Distinct clinical characteristics of myeloproliferative neoplasms with calreticulin mutations.

Somatic insertions/deletions in the calreticulin gene have recently been discovered to be causative alterations in myeloproliferative neoplasms. A combination of qualitative and quantitative allele-specific polymerase chain reaction, fragment-sizing, high resolution melting and Sanger-sequencing was applied for the detection of three driver mutations (in Janus kinase 2, calreticulin and myeloproliferative leukemia virus oncogene genes) in 289 cases of essential thrombocythemia and 99 cases of primary myelofibrosis. In essential thrombocythemia, 154 (53%) Janus kinase 2 V617F, 96 (33%) calreticulin, 9 (3%) myeloproliferative leukemia virus oncogene gene mutation-positive and 30 triple-negative (11%) cases were identified, while in primary myelofibrosis 56 (57%) Janus kinase 2 V617F, 25 (25%) calreticulin, 7 (7%) myeloproliferative leukemia virus oncogene gene mutation-positive and 11 (11%) triple-negative cases were identified. Patients positive for the calreticulin mutation were younger and had higher platelet counts compared to Janus kinase 2 mutation-positive counterparts. Calreticulin mutation-positive patients with essential thrombocythemia showed a lower risk of developing venous thrombosis, but no difference in overall survival. Calreticulin mutation-positive patients with primary myelofibrosis had a better overall survival compared to that of the Janus kinase 2 mutation-positive (P=0.04) or triple-negative cases (P=0.01). Type 2 calreticulin mutation occurred more frequently in essential thrombocythemia than in primary myelofibrosis (P=0.049). In essential thrombocythemia, the calreticulin mutational load was higher than the Janus kinase 2 mutational load (P<0.001), and increased gradually in advanced stages. Calreticulin mutational load influenced blood counts even at the time point of diagnosis in essential thrombocythemia. We confirm that calreticulin mutation is associated with distinct clinical characteristics and explored relationships between mutation type, load and clinical outcome.