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

作者：Yan Zhou, Yingrui Wang, Xiao Shi, Jiatong Wang, Zelin Zang, Likun Zhang, Zhiqiang Gui, Xue Cai, Pingping Hu, Jiaxi Wang, Hanqing Liu, Zhihong Wang, Haixia Guan, Xiaohong Wu, Cenkai Shen, yi He, Mo Li, Hao Zhang, Jianbiao Wang, Yijun Wu, Chuang Chen, Yi Zhu, Yaoting Sun, Zhiyan Liu, Yu Wang, Tiannan Guo · 发表于：Nature Communications · 年份：2026 · DOI：10.1038/s41467-025-67533-7 · 被引用次数：2 · 研究领域：Thyroid Cancer Diagnosis and Treatment、Ferroptosis and cancer prognosis、Clusterin in disease pathology

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. Medullary thyroid carcinoma (MTC) is a rare and aggressive neuroendocrine tumor with limited risk stratification. Here, the authors perform multi-omic analysis of MTC samples from 452 patients across 10 Chinese clinical centers, identify molecular subtypes and develop a prediction model.