Alteration of amino acid and biogenic amine metabolism in hepatobiliary cancers: Findings from a prospective cohort study

Advancements in Mass Spectrometry-Based Targeted Metabolomics and Lipidomics: Implications for Clinical Research

Targeted metabolomics and lipidomics are increasingly utilized in clinical research, providing quantitative and comprehensive assessments of metabolic profiles that underlie physiological and pathological mechanisms. These approaches enable the identification of critical metabolites and metabolic alterations essential for accurate diagnosis and precision treatment. Mass spectrometry, in combination with various separation techniques, offers a highly sensitive and specific platform for implementing targeted metabolomics and lipidomics in clinical settings. Nevertheless, challenges persist in areas such as sample collection, quantification, quality control, and data interpretation. This review summarizes recent advances in targeted metabolomics and lipidomics, emphasizing their applications in clinical research. Advancements, including microsampling, dynamic multiple reaction monitoring, and integration of ion mobility mass spectrometry, are highlighted. Additionally, the review discusses the critical importance of data standardization and harmonization for successful clinical implementation.

Altered Metabolites in Hepatocellular Carcinoma (HCC) Paving the Road for Metabolomics Signature and Biomarkers for Early Diagnosis of HCC

Globally, hepatocellular carcinoma (HCC) is one of the most commonly encountered cancers. Because the current early diagnostic tests for HCC are not very sensitive, most cases of the disease are discovered late when it is in its terminal stage. Cellular metabolism changes during carcinogenesis to enable cancer cells to adapt to the hypoxic milieu, boost anabolic synthesis, promote survival, and evade apoptotic death signals. Omic techniques represent a breakthrough in the field of diagnostic technology. For example, Metabolomics analysis could be used to identify these metabolite alterations. Understanding the metabolic alterations linked to HCC is crucial for improving high-risk patients' surveillance and understanding the illness's biology. This review highlights the metabolic alterations linked to energy production in cancer cells, as well as the significantly altered metabolites and pathways associated with hepatocarcinogenesis, including acylcarnitines (ACs), amino acids, proteins, lipids, carbohydrates, glucose, and lactate, which reflect the anabolic and catabolic changes occurring in these cells. Additionally, it discusses the clinical implications of recent metabolomics that may serve as potential biomarkers for early diagnosis and monitoring of the progression of HCC.

Acute kidney injury development is associated with mortality in Japanese patients with cirrhosis: impact of amino acid imbalance

BACKGROUND

Acute kidney injury (AKI) is a serious complication of cirrhosis. This study analyzed the prognostic effect of AKI in patients with cirrhosis and its risk factors, particularly in relation to amino acid imbalance.

METHODS

This retrospective study reviewed 808 inpatients with cirrhosis at two institutes in Gifu, Japan. AKI was diagnosed according to the recommendations of the International Club of Ascites. Amino acid imbalance was assessed by measuring serum branched-chain amino acid (BCAA) levels, tyrosine levels, and the BCAA-to-tyrosine ratio (BTR). Factors associated with mortality and AKI development were assessed using the Cox proportional hazards regression model with AKI as a time-dependent covariate and the Fine-Gray competing risk regression model, respectively.

RESULTS

Of the 567 eligible patients without AKI at baseline, 27% developed AKI and 25% died during a median follow-up period of 4.7 years. Using a time-dependent covariate, AKI development (hazard ratio [HR], 6.25; 95% confidence interval [CI], 3.98-9.80; p < 0.001) was associated with mortality in patients with cirrhosis independent of potential covariates. In addition, alcohol-associated/-related liver disease, metabolic dysfunction-associated steatohepatitis, Child-Pugh score, and BTR (subdistribution HR 0.78; 95% CI 0.63-0.96; p = 0.022) were independently associated with AKI development in patients with cirrhosis. Similar results were obtained in the multivariate model that included BCAA and tyrosine levels instead of BTR.

CONCLUSIONS

AKI is common and associated with mortality in Japanese patients with cirrhosis. An amino acid imbalance is strongly associated with the development of AKI in patients with cirrhosis.

A Novel Amino Acid-Related Gene Signature Predicts Overall Survival in Patients With Hepatocellular Carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is an extremely harmful malignant tumor in the world. Since the energy metabolism and biosynthesis of HCC cells are closely related to amino acids, it is necessary to further explore the relationship between amino acid-related genes and the prognosis of HCC to achieve individualized treatment. We herein aimed to develop a prognostic model for HCC based on amino acid genes.

METHODS

In this study, RNA-sequencing data of HCC patients were downloaded from the TCGA-LIHC cohort as the training cohort and the GSE14520 cohort as the validation cohort. Amino acid-related genes were derived from the Molecular Signatures Database. Univariate Cox and Lasso regression analysis were used to construct an amino acid-related signature (AARS). The predictive value of this risk score was evaluated by Kaplan-Meier (K-M) curve, receiver operating characteristic (ROC) curve, univariate and multivariate Cox regression analysis. Gene set variation analysis (GSVA) and immune characteristics evaluation were used to explore the underlying mechanisms. Finally, a nomogram was established to help the personalized prognosis assessment of patients with HCC.

RESULTS

The AARS comprises 14 amino acid-related genes to predict overall survival (OS) in HCC patients. HCC patients were divided into AARS-high group and AARS-low group according to the AARS scores. The K-M curve, ROC curve, and univariate and multivariate Cox regression analysis verified the good prediction efficiency of the risk score. Using GSVA, we found that AARS variants were concentrated in four pathways, including cholesterol metabolism, delayed estrogen response, fatty acid metabolism, and myogenesis metabolism.

CONCLUSION

Our results suggest that the AARS as a prognostic model based on amino acid-related genes is of great value in the prediction of survival of HCC, and can help improve the individualized treatment of patients with HCC.

Optimal transport for automatic alignment of untargeted metabolomic data

Untargeted metabolomic profiling through liquid chromatography-mass spectrometry (LC-MS) measures a vast array of metabolites within biospecimens, advancing drug development, disease diagnosis, and risk prediction. However, the low throughput of LC-MS poses a major challenge for biomarker discovery, annotation, and experimental comparison, necessitating the merging of multiple datasets. Current data pooling methods encounter practical limitations due to their vulnerability to data variations and hyperparameter dependence. Here, we introduce GromovMatcher, a flexible and user-friendly algorithm that automatically combines LC-MS datasets using optimal transport. By capitalizing on feature intensity correlation structures, GromovMatcher delivers superior alignment accuracy and robustness compared to existing approaches. This algorithm scales to thousands of features requiring minimal hyperparameter tuning. Manually curated datasets for validating alignment algorithms are limited in the field of untargeted metabolomics, and hence we develop a dataset split procedure to generate pairs of validation datasets to test the alignments produced by GromovMatcher and other methods. Applying our method to experimental patient studies of liver and pancreatic cancer, we discover shared metabolic features related to patient alcohol intake, demonstrating how GromovMatcher facilitates the search for biomarkers associated with lifestyle risk factors linked to several cancer types.

Combination of histological and metabolomic assessments to evaluate the potential pharmacological efficacy of saikosaponin D

Saikosaponin D (SsD), a natural triterpenoid saponin compound, exhibits notable potential in suppressing tumor growth and inhibiting metastasis, particularly in breast cancer. However, its underlying mechanism of action for SsD remains unclear. In this study, a combination strategy to reveal the metabolism modulation of SsD on breast cancer was performed by integration of histopathological assessments and untargeted metabolomics analysis. Pathological evaluation of the efficacy of SsD from a visual and intuitive perspective. Accordingly, a non-targeted metabolomics study was used to investigate the pharmacological efficacy using a set of serum samples from mice before and after (0-30 days) modulated with SsD based on ultra-high performance liquid chromatography tandem orbitrap mass spectrometry to discover metabolite biomarkers for finding the key metabolic mechanism in a molecular perspective. As a result, 20 metabolites were selected as potential biomarkers for SsD efficacy evaluation with high sensitivity and specificity. These metabolites changes were involved in sphingolipid metabolism, glycerophospholipid metabolism, phenylalanine and tryptophan metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis pathways, suggesting that SsD exerted anti-breast cancer effects through the regulation of the underlying metabolism. In conclusion, we developed a new analysis strategy that effectively discovers tumor-progressing related metabolite biomarkers in serum for pharmacological efficacy evaluation.

Dietary melatonin and liver cancer incidence in Japan: From the Takayama study

There is some biological plausibility that exogenous melatonin plays a role in preventing liver carcinogenesis. There has been little research on the association between melatonin intake in a normal diet and health outcomes. We evaluated the association between dietary melatonin intake and the incidence of liver cancer in a population-based prospective study in Japan. This study included 30,824 residents of Takayama city who were 35 years of age or older in 1992 and had participated in the Takayama study, Japan. Dietary intake was assessed using a validated food frequency questionnaire at the baseline. Melatonin content in foods was measured by liquid chromatography-tandem mass spectrometry. Cancer incidence was confirmed through regional population-based cancer registries in Gifu. Liver cancer was defined as code C22 according to the International Classification of Diseases and Related Health Problems, 10th Revision. Hazard ratios for liver cancer were estimated for the tertile groups of melatonin intake using a Cox proportional hazards model. During the mean follow-up period of 13.6 years, 189 individuals developed liver cancer. Compared with subjects in the lowest tertile of melatonin intake, those in the middle and highest tertiles had decreased risks of liver cancer, with a significant linear trend after multivariate adjustments (hazard ratios: 0.64 and 0.65, respectively, trend p = 0.023). There was no significant interaction by sex (interaction p = 0.54). This initial finding, which needs to be confirmed by further studies, suggests that consuming melatonin-containing foods might play a role in the prevention of liver cancer.

Tryptophan metabolism in digestive system tumors: unraveling the pathways and implications

Tryptophan (Trp) metabolism plays a crucial role in influencing the development of digestive system tumors. Dysregulation of Trp and its metabolites has been identified in various digestive system cancers, including esophageal, gastric, liver, colorectal, and pancreatic cancers. Aberrantly expressed Trp metabolites are associated with diverse clinical features in digestive system tumors. Moreover, the levels of these metabolites can serve as prognostic indicators and predictors of recurrence risk in patients with digestive system tumors. Trp metabolites exert their influence on tumor growth and metastasis through multiple mechanisms, including immune evasion, angiogenesis promotion, and drug resistance enhancement. Suppressing the expression of key enzymes in Trp metabolism can reduce the accumulation of these metabolites, effectively impacting their role in the promotion of tumor progression and metastasis. Strategies targeting Trp metabolism through specific enzyme inhibitors or tailored drugs exhibit considerable promise in enhancing therapeutic outcomes for digestive system tumors. In addition, integrating these approaches with immunotherapy holds the potential to further enhance treatment efficacy.

Prediagnostic plasma metabolite concentrations and liver cancer risk: a population-based study of Chinese men

BACKGROUND

Previous metabolic profiling of liver cancer has mostly used untargeted metabolomic approaches and was unable to quantitate the absolute concentrations of metabolites. In this study, we examined the association between the concentrations of 186 targeted metabolites and liver cancer risk using prediagnostic plasma samples collected up to 14 years prior to the clinical diagnosis of liver cancer.

METHODS

We conducted a nested case-control study (n = 322 liver cancer cases, n = 322 matched controls) within the Shanghai Men's Health Study. Conditional logistic regression models adjusted for demographics, lifestyle factors, dietary habits, and related medical histories were used to estimate the odds ratios. Restricted cubic spline functions were used to characterise the dose-response relationships between metabolite concentrations and liver cancer risk.

FINDINGS

After adjusting for potential confounders and correcting for multiple testing, 28 metabolites were associated with liver cancer risk. Significant non-linear relationships were observed for 22 metabolites. The primary bile acid biosynthesis and phenylalanine, tyrosine and tryptophan biosynthesis were found to be important pathways involved in the aetiology of liver cancer. A metabolic score consisting of 10 metabolites significantly improved the predictive ability of traditional epidemiological risk factors for liver cancer, with an optimism-corrected AUC increased from 0.84 (95% CI: 0.81-0.87) to 0.89 (95% CI: 0.86-0.91).

INTERPRETATION

This study characterised the dose-response relationships between metabolites and liver cancer risk, providing insights into the complex metabolic perturbations prior to the clinical diagnosis of liver cancer. The metabolic score may serve as a candidate risk predictor for liver cancer.

FUNDING

National Key Project of Research and Development Program of China [2021YFC2500404, 2021YFC2500405]; US National Institutes of Health [subcontract of UM1 CA173640].

Profile Characterization of Biogenic Amines in Glioblastoma Patients Undergoing Standard-of-Care Treatment

INTRODUCTION

Biogenic amines play important roles throughout cellular metabolism. This study explores a role of biogenic amines in glioblastoma pathogenesis. Here, we characterize the plasma levels of biogenic amines in glioblastoma patients undergoing standard-of-care treatment.

METHODS

We examined 138 plasma samples from 36 patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma at multiple stages of treatment. Untargeted gas chromatography-time of flight mass spectrometry (GC-TOF MS) was used to measure metabolite levels. Machine learning approaches were then used to develop a predictive tool based on these datasets.

RESULTS

Surgery was associated with increased levels of 12 metabolites and decreased levels of 11 metabolites. Chemoradiation was associated with increased levels of three metabolites and decreased levels of three other metabolites. Ensemble learning models, specifically random forest (RF) and AdaBoost (AB), accurately classified treatment phases with high accuracy (RF: 0.81 ± 0.04, AB: 0.78 ± 0.05). The metabolites sorbitol and N-methylisoleucine were identified as important predictive features and confirmed via SHAP.

CONCLUSION

To our knowledge, this is the first study to describe plasma biogenic amine signatures throughout the treatment of patients with glioblastoma. A larger study is needed to confirm these results with hopes of developing a diagnostic algorithm.

Circulating amino acid levels and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition and UK Biobank cohorts

BACKGROUND

Amino acid metabolism is dysregulated in colorectal cancer patients; however, it is not clear whether pre-diagnostic levels of amino acids are associated with subsequent risk of colorectal cancer. We investigated circulating levels of amino acids in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts.

METHODS

Concentrations of 13-21 amino acids were determined in baseline fasting plasma or serum samples in 654 incident colorectal cancer cases and 654 matched controls in EPIC. Amino acids associated with colorectal cancer risk following adjustment for the false discovery rate (FDR) were then tested for associations in the UK Biobank, for which measurements of 9 amino acids were available in 111,323 participants, of which 1221 were incident colorectal cancer cases.

RESULTS

Histidine levels were inversely associated with colorectal cancer risk in EPIC (odds ratio [OR] 0.80 per standard deviation [SD], 95% confidence interval [CI] 0.69-0.92, FDR P-value=0.03) and in UK Biobank (HR 0.93 per SD, 95% CI 0.87-0.99, P-value=0.03). Glutamine levels were borderline inversely associated with colorectal cancer risk in EPIC (OR 0.85 per SD, 95% CI 0.75-0.97, FDR P-value=0.08) and similarly in UK Biobank (HR 0.95, 95% CI 0.89-1.01, P=0.09) In both cohorts, associations changed only minimally when cases diagnosed within 2 or 5 years of follow-up were excluded.

CONCLUSIONS

Higher circulating levels of histidine were associated with a lower risk of colorectal cancer in two large prospective cohorts. Further research to ascertain the role of histidine metabolism and potentially that of glutamine in colorectal cancer development is warranted.

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.

Ultrasensitive quantification of trace amines based on N-phosphorylation labeling chip 2D LC-QQQ/MS

Trace amines (TAs) are metabolically related to catecholamine and associated with cancer and neurological disorders. Comprehensive measurement of TAs is essential for understanding pathological processes and providing proper drug intervention. However, the trace amounts and chemical instability of TAs challenge quantification. Here, diisopropyl phosphite coupled with chip two-dimensional (2D) liquid chromatography tandem triple-quadrupole mass spectrometry (LC-QQQ/MS) was developed to simultaneously determine TAs and associated metabolites. The results showed that the sensitivities of TAs increased up to 5520 times compared with those using nonderivatized LC-QQQ/MS. This sensitive method was utilized to investigate their alterations in hepatoma cells after treatment with sorafenib. The significantly altered TAs and associated metabolites suggested that phenylalanine and tyrosine metabolic pathways were related to sorafenib treatment in Hep3B cells. This sensitive method has great potential to elucidate the mechanism and diagnose diseases considering that an increasing number of physiological functions of TAs have been discovered in recent decades.

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.

Circulating Metabolic Markers Related to the Diagnosis of Hepatocellular Carcinoma

Primary liver carcinoma is the sixth most common cancer worldwide, while hepatocellular carcinoma (HCC) is the most dominant cancer type. Chronic hepatitis B and C virus infections and aflatoxin exposure are the main risk factors, while nonalcoholic fatty liver disease caused by obesity, diabetes, and metabolic syndrome are the more common risk factors for HCC. Metabolic disorders caused by these high-risk factors are closely related to the tumor microenvironment of HCC, revealing a possible cause-and-effect relationship between the two. These metabolic disorders involve many complex metabolic pathways, such as carbohydrate, lipid, lipid derivative, amino acid, and amino acid derivative metabolic processes. The resulting metabolites with significant abnormal changes in the concentration level in circulating blood may be used as biomarkers to guide the diagnosis, treatment, or prognosis of HCC. At present, there are high-throughput technologies that can quickly detect small molecular metabolites in many samples. Compared to tissue biopsy, blood samples are easier to obtain, and patients' willingness to participate is higher, which makes it possible to study blood HCC biomarkers. Over the past few years, a substantial body of research has been performed worldwide, and other potential biomarkers have been identified. Unfortunately, due to the limitations of each study, only a few markers have been widely verified and are suitable for clinical use. This review briefly summarizes the potential blood metabolic markers related to the diagnosis of HCC, mainly focusing on amino acids and their derivative metabolism, lipids and their derivative metabolism, and other possible related metabolisms.

Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition

BACKGROUND

Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations.

METHODS

We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty.

RESULTS

Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk.

CONCLUSIONS

These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.

A systematic review on omics data (metagenomics, metatranscriptomics, and metabolomics) in the role of microbiome in gallbladder disease

Microbiotas are the range of microorganisms (mainly bacteria and fungi) colonizing multicellular, macroscopic organisms. They are crucial for several metabolic functions affecting the health of the host. However, difficulties hamper the investigation of microbiota composition in cultivating microorganisms in standard growth media. For this reason, our knowledge of microbiota can benefit from the analysis of microbial macromolecules (DNA, transcripts, proteins, or by-products) present in various samples collected from the host. Various omics technologies are used to obtain different data. Metagenomics provides a taxonomical profile of the sample. It can also be used to obtain potential functional information. At the same time, metatranscriptomics can characterize members of a microbiome responsible for specific functions and elucidate genes that drive the microbiotas relationship with its host. Thus, while microbiota refers to microorganisms living in a determined environment (taxonomy of microorganisms identified), microbiome refers to the microorganisms and their genes living in a determined environment and, of course, metagenomics focuses on the genes and collective functions of identified microorganisms. Metabolomics completes this framework by determining the metabolite fluxes and the products released into the environment. The gallbladder is a sac localized under the liver in the human body and is difficult to access for bile and tissue sampling. It concentrates the bile produced in the hepatocytes, which drains into bile canaliculi. Bile promotes fat digestion and is released from the gallbladder into the upper small intestine in response to food. Considered sterile originally, recent data indicate that bile microbiota is associated with the biliary tract’s inflammation and carcinogenesis. The sample size is relevant for omic studies of rare diseases, such as gallbladder carcinoma. Although in its infancy, the study of the biliary microbiota has begun taking advantage of several omics strategies, mainly based on metagenomics, metabolomics, and mouse models. Here, we show that omics analyses from the literature may provide a more comprehensive image of the biliary microbiota. We review studies performed in this environmental niche and focus on network-based approaches for integrative studies.

Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer

Three metabolite patterns have previously shown prospective inverse associations with the risk of aggressive prostate cancer within the European Prospective Investigation into Cancer and Nutrition (EPIC). Here, we investigated dietary and lifestyle correlates of these three prostate cancer-related metabolite patterns, which included: 64 phosphatidylcholines and three hydroxysphingomyelins (Pattern 1), acylcarnitines C18:1 and C18:2, glutamate, ornithine, and taurine (Pattern 2), and 8 lysophosphatidylcholines (Pattern 3). In a two-stage cross-sectional discovery (n = 2524) and validation (n = 518) design containing 3042 men free of cancer in EPIC, we estimated the associations of 24 dietary and lifestyle variables with each pattern and the contributing individual metabolites. Associations statistically significant after both correction for multiple testing (False Discovery Rate = 0.05) in the discovery set and at p < 0.05 in the validation set were considered robust. Intakes of alcohol, total fish products, and its subsets total fish and lean fish were positively associated with Pattern 1. Body mass index (BMI) was positively associated with Pattern 2, which appeared to be driven by a strong positive BMI-glutamate association. Finally, both BMI and fatty fish were inversely associated with Pattern 3. In conclusion, these results indicate associations of fish and its subtypes, alcohol, and BMI with metabolite patterns that are inversely associated with risk of aggressive prostate cancer.

Determinants of blood acylcarnitine concentrations in healthy individuals of the European Prospective Investigation into Cancer and Nutrition

BACKGROUND & AIMS

Circulating levels of acylcarnitines (ACs) have been associated with the risk of various diseases such as cancer and type 2 diabetes. Diet and lifestyle factors have been shown to influence AC concentrations but a better understanding of their biological, lifestyle and metabolic determinants is needed.

METHODS

Circulating ACs were measured in blood by targeted (15 ACs) and untargeted metabolomics (50 ACs) in 7770 and 395 healthy participants of the European Prospective Investigation into Cancer and Nutrition (EPIC), respectively. Associations with biological and lifestyle characteristics, dietary patterns, self-reported intake of individual foods, estimated intake of carnitine and fatty acids, and fatty acids in plasma phospholipid fraction and amino acids in blood were assessed.

RESULTS

Age, sex and fasting status were associated with the largest proportion of AC variability (partial-r up to 0.19, 0.18 and 0.16, respectively). Some AC species of medium or long-chain fatty acid moiety were associated with the corresponding fatty acids in plasma (partial-r = 0.24) or with intake of specific foods such as dairy foods containing the same fatty acid. ACs of short-chain fatty acid moiety (propionylcarnitine and valerylcarnitine) were moderately associated with concentrations of branched-chain amino acids (partial-r = 0.5). Intake of most other foods and of carnitine showed little association with AC levels.

CONCLUSIONS

Our results show that determinants of ACs in blood vary according to their fatty acid moiety, and that their concentrations are related to age, sex, diet, and fasting status. Knowledge on their potential determinants may help interpret associations of ACs with disease risk and inform on potential dietary and lifestyle factors that might be modified for disease prevention.

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.

Serum Amino Acid Profiles Predict the Development of Hepatocellular Carcinoma in Patients with Chronic HBV Infection

Background: The study aimed to find out the alterations in serum amino acid (AA) profiles and to detect their relationship with carcinoma formation. Methods: Targeted metabolomics based on ultraperformance liquid chromatography triple quadrupole mass spectrometry to quantitatively analyze serum AA levels in 136 hepatitis B (CHB) patients and 93 hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients. Results: It was shown that decreased serum levels of leucine, lysine, threonine, tryptophan, valine, serotonin, and taurine were observed in more HCC patients than CHB patients, but the serum phenylalanine level was increased. Serum valine and serotonin were lower in Class C than Class A and Class B in HCC patients. Accompanied with the higher score of Model for End-Stage Liver Disease, serum phenylalanine was increased not only in CHB patients but also in HCC patients. The serum level of phenylalanine increased in the decompensated stage more than in the compensated stage, while serum leucine and serotonin significantly decreased. Serum serotonin still had significant differences between CHB and HCC both in the HBV desoxyribonucleic acid (HBV-DNA) negative group and in the HBV-DNA positive group. Furthermore, it was shown that the tryptophan ratio, branched-chain amino acids (BCAA)/aromatic amino acids ratio, BCAAs/tyrosine ratio, Fischer's ratio, and serotonin-to-tryptophan ratio significantly decreased, while the tyrosine ratio and the kynurenine-to-tryptophan ratio increased in HCC patients more than those in CHB. Conclusions: A distinct metabolite signature of some specific serum amino acids was found between CHB and HCC patients, which may help predict the development of HCC at an early stage.

Metabolic Signatures of Healthy Lifestyle Patterns and Colorectal Cancer Risk in a European Cohort

BACKGROUND & AIMS

Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort.

METHODS

Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1-5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer and Nutrition participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression.

RESULTS

Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29-0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50-0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86-1.00) overall. Signature associations were stronger in male compared with female participants.

CONCLUSIONS

Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer.

Molecular Probes, Chemosensors, and Nanosensors for Optical Detection of Biorelevant Molecules and Ions in Aqueous Media and Biofluids

Synthetic molecular probes, chemosensors, and nanosensors used in combination with innovative assay protocols hold great potential for the development of robust, low-cost, and fast-responding sensors that are applicable in biofluids (urine, blood, and saliva). Particularly, the development of sensors for metabolites, neurotransmitters, drugs, and inorganic ions is highly desirable due to a lack of suitable biosensors. In addition, the monitoring and analysis of metabolic and signaling networks in cells and organisms by optical probes and chemosensors is becoming increasingly important in molecular biology and medicine. Thus, new perspectives for personalized diagnostics, theranostics, and biochemical/medical research will be unlocked when standing limitations of artificial binders and receptors are overcome. In this review, we survey synthetic sensing systems that have promising (future) application potential for the detection of small molecules, cations, and anions in aqueous media and biofluids. Special attention was given to sensing systems that provide a readily measurable optical signal through dynamic covalent chemistry, supramolecular host-guest interactions, or nanoparticles featuring plasmonic effects. This review shall also enable the reader to evaluate the current performance of molecular probes, chemosensors, and nanosensors in terms of sensitivity and selectivity with respect to practical requirement, and thereby inspiring new ideas for the development of further advanced systems.

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.

Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort

BACKGROUND

Metabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2).

METHODS

To identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786).

RESULTS

For the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed.

CONCLUSIONS

These associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cancer. Further research is needed to identify potential non-lifestyle correlates of the metabolites investigated.

Novel Biomarkers of Habitual Alcohol Intake and Associations With Risk of Pancreatic and Liver Cancers and Liver Disease Mortality

BACKGROUND

Alcohol is an established risk factor for several cancers, but modest alcohol-cancer associations may be missed because of measurement error in self-reported assessments. Biomarkers of habitual alcohol intake may provide novel insight into the relationship between alcohol and cancer risk.

METHODS

Untargeted metabolomics was used to identify metabolites correlated with self-reported habitual alcohol intake in a discovery dataset from the European Prospective Investigation into Cancer and Nutrition (EPIC; n = 454). Statistically significant correlations were tested in independent datasets of controls from case-control studies nested within EPIC (n = 280) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC; n = 438) study. Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations of alcohol-associated metabolites and self-reported alcohol intake with risk of pancreatic cancer, hepatocellular carcinoma (HCC), liver cancer, and liver disease mortality in the contributing studies.

RESULTS

Two metabolites displayed a dose-response association with self-reported alcohol intake: 2-hydroxy-3-methylbutyric acid and an unidentified compound. A 1-SD (log2) increase in levels of 2-hydroxy-3-methylbutyric acid was associated with risk of HCC (OR = 2.54, 95% CI = 1.51 to 4.27) and pancreatic cancer (OR = 1.43, 95% CI = 1.03 to 1.99) in EPIC and liver cancer (OR = 2.00, 95% CI = 1.44 to 2.77) and liver disease mortality (OR = 2.16, 95% CI = 1.63 to 2.86) in ATBC. Conversely, a 1-SD (log2) increase in questionnaire-derived alcohol intake was not associated with HCC or pancreatic cancer in EPIC or liver cancer in ATBC but was associated with liver disease mortality (OR = 2.19, 95% CI = 1.60 to 2.98) in ATBC.

CONCLUSIONS

2-hydroxy-3-methylbutyric acid is a candidate biomarker of habitual alcohol intake that may advance the study of alcohol and cancer risk in population-based studies.

Metabolism-Associated Epigenetic and Immunoepigenetic Reprogramming in Liver Cancer

Metabolic reprogramming and epigenetic changes have been characterized as hallmarks of liver cancer. Independently of etiology, oncogenic pathways as well as the availability of different energetic substrates critically influence cellular metabolism, and the resulting perturbations often cause aberrant epigenetic alterations, not only in cancer cells but also in the hepatic tumor microenvironment. Metabolic intermediates serve as crucial substrates for various epigenetic modulations, from post-translational modification of histones to DNA methylation. In turn, epigenetic changes can alter the expression of metabolic genes supporting on the one hand, the increased energetic demand of cancer cells and, on the other hand, influence the activity of tumor-associated immune cell populations. In this review, we will illustrate the most recent findings about metabolic reprogramming in liver cancer. We will focus on the metabolic changes characterizing the tumor microenvironment and on how these alterations impact on epigenetic mechanisms involved in the malignant progression. Furthermore, we will report our current knowledge about the influence of cancer-specific metabolites on epigenetic reprogramming of immune cells and we will highlight how this favors a tumor-permissive immune environment. Finally, we will review the current strategies to target metabolic and epigenetic pathways and their therapeutic potential in liver cancer, alone or in combinatorial approaches.

Urinary metabolomics of HCV patients with severe liver fibrosis before and during the sustained virologic response achieved by direct acting antiviral treatment

Hepatitis C virus (HCV) infection induces a long-term inflammatory response and oxidative-stress in the liver microenvironment, leading to hepatic fibrosis and metabolic alterations. Direct-acting-antiviral-agents (DAAs) induce HCV-clearance, even though liver damage is only partially restored. In this context, understanding the impact of viral-eradication on liver metabolic activities could allow optimizing the metabolic care of the patient. The present prospective longitudinal study aims at characterizing the urinary metabolic profile of HCV-induced severe liver fibrosis and the metabolic changes induced by DAAs and HCV-clearance by nuclear magnetic resonance-based metabolomics. The urinary metabolic profile of 23 HCV males with severe liver fibrosis and 20 age-matched healthy-controls was analyzed by NMR-based-metabolomics before starting DAAs, at the end-of-therapy, after one and three months of follow-up. The urinary metabolic profile of patients with severe liver fibrosis was associated to pseudouridine, hypoxanthine, methylguanidine and dimethylamine, highlighting a profile related to oxidative damage, and to tyrosine and glutamine, related to a decreased breakdown of aromatic aminoacids and ammonia detoxification, respectively. 1-methylnicotinamide, a catabolic intermediate of nicotinamide-adenine-dinucleotide, was significantly increased in HCV-patients and restored after HCV-clearance, probably due to the reduced hepatic inflammation. 3-hydroxy-3-methylbutyrate, an intermediate of leucine-catabolism which was permanently restored after HCV-clearance, suggested an improvement of skeletal muscle protein synthesis. Finally, 3-hydroxyisobutyrate and 2,3-dihydroxy-2-methylbutyrate, intermediates of valine-catabolism, glycine and choline increased temporarily during therapy, resulting as potential biomarkers of DAAs systemic effects.

A New Pipeline for the Normalization and Pooling of Metabolomics Data

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

Prospective analysis of circulating metabolites and endometrial cancer risk

BACKGROUND

Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC).

METHODS

A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed.

RESULTS

After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR1SD: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR1SD: 0.89, 95% CI: 0.80-0.99; OR1SD: 0.89, 95% CI: 0.79-1.00 and OR1SD: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR1SD: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR1SD: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results.

CONCLUSION

These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention.

Associations between dietary amino acid intakes and blood concentration levels

BACKGROUND AND AIMS

Emerging evidence suggests a role of amino acids (AAs) in the development of various diseases including renal failure, liver cirrhosis, diabetes and cancer. However, mechanistic pathways and the effects of dietary AA intakes on circulating levels and disease outcomes are unclear. We aimed to compare protein and AA intakes, with their respective blood concentrations in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

METHODS

Dietary protein and AA intakes were assessed via the EPIC dietary questionnaires (DQ) and 24-h dietary recalls (24-HDR). A subsample of 3768 EPIC participants who were free of cancer had blood AA concentrations measured. To investigate how circulating levels relate to their respective intakes, dietary AA intake was examined in quintiles and ANOVA tests were run. Pearson correlations were examined for continous associations between intakes and blood concentrations.

RESULTS

Dietary AA intakes (assessed with the DQ) and blood AA concentrations were not strongly correlated (-0.15 ≤ r ≤ 0.17) and the direction of the correlations depended on AA class: weak positive correlations were found for most essential AAs (isoleucine, leucine, lysine, methionine, threonine, tryptophan, and valine) and conditionally essential AAs (arginine and tyrosine), while negative associations were found for non-essential AAs. Similar results were found when using the 24-HDR. When conducting ANOVA tests for essential AAs, higher intake quintiles were linked to higher blood AA concentrations, except for histidine and phenylalanine. For non-essential AAs and glycine, an inverse relationship was observed. Conditionally-essential AAs showed mixed results.

CONCLUSIONS

Weak positive correlations and dose responses were found between most essential and conditionally essential AA intakes, and blood concentrations, but not for the non-essential AAs. These results suggest that intake of dietary AA might be related to physiological AA status, particularly for the essential AAs. However, these results should be further evaluated and confirmed in large-scale prospective studies.

The role of metabolomics in hepatocellular carcinoma

Background

Hepatocellular carcinoma is the most common primary liver malignancy, with the highest incidence in the developing world, including Egypt. Hepatocellular carcinoma is usually diagnosed in the terminal stage of the disease because of the low sensitivity of the available screening tests. During the process of carcinogenesis, the cellular metabolism is altered to allow cancer cells to adapt to the hypoxic environment and therefore increase anabolic synthesis and survival and avoid the apoptotic death signals. These changes in metabolic status can be tracked by metabolomics analysis.

Main body

Metabolomics is a comprehensive approach for identifying metabolic signatures towards the screening, prediction, and earlier diagnosis of hepatocellular carcinoma with greater efficiency than the conventional diagnostic biomarker. The identification of metabolic changes associated with hepatocellular carcinoma is essential to the understanding of disease pathophysiology and enables better monitoring of high-risk individuals. However, due to the complexity of the metabolic pathways associated with hepatocellular carcinoma, the details of these perturbations are still not adequately characterized. The current status of biomarkers for hepatocellular carcinoma and their insufficiencies and metabolic pathways linked to hepatocellular carcinogenesis are briefly addressed in this mini-review. The review focused on the significantly changed metabolites and pathways associated with hepatocellular carcinoma such as phospholipids, bile acids, amino acids, reactive oxygen species metabolism, and the metabolic changes related to energy production in a cancer cell. The review briefly discusses the sensitivity of metabolomics in the prediction and prognosis of hepatocellular carcinoma and the effect of coexisting multiple etiologies of the disease.

Conclusions

Metabolomics profiling is a potentially promising tool for better predicting, diagnosis, and prognosis of hepatocellular carcinoma.

Accuracy and uniformity of the nomenclature of biogenic amines and polyamines in metabolomics studies: A preliminary study

Metabolomics is one of the newest areas in biochemistry dedicated to investigating small biomolecules in biofluids, tissues, and cells. Cutting edge instruments used in metabolomics studies make it possible to identify thousands of biomolecules and determine their interactions with biological networks. This tremendous area has increased the significance of accurate chemical nomenclature of compounds. Therefore, the classification of the organic molecules has become one of the most important issues in the field. Biogenic amines are nitrogenous compounds of low molecular weight formed by the decarboxylation of amino acids or by the amination and the transamination of aldehydes and ketones during normal metabolic processes. This letter covers the topic of nomenclature with respect to the current usage of biogenic amines in scientific literature. We use metabolomics as an example of field reporting data on trace levels of molecules that may be miscategorized in primary literature. We suggest that the incorrect classification of molecules will influence science education adversely because resources used for teaching are drawn from primary literature references that may contain errors.

NMR metabolomic profiles associated with long-term risk of prostate cancer

INTRODUCTION

Prostate cancer is a multifactorial disease whose aetiology is still not fully understood. Metabolomics, by measuring several hundred metabolites simultaneously, could enhance knowledge on the metabolic changes involved and the potential impact of external factors.

OBJECTIVES

The aim of the present study was to investigate whether pre-diagnostic plasma metabolomic profiles were associated with the risk of developing a prostate cancer within the following decade.

METHODS

A prospective nested case-control study was set up among the 5141 men participant of the SU.VI.MAX cohort, including 171 prostate cancer cases, diagnosed between 1994 and 2007, and 171 matched controls. Nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples using NOESY1D and CPMG sequences. Multivariable conditional logistic regression models were computed for each individual NMR signal and for metabolomic patterns derived using principal component analysis.

RESULTS

Men with higher fasting plasma levels of valine (odds ratio (OR) = 1.37 [1.07-1.76], p = .01), glutamine (OR = 1.30 [1.00-1.70], p = .047), creatine (OR = 1.37 [1.04-1.80], p = .02), albumin lysyl (OR = 1.48 [1.12-1.95], p = .006 and OR = 1.51 [1.13-2.02], p = .005), tyrosine (OR = 1.40 [1.06-1.85], p = .02), phenylalanine (OR = 1.39 [1.08-1.79], p = .01), histidine (OR = 1.46 [1.12-1.88], p = .004), 3-methylhistidine (OR = 1.37 [1.05-1.80], p = .02) and lower plasma level of urea (OR = .70 [.54-.92], p = .009) had a higher risk of developing a prostate cancer during the 13 years of follow-up.

CONCLUSIONS

This exploratory study highlighted associations between baseline plasma metabolomic profiles and long-term risk of developing prostate cancer. If replicated in independent cohort studies, such signatures may improve the identification of men at risk for prostate cancer well before diagnosis and the understanding of this disease.

FOXC1 promotes HCC proliferation and metastasis by Upregulating DNMT3B to induce DNA Hypermethylation of CTH promoter

BACKGROUND

Forkhead box C1 (FOXC1), as a member of the FOX family, is important for promote HCC invasion and metastasis. FOX family protein lays a pivotal role in metabolism. ROS is involved in tumor progression and is associated with the expression of lots of transcription factors. We next explored the mechanism underlying FOXC1 modulating the metabolism and ROS hemostasis in HCC.

METHODS

We used amino acids arrays to verify which metabolism is involved in FOXC1-induced HCC. The kits were used to detect the ROS levels in HCC cells with over-expression or down-expression of FOXC1. After identified the downstream target genes and candidate pathway which regulated by FOXC1 during HCC progression in vitro and in vivo, we used western blot, immunohistochemistry, bisulfite genomic sequencing, methylation-specific PCR, chromatin immunoprecipitation analysis and luciferase reporter assays to explore the relationship of FOXC1 and downstream genes. Moreover, the correlation between FOXC1 and target genes and the correlation between target genes and the recurrence and overall survival were analyzed in two independent human HCC cohorts.

RESULTS

Here, we reported that FOXC1 could inhibit the cysteine metabolism and increase reactive oxygen species (ROS) levels by regulating cysteine metabolism-related genes, cystathionine γ-lyase (CTH). Overexpression of CTH significantly suppressed FOXC1-induced HCC proliferation, invasion and metastasis, while the reduction in cell proliferation, invasion and metastasis caused by the inhibition of FOXC1 could be reversed by knockdown of CTH. Meanwhile, FOXC1 upregulated de novo DNA methylase 3B (DNMT3B) expression to induce DNA hypermethylation of CTH promoter, which resulted in low expression of CTH in HCC cells. Moreover, low levels of ROS induced by N-acetylcysteine (NAC) which is an antioxidant inhibited the cell proliferation, migration, and invasion abilities mediated by FOXC1 overexpression, whereas high levels of ROS induced by L-Buthionine-sulfoximine (BSO) rescued the suppression results mediated by FOXC1 knockdown. Our study demonstrated that the overexpression of FOXC1 that was induced by the ROS dependent on the extracellular regulated protein kinases 1 and 2 (ERK1/2)- phospho-ETS Transcription Factor 1 (p-ELK1) pathway. In human HCC tissues, FOXC1 expression was positively correlated with oxidative damage marker 8-hydroxy-2'-deoxyguanosine (8-OHdG), p-ELK1 and DNMT3B expression, but negatively correlated with CTH expression. HCC patients with positive co-expression of 8-OHdG/FOXC1 or p-ELK1/FOXC1 or FOXC1/DNMT3B had the worst prognosis, whereas HCC patients who had positive FOXC1 and negative CTH expression exhibited the worst prognosis.

CONCLUSION

In a word, we clarify that the positive feedback loop of ROS-FOXC1-cysteine metabolism-ROS is important for promoting liver cancer proliferation and metastasis, and this pathway may provide a prospective clinical treatment approach for HCC.

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.

Recent Advances of Microbiome-Associated Metabolomics Profiling in Liver Disease: Principles, Mechanisms, and Applications

Advances in high-throughput screening of metabolic stability in liver and gut microbiota are able to identify and quantify small-molecule metabolites (metabolome) in different cellular microenvironments that are closest to their phenotypes. Metagenomics and metabolomics are largely recognized to be the “-omics” disciplines for clinical therapeutic screening. Here, metabolomics activity screening in liver disease (LD) and gut microbiomes has significantly delivered the integration of metabolomics data (i.e., a set of endogenous metabolites) with metabolic pathways in cellular environments that can be tested for biological functions (i.e., phenotypes). A growing literature in LD and gut microbiomes reports the use of metabolites as therapeutic targets or biomarkers. Although growing evidence connects liver fibrosis, cirrhosis, and hepatocellular carcinoma, the genetic and metabolic factors are still mainly unknown. Herein, we reviewed proof-of-concept mechanisms for metabolomics-based LD and gut microbiotas’ role from several studies (nuclear magnetic resonance, gas/lipid chromatography, spectroscopy coupled with mass spectrometry, and capillary electrophoresis). A deeper understanding of these axes is a prerequisite for optimizing therapeutic strategies to improve liver health.

The Adipose Microenvironment Dysregulates the Mammary Myoepithelial Cells and Could Participate to the Progression of Breast Cancer

Breast cancer is the most common cancer among women worldwide. Overweight and obesity are now recognized as established risk factors for this pathology in postmenopausal women. These conditions are also believed to be responsible for higher recurrence and mortality rates. Reciprocal interactions have been described between adipose and cancer cells. An adipose microenvironment favors a greater proliferation of cancer cells, their invasion and even resistance to anti-cancer treatments. In addition, the chronic low-grade inflammation observed in obese individuals is believed to amplify these processes. Among the cell types present in the breast, myoepithelial cells (MECs), located at the interface of the epithelial cells and the stroma, are considered "tumor suppressor" cells. During the transition from ductal carcinoma in situ to invasive cancer, disorganization or even the disappearance of MECs is observed, thereby enhancing the ability of the cancer cells to migrate. As the adipose microenvironment is now considered as a central actor in the progression of breast cancer, our objective was to evaluate if it could be involved in MEC functional modifications, leading to the transition of in situ to invasive carcinoma, particularly in obese patients. Through a co-culture model, we investigated the impact of human adipose stem cells from women of normal weight and obese women, differentiated or not into mature adipocytes, on the functionality of the MECs by measuring changes in viability, apoptosis, gene, and miRNA expressions. We found that adipose cells (precursors and differentiated adipocytes) could decrease the viability of the MECs, regardless of the original BMI. The adipose cells could also disrupt the expression of the genes involved in the maintenance of the extracellular matrix and to amplify the expression of leptin and inflammatory markers. miR-122-5p and miR-132-3p could also be considered as targets for adipose cells. The metabolite analyses revealed specific profiles that may be involved in the growth of neoplastic cells. All of these perturbations could thus be responsible for the loss of tumor suppressor status of MECs and promote the transition from in situ to invasive carcinoma.

Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics

Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.

Serum kynurenine levels are a novel biomarker to predict the prognosis of patients with hepatocellular carcinoma

BACKGROUND

We examined serum kynurenine levels in patients with chronic hepatitis C virus infection, and the relationship between serum kynurenine and prognosis in patients with hepatocellular carcinoma (HCC) and chronic hepatitis C.

METHODS

We retrospectively analyzed 604 patients with HCC diagnosed between January 1999 and December 2015, and 288 patients without HCC who were seen at the National Hospital Organization Nagasaki Medical Center between October 2014 and November 2017. The association between serum kynurenine and prognosis was evaluated using the Cox's proportional hazards regression analysis.

RESULTS

Patients with HCC had significantly higher values of serum kynurenine than patients without HCC (median: 557.1 vs. 464.2 ng/mL, p<0.001). Five-year survival rates of HCC patients with serum kynurenine ≥900 (n = 65), 600-899 (n = 194), and <600 ng/mL (n = 345) were 30.6%, 47.4%, and 61.4%, respectively (p = 0.001, log-rank test). Multivariate analysis identified serum kynurenine as an independent predictor for prognosis of HCC patients. The hazard ratio of serum kynurenine ≥900, and 600-899 compared with serum kynurenine <600 ng/mL were 1.91 (p<0.001) and 1.37 (p = 0.015), respectively.

CONCLUSIONS

A high level of serum kynurenine correlated with poor prognosis of HCC. Serum kynurenine levels may be a novel biomarker to predict the prognosis of patients with HCC. The development of drugs that inhibit kynurenine production is expected to help improve the prognosis of patients with HCC.

Longitudinal change of metabolite profile and its relation to multiple risk factors for the risk of developing hepatitis B-related hepatocellular carcinoma

Despite considerable knowledge of viral pathogenesis, the pathophysiological changes related to the multifactorial, multistep process of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) development remains unclear. Longitudinal metabolomics study can reveal biological process for disease progression. We performed metabolite profiling with longitudinal prediagnostic plasma samples from two nested case-control studies of hepatitis B surface antigen carriers participating in ultrasound screening for HCC, one within a government employee cohort (870 samples from 109 HCC cases and 107 controls) and the other within a hospital-based cohort (266 samples from 63 HCC cases and 114 controls). Of the 34 measured metabolites, tyrosine, isoleucine, and glutamine were consistently associated with HCC. In analyses combining longitudinal data, a high metabolic risk score based on the three amino acids was robustly associated with increased risk of HCC (OR = 3.71, 95% confidence interval: 2.53-5.42), even after adjustment for clinical factors, or when assessed for different times up to ≥8 years before diagnosis. Similar association was observed in an independent, prospective analysis comprising 633 randomly selected individuals of the government employee cohort. More importantly, this metabolite signature was longitudinally influenced by HBV-infection phase and involved in gradual progression to liver fibrosis and cirrhosis. Furthermore, mediation analysis showed that the score mediated substantial proportions of the associations of key viral factors, insulin resistance, and diabetes status with HCC risk. Our results suggest that an amino-acid dysregulation metabotype may play a role in HBV-related HCC development, and may also be linked to common pathways that mediate increased HCC risks.

Diagnosis of papillary thyroid carcinoma by 1H NMR spectroscopy-based metabolomic analysis of whole blood

The incidence rate of thyroid carcinoma, especially papillary thyroid carcinoma (PTC), has increased significantly over time. As a primary pathway for metastasis, the lymphatic system is an important prognostic factor for PTC patients. Although the metabolic changes in PTC patients have been investigated in extensive studies, few studies focused on the whole blood metabolic profiling of PTC patients. In this study, we investigated the ¹H NMR-based metabolic profiles of whole blood samples that were obtained from healthy individuals and PTC patients, with or without lymph node metastasis. The estimation of the predictive potential of metabolites was evaluated using multivariate statistical analyses, which revealed that the whole blood carries information that is sufficient for distinguishing between PTC patients and healthy individuals. However, PTC patients were not well classified as positive or negative according to the lymph nodes. We did not find a metabolite that could discriminate the presence of lymph node metastasis. Further studies with larger sample sizes are needed to elucidate significant metabolites to indicate the presence of lymph node metastasis in patients with PTC.

Prospective Investigation of Serum Metabolites, Coffee Drinking, Liver Cancer Incidence, and Liver Disease Mortality

BACKGROUND

Coffee has been consistently associated with lower risk of liver cancer and chronic liver disease, suggesting that coffee affects mechanisms underlying disease development.

METHODS

We measured serum metabolites using untargeted metabolomics in 1:1 matched nested case-control studies of liver cancer (n = 221 cases) and fatal liver disease (n = 242 cases) in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention cohort (n = 29 133). Associations between baseline coffee drinking and metabolites were identified using linear regression; conditional logistic regression models were used to identify associations with subsequent outcomes.

RESULTS

Overall, 21 metabolites were associated with coffee drinking and also each subsequent endpoint; nine metabolites and trigonelline, a known coffee biomarker, were identified. Tyrosine and two bile acids, glycochenodeoxycholic acid (GCDCA) and glycocholic acid (GCA), were inversely associated with coffee but positively associated with both outcomes; odds ratios (ORs) comparing the 90th to 10th percentile (modeled on a continuous basis) ranged from 3.93 (95% confidence interval [CI] = 2.00 to 7.74) for tyrosine to 4.95 (95% CI = 2.64 to 9.29) for GCA and from 4.00 (95% CI = 2.42 to 6.62) for GCA to 6.77 (95% CI = 3.62 to 12.65) for GCDCA for liver cancer and fatal liver disease, respectively. The remaining six metabolites and trigonelline were positively associated with coffee drinking but inversely associated with both outcomes; odds ratio ranged from 0.16 to 0.37. Associations persisted following diet adjustment and for outcomes occurring greater than 10 years after blood collection.

CONCLUSIONS

A broad range of compounds were associated with coffee drinking, incident liver cancer, and liver disease death over 27 years of follow-up. These associations provide novel insight into chronic liver disease and liver cancer etiology and support a possible hepatoprotective effect of coffee.

Mass spectrometry based proteomics and metabolomics in personalized oncology

Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.

Mitochondrial Dysfunction in the Transition from NASH to HCC

The liver constantly adapts to meet energy requirements of the whole body. Despite its remarkable adaptative capacity, prolonged exposure of liver cells to harmful environmental cues (such as diets rich in fat, sugar, and cholesterol) results in the development of chronic liver diseases (including non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH)) that can progress to hepatocellular carcinoma (HCC). The pathogenesis of these diseases is extremely complex, multifactorial, and poorly understood. Emerging evidence suggests that mitochondrial dysfunction or maladaptation contributes to detrimental effects on hepatocyte bioenergetics, reactive oxygen species (ROS) homeostasis, endoplasmic reticulum (ER) stress, inflammation, and cell death leading to NASH and HCC. The present review highlights the potential contribution of altered mitochondria function to NASH-related HCC and discusses how agents targeting this organelle could provide interesting treatment strategies for these diseases.

Plasma Metabolomic Signatures Associated with Long-term Breast Cancer Risk in the SU.VI.MAX Prospective Cohort

BACKGROUND

Breast cancer is a major cause of death in occidental women. The role of metabolism in breast cancer etiology remains unclear. Metabolomics may help to elucidate novel biological pathways and identify new biomarkers to predict breast cancer long before symptoms appear. The aim of this study was to investigate whether untargeted metabolomic signatures from blood draws of healthy women could contribute to better understand and predict the long-term risk of developing breast cancer.

METHODS

A nested case-control study was conducted within the SU.VI.MAX prospective cohort (13 years of follow-up) to analyze baseline plasma samples of 211 incident breast cancer cases and 211 matched controls by LC/MS. Multivariable conditional logistic regression models were computed.

RESULTS

A total of 3,565 ions were detected and 1,221 were retained for statistical analysis. A total of 73 ions were associated with breast cancer risk (P < 0.01; FDR ≤ 0.2). Notably, we observed that a lower plasma level of O-succinyl-homoserine (OR = 0.70, 95%CI = [0.55-0.89]) and higher plasma levels of valine/norvaline [1.45 (1.15-1.83)], glutamine/isoglutamine [1.33 (1.07-1.66)], 5-aminovaleric acid [1.46 (1.14-1.87)], phenylalanine [1.43 (1.14-1.78)], tryptophan [1.40 (1.10-1.79)], γ-glutamyl-threonine [1.39 (1.09-1.77)], ATBC [1.41 (1.10-1.79)], and pregnene-triol sulfate [1.38 (1.08-1.77)] were associated with an increased risk of developing breast cancer during follow-up.Conclusion: Several prediagnostic plasmatic metabolites were associated with long-term breast cancer risk and suggested a role of microbiota metabolism and environmental exposure.

IMPACT

After confirmation in other independent cohort studies, these results could help to identify healthy women at higher risk of developing breast cancer in the subsequent decade and to propose a better understanding of the complex mechanisms involved in its etiology.