Prognostic Mutations in Myelodysplastic Syndrome after Stem-Cell Transplantation

Abstract

Background: Genetic mutations drive the pathogenesis of the myelodysplastic syndrome (MDS) and are closely associated with clinical phenotype. Therefore, genetic mutations may predict clinical outcomes after allogeneic hematopoietic stem-cell transplantation.

Methods: We performed targeted mutational analysis on samples obtained before transplantation from 1514 patients with MDS who were enrolled in the Center for International Blood and Marrow Transplant Research Repository between 2005 and 2014. We evaluated the association of mutations with transplantation outcomes, including overall survival, relapse, and death without relapse.

Results: TP53 mutations were present in 19% of the patients and were associated with shorter survival and a shorter time to relapse than was the absence of TP53 mutations, after adjustment for significant clinical variables (P<0.001 for both comparisons). Among patients 40 years of age or older who did not have TP53 mutations, the presence of RAS pathway mutations was associated with shorter survival than was the absence of RAS pathway mutations (P=0.004), owing to a high risk of relapse, and the presence of JAK2 mutations was associated with shorter survival than was the absence of JAK2 mutations (P=0.001), owing to a high risk of death without relapse. The adverse prognostic effect of TP53 mutations was similar in patients who received reduced-intensity conditioning regimens and those who received myeloablative conditioning regimens. By contrast, the adverse effect of RAS pathway mutations on the risk of relapse, as compared with the absence of RAS pathway mutations, was evident only with reduced-intensity conditioning (P<0.001). In young adults, 4% of the patients had compound heterozygous mutations in the Shwachman-Diamond syndrome-associated SBDS gene with concurrent TP53 mutations and a poor prognosis. Mutations in the p53 regulator PPM1D were more common among patients with therapy-related MDS than those with primary MDS (15% vs. 3%, P<0.001).

Conclusions: Genetic profiling revealed that molecular subgroups of patients undergoing allogeneic hematopoietic stem-cell transplantation for MDS may inform prognostic stratification and the selection of conditioning regimen. (Funded by the Edward P. Evans Foundation and others.).

Figure 1. Frequency of Driver Mutations and Age-Independent Association of TP53 Mutations with Poor Overall Survival

Panel A shows the frequency of driver mutations in the study cohort; included are the 32 genes that were evaluated in the multivariable models. A complete list of mutation frequencies is provided in Table S7 in the Supplementary Appendix. Panel B shows Kaplan–Meier curves for overall survival according to TP53 mutation status. Tick marks indicate censored data. Panel C shows Kaplan–Meier curves for overall survival among patients with TP53 mutations (red) or without TP53 mutations (black), according to age. Dashed lines represent patients younger than 40 years of age, and solid lines patients 40 years of age or older. Among patients without TP53 mutations, younger patients had longer survival than older patients (hazard ratio for death, 0.54; 95% confidence interval [CI], 0.45 to 0.65; P<0.001). Among patients with TP53 mutations, survival was similar among younger patients and older patients (hazard ratio, 0.86; 95% CI, 0.56 to 1.31; P = 0.50).

Figure 2. PPM1D and TP53 Mutations Associated with Therapy-Related MDS

Panel A shows the association between gene mutations and therapy-related MDS or primary MDS. A volcano plot was constructed by plotting the negative log of the P value on the y axis; the x axis shows the magnitude of association (log₂ odds ratio), and the y axis the −log₂ P value. The gray line represents the threshold of significance determined by correcting for multiple hypothesis testing. Each circle represents a mutated gene, and the size of each circle corresponds to the frequency of the mutation among patients with therapy-related MDS, as indicated. Genes in the upper right quadrant were significantly associated with therapy-related MDS (red), and genes in the upper left quadrant with primary MDS. Panel B shows the proportion of patients with primary MDS or therapy-related MDS according to TP53 and PPM1D mutation status. Panel C shows the proportion of patients with complex karyotype (>3 alterations) or noncomplex karyotype (≤3 alterations) according to TP53 and PPM1D mutation status. The numbers above the bars in Panels B and C show the total number of patients in each group.

Figure 3. Biallelic SBDS Mutations in Young Adult Patients and Association with Poor Survival

Panel A shows the association between mutated genes and the age of the patient. Each circle represents a mutated gene, and the size of each circle corresponds to the frequency of the mutation in the total cohort, as indicated. Genes in the upper right quadrant were significantly associated with an age of 40 years or more (blue), and genes in the upper left quadrant with an age of less than 40 years (red). Panel B shows Kaplan–Meier curves for overall survival among patients younger than 40 years of age according to PIGA, GATA2, or SBDS mutation status. Data for patients without mutations in these genes are shown in gray. Patients with biallelic SBDS mutations (SBDS×2, red) had shorter survival than those without SBDS mutation (P = 0.009). Tick marks indicate censored data.

Figure 4. Models for Overall Survival, Including Clinical and Genetic Variables and Effect of Conditioning Intensity

Shown is a hierarchical prognostic model for overall survival that was based on recursive partitioning analysis.