Liquid Chromatography Mass Spectrometry-Based Metabolite Pathway Analyses of Myeloma and Non-Hodgkin’s Lymphoma Patients

(Pages: 44-54)
Carl Angelo D. Medriano, M.Eng, 1Jinhyuk Na, Pharm.D, 1Kyung-min Lim, Ph.D, 2Jin-ho Chung, Ph.D, 3Youngja H. Park, Ph.D, 1,*
Metabolomics Laboratory, College of Pharmacy, Korea University, Sejong City, Korea
College of Pharmacy, Ewha Woman’s University, Seoul, Korea
College of Pharmacy, Seoul National University, Seoul, Korea
Metabolomics Laboratory, College of Pharmacy, Korea University, Sejong City, Korea
College of Pharmacy, Ewha Woman’s University, Seoul, Korea
College of Pharmacy, Seoul National University, Seoul, Korea
*Corresponding Address: Metabolomics Laboratory College of Pharmacy Korea University Sejong City Korea Email:yjhwang@korea.ac.kr
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Medriano Carl Angelo D., Na Jinhyuk, Lim Kyung-min, Chung Jin-ho, Park Youngja H.. Liquid Chromatography Mass Spectrometry-Based Metabolite Pathway Analyses of Myeloma and Non-Hodgkin’s Lymphoma Patients. Cell J. 2017; 19(Suppl 1): 44-54.

Abstract

Objective

This study attempted to identify altered metabolism and pathways related to non-Hodgkin’s lymphoma (NHL) and myeloma patients.

Materials and Methods

In this retrospective study, we collected plasma samples from 11 patients-6 healthy controls with no evidence of any blood cancers and 5 patients with either multiple myeloma (n=3) or NHL (n=2) during the preliminary study period. Samples were analyzed using quadrupole time-of-flight liquid chromatography mass spectrometry (LC-MS). Significant features generated after statistical analyses were used for metabolomics and pathway analysis.

Results

Data after false discovery rate (FDR) adjustment at q=0.05 of features showed 136 for positive and 350 significant features for negative ionization mode in NHL patients as well as 262 for positive and 98 features for negative ionization mode in myeloma patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis determined that pathways such as steroid hormone biosynthesis, ABC transporters, and arginine and proline metabolism were affected in NHL patients. In myeloma patients, pyrimidine metabolism, carbon metabolism, and bile secretion pathways were potentially affected by the disease.

Conclusion

The results have shown tremendous differences in the metabolites of healthy individuals compared to myeloma and lymphoma patients. Validation through quantitative metabolomics is encouraged, especially for the metabolites with significantly expression in blood cancer patients.