Diagnostic and prognostic application of proteomic patterns in breast cancer / 中国病理生理杂志

ABSTRACT

AIM: To detect the serum proteomic patterns in patients of breast cancer by the method of SELDI-TOF-MS and CM10 ProteinChip, and to screen the biomarker candidates, build and validate the diagnostic models, and evaluate its clinical value in surveillance and follow-up after operation. METHODS: The SELDI-TOF-MS technology and CM10 ProteinChip were used to detect the proteomic patterns of serum from 63 breast cancer patients and 40 healthy women. The biomarker candidates were screened and the diagnostic models were constructed by ZJU-PDAS software. Meanwhile, the model was blind-validated in another 23 patients and 20 healthy women. At the same time, 16 serum samples were detected to evaluate its value in surveillance and follow-up after operation. RESULTS: The best model was composed by two protein peaks (BC1/3.9 kD and BC2/5.6 kD) with its sensitivity and specificity of 87.30% (55/63) and 95.00% (38/40), respectively. The sensitivity and specificity in the blind-validation of new cases were 95.65% (22/23) and 85.00% (17/20), respectively. The diagnostic efficacies were the same to the patients of different stages (P>0.05). The expression of BC1 increased while BC2 decreased after operation. The expression of BC2 in the patients with recurrence or metastasis was higher than that in the tumor-free survivors (P<0.05). CONCLUSION: This method shows its potential in detection, surveillance and follow-up after operation. The method is also useful for screening the novel and better biomarkers in breast cancer.