Summary of Study ST002067

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001309. The data can be accessed directly via it's Project DOI: 10.21228/M8HH60 This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST002067
Study TitleTime-Resolved Metabolomics of a Mouse Model of Ovarian High-Grade Serous Carcinoma (LC-MS)
Study SummaryThe dismally-low survival rate of ovarian cancer patients diagnosed with high-grade serous carcinoma (HGSC) emphasizes the lack of effective screening strategies. One major obstacle is the limited knowledge of the underlying mechanisms of HGSC pathogenesis at very early stages. Here, we present the first 10-month time-resolved serum metabolic profile of a triple mutant (TKO) HGSC mouse model, along with the spatial lipidome profile of its entire reproductive system. A high-coverage liquid chromatography mass spectrometry-based metabolomics approach was applied to longitudinally-collected serum samples from both TKO and TKO control mice, tracking metabolome and lipidome changes from disease onset until death. Spatial lipid distributions within the reproductive system were also mapped via ultrahigh-resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, and compared with serum lipid profiles for various lipid classes. Altogether, our results show that the remodeling of lipid and fatty acid metabolism, amino acid biosynthesis, TCA cycle and ovarian steroidogenesis are critical components of HGSC onset and development. These metabolic alterations are accompanied by changes in energy metabolism, mitochondrial and peroxisomal function, redox homeostasis, and inflammatory response, collectively supporting tumorigenesis.
Institute
Georgia Institute of Technology
Last NameSah
First NameSamyukta
Address901 Atlantic Dr NE, Atlanta, GA, 30332, USA
Emailssah9@gatech.edu
Phone574-678-0124
Submit Date2022-01-26
Raw Data AvailableYes
Raw Data File Type(s)raw(Thermo)
Analysis Type DetailLC-MS
Release Date2022-02-14
Release Version1
Samyukta Sah Samyukta Sah
https://dx.doi.org/10.21228/M8HH60
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Sample Preparation:

Sampleprep ID:SP002155
Sampleprep Summary:Serum samples were thawed on ice, followed by metabolite extraction of both non-polar (lipid) and polar metabolites using two different sample preparation protocols. The extraction solvent for RP UHPLC-MS was prepared by adding the isotopically labeled lipid standard mixture to 2-propanol in a 1:60 ratio. Likewise, for HILIC UHPLC-MS, the extraction solvent was prepared by mixing an isotopically labeled mixture of polar metabolites and methanol in a 1:60 ratio. These extraction solvents were added to serum samples in a 3:1 ratio to precipitate proteins. Following this step, samples were vortex-mixed for 30 seconds and centrifuged at 13,000 rpm for 7 minutes. The resulting supernatant was transferred to snap-on LC vials and stored at -80 °C until UHPLC-MS analysis, which was performed within a week. A blank sample, prepared with LC-MS grade water, and 2-propanol (or methanol) underwent the same preparation process as the serum samples, and analyzed together simultaneously. A pooled quality control (QC) was prepared by mixing 5-10 μL aliquots of the extract of each serum sample. This pooled sample was analyzed every 10 runs to monitor LC-MS instrument stability and latter correct for any sensitivity drift. Samples were run in a randomized order on consecutive days.
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