Literature DB >> 31127562

Proteometabolomics of Melphalan Resistance in Multiple Myeloma.

David C Koomen1, Joy D Guingab-Cagmat2, Paula S Oliveira1, Bin Fang1, Min Liu1, Eric A Welsh1, Mark B Meads1, Tuan Nguyen1, Laurel Meke2, Steven A Eschrich1, Kenneth H Shain1, Timothy J Garrett3, John M Koomen4.   

Abstract

Drug resistance remains a critical problem for the treatment of multiple myeloma (MM), which can serve as a specific example for a highly prevalent unmet medical need across almost all cancer types. In MM, the therapeutic arsenal has expanded and diversified, yet we still lack in-depth molecular understanding of drug mechanisms of action and cellular pathways to therapeutic escape. For those reasons, preclinical models of drug resistance are developed and characterized using different approaches to gain insights into tumor biology and elucidate mechanisms of drug resistance. For MM, numerous drugs are used for treatment, including conventional chemotherapies (e.g., melphalan or L-phenylalanine nitrogen mustard), proteasome inhibitors (e.g., Bortezomib), and immunomodulators (e.g., Lenalidomide). These agents have diverse effects on the myeloma cells, and several mechanisms of drug resistance have been previously described. The disparity of these mechanisms and the complexity of these biological processes lead to the formation of complicated hypotheses that require omics approaches for efficient and effective analysis of model systems that can then be interpreted for patient benefit. Here, we describe the combination of metabolomics and proteomics to assess melphalan resistance in MM by examining three specific areas: drug metabolism, modulation of endogenous metabolites to assist in therapeutic escape, and changes in protein activity gauged by ATP probe uptake.

Entities:  

Keywords:  Activity-based protein profiling (ABPP); Cancer treatment; Drug resistance; LC-MS/MS; Melphalan; Metabolomics; Multiple myeloma

Mesh:

Substances:

Year:  2019        PMID: 31127562      PMCID: PMC7771550          DOI: 10.1007/978-1-4939-9488-5_21

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  54 in total

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2.  Covalent adducts of melphalan with free amino acids and a model peptide studied by liquid chromatography/tandem mass spectrometry.

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4.  Reversal of melphalan resistance in vivo and in vitro by modulation of glutathione metabolism.

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Journal:  Biochem Pharmacol       Date:  1991-07-05       Impact factor: 5.858

5.  Data Conversion with ProteoWizard msConvert.

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6.  Prognostic factors with high-dose melphalan for refractory multiple myeloma.

Authors:  B Barlogie; R Alexanian; L Smallwood; B Cheson; D Dixon; K Dicke; F Cabanillas
Journal:  Blood       Date:  1988-12       Impact factor: 22.113

7.  Bendamustine and melphalan kill myeloma cells similarly through reactive oxygen species production and activation of the p53 pathway and do not overcome resistance to each other.

Authors:  Sylvanie Surget; Emilie Lemieux-Blanchard; Sophie Maïga; Géraldine Descamps; Steven Le Gouill; Philippe Moreau; Martine Amiot; Catherine Pellat-Deceunynck
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8.  How to submit MS proteomics data to ProteomeXchange via the PRIDE database.

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Journal:  Proteomics       Date:  2014-08-21       Impact factor: 3.984

9.  Evidence for different mechanisms of 'unhooking' for melphalan and cisplatin-induced DNA interstrand cross-links in vitro and in clinical acquired resistant tumour samples.

Authors:  Victoria J Spanswick; Helen L Lowe; Claire Newton; John P Bingham; Alessia Bagnobianchi; Konstantinos Kiakos; Charles Craddock; Jonathan A Ledermann; Daniel Hochhauser; John A Hartley
Journal:  BMC Cancer       Date:  2012-09-28       Impact factor: 4.430

10.  XPO1 inhibitor combination therapy with bortezomib or carfilzomib induces nuclear localization of IκBα and overcomes acquired proteasome inhibitor resistance in human multiple myeloma.

Authors:  Joel G Turner; Trinayan Kashyap; Jana L Dawson; Juan Gomez; Alexis A Bauer; Steven Grant; Yun Dai; Kenneth H Shain; Mark Meads; Yosef Landesman; Daniel M Sullivan
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1.  Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages.

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Review 2.  Metabolic Disorders in Multiple Myeloma.

Authors:  Maria Gavriatopoulou; Stavroula A Paschou; Ioannis Ntanasis-Stathopoulos; Meletios A Dimopoulos
Journal:  Int J Mol Sci       Date:  2021-10-22       Impact factor: 5.923

Review 3.  Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma.

Authors:  Sara Ovejero; Jerome Moreaux
Journal:  Explor Target Antitumor Ther       Date:  2021-02-28
  3 in total

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