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Renal gene and protein expression signatures for prediction of kidney disease progression.

ABSTRACT: Although chronic kidney disease (CKD) is common, only a fraction of CKD patients progress to end-stage renal disease. Molecular predictors to stratify CKD populations according to their risk of progression remain undiscovered. Here we applied transcriptional profiling of kidneys from transforming growth factor-beta1 transgenic (Tg) mice, characterized by heterogeneity of kidney disease progression, to identify 43 genes that discriminate kidneys by severity of glomerular apoptosis before the onset of tubulointerstitial fibrosis in 2-week-old animals. Among the genes examined, 19 showed significant correlation between mRNA expression in uninephrectomized left kidneys at 2 weeks of age and renal disease severity in right kidneys of Tg mice at 4 weeks of age. Gene expression profiles of human orthologs of the 43 genes in kidney biopsies were highly significantly related (R(2) = 0.53; P < 0.001) to the estimated glomerular filtration rates in patients with CKD stages I to V, and discriminated groups of CKD stages I/II and III/IV/V with positive and negative predictive values of 0.8 and 0.83, respectively. Protein expression patterns for selected genes were successfully validated by immunohistochemistry in kidneys of Tg mice and kidney biopsies of patients with IgA nephropathy and CKD stages I to V, respectively. In conclusion, we developed novel mRNA and protein expression signatures that predict progressive renal fibrosis in mice and may be useful molecular predictors of CKD progression in humans.

SUBMITTER: Ju W

PROVIDER: S-EPMC2684173 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

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Renal gene and protein expression signatures for prediction of kidney disease progression.

Ju Wenjun W Eichinger Felix F Bitzer Markus M Oh Jun J McWeeney Shannon S Berthier Celine C CC Shedden Kerby K Cohen Clemens D CD Henger Anna A Krick Stefanie S Kopp Jeffrey B JB Stoeckert Christian J CJ Dikman Steven S Schröppel Bernd B Thomas David B DB Schlondorff Detlef D Kretzler Matthias M Böttinger Erwin P EP

The American journal of pathology 20090601 6

Although chronic kidney disease (CKD) is common, only a fraction of CKD patients progress to end-stage renal disease. Molecular predictors to stratify CKD populations according to their risk of progression remain undiscovered. Here we applied transcriptional profiling of kidneys from transforming growth factor-beta1 transgenic (Tg) mice, characterized by heterogeneity of kidney disease progression, to identify 43 genes that discriminate kidneys by severity of glomerular apoptosis before the onse ...[more]

PMID: 19465643

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Project description:BackgroundIn 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC's prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA).ResultsWith comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data.ConclusionsThrough pan-cancer screening, we found that many protein biomarkers were prognostic for patients' survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These biomarkers shared a significant overlap, indicating that they were technically replicable.

Dataset Information

Renal gene and protein expression signatures for prediction of kidney disease progression.

Publications

Renal gene and protein expression signatures for prediction of kidney disease progression.

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