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-JAK2V617F and CALRm-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 CALRm mutations tend to occur later in life than JAK2V617F. Our results confirm the higher proliferative advantage of the CALRm malignant clone compared to JAK2V617F. Furthermore, we illustrate how mathematical modeling and Bayesian inference can be used for setting up early screening strategies.
Keywords: JAK2/CALR mutations; approximate bayesian computation; cancer early detection; mathematical modeling of cell populations; myeloproliferative neoplasms.