In-depth mapping carboxylic acid metabolome reveals the potential biomarkers in colorectal cancer through characteristic fragment ions and metabolic flux

Polar metabolomics using trichloroacetic acid extraction and porous graphitic carbon stationary phase

INTRODUCTION

Accurately identifying and quantifying polar metabolites using untargeted metabolomics has proven challenging in comparison to mid to non-polar metabolites. Hydrophilic interaction chromatography and gas chromatography-mass spectrometry are predominantly used to target polar metabolites.

OBJECTIVES

This study aims to demonstrate a simple one-step extraction combined with liquid chromatography-mass spectrometry (LC-MS) that reliably retains polar metabolites.

METHODS

The method involves a MilliQ + 10% trichloroacetic acid extraction from 6 healthy individuals serum, combined with porous graphitic carbon liquid chromatography-mass spectrometry (LC-MS). The coefficient of variation (CV) assessed retention reliability of polar metabolites with logP as low as - 9. QreSS (Quantification, Retention, and System Suitability) internal standards determined the method's consistency and recovery efficiency.

RESULTS

The method demonstrated reliable retention (CV < 0.30) of polar metabolites within a logP range of - 9.1 to 5.6. QreSS internal standards confirmed consistent performance (CV < 0.16) and effective recovery (70-130%) of polar to mid-polar metabolites. Quality control dilution series demonstrated that ~ 80% of annotated metabolites could be accurately quantified (Pearson's correlation coefficient > 0.80) within their concentration range. Repeatability was demonstrated through clustering of repeated extractions from a single sample.

CONCLUSION

This LC-MS method is better suited to covering the polar segment of the metabolome than current methods, offering a reliable and efficient approach for accurate quantification of polar metabolites in untargeted metabolomics.

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.

Ganoderma lucidum Polysaccharide Supplementation Significantly Activates T-Cell-Mediated Antitumor Immunity and Enhances Anti-PD-1 Immunotherapy Efficacy in Colorectal Cancer

Ganoderma lucidum polysaccharide (GLP) is a prebiotic with immunomodulatory effects. However, the therapeutic potential of GLP in tumor immunotherapy has not been fully explored, especially in T cell-mediated antitumor immunity. In this study, we found that GLP significantly inhibited tumor growth and activated antitumor immunity in colorectal cancer (CRC). In the spleens and tumor tissues, the proportion of cytotoxic CD8+T cells and Th1 helper cells increased, while immunosuppressive Tregs decreased. Additionally, microbiota dysbiosis was alleviated by GLP, and short-chain fatty acid production was increased. Meanwhile, GLP decreased the ratio of kynurenine and tryptophan (Kyn/Trp) in the serum, which contributed to antitumor immunity of T cells. More importantly, the combination of GLP and the immune checkpoint inhibitor anti-PD-1 monoclonal antibody further enhanced the efficacy of anti-PD-1 immunotherapy. Thus, GLP as a prebiotic has the potential to be used in tumor immunotherapy.

Identification and validation of key miRNAs and a microRNA-mRNA regulatory network associated with liver cancer

MiRNAs play crucial regulatory roles in the growth and development of tumor cells by serving as carriers of post-transcriptional regulatory information derived from genes. Investigating the potential function and clinical significance of miRNA-mediated mRNA regulatory networks in liver cancer can offer novel insights and therapeutic strategies for the treatment of this disease. We identified 300 differentially expressed miRNAs, and five miRNAs were identified to be correlated with overall survival and could be used as an independent prognostic. GO enrichment analysis mainly included carboxylic acid biosynthesis, organic acid biosynthesis, peroxisomal membrane, microsomal membrane, DNA binding, C-acyltransferase activity, etc. KEGG enrichment analysis showed that the pathways of target genes related to liver cancer were mainly focused on butyric acid metabolism and partial amino acid metabolism. Eight of the top 10 HUB genes were associated with prognosis, and the expression of four genes was positively correlated with prognosis, of which ABAT, BHMT, and SHMT1 were target genes of hsa-miR-5003-3p. MiR-5003-3p inhibits ABAT/BHMT/SHMT1 expression, thereby promoting liver cancer development. Overall, our study provides new ideas for the treatment of liver cancer, and these five miRNAs may be independent prognostic biomarkers and therapeutic targets for liver cancer patients. And miR-5003-3p may be a critical factor in the mechanism of liver cancer development.

The fusion of multi-omics profile and multimodal EEG data contributes to the personalized diagnostic strategy for neurocognitive disorders

BACKGROUND

The increasing prevalence of neurocognitive disorders (NCDs) in the aging population worldwide has become a significant concern due to subjectivity of evaluations and the lack of precise diagnostic methods and specific indicators. Developing personalized diagnostic strategies for NCDs has therefore become a priority.

RESULTS

Multimodal electroencephalography (EEG) data of a matched cohort of normal aging (NA) and NCDs seniors were recorded, and their faecal samples and urine exosomes were collected to identify multi-omics signatures and metabolic pathways in NCDs by integrating metagenomics, proteomics, and metabolomics analysis. Additionally, experimental verification of multi-omics signatures was carried out in aged mice using faecal microbiota transplantation (FMT). We found that NCDs seniors had low EEG power spectral density and identified specific microbiota, including Ruminococcus gnavus, Enterocloster bolteae, Lachnoclostridium sp. YL 32, and metabolites, including L-tryptophan, L-glutamic acid, gamma-aminobutyric acid (GABA), and fatty acid esters of hydroxy fatty acids (FAHFAs), as well as disturbed biosynthesis of aromatic amino acids and TCA cycle dysfunction, validated in aged mice. Finally, we employed a support vector machine (SVM) algorithm to construct a machine learning model to classify NA and NCDs groups based on the fusion of EEG data and multi-omics profiles and the model demonstrated 92.69% accuracy in classifying NA and NCDs groups.

CONCLUSIONS

Our study highlights the potential of multi-omics profiling and EEG data fusion in personalized diagnosis of NCDs, with the potential to improve diagnostic precision and provide insights into the underlying mechanisms of NCDs. Video Abstract.

Mass filtering combined with photochemical derivatization enables high throughput mass spectrometric analysis of unsaturated phosphatidylcholine isomers

Phosphatidylcholines (PCs) are closely related to coronary heart disease, such as myocardial infarction. The analysis of the deep structure of PCs is of great significance for exploring the effects of exercise rehabilitation and lipid metabolism. Here, we present a mass filtering combined with photochemical derivatization method for rapid screening and accurate identification of the CC position and sn-location isomer of PCs. This method is simple to execute and easily implementable for routine analysis. The accurate qualitative and quantitative analysis of PCs and isomers facilitates the discovery of biomarkers for exercise rehabilitation of patients with myocardial infarction.

The association of serum serine levels with the risk of incident cancer: results from a nested case-control study

Background: Cancer is associated with the dysregulation of serum serine levels, and tumor growth is supported by increased serine biosynthesis. This study aims to explore the association of serum serine levels with incident cancer risk in Chinese hypertensive adults. Materials and methods: 1391 patients with incident cancer and 1391 matched controls in terms of age, sex, and residence with cases in a 1 : 1 ratio were included in this nested case-control study. The serum serine concentrations were determined by liquid chromatography with tandem quadrupole mass spectrometry (LC-MS/MS) at the baseline. The associations of serum serine levels with the risk of overall, digestive system, non-digestive system, and lung cancers (the most common type) were assessed by conditional logistic regression. Results: When serum serine concentration was assessed as quartiles, a significantly higher risk of total cancer (OR = 1.32; 95% CI: 1.01-1.71; P = 0.038) was found in participants in the highest quartile (≥17.68 μg mL-1) compared with participants in the lowest quartile (<13.27 μg mL-1). Similar results were also observed for non-digestive system and lung cancers, but not for digestive system cancers. Significant associations of serum with overall cancer risk were found among all age subgroups, men, non-smokers, non-drinkers, and individuals with lower folic acid levels. Conclusion: High serum serine concentrations were associated with an increased risk of overall, non-digestive system, and lung cancers among Chinese hypertensive adult patients.

Identification of polyunsaturated fatty acids as potential biomarkers of osteoarthritis after sodium hyaluronate and mesenchymal stem cell treatment through metabolomics

Introduction: Osteoarthritis (OA) is a prevalent joint disorder worldwide. Sodium hyaluronate (SH) and mesenchymal stem cells (MSCs) are promising therapeutic strategies for OA. Previous studies showed they could improve knee function and clinical symptoms of OA. However, the mechanism of the therapeutic effects on the improvement of OA has not been clearly explained. Methods: In our study, we used a technique called 5-(diisopropylamino)amylamine derivatization liquid chromatography coupled with mass spectrometry to find the metabolites in OA synovial fluid under different treatments. Results and Discussion: After looking into the metabolomics, we discovered that SH and MSC treatment led to the downregulation of ω-6 polyunsaturated fatty acids (PUFAs) and the upregulation of ω-3 PUFAs. Significantly, the contents of 5(S)-HETE, PGA2, PGB2, and PGJ2 were lower in the MSC group than in the SH group after quantification using 5-(diisopropylamino)amylamine derivatization-UHPLC-QQQ-MS. This is the first report on the relationship of 11(S)-HETE, PGA2, PGB2, PGF2β, 11β-PGF2α, and DK-PGE2 with OA. Moreover, the correlation analysis of metabolites and inflammation factors showed the positive association of ω-6 PUFAs with pro-inflammation cytokines, and of ω-3 PUFAs with anti-inflammation cytokines. Our results indicated the therapeutic effect of SH and MSCs in patients with OA. In addition, this reliable metabolic approach could uncover novel biomarkers to treat OA.

Carboxyl-containing components delineation via feature-based molecular networking: A key to processing conditions of fermented soybean

Carboxyl-containing components (CCCs) was the key chemical markers for fermented soybean, whose composition and content would be dramatically changed during the fermentation processes. To select the optimal fermented conditions, a rapid and sensitive 5-(diisopropylamino)amylamine derivatization, ultra-high performance liquid chromatography-quadrupole-time-of-flight/mass spectrometry and feature-based molecular networking method was established for determination CCCs and the developed method was successfully applied to compare the dynamic changes of CCCs under different processing conditions. A total of 120 components were identified, the optimum fermentation conditions were the temperature at 30 °C, 50% humidity, with a 2-hour steaming time. Sixteen chemical markers with significant differences were screened. Furthermore, molecular docking technology was used to verify the antiperoxidative effect of these chemical markers. Accordingly, we focused on the high-content, little-studied active CCCs rather than the low-content and well-studied flavonoids. This study was helpful for the nutraceutical development and contributed scientific basis to further exploring quality evaluation of fermented food.

Urinary volatile organic compounds for colorectal cancer screening, a systematic review and meta-analysis

BACKGROUND

The faecal immunochemical test (FIT) suffers from suboptimal performance and participation in colorectal cancer (CRC) screening. Urinary volatile organic compounds (VOCs) may be a useful alternative. We aimed to determine the diagnostic potential of urinary VOCs for CRC/adenomas. By relating VOCs to known pathways, we aimed to gain insight into the pathophysiology of colorectal neoplasia.

METHODS

A systematic search was performed in PubMed, EMBASE and Web of Science. Original studies on urinary VOCs for CRC/adenoma detection with a control group were included. QUADAS-2 tool was used for quality assessment. Meta-analysis was performed by adopting a bivariate model for sensitivity/specificity. Fagan's nomogram estimated the performance of combined FIT-VOC. Neoplasm-associated VOCs were linked to pathways using the KEGG database.

RESULTS

Sixteen studies-involving 837 CRC patients and 1618 controls-were included; 11 performed chemical identification and 7 chemical fingerprinting. In all studies, urinary VOCs discriminated CRC from controls. Pooled sensitivity and specificity for CRC based on chemical fingerprinting were 84% (95% CI 73-91%) and 70% (95% CI 63-77%), respectively. The most distinctive individual VOC was butanal (AUC 0.98). The estimated probability of having CRC following negative FIT was 0.38%, whereas 0.09% following negative FIT-VOC. Combined FIT-VOC would detect 33% more CRCs. In total 100 CRC-associated urinary VOCs were identified; particularly hydrocarbons, carboxylic acids, aldehydes/ketones and amino acids, and predominantly involved in TCA-cycle or alanine/aspartate/glutamine/glutamate/phenylalanine/tyrosine/tryptophan metabolism, which is supported by previous research on (colorectal)cancer biology. The potential of urinary VOCs to detect precancerous adenomas or gain insight into their pathophysiology appeared understudied.

CONCLUSION

Urinary VOCs hold potential for non-invasive CRC screening. Multicentre validation studies are needed, especially focusing on adenoma detection. Urinary VOCs elucidate underlying pathophysiologic processes.

Identification of proline, 1-pyrroline-5-carboxylate and glutamic acid as biomarkers of depression reflecting brain metabolism using carboxylomics, a new metabolomics method

AIM

Depression is a psychiatric disease which is accompanied by metabolic disorder. Though depression has been widely studied, its metabolism is yet to be illustrated. We aimed to manifest the underlying mechanisms to diagnose depression.

METHODS

One hundred thirty serum samples, including 65 patients and 65 healthy controls from different hospitals (training and validation cohorts), were recruited into the research. Sensitive Profiling for ChemoSelective Derivatization Carboxylomics (SPCSDCarboxyl) was applied to deeply hunt for the differential metabolites. Then, the serum, CSF, and hippocampus from depression rat models (CUMS group) were used to further confirm the results. Additionally, the co-occurrence between enzymes and biomarkers, as well as the combinatorial marker panel and the correlation of biomarkers among serum, CSF, or hippocampus were elucidated.

RESULTS

Two hundred eight metabolites were identified from the sera of patients. Proline, 1-pyrroline-5-carboxylate (P5C), and glutamic acid could discriminate patients from healthy humans and were confirmed to be the potential biomarkers. After further validation through CUMS rats, proline, and P5C were enriched, while glutamic acid was depleted in the CUMS group. The co-occurrence analysis of enzymes and biomarkers indicated that they could be used for the diagnosis of depression. Moreover, the combinatorial marker panel and the correlation analysis of biomarkers between serum and CSF or between serum and hippocampus revealed that serum could be an alternative approach to directly reflect the potential physiological mechanisms and diagnose depression instead of brain samples.

CONCLUSION

These integrated methods may facilitate the identification of biomarkers and help manifest the underlying mechanisms of depression.

NMR-based isotope editing, chemoselection and isotopomer distribution analysis in stable isotope resolved metabolomics

NMR is a very powerful tool for identifying and quantifying compounds within complex mixtures without the need for individual standards or chromatographic separation. Stable Isotope Resolved Metabolomics (or SIRM) is an approach to following the fate of individual atoms from precursors through metabolic transformation, producing an atom-resolved metabolic fate map. However, extracts of cells or tissue give rise to very complex NMR spectra. While multidimensional NMR experiments may partially overcome the spectral overlap problem, additional tools may be needed to determine site-specific isotopomer distributions. NMR is especially powerful by virtue of its isotope editing capabilities using NMR active nuclei such as 13C, 15N, 19F and 31P to select molecules containing just these atoms in a complex mixture, and provide direct information about which atoms are present in identified compounds and their relative abundances. The isotope-editing capability of NMR can also be employed to select for those compounds that have been selectively derivatized with an NMR-active stable isotope at particular functional groups, leading to considerable spectral simplification. Here we review isotope analysis by NMR, and methods of chemoselection both for spectral simplification, and for enhanced isotopomer analysis.

In-depth profiling of carboxyl compounds in Chinese Baijiu based on chemical derivatization and ultrahigh-performance liquid chromatography coupled to high-resolution mass spectrometry

•

A systematic strategy for detection and annotation of carboxyl compound was developed.

•

197 carboxyl compounds were detected in Chinese Baijiu for the first time.

•

Annotation was based on MS1, t_R, in-silico MS/MS, and characteristic fragments.

•

Three of carboxyl compounds were newly identified in Chinese Baijiu.

•

Distribution of carboxyl compounds in Baijiu with different flavors was revealed.

Carboxyl compounds have a significant influence on the flavor of Chinese Baijiu. However, because of the structural diversity and low concentration, the deep profiling of carboxyl compounds in Chinese Baijiu is still challenging. In this work, a systematic method for comprehensive analysis of carboxyl compounds in Chinese Baijiu was established. After derivatized under optimized conditions, 197 p-dimethylaminophenacyl bromide-derived carboxylic compounds were annotated by multidimensional information including accurate mass, predicted t_R, in-silico MS/MS, and diagnostic ions for the first time. In addition, 48 of the 197 carboxyl compounds were positively identified, and three of them were newly identified in Chinese Baijiu. Moreover, we found the number and the concentration of carboxyl compounds in sauce-flavor Baijiu were more abundant than in strong-flavor Baijiu. This work provides a novel method for the analysis of carboxyl compounds in Baijiu and other complex samples.

A prognostic Risk Score model for oral squamous cell carcinoma constructed by 6 glycolysis-immune-related genes

Background

Oral squamous cell carcinoma (OSCC) is the most frequent tumor of the head and neck. The glycolysis-related genes and immune-related genes have been proven prognostic values in various cancers. Our study aimed to test the prognostic value of glycolysis-immune-related genes in OSCC.

Methods

Data of OSCC patients were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Enrichment analysis was applied to the glycolysis- and immune-related genes screened by differential expression analysis. Univariate Cox and LASSO Cox analyses were used to filtrate the genes related to the prognosis of OSCC and to construct Risk Score model.

Results

A Risk Score model was constructed by six glycolysis-immune-related genes (including ALDOC, VEGFA, HRG, PADI3, IGSF11 and MIPOL1). High risk OSCC patients (Risk Score >−0.3075) had significantly worse overall survival than that of low risk patients (Risk Score <−0.3075).

Conclusions

The Risk Score model constructed basing on 6 glycolysis-immune-related genes was reliable in stratifying OSCC patients with different prognosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-022-02358-0.

Microbiota drive insoluble polysaccharides utilization via microbiome-metabolome interplay during Pu-erh tea fermentation

Polysaccharides are abundant components in Pu-erh tea, yet the utilization of insoluble polysaccharides under the actions of microbiota has rarely been studied. The aim of this work was to study how insoluble polysaccharides were utilized during fermentation through the investigation of the variations and correlation of microbiota with polysaccharides degradation products. Genomics study revealed the significant changes of microbiota. Metabolomics analysis showed monosaccharides (types 1 and 3) were consumed during early and middle fermentation stages, while carboxylic acids and other monosaccharides (type 2) were accumulated at middle and late pile-fermentation stages. Correlation revealed that type 1 and 3 monosaccharides, which act as energy providers, were positively associated with Aspergillus, while type 2 monosaccharides possessing multiple bioactivities and carboxylic acids influencing tea taste were positively related to Rasamsonia, Thermomyces, Bacillaceae, and Lactobacillaceae. This study would be beneficial to improve production efficiency and provide basis for quality control of Pu-erh tea fermentation.

Investigation and dynamic profiling of oligopeptides, free amino acids and derivatives during Pu-erh tea fermentation by ultra-high performance liquid chromatography tandem mass spectrometry

Microbial fermentation is the critical step of Pu-erh tea manufacture, which will induce dramatic changes in the chemical composition and content of tea. In this research, we applied multi-methods based on UHPLC-Q-TOF/MS to profile the dynamic changes of oligopeptides, free amino acids, and derivatives (OPADs) during Pu-erh fermentation and predicted the potential bioactivities in silico. A total of 60 oligopeptides, 18 free amino acids, and 42 amino acid derivatives were identified, and the contents of most of them decreased after fermentation. But several N-acetyl amino acids increased 7-36 times after fermentation, and they might be the potential inhibitors of neurokinin-1 receptor. Moreover, the results of metamicrobiology showed Aspergillus niger and Aspergillus luchuensis were more prominent to metabolize protein, oligopeptides, and amino acids. Overall, these findings provide valuable insights about dynamic variations of OPADs during Pu-erh tea fermentation and are beneficial for guiding practical fermentation and quality control of Pu-erh tea.

Dynamic changes of phenolic acids and antioxidant activity of Citri Reticulatae Pericarpium during aging processes

Citri reticulatae pericarpium (CRP) shows multiple bioactivities, including antioxidant, anti-tumor, and anti-inflammation. The folk proverb "CRP, the older, the better" means storing for longer time would improve its quality, which attributed to the influence of bioactive compounds. The aim of this work was to study which compounds are the factors that long storage would influence the quality of CRP. 161 compounds, including 65 flavonoids, 51 phenolic acids, 27 fatty acids, and 18 amino acids were identified through derivatization and non-derivatization liquid chromatography mass spectrometry approaches. Their dynamic changes indicated phenolic acids, which were reported to have various activities, were the main increased components. Furthermore, the representative phenolic acids were quantified and correlation analysis between their contents and antioxidant activity implicated they were the possible indicators that long storage would improve CRP quality. The results would provide basis for quality control of CRP during storage.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.