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Myelodysplastic syndrome

Impact of TP53 mutation variant allele frequency on phenotype and outcomes in myelodysplastic syndromes

Abstract

Although next-generation sequencing has allowed for the detection of somatic mutations in myelodysplastic syndromes (MDS), the clinical relevance of variant allele frequency (VAF) for the majority of mutations is unknown. We profiled TP53 and 20 additional genes in our training set of 219 patients with MDS or secondary acute myeloid leukemia with findings confirmed in a validation cohort. When parsed by VAF, TP53 VAF predicted for complex cytogenetics in both the training (P=0.001) and validation set (P<0.0001). MDS patients with a TP53 VAF > 40% had a median overall survival (OS) of 124 days versus an OS that was not reached in patients with VAF <20% (hazard ratio (HR), 3.52; P=0.01) with validation in an independent cohort (HR, 4.94, P=0.01). TP53 VAF further stratified distinct prognostic groups independent of clinical prognostic scoring systems (P=0.0005). In multivariate analysis, only a TP53 VAF >40% was an independent covariate (HR, 1.61; P<0.0001). In addition, SRSF2 VAF predicted for monocytosis (P=0.003), RUNX1 VAF with thrombocytopenia (P=0.01) and SF3B1 with ringed sideroblasts (P=0.001). Together, our study indicates that VAF should be incorporated in patient management and risk stratification in MDS.

Introduction

Myelodysplastic syndromes (MDS) represent a diverse group of hematopoietic stem cell malignancies characterized by ineffective hematopoiesis, dysplasia and a propensity for transformation to acute myeloid leukemia (AML). Central to the heterogeneity of MDS is the genetic diversity, which drives the clinical phenotype and prognosis of MDS patients. Targeted next-generation sequencing (NGS) of 111 genes in a large cohort of patients (n=738) with MDS and MDS-myeloproliferative neoplasms (MDS-MPN) identified pathogenic mutations in 74%, with 43% of patients having two or three molecular and/or cytogenetic abnormalities.1 Furthermore, striking genotype–phenotype associations were demonstrated for several recurrently mutated genes. For example, SF3B1 and co-mutations of SRSF2/TET2 are highly specific for refractory anemia with ringed sideroblasts (RS) and chronic myelomonocytic leukemia (CMML), respectively.1, 2, 3, 4

TP53 mutations have been reported in 5–10% of MDS patients, although enriched in those patients with deletion of 5q (del(5q)) or complex cytogenetics.5, 6, 7 Several reports have shown that mutations involving ASXL1, ETV6, EZH2, RUNX1 and TP53 portend an inferior overall survival (OS); and complement clinical scoring systems with improved prognostic discrimination.6 More recently, mutations of TP53, DNMT3A and/or TET2 have been shown to predict inferior outcomes for patients undergoing allogeneic bone marrow (BM) transplantation.8 Although hypomethylating agents (HMA) remain the standard of care for higher risk MDS patients, TP53 mutation has been associated with inferior survival in comparison with TP53 wild-type (WT) patients treated with HMA despite no difference in response rates.9, 10 Further, TP53 mutation appears to be the critical driver of poor survival in patients with complex cytogenetics as patients with WT TP53 and complex cytogenetics do not experience inferior outcomes in the context of treatment with HMA or BM transplantation.8, 9, 10

NGS is being increasingly incorporated into clinical management decisions and the evaluation of patients with MDS and MDS-MPN. However, current results of NGS are reported and interpreted based solely on the presence or absence of mutations of interest without regard to the mutation allelic burden. Variant allele frequency (VAF) of somatic mutations has been used to reconstruct the clonal architecture in MDS and secondary AML and demonstrated to be intimately associated with the natural history and clinical course of these conditions, suggesting that the relative amount of mutation variants is actionable.11 In addition, other myeloid malignancies such as MPN have been reported to have key phenotypic differences associated with the allelic burden of JAK2 V617F.12 We therefore sought to investigate the clinical importance of VAF in highly recurrent gene mutations for which genotype–phenotype relationships have been characterized in MDS.

Subjects and methods

Patients

The training set was obtained from patients at Moffitt Cancer Center (MCC) who had NGS performed and a diagnosis of MDS, CMML, MDS/MPN, secondary AML or de novo AML with MDS features according to World Health Organization (WHO) criteria.13 Pathology review was performed at MCC. From May 2013 to October 2014, 219 patients were identified in the training set that met the above clinical criteria and had at least one pathogenic mutation. Clinical characteristics were abstracted from the date of mutational analysis. This study was approved by the MCC Scientific Review Committee and institutional review board.

The validation set for TP53 mutation was obtained from MDS patients who had NGS performed at Genoptix with peripheral blood and cytogenetic information (n=150). Genoptix-profiled patients with a RUNX1 mutation and a CBC were identified to evaluate for association with thrombocytopenia (n=41). The validation set also included co-mutated TET2 and SRSF2 or ZRSR2 patients who had a CBC with differential for evaluation of monocytosis (n=78 and 10, respectively) and SF3B1 mutated patients with pathologic quantitation of erythroid RS (n=35).

Gene mutation analysis

Genomic DNA was extracted from mononuclear cells of BM aspirate or peripheral blood (Supplementary Table S1). Recent data have shown strong concordance (>95%) for both mutation identification and VAF between peripheral blood and BM samples.14 Selected exons and flanking sequences of 21 myeloid genes (ASXL1, EZH2, ETV6, RUNX1, TP53, CBL, DNMT3A, IDH1, IDH2, JAK2, KIT, MPL, NPM1, NRAS, PHF6, SETBP1, SF3B1, SRSF2, TET2, U2AF1 and ZRSR2) were amplified by multiplex PCR. Libraries were created (560 amplicons across 117 coding regions) using a Fluidigm Access Array system (Fluidigm Corporation, South San Francisco, CA, USA). Amplicon libraries were split to be sequenced on the Illumina MiSeq platform (Illumina, San Diego, CA, USA) in duplicate. The lower limit of detection of this clinically validated assay was set at 5% mutant allele reads and the minimum depth of coverage was 500 ×. Alignment and variant calling were performed using NextGENe software (SoftGenetics, LLC, State College, PA, USA). Variant calls were then compared between the duplicate samples and annotated and filtered according to established guidelines using software that queried a variety of databases containing known germline and somatic variants (Supplementary Methods).15 Variant assessment and classifications were performed by board-certified molecular geneticists. Synonymous variants, noncoding variants more than six bases from splice junctions or germline polymorphisms at a population frequency of 1% were excluded. VAF was derived by counting the number of variant reads divided by the number of reference reads detected for any given genomic position and reported as a percentage.

For validation of TP53 VAF and survival analyses, an independent cohort (n=30) was obtained from King’s College Hospital, London, UK. In this cohort, TP53 mutations were analyzed using the Roche GS FLX sequencing platform (Roche, Indianapolis, IN, USA) as described previously.16

Statistical analysis

Survival analyses were evaluated utilizing the Kaplan–Meier method and curves compared via the log-rank test. OS was calculated from the date of mutation analysis to the date of death. Surviving patients were censored from the last date the patient was known to be alive. Multivariate Cox regression models were created to adjust for clinical and treatment characteristics with a backward selection algorithm incorporating variables with P<0.1 on univariate analysis. Categorical and continuous variables were compared by Fisher’s exact test and Mann–Whitney’s test, respectively. Optimal cutpoints were evaluated using recursive partitioning algorithms in relation to OS using the R statistical package rpart. All tests were two-sided and considered statistically significant if P<0.05.

Results

Patient characteristics

The clinical characteristics of patients in the training set (n=219) are summarized in Table 1 according to TP53 gene mutation status. Overall, TP53 WT was detected in 172 patients, whereas a TP53 mutation (TP53 MT) was detected in 47. The median follow-up in the training set was 12 months (range 6–23 months). The demographics were similar in the TP53 MT and TP53 WT cohorts with a median age of 70 years and male predominance. All patients with CMML were TP53 WT, which is concordant with the previous observation that TP53 mutation in CMML is a rare event.1, 17 Patients with a TP53 mutation, as expected, had higher risk features relative to the WT counterparts with respect to cytopenias, BM blasts and abnormal karyotype (91% in TP53 MT patients versus 50% in TP53 WT patients; P<0.0001). Consequently, patients with TP53 mutation had higher rates of secondary AML in comparison with TP53 WT patients (P=0.03). At a median follow-up of 12 months, 62% of TP53 MT patients had died compared with 28% in TP53 WT patients.

Table 1 Baseline characteristics of the study population

The mutation spectrum of the training set is shown in Figure 1a. Of note, 16% of patients (n=37) had analysis of only ASXL1, ETV6, EZH2, RUNX1 and TP53. The mutational spectrum of our cohort was enriched for higher risk mutations in comparison with previously published cohorts in regards to mutation of ASXL1 (32%), TP53 (21%), DNMT3A (15%) and RUNX1 (14%).1, 5, 6, 7 Consistent with a higher risk cohort, mutations of SF3B1, which are associated with improved OS in MDS, were present in 13% of patients, a fraction that is lower than previous studies.2, 3, 18 Missense mutations represented the most common aberration in TP53 MT patients accounting for 85% overall (n=40; Supplementary Table S2). As previously reported, TP53 MT strongly predicted for the presence of complex karyotype, occurring in 75% of TP53 MT patients versus only 6% of TP53 WT patients (Figure 1b; P<0.0001).6, 7

Figure 1
figure1

Mutational spectrum across patients profiled at Moffitt Cancer Center. (a) A total of 219 patients were identified by next-generation sequencing for mutation in a 21-gene panel. Each column represents an individual patient and each colored box represents mutation of the gene listed to the left. The presence of complex cytogenetics is shown in black for each individual patient in the most inferior row. Bar graph on right shows distribution of each mutation. TP53 VAF and number of mutations for each TP53 mutated patient are depicted in the superior and inferior bar graphs, respectively. (b) Presence of complex cytogenetics in TP53 mutant (TP53 MT) and TP53 wild-type (TP53 WT) patients. (c) TP53 VAF for the 47 TP53 MT patients along with presence of complex cytogenetics. Dashed bar highlights patients with TP53 mutation with additional somatic mutations.

TP53 VAF and complex cytogenetics

To investigate the effect of TP53 clonal burden on chromosomal complexity, we stratified our TP53 MT patients from highest to lowest VAF and the presence of complex karyotype, which demonstrated a striking relationship between VAF and frequency of karyotype complexity (Figure 1c). The median VAF was significantly higher in patients with complex karyotype than noncomplex patients (49% versus 14%; P=0.001; Figure 2b). Next, we analyzed TP53 MT patients stratified by those with a VAF >40% versus a VAF <20%. An a priori VAF cutpoint of >40% was chosen because it is likely to enrich for mutants residing in a dominant clone as reported in multiple recent studies.18, 19, 20, 21 To confirm that a VAF >40% is a suitable cut point that enriches for mutations within the dominant clone, we analyzed those TP53 mutant patients with a VAF >40% who harbored additional mutations and confirmed that a clonal burden >40% was the highest VAF when compared with other acquired mutations.

Figure 2
figure2

TP53 VAF strongly predicts for complex cytogenetics in the training (a, b) and validation sets (ce). (a) Presence of complex cytogenetics in in patients with TP53 mutation with VAF >40% versus <20%. (b) Median TP53 VAF in patients with and without complex cytogenetics in the training set. (c) Presence of complex cytogenetics in patients with TP53 mutation with VAF >40% versus <20%. (d) Median TP53 VAF in patients with and without complex cytogenetics in the validation set. (e) Association of complex cytogenetics stratified across three VAF cohorts.

In our training set, all TP53 MT patients (n=21) with a VAF >40% had a complex karyotype versus 54% of patients (n=7) with a VAF <20% (P=0.001; Figure 2a). In addition, TP53 MT patients with a VAF >40% infrequently had additional mutations versus patients with a lower VAF (20% versus 46%; P=0.07; Supplementary Figure S1), a finding consistent with recent studies.7, 8 In our validation set of 150 patients with a TP53 mutation, a striking association of VAF with complex cytogenetics was again observed occurring in 78% of patients (n=46) with a dominant clone and only 38% of patients (n=18) with a VAF <20% (P<0.0001; Figure 2c). Patients with a complex karyotype in the validation set also had a significantly increased median VAF in comparison with noncomplex patients (40% versus 20%; P<0.0001; Figure 2d). To further evaluate the association of TP53 VAF and complex cytogenetics in our validation set, we further stratified VAF into three cohorts and again found a significant association between VAF and complex karyotype (P=0.0002; Figure 2e).

TP53 VAF and survival

Because TP53 mutation status is an important risk factor for OS in MDS, we next evaluated the clinical impact of TP53 VAF on OS. As expected, TP53 mutation predicated for an inferior OS confirming previously reported data (162 days versus not reached; hazard ratio (HR), 2.64; 95% confidence interval (CI) 2.00–6.31; P<0.0001; Figure 3a).6 Patients with complex cytogenetics and TP53 mutation had a median OS of 161 days versus 374 days in TP53 WT patients with complex cytogenetics (HR, 2.08; 95% CI 0.80–4.34; P=0.16; Supplementary Figure S2).8 In addition, TP53 MT patients with additional molecular abnormalities had similar survival to those with isolated TP53 mutation (Supplementary Figure S3).

Figure 3
figure3

OS by TP53 mutation status and TP53 VAF. (a) OS of patients stratified by TP53 mutation status. OS of patients (b) stratified by TP53 VAF >40% versus <20% and (c) across three VAF cohorts. (d) In our validation cohort, OS of patients stratified by TP53 VAF >40% versus <20%.

We next examined the impact of VAF on the prognosis of patients with TP53 mutation compared with binary mutational analysis alone. Patients with a TP53 VAF >40% had a poor OS of only 124 days in contrast to a median OS that was not reached in patients with VAF <20% (HR, 3.52; 95% CI 1.24–6.50; P=0.01; Figure 3b). Furthermore, stratification of TP53 VAF into three distinct categories (VAF>40%, VAF 20–40% and VAF <20%) inversely correlated with inferior OS (P=0.02; Figure 3c). External validation of an independent cohort of 30 TP53 mutant patients from the King’s College demonstrated that patients with a TP53 VAF >40% had a median survival of 272 days compared with 1372 days with TP53 VAF <20% (HR 4.94, 95% CI 1.43–9.21; P=0.01; Figure 3d), confirming our initial findings. As a continuous measure in TP53 mutant patients across both cohorts (n=77), increasing TP53 VAF was significantly associated with inferior OS (P=0.01). Using a recursive partitioning algorithm to stratify our data relative to OS, an optimal VAF cutpoint was identified at 20% (Supplementary Figure S4). Specifically, median OS with TP53 VAF <20% was 685 days versus 183 days with VAF 20% (P=0.0036). Furthermore, there was no survival difference based on VAF in regards to the other most commonly mutated genes in the training set including ASXL1, TET2, DNMT3A and RUNX1.

Because binary output from genetic profiling refines MDS prognosis above that achieved with the international prognostic scoring system (IPSS) alone,6 we sought to determine whether TP53 VAF would complement current risk models. Our analysis focused on TP53 VAF in higher risk MDS because the majority of TP53 MT patients had intermediate-2/high risk disease by the IPSS (74%, n=26). In patients with intermediate-2 risk disease (n=12), the presence of TP53 mutation was predictive of an inferior survival with a median OS of 93 days versus 297 days in TP53 WT patients (HR, 3.15; 95% CI 1.45–12.53; P=0.009; Figure 4a). Interestingly, TP53 VAF further refined poor prognosis in patients with intermediate-2 risk disease. Patients with a VAF >40% had a median OS of 55 days compared with 154 days in those with VAF <40%, and 297 days in TP53 WT patients (P=0.0005; Figure 4b). These findings were also recapitulated in patients with IPSS-defined high risk disease (n=14) when similarly stratified by TP53 mutation status (HR, 2.56; 95% CI 1.14–7.54; P=0.03; Figure 4c).6 When stratified by TP53 VAF, high risk TP53 MT patients demonstrated an inverse correlation between VAF and OS, which was not statistically significant (P=0.07; Figure 4d).

Figure 4
figure4

OS by TP53 VAF and IPSS risk category. OS of intermediate-2 (int-2) patients (a) and high risk patients (c) stratified by TP53 mutation status. (b) OS of int-2 patients and high risk patients (d) stratified by the mutational VAF of TP53 in comparison with TP53 WT patients.

Because our data suggest that analysis of TP53 VAF refines the prognosis of MDS compared with binary mutational analysis, we developed a multivariate Cox model to determine the impact of VAF versus binary mutational analysis for prognosis (Table 2). In regards to disease-modifying therapy, there was no difference in utilization of HMA therapy or allogeneic BM transplantation based on TP53 VAF (Supplementary Table S3). In univariate analysis, only a trend for significance in patients with a TP53 VAF of 20–40% (HR, 2.13; 95% CI 0.91–9.32; P=0.07) and no significance in patients with a VAF <20% (HR, 1.18; 95% CI 0.40–3.57; P=0.75) was identified with respect to OS. Further, in our final multivariable Cox model that incorporates age, sex, BM transplant status and IPSS, only the mutational status of TP53 (HR, 1.47; 95% CI 1.16–1.86; P=0.002) and TP53 mutation VAF >40% retained prognostic significance (HR, 1.61; 95% CI 1.25–2.08; P<0.0001). The above analyses were also validated with incorporation of the revised-IPSS (RIPSS).

Table 2 Prognostic impact of TP53 mutation and TP53 VAF in the training set in univariate (log-rank tests) and multivariatea (Cox models) analyses

VAF is associated with phenotype penetrance across multiple genes

Because we have shown that TP53 VAF correlates strongly with complex karyotype, we hypothesized that VAF could influence the genotype–phenotype association with additional gene mutations in MDS patients. Malcovati et al.18 previously reported the association of SF3B1 VAF with an increase in BM percentage of RS. Given the lower proportion of SF3B1 MT patients in our training set, we sought to investigate this previous finding in our validation set in patients with an absolute quantity of RS on the BM (n=35). Although the distribution of SF3B1 MT VAF was Gaussian rather than bimodal in our cohort, which differs from the previously mentioned study, SF3B1 VAF indeed strongly predicted for the percentage of RS with median RS of 60% in patients with a dominant clone versus 15% in patients with a VAF <20% (P=0.001; Supplementary Figure S5).

Co-mutation of TET2 and SRSF2 or ZRSR2 has been found to be highly specific for CMML with a specificity of 98.4% in a cohort of 308 patients.4 Therefore, we investigated the impact of SRSF2 and/or ZRSR2 VAF on monocytosis in our data set. SRSF2 MT VAF strongly predicted for the presence of monocytosis defined as a monocyte count of greater than 1000/dl, 83% (n=10) with SRSF2 VAF >40% versus 33% (n=5) with SRSF2 VAF <20% (n=78; P=0.003; Figure 5a). Further, the SRSF2 median VAF was significantly higher in patients with monocytosis (32% versus 18%; P=0.0003; Figure 5b) and was also predictive of the degree of monocytosis (median monocyte count 1750 versus 550; P=0.004; Figure 5c). Although limited numbers, ZRSR2 VAF in TET2/ZRSR2 MT patients did not correlate with the presence of monocytosis (n=10; P=0.37; Figure 5d).

Figure 5
figure5

VAF is associated with phenotype penetrance across multiple genes. (a) Presence of monocytosis (monocyte count >1000 cells/dl) in co-mutated TET2/SRSF2 mutant patients stratified by SRSF2 VAF. (b) Median SRSF2 VAF in patients with co-mutated TET2/SRSF2 with and without monocytosis. (c) Absolute monocyte count in TET2/SRSF2 mutant patients with SRSF2 VAF >40% versus <20%. (d) Median ZRSR2 VAF in TET2/ZRSR2 mutant patients with and without monocytosis. Median RUNX1 VAF in patients with and without thrombocytopenia in the training (e) and validation (f) sets. Median platelet counts in patients with RUNX1 mutation with VAF >40% versus <20% in the training (g) and validation (h) sets.

Because severe thrombocytopenia has been reported to be associated with mutation of RUNX1,6, 22 we next investigated whether RUNX1 VAF could predict for the presence of thrombocytopenia (platelet count <150 × 109/l) and/or its severity. Indeed, thrombocytopenia was influenced by the VAF of RUNX1 mutation with a median RUNX1 MT VAF of 31% in thrombocytopenic patients versus 12% in those without thrombocytopenia within our training set (P=0.01; Figure 5e), which approached significance in the validation set (median VAF 24% versus 11%; P=0.09; Figure 5f). Patients with a RUNX1 MT VAF >40% had lower platelet counts than patients with a VAF <20% in both the training set (29 × 109/l versus 48 × 109/l; P=0.53; Figure 5g) and validation set (54 × 109/l versus 77 × 109/l; P=0.10; Figure 5h), although this did not reach statistical significance.

Discussion

The optimization of genomics in routine clinical MDS management remains an evolving challenge. Although the importance of VAF is implied across many genetic MDS studies, the clinical impact of VAF has been largely unexplored.1, 18 Furthermore, there was no difference in leukemia-free survival when mutations involving TET2, SF3B1, ASXL1, SRSF2, CBL, EZH2 and RUNX1 were identified in the dominant clone versus a sublcone.1, 18

To comprehensively investigate the clinical relevance of mutation VAF in MDS, we molecularly profiled 219 patients and characterized clinical variables at the time of mutation analysis. Because TP53 mutation is a critical adverse risk factor in MDS,6, 16, 23, 24, 25 we focused our efforts on the influence of TP53 VAF on outcome by leveraging a training set (n=47), a validation set (n=150) and an external independent cohort (n=30) that collectively represents among the largest MDS cohorts assembled to date for the clinical evaluation of TP53 mutation. Mutations of TP53 have historically been associated with complex cytogenetics that was also evident in our study.23, 24, 26 However, we show that VAF strongly influences this association with the vast majority of patients with a TP53 mutation in the dominant clone having a complex karyotype. Furthermore, TP53 VAF was directly proportional to the absolute number of cytogenetic abnormalities (Supplementary Figure S6). This has particular clinical relevance because of the inferior survival in patients with five or more chromosome abnormalities compared with patients with three to four abnormalities.25 We also report that the mutation VAF is strongly associated with specific clinical phenotypes across multiple gene mutations, suggesting that allelic burden is likely to influence phenotype across the genetic spectrum of MDS. Specifically, SRSF2 mutation in co-mutated TET2/SRSF2 patients was strongly concordant with monocytosis. Furthermore, we also identified RUNX1 VAF to predict for the presence and severity of thrombocytopenia and confirmed the association of SF3B1 VAF with BM RS percentage. Together, these data indicate the importance of allelic burden in clinical phenotype in patients with MDS and perhaps other myeloid malignancies.

Although multivariable analyses validated the independent negative prognostic impact of TP53 mutation,6 our Cox regression model highlights that this is dependent on its location within the clonal hierarchy as only patients with a VAF >40% had inferior survival. Notably, patients with TP53 VAF of 20–40% had a trend for inferior survival in univariate analysis and no survival difference in TP53 MT patients with a VAF <20%, suggesting that VAF is a critical determinant of prognosis in MDS patients. Furthermore, we validated our survival findings in an independent cohort and identified a VAF threshold of 20% as the optimal cutoff to stratify survival. Although our data suggest that VAF of recurrent mutations influences clinical characteristics, we fully recognize that clonal hierarchy is a dynamic process. Notably, recent data identified that an increase in TP53 VAF was greatest at the time of progression to higher risk disease or AML.27 This highlights the potential importance of serial analysis, particularly in the examination of TP53 VAF and suggests that TP53 may be uniquely connected to adverse clinical trajectories.

Another distinct issue is that recent molecular characterization of large cohorts of patients with no known hematologic disease demonstrated that clonal hematopoiesis is a common event with age occurring in approximately 5–10% of patients over the age of 65.28, 29, 30 Although the overall risk of progression to overt hematologic malignancy was uncommon (1% per year), the risk was significantly higher in patients with a higher clonal burden with a 50-fold increase in patients with a VAF >10%.29 Although TP53 mutations were overall a rare event in these studies, they did occur in 1–5% of patients profiled. Whether mutations with a low VAF truly impart the same prognosis should be explored.

The present study highlights the value of VAF across MDS mutations and strongly suggests that TP53 VAF should be incorporated into routine clinical prognostication and treatment decisions of MDS. They further support a critical need for sequential investigation of patients with MDS to improve real-time prognostication and genetically inform treatment-related decisions such as BM transplantation and HMA therapy. International collaborative efforts are ongoing to definitively characterize the mutational spectrum of MDS and its influence on clinical phenotype and outcomes.25

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Correspondence to E Padron.

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CV, MM, SN and JH are employees of Genoptix, Inc., a Novartis company and own stock in the company. The other authors declare no conflict of interest.

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DS and EP designed the research, analyzed data and wrote the paper. MM, SN, KM, NA, AS and AK collected the data and gave final approval. RK, TC and SG analyzed data and gave the final approval. CV and JH collected the data, reviewed the paper and gave the final approval. JL, GM and AL reviewed the paper and gave the final approval.

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Sallman, D., Komrokji, R., Vaupel, C. et al. Impact of TP53 mutation variant allele frequency on phenotype and outcomes in myelodysplastic syndromes. Leukemia 30, 666–673 (2016). https://doi.org/10.1038/leu.2015.304

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