Multi-center multi-omics integration predicts individualized prognosis in medullary thyroid carcinoma

Medullary thyroid carcinoma (MTC) is a rare, aggressive neuroendocrine tumor with limited treatment options and frequent recurrence. Comprehensive recurrence risk stratification remains lacking. Here, we profile 482 MTC samples from 452 patients across ten Chinese clinical centers, identifying 10,092 proteins and mutations in 87.0% of patients. Clinically, MTC grading, concurrent papillary thyroid carcinoma, and lymph node metastasis are significant recurrence risk factors, whereas at the genetic level, RET M918T and RET S891A mutations are correlated with high recurrence risk in sporadic and hereditary MTC, respectively. Ubiquitinomics show downregulated E3 ligases CUL4B and TRIM32 are associated with structural recurrence. We define three molecular subtypes with distinct outcomes and present an integrative machine learning model combining clinical, genomic, and proteomic features, validated in an independent test dataset of 105 patients and a published dataset. This multi-center, multi-omics study enhances the understanding of MTC heterogeneity and facilitates personalized patient management.

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Publication Details

Journal
Nature Communications
Published
2026-01-14
DOI
https://doi.org/10.1038/s41467-025-67533-7
Primary Topic
Thyroid Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-center multi-omics integration predicts individualized prognosis in medullary thyroid carcinoma

Zhiqiang Gui, Likun Zhang, Yaoting Sun, Cenkai Shen et al.
Nature Communications
Thyroid Cancer Diagnosis and Treatment
article

Multi-center multi-omics integration predicts individualized prognosis in medullary thyroid carcinoma

Zhiqiang Gui, Likun Zhang, Yaoting Sun, Cenkai Shen, Zelin Zang, Jiaxi Wang, Hao Zhang, Zhihong Wang, Jiatong Wang, Tiannan Guo, Xue Cai, Hanqing Liu, Yi Zhu, Mo Li, Xiao Shi, Pingping Hu, Yingrui Wang, Zhiyan Liu, Haixia Guan, Xiaohong Wu, Yan Zhou, Jianbiao Wang, yi He, Yu Wang, Chuang Chen, Yijun Wu
article en

Abstract

Medullary thyroid carcinoma (MTC) is a rare, aggressive neuroendocrine tumor with limited treatment options and frequent recurrence. Comprehensive recurrence risk stratification remains lacking. Here, we profile 482 MTC samples from 452 patients across ten Chinese clinical centers, identifying 10,092 proteins and mutations in 87.0% of patients. Clinically, MTC grading, concurrent papillary thyroid carcinoma, and lymph node metastasis are significant recurrence risk factors, whereas at the genetic level, RET M918T and RET S891A mutations are correlated with high recurrence risk in sporadic and hereditary MTC, respectively. Ubiquitinomics show downregulated E3 ligases CUL4B and TRIM32 are associated with structural recurrence. We define three molecular subtypes with distinct outcomes and present an integrative machine learning model combining clinical, genomic, and proteomic features, validated in an independent test dataset of 105 patients and a published dataset. This multi-center, multi-omics study enhances the understanding of MTC heterogeneity and facilitates personalized patient management.

Nature CommunicationsVol. 17(1)
Shanghai Medical College of Fudan University (CN), Shanghai Jiao Tong University (CN), Dalian Medical University (CN), Sir Run Run Shaw Hospital (CN), Westlake University (CN), Wuhan University (CN), Fudan University Shanghai Cancer Center (CN), Second Affiliated Hospital of Dalian Medical University (CN), Zhejiang Provincial People's Hospital (CN), Renmin Hospital of Wuhan University (CN), First Hospital of China Medical University (CN), Shanghai Sixth People's Hospital (CN), Guangdong Academy of Medical Sciences (CN), Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN), Guangdong Provincial People's Hospital (CN), Liaoning Cancer Hospital & Institute (CN), Hangzhou Medical College (CN), Southern Medical University (CN), Zhejiang University (CN), China Medical University (CN)
Westlake University, National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality
Good health and well-being
Openalex Percentile: Top 89%
Thyroid Cancer Diagnosis and Treatment
DOIOpen Access PDFOpenAlex
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