Cerebrospinal Fluid Metabolic Markers Predict Prognosis behavior of Primary CNS Lymphoma with HD-MTX Based Chemotherapeutic Treatment


 
 
 Primary central nervous system lymphoma (PCNSL) is a highly aggressive non-Hodgkin’s B-cell lymphoma which normally treated by a high-dose methotrexate (HD-MTX)-based chemotherapy. However, such treatment cannot always guarantee a good prognosis outcome while suffering several side effects. Thus, biomarkers or biomarker-based model that can predict PCNSL patient prognosis would be benefit.
 
 
 
 We firstly collected 48 patients with PCNSL and applied HPLC-MS/MS based metabolomic analysis on such retrospective PCNSL patient samples. We then selected the highly dysregulated metabolites to build a logical regression model that can distinguish the survival time length by a scoring standard. Finally, we validated the logical regression model on a 33-patient prospective PCNSL cohort.
 
 
 
 Six metabolic features were selected from the cerebrospinal fluid (CSF) that can form a logical regression model to distinguish the patients with relatively good prognosis (Z score ≤ 0.06) from the discovery cohort. We applied the metabolic marker-based model onto a prospective recruited PCNSL patient cohort for a further validation, and the model preformed nicely on such validation cohort (AUC = 0.745).
 
 
 
 We developed a logical regression model based on metabolic markers in CSF that can effectively predict PCNSL patient prognosis before the HD-MTX based chemotherapy treatments.
