Nuclear magnetic resonance-based tissue metabolomic analysis clarifies molecular mechanisms of gastric carcinogenesis

Integrating metabolomics and network pharmacology to investigate Mu Jin Powder prevents ethanol-induced gastric ulcer in rats

ETHNOPHARMACOLOGICAL RELEVANCE

Gastric ulcer (GU) is a common multifactorial gastrointestinal disorder, affecting millions of people worldwide. Mu Jin Powder (MJP), a renowned herbal pair, was recorded in Yizong Jinjian by Wu Qian during the Qing dynasty. This combination has been integrated into traditional Chinese medicine (TCM) prescriptions for gastrointestinal diseases, particularly GU, and has demonstrated significant results in modern medicine studies. However, the specific advantages of MJP for GU and its underlying mechanisms remain insufficiently understood, requiring further investigation.

AIM OF THE STUDY

To assess the preventive effects of MJP on ethanol-induced gastric mucosal injury and elucidate its underlying mechanisms.

MATERIALS AND METHODS

This study was based on ethanol induced SD rat model to elucidate the pharmacological effects of MJP. The chemical components of MJP and the absorbed components in the serum of treated rats were identified by UPLC-Q-TOF-MS. Serum metabolomics and Network pharmacology were applied to investigate the potential mechanisms of MJP against GU, and the mechanistic pathways were verified through PCR and Western blot analyses.

RESULTS

In vivo pharmacological experiments demonstrated that MJP significantly reduced ulcer area and improved the histopathological features of gastric tissues. Fifty-three chemical components were determined in MJP, and 18 absorbed components were detected in the serum of treated rats for the first time. Non-targeted serum metabolomics revealed 28 significantly altered differential metabolites, most of which were modulated and normalized by MJP. Comprehensive network pharmacology and metabolomics analyses indicated that MJP exerted anti-GU effects by intervening in 5 key target proteins (PTG2, CHRNA7, CA1, PTG1, CASP3, and AKT1) and regulating differential metabolites. PCR and Western blot analyses suggested that MJP may inhibit the PI3K/Akt/NF-κB pathway to prevent ethanol-induced gastric ulcers.

CONCLUSIONS

Mu Jin Powder effectively ameliorates ethanol-induced gastric ulcers in rats, potentially by inhibiting the PI3K/Akt/NF-κB pathway.

Targeting amino acid metabolism to inhibit gastric cancer progression and promote anti-tumor immunity: a review

The incidence of gastric cancer remains high and poses a serious threat to human health. Recent comprehensive investigations into amino acid metabolism and immune system components within the tumor microenvironment have elucidated the functional interactions between tumor cells, immune cells, and amino acid metabolism. This study reviews the characteristics of amino acid metabolism in gastric cancer, with a particular focus on the metabolism of methionine, cysteine, glutamic acid, serine, taurine, and other amino acids. It discusses the relationship between these metabolic processes, tumor development, and the body's anti-tumor immunity, and analyzes the importance of targeting amino acid metabolism in gastric cancer for chemotherapy and immunotherapy.

Integrated gene-metabolite association network analysis reveals key metabolic pathways in gastric adenocarcinoma

Gastric adenocarcinoma is one of the most death cause cancers worldwide. Metabolomics is an effective approach for investigating the occurrence and progression of cancer and detecting prognostic biomarkers by studying the profiles of small bioactive molecules. To fully decipher the functional roles of the disrupted metabolites that modulate the cellular mechanism of gastric cancer, integrated gene-metabolite association network methods are critical to map the associations between metabolites and genes. In this study, we constructed a knowledge-based gene-metabolite association network of gastric cancer using the dysregulated metabolites and genes between gastric cancer patients and control group. The topological pathway analysis and gene-protein-metabolite-disease association analysis revealed four key gene-metabolite pathways which include eleven metabolites associated with modulated genes. The integrated gene-metabolite association network enables mechanistic investigation and provides a comprehensive overview regarding the investigation of molecular mechanisms of gastric cancer, which facilitates the in-depth understanding of metabolic biomarker roles in gastric cancer.

Metabolites, Healthy Lifestyle, and Polygenic Risk Score Associated with Upper Gastrointestinal Cancer: Findings from the UK Biobank Study

Previous metabolomics studies have highlighted the predictive value of metabolites on upper gastrointestinal (UGI) cancer, while most of them ignored the potential effects of lifestyle and genetic risk on plasma metabolites. This study aimed to evaluate the role of lifestyle and genetic risk in the metabolic mechanism of UGI cancer. Differential metabolites of UGI cancer were identified using partial least-squares discriminant analysis and the Wilcoxon test. Then, we calculated the healthy lifestyle index (HLI) score and polygenic risk score (PRS) and divided them into three groups, respectively. A total of 15 metabolites were identified as UGI-cancer-related differential metabolites. The metabolite model (AUC = 0.699) exhibited superior discrimination ability compared to those of the HLI model (AUC = 0.615) and the PRS model (AUC = 0.593). Moreover, subgroup analysis revealed that the metabolite model showed higher discrimination ability for individuals with unhealthy lifestyles compared to that with healthy individuals (AUC = 0.783 vs 0.684). Furthermore, in the genetic risk subgroup analysis, individuals with a genetic predisposition to UGI cancer exhibited the best discriminative performance in the metabolite model (AUC = 0.770). These findings demonstrated the clinical significance of metabolic biomarkers in UGI cancer discrimination, especially in individuals with unhealthy lifestyles and a high genetic risk.

High-Throughput Metabolic Pattern Screening Strategy for Early Colorectal and Gastric Cancers Based on Covalent Organic Frameworks-Assisted Laser Desorption/Ionization Mass Spectrometry

Precise early diagnosis and staging are conducive to improving the prognosis of colorectal cancer (CRC) and gastric cancer (GC) patients. However, due to intrusive inspections and limited sensitivity, the prevailing diagnostic methods impede precisely large-scale screening. In this work, we reported a high-throughput serum metabolic patterns (SMP) screening strategy based on covalent organic frameworks-assisted laser desorption/ionization mass spectrometry (hf-COFsLDI-MS) for early diagnosis and staging of CRC and GC. Notably, 473 high-quality SMP were extracted without any tedious sample pretreatment and coupled with multiple machine learning algorithms; the area under the curve (AUC) value is 0.938 with 96.9% sensitivity for early CRC diagnosis, and the AUC value is 0.974 with 100% sensitivity for early GC diagnosis. Besides, the discrimination of CRC and GC is accomplished with an AUC value of 0.966 for the validation set. Also, the screened-out features were identified by MS/MS experiments, and 8 metabolites were identified as the biomarkers for CRC and GC. Finally, the corresponding disordered metabolic pathways were revealed, and the staging of CRC and GC was completed. This work provides an alternative high-throughput screening strategy for CRC and GC and highlights the potential of metabolic molecular diagnosis in clinical applications.

Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer

Gastric cancer (GC) represents a significant burden of cancer-related mortality worldwide, underscoring an urgent need for the development of early detection strategies and precise postoperative interventions. However, the identification of non-invasive biomarkers for early diagnosis and patient risk stratification remains underexplored. Here, we conduct a targeted metabolomics analysis of 702 plasma samples from multi-center participants to elucidate the GC metabolic reprogramming. Our machine learning analysis reveals a 10-metabolite GC diagnostic model, which is validated in an external test set with a sensitivity of 0.905, outperforming conventional methods leveraging cancer protein markers (sensitivity < 0.40). Additionally, our machine learning-derived prognostic model demonstrates superior performance to traditional models utilizing clinical parameters and effectively stratifies patients into different risk groups to guide precision interventions. Collectively, our findings reveal the metabolic landscape of GC and identify two distinct biomarker panels that enable early detection and prognosis prediction respectively, thus facilitating precision medicine in GC.

Abnormal arginine synthesis confers worse prognosis in patients with middle third gastric cancer

BACKGROUND

Gastric cancer at different locations has distinct prognoses and biological behaviors, but the specific mechanism is unclear.

METHODS

Non-targeted metabolomics was performed to examine the differential metabolite phenotypes that may be associated with the effects of tumor location on the prognosis of gastric cancer. And silencing of the rate-limiting enzyme to evaluate the effect of abnormal changes in metabolic pathway on the functional biological assays of gastric cancer cells HGC-27 and MKN28.

RESULTS

In a retrospective study of 94 gastric cancer patients, the average survival time of patients with gastric cancer in the middle third of the stomach was significantly lower than that of patients with gastric cancer in other locations (p < 0.05). The middle third location was also found to be an independent risk factor for poor prognosis (HR = 2.723, 95%CI 1.334-5.520), which was closely associated with larger tumors in this location. Non-targeted metabolomic analysis showed that the differential metabolites affected 16 signaling pathways including arginine synthesis, retrograde endocannabinoid signaling, arginine biosynthesis, and alanine and aspartate and glutamate metabolism between gastric cancer and normal tissue, as well as between tumors located in the middle third of the stomach and other locations. Argininosuccinate synthetase 1 (ASS1), the rate-limiting enzyme of the arginine biosynthesis pathway, catalyzes the production of argininosuccinic acid. Here, knockdown of ASS1 significantly inhibited the proliferation, colony formation, and migration/invasion of gastric cancer cells, and promoted apoptosis.

CONCLUSIONS

Our study suggests that abnormal arginine synthesis may lead to larger tumor size and worse prognosis in gastric cancer located in the middle third position of the stomach. These findings may provide the basis for the stratification and targeted treatment of gastric cancer in different locations.

H2S-Synthesizing Enzymes Are Putative Determinants in Lung Cancer Management toward Personalized Medicine

Lung cancer is a lethal disease with no truly efficient therapeutic management despite the progresses, and metabolic profiling can be a way of stratifying patients who may benefit from new therapies. The present study is dedicated to profiling cysteine metabolic pathways in NSCLC cell lines and tumor samples. This was carried out by analyzing hydrogen sulfide (H2S) and ATP levels, examining mRNA and protein expression patterns of cysteine catabolic enzymes and transporters, and conducting metabolomics analysis using nuclear magnetic resonance (NMR) spectroscopy. Selenium-chrysin (SeChry) was tested as a therapeutic alternative with the aim of having an effect on cysteine catabolism and showed promising results. NSCLC cell lines presented different cysteine metabolic patterns, with A549 and H292 presenting a higher reliance on cystathionine β-synthase (CBS) and cystathionine γ-lyase (CSE) to maintain H2S levels, while the PC-9 cell line presented an adaptive behavior based on the use of mercaptopyruvate sulfurtransferase (MST) and cysteine dioxygenase (CDO1), both contributing to the role of cysteine as a pyruvate source. The analyses of human lung tumor samples corroborated this variability in profiles, meaning that the expression of certain genes may be informative in defining prognosis and new targets. Heterogeneity points out individual profiles, and the identification of new targets among metabolic players is a step forward in cancer management toward personalized medicine.

Bovine Omasum-Inspired Interfacial Carbon-Based Nanocomposite for Saliva Metabolic Screening of Gastric Cancer

Gastric cancer is one of the most common malignant digestive cancers, and its diagnostic has still faced challenges based on metabolic analysis due to complex sample pretreatment and low metabolite abundance. In this study, inspired by the structure of bovine omasum, we in situ synthesized a novel interfacial carbon-based nanocomposite of graphene supported nickel nanoparticles-encapsulated in the nitrogen-doped carbon nanotube (Ni/N-CNT/rGO), which was served as a novel matrix with enhanced ionization efficiency for the matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) saliva metabolic analysis of gastric cancer. Benefiting from its high sp² graphitic degree, large surface area, strong UV absorption, and rich active sites, Ni/N-CNT/rGO matrix exhibited excellent performances of reproducibility, coverage, salt-tolerance, sensitivity, and adsorption ability in MALDI-TOF MS. The differential scanning calorimetry (DSC) and thermal conversion behaviors explained the highly efficient LDI mechanism. Based on saliva metabolic fingerprints, Ni/N-CNT/rGO assisted LDI MS with cross-validation analysis could successfully distinguish gastric cancer patients from healthy controls through the screening of four potential biomarkers with an accuracy of 92.50%, specificity of 88.03%, and sensitivity of 97.12%. This work provided a fast and sensitive MS sensing platform for the metabolomics characterization of gastric cancer and might have potential value for precision medicine in the future.

Metabolic codependencies in the tumor microenvironment and gastric cancer: Difficulties and opportunities

Oncogenesis and the development of tumors affect metabolism throughout the body. Metabolic reprogramming (also known as metabolic remodeling) is a feature of malignant tumors that is driven by oncogenic changes in the cancer cells themselves as well as by cytokines in the tumor microenvironment. These include endothelial cells, matrix fibroblasts, immune cells, and malignant tumor cells. The heterogeneity of mutant clones is affected by the actions of other cells in the tumor and by metabolites and cytokines in the microenvironment. Metabolism can also influence immune cell phenotype and function. Metabolic reprogramming of cancer cells is the result of a convergence of both internal and external signals. The basal metabolic state is maintained by internal signaling, while external signaling fine-tunes the metabolic process based on metabolite availability and cellular needs. This paper reviews the metabolic characteristics of gastric cancer, focusing on the intrinsic and extrinsic mechanisms that drive cancer metabolism in the tumor microenvironment, and interactions between tumor cell metabolic changes and microenvironment metabolic changes. This information will be helpful for the individualized metabolic treatment of gastric cancers.

Microbiota and metabolites alterations in proximal and distal gastric cancer patients

Background

Globally, gastric cancer is the third most common cancer and the third leading cause of cancer death. Proximal and distal gastric cancers have distinct clinical and biological behaviors. The microbial composition and metabolic differences in proximal and distal gastric cancers have not been fully studied and discussed.

Methods

In this study, the gastric microbiome of 13 proximal gastric cancer tissues, 16 distal gastric cancer tissues, and their matched non-tumor tissues were characterized using 16S rRNA amplicon sequencing. Additionally, 10 proximal gastric cancer tissues, 11 distal gastric cancer tissues, and their matched non-tumor tissues were assessed by untargeted metabolomics.

Results

There was no significant difference in microbial diversity and richness between the proximal and distal gastric cancer tissues. At the genus level, the abundance of Rikenellaceae_RC9_gut_group, Porphyromonas, Catonella, Proteus, Oribacterium, and Moraxella were significantly increased in Proximal T, whereas that of Methylobacterium_Methylorubrum was significantly increased in Distal T. The untargeted metabolomics analysis revealed 30 discriminative metabolites between Distal T and Distal N. In contrast, there were only 4 discriminative metabolites between Proximal T and Proximal N. In distal gastric cancer, different metabolites were scattered through multiple pathway, including the sphingolipid signaling pathway, arginine biosynthesis, protein digestion and absorption, alanine, aspartate and, glutamate metabolism, etc.In proximal gastric cancer, differential microbial metabolites were mainly related to hormone metabolism.

Conclusion

Methylobacterium-Methylorubrum was significantly increased in Distal T, positively correlated with cancer-promoting metabolites, and negatively correlated with cancer-inhibiting metabolites. Rikenellaceae_RC_gut_group was significantly increased in Proximal T and positively correlated with cancer-promoting metabolites. Further studies regarding the functions of the above-mentioned microorganisms and metabolites were warranted as the results may reveal the different mechanisms underlying the occurrence and development of proximal and distal gastric cancers and provide a basis for future treatments.

Importance

First, the differences in microbial composition and metabolites between the proximal and distal gastric cancers were described; then, the correlation between microbiota and metabolites was preliminarily discussed. These microbes and metabolites deserve further investigations as they may reveal the different mechanisms involved in the occurrence and development of proximal and distal gastric cancers and provide a basis for future treatments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03650-x.

Carbon Ion Radiotherapy Induce Metabolic Inhibition After Functional Imaging-Guided Simultaneous Integrated Boost for Prostate Cancer

Purpose

As local recurrence remains a challenge and the advantages of the simultaneous integrated boost (SIB) technique have been validated in photon radiotherapy, we applied the SIB technique to CIRT. The aim was to investigate the metabolomic changes of the CIRT with concurrent androgen deprivation therapy (ADT) in localized prostate cancer (PCa) and the unique metabolic effect of the SIB technique.

Material and Methods

This study enrolled 24 pathologically confirmed PCa patients. All patients went through CIRT with concurrent ADT. The gross target volume (GTV) boost was defined as positive lesions on both 68Ga-PSMA PET/CT and mpMRI images. Urine samples collected before and after CIRT were analyzed by the Q-TOF UPLC-MS/MS system. R platform and MetDNA were used for peak detection and identification. Statistical analysis and metabolic pathway analysis were performed on Metaboanalyst.

Results

The metabolite profiles were significantly altered after CIRT. The most significantly altered metabolic pathway is PSMA participated alanine, aspartate and glutamate metabolism. Metabolites in this pathway showed a trend to be better suppressed in the SIB group. A total of 11 identified metabolites were significantly discriminative between two groups and all of them were better down-regulated in the SIB group. Meanwhile, among these metabolites, three metabolites in DNA damage and repair related purine metabolism were down-regulated to a greater extent in the SIB group.

Conclusion

Metabolic dysfunction was one of the typical characteristics of PCa. CIRT with ADT showed a powerful inhibition of PCa metabolism, especially in PSMA participated metabolic pathway. The SIB CIRT showed even better performance on down-regulation of most metabolism than uniform-dose-distribution CIRT. Meanwhile, the SIB CIRT also showed its unique superiority to inhibit purine metabolism. PSMA PET/CT guided SIB CIRT showed its potentials to further benefit PCa patients.

Combined Microbiome and Metabolome Analysis Reveals a Novel Interplay Between Intestinal Flora and Serum Metabolites in Lung Cancer

As the leading cause of cancer death, lung cancer seriously endangers human health and quality of life. Although many studies have reported the intestinal microbial composition of lung cancer, little is known about the interplay between intestinal microbiome and metabolites and how they affect the development of lung cancer. Herein, we combined 16S ribosomal RNA (rRNA) gene sequencing and liquid chromatography-mass spectrometry (LC-MS) technology to analyze intestinal microbiota composition and serum metabolism profile in a cohort of 30 lung cancer patients with different stages and 15 healthy individuals. Compared with healthy people, we found that the structure of intestinal microbiota in lung cancer patients had changed significantly (Adonis, p = 0.021). In order to determine how intestinal flora affects the occurrence and development of lung cancer, the Spearman rank correlation test was used to find the connection between differential microorganisms and differential metabolites. It was found that as thez disease progressed, L-valine decreased. Correspondingly, the abundance of Lachnospiraceae_UCG-006, the genus with the strongest association with L-valine, also decreased in lung cancer groups. Correlation analysis showed that the gut microbiome and serum metabolic profile had a strong synergy, and Lachnospiraceae_UCG-006 was closely related to L-valine. In summary, this study described the characteristics of intestinal flora and serum metabolic profiles of lung cancer patients with different stages. It revealed that lung cancer may be the result of the mutual regulation of L-valine and Lachnospiraceae_UCG-006 through the aminoacyl-tRNA biosynthesis pathway, and proposed that L-valine may be a potential marker for the diagnosis of lung cancer.

NMR-Based Metabolomic Analysis of Sera in Mouse Models of CVB3-Induced Viral Myocarditis and Dilated Cardiomyopathy

Viral myocarditis (VMC) is an inflammatory heart condition which can induce dilated cardiomyopathy (DCM). However, molecular mechanisms underlying the progression of VMC into DCM remain exclusive. Here, we established mouse models of VMC and DCM by infecting male BALB/c mice with Coxsackievirus B3 (CVB3), and performed NMR-based metabonomic analyses of mouse sera. The mouse models covered three pathological stages including: acute VMC (aVMC), chronic VMC (cVMC) and DCM. We recorded ¹D ¹H-NMR spectra on serum samples and conducted multivariate statistical analysis on the NMR data. We found that metabolic profiles of these three pathological stages were distinct from their normal controls (CON), and identified significant metabolites primarily responsible for the metabolic distinctions. We identified significantly disturbed metabolic pathways in the aVMC, cVMC and DCM stages relative to CON, including: taurine and hypotaurine metabolism; pyruvate metabolism; glycine, serine and threonine metabolism; glycerolipid metabolism. Additionally, we identified potential biomarkers for discriminating a VMC, cVMC and DCM from CON including: taurine, valine and acetate for aVMC; glycerol, valine and leucine for cVMC; citrate, glycine and isoleucine for DCM. This work lays the basis for mechanistically understanding the progression from acute VMC to DCM, and is beneficial to exploitation of potential biomarkers for prognosis and diagnosis of heart diseases.

Tongue-coating microbiome as a cancer predictor: A scoping review

OBJECTIVE

The tongue microbiome has emerged as a non-invasive diagnostic and tracking prognostic tool in the detection of diseases mainly cancer. This scoping review aimed to identify the association between tongue microbiome and pre-cancer or cancer lesions.

DESIGN

A comprehensive electronic database search including PubMed, Web of Science, and Scopus was undertaken up to March 2021, without language or date restrictions. This review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline. All observational studies that compared microbial community on the dorsal surface of the tongue between cancer or precancerous cases and healthy controls using NGS techniques were included.

RESULTS

Of 274 records identified, nine studies were eligible to be included. Despite the inconsistent observations in terms of diversity and richness, most studies reported alteration in bacterial communities between pre-cancer or cancer cases and control groups. The bacterial profile among cases was so far correlated at the phylum level with a noticeable diverse degree at the genus level. The majority of included studies reported a higher abundance of certain kinds of microorganisms as compared to healthy participants including Firmicutes, Fusobacteria and Actinobacteria at phyla level as well as Streptococcus, Actinomyces, Leptotrichia, Campylobacter, and Fusobacterium at the genus level.

CONCLUSION

The alteration of the tongue microbial community has been associated with several diseases mainly cancer. So, the tongue microbiome may serve as a promising diagnostic tool or as a long-term monitor in precancerous or cancer cases.

NMR-Based Metabolomics Analysis Predicts Response to Neoadjuvant Chemotherapy for Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most fatal type of breast cancer (BC). Due to the lack of relevant targeted drug therapy, in addition to surgery, chemotherapy is still the most common treatment option for TNBC. TNBC is heterogeneous, and different patients have an unusual sensitivity to chemotherapy. Only part of the patients will benefit from chemotherapy, so neoadjuvant chemotherapy (NAC) is controversial in the treatment of TNBC. Here, we performed an NMR spectroscopy–based metabolomics study to analyze the relationship between the patients’ metabolic phenotypes and chemotherapy sensitivity in the serum samples. Metabolic phenotypes from patients with pathological partial response, pathological complete response, and pathological stable disease (pPR, pCR, and pSD) could be distinguished. Furthermore, we conducted metabolic pathway analysis based on identified significant metabolites and revealed significantly disturbed metabolic pathways closely associated with three groups of TNBC patients. We evaluated the discriminative ability of metabolites related to significantly disturbed metabolic pathways by using the multi-receiver–operating characteristic (ROC) curve analysis. Three significantly disturbed metabolic pathways of glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, and alanine, aspartate, and glutamate metabolism could be used as potential predictive models to distinguish three types of TNBC patients. These results indicate that a metabolic phenotype could be used to predict whether a patient is suitable for NAC. Metabolomics research could provide data in support of metabolic phenotypes for personalized treatment of TNBC.

Pharmacometabolomics by NMR in Oncology: A Systematic Review

Pharmacometabolomics (PMx) studies aim to predict individual differences in treatment response and in the development of adverse effects associated with specific drug treatments. Overall, these studies inform us about how individuals will respond to a drug treatment based on their metabolic profiles obtained before, during, or after the therapeutic intervention. In the era of precision medicine, metabolic profiles hold great potential to guide patient selection and stratification in clinical trials, with a focus on improving drug efficacy and safety. Metabolomics is closely related to the phenotype as alterations in metabolism reflect changes in the preceding cascade of genomics, transcriptomics, and proteomics changes, thus providing a significant advance over other omics approaches. Nuclear Magnetic Resonance (NMR) is one of the most widely used analytical platforms in metabolomics studies. In fact, since the introduction of PMx studies in 2006, the number of NMR-based PMx studies has been continuously growing and has provided novel insights into the specific metabolic changes associated with different mechanisms of action and/or toxic effects. This review presents an up-to-date summary of NMR-based PMx studies performed over the last 10 years. Our main objective is to discuss the experimental approaches used for the characterization of the metabolic changes associated with specific therapeutic interventions, the most relevant results obtained so far, and some of the remaining challenges in this area.

Altered Follicular Fluid Metabolic Pattern Correlates with Female Infertility and Outcome Measures of In Vitro Fertilization

Nearly 40-50% of infertility problems are estimated to be of female origin. Previous studies dedicated to the analysis of metabolites in follicular fluid (FF) produced contrasting results, although some valuable indexes capable to discriminate control groups (CTRL) from infertile females (IF) and correlate with outcome measures of assisted reproduction techniques were in some instances found. In this study, we analyzed in blind FF of 35 control subjects (CTRL = patients in which inability to obtain pregnancy was exclusively due to a male factor) and 145 IF (affected by: endometriosis, n = 19; polycystic ovary syndrome, n = 14; age-related reduced ovarian reserve, n = 58; reduced ovarian reserve, n = 29; unexplained infertility, n = 14; genetic infertility, n = 11) to determine concentrations of 55 water- and fat-soluble low molecular weight compounds (antioxidants, oxidative/nitrosative stress-related compounds, purines, pyrimidines, energy-related metabolites, and amino acids). Results evidenced that 27/55 of them had significantly different values in IF with respect to those measured in CTRL. The metabolic pattern of these potential biomarkers of infertility was cumulated (in both CTRL and IF) into a Biomarker Score index (incorporating the metabolic anomalies of FF), that fully discriminated CTRL (mean Biomarker Score value = 4.00 ± 2.30) from IF (mean Biomarker Score value = 14.88 ± 3.09, p < 0.001). The Biomarker Score values were significantly higher than those of CTRL in each of the six subgroups of IF. Posterior probability curves and ROC curve indicated that values of the Biomarker Score clustered CTRL and IF into two distinct groups, based on the individual FF metabolic profile. Furthermore, Biomarker Score values correlated with outcome measures of ovarian stimulation, in vitro fertilization, number and quality of blastocysts, clinical pregnancy, and healthy offspring. These results strongly suggest that the biochemical quality of FF deeply influences not only the effectiveness of IVF procedures but also the following embryonic development up to healthy newborns. The targeted metabolomic analysis of FF (using empowered Redox Energy Test) and the subsequent calculation of the Biomarker Score evidenced a set of 27 low molecular weight infertility biomarkers potentially useful in the laboratory managing of female infertility and to predict the success of assisted reproduction techniques.

Metabolome and microbiome alterations in tongue coating of gastric precancerous lesion patients

Objective: This paper seeks to provide mechanistic insight into the pathological transition through the analysis of metabolites and microorganisms in the tongue coating of gastric precancerous lesions (GPL) patients.Methods: GC-TOF-MS and UHPLC-QE-MS metabolomics, combined with 16S rRNA microbiome techniques, were performed to explore the changes in metabolites and microorganisms in the tongue coating of GPL patients.Results: When compared with 15 controls, 133 metabolites were found to be differentially expressed in 60 GPL cases, of which could be divided into ten categories. Among them, most of the differentially expressed metabolites identified were lipids or lipid-like molecules. These metabolites were implicated in 6 metabolic pathways including glycine, serine and threonine metabolism, arginine and proline metabolism, sphingolipid metabolism, valine, leucine and isoleucine degradation, arachidonic acid metabolism, and tyrosine metabolism. The relative abundances of Alloprevotella, Solobacterium, Rothia, Eikenella, and Aggregatibacter in the GPL group increased significantly relative to the controls and were associated with lipids and lipid-like molecules, organic nitrogen compounds, organic oxygen compounds, phenylpropanoids and polyketides, and organoheterocyclic compounds, respectively.Conclusions: Compared with healthy people, the changes of tongue coating metabolites in GPL patients were mainly characterized by alterations in lipid metabolism and were associated with localized changes in the microbiome.

Liquid chromatography-mass spectrometry based metabolic characterization of pleural effusion in patients with acquired EGFR-TKI resistance

Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) acquired resistance remains a major barrier in the clinical treatment of lung adenocarcinoma with epidermal growth factor receptor (EGFR) mutations. Despite extensive efforts, mechanism of acquired resistance has not yet been elucidated clearly. The subject of this study was to characterize the metabolic signatures relevant to acquired EGFR-TKI resistance in pleural effusion (PE), and identify potential biomarkers in PE of patients with acquired EGFR-TKI resistance. PE from EGFR-TKI untreated group (n = 30) and EGFR-TKI resistant group (n = 18) was analyzed using liquid chromatography-mass spectrometry (LCMS) based metabolomic. Multivariate statistical analysis revealed distinctive diff ;erences between the groups. A total of 34 significantly differential metabolites in PE were identified, among which, the acquired EGFR-TKI resistant group had higher levels of l-lysine, taurine, ornithine and citrulline, and lower levels of l-tryptophan, kynurenine, l-phenylalanine, l-leucine, N-formyl-l-methionine, 3-hydroxyphenylacetic acid and N-acetyl-d-phenylalanine in PE than that of the EGFR-TKI untreated group. These metabolites are mainly involved in six amino acid metabolic pathways. In addition, 3-hydroxyphenylacetic acid and N-acetyl-d-phenylalanine showed the highest AUC values of 0.934 and 0.929 in receiver operating characteristic analysis. Through LCMS metabolomics, our study identified potential biomarkers in PE, differentiating EGFR-TKI resistant patients from untreated patients, as well as the mechanisms underlying acquired EGFR-TKI resistance; thus, providing novel insights into acquired EGFR-TKI resistance.

Plasmonic Alloys Reveal a Distinct Metabolic Phenotype of Early Gastric Cancer

Gastric cancer (GC) is a multifactorial process, accompanied by alterations in metabolic pathways. Non-invasive metabolic profiling facilitates GC diagnosis at early stage leading to an improved prognostic outcome. Herein, mesoporous PdPtAu alloys are designed to characterize the metabolic profiles in human blood. The elemental composition is optimized with heterogeneous surface plasmonic resonance, offering preferred charge transfer for photoinduced desorption/ionization and enhanced photothermal conversion for thermally driven desorption. The surface structure of PdPtAu is further tuned with controlled mesopores, accommodating metabolites only, rather than large interfering compounds. Consequently, the optimized PdPtAu alloy yields direct metabolic fingerprints by laser desorption/ionization mass spectrometry in seconds, consuming 500 nL of native plasma. A distinct metabolic phenotype is revealed for early GC by sparse learning, resulting in precise GC diagnosis with an area under the curve of 0.942. It is envisioned that the plasmonic alloy will open up a new era of minimally invasive blood analysis to improve the surveillance of cancer patients in the clinical setting.

NMR-based metabolomics with enhanced sensitivity

NMR-based metabolomics, which emerged along with mass spectrometry techniques, is the preferred method for studying metabolites in medical research and food industries. However, NMR techniques suffer from inherently low sensitivity, regardless of their superior reproducibility. To overcome this, we made two beneficial modifications: we detuned the probe to reach a position called "Spin Noise Tuning Optimum" (SNTO), and we replaced the conventional cylindrical 5 mm NMR tube with an electric field component-optimized shaped tube. We found that concerted use of both modifications can increase the sensitivity (signal to noise ratio per unit volume) and detection of metabolites and decrease the measurement time by order of magnitude. In this study, we demonstrate and discuss the achieved signal enhancement of metabolites on model non-human (bovine serum, amino acid standard mixture) and human urine samples.

UPLC-Q-TOF/MS-Based Serum and Urine Metabonomics Study on the Ameliorative Effects of Palmatine on Helicobacter pylori-Induced Chronic Atrophic Gastritis

OBJECTIVE

The main objective of this study was to investigate the ameliorative effects of Palmatine (Pal) on Helicobacter pylori (H. pylori) induced chronic atrophic gastritis (CAG).

METHOD

Body function, serum biochemical indicators and histopathology were used to evaluate the pharmacodynamics of Pal on CAG rats. The target genes expression levels were verified and assessed by RT-PCR and immunohistochemistry (IHC). Moreover, UPLC-Q-TOF/MS analysis based on urine and serum was performed to identify the potential metabolites in the pathological process of CAG induced by H. pylori. Metabolic pathway analysis was performed to elucidate the metabolic network associated with Pal treatment of CAG.

RESULTS

Pal (10, 20, 40 mg/kg/day) significantly restored the body function of CAG rats, reduced the serum biochemical indicators, and maintained the integrity of the gastric mucosal epithelial barrier while alleviated gastric histological damage. Metabolomics analysis shows that the therapeutic effect of Pal on CAG involves 10 metabolites and 10 metabolic pathways, of which the Taurine and hypotaurine metabolism, Glycerophospholipid metabolism and Pentose and glucuronate interconversions are closely related to the gastrointestinal protection of Pal, and these metabolic pathways crosstalk with each other due to the internet hub of citric acid cycle.

CONCLUSIONS

Metabolomics was used for the first time to identify potential biomarkers of CAG and to illuminate the therapeutic mechanism of Pal on CAG induced by H. pylori. The results provided a new insight for further research on CAG treatment.

Nuclear magnetic resonance-based tissue metabolomic analysis clarifies molecular mechanisms of gastric carcinogenesis

Gastric cancer (GC) is one of the deadliest cancers worldwide, and the progression of gastric carcinogenesis (GCG) covers multiple complicated pathological stages. Molecular mechanisms of GCG are still unclear. Here, we undertook NMR-based metabolomic analysis of aqueous metabolites extracted from gastric tissues in an established rat model of GCG. We showed that the metabolic profiles were clearly distinguished among 5 histologically classified groups: control, gastritis, low-grade gastric dysplasia, high-grade gastric dysplasia (HGD), and GC. Furthermore, we carried out metabolic pathway analysis based on identified significant metabolites and revealed significantly disturbed metabolic pathways closely associated with the 4 pathological stages, including oxidation stress, choline phosphorylation, amino acid metabolism, Krebs cycle, and glycolysis. Three metabolic pathways were continually disturbed during the progression of GCG, including taurine and hypotaurine metabolism, glutamine and glutamate metabolism, alanine, aspartate, and glutamate metabolism. Both the Krebs cycle and glycine, serine, and threonine metabolism were profoundly impaired in both the HGD and GC stages, potentially due to abnormal energy supply for tumor cell proliferation and growth. Furthermore, valine, leucine, and isoleucine biosynthesis and glycolysis were significantly disturbed in the GC stage for higher energy requirement of the rapid growth of tumor cells. Additionally, we identified potential gastric tissue biomarkers for metabolically discriminating the 4 pathological stages, which also showed good discriminant capabilities for their serum counterparts. This work sheds light on the molecular mechanisms of GCG and is of benefit to the exploration of potential biomarkers for clinically diagnosing and monitoring the progression of GCG.