Supplemental Figure 2. Overall survival from Collection of sample. Survival differences were also analyzed from the time of collection of sample instead of time of diagnosis. Panel A shows survival difference between MF with 0-3 variants and >=4 variants. Panel B shows survival difference between MF patients harboring Ras pathway mutations and those not. Panel C shows the percent survival of patients with ASXL1 mutations in <=60 and >60 age groups as compared to patients without ASXL1 mutation in the same age brackets.
ARTICLE ABSTRACT
Myeloproliferative neoplasms (MPN) are characterized by the overproduction of differentiated myeloid cells. Mutations in JAK2, CALR, and MPL are considered drivers of Bcr-Abl−ve MPN, including essential thrombocythemia (ET), polycythemia vera (PV), prefibrotic primary myelofibrosis (prePMF), and overt myelofibrosis (MF). However, how these driver mutations lead to phenotypically distinct and/or overlapping diseases is unclear.
To compare the genetic landscape of MF to ET/PV/PrePMF, we sequenced 1,711 genes for mutations along with whole transcriptome RNA sequencing of 137 patients with MPN.
In addition to driver mutations, 234 and 74 genes were found to be mutated in overt MF (N = 106) and ET/PV/PrePMF (N = 31), respectively. Overt MF had more mutations compared with ET/PV/prePMF (5 vs. 4 per subject, P = 0.006). Genes frequently mutated in MF included high-risk genes (ASXL1, SRSF2, EZH2, IDH1/2, and U2AF1) and Ras pathway genes. Mutations in NRAS, KRAS, SRSF2, EZH2, IDH2, and NF1 were exclusive to MF. Advancing age, higher DIPSS, and poor overall survival (OS) correlated with increased variants in MF. Ras mutations were associated with higher leukocytes and platelets and poor OS. The comparison of gene expression showed upregulation of proliferation and inflammatory pathways in MF. Notably, ADGRL4, DNASE1L3, PLEKHGB4, HSPG2, MAMDC2, and DPYSL3 were differentially expressed in hematopoietic stem and differentiated cells.
Our results illustrate that evolution of MF from ET/PV/PrePMF likely advances with age, accumulation of mutations, and activation of proliferative pathways. The genes and pathways identified by integrated genomics approach provide insight into disease transformation and progression and potential targets for therapeutic intervention.
