Update on: proteome analysis in thyroid pathology - part II: overview of technical and clinical enhancement of proteomic investigation of the thyroid lesions

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology

INTRODUCTION

Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions.

AREAS COVERED

This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions.

EXPERT COMMENTARY

Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

Study on Clinicopathological Features and Risk Factors of Patients with Multiple Primary Breast Cancers and Thyroid Disease

Objective

To explore the clinicopathological features and risk factors of patients with multiple primary breast cancers and thyroid disease.

Method

An analytic approach of the reviewing method was adopted to analyze the clinical data of 80 breast cancer patients who were admitted to our hospital from January 2020 to January 2022. They were divided into an observation group (breast cancer with thyroid lesions) and a control group (simple breast cancer) according to whether the clinical data were accompanied with thyroid lesions to compare the clinical characteristics, pathological types, staging characteristics, and molecular biological characteristics of the two groups and to research the risk factors of the two groups.

Result

(1) In the comparison of clinical data, the number of people aged ≥60 in the observation group was higher than that in the control group, and there was significant difference between the groups in the menopausal status data (P < 0.05). There was no statistical difference between the observation group and the control group in the comparison of clinical data of the body mass index, pregnancy frequency, labor frequency, and abortion history (P > 0.05). (2) In the comparison of pathological type and staging data, there was no statistical difference in the comparison of data on the pathological type, histological grade, T staging, N staging, and TNM staging between the observation group and the control group (P > 0.05). (3) In the comparison of data on molecular biology characteristics, there was a statistical difference in the nuclear proliferation antigen data between the observation group and the control group (P < 0.05). There was no statistical difference in the comparison of data on the estrogen receptor, progesterone receptor, human epidermal growth factor receptor-2, and molecular typing between the observation group and the control group (P > 0.05). (4) Logistic regression analysis showed that age, menopausal status, and nuclear proliferation antigen index were the high-risk inflammatory factors for combined thyroid lesions (P < 0.05).

Conclusion

For patients with simple breast cancer, age, menopausal status, and nuclear proliferation antigen index are risk factors for combined thyroid lesions. Therefore, clinical attention should be paid to the above factors in the process of clinical treatment, and early-risk screening should be performed to achieve the purpose of improving the prognosis to the greatest extent.

Proteomic Analysis of Zn Depletion/Repletion in the Hormone-Secreting Thyroid Follicular Cell Line FRTL-5

Zinc deficiency predisposes to a wide spectrum of chronic diseases. The human Zn proteome was predicted to represent about 10% of the total human proteome, reflecting the broad array of metabolic functions in which this micronutrient is known to participate. In the thyroid, Zn was reported to regulate cellular homeostasis, with a yet elusive mechanism. The Fischer Rat Thyroid Cell Line FRTL-5 cell model, derived from a Fischer rat thyroid and displaying a follicular cell phenotype, was used to investigate a possible causal relationship between intracellular Zn levels and thyroid function. A proteomic approach was applied to compare proteins expressed in Zn deficiency, obtained by treating cells with the Zn-specific chelator N,N,N′,N′-tetrakis (2-pyridylmethyl) ethylene-diamine (TPEN), with Zn repleted cells. Quantitative proteomic analysis of whole cell protein extracts was performed using stable isotope dimethyl labelling coupled to nano-ultra performance liquid chromatography-mass spectrometry (UPLC-MS). TPEN treatment led to almost undetectable intracellular Zn, while decreasing thyroglobulin secretion. Subsequent addition of ZnSO₄ fully reversed these phenotypes. Comparative proteomic analysis of Zn depleted/repleted cells identified 108 proteins modulated by either treatment. Biological process enrichment analysis identified functions involved in calcium release and the regulation of translation as the most strongly regulated processes in Zn depleted cells.