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

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.

SUBMITTER: Xu L

PROVIDER: S-EPMC8453689 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background:Cholangiocarcinoma (CCA) is an invasive malignancy arising from biliary epithelial cells; it is the most common primary tumour of the bile tract and has a poor prognosis. The aim of this study was to screen prognostic biomarkers for CCA by integrated multiomics analysis. Methods:The GSE32225 dataset was derived from the Gene Expression Omnibus (GEO) database and comprehensively analysed by using R software and The Cancer Genome Atlas (TCGA) database to obtain the differentially expressed RNAs (DERNAs) associated with CCA prognosis. Quantitative isobaric tags for relative and absolute quantification (iTRAQ) proteomics was used to screen differentially expressed proteins (DEPs) between CCA and nontumour tissues. Through integrated analysis of DERNA and DEP data, we obtained candidate proteins APOF, ITGAV and CASK, and immunohistochemistry was used to detect the expression of these proteins in CCA. The relationship between CASK expression and CCA prognosis was further analysed. Results:Through bioinformatics analysis, 875 DERNAs were identified, of which 10 were associated with the prognosis of the CCA patients. A total of 487 DEPs were obtained by using the iTRAQ technique. Comprehensive analysis of multiomics data showed that CASK, ITGAV and APOF expression at both the mRNA and protein levels were different in CCA compared with nontumour tissues. CASK was found to be expressed in the cytoplasm and nucleus of CCA cells in 38 (45%) of 84 patients with CCA. Our results suggested that patients with positive CASK expression had significantly better overall survival (OS) and recurrence-free survival (RFS) than those with negative CASK expression. Univariate and multivariate analyses demonstrated that negative expression of CASK was a significantly independent risk factor for OS and RFS in CCA patients. Conclusions:CASK may be a tumour suppressor; its low expression is an independent risk factor for a poor prognosis in CCA patients, and so it could be used as a clinically valuable prognostic marker.

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

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