Serum metabolomic signatures of lymph node metastasis of esophageal squamous cell carcinoma

Risk of serum circulating environmental chemical residues to esophageal squamous cell carcinoma: a nested case-control metabolome-wide association study

Esophageal squamous cell carcinoma (ESCC) is the primary histological subtype of esophageal carcinoma, yet research on environmental exposure risks and associated metabolic alterations preceding ESCC is limited. In a nested case-control cohort of 396 adults (199 diagnosed with ESCC and 197 healthy controls (HC)), we combined exposomics and metabolomics to assess circulating chemical residues and early serum metabolic changes linked to ESCC risk. A cell experiment further evaluated the proliferative impact of 1H,1H,2H,2H-perfluorooctanesulfonic acid (6:2 FTS), identifying it as a risk factor for ESCC, primarily through lipid metabolism-related chronic inflammation. Significant metabolic disruptions were observed in ESCC cases, characterized by increased carnitines, phosphatidylcholines (PCs), and triglycerides (TGs) alongside reduced lysophosphatidylcholines (LPCs) and ether lysophosphatidylcholines (LPC-Os). An early-warning biomarker panel, including glutamic acid, methionine, choline, LPC-O 18:0, TG (14:0_18:2_20:5), and PC (18:0_20:4)/LPC 18:0, showed improved predictive capacity when combined with 6:2 FTS. Metabolome-exposome-wide association studies largely confirmed 6:2 FTS as a potential ESCC risk factor through lipid mediation. This study offers novel insights for ESCC prevention and early diagnosis through a combined biomarker panel integrating metabolic and environmental risk indicators.

Biomarkers of lymph node metastasis in esophageal cancer

Esophageal cancer (EC) is among the most aggressive malignancies, ranking as the seventh most prevalent malignant tumor worldwide. Lymph node metastasis (LNM) indicates localized spread of cancer and often correlates with a poorer prognosis, emphasizing the necessity for neoadjuvant systemic therapy before surgery. However, accurate identification of LNM in EC presents challenges due to the lack of satisfactory diagnostic techniques. Imaging techniques, including ultrasound and computerized tomography scans, have low sensitivity and accuracy in assessing LNM. Additionally, the existing serological detection lacks precise biomarkers. The intricate and not fully understood molecular processes involved in LNM of EC contribute to current detective limitations. Recent research has shown potential in using various molecules, circulating tumor cells (CTCs), and changes in the microbiota to identify LNM in individuals with EC. Through summarizing potential biomarkers associated with LNM in EC and organizing the underlying mechanisms involved, this review aims to provide insights that facilitate biomarker development, enhance our understanding of the underlying mechanisms, and ultimately address the diagnostic challenges of LNM in clinical practice.

Latest insights into the global epidemiological features, screening, early diagnosis and prognosis prediction of esophageal squamous cell carcinoma

As a highly invasive carcinoma, esophageal cancer (EC) was the eighth most prevalent malignancy and the sixth leading cause of cancer-related death worldwide in 2020. Esophageal squamous cell carcinoma (ESCC) is the major histological subtype of EC, and its incidence and mortality rates are decreasing globally. Due to the lack of specific early symptoms, ESCC patients are usually diagnosed with advanced-stage disease with a poor prognosis, and the incidence and mortality rates are still high in many countries, especially in China. Therefore, enormous challenges still exist in the management of ESCC, and novel strategies are urgently needed to further decrease the incidence and mortality rates of ESCC. Although the key molecular mechanisms underlying ESCC pathogenesis have not been fully elucidated, certain promising biomarkers are being investigated to facilitate clinical decision-making. With the advent and advancement of high-throughput technologies, such as genomics, proteomics and metabolomics, valuable biomarkers with high sensitivity, specificity and stability could be identified for ESCC. Herein, we aimed to determine the epidemiological features of ESCC in different regions of the world, especially in China, and focused on novel molecular biomarkers associated with ESCC screening, early diagnosis and prognosis prediction.

Effects of dietary chlorogenic acid on cecal microbiota and metabolites in broilers during lipopolysaccharide-induced immune stress

Aims

The aim of this study was to investigate the effects of chlorogenic acid (CGA) on the intestinal microorganisms and metabolites in broilers during lipopolysaccharide (LPS)-induced immune stress.

Methods

A total of 312 one-day-old Arbor Acres (AA) broilers were randomly allocated to four groups with six replicates per group and 13 broilers per replicate: (1) MS group (injected with saline and fed the basal diet); (2) ML group (injected with 0.5 mg LPS/kg and fed the basal diet); (3) MA group (injected with 0.5 mg LPS/kg and fed the basal diet supplemented with 1,000 mg/kg CGA); and (4) MB group (injected with saline and fed the basal diet supplemented with 1,000 mg/kg CGA).

Results

The results showed that the abundance of beneficial bacteria such as Bacteroidetes in the MB group was significantly higher than that in MS group, while the abundance of pathogenic bacteria such as Streptococcaceae was significantly decreased in the MB group. The addition of CGA significantly inhibited the increase of the abundance of harmful bacteria such as Streptococcaceae, Proteobacteria and Pseudomonas caused by LPS stress. The population of butyric acid-producing bacteria such as Lachnospiraceae and Coprococcus and beneficial bacteria such as Coriobacteriaceae in the MA group increased significantly. Non-targeted metabonomic analysis showed that LPS stress significantly upregulated the 12-keto-tetrahydroleukotriene B4, riboflavin and mannitol. Indole-3-acetate, xanthurenic acid, L-formylkynurenine, pyrrole-2-carboxylic acid and L-glutamic acid were significantly down-regulated, indicating that LPS activated inflammation and oxidation in broilers, resulting in intestinal barrier damage. The addition of CGA to the diet of LPS-stimulated broilers significantly decreased 12-keto-tetrahydro-leukotriene B4 and leukotriene F4 in arachidonic acid metabolism and riboflavin and mannitol in ABC transporters, and significantly increased N-acetyl-L-glutamate 5-semialdehyde in the biosynthesis of amino acids and arginine, The presence of pyrrole-2-carboxylic acid in D-amino acid metabolism and the cecal metabolites, indolelactic acid, xanthurenic acid and L-kynurenine, indicated that CGA could reduce the inflammatory response induced by immune stress, enhance intestinal barrier function, and boost antioxidant capacity.

Conclusion

We conclude that CGA can have a beneficial effect on broilers by positively altering the balance of intestinal microorganisms and their metabolites to inhibit intestinal inflammation and barrier damage caused by immune stress.

Multi-omics analysis reveals NNMT as a master metabolic regulator of metastasis in esophageal squamous cell carcinoma

Metabolic reprogramming has been observed in cancer metastasis, whereas metabolic changes required for malignant cells during lymph node metastasis of esophageal squamous cell carcinoma (ESCC) are still poorly understood. Here, we performed single-cell RNA sequencing (scRNA-seq) of paired ESCC tumor tissues and lymph nodes to uncover the reprogramming of tumor microenvironment (TME) and metabolic pathways. By integrating analyses of scRNA-seq data with metabolomics of ESCC tumor tissues and plasma samples, we found nicotinate and nicotinamide metabolism pathway was dysregulated in ESCC patients with lymph node metastasis (LN+), exhibiting as significantly increased 1-methylnicotinamide (MNA) in both tumors and plasma. Further data indicated high expression of N-methyltransferase (NNMT), which converts active methyl groups from the universal methyl donor, S-adenosylmethionine (SAM), to stable MNA, contributed to the increased MNA in LN+ ESCC. NNMT promotes epithelial-mesenchymal transition (EMT) and metastasis of ESCC in vitro and in vivo by inhibiting E-cadherin expression. Mechanically, high NNMT expression consumed too much active methyl group and decreased H3K4me3 modification at E-cadherin promoter and inhibited m6A modification of E-cadherin mRNA, therefore inhibiting E-cadherin expression at both transcriptional and post-transcriptional level. Finally, a detection method of lymph node metastasis was build based on the dysregulated metabolites, which showed good performance among ESCC patients. For lymph node metastasis of ESCC, this work supports NNMT is a master regulator of the cross-talk between cellular metabolism and epigenetic modifications, which may be a therapeutic target.

Biodegradation enhancement of high concentrations formaldehyde waste gas and verification of the metabolic mechanism

The enhanced effects of formaldehyde biodegradation in a biofilm packing tower are investigated in this study. Three experimental groups were established: a blank control group, a biochar addition group, and a lanthanum addition group. The inlet gas flow rate, the inlet gas concentration, and the structural succession characteristics of the microbial community in the tower were investigated by regular sampling. The intracellular metabolites and key enzymes of the dominant functional bacteria, Pseudomonas P1 and Methylobacterium Q1, in the tower were analyzed. The results indicated that with the biochar addition, the formaldehyde purification efficiency increased significantly from 91.67-94.67 % to 94.12 96.85 %, and the bio-elimination capacity increased with an increase in the inlet gas flow rate from 2.314 to 13.988 mg L-1h-1 to 2.697-15.051 mg L-1h-1. With the addition of lanthanum, the purification efficiency increased significantly from 90.80-93.98 % to 94.36-96.78 %, and the bio-elimination capacity increased with an increase in the inlet gas concentration from 1.099-11.284 mg L-1h-1 to 1.266-11.961 mg L-1h-1. The microbial community structure in the tower changed with system operation, and the formaldehyde degrading functional bacteria formed the dominant bacteria. It was verified that P1 and Q1 metabolized high concentrations of formaldehyde by the serine cycle and the ribulose monophosphate (RuMP) cycle.

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.

Integrative analysis of transcriptomic and metabolomic profiles reveals enhanced arginine metabolism in androgen-independent prostate cancer cells

BACKGROUND

Prostate cancer is a common solid tumor that affects a significant number of men worldwide. Conventional androgen deprivation therapy (ADT) increases the risk of developing castration-resistant prostate cancer (CRPC). Effective clinical management of patients with CRPC is challenging due to the limited understanding.

METHODS

In this study, transcriptomic and metabolomic profiles of androgen-dependent prostate cancer cell line LNCaP and the androgen-independent cells developed from LNCaP cells (LNCaP-ADR) were investigated using RNA-sequencing and LC-MS/MS, respectively. The differentially expressed genes and metabolites were analyzed, and integrative analysis of transcriptomic and metabolomic data was further conducted to obtain a comprehensive understanding of the metabolic characteristics in LNCaP-ADR cells. Quantitative real-time PCR (QPCR) was employed to ascertain the mRNA expression levels of the selected differentially expressed genes.

RESULTS

The arginine and proline metabolism pathway was identified as a commonly altered pathway at both the transcriptional and metabolic levels. In the LNCaP-ADR cells, significant upregulation was observed for metabolites including 5-Aminopentanoic acid, L-Arginine, L-Glutamic acid, N-Acetyl-L-alanine, and Pyrrole-2-carboxylic acid at the metabolic level. At the transcriptional level, MAOA, ALDH3A2, ALDH2, ARG1, CKMT2, and CNDP1 were found to be significantly upregulated in the LNCaP-ADR cells. Gene set enrichment analysis (GSEA) identified various enriched gene sets in the LNCaP-ADR cells, encompassing inflammatory response, 9plus2 motile cilium, motile cilium, ciliary plasm, cilium or flagellum-dependent cell motility, cilium movement, cilium, response to endoplasmic reticulum stress, PTEN DN.V1 DN, SRC UP.V1 UP, IL15 UP.V1 DN, RB DN.V1 DN, AKT UP MTOR DN.V1 UP, VEGF A UP.V1 UP, and KRAS.LUNG.BREAST UP.V1 UP.

CONCLUSIONS

These findings highlight the substantial association between the arginine and proline metabolism pathway and CRPC, emphasizing the need to prioritize strategies that target dysregulated metabolites and differentially expressed genes as essential interventions in the clinical management of CRPC.

GABA regulates the proliferation and apoptosis of head and neck squamous cell carcinoma cells by promoting the expression of CCND2 and BCL2L1

Gamma-aminobutyric acid (GABA) is a multifunctional molecule that is widely present in the nervous system and nonneuronal tissues. It plays pivotal roles in neurotransmission, regulation of secretion, cell differentiation, proliferation, and tumorigenesis. However, the exact mechanisms of GABA in head and neck squamous cell carcinomas (HNSCCs) are unknown. We took advantage of RNA sequencing in this work and uncovered the potential gene expression profiles of the GABA-treated HNSCC cell line HN4-2. We found that the expression of CCND2 and BCL2L1 was significantly upregulated. Furthermore, GABA treatment inhibited the cell apoptosis induced by cisplatin and regulated the cell cycle after treatment with cisplatin in HN4-2 cells. Moreover, we also found that GABA could upregulate the expression of CCND2 and BCL2L1 after treatment with cisplatin. Our results not only reveal the potential pro-tumorigenic effect of GABA on HNSCCs but also provide a novel therapeutic target for HNSCC treatment.

Metabolic control of cancer metastasis: role of amino acids at secondary organ sites

Most cancer-related deaths are caused by the metastases, which commonly develop at multiple organ sites including the brain, bone, and lungs. Despite longstanding observations that the spread of cancer is not random, our understanding of the mechanisms that underlie metastatic spread to specific organs remains limited. However, metabolism has recently emerged as an important contributor to metastasis. Amino acids are a significant nutrient source to cancer cells and their metabolism which can serve to fuel biosynthetic pathways capable of facilitating cell survival and tumor expansion while also defending against oxidative stress. Compared to the primary tumor, each of the common metastatic sites exhibit vastly different nutrient compositions and environmental stressors, necessitating the need of cancer cells to metabolically thrive in their new environment during colonization and outgrowth. This review seeks to summarize the current literature on amino acid metabolism pathways that support metastasis to common secondary sites, including impacts on immune responses. Understanding the role of amino acids in secondary organ sites may offer opportunities for therapeutic inhibition of cancer metastasis.

RAE1 promotes nitrosamine-induced malignant transformation of human esophageal epithelial cells through PPARα-mediated lipid metabolism

Esophageal cancer (EC) is the sixth cause of cancer-related deaths and still is a significant public health problem globally. Nitrosamines exposure represents a major health concern increasing EC risks. Exploring the mechanisms induced by nitrosamines may contribute to the prevention and early detection of EC. However, the mechanism of nitrosamine carcinogenesis remains unclear. Ribonucleic acid export 1 (RAE1), has an important role in mediating diverse cancer types, but, to date, there has been no study for any functional role of RAE1 in esophageal carcinogenesis. Here, we successfully verified the nitrosamine-induced malignant transformation cell (MNNG-M) by xenograft tumor model, based on which it was found that RAE1 was upregulation in the early stage of nitrosamine-induced esophageal carcinogenesis and EC tissues. RAE1 knockdown led to severe blockade in G2/M phase and significant inhibition of proliferation of MNNG-M cells, whereas RAE1 overexpression had the opposite effect. In addition, peroxisome proliferator-activated receptor-alpha (PPARα), was demonstrated as a downstream target gene of RAE1, and its down-regulation reduced lipid accumulation, resulting in causing cells accumulation in the G2/M phase. Mechanistically, we found that RAE1 regulates the lipid metabolism by maintaining the stability of PPARα mRNA. Taken together, our study reveals that RAE1 promotes malignant transformation of human esophageal epithelial cells (Het-1A) by regulating PPARα-mediated lipid metabolism to affect cell cycle progression, and offers a new explanation of the mechanisms underlying esophageal carcinogenesis.

Amino Acid Metabolism in Bone Metastatic Disease

PURPOSE OF REVIEW

Breast and prostate tumors frequently metastasize to the bone, but the underlying mechanisms for osteotropism remain elusive. An emerging feature of metastatic progression is metabolic adaptation of cancer cells to new environments. This review will summarize the recent advances on how cancer cells utilize amino acid metabolism during metastasis, from early dissemination to interactions with the bone microenvironment.

RECENT FINDINGS

Recent studies have suggested that certain metabolic preferences for amino acids may be associated with bone metastasis. Once in the bone microenvironment, cancer cells encounter a favorable microenvironment, where a changing nutrient composition of the tumor-bone microenvironment may alter metabolic interactions with bone-resident cells to further drive metastatic outgrowth. Enhanced amino acid metabolic programs are associated with bone metastatic disease and may be further augmented by the bone microenvironment. Additional studies are necessary to fully elucidate the role of amino acid metabolism on bone metastasis.

Serum Metabolomic Signatures of Hirschsprung's Disease Based on GC-MS and LC-MS

Hirschsprung's disease (HSCR) is a congenital digestive tract malformation characterized by the absence of intramural ganglion cells in the myenteric and submucosal plexuses along variable lengths of the gastrointestinal tract. Although the improvement of surgical methods has allowed great progress in the treatment of HSCR, its incidence and postoperative prognosis are still not ideal. The pathogenesis of HSCR remains unclear to date. In this study, metabolomic profiling of HSCR serum samples was performed by an integrated analysis of gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS) as well as multivariate statistical analyses. Based on the random forest algorithm and receiver operator characteristic analysis, 21 biomarkers related to HSCR were optimized. Several amino acid metabolism pathways were identified as important disordered pathways of HSCR, among which tryptophan metabolism was crucial. To our knowledge, this is the first serum metabolomics study focusing on HSCR, and it provides a new perspective for explaining the mechanism of HSCR.

Single-cell metabolic fingerprints discover a cluster of circulating tumor cells with distinct metastatic potential

Circulating tumor cells (CTCs) are recognized as direct seeds of metastasis. However, CTC count may not be the "best" indicator of metastatic risk because their heterogeneity is generally neglected. In this study, we develop a molecular typing system to predict colorectal cancer metastasis potential based on the metabolic fingerprints of single CTCs. After identification of the metabolites potentially related to metastasis using mass spectrometry-based untargeted metabolomics, setup of a home-built single-cell quantitative mass spectrometric platform for target metabolite analysis in individual CTCs and use of a machine learning method composed of non-negative matrix factorization and logistic regression, CTCs are divided into two subgroups, C1 and C2, based on a 4-metabolite fingerprint. Both in vitro and in vivo experiments demonstrate that CTC count in C2 subgroup is closely associated with metastasis incidence. This is an interesting report on the presence of a specific population of CTCs with distinct metastatic potential at the single-cell metabolite level.

Identification and detection of plasma extracellular vesicles-derived biomarkers for esophageal squamous cell carcinoma diagnosis

Esophageal cancer is a malignant tumor with two-thirds of patients having a local recurrence or distant metastasis. To date, diagnostic biomarkers with high sensitivity and specificity are lacking. Extracellular vesicles (EVs) have shown their potential values as disease biomarkers as they carry specific proteins and RNAs derived from cancer cells. In this study, we investigate ESCC precision diagnostics from the insights of circulating EVs, and integrate the ultrafast EV isolation approach (EXODUS) and ELISA for fast detection and screening of ESCC patients. First, we isolate and characterize the high-purity plasma EVs with EXODUS and identify 401 proteins and 372 proteins from ESCC patient and healthy individuals, respectively. Further looking into the differentially expressed proteins (DEPs) of ESCC patients and enriched KEGG pathways, we discover EV-CD14 as a potential diagnostic biomarker for ESCC, which has been further validated as a significantly differentially expressed protein by Western Blot and immunogold labelling TEM. For fast screening and detection of ESCC towards clinical applications, we apply ELISA method to diagnose ESCC from 60 clinical samples based on circulating EV-CD14, which shows a high AUC value up to 96.0% for detection of ESCC in a test set (30 samples), and displays a high accuracy rate up to 90% for prediction of ESCC in a screening test (30 samples). Our results suggest that the circulating EV-CD14 may highly be related to the initiation and progression of ESCC, providing a novel method for the diagnosis and prognosis of ESCC towards clinical translations.

The Importance of Fatty Acid Precision Nutrition: Effects of Dietary Fatty Acid Composition on Growth, Hepatic Metabolite, and Intestinal Microbiota in Marine Teleost Trachinotus ovatus

Our recent study demonstrated that diet with blend oil (named BO1) as lipid, which is designed on the base of essential fatty acid requirement of Trachinotus ovatus, achieved good performance. Here, to confirm its effect and investigate the mechanism, three isonitrogenous (45%) and isolipidic (13%) diets (D1-D3) only differing in dietary lipids, which were, respectively, fish oil (FO), BO1, and blend oil 2 (BO2) consisting of FO and soybean oil at 2 : 3, were formulated and used to feed the T. ovatus juveniles (average initial weight: 7.65 g) for 9 weeks. The results showed that the weight gain rate of fish fed D2 was higher than that of fish fed D3 (P < 0.05) and had no significant difference from that of fish fed D1 (P > 0.05). Correspondingly, compared with the D3 group, fish of the D2 group exhibited better oxidative stress parameters such as lower serum malondialdehyde content and inflammatory indexes in the liver such as the lower expression level of genes encoding four interleukin proteins and tumor necrosis factor α, as well as higher hepatic immune-related metabolites such as valine, gamma-aminobutyric acid, pyrrole-2-carboxylic acid, tyramine, l-targinine, p-synephrine, and butyric acid (P < 0.05). Furthermore, the intestinal probiotic (Bacillus) proportion was significantly higher, while the pathogenic bacteria (Mycoplasma) proportion was significantly lower in the D2 group than that in the D3 group (P < 0.05). The main differential fatty acids of diet D2 were close to those of D1, while the levels of linoleic acid and n-6 PUFA, as well as the ratio of DHA/EPA of D3, were higher than those of D1 and D2. These results indicated that the better performance of D2 such as enhancing growth, reducing oxidative stress, and improving immune responses and intestinal microbial communities in T. ovatus may be mainly due to the good fatty acid composition of BO1, which indicated the importance of fatty acid precision nutrition.

Oxidative stress genes in patients with esophageal squamous cell carcinoma: construction of a novel prognostic signature and characterization of tumor microenvironment infiltration

Background

Oxidative stress plays an important role in the progression of various types of tumors. However, its role in esophageal squamous cell carcinoma (ESCC) has seldom been explored. This study aimed to discover prognostic markers associated with oxidative stress in ESCC to improve the prediction of prognosis and help in the selection of effective immunotherapy for patients.

Results

A consensus cluster was constructed using 14 prognostic differentially expressed oxidative stress-related genes (DEOSGs) that were remarkably related to the prognosis of patients with ESCC. The infiltration levels of neutrophils, plasma cells, and activated mast cells, along with immune score, stromal score, and estimated score, were higher in cluster 1 than in cluster 2. A prognostic signature based on 10 prognostic DEOSGs was devised that could evaluate the prognosis of patients with ESCC. Calculated risk score proved to be an independent clinical prognostic factor in the training, testing, and entire sets. P53 signaling pathway was highly enriched in the high-risk group. The calculated risk score was positively related to the infiltration levels of resting mast cells, memory B cells, and activated natural killer (NK) cells and negatively associated with the infiltration levels of M1 and M2 macrophages. The relationship between clinical characteristics and risk score has not been certified. The half-maximal inhibitory concentration (IC50) values for sorafenib and gefitinib were lower for patients in the low-risk group.

Conclusion

Our prognostic signature based on 10 prognostic DEOSGs could predict the disease outcomes of patients with ESCC and had strong clinical value. Our study improves the understanding of oxidative stress in tumor immune microenvironment (TIME) and provides insights for developing improved and efficient immunotherapy strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04956-9.

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.

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.

The overall process of metastasis: From initiation to a new tumor

Metastasis-a process that involves the migration of cells from the primary site to distant organs-is the leading cause of cancer-associated death. Improved technology and in-depth research on tumors have furthered our understanding of the various mechanisms involved in tumor metastasis. Metastasis is initiated by cancer cells of a specific phenotype, which migrate with the assistance of extracellular components and metastatic traits conferred via epigenetic regulation while modifying their behavior in response to the complex and dynamic human internal environment. In this review, we have summarized the general steps involved in tumor metastasis and their characteristics, incorporating recent studies and topical issues, including epithelial-mesenchymal transition, cancer stem cells, neutrophil extracellular traps, pre-metastatic niche, extracellular vesicles, and dormancy. Several feasible treatment directions have also been summarized. In addition, the correlation between cancer metastasis and lifestyle factors, such as obesity and circadian rhythm, has been illustrated.

A Feature Selection Approach Guided an Early Prediction of Anthocyanin Accumulation Using Massive Untargeted Metabolomics Data in Mulberry

Identifying the early predictive biomarkers or compounds represents a pivotal task for guiding a targeted agricultural practice. Despite the various available tools, it remains challenging to define the ideal compound combination and thereby elaborate an effective predictive model fitting that. Hence, we employed a stepwise feature selection approach followed by a maximum relevance and minimum redundancy (MRMR) on the untargeted metabolism in four mulberry genotypes at different fruit developmental stages (FDSs). Thus, we revealed that 7 out of 226 differentially abundant metabolites (DAMs) explained up to 80% variance of anthocyanin based on linear regression model and stepwise feature selection approach accompanied by an MRMR across the genotypes over the FDSs. Among them, the phosphoenolpyruvate, d-mannose and shikimate show the top 3 attribution indexes to the accumulation of anthocyanin in the fruits of these genotypes across the four FDSs. The obtained results were further validated by assessing the regulatory genes expression levels and the targeted metabolism approach. Taken together, our findings provide valuable evidences on the fact that the anthocyanin biosynthesis is somehow involved in the coordination between the carbon metabolism and secondary metabolic pathway. Our report highlights as well the importance of using the feature selection approach for the predictive biomarker identification issued from the untargeted metabolomics data.

Plasma Metabolomics Reveals Diagnostic Biomarkers and Risk Factors for Esophageal Squamous Cell Carcinoma

Esophageal squamous carcinoma (ESCC) has a high morbidity and mortality rate. Identifying risk metabolites associated with its progression is essential for the early prevention and treatment of ESCC. A total of 373 ESCC, 40 esophageal squamous dysplasia (ESD), and 218 healthy controls (HC) subjects were enrolled in this study. Gas chromatography-mass spectrometry (GC/MS) was used to acquire plasma metabolic profiles. Receiver operating characteristic curve (ROC) and adjusted odds ratio (OR) were calculated to evaluate the potential diagnosis and prediction ability markers. The levels of alpha-tocopherol and cysteine were progressively decreased, while the levels of aminomalonic acid were progressively increased during the various stages (from precancerous lesions to advanced-stage) of exacerbation in ESCC patients. Alpha-tocopherol performed well for the differential diagnosis of HC and ESD/ESCC (AUROC>0.90). OR calculations showed that a high level of aminomalonic acid was not only a risk factor for further development of ESD to ESCC (OR>13.0) but also a risk factor for lymphatic metastasis in ESCC patients (OR>3.0). A low level of alpha-tocopherol was a distinguished independent risk factor of ESCC (OR< 0.5). The panel constructed by glycolic acid, oxalic acid, glyceric acid, malate and alpha-tocopherol performed well in distinguishing between ESD/ESCC from HC in the training and validation set (AUROC>0.95). In conclusion, the oxidative stress function was impaired in ESCC patients, and improving the body’s antioxidant function may help reduce the early occurrence of ESCC.

Metabolomic Characterization Reveals ILF2 and ILF3 Affected Metabolic Adaptions in Esophageal Squamous Cell Carcinoma

Esophageal cancer (EC) is a common malignant disease in eastern countries. However, a study of the metabolomic characteristics associated with other biological factors in esophageal squamous cell carcinoma (ESCC) is limited. Interleukin enhancer binding factor 2 (ILF2) and ILF3, double-stranded RNA-binding proteins, have been reported to contribute to the occurrence and development of various types of malignancy. Nevertheless, the underlying functions of ILF2 and ILF3 in ESCC metabolic reprogramming have never been reported. This study aimed to contribute to the metabolic characterization of ESCC and to investigate the metabolomic alterations associated with ILF2 and ILF3 in ESCC tissues. Here, we identified 112 differential metabolites, which were mainly enriched in phosphatidylcholine biosynthesis, fatty acid metabolism, and amino acid metabolism pathways, based on liquid chromatography–mass spectrometry and capillary electrophoresis–mass spectrometry approaches using ESCC tissues and paired para-cancer tissues from twenty-eight ESCC patients. In addition, ILF2 and ILF3 expression were significantly elevated in EC tissues compared to the histologically normal samples, and closely associated with PI3K/AKT and MAPK signaling pathways in ESCC. Moreover, in ESCC tissues with a high ILF2 expression, several short-chain acyl-carnitines (C3:0, C4:0, and C5:0) related to the BCAA metabolic pathway and long-chain acyl-carnitines (C14:0, C16:0, C16:0-OH, and C18:0) involved in the oxidation of fatty acids were obviously upregulated. Additionally, a series of intermediate metabolites involved in the glycolysis pathway, including G6P/F6P, F1,6BP, DHAP, G3P, and 2,3BPG, were remarkably downregulated in highly ILF3-expressed ESCC tissues compared with the corresponding para-cancer tissues. Overall, these findings may provide evidence for the roles of ILF2 and ILF3 during the process of ESCC metabolic alterations, and new insights into the development of early diagnosis and treatment for ESCC. Further investigation is needed to clarify the underlying mechanism of ILF2 and ILF3 on acyl-carnitines and the glycolysis pathway, respectively.

Plasma-metabolite-based machine learning is a promising diagnostic approach for esophageal squamous cell carcinoma investigation

The aim of this study was to develop a diagnostic strategy for esophageal squamous cell carcinoma (ESCC) that combines plasma metabolomics with machine learning algorithms. Plasma-based untargeted metabolomics analysis was performed with samples derived from 88 ESCC patients and 52 healthy controls. The dataset was split into a training set and a test set. After identification of differential metabolites in training set, single-metabolite-based receiver operating characteristic (ROC) curves and multiple-metabolite-based machine learning models were used to distinguish between ESCC patients and healthy controls. Kaplan-Meier survival analysis and Cox proportional hazards regression analysis were performed to investigate the prognostic significance of the plasma metabolites. Finally, twelve differential plasma metabolites (six up-regulated and six down-regulated) were annotated. The predictive performance of the six most prevalent diagnostic metabolites through the diagnostic models in the test set were as follows: arachidonic acid (accuracy: 0.887), sebacic acid (accuracy: 0.867), indoxyl sulfate (accuracy: 0.850), phosphatidylcholine (PC) (14:0/0:0) (accuracy: 0.825), deoxycholic acid (accuracy: 0.773), and trimethylamine N-oxide (accuracy: 0.653). The prediction accuracies of the machine learning models in the test set were partial least-square (accuracy: 0.947), random forest (accuracy: 0.947), gradient boosting machine (accuracy: 0.960), and support vector machine (accuracy: 0.980). Additionally, survival analysis demonstrated that acetoacetic acid was an unfavorable prognostic factor (hazard ratio (HR): 1.752), while PC (14:0/0:0) (HR: 0.577) was a favorable prognostic factor for ESCC. This study devised an innovative strategy for ESCC diagnosis by combining plasma metabolomics with machine learning algorithms and revealed its potential to become a novel screening test for ESCC.

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Six most prevalent diagnostic plasma metabolites were identified in ESCC.

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Plasma-metabolite-based machine learning models (PLS, RF, GBM, and SVM) for ESCC diagnosis.

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Acetoacetic acid was an unfavorable prognostic factor, while PC (14:0/0:0) was a favorable prognostic factor for ESCC.

Serum metabolomic profiling based on GC/MS helped to discriminate Diffuse Large B-cell Lymphoma patients with different prognosis

BACKGROUND

The varied clinical outcomes of patients with Diffuse Large B Cell Lymphoma (DLBCL) are attributed to the different genetic and phenotypic subtypes. The purpose of this study was to determine whether metabolic alterations were related to cell-of-origin subtypes of DLBCL and find some metabolites which are associated with the clinical outcomes.

METHODS

Pre-treatment serum samples from eighty (80) newly diagnosed DLBCL patients, including twenty-eight (28) patients with Germinal Center B cell-like (GCB) subtypes and fifty-two (52) patients with non-GCB subtypes, were tested by the Gas Chromatography-Mass Spectrometry (GC-MS) technique. Univariate and multivariate analysis methods, principal component analysis (PCA), and partial least square discriminant analysis (PLS-DA) were conducted to examine the potential differential metabolites. Overall survival (OS) was calculated.

RESULTS

Overall, 65 out of 1472 entities were identified for subsequent analysis. Unfortunately, the initial PLS-DA analysis failed to discriminate GCB from non-GCB samples. Intriguingly, further PLS-DA analysis identified two subgroups of DLBCL (named as group A and group B) and the metabolic subgroups were significantly associated with overall survival. Valine, hexadecenoic acid, and pyroglutamic acid were identified and verified as the most important altered metabolites and could be candidate biomarkers for the prognosis of DLBCL.

CONCLUSIONS

Our results demonstrated that metabolic alterations in serum could be helpful to predict different clinical outcomes of DLBCL patients. Further studies are warranted to understand whether the altered metabolites might serve as prognostic factors for DLBCL.

Metabolic Profiling of Urinary Chiral Amino-Containing Biomarkers for Gastric Cancer Using a Sensitive Chiral Chlorine-Labeled Probe by HPLC-MS/MS

Screening of characteristic biomarkers from chiral amino-containing metabolites in biological samples is difficult and important for the noninvasive diagnosis of gastric cancer (GC). Here, an enantiomeric pair of chlorine-labeled probes d-BPCl and l-BPCl was synthesized to selectively label d- and l-amino-containing metabolites in biological samples, respectively. Incorrect structural annotations were excluded according to the characteristic 3:1 abundance ratio of natural chlorine isotopes (³⁵Cl and ³⁷Cl) derived from the probes. A sensitive C18 HPLC-QQQ-MS/MS method in combination with the probes was then developed and applied in metabolomic analysis of amino-containing metabolites in urine samples. A total of 161 amino-containing metabolites were rapidly separated and determined, and 28 chiral amino acids and achiral glycine were quantified with good precision and accuracy. A total of 18 differential variables were discriminated by analyzing chiral amino-containing metabolites in urine samples of the GC patient and healthy person using the probe-based HPLC-MS/MS-MRM method combined with the orthogonal partial least squares discriminant analysis and Mann-Whitney U test with false discovery rate correction for multiple hypotheses. A diagnostic regression model including d-isoleucine, d-serine, and β-(pyrazol-1-yl)-l-alanine and age was then constructed with an average prediction correctness of 88.9% in the validation set. This work established a close connection between gastric cancer and chiral amino-containing metabolites. The mass spectrometry data analyzed in the study are publicly available via Mendeley Data (DOI: 10.17632/4bd93j9yrr.1).

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.

Metabolomics of Oral/Head and Neck Cancer

Oral/head and neck cancer is the sixth most common human malignancies in the world. Despite the treatment advances in surgery, chemotherapy, and radiotherapy, the patient survival has not been significantly improved in the past several decades. As a new methodological approach, metabolomics may help reveal the metabolic reprogramming mechanisms underlying head and neck cancer cell proliferation, invasion, and metastasis and may be used to identify metabolite biomarkers for clinical applications of the disease. In this chapter, we briefly review recent metabolomic applications in head and neck cancer.

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 metabolism of cancer cells during metastasis

Metastasis formation is the major cause of death in most patients with cancer. Despite extensive research, targeting metastatic seeding and colonization is still an unresolved challenge. Only recently, attention has been drawn to the fact that metastasizing cancer cells selectively and dynamically adapt their metabolism at every step during the metastatic cascade. Moreover, many metastases display different metabolic traits compared with the tumours from which they originate, enabling survival and growth in the new environment. Consequently, the stage-dependent metabolic traits may provide therapeutic windows for preventing or reducing metastasis, and targeting the new metabolic traits arising in established metastases may allow their eradication.

Comprehensive metabolomic profiling of osteosarcoma based on UHPLC-HRMS

INTRODUCTION

Osteosarcoma (OS) is the most common primary malignant bone tumor in children and adolescents. An increasing number of studies have demonstrated that tumor proliferation and metastasis are closely related to complex metabolic reprogramming. However, there are limited data to provide a comprehensive metabolic picture of osteosarcoma.

OBJECTIVES

Our study aims to identify aberrant metabolic pathways and seek potential adjuvant biomarkers for osteosarcoma.

METHODS

Serum samples were collected from 65 osteosarcoma patients and 30 healthy controls. Nontargeted metabolomic profiling was performed by liquid chromatography-mass spectrometry (LC-MS) based on univariate and multivariate statistical analyses.

RESULTS

The OPLS-DA model analysis identified clear separations among groups. We identified a set of differential metabolites such as higher serum levels of adenosine-5-monophosphate, inosine-5-monophosphate and guanosine monophosphate in primary OS patients compared to healthy controls, and higher serum levels of 5-aminopentanamide, 13(S)-HpOTrE (FA 18:3 + 2O) and methionine sulfoxide in lung metastatic OS patients compared to primary OS patients, revealing aberrant metabolic features during the proliferation and metastasis of osteosarcoma. We found a group of metabolites especially lactic acid and glutamic acid, with AUC values of 0.97 and 0.98, which could serve as potential adjuvant diagnostic biomarkers for primary osteosarcoma, and a panel of 2 metabolites, 5-aminopentanamide and 13(S)-HpOTrE (FA 18:3 + 2O), with an AUC value of 0.92, that had good monitoring ability for lung metastases.

CONCLUSIONS

Our study provides new insight into the aberrant metabolic features of osteosarcoma. The potential biomarkers identified here may have translational significance.

Angustoline Inhibited Esophageal Tumors Through Regulating LKB1/AMPK/ELAVL1/LPACT2 Pathway and Phospholipid Remodeling

Esophageal cancer is a type of gastrointestinal carcinoma and is among the 10 most common causes of cancer death worldwide. However, the specific mechanism and the biomarkers in the proliferation and metastasis of esophageal tumors are still unclear. Therefore, the development of several natural products which could inhibit esophageal tumors deserve attention. In the present study, different sources of cancer cells were used to select the sensitive cell line (esophageal cancer cell KYSE450) and the proper dose of angustoline, which were utilized in the following cell viability, migration and invasion assays. Then the lipidomic detection of clinical samples (tissue and blood plasma) from esophageal cancer patients was performed, to screen out the specific phospholipid metabolites [PC (16:0/18:1) and LPC (16:0)]. Considering lysophosphatidylcholine acyltransferase 2 (LPCAT2) was tightly relative with phospholipids conversion, serine/threonine-protein kinase 11 (LKB1), 5'-monophosphate (AMP)-activated protein kinase (AMPK) and embryonic lethal, and abnormal vision, drosophila-like 1 (ELAVL1) were investigated, to evaluate their expression levels in esophageal tumor tissue and KYSE450 cells. Additionally, KYSE450 tumor bearing mouse model was constructed, the role of angustoline in inhibiting esophageal tumors through regulating LKB1/AMPK/ELAVL1/LPCAT2 pathway was validated, and found that the conversion from LPC (16:0) to PC (16:0/18:1) was blocked by angustoline in some degree. The above results for the first time proved that angustoline suppressed esophageal tumors through activating LKB1/AMPK and inhibiting ELAVL1/LPCAT2, which consequently blocked phospholipid remodeling from LPC (16:0) to PC (16:0/18:1).

Blood-based biomarkers for early detection of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive system worldwide, especially in China. Due to the lack of effective early detection methods, ESCC patients often present at an advanced stage at the time of diagnosis, which seriously affects the prognosis of patients. At present, early detection of ESCC mainly depends on invasive and expensive endoscopy and histopathological biopsy. Therefore, there is an unmet need for a non-invasive method to detect ESCC in the early stages. With the emergence of a large class of non-invasive diagnostic tools, serum tumor markers have attracted much attention because of their potential for detection of early tumors. Therefore, the identification of serum tumor markers for early detection of ESCC is undoubtedly one of the most effective ways to achieve early diagnosis and treatment of ESCC. This article reviews the recent advances in the discovery of blood-based ESCC biomarkers, and discusses the origins, clinical applications, and technical challenges of clinical validation of various types of biomarkers.

Microbial and metabolomic analysis of gingival crevicular fluid in general chronic periodontitis patients: lessons for a predictive, preventive, and personalized medical approach

Objectives

General chronic periodontitis (GCP) is a bacterial inflammatory disease with complex pathology. Despite extensive studies published on the variation in the oral microbiota and metabolic profiles of GCP patients, information is lacking regarding the correlation between host-bacterial interactions and biochemical metabolism. This study aimed to analyze the oral microbiome, the oral metabolome, and the link between them and to identify potential molecules as useful biomarkers for predictive, preventive, and personalized medicine (PPPM) in GCP.

Methods

In this study, gingival crevicular fluid (GCF) samples were collected from patients with GCP (n = 30) and healthy controls (n = 28). The abundance of oral microbiota constituents was obtained by Illumina sequencing, and the relative level of metabolites was measured by gas chromatography-mass spectrometry. Full-mouth probing depth, clinical attachment loss, and bleeding on probing were recorded as indices of periodontal disease.

Results

The relative abundances of 7 phyla and 82 genera differed significantly between the GCP and healthy groups. Seventeen differential metabolites involved in different metabolism pathways were selected based on variable influence on projection values (VIP > 1) and P values (P < 0.05). Through Spearman's correlation analysis, microorganisms, metabolites in GCF, and clinical data together showed a clear trend, and clinical data regarding periodontitis can be reflected in the shift of the oral microbial community and the change in metabolites in GCF. A combination of citramalic acid and N-carbamylglutamate yielded satisfactory accuracy (AUC = 0.876) for the predictive diagnosis of GCP.

Conclusions

Dysbiosis in the polymicrobial community structure and changes in metabolism could be mechanisms underlying periodontitis. The differential microorganisms and metabolites in GCF between periodontitis patients and healthy individuals are possibly biomarkers, pointing to a potential strategy for the prediction, diagnosis, prognosis, and management of personalized periodontal therapy.

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.

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.

Targeting citrate as a novel therapeutic strategy in cancer treatment

An important feature shared by many cancer cells is drastically altered metabolism that is critical for rapid growth and proliferation. The distinctly reprogrammed metabolism in cancer cells makes it possible to manipulate the levels of metabolites for cancer treatment. Citrate is a key metabolite that bridges many important metabolic pathways. Recent studies indicate that manipulating the level of citrate can impact the behaviors of both cancer and immune cells, resulting in induction of cancer cell apoptosis, boosting immune responses, and enhanced cancer immunotherapy. In this review, we discuss the recent developments in this emerging area of targeting citrate in cancer treatment. Specifically, we summarize the molecular basis of altered citrate metabolism in both tumors and immune cells, explore the seemingly conflicted growth promoting and growth inhibiting roles of citrate in various tumors, discuss the use of citrate in the clinic as a novel biomarker for cancer progression and outcomes, and highlight the new development of combining citrate with other therapeutic strategies in cancer therapy. An improved understanding of complex roles of citrate in the suppressive tumor microenvironment should open new avenues for cancer therapy.

Clinical, pathophysiologic, and genomic analysis of the outcomes of primary head and neck malignancy after pulmonary metastasectomy

The median overall survival (OS) of some head and neck malignancies, such as head and neck squamous cell carcinoma (HNSCC), with metastatic lesions was only 12 months. Whether aggressive pulmonary metastasectomy (PM) improves survival is controversial. Patients with primary head and neck malignancy undergoing PM were enrolled. Clinical outcomes were compared among different histological types. Whole-exome sequencing was used for matched pulmonary metastatic samples. The genes where genetic variants have been identified were sent for analysis by DAVID, IPA, and STRING. Forty-nine patients with primary head and neck malignancies were enrolled. Two-year postmetastasectomy survival (PMS) rates of adenoid cystic carcinoma, thyroid carcinoma, nasopharyngeal carcinoma, and HNSCC were 100%, 88.2%, 71.4%, and 59.2%, respectively (P = 0.024). In HNSCC, the time to distant metastasis was an independent predictive factor of the efficacy of PM. Several pathways, such as branched-chain amino acid (BCAA) consumption, were significantly associated with the progression of HNSCC [P < 0.001, fold enrichment (FE) = 5.45]. Moreover, metabolism-associated signaling pathways also seemed to be involved in cancer metastasis. Histological types and time to distant metastasis were important factors influencing the clinical outcomes of PM. For HNSCC, metabolic-associated signaling pathways were significantly associated with tumor progression and distant metastasis. Future validations are warranted.

Toxicity and serum metabolomics investigation of Mn-doped ZnS quantum dots in mice

Purpose

Mn-doped ZnS quantum dots (QDs) with special luminescent properties have been widely researched and applied in various fields. Thus, their release toxicity and security cannot be ignored.

Methods

In the present study, the toxicity and non-targeted metabolomics of Mn-doped ZnS QDs were investigated after single intravenous injection. Serum metabolites were evaluated based on gas chromatography–mass spectrometry together with multivariate statistical analyses [principal component analysis, partial least squares discriminant analysis, and orthogonal PLS-DA].

Results

The modified metabolites (variable importance in the projection (VIP) >1 and p<0.05) revealed that Mn-doped ZnS QDs exposure disturbed glycolysis, tricarboxylic acid cycle, ketoplasia, glutaminolysis, and amino acid and lipid metabolism. The behavior, coefficients of organs, and histological changes were the same as in the control group, and the disturbance of hematology and serum biochemistry was not dose- or time-dependent.

Conclusion

Our study provides a general observation regarding the toxicity and potential metabolic responses of mice exposed to Mn-doped ZnS QDs.

Plant Root Exudates Are Involved in Bacillus cereus AR156 Mediated Biocontrol Against Ralstonia solanacearum

The biological control process mediated by microbes relies on multiple interactions among plants, pathogens and biocontrol agents (BCAs). One such efficient BCA is Bacillus cereus AR156, a bacterial strain that controls a broad spectrum of plant diseases and potentially works as a microbe elicitor of plant immune reactions. It remains unclear, however, whether the interaction between plants and B. cereus AR156 may facilitate composition changes of plant root exudates and whether these changes directly affect the growth of both plant pathogens and B. cereus AR156 itself. Here, we addressed these questions by analyzing the influences of root exudate changes mediated by B. cereus AR156 during biocontrol against tomato bacterial wilt caused by Ralstonia solanacearum. Indeed, some upregulated metabolites in tomato root exudates induced by B. cereus AR156 (REB), such as lactic acid and hexanoic acid, induced the growth and motile ability of in vitro B. cereus AR156 cells. Exogenously applying hexanoic acid and lactic acid to tomato plants showed positive biocontrol efficacy (46.6 and 39.36%) against tomato bacterial wilt, compared with 51.02% by B. cereus AR156 itself. Furthermore, fructose, lactic acid, sucrose and threonine at specific concentrations stimulated the biofilm formation of B. cereus AR156 in Luria-Bertan- Glycerol- Magnesium medium (LBGM), and we also detected more colonized cells of B. cereus AR156 on the tomato root surface after adding these four compounds to the system. These observations suggest that the ability of B. cereus AR156 to induce some specific components in plant root exudates was probably involved in further biocontrol processes.

1H-NMR spectroscopy identifies potential biomarkers in serum metabolomic signatures for early stage esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. Here, we used ¹H nuclear magnetic resonance spectroscopy (¹H-NMR) to identify potential serum biomarkers in patients with early stage ESCC.

METHODS

Sixty-five serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analysed using ¹H-NMR spectroscopy. We distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers.

RESULTS

Using OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence.

CONCLUSIONS

¹H-NMR spectroscopy may be a useful tumour detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC.

Exploring potential biomarkers of early stage esophageal squamous cell carcinoma in pre- and post-operative serum metabolomic fingerprint spectrum using 1H-NMR method

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancy. Here, we used ¹H nuclear magnetic resonance spectroscopy (¹H-NMR) to identify potential pre- and post-operative serum biomarkers in patients with early stage ESCC using metabolomic fingerprint spectrum. Serum samples from preoperative patients with ESCC (ESCC, n = 25), postoperative patients with ESCC (PO, n = 24), and controls (n = 40) were analysed using ¹H-NMR spectroscopy. Using orthogonal partial least squares-discriminant analysis, 31 altered serum metabolites were successfully identified among the three groups. These metabolites are indicative of the changes that occur with glycometabolism, the metabolism of fatty acids, amino acids, choline, ketone bodies, nucleotides, and lipids. Based on receiver operating characteristic (ROC) curve analysis and a biomarker panel with an area under the curve (AUC) of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential diagnostic biomarkers for early stage ESCC. Additionally, four potential PO biomarkers (α-glucose, pyruvate, glutamate, and valine) with an AUC of 0.985 were selected to distinguish ESCC and PO. Many metabolites trended towards normalisation in PO patients, with only choline remaining high with an AUC of 0.858, suggesting that it may be a valuable potential biomarker for neoplasm progression, recurrence, chemoradiotherapy, and prognosis. ¹H-NMR spectroscopy may be a useful tumour detection approach in the early diagnosis of ESCC. These results also indicate that it is useful to differentiate pre- and post-operative ESCC, evaluate surgery therapeutic responses, and monitor postoperative chemoradiotherapy.

BAG2 Overexpression Correlates with Growth and Poor Prognosis of Esophageal Squamous Cell Carcinoma

Previous studies have suggested that Bcl2-associated athanogene 2 (BAG2) serves as a crucial regulator for tumorigenesis in multiple tumors. However, little is known about the effect of BAG2 on esophageal squamous cell carcinoma (ESCC). This study focused on investigating whether BAG2 functions as a cancer-promoting gene in ESCC. In this work, gene expression data and clinical information from the NCBI Gene Expression Omnibus (GEO), Oncomine and The Cancer Genome Atlas (TCGA) were collected and analyzed. Expression of BAG2 in ESCC was determined using quantitative reverse transcription polymerase chain reaction (qRT-PCR). BAG2 was knocked down using small interference RNA (si-RNA) approach. Cell proliferation, migration and invasion were assessed by Cell Counting Kit-8 (CCK-8) and transwell assays. Molecular mechanism was detected by western blotting assay. The expression of BAG2 both in ESCC tissues and cells was upregulated and overexpression was associated with worsened prognosis. BAG2 silencing inhibited ESCC cell proliferation, migration and invasion, which was regulated by the phosphatidylinositol-3-kinase (PI3K)/ protein kinase B (AKT) signaling pathway. These results reveal contributions of BAG2 as a predictor and potential therapeutic target in ESCC.

Insight into the surfactin production of Bacillus velezensis B006 through metabolomics analysis

Bacillus velezensis B006 is a biocontrol agent which functions through effective colonization and surfactin production. To reveal the surfactin-producing mechanism, gas chromatography–mass spectrometry based untargeted metabolomics was performed to compare the metabolite profiles of strain B006 grown in industrial media M3 and M4. Based on the statistical and pathway topology analyses, a total of 31 metabolites with a fold change of less than − 1.0 were screened as the significantly altered metabolites, which distributed in 15 metabolic pathways. Fourteen amino acids involving in the metabolisms of alanine/aspartate/glutamate, glycine/serine/threonine, arginine/proline, glutathione/cysteine/methionine and valine/leucine/isoleucine as well as succinic acid in TCA cycle were identified to be the hub metabolites. Aminoacyl-tRNA biosynthesis, glycerolipid metabolism, and pantothenate/CoA biosynthesis also contributed to surfactin production. To the best of our knowledge, this study is the first to investigate the metabolic pathways of B. velezensis on surfactin production, and will benefit the optimization of commercial fermentation for higher surfactin yield.

Combined detection of IL-6 and IL-8 is beneficial to the diagnosis of early stage esophageal squamous cell cancer: a preliminary study based on the screening of serum markers using protein chips

Background

The diagnosis rate of early stage esophageal squamous cell carcinoma (ESCC) is low due to the lack of specific tumor markers. Seeking for these markers is beneficial to improve the early diagnosis rate and the prognosis of patients. This study profiles the differentially expressed proteins of early stage ESCC patients via the AAH-BLG-507 protein chip, which further consolidates the clinical evidence of ESCC diagnosis.

Materials and methods

In this study, 20 serum samples were collected from Taihe Hospital between August 2016 and June 2017. Ten of them carried ESCC, while the rest were healthy controls. To profile the proteins’ expression level, the AAH-BLG-507 protein chip was used, and both highly expressed and lowly expressed proteins were fished out. Meanwhile, their biological roles were examined by using Gene Ontology (GO) database and String database, and they were further verified by ELISA.

Results

Results showed that the expression levels of AXL, ARTN, Ang2, BDNF, BMP7, cripto-1, CCL28, E-selectin, IL-6, IL-8 and SHH in the serum of early ESCC were significantly upregulated (P<0.05), particularly IL-6 and IL-8. The expression levels of TSP1 and MMP-8 were markedly downregulated (P<0.05). Analysis showed that these proteins were mainly involved in angiogenesis, signal transduction, cell proliferation and migration, indicating the close relationship with the development of ESCC.

Conclusion

It suggested that IL-6 and IL-8 proteins could be considered as the markers for ESCC diagnosis.

Identification of serum biomarkers of chemoradiosensitivity in esophageal cancer via the targeted metabolomics approach

AIM

To identify the serum metabolomics signature that is correlated with the chemoradiosensitivity of esophageal squamous cell carcinoma (ESCC).

MATERIALS & METHODS

Untargeted and targeted metabolomics analysis of serum samples from 26 ESCC patients, which were collected before the neoadjuvant chemoradiotherapy, was performed.

RESULTS

On receiving the results of untargeted metabolomics analysis, we performed the targeted metabolomics analysis of the six metabolites (arabitol, betaine, glycine, L-serine, L-arginine and L-aspartate). The serum levels of the four metabolites (arabitol, glycine, L-serine and L-arginine) were significantly lower in the patients who achieved pathological complete response with neoadjuvant chemoradiotherapy compared with the patients who did not achieve pathological complete response (p = 0.0086, 0.0345, 0.0106 and 0.0373, respectively).

CONCLUSION

The serum levels of metabolites might be useful for predicting the chemoradiosensitivity of ESCC patients.

Analysis of metabolic profiles of generalized aggressive periodontitis

BACKGROUND AND OBJECTIVE

The specific pathogenesis of generalized aggressive periodontitis (GAgP) has not yet been clarified, and few studies have focused on the association between GAgP and metabolomics. To elucidate the roles of metabolic profiles in the status of GAgP, this study aimed to identify the differential metabolic profiles between patients with GAgP and healthy controls using an untargeted metabolomic profiling method.

MATERIAL AND METHODS

Serum and gingival crevicular fluid samples were collected from healthy controls (n = 20) and patients with GAgP (n = 20) in this cross-sectional study. The relative levels of biomarkers in the samples were measured by gas chromatography-mass spectrometry. Principal components analysis and orthogonal partial least-squares discriminant analysis were used for statistical analysis. Metabolites were analysed qualitatively using the FiehnLib and NIST databases. Full-mouth probing depth and clinical attachment loss were recorded as indexes of periodontal disease.

RESULTS

A total of 349 metabolites were qualitatively detected in the gingival crevicular fluid samples, and 200 metabolites were detected in the serum samples. Compared with healthy controls, patients with GAgP showed significant increases in serum urea and allo-inositol levels. In contrast, glutathione, 2,5-dihydroxybenzaldehyde, adipic acid and 2-deoxyguanosine levels were decreased in patients with GAgP. In the gingival crevicular fluid samples, noradrenaline, uridine, α-tocopherol, dehydroascorbic acid, xanthine, galactose, glucose-1-phosphate and ribulose-5-phosphate levels were increased in patients with GAgP, while thymidine, glutathione and ribose-5-phosphate levels were decreased.

CONCLUSION

The metabolomics analysis by gas chromatography-mass spectrometry is an effective and minimally non-invasive way to differentiate the metabolites characteristic of patients with GAgP. Both serum and gingival crevicular fluid metabolomics are significantly different between patients with GAgP and healthy controls. These metabolic profiles have great potential in detecting GAgP and helping to understand its underlying mechanisms.

Systematic biology analysis on photosynthetic carbon metabolism of maize leaf following sudden heat shock under elevated CO2

Plants would experience more complex environments, such as sudden heat shock (SHS) stress combined with elevated CO₂ in the future, and might adapt to this stressful condition by optimizing photosynthetic carbon metabolism (PCM). It is interesting to understand whether this acclimation process would be altered in different genotypes of maize under elevated CO₂, and which metabolites represent key indicators reflecting the photosynthetic rates (P_N) following SHS. Although B76 had greater reduction in P_N during SHS treatment, our results indicated that P_N in genotype B76, displayed faster recovery after SHS treatment under elevated CO₂ than in genotype B106. Furthermore, we employed a stepwise feature extraction approach by partial linear regression model. Our findings demonstrated that 9 key metabolites over the total (35 metabolites) can largely explain the variance of P_N during recovery from SHS across two maize genotypes and two CO₂ grown conditions. Of these key metabolites, malate, valine, isoleucine, glucose and starch are positively correlated with recovery pattern of P_N. Malate metabolites responses to SHS were further discussed by incorporating with the activities and gene expression of three C₄ photosynthesis-related key enzymes. We highlighted the importance of malate metabolism during photosynthesis recovery from short-term SHS, and data integration analysis to better comprehend the regulatory framework of PCM in response to abiotic stress.

Activation of choline kinase drives aberrant choline metabolism in esophageal squamous cell carcinomas

Esophageal squamous cell carcinoma (ESCC) is a major health threat worldwide. Research focused on molecular events associated with ESCC carcinogenesis for diagnosis, treatment and prevention is needed. Our goal is to discover novel biomarkers and investigate the underlying molecular mechanisms of ESCC progression by employing a global metabolomic approach. Sera from 34 ESCC patients and 32 age and sex matched healthy controls were profiled using two-dimensional liquid chromatography-mass spectrometry (2D LC-MS). We identified 120 differential metabolites in ESCC patient serums compared to healthy controls. Several amino acids, serine, arginine, lysine and histidine were significantly changed in ESCC patients. Most importantly, we found dysregulated lipid metabolism as an important characteristic in ESCC patients. Several free fat acids (FFA) and carnitines were found down-regulated in ESCC patients. Choline was significantly increased and phosphatidylcholines (PC) were significantly decreased in ESCC serum. The high expression of choline and low expression of total PC in patient serum were associated with the high expression of choline kinase (Chok) and activated Kennedy pathway in ESCC cells. Chok expression can serve as a significant biomarker for ESCC prognosis. In conclusion, metabolite profiles in the ESCC patient serum were significantly different from those in the healthy controls. Phosphatidylcholines and Chok, the key enzyme in the PC metabolism pathway, may serve as novel biomarkers for ESCC.