ccRCC is a complex disease with remarkable immune and metabolic heterogeneity. Here, we present a TJ-RCC cohort, performing genomic, transcriptomic, proteomic, metabonomic and spatial multi-omic profiling on 100 ccRCC cases. Using the scRNA-seq-derived signature, we identify 4 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, extremely 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 indicates worse outcomes and higher recurrence rate, indicating it cannot be cured by nephrectomy alone. This study provides a treatment strategy based on immune subtypes, which could enable precise clinical management of ccRCC.
The source code has been meticulously organized to mirror the sequence of its appearance within the article. We have segmented the code pertinent to various omics studies and appropriately allocated them across corresponding directories. Additionally, the source data associated with each section of the code have been conveniently bundled within their respective file folders. Sequencing datasets generated in this work are available at Zenodo (https://zenodo.org/record/8063124) and Mendeley database under (DOI: 10.17632/x4krt22tf4.1) and (DOI: 10.17632/rhh5rpvxhd.1).