A molecular signature predicts hematologic evolution in polycythemia vera patients

Genetic analyses have been included in scoring systems to improve the prognostic stratification of hematologic malignancies. Until now, molecular risk scores have not been included into the practical management of patients with polycythemia vera (PV). In this work, we studied 439 PV patients recruited from 15 French centers and described their mutational landscape using high-throughput sequencing. We detected an additional mutation in 53.3% of patients, 22.7% of them having 2 or more mutations. A Bayesian approach identified preferential associations between mutations. Based on these associations, we identified high molecular risk abnormalities in PV (PV-HMR), consisting in mutations in SRSF2, IDH1/2, EZH2 or NFE2 genes, copy number variations (CNV) and carrying 2 or more non-driver mutations. These PV-HMR were associated with decreased overall survival (OS) and/or transformation-free survival (TFS). Notably, ASXL1 mutations were not associated with a pejorative impact on OS or TFS when isolated. Based on these results, we developed a genomic 3-tier classification that efficiently predicted OS and more importantly TFS independently of age, sex, history of thrombosis and leukocyte and platelet counts. This model outperformed the IWG-PV and MIPSS-PV scoring systems in predicting the hematologic evolution of PV patients, which was confirmed in 2 external cohorts.

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Journal
Leukemia
Published
2025-06-18
DOI
https://doi.org/10.1038/s41375-025-02660-0
Primary Topic
Myeloproliferative Neoplasms: Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
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A molecular signature predicts hematologic evolution in polycythemia vera patients

Christopher Nunes Gomes, Guillaume Denis, Lydia Roy, Jean‐Jacques Kiladjian et al.
Leukemia
Myeloproliferative Neoplasms: Diagnosis and Treatment
article

A molecular signature predicts hematologic evolution in polycythemia vera patients

Christopher Nunes Gomes, Guillaume Denis, Lydia Roy, Jean‐Jacques Kiladjian, Jean‐Christophe Ianotto, Léa Sureau, Valérie Ugo, Juliette Soret‐Dulphy, Jérémie Riou, François Girodon, Véronique Mansat‐De Mas, Olivier Mansier, Claire Calmettes, Lina Benajiba, Emmanuelle Verger, Ivan Sloma, Fiorenza Barraco, Aurélie Chauveau, Fabienne Vacheret, Laurence Legros, Éric Lippert, Dana Ranta, Sarah Huet, Damien Luque Paz, Marion Divoux, Corentin Orvain, Suzanne Tavitian, Joris Argentin, Bruno Cassinat, Clémence Mediavilla, Mélanie Mercier, Françoise Boyer, Anne Parry, Mélinda Fanet
article en

Abstract

Genetic analyses have been included in scoring systems to improve the prognostic stratification of hematologic malignancies. Until now, molecular risk scores have not been included into the practical management of patients with polycythemia vera (PV). In this work, we studied 439 PV patients recruited from 15 French centers and described their mutational landscape using high-throughput sequencing. We detected an additional mutation in 53.3% of patients, 22.7% of them having 2 or more mutations. A Bayesian approach identified preferential associations between mutations. Based on these associations, we identified high molecular risk abnormalities in PV (PV-HMR), consisting in mutations in SRSF2, IDH1/2, EZH2 or NFE2 genes, copy number variations (CNV) and carrying 2 or more non-driver mutations. These PV-HMR were associated with decreased overall survival (OS) and/or transformation-free survival (TFS). Notably, ASXL1 mutations were not associated with a pejorative impact on OS or TFS when isolated. Based on these results, we developed a genomic 3-tier classification that efficiently predicted OS and more importantly TFS independently of age, sex, history of thrombosis and leukocyte and platelet counts. This model outperformed the IWG-PV and MIPSS-PV scoring systems in predicting the hematologic evolution of PV patients, which was confirmed in 2 external cohorts.

LeukemiaVol. 39(8)
Centre National de la Recherche Scientifique (FR), Université Toulouse III - Paul Sabatier (FR), Université de Bordeaux (FR), Inserm (FR), Université de Bretagne Occidentale (FR), École nationale d'ingénieurs de Brest (FR), Université Paris-Est Créteil (FR), Université Paris Cité (FR), Centre Hospitalier Universitaire de Bordeaux (FR), Centre Hospitalier Universitaire Henri-Mondor (FR), Clinique des Cèdres (FR), Centre Hospitalier de Perpignan (FR), Centre de Recherche en Cancérologie et Immunologie Intégrée Nantes Angers (FR), Assistance Publique – Hôpitaux de Paris (FR), Institut universitaire du cancer de Toulouse Oncopole (FR), Centre Hospitalier Régional et Universitaire de Nancy (FR), Hospices Civils de Lyon (FR), Bordeaux Population Health (FR), Centre hospitalier Bretagne Atlantique (FR), Centre Hospitalier Universitaire d'Angers (FR), Hôpital Lyon Sud (FR), CHU Dijon Bourgogne (FR), Centre Hospitalier de Cornouaille (FR), Hôpitaux Universitaires Henri-Mondor (FR), Centre Hospitalier Régional Universitaire de Brest (FR), Centre Hospitalier de Rochefort (FR), Centre Hospitalier Annecy Genevois (FR), Hôpital Saint-Louis (FR), Institut Mondor de Recherche Biomédicale (FR), Bicêtre Hospital (FR), Université d'Angers (FR), Nantes Université (FR)
Institut National de la Santé et de la Recherche Médicale, Institut National Du Cancer, Centre Hospitalier Universitaire de Bordeaux
Good health and well-being
Openalex Percentile: Top 80%
Myeloproliferative Neoplasms: Diagnosis and Treatment
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