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Early detection of breast cancer is paramount to successful clinical therapy. Yet, early-stage breast cancer lacks specific symptoms or biomarkers. With the emerging of the mass spectrometric (MS) -based signatures as biomarkers, we investigated breast cancer-related serum profile pattern through class prediction and independent validation, and used Fourier transfer MS to identify breast cancer signature. We now show a distinctive serum peptide pattern that discriminates breast cancer from healthy controls with 93.2% sensitivity and 95.4% specificity. m/z 5901.70 and 4465.74 of ion fragment of FPA and alpha1-antichymotrypsin are found in the signatures that predominantly discriminate breast cancer from healthy individuals. These novel findings identify an MS-based serum peptide pattern of breast cancer that may have direct clinical utility in future.
Early detection of breast cancer is paramount to successful clinical therapy. With the emerging of the mass spectrometric (MS) -based signatures as biomarkers, we investigated breast cancer-related serum profile pattern through class prediction and independent validation, and used Fourier transfer MS to identify breast cancer signature. We now show a distinctive serum peptide pattern that discriminates breast cancer from healthy controls with 93.2% sensitivity and 95.4% specificity. m / z 5901.70 and 4465.74 of ion fragment of FPA and alpha1-antichymotrypsin are found in the signatures that predominantly discriminate breast cancer from healthy individuals. These novel findings identify an MS-based serum peptide pattern of breast cancer that may have direct clinical utility in future.