4.7 Article

Potential biomarkers of childhood brain tumor identified by proteomics of cerebrospinal fluid from extraventricular drainage (EVD)

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SCIENTIFIC REPORTS
卷 11, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41598-020-80647-w

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Brain tumors are the most common solid tumors in childhood, and biomarkers for residual disease, therapy response, and recurrence are needed. This study identified potential protein biomarkers in cerebrospinal fluid that could distinguish between control and tumor groups, as well as differentiate among different types of brain tumors. Validation using ELISA showed promising clinical applications for these biomarkers.
Brain tumors are the most common solid tumors in childhood. There is the need for biomarkers of residual disease, therapy response and recurrence. Cerebrospinal fluid (CSF) is a source of brain tumor biomarkers. We analyzed the proteome of waste CSF from extraventricular drainage (EVD) from 29 children bearing different brain tumors and 17 controls needing EVD insertion for unrelated causes. 1598 and 1526 proteins were identified by liquid chromatography-coupled tandem mass spectrometry proteomics in CSF control and brain tumor patients, respectively, 263 and 191 proteins being exclusive of either condition. Bioinformatic analysis revealed promising protein biomarkers for the discrimination between control and tumor (TATA-binding protein-associated factor 15 and S100 protein B). Moreover, Thymosin beta-4 (TMSB4X) and CD109, and 14.3.3 and HSP90 alpha could discriminate among other brain tumors and low-grade gliomas plus glyoneuronal tumors/pilocytic astrocytoma, or embryonal tumors/medulloblastoma. Biomarkers were validated by ELISA assay. Our method was able to distinguish among brain tumor vs non-tumor/hemorrhagic conditions (controls) and to differentiate two large classes of brain tumors. Further prospective studies may assess whether the biomarkers proposed by our discovery approach can be identified in other bodily fluids, therefore less invasively, and are useful to guide therapy and predict recurrences.

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