Acetylcarnitine Is a Candidate Diagnostic and Prognostic Biomarker of Hepatocellular Carcinoma

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.

Dysfunction of the carnitine cycle in tumor progression

The carnitine cycle is responsible for the transport of cytoplasmic fatty acids to the mitochondria for subsequent β-oxidation to maintain intracellular energy homeostasis. Recent studies have identified abnormalities in the carnitine cycle in various types of tumors; these abnormalities include the altered expression levels of carnitine cycle-related metabolic enzymes and transport proteins. Dysfunction of the carnitine cycle has been shown to influence tumorigenesis and progression by altering intracellular oxidative and inflammatory status or regulating tumor metabolic flexibility. Many therapeutic strategies targeting the carnitine cycle are actively being explored to modify the dysfunction of the carnitine cycle in patients with malignant tumors; such approaches include carnitine cycle-related enzyme inhibitors and exogenous carnitine supplementation. Therefore, here, we review the studies of carnitine in tumors, aiming to scientifically illustrate the dysfunction of the carnitine cycle in tumor progression and provide new ideas for further research.

Plasma metabolomics of immune-related adverse events for patients with lung cancer treated with PD-1/PD-L1 inhibitors

BACKGROUND

Metabolomics has the characteristics of terminal effects and reflects the physiological state of biological diseases more directly. Several current biomarkers of multiple omics were revealed to be associated with immune-related adverse events (irAEs) occurrence. However, there is a lack of reliable metabolic biomarkers to predict irAEs. This study aims to explore the potential metabolic biomarkers to predict risk of irAEs and to investigate the association of plasma metabolites level with survival in patients with lung cancer receiving PD-1/PD-L1 inhibitor treatment.

METHODS

The study collected 170 plasmas of 85 patients with lung cancer who received immune checkpoint inhibitors (ICIs) treatment. 58 plasma samples of 29 patients with irAEs were collected before ICIs treatment and at the onset of irAEs. 112 plasma samples of 56 patients who did not develop irAEs were collected before ICIs treatment and plasma matched by treatment cycles to onset of irAEs patients. Untargeted metabolomics analysis was used to identify the differential metabolites before initiating ICIs treatment and during the process that development of irAEs. Kaplan-Meier curves analysis was used to detect the associations of plasma metabolites level with survival of patients with lung cancer.

RESULTS

A total of 24 differential metabolites were identified to predict the occurrence of irAEs. Baseline acylcarnitines and steroids levels are significantly higher in patients with irAEs, and the model of eight acylcarnitine and six steroid metabolites baseline level predicts irAEs occurrence with area under the curve of 0.91. Patients with lower concentration of baseline decenoylcarnitine(AcCa(10:1) 2, decenoylcarnitine(AcCa(10:1) 3 and hexanoylcarnitine(AcCa(6:0) in plasma would have better overall survival (OS). Moreover, 52 differential metabolites were identified related to irAEs during ICIs treatment, dehydroepiandrosterone sulfate, corticoserone, cortisol, thyroxine and sphinganine 1-phaosphate were significantly decreased in irAEs group while oxoglutaric acid and taurocholic acid were significantly increased in irAEs group.

CONCLUSIONS

High levels of acylcarnitines and steroid hormone metabolites might be risk factor to development of irAEs, and levels of decenoylcarnitine (AcCa(10:1) 2, decenoylcarnitine (AcCa(10:1) 3 and hexanoylcarnitine (AcCa(6:0) could be used to predict OS for patients with lung cancer received ICIs treatment.

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.

The role of serum acylcarnitine profiling for the detection of multiple solid tumors in humans

Metabolic reprogramming is an essential hallmark of cancer. Several studies have reported the dysregulation of acylcarnitine (ACar) metabolism in tumor cells, suggesting that changes in the blood ACar may be related to tumor growth. Accordingly, this study aimed to understand the alteration of serum ACar profiles in various solid tumors and explore the potential of differential serum ACars as diagnostic biomarkers. A series of 69 relatively abundant ACars were identified via untargeted analysis. Then, targeted metabolomics was used to describe the metabolic alterations in ACars between normal controls and patients with six types of solid tumors. The results suggested that changes in ACars correlated with their carbon chain length and saturation. The six tumor types had highly similar ACar metabolic profiles, indicating similar fatty acid oxidation (FAO) metabolic pathways. Moreover, the receiver operating curve analysis of differential ACars showed that 16 ACars (C8-C14) had high diagnostic capability towards the studied solid tumors. Specifically, the area under the curve of ACar 10:2 isomer2 and ACar 12:2 isomer2 was greater than 0.95. In conclusion, the marked decrease in the levels of medium- and long-chain ACars (C8-C18) in the six solid tumors suggests that they may have similar FAO-based metabolic pathways, which could afford a common target for cancer therapy. Additionally, 16 ACars (C8-C14) were identified as potential biomarkers for diagnosing six types of solid tumors.

Interfacial Electromigration for Analysis of Biofluid Lipids in Small Volumes

Lipids are important biomarkers within the field of disease diagnostics and can serve as indicators of disease progression and predictors of treatment effectiveness. Although lipids can provide important insight into how diseases initiate and progress, mass spectrometric methods for lipid characterization and profiling are limited due to lipid structural diversity, particularly the presence of various lipid isomers. Moreover, the difficulty of handling small-volume samples exacerbates the intricacies of biological analyses. In this work, we have developed a strategy that electromigrates a thin film of a small-volume biological sample directly to the air-liquid interface formed at the tip of a theta capillary. Importantly, we seamlessly integrated in situ biological lipid extraction with accelerated chemical derivatization, enabled by the air-liquid interface, and conducted isomeric structural characterization within a unified platform utilizing theta capillary nanoelectrospray ionization mass spectrometry, all tailored for small-volume sample analysis. We applied this unified platform to the analysis of lipids from small-volume human plasma and Alzheimer's disease mouse serum samples. Accelerated electro-epoxidation of unsaturated lipids at the interface allowed us to characterize lipid double-bond positional isomers. The unique application of electromigration of a thin film to the air-liquid interface in combination with accelerated interfacial reactions holds great potential in small-volume sample analysis for disease diagnosis and prevention.

HNF4α isoforms regulate the circadian balance between carbohydrate and lipid metabolism in the liver

Hepatocyte Nuclear Factor 4α (HNF4α), a master regulator of hepatocyte differentiation, is regulated by two promoters (P1 and P2) which drive the expression of different isoforms. P1-HNF4α is the major isoform in the adult liver while P2-HNF4α is thought to be expressed only in fetal liver and liver cancer. Here, we show that P2-HNF4α is indeed expressed in the normal adult liver at Zeitgeber time (ZT)9 and ZT21. Using exon swap mice that express only P2-HNF4α we show that this isoform orchestrates a distinct transcriptome and metabolome via unique chromatin and protein-protein interactions, including with different clock proteins at different times of the day leading to subtle differences in circadian gene regulation. Furthermore, deletion of the Clock gene alters the circadian oscillation of P2- (but not P1-)HNF4α RNA, revealing a complex feedback loop between the HNF4α isoforms and the hepatic clock. Finally, we demonstrate that while P1-HNF4α drives gluconeogenesis, P2-HNF4α drives ketogenesis and is required for elevated levels of ketone bodies in female mice. Taken together, we propose that the highly conserved two-promoter structure of the Hnf4a gene is an evolutionarily conserved mechanism to maintain the balance between gluconeogenesis and ketogenesis in the liver in a circadian fashion.

Non-alcoholic fatty liver disease and diabetes mellitus as growing aetiologies of hepatocellular carcinoma

Obesity-related complications such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D) are well-established risk factors for the development of hepatocellular carcinoma (HCC). This review provides insights into the molecular mechanisms that underlie the role of steatosis, hyperinsulinemia and hepatic inflammation in HCC development and progression. We focus on recent findings linking intracellular pathways and transcription factors that can trigger the reprogramming of hepatic cells. In addition, we highlight the role of enzymes in dysregulated metabolic activity and consequent dysfunctional signalling. Finally, we discuss the potential uses and challenges of novel therapeutic strategies to prevent and treat NAFLD/T2D-associated HCC.

Reprogramming of lipid metabolism in hepatocellular carcinoma resulting in downregulation of phosphatidylcholines used as potential markers for diagnosis and prediction

BACKGROUND

Aberrant methylation and metabolic perturbations may deepen our understanding of hepatocarcinogenesis and help identify novel biomarkers for diagnosing hepatocellular carcinoma (HCC). We aimed to develop an HCC model based on a multi-omics.

RESEARCH DESIGN AND METHODS

Four hundred patient samples (200 with HCC and 200 with hepatitis B virus-related liver disease (HBVLD)) were subjected to liquid chromatography-mass spectrometry and multiplex bisulfite sequencing. Integrative analysis of clinical data, CpG data, and metabolome for the 20 complete imputation datasets within a for-loopwas used to identify biomarker.

RESULTS

Totally, 1,140 metabolites were annotated, of which 125 were differentially expressed. Lipid metabolism reprogramming in HCC, resulting in phosphatidylcholines (PC) significantly downregulated, partly due to the altered mitochondrial beta-oxidation of fatty acids with diverse chain lengths. Age, sex, serum-fetoprotein levels, cg05166871,cg14171514, cg18772205, PC (O-16:0/20:3(8Z, 11Z, 14Z)), and PC (16:1(9Z)/P-18:0) were used to develop the HCC model. The model presented a good diagnostic and an acceptable predictive performance. The cumulative incidence of HCC in low- and high-risk groups of HBVLD patients were 1.19% and 21.40%, respectively (p = 0.0039).

CONCLUSIONS

PCs serve as potential plasma biomarkers and help identify patients with HBVLD at risk of HCC who should be screened for early diagnosis and intervention.

Circular RNAs in ferroptosis: regulation mechanism and potential clinical application in disease

Ferroptosis, an iron-dependent non-apoptotic form of cell death, is reportedly involved in the pathogenesis of various diseases, particularly tumors, organ injury, and degenerative pathologies. Several signaling molecules and pathways have been found to be involved in the regulation of ferroptosis, including polyunsaturated fatty acid peroxidation, glutathione/glutathione peroxidase 4, the cysteine/glutamate antiporter system Xc-, ferroptosis suppressor protein 1/ubiquinone, and iron metabolism. An increasing amount of evidence suggests that circular RNAs (circRNAs), which have a stable circular structure, play important regulatory roles in the ferroptosis pathways that contribute to disease progression. Hence, ferroptosis-inhibiting and ferroptosis-stimulating circRNAs have potential as novel diagnostic markers or therapeutic targets for cancers, infarctions, organ injuries, and diabetes complications linked to ferroptosis. In this review, we summarize the roles that circRNAs play in the molecular mechanisms and regulatory networks of ferroptosis and their potential clinical applications in ferroptosis-related diseases. This review furthers our understanding of the roles of ferroptosis-related circRNAs and provides new perspectives on ferroptosis regulation and new directions for the diagnosis, treatment, and prognosis of ferroptosis-related diseases.

Development and internal validation of nomograms based on plasma metabolites to predict non-small cell lung cancer risk in smoking and nonsmoking populations

BACKGROUND

Lung cancer has significantly higher incidence and mortality rates worldwide. In this study, we analyzed the metabolic profiles of non-small cell lung cancer (NSCLC) patients and constructed prediction models for smokers and nonsmokers with internal validation.

METHODS

Plasma was collected from all patients enrolled for metabolic profiling by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The total population was divided into two groups according to smoking or not. Statistical analysis of metabolites was performed separately for each group and prediction models were constructed.

RESULTS

A total of 1723 patients (1109 NSCLC patients and 614 healthy controls) were enrolled from the affiliated hospital during 2018 to 2021. After grouping by smoking history, each group was statistically analyzed and prediction models were constructed, which resulted in eight indicators (propionylcarnitine, arginine, citrulline, etc.) significantly associated with lung cancer risk for smokers and eight indicators (dodecanoylcarnitine, hydroxybutyrylcarnitine, asparagine, etc.) for nonsmokers (p < 0.05). The smoker model indicated an AUC of 0.860 in the training set and 0.850 in the validation set. The nonsmoker model showed an AUC of 0.783 in the training set and 0.762 in the validation set. Further calibration tests for both models indicated excellent goodness-of-fit results.

CONCLUSIONS

In this study, we found a series of metabolites significantly associated with lung cancer incidence and constructed respectively prediction models for NSCLC risk in smokers and nonsmokers, with internal validation to confirm the efficiency to discriminate lung cancer risk in both smoking and nonsmoking states.

Metabolomics and network analysis uncovered profound inflammation-associated alterations in hepatitis B virus-related cirrhosis patients with early hepatocellular carcinoma

Patients with hepatitis B virus (HBV)-related liver cirrhosis (LC) are at high risk for hepatocellular carcinoma (HCC). Limitations in the early detection of HCC give rise to poor survival in this high-risk population. Here, we performed comprehensive metabolomics on health individuals and HBV-related LC patients with and without early HCC. Compared to non-HCC patients (N = 108) and health controls (N = 80), we found that patients with early HCC (N = 224) exhibited a specific plasma metabolome map dominated by lipid alterations, including lysophosphatidylcholines, lysophosphatidic acids and bile acids. Pathway and function network analyses indicated that these metabolite alterations were closely associated with inflammation responses. Using multivariate regression and machine learning approaches, we identified a five-metabolite combination that showed significant performances in differentiating early-HCC from non-HCC than α-fetoprotein (area under the curve values, 0.981 versus 0.613). At metabolomic levels, this work provides additional insights of metabolic dysfunction related to HCC progressions and demonstrates the plasma metabolites might be measured to identify early HCC in patients with HBV-related LC.

Low-Magnitude Mechanical Signals Combined with Zoledronic Acid Reduce Musculoskeletal Weakness and Adiposity in Estrogen-Deprived Mice

Combination treatment of Low-Intensity Vibration (LIV) with zoledronic acid (ZA) was hypothesized to preserve bone mass and muscle strength while reducing adipose tissue accrual associated with complete estrogen (E ₂ )-deprivation in young and skeletally mature mice. Complete E ₂ -deprivation (surgical-ovariectomy (OVX) and daily injection of aromatase inhibitor (AI) letrozole) were performed on 8-week-old C57BL/6 female mice for 4 weeks following commencement of LIV administration or control (no LIV), for 28 weeks. Additionally, 16-week-old C57BL/6 female E ₂ -deprived mice were administered ±LIV twice daily and supplemented with ±ZA (2.5 ng/kg/week). By week 28, lean tissue mass quantified by dual-energy X-ray absorptiometry was increased in younger OVX/AI+LIV(y) mice, with increased myofiber cross-sectional area of quadratus femorii. Grip strength was greater in OVX/AI+LIV(y) mice than OVX/AI(y) mice. Fat mass remained lower in OVX/AI+LIV(y) mice throughout the experiment compared with OVX/AI(y) mice. OVX/AI+LIV(y) mice exhibited increased glucose tolerance and reduced leptin and free fatty acids than OVX/AI(y) mice. Trabecular bone volume fraction and connectivity density increased in the vertebrae of OVX/AI+LIV(y) mice compared to OVX/AI(y) mice; however, this effect was attenuated in the older cohort of E ₂ -deprived mice, specifically in OVX/AI+ZA mice, requiring combined LIV with ZA to increase trabecular bone volume and strength. Similar improvements in cortical bone thickness and cross-sectional area of the femoral mid-diaphysis were observed in OVX/AI+LIV+ZA mice, resulting in greater fracture resistance. Our findings demonstrate that the combination of mechanical signals in the form of LIV and anti-resorptive therapy via ZA improve vertebral trabecular bone and femoral cortical bone, increase lean mass, and reduce adiposity in mice undergoing complete E ₂ -deprivation. One Sentence Summary: Low-magnitude mechanical signals with zoledronic acid suppressed bone and muscle loss and adiposity in mice undergoing complete estrogen deprivation.

TRANSLATIONAL RELEVANCE

Postmenopausal patients with estrogen receptor-positive breast cancer treated with aromatase inhibitors to reduce tumor progression experience deleterious effects to bone and muscle subsequently develop muscle weakness, bone fragility, and adipose tissue accrual. Bisphosphonates (i.e., zoledronic acid) prescribed to inhibit osteoclast-mediated bone resorption are effective in preventing bone loss but may not address the non-skeletal effects of muscle weakness and fat accumulation that contribute to patient morbidity. Mechanical signals, typically delivered to the musculoskeletal system during exercise/physical activity, are integral for maintaining bone and muscle health; however, patients undergoing treatments for breast cancer often experience decreased physical activity which further accelerates musculoskeletal degeneration. Low-magnitude mechanical signals, in the form of low-intensity vibrations, generate dynamic loading forces similar to those derived from skeletal muscle contractility. As an adjuvant to existing treatment strategies, low-intensity vibrations may preserve or rescue diminished bone and muscle degraded by breast cancer treatment.

Metabolomic biomarkers for the diagnosis and post-transplant outcomes of AFP negative hepatocellular carcinoma

Background

Early diagnosis for α-fetoprotein (AFP) negative hepatocellular carcinoma (HCC) remains a critical problem. Metabolomics is prevalently involved in the identification of novel biomarkers. This study aims to identify new and effective markers for AFP negative HCC.

Methods

In total, 147 patients undergoing liver transplantation were enrolled from our hospital, including liver cirrhosis patients (LC, n=25), AFP negative HCC patients (NEG, n=44) and HCC patients with AFP over 20 ng/mL (POS, n=78). 52 Healthy volunteers (HC) were also recruited in this study. Metabolomic profiling was performed on the plasma of those patients and healthy volunteers to select candidate metabolomic biomarkers. A novel diagnostic model for AFP negative HCC was established based on Random forest analysis, and prognostic biomarkers were also identified.

Results

15 differential metabolites were identified being able to distinguish NEG group from both LC and HC group. Random forest analysis and subsequent Logistic regression analysis showed that PC(16:0/16:0), PC(18:2/18:2) and SM(d18:1/18:1) are independent risk factor for AFP negative HCC. A three-marker model of Metabolites-Score was established for the diagnosis of AFP negative HCC patients with an area under the time-dependent receiver operating characteristic curve (AUROC) of 0.913, and a nomogram was then established as well. When the cut-off value of the score was set at 1.2895, the sensitivity and specificity for the model were 0.727 and 0.92, respectively. This model was also applicable to distinguish HCC from cirrhosis. Notably, the Metabolites-Score was not correlated to tumor or body nutrition parameters, but difference of the score was statistically significant between different neutrophil-lymphocyte ratio (NLR) groups (≤5 vs. >5, P=0.012). Moreover, MG(18:2/0:0/0:0) was the only prognostic biomarker among 15 metabolites, which is significantly associated with tumor-free survival of AFP negative HCC patients (HR=1.160, 95%CI 1.012-1.330, P=0.033).

Conclusion

The established three-marker model and nomogram based on metabolomic profiling can be potential non-invasive tool for the diagnosis of AFP negative HCC. The level of MG(18:2/0:0/0:0) exhibits good prognosis prediction performance for AFP negative HCC.

Primary Liver Cancers: Connecting the Dots of Cellular Studies and Epidemiology with Metabolomics

Liver cancers are rising worldwide. Between molecular and epidemiological studies, a research gap has emerged which might be amenable to the technique of metabolomics. This review investigates the current understanding of liver cancer's trends, etiology and its correlates with existing literature for hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA) and hepatoblastoma (HB). Among additional factors, the literature reports dysfunction in the tricarboxylic acid metabolism, primarily for HB and HCC, and point mutations and signaling for CCA. All cases require further investigation of upstream and downstream events. All liver cancers reported dysfunction in the WNT/β-catenin and P13K/AKT/mTOR pathways as well as changes in FGFR. Metabolites of IHD1, IDH2, miRNA, purine, Q10, lipids, phosphatidylcholine, phosphatidylethanolamine, acylcarnitine, 2-HG and propionyl-CoA emerged as crucial and there was an attempt to elucidate the WNT/β-catenin and P13K/AKT/mTOR pathways metabolomically.

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.

Interplay Between Fatty Acids, Stearoyl-Co-A Desaturase, Mechanistic Target of Rapamycin, and Yes-Associated Protein/Transcriptional Coactivator With PDZ-Binding Motif in Promoting Hepatocellular Carcinoma

Nonalcoholic fatty liver disease has reached pandemic proportions with one of its most consequential complications being hepatocellular carcinoma (HCC). Nonalcoholic fatty liver disease-related HCC is becoming the leading indication for liver transplantation in the United States. Given the scarcity of available organs, early detection and prevention remain key in prevention and management of the disease. Over the years, the yes-associated protein (YAP)/transcriptional coactivator with PDZ-binding motif (TAZ) pathway emerged as a key signal transduction pathway in the pathogenesis of HCC. In this review, we explore the interplay between the YAP/TAZ pathway as a point of convergence in HCC pathogenesis. We review the evidence of how lipid reprogramming and key lipid pathways, saturated and monounsaturated fatty acids (through the rate-limiting enzyme stearoyl Co-A desaturase), the mevalonic acid pathway (the role of statins), and mechanistic target of rapamycin all play critical roles in intricate and complex networks that tightly regulate the YAP/TAZ pro-oncogenic pathway.

Acylcarnitines: Nomenclature, Biomarkers, Therapeutic Potential, Drug Targets, and Clinical Trials

Acylcarnitines are fatty acid metabolites that play important roles in many cellular energy metabolism pathways. They have historically been used as important diagnostic markers for inborn errors of fatty acid oxidation and are being intensively studied as markers of energy metabolism, deficits in mitochondrial and peroxisomal β -oxidation activity, insulin resistance, and physical activity. Acylcarnitines are increasingly being identified as important indicators in metabolic studies of many diseases, including metabolic disorders, cardiovascular diseases, diabetes, depression, neurologic disorders, and certain cancers. The US Food and Drug Administration-approved drug L-carnitine, along with short-chain acylcarnitines (acetylcarnitine and propionylcarnitine), is now widely used as a dietary supplement. In light of their growing importance, we have undertaken an extensive review of acylcarnitines and provided a detailed description of their identity, nomenclature, classification, biochemistry, pathophysiology, supplementary use, potential drug targets, and clinical trials. We also summarize these updates in the Human Metabolome Database, which now includes information on the structures, chemical formulae, chemical/spectral properties, descriptions, and pathways for 1240 acylcarnitines. This work lays a solid foundation for identifying, characterizing, and understanding acylcarnitines in human biosamples. We also discuss the emerging opportunities for using acylcarnitines as biomarkers and as dietary interventions or supplements for many wide-ranging indications. The opportunity to identify new drug targets involved in controlling acylcarnitine levels is also discussed. SIGNIFICANCE STATEMENT: This review provides a comprehensive overview of acylcarnitines, including their nomenclature, structure and biochemistry, and use as disease biomarkers and pharmaceutical agents. We present updated information contained in the Human Metabolome Database website as well as substantial mapping of the known biochemical pathways associated with acylcarnitines, thereby providing a strong foundation for further clarification of their physiological roles.

CRIP1 suppresses BBOX1-mediated carnitine metabolism to promote stemness in hepatocellular carcinoma

Carnitine metabolism is thought to be negatively correlated with the progression of hepatocellular carcinoma (HCC) and the specific molecular mechanism is yet to be fully elucidated. Here, we report that little characterized cysteine-rich protein 1 (CRIP1) is upregulated in HCC and associated with poor prognosis. Moreover, CRIP1 promoted HCC cancer stem-like properties by downregulating carnitine energy metabolism. Mechanistically, CRIP1 interacted with BBOX1 and the E3 ligase STUB1, promoting BBOX1 ubiquitination and proteasomal degradation, and leading to the downregulation of carnitine. BBOX1 ubiquitination at lysine 240 is required for CRIP1-mediated control of carnitine metabolism and cancer stem-like properties. Further, our data showed that acetylcarnitine downregulation in CRIP1-overexpressing cells decreased beta-catenin acetylation and promoted nuclear accumulation of beta-catenin, thus facilitating cancer stem-like properties. Clinically, patients with higher CRIP1 protein levels had lower BBOX1 levels but higher nuclear beta-catenin levels in HCC tissues. Together, our findings identify CRIP1 as novel upstream control factor for carnitine metabolism and cancer stem-like properties, suggesting targeting of the CRIP1/BBOX1/β-catenin axis as a promising strategy for HCC treatment.

Optimized Systematic Review Tool: Application to Candidate Biomarkers for the Diagnosis of Hepatocellular Carcinoma

This review aims to develop an appropriate review tool for systematically collating metabolites that are dysregulated in disease and applies the method to identify novel diagnostic biomarkers for hepatocellular carcinoma (HCC). Studies that analyzed metabolites in blood or urine samples where HCC was compared with comparison groups (healthy, precirrhotic liver disease, cirrhosis) were eligible. Tumor tissue was included to help differentiate primary and secondary biomarkers. Searches were conducted on Medline and EMBASE. A bespoke "risk of bias" tool for metabolomic studies was developed adjusting for analytic quality. Discriminant metabolites for each sample type were ranked using a weighted score accounting for the direction and extent of change and the risk of bias of the reporting publication. A total of 84 eligible studies were included in the review (54 blood, 9 urine, and 15 tissue), with six studying multiple sample types. High-ranking metabolites, based on their weighted score, comprised energy metabolites, bile acids, acylcarnitines, and lysophosphocholines. This new review tool addresses an unmet need for incorporating quality of study design and analysis to overcome the gaps in standardization of reporting of metabolomic data. Validation studies, standardized study designs, and publications meeting minimal reporting standards are crucial for advancing the field beyond exploratory studies.

Study on the levels of N-nitrosamine compounds and untargeted metabolomics in patients with colorectal cancer

Plasma samples were collected from 34 patients with advanced CRC and 92 healthy persons (control group), and the levels of 9 VNAs were measured using GC-MS. Untargeted metabolomics analysis was performed using LC-MS/MS. Partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis were used to determine differential metabolites between the 2 groups. Receiver operating characteristic (ROC) curve analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed on the differential metabolites. It turned out that the detection rates of N-nitrosodimethylamine (NDMA) and N-nitrosopyrrolidine (NPYR) in patients with CRC were higher than in the control group (P < 0.05). N-nitrosomethylethylamine (NMEA) and N-nitrosodiphenylamine (NDPhA) were not detected in CRC patients. NDMA, N-nitrosodibutylamine (NDBA), N-nitrosopiperidine (NPIP), and NPYR were detected in male and female patients with CRC. There was no difference in VNAs exposure between the sexes of CRC patients. In the positive and negative ion mode, a total of 132 differential metabolites and 6 differential metabolic pathways were detected. Adenosine 5'-monophosphate, hypoxanthine, 11,12-epoxy-(5Z,8Z,11Z)-icosatrienoic acid, 16(R)-HETE, acetylcarnitine, and lysophosphatidic acid (LPA 20:5, LPA 20:4) were candidate biomarkers with higher predictive value. Hypoxanthine and xanthine metabolic pathways were associated with changes in VNAs in CRC patients. In summary, the effects of changes of VNAs in the plasma of CRC patients (especially NDMA and NPYR) on the progression of CRC should attract attention. Abnormalities of adenine and guanine and downstream hypoxanthine-xanthine metabolic pathways were closely related to changes of VNAs and metabolomics in CRC patients.

Potential Biomarkers for Liver Cancer Diagnosis Based on Multi-Omics Strategy

Liver cancer is the fourth leading cause of cancer-related death worldwide. Hepatocellular carcinoma (HCC) accounts for about 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients are eligible for curative therapy mainly due to the lack of early-detection strategies, highlighting the significance of reliable and accurate biomarkers. The integration of multi-omics became an important tool for biomarker screening and unique alterations in tumor-associated genes, transcripts, proteins, post-translational modifications and metabolites have been observed. We here summarized the novel biomarkers for HCC diagnosis based on multi-omics technology as well as the clinical significance of these potential biomarkers in the early detection of HCC.

Metabolomic biomarkers for hepatocellular carcinoma: A systematic review

Hepatocellular carcinoma (HCC) is a highly malignant cancer which lack of effective diagnosis and prognosis biomarkers, therefore surging studies focused on the metabolite candidates for HCC. The current study was designed to systematically review the metabolic studies for HCC, summarize the current available evidence and provide implication for further studies within this area. By systematically screening Pubmed and Embase, and eligibility assessment, we eventually included 55 pieces of studies. After summarized their characteristics, we reviewed them by 3 parts, regarding to the different biofluid they carried out the experiments. By collecting the candidates from all the included studies, we carried out pathway enrichment to see the representative of the reported candidates, as expected the pathway consistent with the current knowledge of HCC. Next, we conduct quality assessment on the included studies. Only 36% of the current evidence grouped as high quality, indicating the quality of metabolic studies needs further improvement.

Characterization of metabolic landscape in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, accounting for approximately 75%-85% of primary liver cancers. Metabolic alterations have been labeled as an emerging hallmark of tumors. Specially, the last decades have registered a significant improvement in our understanding of the role of metabolism in driving the carcinogenesis and progression of HCC. In this paper, we provide a review of recent studies that investigated the metabolic traits of HCC with a specific focus on three common metabolic alterations involving glycolysis, lipid metabolism, and glutamine addiction which have been gaining much attention in the field of HCC. Next, we describe some representative diagnostic markers or tools, and promising treatment agents that are proposed on the basis of the aforementioned metabolic alterations for HCC. Finally, we present some challenges and directions that may promisingly speed up the process of developing objective diagnostic markers and therapeutic options underlying HCC. Specifically, we recommend future investigations to carefully take into account the influence of heterogeneity, control for study-specific confounds, and invite the validation of existing biomarkers.

Involvement of Tricarboxylic Acid Cycle Metabolites in Kidney Diseases

Mitochondria are complex organelles that orchestrate several functions in the cell. The primary function recognized is energy production; however, other functions involve the communication with the rest of the cell through reactive oxygen species (ROS), calcium influx, mitochondrial DNA (mtDNA), adenosine triphosphate (ATP) levels, cytochrome c release, and also through tricarboxylic acid (TCA) metabolites. Kidney function highly depends on mitochondria; hence mitochondrial dysfunction is associated with kidney diseases. In addition to oxidative phosphorylation impairment, other mitochondrial abnormalities have been described in kidney diseases, such as induction of mitophagy, intrinsic pathway of apoptosis, and releasing molecules to communicate to the rest of the cell. The TCA cycle is a metabolic pathway whose primary function is to generate electrons to feed the electron transport system (ETS) to drives energy production. However, TCA cycle metabolites can also release from mitochondria or produced in the cytosol to exert different functions and modify cell behavior. Here we review the involvement of some of the functions of TCA metabolites in kidney diseases.

Identification of Novel Serum Metabolic Biomarkers as Indicators in the Progression of Intravenous Leiomyomatosis: A High Performance Liquid Chromatography-Tandem Mass Spectrometry-Based Study

Background

Intravenous leiomyomatosis (IVL) is a rare estrogen-dependent neoplasm. However, identifiable and reliable biomarkers are still not available for clinical application, especially for the diagnosis and prognosis of the disease.

Methods

In the present study, 30 patients with IVL and 30 healthy controls were recruited. Serum samples were isolated from these participants for further high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis to study metabolomics alterations and identify differentially expressed metabolites based on orthogonal partial least-squares discriminant analysis (OPLS-DA). Subsequently, lasso regression analysis and a generalized linear regression model were applied to screen out hub metabolites associated with the progression of IVL.

Results

First, 16 metabolites in the positive ion mode were determined from the 240 identifiable metabolites at the superclass level, with ten metabolites upregulated in the IVL group and the remaining six metabolites downregulated. Our data further proved that four metabolites [hypoxanthine, acetylcarnitine, glycerophosphocholine, and hydrocortisone (cortisol)] were closely related to the oncogenesis of IVL. Hypoxanthine and glycerophosphocholine might function as protective factors in the development of IVL (OR = 0.19 or 0.02, respectively). Nevertheless, acetylcarnitine and hydrocortisone (cortisol), especially the former, might serve as risk indicators for the disease to promote the development or recurrence of IVL (OR = 18.16 or 2.10, respectively). The predictive accuracy of these hub metabolites was further validated by the multi-class receiver operator characteristic curve analysis (ROC) with the Scikit-learn algorithms.

Conclusion

Four hub metabolites were finally determined via comprehensive bioinformatics analysis, and these substances could potentially serve as novel biomarkers in predicting the prognosis or progression of IVL.

The metabolic landscape of decidua in recurrent pregnancy loss using a global metabolomics approach

INTRODUCTION

Maternal metabolism undergoes dynamic changes during pregnancy. A deviation from this physiological metabolic status might be involved in the pathogenesis of pregnancy complications, such as recurrent pregnancy loss (RPL). Decidua is an important uterine tissue, which provides immunological protection as well as nutritional support to the developing embryo during early pregnancy. Previous studies have shown that aberrant metabolism of the decidua is related to the etiology of RPL. However, the metabolic profile of the decidua in RPL has not yet been fully elucidated.

METHODS

In the current study, decidual samples from RPL patients (n = 23) and normal pregnancy (NP) women (n = 30) were collected, and hydrophilic and hydrophobic metabolites were extracted and measured using a liquid chromatography electrospray ionization tandem mass spectrometry system. Besides, the mRNA expression of several critical enzymes involved in sphingolipid metabolism and glycerophospholipid metabolism was detected.

RESULTS

The OSC-PLS-DA scores plot illustrates that metabolic differences are present in the decidual tissue of RPL patients compared with that of NP women. Combining multivariate analysis with univariate statistical analysis, a total of 62 metabolites related to RPL were selected, including carnitine, glycerophospholipids, sphingomyelin (SM), ceramide, organic acids and their derivatives, and amino acid metabolomics. KEGG analysis showed that abnormalities in multiple metabolic pathways occurred in RPL decidua, including vitamin digestion and absorption, tryptophan metabolism, citrate cycle, arginine biosynthesis, glycerophospholipid metabolism, sphingolipid metabolism, and sphingolipid signaling pathway. Increased SM synthase and decreased Phospholipase A2 Group IIE mRNA levels were detected in RPL compared with NP group.

DISCUSSION

Disruption of decidual metabolism, especially glycerophospholipid metabolism and sphingolipid metabolism, might be involved in the occurrence of RPL.

Tumor metabolism and associated serum metabolites define prognostic subtypes of Asian hepatocellular carcinoma

Treatment effectiveness in hepatocellular carcinoma (HCC) depends on early detection and precision-medicine-based patient stratification for targeted therapies. However, the lack of robust biomarkers, particularly a non-invasive diagnostic tool, precludes significant improvement of clinical outcomes for HCC patients. Serum metabolites are one of the best non-invasive means for determining patient prognosis, as they are stable end-products of biochemical processes in human body. In this study, we aimed to identify prognostic serum metabolites in HCC. To determine serum metabolites that were relevant and representative of the tissue status, we performed a two-step correlation analysis to first determine associations between metabolic genes and tissue metabolites, and second, between tissue metabolites and serum metabolites among 49 HCC patients, which were then validated in 408 additional Asian HCC patients with mixed etiologies. We found that certain metabolic genes, tissue metabolites and serum metabolites can independently stratify HCC patients into prognostic subgroups, which are consistent across these different data types and our previous findings. The metabolic subtypes are associated with β-oxidation process in fatty acid metabolism, where patients with worse survival outcome have dysregulated fatty acid metabolism. These serum metabolites may be used as non-invasive biomarkers to define prognostic tumor molecular subtypes for HCC.

HCC and Tumor Biomarkers: Does One Size Fits All?

Hepatocellular carcinoma (HCC) is a highly malignant disease and early diagnosis rates remain to be unsatisfactory. Owing to this limitation, advances in treatment options including liver transplantation (LT) are limited to improve survival. Recent HCC guidelines no longer recommend alpha-fetoprotein (AFP) as a surveillance and diagnostic tool for HCC. Hence, utilization of novel biomarkers has become imperative to improve disease management strategies. Noninvasive, serum-based biomarkers are potential options to aid early diagnosis as well as prompting treatment. However, further studies are required to find out the accuracy and potential of these approaches and introduce into clinical practice.

Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.

Multiple reaction monitoring profiling as an analytical strategy to investigate lipids in extracellular vesicles

Extracellular vesicles (EVs) convey information used in cell-to-cell interactions. Lipid analysis of EVs remains challenging because of small sample amounts available. Lipid discovery using traditional mass spectrometry platforms based on liquid chromatography and high mass resolution typically employs milligram sample amounts. We report a simple workflow for lipid profiling of EVs based on multiple reaction monitoring (MRM) profiling that uses microgram amounts of sample. After liquid-liquid extraction, individual EV samples were injected directly into the electrospray ionization (ESI) ion source at low flow rates (10 μl/min) and screened for 197 MRM transitions chosen to be a characteristic of several classes of lipids. This choice was based on a discovery experiment, which applied 1,419 MRMs associated with multiple lipid classes to a representative pooled sample. EVs isolated from 12 samples of human lymphocytes and 16 replicates from six different rat cells lines contained an estimated amount of total lipids of 326 to 805 μg. Samples showed profiles that included phosphatidylcholine (PC), sphingomyelin (SM), cholesteryl ester (CE), and ceramide (Cer) lipids, as well as acylcarnitines. The lipid profiles of human lymphocyte EVs were distinguishable using principal component and cluster analysis in terms of prior antibody and drug exposure. Lipid profiles of rat cell lines EV's were distinguishable by their tissue of origin.

Untargeted Metabolomic Characterization of Ovarian Tumors

Simple Summary

This study utilized untargeted metabolomic techniques to detect urine and plasma metabolites. Using support vector machine algorithm, three models for ovarian tumors diagnosis, benign-malignant distinguishing, early diagnosis and borderline-malignant distinguishing were developed. These models have good classification performance and provided a novel insight for non-invasive diagnosis of ovarian cancer.

Abstract

Diagnosis of ovarian cancer is difficult due to the lack of clinical symptoms and effective screening algorithms. In this study, we aim to develop models for ovarian cancer diagnosis by detecting metabolites in urine and plasma samples. Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive ion mode was used for metabolome quantification in 235 urine samples and 331 plasma samples. Then, Urine and plasma metabolomic profiles were analyzed by univariate and multivariate statistics. Four groups of samples: normal control, benign, borderline and malignant ovarian tumors were enrolled in this study. A total of 1330 features and 1302 features were detected from urine and plasma samples respectively. Based on two urine putative metabolites, five plasma putative metabolites and five urine putative metabolites, three models for distinguishing normal-ovarian tumors, benign-malignant (borderline + malignant) and borderline-malignant ovarian tumors were developed respectively. The AUC (Area Under Curve) values were 0.987, 0876 and 0.943 in discovery set and 0.984, 0.896 and 0.836 in validation set for three models. Specially, the diagnostic model based on 5 plasma putative metabolites had better early-stage diagnosis performance than CA125 alone. The AUC values of the model were 0.847 and 0.988 in discovery and validation set respectively. Our results showed that normal and ovarian tumors have unique metabolic signature in urine and plasma samples, which shed light on the ovarian cancer diagnosis and classification.

A glycolysis-related gene pairs signature predicts prognosis in patients with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most universal malignant liver tumors worldwide. However, there were no systematic studies to establish glycolysis‑related gene pairs (GRGPs) signatures for the patients with HCC. Therefore, the study aimed to establish novel GRGPs signatures to better predict the prognosis of HCC.

Methods

Based on the data from Gene Expression Omnibus, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium databases, glycolysis-related mRNAs were used to construct GRGPs. Cox regression was applied to establish a seventeen GRGPs signature in TCGA dataset, which was verified in two validation (European and American, and Asian) datasets.

Results

Seventeen prognostic GRGPs (HMMR_PFKFB1, CHST1_GYS2, MERTK_GYS2, GPC1_GYS2, LDHA_GOT2, IDUA_GNPDA1, IDUA_ME2, IDUA_G6PD, IDUA_GPC1, MPI_GPC1, SDC2_LDHA, PRPS1_PLOD2, GALK1_IER3, MET_PLOD2, GUSB_IGFBP3, IL13RA1_IGFBP3 and CYB5A_IGFBP3) were identified to be significantly progressive factors for the patients with HCC in the TCGA dataset, which constituted a GRGPs signature. The patients with HCC were classified into low-risk group and high-risk group based on the GRGPs signature. The GRGPs signature was a significantly independent prognostic indicator for the patients with HCC in TCGA (log-rank P = 2.898e−14). Consistent with the TCGA dataset, the patients in low-risk group had a longer OS in two validation datasets (European and American: P = 1.143e−02, and Asian: P = 6.342e−08). Additionally, the GRGPs signature was also validated as a significantly independent prognostic indicator in two validation datasets.

Conclusion

The seventeen GRGPs and their signature might be molecular biomarkers and therapeutic targets for the patients with HCC.

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

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

Magnetic organic porous polymer as a solid-phase extraction adsorbent for enrichment and quantitation of gastric cancer biomarkers (P-cresol and 4-hydroxybenzoic acid) in urine samples by UPLC

A novel magnetic organic porous polymer (denoted as Fe₃O₄@PC-POP) was developed for magnetic solid-phase extraction (MSPE) of two gastric cancer biomarkers (P-cresol and 4-hydroxybenzoic acid) from urine samples prior to high-performance liquid chromatographic analysis. The adsorbent was characterized by scanning electron microscope, transmission electron microscope, FTIR, powder X-ray diffraction, and other techniques. The result of dynamic light scattering shows that the particle size of the adsorbent is mainly distributed around 400 nm. Based on the design concept of the Fe₃O₄@PC-POP, the proposed material can effectively capture the target analytes through electrostatic and hydrophobic interaction mechanism. Furthermore, the enrichment conditions were optimized by the response surface method, and the method was utilized for the determination of P-cresol and 4-hydroxybenzoic acid in real urine samples from health and gastric cancer patients with high enrichment factors (34.8 times for P-cresol and 38.7 times for 4-hydroxybenzoic acid), low limit of detection (0.9-5.0 μg L^-1), wide linear ranges (3.0-1000 μg L^-1), satisfactory relative standard deviation (2.5%-8.5%), and apparent recoveries (85.3-112% for healthy people's and 86.0-112% for gastric cancer patients' urine samples). This study provides a guided principle for design of the versatile polymer with specific capturing of the target compounds from complex biological samples. Graphical abstract.

Serum metabolites may be useful markers to assess vascular invasion and identify normal alpha-fetoprotein in hepatocellular carcinoma undergoing liver resection: a pilot study

Purpose

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver with a dismal prognosis. Vascular invasion, among others, is the most robust indicator of postoperative recurrence and overall survival after liver resection for HCC. Few studies to date have attempted to search for effective markers to predict vascular invasion before the operation. The current study would examine the plasma metabolic profiling via ¹H-NMR of HCC patients undergoing liver resection and aim to search for potential biomarkers in the early detection of HCC with normal alpha-fetoprotein (AFP) and the diagnosis of vascular invasion preoperatively.

Materials and methods

HCC patients scheduled to receive liver resections for their HCC were recruited and divided into two separate groups, investigation cohort and validation cohort. Their preoperative blood samples were collected and subjected to a comprehensive metabolomic profiling using ¹H-nuclear magnetic resonance spectroscopy (NMR).

Results

There were 35 HCC patients in the investigation group and 22 patients in the validation group. Chronic hepatitis B remained the most common etiology of HCC, followed by chronic HCV infection. The two study cohorts were essentially comparable in terms of major clinicopathological variables. After ¹H-nuclear NMR analysis, we found in the investigation cohort that HCC with normal alpha-fetoprotein (AFP < 15 ng/mL) had significantly higher serum level of O-acetylcarnitine than those with higher AFP (AFP ≥ 15 ng/mL, P = 0.025). In addition, HCC with microscopic vascular invasion (VI) had significantly higher preoperative serum level of formate than HCC without microscopic VI (P = 0.023). These findings were similar in the validation cohort.

Conclusion

A comprehensive metabolomic profiling of HCC demonstrated that serum metabolites may be utilized to assist the early diagnosis of AFP-negative HCC patients and recognition of microvascular invasion in order to facilitate preoperative surgical planning and postoperative follow-up. Further, larger scale prospective studies are warranted to consolidate our findings.

Lipid Metabolism in Development and Progression of Hepatocellular Carcinoma

: Metabolic reprogramming is critically involved in the development and progression of cancer. In particular, lipid metabolism has been investigated as a source of energy, micro-environmental adaptation, and cell signalling in neoplastic cells. However, the specific role of lipid metabolism dysregulation in hepatocellular carcinoma (HCC) has not been widely described yet. Alterations in fatty acid synthesis, β-oxidation, and cellular lipidic composition contribute to initiation and progression of HCC. The aim of this review is to elucidate the mechanisms by which lipid metabolism is involved in hepatocarcinogenesis and tumour adaptation to different conditions, focusing on the transcriptional aberrations with new insights in lipidomics and lipid zonation. This will help detect new putative therapeutic approaches in the second most frequent cause of cancer-related death.

Mass spectrometry imaging-based metabolomics to visualize the spatially resolved reprogramming of carnitine metabolism in breast cancer

New insights into tumor-associated metabolic reprogramming have provided novel vulnerabilities that can be targeted for cancer therapy. Here, we propose a mass spectrometry imaging (MSI)-based metabolomic strategy to visualize the spatially resolved reprogramming of carnitine metabolism in heterogeneous breast cancer. Methods: A wide carnitine coverage MSI method was developed to investigate the spatial alternations of carnitines in cancer tissues of xenograft mouse models and human samples. Spatial expression of key metabolic enzymes that are closely associated with the altered carnitines was examined in adjacent cancer tissue sections. Results: A total of 17 carnitines, including L-carnitine, 6 short-chain acylcarnitines, 3 middle-chain acylcarnitines, and 7 long-chain acylcarnitines were imaged. L-carnitine and short-chain acylcarnitines are significantly reprogrammed in breast cancer. A classification model based on the carnitine profiles of 170 cancer samples and 128 normal samples enables an accurate identification of breast cancer. CPT 1A, CPT 2, and CRAT, which are extensively involved in carnitine system-mediated fatty acid β-oxidation pathway were also found to be abnormally expressed in breast cancer. Remarkably, the expressions of CPT 2 and CRAT were found for the first time to be altered in breast cancer. Conclusion: These data not only expand our understanding of the complex tumor metabolic reprogramming, but also provide the first evidence that carnitine metabolism is reprogrammed at both the metabolite and enzyme levels in breast cancer.

Liquid Biopsies in Hepatocellular Carcinoma: Are We Winning?

Hepatocellular carcinoma (HCC) represents the sixth most common cancer worldwide and the third most common cause of cancer-related death. One of the major problems faced by researchers and clinicians in this area is the lack of reliable disease biomarkers, which would allow for an earlier diagnosis, follow-up or prediction of treatment response, among others. In this regard, the “HCC circulome”, defined as the pool of circulating molecules in the bloodstream derived from the primary tumor, represents an appealing target, the so called liquid biopsy. Such molecules encompass circulating tumor proteins, circulating tumor cells (CTCs), extracellular vesicles (EVs), tumor-educated platelets (TEPs), and circulating tumor nucleic acids, namely circulating tumor DNA (ctDNA) and circulating tumor RNA (ctRNA). In this article, we summarize recent findings highlighting the promising role of liquid biopsies as novel potential biomarkers in HCC, emphasizing on its clinical performance.

Comprehensive metabolomics analysis of prostate cancer tissue in relation to tumor aggressiveness and TMPRSS2-ERG fusion status

Background

Prostate cancer (PC) can display very heterogeneous phenotypes ranging from indolent asymptomatic to aggressive lethal forms. Understanding how these PC subtypes vary in their striving for energy and anabolic molecules is of fundamental importance for developing more effective therapies and diagnostics. Here, we carried out an extensive analysis of prostate tissue samples to reveal metabolic alterations during PC development and disease progression and furthermore between TMPRSS2-ERG rearrangement-positive and -negative PC subclasses.

Methods

Comprehensive metabolomics analysis of prostate tissue samples was performed by non-destructive high-resolution magic angle spinning nuclear magnetic resonance (¹H HR MAS NMR). Subsequently, samples underwent moderate extraction, leaving tissue morphology intact for histopathological characterization. Metabolites in tissue extracts were identified by ¹H/³¹P NMR and liquid chromatography-mass spectrometry (LC-MS). These metabolomics profiles were analyzed by chemometric tools and the outcome was further validated using proteomic data from a separate sample cohort.

Results

The obtained metabolite patterns significantly differed between PC and benign tissue and between samples with high and low Gleason score (GS). Five key metabolites (phosphocholine, glutamate, hypoxanthine, arginine and α-glucose) were identified, who were sufficient to differentiate between cancer and benign tissue and between high to low GS. In ERG-positive PC, the analysis revealed several acylcarnitines among the increased metabolites together with decreased levels of proteins involved in β-oxidation; indicating decreased acyl-CoAs oxidation in ERG-positive tumors. The ERG-positive group also showed increased levels of metabolites and proteins involved in purine catabolism; a potential sign of increased DNA damage and oxidative stress.

Conclusions

Our comprehensive metabolomic analysis strongly indicates that ERG-positive PC and ERG-negative PC should be considered as different subtypes of PC; a fact requiring different, sub-type specific treatment strategies for affected patients.

Metabolomic Analysis of the Liver of a Dextran Sodium Sulfate-Induced Acute Colitis Mouse Model: Implications of the Gut-Liver Connection

The incidence of ulcerative colitis (UC) is increasing worldwide, and it has become a growing problem in Asia. Previous research on UC has focused on serum, plasma, urine, gut tissues, and fecal metabolic profiling, but a comprehensive investigation into the correlation between the severity of colitis and changes in liver metabolism is still lacking. Since the liver and gut exchange nutrients and metabolites through a complex network, intestinal diseases can affect both the liver and other organs. In the present study, concentration-dependent dextran sodium sulfate (DSS)-induced ulcerative colitis was employed to examine changes in liver metabolism using a proton nuclear magnetic resonance spectroscopy (¹H-NMR)-and ultra-performance liquid chromatography time of flight mass spectroscopy (UPLC-TOF MS)-based metabolomics study. Using the multivariate statistical analysis method orthogonal projections to latent structures discriminant analysis (OPLS-DA), changes in metabolites depending on the DSS dose could be clearly distinguished. Specifically, hepatic metabolites involved in one-carbon metabolism, carnitine-related metabolism, and nucleotide synthesis were found to be affected by intestinal inflammation, implying the existence of a metabolic connection between the gut and liver. We are currently investigating the significance of this metabolic condition in UC.

1H-NMR Based Serum Metabolomics Highlights Different Specific Biomarkers between Early and Advanced Hepatocellular Carcinoma Stages

The application of non-targeted serum metabolomics profiling represents a noninvasive tool to identify new clinical biomarkers and to provide early diagnostic differentiation, and insight into the pathological mechanisms underlying hepatocellular carcinoma (HCC) progression. In this study, we used proton Nuclear Magnetic Resonance (¹H-NMR) Spectroscopy and multivariate data analysis to profile the serum metabolome of 64 HCC patients, in early (n = 28) and advanced (n = 36) disease stages. We found that ¹H-NMR metabolomics profiling could discriminate early from advanced HCC patients with a cross-validated accuracy close to 100%. Orthogonal partial least squares discriminant analysis (OPLS-DA) showed significant changes in serum glucose, lactate, lipids and some amino acids, such as alanine, glutamine, 1-methylhistidine, lysine and valine levels between advanced and early HCC patients. Moreover, in early HCC patients, Kaplan-Meier analysis highlighted the serum tyrosine level as a predictor for overall survival (OS). Overall, our analysis identified a set of metabolites with possible clinical and biological implication in HCC pathophysiology.

Mass spectrometry imaging to detect lipid biomarkers and disease signatures in cancer

BACKGROUND

Current methods to identify, classify, and predict tumor behavior mostly rely on histology, immunohistochemistry, and molecular determinants. However, better predictive markers are required for tumor diagnosis and evaluation. Due, in part, to recent technological advancements, metabolomics and lipid biomarkers have become a promising area in cancer research. Therefore, there is a necessity for novel and complementary techniques to identify and visualize these molecular markers within tumors and surrounding tissue.

RECENT FINDINGS

Since its introduction, mass spectrometry imaging (MSI) has proven to be a powerful tool for mapping analytes in biological tissues. By adding the label-free specificity of mass spectrometry to the detailed spatial information of traditional histology, hundreds of lipids can be imaged simultaneously within a tumor. MSI provides highly detailed lipid maps for comparing intra-tumor, tumor margin, and healthy regions to identify biomarkers, patterns of disease, and potential therapeutic targets. In this manuscript, recent advancement in sample preparation and MSI technologies are discussed with special emphasis on cancer lipid research to identify tumor biomarkers.

CONCLUSION

MSI offers a unique approach for biomolecular characterization of tumor tissues and provides valuable complementary information to histology for lipid biomarker discovery and tumor classification in clinical and research cancer applications.

Acylcarnitine: Useful biomarker for early diagnosis of hepatocellular carcinoma in non-steatohepatitis patients

BACKGROUND

Early diagnosis of hepatocellular carcinoma (HCC) is necessary to improve the prognosis of patients. However, the currently available tumor biomarkers are insufficient for the early detection of HCC. Acylcarnitine is essential in fatty acid metabolic pathways. A recent study reported that a high level of acylcarnitine may serve as a useful biomarker for the early diagnosis of HCC in steatohepatitis (SH) patients. In contrast, another study reported that the level of acetylcarnitine (AC2) - one of the acylcarnitine species - in non-SH patients with HCC was decreased vs that reported in those without HCC.

AIM

To investigate the usefulness of acylcarnitine as a biomarker for the early diagnosis of HCC in non-SH patients.

METHODS

Thirty-three non-SH patients (14 with HCC and 19 without HCC) were enrolled in this study. Blood samples were obtained from patients at the time of admission. The levels of acylcarnitine and AC2 in the serum were determined through tandem mass spectrometry. The levels of vascular endothelial growth factor (VEGF) and VEGF receptor 2 (VEGFR-2) were determined by enzyme-linked immunosorbent assay. Univariate and multivariate analyses were used to determine early diagnostic factors of HCC.

RESULTS

The level of acylcarnitine was significantly lower in non-SH patients with HCC vs those without HCC (P < 0.05). In contrast, the level of lens culinaris agglutinin-reactive fraction of α-fetoprotein (AFP) - AFP-L3% - was significantly higher in non-SH patients with HCC vs those without HCC (P < 0.05). However, the levels of total carnitine, free carnitine, AFP, des-γ-carboxy prothrombin, VEGF, and VEGFR-2 were not different between patients with and without HCC. The multivariate analysis showed that a low level of acylcarnitine was the only independent factor for the early diagnosis of HCC. The patients with a low level of AC2 had a significantly higher level of VEGF vs those with a high level of AC2 (P < 0.05).

CONCLUSION

The metabolic pathways of fatty acids may differ between SH HCC and non-SH HCC. Further studies are warranted to investigate these differences.

MicroRNA-194 inhibits cell invasion and migration in hepatocellular carcinoma through PRC1-mediated inhibition of Wnt/β-catenin signaling pathway

BACKGROUND

Hepatocellular carcinoma (HCC) is a commonly occurring malignancy accompanied by significant mortality rates. More recently, extensive investigations into microRNA (miRNA) expression profiles have been conducted to identify their ability to inhibit tumors. Thus, this study explored the role of miR-194 in epithelial-mesenchymal transition (EMT), cell invasion and migration through Wnt/β-catenin signaling pathway by binding to protein regulator of cytokinesis 1 (PRC1) in HCC.

METHODS

Initially, HCC related microarray data were retrieved and analyzed, and regulatory miRNAs of PRC1 were predicted accordingly. Next, the roles of miR-194, PRC1, and Wnt/β-catenin signaling pathway in HCC were determined, with relationship between PRC1 and miR-194 being verified subsequently. The role of miR-194 in cell EMT, migration, proliferation and invasion was evaluated through gain- and loss- function studies. Finally, tumor xenograft in nude mice was induced to assess tumor growth of HCC.

RESULTS

miR-194 affected HCC development in Wnt/β-catenin signaling pathway with putative binding sites to PRC1. MiR-194 could target PRC1. MiR-194 was downregulated while PRC1 was upregulated in HCC tissues. Additionally, miR-194 elevation and PRC1 silencing could suppress EMT, growth, proliferation, invasion, and migration in HCC cells by inactivating Wnt/β-catenin signaling pathway.

CONCLUSION

Taken together, this study demonstrated that miR-194 inhibited EMT, cell invasion and migration through inactivation of PRC1-dependent Wnt/β-catenin signaling pathway.

Multiple “Omics” data-based biomarker screening for hepatocellular carcinoma diagnosis

The huge prognostic difference between early and late stage hepatocellular carcinoma (HCC) is a challenging diagnostic problem. Alpha-fetoprotein is the mostly widely used biomarker for HCC used in the clinic, however it’s sensitivity and specificity of is not optimal. The development and application of multiple biotechnologies, including next generation sequencing, multiple “omics” data, that include genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics has been used for HCC diagnostic biomarker screening. Effective biomarkers/panels/models have been identified and validated at different clinical levels. A large proportion of these have a good diagnostic performance for HCC, especially for early HCC. In this article, we reviewed the various HCC biomarkers derived from “omics” data and discussed the advantages and disadvantages for diagnosis HCC.