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

Clear cell renal cell carcinoma (ccRCC) is a complex disease with remarkable immune and metabolic heterogeneity. Here, we present a TJ-RCC cohort (RCC cohort of Tongji hospital), and we perform genomic, transcriptomic, proteomic, metabonomic and spatial multi-omic profiling on 100 ccRCC cases. Using the scRNA-seq-derived signature, we identify 4 ccRCC subtypes. Multilevel profiling distinguishes a unique ccRCC subtype, De-clear cell differentiated (DCCD) -ccRCC, with distinctive metabolic features. DCCD cancer cells are characterized by fewer lipid droplets, more inhibited metabolic activity, enhanced nutrients 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 it cannot be cured by nephrectomy alone. This study provides a treatment strategy based on immune subtypes, which could guide clinical management of ccRCC.