Purine metabolism in human neuroblastoma cell lines.

Abstract

Neuroblastoma is the second most common solid tumor of childhood, originating from the embryonic neural crest (1). The clinical picture is polymorphic due to varied histological patterns, different localization and different degrees of malignancy. Despite aggressive I treatment, the overall prognosis has not changed in the last 2 decades. There are only few reports on clinical trials with drugs j affecting nucleotide metabolism, such as methotrexate (2) and trifluoromethyl-2-deoxyuridine (3). In the present study we describe in detail the metabolism of purine nucleotide as a possible target for chemotherapy in neuroblastoma. Two different human neuroblastoma cell lines established from surgically resected tumor were used in this study, NUB-6, from a patient with a localized disease and EW-2 from a patient with recurrent metastatic disease. The cells were grown in alpha-medium supplemented with 20% inactivated fetal calf serum. EW-2 f cells formed monolayers whereas NUB-6 cells formed spheroid-like aggregates with an average size of 400 μm. All assays were performed on a single cell suspension achieved by gentle shaking in citrate-saline and mild trypsinization for two minutes. Viability of over 95% was kept through all experiments. The availability of twof biologically different cell lines may allow us to relate changes in nucleotide metabolism to these phenotypic differences. For the assessment of nucleotide metabolism, labelled adenine, hypoxanthine, adenosine, guanosine, formic acid and glycine were used, and the incorporation of radioactivity into the respective purine ribonucleotides, ribonucleosides and bases was assayed as previously described (4). The cytotoxic effect of a number of drugs was evaluated in a clonogenic assay (6).KeywordsNeuroblastoma Cell LineClonogenic AssayPurine MetabolismPurine NucleotideNucleotide MetabolismThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.