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Quantitation of methotrexate polyglutamates in human whole blood, erythrocytes and leukocytes collected via venepuncture and volumetric absorptive micro-sampling: a green LC-MS/MS-based method.

ABSTRACT: Low-dose methotrexate (MTX) plays a key role in treatment of rheumatoid arthritis. However, not all patients respond satisfactorily, and no therapeutic drug monitoring has been implemented in clinical practice, despite the fact that MTX therapy has now been available for decades. Analysis of individual intracellular MTX metabolites among rheumatoid arthritis (RA) patients is hampered by the low intracellular concentrations of MTX-PGs which require a highly sensitive method to quantify. Here, we present a rapid and highly sensitive LC (HILIC) MS/MS method with LLOQ 0.1 nM, 0.8 nmol/L for each metabolite of MTX-PG_1-5 and MTX-PG_6-7 respectively. Over a linear range of 0.1-100 nM, 0.8-100 nmol/L for each metabolite of MTX-PG_1-5 and MTX-PG_6-7, respectively, the inter- and intra- accuracy and precision were within 15% of the nominal value for all MTX metabolites. The presented assay was used to assess and compare MTX metabolite concentrations extracted from four different matrices: red blood cells, plasma, peripheral blood mononuclear cells, and whole blood that have been collected either using traditional venepuncture or volumetric absorptive micro-sampling (VAMS) sampling techniques. The presented method not only improves analyte coverage and sensitivity as compared to other published methods; it also improves the greenness.

SUBMITTER: Daraghmeh DN

PROVIDER: S-EPMC9314280 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Despite immense interest in the proteome as a source of biomarkers in cancer, mass spectrometry has yet to yield a clinically useful protein biomarker for tumor classification. To explore the potential of a particular class of mass spectrometry-based quantitation approaches, label-free alignment of liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) data sets, for the identification of biomarkers for acute leukemias, we asked whether a label-free alignment algorithm could distinguish known classes of leukemias on the basis of their proteomes. This approach to quantitation involves (1) computational alignment of MS1 peptide peaks across large numbers of samples; (2) measurement of the relative abundance of peptides across samples by integrating the area under the curve of the MS1 peaks; and (3) assignment of peptide IDs to those quantified peptide peaks on the basis of the corresponding MS2 spectra. We extracted proteins from blasts derived from four patients with acute myeloid leukemia (AML, acute leukemia of myeloid lineage) and five patients with acute lymphoid leukemia (ALL, acute leukemia of lymphoid lineage). Mobilized CD34+ cells purified from peripheral blood of six healthy donors and mononuclear cells (MNC) from the peripheral blood of two healthy donors were used as healthy controls. Proteins were analyzed by LC-MS/MS and quantified with a label-free alignment-based algorithm developed in our laboratory. Unsupervised hierarchical clustering of blinded samples separated the samples according to their known biological characteristics, with each sample group forming a discrete cluster. The four proteins best able to distinguish CD34+, AML, and ALL were all either known biomarkers or proteins whose biological functions are consistent with their ability to distinguish these classes. We conclude that alignment-based label-free quantitation of LC-MS/MS data sets can, at least in some cases, robustly distinguish known classes of leukemias, thus opening the possibility that large scale studies using such algorithms can lead to the identification of clinically useful biomarkers.

Dataset Information

Quantitation of methotrexate polyglutamates in human whole blood, erythrocytes and leukocytes collected via venepuncture and volumetric absorptive micro-sampling: a green LC-MS/MS-based method.

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