iTRAQ-based quantitative proteomic analysis reveals potential early diagnostic markers of clear-cell Renal cell carcinoma.

Early detection is the key to improve the prognosis of kidney cancer. This study profiled and identified differentially expressed serum proteins in stage T1a renal cell carcinoma (RCC) using isobaric tags for relative and absolute quantification (iTRAQ)-based mass spectrometry. A total amount of 99 serum samples including 29 patients with ccRCC, 24 patients with a benign kidney mass, 28 patients with another type of urological tumor (20 cases of transitional cell carcinoma and 8 cases of prostate cancer or a male genital tumor), and 18 healthy controls were subjected to iTRAQ-based mass spectrometry. ProteinPilot software was used to identify the differentially expressed serum proteins in RCC compared to the other three populations. Hierarchical clustering analysis according to The Cancer Genome Atlas (TCGA) RCC database was then performed as the cross-platform validation. Immunohistochemistry was performed to verify the expression of selected proteins in tissue samples from these subjects. iTRAQ identified 27 differentially expressed serum proteins in the RCC patients, and 11 of these proteins were cross validated in RCC tissues from the TCGA database. The expression of C1QC, C1QB, S100A8, S100A9, ceruplasmin, and lumican was verified and associated with the tumor stage and/or grade. There were 27 differentially expressed proteins in early-stage RCC identified by iTRAQ; among them, the expression of C1QC, C1QB, S100A8, S100A9, ceruplasmin, and lumican were associated with the tumor stage and/or grade. Further studies are needed to confirm these data for their use as biomarkers for the early detection of RCC.

Proteins S100A8 and S100A9 are potential biomarkers for renal cell carcinoma in the early stages: results from a proteomic study integrated with bioinformatics analysis.

In order to investigate the two members of the EF­hand Ca2+ binding protein S100 family, S100A8 and S100A9, in renal cell carcinoma (RCC), serum samples were collected from patients with RCC, transitional cell carcinoma in the kidney, benign renal masses and normal controls. The samples were analyzed by isobaric tags for relative and absolute quantification technology to identify the differential expression of S100A8 and S100A9 in the respective groups. Hierarchical clustering analysis was then conducted for the samples and the relevant selected gene. The cross­platform analysis for the external validation was performed by means of The Cancer Genome Atlas database, containing the gene/microRNA expression pattern and clinical information of patients with RCC. Immunohistochemical staining was used to verify the expression of S100A8 and S100A9 in the four groups. As a result, serum and mRNA expression levels of S100A8 and S100A9 were found to be upregulated in patients with RCC compared with the other three groups, which was consistent with the result of the upregulated expression of mRNA levels in RCC tissue. The overexpression of S100A8 and S100A9 in cancer cells was also confirmed by immunohistochemistry. In addition, bioinformatics revealed that let­7, a microRNA formerly identified as an inhibiting factor of RCC was downregulated in RCC, which contrasted with S100A8. It was also complementary to the sequence at the 3' untranslated region terminal of S100A8. Therefore, indicating that S100A8 and S100A9 may serve as biomarkers for the detection of RCC.