Impact of genomic alterations on outcomes in myelofibrosis patients undergoing JAK1/2 inhibitor therapy

Abstract

In myelofibrosis (MF), driver mutations in JAK2, MPL, or CALR impact survival and progression to blast phase, with the greatest risk conferred by triple-negative status. Subclonal mutations, including mutations in high-molecular risk (HMR) genes, such as ASXL1, EZH2, IDH1/2, and SRSF2 have also been associated with inferior prognosis. However, data evaluating the impact of next-generation sequencing in MF patients treated with JAK1/2 inhibitors are lacking. Using a 54-gene myeloid panel, we performed targeted sequencing on 100 MF patients treated with ruxolitinib (n = 77) or momelotinib (n = 23) and correlated mutational profiles with treatment outcomes. Ninety-nine patients had at least 1 mutation identified, 46 (46%) had 2 mutations, and 34 (34%) patients had ≥3 mutations. Seventy-nine patients carried a mutation in JAK2V617F, 14 patients had mutations in CALR, 6 patients had an MPL mutation, and 2 patients were triple negative. No mutation was significantly associated with spleen or anemia response. A high Dynamic International Prognostic Scoring System score and pretreatment transfusion dependence were associated with a shorter time to treatment failure (TTF), and this association retained significance on multivariable analysis. Patients with ASXL1 (hazard ratio [HR], 1.86; P = .03) and EZH2 mutations (HR, 2.94; P = .009) and an HMR profile (HR, 2.06; P = .01) had shorter TTF. On multivariate analysis, ASXL1 or EZH2 mutations were independently associated with shorter TTF and overall survival. These findings help identify patients unlikely to have a durable response with current JAK1/2 inhibitors and provide a framework for future studies.

Conflict of interest statement

Conflict-of-interest disclosure: T.P. provided consultancy services to Celgene. A. Schimmer, D.M., and N.S. received honoraria from Novartis. A. Schuh served on the advisory board of Amgen. K.Y. received research funding and served on the advisory board of Novartis. S.K.-R. received research funding from Bristol-Myers Squibb. V.G. received research funding through his institution and honoraria from Novartis and Incyte and has served on the advisory board of Novartis. The remaining authors declare no competing financial interests.

Figures

Graphical abstract

Figure 1.

Landscape plot of mutations. Each column represents an individual patient. The bar graph represents the number of mutations per patient.

Figure 2.

Kaplan-Meier curves for TTF. (A) DIPSS score. (B) Pretreatment transfusion dependence. (C) ASXL1/EZH2 mutations. (D) Number of mutations, stratified by HMR.

Figure 3.

Kaplan-Meier curves for OS. (A) DIPSS score. (B) Pretreatment transfusion dependency. (C) ASXL1/EZH2 mutations. (D) Number of mutations, stratified by HMR.