Summary of Study ST002136
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 PR001353. The data can be accessed directly via it's Project DOI: 10.21228/M8TQ43 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.
| Study ID | ST002136 |
| Study Title | Targeted Microchip Capillary Electrophoresis-Orbitrap Mass Spectrometry Metabolomics to Monitor Ovarian Cancer Progression (calibration standards) |
| Study Summary | The 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. |
| Institute | Georgia Institute of Technology |
| Last Name | Sah |
| First Name | Samyukta |
| Address | 901 Atlantic Dr NW, Atlanta, GA, 30332, USA |
| ssah9@gatech.edu | |
| Phone | 5746780124 |
| Submit Date | 2022-04-11 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2022-05-02 |
| Release Version | 1 |
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Collection:
| Collection ID: | CO002214 |
| Collection Summary: | To improve CE peak shape and support electrophoretic focusing, a sample diluent consisting of 133 mM ammonium acetate, and 0.1% formic acid was prepared.13 This sample diluent was spiked with 1 µM 13C phenylalanine, 3 µM 13C6 arginine and 0.8 µM 13C methionine D3 as internal standards. Calibration mixtures were prepared from serial dilution of stock standard solutions using the spiked sample diluent in a 1:4 ratio. Each calibration standard was analyzed twice to yield calibration curves, calculate figures of merit, and perform metabolite quantification. |
| Sample Type: | Synthetic Mixture |
