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Intergrated Multi-omics Sequencing Reveals Metabolic Reprograms in the Progression of ccRCC

<p>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.</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0