Endocrinology and Metabolism

Original Articles

Comprehensive Proteomics and Machine Learning Analysis to Distinguish Follicular Adenoma and Follicular Thyroid Carcinoma from Indeterminate Thyroid Nodules: Hee-Sung Ahn, Eyun Song, Chae A Kim, Min Ji Jeon, Yu-Mi Lee, Tea-Yon Sung, Dong Eun Song, Jiyoung Yu, Ji Min Shin, Yeon-Sook Choi, Kyunggon Kim, Won Gu Kim; Received October 16, 2024 Accepted February 24, 2025 Published online April 10, 2025; DOI: https://doi.org/10.3803/EnM.2024.2208 [Epub ahead of print]

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Abstract PDF Supplementary Material PubReader ePub: Background
The preoperative diagnosis of follicular thyroid carcinoma (FTC) is challenging because it cannot be readily distinguished from follicular adenoma (FA) or benign follicular nodular disease (FND) using the sonographic and cytological features typically employed in clinical practice.
Methods
We employed comprehensive proteomics and machine learning (ML) models to identify novel diagnostic biomarkers capable of classifying three subtypes: FTC, FA, and FND. Bottom-up proteomics techniques were applied to quantify proteins in formalin-fixed, paraffin-embedded (FFPE) thyroid tissues. In total, 202 FFPE tissue samples, comprising 62 FNDs, 72 FAs, and 68 FTCs, were analyzed.
Results
Close spectrum-spectrum matching quantified 6,332 proteins, with approximately 9% (780 proteins) differentially expressed among the groups. When applying an ML model to the proteomics data from samples with preoperative indeterminate cytopathology (n=183), we identified distinct protein panels: five proteins (CNDP2, DNAAF5, DYNC1H1, FARSB, and PDCD4) for the FND prediction model, six proteins (DNAAF5, FAM149B1, RPS9, TAGLN2, UPF1, and UQCRC1) for the FA model, and seven proteins (ACTN4, DSTN, MACROH2A1, NUCB1, SPTAN1, TAGLN, and XRCC5) for the FTC model. The classifiers’ performance, evaluated by the median area under the curve values of the random forest models, was 0.832 (95% confidence interval [CI], 0.824 to 0.839) for FND, 0.826 (95% CI, 0.817 to 0.835) for FA, and 0.870 (95% CI, 0.863 to 0.877) for FTC.
Conclusion
Quantitative proteome analysis combined with an ML model yielded an optimized multi‐protein panel that can distinguish FTC from benign subtypes. Our findings indicate that a proteomic approach holds promise for the differential diagnosis of FTC.

Thyroid
Prognostic Impact of Primary Tumor Size in Papillary Thyroid Carcinoma without Lymph Node Metastasis: Chae A Kim, Hye In Kim, Na Hyun Kim, Tae Yong Kim, Won Bae Kim, Jae Hoon Chung, Min Ji Jeon, Tae Hyuk Kim, Sun Wook Kim, Won Gu Kim; Endocrinol Metab. 2025;40(3):405-413. Published online February 25, 2025; DOI: https://doi.org/10.3803/EnM.2024.2199

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We aimed to investigate the prognostic significance of primary tumor size in patients with pT1–T3a N0 M0 papillary thyroid carcinoma (PTC), minimizing the impact of confounding factors.
Methods
A multicenter retrospective study included 5,759 patients with PTC. Those with lymph node metastasis, gross extrathyroidal extension (ETE), and aggressive variants were excluded. Patients were categorized by primary tumor size (≤1, 1.1–2, 2.1–4, and >4 cm) and subdivided based on the presence of microscopic ETE (mETE).
Results
The median age was 48.0 years, and 87.5% were female. The median primary tumor size was 0.7 cm, with mETE identified in 43.7%. The median follow-up was 8.0 years, with an overall recurrent/persistent disease rate of 2.8%. Multivariate analysis identified male sex, larger tumor size, and the presence of mETE as significant prognostic risk factors. The 10-year recurrent/persistent disease rates for tumors ≤1, 1.1–2, 2.1–4, and >4 cm were 2.5%, 4.7%, 11.1%, and 6.0%, respectively. The 2.1–4 cm group had a significantly higher hazard ratio (HR), with the >4 cm group had the highest HR than the ≤1 cm group. Patients with mETE had a higher recurrent/persistent disease rate (4.5%) than those without, with rates by tumor size being 2.6%, 5.6%, 16.7%, and 8.2%.
Conclusion
Larger tumor size and the presence of mETE significantly increased the risk of recurrent/persistent disease in PTC. Patients with pT2–T3a N0 M0 PTC (>2 cm) had a recurrent/persistent disease risk exceeding 5%, warranting vigilant management.

Thyroid
Dynamic Risk Model for the Medical Treatment of Graves’ Hyperthyroidism according to Treatment Duration: Meihua Jin, Chae A Kim, Min Ji Jeon, Won Bae Kim, Tae Yong Kim, Won Gu Kim; Endocrinol Metab. 2024;39(4):579-589. Published online May 23, 2024; DOI: https://doi.org/10.3803/EnM.2024.1918

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Background
Changes in thyrotropin receptor antibody (TRAb) levels are associated with the clinical outcomes of Graves’ hyperthyroidism. However, the effects of the patterns of TRAb changes on patient prognosis according to the treatment duration of antithyroid drugs (ATDs) are not well established.
Methods
In this retrospective cohort study, 1,235 patients with Graves’ hyperthyroidism who were treated with ATDs for more than 12 months were included. Patients were divided into two groups according to treatment duration: group 1 (12–24 months) and group 2 (>24 months). Risk prediction models comprising age, sex, and either TRAb levels at ATD withdrawal (model A) or patterns of TRAb changes (model B) were compared.
Results
The median treatment duration in groups 1 (n=667, 54%) and 2 (n=568, 46%) was 17.3 and 37.1 months, respectively. The recurrence rate was significantly higher in group 2 (47.9%) than in group 1 (41.4%, P=0.025). Group 2 had significantly more goiter, thyroid eye disease, and fluctuating and smoldering type of TRAb pattern compared with group 1 (all P<0.001). The patterns of TRAb changes were an independent risk factor for recurrence after adjusting for other confounding factors in all patients, except in group 1. Integrated discrimination improvement and net reclassification improvement analyses showed that model B performed better than model A in all patients, except in group 1.
Conclusion
The dynamic risk model, including the patterns of TRAb changes, was more suitable for predicting prognosis in patients with Graves’ hyperthyroidism who underwent longer ATD treatment duration.

Citations

Citations to this article as recorded by

Integrating shear wave elastography into clinical prediction of Graves’ disease recurrence: a novel risk scoring system
Xiao-Yun Zha, Ze-Hong Xu, Jia-Jia Dong, Liang-Xiao Xie, Peng-Bin Lai, Chang-Shun Wei, Hua-Qiang Zheng, Duo-Bin Huang, Jin-Zhi Wu
Frontiers in Endocrinology.2025;[Epub] CrossRef

Thyroid
Prognostic Roles of Inflammatory Biomarkers in Radioiodine-Refractory Thyroid Cancer Treated with Lenvatinib: Chae A Kim, Mijin Kim, Meihua Jin, Hee Kyung Kim, Min Ji Jeon, Dong Jun Lim, Bo Hyun Kim, Ho-Cheol Kang, Won Bae Kim, Dong Yeob Shin, Won Gu Kim; Endocrinol Metab. 2024;39(2):334-343. Published online April 4, 2024; DOI: https://doi.org/10.3803/EnM.2023.1854

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Background
Inflammatory biomarkers, such as the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR), serve as valuable prognostic indicators in various cancers. This multicenter, retrospective cohort study assessed the treatment outcomes of lenvatinib in 71 patients with radioactive iodine (RAI)-refractory thyroid cancer, considering the baseline inflammatory biomarkers.
Methods
This study retrospectively included patients from five tertiary hospitals in Korea whose complete blood counts were available before lenvatinib treatment. Progression-free survival (PFS) and overall survival (OS) were evaluated based on the median value of inflammatory biomarkers.
Results
No significant differences in baseline characteristics were observed among patients grouped according to the inflammatory biomarkers, except for older patients with a higher-than-median NLR (≥2) compared to their counterparts with a lower NLR (P= 0.01). Patients with a higher-than-median NLR had significantly shorter PFS (P=0.02) and OS (P=0.017) than those with a lower NLR. In multivariate analysis, a higher-than-median NLR was significantly associated with poor OS (hazard ratio, 3.0; 95% confidence interval, 1.24 to 7.29; P=0.015). However, neither the LMR nor the PLR was associated with PFS. A higher-than-median LMR (≥3.9) was significantly associated with prolonged OS compared to a lower LMR (P=0.036). In contrast, a higher-than-median PLR (≥142.1) was associated with shorter OS compared to a lower PLR (P=0.039).
Conclusion
Baseline inflammatory biomarkers can serve as predictive indicators of PFS and OS in patients with RAI-refractory thyroid cancer treated with lenvatinib.

Citations

Citations to this article as recorded by

Nomogram Model for Prognosis of Distant Metastatic DTC Based on Inflammatory and Clinicopathological Factors
Chenghui Lu, Guoqiang Wang, Zengmei Si, Fengqi Li, Xinfeng Liu, Na Han, Congcong Wang, Jiao Li, Xufu Wang
Journal of the Endocrine Society.2025;[Epub] CrossRef

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