Associations Between Pre-diagnostic Plasma Metabolites and Ovarian Cancer: A Prospective Case-Cohort Analysis in the Cancer Prevention Study-3

BACKGROUND: Ovarian cancer remains a significant health concern among U.S. women, yet its underlying etiology is not fully understood. Untargeted metabolomics enables comprehensive profiling of small molecules that may provide insight into metabolic alterations associated with ovarian cancer risk. METHODS: We conducted a case-cohort study within the Cancer Prevention Study-3, measuring pre-diagnostic plasma metabolites via untargeted metabolomics in 127 ovarian cancer cases and a randomly selected sub-cohort of 1,811 women, one of whom was later diagnosed with ovarian cancer. Median follow-up time was 2.4 years (IQR: 1.2-3.6) among ovarian cancer cases and 3.2 years (IQR: 2.5-5.2) in the sub-cohort. Metabolite associations with ovarian cancer risk were estimated using multivariable Prentice-weighted Cox models, and pathway enrichment analyses were performed. False discovery rate (FDR) correction was applied, considering FDR < 0.2 statistically significant. RESULTS: Among 868 plasma metabolites analyzed, none showed statistically significant associations with ovarian cancer risk after FDR correction. In stratified analyses by menopausal status, five metabolites remained statistically significant after FDR correction among postmenopausal women only. Pathway enrichment analyses identified several lipid-related sub-pathways enriched among metabolites associated with ovarian cancer risk (FDR-adjusted p-value < 0.2), with the strongest positive enrichment observed for primary bile acid metabolism and the strongest negative enrichment for sphingomyelins. CONCLUSIONS: In this prospective metabolomics analysis, individual pre-diagnostic plasma metabolites were not associated with ovarian cancer risk, but lipid-related pathways and possible differences by menopausal status may warrant additional investigation. IMPACT: These findings contribute to the growing untargeted metabolomics literature on ovarian cancer.

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Journal
Cancer Epidemiology Biomarkers & Prevention
Published
2026-09-10
DOI
https://doi.org/10.1158/1055-9965.epi-26-0544
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
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article

Associations Between Pre-diagnostic Plasma Metabolites and Ovarian Cancer: A Prospective Case-Cohort Analysis in the Cancer Prevention Study-3

Alpa V. Patel, Lauren R. Teras, Clara Bodelón, Matthew Masters et al.
Cancer Epidemiology Biomarkers & Prevention
Metabolomics and Mass Spectrometry Studies
article

Associations Between Pre-diagnostic Plasma Metabolites and Ovarian Cancer: A Prospective Case-Cohort Analysis in the Cancer Prevention Study-3

Alpa V. Patel, Lauren R. Teras, Clara Bodelón, Matthew Masters, Donghai Liang, Shamim Shahi, Victoria L. Stevens, Brigitte A. Pfluger, Ying Wang, Nancy B. Nguyen
article en

Abstract

BACKGROUND: Ovarian cancer remains a significant health concern among U.S. women, yet its underlying etiology is not fully understood. Untargeted metabolomics enables comprehensive profiling of small molecules that may provide insight into metabolic alterations associated with ovarian cancer risk. METHODS: We conducted a case-cohort study within the Cancer Prevention Study-3, measuring pre-diagnostic plasma metabolites via untargeted metabolomics in 127 ovarian cancer cases and a randomly selected sub-cohort of 1,811 women, one of whom was later diagnosed with ovarian cancer. Median follow-up time was 2.4 years (IQR: 1.2-3.6) among ovarian cancer cases and 3.2 years (IQR: 2.5-5.2) in the sub-cohort. Metabolite associations with ovarian cancer risk were estimated using multivariable Prentice-weighted Cox models, and pathway enrichment analyses were performed. False discovery rate (FDR) correction was applied, considering FDR < 0.2 statistically significant. RESULTS: Among 868 plasma metabolites analyzed, none showed statistically significant associations with ovarian cancer risk after FDR correction. In stratified analyses by menopausal status, five metabolites remained statistically significant after FDR correction among postmenopausal women only. Pathway enrichment analyses identified several lipid-related sub-pathways enriched among metabolites associated with ovarian cancer risk (FDR-adjusted p-value < 0.2), with the strongest positive enrichment observed for primary bile acid metabolism and the strongest negative enrichment for sphingomyelins. CONCLUSIONS: In this prospective metabolomics analysis, individual pre-diagnostic plasma metabolites were not associated with ovarian cancer risk, but lipid-related pathways and possible differences by menopausal status may warrant additional investigation. IMPACT: These findings contribute to the growing untargeted metabolomics literature on ovarian cancer.

Cancer Epidemiology Biomarkers & Prevention
American Cancer Society (US), Emory University (US), Social and Scientific Systems (United States) (US), Scientific Systems (United States) (US)
Good health and well-being
Openalex Percentile: Top 18%
Metabolomics and Mass Spectrometry Studies
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