Dataset Information

Concurrent lipidomics and proteomics on malignant plasma cells from multiple myeloma patients: Probing the lipid metabolome.

ABSTRACT: BACKGROUND:Multiple myeloma (MM) is a hematological malignancy characterized by the clonal expansion of malignant plasma cells. Though durable remissions are possible, MM is considered incurable, with relapse occurring in almost all patients. There has been limited data reported on the lipid metabolism changes in plasma cells during MM progression. Here, we evaluated the feasibility of concurrent lipidomics and proteomics analyses from patient plasma cells, and report these data on a limited number of patient samples, demonstrating the feasibility of the method, and establishing hypotheses to be evaluated in the future. METHODS:Plasma cells were purified from fresh bone marrow aspirates using CD138 microbeads. Proteins and lipids were extracted using a bi-phasic solvent system with methanol, methyl tert-butyl ether, and water. Untargeted proteomics, untargeted and targeted lipidomics were performed on 7 patient samples using liquid chromatography-mass spectrometry. Two comparisons were conducted: high versus low risk; relapse versus newly diagnosed. Proteins and pathways enriched in the relapsed group was compared to a public transcriptomic dataset from Multiple Myeloma Research Consortium reference collection (n = 222) at gene and pathways level. RESULTS:From one million purified plasma cells, we were able to extract material and complete untargeted (~6000 and ~3600 features in positive and negative mode respectively) and targeted lipidomics (313 lipids), as well as untargeted proteomics analysis (~4100 reviewed proteins). Comparative analyses revealed limited differences between high and low risk groups (according to the standard clinical criteria), hence we focused on drawing comparisons between the relapsed and newly diagnosed patients. Untargeted and targeted lipidomics indicated significant down-regulation of phosphatidylcholines (PCs) in relapsed MM. Although there was limited overlap of the differential proteins/transcripts, 76 significantly enriched pathways in relapsed MM were common between proteomics and transcriptomics data. Further evaluation of transcriptomics data for lipid metabolism network revealed enriched correlation of PC, ceramide, cardiolipin, arachidonic acid and cholesterol metabolism pathways to be exclusively correlated among relapsed but not in newly-diagnosed patients. CONCLUSIONS:This study establishes the feasibility and workflow to conduct integrated lipidomics and proteomics analyses on patient-derived plasma cells. Potential lipid metabolism changes associated with MM relapse warrant further investigation.

SUBMITTER: Mohamed A

PROVIDER: S-EPMC6948732 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Concurrent lipidomics and proteomics on malignant plasma cells from multiple myeloma patients: Probing the lipid metabolome.

Mohamed Ahmed A Collins Joel J Jiang Hui H Molendijk Jeffrey J Stoll Thomas T Torta Federico F Wenk Markus R MR Bird Robert J RJ Marlton Paula P Mollee Peter P Markey Kate A KA Hill Michelle M MM

PloS one 20200108 1

<h4>Background</h4>Multiple myeloma (MM) is a hematological malignancy characterized by the clonal expansion of malignant plasma cells. Though durable remissions are possible, MM is considered incurable, with relapse occurring in almost all patients. There has been limited data reported on the lipid metabolism changes in plasma cells during MM progression. Here, we evaluated the feasibility of concurrent lipidomics and proteomics analyses from patient plasma cells, and report these data on a lim ...[more]

PMID: 31914155

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Project description:Although the "seed and soil" hypothesis was proposed by Stephen Paget at the end of the 19th century, where he postulated that tumor cells (seeds) need a propitious medium (soil) to be able to establish metastases, only recently the tumor microenvironment started to be more studied in the field of Oncology. Multiple myeloma (MM), a malignancy of plasma cells, can be considered one of the types of cancers where there is more evidence in the literature of the central role that the bone marrow (BM) microenvironment plays, contributing to proliferation, survival, migration, and drug resistance of tumor cells. Despite all advances in the therapeutic arsenal for MM treatment in the last years, the disease remains incurable. Thus, studies aiming a better understanding of the pathophysiology of the disease, as well as searching for new therapeutic targets are necessary and welcome. Therefore, the present study aimed to evaluate the protein expression profiling of mononuclear cells derived from BM of MM patients in comparison with these same cell types derived from healthy individuals, in order to fill this gap in MM treatment. Proteomic analysis was performed using the mass spectrometry technique and further analyses were done using bioinformatics tools, to identify dysregulated biological pathways and/or processes in the BM microenvironment of patients with MM as a result of the disease. Among the pathways identified in this study, we can highlight an upregulation of proteins related to protein biosynthesis, especially chaperone proteins, in patients with MM. Additionally, we also found an upregulation of several proteins involved in energy metabolism, which is one of the cancer hallmarks. Finally, with regard to the downregulated proteins, we can highlight mainly those involved in different pathways of the immune response, corroborating the data that has demonstrated that the immune system of MM is impaired and, therefore, the immunotherapies that have been studied recently for the treatment of the disease are extremely necessary in the search for a control and a cure for these patients who live with the disease.

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Concurrent lipidomics and proteomics on malignant plasma cells from multiple myeloma patients: Probing the lipid metabolome.

Publications

Concurrent lipidomics and proteomics on malignant plasma cells from multiple myeloma patients: Probing the lipid metabolome.

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