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Chronic myeloproliferative neoplasms

Long-term follow-up of JAK2 exon 12 polycythemia vera: a French Intergroup of Myeloproliferative Neoplasms (FIM) study

Leukemia volume 35, pages 871–875 (2021)Cite this article

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Classical Philadelphia-negative MPN, including polycythemia Vera (PV), essential thrombocythemia, and primary myelofibrosis, are characterized by somatic driver mutations in JAK2, CALR, and MPL genes that lead to the constitutive activation of the JAK2-STAT5 pathway. Almost all PV patients harbor a JAK2 mutation either at the V617F hotspot in 97% of cases or in the exon 12 in 1% of cases [1, 2]. Unlike the V617F substitution, mutations in the exon 12 of JAK2 are exclusively encountered in PV [3]. Mouse models have demonstrated the ability of JAK2 exon 12 mutations to induce a MPN phenotype with prominent erythrocytosis [4, 5]. However, the molecular mechanisms underlying erythrocytosis due to JAK2 exon 12 mutations remain poorly understood. Differences in cell signaling pathways or in the metabolism of iron have been proposed [4, 6]. PV patients with exon 12 mutation might present specific characteristics but few data are currently available in the literature [7, 8]. The aim of our study was to report the clinical and biological features at diagnosis and the long-term prognosis of a large French cohort of JAK2 exon 12-mutated PV compared with JAK2V617F-mutated PV.

We recruited JAK2 exon 12-mutated PV diagnosed before 2013 according to the 2001/2008 WHO criteria. A total of 65 patients from 33 French hospitals were included and were compared to 348 unselected JAK2V617F-mutated PV patients from the French Intergroup of Myeloproliferative Neoplasms (FIM) clinical and biological database (FIMBANK), diagnosed according to the 2008 or 2016 WHO criteria. Statistical analysis was performed using R software (version 3.5.1, www.R-project.org, Vienna, Austria). Data were compared using the Fisher exact test for categorical variables and Mann–Whitney test for continuous variables. Weighting-based Propensity scores (Inverse Probability Weighting) were used to account for individuals profile differences between JAK2 exon 12 mutations and JAK2V617F mutation. This weighting-based adjustment enabled us to report the specific causal effect of exon 12 mutations on OS (overall survival) and EFS (event free survival). To do this, a survival analysis was performed using a weighting multivariate Cox modeling. The graphical representation was performed using Kaplan–Meier curves taking this weighting into account.

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Fig. 1: Prognostic impact of JAK2 exon 12 mutations.

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Acknowledgements

This work was supported in part by grants from the French National Institute of Cancer (FIMBANK, INCa BCB 2013). The authors thank the Brest Biological Resources Center BB-0033–00037 (“CRB Santé du CHRU de Brest”) for providing high-quality annotated samples. The authors thank Laurence Sanhes, Célia Belkhodjia, Pascale Cony-Makhoul, Jérôme Poirot, Valérie Bardet, Gandhi Damaj and Loïc Garçon for providing clinical and biological data of patients.

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Authors and Affiliations

  1. CHU Grenoble, Laboratoire de Génétique des hémopathies, Institut de Biologie et Pathologie, Grenoble, France

    Sylvie Tondeur

  2. CNRS UMR 5309, INSERM, U1209, Université Grenoble Alpes, Institute for Advanced Bioscience, Grenoble, France

    Sylvie Tondeur

  3. CHU Montpellier, Service d’Hématologie clinique, Montpellier, France

    Franciane Paul

  4. Université d’Angers, INSERM 1066 MINT, Angers, France

    Jérémie Riou

  5. CHU de Bordeaux, Laboratoire d’Hématologie et Université de Bordeaux, Inserm U1034, Bordeaux, France

    Olivier Mansier

  6. CHU Nancy, Hématologie clinique, Nancy, France

    Dana Ranta

  7. CH Quimper, Hématologie Clinique, Quimper, France

    Lenaïg Le Clech

  8. CHRU Brest, Laboratoire d’Hématologie, Brest, France

    Eric Lippert

  9. Fédération Hospitalo-Universitaire ‘Grand Ouest Against Leukemia’ (FHU GOAL), Brest, France

    Eric Lippert, Laurane Cottin, Jean-Christophe Ianotto, Françoise Boyer, Corentin Orvain, Mathilde Hunault-Berger, Valérie Ugo & Damien Luque Paz

  10. Université Brest, Inserm, EFS, UMR 1078, GGB, Brest, France

    Eric Lippert

  11. CHU Toulouse, Service d’Hématologie, Toulouse Oncopole, Toulouse, France

    Suzanne Tavitian

  12. CH Argenteuil, Service d’Hématologie, Argenteuil, France

    Driss Chaoui

  13. CH Vannes, Hématologie clinique, Vannes, France

    Mélanie Mercier

  14. CHU Clermont-Ferrand, Hématologie clinique, Clermont-Ferrand, France

    Benoit De Renzis

  15. CHU Angers, Laboratoire d’hématologie, Angers, France

    Laurane Cottin, Valérie Ugo & Damien Luque Paz

  16. Université d’Angers, UFR Santé, Angers, France

    Laurane Cottin, Mathilde Hunault-Berger, Valérie Ugo & Damien Luque Paz

  17. Université d’Angers, Inserm, CRCINA, F-49000, Angers, France

    Laurane Cottin, Mathilde Hunault-Berger, Valérie Ugo & Damien Luque Paz

  18. APHP, Hôpital Saint Louis, Laboratoire de Biologie Cellulaire, Paris, France

    Bruno Cassinat

  19. CHU Angers, DRCI Cellule de Gestion des Données et Evaluation, Angers, France

    Jean-Marie Chrétien

  20. CHRU Brest, Service d’hématologie clinique, Brest, France

    Jean-Christophe Ianotto

  21. CH Saint-Brieuc, Hématologie Clinique, Brest, France

    Olivier Allangba

  22. Gustave Roussy, Département de Biologie et Pathologie médicales, Brest, France

    Christophe Marzac

  23. Centre Hospitalier William Morey, Chalon-sur-Saône, France

    Laurent Voillat

  24. CHU Angers, Service des maladies du sang, Angers, France

    Françoise Boyer, Corentin Orvain & Mathilde Hunault-Berger

  25. CHU Dijon, Service d’Hématologie Biologique, Dijon, France

    François Girodon

  26. APHP, Hôpital Saint Louis, INSERM UMRS 1131, Institut Universitaire d’Hématologie, Paris, France

    Jean-Jacques Kiladjian

Authors
  1. Sylvie Tondeur
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  2. Franciane Paul
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  3. Jérémie Riou
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  4. Olivier Mansier
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  21. Mathilde Hunault-Berger
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  23. Jean-Jacques Kiladjian
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  24. Valérie Ugo
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Contributions

ST, DLP and VU conceived and designed the study. ST, FP, VU and DLP collected clinical data. JMC conceived and supervised the biological clinical database of FIMBANK. DLP, JR, ST, and VU analyzed and interpreted the data. DR, LLC, ST, DC, MM, BDR, LC, JCI, FB, CO, FG and JJK cared for the patients. DLP, ST and VU wrote the manuscript and OM, BC, JJK, JCI, EL and MH revised it critically.

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Correspondence to Damien Luque Paz.

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Tondeur, S., Paul, F., Riou, J. et al. Long-term follow-up of JAK2 exon 12 polycythemia vera: a French Intergroup of Myeloproliferative Neoplasms (FIM) study. Leukemia 35, 871–875 (2021). https://doi.org/10.1038/s41375-020-0991-x

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