Summary of Study ST002137

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench,, where it has been assigned Project ID PR001353. The data can be accessed directly via it's Project DOI: 10.21228/M8TQ43 This work is supported by NIH grant, U2C- DK119886.


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 IDST002137
Study TitleTargeted Microchip Capillary Electrophoresis-Orbitrap Mass Spectrometry Metabolomics to Monitor Ovarian Cancer Progression. (Ovarian cancer mouse data)
Study SummaryThe lack of effective screening strategies for high-grade serous carcinoma (HGSC), a subtype of ovarian cancer (OC) responsible for 80% of OC related deaths, emphasizes the need for new diagnostic markers and a better understanding of disease pathogenesis. Capillary electrophoresis (CE) coupled with high-resolution mass spectrometry (HRMS) offers high selectivity and sensitivity, thereby increasing metabolite coverage and consequently enhancing biomarker discovery. Recent advances in CE-MS include small, chip-based CE systems coupled with nanoelectrospray ionization (nanoESI) to provide rapid, high-resolution analysis of biological specimens. Here, we describe the development of a targeted microchip (µ) CE-HRMS method to analyze 40 target metabolites in serum samples from a triple-mutant (TKO) mouse model of HGSC, with an acquisition time of only 3 min. Extracted ion electropherograms showed sharp, highly resolved peak shapes, even for structural isomers such as leucine and isoleucine. All analytes maintained good linearity with an average R2 of 0.994, while detection limits were in the nM range. Thirty metabolites were detected in mice serum, with recoveries ranging from 78 to 120 %, indicating minimal ionization suppression and good accuracy. We applied the µCE-HRMS method to sequentially-collected serum samples from TKO and TKO-control mice. Time-resolved analysis revealed characteristic temporal trends for amino acids, nucleosides, and amino acids derivatives associated with HGSC progression. Comparison of the µCE-HRMS dataset with non-targeted ultra-high performance liquid chromatography (UHPLC) – MS results revealed identical temporal trends for the 5 metabolites detected on both platforms, indicating the µCE-HRMS method performed satisfactorily in terms of capturing metabolic reprogramming due to HGSC progression, while reducing the total analysis time 3-fold.
Georgia Institute of Technology
Last NameSah
First NameSamyukta
Address901 Atlantic Dr NW, Atlanta, GA, 30332, USA
Submit Date2022-04-11
Raw Data AvailableYes
Raw Data File Type(s)raw(Thermo)
Analysis Type DetailLC-MS
Release Date2022-05-02
Release Version1
Samyukta Sah Samyukta Sah application/zip

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Subject ID:SU002222
Subject Type:Mammal
Subject Species:Mus musculus
Taxonomy ID:10090