Supplemental Figure 2 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population

This is a PLSDA study (also classified as: ANOVA, Observational).

Key Points

Gangliosides may serve as effective biomarkers for the early detection of ovarian cancer.
The study utilized PLSDA to compare lipid profiles of controls with those having ovarian cancer and early-stage cases.
Heatmaps identified top gangliosides significantly differing by ANOVA, providing insights into potential diagnostic approaches.
Findings suggest that machine learning combined with lipidomics could enhance early diagnosis of ovarian cancer.

Analysis reveals gangliosides as biomarkers for ovarian cancer detection, highlighting their role in early diagnosis.

Supplemental Figure 2. Cohort 1 PLSDA and heatmaps of top 50 gangliosides by ANOVA comparing controls to OC and early-stage OC

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Giles et al. (2025) studied this question.

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