Supplemental Figure 3 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population | Synapse
September 10, 2025Open Access
Supplemental Figure 3 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Puntos clave
Machine learning successfully identifies gangliosides for early-stage ovarian cancer detection.
Top 50 gangliosides were evaluated using ANOVA, highlighting significant differences between control and cancer groups.
The approach utilized PLSDA to analyze lipidomic data for effective differentiation in detection.
These findings support the potential of lipidomics as a promising biomarker for early ovarian cancer screening.
Resumen
Supplemental Figure 3. Cohort 2 PLSDA and heatmaps of top 50 gangliosides by ANOVA comparing controls to OC and early-stage OC