CLINICAL NEWS
Researchers Identify Genetic Prognostic
Predictors in Myeloproliferative Neoplasms
A team of European and American researchers
have identified and characterized associations
between specific genetic mutations and prognosis
in patients with myeloproliferative neoplasms
(MPNs), findings that suggest a tailored predic-
tion model based on genomic associations
could predict outcomes and improve care in this
population.
Lead author Jacob Grinfield, MBChB, and
co-authors published their findings in the New
England Journal of Medicine. The development
of a genomics-guided prediction model could
overcome some of the challenges in identify-
ing patients who would benefit from targeted
therapies, the authors wrote. “A genomic clas-
sification has the virtue of identifying patients
with shared causative biologic factors, is stable
over time, and does not rely on blood-count
thresholds for assigning particular disease
labels.”
The investigators collected tumor DNA
samples derived from bone marrow mononu-
clear cells, blood granulocytes, or whole blood
from all participants.
classification, but, the
authors noted, “the biologic
factors underlying these
distinctions are incom-
pletely understood.” In this
analysis, the number of
driver mutations differed
according to MPN subtype.
Germline predisposi-
tions to MPN subtypes
also differed. For example,
patients with the JAK2
46/1 haplotype were more
likely to have polycythe-
mia vera (odds ratio [OR]
= 2.3; 95% CI, 1.7-3.3;
p=0.004).
The authors were able to define eight
genomic subgroups that showed distinct clini-
cal phenotypes, including blood counts, risk
of leukemic transformation, and event-free
survival. One of the most striking prognostic
factors was TP53 mutation status. Compared
with patients with TP53 wild-type disease,
“A genomic classification has the virtue
of identifying patients with shared
causative biologic factors [and] is
stable over time.”
—JACOB GRINFIELD, MBChB
The final analysis included 2,035 patients;
targeted sequencing for the full coding se-
quence of 69 genes and genome-wide copy-
number information was performed in 1,887
patients, while 148 patients underwent whole-
exome sequencing. Patients presented with the
following diagnoses:
• essential thrombocythemia (n=1,321)
• polycythemia vera (n=356)
• myelofibrosis (n=309)
• other diagnoses of MPNs (n=49)
Thirty-three genes had driver mutations in at
least five patients. Mutations in JAK2, CALR, or
MPL were the sole abnormality in 45 percent of
the patients. A total of 1,075 driver mutations
were identified across other genes. Age and ad-
vanced disease were associated with an increase
in the number of driver mutations.
MPNs are currently classified by clinical
and laboratory criteria such as those included
in the World Health Organization diagnostic
ASHClinicalNews.org
those with TP53 mutations were more likely to
transform to acute myeloid leukemia (AML;
hazard ratio [HR] = 15.5; 95% CI, 7.5-31.4;
p<0.001) and die early (HR=2.4; 95% CI 1.6-
3.6; p<0.001).
Patients with MPL-mutated myelofibrosis
were more likely than patients with JAK2-
heterozygosity to progress to AML (HR=8.6;
95% CI 1.4-49.1; p=0.02). Similarly, a subgroup
of patients with NFE2 mutations and patients
with polycythemia vera had higher likelihood of
myelofibrosis transformation (HR=3.0; 95% CI
1.3-6.6; p=0.007).
Patients with the following characteristics also
had higher risks of transformation to myelofi-
brosis (HR=5.4; 95% CI 2.7-11.0; p<0.001) and
shorter event-free survival (HR for disease pro-
gression or death = 2.6; 95% CI 2.1-3.2; p<0.001):
• ≥1 mutation in 16 myeloid cancer
genes (e.g., chromatin and spliceosome
regulators)
• loss of heterozygosity at chromosome 4q
• abnormalities in chromosomes 7 and 7q
“Our model accurately identified a minority of
patients with chronic-phase MPNs who were
at substantial risk for disease progression,”
the researchers wrote. “Such patients could be
considered for clinical trials of new therapeutic
agents, since they are the most likely to benefit
and the trials would be more efficient if higher-
risk patients are preferentially enrolled.”
A subgroup that included patients without
identified drivers “had particularly benign
outcomes,” the authors reported. “Only one
patient (0.5%) had myelofibrosis transforma-
tion and two (1%) had AML transformation
during a median follow-up of eight years.” For
these patients, “experimental therapy would
be unnecessary, and a conservative treatment
strategy that is based on cytoreduction and
reduction of vascular risk will suffice to give
long-term, event-free survival,” the investiga-
tors recommended.
According to the researchers, the observed
and predictive outcomes in this study were
associated with good correlation in an internal
cross-validation of a training cohort of 515 pa-
tients with MPNs, as well as in an independent
external cohort of 270 patients with MPNs.
“Comprehensive gene sequencing of patients
with blood cancers is becoming increasingly
accessible and routine,” the investigators con-
cluded, allowing for the integration of clinical
data with genomic-profiling data. “Regarding
patients with MPNs, such information will em-
power the clinician and support complex deci-
sions around the choice and intensity of therapy,
recruitment into clinical trials, and long-term
clinical outlook.”
The authors reported financial relationships
with the Wellcome Trust, Wellcome-MRC Stem
Cell Institute, National Institute for Health Re-
search Cambridge Biomedical Research Centre,
Cancer Research UK, Bloodwise, the Kay Kend-
all Leukemia Fund, the Leukemia & Lymphoma
Society, the European Hematology Association,
the Li Ka Shing Foundation, and the Medical
Research Council.
REFERENCE
Grinfeld J, Nangalia J, Baxter EJ, et al. Classification and Personalized Prognosis
in Myeloproliferative Neoplasms. N Engl J Med. 2018;379:1416-30.
ASH Clinical News
63