Global and targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers

Esophageal cancer risk is influenced by genetically determined blood metabolites

It remains unclear what causes esophageal cancer (EC), but blood metabolites have been connected to it. Our study performed a Mendelian randomization (MR) analysis to assess the causality from genetically proxied 1400 blood metabolites to EC level. A two-sample MR analysis was employed to evaluate the causal relationship between 1400 blood metabolites and EC. Initially, the EC genome-wide association study (GWAS) data (from Jiang L et al) were examined, leading to the identification of certain metabolites. Subsequently, another set of EC GWAS data from FINNGEN was utilized to validate the findings. Causality was primarily determined through inverse variance weighting, with additional support from the MR-Egger, weighted median, and MR-PRESSO models. Heterogeneity was assessed using the MR Cochran Q test. The MR-Egger intercept and MR-PRESSO global methods were employed to detect multicollinearity. In this study, Bonferroni corrected P value was used for significance threshold. We found 2 metabolites with overlaps, which are lipids. Docosatrienoate (22:3n3) was found to be causally associated with a decreased risk of EC, as evidenced by the EC GWAS data (from Jiang et al) (odds ratio [OR] = 0.620, 95% confidence interval [CI] = 0.390-0.986, P = .044) and the EC GWAS data (from FINNGEN) (OR = 0.77, 95% CI = 0.6-0.99, P = .042), these results were consistent across both data sets. Another overlapping metabolite, glycosyl-N-(2-hydroxyneuramoyl)-sphingosine, was associated with the risk of ES, with EC GWAS data (from Jiang L et al) (OR = 1.536, 95% CI = 1.000-2.360, P = .049), while EC GWAS data (from FINNGEN) (OR = 0.733, 95% CI = 0.574-0.937, P = .013), the 2 data had opposite conclusions. The findings of this study indicate a potential association between lipid metabolites (Docosatrienoate (22:3n3) and glycosyl-N-(2-hydroxynervonoyl)-sphingosine (d18:1/24:1 (2OH))) and the risk of esophageal carcinogenesis.

Identification of genome-wide copy number variation-driven subtypes for the treatment and prognostic prediction of esophageal carcinoma

Background

Esophageal carcinoma (ESCA) is a frequently detected gastrointestinal cancer. Copy number variants (CNVs) have a dramatic impact on the screening, diagnosis and prognostic prediction of cancers. However, the mechanism of action of CNVs on ESCA occurrence and progression remains unclear.

Methods

ESCA samples from The Cancer Genome Atlas (TCGA) were typed by consensus clustering using CNV-associated genes. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to section gene modules closely related to the two clusters, and sub-networks were constructed as hub genes. In addition, seven prognosis-correlated genes were further screened and retained by multivariate Cox regression analysis to develop a prognostic assessment model. The ssGSEA algorithm assessed energy metabolism levels in patients from different clusters and risk groups. Finally, quantitative real-time PCR (qRT-PCR) and live-dead cell staining verified the expression of genes associated with CNV risk scores.

Results

ESCA was classified into two subtypes based on CNV values. Compared with cluster 1, cluster 2 had significantly higher level of immune score and tumor-associated immune cell infiltration as well as a noticeably better overall survival. The three modules most associated with the two clusters were identified by WGCNA, and a prognostic model with a strong prediction performance was constructed with their genes. Glycolysis, lactate metabolism, fatty acid synthesis, glutathione, methionine, and tryptophan metabolic pathway enrichment scores were remarkably higher in patients in cluster 1 and the high-risk group than in cluster 2 and the low-risk group. Knockdown PIK3C2A promoted ESCA cells apoptosis and inhibited cell vibiality.

Conclusion

The current research maybe provides new understanding for the pathogenesis of ESCA based on CNV, providing an effective guidance for its clinical diagnosis and prognostic evaluation.

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.

Construction and validation of serum Metabolic Risk Score for early warning of malignancy in esophagus

Using noninvasive biomarkers to identify high-risk individuals prior to endoscopic examination is crucial for optimization of screening strategies for esophageal squamous cell carcinoma (ESCC). We conducted a nested case-control study based on two community-based screening cohorts to evaluate the warning value of serum metabolites for esophageal malignancy. The serum samples were collected at enrollment when the cases had not been diagnosed. We identified 74 differential metabolites and two prominent perturbed metabolic pathways, and constructed Metabolic Risk Score (MRS) based on 22 selected metabolic predictors. The MRS generated an area under the receiver operating characteristics curve (AUC) of 0.815. The model performed well for the within-1-year interval (AUC: 0.868) and 1-to-5-year interval (AUC: 0.845) from blood draw to diagnosis, but showed limited ability in predicting long-term cases (>5 years). In summary, the MRS could serve as a potential early warning and risk stratification tool for establishing a precision strategy of ESCC screening.

A systematic review of circulating predictive and prognostic biomarkers to aid the personalised use of radiotherapy in the radical treatment of patients with oesophageal cancer

BACKGROUND

The availability of circulating biomarkers that are predictive of treatment response or prognostic of overall outcome could enable the personalised and adaptive use of radiotherapy (RT) in patients with oesophageal adenocarcinoma (OAC) and squamous cell carcinoma (OSCC).

METHODS

A systematic review was carried out following Preferred Reporting Items for Systematic Reviews guidance. Medline, EMBASE, PubMed, Cochrane Library, CINAHL, Scopus and the Web of Science databases were searched for studies published between January 2005-February 2023 relating to circulating biomarkers evaluated in the context of neoadjuvant or definitive RT delivered for OAC/OSCC. Study quality was assessed using predefined criteria.

RESULTS

A total of 3012 studies were screened and 57 subsequently included, across which 61 biomarkers were reported. A majority (43/57,75.4%) of studies were of Asian origin and retrospective (40/57, 70.2%), with most (52/57, 91.2%) biomarkers reported in the context of patients with OSCC. There was marked inter-study heterogeneity in patient populations, treatment characteristics, biomarker measurement and the cut points used to define biomarker positivity. Nevertheless, there is evidence for the prognostic and predictive value of circulating tumour DNA and numerous miRNAs in OAC and OSCC, as well as for the prognostic and predictive value of circulating levels of CYFRA21.1 in OSCC.

CONCLUSIONS

There is consistent evidence for the potential predictive and prognostic value of a small number of biomarkers in OSCC and OAC, though these data are insufficient for translation to current clinical practice. Well-designed prospective studies are now required to validate their role in stratified and personalised RT treatment approaches.

Is Lipid Metabolism of Value in Cancer Research and Treatment? Part I- Lipid Metabolism in Cancer

For either healthy or diseased organisms, lipids are key components for cellular membranes; they play important roles in numerous cellular processes including cell growth, proliferation, differentiation, energy storage and signaling. Exercise and disease development are examples of cellular environment alterations which produce changes in these networks. There are indications that alterations in lipid metabolism contribute to the development and progression of a variety of cancers. Measuring such alterations and understanding the pathways involved is critical to fully understand cellular metabolism. The demands for this information have led to the emergence of lipidomics, which enables the large-scale study of lipids using mass spectrometry (MS) techniques. Mass spectrometry has been widely used in lipidomics and allows us to analyze detailed lipid profiles of cancers. In this article, we discuss emerging strategies for lipidomics by mass spectrometry; targeted, as opposed to global, lipid analysis provides an exciting new alternative method. Additionally, we provide an introduction to lipidomics, lipid categories and their major biological functions, along with lipidomics studies by mass spectrometry in cancer samples. Further, we summarize the importance of lipid metabolism in oncology and tumor microenvironment, some of the challenges for lipodomics, and the potential for targeted approaches for screening pharmaceutical candidates to improve the therapeutic efficacy of treatment in cancer patients.

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.

Combining fecal microbiome and metabolomics reveals diagnostic biomarkers for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most predominant subtypes of esophageal cancer. The characteristics of the gut microbiome and its metabolites from patients with ESCC have not been adequately studied and discussed. In this study, 40 fecal samples (20 from ESCC patients and 20 from healthy controls) were analyzed by 16S rRNA gene sequencing and untargeted metabolomics. The data sets were analyzed individually and synthesized using various bioinformatics methods. Alpha and beta diversity indicated significant differences in microbial diversity and abundance between ESCC and healthy control feces. At the genus level, the abundance of Phascolarctobacterium, Sutterella, and Streptococcus was significantly increased in ESCC. At the genus level, linear discriminant analysis effect size identified two biomarkers: Bacteroides_stercoris and Prevotella_copri. Untargeted metabolomics analysis revealed 307 differential metabolites between ESCC and healthy control feces, with indoles and derivatives, tropane alkaloids, lipids, and lipid-like molecules in higher relative abundance in ESCC feces than in healthy control feces. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that unsaturated fatty acids (FAs), ascorbate and aldarate metabolism, and hypoxia-inducible factor 1 signaling pathway were significantly associated with differential metabolite. Phenylethanolamine and despropionyl p-fluoro fentanyl could be used as reliable biomarkers to differentiate ESCC from healthy control. The correlation analysis showed that Prevotella may be involved in the synthesis of fatty acyl, carboxylic acids and derivatives, benzenes and substituted derivatives, organic oxygenates, and indoles and derivatives as metabolites. Fusicatenibacter and Lachnospira may be involved in the degradation of indoles and derivatives. Alistipes, Agathobacter, and Parabacteroides may be involved in the synthesis of indoles and derivatives with strong contributions. There is an intricate relationship between the gut microbiome and the levels of several metabolites (e.g., fatty acyls, carboxylic acids and derivatives, indoles, and derivatives). Microbial-associated metabolites can be used as diagnostic biomarkers in therapeutic exploration. Further analysis revealed that Prevotella, Alistipes, Agathobacter, and Parabacteroides might promote ESCC by regulating the synthesis of indoles and their derivatives. The results of this study provide favorable evidence for the early diagnosis of ESCC and subsequent individualized treatment and targeted interventions.IMPORTANCEWe describe for the first time the differences in fecal microbiome composition and metabolites between patients with esophageal squamous cell carcinoma (ESCC) and healthy controls by 16S rRNA gene sequencing and untargeted metabolomics. The results of this study provide a favorable basis for the early diagnosis of ESCC and subsequent targeted interventional therapy.

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.

Strategy for characterization and quantification of fatty acids in plasma by parallel d0/d6-dansylhydrazine derivatization combined with UPLC-MS/MS

Fatty acids (FAs) play a vital physiological role in lipid metabolism, which is reported as potential diagnostic biomarker for various diseases. Thus, it is urgent to develop a credible method that can profile FA metabolism with a holistic view. Here, a targeted strategy to screen FAs was developed by parallel labeling with d0/d6-dansylhydrazine (d0/d6-DnsHz) and using ultra-high performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-MS/MS) in data-dependent MS/MS (ddMS2) mode. The simple and mild derivatization procedure within 3 h allowed for a significant improvement in sensitivity. Additionally, the characteristic product ions introduced by the derivatization reagent assist to identify the unknown FA species. A quantitation method was established by multiple reaction monitoring (MRM) and the d6-DnsHz tagged standards for each analyte were used as internal standards to overcome the matrix effects. By applying the method to determine FA levels in plasma collected from the esophageal squamous cell carcinoma (ESCC) patients and healthy controls, 65 FA metabolites were characterized and six FAs were found to be altered by the invasion of tumors. The parallel derivatization strategy provides insights into the identification of unknown FAs and paves a new way for targeted metabolomics. Also, this novel method is a powerful tool for characterization and quantification of FAs in biological samples, which shows a great potential application in clinical diagnosis and investigation of disease mechanisms.

Decanoylcarnitine Inhibits Triple-Negative Breast Cancer Progression via Mmp9 in an Intermittent Fasting Obesity Mouse

Purpose: Treatment of triple-negative breast cancer (TNBC) remains challenging. Intermittent fasting (IF) has emerged as a promising approach to improve metabolic health of various metabolic disorders. Clinical studies indicate IF is essential for TNBC progression. However, the molecular mechanisms underlying metabolic remodeling in regulating IF and TNBC progression are still unclear. Methods: In this study, we utilized a robust mouse model of TNBC and exposed subjects to a high-fat diet (HFD) with IF to explore its impact on the metabolic reprogramming linked to cancer progression. To identify crucial serum metabolites and signaling events, we utilized targeted metabolomics and RNA sequencing (RNA-seq). Furthermore, we conducted immunoblotting, real-time quantitative polymerase chain reaction (RT-qPCR), cell migration assays, lentivirus-mediated Mmp9 overexpression, and Mmp9 inhibitor experiments to elucidate the role of decanoylcarnitine/Mmp9 in TNBC cell migration. Results: Our observations indicate that IF exerts notable inhibitory effects on both the proliferation and cancer metastasis. Utilizing targeted metabolomics and RNA-seq, we initially identified pivotal serum metabolites and signaling events in the progression of TNBC. Among the 349 serum metabolites identified, decanoylcarnitine was picked out to inhibit TNBC cell proliferation and migration. RNA-seq analysis of TNBC cells treated with decanoylcarnitine revealed its suppressive effects on extracellular matrix-related protein components, with a notable reduction observed in Mmp9. Further investigations confirmed that decanoylcarnitine could inhibit Mmp9 expression in TNBC cells, primary tumors, lung, and liver metastasis tissues. Mmp9 overexpression abolished the inhibitory effect of decanoylcarnitine on cell migration. Conclusion: This study pioneers the exploration of IF intervention and the role of decanoylcarnitine/Mmp9 in the progression of TNBC in obese mice, enhancing our comprehension of the potential roles of various dietary patterns in the process of cancer treatment.

Lipid metabolism analysis in esophageal cancer and associated drug discovery

Esophageal cancer is an upper gastrointestinal malignancy with a bleak prognosis. It is still being explored in depth due to its complex molecular mechanisms of occurrence and development. Lipids play a crucial role in cells by participating in energy supply, biofilm formation, and signal transduction processes, and lipid metabolic reprogramming also constitutes a significant characteristic of malignant tumors. More and more studies have found esophageal cancer has obvious lipid metabolism abnormalities throughout its beginning, progress, and treatment resistance. The inhibition of tumor growth and the enhancement of antitumor therapy efficacy can be achieved through the regulation of lipid metabolism. Therefore, we reviewed and analyzed the research results and latest findings for lipid metabolism and associated analysis techniques in esophageal cancer, and comprehensively proved the value of lipid metabolic reprogramming in the evolution and treatment resistance of esophageal cancer, as well as its significance in exploring potential therapeutic targets and biomarkers.

Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer

Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric cancer forms the cornerstone of precision medicine. Several studies have been conducted to investigate early biomarkers of gastric cancer using genomics, transcriptomics, proteomics, and metabolomics, respectively. However, endogenous substances associated with various omics are concurrently altered during gastric cancer development. Furthermore, environmental exposures and family history can also induce modifications in endogenous substances. Therefore, in this study, we primarily investigated alterations in DNA mutation, DNA methylation, mRNA, lncRNA, miRNA, circRNA, and protein, as well as glucose, amino acid, nucleotide, and lipid metabolism levels in the context of GC development, employing genomics, transcriptomics, proteomics, and metabolomics. Additionally, we elucidate the impact of exposure factors, including HP, EBV, nitrosamines, smoking, alcohol consumption, and family history, on diagnostic biomarkers of gastric cancer. Lastly, we provide a summary of the application of machine learning in integrating multi-omics data. Thus, this review aims to elucidate: i) the biomarkers of gastric cancer related to genomics, transcriptomics, proteomics, and metabolomics; ii) the influence of environmental exposure and family history on multiomics data; iii) the integrated analysis of multi-omics data using machine learning techniques.

DT-109 ameliorates nonalcoholic steatohepatitis in nonhuman primates

Nonalcoholic steatohepatitis (NASH) prevalence is rising with no pharmacotherapy approved. A major hurdle in NASH drug development is the poor translatability of preclinical studies to safe/effective clinical outcomes, and recent failures highlight a need to identify new targetable pathways. Dysregulated glycine metabolism has emerged as a causative factor and therapeutic target in NASH. Here, we report that the tripeptide DT-109 (Gly-Gly-Leu) dose-dependently attenuates steatohepatitis and fibrosis in mice. To enhance the probability of successful translation, we developed a nonhuman primate model that histologically and transcriptionally mimics human NASH. Applying a multiomics approach combining transcriptomics, proteomics, metabolomics, and metagenomics, we found that DT-109 reverses hepatic steatosis and prevents fibrosis progression in nonhuman primates, not only by stimulating fatty acid degradation and glutathione formation, as found in mice, but also by modulating microbial bile acid metabolism. Our studies describe a highly translatable NASH model and highlight the need for clinical evaluation of DT-109.

Untargeted, High-Resolution Metabolomics in Pediatric Eosinophilic Esophagitis

BACKGROUND/OBJECTIVES

Eosinophilic esophagitis (EoE) is an inflammatory disease of unclear etiology. The aim of this study was to use untargeted plasma metabolomics to identify metabolic pathway alterations associated with EoE to better understand the pathophysiology.

METHODS

This prospective, case-control study included 72 children, aged 1-17 years, undergoing clinically indicated upper endoscopy (14 diagnosed with EoE and 58 controls). Fasting plasma samples were analyzed for metabolomics by high-resolution dual-chromatography mass spectrometry. Analysis was performed on sex-matched groups at a 2:1 ratio. Significant differences among the plasma metabolite features between children with and without EoE were determined using multivariate regression analysis and were annotated with a network-based algorithm. Subsequent pathway enrichment analysis was performed.

RESULTS

Patients with EoE had a higher proportion of atopic disease (85.7% vs 50%, P = 0.019) and any allergies (100% vs 57.1%, P = 0.0005). Analysis of the dual chromatography features resulted in a total of 918 metabolites that differentiated EoE and controls. Glycerophospholipid metabolism was significantly enriched with the greatest number of differentiating metabolites and overall pathway enrichment ( P < 0.01). Multiple amino and fatty acid pathways including linoleic acid were also enriched, as well as pyridoxine metabolism ( P < 0.01).

CONCLUSIONS

In this pilot study, we found differences in metabolites involved in glycerophospholipid and inflammation pathways in pediatric patients with EoE using untargeted metabolomics, as well as overlap with amino acid metabolome alterations found in atopic disease.

Creation of a Plant Metabolite Spectral Library for Untargeted and Targeted Metabolomics

Large-scale high throughput metabolomic technologies are indispensable components of systems biology in terms of discovering and defining the metabolite parts of the system. However, the lack of a plant metabolite spectral library limits the metabolite identification of plant metabolomic studies. Here, we have created a plant metabolite spectral library using 544 authentic standards, which increased the efficiency of identification for untargeted metabolomic studies. The process of creating the spectral library was described, and the mzVault library was deposited in the public repository for free download. Furthermore, based on the spectral library, we describe a process of creating a pseudo-targeted method, which was applied to a proof-of-concept study of Arabidopsis leaf extracts. As authentic standards become available, more metabolite spectra can be easily incorporated into the spectral library to improve the mzVault package.

Targeting Strategies for Aberrant Lipid Metabolism Reprogramming and the Immune Microenvironment in Esophageal Cancer: A Review

Esophageal cancer is of high importance to occurrence, development, and treatment resistance. As evidenced by recent studies, pathways (e.g., Wnt/β-catenin, AMPK, and Hippo) are critical to the proliferation, differentiation, and self-renewal of esophageal cancer. In addition, the above pathways play a certain role in regulating esophageal cancer and act as potential therapeutic targets. Over the past few years, the function of lipid metabolism in controlling tumor cells and immune cells has aroused extensive attention. It has been reported that there are intricate interactions between lipid metabolism reprogramming between immune and esophageal cancer cells, whereas molecular mechanisms should be studied in depth. Immune cells have been commonly recognized as a vital player in the esophageal cancer microenvironment, having complex crosstalk with cancer cells. It is increasingly evidenced that the function of immune cells in the tumor microenvironment (TME) is significantly correlated with abnormal lipid metabolism. In this review, the latest findings in lipid metabolism reprogramming in TME are summarized, and the above findings are linked to esophageal cancer progression. Aberrant lipid metabolism and associated signaling pathways are likely to serve as a novel strategy to treat esophageal cancer through lipid metabolism reprogramming.

Serum phosphopeptide profiling for colorectal cancer diagnosis using liquid chromatography-mass spectrometry

RATIONALE

The identification and evaluation of novel biomarkers are essential to clinical diagnosis and prognosis of colorectal cancer (CRC). Serum phosphopeptides have been recognized as a potential signature pool for cancers; therefore, we aim to profile the expression of serum phosphopeptides and to evaluate their feasibility in CRC diagnosis.

METHODS

We conducted the characterization and absolute quantification of endogenous phosphopeptides in sera using liquid chromatography-mass spectrometry analysis in combination with enrichment of phosphopeptides by ZrAs-Fe₃ O₄ @SiO₂ nanoparticles and use of deuterium-labeled standards. Differentially expressed analysis of four phosphopeptides was performed, generating a two-phosphopeptide-based biomarker, L_F3-4 , by logistic regression analysis, where L_F3-4 is equal to (5.85 - 5.13 × [F3] - 3.57 × [F4]), and [F3] and [F4] are the concentration of phosphopeptides DpSGEGDFLAEGGGVR and ADpSGEGDFLAEGGGVR in sera, respectively.

RESULTS

The L_F3-4 values showed significant difference in CRC cases compared with controls, and yielded a specificity of 100%, leading to correct classification of 56 (93%) out of 60 CRC patients, including 12 (92.3%) of 13 CRC cases in stage I. Double-blind validation showed that 97.5% of CRC cases were discriminated accurately.

CONCLUSIONS

The L_F3-4 value was firstly verified to be a potential biomarker for CRC diagnosis, and may expand our view in underlying mechanisms for CRC.

New Metabolic Alterations and A Predictive Marker Pipecolic Acid in Sera for Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is a major histological subtype of esophageal cancer with a poor prognosis. Although several serum metabolomic investigations have been reported, ESCC tumor-associated metabolic alterations and predictive biomarkers in sera have not been defined. Here, we enrolled 34 treatment-naive patients with ESCC and collected their pre- and post-esophagectomy sera together with the sera from 34 healthy volunteers for a metabolomic survey. Our comprehensive analysis identified ESCC tumor-associated metabolic alterations as represented by a panel of 12 serum metabolites. Notably, postoperative abrosia and parenteral nutrition substantially perturbed the serum metabolome. Furthermore, we performed an examination using sera from carcinogen-induced mice at the dysplasia and ESCC stages and identified three ESCC tumor-associated metabolites conserved between mice and humans. Notably, among these metabolites, the level of pipecolic acid was observed to be progressively increased in mouse sera from dysplasia to cancerization, and it could be used to accurately discriminate between mice at the dysplasia stage and healthy control mice. Furthermore, this metabolite is essential for ESCC cells to restrain oxidative stress-induced DNA damage and cell proliferation arrest. Together, this study revealed a panel of 12 ESCC tumor-associated serum metabolites with potential for monitoring therapeutic efficacy and disease relapse, presented evidence for refining parenteral nutrition composition, and highlighted serum pipecolic acid as an attractive biomarker for predicting ESCC tumorigenesis.

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.

Precise Metabolomics Reveals a Diversity of Aging-Associated Metabolic Features

Mass spectrometry-based metabolomics has emerged as a powerful technique for biomedical research, although technical issues with its analytical precision and structural characterization remain. Herein, a robust non-targeted strategy for accurate quantitation and precise profiling of metabolomes is developed and applied to investigate plasma metabolic features associated with human aging. A comprehensive set of isotope-labeled standards (ISs) covering major metabolic pathways is incorporated to quantify polar metabolites. Matching rules to select ISs for calibration follow a primary criterion of minimal coefficients of variations (COVs). If minimal COVs between specific ISs for a particular metabolite fall within 5% window, a further selection of ISs is conducted based on structural similarities and proximity in retention time. The introduction and refined selection of appropriate ISs for quantitation reduces the COVs of 480 identified metabolites in quality control samples from 14.3% to 9.8% and facilitates identification of additional metabolite. Finally, the precise metabolomics approach reveals perturbations in a diverse array of metabolic pathways across aging that principally implicate steroid metabolism, amino acid metabolism, lipid metabolism, and purine metabolism, which allows the authors to draw correlates to the pathology of various age-related diseases. These findings provide clues for the prevention and treatment of these age-related diseases.

Metabolomics of Esophageal Squamous Cell Carcinoma Tissues: Potential Biomarkers for Diagnosis and Promising Targets for Therapy

Background

The incidence of esophageal squamous cell carcinoma in China ranks first in the world. The early diagnosis technology is underdeveloped, and the prognosis is poor, which seriously threatens the quality of life of the Chinese people. Epidemiological findings are related to factors such as diet, living habits, and age. The specific mechanism is not clear yet. Metabolomics is a kind of omics that simultaneously and quantitatively analyzes the comprehensive profile of metabolites in living systems. It has unique advantages in the study of the diagnosis and pathogenesis of tumor-related diseases, especially in the search for biomarkers. Therefore, it is desirable to perform metabolic profiling analysis of cancer tissues through metabolomics to find potential biomarkers for the diagnosis and treatment of esophageal squamous cell carcinoma.

Methods

HPLC-TOF-MS/MS technology and Illumina Hiseq Xten Sequencing was used for the analysis of 210 pairs of matched esophageal squamous cell carcinoma tissues and normal tissues in Zhenjiang City, Jiangsu Province, a high-incidence area of esophageal cancer in China. Bioinformatics analysis was also performed.

Results

Through metabolomic and transcriptomic analysis, this study found that a total of 269 differential metabolites were obtained in esophageal squamous cell carcinoma and normal tissues, and 48 differential metabolic pathways were obtained through KEGG enrichment analysis. After further screening and identification, 12 metabolites with potential biomarkers to differentiate esophageal squamous cell carcinoma from normal tissues were obtained.

Conclusions

From the metabolomic data, 4 unknown compounds were found to be abnormally expressed in esophageal squamous cell carcinoma for the first time, such as 9,10-epoxy-12,15-octadecadienoate; 3 metabolites were found in multiple abnormal expression in another tumor, but upregulation or downregulation was found for the first time in esophageal cancer, such as oleoyl glycine; at the same time, it was further confirmed that five metabolites were abnormally expressed in esophageal squamous cell carcinoma, which was similar to the results of other studies, such as PE.

Lipid Alterations in Early-Stage High-Grade Serous Ovarian Cancer

Epithelial ovarian cancer (OC) ranks first in the number of deaths among diseases of the female reproductive organs. Identification of OC at early stages is highly beneficial for the treatment but is highly challenging due to the asymptomatic or low-symptom disease development. In this study, lipid extracts of venous blood samples from 41 female volunteers, including 28 therapy-naive patients with histologically verified high-grade serous ovarian cancer at different stages (5 patients with I-II stages; 23 patients with III-IV stages) and 13 apparently healthy women of reproductive age, were profiled by high-performance liquid chromatography mass spectrometry (HPLC-MS). Based on MS signals of 128 differential lipid species with statistically significant level variation between the OC patients and control group, an OPLS-DA model was developed for the recognition of OC with 100% sensitivity and specificity R 2 = 0.87 and Q2 = 0.80. The second OPLS-DA model was developed for the differentiation between I-II OC stages and control group with R 2 = 0.97 and Q2 = 0.86 based on the signal levels of 108 differential lipid species. The third OPLS-DA model was developed for the differentiation between I-II OC stages and III-IV stages based on the signal levels of 99 differential lipid species. Various lipid classes (diglycerides, triglycerides, phosphatidylchlorines, ethanolamines, sphingomyelins, ceramides, phosphatidylcholines and phosphoinositols) in blood plasma samples display distinctly characteristic profiles in I-II OC, which indicates the possibility of their use as marker oncolipids in diagnostic molecular panels of early OC stages. Our results suggest that lipid profiling by HPLC-MS can improve identification of early-stage OC and thus increase the efficiency of treatment.

Application of liquid biopsy as multi-functional biomarkers in head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) is a molecularly heterogeneous disease, with a 5-year survival rate that still hovers at ~60% despite recent advancements. The advanced stage upon diagnosis, limited success with effective targeted therapy and lack of reliable biomarkers are among the key factors underlying the marginally improved survival rates over the decades. Prevention, early detection and biomarker-driven treatment adaptation are crucial for timely interventions and improved clinical outcomes. Liquid biopsy, analysis of tumour-specific biomarkers circulating in bodily fluids, is a rapidly evolving field that may play a striking role in optimising patient care. In recent years, significant progress has been made towards advancing liquid biopsies for non-invasive early cancer detection, prognosis, treatment adaptation, monitoring of residual disease and surveillance of recurrence. While these emerging technologies have immense potential to improve patient survival, numerous methodological and biological limitations must be overcome before their implementation into clinical practice. This review outlines the current state of knowledge on various types of liquid biopsies in HNSCC, and their potential applications for diagnosis, prognosis, grading treatment response and post-treatment surveillance. It also discusses challenges associated with the clinical applicability of liquid biopsies and prospects of the optimised approaches in the management of HNSCC.

Serum Metabolomic Profiling Reveals Biomarkers for Early Detection and Prognosis of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common aggressive malignancies worldwide, particularly in northern China. The absence of specific early symptoms and biomarkers leads to late-stage diagnosis, while early diagnosis and risk stratification are crucial for improving overall prognosis. We performed UPLC-MS/MS on 450 ESCC patients and 588 controls consisting of a discovery group and two validation groups to identify biomarkers for early detection and prognosis. Bioinformatics and clinical statistical methods were used for profiling metabolites and evaluating potential biomarkers. A total of 105 differential metabolites were identified as reliable biomarker candidates for ESCC with the same tendency in three cohorts, mainly including amino acids and fatty acyls. A predictive model of 15 metabolites [all-trans-13,14-dihydroretinol, (±)-myristylcarnitine, (2S,3S)-3-methylphenylalanine, 3-(pyrazol-1-yl)-L-alanine, carnitine C10:1, carnitine C10:1 isomer1, carnitine C14-OH, carnitine C16:2-OH, carnitine C9:1, formononetin, hyodeoxycholic acid, indole-3-carboxylic acid, PysoPE 20:3, PysoPE 20:3(2n isomer1), and resolvin E1] was developed by logistic regression after LASSO and random forest analysis. This model held high predictive accuracies on distinguishing ESCC from controls in the discovery and validation groups (accuracies > 89%). In addition, the levels of four downregulated metabolites [hyodeoxycholic acid, (2S,3S)-3-methylphenylalanine, carnitine C9:1, and indole-3-carboxylic acid] were significantly higher in early cancer than advanced cancer. Furthermore, three independent prognostic markers were identified by multivariate Cox regression analyses with and without clinical indicators: a high level of MG(20:4)isomer and low levels of 9,12-octadecadienoic acid and L-isoleucine correlated with an unfavorable prognosis; the risk score based on these three metabolites was able to stratify patients into low or high risk. Moreover, pathway analysis indicated that retinol metabolism and linoleic acid metabolism were prominent perturbed pathways in ESCC. In conclusion, metabolic profiling revealed that perturbed amino acids and lipid metabolism were crucial metabolic signatures of ESCC. Both panels of diagnostic and prognostic markers showed excellent predictive performances. Targeting retinol and linoleic acid metabolism pathways may be new promising mechanism-based therapeutic approaches. Thus, this study would provide novel insights for the early detection and risk stratification for the clinical management of ESCC and potentially improve the outcomes of ESCC.

Metabolomics based plasma biomarkers for diagnosis of oral squamous cell carcinoma and oral erosive lichen planus

Backgrounds: To identify diagnostic biomarkers for differentiating oral squamous cell carcinoma (OSCC) from oral erosive lichen planus (OELP) and investigate potential biomarkers associated with malignant transformation. Methods: In this study, 72 patients with OSCC, 75 patients with OELP subjects were recruited. Their plasma samples were analyzed by ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry, (UHPLC/Q-Orbitrap HRMS). Principal component analysis, orthogonal partial least square discrimination analysis, t-test analysis and false discovery rate were used to identify different metabolites in patients with OSCC and OELP. The metabolic pathway analysis was performed by MetaboAnalyst. To further screen and identify the biomarkers of OSCC and establish a diagnostic panel, binary logistic regression analysis and receiver operating characteristic analysis were used. The data were then combined with blood samples from healthy individuals for mass spectrometry analysis to obtain biomarkers related to malignant transformation. Results: A total of 20 kinds of endogenous metabolites were identified from plasma samples of OSCC patients and OELP patients. Metabolic pathway analysis showed that the biomarkers associated with OSCC were closely related to cholic acid metabolism and amino acid metabolism. Finally, a diagnostic panel composed of decanoylcarnitine, cysteine and cholic acid was established. This diagnostic panel had good diagnostic efficiency with the AUC=0.998. Other metabolites including uridine, taurine, glutamate, citric acid and LysoPC(18:1) were identified to be general biomarkers for malignant transformation of OELP. Conclusion: Biomarkers based on plasma metabolomics are of great significance for the prediction of malignant transformation of OELP and early diagnosis of OSCC.

Spatially Resolved Metabolomics Based on Air-Flow-Assisted Desorption Electrospray Ionization-Mass Spectrometry Imaging Reveals Region-Specific Metabolic Alterations in Diabetic Encephalopathy

Spatially resolved metabolic profiling of brain is vital for elucidating tissue-specific molecular histology and pathology underlying diabetic encephalopathy (DE). In this study, a spatially resolved metabolomic method based on air-flow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) was developed for investigating the region-specific metabolic disturbances in the brain of DE model rats induced by a high-fat diet in combination with streptozotocin administration. A total of 19 discriminating metabolites associated with glycolysis and the pentose phosphate pathway (PPP); the glutamate/gamma aminobutyric acid-glutamine cycle and tricarboxylic acid cycle; nucleotide metabolism; lipid metabolism; carnitine homeostasis; and taurine, ascorbic acid, histidine, and choline metabolism were identified and located in the brains of the diabetic rats simultaneously for the first time. The results indicated that increased glycolytic and PPP activity; dysfunction of mitochondrial metabolism; dysregulation of adenosinergic, glutamatergic, dopaminergic, cholinergic, and histaminergic systems; disorder of osmotic regulation and antioxidant system; and disorder of lipid metabolism occur in a region-specific fashion in the brains of DE rats. Thus, this study provides valuable information regarding the molecular pathological signature of DE. These findings also underline the high potential of AFADESI-MSI for applications in various central nervous system diseases.

HMGB1 knockdown increases the radiosensitivity of esophageal squamous cell carcinoma by regulating the expression of molecules involved in DNA repair

Radiotherapy is an effective therapeutic strategy in esophageal squamous cell carcinoma (ESCC). However, acquired radioresistance of cancer cells leads to radiotherapy failure. The present study aimed to investigate the mechanisms of the effect of high mobility group box 1 (HMGB1) on the radiation sensitivity of ESCC. Small interfering RNA (si) transfection was used to generate three groups of TE-1 cells (TE-1, negative control and TE-1+siHMGB1), and the protein expression levels of HMGB1 in TE-1 cells were detected by western blotting. These groups of TE-1 cells were irradiated with different doses (0, 2, 4, 6 and 8 Gy) of X-rays after transfection. Subsequently, the viability of TE-1 cells was detected using an MTT assay, and the survival fraction of TE-1 cells was observed using a colony formation assay. The apoptotic rate, reactive oxygen species (ROS) content and levels of phosphorylated (p)-histone H2AX at S139 (p-γH2AX) of the cells were detected by flow cytometry. The alterations in mRNA expression levels of nicotinamide adenine nucleotide phosphate oxidase (NOX)1 and NOX5 were detected by reverse transcription-quantitative PCR, while the changes in protein levels of caspase-3, poly(ADP-ribose) polymerase, p-p38, p-ERK1/2 and p-JNK were detected by western blotting. The results revealed that HMGB1 knockdown significantly decreased cell viability, and the apoptosis rate of TE-1 cells transfected with siHMGB1 combined with radiation treatment was increased compared with that in cells with either siHMGB1 transfection or radiation treatment alone. HMGB1 knockdown increased nicotinamide adenine nucleotide phosphate oxidase-mediated ROS production and induced DNA damage via the MAPK signaling pathway, which may promote apoptosis and radiosensitivity after radiation in TE-1 cells. In conclusion, targeting HMGB1 may represent a promising strategy to increase the efficacy of radiation therapy for ESCC.

Liquid Biopsies in Head and Neck Cancer: Current State and Future Challenges

Head and neck cancers are the seventh most frequent malignancy worldwide, consisting of a heterogeneous group of cancers that develop in the oral cavity, pharynx, and larynx, with head and neck squamous cell carcinoma (HNSCC) being the most common pathology. Due to limitations with screening and physical examination, HNSCC often presents in advanced disease states and is thus associated with poor survival. In this setting, liquid biopsies, or obtaining patient bodily fluid samples for cancer diagnosis and prognosis, may play a dramatic role in optimizing care for HNSCC patients. In recent years, there have been dramatic advancements in investigations focused on optimizing and implementing liquid biopsies in general, and specifically for HNSCC patients. Moving forward, there remain significant challenges in liquid biopsy technological development, as well as opportunities for the development of HNSCC liquid biopsy clinical trials and treatment paradigms. In this review, we discuss the current state of liquid biopsy technologies via circulating tumor cells, circulating tumor DNA and exosomes, approaches in head and neck cancer, challenges to optimization and application of liquid biopsies for clinical study, and future prospects for this field of research as it applies to head and neck cancer.

Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma

BACKGROUND: Previous metabolomics studies have found differences in metabolic characteristics between the healthy and ESCC patients. However, few of these studies concerned the whole process of the progression of ESCC. This study aims to explore serum metabolites associated with the progression of ESCC.

METHODS: Serum samples from 653 participants (305 normal, 77 esophagitis, 228 LGD, and 43 HGD/ESCC) were examined by ultra-high performance liquid chromatography quadruple time-of-flight mass spectrometry (UHPLC-QTOF/MS). Principal component analysis (PCA) was first applied to obtain an overview of the clustering trend for the multidimensional data. Fuzzy c-means (FCM) clustering was then used to screen metabolites with a changing tendency in the progression of ESCC. Univariate ordinal logistic regression analysis and multiple ordinal logistic regression analysis were applied to evaluate the association of metabolites with the risk of ESCC progression, and adjusted for age, gender, BMI, tobacco smoking, and alcohol drinking status.

RESULTS: After FCM clustering analysis, a total of 38 metabolites exhibiting changing tendency among normal, esophagitis, LGD, and HGD/ESCC patients. Final results showed 15 metabolites associated with the progression of ESCC. Ten metabolites (dopamine, L-histidine, 5-hydroxyindoleacetate, L-tryptophan, 2'-O-methylcytidine, PC (14:0/0:0), PC (O-16:1/0:0), PE (18:0/0:0), PC (16:1/0:0), PC (18:2/0:0)) were associated with decreased risk of developing ESCC. Five metabolites (hypoxanthine, inosine, carnitine (14:1), glycochenodeoxycholate, PC (P-18:0/18:3)) were associated with increased risk of developing ESCC.

CONCLUSIONS: These results demonstrated that serum metabolites are associated with the progression of ESCC. These metabolites are capable of potential biomarkers for the risk prediction and early detection of ESCC.

Efficacy of Analytical Technologies in Metabolomics Studies of the Gastrointestinal Cancers

According to the reports of the World Health Organization and the International Agency for Research on Cancer, cancer is the second leading cause of human death worldwide. However, early-stage detection of cancers can efficiently enhance the chance of therapy and saving lives. Metabolomics strategies apply a variety of approaches to discover new potential diagnoses, prognoses, and/or therapeutic biomarkers of various diseases. Metabolomics aims to identify and measure different low-molecular-weight biomolecules in physiological environments. In these studies, special metabolites are extracted from biological samples and identified using analytical techniques. Afterward, using data processing programs discovering significantly associated biomarkers is pursued. In the present review, we aimed to discuss recently reported analytical approaches on the metabolomics studies of gastrointestinal cancers including gastric, colorectal, and esophageal cancers. The gas- and liquid-chromatography with different detectors have been shown that are the main analytical techniques and for metabolites quantification, nuclear magnetic resonance has been utilized as a master method.

The Distinctive Serum Metabolomes of Gastric, Esophageal and Colorectal Cancers

Simple Summary

Cancer of the stomach, esophagus and colon are often fatal. Ways are being sought to establish patient-friendly screening tests that would allow these cancers to be detected earlier. Examination of the metabolomics results of cancer patient’s serum for certain metabolites unique for a particular cancer was the goal of this review. From studies conducted within the past five years several metabolites were found to be changed in cancer compared to non-cancer patients for each of the three cancers. Further confirmation of what was discovered in this review coupled with establishment of standard protocols may allow for cancer screening on patient blood samples to become routine clinical tests.

Abstract

Three of the most lethal cancers in the world are the gastrointestinal cancers—gastric (GC), esophageal (EC) and colorectal cancer (CRC)—which are ranked as third, sixth and fourth in cancer deaths globally. Early detection of these cancers is difficult, and a quest is currently on to find non-invasive screening tests to detect these cancers. The reprogramming of energy metabolism is a hallmark of cancer, notably, an increased dependence on aerobic glycolysis which is often referred to as the Warburg effect. This metabolic change results in a unique metabolic profile that distinguishes cancer cells from normal cells. Serum metabolomics analyses allow one to measure the end products of both host and microbiota metabolism present at the time of sample collection. It is a non-invasive procedure requiring only blood collection which encourages greater patient compliance to have more frequent screenings for cancer. In the following review we will examine some of the most current serum metabolomics studies in order to compare their results and test a hypothesis that different tumors, notably, from EC, GC and CRC, have distinguishing serum metabolite profiles.

Proteogenomic examination of esophageal squamous cell carcinoma (ESCC): new lines of inquiry

Introduction: Esophageal squamous cell carcinoma (ESCC), a histopathologic subtype of esophageal cancer is a major cause of cancer-related morbidity and mortality worldwide. This is primarily because patients are diagnosed at an advanced stage by the time symptoms appear. The genomics and mass spectrometry-based proteomics continue to provide important leads toward biomarker discovery for ESCC. However, such leads are yet to be translated into clinical utilities. Areas covered: We gathered information pertaining to proteomics and proteogenomics efforts in ESCC from the literature search until 2020. An overview of omics approaches to discover the candidate biomarkers for ESCC were highlighted. We present a summary of recent investigations of alterations in the level of gene and protein expression observed in biological samples including body fluids, tissue/biopsy and in vitro-based models. Expert opinion: A large number of protein-based biomarkers and therapeutic targets are being used in cancer therapy. Several candidates are being developed as diagnostics and prognostics for the management of cancers. High-resolution proteomic and proteogenomic approaches offer an efficient way to identify additional candidate biomarkers for diagnosis, monitoring of disease progression, prediction of response to chemo and radiotherapy. Some of these biomarkers can also be developed as therapeutic targets.

Serum Metabolomics for Biomarker Screening of Esophageal Squamous Cell Carcinoma and Esophageal Squamous Dysplasia Using Gas Chromatography-Mass Spectrometry

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies with poor diagnosis. Esophageal squamous dysplasia (ESD) is considered as an immediate precancerous lesion of ESCC. Lack of biomarkers for discriminating ESCC and ESD from healthy subjects limits the early diagnosis and treatment of ESCC. Therefore, a serum metabolomic strategy was conducted to identify and validate potential metabolic markers for the screening of ESCC and ESD subjects.

METHODS

A total of 74 patients with ESCC, 72 patients with ESD, and 75 normal control (NC) subjects were enrolled in this study. Gas chromatography-mass spectrometry was used to acquire serum metabolic profiles. Pathway analysis was conducted to uncover the fluctuated metabolic pathways during ESCC. Multivariate analyses were used to screen and validate the biomarkers.

RESULTS

ESCC, ESD, and NC subjects revealed progressively altered metabolic profiles, in which amino acids globally increased, while fatty acids decreased in ESCCs compared with the control groups. Pathway analysis demonstrated the activated biosynthesis of amino acids and inhibited desaturation of saturated fatty acids. The panel constructed with propanoic acid, linoleic acid, glycerol-3-phosphate, and l-glutamine showed the area under the curve (AUC), sensitivity, and specificity of 0.817, 0.75, and 0.74, respectively, in the discrimination of ESCC/ESD patients from NC subjects. The panel constructed by propanoic acid, l-leucine, and hydroxyproline revealed the AUC, sensitivity, and specificity of 0.819, 0.76, and 0.72, respectively, in the discrimination of ESD from NC subjects. The combination of hypoxanthine, 2-ketoisocaproic acid, l-glutamate, and l-aspartate showed the AUC, sensitivity, and specificity of 0.818, 0.83, and 0.74, respectively, in the discrimination of ESCC patients from ESD subjects.

CONCLUSIONS

Our study revealed the systematic landscape for metabolic alterations in sera of ESD and ESCC patients. The defined metabolite markers showed reasonable performance in the discrimination of ESCC and ESD patients, and may provide helpful reference for clinicians and biologists.

Study of the Relationship Between Serum Amino Acid Metabolism and Lymph Node Metastasis in Patients with Colorectal Cancer

Purpose

Lymph node metastasis is one of the important prognostic factors of colorectal cancer, and an important index of individualized treatment. The purpose of this study is to use metabonomics to identify potential molecular markers of lymph node metastasis in colorectal cancer (CRC).

Patients and Methods

Peripheral blood samples of 223 CRC patients were collected. The metabolic levels of amino acids and carnitine in peripheral blood of CRC patients, with and without lymph node metastasis, were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS).

Results

The results show that there were significant differences in the levels of serum amino acids and carnitine between lymph node metastatic patients and lymph node non-metastatic patients. The diagnostic model that was constructed by 9 types of serum metabolites has a high diagnostic ability.

Conclusion

LC-MS/MS is a detection method that has a broad application in predicting CRC prognosis, individualized treatment, and in studying the mechanism of lymph node metastasis.

Real-time metabolic profiling of oesophageal tumours reveals an altered metabolic phenotype to different oxygen tensions and to treatment with Pyrazinib

Oesophageal cancer is the 6th most common cause of cancer related death worldwide. The current standard of care for oesophageal adenocarcinoma (OAC) focuses on neoadjuvant therapy with chemoradiation or chemotherapy, however the 5-year survival rates remain at < 20%. To improve treatment outcomes it is critical to further investigate OAC tumour biology, metabolic phenotype and their metabolic adaptation to different oxygen tensions. In this study, by using human ex-vivo explants we demonstrated using real-time metabolic profiling that OAC tumour biopsies have a significantly higher oxygen consumption rate (OCR), a measure of oxidative phosphorylation compared to extracellular acidification rate (ECAR), a measure of glycolysis (p = 0.0004). Previously, we identified a small molecule compound, pyrazinib which enhanced radiosensitivity in OAC. Pyrazinib significantly inhibited OCR in OAC treatment-naïve biopsies (p = 0.0139). Furthermore, OAC biopsies can significantly adapt their metabolic rate in real-time to their environment. Under hypoxic conditions pyrazinib produced a significant reduction in both OCR (p = 0.0313) and ECAR in OAC treatment-naïve biopsies. The inflammatory secretome profile from OAC treatment-naïve biopsies is heterogeneous. OCR was positively correlated with three secreted factors in the tumour conditioned media: vascular endothelial factor A (VEGF-A), IL-1RA and thymic stromal lymphopoietin (TSLP). Pyrazinib significantly inhibited IL-1β secretion (p = 0.0377) and increased IL-3 (p = 0.0020) and IL-17B (p = 0.0181). Importantly, pyrazinib did not directly alter the expression of dendritic cell maturation markers or reduce T-cell viability or activation markers. We present a new method for profiling the metabolic rate of tumour biopsies in real-time and demonstrate the novel anti-metabolic and anti-inflammatory action of pyrazinib ex-vivo in OAC tumours, supporting previous findings in-vitro whereby pyrazinib significantly enhanced radiosensitivity in OAC.

Lipid and protein tumor markers for head and neck squamous cell carcinoma identified by imaging mass spectrometry

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. To improve pre- and post-operative diagnosis and prognosis novel molecular markers are desirable. Here we used MALDI imaging mass spectrometry (IMS) and immunohistochemistry (IHC) to seek tumor specific expression of proteins and lipids in HNSCC samples. Among low molecular weight proteins visualized, S100A8 and S100A9 were found to be expressed in the regions of tumor tissue but not in the surrounding healthy stroma of a post-operative microdissected tissue. Marker potential of S100A8 and S100A9 was confirmed by immunohistochemistry of paraffin-embedded pathological samples. Imaging lipids showed a remarkable depletion of lysophosphatidylcholine species LPC[16:0], LPC[18:2] and, in parallel, accumulation of major glycerophospholipid species PE-P[36:4], PC[32:1], PC[34:1] in neoplastic areas. This was confirmed by shotgun lipidomics of dissected healthy and tumor tissue sections. A combination of the negative (LPC[16:0]) and positive (PC[32:1], PC[34:1]) markers was also applicable to uncover tumorous character of a pre-operative biopsy. Furthermore, marker potential of lysophospholipids was supported by elevated expression levels of the lysophospholipid degrading enzyme lysophospholipase A1 (LYPLA1) in the tumor regions of paraffin-embedded HNSCC samples. Finally, experimental evidence of 3D cell spheroid tests showed that LPC[16:0] facilitates HNSCC invasion, implying that HNSCC progression in vivo may be dependent on lysophospholipid supply. Altogether, a series of novel proteins and lipid species were identified by IMS and IHC screening, which may serve as potential molecular markers for tumor diagnosis, prognosis, and may pave the way to better understand HNSCC pathophyisiology.

Distribution and clinical relevance of phospholipids in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common liver cancer and featured with prominent disparity in incidence and mortality rate between male and female. It remains unclear whether alterations of phospholipids (PL) in hepatic tissues contribute to the pathogenesis, progression, and disparity of HCC.

Methods

Using electrospray ionization mass spectrometry (ESI–MS), PL profiles including 320 individual phospholipid species in 13 PL classes were determined in paired samples from HCC and adjacent benign hepatic tissues (BHT).

Results

(1) Concentrations of PLs in most of individual species, in subgroups and in total were decreased in HCC than in BHT in all studied population; (2) the number of individual PL species significantly different between HCC and BHT, and the number of PLs in six subgroups and in total decreased in HCC were more in male population than in female population; (3) panels of PL parameters (more in male population than in female population) were identified as biomarkers in differentiation of HCC from BHT, and in the prediction of pathological grade and clinical stage of HCC with high sensitivity, specificity, and accuracy.

Conclusion

It is concluded that alterations of PLs in hepatic tissues play important roles in pathogenesis, progression, and gender disparity of HCC.

Electronic supplementary material

The online version of this article (10.1007/s12072-020-10056-8) contains supplementary material, which is available to authorized users.

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.

Virulence Characteristics of mecA-Positive Multidrug-Resistant Clinical Coagulase-Negative Staphylococci

Coagulase-negative staphylococci (CoNS) are an important group of opportunistic pathogenic microorganisms that cause infections in hospital settings and are generally resistant to many antimicrobial agents. We report on phenotypic and genotypic virulence characteristics of a select group of clinical, mecA-positive (encoding penicillin-binding protein 2a) CoNS isolates. All CoNS were resistant to two or more antimicrobials with S. epidermidis strain 214EP, showing resistance to fifteen of the sixteen antimicrobial agents tested. Aminoglycoside-resistance genes were the ones most commonly detected. The presence of megaplasmids containing both horizontal gene transfer and antimicrobial resistance genetic determinants indicates that CoNS may disseminate antibiotic resistance to other bacteria. Staphylococcus sciuri species produced six virulence enzymes, including a DNase, gelatinase, lipase, phosphatase, and protease that are suspected to degrade tissues into nutrients for bacterial growth and contribute to the pathogenicity of CoNS. The PCR assay for the detection of biofilm-associated genes found the eno (encoding laminin-binding protein) gene in all isolates. Measurement of their biofilm-forming ability and Spearman’s rank correlation coefficient analyses revealed that the results of crystal violet (CV) and extracellular polymeric substances (EPS) assays were significantly correlated (ρ = 0.9153, P = 3.612e-12). The presence of virulence factors, biofilm-formation capability, extracellular enzymes, multidrug resistance, and gene transfer markers in mecA-positive CoNS clinical strains used in this study makes them powerful opportunistic pathogens. The study also warrants a careful evaluation of nosocomial infections caused by CoNS and may be useful in studying the mechanism of virulence and factors associated with their pathogenicity in vivo and developing effective strategies for mitigation.

Untargeted Metabolomics Analysis of Esophageal Squamous Cell Carcinoma Discovers Dysregulated Metabolic Pathways and Potential Diagnostic Biomarkers

Background: Esophageal squamous cell carcinoma (ESCC) is one of the most fatal diseases worldwide. Because early diagnosis is difficult, ESCC is mostly diagnosed at an advanced stage, leading to a poor overall prognosis. The purpose of this study was to explore the differences between plasma metabolic profiles in ESCC patients and healthy controls and to establish a diagnostic model of ESCC.

Methods: In this study, a cohort of 310 subjects, containing 140 ESCC patients and 170 healthy controls (HC), was recruited. Participants were randomly separated into a training set (80 ESCCs, 80 HCs) and a validation set (60 ESCCs, 90 HCs) and their plasma metabolomics profiles were analyzed by ultra-performance liquid chromatography-tandem quadruple time-of-flight mass spectrometry (UPLC-QTOF/MS) technique. Univariate statistical analysis and multivariate analysis (MVA) methods were used to identify differential metabolites. Finally, the dysregulated pathways associated with ESCC were further explored and the diagnostic performance of the biomarker panel was evaluated.

Results: Metabolic analyses identified 34 significant metabolites involved in the metabolism of amino acids, phospholipids, fatty acids, purine, and choline. Farthermore, an effective diagnostic model for ESCC was constructed based on eight metabolites. This panel of biomarkers consisted of hypoxanthine, proline betaine, indoleacrylic acid, inosine, 9-decenoylcarnitine, tetracosahexaenoic acid, LPE (20:4), and LPC (20:5). The model was verified and evaluated in the validation set. The AUC value of the ROC curve was 0.991(95% CI: 0.981-1.000, CI, Confidence interval), with a sensitivity (SE) of 98.8% and a specificity (SP) of 94.9% for the training set and 0.965(95% CI: 0.936-0.993), with a SE of 88.3% and a SP of 88.9% for the validation set. Among them, three biomarkers, indoleacrylic acid, LPC (20:5), and LPE (20:4), exhibited a trend associated with the ESCC progression.

Conclusions: Our study identified a novel plasma biomarker panel, which clearly distinguishes ESCC patients and provides insight into the mechanisms of ESCC. This finding may form the basis for the development of a minimally invasive method for ESCC detection.

Strategy for Global Profiling and Identification of 2- and 3-Hydroxy Fatty Acids in Plasma by UPLC-MS/MS

2-Hydroxy fatty acids (2-OHFAs) and 3-hydroxy fatty acids (3-OHFAs) with the same carbon backbone are isomers, both of which are closely related to diseases involving fatty acid oxidation disorder. However, the comprehensive profiling of 2- and 3-OHFAs remains an ongoing challenge due to their high structure similarity, few structure-informative product ions, and limited availability of standards. Here, we developed a new strategy to profile and identify 2- and 3-OHFAs according to structure-dependent retention time prediction models using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Both accurate MS and MS/MS spectra were collected for peak annotation by comparison with an in-house database of theoretically possible 2- and 3-OHFAs. The structures were further confirmed by the validated structure-dependent retention time prediction models, taking advantage of the correlation between the retention time, carbon chain length and number of double bonds, as well as the hydroxyl position-induced isomeric retention time shift rule. With the use of this strategy, 18 2-OHFAs and 32 3-OHFAs were identified in the pooled plasma, of which 7 2-OHFAs and 20 3-OHFAs were identified for the first time in this work, furthering our understanding of OHFA metabolism. Subsequent quantitation method was developed by scheduled multiple reaction monitoring (MRM) and then applied to investigate the alteration of 2- and 3-OHFAs in esophageal squamous cell carcinoma (ESCC) patients. Finally, a potential biomarker panel consisting of six OHFAs with good diagnostic performance was achieved. Our study provides a new strategy for isomer identification and analysis, showing great potential for targeted metabolomics in clinical biomarker discovery.

Metabolic Biomarkers of Squamous Cell Carcinoma of the Aerodigestive Tract: A Systematic Review and Quality Assessment

Introduction. Aerodigestive squamous cell carcinomas (ASCC) constitute a major source of global cancer deaths. Patients typically present with advanced, incurable disease, so new means of detecting early disease are a research priority. Metabolite quantitation is amenable to point-of-care analysis and can be performed in ASCC surrogates such as breath and saliva. The purpose of this systematic review is to summarise progress of ASCC metabolomic studies, with an emphasis on the critical appraisal of methodological quality and reporting.

METHOD

A systematic online literature search was performed to identify studies reporting metabolic biomarkers of ASCC. This review was conducted in accordance with the recommendations of the Cochrane Library and MOOSE guidelines.

RESULTS

Thirty studies comprising 2117 patients were included in the review. All publications represented phase-I biomarker discovery studies, and none validated their findings in an independent cohort. There was heterogeneity in study design and methodological and reporting quality. Sensitivities and specificities were higher in oesophageal and head and neck squamous cell carcinomas compared to those in lung squamous cell carcinoma. The metabolic phenotypes of these cancers were similar, as was the kinetics of metabolite groups when comparing blood, tissue, and breath/saliva concentrations. Deregulation of amino acid metabolism was the most frequently reported theme.

CONCLUSION

Metabolite analysis has shown promising diagnostic performance, especially for oesophageal and head and neck ASCC subtypes, which are phenotypically similar. However, shortcomings in study design have led to inconsistencies between studies. To support future studies and ultimately clinical adoption, these limitations are discussed.

Association of serum levels of deoxyribose 1-phosphate and S-lactoylglutathione with neoadjuvant chemotherapy sensitivity in patients with gastric cancer: A metabolomics study

The present study screened serum samples from patients with advanced-stage gastric cancer and known sensitivities to neoadjuvant chemotherapy, in order to identify metabolites that may serve as potential biomarkers for chemotherapy sensitivity. A total of 47 patients with stage III (T4b) or IV gastric cancer, including 31 in the training group and 16 in a validation group, were classified based on their responses to conversion therapy consisting of oxaliplatin, tegafur and continuous hyperthermic peritoneal perfusion with cisplatin. Serum samples were analyzed by liquid chromatography-mass spectrometry to obtain a metabolite profile of each patient. Patients who were responsive and non-responsive to neoadjuvant chemotherapy exhibited significant differences in serum levels of deoxyribose 1-phosphate, S-lactoylglutathione, lysophosphatidylcholine (16:0) and O-arachidonoyl ethanolamine. Logistic regression analysis indicated that deoxyribose 1-phosphate and S-lactoylglutathione were independently associated with chemosensitivity. Serum levels of deoxyribose 1-phosphate and S-lactoylglutathione were independently associated with the sensitivity of gastric cancer to neoadjuvant chemotherapy, therefore, serving as potential predictors of patient response.

Metabolomics studies in gastrointestinal cancer: a systematic review

Introduction: This systemic review provides an overview of metabolic perturbations and possible mechanisms in gastrointestinal cancer. The authors discuss emerging challenges of technical and clinical applications.Areas covered: In this systemic review, the authors summarized the currently available results of metabolomic biomarkers linked to GI cancer, and discussed the altered metabolism pathways including carbohydrate metabolism, amino acid metabolism, lipids, and nucleotide metabolism and other metabolisms. Furthermore, future efforts need to adhere to normalize analysis procedures, validate with the larger cohort and utilize multiple-omics technologies. The search was conducted in PubMed with the following search terms (biomarker, gastrointestinal cancer, colorectal cancer, and esophageal cancer) from 2013 to 2019.Expert opinion: This systemic review summarized the currently available results of metabolomic biomarkers linked to gastrointestinal cancer, and discussed the altered metabolism pathways. The authors believe that metabolomics will benefit deeper understandings of the pathogenic mechanism, discovery of biomarkers and aid the search for drug targets as we move toward the era of personalized medicine. Personalized medication for tumors can improve the curative effect, avoid side effects and medical resource waste. As a promisingtool, metabolomics that targets the entire cancer-specific metabolite network should be applied more widely in cancer research.

Serum metabolomics reveals the progression of coronary artery stenosis in patients with hypercholesterolemia: a pilot study

: The current study explores potential characteristic metabolic signatures associated with the high cholesterol (CHO), and the progression of coronary artery stenosis (CAS) in high-CHO patients. A metabolomics strategy based on ultra high-performance liquid chromatography/MS-MS and multivariate statistics has been implemented to identify potential biomarkers in high-CHO patients with different levels of CAS. The current study included 57 individuals, comprising 17 healthy paticipants, and 40 high-CHO patients. The high CHO patients were subgrouped based on the computed tomography angiography results, that is, CHO+ no ART (n = 10), CHO+ ART less than 50% (n = 13), CHO+ ART 50-75% (n = 11), and CHO+ ART more than 75% (n = 6). After metabolomics study, 16 discriminating metabolites in positive ion mode and 17 discriminating metabolites in negative ion mode were regarded as possible biomarker candidates to reflect metabolic traits differences between patients with healthy subjects and CHO. A total of six metabolites were tentatively identified as potential biomarkers for the progression diagnosis of CAS: three lysophosphatidylcholines (Lyso-phosphocholine, lysoPC and Lysopersicon esculentum, lysoPE), proline betaine and tryptophan, and prasterone sulfate. The results demonstrated that tryptophan and proline betaine could differentiate the patients with or without high CHO. Tryptophan, prasterone sulfate, LysoPE (0 : 0/18 : 2) or LysoPE (18 : 2/0 : 0), and LysoPE (0 : 0/18 : 1) or LysoPE (18 : 1/0 : 0) could differentiate the patients with severe stenosis (ART > 70%) from the healthy or mild stenosis ones. Proline betaine and significant decrease of LysoPC (17 : 0) could also be a promising biomarker for the mild stenosis (ART < 50%).

Accurate Classification of Non-small Cell Lung Cancer (NSCLC) Pathology and Mapping of EGFR Mutation Spatial Distribution by Ambient Mass Spectrometry Imaging

Objectives: Tumor pathology examination especially epidermal growth factor receptor (EGFR) mutations molecular testing has been integral part of lung cancer clinical practices. However, the EGFR mutations spatial distribution characteristics remains poorly investigated, which is critical to tumor heterogeneity analysis and precision diagnosis. Here, we conducted an exploratory study for label-free lung cancer pathology diagnosis and mapping of EGFR mutation spatial distribution using ambient mass spectrometry imaging (MSI).

Materials and Methods: MSI analysis were performed in 55 post-operative non-small cell lung cancer (NSCLC) tumor and paired normal tissues to distinguish tumor from normal and classify pathology. We then compared diagnostic sensitivity of MSI and ADx-amplification refractory mutation system (ARMS) for the detection of EGFR mutation in pathological confirmed lung adenocarcinoma (AC) and explored EGFR mutations associated biomarkers to depict EGFR spatial distribution base on ambient MSI.

Results: Of 55 pathological confirmed NSCLC, MSI achieved a diagnostic sensitivity of 85.2% (23/27) and 82.1% (23/28) for AC and squamous cell carcinoma (SCC), respectively. Among 27 AC, there were 17 EGFR-wild-type and 10 EGFR-mutated-positive samples detected by ARMS, and MSI achieved a diagnostic sensitivity of 82.3% (14/17) and 80% (8/10) for these two groups. Several phospholipids were specially enriched in AC compared with SCC tissues, with the higher ions intensity of phospholipids in EGFR-mutated-positive compared with EGFR-wild-type AC tissues. We also found EGFR mutations distribution was heterogeneous in different regions of same tumor by multi-regions ARMS detection, and only the regions with higher ions intensity of phospholipids were EGFR-mutated-positive.

Conclusion: MSI method could accurately distinguish tumor pathology and subtypes, and phospholipids were reliable EGFR mutations associated biomarkers, phospholipids imaging could intuitively visualize EGFR mutations spatial distribution, may facilitate our understanding of tumor heterogeneity.