Integrated proteogenomic and metabolomic characterization of papillary thyroid cancer with different recurrence risks

Ning Qu, Di Chen, Ben Ma, Lijun Zhang, Qiuping Wang, Yuting Wang, Hongping Wang, Zhaoxian Ni, Wen Wang, Tian Liao, Jun Xiang, Yulong Wang, Shi Jin, Dixin Xue, Weili Wu, Yu Wang (), Qinghai Ji (), Hui He (), Hai-long Piao () and Rongliang Shi ()
Additional contact information
Ning Qu: Fudan University Shanghai Cancer Center
Di Chen: Chinese Academy of Sciences
Ben Ma: Fudan University Shanghai Cancer Center
Lijun Zhang: Ganmei Affiliated Hospital of Kunming Medical University (The First People’s Hospital of Kunming)
Qiuping Wang: Chinese Academy of Sciences
Yuting Wang: Fudan University Shanghai Cancer Center
Hongping Wang: Shanghai University of Traditional Chinese Medicine
Zhaoxian Ni: Fudan University Shanghai Cancer Center
Wen Wang: Chinese Academy of Sciences
Tian Liao: Fudan University Shanghai Cancer Center
Jun Xiang: Fudan University Shanghai Cancer Center
Yulong Wang: Fudan University Shanghai Cancer Center
Shi Jin: The First Affiliated Hospital of Dalian Medical University
Dixin Xue: The Third Affiliated Hospital of Wenzhou Medical University
Weili Wu: The Third Affiliated Hospital of Wenzhou Medical University
Yu Wang: Fudan University Shanghai Cancer Center
Qinghai Ji: Fudan University Shanghai Cancer Center
Hui He: Fudan University Shanghai Cancer Center
Hai-long Piao: Chinese Academy of Sciences
Rongliang Shi: Fudan University Shanghai Cancer Center

Nature Communications, 2024, vol. 15, issue 1, 1-18

Abstract: Abstract Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to different recurrence risks (RRs) remain poorly defined. Here, we perform an integrative proteogenomic and metabolomic characterization of 102 Chinese PTC patients with different RRs. Genomic profiling reveals that mutations in MUC16 and TERT promoter as well as multiple gene fusions like NCOA4-RET are enriched by the high RR. Integrative multi-omics analyses further describe the multi-dimensional characteristics of PTC, especially in metabolism pathways, and delineate dominated molecular patterns of different RRs. Moreover, the PTC patients are clustered into four subtypes (CS1: low RR and BRAF-like; CS2: high RR and metabolism type, worst prognosis; CS3: high RR and immune type, better prognosis; CS4: high RR and BRAF-like) based on the omics data. Notably, the subtypes display significant differences considering BRAF and TERT promoter mutations, metabolism and immune pathway profiles, epithelial cell compositions, and various clinical factors (especially RRs and prognosis) as well as druggable targets. This study can provide insights into the complex molecular characteristics of PTC recurrences and help promote early diagnosis and precision treatment of recurrent PTC.

Date: 2024
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DOI: 10.1038/s41467-024-47581-1

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