Enantioanalysis of glutamine—a key factor in establishing the metabolomics process in gastric cancer

Staden, Raluca‐Ioana Stefan‐van; Ilie-Mihai, Ruxandra-Maria; Măgeruşan, Lidia; Coroș, Maria; Pruneanu, Stela

doi:10.1007/s00216-020-02575-y

Cited by 30 publications

(29 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But due to signal amplification in the direction of genome-proteome-metabolome, unique metabolites are closely related to the phenotype and allow more precise and earlier diagnosis for cancer (12). Apart from "omics" techniques, several studies have designed various stochastic sensors, which could be used for the recognition and quantification of cancer biomarkers based on a prior information (35)(36)(37)(38). Compared with stochastic sensors, untargeted metabolomics offers an unbiased means to measure the broadest range of metabolites without priori information, which could reveal novel and unique perturbations in cancer (14).…”

Section: Discussionmentioning

confidence: 99%

Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma

et al. 2022

View full text Add to dashboard Cite

Background & ObjectivesPancreatic ductal adenocarcinoma remains an extremely malignant tumor having a poor prognosis. The 5-year survival rate of PDAC is related to its stage (about 80% for stage I vs 20% for other stages). However, detection of PDAC in an early stage is difficult due to the lack of effective screening methods. In this study, we aimed to construct a novel metabolic model for stage-I PDAC detection, using both serum and tissue samples.MethodsWe employed an untargeted technique, UHPLC-Q-TOF-MS, to identify the potential metabolite, and then used a targeted technique, GC-TOF-MS, to quantitatively validate. Multivariate and univariate statistics were performed to analyze the metabolomic profiles between stage-I PDAC and healthy controls, including 90 serum and 53 tissue samples. 28 patients with stage-I PDAC and 62 healthy controls were included in this study.ResultsA total of 10 potential metabolites presented the same expression levels both in serum and in tissue. Among them, a 2-metabolites-model (isoleucine and adrenic acid) for stage-I PDAC was constructed. The area under the curve (AUC) value was 0.93 in the discovery set and 0.90 in the independent validation set. Especially, the serum metabolite model had a better diagnostic performance than CA19-9 (AUC = 0.79). Pathway analysis revealed 11 altered pathways in both serum and tissue of stage-I PDAC.ConclusionsThis study developed a novel serum metabolites model that could early separate stage-I PDAC from healthy controls.

show abstract

Section: Discussionmentioning

confidence: 99%

Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma

et al. 2022

View full text Add to dashboard Cite

show abstract

“…It is by now well established that d -amino acids are biomarkers of diseases with diagnostic value [ 11 , 12 , 13 , 14 ]. The distribution, function, and physiological role of these amino acids have been the motif of several research projects in the last decade.…”

Section: Chiral Metabolites and Lipids Separation By Liquid Chromatographymentioning

confidence: 99%

Enantioselectivity Effects in Clinical Metabolomics and Lipidomics

2021

View full text Add to dashboard Cite

Metabolomics and lipidomics have demonstrated increasing importance in underlying biochemical mechanisms involved in the pathogenesis of diseases to identify novel drug targets and/or biomarkers for establishing therapeutic approaches for human health. Particularly, bioactive metabolites and lipids have biological activity and have been implicated in various biological processes in physiological conditions. Thus, comprehensive metabolites, and lipids profiling are required to obtain further advances in understanding pathophysiological changes that occur in cells and tissues. Chirality is one of the most important phenomena in living organisms and has attracted long-term interest in medical and natural science. Enantioselective separation plays a pivotal role in understanding the distribution and physiological function of a diversity of chiral bioactive molecules. In this context, it has been the goal of method development for targeted and untargeted metabolomics and lipidomic assays. Herein we will highlight the benefits and challenges involved in these stereoselective analyses for clinical samples.

show abstract

“…A solution of α-cyclodextrin 10 −3 mol L −1 was used as a modifier in the design of new disposable stochastic sensors based on Ag, AgC and AgC/Ag coatings materials onto plastic substrates. As shown in previous publications [ 16 , 17 , 18 ], 10 −3 mol L −1 was the optimum concentration of modifier (α-cyclodextrin); using higher or lower concentrations of α-cyclodextrin, no response was obtained for the proposed sensors.…”

Section: Methodsmentioning

confidence: 59%

Disposable Stochastic Sensors Based on Nanolayer Deposition(s) of Silver and AgC Composite on Plastic for the Assay of α-amylase in Whole Blood and Saliva

2020

Self Cite

View full text Add to dashboard Cite

Nanolayer deposition(s) of Ag and AgC composite on a plastic substrate was used to design disposable stochastic sensors. Three shapes of nanocoatings were tested. The first shape was obtained by deposition of a nanofilm of Ag on the plastic material; the second shape was obtained by deposition of a composite AgC nanolayer on the plastic material; the third shape was obtained by nanolayer deposition of a composite material of AgC on the top of the Ag nanofilm deposited on the plastic material. α-Cyclodextrin was used to modify the active surface of the sensor. Wide linear concentration ranges were obtained as follows: for de-assay of α-amylase in whole blood: 1.00 × 10−7–1.00 × 103 U mL−1 and for the assay of α-amylase in saliva: 1.5 × 10−15–1.5 × 102 U mL−1. α-Amylase was reliably determined from whole blood and saliva samples using the proposed disposable stochastic sensors.

show abstract

Enantioanalysis of glutamine—a key factor in establishing the metabolomics process in gastric cancer

Cited by 30 publications

References 24 publications

Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma

Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma

Enantioselectivity Effects in Clinical Metabolomics and Lipidomics

Disposable Stochastic Sensors Based on Nanolayer Deposition(s) of Silver and AgC Composite on Plastic for the Assay of α-amylase in Whole Blood and Saliva

Contact Info

Product

Resources

About