Specific matrix metalloproteinase profiles in the cerebrospinal fluid correlated with the presence of malignant astrocytomas, brain metastases, and carcinomatous meningitis.

ABSTRACT

BACKGROUND: Detection in tumor tissue of specific matrix metalloproteinases (MMPs), particularly gelatinases A and B, correlates with the grade and aggressiveness of primary and metastatic brain tumors. The ability to detect these enzymes in the cerebrospinal fluid (CSF) would be a minimally invasive method of evaluating brain tumors. METHODS: CSF from 66 patients with white blood cell counts of < or = 5 microL were analyzed for the presence of gelatinolytic activity by zymography. Twenty-nine patients had malignant astrocytomas, 10 had brain metastases from systemic malignancies, 4 had systemic cancer not involving the central nervous system, 4 had nonmalignant neurologic diseases, and 19 were healthy controls. Fifteen CSF samples had positive cytologies. The zymographic results were retrospectively correlated with clinical information and CSF cytologic data. RESULTS: CSF from all patients with malignant astrocytomas or brain metastases contained precursor gelatinase A (pMMP2) and precursor gelatinase B (pMMP9), whereas control CSF contained only pMMP2. All patients with positive CSF cytologies had activated MMP2. A similar correlation was observed between the presence of activated MMP9 and positive CSF cytology. CONCLUSIONS: The precursor and activated forms of gelatinases A and B can be detected in the CSF of patients with primary and metastatic brain tumors. The distribution of gelatinase activity in CSF distinguishes patients with malignant gliomas or brain metastases from those without brain tumors, and distinguishes patients with meningeal carcinomatosis from those without CSF spread of tumor, regardless of their brain tumor status. Analysis of MMPs in the CSF may be a sensitive technique for diagnosing CNS tumors and provide an early indication of tumor recurrence. This technique may also provide longitudinal information that would be useful in evaluating ongoing treatment and predicting tumor behavior.