Metabolomic Analysis Reveals the Association of Severe Bronchopulmonary Dysplasia with Gut Microbiota and Oxidative Response in Extremely Preterm Infants.

Bronchopulmonary dysplasia (BPD) is a chronic lung disease mainly affecting premature infants needing ventilation or oxygen for respiratory distress. This study aimed to evaluate the molecular linkages for BPD in very and extremely preterm infants using a metabolomics-based approach. A case-control study of enrolling preterm infants born before 32 weeks gestational age (GA) was prospectively performed. These preterm infants were subsequently stratified into the following two groups for further analysis: no or mild BPD, and moderate or severe BPD based on the 2019 NICHD criteria. Urinary metabolomic profiling was performed using 1H-Nuclear magnetic resonance (NMR) spectroscopy coupled with partial least squares discriminant analysis (PLS-DA) at a corrected age of 6 months. Metabolites significantly differentially related to GA and BPD severity were performed between groups, and their roles in functional metabolic pathways were also assessed. A total of 89 preterm infants born before 32 weeks gestation and 50 infants born at term age (above 37 completed weeks' gestation) served as controls and were enrolled into the study. There were 21 and 24 urinary metabolites identified to be significantly associated with GA and BPD severity, respectively (p < 0.05). Among them, N-phenylacetylglycine, hippurate, acetylsalicylate, gluconate, and indoxyl sulfate were five metabolites that were significantly higher, with the highest importance in both infants with GA < 28 weeks and those with moderate to severe BPD, whereas betaine and N,N-dimethylglycine were significantly lower (p < 0.05). Furthermore, ribose and a gluconate related pentose phosphate pathway were strongly associated with these infants (p < 0.01). In conclusion, urinary metabolomic analysis highlights the crucial role of gut microbiota dysbiosis in the pathogenesis of BPD in preterm infants, accompanied by metabolites related to diminished antioxidative capacity, prompting an aggressive antioxidation response in extremely preterm infants with severe BPD.

The Clinical Experiences of Urine Metabolomics of Genitourinary Urothelial Cancer in a Tertiary Hospital in Taiwan.

Few studies have addressed the impact of diagnostic urine metabolites and the clinical outcomes associated with genitourinary urothelial (GU) cancer to date. Furthermore, longitudinal analysis of the dynamics of urine metabolites contributing to the detection of GU cancer has not yet been fully investigated; therefore, the discovery of novel diagnostic urine biomarkers is of enormous interest. We explored the correlation of the urine metabolomic profiles to GU cancers. The aqueous metabolites of the GU cancer and the control were also identified and analyzed through high-resolution1H nuclear magnetic resonance (NMR) spectroscopy. Compared with the control, the urine metabolites of the tumor were studied in relation to changes over time in a linear mixed model for repeated measures. The urine metabolites of sixty-three (44 male and 19 female) patients with GU cancers were systemically analyzed. The urine metabolite profile in GU cancer was significantly higher than those in the control group (p<0.05). Sevenurine metabolites including histidine, propylene glycol, valine, leucine, acetylsalicylate, glycine, and isoleucine as well as other pathways were identified statistically and were significantly associated with GU cancer detection with longitudinal analysis. We discovered that histidine, propylene glycol, valine, leucine, acetylsalicylate, glycine, isoleucine, succinic acid, lysine2-aminobutyric acid, and acetic acid are involved significantly in all types of male patients in whom the type (upper tract) of urine metabolites were found to be statistically significant compared with the control. We did not find any statistical significance in urine biomarkers between female and male patients. However, a statistically insignificant correlation was found among the grade and stage with the metabolites.

Serum metabolites may be useful markers to assess vascular invasion and identify normal alpha-fetoprotein in hepatocellular carcinoma undergoing liver resection: a pilot study.

PURPOSE: Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver with a dismal prognosis. Vascular invasion, among others, is the most robust indicator of postoperative recurrence and overall survival after liver resection for HCC. Few studies to date have attempted to search for effective markers to predict vascular invasion before the operation. The current study would examine the plasma metabolic profiling via 1H-NMR of HCC patients undergoing liver resection and aim to search for potential biomarkers in the early detection of HCC with normal alpha-fetoprotein (AFP) and the diagnosis of vascular invasion preoperatively. MATERIALS AND METHODS: HCC patients scheduled to receive liver resections for their HCC were recruited and divided into two separate groups, investigation cohort and validation cohort. Their preoperative blood samples were collected and subjected to a comprehensive metabolomic profiling using 1H-nuclear magnetic resonance spectroscopy (NMR). RESULTS: There were 35 HCC patients in the investigation group and 22 patients in the validation group. Chronic hepatitis B remained the most common etiology of HCC, followed by chronic HCV infection. The two study cohorts were essentially comparable in terms of major clinicopathological variables. After 1H-nuclear NMR analysis, we found in the investigation cohort that HCC with normal alpha-fetoprotein (AFP < 15 ng/mL) had significantly higher serum level of O-acetylcarnitine than those with higher AFP (AFP ≥ 15 ng/mL, P = 0.025). In addition, HCC with microscopic vascular invasion (VI) had significantly higher preoperative serum level of formate than HCC without microscopic VI (P = 0.023). These findings were similar in the validation cohort. CONCLUSION: A comprehensive metabolomic profiling of HCC demonstrated that serum metabolites may be utilized to assist the early diagnosis of AFP-negative HCC patients and recognition of microvascular invasion in order to facilitate preoperative surgical planning and postoperative follow-up. Further, larger scale prospective studies are warranted to consolidate our findings.

Nuclear Magnetic Resonance Metabolomics Biomarkers for Identifying High Risk Patients with Extranodal Extension in Oral Squamous Cell Carcinoma.

Extranodal extension (ENE) is an independent adverse prognostic factor in oral squamous cell carcinoma (OSCC), and is difficult to identify preoperatively. We aimed to discover biomarkers for high risk patients with ENE. Tandem tissue, plasma, and urine samples of 110 patients with OSCC were investigated through 600-MHz nuclear magnetic resonance (NMR) metabolomics analysis. We found that the levels of creatine, creatine phosphate, glycine, and tyramine in plasma significantly decreased in stage IV ENE positive OSCC compared with stage IV ENE negative OSCC. To understand the underlying mechanism behind the alteration of plasma metabolites, our tissue analysis revealed that the carnitine level significantly increased in tumors but significantly decreased in the adjacent normal tissue in advanced stage OSCC, in addition to decreased levels of alanine and pyruvate in tumor tissues. The global metabolomics analysis on tumor tissues also showed that stage IV tumors with an ENE positive status demonstrated higher levels of aspartate, butyrate, carnitine, glutamate, glutathione, glycine, glycolate, guanosine, and sucrose but lower levels of alanine, choline, glucose, isoleucine, lactate, leucine, myo-inositol, O-acetylcholine, oxypurinol, phenylalanine, pyruvate, succinate, tyrosine, valine, and xanthine than tumors with an ENE negative status. We concluded that metabolomics alterations in tumor tissues correspond to an increase in the tumor stage and are detectable in plasma samples. Metabolomic alterations of OSCC can serve as potential diagnostic markers and predictors of ENE in patients with stage IV OSCC.

Metabolomic biomarkers in cervicovaginal fluid for detecting endometrial cancer through nuclear magnetic resonance spectroscopy.

INTRODUCTION: Endometrial cancer (EC) is one of the most common gynecologic neoplasms in developed countries but lacks screening biomarkers. OBJECTIVES: We aim to identify and validate metabolomic biomarkers in cervicovaginal fluid (CVF) for detecting EC through nuclear magnetic resonance (NMR) spectroscopy. METHODS: We screened 100 women with suspicion of EC and benign gynecological conditions, and randomized them into the training and independent testing datasets using a 5:1 study design. CVF samples were analyzed using a 600-MHz NMR spectrometer equipped with a cryoprobe. Four machine learning algorithms-support vector machine (SVM), partial least squares discriminant analysis (PLS-DA), random forest (RF), and logistic regression (LR), were applied to develop the model for identifying metabolomic biomarkers in cervicovaginal fluid for EC detection. RESULTS: A total of 54 women were eligible for the final analysis, with 21 EC and 33 non-EC. From 29 identified metabolites in cervicovaginal fluid samples, the top-ranking metabolites chosen through SVM, RF and PLS-DA which existed in independent metabolic pathways, i.e. phosphocholine, malate, and asparagine, were selected to build the prediction model. The SVM, PLS-DA, RF, and LR methods all yielded area under the curve values between 0.88 and 0.92 in the training dataset. In the testing dataset, the SVM and RF methods yielded the highest accuracy of 0.78 and the specificity of 0.75 and 0.80, respectively. CONCLUSION: Phosphocholine, asparagine, and malate from cervicovaginal fluid, which were identified and independently validated through models built using machine learning algorithms, are promising metabolomic biomarkers for the detection of EC using NMR spectroscopy.

Glycerophospholipids pathways and chromosomal instability in gastric cancer: Global lipidomics analysis.

BACKGROUND: Based on the breakthrough of genomics analysis, The Cancer Genome Atlas Research Group recently proposed an integrative genomic analysis, dividing gastric cancer (GC) into four subtypes, characterized by the chromosomal instability (CIN) status. However, the CIN status of GC is still vaguely characterized and lacking the valuable easy-to-use CIN markers to diagnosis in molecular and histological detection. AIM: To explore the associations of CIN with downstream lipidomics profiles. METHODS: We collected cancerous and noncancerous tissue samples from 18 patients with GC; the samples were divided into CIN and non-CIN types based on the system of The Cancer Genome Atlas Research Group and 409 sequenced oncogenes and tumor suppressor genes. We identified the lipidomics profiles of the GC samples and samples of their adjacent noncancerous tissues by using liquid chromatography-mass spectrometry. Furthermore, we selected leading metabolites based on variable importance in projection scores of > 1.0 and P < 0.05. RESULTS: Twelve men and six women participated in this study; the participants had a median age of 67.5 years (range, 52-87 years) and were divided into CIN (n = 9) and non-CIN (n = 9) groups. The GC samples exhibited distinct profiles of lysophosphocholine, phosphocholine, phosphatidylethanolamine, phosphatidylinositol, phosphoserine, sphingomyelin, ceramide, and triglycerides compared with their adjacent noncancerous tissues. The glycerophospholipid levels (phosphocholine, phosphatidylethanolamine, and phosphatidylinositol) were 1.4- to 2.3-times higher in the CIN group compared with the non-CIN group (P < 0.05). Alterations in the glycerolipid and glycerophospholipid pathways indicated progression of GC toward CIN. CONCLUSION: The lipidomics profiles of GC samples were distinct from those of their adjacent noncancerous tissues. CIN status of GC is primarily associated with downstream lipidomics in the glycerophospholipid pathway.

Metabolomics Reveals Anaerobic Bacterial Fermentation and Hypoxanthine Accumulation for Fibrinous Pleural Effusions in Children with Pneumonia.

Fibrin formation in infectious parapneumonic effusion (IPE) characterizes complicated parapneumonic effusion and is important for providing guidelines for the management of IPEs that require aggressive interventions. We aim to identify metabolic mechanisms associated with bacterial invasion, inflammatory cytokines, and biochemical markers in cases of fibrinous infectious pleural effusions in children with pneumonia. Pleural fluid metabolites were determined by 1H nuclear magnetic resonance spectroscopy. Metabolites that contributed to the separation between fibrinous and nonfibrinous IPEs were identified using supervised partial least squares discriminant analysis ( Q2/ R2 = 0.84; Ppermutation < 0.01). IL-1ß in the inflammatory cytokines and glucose in the biochemical markers were significantly correlated with 11 and 9 pleural fluid metabolites, respectively, and exhibited significant overlaps. Four metabolites, including glucose, lactic acid, 3-hydroxybutyric acid, and hypoxanthine, were significantly correlated with plasminogen activator inhibitor type 1 in the fibrinolytic system enzymes. Metabolic pathway analysis revealed that anaerobic bacterial fermentation with increased lactic acid and butyric acid via glucose consumption and adenosine triphosphate hydrolysis with increased hypoxanthine appeared to be associated with fibrinous IPE. Our results demonstrate that an increase in lactic acid anaerobic fermentation and hypoxanthine accumulation under hypoxic conditions are associated with fibrin formation in IPE, representing advanced pleural inflammatory progress in children with pneumonia.

Metabolomic alterations and chromosomal instability status in gastric cancer.

AIM: To explore the correlation of metabolomics profiles of gastric cancer (GC) with its chromosomal instability (CIN) status. METHODS: Nineteen GC patients were classified as CIN and non-CIN type by The Cancer Genome Atlas Research Group system, based on 409 oncogenes and tumor suppressor genes sequenced. The aqueous metabolites of the GC tumor and its surrounding adjacent healthy tissues were identified through liquid chromatography-mass spectrometry. Groups were compared by defining variable importance in projection score of > 1.2, a fold change value or its reciprocal of > 1.2, and a P value of < 0.05 as a significant difference. RESULTS: In total, twelve men and seven women were enrolled, with a median age of 66 years (range, 47-87 years). The numbers of gene alterations in the CIN GC group were significantly higher than those in the non-CIN GC (32-218 vs 2-17; P < 0.0005). Compared with the adjacent healthy tissues, GC tumors demonstrated significantly higher aspartic acid, citicoline, glutamic acid, oxidized glutathione, succinyladenosine, and uridine diphosphate-N-acetylglucosamine levels, but significantly lower butyrylcarnitine, glutathione hydroxyhexanoycarnitine, inosinic acid, isovalerylcarnitine, and threonine levels (all P < 0.05). CIN tumors contained significantly higher phosphocholine and uridine 5'-monophosphate levels but significantly lower beta-citryl-L-glutamic acid levels than did non-CIN tumors (all P < 0.05). CIN GC tumors demonstrated additional altered pathways involving alanine, aspartate, and glutamate metabolism, glyoxylate and dicarboxylate metabolism, histidine metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. CONCLUSION: Metabolomic profiles of GC tumors and the adjacent healthy tissue are distinct, and the CIN status is associated with downstream metabolic alterations in GC.