Acute myeloid leukemia

PTPN11 mutations are associated with poor outcomes across myeloid malignancies

To the Editor:

We read with great interest the letter by Alfayez et al. published in June 2020 on clinical impact of PTPN11 mutations in acute myeloid leukemia (AML). To complement their findings, we report outcomes of a large cohort of PTPN11-mutant (mt) patients across myeloid malignancies. Between 2013 and 2019, all patients with myeloid malignancies and a PTPN11 mutation at Moffitt Cancer Center were identified. A total of 78 PTPN11-mt patients, 56 AML, 14 myelodysplastic syndrome (MDS), 4 MDS/myeloproliferative neoplasm (MPN) and 4 primary myelofibrosis (PMF), were included.

Baseline characteristic are described in Table 1. Median age was 68 years. The majority (63%) of PTPN11-mt were detected at diagnosis. Co-mutations observed in >10% of patients were DNMT3A, NPM1, TET2, ASXL1, RUNX1, BCOR, FLT3 ITD, NRAS, U2AF1, and SRSF2 (Fig. 1). Median VAF was 23.4 (5.1–48.0). In newly diagnosed PTPN11-mt patients, VAF >20% was associated with worse outcomes (median overall survival (OS) 8.9 vs 20.5 months p = 0.04). Allogeneic hematopoietic stem cell transplant (AHSCT), which occurred 30% of patients (n = 23) was associated with improved OS (24.4 vs 5.5 months p < 0.001).

Table 1 Baseline characteristics of patients with PTPN11 mutant myeloid malignancies.
Fig. 1: Distribution of co-occurring somatic gene mutations in PTPN11-mt cohort.

Each column is somatic mutation data from individual patients. Each row represents the presence of an individual mutation in the patient cohort (name and number of mutations are decribed on the right side and rate of mutation is described on the left side). Patients are grouped by disease type and disease state (newly diagnosed vs relapsed) seen at bottom of the plot.

We then compared PTPN11-mt patients to PTPN11-wild type (wt) patients among each disease category. In PTPN11-mt AML patient (n = 56 vs n = 380 in wt AML), similar to Alfayez et al., there was female predominance (54 vs 39% p = 0.04), platelet count was higher (65 vs 45 p = 0.02) and no PTPN11-patients had favorable cytogenetics (0 vs 9% p = 0.02). In our cohort, NPM1 and NRAS were more prevalent in PTPN11-mt AML (p = 0.05 and 0.04). In newly diagnosed patients, there was no difference in overall response rates (ORR) and complete responses (CR) between PTPN11-mt and wt cohorts. The ORR was 73% and CR was 54% with induction chemotherapy (IC) among PTPN11-mt group compared to 70% ORR and 51% CR among patients with PTPN11-wt. For those treated with hypomethylating agents (HMA), ORR was 27% and CR 17% in the PTPN11-mt group compared to 26% ORR and 14% CR in PTPN11-wt. We then looked at transplant outcomes in our AML cohort. 32% of PTPN11-mt AML patient underwent AHSCT vs 26% in the wt group (p = 0.34). PTPN11-mt AML patients who underwent AHSCT had an OS of 24.4 vs 42.7 months in wt patients (p = 0.03) whereas OS in patients that did not undergo AHSCT was 5.6 vs 10.1 months in PTPN11-mt vs wt (p = 0.04). Although similar this difference was not significant in the newly diagnosed cohort alone due to sample size (OS 24.4 vs 42.7 p = 0.12 and 6.8 vs 13.3 p = 0.19). AHSCT significantly improved outcomes for newly diagnosed PTPN11-mt AML patients (OS 24.4 vs 6.8 p = 0.005). Of the 13 patients that underwent AHSCT in PTPN11-mt AML, 92.3% (n = 12) received IC. Given the high frequency in NPM1 mutations in the cohort, we also compared newly diagnosed NPM1-mt/PTPN11-wt to NPM-mt/PTPN11-mt to PTPN11-mt/NPM1-wt AML patients. PTPN11-mt/NPM1-wt AML patients had a significantly worse prognosis (OS 10.3 vs 24.4 and not reached in NPM1-mt/PTPN11-mt and in NPM1-mt/PTPN11-wt p = 0.007). In PTPN11-mt/NPM1-wt, CR rate with IC was 60% and only 11% to HMA (58 and 36% in NPM1-mt cohorts). OS was similar between NPM1-mt/PTPN11-wt and NPM-mt/PTPN11-mt (p = 0.94). Only 26% of PTPN11-mt/NPM-1-wt proceed to AHSCT, however a statistically significant survival benefit was seen in these patients (OS 20.6 vs 6.7 p = 0.04).

Next, we evaluated patients with PTPN11-mt (n = 14) vs wt (n = 106) MDS. PTPN11-mt MDS patients when compared to wild type had higher bone marrow blast (9 vs 3% p = 0.03) and more patients with MDS-EB1/2 by WHO 2016 classification (11/14 (79%) vs 49/105 (46%) p = 0.04). Interestingly, however, no PTPN11-mt MDS patients had complex karyotype and there was no difference in IPSS or IPSS-R categories between groups. ASXL1, RUNX1 and SRSF2 were more frequently co-mutated in PTPN11-mt vs wt MDS (p = 0.01, 0.03 and 0.03). In newly diagnosed cohort, there were no responses to frontline HMA (ORR 0/5 (0%) for mt vs 16/34 (47%) for wt p = 0.07). PTPN11-mt MDS had a significantly worse outcomes compared to wt (OS 8.7 vs 22.3 months p = 0.001), however, this was no longer significant in newly diagnosed group due to small sample size (OS 27.5 vs 44.6 months p = 0.19).

Although rare, we then evaluated patient with PTPN11-mt MDS/MPN and PMF. We compared the 4 PTPN11-mt MDS/MPN (3 CMML, 1 MDS/MPN-U) patients to a cohort of 62 PTPN11-wt MDS/MPN patients (53 CMML). Clinical characteristics appeared similar between the two cohorts except for increased blasts (10 vs 4%) and lower baseline hemoglobin (7.6 vs 10.9) neither of which were significant based on sample size. Median time to AML transformation was 1.7 months in PTPN11-mt patients. Newly diagnosed PTPN11-mt MDS/MPN had significantly worse outcomes compared to wild type (OS 8.9 vs 28.3 months p = 0.01). In comparing the 4 PTPN11-mt PMF patients with 49 wt, there were no clinical or mutational differences. When evaluating newly diagnosed PMF, PTPN11-mt appeared to predict worse outcomes (OS 3.4 vs 12.3 p = 0.06) however this was not statistically significant due to sample size.

Here we present a large cohort of PTPN11-mt myeloid malignancies. In PTPN11-mt AML, consistent with Alfayez et al. we showed that PTPN11 was a predictor of poor prognosis. Additionally, in our cohort, AHSCT appears to significantly improve outcomes in this population. Unlike TP53 where induction is no longer recommended as frontline therapy due to poor outcomes [1], patients with PTPN11-mt AML, in general, required high intensity induction-based regimens in order to get to AHSCT. Despite the fact that HMA based therapies mostly proceeded the FDA approval of venetoclax in combination with hypomethylating agents, early data suggest that PTPN11-AML might have decreased sensitivity to venetoclax [2]. Thus, in patients that are eligible, based on our data, induction chemotherapy therapy followed by AHSCT would likely be recommended in PTPN11-mt AML. In PTPN11-mt MDS, survival was significantly affected. Additionally, no patients responded to frontline HMA therapy. Novel combinations are thus needed to improve outcomes in this subset. Lastly, despite being rare, PTPN11 mutations led to poor outcomes in MDS/MPN and PMF. In conclusion, the overall outcome of PTPN11-mt patients appear dismal. New therapies are needed to target this high-risk subtype of myeloid malignancies.


  1. 1.

    Kadia TM, Jain P, Ravandi F, Garcia-Manero G, Andreef M, Takahashi K, et al. TP53 mutations in newly diagnosed acute myeloid leukemia: Clinicomolecular characteristics, response to therapy, and outcomes. Cancer. 2016;122:3484–91.

    CAS  Article  Google Scholar 

  2. 2.

    Stevens BM, Jones CL, Winters A, Dugan J, Abbott D, Savona MR, et al. PTPN11 mutations confer unique metabolic properties and increase resistance to venetoclax and azacitidine in acute myelogenous leukemia. Blood. 2018;132:909.

    Article  Google Scholar 

Download references

Author information




DMS wrote manuscript, all authors contributed patients and or collected data and interpreted results. All authors approved final manuscript.

Corresponding author

Correspondence to David M. Swoboda.

Ethics declarations

Conflict of interest

DMS, NAA, OC, JS, and MH declare no conflict of interest. EP obtains research funding from Incyte, Kura Oncology and BMS and has received Honorari a from Novartis. ATK is on advisory boards for Blueprint Medicines, Novartis and Prelude and has been part of a speaker’s bureau for BMS. CT is on advisory boards for Abbvie, Celgene, Pfizer, BMS and Novartis and has been part of a speaker’s bureau for Astellas, BMS and Jazz. KS is on advisory committees for Takeda, BMS, Novartis, Agios. She has received research funding from Incyte and has received Honoraria from Stemline and Astellas. JEL has done consulting for AbbVie, Agios, Astella, Daiichi Sankyo, ElevateBio, Jazz and received Honoria from Agios. DAS has received research funding from Celgene and Jazz and done consulting for Celyad, Incyte, Novartis, Agios, BMS, Intellia, Kite and Syndax. RSK has been part of a speaker’s bureau for Jazz, BMS and Agios and received honoraria from Abbvie, Incyte, Acceleron, Novartis and Geron.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Swoboda, D.M., Ali, N.A., Chan, O. et al. PTPN11 mutations are associated with poor outcomes across myeloid malignancies. Leukemia 35, 286–288 (2021).

Download citation


Quick links