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ORIGINAL RESEARCH ARTICLE

Deciphering the prognostic significance of liquid–liquid phase separation-related genes in thyroid carcinoma: A transcriptomic analysis

Wenjun Zhao1† ,  Peng Ma1† ,  Yuesheng Wu2 ,  Kai Ma1 ,  Lei Zhang1 ,  Jian Wang1 ,  Jun Zhao1*
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1 Department of Thyroid Surgery and Bariatric Metabolic Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi, China
2 Department of Blood Transfusion, Shanxi Bethune Hospital, Taiyuan, Shanxi, China
†These authors contributed equally to this work.
CP, 025320050 https://doi.org/10.36922/CP025320050
Received: 8 August 2025 | Revised: 11 June 2026 | Accepted: 26 June 2026 | Published online: 20 July 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Thyroid carcinoma (THCA) is a common endocrine malignancy with heterogeneous clinical outcomes, and the prognostic significance of liquid–liquid phase separation (LLPS)-related genes in THCA remains unexplored. This study focuses on THCA, aiming to explore LLPS-related prognostic genes to provide novel theoretical foundations for its diagnosis and treatment. Utilizing public datasets, we identified LLPS-associated prognostic genes in THCA via differential expression analysis, Cox regression, and machine learning. A risk prediction model was subsequently constructed, followed by drug-sensitivity analysis, while the expression of prognostic genes was validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The results revealed seven key prognostic genes: APOE, ARHGEF4, CCL17, DYRK3, EGF, HSPA1A, and MAP1B. The risk model demonstrated strong predictive performance, with area under the curve values exceeding 0.7 for survival rate prediction. Cox regression analysis indicated that both the risk score and age were significant prognostic factors, with the risk score exhibiting a stronger independent prognostic effect (hazard ratio = 2.328). The nomogram accurately predicted survival, and drug-sensitivity analysis showed significant differences in responses to paclitaxel and cyclophosphamide between different risk groups. RT-qPCR validation confirmed upregulation of APOE, CCL17, ARHGEF4, DYRK3, HSPA1A, and MAP1B, along with downregulation of EGF in the THCA group. In conclusion, the identified prognostic genes and risk score model hold potential clinical value in predicting THCA outcomes, contributing to the development of personalized treatment strategies.

Keywords
Thyroid carcinoma
Liquid–liquid phase separation
Transcriptomics
Nomogram
Risk score
Prognosis
Funding
None.
Conflict of interest
The authors declare they have no competing interests.
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