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 (n = 26) and normal groups (n = 41) 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 cross-validation 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 × 10(-14)), creatine (p < 7 × 10(-8)), lactate (p < 9 × 10(-4)), alanine (p < 7.9 × 10(-3)) and citrate (p < 3 × 10(-4)) 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 (R(2) = 0.3881 and p = 6.66 × 10(-4)), 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.

Keywords: CSF; diagnosis; leptomeningeal carcinomatosis; metabolomics; metastasis.