Hepcidin and ferritin blood level as noninvasive tools for predicting breast cancer.

BACKGROUND: Currently used CA15-3 and CEA have found their clinical application particularly in the follow-up of patients with advanced disease. Novel biomarkers are urgent, especially for improving early diagnosis as well as for discriminating between benign and malignant disease. PATIENTS AND METHODS: In the present study, we used a proteomic approach based on surface-enhanced laser desorption/ionization-time of flight-mass spectrometry screening with the aim of identifying differentially expressed 2-30 kDa proteins in plasma of patients with malignant (65 cases) and benign (88 cases) breast lesions with respect to 121 healthy controls. RESULTS: We found that the most promising SELDI peaks were those corresponding to hepcidin-25 and ferritin light chain. We evaluated the capability of these peaks in predicting malignant and benign breast lesions using the area under the receiver operating characteristic curve (AUC). The results showed a good capacity to predict malignant breast lesions for hepcidin-25 [AUC: 0.82; 95% confidence interval (CI) 0.75-0.90] and ferritin light chain (AUC: 0.86; 95% CI 0.79-0.92). Conversely, a weak and satisfactory capability to predict benign breast lesion was observed for hepcidin-25 (AUC: 0.63; 95% CI 0.41-0.85) and ferritin light chain (AUC: 0.73; 95% CI 0.49-0.97). A significant association between HER2 status and hepcidin-25 was observed and the distribution of transferrin and ferritin were found significantly different in patients with breast cancer when compared with that of controls. CONCLUSIONS: This study provides evidence that hepcidin and ferritin light chain level in plasma may be of clinical usefulness to predict malignant and benign disease with respect to healthy controls.

Characterization of a serum protein pattern from NSCLC patients treated with Gefitinib.

OBJECTIVES: The purpose of this study was to evaluate the efficacy of a protein-based pattern in serum previously determined by MALDI-TOF-MS (Matrix Assisted Laser Desorption Ionization-Time of Flight) and considered potentially useful for prediction of clinical outcome of EGFR (epidermal growth factor receptor) TKIs (tyrosine kinase inhibitors) treated patients. DESIGN AND METHODS: We generated SELDI-TOF (Surface Enhanced Laser Desorption Ionization-Time of Flight) spectra in sera of 11 advanced NSCLC treated with Gefitinib. We detected the clusters with m/z 5843, 11445, 11529, 11685, 11759 and 11903 which were previously reported to be potential predictors of response to Gefitinib treatment. RESULTS: Four cluster peaks with m/z 5843, 11445, 11529, 11685 corresponded to SAA (serum amyloid A) protein on the basis on their calculated molecular weight, peptide fingerprinting and antibodies recognition. CONCLUSIONS: We confirm that several proteins already reported were isoforms of SAA but further studies are in development in order to evaluate the predictive value of such algorithm.