In order to identify the proteomic differences between renal cell carcinoma (RCC) and benign renal tumors, we analyzed 168 serum samples from 65 RCC patients, 34 patients with benign renal tumors, and 69 healthy persons using the IMAC-Cu2+ ProteinChip system by surface enhanced laser desorption/ionization mass spectrometry technology. Two decision trees were generated by Biomarker Pattern software to distinguish between RCC versus healthy and RCC versus patients with benign tumors, respectively. Although the sensitivity and specificity of the RCC vs. healthy decision tree were 97.6% and 95.7%, respectively, it could not be used to distinguish RCC from benign renal tumors. The sensitivity of a blind test process using RCC, benign tumors and healthy persons were 92%. The specificity of the test process was 35.3% for benign tumors and 95.5% for healthy persons. The sensitivity and specificity of the RCC-Benign tumors decision tree were 85.7% and 95.5%, respectively. The blind test process using RCC, benign tumors and healthy persons also showed significant results. The sensitivity was 90.0%. The specificity was 95.7% for healthy persons and 90.0% for benign tumors. Combining these data with the results of CT scanning, the sensitivity can be improved over the use of either CT and decision tree analysis and the specificity may reach 100%. Two peaks with molecular masses of 3887.11 Da and 11079.8 Da were detected that are potentially useful for the diagnosis or screening of RCC. It was found that these two peaks can be used, not only to distinguish the RCC vs. healthy cases, but also to distinguish RCC from benign renal tumors. In combination with CT scanning, the sensitivity and specificity of the diagnosis of renal tumors can be improved. However, the decision tree constructed for RCC and healthy persons may not present good specificity for use in distinguishing malignant from benign renal tumors.

Key words: Renal cell carcinoma; Serum; Diagnosis; Proteomics.