Summary of Study ST002276

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 PR001457. The data can be accessed directly via it's Project DOI: 10.21228/M8D133 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.

Show all samples  |  Perform analysis on untargeted data  
Download mwTab file (text)   |  Download mwTab file(JSON)   |  Download data files (Contains raw data)
Study IDST002276
Study TitleMachine Learning Reveals Lipidome Dynamics in a Mouse Model of Ovarian Cancer
Study SummaryOvarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It presents little or no symptoms at the early stages, and typically unspecific symptoms at later stages. Of the OC subtypes, high-grade serous carcinoma (HGSC) is responsible for most OC deaths. However, very little is known about the metabolic course of this disease. In this longitudinal study, we investigated the temporal course of lipidome changes in a Dicer-Pten Double-Knockout (DKO) HGSC mouse model using machine and statistical learning approaches. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages were marked by more diverse lipids alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations provided evidence of perturbations in cell membrane stability, proliferation, and survival and candidates for early-stage and prognostic markers in humans.
Institute
Georgia Institute of Technology
DepartmentChemistry and Biochemistry
LaboratoryFernandez group
Last NameSah
First NameSamyukta
Address901 Atlantic Dr NW, Atlanta, GA, 30332, USA
Emailssah9@gatech.edu
Phone5746780124
Submit Date2022-09-01
Raw Data AvailableYes
Raw Data File Type(s)raw(Thermo)
Analysis Type DetailLC-MS
Release Date2022-09-28
Release Version1
Samyukta Sah Samyukta Sah
https://dx.doi.org/10.21228/M8D133
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Treatment:

Treatment ID:TR002374
Treatment Summary:Dicerflox/flox Ptenflox/flox without Amhr2cre/+ (DKO Control mice) Dicerflox/flox Ptenflox/flox (DKO mice with high grade serous carcinoma )
  logo