Metabolomic Signatures of Scarff–Bloom–Richardson (SBR) Grade in Non-Metastatic Breast Cancer

Author:

Bailleux Caroline12ORCID,Chardin David13,Gal Jocelyn4ORCID,Guigonis Jean-Marie1,Lindenthal Sabine1,Graslin Fanny13,Arnould Laurent56,Cagnard Alexandre1,Ferrero Jean-Marc2,Humbert Olivier13,Pourcher Thierry1ORCID

Affiliation:

1. Laboratory Transporter in Imaging and Radiotherapy in Oncology (TIRO), Direction de la Recherche Fondamentale (DRF), Institut des Sciences du Vivant Fréderic Joliot, Commissariat à l’Energie Atomique et aux Énergies Alternatives (CEA), Université Côte d’Azur (UCA), 06100 Nice, France

2. Medical Oncology Department, Centre Antoine Lacassagne, University Côte d’Azur, 06189 Nice, France

3. Department of Nuclear Medicine, Antoine Lacassagne Centre, 06189 Nice, France

4. Department of Epidemiology and Biostatistics, Antoine Lacassagne Centre, University of Côte d’Azur, 06189 Nice, France

5. Department of Tumour Biology and Pathology, Georges-François Leclerc Centre, 21079 Dijon, France

6. Cenre de Ressources Biologiques (CRB) Ferdinand Cabanne, 21000 Dijon, France

Abstract

Purpose: Identification of metabolomic biomarkers of high SBR grade in non-metastatic breast cancer. Methods: This retrospective bicentric metabolomic analysis included a training set (n = 51) and a validation set (n = 49) of breast cancer tumors, all classified as high-grade (grade III) or low-grade (grade I–II). Metabolomes of tissue samples were studied by liquid chromatography coupled with mass spectrometry. Results: A molecular signature of the top 12 metabolites was identified from a database of 602 frequently predicted metabolites. Partial least squares discriminant analyses showed that accuracies were 0.81 and 0.82, the R2 scores were 0.57 and 0.55, and the Q2 scores were 0.44431 and 0.40147 for the training set and validation set, respectively; areas under the curve for the Receiver Operating Characteristic Curve were 0.882 and 0.886. The most relevant metabolite was diacetylspermine. Metabolite set enrichment analyses and metabolic pathway analyses highlighted the tryptophan metabolism pathway, but the concentration of individual metabolites varied between tumor samples. Conclusions: This study indicates that high-grade invasive tumors are related to diacetylspermine and tryptophan metabolism, both involved in the inhibition of the immune response. Targeting these pathways could restore anti-tumor immunity and have a synergistic effect with immunotherapy. Recent studies could not demonstrate the effectiveness of this strategy, but the use of theragnostic metabolomic signatures should allow better selection of patients.

Funder

French National Research Agency

Department 06

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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