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

TL;DR

This study identifies blood metabolite signatures in ovarian cancer patients that predict treatment outcomes and survival.

Contribution

The study introduces a 3-metabolite blood-based signature for predicting relapse risk and survival in ovarian cancer.

Findings

Two metabolic signatures at diagnosis predict surgical outcome and relapse risk.

Acetoacetate, 3-hydroxybutyrate, and alanine levels strongly predict clinical outcomes.

Decline in ketone bodies during therapy correlates with worse survival.

Abstract

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.

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