Figure 3 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population

Brendan M. Giles; Rachel Culp‐Hill; Robert Adger Law; Charles M. Nichols; Melvyn Goldberg; Enkhtuya Radnaa; Maria Pik Wong; Connor Hansen; Moises Zapata; Collin Hill; Kian Behbakht; Benjamin G. Bitler; Emma J. Crosbie; Chloe E. Barr; Anna Jeter; Vuna S. Fa; Violeta Beleva Guthrie; Leonardo N. Hagmann; Emily C. Kubota; James R. White; Abigail McElhinny

doi:10.1158/2767-9764.30051284

Key Points

The multiomic model achieved significant performance in distinguishing ovarian cancer from noncancerous controls.
ROC curve analysis showed distinct AUC values for early-stage ovarian cancer, emphasizing detection capacity.
Using serum-derived lipidomics alongside protein biomarkers enhances diagnostic precision through machine learning.
Findings point to the potential of integrating lipidomics and machine learning for clinical ovarian cancer diagnostics.

Implication

Analysis reveals a multiomic model's ability to distinguish ovarian cancer, indicating potential for early detection.

Abstract

Multiomic model performance. ROC curves for distinguishing cancer from noncancer in cohort 1 (training; A) and cohort 2 (test; B). The AUC is shown for each comparison: control vs. ovarian cancer (red) and control vs. early-stage ovarian cancer (blue). OC, ovarian cancer.

Discussion

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Cite This Study

Giles et al. (2025) studied this question.

synapsesocial.com/papers/68c18c089b7b07f3a06147a9 https://doi.org/10.1158/2767-9764.30051284

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Figure 3 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population

Key Points

Implication

Abstract

Discussion

Cite This Study

Figure 3 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population

Key Points

Implication

Abstract

Discussion

Cite This Study

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