The past few decades witnessed a significant increase in the incidence of thyroid cancer worldwide. Hürthle cell carcinoma (HCC), which was also known as oncocytic carcinoma of the thyroid, was reclassified as a distinct histological type of thyroid cancer by the WHO in 2022. Although HCC has a relative poorer prognosis and is generally insensitive to radioiodine treatment, the mechanisms behind HCC are poorly understood currently. In this paper, ioinformatics methods were employed to identify differentially expressed proteins (DEPs) and to analyze their functions in disease. R project was used to identify DEPs in HCC and Hürthle cell adenoma (HCA) with data from the iProx database. DEPs were annotated using the DAVID tool. Protein-protein interaction networks were constructed and visualized using the STRING database and the Cytoscape software. NetworkAnalyst was used to explore the relationships of DEPs, transcription factors, diseases, and drugs. The predicting ability of DEPs were evaluated with receiver operating characteristic (ROC) curves. Three DEPs with best performance were validated using immunohistochemistry. Experimental results show that a total of 793 and 295 DEPs were identified in HCC-normal and HCA-normal comparisons, respectively. The common DEPs of the two comparisons included ATP5F1A, ATP5F1B, UQCRFS1, ATP5F1D, ATP5F1C, COX5A, ATP5PD, ATP5PO, SUCLG1, and ACO2. The ROC analysis showed that ATP5F1B, ATP5F1C, and ATP5PD demonstrated the highest diagnostic accuracy, as indicated by their area under the curve (AUC) values, highlighting their superior performance. Immunohistochemistry confirmed the upregulation of the three proteins in HCC. Differential expression analysis revealed DEPs as potential biomarkers for HCC and HCA. Notably, the most dysregulated proteins are generally involved in the assembly of complex V, indicating a potential association between oxidative phosphorylation and the carcinogenesis of HCC.
A Wed, study studied this question.