used to test the effect of the panel by ELISA.

Results

Compared with the healthy control, cystitis and upper urinary tract cancer samples, the number of differential proteins in the bladder cancer samples was 325, 158 and 473, respectively. The differentially expressed proteins were mainly related to lipid metabolism and iron metabolism and were involved in the proliferation, metabolism and necrosis of bladder cancer cells. The AUC of the panel of APOL1 and ITIH3 was 0.96 in the discovery group. ELISA detection showed an AUC of 0.92 in the validation group.

Conclusion

This study showed that urinary proteins can reflect the pathophysiological changes in bladder cancer and that important molecules can be used as biomarkers for bladder cancer screening. These findings will benefit the application of the urine proteome in clinical research.

Metabolomic profiling of human bladder tissue extracts

INTRODUCTION

Bladder cancer is a common malignancy affecting the urinary tract and effective biomarkers and for which monitoring therapeutic interventions have yet to be identified.

OBJECTIVES

Major aim of this work was to perform metabolomic profiling of human bladder cancer and adjacent normal tissue and to evaluate cancer biomarkers.

METHODS

This study utilized nuclear magnetic resonance (NMR) and high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS) methods to investigate polar metabolite profiles in tissue samples from 99 bladder cancer patients.

RESULTS

Through NMR spectroscopy, six tissue metabolites were identified and quantified as potential indicators of bladder cancer, while LDI-MS allowed detection of 34 compounds which distinguished cancer tissue samples from adjacent normal tissue. Thirteen characteristic tissue metabolites were also found to differentiate bladder cancer tumor grades and thirteen metabolites were correlated with tumor stages. Receiver-operating characteristics analysis showed high predictive power for all three types of metabolomics data, with area under the curve (AUC) values greater than 0.853.

CONCLUSION

To date, this is the first study in which bladder human normal tissues adjacent to cancerous tissues are analyzed using both NMR and MS method. These findings suggest that the metabolite markers identified in this study may be useful for the detection and monitoring of bladder cancer stages and grades.

Metabolic changes preceding bladder cancer occurrence among Korean men: a nested case-control study from the KCPS-II cohort

BACKGROUND

Bladder cancer (BLCA) research in Koreans is still lacking, especially in focusing on the prediction of BLCA. The current study aimed to discover metabolic signatures related to BLCA onset and confirm its potential as a biomarker.

METHODS

We designed two nested case-control studies using Korean Cancer Prevention Study (KCPS)-II. Only males aged 35-69 were randomly selected and divided into two sets by recruitment organizations [set 1, BLCA (n = 35) vs. control (n = 35); set 2, BLCA (n = 31) vs. control (n = 31)]. Baseline serum samples were analyzed by non-targeted metabolomics profiling, and OPLS-DA and network analysis were performed. Calculated genetic risk score (GRS) for BLCA from all KCPS participants was utilized for interpreting metabolomics data.

RESULTS

Critical metabolic signatures shown in the BLCA group were dysregulation of lysine metabolism and tryptophan-indole metabolism. Furthermore, the prediction model consisting of metabolites (lysine, tryptophan, indole, indoleacrylic acid, and indoleacetaldehyde) reflecting these metabolic signatures showed mighty BLCA predictive power (AUC: 0.959 [0.929-0.989]). The results of metabolic differences between GRS-high and GRS-low groups in BLCA indicated that the pathogenesis of BLCA is associated with a genetic predisposition. Besides, the predictive ability for BLCA on the model using GRS and five significant metabolites was powerful (AUC: 0.990 [0.980-1.000]).

CONCLUSION

Metabolic signatures shown in the present research may be closely associated with BLCA pathogenesis. Metabolites involved in these could be predictive biomarkers for BLCA. It could be utilized for early diagnosis, prognostic diagnosis, and therapeutic targets for BLCA.

P2Y2 purinergic receptor gene deletion protects mice from bacterial endotoxin and sepsis-associated liver injury and mortality

The liver plays a significant role in regulating a wide range of metabolic, homeostatic, and host-defense functions. However, the impact of liver injury on the host's ability to control bacteremia and morbidity in sepsis is not well understood. Leukocyte recruitment and activation lead to cytokine and chemokine release, which, in turn, trigger hepatocellular injury and elevate nucleotide levels in the extracellular milieu. P2Y2 purinergic receptors, G protein-coupled and activated by extracellular ATP/UTP, are expressed at the cell surface of hepatocytes and nonparenchymal cells. We sought to determine whether P2Y2 purinergic receptor function is necessary for the maladaptive host response to bacterial infection and endotoxin-mediated inflammatory liver injury and mortality in mice. We report that P2Y2 purinergic receptor knockout mice (P2Y2-/-) had attenuated inflammation and liver injury, with improved survival in response to LPS/galactosamine (LPS/GalN; inflammatory liver injury) and cecal ligation and puncture (CLP; polymicrobial sepsis). P2Y2-/- livers had attenuated c-Jun NH2-terminal kinase activation, matrix metallopeptidase-9 expression, and hepatocyte apoptosis in response to LPS/GalN and attenuated inducible nitric oxide synthase and nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain containing 3 protein expression in response to CLP. Implicating liver injury in the disruption of amino acid homeostasis, CLP led to lower serum arginine and higher bacterial load and morbidity in the WT mice, whereas serum arginine levels were comparable to sham-operated controls in P2Y2-/- mice, which had attenuated bacteremia and improved survival. Collectively, our studies highlight the pathophysiological relevance of P2Y2 purinergic receptor function in inflammatory liver injury and dysregulation of systemic amino acid homeostasis with implications for sepsis-associated immune dysfunction and morbidity in mice.NEW & NOTEWORTHY Our studies provide experimental evidence for P2Y2 purinergic receptor-mediated potentiation of inflammatory liver injury, morbidity, and mortality, in two well-established animal models of inflammatory liver injury. Our findings highlight the potential to target P2Y2 purinergic signaling to attenuate the induction of "cytokine storm" and prevent its deleterious consequences on liver function, systemic amino acid homeostasis, host response to bacterial infection, and sepsis-associated morbidity and mortality.

Plasma metabolomics profiles in Black and White participants of the Adventist Health Study-2 cohort

BACKGROUND

Black Americans suffer disparities in risk for cardiometabolic and other chronic diseases. Findings from the Adventist Health Study-2 (AHS-2) cohort have shown associations of plant-based dietary patterns and healthy lifestyle factors with prevention of such diseases. Hence, it is likely that racial differences in metabolic profiles correlating with disparities in chronic diseases are explained largely by diet and lifestyle, besides social determinants of health.

METHODS

Untargeted plasma metabolomics screening was performed on plasma samples from 350 participants of the AHS-2, including 171 Black and 179 White participants, using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and a global platform of 892 metabolites. Differences in metabolites or biochemical subclasses by race were analyzed using linear regression, considering various models adjusted for known confounders, dietary and/or other lifestyle behaviors, social vulnerability, and psychosocial stress. The Storey permutation approach was used to adjust for false discovery at FDR < 0.05.

RESULTS

Linear regression revealed differential abundance of over 40% of individual metabolites or biochemical subclasses when comparing Black with White participants after adjustment for false discovery (FDR < 0.05), with the vast majority showing lower abundance in Blacks. Associations were not appreciably altered with adjustment for dietary patterns and socioeconomic or psychosocial stress. Metabolite subclasses showing consistently lower abundance in Black participants included various lipids, such as lysophospholipids, phosphatidylethanolamines, monoacylglycerols, diacylglycerols, and long-chain monounsaturated fatty acids, among other subclasses or lipid categories. Among all biochemical subclasses, creatine metabolism exclusively showed higher abundance in Black participants, although among metabolites within this subclass, only creatine showed differential abundance after adjustment for glomerular filtration rate. Notable metabolites in higher abundance in Black participants included methyl and propyl paraben sulfates, piperine metabolites, and a considerable proportion of acetylated amino acids, including many previously found associated with glomerular filtration rate.

CONCLUSIONS

Differences in metabolic profiles were evident when comparing Black and White participants of the AHS-2 cohort. These differences are likely attributed in part to dietary behaviors not adequately explained by dietary pattern covariates, besides other environmental or genetic factors. Alterations in these metabolites and associated subclasses may have implications for the prevention of chronic diseases in Black Americans.

CRAT links cholesterol metabolism to innate immune responses in the heart

Chronic inflammation is associated with increased risk and poor prognosis of heart failure; however, the precise mechanism that provokes sustained inflammation in the failing heart remains elusive. Here we report that depletion of carnitine acetyltransferase (CRAT) promotes cholesterol catabolism through bile acid synthesis pathway in cardiomyocytes. Intracellular accumulation of bile acid or intermediate, 7α-hydroxyl-3-oxo-4-cholestenoic acid, induces mitochondrial DNA stress and triggers cGAS-STING-dependent type I interferon responses. Furthermore, type I interferon responses elicited by CRAT deficiency substantially increase AIM2 expression and AIM2-dependent inflammasome activation. Genetic deletion of cardiomyocyte CRAT in mice of both sexes results in myocardial inflammation and dilated cardiomyopathy, which can be reversed by combined depletion of caspase-1, cGAS or AIM2. Collectively, we identify a mechanism by which cardiac energy metabolism, cholesterol homeostasis and cardiomyocyte-intrinsic innate immune responses are interconnected via a CRAT-mediated bile acid synthesis pathway, which contributes to chronic myocardial inflammation and heart failure progression.

Identification of metabolic pathways contributing to ER+ breast cancer disparities using a machine-learning pipeline

African American (AA) women in the United States have a 40% higher breast cancer mortality rate than Non-Hispanic White (NHW) women. The survival disparity is particularly striking among (estrogen receptor positive) ER+ breast cancer cases. The purpose of this study is to examine whether there are racial differences in metabolic pathways typically activated in patients with ER+ breast cancer. We collected pretreatment plasma from AA and NHW ER+ breast cancer cases (AA n = 48, NHW n = 54) and cancer-free controls (AA n = 100, NHW n = 48) to conduct an untargeted metabolomics analysis using gas chromatography mass spectrometry (GC-MS) to identify metabolites that may be altered in the different racial groups. Unpaired t-test combined with multiple feature selection and prediction models were employed to identify race-specific altered metabolic signatures. This was followed by the identification of altered metabolic pathways with a focus in AA patients with breast cancer. The clinical relevance of the identified pathways was further examined in PanCancer Atlas breast cancer data set from The Cancer Genome Atlas Program (TCGA). We identified differential metabolic signatures between NHW and AA patients. In AA patients, we observed decreased circulating levels of amino acids compared to healthy controls, while fatty acids were significantly higher in NHW patients. By mapping these metabolites to potential epigenetic regulatory mechanisms, this study identified significant associations with regulators of metabolism such as methionine adenosyltransferase 1A (MAT1A), DNA Methyltransferases and Histone methyltransferases for AA individuals, and Fatty acid Synthase (FASN) and Monoacylglycerol lipase (MGL) for NHW individuals. Specific gene Negative Elongation Factor Complex E (NELFE) with histone methyltransferase activity, was associated with poor survival exclusively for AA individuals. We employed a comprehensive and novel approach that integrates multiple machine learning and statistical methods, coupled with human functional pathway analyses. The metabolic profile of plasma samples identified may help elucidate underlying molecular drivers of disproportionately aggressive ER+ tumor biology in AA women. It may ultimately lead to the identification of novel therapeutic targets. To our knowledge, this is a novel finding that describes a link between metabolic alterations and epigenetic regulation in AA breast cancer and underscores the need for detailed investigations into the biological underpinnings of breast cancer health disparities.

Lipidomic Profiling Reveals Biological Differences between Tumors of Self-Identified African Americans and Non-Hispanic Whites with Cancer

In the US, the incidence and mortality of many cancers are disproportionately higher in African Americans (AA). Yet, AA remain poorly represented in molecular studies investigating the roles that biological factors might play in the development, progression, and outcomes of many cancers. Given that sphingolipids, key components of mammalian cellular membranes, have well-established roles in the etiology of cancer progression, malignancy, and responses to therapy, we conducted a robust mass spectrometry analysis of sphingolipids in normal adjacent uninvolved tissues and tumors of self-identified AA and non-Hispanic White (NHW) males with cancers of the lung, colon, liver, and head and neck and of self-identified AA and NHW females with endometrial cancer. In these cancers, AA have worse outcomes than NHW. The goal of our study was to identify biological candidates to be evaluated in future preclinical studies targeting race-specific alterations in the cancers of AA. We have identified that various sphingolipids are altered in race-specific patterns, but more importantly, the ratios of 24- to 16-carbon fatty acyl chain-length ceramides and glucosylceramides are higher in the tumors of AA. As there is evidence that ceramides with 24-carbon fatty acid chain length promote cellular survival and proliferation, whereas 16-carbon chain length promote apoptosis, these results provide important support for future studies tailored to evaluate the potential roles these differences may play in the outcomes of AA with cancer.

Resveratrol attenuates staphylococcal enterotoxin B-activated immune cell metabolism via upregulation of miR-100 and suppression of mTOR signaling pathway

Acute Respiratory Distress Syndrome (ARDS) is triggered by a variety of insults, such as bacterial and viral infections, including SARS-CoV-2, leading to high mortality. In the murine model of ARDS induced by Staphylococcal enterotoxin-B (SEB), our previous studies showed that while SEB triggered 100% mortality, treatment with Resveratrol (RES) completely prevented such mortality by attenuating inflammation in the lungs. In the current study, we investigated the metabolic profile of SEB-activated immune cells in the lungs following treatment with RES. RES-treated mice had higher expression of miR-100 in the lung mononuclear cells (MNCs), which targeted mTOR, leading to its decreased expression. Also, Single-cell RNA-seq (scRNA seq) unveiled the decreased expression of mTOR in a variety of immune cells in the lungs. There was also an increase in glycolytic and mitochondrial respiration in the cells from SEB + VEH group in comparison with SEB + RES group. Together these data suggested that RES alters the metabolic reprogramming of SEB-activated immune cells, through suppression of mTOR activation and its down- and upstream effects on energy metabolism. Also, miR-100 could serve as novel potential therapeutic molecule in the amelioration of ARDS.

Metabolomic and elemental profiling of blood serum in bladder cancer

Bladder cancer (BC) is one of the most frequently diagnosed types of urinary cancer. Despite advances in treatment methods, no specific biomarkers are currently in use. Targeted and untargeted profiling of metabolites and elements of human blood serum from 100 BC patients and the same number of normal controls (NCs), with external validation, was attempted using three analytical methods, i.e., nuclear magnetic resonance, gold and silver-109 nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS), and inductively coupled plasma optical emission spectrometry (ICP-OES). All results were subjected to multivariate statistical analysis. Four potential serum biomarkers of BC, namely, isobutyrate, pyroglutamate, choline, and acetate, were quantified with proton nuclear magnetic resonance, which had excellent predictive ability as judged by the area under the curve (AUC) value of 0.999. Two elements, Li and Fe, were also found to distinguish between cancer and control samples, as judged from ICP-OES data and AUC of 0.807 (in validation set). Twenty-five putatively identified compounds, mostly related to glycans and lipids, differentiated BC from NCs, as detected using LDI-MS. Five serum metabolites were found to discriminate between tumor grades and nine metabolites between tumor stages. The results from three different analytical platforms demonstrate that the identified distinct serum metabolites and metal elements have potential to be used for noninvasive detection, staging, and grading of BC.

Metabolome and microbiome multi-omics integration from a murine lung inflammation model of bronchopulmonary dysplasia

BACKGROUND

Respiratory tract microbial dysbiosis can exacerbate inflammation and conversely inflammation may cause dysbiosis. Dysbiotic microbiome metabolites may lead to bronchopulmonary dysplasia (BPD). Hyperoxia and lipopolysaccharide (LPS) interaction alters lung microbiome and metabolome, mediating BPD lung injury sequence.

METHODS

C57BL6/J mice were exposed to 21% (normoxia) or 70% (hyperoxia) oxygen during postnatal days (PND) 1-14. Pups were injected with LPS (6 mg/kg) or equal PBS volume, intraperitoneally on PND 3, 5, and 7. At PND14, the lungs were collected for microbiome and metabolomic analyses (n = 5/group).

RESULTS

Microbiome alpha and beta diversity were similar between groups. Metabolic changes included hyperoxia 31 up/18 down, LPS 7 up/4 down, exposure interaction 8. Hyperoxia increased Intestinimonas abundance, whereas LPS decreased Clostridiales, Dorea, and Intestinimonas; exposure interaction affected Blautia. Differential co-expression analysis on multi-omics data identified exposure-altered modules. Hyperoxia metabolomics response was integrated with a published matching transcriptome, identifying four induced genes (ALDOA, GAA, NEU1, RENBP), which positively correlated with BPD severity in a published human newborn cohort.

CONCLUSIONS

We report hyperoxia and LPS lung microbiome and metabolome signatures in a clinically relevant BPD model. We identified four genes correlating with BPD status in preterm infants that are promising targets for therapy and prevention.

IMPACT

Using multi-omics, we identified and correlated key biomarkers of hyperoxia and LPS on murine lung micro-landscape and examined their potential clinical implication, which shows strong clinical relevance for future research. Using a double-hit model of clinical relevance to bronchopulmonary dysplasia, we are the first to report integrated metabolomic/microbiome landscape changes and identify novel disease biomarker candidates.

Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts

BACKGROUND

Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk.

METHODS

Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS.

RESULTS

Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS.

CONCLUSIONS

Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.

Untargeted ultra-high-resolution mass spectrometry metabolomic profiling of blood serum in bladder cancer

Bladder cancer (BC) is a common urological cancer of high mortality and recurrence rates. Currently, cystoscopy is performed as standard examination for the diagnosis and subsequent monitoring for recurrence of the patients. Frequent expensive and invasive procedures may deterrent patients from regular follow-up screening, therefore it is important to look for new non-invasive methods to aid in the detection of recurrent and/or primary BC. In this study, ultra-high-performance liquid chromatography coupled with ultra-high-resolution mass spectrometry was employed for non-targeted metabolomic profiling of 200 human serum samples to identify biochemical signatures that differentiate BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation revealed twenty-seven metabolites that differentiate between BC patients from NCs. Abundances of these metabolites displayed statistically significant differences in two independent training and validation sets. Twenty-three serum metabolites were also found to be distinguishing between low- and high-grade of BC patients and controls. Thirty-seven serum metabolites were found to differentiate between different stages of BC. The results suggest that measurement of serum metabolites may provide more facile and less invasive diagnostic methodology for detection of bladder cancer and recurrent disease management.

Lipidomic Profiling Identifies a Novel Lipid Signature Associated with Ethnicity-Specific Disparity of Bladder Cancer

Bladder Cancer (BLCA) is the ninth most frequently diagnosed cancer globally and the sixth most common cancer in the US. African Americans (AA) exhibit half the BLCA incidence compared to European Americans (EA), but they have a 70% higher risk of cancer-related death; unfortunately, this disparity in BLCA mortality remains poorly understood. In this study, we have used an ethnicity-balanced cohort for unbiased lipidomics profiling to study the changes in the lipid fingerprint for AA and EA BLCA tissues collected from similar geographical regions to determine a signature of ethnic-specific alterations. We identified 86 lipids significantly altered between self-reported AA and EA BLCA patients from Augusta University (AU) cohort. The majority of altered lipids belong to phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), ly sophosphatidylcholines (lysoPCs), phosphatidylserines (PSs), and diglycerides (DGs). Interestingly, levels of four lysoPCs (lyso PCs 20:3, lyso PCs 22:1, lyso PCs 22:2, and lyso PCs 26:1) were elevated while, in contrast, the majority of the PCs were reduced in AA BLCA. Significant alterations in long-chain monounsaturated (MonoUN) and polyunsaturated (PolyUN) lipids were also observed between AA and EA BLCA tumor tissues. These first-in-field results implicate ethnic-specific lipid alterations in BLCA.

Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer

Metabolomic analysis has proven to be a useful tool in biomarker discovery and the molecular classification of cancers. In order to find new biomarkers, and to better understand its pathological behavior, bladder cancer also has been studied using a metabolomics approach. In this article, we review the literature on metabolomic studies of bladder cancer, focusing on the different available samples (urine, blood, tissue samples) used to perform the studies and their relative findings. Moreover, the multi-omic approach in bladder cancer research has found novel insights into its metabolic behavior, providing excellent start-points for new diagnostic and therapeutic strategies. Metabolomics data analysis can lead to the discovery of a “signature pathway” associated with the progression of bladder cancer; this aspect could be potentially valuable in predictions of clinical outcomes and the introduction of new treatments. However, further studies are needed to give stronger evidence and to make these tools feasible for use in clinical practice.

Targeted Lipidomics To Measure Phospholipids and Sphingomyelins in Plasma: A Pilot Study To Understand the Impact of Race/Ethnicity in Alzheimer's Disease

The number of people suffering from Alzheimer's disease (AD) is increasing rapidly every year. One aspect of AD that is often overlooked is the disproportionate incidence of AD among African American/Black populations. With the recent development of novel assays for lipidomics analysis in recent times, there has been a drastic increase in the number of studies focusing on changes of lipids in AD. However, very few of these studies have focused on or even included samples from African American/Black individuals samples. In this study, we aimed to determine if the lipidome in AD is universal across non-Hispanic White and African American/Black individuals. To accomplish this, a targeted mass spectrometry lipidomics analysis was performed on plasma samples (N = 113) obtained from cognitively normal (CN, N = 54) and AD (N = 59) individuals from African American/Black (N = 56) and non-Hispanic White (N = 57) backgrounds. Five lipids (PS 18:0_18:0, PS 18:0_20:0, PC 16:0_22:6, PC 18:0_22:6, and PS 18:1_22:6) were altered between AD and CN sample groups (p value < 0.05). Upon racial stratification, there were notable differences in lipids that were unique to African American/Black or non-Hispanic White individuals. PS 20:0_20:1 was reduced in AD in samples from non-Hispanic White but not African American/Black adults. We also tested whether race/ethnicity significantly modified the association between lipids and AD status by including a race × diagnosis interaction term in a linear regression model. PS 20:0_20:1 showed a significant interaction (p = 0.004). The discovery of lipid changes in AD in this study suggests that identifying relevant lipid biomarkers for diagnosis will require diversity in sample cohorts.

Plasma Oxylipin Profile Discriminates Ethnicities in Subjects with Non-Alcoholic Steatohepatitis: An Exploratory Analysis

Non-alcoholic fatty liver disease (NAFLD) is a common liver pathology that includes steatosis, or non-alcoholic fatty liver (NAFL), and non-alcoholic steatohepatitis (NASH). Without a clear pathophysiological mechanism, it affects Hispanics disproportionately compared to other ethnicities. Polyunsaturated fatty acids (PUFAs) and inflammatory lipid mediators including oxylipin (OXL) and endocannabinoid (eCB) are altered in NAFLD and thought to contribute to its pathogenesis. However, the existence of ethnicity-related differences is not clear. We employed targeted lipidomic profiling for plasma PUFAs, non-esterified OXLs and eCBs in White Hispanics (HIS, n = 10) and Caucasians (CAU, n = 8) with biopsy-confirmed NAFL, compared with healthy control subjects (HC; n = 14 HIS; n = 8 CAU). NAFLD was associated with diminished long chain PUFA in HIS, independent of histological severity. Differences in plasma OXLs and eCBs characterized ethnicities in NASH, with lower arachidonic acid derived OXLs observed in HIS. The secondary analysis comparing ethnicities within NASH (n = 12 HIS; n = 17 CAU), confirms these ethnicity-related differences and suggests lower lipoxygenase(s) and higher soluble epoxide hydrolase(s) activities in HIS compared to CAU. While causes are not clear, these lipidomic differences might be with implications for NAFLD severity and are worth further investigation. We provide preliminary data indicating ethnicity-specific lipidomic signature characterizes NASH which requires further validation.

A method establishment and comparison of in vivo lung cancer model development platforms for evaluation of tumour metabolism and pharmaceutical efficacy

BACKGROUND

Currently, the identification of accurate biomarkers for the diagnosis of patients with early-stage lung cancer remains difficult. Fortunately, metabolomics technology can be used to improve the detection of plasma metabolic biomarkers for lung cancer. In a previous study, we successfully utilised machine learning methods to identify significant metabolic markers for early-stage lung cancer diagnosis. However, a related research platform for the investigation of tumour metabolism and drug efficacy is still lacking.

HYPOTHESIS/PURPOSE

A novel methodology for the comprehensive evaluation of the internal tumour-metabolic profile and drug evaluation needs to be established.

METHODS

The optimal location for tumour cell inoculation was identified in mouse chest for the non-traumatic orthotopic lung cancer mouse model. Microcomputed tomography (micro-CT) was applied to monitor lung tumour growth. Proscillaridin A (P.A) and cisplatin (CDDP) were utilised to verify the anti-lung cancer efficacy of the platform. The top five clinically valid biomarkers, including proline, L-kynurenine, spermidine, taurine and palmitoyl-L-carnitine, were selected as the evaluation indices to obtain a suitable lung cancer mouse model for clinical metabolomics research by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).

RESULTS

The platform was successfully established, achieving 100% tumour development rate and 0% surgery mortality. P.A and CDDP had significant anti-lung cancer efficacy in the platform. Compared with the control group, four biomarkers in the orthotopic model and two biomarkers in the metastatic model had significantly higher abundance. Principal component analysis (PCA) showed a significant separation between the orthotopic/metastatic model and the control/subcutaneous/KRAS transgenic model. The platform was mainly involved in arginine and proline metabolism, tryptophan metabolism, and taurine and hypotaurine metabolism.

CONCLUSION

This study is the first to simulate clinical metabolomics by comparing the metabolic phenotype of plasma in different lung cancer mouse models. We found that the orthotopic model was the most suitable for tumour metabolism. Furthermore, the anti-tumour drug efficacy was verified in the platform. The platform can very well match the clinical reality, providing better lung cancer diagnosis and securing more precise evidence for drug evaluation in the future.

Discovery of novel serum metabolic biomarkers in patients with polycystic ovarian syndrome and premature ovarian failure

Several widely recognized metabolites play a role in regulating the pathophysiological processes of various disorders. Nonetheless, the lack of effective biomarkers for the early diagnosis of polycystic ovarian syndrome (PCOS) and premature ovarian failure (POF) has led to the discovery of serum-based metabolic biomarkers for these disorders. We aimed to identify various differentially expressed metabolites (DEMs) through serum-based metabolic profiling in patients with PCOS and POF and in healthy individuals by using liquid chromatography–mass spectrometry analysis. Furthermore, heatmap clustering, correlation, and Z-score analyses were performed to identify the top DEMs. Kyoto Encyclopedia of Genes and Genomes enriched pathways of DEMs were determined using metabolite-based databases. Moreover, the clinical significance of these DEMs was evaluated on the basis of area under the receiver operating characteristic curve. Significantly dysregulated expressions of several metabolites were observed in the intergroup comparisons of the PCOS, POF, and healthy control groups. Furthermore, 6 DEMs were most frequently observed among the three groups. The expressions of these DEMs were not only directly correlated but also exhibited potential significance in patients with PCOS and POF. Novel metabolites with up/downregulated expressions can be discovered in patients with PCOS and POF using serum-based metabolomics; these metabolites show good diagnostic performance and can act as effective biomarkers for the early detection of PCOS and POF. Furthermore, these metabolites might be involved in the pathophysiological mechanisms of PCOS and POF via interplay with corresponding genes.

CHAF1A Blocks Neuronal Differentiation and Promotes Neuroblastoma Oncogenesis via Metabolic Reprogramming

Neuroblastoma (NB) arises from oncogenic disruption of neural crest (NC) differentiation. Treatment with retinoic acid (RA) to induce differentiation has improved survival in some NB patients, but not all patients respond, and most NBs eventually develop resistance to RA. Loss of the chromatin modifier chromatin assembly factor 1 subunit p150 (CHAF1A) promotes NB cell differentiation; however, the mechanism by which CHAF1A drives NB oncogenesis has remained unexplored. This study shows that CHAF1A gain-of-function supports cell malignancy, blocks neuronal differentiation in three models (zebrafish NC, human NC, and human NB), and promotes NB oncogenesis. Mechanistically, CHAF1A upregulates polyamine metabolism, which blocks neuronal differentiation and promotes cell cycle progression. Targeting polyamine synthesis promotes NB differentiation and enhances the anti-tumor activity of RA. The authors' results provide insight into the mechanisms that drive NB oncogenesis and suggest a rapidly translatable therapeutic approach (DFMO plus RA) to enhance the clinical efficacy of differentiation therapy in NB patients.

Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual’s current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.

Reverse Phase Protein Array Reveals Correlation of Retinoic Acid Metabolism With Cardiomyopathy in Friedreich's Ataxia

Identifying biomarkers is important for assessment of disease progression, prediction of symptom development, and determination of treatment effectiveness. While unbiased analyses of differential gene expression using next-generation sequencing methods are now routinely conducted, proteomics studies are more challenging because of traditional methods predominantly being low throughput and offering a limited dynamic range for simultaneous detection of hundreds of proteins that drastically differ in their intracellular abundance. We utilized a sensitive and high-throughput proteomic technique, reverse phase protein array (RPPA), to attain protein expression profiles of primary fibroblasts obtained from patients with Friedreich's ataxia (FRDA) and unaffected controls (CTRLs). The RPPA was designed to detect 217 proteins or phosphorylated proteins by individual antibody, and the specificity of each antibody was validated prior to the experiment. Among 62 fibroblast samples (44 FRDA and 18 CTRLs) analyzed, 30 proteins/phosphoproteins were significantly changed in FRDA fibroblasts compared with CTRL cells (p < 0.05), mostly representing signaling molecules and metabolic enzymes. As expected, frataxin was significantly downregulated in FRDA samples, thus serving as an internal CTRL for assay integrity. Extensive bioinformatics analyses were conducted to correlate differentially expressed proteins with critical disease parameters (e.g., selected symptoms, age of onset, guanine-adenine-adenine sizes, frataxin levels, and Functional Assessment Rating Scale scores). Members of the integrin family of proteins specifically associated with hearing loss in FRDA. Also, RPPA data, combined with results of transcriptome profiling, uncovered defects in the retinoic acid metabolism pathway in FRDA samples. Moreover, expression of aldehyde dehydrogenase family 1 member A3 differed significantly between cardiomyopathy-positive and cardiomyopathy-negative FRDA cohorts, demonstrating that metabolites such as retinol, retinal, or retinoic acid could become potential predictive biomarkers of cardiac presentation in FRDA.

Fatty Acid Synthase Correlates With Prognosis-Related Abdominal Adipose Distribution and Metabolic Disorders of Clear Cell Renal Cell Carcinoma

Purpose: Lipid metabolism reprogramming is a major pathway in tumor evolution. This study investigated fatty acid synthase (FASN) mRNA expression in anthropometric adipose tissue and elucidated the prognostic value and potential mechanism of clear cell renal cell carcinoma (ccRCC).

Materials and Methods: Transcription profiles were obtained from 533 ccRCC samples in The Cancer Genome Atlas (TCGA) cohorts. Real-time quantitative PCR (RT-qPCR) and immunohistochemistry were performed to detect FASN expression in 380 paired ccRCC and normal tissues from the Fudan University Shanghai Cancer Center (FUSCC). Visceral adipose tissue (VAT) and subcutaneous adipose tissue were at the level of the umbilicus as measured by magnetic resonance imaging (MRI). Non-targeted metabolomics and in vitro experiments were used to reveal the biological functions of FASN.

Results: Increased FASN expression was significantly relevant to advanced T, N, and American Joint Committee on Cancer (AJCC) stages (p < 0.01) and significantly correlated to poor progression-free survival (PFS) and overall survival (OS) of 913 ccRCC patients in FUSCC and TCGA cohorts. Pearson's correlation coefficient indicated that FASN amplification was positively correlated to VAT% (r = 0.772, p < 0.001), which significantly correlated to poor PFS (HR = 2.066, p = 0.028) and OS (HR = 2.773, p = 0.023) in the FUSCC cohort. Transient inhibition or overexpression of FASN significantly regulated A498 and 786O cell proliferation and migration by regulating epithelial–mesenchymal transition. Inhibition of FASN led to a higher apoptotic rate and decreased lipid droplet formation compared with normal control in ccRCC cells. Non-targeted metabolomics showed that decreased de novo lipogenesis might be required to sustain an elevation of glycolytic activity in 786O cells by regulating galactinol, dl-lactate, N-acetylaspartylglutamate, and sucrose, thereby participating in carcinogenesis and progression of ccRCC.

Conclusion: This study demonstrated that FASN expression is positively related to aggressive cell proliferation, migration, apoptosis, and lipid droplet formation and regulates metabolic disorders of the ccRCC microenvironment. Additionally, elevated FASN mRNA expression is significantly correlated to the abdominal obesity distribution, especially VAT%, which is a significant predictor of a poor prognosis for ccRCC patients.

Smith AA, Giles C, Huynh K, Cinel M, Mellett NA, Cadby G, Hung J, Hui J, Beilby J, Watts GF, Shaw JS, Moses EK, Magliano DJ, Meikle PJ. High-coverage plasma lipidomics reveals novel sex-specific lipidomic fingerprints of age and BMI: Evidence from two large population cohort studies

Obesity and related metabolic diseases show clear sex-related differences. The growing burden of these diseases calls for better understanding of the age- and sex-related metabolic consequences. High-throughput lipidomic analyses of population-based cohorts offer an opportunity to identify disease-risk-associated biomarkers and to improve our understanding of lipid metabolism and biology at a population level. Here, we comprehensively examined the relationship between lipid classes/subclasses and molecular species with age, sex, and body mass index (BMI). Furthermore, we evaluated sex specificity in the association of the plasma lipidome with age and BMI. Some 747 targeted lipid measures, representing 706 molecular lipid species across 36 classes/subclasses, were measured using a high-performance liquid chromatography coupled mass spectrometer on a total of 10,339 participants from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), with 563 lipid species being validated externally on 4,207 participants of the Busselton Health Study (BHS). Heat maps were constructed to visualise the relative differences in lipidomic profile between men and women. Multivariable linear regression analyses, including sex-interaction terms, were performed to assess the associations of lipid species with cardiometabolic phenotypes. Associations with age and sex were found for 472 (66.9%) and 583 (82.6%) lipid species, respectively. We further demonstrated that age-associated lipidomic fingerprints differed by sex. Specific classes of ether-phospholipids and lysophospholipids (calculated as the sum composition of the species within the class) were inversely associated with age in men only. In analyses with women alone, higher triacylglycerol and lower lysoalkylphosphatidylcholine species were observed among postmenopausal women compared with premenopausal women. We also identified sex-specific associations of lipid species with obesity. Lysophospholipids were negatively associated with BMI in both sexes (with a larger effect size in men), whilst acylcarnitine species showed opposing associations based on sex (positive association in women and negative association in men). Finally, by utilising specific lipid ratios as a proxy for enzymatic activity, we identified stearoyl CoA desaturase (SCD-1), fatty acid desaturase 3 (FADS3), and plasmanylethanolamine Δ1-desaturase activities, as well as the sphingolipid metabolic pathway, as constituent perturbations of cardiometabolic phenotypes. Our analyses elucidate the effect of age and sex on lipid metabolism by offering a comprehensive view of the lipidomic profiles associated with common cardiometabolic risk factors. These findings have implications for age- and sex-dependent lipid metabolism in health and disease and suggest the need for sex stratification during lipid biomarker discovery, establishing biological reference intervals for assessment of disease risk.

Cerebrospinal fluid ctDNA and metabolites are informative biomarkers for the evaluation of CNS germ cell tumors

Serum and cerebrospinal fluid (CSF) levels of α-fetoprotein and β-subunit of human chorionic gonadotropin are used as biomarkers for the management of central nervous system (CNS) germ cell tumors (GCTs). However, additional discriminating biomarkers are required. Especially, biomarkers to differentiate non-germinomatous germ cell tumors (NGGCTs) from germinomas are critical, as these have a distinct prognosis. We investigated CSF samples from 12 patients with CNS-GCT patients (8 germinomas and 4 NGGCTs). We analyzed circulating tumor DNA (ctDNA) in CSF to detect mutated genes. We also used liquid chromatography-mass spectrometry to characterize metabolites in CSF. We detected KIT and/or NRAS mutation, known as frequently mutated genes in GCTs, in 3/12 (25%) patients. We also found significant differences in the abundance of 15 metabolites between control and GCT, with unsupervised hierarchical clustering analysis. Metabolites related to the TCA cycle were increased in GCTs. Urea, ornithine, and short-chain acylcarnitines were decreased in GCTs. Moreover, we also detected several metabolites (e.g., betaine, guanidine acetic acid, and 2-aminoheptanoic acid) that displayed significant differences in abundance in patients with germinomas and NGGCTs. Our results suggest that ctDNA and metabolites in CSF can serve as novel biomarkers for CNS-GCTs and can be useful to differentiate germinomas from NGGCTs.

Δ9-Tetrahydrocannabinol Prevents Mortality from Acute Respiratory Distress Syndrome through the Induction of Apoptosis in Immune Cells, Leading to Cytokine Storm Suppression

Acute Respiratory Distress Syndrome (ARDS) causes up to 40% mortality in humans and is difficult to treat. ARDS is also one of the major triggers of mortality associated with coronavirus-induced disease (COVID-19). We used a mouse model of ARDS induced by Staphylococcal enterotoxin B (SEB), which triggers 100% mortality, to investigate the mechanisms through which Δ9-tetrahydrocannabinol (THC) attenuates ARDS. SEB was used to trigger ARDS in C3H mice. These mice were treated with THC and analyzed for survival, ARDS, cytokine storm, and metabolome. Additionally, cells isolated from the lungs were used to perform single-cell RNA sequencing and transcriptome analysis. A database analysis of human COVID-19 patients was also performed to compare the signaling pathways with SEB-mediated ARDS. The treatment of SEB-mediated ARDS mice with THC led to a 100% survival, decreased lung inflammation, and the suppression of cytokine storm. This was associated with immune cell apoptosis involving the mitochondrial pathway, as suggested by single-cell RNA sequencing. A transcriptomic analysis of immune cells from the lungs revealed an increase in mitochondrial respiratory chain enzymes following THC treatment. In addition, metabolomic analysis revealed elevated serum concentrations of amino acids, lysine, n-acetyl methionine, carnitine, and propionyl L-carnitine in THC-treated mice. THC caused the downregulation of miR-185, which correlated with an increase in the pro-apoptotic gene targets. Interestingly, the gene expression datasets from the bronchoalveolar lavage fluid (BALF) of human COVID-19 patients showed some similarities between cytokine and apoptotic genes with SEB-induced ARDS. Collectively, this study suggests that the activation of cannabinoid receptors may serve as a therapeutic modality to treat ARDS associated with COVID-19.

Differences in plasma metabolites related to Alzheimer's disease, APOE ε4 status, and ethnicity

INTRODUCTION

We investigated metabolites in plasma to capture systemic biochemical changes associated with Alzheimer's disease (AD).

METHODS

Metabolites in plasma were measured in 59 AD cases and 60 healthy participants of African American (AA), Caribbean Hispanic (CH), and non-Hispanic white (NHW) ancestry using untargeted liquid-chromatography-based ultra-high-resolution mass spectrometry. Metabolite differences between AD and healthy, ethnic groups and apolipoprotein E gene (APOE) ε4 status were analyzed. Untargeted network analysis identified pathways enriched in AD-associated metabolites.

RESULTS

A total of 5929 annotated metabolites were measured. Partial least squares discriminant analysis (PLS-DA) inferred that AD clustered separately from healthy controls (area under the curve [AUC] = 0.9816); discriminating pathways included glycerophospholipid, sphingolipid, and non-essential amino acid (alanine, aspartate, glutamate) metabolism. Metabolic features in AA clustered differently from CH and NHW (AUC = 0.9275), and differed between APOE ε4 carriers and non-carriers (AUC = 0.9972).

DISCUSSION

Metabolites, specifically lipids, were associated with AD, APOE ε4, and ethnic group. Metabolite profiling can identify perturbed AD pathways, but genetic and ancestral background need to be considered.

Dysregulated Gut Homeostasis Observed Prior to the Accumulation of the Brain Amyloid-β in Tg2576 Mice

Amyloid plaques in Alzheimer's disease (AD) are associated with inflammation. Recent studies demonstrated the involvement of the gut in cerebral amyloid-beta (Aβ) pathogenesis; however, the mechanisms are still not well understood. We hypothesize that the gut bears the Aβ burden prior to brain, highlighting gut-brain axis (GBA) interaction in neurodegenerative disorders. We used pre-symptomatic (6-months) and symptomatic (15-months) Tg2576 mouse model of AD compared to their age-matched littermate WT control. We identified that dysfunction of intestinal epithelial barrier (IEB), dysregulation of absorption, and vascular Aβ deposition in the IEB occur before cerebral Aβ aggregation is detectible. These changes in the GBA were associated with elevated inflammatory plasma cytokines including IL-9, VEGF and IP-10. In association with reduced cerebral myelin tight junction proteins, we identified reduced levels of systemic vitamin B12 and decrease cubilin, an intestinal B12 transporter, after the development of cerebral Aβ pathology. Lastly, we report Aβ deposition in the intestinal autopsy from AD patients with confirmed cerebral Aβ pathology that is not present in intestine from non-AD controls. Our data provide evidence that gut dysfunction occurs in AD and may contribute to its etiology. Future therapeutic strategies to reverse AD pathology may involve the early manipulation of gut physiology and its microbiota.

Liquid biopsy in the clinical management of bladder cancer: current status and future developments

Introduction: The use of liquid biopsy on the blood from solid malignancies provides a convenient way of detecting actionable mutations, monitoring treatment response, detecting early recurrence and prognosticating outcomes. The aim of this review is to discuss the current status and future direction of serum biomarkers in the clinical management of urinary bladder cancer.Areas covered: This review provides an overview of blood liquid biopsy and bladder cancer using methods of circulating tumors cells, circulating RNA, serum metabolites and cell-free DNA. Recent clinical studies and advances in methodology are emphasized. We performed a literature search using PMC/PubMed with keywords including 'liquid biopsy', 'circulating tumor DNA', 'cell-free DNA', 'biomarkers', 'bladder cancer' 'precision medicine'. Additional articles were obtained from the cited references of key articles. An emphasis was placed on recent studies published since 2018.Expert opinion: Liquid biopsies represent a potential biomarker using cell-free DNA, metabolomic profiles of altered cellular metabolism, circulating cancer cells and RNA. Despite displaying tremendous clinical promise, the current status of the blood liquid biopsies has not reached fruition. However, future investigations should lead the evolution of liquid biomarker into clinical utility for the management of bladder cancer.

Improving diagnosis of genitourinary cancers: Biomarker discovery strategies through mass spectrometry-based metabolomics

The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.

Tobacco carcinogens and the methionine metabolism in human bladder cancer

Cigarette smoking is a strong risk factor for bladder cancer. It has been shown that the duration of smoking is associated with a poor prognosis and a higher risk of recurrence. This is due to tobacco carcinogens forming adducts with DNA and proteins that participate in the DNA repair mechanisms. Additionally, polymorphisms of genes responsible for methyl group transfer in the methionine cycle and dosages of vitamins (from diet and supplements) can cause an increased risk of bladder cancer. Upregulated DNA methyltransferase 1 expression and activity results in a high level of methylated products of metabolism, as well as hypermethylation of tumor suppressor genes. The development of a market that provides new inhibitors of DNA methyltransferase or alternatives for current smokers is essential not only for patients but also for people who are under the danger of secondhand smoking and can experience its long-term exposure consequences.

Serum PlGF and EGF are independent prognostic markers in non-metastatic colorectal cancer

The aim of this study was to determine the prognostic value of circulating angiogenic cytokines in non-metastatic colorectal cancer (CRC) patients. Preoperative serum samples of a training (TC) (n = 219) and a validation cohort (VC) (n = 168) were analyzed via ELISA to determine PlGF, EGF, VEGF, Ang1, PDGF-A, PDGF-B, IL-8 and bFGF levels. In addition, survival was correlated with PlGF and EGF expression measured by microarray and RNAseq in two publicly available, independent cohorts (n = 550 and n = 463, respectively). Prognostic values for overall (OS) and disease-free survival (DFS) were determined using uni- and multivariate Cox proportional hazard analyses. Elevated PlGF is predictive for impaired OS (TC: HR 1.056; p = 0.046; VC: HR 1.093; p = 0.001) and DFS (TC: HR 1.052; p = 0.029; VC: HR 1.091; p = 0.009). Conversely, elevated EGF is associated with favorable DFS (TC: HR 0.998; p = 0.045; VC: HR 0.998; p = 0.018) but not OS (TC: p = 0.201; VC: p = 0.453). None of the other angiogenic cytokines correlated with prognosis. The prognostic value of PlGF (OS + DFS) and EGF (DFS) was confirmed in both independent retrospective cohorts. Serum PlGF and EGF may serve as prognostic markers in non-metastatic CRC.

Urinary peptide panel for prognostic assessment of bladder cancer relapse

Non-invasive tools stratifying bladder cancer (BC) patients according to the risk of relapse are urgently needed to guide clinical intervention. As a follow-up to the previously published study on CE-MS-based urinary biomarkers for BC detection and recurrence monitoring, we expanded the investigation towards BC patients with longitudinal data. Profiling datasets of BC patients with follow-up information regarding the relapse status were investigated. The peptidomics dataset (n = 98) was split into training and test set. Cox regression was utilized for feature selection in the training set. Investigation of the entire training set at the single peptide level revealed 36 peptides being strong independent prognostic markers of disease relapse. Those features were further integrated into a Random Forest-based model evaluating the risk of relapse for BC patients. Performance of the model was assessed in the test cohort, showing high significance in BC relapse prognosis [HR = 5.76, p-value = 0.0001, c-index = 0.64]. Urinary peptide profiles integrated into a prognostic model allow for quantitative risk assessment of BC relapse highlighting the need for its incorporation in prospective studies to establish its value in the clinical management of BC.

Multi-omics Integration Analysis Robustly Predicts High-Grade Patient Survival and Identifies CPT1B Effect on Fatty Acid Metabolism in Bladder Cancer

PURPOSE

The perturbation of metabolic pathways in high-grade bladder cancer has not been investigated. We aimed to identify a metabolic signature in high-grade bladder cancer by integrating unbiased metabolomics, lipidomics, and transcriptomics to predict patient survival and to discover novel therapeutic targets.

EXPERIMENTAL DESIGN

We performed high-resolution liquid chromatography mass spectrometry (LC-MS) and bioinformatic analysis to determine the global metabolome and lipidome in high-grade bladder cancer. We further investigated the effects of impaired metabolic pathways using in vitro and in vivo models.

RESULTS

We identified 519 differential metabolites and 19 lipids that were differentially expressed between low-grade and high-grade bladder cancer using the NIST MS metabolomics compendium and lipidblast MS/MS libraries, respectively. Pathway analysis revealed a unique set of biochemical pathways that are highly deregulated in high-grade bladder cancer. Integromics analysis identified a molecular gene signature associated with poor patient survival in bladder cancer. Low expression of CPT1B in high-grade tumors was associated with low FAO and low acyl carnitine levels in high-grade bladder cancer, which were confirmed using tissue microarrays. Ectopic expression of the CPT1B in high-grade bladder cancer cells led to reduced EMT in in vitro, and reduced cell proliferation, EMT, and metastasis in vivo.

CONCLUSIONS

Our study demonstrates a novel approach for the integration of metabolomics, lipidomics, and transcriptomics data, and identifies a common gene signature associated with poor survival in patients with bladder cancer. Our data also suggest that impairment of FAO due to downregulation of CPT1B plays an important role in the progression toward high-grade bladder cancer and provide potential targets for therapeutic intervention.

Recent advances in the metabolomic study of bladder cancer

INTRODUCTION

Metabolomics is a chemical process, involving the characterization of metabolites and cellular metabolism. Recent studies indicate that numerous metabolic pathways are altered in bladder cancer (BLCA), providing potential targets for improved detection and possible therapeutic intervention. We review recent advances in metabolomics related to BLCA and identify various metabolites that may serve as potential biomarkers for BLCA. Areas covered: In this review, we describe the latest advances in defining the BLCA metabolome and discuss the possible clinical utility of metabolic alterations in BLCA tissues, serum, and urine. In addition, we focus on the metabolic alterations associated with tobacco smoke and racial disparity in BLCA. Expert commentary: Metabolomics is a powerful tool which can shed new light on BLCA development and behavior. Key metabolites may serve as possible markers of BLCA. However, prospective validation will be needed to incorporate these markers into clinical care.