Application Of Serum Protein Fingerprint Model In Diagnosis Of Renal Cell Carcinoma And Their Clinical Significance

Objective:To detect new biomarkers and to establish a serum protein fingerprint model for early detection ,diagnosis and prognosis of renal cell carcinoma and to discuss their clinical significance. Methods: The serum samples of 53 renal cell carcinoma patients, 47 benign renal masses patients ,68 healthy volunteers and 25 patients with renal cell carcinoma after operation were randomly divided into 2 sets:training set(n =118,including 38 renal cell carcinoma patients,30 benign renal masses patients,and 50 healthy volunteers)and test set (n =50).The fingerprint expressions of protein chips were obtained by using surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and CM l0proteinchip,The data of spectra were analyzed by support vector machine(SVM)to establish a diagnostic model. To study the changes of serum proteomic spectra in patients with renal cell carcinoma before and after surgical operation, localized renal cell carcinoma and locally advanced renal cell carcinoma. Results: Five peaks with the molecular weight of 5350,4100,3446,5027 and 6115 were detected and the detective model combined with 5 biomarkers could differentiate the serum of renal cell carcinoma from that of healthy volunteers with a specificity of 92% and a sensitivity of 94.74%. The diagnostic model combined with 3 biomarkers could differentiate renal cell carcinoma from benign renal masses with a specificity of 90% and a sensitivity of 92.11%.The positive predictive value to differentiate clear cell renal cell carcinoma from the renal cell carcinoma of other types was 92.86%, and the positive predictive value of renal cell carcinoma of other pathological types was 81.82%. The proteins that over expressed in serum of preoperative patients were obviously down- regulated. Four peaks with the molecular weight of 3117,3258,4524 and 5521 were detected and the detective model combined with 4 biomarkers could differentiate the serum of localized renal cell carcinoma from that of locally advanced renal cell carcinoma with a positive predictive value of 90.91%, and the positive predictive value of locally advanced renal cell carcinoma was 85%. Conclusion: The predictive models built by the differences of serum proteome fingerprint could be a novel,effective,highly specific and sensitive diagnostic tool in renal cell caecinoma.