PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: Ian M Thompson; Donna Pauler Ankerst; Chen Chi; M Scott Lucia; Phyllis J Goodman; John J Crowley; Howard L Parnes; Charles A Coltman Journal: JAMA Date: 2005-07-06 Impact factor: 56.272
Authors: M F Mitchell; S B Cantor; C Brookner; U Utzinger; D Schottenfeld; R Richards-Kortum Journal: Obstet Gynecol Date: 1999-11 Impact factor: 7.661
Authors: Amnon Zisman; Allan J Pantuck; Jeffery Wieder; Debby H Chao; Fredrick Dorey; Jonathan W Said; Jean B deKernion; Robert A Figlin; Arie S Belldegrun Journal: J Clin Oncol Date: 2002-12-01 Impact factor: 44.544
Authors: Liqun Wang; Kwang-Hwan Jhee; Xiang Hua; Patricia M DiBello; Donald W Jacobsen; Warren D Kruger Journal: Circ Res Date: 2004-04-22 Impact factor: 17.367
Authors: Richard D Unwin; Rachel A Craven; Patricia Harnden; Sarah Hanrahan; Nick Totty; Margaret Knowles; Ian Eardley; Peter J Selby; Rosamonde E Banks Journal: Proteomics Date: 2003-08 Impact factor: 3.984
Authors: Jopi J W Mikkonen; Surya P Singh; Ramin Akhi; Tuula Salo; Reijo Lappalainen; Wilfredo A González-Arriagada; Márcio Ajudarte Lopes; Arja M Kullaa; Sami Myllymaa Journal: Oncol Lett Date: 2018-09-07 Impact factor: 2.967