Label-free quantitative proteomic analysis reveals potential biomarkers and pathways in renal cell carcinoma

Renal cell carcinoma (RCC) is one of the most common malignancies in adults, and there is still no acknowledged biomarker for its diagnosis, prognosis, recurrence monitoring, and treatment stratification. Besides, little is known about the post-translational modification (PTM) of proteins in RCC. Here, we performed quantitative proteomic analysis on 12 matched pairs of clear cell RCC (ccRCC) and adjacent kidney tissues using liquid chromatography-tandem mass spectrometry (nanoLCMS/MS) and Progenesis LC-MS software (label-free) to identify and quantify the dysregulated proteins. A total of 1872 and 1927 proteins were identified in ccRCC and adjacent kidney tissues, respectively. Among these proteins, 1037 proteins were quantified by Progenesis LC-MS, and 213 proteins were identified as dysregulated proteins between ccRCC and adjacent tissues. Pathway analysis using IPA, STRING, and David tools was performed, which demonstrated the enrichment of cancer-related signaling pathways and biological processes such as mitochondrial dysfunction, metabolic pathway, cell death, and acetylation. Dysregulation of two mitochondrial proteins, acetyl-CoA acetyltransferase 1 (ACAT1) and manganese superoxide dismutase (MnSOD) were selected and confirmed by Western blotting and immunohistochemistry assays using another 6 pairs of ccRCC and adjacent tissues. Further mass spectrometry analysis indicated that both ACAT1 and MnSOD had characterized acetylation at lysine residues, which is the first time to identify acetylation of ACAT1 and MnSOD in ccRCC. Collectively, these data revealed a number of dysregulated proteins and signaling pathways by label-free quantitative proteomic approach in RCC, which shed light on potential diagnostic or prognostic biomarkers and therapeutic molecular targets for clinical intervention of RCC.