Metabolic characterization of hepatocellular carcinoma using nontargeted tissue metabolomics

Identifying biomarkers for nasopharyngeal carcinoma diagnosis and chemoradiotherapy response using serum endogenous small molecules profiling

Changes in metabolic characteristics are important features of tumor progression and prognosis, including nasopharyngeal carcinoma (NPC). Identifying serum metabolites as potential diagnostic and chemoradiotherapy response biomarkers for NPC is therefore crucial. In this study, ultra-performance liquid chromatography coupled with linear ion trap quadrupole orbitrap high-resolution mass spectrometry (UPLC-LTQ-Orbitrap MS) was used to analyze metabolic variations among controls, NPC patients, and NPC patients undergoing chemoradiotherapy (CRT). Univariate and multivariate analyses revealed seven differential metabolites between the control and NPC groups and eleven metabolites between the CRT and NPC groups. Five common metabolites, gluconic acid, palmitic acid, LysoPC (15:0/0:0), stearic acid, and LysoPC (20:2(11Z,14Z)/0:0), were consistently altered across groups. Notably, the first four metabolites were adjusted closer to normal after chemoradiotherapy, while this change is not reflected at LysoPC (20:2(11Z,14Z)/0:0). These common metabolites were enriched in five pathways. These findings underscore the importance of serum metabolite profiling in NPC diagnosis and treatment response assessment and offer a promising foundation for further clinical research.

Alterations of Ceramides, Acylcarnitines, GlyceroLPLs, and Amines in NSCLC Tissues

Abnormal lipid metabolism plays an important role in cancer development. In this study, nontargeted lipidomic study on 230 tissue specimens from 79 nonsmall cell lung cancer (NSCLC) patients was conducted using ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS). Downregulation of sphingosine and medium-long-chain ceramides and short-medium-chain acylcarnitine, upregulation of long-chain acylcarnitine C20:0, and enhanced histamine methylation were revealed in NSCLC tissues. Compared with paired noncancerous tissues, adenocarcinoma (AC) tissues had significantly decreased levels of sphingosine, medium-long-chain ceramides (Cer d18:1/12:0 and Cer d16:1/14:0, Cer d18:0/16:0, Cer d18:1/16:0, Cer d18:2/16:0, Cer d18:2/18:0), short-medium-chain (C2-C16) acylcarnitines, LPC 20:0 and LPC 22:1, and significantly increased levels of the long-chain acylcarnitine C20:0, LPC 16:0, LPC P-16:0, LPC 20:1, LPC 20:2, glyceroPC, LPE 16:0, and LPE 18:2. In squamous cell carcinoma (SCC) tissues, sphingosine, Cer d18:2/16:0 and Cer d18:2/18:0, and short-medium-chain acylcarnitines had significantly lower levels, while long-chain acylcarnitines (C20:0, and C22:0 or C22:0 M), LPC 20:1, LPC 20:2, and N1,N12-diacetylspermine had significantly higher levels compared to controls. In AC and SCC tissues, the levels of LPG 18:0, LPG 18:1, and LPS 18:1 were significantly decreased, while the levels of ceramide-1-phosphate (C1P) d18:0/3:0 or LPE P-16:0, N1-acetylspermidine, and 1-methylhistamine were significantly increased than controls. Furthermore, an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model based on a 4-lipid panel was established, showing good discrimination ability between cancerous and noncancerous tissues.

Mitochondrial metabolism: A moving target in hepatocellular carcinoma therapy

Mitochondria are pivotal contributors to cancer mechanisms due to their homeostatic and pathological roles in cellular bioenergetics, biosynthesis, metabolism, signaling, and survival. During transformation and tumor initiation, mitochondrial function is often disrupted by oncogenic mutations, leading to a metabolic profile distinct from precursor cells. In this review, we focus on hepatocellular carcinoma, a cancer arising from metabolically robust and nutrient rich hepatocytes, and discuss the mechanistic impact of altered metabolism in this setting. We provide distinctions between normal mitochondrial activity versus disease-related function which yielded therapeutic opportunities, along with highlighting recent preclinical and clinical efforts focused on targeting mitochondrial metabolism. Finally, several novel strategies for exploiting mitochondrial programs to eliminate hepatocellular carcinoma cells in metabolism-specific contexts are presented to integrate these concepts and gain foresight into the future of mitochondria-focused therapeutics.

Identification of the Metabolic Signature of Aging Retina

Purpose

This study aims to explore the metabolic signature of aging retina and identify the potential metabolic biomarkers for the diagnosis of retinal aging.

Methods

Retinal samples were collected from both young (two months) and aging (14 months) mice to conduct an unbiased metabolic profiling. Liquid chromatography-tandem mass spectrometry analysis was conducted to screen for the metabolic biomarkers and altered signaling pathways associated with retinal aging.

Results

We identified 166 metabolites differentially expressed between young and aged retinas using a threshold of orthogonal projection to latent structures discriminant analysis variable importance in projection >1 and P < 0.05. These metabolites were significantly enriched in several metabolic pathways, including purine metabolism, citrate cycle, phenylalanine, tyrosine and tryptophan biosynthesis, glycerophospholipid metabolism, and alanine, aspartate and glutamate metabolism. Among these significantly enriched pathways, glycerophospholipid metabolites emerged as promising candidates for retinal aging biomarkers. We assessed the potential of these metabolites as biomarkers through an analysis of their sensitivity and specificity, determined by the area under the receiver-operating characteristic (ROC) curves. Notably, the metabolites like PC (15:0/22:6), PC (17:0/14:1), LPC (P-16:0), PE (16:0/20:4), and PS (17:0/16:1) demonstrated superior performance in sensitivity, specificity, and accuracy in predicting retinal aging.

Conclusions

This study sheds light on the molecular mechanisms underlying retinal aging by identifying distinct metabolic profiles and pathways. These findings provide a valuable foundation for developing future clinical applications in diagnosing, identifying, and treating age-related retinal degeneration.

Translational Relevance

This study sheds light on novel metabolic profiles and biomarkers in aging retinas, potentially paving the way for targeted interventions in preventing, diagnosing, and treating age-related retinal degeneration and other retinal diseases.

Metabolic reprogramming in hepatocellular carcinoma: a bibliometric and visualized study from 2011 to 2023

Background and aims

Metabolic reprogramming has been found to be a typical feature of tumors. Hepatocellular carcinoma (HCC), a cancer with high morbidity and mortality, has been extensively studied for its metabolic reprogramming-related mechanisms. Our study aims to identify the hotspots and frontiers of metabolic reprogramming research in HCC and to provide guidance for future scientific research and decision-making in HCC metabolism.

Methods

Relevant studies on the metabolic reprogramming of HCC were derived from the Web of Science Core Collection (WoSCC) database up until November 2023. The bibliometrix tools in R were used for scientometric analysis and visualization.

Results

From 2011 to 2023, a total of 575 publications were obtained from WoSCC that met the established criteria. These publications involved 3,904 researchers and 948 organizations in 37 countries, with an average annual growth rate of 39.11% in research. These studies were published in 233 journals, with Cancers (n = 29) ranking first, followed by Frontiers in Oncology (n = 20) and International Journal of Molecular Sciences (n = 19). The top ten journals accounted for 26% of the 575 studies. The most prolific authors were Wang J (n = 14), Li Y (n = 12), and Liu J (n = 12). The country with the most publications is China, followed by the United States, Italy, and France. Fudan University had the largest percentage of research results with 15.48% (n = 89). Ally A's paper in Cell has the most citations. A total of 1,204 keywords were analyzed, with the trend themes such as "glycolysis," "tumor microenvironment," "Warburg effect," "mitochondria," "hypoxia ," etc. Co-occurrence network and cluster analysis revealed the relationships between keywords, authors, publications, and journals. Moreover, the close collaboration between countries in this field was elucidated.

Conclusion

This bibliometric and visual analysis delves into studies related to metabolic reprogramming in HCC between 2012 and 2023, elucidating the characteristics of research in this field, which has gradually moved away from single glycolipid metabolism studies to the integration of overall metabolism in the body, pointing out the trend of research topics, and the dynamics of the interaction between the tumor microenvironment and metabolic reprogramming will be the future direction of research, which provides blueprints and inspirations for HCC prevention and treatment programs to the researchers in this field.

Systematic Review Registration: [https://www.bibliometrix.org].

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

Early interferon lambda production is induced by double-stranded RNA in iPS-derived hepatocyte-like cells

Hepatotropic viruses are amongst the most ubiquitous pathogens worldwide, causing significant morbidity and mortality. As hepatocytes are among the primary targets of these viruses, their ability to mount early effective innate defence responses is of major research interest. Interferon lambda (IFNL) is produced early in response to viral stimulation in other cell types, but hepatocyte production of this interferon is little investigated. Due to the difficulty and significant costs in obtaining and culturing human primary hepatocytes, surrogate systems are widely sought. Here we used induced pluripotent stem (iPS)-derived hepatocyte-like cells (HLCs) to investigate hepatic IFNL expression in response to viral-like ligands. We demonstrate that hepatocytes rely on cytoplasmic pattern recognition receptors (PRRs) such as Protein Kinase RNA-dependent (PKR) and retinoic acid-inducible gene-I (RIG-I)-like receptors (RLR) for the detection of double stranded RNA. Stimulation of HLCs by viral-like RNA ligands activating cytosolic RNA sensors resulted in thousand fold increase of type III interferon gene expression. These results are in contrast with type I IFN expression, which was induced to a lower extent. Concomitant induction of interferon stimulated genes, such as interferon-stimulated gene 15 (ISG15) and CXCL10, indicated the ability of HLCs to activate interferon-dependent activity. These results demonstrate that HLCs mount an innate antiviral response upon stimulation with viral-like RNA characterized by the induction of type III IFN.

Advanced Mass Spectrometry-Based Biomarker Identification for Metabolomics of Diabetes Mellitus and Its Complications

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

Glutamine metabolism, a double agent combating or fuelling hepatocellular carcinoma

The reprogramming of glutamine metabolism is a key event in cancer more generally and in hepatocellular carcinoma (HCC) in particular. Glutamine consumption supplies tumours with ATP and metabolites through anaplerosis of the tricarboxylic acid cycle, while glutamine production can be enhanced by the overexpression of glutamine synthetase. In HCC, increased glutamine production is driven by activating mutations in the CTNNB1 gene encoding β-catenin. Increased glutamine synthesis or utilisation impacts tumour epigenetics, oxidative stress, autophagy, immunity and associated pathways, such as the mTOR (mammalian target of rapamycin) pathway. In this review, we will discuss studies which emphasise the pro-tumoral or tumour-suppressive effect of glutamine overproduction. It is clear that more comprehensive studies are needed as a foundation from which to develop suitable therapies targeting glutamine metabolic pathways, depending on the predicted pro- or anti-tumour role of dysregulated glutamine metabolism in distinct genetic contexts.

Concentric Hybrid Nanoelectrospray Ionization-Atmospheric Pressure Chemical Ionization Source for High-Coverage Mass Spectrometry Analysis of Single-Cell Metabolomics

High-coverage mass spectrometry analysis of single-cell metabolomics remains challenging due to the extremely low abundance and wide polarity of metabolites and ultra-small volume in single cells. Herein, a novel concentric hybrid ionization source, nanoelectrospray ionization-atmospheric pressure chemical ionization (nanoESI-APCI), is ingeniously designed to detect polar and nonpolar metabolites simultaneously in single cells. The source is constructed by inserting a pulled glass capillary coaxially into a glass tube that acts as a dielectric barrier layer. Benefitting from the integrated advantages of nanoESI and APCI, its limit of detection is improved by one order of magnitude to 10 pg mL-1. After the operational parameter optimization, 254 metabolites detected in nanoESI-APCI are tentatively identified from a single cell, and 82 more than those in nanoESI. The developed nanoESI-APCI is successively applied to study the metabolic heterogeneity of human hepatocellular carcinoma tissue microenvironment united with laser capture microdissection (LCM), the discrimination of cancer cell types and subtypes, the metabolic perturbations to glucose starvation in MCF7 cells and the metabolic regulation of cancer stem cells. These results demonstrated that the nanoESI-APCI not only opens a new avenue for high-coverage and high-sensitivity metabolomics analysis of single cell, but also facilitates spatially resolved metabolomics study coupled with LCM.

Echinacea purpurea polysaccharide intervene in hepatocellular carcinoma via modulation of gut microbiota to inhibit TLR4/NF-κB pathway

Echinacea purpurea polysaccharide (EPP) exhibit various pharmacological activities, including immunomodulatory, anti-inflammatory, and anti-tumor effects. In this study, we investigated the potential mechanism of EPP intervention in hepatocellular carcinoma (HCC). The results demonstrated that EPP effectively mitigated liver injury caused by HCC, inhibited the proliferation of HCC, and induced apoptosis. Following EPP intervention, there was a significant increase in propionic acid and butyric acid-producing gut microbiota such as Coprococcus, Clostridium and Roseburia, leading to enhanced expression of intestinal tight junction proteins and the repair of the intestinal barrier. This controls lipopolysaccharide (LPS) leakage, which in turn inhibits the TLR4/NF-κB pathway and reduces the expression of inflammatory factors such as IL-6, as well as migration factors like MMP-2. Metabolomics revealed the downregulation of pyrimidine metabolism and nucleotide metabolism, along with the upregulation of butyrate metabolism in tumor cells. This study demonstrated that EPP effectively regulated LPS leakage by modulating gut microbes, and this modulation influenced the TLR4/NF-κB pathway, ultimately disrupting tumor cell survival induced by HCC in mice.

Non-targeted metabolomics study for discovery of hepatocellular carcinoma serum diagnostic biomarker

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant cancers worldwide. Due to the asymptomatic features of HCC at early stages, patients are often diagnosed at advanced stages and missed effective treatment. Thus, there is an urgent need to identify sensitive and specific biomarkers for HCC early diagnosis. In the present study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) approach was used to profile serum metabolites from HCC patients, liver cirrhosis (LC) patients, and normal controls (NC). Univariate and multivariate statistical analyses were performed to obtain the metabolomic differences of the three groups and select significantly changed metabolites that can be used as diagnostic biomarkers. In total, 757 differential metabolites were quantified among the three groups, and pathway enrichment analysis of these metabolites indicated that glycerophospholipid metabolism, pentose and glucuronate interconversions, phenylalanine, tyrosine and tryptophan biosynthesis, and linoleic acid metabolism were the most altered pathways involved in HCC development. Receiver operating characteristic (ROC) curve analysis was performed to select and evaluate the diagnostic biomarker performance. Seven metabolites were identified as potential biomarkers that can differentiate HCC from LC and NC, and LC from NC with the good diagnostic performance of area under the curve (AUC) from 0.890 to 0.990. In summary, our findings provide highly effective biomarker candidates to differentiate HCC from LC and NC, LC, and NC, which shed insight into HCC pathological mechanisms and will be helpful in better understanding and managing HCC.

Metabolic reprogramming in the tumor microenvironment of liver cancer

The liver is essential for metabolic homeostasis. The onset of liver cancer is often accompanied by dysregulated liver function, leading to metabolic rearrangements. Overwhelming evidence has illustrated that dysregulated cellular metabolism can, in turn, promote anabolic growth and tumor propagation in a hostile microenvironment. In addition to supporting continuous tumor growth and survival, disrupted metabolic process also creates obstacles for the anticancer immune response and restrains durable clinical remission following immunotherapy. In this review, we elucidate the metabolic communication between liver cancer cells and their surrounding immune cells and discuss how metabolic reprogramming of liver cancer impacts the immune microenvironment and the efficacy of anticancer immunotherapy. We also describe the crucial role of the gut-liver axis in remodeling the metabolic crosstalk of immune surveillance and escape, highlighting novel therapeutic opportunities.

Integrated plasma metabolomics and lipidomics profiling highlights distinctive signature of hepatocellular carcinoma in HCV patients

BACKGROUND

Early diagnosis of hepatocellular carcinoma (HCC) is essential towards the improvement of prognosis and patient survival. Circulating markers such as α-fetoprotein (AFP) and micro-RNAs represent useful tools but still have limitations. Identifying new markers can be fundamental to improve both diagnosis and prognosis. In this approach, we harness the potential of metabolomics and lipidomics to uncover potential signatures of HCC.

METHODS

A combined untargeted metabolomics and lipidomics plasma profiling of 102 HCV-positive patients was performed by HILIC and RP-UHPLC coupled to Mass Spectrometry. Biochemical parameters of liver function (AST, ALT, GGT) and liver cancer biomarkers (AFP, CA19.9 e CEA) were evaluated by standard assays.

RESULTS

HCC was characterized by an elevation of short and long-chain acylcarnitines, asymmetric dimethylarginine, methylguanine, isoleucylproline and a global reduction of lysophosphatidylcholines. A supervised PLS-DA model showed that the predictive accuracy for HCC class of metabolomics and lipidomics was superior to AFP for the test set (100.00% and 94.40% vs 55.00%). Additionally, the model was applied to HCC patients with AFP values < 20 ng/mL, and, by using only the top 20 variables selected by VIP scores achieved an Area Under Curve (AUC) performance of 0.94.

CONCLUSION

These exploratory findings highlight how metabo-lipidomics enables the distinction of HCC from chronic HCV conditions. The identified biomarkers have high diagnostic potential and could represent a viable tool to support and assist in HCC diagnosis, including AFP-negative patients.

Effects of food-borne docosahexaenoic acid supplementation on bone lead mobilisation, mitochondrial function and serum metabolomics in pre-pregnancy lead-exposed lactating rats

Large bone lead (Pb) resulting from high environmental exposure during childhood is an important source of endogenous Pb during pregnancy and lactation. Docosahexaenoic acid (DHA) attenuates Pb toxicity, however, the effect of DHA on bone Pb mobilisation during lactation has not been investigated. We aimed to study the effects of DHA supplementation during pregnancy and lactation on bone Pb mobilisation during lactation and its potential mechanisms. Weaning female rats were randomly divided into control (0.05% sodium acetate) and Pb-exposed (0.05% Pb acetate) groups, after a 4-week exposure by ad libitum drinking and a subsequent 4-week washout period, all female rats were mated with healthy males until pregnancy. Then exposed rats were randomly divided into Pb and Pb + DHA groups, and the latter was given a 0.14% DHA diet, while the remaining groups were given normal feed until the end of lactation. Pb and calcium levels, bone microarchitecture, bone turnover markers, mitochondrial function and serum metabolomics were analyzed. The results showed that higher blood and bone Pb levels were observed in the Pb group compared to the control, and there was a significant negative correlation between blood and bone Pb. Also, Pb increased trabecular bone loss along with slightly elevated serum C-telopeptide of type I collagen (CTX-I) levels. However, DHA reduced CTX-I levels and improved trabecular bone microarchitecture. Metabolomics showed that Pb affected mitochondrial function, which was further demonstrated in bone tissue by significant reductions in ATP levels, Na+-K+-ATPase, Ca2+-Mg2+-ATPase and CAT activities, and elevated levels of MDA, IL-1β and IL-18. However, these alterations were partially mitigated by DHA. In conclusion, DHA supplementation during pregnancy and lactation improved bone Pb mobilisation and mitochondrial dysfunction in lactating rats induced by pre-pregnancy Pb exposure, providing potential means of mitigating bone Pb mobilisation levels during lactation, but the mechanism still needs further study.

Metabolic reprogramming and its clinical implication for liver cancer

Cancer cells often encounter hypoxic and hypo-nutrient conditions, which force them to make adaptive changes to meet their high demands for energy and various biomaterials for biomass synthesis. As a result, enhanced catabolism (breakdown of macromolecules for energy production) and anabolism (macromolecule synthesis from bio-precursors) are induced in cancer. This phenomenon is called "metabolic reprogramming," a cancer hallmark contributing to cancer development, metastasis, and drug resistance. HCC and cholangiocarcinoma (CCA) are 2 different liver cancers with high intertumoral heterogeneity in terms of etiologies, mutational landscapes, transcriptomes, and histological representations. In agreement, metabolism in HCC or CCA is remarkably heterogeneous, although changes in the glycolytic pathways and an increase in the generation of lactate (the Warburg effect) have been frequently detected in those tumors. For example, HCC tumors with activated β-catenin are addicted to fatty acid catabolism, whereas HCC tumors derived from fatty liver avoid using fatty acids. In this review, we describe common metabolic alterations in HCC and CCA as well as metabolic features unique for their subsets. We discuss metabolism of NAFLD as well, because NAFLD will likely become a leading etiology of liver cancer in the coming years due to the obesity epidemic in the Western world. Furthermore, we outline the clinical implication of liver cancer metabolism and highlight the computation and systems biology approaches, such as genome-wide metabolic models, as a valuable tool allowing us to identify therapeutic targets and develop personalized treatments for liver cancer patients.

The Role of Mass Spectrometry in Hepatocellular Carcinoma Biomarker Discovery

Hepatocellular carcinoma (HCC) is the main liver malignancy and has a high mortality rate. The discovery of novel biomarkers for early diagnosis, prognosis, and stratification purposes has the potential to alleviate its disease burden. Mass spectrometry (MS) is one of the principal technologies used in metabolomics, with different experimental methods and machine types for different phases of the biomarker discovery process. Here, we review why MS applications are useful for liver cancer, explain the MS technique, and briefly summarise recent findings from metabolomic MS studies on HCC. We also discuss the current challenges and the direction for future research.

Analysis of the Inhibitory Effect of hsa-miR-145-5p and hsa-miR-203a-5p on Imatinib-Resistant K562 Cells by GC/MS Metabolomics Method

Imatinib (IM) resistance is considered to be a significant challenge in the management of chronic myeloid leukemia (CML). Previous studies have reported that hsa-miR-145-5p and hsa-miR-203a-5p can overcome IM resistance and hsa-miR-203a-5p can alter glutathione metabolism in IM-resistant cells. The purpose of this study was to examine whether hsa-miR-145-5p or hsa-miR-203a-5p counters IM resistance by targeting the overall metabolic profile of IM-resistant K562 cells. The metablic profiling of cell lysates obtained from IM-sensitive, IM-resistant, and miR-transfected IM-resistant K562 cells was carried out using the GC-MS technique. Overall, 75 major metabolites were detected, of which 32 were present in all samples. The pathway analysis of MetaboAnalyst 5.0 revealed that the majorly enriched pathways included glucose metabolism, fatty acid biosynthesis, lipogenesis, and nucleotide metabolism. Eleven of identified metabolites, l-glutamine, l-glutamic acid, l-lactic acid, phosphoric acid, 9,12-octadecadienoic acid, 9-octadecenoic acid, myristic acid, palmitic acid, cholesterol, and β-alanine, appeared in enriched pathways. IM-resistant cells had comparatively higher concentrations of all of these metabolites. Notably, the introduction of hsa-miR-145-5p or hsa-miR-203a-5p into resistant cells resulted in a decrease in levels of these metabolites. The efficacy of miR-203a-5p was particularly remarkable in comparison with miR-145-5p, as evidenced by partial least-squares-discriminant analysis (PLS-DA), which showed a high level of similarity in metabolic profile between IM-sensitive K562 cells and IM-resistant cells transfected with hsa-miR-203a-5p. The results indicate that GC-MS-based metabolic profiling has the potential to distinguish between drug-resistant and -sensitive cells. This approach can also be used to routinely monitor therapeutic response in drug-resistant patients, thus, enabling personalized therapy.

Targeted Energy Metabolomics Combined with Spatial Metabolomics Study on the Efficacy of Guhong Injection Against Cerebral Ischemia Reperfusion

Optimizing the metabolic phenotype to improve cerebral function is critical for treatment of cerebral ischemia-reperfusion (I/R) injury. Guhong injection (GHI), which comprised safflower extract and aceglutamide, is widely prescribed in Chinese medicine for the treatment of cerebrovascular diseases. In this study, a combination of LC-QQQ-MS and MALDI-MSI were utilized to explore tissue-specific metabolic alterations in the brain of I/R, as well as to evaluate the therapeutic effect of GHI. Pharmacological evaluation demonstrated that GHI can significantly improve infarction rate, neurological deficit, cerebral blood flow, and neuronal damage in I/R rats. Based on LC-QQQ-MS, 23 energy metabolites were found to be significantly altered in the I/R group compared to the sham group (P < 0.05). After GHI treatment, 12 metabolites, including G6P, TPP, NAD, citrate, succinate, malate, ATP, GTP, GDP, ADP, NADP, and FMN showed a significant tendency of returning to baseline values (P < 0.05). Based on MALDI-MSI, 4 metabolites in glycolysis and TCA, 4 metabolites in nucleic acid metabolism, 4 amino acid metabolites, and 6 metabolites were discovered and compared between the different groups in the four special regions of cortex, hippocampus, hypothalamus, and striatum. Parts of these were found to have significant changes after I/R in the special brain region, and were regulated by GHI. The study provides comprehensive and detailed information for specific metabolic reprogramming of brain tissue in rats with I/R, and the therapeutic effect of GHI. Schema describing the discovery strategies of integrated LC-MS and MALDI-MSI to identify cerebral ischemia reperfusion metabolic reprogramming and GHI therapeutic effects.

miR-21-5p promotes NASH-related hepatocarcinogenesis

BACKGROUND AND AIMS

The mechanisms governing the progression of non-alcoholic fatty liver disease (NAFLD) towards steatohepatitis (NASH) and hepatocellular carcinoma (HCC) remain elusive. Here, we evaluated the role of hsa-miRNA-21-5p in NASH-related hepatocarcinogenesis.

METHODS

Hepatic hsa-miR-21-5p expression was evaluated in two cohorts of patients with biopsy-proven NAFLD (n = 199) or HCC (n = 366 HCC and n = 11 NAFLD-HCC). Serum/liver metabolomic profiles were correlated with hsa-miR-21-5p in NAFLD obese patients. Wild-type (WT) and Mir21 KO mice were fed a choline-deficient, amino acid-defined (CDAA) diet for 32 and 66 weeks to induce NASH and NASH-HCC, respectively.

RESULTS

In obese individuals, hsa-miR-21-5p expression increased with NAFLD severity and associated with a hepatic lipotoxic profile. CDAA-fed WT mice displayed increased hepatic mmu-miR-21-5p levels and progressively developed NASH and fibrosis, with livers presenting macroscopically discernible pre-neoplastic nodules, hyperplastic foci and deregulated cancer-related pathways. Mir21 KO mice exhibited peroxisome-proliferator-activated receptor α (PPARα) activation, augmented mitochondrial activity, reduced liver injury and NAS below the threshold for NASH diagnosis, with the pro-inflammatory/fibrogenic milieu reversing to baseline levels. In parallel, Mir21 KO mice displayed reduced number of pre-neoplastic nodules, hepatocyte proliferation and activation of oncogenic signalling, being protected from NASH-associated carcinogenesis. The hsa-miRNA-21-5p/PPARα pathway was similarly deregulated in patients with HCC- or NASH-related HCC, correlating with HCC markers and worse prognosis.

CONCLUSIONS

Hsa-miR-21-5p is a key inducer of whole-spectrum NAFLD progression, from simple steatosis to NASH and NASH-associated carcinogenesis. The inhibition of hsa-miR-21-5p, leading to a pro-metabolic profile, might constitute an appealing therapeutic approach to ameliorate NASH and prevent progression towards HCC.

Loss of hepatic FTCD promotes lipid accumulation and hepatocarcinogenesis by upregulating PPARγ and SREBP2

Background & Aims

Exploiting key regulators responsible for hepatocarcinogenesis is of great importance for the prevention and treatment of hepatocellular carcinoma (HCC). However, the key players contributing to hepatocarcinogenesis remain poorly understood. We explored the molecular mechanisms underlying the carcinogenesis and progression of HCC for the development of potential new therapeutic targets.

Methods

The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and Genotype-Tissue Expression (GTEx) databases were used to identify genes with enhanced expression in the liver associated with HCC progression. A murine liver-specific Ftcd knockout (Ftcd-LKO) model was generated to investigate the role of formimidoyltransferase cyclodeaminase (FTCD) in HCC. Multi-omics analysis of transcriptomics, metabolomics, and proteomics data were applied to further analyse the molecular effects of FTCD expression on hepatocarcinogenesis. Functional and biochemical studies were performed to determine the significance of loss of FTCD expression and the therapeutic potential of Akt inhibitors in FTCD-deficient cancer cells.

Results

FTCD is highly expressed in the liver but significantly downregulated in HCC. Patients with HCC and low levels of FTCD exhibited worse prognosis, and patients with liver cirrhosis and low FTCD levels exhibited a notable higher probability of developing HCC. Hepatocyte-specific knockout of FTCD promoted both chronic diethylnitrosamine-induced and spontaneous hepatocarcinogenesis in mice. Multi-omics analysis showed that loss of FTCD affected fatty acid and cholesterol metabolism in hepatocarcinogenesis. Mechanistically, loss of FTCD upregulated peroxisome proliferator-activated receptor (PPAR)γ and sterol regulatory element-binding protein 2 (SREBP2) by regulating the PTEN/Akt/mTOR signalling axis, leading to lipid accumulation and hepatocarcinogenesis.

Conclusions

Taken together, we identified a FTCD-regulated lipid metabolic mechanism involving PPARγ and SREBP2 signaling in hepatocarcinogenesis and provide a rationale for therapeutically targeting of HCC driven by downregulation of FTCD.

Impact and implications

Exploiting key molecules responsible for hepatocarcinogenesis is significant for the prevention and treatment of HCC. Herein, we identified formimidoyltransferase cyclodeaminase (FTCD) as the top enhanced gene, which could serve as a predictive and prognostic marker for patients with HCC. We generated and characterised the first Ftcd liver-specific knockout murine model. We found loss of FTCD expression upregulated peroxisome proliferator-activated receptor (PPAR)γ and sterol regulatory element-binding protein 2 (SREBP2) by regulating the PTEN/Akt/mTOR signalling axis, leading to lipid accumulation and hepatocarcinogenesis, and provided a rationale for therapeutic targeting of HCC driven by downregulation of FTCD.

Mass spectrometry-based metabolic profiling for identification of biomarkers related to footpad dermatitis in ducks

1. A new assessment method for duck footpad dermatitis (FPD) evaluation was developed, combining visual and histological characters using the images and sections of 400 ducks' feet at 340 d of age. All ducks were graded as G0 (healthy), G1 (mild), G2 (moderate) and G3 (severe) according to the degree of FPD.2. To reveal the potential biomarkers in serum related to duck FPD, non-targeted metabolomics and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to explore differential metabolites in each group.3. There were 57, 91 and 210 annotated differential metabolites in groups G1, G2 and G3 compared with G0, which meant that the severity of FPD increased in line with the number of metabolites. Four metabolites, L-phenylalanine, L-arginine, L-leucine and L-lysine, were considered potential biomarkers related to FPD.4. KEGG enrichment analysis showed that the FPD was mainly involved in glycolysis, the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway and amino acid metabolism. These are related to production metabolism and can affect the physiological activities of ducks, which might explain the decrease in production performance.

Analysis of proteome and post-translational modifications of 2-hydroxyisobutyrylation reveals the glycolysis pathway in oral adenoid cystic carcinoma

PURPOSE

Oral adenoid cystic carcinoma (OACC) has high rates of both local-regional recurrence and distant metastasis. The objective of this study is to investigate the impact of Khib on OACC and its potential as a targeted therapeutic intervention. EXPERIMENTAL DESIGN: We investigated the DEPs (differentially expressed proteins) and DHMPs between OACC-T and OACC-N using LC-MS/MS-based quantitative proteomics and using several bioinformatics methods, including GO enrichment analysis, KEGG pathway analysis, subcellular localization prediction, MEA (motif enrichment analysis), and PPI (protein-protein interaction networks) to illustrate how Khib modification interfere with OACC evolution.

RESULTS

Compared OACC-tumor samples (OACC-T) with the adjacent normal samples (OACC-N), there were 3243 of the DEPs and 2011 Khib sites were identified on 764 proteins (DHMPs). DEPs and DHMPs were strongly associated to glycolysis pathway. GAPDH of K254, ENO of K228, and PGK1 of K323 were modified by Khib in OACC-T. Khib may increase the catalytic efficiency to promote glycolysis pathway and favor OACC progression.

CONCLUSIONS AND CLINICAL RELEVANCE

Khib may play a significant role in the mechanism of OACC progression by influencing the enzyme activity of the glycolysis pathway. These findings may provide new therapeutic options of OACC.

The Current Status of the Liver Liquid Biopsy in MASH Related HCC: Overview and Future Directions

Metabolic dysfunction-associated steatohepatitis (MASH) is one of the major risk factors for chronic liver disease and hepatocellular carcinoma (HCC). The incidence of MASH in Western countries continues to rise, driving HCC as the third cause of cancer-related death worldwide. HCC has become a major global health challenge, partly from the obesity epidemic promoting metabolic cellular disturbances but also from the paucity of biomarkers for its early detection. Over 50% of HCC cases are clinically present at a late stage, where curative measures are no longer beneficial. Currently, there is a paucity of both specific and sensitive biological markers for the early-stage detection of HCC. The search for biological markers in the diagnosis of early HCC in high-risk populations is intense. We described the potential role of surrogates for a liver biopsy in the screening and monitoring of patients at risk for nesting HCC.

Untargeted metabolomics reveals sour jujube kernel benefiting the nutritional value and flavor of Morchella esculenta

Nucleosides, organic acids, and amino acids separated from Morchella esculenta are well known for their nutritional value and flavor. However, how to increase their content in a better way has been a challenge. In this study, the effect of adding jujube kernel on the active components of M. esculenta was investigated by untargeted metabolomics using UPLC-MS/MS. A total of 1,243 metabolites were identified, of which 262 metabolites (21.078%) were organic acids and derivatives, 245 metabolites (19.71%) were lipids and lipid-like molecules, and 26 metabolites (2.092%) were nucleosides, nucleotides, and analogues. Subsequently, differential metabolites between groups were screened by the orthogonal partial least squares-discriminant analysis model, which showed that 256 metabolites were identified as significantly different for the positive ion model and 149 for the negative ion model. Moreover, significant differential metabolites (VIP > 1, P < 0.05) in annotation of kyoto encyclopedia of genes and genomes pathway were investigated, which showed that ABC transporters were the most commonly observed transporters, followed by pyrimidine metabolism and purine metabolism. The results indicated that the main components of jujube kernel might be conducive to the accumulation of nucleoside organic acids and amino acid metabolites in M. esculenta. These results provide important information for the understanding of more suitable way for cultivation of M. esculenta.

Hollow multishelled heterostructures with enhanced performance for laser desorption/ionization mass spectrometry based metabolic diagnosis

High-performance metabolic diagnosis-based laser desorption/ionization mass spectrometry (LDI-MS) improves the precision diagnosis of diseases and subsequent treatment. Inorganic matrices are promising for the detection of metabolites by LDI-MS, while the structure and component impacts of the matrices on the LDI process are still under investigation. Here, we designed a multiple-shelled ZnMn2O4/(Co, Mn)(Co, Mn)2O4 (ZMO/CMO) as the matrix from calcined MOF-on-MOF for detecting metabolites in LDI-MS and clarified the synergistic impacts of multiple-shells and the heterostructure on LDI efficiency. The ZMO/CMO heterostructure allowed 3-5 fold signal enhancement compared with ZMO and CMO with the same morphology. Furthermore, the ZMO/CMO heterostructure with a triple-shelled hollow structure displayed a 3-fold signal enhancement compared to its nanoparticle counterpart. Taken together, the triple-shelled hollow ZMO/CMO exhibits 102-fold signal enhancement compared to the commercial matrix products (e.g., DHB and DHAP), allowing for sensitive metabolic profiling in bio-detection. We directly extracted metabolic patterns by the optimized triple-shelled hollow ZMO/CMO particle-assisted LDI-MS within 1 s using 100 nL of serum and used machine learning as the readout to distinguish hepatocellular carcinoma from healthy controls with the area under the curve value of 0.984. Our approach guides us in matrix design for LDI-MS metabolic analysis and drives the development of a nanomaterial-based LDI-MS platform toward precision diagnosis.

Spatially resolved visualization of reprogrammed metabolism in hepatocellular carcinoma by mass spectrometry imaging

BACKGROUND

Metabolic reprogramming refers to tumor-associated metabolic alterations during tumorigenesis and has been regarded as one of the most important features of cancer. Profiling the altered metabolites and lipids in hepatocellular carcinoma with spatial signature will not only enhance our understanding of tumor metabolic reprogramming, but also offer potential metabolic liabilities that might be exploited for hepatocellular carcinoma therapy.

METHODS

We perform matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) analysis on both hepatocellular carcinoma xenograft mouse model and hepatocellular carcinoma patients. Discriminatory metabolites that altered during the development of hepatocellular carcinoma are screened and imaged in xenograft mouse model and are further validated in 21 hepatocellular carcinoma patients.

RESULTS

We discover stepwise metabolic alterations and progressively increasing metabolic heterogeneity during the growth of hepatocellular carcinoma. Arginine and its metabolites spermine and spermidine, choline and phosphatidylcholine metabolism, and fatty acids were found to be significantly reprogrammed in hepatocellular carcinoma tissues.

CONCLUSIONS

The spatially resolved profiling of the metabolites and lipids in highly heterogeneous hepatocellular carcinoma tissue will contribute to obtaining precise metabolic information for the understanding of tumor metabolic reprogramming.

PTTG1 Reprograms Asparagine Metabolism to Promote Hepatocellular Carcinoma Progression

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and has a poor prognosis. Pituitary tumor transforming gene 1 (PTTG1) is highly expressed in HCC, suggesting it could play an important role in hepatocellular carcinogenesis. Here, we evaluated the impact of PTTG1 deficiency on HCC development using a diethylnitrosamine (DEN)-induced HCC mouse model and a hepatitis B virus (HBV) regulatory X protein (HBx)-induced spontaneous HCC mouse model. PTTG1 deficiency significantly suppressed DEN- and HBx-induced hepatocellular carcinogenesis. Mechanistically, PTTG1 promoted asparagine synthetase (ASNS) transcription by binding to its promoter, and asparagine (Asn) levels were correspondingly increased. The elevated levels of Asn subsequently activated the mTOR pathway to facilitate HCC progression. In addition, asparaginase treatment reversed the proliferation induced by PTTG1 overexpression. Furthermore, HBx promoted ASNS and Asn metabolism by upregulating PTTG1 expression. Overall, PTTG1 is involved in the reprogramming of Asn metabolism to promote HCC progression and may serve as a therapeutic and diagnostic target for HCC.

SIGNIFICANCE

PTTG1 is upregulated in hepatocellular carcinoma and increases asparagine production to stimulate mTOR activity and promote tumor progression.

Serum Metabolite Biomarkers for Pancreatic Tumors: Neuroendocrine and Pancreatic Ductal Adenocarcinomas-A Preliminary Study

BACKGROUND

Pancreatic cancer is the most common pancreatic solid malignancy with an aggressive clinical course and low survival rate. There are a limited number of reliable prognostic biomarkers and a need to understand the pathogenesis of pancreatic tumors; neuroendocrine (PNET) and pancreatic ductal adenocarcinomas (PDAC) encouraged us to analyze the serum metabolome of pancreatic tumors and disturbances in the metabolism of PDAC and PNET.

METHODS

Using the AbsoluteIDQ^® p180 kit (Biocrates Life Sciences AG, Innsbruck, Austria) with liquid chromatography-mass spectrometry (LC-MS), we identified changes in metabolite profiles and disrupted metabolic pathways serum of NET and PDAC patients.

RESULTS

The concentration of six metabolites showed statistically significant differences between the control group and PDAC patients (p.adj < 0.05). Glutamine (Gln), acetylcarnitine (C2), and citrulline (Cit) presented a lower concentration in the serum of PDAC patients, while phosphatidylcholine aa C32:0 (PC aa C32:0), sphingomyelin C26:1 (SM C26:1), and glutamic acid (Glu) achieved higher concentrations compared to serum samples from healthy individuals. Five of the tested metabolites: C2 (FC = 8.67), and serotonin (FC = 2.68) reached higher concentration values in the PNET serum samples compared to PDAC, while phosphatidylcholine aa C34:1 (PC aa C34:1) (FC = -1.46 (0.68)) had a higher concentration in the PDAC samples. The area under the curves (AUC) of the receiver operating characteristic (ROC) curves presented diagnostic power to discriminate pancreatic tumor patients, which were highest for acylcarnitines: C2 with AUC = 0.93, serotonin with AUC = 0.85, and PC aa C34:1 with AUC = 0.86.

CONCLUSIONS

The observations presented provide better insight into the metabolism of pancreatic tumors, and improve the diagnosis and classification of tumors. Serum-circulating metabolites can be easily monitored without invasive procedures and show the present clinical patients' condition, helping with pharmacological treatment or dietary strategies.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

Identification of mouse metabolic variations related to patulin-induced acute and subacute hepatotoxicity by ultra-high-performance liquid chromatography high-resolution mass spectrometry

Patulin (PAT), a toxin produced by molds in fruits and related products, has caused frequent food poisoning incidents worldwide. However, its potential mechanism of hepatotoxicity remains presently unclear. Herein, we intragastrically administered the C57BL/6J mice with 0, 1, 4, and 16 mg/kg b.wt of PAT on a single occasion (acute model), and 0, 50, 200, and 800 μg/kg b.wt of PAT daily over two weeks (subacute model). Assessments of histopathology and aminotransferase activities confirmed that significant hepatic damages were induced. Metabolic profiling on the liver using ultra-high-performance liquid chromatography high-resolution mass spectrometry discovered 43 and 61 differential metabolites in two models, respectively. Notably, acute and subacute models shared the common 18 differential metabolites, among which N-acetyl-leucine, inosine, 2-O-methyladenosine, PC 40:7, PC 38:6, and PC 34:2 could be regarded as the biomarkers indicative of PAT exposure. Moreover, analysis of metabolic pathways demonstrated that pentose phosphate pathway and purine metabolism were the main altered pathways in the acute model. Nevertheless, more pathways related to amino acids were affected in the subacute model. These results reveal the comprehensive influence of PAT on hepatic metabolism and provide a deeper understanding of the hepatotoxicity mechanism of PAT.

Integration of the Microbiome, Metabolome and Transcriptome Reveals Escherichia coli F17 Susceptibility of Sheep

Escherichia coli (E. coli) F17 is one of the most common pathogens causing diarrhea in farm livestock. In the previous study, we accessed the transcriptomic and microbiomic profile of E. coli F17-antagonism (AN) and -sensitive (SE) lambs; however, the biological mechanism underlying E. coli F17 infection has not been fully elucidated. Therefore, the present study first analyzed the metabolite data obtained with UHPLC-MS/MS. A total of 1957 metabolites were profiled in the present study, and 11 differential metabolites were identified between E. coli F17 AN and SE lambs (i.e., FAHFAs and propionylcarnitine). Functional enrichment analyses showed that most of the identified metabolites were related to the lipid metabolism. Then, we presented a machine-learning approach (Random Forest) to integrate the microbiome, metabolome and transcriptome data, which identified subsets of potential biomarkers for E. coli F17 infection (i.e., GlcADG 18:0-18:2, ethylmalonic acid and FBLIM1); furthermore, the PCCs were calculated and the interaction network was constructed to gain insight into the crosstalk between the genes, metabolites and bacteria in E. coli F17 AN/SE lambs. By combing classic statistical approaches and a machine-learning approach, our results revealed subsets of metabolites, genes and bacteria that could be potentially developed as candidate biomarkers for E. coli F17 infection in lambs.

Decreased propionyl-CoA metabolism facilitates metabolic reprogramming and promotes hepatocellular carcinoma

BACKGROUND & AIMS

Alterations of multiple metabolites characterize distinct features of metabolic reprograming in hepatocellular carcinoma (HCC). However, the role of most metabolites, including propionyl-CoA (Pro-CoA), in metabolic reprogramming and hepatocarcinogenesis remains elusive. In this study, we aimed to dissect how Pro-CoA metabolism affects these processes.

METHODS

TCGA data and HCC samples were used to analyze ALDH6A1-mediated Pro-CoA metabolism and its correlation with HCC. Multiple metabolites were assayed by targeted mass spectrometry. The role of ALDH6A1-generated Pro-CoA in HCC was evaluated in HCC cell lines as well as xenograft nude mouse models and primary liver cancer mouse models. Non-targeted metabolomic and targeted energy metabolomic analyses, as well as multiple biochemical assays, were performed.

RESULTS

Decreases in Pro-CoA and its derivative propionyl-L-carnitine due to ALDH6A1 downregulation were tightly associated with HCC. Functionally, ALDH6A1-mediated Pro-CoA metabolism suppressed HCC proliferation in vitro and impaired hepatocarcinogenesis in mice. The aldehyde dehydrogenase activity was indispensable for this function of ALDH6A1, while Pro-CoA carboxylases antagonized ALDH6A1 function by eliminating Pro-CoA. Mechanistically, ALDH6A1 caused a signature enrichment of central carbon metabolism in cancer and impaired energy metabolism: ALDH6A1-generated Pro-CoA suppressed citrate synthase activity, which subsequently reduced tricarboxylic acid cycle flux, impaired mitochondrial respiration and membrane potential, and decreased ATP production. Moreover, Pro-CoA metabolism generated 2-methylcitric acid, which mimicked the inhibitory effect of Pro-CoA on citrate synthase and dampened mitochondrial respiration and HCC proliferation.

CONCLUSIONS

The decline of ALDH6A1-mediated Pro-CoA metabolism contributes to metabolic remodeling and facilitates hepatocarcinogenesis. Pro-CoA, propionyl-L-carnitine and 2-methylcitric acid may serve as novel metabolic biomarkers for the diagnosis and treatment of HCC. Pro-CoA metabolism may provide potential targets for development of novel strategies against HCC.

IMPACT AND IMPLICATIONS

Our study presents new insights on the role of propionyl-CoA metabolism in metabolic reprogramming and hepatocarcinogenesis. This work has uncovered potential diagnostic and predictive biomarkers, which could be used by physicians to improve clinical practice and may also serve as targets for the development of therapeutic strategies against HCC.

PHGDH arginine methylation by PRMT1 promotes serine synthesis and represents a therapeutic vulnerability in hepatocellular carcinoma

Serine synthesis is crucial for tumor growth and survival, but its regulatory mechanism in cancer remains elusive. Here, using integrative metabolomics and transcriptomics analyses, we show a heterogeneity between metabolite and transcript profiles. Specifically, the level of serine in hepatocellular carcinoma (HCC) tissues is increased, whereas the expression of phosphoglycerate dehydrogenase (PHGDH), the first rate-limiting enzyme in serine biosynthesis pathway, is markedly downregulated. Interestingly, the increased serine level is obtained by enhanced PHGDH catalytic activity due to protein arginine methyltransferase 1 (PRMT1)-mediated methylation of PHGDH at arginine 236. PRMT1-mediated PHGDH methylation and activation potentiates serine synthesis, ameliorates oxidative stress, and promotes HCC growth in vitro and in vivo. Furthermore, PRMT1-mediated PHGDH methylation correlates with PHGDH hyperactivation and serine accumulation in human HCC tissues, and is predictive of poor prognosis of HCC patients. Notably, blocking PHGDH methylation with a TAT-tagged nonmethylated peptide inhibits serine synthesis and restrains HCC growth in an HCC patient-derived xenograft (PDX) model and subcutaneous HCC cell-derived xenograft model. Overall, our findings reveal a regulatory mechanism of PHGDH activity and serine synthesis, and suggest PHGDH methylation as a potential therapeutic vulnerability in HCC.

Metabolism as a New Avenue for Hepatocellular Carcinoma Therapy

Hepatocellular carcinoma is today the sixth leading cause of cancer-related death worldwide, despite the decreased incidence of chronic hepatitis infections. This is due to the increased diffusion of metabolic diseases such as the metabolic syndrome, diabetes, obesity, and nonalcoholic steatohepatitis (NASH). The current protein kinase inhibitor therapies in HCC are very aggressive and not curative. From this perspective, a shift in strategy toward metabolic therapies may represent a promising option. Here, we review current knowledge on metabolic dysregulation in HCC and therapeutic approaches targeting metabolic pathways. We also propose a multi-target metabolic approach as a possible new option in HCC pharmacology.

Biomarkers for pancreatic cancer based on tissue and serum metabolomics analysis in a multicenter study

BACKGROUND

Early detection of pancreatic ductal adenocarcinoma (PDAC) may improve the prognosis of patients. This study was to identify metabolic features of PDAC and to discover early detection biomarkers for PDAC by tissue and serum metabolomics analysis.

METHODS

We conducted nontargeted metabolomics analysis in tissue samples of 51 PDAC tumors, 40 noncancerous pancreatic tissues (NT), and 14 benign pancreatic neoplasms (BP) as well as serum samples from 80 patients with PDAC, 36 with BP, and 48 healthy controls (Ctr). The candidate metabolites identified from the initial analysis were further quantified using targeted analysis in serum samples of an independent cohort of 22 early stage PDAC, 27 BP, and 27 Ctr subjects. Unconditional binary logistic regression analysis was used to construct the optimal model for PDAC diagnosis.

RESULTS

Upregulated levels of fatty acids and lipids and downregulated amino acids were observed in tissue and serum samples of PDAC patients. Proline, creatine, and palmitic acid were identified as a panel of potential biomarkers to distinguish PDAC from BP and Ctr (odds ratio = 2.17, [95% confidence interval 1.34-3.53]). The three markers showed area under the receiver-operating characteristic curves (AUCs) of 0.854 and 0.865, respectively, for the comparison of PDAC versus Ctr and PDAC versus BP. The AUCs were 0.830 and 0.852 in the validation set and were improved to 0.949 and 0.909 when serum carbohydrate antigen 19-9 (CA19-9) was added to the model.

CONCLUSION

The novel metabolite biomarker panel identified in this study exhibited promising performance in distinguishing PDAC from BP or Ctr, especially in combination with CA19-9.

Serum metabolomic analysis reveals key metabolites in drug treatment of central precocious puberty in female children

Precocious puberty (PP) is a common condition among children. According to the pathogenesis and clinical manifestations, PP can be divided into central precocious puberty (CPP, gonadotropin dependent), peripheral precocious puberty (PPP, gonadotropin independent), and incomplete precocious puberty (IPP). Identification of the variations in key metabolites involved in CPP and their underlying biological mechanisms has increased the understanding of the pathological processes of this condition. However, little is known about the role of metabolite variations in the drug treatment of CPP. Moreover, it remains unclear whether the understanding of the crucial metabolites and pathways can help predict disease progression after pharmacological therapy of CPP. In this study, systematic metabolomic analysis was used to examine three groups, namely, healthy control (group N, 30 healthy female children), CPP (group S, 31 female children with CPP), and treatment (group R, 29 female children) groups. A total of 14 pathways (the top two pathways were aminoacyl-tRNA biosynthesis and phenylalanine, tyrosine, and tryptophan biosynthesis) were significantly enriched in children with CPP. In addition, two short peptides (His-Arg-Lys-Glu and Lys-Met-His) were found to play a significant role in CPP. Various metabolites associated with different pathways including amino acids, PE [19:1(9Z)0:0], tumonoic acid I, palmitic amide, and linoleic acid-biotin were investigated in the serum of children in all groups. A total of 45 metabolites were found to interact with a chemical drug [a gonadotropin-releasing hormone (GnRH) analog] and a traditional Chinese medicinal formula (DBYW). This study helps to understand metabolic variations in CPP after drug therapy, and further investigation may help develop individualized treatment approaches for CPP in clinical practice.

Metabolomics in hepatocellular carcinoma: From biomarker discovery to precision medicine

Hepatocellular carcinoma (HCC) remains a global health burden, and is mostly diagnosed at late and advanced stages. Currently, limited and insensitive diagnostic modalities continue to be the bottleneck of effective and tailored therapy for HCC patients. Moreover, the complex reprogramming of metabolic patterns during HCC initiation and progression has been obstructing the precision medicine in clinical practice. As a noninvasive and global screening approach, metabolomics serves as a powerful tool to dynamically monitor metabolic patterns and identify promising metabolite biomarkers, therefore holds a great potential for the development of tailored therapy for HCC patients. In this review, we summarize the recent advances in HCC metabolomics studies, including metabolic alterations associated with HCC progression, as well as novel metabolite biomarkers for HCC diagnosis, monitor, and prognostic evaluation. Moreover, we highlight the application of multi-omics strategies containing metabolomics in biomarker discovery for HCC. Notably, we also discuss the opportunities and challenges of metabolomics in nowadays HCC precision medicine. As technologies improving and metabolite biomarkers discovering, metabolomics has made a major step toward more timely and effective precision medicine for HCC patients.

Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning

Biopsy is the recommended standard for pathological diagnosis of liver carcinoma. However, this method usually requires sectioning and staining, and well-trained pathologists to interpret tissue images. Here, we utilize Raman spectroscopy to study human hepatic tissue samples, developing and validating a workflow for in vitro and intraoperative pathological diagnosis of liver cancer. We distinguish carcinoma tissues from adjacent non-tumour tissues in a rapid, non-disruptive, and label-free manner by using Raman spectroscopy combined with deep learning, which is validated by tissue metabolomics. This technique allows for detailed pathological identification of the cancer tissues, including subtype, differentiation grade, and tumour stage. 2D/3D Raman images of unprocessed human tissue slices with submicrometric resolution are also acquired based on visualization of molecular composition, which could assist in tumour boundary recognition and clinicopathologic diagnosis. Lastly, the potential for a portable handheld Raman system is illustrated during surgery for real-time intraoperative human liver cancer diagnosis.

Activated abscisic acid pathway and C4 pathway, inhibited cell cycle progression, responses of Ulva prolifera to short term high temperature elucidated by multi-omics

The annual outbreak of green tides since 2007 has destroyed coastal waters' ecological environment and caused substantial economic losses. Ulva prolifera, known as the dominant species of green tides, is influenced by temperatures. Omics-based technology was used to analyze U. prolifera under 12 h of treatment at 30 °C in the work. High temperature has the following advantages, e.g., activating the abscisic acid signaling pathway, improving the heat tolerance of U. prolifera, up-regulating metabolites such as glycolipids, glyceroyl, and glutamic acid to maintain the stability and fluidity of cells, and reducing the stimulatory effect of external stress on cells. The key genes and proteins of the tricarboxylic acid cycle, glycolysis, and pentose phosphorylation pathways were inhibited; however, the key enzyme pyruvate phospho-dikinase of the C4 pathway was up-regulated. The C4 pathway was activated in U. prolifera in response to high-temperature stress and may play a key role in photosynthesis. Besides, U. prolifera metabolizing amino acids was active. High temperature inhibited genes and proteins related to DNA replication and cell cycle in the transcriptome and proteome as well as the growth and reproduction of U. prolifera.

Correlation between metastatic patterns and age in patients with metastatic primary liver cancer: A population-based study

AIM

Primary liver cancer is usually diagnosed at advanced stages with distant metastasis, underlying the high metastatic rate and mortality in patients. This study aimed to analyse the metastatic patterns and prognosis of primary liver cancer, and its relationship with age and several other factors, such as histological variants, TNM stage, and grade.

METHODS

We included data from 5274 patients from the Surveillance, Epidemiology, and End Results (SEER) database of the American National Cancer Institute diagnosed with primary liver cancer with metastatic disease between 2010 and 2015. The correlation between the metastatic patterns of primary liver cancer and age was evaluated. The hazard ratio (HR) and 95% confidence intervals (CI) for overall survival were calculated by applying univariate Cox analysis, while the correlation between the metastatic patterns and age was analysed by applying multivariate Cox analysis. We also plotted Kaplan-Meier curves to illustrate the correlation between overall survival (OS) and various factors.

RESULTS

Several factors were associated with poorer prognosis, including age>60 years, histologic type of spindle cell variant, higher grade, no surgery, tumour size ≥ 1 cm, and lung metastasis. The rate of metastasis increased with age. Older patients (> 50 years) were prone to bone metastasis, while less likely to have lung metastasis compared with younger patients (< 50 years). Patients with lung metastasis had a higher risk of being diagnosed with metastasis in other locations. Furthermore, surgery significantly reduced mortality and primary site surgery in particular, mitigated the risk of bone and lung metastases.

CONCLUSIONS

Our study shows the correlation of prognosis and metastatic patterns with age and several other factors. The findings can hopefully provide knowledge that will allow a better diagnosis and management of elderly patients with primary liver cancer.

Integrated analysis of transcriptomics and metabolomics in human hepatocellular carcinoma HepG2215 cells after YAP1 knockdown

Yes-associated protein 1 (YAP1) plays a critical role in hepatocellular carcinoma (HCC). Inhibition of YAP1 expression suppresses HCC progression, but the underlying mechanism is still unclear. In this study, we studied the effects and molecular mechanisms of YAP1 knockdown on the growth and metabolism in human HCC HepG2215 cells. Inhibition of YAP1 expression inhibits the proliferation and metastasis in HepG2215 cells, and differentially expressed genes (DEGs) and metabolites were identified in shYAP1-HepG2215 cells. Further, 805 DEGs, mainly associated with metabolism and particularly lipid metabolism, were identified by transcriptome sequencing analyses in shYAP1-HepG2215 cells. YAP1 knockdown increased albumin (ALB) levels by Protein-protein interaction (PPI) network analyses in HepG2215 cells. Metabolomic profiling identified 37 metabolites with significant differences in the shYAP1 group, and amino acid metabolism generally decreased in the shYAP1 group. Comprehensive analysis of transcriptomics and metabolomics revealed that the ATP-binding cassette (ABC) transporters play a central role after YAP1 knockdown in HepG2215 cells. Therefore, YAP1 knockdown inhibited HCC growth, which affected the metabolism of lipids and amino acids by regulating the expression of ALB and ABC transporters in HepG2215 cells.

A novel cuproptosis-related lncRNA signature predicts the prognosis and immunotherapy for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most serious malignant tumors with a poor prognosis worldwide. Cuproptosis is a novel copper-dependent cell death form, involving mitochondrial respiration and lipoylated components of the tricarboxylic acid (TCA) cycle. Long non-coding RNAs (lncRNAs) have been demonstrated to affect the tumorigenesis, growth, and metastasis of HCC.

OBJECTIVE

We explored the potential roles of cuproptosis-related lncRNAs in predicting the prognosis for HCC.

METHODS

The RNA-seq transcriptome data, mutation data, and clinical information data of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analyses were performed to identify a prognostic cuproptosis-related lncRNA signature. The receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of the lncRNA signature for HCC. The enrichment pathways, immune functions, immune cell infiltration, tumor mutation burden, and drug sensitivity were also analyzed.

RESULTS

We constructed a prognostic model consisting of 8 cuproptosis-related lncRNAs for HCC. The patients were divided into high-risk group and low-risk group according to the riskscore calculated using the model. Kaplan-Meier analysis revealed that the high-risk lncRNA signature was correlated with poor overall survival [hazard ratio (HR) =1.009, 95% confidence interval (CI) = 1.002-1.015; p= 0.010)] of HCC. A prognostic nomogram incorporated the lncRNA signature and clinicopathological features were constructed and showed favorable performance for predicting prognosis of HCC patients. In addition, the most immune-related functions were significantly different between the high-risk and low-risk groups. Tumor mutation burden (TMB) and immune checkpoints were also expressed differently between the two risk groups. Finally, HCC patients with low-risk score were more sensitive to several chemotherapy drugs.

CONCLUSIONS

The novel cuproptosis-related lncRNA signature could be used to predict prognosis and evaluate the effect of chemotherapy for HCC.

Targeting cancer-specific metabolic pathways for developing novel cancer therapeutics

Cancer is a heterogeneous disease characterized by various genetic and phenotypic aberrations. Cancer cells undergo genetic modifications that promote their proliferation, survival, and dissemination as the disease progresses. The unabated proliferation of cancer cells incurs an enormous energy demand that is supplied by metabolic reprogramming. Cancer cells undergo metabolic alterations to provide for increased energy and metabolite requirement; these alterations also help drive the tumor progression. Dysregulation in glucose uptake and increased lactate production via "aerobic glycolysis" were described more than 100 years ago, and since then, the metabolic signature of various cancers has been extensively studied. However, the extensive research in this field has failed to translate into significant therapeutic intervention, except for treating childhood-ALL with amino acid metabolism inhibitor L-asparaginase. Despite the growing understanding of novel metabolic alterations in tumors, the therapeutic targeting of these tumor-specific dysregulations has largely been ineffective in clinical trials. This chapter discusses the major pathways involved in the metabolism of glucose, amino acids, and lipids and highlights the inter-twined nature of metabolic aberrations that promote tumorigenesis in different types of cancer. Finally, we summarise the therapeutic interventions which can be used as a combinational therapy to target metabolic dysregulations that are unique or common in blood, breast, colorectal, lung, and prostate cancer.

Identification of Biomarkers for Methamphetamine Exposure Time Prediction in Mice Using Metabolomics and Machine Learning Approaches

Methamphetamine (METH) abuse has become a global public health and safety problem. More information is needed to identify the time of drug abuse. In this study, methamphetamine was administered to male C57BL/6J mice with increasing doses from 5 to 30 mg kg^-1 (once a day, i.p.) for 20 days. Serum and urine samples were collected for metabolomics studies using gas chromatography-mass spectrometry (GC-MS). Six machine learning models were used to infer the time of drug abuse and the best model was selected to predict administration time preliminarily. The metabolic changes caused by methamphetamine were explored. As results, the metabolic patterns of methamphetamine exposure mice were quite different from the control group and changed over time. Specifically, serum metabolomics showed enhanced amino acid metabolism and increased fatty acid consumption, while urine metabolomics showed slowed metabolism of the tricarboxylic acid (TCA) cycle, increased organic acid excretion, and abnormal purine metabolism. Phenylalanine in serum and glutamine in urine increased, while palmitic acid, 5-HT, and monopalmitin in serum and gamma-aminobutyric acid in urine decreased significantly. Among the six machine learning models, the random forest model was the best to predict the exposure time (serum: MAE = 1.482, RMSE = 1.69, R squared = 0.981; urine: MAE = 2.369, RMSE = 1.926, R squared = 0.946). The potential biomarker set containing four metabolites in the serum (palmitic acid, 5-hydroxytryptamine, monopalmitin, and phenylalanine) facilitated the identification of methamphetamine exposure. The random forest model helped predict the methamphetamine exposure time based on these potential biomarkers.

Spatial metabolomics on liver cirrhosis to hepatocellular carcinoma progression

Background

Hepatocellular carcinoma (HCC) is one of the deadliest cancers and is mainly developed from chronic liver diseases such as hepatitis-B infection-associated liver cirrhosis (LC). The progression from LC to HCC makes the detection of diagnostic biomarkers to be challenging. Hence, there have been constant efforts to improve on identifying the critical and predictive changes accompanying the disease progression.

Methods

In this study, we looked to using the mass spectrometry mediated spatial metabolomics technique to simultaneous examine hundreds of metabolites in an untargeted fashion. Additionally, metabolic profiles were compared between six subregions within the HCC tissue to collect spatial information.

Results

Through those metabolites, altered metabolic pathways in LC and HCC were identified. Specifically, the amino acid metabolisms and the glycerophospholipid metabolisms experienced the most changes. Many of the altered metabolites and metabolic pathways were able to be connected through the urea cycle.

Conclusions

The identification of the key metabolites and pathways can expand our knowledge on HCC metabolic reprogramming and help us exam potential biomarkers for earlier detection of the malignant disease progression.

Essential amino acids as diagnostic biomarkers of hepatocellular carcinoma based on metabolic analysis

Metabolomics, defined as the comprehensive identification of all small metabolites in a biological sample, has the power to shed light on phenotypic changes associated with various diseases, including cancer. To discover potential metabolomic biomarkers of hepatocellular carcinoma (HCC), we investigated the metabolomes of tumor and non-tumor tissue in 20 patients with primary HCC using capillary electrophoresis-time-of-flight mass spectrometry. We also analyzed blood samples taken immediately before and 14 days after hepatectomy to identify associated changes in the serum metabolome. Marked changes were detected in the different quantity of 61 metabolites that could discriminate between HCC tumor and paired non-tumor tissue and additionally between HCC primary tumors and colorectal liver metastases. Among the 30 metabolites significantly upregulated in HCC tumors compared with non-tumor tissues, 10 were amino acids, and 7 were essential amino acids (leucine, valine, tryptophan, isoleucine, methionine, lysine, and phenylalanine). Similarly, the serum metabolomes of HCC patients before hepatectomy revealed a significant increase in 16 metabolites, including leucine, valine, and tryptophan. Our results reveal striking differences in the metabolomes of HCC tumor tissue compared with non-tumor tissue, and identify the essential amino acids leucine, valine, and tryptophan as potential metabolic biomarkers for HCC.

The altered lipidome of hepatocellular carcinoma

Alterations in metabolic pathways are a hallmark of cancer. A deeper understanding of the contribution of different metabolites to carcinogenesis is thus vitally important to elucidate mechanisms of tumor initiation and progression to inform therapeutic strategies. Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide and its altered metabolic landscape is beginning to unfold with the advancement of technologies. In particular, characterization of the lipidome of human HCCs has accelerated, and together with biochemical analyses, are revealing recurrent patterns of alterations in glycerophospholipid, sphingolipid, cholesterol and bile acid metabolism. These widespread alterations encompass a myriad of lipid species with numerous roles affecting multiple hallmarks of cancer, including aberrant growth signaling, metastasis, evasion of cell death and immunosuppression. In this review, we summarize the current trends and findings of the altered lipidomic landscape of HCC and discuss their potential biological significance for hepatocarcinogenesis.