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Metabolomics

, 14:141 | Cite as

Diagnosis of post-surgical fine-needle aspiration biopsies of thyroid lesions with indeterminate cytology using HRMAS NMR-based metabolomics

  • Lamya Rezig
  • Adele Servadio
  • Liborio Torregrossa
  • Paolo Miccoli
  • Fulvio Basolo
  • Laetitia Shintu
  • Stefano Caldarelli
Original Article
  • 25 Downloads

Abstract

Introduction

Ultrasound examination coupled with fine-needle aspiration (FNA) cytology is the gold standard for the diagnosis of thyroid cancer. However, about 10–40% of these analyses cannot be conclusive on the malignancy of the lesions and lead to surgery. The cytological indeterminate FNA biopsies are mainly constituted of follicular—patterned lesions, which are benign in 80% of the cases.

Objectives

The development of a FNAB classification approach based on the metabolic phenotype of the lesions, complementary to cytology and other molecular tests in order to limit the number of patients undergoing unnecessary thyroidectomy.

Methods

We explored the potential of a NMR-based metabolomics approach to improve the quality of the diagnosis from FNABs, using thyroid tissues collected post-surgically.

Results

The NMR-detected metabolites were used to produce a robust OPLSDA model to discriminate between benign and malignant tumours. Malignancy was correlated with amino acids such as tyrosine, serine, alanine, leucine and phenylalanine and anti-correlated with myo-inositol, scyllo-inositol and citrate. Diagnosis accuracy was of 84.8% when only indeterminate lesions were considered.

Conclusion

These results on model FNAB indicate that there is a clear interest in exploring the possibility to export NMR metabolomics to pre-surgical diagnostics.

Keywords

Thyroid cancer Fine-needle aspiration Indeterminate cytology Follicular NMR-based metabolomics Diagnosis 

Abbreviations

FNA

Fine-needle aspiration

FNAB

Fine-needle aspiration biopsy

FA

Follicular adenoma

FTC

Follicular thyroid carcinoma

PTC

Papillary thyroid carcinoma

MTC

Medullary thyroid carcinoma

TCV-PTC

Tll cell variant of papillary thyroid carcinoma

CV-PTC

Classic variant of papillary thyroid carcinoma

FV-PTC

Follicular variant of papillary thyroid carcinoma

HRMAS

High-resolution magic angle spinning

NMR

Nuclear magnetic resonance

PCA

Principal component analysis

OPLS-DA

Orthogonalized projections to the latent structures discriminant analysis

CV-ANOVA

Cross-validation analysis of variance

Tg

Thyroglobulin

TCA

Tricarboxylic acid

VIP

Variable importance in the prediction

Notes

Acknowledgements

This study was funded by Agence nationale de la recherche (Grant No. ANR-2011- JS08-014-01).

Author Contributions

PM, FB and SC designed research. LR, AS performed research. AS and LT performed the cytological and histological analyses. LS analysed the data. LS and LT wrote the paper. All authors read and approved the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments and approved by the Local Ethics Committee of the Azienda Ospedaliero Universitaria Pisana.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

11306_2018_1437_MOESM1_ESM.docx (642 kb)
Supplementary material 1 (DOCX 642 KB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Aix Marseille Univ, CNRS, Centrale Marseille, iSm2MarseilleFrance
  2. 2.Division of Surgical PathologyUniversity Hospital of PisaPisaItaly
  3. 3.Department of Surgical, Medical, Molecular Pathology and Critical AreaUniversity of PisaPisaItaly

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