Systemic and Local Metabolic Alterations in Sleep-Deprivation-Induced Stress: A Multiplatform Mass-Spectrometry-Based Lipidomics and Metabolomics Approach

The lipidome landscape of amiodarone toxicity: An in vivo lipid-centric multi-omics study

Amiodarone is an effective therapy for arrhythmias, its prolonged management may lead to significant adverse drug reactions. Amiodarone-induced hepatotoxicity is described by phospholipidosis, hepatic steatosis, cholestatic hepatitis, and cirrhosis. However, the systemic and hepatic lipidome disturbances and underlying toxicological mechanisms remain comprehensively elucidated. Untargeted lipidomics were utilized to analyze serum and liver samples from the rats orally administered a daily dose of amiodarone of either 100 or 300 mg/kg for one week. Changes in the expression of hepatic lipid-related genes were also examined utilizing transcriptomics. We found a higher magnitude of lipidome alterations in the 300 mg/kg than those in the 100 mg/kg groups. Treated animals showed elevated abundances of phosphatidylcholines, ether-linked phosphatidylcholines, sphingomyelins, and ceramides, and decreased levels of triacylglycerols, ether-linked triacylglycerols, and fatty acids. We also found 199 lipid-related differentially expressed hepatic genes between the 300 mg/kg group versus controls, implying lipid metabolism and signaling pathways disturbances. Specifically, elevation of serum phosphatidylcholines and ether-linked phosphatidylcholines, as well as hepatic bismonoacylglycerophosphates might be associated with reduced expression of phospholipase genes and elevated expression of glycerophospholipid biosynthesis genes, possibly driving phospholipidosis. Perturbations of sphingolipid metabolism might also be the key events for amiodarone-induced toxicity. Alterations in gene expression levels related to lipid storage and metabolism, mitochondria functions, and energy homeostasis were also found. Collectively, our study characterized the sophisticated perturbations in the lipidome and transcriptome of amiodarone-treated rats and suggested potential mechanisms responsible for amiodarone-induced hepatotoxicity.

Inadequate sleep increases stroke risk: evidence from a comprehensive meta-analysis of incidence and mortality

The link between abnormal sleep duration and stroke outcomes remains contentious. This meta-analysis quantifies how both short and long sleep durations impact stroke incidence and mortality. A comprehensive search was conducted in PubMed, Web of Science, Cochrane Library, Embase, and Google Scholar up to November 1, 2024, to identify cohort studies evaluating sleep duration and stroke outcomes. Meta-analysis was performed using MetaAnalysisOnline.com and a random-effects model to estimate pooled hazard ratios (HRs). Results were visualized through Forest and Funnel plots. Analysis of 43 studies (35 on stroke incidence, 8 on mortality) revealed significant associations between sleep duration and stroke outcomes. Short sleep duration (≤ 5-6 h) was associated with increased stroke incidence (HR 1.29, 95% CI 1.19-1.40, p < 0.01) and modestly elevated mortality (HR 1.12, 95% CI 1.01-1.25, p = 0.03). Long sleep duration (> 8-9 h) demonstrated stronger associations with both increased stroke incidence (HR 1.46, 95% CI 1.33-1.60, p < 0.01) and mortality (HR 1.45, 95% CI 1.31-1.60, p < 0.01). Significant heterogeneity was observed in incidence studies (I2 = 74-75%), while mortality analyses showed moderate to low heterogeneity (I2 = 35-40%). This meta-analysis highlights a U-shaped association between sleep duration and stroke risk, with both short and long sleep durations linked to higher stroke incidence and mortality. These findings underscore the importance of balanced sleep duration as a modifiable risk factor in stroke prevention strategies and provide a foundation for the Semmelweis Study, a prospective workplace cohort investigating the role of modifiable lifestyle factors in unhealthy cerebrovascular and brain aging.

Integrative Multi-omics Analysis Reveals Different Metabolic Phenotypes Based on Molecular Characteristics in Thyroid Cancer

PURPOSE

Thyroid cancer metabolic characteristics vary depending on the molecular subtype determined by mutational status. We aimed to investigate the molecular subtype-specific metabolic characteristics of thyroid cancers.

EXPERIMENTAL DESIGN

An integrative multi-omics analysis was conducted, incorporating transcriptomics, metabolomics, and proteomics data obtained from human tissues representing distinct molecular characteristics of thyroid cancers: BRAF-like (papillary thyroid cancer with BRAFV600E mutation; PTC-B), RAS-like (follicular thyroid cancer with RAS mutation; FTC-R), and ATC-like (anaplastic thyroid cancer with BRAFV600E or RAS mutation; ATC-B or ATC-R). To validate our findings, we employed tissue microarray of human thyroid cancer tissues and performed in vitro analyses of cancer cell phenotypes and metabolomic assays after inducing genetic knockdown.

RESULTS

Metabolic properties differed between differentiated thyroid cancers of PTC-B and FTC-R, but were similar in dedifferentiated thyroid cancers of ATC-B/R, regardless of their mutational status. Tricarboxylic acid (TCA) intermediates and branched-chain amino acids (BCAA) were enriched with the activation of TCA cycle only in FTC-R, whereas one-carbon metabolism and pyrimidine metabolism increased in both PTC-B and FTC-R and to a great extent in ATC-B/R. However, the protein expression levels of the BCAA transporter (SLC7A5) and a key enzyme in one-carbon metabolism (SHMT2) increased in all thyroid cancers and were particularly high in ATC-B/R. Knockdown of SLC7A5 or SHMT2 inhibited the migration and proliferation of thyroid cancer cell lines differently, depending on the mutational status.

CONCLUSIONS

These findings define the metabolic properties of each molecular subtype of thyroid cancers and identify metabolic vulnerabilities, providing a rationale for therapies targeting its altered metabolic pathways in advanced thyroid cancer.

Unraveling the role of the mitochondrial one-carbon pathway in undifferentiated thyroid cancer by multi-omics analyses

The role of the serine/glycine metabolic pathway (SGP) has recently been demonstrated in tumors; however, the pathological relevance of the SGP in thyroid cancer remains unexplored. Here, we perform metabolomic profiling of 17 tumor-normal pairs; bulk transcriptomics of 263 normal thyroid, 348 papillary, and 21 undifferentiated thyroid cancer samples; and single-cell transcriptomes from 15 cases, showing the impact of mitochondrial one-carbon metabolism in thyroid tumors. High expression of serine hydroxymethyltransferase-2 (SHMT2) and methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is associated with low thyroid differentiation scores and poor clinical features. A subpopulation of tumor cells with high mitochondrial one-carbon pathway activity is observed in the single-cell dataset. SHMT2 inhibition significantly compromises mitochondrial respiration and decreases cell proliferation and tumor size in vitro and in vivo. Collectively, our results highlight the importance of the mitochondrial one-carbon pathway in undifferentiated thyroid cancer and suggest that SHMT2 is a potent therapeutic target.

Unravelling the brain metabolome: A review of liquid chromatography - mass spectrometry strategies for extracellular brain metabolomics

The analysis of the brain extracellular metabolome is of interest for numerous subdomains within neuroscience. Not only does it provide information about normal physiological functions, it is even more of interest for biomarker discovery and target discovery in disease. The extracellular analysis of the brain is particularly interesting as it provides information about the release of mediators in the brain extracellular fluid to look at cellular signaling and metabolic pathways through the release, diffusion and re-uptake of neurochemicals. In vivo samples are obtained through microdialysis, cerebral open-flow microperfusion or solid-phase microextraction. The analytes of potential interest are typically low in concentration and can have a wide range of physicochemical properties. Liquid chromatography coupled to mass spectrometry has proven its usefulness in brain metabolomics. It allows sensitive and specific analysis of low sample volumes, obtained through different approaches. Several strategies for the analysis of the extracellular fluid have been proposed. The most widely used approaches apply sample derivatization, specific stationary phases and/or hydrophilic interaction liquid chromatography. Miniaturization of these methods allows an even higher sensitivity. The development of chiral metabolomics is indispensable, as it allows to compare the enantiomeric ratio of compounds and provides even more challenges. Some limitations continue to exist for the previously developed methods and the development of new, more sensitive methods remains needed. This review provides an overview of the methods developed for sampling and liquid chromatography-mass spectrometry analysis of the extracellular metabolome.

Modulatory effect of n-3 polyunsaturated fatty acids on depressive-like behaviors in rats with chronic sleep deprivation: potential involvement of melatonin receptor pathway and brain lipidome

Clinical evidence suggests that a bidirectional relationship is present between sleep loss and psychiatric disorders. Both melatonin receptor agonist ramelteon (RMT) and n-3 polyunsaturated fatty acids (n-3 PUFAs) exhibit antidepressant effects, while their underlying molecular mechanisms might be different. Thus, the present study aims to investigate the add-on effects and possible mechanisms of how RMT and different n-3 PUFAs modulate the melatonin receptor pathway as well as brain lipidome to ameliorate the neuropsychiatric behaviors displayed in rats under chronic sleep deprivation. Thirty-one 6-week-old male Wistar rats were divided into five groups: control (C), sleep deprivation (S), sleep deprivation treated with RMT (SR), sleep deprivation treated with RMT and eicosapentaenoic acid (C20:5n-3, EPA) (SRE), and sleep deprivation treated with RMT and docosahexaenoic acid (C22:6n-3, DHA) (SRD) groups. The results reveal that RMT plus EPA alleviated depressive-like behavior when the rats were subjected to the forced swimming test, whereas RMT plus DHA alleviated anxiety-like behavior when the rats were subjected to the elevated plus maze test. The results of a western blot analysis further revealed that compared with the rats in the S group, those in the SRE and SRD groups exhibited a significantly increased expression of MT₂ in the prefrontal cortex, with greater benefits observed in the SRE group. In addition, decreased BDNF and TrkB expression levels were upregulated only in the SRE group. Lipidomic analysis further revealed possible involvement of aberrant lipid metabolism and neuropsychiatric behaviors. RMT plus EPA demonstrated promise as having the effects of reversing the levels of the potential biomarkers of depressive-like behaviors. RMT plus EPA or DHA could ameliorate depressive- and anxiety-like behaviors in sleep-deprived rats through the alteration of the lipidome and MT₂ receptor pathway in the brain, whereas EPA and DHA exerted a differential effect.

An integrated targeted metabolomics and network pharmacology approach to exploring the mechanism of ellagic acid against sleep deprivation-induced memory impairment and anxiety

Background

As a neuroprotective agent, ellagic acid (EA) is extremely beneficial. Our previous study found that EA can alleviate sleep deprivation (SD)-induced abnormal behaviors, although the mechanisms underlying this protective effect have not yet been fully elucidated.

Objective

An integrated network pharmacology and targeted metabolomics approach was utilized in this study to investigate the mechanism of EA against SD-induced memory impairment and anxiety.

Methods

Behavioral tests were conducted on mice after 72 h of SD. Hematoxylin and eosin staining and nissl staining were then carried out. Integration of network pharmacology and targeted metabolomics was performed. Eventually, the putative targets were further verified using molecular docking analyses and immunoblotting assays.

Results

The present study findings confirmed that EA ameliorated the behavioral abnormalities induced by SD and prevented histopathological and morphological damage to hippocampal neurons. Through multivariate analysis, clear clustering was obtained among different groups, and potential biomarkers were identified. Four key targets, catechol-O-methyltransferase (COMT), cytochrome P450 1B1 (CYP1B1), glutathione S-transferase A2 (GSTA2), and glutathione S-transferase P1 (GSTP1), as well as the related potential metabolites and metabolic pathways, were determined by further integrated analysis. Meanwhile, in-silico studies revealed that EA is well located inside the binding site of CYP1B1 and COMT. The experimental results further demonstrated that EA significantly reduced the increased expression of CYP1B1 and COMT caused by SD.

Conclusion

The findings of this study extended our understanding of the underlying mechanisms by which EA treats SD-induced memory impairment and anxiety, and suggested a novel approach to address the increased health risks associated with sleep loss.

Impact of spaceflight stressors on behavior and cognition: A molecular, neurochemical, and neurobiological perspective

The response of the human body to multiple spaceflight stressors is complex, but mounting evidence implicate risks to CNS functionality as significant, able to threaten metrics of mission success and longer-term behavioral and neurocognitive health. Prolonged exposure to microgravity, sleep disruption, social isolation, fluid shifts, and ionizing radiation have been shown to disrupt mechanisms of homeostasis and neurobiological well-being. The overarching goal of this review is to document the existing evidence of how the major spaceflight stressors, including radiation, microgravity, isolation/confinement, and sleep deprivation, alone or in combination alter molecular, neurochemical, neurobiological, and plasma metabolite/lipid signatures that may be linked to operationally-relevant behavioral and cognitive performance. While certain brain region-specific and/or systemic alterations titrated in part with neurobiological outcome, variations across model systems, study design, and the conspicuous absence of targeted studies implementing combinations of spaceflight stressors, confounded the identification of specific signatures having direct relevance to human activities in space. Summaries are provided for formulating new research directives and more predictive readouts of portending change in neurobiological function.

Metabolomic and pharmacologic analyses of brain substances associated with sleep pressure in mice

Sleep pressure, the driving force of the homeostatic sleep regulation, is accumulated during wakefulness and dissipated during sleep. Sleep deprivation (SD) has been used as a method to acutely increase animal's sleep pressure for investigating the molecular changes under high sleep pressure. However, SD induces changes not only reflecting increased sleep pressure but also inevitable stresses and prolonged wake state itself. The Sik3^Sleepy mutant mice (Sleepy) exhibit constitutively high sleep pressure despite sleeping longer, and have been useful as a model of increased sleep pressure. Here we conducted a cross-comparison of brain metabolomic profiles between SD versus ad lib slept mice, as well as Sleepy mutant versus littermate wild-type mice. Targeted metabolome analyses of whole brains quantified 203 metabolites in total, of which 43 metabolites showed significant changes in SD, whereas three did in Sleepy mutant mice. The large difference in the number of differential metabolites highlighted limitations of SD as methodology. The cross-comparison revealed that a decrease in betaine and an increase in imidazole dipeptides are associated with high sleep pressure in both models. These metabolites may be novel markers of sleep pressure at the whole-brain level. Furthermore, we found that intracerebroventricular injection of imidazole dipeptides increased subsequent NREM sleep time, suggesting the possibility that imidazole dipeptides may participate in the regulation of sleep in mice.

Human blood serum proteome changes after 6 hours of sleep deprivation at night

Background

The aim of this study was to discover significantly changed proteins in human blood serum after loss of 6 h sleep at night. Furthermore, to reveal affected biological process- and molecular function categories that might be clinically relevant, by exploring systems biological databases.

Methods

Eight females were recruited by volunteer request. Peripheral venous whole blood was sampled at 04:00 am, after 6 h of sleep and after 6 h of sleep deprivation. We used within-subjects design (all subjects were their own control). Blood serum from each subject was depleted before protein digestion by trypsin and iTRAQ labeling. Labled peptides were analyzed by mass spectrometry (LTQ OritrapVelos Elite) connected to a LC system (Dionex Ultimate NCR-3000RS).

Results

We identified 725 proteins in human blood serum. 34 proteins were significantly differentially expressed after 6 h of sleep deprivation at night. Out of 34 proteins, 14 proteins were up-regulated, and 20 proteins were down-regulated. We emphasized the functionality of the 16 proteins commonly differentiated in all 8 subjects and the relation to pathological conditions. In addition, we discussed Histone H4 (H4) and protein S100-A6/Calcyclin (S10A6) that were upregulated more than 1.5-fold. Finally, we discussed affected biological process- and molecular function categories.

Conclusions

Overall, our study suggest that acute sleep deprivation, at least in females, affects several known biological processes- and molecular function categories and associates to proteins that also are changed under pathological conditions like impaired coagulation, oxidative stress, immune suppression, neurodegenerative related disorder, and cancer. Data are available via ProteomeXchange with identifier PXD021004.

Integrated metabolomics and proteomics analysis reveals energy metabolism disorders in the livers of sleep-deprived mice

Sleep deprivation (SD) has been linked to impaired mental and physical health, obesity, and various diseases. However, the molecular mechanism underlying the effects of SD in the liver is still unclear. To investigate the metabolome and proteome alterations in the liver, an in vivo model of SD was established based on automated random motion platform techniques by applying a strategy of 10 consecutive days of 20 h of sleep deprivation +4 h of resting. The liver's altered metabolites and proteins were detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and data analyses were performed with MetaboAnalyst 5.0. This study found 15 differential metabolites, including 12 upregulated- metabolites and 3 downregulated- metabolites. A total of 493 proteins were differentially regulated, including 377 upregulated- proteins and 116 downregulated- proteins. The glutathione metabolism, fructose and mannose metabolism, and pyruvate metabolism pathways had significant effects on the sleep-deprived mouse livers. These three active pathways cause energy metabolism disorder and may induce obesity. In conclusion, this study demonstrates that SD could change the metabolism of glucose, and specific fatty acids, amino acids, and critical enzymes in the liver, providing a reference for the health effects of insufficient sleep. SIGNIFICANCE STATEMENT: So far, little is known about the changes in metabolites and proteins in the liver of individuals who suffer from SD. Metabolites and proteins in serum, urine and hypothalamus do not entirely reflect the effects of sleep deprivation on the whole body. In addition, many SD-induced models used the multiplatform water environment method, which causes mice to fall into the water frequently. Under this condition, the physical exertion of mice is extremely high, and it is not suitable for long-term sleep deprivation. The SD induction process has caused some influence on the model. Finally, few studies have elucidated the imbalance of energy metabolism caused by SD to induce obesity from the molecular mechanism. This study used a rotary table deprivation apparatus to trigger SD. This method will not cause excessive consumption and stimulation of mice. Furthermore, this study analyzed the metabolic and proteomic changes in the liver and enriched the range and means of metabolic and proteomic changes in sleep deprived mice. Finally, this research provides reference for elucidating the molecular mechanism of sleep deprivation causing energy metabolism disorders in the liver of mice.

Machine and Deep Learning in Molecular and Genetic Aspects of Sleep Research

Epidemiological sleep research strives to identify the interactions and causal mechanisms by which sleep affects human health, and to design intervention strategies for improving sleep throughout the lifespan. These goals can be advanced by further focusing on the environmental and genetic etiology of sleep disorders, and by development of risk stratification algorithms, to identify people who are at risk or are affected by, sleep disorders. These studies rely on comprehensive sleep-related data which often contains complex multi-dimensional physiological and molecular measurements across multiple timepoints. Thus, sleep research is well-suited for the application of computational approaches that can handle high-dimensional data. Here, we survey recent advances in machine and deep learning together with the availability of large human cohort studies with sleep data that can jointly drive the next breakthroughs in the sleep-research field. We describe sleep-related data types and datasets, and present some of the tasks in the field that can be targets for algorithmic approaches, as well as the challenges and opportunities in pursuing them.

"Operator syndrome": A unique constellation of medical and behavioral health-care needs of military special operation forces

OBJECTIVE

U.S. military special operation forces represent the most elite units of the U.S. Armed Forces. Their selection is highly competitive, and over the course of their service careers, they experience intensive operational training and combat deployment cycles. Yet, little is known about the health-care needs of this unique population.

METHOD

Professional consultations with over 50 special operation forces operators (and many spouses or girlfriends) over the past 6 years created a naturalistic, observational base of knowledge that allowed our team to identify a unique pattern of interrelated medical and behavioral health-care needs.

RESULTS

We identified a consistent pattern of health-care difficulties within the special operation forces community that we and other special operation forces health-care providers have termed "Operator Syndrome." This includes interrelated health and functional impairments including traumatic brain injury effects; endocrine dysfunction; sleep disturbance; obstructive sleep apnea; chronic joint/back pain, orthopedic problems, and headaches; substance abuse; depression and suicide; anger; worry, rumination, and stress reactivity; marital, family, and community dysfunction; problems with sexual health and intimacy; being "on guard" or hypervigilant; memory, concentration, and cognitive impairments; vestibular and vision impairments; challenges of the transition from military to civilian life; and common existential issues.

CONCLUSIONS

"Operator Syndrome" may be understood as the natural consequences of an extraordinarily high allostatic load; the accumulation of physiological, neural, and neuroendocrine responses resulting from the prolonged chronic stress; and physical demands of a career with the military special forces. Clinical research and comprehensive, intensive immersion programs are needed to meet the unique needs of this community.

Circadian and Sleep Metabolomics Across Species

Under normal circadian function, metabolic control is temporally coordinated across tissues and behaviors with a 24-h period. However, circadian disruption results in negative consequences for metabolic homeostasis including energy or redox imbalances. Yet, circadian disruption has become increasingly prevalent within today's society due to many factors including sleep loss. Metabolic consequences of both have been revealed by metabolomics analyses of circadian biology and sleep. Specifically, two primary analytical platforms, mass spectrometry and nuclear magnetic resonance spectroscopy, have been used to study molecular clock and sleep influences on overall metabolic rhythmicity. For example, human studies have demonstrated the prevalence of metabolic rhythms in human biology, as well as pan-metabolome consequences of sleep disruption. However, human studies are limited to peripheral metabolic readouts primarily through minimally invasive procedures. For further tissue- and organism-specific investigations, a number of model systems have been studied, based upon the conserved nature of both the molecular clock and sleep across species. Here we summarize human studies as well as key findings from metabolomics studies using mice, Drosophila, and zebrafish. While informative, a limitation in existing literature is a lack of interpretation regarding dynamic synthesis or catabolism within metabolite pools. To this extent, future work incorporating isotope tracers, specific metabolite reporters, and single-cell metabolomics may provide a means of exploring dynamic activity in pathways of interest.

Omics approach reveals perturbation of metabolism and phenotype in Caenorhabditis elegans triggered by perfluorinated compounds

Perfluorinated compounds (PFCs) are widely used in consumer products because of their remarkable endurance. However, their distinct stability prolongs degradation, resulting in bioaccumulation in the environment which is a severe environmental issue. Perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) are principal constituents in the PFCs. In this study, the potential toxic effects of PFOS and PFOA were evaluated by adopting an in vivo animal model, Caenorhabditis elegans (C. elegans). The uptake of PFCs was confirmed by the quantification of internal concentration in C. elegans. Metabolomics and lipidomics were applied along with reproduction assay and reactive oxygen species (ROS) assay. In the C. elegans exposed to PFOS and PFOA, amino acids including phenylalanine, tyrosine, and tryptophan, were significantly affected. Also, various species that belong to glycerophospholipids and triacylglycerol were perturbed in the exposed groups. The alteration patterns of the lipidome in PFOS and PFOA treated C. elegans were significantly different. Additionally, dichlorodihydrofluorescein diacetate (H₂DCFDA)-based ROS assay revealed increased internal ROS in PFOS (1.5 fold, p-value = 0.0067) and PFOA (1.46 fold, p-value = 0.0253) groups. Decrease in reproduction was confirmed in PFOS (0.53 fold, p-value < 0.0001) and PFOA (0.69 fold, p-value = 0.0003) by counting progeny. Collectively, our findings suggest that exposure to PFCs in C. elegans leads to perturbation of various phenotypes as well as crucial amino acid and lipid metabolism.

Feeding the Outer Bran Fraction of Rice Alters Hepatic Carbohydrate Metabolism in Rats

Dietary intake of fiber-rich food has been reported to contribute to multiple health benefits. The aim of the current study is to investigate the effects of a diet containing the outer bran fraction of rice (OBFR), which is rich in insoluble fiber, on the intestinal environment and metabolite profiles of rats. Fourteen 8-week-old male Sprague–Dawley rats were divided into a control group and an OBFR group. For a period of 21 days, the control group was fed a control diet, while the OBFR group was fed a diet containing 5% OBFR. Metabolomics analysis revealed drastic changes in the cecal metabolites of the rats fed the OBFR diet. Furthermore, in the plasma and liver tissue, the concentrations of metabolites involved in pyruvate metabolism, the pentose phosphate pathway, gluconeogenesis, or valine, leucine, isoleucine degradation were changed. Concordantly, the OBFR diet increased the expression of genes encoding enzymes involved in these metabolic pathways in the livers of the rats. Collectively, these results suggest that the OBFR diet altered the concentrations of metabolites in the cecal contents, plasma, and liver, and the hepatic gene expressions of rats, and that this may have mainly contributed to carbohydrate metabolism in the liver.

Comprehensive Multi-Omics Analysis Reveals Aberrant Metabolism of Epstein-Barr-Virus-Associated Gastric Carcinoma

The metabolic landscape of Epstein–Barr-virus-associated gastric cancer (EBVaGC) remains to be elucidated. In this study, we used transcriptomics, metabolomics, and lipidomics to comprehensively investigate aberrant metabolism in EBVaGC. Specifically, we conducted gene expression analyses using microarray-based data from gastric adenocarcinoma epithelial cell lines and tissue samples from patients with clinically advanced gastric carcinoma. We also conducted complementary metabolomics and lipidomics using various mass spectrometry platforms. We found a significant downregulation of genes related to metabolic pathways, especially the metabolism of amino acids, lipids, and carbohydrates. The effect of dysregulated metabolic genes was confirmed in a survival analysis of 3951 gastric cancer patients. We found 57 upregulated metabolites and 31 metabolites that were downregulated in EBVaGC compared with EBV-negative gastric cancer. Sixty-nine lipids, mainly ether-linked phospholipids and triacylglycerols, were downregulated, whereas 45 lipids, mainly phospholipids, were upregulated. In total, 15 metabolisms related to polar metabolites and 15 lipid-associated pathways were involved in alteration of metabolites by EBV in gastric cancer. In this work, we have described the metabolic landscape of EBVaGC at the multi-omics level. These findings could help elucidate the mechanism of EBVaGC oncogenesis.

Steroidomics for the Prevention, Assessment, and Management of Cancers: A Systematic Review and Functional Analysis

Steroidomics, an analytical technique for steroid biomarker mining, has received much attention in recent years. This systematic review and functional analysis, following the PRISMA statement, aims to provide a comprehensive review and an appraisal of the developments and fundamental issues in steroid high-throughput analysis, with a focus on cancer research. We also discuss potential pitfalls and proposed recommendations for steroidomics-based clinical research. Forty-five studies met our inclusion criteria, with a focus on 12 types of cancer. Most studies focused on cancer risk prediction, followed by diagnosis, prognosis, and therapy monitoring. Prostate cancer was the most frequently studied cancer. Estradiol, dehydroepiandrosterone, and cortisol were mostly reported and altered in at least four types of cancer. Estrogen and estrogen metabolites were highly reported to associate with women-related cancers. Pathway enrichment analysis revealed that steroidogenesis; androgen and estrogen metabolism; and androstenedione metabolism were significantly altered in cancers. Our findings indicated that estradiol, dehydroepiandrosterone, cortisol, and estrogen metabolites, among others, could be considered oncosteroids. Despite noble achievements, significant shortcomings among the investigated studies were small sample sizes, cross-sectional designs, potential confounding factors, and problematic statistical approaches. More efforts are required to establish standardized procedures regarding study design, analytical procedures, and statistical inference.