Patients with triple-negative, JAK2V617F- and CALR-mutated essential thrombocythemia share a unique gene expression signature
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Patients with triple-negative, JAK2V617F- and CALR-mutated essential thrombocythemia share a unique gene expression signature Alimam, S., Villiers, W., Dillon, R., Simpson, M., Runglall, M., Smith, A., Chatzikyriakou, P., Lavender, P., Kanda, A., Mills, K., Bellosillo Paricio, B., Kaufman-Cook, J., Ord, S., Kordasti, S., Radia, D., Woodley, C., Francis, Y., Mufti, G., McLornan, D. P., & Harrison, C. N. (2021). Patients with triple-negative, JAK2V617F- and CALR- mutated essential thrombocythemia share a unique gene expression signature. Blood Advances, 5(4), 1059- 1068. https://doi.org/10.1182/bloodadvances.2020003172 Published in: Blood Advances Document Version: Publisher's PDF, also known as Version of record Queen's University Belfast - Research Portal: Link to publication record in Queen's University Belfast Research Portal Publisher rights © 2021 by The American Society of Hematology This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher. General rights Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the Research Portal that you believe breaches copyright or violates any law, please contact openaccess@qub.ac.uk. Download date:20. Dec. 2021
REGULAR ARTICLE
Patients with triple-negative, JAK2V617F- and CALR-mutated essential
thrombocythemia share a unique gene expression signature
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Samah Alimam,1,2,* William Villiers,2,* Richard Dillon,1,2 Michael Simpson,2 Manohursingh Runglall,3 Alexander Smith,4
Prodromos Chatzikyriakou,5 Paul Lavender,6 Anju Kanda,2 Ken Mills,7 Beatriz Bellosillo Paricio,8 James Kaufman-Cook,2 Sophie Ord,2
Shahram Kordasti,1,9 Deepti Radia,1 Claire Woodley,1 Yvonne Francis,1 Ghulam Mufti,4 Donal P. McLornan,1,† and Claire N. Harrison1,†
1
Department of Haematology, Guy’s and St. Thomas’ NHS Foundation Trust, London, United Kingdom; 2Department of Medical and Molecular Genetics, King’s College London, London,
United Kingdom; 3NIHR Comprehensive Biomedical Research Centre at Guy’s and St. Thomas’ NHS Foundation Trust in partnership with King’s College London and King’s College
Hospital, London, United Kingdom; 4Department of Haematology, King’s College NHS Trust, London, United Kingdom; 5Genetics and Molecular Medicine Research Division, King’s
College London, London, United Kingdom; 6School of Immunology & Microbial Sciences, MRC and Asthma UK Centre in Allergic Mechanisms of Asthma, King’s College London, London,
United Kingdom; 7Centre for Cancer Research and Cell Biology, Queen’s University, Belfast, United Kingdom; 8Laboratori de Diagnòstic Molecular, Servei de Patologia, Hospital del Mar,
Barcelona, Spain; and 9Systems Cancer Immunology, Comprehensive Cancer Centre, School of Cancer and Pharmaceutical Sciences, King’s College London, London, United Kingdom
Approximately 10% to 15% of patients with essential thrombocythemia (ET) lack the common
Key Points
driver mutations, so-called “triple-negative” (TN) disease. We undertook a systematic
• According to next- approach to investigate for somatic mutations and delineate gene expression signatures in
generation deep se- 46 TN patients and compared the results to those with known driver mutations and healthy
quencing, TN patients
volunteers. Deep, error-corrected, next-generation sequencing of peripheral blood
with ET may have “low-
mononuclear cells using the HaloPlexHS platform and whole-exome sequencing was
level” driver mutations
performed. Using this platform, 10 (22%) of 46 patients had detectable mutations (MPL, n 5
affecting JAK2 or MPL.
6; JAK2V617F, n 5 4) with 3 of 10 cases harboring germline MPL mutations. RNA-sequencing
• Gene expression analy- and DNA methylation analysis were also performed by using peripheral blood mononuclear
sis suggests that in ET,
cells. Pathway analysis comparing healthy volunteers and ET patients (regardless of
including “true” TN,
mutational status) identified significant enrichment for genes in the tumor necrosis factor,
transcriptional misregu-
NFkB, and MAPK pathways and upregulation of platelet proliferative drivers such as ITGA2B
lation occurs with
and ITGB3. Correlation with DNA methylation showed a consistent pattern of
resultant JAK-STAT
pathway activation. hypomethylation at upregulated gene promoters. Interrogation of these promoter regions
highlighted enrichment of transcriptional regulators, which were significantly upregulated
in patients with ET regardless of mutation status, including CEBPb and NFkB. For “true” TN
ET, patterns of gene expression and DNA methylation were similar to those in ET patients
with known driver mutations. These observations suggest that the resultant ET phenotype
may, at least in part and regardless of mutation type, be driven by transcriptional
misregulation and may propagate downstream via the MAPK, tumor necrosis factor, and
NFkB pathways with resultant JAK-STAT activation. These findings identify potential novel
mechanisms of disease initiation that require further evaluation.
Introduction
Classical Philadelphia-negative myeloproliferative neoplasms (MPNs) are multipotent, clonal hemato-
poietic stem cell neoplasms encompassing essential thrombocythemia (ET), polycythemia vera (PV), and
primary myelofibrosis. These disorders have an overlapping yet heterogeneous clinical spectrum, with
Submitted 11 August 2020; accepted 10 December 2020; published online 18 The data reported in this article have been deposited in the Gene Expression Omnibus
February 2021. DOI 10.1182/bloodadvances.2020003172. database (accession number GSE156547).
*S.A. and W.V. are joint first authors. The full-text version of this article contains a data supplement.
†D.P.M. and C.N.H. are joint senior authors. © 2021 by The American Society of Hematology
23 FEBRUARY 2021 x VOLUME 5, NUMBER 4 1059both ET and PV having the potential to transform to myelofibrosis.1,2 protocols. Details of the bioinformatics analysis pipeline are
Furthermore, MPNs predispose to an increased risk of thrombo- provided in the supplemental Methods. Briefly, genomic DNA
embolic events and have an inherent risk of transformation to acute libraries prepared by using SureSelectXT Human All Exon V4 were
myeloid leukemia (AML; 1% to 2% for ET/PV and up to 10% to sequenced on the Illumina HiSeq 2000 platform (Illumina) with
20% in primary myelofibrosis at 10 years).2,3 100 bp paired-end reads. Reads were aligned to the reference
human genome (hg19, b37) using NovoAlign (Novocraft Technol-
ET is specifically characterized by increased numbers of abnormal,
ogies). Alignments underwent quality control and filtering. In each
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clonal megakaryocytes and a clinical phenotype of thrombocy-
sample, .87% of the GENCODE-defined coding bases of the
tosis. Although rare cases of hereditary ET have been observed,
exome was represented by at least 20 reads. Pairwise variant calling
the majority of ET cases occur sporadically, most commonly
was performed by using SAM tools and filtered by using VarScan2.
associated with somatic mutations in either JAK2 exon 14, CALR
exon 9, or MPL exon 10, all of which lead to upregulated JAK-
STAT signaling.4 Mutations in JAK2, CALR, and MPL are usually Targeted next-generation sequencing
mutually exclusive, with an incidence of 55%, 25%, and 3%, Targeted deep sequencing of genes known to be mutated in
respectively.5 However, 10% to 15% of patients with ET do not myeloid malignancies was performed by using the HaloPlexHS
harbor detectable “driver” mutations, at least according to con- platform (Agilent Technologies) on peripheral blood PBMCs. The
ventional diagnostic assays, and are termed “triple negative” (TN). mean sequencing coverage was 95%, and 90% of target
Previous research using whole-exome sequencing (WES) has sequences could be analyzed with a coverage .90%. A list of
reported novel MPL and JAK2 mutations in TN MPN, highlighting the genes covered and details of the analysis pipeline are provided
disease heterogeneity.4 in supplemental Table 1.
Limited data exist concerning both extended gene expression
analyses and detailed methylation profiles of ET progenitor cells, Gene expression profiles
particularly regarding the TN ET population. Using genome-wide RNA-sequencing was performed on a selected subset of individuals
methylation arrays, Pérez et al6 evaluated the epigenetic landscape based on sample availability, which included 12 “true” TN patients,
of 71 patients with chronic MPN and 13 with transformed MPN 3 known JAK2V617F and 3 CALR mutated patients, and 4 HVs.
compared with healthy volunteers (HVs). Although a distinct MPN- RNA was extracted from PBMCs by using TRIzol reagent (Life
associated methylation signature was evident compared with HVs, Technologies). Libraries were prepared by using the Illumina
no differential pattern existed between the chronic disease TruSeq Stranded RNA kit following the manufacturer’s instructions
categories (primary myelofibrosis vs PV/ET). The differentially and sequenced by using an Illumina HiSeq 2500 instrument.
methylated regions appear enriched in a gene network centered Differentially expressed genes were identified by using limma.9 Full
on inflammation and the NFkB pathway. In a cohort of patients with details of the bioinformatics analysis are provided in the supple-
MPN, Rice et al7 described aberrations affecting components of mental Methods.
a noncanonical polycomb repressive complex 2 (EZH1, SUZ12,
and JARID2) and, interestingly, upregulation of the transcription Epigenetic signatures
factor (TF) NFIB, resulting in cellular protection from apoptosis.
Methylation profiles were performed in a selected cohort of enrolled
More recently, Wong et al8 reported significant pro-inflammatory
individuals based on sample availability: 21 TN patients (12 of 21
gene upregulation in an MPN cohort.
had gene expression performed as described earlier) and
We hypothesized that patients with ET have a unique gene 4 JAK2V617F mutated, 2 MPL mutated, and 3 CALR mutated
expression and methylation signature that may serve as a diagnostic (one JAK2V617F and 2 MPL patients were identified in retrospect
tool in those who lack classical driver mutations. We therefore from the WES data) patients. Genomic DNA extracted from
evaluated 46 TN ET patients, aiming to delineate if there are PBMCs was bisulfite converted by using the EZ DNA Methylation kit
differential epigenetic and gene expression profiles compared with (Zymo Research), as per the manufacturer’s protocol and
ET patients with known driver mutations. processed on an Infinium Human-Methylation 850K BeadChip
platform. Further details are provided in the supplemental Methods.
Methods
Patient samples Reverse-transcriptase quantitative polymerase
A total of 56 patients with ET, 2 patients with post-ET myelofibrosis chain reaction
as defined by the 2008 World Health Organization criteria, and 4 To investigate the abundance of the gene-specific transcript of 20
healthy HVs were enrolled into the study. Baseline mutation status candidate genes identified with altered expression, we prepared
to exclude the presence of JAK2V617F, CALR, or MPL mutations complementary DNA from total RNA in an additional 20 peripheral
was determined per local clinical laboratory protocols. Written blood samples of ET patients (9 JAK2V617F positive, 7 CALR
informed consent was obtained in accordance with the Declaration positive, and 4 TN) and 6 HVs10 (supplemental Table 2). Gene
of Helsinki and with approval from the local ethical review expression was assessed with reverse-transcriptase quantitative
committee. polymerase chain reaction (RT-qPCR) using gene-specific probes
for the following 20 candidate genes: CEBPb, ELK1, FAXDC2,
Whole-exome sequencing FOSL2, GP1BB, GTPBP1, ITGA2B, ITGA7, ITGB3, JUN, JUND,
Using peripheral blood mononuclear cells (PBMCs), WES libraries KLF1, MAPKAPK2, MARCKS, NFkB2, PFKFB3, RELA, SPI1,
were prepared using the SureSelectXT Human All Exon V4 (Agilent TAL1, and TGFB1 (supplemental Table 3). Assays were run in
Technologies) target enrichment system as per manufacturer’s triplicate on the ABI7900 platform (Applied Biosystems).
1060 ALIMAM et al 23 FEBRUARY 2021 x VOLUME 5, NUMBER 4Table 1. Clinical and hematologic parameters of patients enrolled in that were not detected by conventional testing. However, most
the study patients displaying a clinical ET phenotype still had no detectable
Parameter TN JAK2 CALR driver mutations via next-generation sequencing, and hence we
No. of patients
proceeded to investigate the gene expression profiles of these so-
called “true” TN patients.
ET 46 6 6
Post–ET MF 2 0 0 RNA-sequencing was performed on 12 true TN patients (ie, no
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Sex
driver mutations identified by next-generation sequencing), three
JAK2V617F-mutated patients, three CALR-mutated patients, and
Female 35 4 3
four HVs. First, the data were interrogated to identify if any gene
Male 11 2 3
expression differences existed between the TN cohort and patients
Platelet count at study entry (range), 310 /L
9
443 374 772 with known CALR and JAK2V617F mutations. Notably, gene
(236-1053) (308-457) (262-1709)
expression profiles correlated strongly with each other across all ET
Hemoglobin at study entry (range), g/L 131 133.5 132.5 patients regardless of mutational status (supplemental Figure 1A).
(99-161) (129-159) (118-162)
Moreover, direct comparisons between the 12 TN patients and 6
White blood cell count at study entry (range), 6.7 (2.7- 5.7 (3.5- 5.3 (3.6-
3109/L 14.5) 8.2) 10.2)
patients with known mutations yielded limited significant differences
(supplemental Figure 1B). In contrast, compared with that of HVs,
Drug treatment at study entry
the gene expression profiles of each ET subset showed consistent
No treatment 23 1 1 significant differences, regardless of disease subtype, platelet
HU 11 0 0 counts, treatment, and age (Figure 1A). Because there seemed to
IFN 8 5 4 be a set of unique genes in the TN comparison, we further analyzed
ANA 3 0 0
these genes; however, no significant differences in expression were
determined comparing TN samples vs the rest of the ET cohort.
HU and ANA 0 0 1
Moreover, these genes followed a similar expression pattern in the
HU, IFN, and ANA 1 0 0
JAK2V617F and CALR samples compared with the HV samples
ANA, anagrelide; CALR, calreticulin; HU, hydroxycarbamide; IFN, interferon; JAK2, (supplemental Figure 1C-D).
JAK2V617F; MF, myelofibrosis.
From our adjusted analysis comparing all ET patients vs HVs, a total
of 838 differentially expressed genes (DEGs; adjusted P ,.05)
(Figure 1B) were identified. Clearly, these genes define a gene set
Assays were performed as previously described11; ABL1 cycle
that could distinguish ET from HV in this cohort (Figure 1C). We
threshold values #30 were used for quality assessment. We
also recognized that the disease-modifying nature of interferon
quantified differences in the expression level (fold change) of the 20
treatment may affect gene expression patterns; however, sample
candidate genes between the ET cohort and HVs by using
clustering highlighted no anomalies (supplemental Figure 1A,H).
a comparative cycle threshold values platform (Applied Biosys-
We performed an additional differential analysis comparing patients
tems), and gene expression in the ET samples was compared with
with and without interferon and could not show any significant
HVs, with ABL1 as a reference gene. No-template and no-reverse-
differences in gene expression profiles (supplemental Figure 1I-J).
transcriptase controls were used to ensure specific amplification of
target transcripts. Ingenuity pathway analysis (IPA) of the 838 DEGs highlighted
upregulated genes were enriched for genes critical for myeloid cell
Results differentiation and proliferation, specifically activation of megakar-
The clinical and hematologic parameters and treatment regimens yopoiesis and oncogenic signatures (Figure 1D; supplemental
for the TN patients enrolled in this study are shown in Table 1. Figure 2A). The converse was also true (ie, enrichment for
thrombocytopenia among downregulated genes). Notable upregu-
Identification of somatic and germline mutations lated DEGs included ITGB3, ITGA2B, ITGA7, GP1BB, FAXDC2,
Targeted, error-corrected sequencing and WES identified somatic SPI1 (PU.1), TAL1, TGFB1, and CSF2RB; their mean expression
or germline mutations in 10 patients (Table 2). Six patients were levels are displayed in Figure 1E.
identified as having mutations in MPL: 4 patients with mutations in
To understand the potential molecular pathways that may be driving
exon 10 (W515R, W5151G/S, and S505N), 1 patient with
the expression of these proliferative genes critical for megakar-
a mutation in exon 11 (R537W), and 1 patient with a mutation in
yopoiesis, functional enrichment was performed using the KEGG
exon 9 (MPL P453R). Four patients had the JAK2V617F mutation.
database. This analysis revealed that upregulated DEGs were
Among the 6 patients identified as having an MPL mutation, this
enriched for several proliferative and inflammatory pathways,
was a germline mutation in 3 patients, including an MPL P435R
including JAK-STAT, tumor necrosis factor (TNF), NFkB, and
mutation in a female patient with post-ET myelofibrosis, and an MPL
MAPK pathways (P , .001) (supplemental Figure 2B-C). Re-
S505N mutation shared by a father and son pair. In the latter cases,
garding proliferative pathways, key downstream targets of these
the MPL S505N mutation was confirmed to be a germline mutation
pathways, including the TFs JUN, JUND, and CCAAT enhancer
as it was detected by WES in both PBMCs and skin.
binding protein b (CEBPb), were also upregulated.
Gene expression profiling These data suggest that regardless of disease subtype, ET
In total, 22% of clinically diagnosed TN ET patients in our cohort converges onto similar gene expression profiles, which potentially
harbored driver mutations detected by next-generation sequencing drive the disease phenotype. To test this theory in an independent
23 FEBRUARY 2021 x VOLUME 5, NUMBER 4 GENOMIC CHARACTERIZATION OF “TRIPLE-NEGATIVE” ET 1061Table 2. Mutation profile of TN patients identified as having somatic or germline mutations
Sex Age at diagnosis, y Gene VAF, % Treatment Platelet count, 3109/L
Male 45 MPL W515R 5 HC 457
Male 14 MPL R537W 2 Nil 521
Female 19 MPL P453R* 52 IFN 471
Male 26 MPL S505N* 52 Nil 1024
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Male 55 MPL S505N* 52 HC 466
Female 38 MPL Nil 1053
W5151G 10
and W515S 10
Female 45 JAK2V617F 2 HC 325
Female 52 JAK2V617F 4 Nil 437
Female 36 JAK2V617F 8 HC 310
Female 69 JAK2V617F 2 HC 416
HC, hydroxycarbamide; IFN, interferon; Nil, no treatment; VAF, variant allele frequency.
*Germline mutations.
cohort, we processed previously published gene expression array For each patient sample, we aggregated promoter- or gene
data (described in the supplemental Methods) from a mixed ET body–associated CpGs for each gene and explored regions that
cohort (n 5 20) with HVs (n 5 20).12 Directly comparing the ET had consistently hypomethylated/hypermethylated CpGs across all
samples vs the HV samples, we identified that 32 of the upregulated ET patient samples for that gene. We found that 9611 genes had
genes delineated in our analysis were also significantly upregulated hypomethylated promoters and 71 genes had hypermethylated
in this cohort. Among the overlapping genes were key inflammatory promoters; 33 genes had hypomethylated gene bodies and 159
genes: FAXDC2, ITGA2B, ITGA7, FOSL2, and ITGA2B (supple- genes had hypermethylated gene bodies (Figure 2A). As expected,
mental Figure 2D).13 correlation with gene expression profiling showed that genes with
hypermethylated promoters had significantly lower expression than
To gain further validation of the gene expression profile differences genes with either hypomethylated promotors or hypomethylated/
observed between the ET patients and HVs, RT-qPCR was hypermethylated gene bodies (Figure 2B; supplemental Figure 3D).
performed on an additional 20 independent patients with ET Interestingly, however, genes identified as having a consistent
(9 JAK2V617F positive, 7 CALR positive, and 4 TN) and six HVs hypomethylated/hypermethylated pattern at either their promoter of
(supplemental Table 1) on 20 candidate genes identified to have gene body had a significantly higher expression than genes without
altered expression. The cycle threshold values for the 20 candidate a clear hypomethylation/hypermethylation pattern. This was con-
genes (CEBPb, ELK1, FAXDC2, FOSL2, GP1BB, GTPBP1, sistent for all patient samples in the RNA-sequencing cohort.
ITGA2B, ITGA7, ITGB3, JUN, JUND, KLF1, MAPKAPK2, Although the exact significance of gene body methylation remains
MARCKS, NFkB2, PFKFB3, RELA, SPI1, TAL1, and TGFB1) unclear, gene body hypermethylation has been reported to be
are listed in supplemental Table 3. As shown in Figure 1F, all of the associated with increased gene expression.15,16
candidate genes had significantly higher expression in the patients
with ET compared with the HVs, irrespective of mutation subtype. We next questioned if there were any methylation changes
compared with HV PBMCs (n 5 2). We identified 652 CpGs with
Methylation profiling significantly different methylation (adjusted P # .01), of which 572
(80%) CpGs had increased methylation and 80 (20%) had
We next explored whether the epigenetic landscape at the level of
decreased methylation in the ET cohort (supplemental Figure 4A).
DNA methylation profiles differed among the patients with ET
There was no significant overlap between genes with differential
according to their mutation subtypes. The DNA methylation profiles
methylation and DEGs (x2 . 0.5), with only 15 overlapping genes.
of 25 TN ET patients, 4 JAK2V617F-mutated ET patients, and
This finding suggests that gene expression changes between ET
3 CALR-mutated ET patients were determined by using the human
and HV result primarily from DNA methylation–independent
methylation 850K array. Similar to their gene expression profiles, all
mechanisms.
ET samples, regardless of mutation subtype, shared highly
correlated methylation profiles, with a median Pearson correlation We subsequently investigated the promoter methylation patterns of
of 0.98 (supplemental Figure 3A). Methylation profiles did not DEGs. A significant difference was observed in the median
cluster on the basis of cytoreductive agent, age, sex, or white blood methylation between upregulated and downregulated gene pro-
cell composition (supplemental Figure 3B). On average, 43% of moters (Figure 2C). Interestingly, however, both upregulated and
cytosine guanine dinucleotides (CpGs) were hypermethylated and downregulated promoters were predominantly hypomethylated.
25% were hypomethylated. As expected, gene promoters were Overall, 58% of the DEGs had consistently hypomethylated
predominantly hypomethylated, whereas gene bodies showed promoters, and almost none were hypermethylated (Figure 2D).
a methylation distribution similar to that of total CpGs (supplemental Furthermore, the 58% of DEGs with hypomethylated promoters
Figure 3C).14 maintained enrichment for key genes involved in upregulated
1062 ALIMAM et al 23 FEBRUARY 2021 x VOLUME 5, NUMBER 4A B C
Key
TN
6000
Frequency
All ET vs Controls JAK2
4000 CALR
Decreased Expression Increased Expression
2000 Control
2 e-42
*X =1.3 0
4 -10 -5 0 5 10
*X =7.7
2 e-15 CALR ADJ 2
*X =6.5
e-56 310
Log2(CPM+0.5)
JAK2 TN 528
124 122
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-log10(adjusted p-value)
3
456 1 61
Decreased in ET
1603 129 3 114
2
211
150 14
161 48 1
96
Increased in ET
0
JAK2 = JAK2 (n = 3) vs Controls (n = 4)
CALR = CALR (n = 3) vs Controls (n = 4)
TN = TN (n = 12) vs Controls (n = 4) -5 0 5
ADJ = (CALR,JAK2,TN) vs Controls (n = 4)
Log2 fold change
D E
10
JUNB
ET
HV
15
Hyperplasia of lymphoid organ 8 THBS1 ITGA2B
Quantity of CD4+ T-lymphocytes Activated XRCC5
GRB2
RAC1
Osteopetrosis TIMP1
Log2(CPM +0.5)
TGFB1 FAXDC2 CEBPB
CEBPD
Enriched annotation
Thrombocytopenia CSF2RB TAL1 MAFB CDKN1A JUN
Hemorrhagic disease
6 APC
RXRA UBE2I SPI1
SIRPA
PRKCQ RBM47
LILRB3 MYLB
RARA
Differentiation of bone marrow cells SIGLEC10
10 Cancer
SRF GNA15
SSBP3 MAFG
PRMT1
Megakaryocytopoiesis RBBP5
4 HHEX
Myelopoiessis of hematopoietic progenitor cells CD40
Deactivated ID1
Differentiation of hematopoietic progenitor cells EMP1
RFRSF12A
C12orf29
Growth of connective tissue CCR6
5 Cell movement of neutrophils 2 CIAO3
ZNF616 FOSL1
Proliferation of connective tissue cells
Differentiation of hematopoietic cells
0
-4 -2 0 2 4
Gene expression rank in controls
Annotation Z-score
F ELK1 GTPBP1 ITGA2B MAPKAPK2 MARCKS GP1BB ITGA7 ITGB3 KLF1 SPI1
4.5 9 4 7 -2.5 9
1.0 5.0 2
4.0 8 6 -3.0 8
3 0 8
0.8
7 4.5
Mean -ΔCT
Mean -ΔCT
3.5 5 -3.5 7
0.6 6 2 6 -2
0.4 3.0 4 -4.0
5 4.0 -4 6
0.2 2.5 1 3
4 -4.5 4 -6 5
0.0 2.0 3.5 2
3 0 -5.0 -8 4
-0.2 1.5 2 1 2
3.0
12345 12345 12345 12345 12345 12345 12345 12345 12345 12345
NFKB2 PFKFB3 RELA FAXDC2 FOSL2 TAL1 TGFB1 CEBPB* JUN* JUND*
6 4
4.5 8.0 0
4.5 8 6.0
5 4 3 7.5
4.0 4 5.5
4.0 7 -1
Mean -ΔCT
Mean -ΔCT
3 2 7.0
4 3.5 5.0
3.5 6.5 6
2 3 -2 4.5
3 3.0 1
3.0 6.0 5 4.0
1 -3
2.5 2 2.5 2 0 5.5 4 3.5
0 5.0 3.0
2.0 1 2.0 -1 3 -4
12345 12345 12345 12345 12345 12345 12345 12345 12345 12345
12
10
HV
-log10(p-value)
AII ET 8
CALR 6
JAK2 4
TN
2
p-valueA B C D
1.0
15 ** = < 2.5e-5
*pvalue< 0.0006
*= 0.0002
0.8
G Hypo G Hyper ** **
Up Down
10 **
P Hypo 9 46 P Hyper P Hypo 151 201 P Hyper
Normalised b -value
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Log2(CPM+0.5)
22 0 0 159 0 1 0.6
9476 0 0 69 9126 0 0 70
5
0 0 0.4
113 2 326 0
0 0 0 0
0 0 0
0.2 Hypomethylation
-5
om 15 Hy per rom on
0.0
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Figure 2. Methylation profiling of genes with altered expression. (A) Venn diagram illustrating the overlap of genes with hypomethylated or hypermethylated promoters
and hypermethylated or hypomethylated gene bodies. (B) Boxplot showing the expression distributions of genes with different methylation patterns. From left to right, green
indicates all genes; light red, 9618 genes with hypomethylated promoters; light blue, 71 genes with hypermethylated promoters; dark red, 33 genes with hypomethylated gene
bodies; gray, 159 genes with hypermethylated gene bodies; and yellow, 133 genes with both hypomethylated promoters and hypomethylated gene bodies. *Indicates the
Student t test P value when comparing each set vs the set with hypermethylated promoters (light blue). (C) Venn diagram shows the overlap of genes with hypomethylated or
hypermethylated promoters and genes that were differentially expressed. (D) Boxplots of the b value distributions of all genes promoters (light blue), upregulated promoters
(green), and downregulated promoters (red). The hypomethylated (b $ 0.2) region is highlighted by red shading. *The Student t test P value, determining the significance of
the difference between up/downregulated promoter b values. Down, gene expression is downregulated in ET vs HVP; Up, gene expression is upregulated in ET vs HV; P
hyper, promoter hypermethylated; P hypo, promoter hypomethylated.
pathways uncovered in our RNA-sequencing analysis, including the pathways such as JUN, JUNB, FOSL2, RELA, and BCL6 were
TNF, MAPK, and platelet pathways. Overall, although promoter identified, all of which were upregulated in the ET cohort.
hypomethylation is consistently observed at upregulated DEGs, it Interestingly we also observed enrichment for RARA and its co-
does not appear that changes in DNA methylation alone can factor RXRA. Using this approach, several TFs were identified
account for these changes in gene expression. that could be driving the expression of genes leading to the ET
phenotype.
Transcriptional regulation by TFs
A fundamental aspect of gene regulation is by TFs and repressors. To understand if these gene promoters are active and accessible to
Thus, to explore the regulatory influence of TFs on the DEGs, the allow TF binding in an ET context, we interrogated publicly available
promoters of all upregulated DEGs were assessed for TF-binding RNA-sequencing and H3k27ac (acetylation) data in the SET-2 cell
motifs. There was a significant enrichment for many TFs involved in line.17,18 We first explored expression of the upregulated genes
myeloid cell development, including RARA, PU.1, and several KLF previously uncovered. Most upregulated genes have a high
genes (Figure 3A). Twenty-five of the enriched TFs were highly expression in the SET-2 cell line, with 63% in the upper expression
expressed in the ET cohort, with expression levels in the top quartile. quartile, which is significantly higher than average (Figure 3B). We
A significant enrichment for TFs key in the NFkB, MAPK, and TNF also found that 42% of gene promotors have significant H3K27ac
Figure 1. (continued) score; the higher the score, the greater the activation, with a negative score indicating deactivation. Circle size is based on the –log10 P value for the
enrichment of each annotated term. All terms have an enrichment P value ,3.4e-03. (E) Ranked plot of the gene expression values for all genes involved in activated terms
derived from IPA. The x-axis represents each gene. The y-axis is the mean log2(CPM 10.5) expression for each gene in the ET cohort (purple) and the HVs (gold). The plot
centers around the ranked expression of each gene in the HV (from highest to lowest expression). The size of each red point represents the –log10 adjusted P value for how
significantly differentially expressed the gene is in the ET cohort vs the HV cohort. The shaded background represents the gene expression quantiles (green 5 upper quantile
[Q3 1 Q4], yellow 5 mid/low quantile [Q2], red 5 lowest quantile [Q1]). (F) Boxplots illustrating the qPCR results, comparing the mean –delta cycle threshold (CT) vs
reference gene for the HV samples (gold), all ET samples (purple), CALR samples (pink), JAK2 samples (blue), and TN samples (red). The purple bar plot illustrates the
significance of the difference between the HV and the ET cohort as a whole as determined by a Student t test. The –log10 P value is used here; thus, the higher the bar, the
more significant the difference to HV. *Probes used for these 3 genes may detect genomic DNA.
1064 ALIMAM et al 23 FEBRUARY 2021 x VOLUME 5, NUMBER 4A B
10 Up Regulated vs Control
JUNB
Down Regulated vs Control SET2 Cell line analysis: RNA-seq
Expression in ET
FOSBACH1
FOXP1 Expression in Control 15
FOXO3
NFKB1
NFE2L2 JUN
FOSL2
NF1 RXRAKLF4SPI1NFE2BCL6
BACH2 RARA
RELA
e-09 e-08
5 * = 3.8 * = 1.1
Log2(CPM+0.5)
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MAFK EGR1
ZNF675
VDR
ZNF189 ZNF692 PPARA MYB
ZNF41
BATF
10
SPIB ATF3
RFX1
Log2 CPM in the SET2 cell line
ZNF341
GLIS3
0 HOXA9
5
NANOG
NR5A2
FOXA2 HNF4A
EBF2 FOXA1
PGR WT1ZIC2
ISL1FOXD3
-5
20 Gene Expression Rank in Controls 0
18
39
15 24
15 -5
35
-log10(qvalue)
10 74
35 27 37 61
sio e
en d
27 es
es en
G ate
3k n
n
es
ac
2 42 4 47 40 37
H Ge
pr G
ul
10 67 69
g
Ex T2
T2 ed
re
5
E
21 79 35 2 25 78 17 51 45 66
Up
t
lS
SE ula
3 22 72 44 52 90 11 16 48 88 85 11 96 75 38
ur
Al
ith g
w re
O
Up
ur
O
0
JUNB
FOXP1
FOS
BACH1
NFKB1
NF1
NFE2L2
FOXO3
BACH2
RXRA
KLF4
SPI1
NFE2
BCL6
FOSL2
ZNF41
ZNF189
ZNF675
ZNF692
RELA
RARA
BATF
JUN
PPARA
SPIB
MAFK
MYB
EGR1
VDR
RFX1
ZNF341
ATF3
GLIS3
HOXA9
PGR
NANOG
NR5A2
WT1
ZIC2
FOXA2
EBF2
HNF4A
ISL1
FOXD3
Enriched motifs in promoters
Figure 3. Motif landscape at differentially expressed genes. (A) Plot describes the top 45 motifs enriched at the 310 upregulated gene promoters. The bottom bar plot
illustrates the relative enrichment of each motif (–log10 q value), and the number on top of each bar is the percentage of promoters enriched with the motif. The top line plot
illustrates the expression of each of the 45 motifs in the HV samples (control) (gold) and the ET population (red). Green dots indicate genes that are significantly upregulated
vs HV, and pink dots indicate genes that are significantly downregulated vs HV (control). The highlighted color segments correspond to the expression quantiles (green 5
highest, yellow 5 medium, orange 5 low). (B) Boxplots illustrating the expression levels of genes in the SET-2 cell line. The gold box is the distribution of all SET-2 genes; the
pink box is the SET-2 expression levels of the 310 upregulated genes in the ET cohort; and the purple box is the SET-2 expression levels of upregulated genes with high
H3k27ac deposition at their promoters. *The Student t test P value when comparing each box vs the expression of all genes (gold box).
deposition, including ITGA2B, ITGB3, FOSL2, TAL1, JUND, and been previously detailed in ET. The germline mutation in S505N,
MAPK3 (supplemental Figure 5). Those genes with this active mark a point mutation that leads to the loss of the inhibitory effect on the
had a considerably higher expression overall. This suggests these TPO genes, was identified in 2 patients in the study cohort and is
promoters are highly active in this cell line and could be regulated well recognized in several kindreds.21 Four of 10 patients harbored
through the TF-binding sites we identified. the classic mutation JAK2V617F. No germline JAK2 mutations
were identified in our cohort.
Discussion It is important to note that the absence of mutations does not
In keeping with the literature, WES and targeted sequencing exclude alternative disease drivers, as it is well established that
facilitated the identification of canonical and noncanonical muta- WES cannot detect fusion oncogenes, mutations in regulatory
tions in MPL and JAK2 in 22% (10 of 46) of our TN cohort. This sequences, or alterations in gene expression. To further character-
included 2 of 10 patients harboring a somatic MPL mutation in exon ize the remaining true TN cohort, we used RNA-sequencing to
10 at positions W515R/G/S, all previously reported in patients with directly compare them with ET patients with known driver mutations
MPN.19 One patient had a mutation on exon 11 position R537W. and HVs. Significant correlations in gene expression were noted
The MPLR537W mutation is not widely described in ET; this regardless of mutation status, and consistent differences were
missense mutation in MPL located within the cytoplasmic domain found between the ET patients and HVs. Consistent with the well-
results in failure of JAK binding and signal transduction, and has established “inflammatory” phenotype associated with MPN, we
been associated with congenital amegakaryocytic thrombocytope- found upregulation of several pathways involved in hematopoiesis,
nia.20 We found MPL germline mutations in 3 patients: MPL P453R inflammation, and immune regulation, specifically NFkB, MAPK,
(n 5 1) and MPL S505N (n 5 2). The mutation on exon 9, position and TNF signaling, in parallel with upregulation of genes that drive
P453R is associated with the cytokine receptor domain and has not megakaryopoesis.22
23 FEBRUARY 2021 x VOLUME 5, NUMBER 4 GENOMIC CHARACTERIZATION OF “TRIPLE-NEGATIVE” ET 1065We identified 838 genes in ET patients that are consistently expression, and methylation profiles. We acknowledge that a
differentially expressed compared with HVs. Contrary to our potential weakness of our work is the absence of comparison
expectation, however, ET gene expression profiles correlated highly with reactive thrombocytosis patients; this topic could be assessed
with one another and did not cluster according to mutation in future studies. However, we are able to show that a proportion of
subtypes. Indeed, this was also observed at an epigenetic level in TN ET patients have low-level canonical and noncanonical
terms of DNA methylation profiles, with no clustering based on mutations in MPL and JAK2 genes. ET gene expression and DNA
mutation subtypes. This was validated further with RT-qPCR in an methylation profiles correlated highly with one another and did not
Downloaded from http://ashpublications.org/bloodadvances/article-pdf/5/4/1059/1800642/advancesadv2020003172.pdf by QUEEN'S UNIVERSITY MEDICAL LIBRARY user on 23 February 2021
independent ET cohort, which exhibited significant upregulation of cluster according to mutation subtypes. Thus, it is suggested that
20 key candidate genes in the ET population compared with HVs, different driver mutations activate similar molecular pathways that
irrespective of mutation subtype. Taken together, our systematic converge on a similar gene expression profile (that includes
genetic and epigenetic profiling indicates that different driver upregulation of genes implicated in platelet proliferation such as
mutations may activate similar molecular pathways that converge on ITGA2B and ITGB3), which ultimately results in the development of
a similar gene expression profile that ultimately results in the ET ET. We speculate that this gene expression profile may be
phenotype. regulated by JUN family TFs, downstream of NFkB, MAPK, and
TNF signaling. We hence provide an insight into the transcriptional
In our cohort, upregulation of genes associated with megakaryo-
poiesis, including ITGA2B and ITGB3, were identified. Such and epigenetic regulation of ET and identify putative underlying
upregulation of ITGA2B and ITGB3 is in keeping with previous molecular pathways that should be investigated further for the
findings by Müller et al,23 who also described altered expression in potential for therapeutic targeting.
an MPN population. The ITGA2B gene encodes the aIIb subunit Acknowledgments
(GPIIb) and is restricted to the megakaryocyte lineage, whereas the
ITGB3 gene encodes b3 (GPIIIa) and occurs in many cell types as The authors thank all the patients and HVs who participated in this
a component of the vitronectin receptor (avb3).24,25 Together, they study. The authors extend a special thanks to the Cangen group for
form the GPIIb/IIIa complex, which is a platelet–platelet contact their support throughout the project.
receptor for the clotting factors von Willebrand factor and
fibrinogen in activated platelets, and initiates aggregation.25,26
Authorship
The synthesis of GPIIb/IIIa occurs primarily in the megakaryocytes Contribution: S.A. designed the study, collected and processed
and is detectable at an early stage of maturation.27 samples, conducted experiments, analyzed data, and wrote the
manuscript; W.V. analyzed data and contributed to writing of the
As highlighted, upregulated DEGs displayed consistent promoter
manuscript; R.D. oversaw experimental design, processed samples,
hypomethylation. The DEG promoter sequences were enriched for
and contributed to the manuscript; M.S., A.S., P.L., and K.M. per-
TF-binding motifs, including that of JUN family members. We
formed data analysis; P.C. performed data analysis and contributed
identified that a large proportion of these gene promoters may be
to the manuscript; M.R., A.K., J.K.-C., S.O., and B.B.P. processed
highly active and accessible to the TFs in an ET cell line (SET-2).
samples; D.R. contributed patients to the study; C.W. and Y.F. per-
The activating protein-1 TF family is made up of multiple Jun
formed sample collection; S.K. contributed to the manuscript; G.M.
(cJun, JunB, and JunD) and FOS members. Activating protein-1,
supervised the project; D.P.M. and C.N.H. supervised the project and
as with NFkB, regulates many of the inflammatory and immune
contributed to writing the manuscript; and all authors read and ap-
pathways, functioning downstream of the MAPK pathway and
proved the submitted manuscript.
resulting in essential cellular processes that include proliferation
and differentiation.28 Conflict-of-interest disclosure: C.N.H. reports funded research
from Novartis; speaker fees from Novartis, Janssen, CTI, Celgene,
The JAK signal transducer, which has a central role in MPN
and Medscape; and advisory board membership for Incyte, CTI,
pathogenesis, is critical for signaling of multiple cytokines and, in
Sierra Oncology, Novartis, Celgene, Roche, AOP pharma, Geron,
addition to STAT, leads to MAPK pathway activation with resultant
and AstraZeneca. D.P.M. reports speaker fees and advisory board
dysregulation of cellular proliferation.29 Across this ET cohort, we
memberships with Novartis, Celgene, and Jazz Pharmaceuticals.
reported the upregulation of genes downstream of the MAPK
S.K. reports research grants from Celgene and Novartis; and
pathway that included MAP3K11, ELK1, NFkB, JUND, and JUN
speaker honorarium from Alexion. The remaining authors declare no
(supplemental Figure 2). We also observed an upregulation of
competing financial interests.
the FAXDC2 gene, which has been recently implicated as
a driver critical for megakaryopoiesis, acting through the ORCID profiles: S.A., 0000-0003-4784-7324; R.D., 0000-
activation of MAPK/extracellular signal-regulated kinase sig- 0001-9333-5296; P.C., 0000-0002-0048-4100; K.M., 0000-
naling. 30 Moreover, we identified upregulation of NFkB, in 0002-6362-4481; B.B.P., 0000-0002-5335-2726; S.K., 0000-
parallel with the subunit RELA, which is the primary driver for 0002-0347-4207.
inflammation and cell proliferation. 31 In many cells, NFkB Correspondence: Samah Alimam, Department of Haematology,
promotes a prosurvival state by enhancing the G1 phase to the 4th Floor, Southwark Wing, Guy’s and St. Thomas’ NHS Founda-
S phase cell cycle progression and upregulating antiapoptotic tion Trust, Great Maze Pond, London SE1 9RT, United Kingdom;
proteins such as BCL2 and BCL-xl; however, in platelets, their e-mail: samah.alimam@nhs.net; and Claire N. Harrison, Department
functional relevance remains unclear. 32-35 of Haematology, 4th Floor, Southwark Wing, Guy’s and St. Thomas’
To our knowledge, this study is the first to use a systematic NHS Foundation Trust, Great Maze Pond, London SE1 9RT, United
approach to TN ET patients in the evaluation of molecular, gene Kingdom; e-mail: claire.harrison@gstt.nhs.uk.
1066 ALIMAM et al 23 FEBRUARY 2021 x VOLUME 5, NUMBER 4References
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