Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression

透明细胞肾细胞癌的多组学分析确定了与疾病进展相关的代谢重编程

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作者:Junyi Hu #, Shao-Gang Wang #, Yaxin Hou #, Zhaohui Chen #, Lilong Liu, Ruizhi Li, Nisha Li, Lijie Zhou, Yu Yang, Liping Wang, Liang Wang, Xiong Yang, Yichen Lei, Changqi Deng, Yang Li, Zhiyao Deng, Yuhong Ding, Yingchun Kuang, Zhipeng Yao, Yang Xun, Fan Li, Heng Li, Jia Hu, Zheng Liu, Tao Wang, Yi H

Abstract

Clear cell renal cell carcinoma (ccRCC) is a complex disease with remarkable immune and metabolic heterogeneity. Here we perform genomic, transcriptomic, proteomic, metabolomic and spatial transcriptomic and metabolomic analyses on 100 patients with ccRCC from the Tongji Hospital RCC (TJ-RCC) cohort. Our analysis identifies four ccRCC subtypes including De-clear cell differentiated (DCCD)-ccRCC, a subtype with distinctive metabolic features. DCCD cancer cells are characterized by fewer lipid droplets, reduced metabolic activity, enhanced nutrient uptake capability and a high proliferation rate, leading to poor prognosis. Using single-cell and spatial trajectory analysis, we demonstrate that DCCD is a common mode of ccRCC progression. Even among stage I patients, DCCD is associated with worse outcomes and higher recurrence rate, suggesting that it cannot be cured by nephrectomy alone. Our study also suggests a treatment strategy based on subtype-specific immune cell infiltration that could guide the clinical management of ccRCC.

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