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BACKGROUND: A proportion of the human IgM repertoire (IgM igome) antibodies is partially autoreactive and by interacting with intrinsic structures, this part can reflect changes in the internal environment. Thus, it can be a potential source of biomarkers for various pathological processes. The aim of the current study is to create an optimal library of probes (IgM mimotopes) to test the applicability and the diagnostic potential of IgM igome biomarkers for patients with brain tumors using a method that is clinically suitable and convenient. MATERIAL AND METHODS: Sera from 34 patients with glioblastoma (GBM), cerebral metastases of breast cancer (MB) and from non-tumor-bearing patients (C) (e.g. trauma, etc.) were tested using custom PEPperPRINT™ microarray chips containing a set of 594 7-mer peptides selected from 220 000 IgM mimotopes. The chips were scanned using a GenePix 4000 Microarray Scanner and the data was normalized and analyzed using cluster analysis based feature selection. An optimal feature set was used to build a proof of principle model separating glioblastoma from other brain tumors using kernel based support vector machine. RESULTS: An IgM mimotope library containing 220 000 7-mer sequences was used to select an optimal set of 594 mimotopes designed as a multipurpose diagnostic tool. In a proof of principle predictor it differentiated between the three groups of brain tumor patients based on the mimotope reactivities of the individual patients’ sera. Four cases of GBM and two cases of breast cancer metastases set aside as a testing set were diagnosed correctly using a GBM-targeted feature set based on 8 controls, 11 GBM and 9 lung cancer metastasis patients. CONCLUSION: IgM repertoire monitoring can be used as a diagnostic tool to provide clinically relevant information regarding neoplasms, including tumors of the central nervous system, and has the potential to be used as a predictor in the future. |
