Multi-omics Analysis of ACAD11-mediated Lipid Metabolic Reprogramming in the Prognosis of Clear Cell Renal Cell

ABSTRACT: Clear cell renal cell carcinoma (ccRCC) is pathologically characterized by profound intracellular lipid droplet accumulation. To explore the dysregulated lipid metabolic network and identify crucial drivers, an integrated transcriptomic and untargeted metabolomic analysis was conducted. In this study, metabolism-related differentially expressed genes (mDEGs) were screened from the TCGA-KIRC dataset and validated in an independent cohort of 11 paired clinical ccRCC specimens using single-sample gene set enrichment analysis (ssGSEA), confirming the widespread suppression of lipid metabolic pathways. Weighted gene co-expression network analysis (WGCNA) integrated with transcriptomic profiling identified ACAD11 as a core metabolic hub gene. Downregulation of ACAD11 at both transcript and protein levels was validated across clinical stages, WHO/ISUP grades, and tissue microarrays via immunohistochemistry (IHC). Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics was performed on clinical ccRCC tissues and matched adjacent non-tumor controls to capture the ACAD11-associated metabolic landscape. Multi-omics integration demonstrated that ACAD11 deficiency blocks fatty acid $\beta$-oxidation, leading to the pathological accumulation of multiple acylcarnitines. This dataset provides liquid chromatography-mass spectrometry (LC-MS) raw data for ccRCC metabolic profiling.

INSTRUMENT(S): Liquid Chromatography MS - negative - reverse-phase, Liquid Chromatography MS - positive - reverse-phase

PROVIDER: MTBLS15414 | MetaboLights | 2026-08-31

REPOSITORIES: MetaboLights