Dataset Information

Differential activation of NRF2 signaling pathway in renal cell carcinoma cells

ABSTRACT: Comprehensive comparative proteomic analysis of Caki-1, a classical ccRCC cell line versusCaki-2 cells using tandem mass tag reagents based approach for identification and quantitation of proteins in the two cell lines by liquid chromatography tandem mass spectrometry (LC/MS/MS).

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Kidney

DISEASE(S): Kidney Cancer

SUBMITTER: Julius Nyalwidhe

LAB HEAD: Julius O Nyalwidhe

PROVIDER: PXD040083 | Pride | 2023-07-20

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	CAKI-Cells_TMT.msf	Msf
	CAKI-Cells_TMT.tsv.xlsx	Xlsx
	CAKI-Cells_TMT_Fraction_1.raw	Raw
	CAKI-Cells_TMT_Fraction_2.raw	Raw
	CAKI-Cells_TMT_Fraction_3.raw	Raw

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Publications

Differential Activation of NRF2 Signaling Pathway in Renal-Cell Carcinoma Caki Cell Lines.

Hitefield Naomi L NL Mackay Stephen S Hays Lauren E LE Chen Shimin S Oduor Ian O IO Troyer Dean A DA Nyalwidhe Julius O JO

Biomedicines 20230324 4

Renal-cell carcinoma (RCC) is a heterogeneous disease consisting of several subtypes based on specific genomic profiles and histological and clinical characteristics. The subtype with the highest prevalence is clear-cell RCC (ccRCC), next is papillary RCC (pRCC), and then chromophobe RCC (chRCC). The ccRCC cell lines are further subdivided into prognostic expression-based subtypes ccA or ccB. This heterogeneity necessitates the development, availability, and utilization of cell line models with ...[more]

PMID: 37189628

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Project description:Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney. Currently, there are no biomarkers for the diagnostic, prognostic, or predictive applications in RCC. MicroRNAs (miRNAs) are short non protein-coding RNAs that negatively regulate gene expression and have been shown to be involved in cancer. We analyzed a total of 70 matched pairs of clear cell RCC (ccRCC) and normal kidney tissues from the same patients by microarray analysis and validated our results by quantitative real time PCR. We identified 166 miRNAs significantly dysregulated in ccRCC. MiR-122, miR-155 and miR-210 had the highest fold changes of overexpression while miR-200c, miR-335, and miR-218 were the most downregulated. We performed extensive bioinformatics analysis including a combinatorial analysis of previously reported miRNAs dysregulated in RCC and extensive target prediction analysis. Many miRNAs were predicted to target a number of genes involved in RCC pathogenesis. Our results showed that miRNA dysregulation in RCC can be attributed in part, to chromosomal aberrations, the co-regulation of miRNA clusters, and co-expression with host genes. We also correlated miRNA expression with clinical characteristics and found miR-155 expression was correlated with ccRCC tumor size. In conclusion, our analysis showed that a number of miRNAs are dysregulated in ccRCC and may contribute to kidney cancer pathogenesis by targeting more than one key molecule. We identified mechanisms that may contribute to miRNA dysregulation in ccRCC. Dysregulated miRNAs represent potential biomarkers for kidney cancer. We preformed a miRNA microarray on 20 pairs of matched primary clear cell renal cell carcinoma (ccRCC) and normal kidney tissue from the same patient (St. Michael's Hospital, Toronto, Canada). One matched pair was used per array for a total of 20 arrays. Microarray results were validated by quantitative real time PCR using an independent set of 50 matched pairs of ccRCC and normal kidney tissue from the same patient.