Abstract
This study examined metabolite profile differences between serum samples of thyroid papillary carcinoma (PTC) patients and healthy controls, aiming to identify candidate biomarkers and pathogenesis pathways in this cancer type. Serum samples were collected from PTC patients (n = 80) and healthy controls (n = 80). Using principal component analysis (PCA), partial least squares discrimination analysis(PLS-DA), orthogonal partial least square discriminant analysis (OPLS-DA), t-tests, and the volcano plot, a model of abnormal metabolic pathways in PTC was constructed. PCA, PLS-DA, and OPLS-DA analysis revealed differences in serum metabolic profiles between the PTC and control group. OPLS-Loading plot analysis, combined with Variable importance in the projection (VIP)>1, Fold change (FC) > 1.5, and p < 0.05 were used to screen 64 candidate metabolites. Among them, 22 metabolites, including proline betaine, taurocholic acid, L-phenylalanine, retinyl beta-glucuronide, alpha-tocotrienol, and threonine acid were upregulated in the PTC group; meanwhile, L-tyrosine, L-tryptophan, 2-arachidonylglycerol, citric acid, and other 42 metabolites were downregulated in this group. There were eight abnormal metabolic pathways related to the differential metabolites, which may be involved in the pathophysiology of PTC. Six metabolites yielded an area under the receiver operating curve of >0.75, specifically, 3-hydroxy-cis-5-tetradecenoylcarnitine, aspartylphenylalanine, l-kynurenine, methylmalonic acid, phenylalanylphenylalanine, and l-glutamic acid. The Warburg effect was observed in PTC. The levels of 3-hydroxy-cis-5-tetradecenoylcarnitine, aspartylphenylalanine, l-kynurenine, methylmalonic acid, phenylalanine, and L-glutamic acid may help distinguish PTC patients from healthy controls. Aspartic acid metabolism, glutamic acid metabolism, urea cycle, and tricarboxylic acid cycle are involved in the mechanism of PTC.
Highlights
Thyroid cancer is the most common type of endocrine tumor in clinical practice, accounting for 1.1% of all malignant tumors (Bray et al, 2018), while PTC is the most common type of thyroid cancer, accounting for ∼90% of all cases
In the positive and negative ion mode, through the principal component analysis (PCA) model, we found that the clustering degree of the Quality Control (QC) samples was good, indicating that the instrument was stable during this experiment
After 200 permutations tests, the R2 intercept of the substitution test in the positive ion mode was 0.831, and the intercept of Q2 was −0.0441 (Figure 2F), suggesting model reliability, given no evidence of over-fitting. These findings indicate that the PLS-DA model could be used to distinguish PTC patients from healthy controls; The parameters included in the model in both ion modes are shown in Supplementary Tables 3, 4
Summary
Thyroid cancer is the most common type of endocrine tumor in clinical practice, accounting for 1.1% of all malignant tumors (Bray et al, 2018), while PTC is the most common type of thyroid cancer, accounting for ∼90% of all cases. FNAC is an invasive examination, and the preoperative acceptance of patients is generally limited, but the clinical applicability of the latter is not very strong. Overall, this evidence indicates a need for a stable and reliable biomarker to assist in the diagnosis of thyroid cancer
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