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Serum amino acid levels as a biomarker for renal cell carcinoma.

ABSTRACT: Prognosis in renal cell carcinoma is dependent on tumor stage at presentation, with significant differences in survival between early and late stage disease. Currently to our knowledge no screening tests or biomarkers have been identified for the early detection of kidney cancer. Therefore, we investigated whether serum amino acid profiles are a potentially useful biomarker in patients with renal cell carcinoma.The concentrations of 26 amino acids were determined in serum taken preoperatively from 189 patients with renal cell carcinoma, and from 104 age and sex matched controls.Statistically significant changes were observed in patient levels of 15 amino acids, with 13 being decreased and 2 being increased. A logistic regression model using 8 amino acids including cysteine, ornithine, histidine, leucine, tyrosine, proline, valine and lysine was created to distinguish cases from controls. A receiver operator curve based on this model had an area under the curve of 0.81. This same model also had predictive value in terms of overall survival and tumor recurrence in patients with renal cell carcinoma.Our findings suggest that serum amino acid levels may be useful as a screening tool for the identification of individuals with renal cell carcinoma and the prediction of outcomes.

SUBMITTER: Mustafa A

PROVIDER: S-EPMC3180900 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature

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Serum amino acid levels as a biomarker for renal cell carcinoma.

Mustafa Aladdin A Gupta Sapna S Hudes Gary R GR Egleston Brian L BL Uzzo Robert G RG Kruger Warren D WD

The Journal of urology 20110817 4

<h4>Purpose</h4>Prognosis in renal cell carcinoma is dependent on tumor stage at presentation, with significant differences in survival between early and late stage disease. Currently to our knowledge no screening tests or biomarkers have been identified for the early detection of kidney cancer. Therefore, we investigated whether serum amino acid profiles are a potentially useful biomarker in patients with renal cell carcinoma.<h4>Materials and methods</h4>The concentrations of 26 amino acids we ...[more]

PMID: 21849193

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Project description:Background: Amino acid metabolism (AAM) deregulation, an emerging metabolic hallmark of malignancy, plays an essential role in tumour proliferation, invasion, and metastasis. However, the expression of AAM-related genes and their correlation with prognosis in clear cell renal cell carcinoma (ccRCC) remain elusive. This study aims to develop a novel consensus signature based on the AAM-related genes. Methods: The RNA-seq expression data and clinical information for ccRCC were downloaded from the TCGA (KIRC as training dataset) and ArrayExpress (E-MTAB-1980 as validation dataset) databases. The AAM-related differentially expressed genes were screened via the "limma" package in TCGA cohorts for further analysis. The machine learning algorithms (Lasso and stepwise Cox (direction = both)) were then utilised to establish a novel consensus signature in TCGA cohorts, which was validated by the E-MTAB-1980 cohorts. The optimal cutoff value determined by the "survminer" package was used to categorise patients into two risk categories. The Kaplan-Meier curve, the receiver operating characteristic (ROC) curve, and multivariate Cox regression were utilised to evaluate the prognostic value. The nomogram based on the gene signature was constructed, and its performance was analysed using ROC and calibration curves. Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were conducted on its potential mechanisms. The relationship between the gene signature and key immune checkpoint, N6-methyladenosine (m6A)-related genes, and sensitivity to chemotherapy was assessed. Results: A novel consensus AMM-related gene signature consisting of IYD, NNMT, ACADSB, GLDC, and PSAT1 is developed to predict prognosis in TCGA cohorts. Kaplan-Meier survival shows that overall survival in the high-risk group was more dismal than in the low-risk group in the TCGA cohort, validated by the E-MTAB-1980 cohort. Multivariate regression analysis also demonstrates that the gene signature is an independent predictor of ccRCC. Immune infiltration analysis highlighted that the high-risk group indicates an immunosuppressive microenvironment. It is also closely related to the level of key immune checkpoints, m6A modification, and sensitivity to chemotherapy drugs. Conclusion: In this study, a novel consensus AAM-related gene signature is developed and validated as an independent predictor to robustly predict the overall survival from ccRCC, which would further improve the clinical outcomes.

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Serum amino acid levels as a biomarker for renal cell carcinoma.

Publications

Serum amino acid levels as a biomarker for renal cell carcinoma.

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