Abstract
Pediatric lymphoma is a kind of malignant tumor with high mortality. The complexity of pediatric lymphoma shows a great challenge for effective diagnosis and treatment. In order to meet the challenge, the combination of pseudotargeted and targeted metabolomics was used to analyze the serum metabolites in pediatric lymphoma patients and healthy controls for discovering the metabolites related to pediatric lymphoma. The serum samples were obtained from the treatment group (n = 43), the control group (n = 26), and the patients group (n = 18). A total of 17 serum metabolites, including carnitine, leucine, creatine, urea, (6Z,9Z,12Z)-octadecatrienoic acid, linoleate, octadecenoic acid, L-palmitoylcarnitine, hexadecanoic acid, tetradecanoic acid, (9Z)-hexadecenoic acid, uric acid, glucose, 1-methylnicotinamide, hypoxanthine, L-glutamine, and taurine, were found to be related to pediatric lymphoma. They could provide a scientific diagnostic basis and therapeutic target for pediatric lymphoma and elucidate the mechanism of pediatric lymphoma.
Highlights
Lymphoma is one of the most common pediatric cancers, accounting for nearly one third of all pediatric cancers
The relative standard deviation (RSD) of peak areas of quality control (QC) samples was used to evaluate the repeatability of the analytical method
Our pseudotargeted metabolomics method was suitable for pediatric lymphoma serum detection
Summary
Lymphoma is one of the most common pediatric cancers, accounting for nearly one third of all pediatric cancers. It is one of the main causes of death in children ages 1 to 10 [1]. The number of pediatric lymphoma patients will significantly increase. There are no available serum metabolomics studies on pediatric lymphoma. We utilized a combination of pseudotargeted and targeted metabolomics to analyze the serum metabolites in pediatric lymphoma patients and healthy control subjects. Two batches of serum were collected from pediatric lymphoma patients and healthy subjects. One batch of serum was used for pseudotargeted metabolomics analysis. The results may provide valuable information for the diagnosis and personalized treatment of pediatric lymphoma
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