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Myeloproliferative neoplasms (MPN) represent a heterogeneous group of disorders with variable risk of progression to leukemic, blast phase disease. The leukemic transformation of MPN is associated with a very poor prognosis.
At the 62nd American Society of Hematology (ASH) Annual Meeting and Exposition, two studies investigated the genes and mutations influencing leukemic transformation in patients with MPN. Christian Marinaccio reported on the impact of loss of the serine threonine kinase 11 (STK11) gene on the progression of MPN in murine models,1 and the data has subsequently been published in Cancer Discovery.2 Clemence Marcault presented clinical data demonstrating a role for nuclear factor erythroid 2 (NFE2) mutations in leukemic transformation of MPN.3 Here we report the findings from these studies.
A CRISPR-Cas9 screen was performed to identify the genetic determinants of MPN progression using mice harboring the JAK2 V617F mutation with constitutive Cas9 expression in hematopoietic cells transduced with lentiviral CRISPR libraries containing short guide RNAs against various tumor suppressor genes. The screen showed short guide RNA enrichment for the STK11 gene, also known as liver kinase B1 (LKB1), in a serial replating assay.
Taken together, these results suggest that STK11 is a tumor suppressor in MPN, and loss of this gene is associated with progression to leukemic, blast phase disease. Hypoxia-inducible proteins could be potential therapeutic targets in blast phase MPN.
Although NFE2 mutations occur in only a small subset of patients with MPN, epigenetically induced overexpression of NFE2 is found in most patients, and mutation or overexpression of NFE2 in murine models is associated with an MPN phenotype.
To determine the clinical impact of NFE2 mutation, a total of 1,243 patients diagnosed with MPN at a single institution were followed between January 2011 and May 2020. Diagnostic and follow-up samples from 707 of these patients were analyzed by next-generation sequencing, targeting 36 myeloid genes.
Table 1. Median follow-up and response rates for NFE2-mutated vs non-mutated patients3
CHR, complete hematological response; CI, clinical improvement; CR, complete response; IQR, interquartile range; PD, progressive disease; PR, partial response; SD, stable disease. |
||||
|
All patients |
NFE2‑mutated patients |
NFE2‑non-mutated patients |
p value |
---|---|---|---|---|
Median follow-up, months (IQR) |
103.8 |
181.3 |
119.8 |
— |
Response, % |
||||
CR/CHR |
46.10 |
41.67 |
49.18 |
0.026 |
PR |
11.83 |
11.11 |
8.79 |
|
CI |
4.57 |
0 |
3.73 |
|
SD |
12.23 |
25.00 |
14.61 |
|
PD |
7.00 |
22.22 |
6.71 |
Table 2. Factors associated with leukemic transformation and OS in multivariate analysis3
AML, acute myeloid leukemia; CI, confidence interval; HMR, high-molecular risk; HR, hazard ratio; MDS, myelodysplastic syndrome; MPN, myeloproliferative neoplasms; NFE2, nuclear factor erythroid 2; OS, overall survival; PMF, primary myelofibrosis. |
|||
|
HR |
95% CI |
p value |
---|---|---|---|
Factors associated with AML/MDS transformation |
|||
Age at MPN diagnosis |
1.08 |
1.05–1.12 |
< 0.001 |
PMF subtype |
6.44 |
2.62–15.81 |
< 0.001 |
NFE2 mutation |
10.29 |
3.58–29.61 |
< 0.001 |
HMR mutations |
2.51 |
1.16–5.43 |
0.020 |
Factors associated with OS |
|||
Age at MPN diagnosis |
1.09 |
1.07–1.12 |
< 0.001 |
PMF subtype |
3.68 |
1.96–6.91 |
< 0.001 |
MDS/MPN subtype |
5.73 |
1.27–25.82 |
0.023 |
NFE2 mutation |
8.24 |
3.67–18.52 |
< 0.001 |
HMR mutations |
2.13 |
1.22–3.70 |
0.007 |
The presence of an NFE2 mutation is associated with a greater risk of leukemic transformation, and shorter OS in patients with MPN, presenting a rationale for routine assessment for NFE2 mutations during MPN diagnosis and follow-up.
These studies identified loss of STK11, a putative tumor suppressor, and mutated or overexpressed NFE2, a potential oncogene, as genetic factors that may both independently contribute to leukemic transformation in MPN. These findings support our increased knowledge of the genetic determinants of progression in MPN and may help to better predict blast phase transformation and identify patients at high risk who would benefit from early intervention.
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