Summary of project PR001623
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 PR001623. The data can be accessed directly via it's Project DOI: 10.21228/M8X42D This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Project ID: | PR001623 |
| Project DOI: | doi: 10.21228/M8X42D |
| Project Title: | Wide-Coverage Serum Metabolomic Profiling Reveals a Comprehensive Lipidome Signature of Ovarian Cancer. |
| Project Summary: | Distinguishing ovarian cancer (OC) from other benign or cancerous gynecological malignancies remains a critical unmet medical need with significant implications on patient survival. Substantially better results are observed when women with OC are correctly diagnosed and ensured the right treatment. However, non-specific symptoms along with our lack of understanding of OC pathogenesis hinder its diagnosis, consequently leading to a very low survival rate. Accumulating evidence suggests the link between OC and deregulated lipid metabolism. Most studies, however, are limited by small sample sizes and metabolite coverage, thereby constraining the robustness of the results. Here, we performed a comprehensive serum lipidome profiling of OC and various other gynecological malignancies (non-OC). A relatively large patient cohort with 208 OC and 137 non-OC patients, including 93 OC patients with early-stage OC, was recruited from two independent clinical sites in South Korea. Samples were analyzed with high-coverage liquid chromatography high-resolution mass spectrometry, providing extensive lipidome coverage with 994 successfully annotated lipid features. Lipidome differences between OC and other gynecological malignancies were investigated via statistical and machine learning approaches. Our data suggest that lipidome alterations unique to OC can be detected as early as when the cancer is localized, and those changes amplify as the diseases progresses. Comparison of the relative lipid abundances revealed specific patterns based on lipid class with most lipid classes showing decreased abundance in ovarian cancer. This study provides a systemic analysis of lipidome alterations in OC, emphasizing the potential of circulating lipids as a complementary class of blood-based biomarkers for OC diagnosis. |
| Institute: | Georgia Institute of Technology |
| Last Name: | Sah |
| First Name: | Samyukta |
| Address: | 901 Atlantic Dr NW, Atlanta, GA 30318 |
| Email: | ssah9@gatech.edu |
| Phone: | 574-678-0124 |
Summary of all studies in project PR001623
| Study ID | Study Title | Species | Institute | Analysis(* : Contains Untargted data) | Release Date | Version | Samples | Download(* : Contains raw data) |
|---|---|---|---|---|---|---|---|---|
| ST002521 | Wide-Coverage Serum Metabolomic Profiling Reveals a Comprehensive Lipidome Signature of Ovarian Cancer. | Homo sapiens | Georgia Institute of Technology | MS* | 2023-04-12 | 1 | 426 | Uploaded data (114.3G)* |
