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Multi-omics characterization of esophageal squamous cell carcinoma identifies molecular subtypes and therapeutic targets
Dengyun Zhao, … , Zigang Dong, Kangdong Liu
Dengyun Zhao, … , Zigang Dong, Kangdong Liu
Published April 23, 2024
Citation Information: JCI Insight. 2024;9(10):e171916. https://doi.org/10.1172/jci.insight.171916.
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Research Article Oncology Therapeutics

Multi-omics characterization of esophageal squamous cell carcinoma identifies molecular subtypes and therapeutic targets

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Abstract

Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal cancer and is characterized by an unfavorable prognosis. To elucidate the distinct molecular alterations in ESCC and investigate therapeutic targets, we performed a comprehensive analysis of transcriptomics, proteomics, and phosphoproteomics data derived from 60 paired treatment-naive ESCC and adjacent nontumor tissue samples. Additionally, we conducted a correlation analysis to describe the regulatory relationship between transcriptomic and proteomic processes, revealing alterations in key metabolic pathways. Unsupervised clustering analysis of the proteomics data stratified patients with ESCC into 3 subtypes with different molecular characteristics and clinical outcomes. Notably, subtype III exhibited the worst prognosis and enrichment in proteins associated with malignant processes, including glycolysis and DNA repair pathways. Furthermore, translocase of inner mitochondrial membrane domain containing 1 (TIMMDC1) was validated as a potential prognostic molecule for ESCC. Moreover, integrated kinase-substrate network analysis using the phosphoproteome nominated candidate kinases as potential targets. In vitro and in vivo experiments further confirmed casein kinase II subunit α (CSNK2A1) as a potential kinase target for ESCC. These underlying data represent a valuable resource for researchers that may provide better insights into the biology and treatment of ESCC.

Authors

Dengyun Zhao, Yaping Guo, Huifang Wei, Xuechao Jia, Yafei Zhi, Guiliang He, Wenna Nie, Limeng Huang, Penglei Wang, Kyle Vaughn Laster, Zhicai Liu, Jinwu Wang, Mee-Hyun Lee, Zigang Dong, Kangdong Liu

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