Metabolite signature of human malignant thyroid tissue: A systematic review and meta-analysis

Abstract

Background: Thyroid cancer (TC) is the predominant malignancy within the endocrine system. However, the standard method for TC diagnosis lacks the capability to identify the pathological condition of all thyroid lesions. The metabolomics approach has the potential to manage this problem by identifying differential metabolites.

Aims: This study conducted a systematic review and meta-analysis of the NMR-based metabolomics studies in order to identify significant altered metabolites associated with TC.

Methods: A systematic search of published literature in any language in three databases including Embase, PubMed, and Scopus was conducted. Out of 353 primary articles, 12 studies met the criteria for inclusion in the systematic review. Among these, five reports belonging to three articles were eligible for meta-analysis. The correlation coefficient of the orthogonal partial least squares discriminant analysis, a popular model in the multivariate statistical analysis of metabolomic data, was chosen for meta-analysis. The altered metabolites were chosen based on the fact that they had been found in at least three studies.

Results: In total, 49 compounds were identified, 40 of which were metabolites. The increased metabolites in thyroid lesions compared normal samples included lactate, taurine, alanine, glutamic acid, glutamine, leucine, lysine, phenylalanine, serine, tyrosine, valine, choline, glycine, and isoleucine. Lipids were the decreased compounds in thyroid lesions. Lactate and alanine were increased in malignant versus benign thyroid lesions, while, myo-inositol, scyllo-inositol, citrate, choline, and phosphocholine were found to be decreased. The meta-analysis yielded significant results for three metabolites of lactate, alanine, and citrate in malignant versus benign specimens.

Discussion: In this study, we provided a concise summary of 12 included metabolomic studies, making it easier for future researchers to compare their results with the prior findings.

Conclusion: It appears that the field of TC metabolomics will experience notable advancement, leading to the discovery of trustworthy diagnostic and prognostic biomarkers.

Keywords: NMR; metabolomics; meta‐analysis; thyroid carcinoma; thyroid lesions.

FIGURE 1

Flow chart of study selection for the systematic review and meta‐analysis.

FIGURE 2

Increased metabolites (A) and decreased metabolites (B) in thyroid lesions versus normal specimens according a qualitative vote‐counting results. Each metabolite received one vote per article.

FIGURE 3

The bipartite network (A) and the bipartite network projection (B) of increased metabolites in thyroid lesions versus normal. The network was drown based on the Table S2. Compounds with a general term that were not an identifiable metabolite were removed.

FIGURE 4

Correlation diagram of increased metabolites in thyroid lesions versus normal.

FIGURE 5

Increased metabolites (A) and decreased metabolites (B) in malignant vs. benign specimens according a qualitative vote‐counting results. Each metabolite received one vote per article. The correlation between increased (C) and decreased (D) metabolites in malignant vs. benign specimens.

FIGURE 6

Forest plots of meta‐analysis of lactate, alanine, and citrate on the correlation coefficients obtained from the OPLS‐DA models.