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Genome-wide transcriptomics leads to the identification of deregulated genes after deferasirox therapy in low-risk MDS patients

The Pharmacogenomics Journal volume 20, pages 664–671 (2020)Cite this article

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Abstract

The iron chelator deferasirox is widely used in patients with iron overload. Patients with low-grade myelodysplastic syndromes (MDS) get transfusion dependency and need to be treated with deferasirox to avoid iron overload. Moreover, in some patients an increase in both erythroid and platelets have been observed after deferasirox therapy. However, the mechanisms involved in these clinical findings are poorly understood. The aim of this work was to analyze, in patients treated with deferasirox, the changes in the gene-expression profile after receiving the treatment. A total of 15 patients with the diagnosis of low-grade MDS were studied. Microarrays were carried out in RNA from peripheral blood before and after 14 weeks of deferasirox therapy. Changes in 1457 genes and 54 miRNAs were observed: deferasirox induced the downregulation of genes related to the Nf kB pathway leading of an overall inactivation of this pathway. In addition, the iron chelator also downregulated gamma interferon. Altogether these changes could be related to the improvement of erythroid response observed in these patients after therapy. Moreover, the inhibition of NFE2L2/NRF2, which was predicted in silico, could be playing a critical role in the reduction of reactive oxygen species (ROS). Of note, miR-125b, overexpressed after deferasirox treatment, could be involved in the reduced inflammation and increased hematopoiesis observed in the patients after treatment. In summary this study shows, for the first time, the mechanisms that could be governing deferasirox impact in vivo.

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Fig. 1
Fig. 2: In silico upstream regulator analysis predicts the inhibition of nuclear factor erythroid 2 in low-risk MDS patients treated with deferasirox.
Fig. 3: Most significant cellular functions affected by the deregulation of miRNAs in MDS patients treated with deferasirox.

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Acknowledgements

This work was partially supported by grants from the Spanish Fondo de Investigaciones Sanitarias PI15/01471, PI17/01741, PI18/01500, Instituto de Salud Carlos III (ISCIII), European Regional Development Fund (ERDF) “Una manera de hacer Europa”, “Consejería de Educación, Junta de Castilla y León” (SA271P18), “Proyectos de Investigación del SACYL”, Spain: GRS 1847/A/18, GRS 1653/A17, GRS 1850/A/18, “Fundación Memoria Don Samuel Solórzano Barruso”, by grants (RD12/0036/0069) from Red Temática de Investigación Cooperativa en Cáncer (RTICC) and Centro de Investigación Biomédica en Red de Cáncer (CIBERONC CB16/12/00233). JMHS and AERV are supported by a research grant by FEHH (“Fundación Española de Hematología y Hemoterapia”). We are grateful to I. Rodríguez, S. González, T. Prieto, M. Á. Ramos, AM, A. Díaz, A. Simón, M. del Pozo, V. Gutiérrez, and S. Pujante, Sandra Santos and Cristina Miguel from Cancer research Center of Salamanca, Salamanca, for their technical assistance.

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Author notes

  1. These authors contributed equally: Jesús María Hernández-Rivas, Ana Eugenia Rodríguez Vicente

Authors and Affiliations

  1. IBSAL. IBMCC, CIC Universidad de Salamanca—CSIC, Salamanca, Spain

    Jesús María Hernández Sánchez, Eva Lumbreras, Teresa González, María Abáigar, Mónica del Rey, Jesús María Hernández-Rivas & Ana Eugenia Rodríguez Vicente

  2. Servicio de Hematología, Hospital Universitario, Salamanca, Spain

    María Díez-Campelo, Teresa González, Ana África Martín & Jesús María Hernández-Rivas

  3. Unidad de Bioinformática, Centro de Investigación del Cáncer (CSIC-USAL), Salamanca, Spain

    Diego Alonso López

  4. Servicio de Hematología, Hospital Universitario La Paz, Madrid, Spain

    Raquel de Paz

  5. Servicio de Hematología, Hospital Universitario de Cruces, Barakaldo, Vizcaya, Spain

    Sara Erquiaga & Beatriz Arrizabalaga

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Contributions

JMHS designed the experiment, interpreted the results and performed bioinformatic analysis; DAL performed bioinformatic analysis; EL, MA, and MDR contributed to the interpretation of the results; TG, MDC, AAM, RP, SE, BA, and JMHR performed patient selection and provided clinical data; JMHR and AERV contributed to the interpretation of the results and wrote the paper. All authors revised the paper.

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Correspondence to Ana Eugenia Rodríguez Vicente.

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Sánchez, J.M.H., Lumbreras, E., Díez-Campelo, M. et al. Genome-wide transcriptomics leads to the identification of deregulated genes after deferasirox therapy in low-risk MDS patients. Pharmacogenomics J 20, 664–671 (2020). https://doi.org/10.1038/s41397-020-0154-5

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