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Schizophrenia is a psychiatric condition characterized by poor prognosis and severe symptoms that decrease the quality of life of patients. It is therefore important to develop rapid and reliable methods for early diagnosis. To achieve this aim, identification of accurate biomarkers will promote research into the mechanisms of schizophrenia and the design of effective diagnosis tools. Discriminative peptides in the serum of participants (277 schizophrenia patients and 294 healthy controls) were detected using the matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry (MALDI-TOF-MS). The diagnostic model for schizophrenia was validated using the ClinProTool software. Discrimination models were tested in the training set (200 schizophrenia patients and 200 healthy controls), and the robustness of the models was evaluated using the independent test set (77 cases and 94 controls). A total of 77 peaks were significantly different between schizophrenia patients and healthy controls with a signal-to-noise ratio of over 5. Among them, 35 peptides were down-regulated and 42 peptides were up-regulated in schizophrenia patients. With a cross-validation rate of 92.7% and a recognition capability rate of 96.5%, the supervised neural network comprising 25 discriminative peaks was found to be the most efficient model for schizophrenia diagnosis (sensitivity = 96.10%, specificity = 94.68%). Peptides at m/z = 2022.18 corresponded to complement C3f, and peptides at m/z = 1020.89, 1351.02, 1466.1 were identified as fragments of fibrinopeptide A. These two peptides may be potential biomarkers for schizophrenia in the Chinese population. The serum peptide levels present a potential clinical diagnostic tool for schizophrenia.

No ideal serum biomarker currently exists for the early diagnosis of colorectal cancer (CRC). Magnetic bead-based fractionation coupled with MALDI-TOF MS was used to screen serum samples from CRC patients, healthy controls, and other cancer patients. A diagnostic model with five proteomic features (m/z 1778.97, 1866.16, 1934.65, 2022.46, and 4588.53) was generated using Fisher algorithm with best performance. The Fisher-based model could discriminate CRC patients from the controls with 100% (46/46) sensitivity and 100% (35/35) specificity in the training set, 95.6% (43/45) sensitivity and 83.3% (35/42) specificity in the test set. We further validated the model with 94.4% (254/269) sensitivity and 75.5% (83/110) specificity in the external independent group. In other cancers group, the Fisher-based model classified 25 of 46 samples (54.3%) as positive and the other 21 as negative. With FT-ICR-MS, the proteomic features of m/z 1778.97, 1866.16, 1934.65, and 2022.46, of which intensities decreased significantly in CRC, were identified as fragments of complement C3f. Therefore, the Fisher-based model containing five proteomic features was able to effectively differentiate CRC patients from healthy controls and other cancers with a high sensitivity and specificity, and may be CRC-specific. Serum complement C3f, which was significantly decreased in CRC group, may be relevant to the incidence of CRC. J. Cell. Biochem. 114: 448–455, 2013. © 2012 Wiley Periodicals, Inc.

BACKGROUND: Prostate cancer (PCa) is the second cause of mortality in men worldwide. The prostate-specific antigen (PSA) test is routinely adopted in diagnosis; nevertheless more reliable biomarkers are continuously under investigation by monitoring the release of molecules into the bloodstream. The serum protein profiles appear to provide cancer-specific fingerprints that help to discriminate patients (especially with low PSA level) from controls, improving the performance of existing clinical tests. METHODS: Samples from healthy controls and PCa patients with low (4ng/mL) levels were analyzed by MALDI profiling, and by a multi fractionation approach coupled to ESI-MS for peaks identification. RESULTS: MALDI profiling achieved to detect 10 and 14 changed peaks (p-value

Background: Prostate cancer (PCa) is the second cause of mortality in men worldwide. The prostate-specific antigen (PSA) test is routinely adopted in diagnosis; nevertheless more reliable biomarkers are continuously under investigation by monitoring the release of molecules into the bloodstream. The serum protein profiles appear to provide cancer-specific fingerprints that help to discriminate patients (especially with low PSA level) from controls, improving the performance of existing clinical tests. Methods: Samples from healthy controls and PCa patients with low (≤. 4. ng/mL) and high PSA (>. 4. ng/mL) levels were analyzed by MALDI profiling, and by a multi fractionation approach coupled to ESI-MS for peaks identification. Results: MALDI profiling achieved to detect 10 and 14 changed peaks (p-value

Gross cystic disease (GCDB) is a breast benign condition predisposing to breast cancer. Cryopreserved sera from GCDB patients, some of whom later developed a cancer (cases), were studied to identify potential risk markers. A MALDI-TOF mass spectrometry analysis found several complement C3f fragments having a significant increased abundance in cases compared to controls. After multivariate analysis, the full-length form of C3f maintained a predictive value of breast cancer risk. Higher levels of C3f in the serum of women affected by a benign condition like GCDB thus appears to be correlated to the development of breast cancer even 20 years later. Biological significance Increased complement system activation has been found in the sera of women affected by GCDB who developed a breast cancer, even twenty or more years later. C3f may predict an increased breast cancer risk in the healthy population and in women affected by predisposing conditions.

Background Qiangji Jianli Fang (QJF) has been used for treatment of myasthenia gravis (MG) in China. However, our understanding of the effects of QJF against MG at the molecular level is limited. This study aims to investigate the effects of QJF treatment of MG patients on the protein, peptide and metabolite levels in serum. Methods High-throughput proteomic, peptidomic and metabolomic techniques were applied to investigate serum samples from 21 healthy individuals and 47 MG patients before and after QJF treatment via two-dimensional gel electrophoresis, matrix-assisted laser desorption/ionization time of flight mass spectrometry and liquid chromatography Fourier transform mass spectrometry, respectively. Results After QJF treatment, the expression levels of peptides m/z 1865.019, 2021.128 and 1211.668 of complement C3f increased (P = 0.004, P = 0.001 and P = 0.043, respectively), while that of peptide m/z 1739.931 of component C4b decreased (P = 0.043), in the serum of MG patients. The levels of γ-aminobutyric acid (P = 0.000) and coenzyme Q4 (P = 0.000) resumed their normal states. Conclusion QJF could inhibit the activity of the complement system and restore the normal levels of metabolites.