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Evaluation of metabolomic changes during neoadjuvant chemotherapy combined with bevacizumab in breast cancer using MR spectroscopy

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Abstract

Introduction

Metabolomics investigates biochemical processes directly, potentially complementing transcriptomics and proteomics in providing insight into treatment outcome.

Objectives

This study aimed to use magnetic resonance (MR) spectroscopy on breast tumor tissue to explore the effect of neoadjuvant therapy on metabolic profiles, determine metabolic effects of the antiangiogenic drug bevacizumab, and investigate metabolic differences between responders and non-responders.

Methods

Breast tumors from 122 patients were profiled using high resolution magic angle spinning MR spectroscopy. All patients received neoadjuvant chemotherapy, and were randomized to receive bevacizumab or not. Tumors were biopsied prior, during, and after treatment.

Results

Principal component analysis showed clear metabolic changes indicating a decline in glucose consumption and a transition to normal breast adipose tissue as an effect of chemotherapy. Partial least squares-discriminant analysis revealed metabolic differences between pathological minimal residual disease patients and pathological non-responders after treatment (accuracy of 77%, p < 0.001), but not before or during treatment. Lower glucose and higher lactate was observed in patients exhibiting a good response (≥90% tumor reduction) compared to those with no response (≤10% tumor reduction) before treatment, while the opposite was observed after treatment. Bevacizumab-receiving and chemotherapy-only patients could not be discriminated at any time point. Linear mixed-effects models revealed a significant interaction between time and bevacizumab for glutathione, indicating higher levels of this antioxidant in chemotherapy-only patients than in bevacizumab receivers after treatment.

Conclusion

MR spectroscopy showed potential in detecting metabolic response to treatment and complementing other molecular assays for the elucidation of underlying mechanisms affecting pathological response.

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Abbreviations

Ala:

Alanine

Asc:

Ascorbate

ATP:

Adenosine triphosphate

Cho:

Choline

Cr:

Creatine

CV:

Cross validation

ER:

Estrogen receptor

FDR:

False discovery rate

FEC:

5-Fluorouracil-epirubicin-cyclophosphamide

Glc:

Glucose

Glu:

Glutamate

Gly:

Glycine

GPC:

Glycerophosphocholine

GR:

Good response

GSH:

Glutathione

HER2:

Human epidermal growth factor receptor 2

HIF:

Hypoxia-inducible factor

HR MAS MRS:

High resolution magic angle spinning magnetic resonance spectroscopy

IL-8:

Interleukin 8

IR:

Intermediate response

Lac:

Lactate

LMM:

Linear mixed-effects model

LV:

Latent variable

MICE:

Multiple imputation by chained equations

MR:

Magnetic resonance

MRI:

Magnetic resonance imaging

NR:

No response

OPLS:

Orthogonal partial least squares

OS:

Overall survival

PAM50:

Prediction analysis of microarrays 50

PC:

Principal component

PCA:

Principal component analysis

PCh:

Phosphocholine

pCR:

Pathological complete response

PFS:

Progression-free survival

PLS-DA:

Partial least squares-discriminant analysis

pMRD:

Pathological minimal residual disease

pNR:

Pathological non-responder

PQN:

Probabilistic quotient normalization

q–q:

Quantile–quantile

RMSE:

Root mean square error

ROS:

Reactive oxygen species

R2 :

Coefficient of determination

SDH:

Succinate dehydrogenase

Succ:

Succinate

Tau:

Taurine

TCA:

Tricarboxylic acid

TP:

Time point

VEGF:

Vascular endothelial growth factor

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Acknowledgements

The authors would like to thank Øyvind Salvesen for useful discussions regarding linear mixed-effects models and Santosh Lamichhane for technical support during HR MAS MRS acquisition. The HR MAS MRS analysis was performed at the MR Core Facility, Norwegian University of Science and Technology (NTNU), which is funded by the Faculty of Medicine and Health Sciences at NTNU and the Central Norway Regional Health Authority. The study was funded in part by generous grants from: (1) The Research Council of Norway, Imaging the breast cancer metabolome, Project no 221879, (2) The Pink Ribbon Movement and Norwegian Breast Cancer Society, (3) K. G. Jebsen Center for Breast Cancer Research, (4) Roche Norway, (5) Sanofi-Aventis Norway. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests

The NeoAva study was co-sponsored by Roche Norway and Sanofi-Aventis Norway. Oslo University Hospital is the main sponsor for the NeoAva study.

Authors' contributions

LRE, THH, GFG, RV, JE, LSP, GP, LMCB, ALBD, OE, and TFB participated in the design of the study. ALBD, OE, and TFB conceived the study. LRE, THH, GFG, RV, JE, GP, LMCB, ALBD, OE, and TFB interpreted the data. LRE performed the HR MAS MRS acquisition, statistical analysis, and drafted the manuscript. LSP, SL, EB, OG, ALBD, OE, and TFB participated in acquisition of the data. All authors have read and helped to revise the manuscript. The final manuscript is approved by all the authors.

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Correspondence to Leslie R. Euceda.

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Euceda, L.R., Haukaas, T.H., Giskeødegård, G.F. et al. Evaluation of metabolomic changes during neoadjuvant chemotherapy combined with bevacizumab in breast cancer using MR spectroscopy. Metabolomics 13, 37 (2017). https://doi.org/10.1007/s11306-017-1168-0

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