Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression.
Junyi HuShao-Gang WangYaxin HouZhaohui ChenLilong LiuRuizhi LiNisha LiLijie ZhouYu YangLiping WangLiang WangXiong YangYichen LeiChangqi DengYang LiZhiyao DengYuhong DingYingchun KuangZhipeng YaoYang XunFan LiHeng LiJia HuZheng LiuTao WangYi HaoXuanmao JiaoWei GuanZhen TaoShancheng RenKe ChenPublished in: Nature genetics (2024)
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.
Keyphrases
- single cell
- poor prognosis
- rna seq
- long non coding rna
- high throughput
- newly diagnosed
- genome wide
- ejection fraction
- healthcare
- renal cell carcinoma
- emergency department
- clear cell
- robot assisted
- metabolic syndrome
- chronic kidney disease
- adipose tissue
- dna methylation
- fatty acid
- weight loss
- insulin resistance
- label free