way to detect brain mets early, follow response to treatment, spot recurrence early

[Lani]

Neuro Oncol. 2012 Apr 4. [Epub ahead of print]
MicroRNAs in cerebrospinal fluid identify glioblastoma and metastatic brain cancers and reflect disease activity.
Teplyuk NM, Mollenhauer B, Gabriely G, Giese A, Kim E, Smolsky M, Kim RY, Saria MG, Pastorino S, Kesari S, Krichevsky AM.
Source
Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts (N.M.T., G.G., M.S., A.M.K.); Paracelsus-Elena-Klinik, Kassel and Georg-August University Göttingen, Germany (B.M.); Department of Neurosurgery, Georg-August University Medical Center Göttingen, Germany (A.G., E.K.); Department of Neurosciences, Translational Neuro-Oncology Laboratories, Moores UCSD Cancer Center, UC San Diego, La Jolla, California (R.Y.K., M.G.S., S.P., S.K.).
Abstract
An accurate, nonsurgical diagnostic test for brain tumors is currently unavailable, and the methods of monitoring disease progression are not fully reliable. MicroRNA profiling of biological fluids has recently emerged as a diagnostic tool for several pathologic conditions. Here we tested whether microRNA profiling of cerebrospinal fluid (CSF) enables detection of glioblastoma, discrimination between glioblastoma and metastatic brain tumors, and reflects disease activity. We determined CSF levels of several cancer-associated microRNAs for 118 patients diagnosed with different types of brain cancers and nonneoplastic neuropathologies by quantitative reverse transcription PCR analysis. The levels of miR-10b and miR-21 are found significantly increased in the CSF of patients with glioblastoma and brain metastasis of breast and lung cancer, compared with tumors in remission and a variety of nonneoplastic conditions. Members of the miR-200 family are highly elevated in the CSF of patients with brain metastases but not with any other pathologic conditions, allowing discrimination between glioblastoma and metastatic brain tumors. Quantification of as few as 7 microRNAs in CSF enables differential recognition of glioblastoma and metastatic brain cancer using computational machine learning tools (Support Vector Machine) with high accuracy (91%-99%) on a test set of samples. Furthermore, we show that disease activity and treatment response can be monitored by longitudinal microRNA profiles in the CSF of glioblastoma and non-small cell lung carcinoma patients. This study demonstrates that microRNA-based detection of brain malignancies can be reliably performed and that microRNAs in CSF can serve as biomarkers of treatment response in brain cancers.
PMID: 22492962