An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis

Leptomeningeal carcinomatosis (LC) is the third most common metastatic complication of the central nervous system. However, the current modalities to reliably diagnose this condition are not satisfactory. Here we report a preclinical proof of concept for a metabolomics-based diagnostic strategy, using a rat LC model incorporating glioma cells that stably expressed green fluorescent protein. Cytological diagnoses gave 66.7% sensitivity for the 7-day LC group and 0% for the 3-day LC group. MR imaging could not diagnose LC at these stages. In contrast, NMR-based metabolomics on cerebrospinal fluid (CSF) detected marked differences between the normal and LC groups. Predictions based on the multivariate model provided sensitivity, specificity and overall accuracy of 88-89% in both groups for LC diagnosis. Further statistical analyses identified lactate, acetate, and creatine as specific for the 7-day LC group, with glucose a specific marker of the normal group. Overall, we demonstrated that the metabolomics approach provided both earlier and more accurate diagnostic results than cytology and MR imaging in current use. on April 3, 2017. © 2012 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on August 27, 2012; DOI: 10.1158/0008-5472.CAN-12-0755