Quantitative global proteome and phosphorylome analyses reveal potential biomarkers in kidney cancer

Oncol Rep. 2021 Nov;46(5):237. doi: 10.3892/or.2021.8188. Epub 2021 Sep 16.

Abstract

Currently, high‑throughput quantitative proteomic and transcriptomic approaches have been widely used for exploring the molecular mechanisms and acquiring biomarkers for cancers. Our study aimed to illuminate the multi-dimensional molecular mechanisms underlying renal cell carcinoma (RCC) via investigating the quantitative global proteome and the profile of phosphorylation. A total of 5,428 proteins and 8,632 phosphorylation sites were quantified in RCC tissues, with 709 proteins and 649 phosphorylation sites found to be altered in expression compared with the matched adjacent non‑tumor tissues. These differentially expressed proteins were mainly involved in metabolic process terms involving the glycolysis pathway, oxidative phosphorylation and fatty acid metabolism which have been considered to be a potential mechanism of RCC progression. Moreover, phosphorylation analysis indicated that these upregulated phosphorylated proteins are implicated in the glucagon signaling pathway and cholesterol metabolism, while the downregulated phosphorylated proteins were found to be predominantly involved in glycolysis, the pentose phosphate pathway, carbon metabolism and biosynthesis of amino acids. In addition, several new candidate proteins, CD14, MPO, NCF2, SOD2, PARP1, were found to be upregulated and MUT, ACADM, PCK1 were downregulated in RCC. These proteins may be recognized as new biomarkers for RCC. These findings could broaden our insight into the underlying molecular mechanisms of RCC and identify candidate biomarkers for the treatment of RCC.

Keywords: biomarkers; pathways; phosphorylome; proteome; renal cell carcinoma.

MeSH terms

  • Adult
  • Biomarkers, Tumor / metabolism*
  • Carcinoma, Renal Cell / metabolism*
  • Female
  • Humans
  • Kidney Neoplasms / metabolism*
  • Male
  • Middle Aged
  • Phosphorylation
  • Proteome / metabolism*

Substances

  • Biomarkers, Tumor
  • Proteome

Grants and funding

This work was supported by the National Natural Science Foundation of China (grant nos. 21402173, 81672520, 81773389 and 30973001); the Zhejiang Provincial Natural Science Foundation of China (grant nos. LY17H160020 and LY17H050003); the Zhejiang Province Medical Program (nos. 2014ZDA011 and 2014KYB134); the National Basic Research 973 Program of China (no. 2012CB518304) and the Health Department of Zhejiang Province (no. 2019ZD027).