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Figure 2 from A Urinary Three-Metabolite Signature Enables Noninvasive Identification of Patients with High-Risk Ovarian Cancer

Year: 2026

Type: other

Abstract: Identification of prognostically informative urinary metabolites. A, Overview of the analytic workflow used to identify urinary metabolites with prognostic relevance. B, Regularization path of Cox-LASSO regression across λ-values. C, Nonzero β-coefficients at optimal λ (λ_min) for retained metabolites. Here, β denotes the Cox regression model coefficient and is shown as the log HR for each metabolite, not the metabolite concentration. D, Pairwise Pearson correlations among retained metabolites (n = 190); all r < 0.28. (A, Image created with BioRender.com. Schwarz, F. [2026] https://BioRender.com/7oq101y.)

DOI: 10.1158/1078-0432.33014282

Authors: Alexander Max Funk, Mareike Brieske, Franziska Maria Schwarz, Theresa Link, Sophie Jonas, Pauline Wimberger, Lisa Freitag, Anna Klimova, Triantafyllos Chavakis, Peter Mirtschink, Jan Dominik Kuhlmann

Language: English

Topic: Metabolomics and Mass Spectrometry Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

OpenAlex ID: W7169531389

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