An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis in lung adenocarcinoma cancer patients

Abstract

Leptomeningeal carcinomatosis (LC) is a metastatic cancer invading the central nervous system (CNS). We previously reported a metabolomic diagnostic approach as tested on an animal model and compared with current modalities. Here, we provide a proof of concept by applying it to human LC originating from lung cancer, the most common cause of CNS metastasis. Cerebrospinal fluid from LC (n526) and normal groups (n541) were obtained, and the diagnosis was established with clinical signs, cytology, MRI and biochemical tests. The cytology on the CSF, the current gold standard, exhibited 69% sensitivity (~100% specificity) from the first round of CSF tapping. In comparison, the nuclear magnetic resonance spectra on the CSF showed a clear difference in the metabolic profile between the LC and normal groups. Multivariate analysis and crossvalidation yielded the diagnostic sensitivity of 92%, the specificity of 96% and the area under the curve (AUC) of 0.991. Further spectral and statistical analysis identified myo-inositol (p < 5 3 10214), creatine (p < 7 3 1028), lactate (p < 9 3 1024), alanine (p < 7.9 3 1023) and citrate (p < 3 3 1024) as the most contributory metabolites, whose combination exhibited an receiver.operating characteristic diagnostic AUC of 0.996. In addition, the metabolic profile could be correlated with the grading of radiological leptomeningeal enhancement (R250.3881 and p56.66 3 1024), suggesting its potential utility in grading LC. Overall, we propose that the metabolomic approach might augment current diagnostic modalities for LC, the accurate diagnosis of which remains a challenge.