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Metabolic Profiling of Visceral and Subcutaneous Adipose Tissue from Colorectal Cancer Patients: GC-TOF MS analyis of serum samples

ABSTRACT:

ORGANISM(S): Homo Sapiens

TISSUE(S): Adipose Tissue

DISEASE(S): Cancer

PROVIDER: ST000065 | MetabolomicsWorkbench |

REPOSITORIES: MetabolomicsWorkbench

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Metabolic Profiling of Visceral and Subcutaneous Adipose Tissue from Colorectal Cancer Patients: GC-TOF MS analyis of subcutaneous and visceral adipose tissue samples

Project description: Not available

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Metabolomics Workbench ST000061 -GNPS - Metabolic Profiling of Visceral and Subcutaneous Adipose Tissue from Colorectal Cancer Patients: GC-TOF MS analyis of subcutaneous and visceral adipose tissue samples

Project description:This West Coast Metabolomics Center pilot and feasibility project was granted to Johanna Lampe (Fred Hutchinson Cancer Research Center at Univ. of Washington, Seattle). In the current investigation, unbiased profiling of the metabolome and lipidome of adipose tissue samples (visceral(VAT) and subcutaenous (SAT)) and serum of 50 CRC patients, including stages I-IV, from the Fred Hutchinson Cancer Center (Seattle,WA) and the German Cancer Research Center (Heidelberg, Germany) was conducted. The lipidome and metabolome of adipose tissue (VAT/SAT) and serum were analyzed using established UPLC-QTOFMS analysis and GC-TOFMS analyses, respectively. The primary objectives of this project were to 1) compare the metabolome and lipidome of matched VAT and SAT adipose tissue of n=50 Colorectal Cancer Cell (CRC) patients, 2) characterize the associations between the lipidome and metabolome in adipose tissue (VAT/SAT) and serum of n=50 CRC patients and 3) test the associations between the lipidome/metabolome of VAT and serum with the tumor stage of CRC patients.

2019-07-01 | MSV000084042 | GNPS

Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS.

Project description:Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.

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Application of GC-TOF/MS and GC×GC-TOF/MS to Discriminate Coffee Products in Three States (Bean, Powder, and Brew).

Project description:The volatiles in coffee play an important part in the overall flavor profile. In this study, GC-TOF/MS and GC×GC-TOF/MS were used to detect the volatile organic compounds (VOCs) in coffee samples of three different brands at three states (bean, powder, and brew). The differences between the two methods in characterizing VOCs were analyzed using the Venn diagram and PCA (principal component analysis). The important aroma-contributing compounds were further compared and analyzed. The results of the venn diagrams of different coffee samples showed that most VOCs existed in 2-3 kinds of coffee. The PCA of VOCs in different coffee samples showed that the VOCs detected by GC-TOF/MS could distinguish the coffee samples in the different states. GC×GC-TOF/MS was suitable for the further identification and differentiation of the different brands of coffee samples. In addition, pyridine, pyrrole, alcohols, and phenols greatly contributed to distinguishing coffee in three states, and alcohols greatly contributed to distinguishing the three brands of coffee.

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Metabolomics Workbench ST000065 - GNPS - Metabolic Profiling of Visceral and Subcutaneous Adipose Tissue from Colorectal Cancer Patients: GC-TOF MS analyis of serum samples

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Visceral Adipose Tissue Inflammation and Radiographic Visceral-to-Subcutaneous Adipose Tissue Ratio in Patients with Cirrhosis.

Project description:Background and aimsAccumulation of visceral adipose tissue is associated with hepatic inflammation and fibrosis, suggestive of its metabolic and inflammatory properties. We aimed to examine the histologic findings of visceral and subcutaneous adipose tissue and to associate these findings with clinical and radiologic characteristics in patients with cirrhosis.MethodsIncluded were 55 adults with cirrhosis who underwent liver transplantation from 3/2017-12/2018 and had an abdominal computed tomography (CT) scan within 6 months prior to transplant. Visceral-to-subcutaneous adipose tissue ratio (VSR) was calculated using visceral (VATI) and subcutaneous adipose tissue index (SATI) quantified by CT at the L3-vertebral level and normalized for height (cm2/m2). VAT (greater omentum), SAT (abdominal wall), and skeletal muscle (rectus abdominis) biopsies were collected at transplant.ResultsMajority of patients had VAT inflammation (71%); only one patient (2%) had SAT inflammation. Patients with VAT inflammation had similar median VATI (42 vs 41 cm2/m2), lower median SATI (64 vs 97 cm2/m2), and higher median VSR (0.63 vs 0.37, p = 0.002) than patients without inflammation. In univariable logistic regression, VSR was associated with VAT inflammation (OR 1.47, 95%CI 1.11-1.96); this association remained significant even after adjusting for age, sex, BMI, HCC, or MELD-Na on bivariable analyses.ConclusionIn patients with cirrhosis undergoing liver transplantation, histologic VAT inflammation was common, but SAT inflammation was not. Increased VSR was independently associated with VAT inflammation. Given the emerging data demonstrating the prognostic value of VSR, our findings support the value of CT-quantified VSR as a prognostic marker for adverse outcomes in the liver transplant setting.

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Metabolic Profiling of Visceral and Subcutaneous Adipose Tissue from Colorectal Cancer Patients: UHPLC-QTOF MS analyis of subcutaneous and visceral adipose tissue samples

Project description: Not available

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The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC-TOF MS metabolome samples.

Project description:Metabolomics by gas chromatography/mass spectrometry (GC/MS) provides a standardized and reliable platform for understanding small molecule biology. Since 2005, the West Coast Metabolomics Center at the University of California at Davis has collated GC/MS metabolomics data from over 156,000 samples and 2000 studies into the standardized BinBase database. We believe that the observations from these samples will provide meaningful insight to biologists and that our data treatment and webtool will provide insight to others who seek to standardize disparate metabolomics studies. We here developed an easy-to-use query interface, BinDiscover, to enable intuitive, rapid hypothesis generation for biologists based on these metabolomic samples. BinDiscover creates observation summaries and graphics across a broad range of species, organs, diseases, and compounds. Throughout the components of BinDiscover, we emphasize the use of ontologies to aggregate large groups of samples based on the proximity of their metadata within these ontologies. This adjacency allows for the simultaneous exploration of entire categories such as "rodents", "digestive tract", or "amino acids". The ontologies are particularly relevant for BinDiscover's ontologically grouped differential analysis, which, like other components of BinDiscover, creates clear graphs and summary statistics across compounds and biological metadata. We exemplify BinDiscover's extensive applicability in three showcases across biological domains.

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Transcriptome profiling by array of visceral and subcutaneous adipose tissue from colorectal cancer patients

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