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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:Breast cancer (BC) is the second most frequently diagnosed cancer and accounts for approximately 25% of new cancer cases in Canadian women. Using biomarkers as a less-invasive BC diagnostic method is currently under investigation but is not ready for practical application in clinical settings. During the last decade, extracellular vesicles (EVs) have emerged as a promising source of biomarkers because they contain cancer-derived proteins, RNAs, and metabolites. In this study, EV proteins from small EVs (sEVs) and medium EVs (mEVs) were isolated from BC MDA-MB-231 and MCF7 and non-cancerous breast epithelial MCF10A cell lines and then analyzed by two approaches: global proteomic analysis and enrichment of EV surface proteins by Sulfo-NHS-SS-Biotin labeling. From the first approach, proteomic profiling identified 2459 proteins, which were subjected to comparative analysis and correlation network analysis. Twelve potential biomarker proteins were identified based on cell line-specific expression and filtered by their predicted co-localization with known EV marker proteins, CD63, CD9, and CD81. This approach resulted in the identification of 11 proteins, four of which were further investigated by Western blot analysis. The presence of transmembrane serine protease matriptase (ST14), claudin-3 (CLDN3), and integrin alpha-7 (ITGA7) in each cell line was validated by Western blot, revealing that ST14 and CLDN3 may be further explored as potential EV biomarkers for BC. The surface labeling approach enriched proteins that were not identified using the first approach. Ten potential BC biomarkers (Glutathione S-transferase P1 (GSTP1), Elongation factor 2 (EEF2), DEAD/H box RNA helicase (DDX10), progesterone receptor (PGR), Ras-related C3 botulinum toxin substrate 2 (RAC2), Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), Aconitase 2 (ACO2), UTP20 small subunit processome component (UTP20), NEDD4 binding protein 2 (N4BP2), Programmed cell death 6 (PDCD6)) were selected from surface proteins commonly identified from MDA-MB-231 and MCF7, but not identified in MCF10A EVs. In total, 846 surface proteins were identified from the second approach, of which 11 were already known as BC markers. This study supports the proposition that Evs are a rich source of known and novel biomarkers that may be used for non-invasive detection of BC. Furthermore, the presented datasets could be further explored for the identification of potential biomarkers in BC.

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

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