Supplemental Figure 5 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population

Key Points

Heatmaps show lipid features related to ovarian cancer risk and highlight differences across cohorts.
Top 100 lipid features were identified using ANOVA to assess variance between conditions.
Machine learning methods were applied to analyze serum-derived lipidomics data for detection.
Findings may enable improved early detection strategies for ovarian cancer in symptomatic populations.

Analysis reveals lipid features and biomarkers associated with ovarian cancer in symptomatic individuals, suggesting early detection strategies.

Supplemental Figure 5. Heatmaps of Top 100 Lipid Features by ANOVA across Cohorts and Comparisons

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Giles et al. (2025) studied this question.

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