Inferring the initiation and development of myeloproliferative neoplasms

Gurvan Hermange (1) , Alicia Rakotonirainy (1) , Mahmoud Bentriou (1) , Amandine Tisserand (2, 3, 4) , Mira El-Khoury (3, 2, 4) , François Girodon (5, 6) , Christophe Marzac (3, 7, 4) , William Vainchenker (3, 8, 4) , Isabelle Plo (3, 8, 4) , Paul-Henry Cournède (1)

1 MICS - Mathématiques et Informatique pour la Complexité et les Systèmes
2 UPCité - Université Paris Cité
3 IGR - Institut Gustave Roussy
4 CSHMyelo - U1287 Inserm - Cellules souches hématopoïétiques et développement des hémopathies myéloïdes
5 CHU Dijon
6 LNC - Lipides - Nutrition - Cancer [Dijon - U1231]
7 Département de biologie et pathologie médicales [Gustave Roussy]
8 Dynamo - Dynamique moléculaire de la transformation hématopoïétique

The developmental history of blood cancer begins with mutation acquisition and the resulting malignant clone expansion. The two most prevalent driver mutations found in myeloproliferative neoplasms— JAK2 V617F and CALR m —occur in hematopoietic stem cells, which are highly complex to observe in vivo. To circumvent this difficulty, we propose a method relying on mathematical modeling and statistical inference to determine disease initiation and dynamics. Our findings suggest that CALR m mutations tend to occur later in life than JAK2 V617F . Our results confirm the higher proliferative advantage of the CALR m malignant clone compared to JAK2 V617F . Furthermore, we illustrate how mathematical modeling and Bayesian inference can be used for setting up early screening strategies.

Domaines: Bio-informatique [q-bio.QM]; Complexité [cs.CC]; Modélisation et simulation

Gurvan Hermange, Alicia Rakotonirainy, Mahmoud Bentriou, Amandine Tisserand, Mira El-Khoury, et al.. Inferring the initiation and development of myeloproliferative neoplasms. Proceedings of the National Academy of Sciences of the United States of America, 2022, 119 (37), ⟨10.1073/pnas.2120374119⟩. ⟨hal-03844872⟩