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<p>We conducted blood-based metabolomic profiling in ovarian cancer and determined its clinical relevance. NMR spectroscopy was performed on a total of <i>n</i> = 760 longitudinal plasma samples from <i>n</i> = 292 ovarian cancer patients, probing for <i>n</i> = 39 metabolites. At primary diagnosis, we revealed two distinguishable signatures, representing blood-based surrogates for a continuum of two metabolic states in ovarian cancer. These signatures shaped two subgroups of patients with differential surgical outcome and relapse risk (HR = 1.605, 95%CI:1.11-2.32, <i>p</i> = 0.009). Deconvolution of the metabolomic signatures identified acetoacetate, 3-hydroxybutyrate and alanine among the most relevant signature-determining metabolites. The acetoacetate<sup>low</sup>/3-hydroxybutyrate<sup>low</sup>/alanine<sup>high</sup>-profile was a strong predictor for superior clinical outcome, independently of FIGO stage and surgical outcome (HR = 0.471, 95%CI:0.236-0.942, <i>p</i> = 0.033). A strong relative decline of the ketone bodies in the course of therapy indicated adverse clinical outcome (acetoacetate: OS: HR = 2.22, 95%CI:1.08-4.55, <i>p</i> = 0.02). We propose a 3-metabolite blood-based signature in ovarian cancer that could be used for independent prediction of relapse risk and survival.</p>

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Exploring translational relevance of baseline and longitudinal metabolic profiling in the blood of ovarian cancer patients

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月24日

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

摘要

We conducted blood-based metabolomic profiling in ovarian cancer and determined its clinical relevance. NMR spectroscopy was performed on a total of n = 760 longitudinal plasma samples from n = 292 ovarian cancer patients, probing for n = 39 metabolites. At primary diagnosis, we revealed two distinguishable signatures, representing blood-based surrogates for a continuum of two metabolic states in ovarian cancer. These signatures shaped two subgroups of patients with differential surgical outcome and relapse risk (HR = 1.605, 95%CI:1.11-2.32, p = 0.009). Deconvolution of the metabolomic signatures identified acetoacetate, 3-hydroxybutyrate and alanine among the most relevant signature-determining metabolites. The acetoacetatelow/3-hydroxybutyratelow/alaninehigh-profile was a strong predictor for superior clinical outcome, independently of FIGO stage and surgical outcome (HR = 0.471, 95%CI:0.236-0.942, p = 0.033). A strong relative decline of the ketone bodies in the course of therapy indicated adverse clinical outcome (acetoacetate: OS: HR = 2.22, 95%CI:1.08-4.55, p = 0.02). We propose a 3-metabolite blood-based signature in ovarian cancer that could be used for independent prediction of relapse risk and survival.