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Hypoxia Inducible Factor (HIF)-2α accelerates disease progression in mouse models of leukemia and lymphoma but is not a poor prognosis factor in human AML



Hypoxia-inducible factor (HIF)-1[alpha] accumulation promotes hematopoietic stem cells quiescence and is necessary to maintain their self-renewal. However the role of HIF-2[alpha] in hematopoietic cells is less clear. We investigated the role of HIF-2[alpha] in leukemia and lymphoma cells. HIF-2[alpha] expression was high in subsets of human and mouse leukemia and lymphoma cells whereas it was low in normal bone marrow leukocytes. To investigate the role of HIF-2[alpha], we transduced human HIF-2[alpha] cDNA in mouse syngeneic models of myeloid pre-leukemia and a transgenic model of B-lymphoma. Ectopic expression of HIF-2[alpha] accelerated leukemia cell proliferation in vitro. Mice transplanted with cells transduced with HIF-2[alpha] died significantly faster of leukemia or B-lymphoma than control mice transplanted with empty vector transduced cells. Conversely, HIF-2[alpha] knock-down in human myeloid leukemia HL60 cells decreased proliferation in vitro and significantly prolonged animal survival fol
Hypoxia Inducible Factor (HIF)-2α accelerates disease progression in mouse 1
models of leukemia and lymphoma but is not a poor prognosis factor in human 2
Running title: Role of HIF-2α in leukemia 5
CE Forristal1, AL Brown3,4, FM Helwani1, IG Winkler2, B Nowlan1, V Barbier2, J 7
Powell3, GA Engler3, SM Diakiw3, ACW Zannettino3,5,6, S Martin3,6, DJ Peet7, D 8
Pattabiraman2, RJ D’Andrea3,4, ID Lewis3,8, JP Levesque1,9
1Stem Cell Biology Group, and 2Cancer and Stem Cells Group, Mater Research 11
Institute – University of Queensland, Woolloongabba, Queensland, Australia; 12
3Division of Haematology, Centre for Cancer Biology, SA Pathology, Adelaide, 13
South Australia; 4School of Pharmacy and Medical Science, Division of Health 14
Sciences, University of South Australia, Adelaide, South Australia. 5Faculty of Health 15
Science, University of Adelaide, Adelaide, South Australia; 6School of Medical 16
Sciences, University of Adelaide, Adelaide, South Australia;7School of Molecular and 17
Biomedical Sciences, University of Adelaide, Adelaide, South Australia; 8South 18
Australian Health and Medical Research Institute, Royal Adelaide Hospital, Adelaide, 19
South Australia, 9School of Medicine, Herston, Queensland, Australia. 20
Address correspondence to: 22
A/Prof Jean-Pierre Levesque, PhD 24
Mater Research Institute – University of Queensland 25
TRI Building 26
37 Kent Street 27
Woolloongabba, QLD 4102 28
Australia 29
Tel: +61 7 3443 7571 31
Fax: +61 7 3463 2550 32
e-mail: 33
Hypoxia-inducible factor (HIF)-1α accumulation promotes hematopoietic stem cells 37
quiescence and is necessary to maintain their self-renewal. However the role of HIF-38
2α in hematopoietic cells is less clear. We investigated the role of HIF-2α in leukemia 39
and lymphoma cells. HIF-2α expression was high in subsets of human and mouse 40
leukemia and lymphoma cells whereas it was low in normal bone marrow leukocytes. 41
To investigate the role of HIF-2α, we transduced human HIF-2α cDNA in mouse 42
syngeneic models of myeloid pre-leukemia and a transgenic model of B-lymphoma. 43
Ectopic expression of HIF-2α accelerated leukemia cell proliferation in vitro. Mice 44
transplanted with cells transduced with HIF-2α died significantly faster of leukemia or 45
B-lymphoma than control mice transplanted with empty vector transduced cells. 46
Conversely, HIF-2α knock-down in human myeloid leukemia HL60 cells decreased 47
proliferation in vitro and significantly prolonged animal survival following 48
transplantation. In human acute myeloid leukemia (AML), HIF-2α mRNA was 49
significantly elevated in several subsets such as t(15;17), inv(16), complex karyotype 50
and favorable cytogenetic groups. However patients with high HIF-2α expression had 51
a trend to higher disease free survival in univariate analysis. The different effects of 52
HIF-2α overexpression in mouse models of leukemia and human AML illustrates the 53
complexity of this mutliclonal disease. 54
High intensity chemotherapies have similarly improved survival for pediatric acute 59
lymphoid leukemia (ALL) and patients with aggressive lymphomas. Despite these 60
improvements, a significant number of patients still relapse. Particularly in acute 61
myeloid leukemia (AML), more than half of young adult patients and about 90% of 62
older patients still relapse following chemotherapy treatment and die from their 63
disease1. The poor cure rates of AML are believed to be due to leukemia stem cells 64
(LSC), also called leukemia initiating cells, which are resistant to cytotoxic therapies2-
4. Therefore novel approaches to treat these treatment resistant hematological 66
malignancies are needed. 67
It is now clearly evident that the tumoral microenvironment plays an important 68
role in disease progression and response to treatments in both solid tumors5-8 and 69
hematological neoplasms2,9-12. It is well established that the center of solid tumors 70
become hypoxic due to the combined effects of enhanced oxygen consumption by 71
proliferating malignant cells, squeezing of the surrounding vasculature13,14, and poor 72
blood perfusion15. Several models of tumor formation in mice suggest that cancer 73
initiating cells (also called cancer stem cells), which are resistant to treatment and 74
responsible for tumor initiation and relapse, are particularly abundant in hypoxic 75
necrotic areas of tumors16,17. Furthermore, the hypoxia-sensing pathway, via hypoxia-76
inducible factors (HIFs), regulates many pathways driving tumor cell metabolic 77
adaptation to hypoxia, cell proliferation, chemotaxis and metastasis to distant sites18-
21, as most malignant cells switch their metabolism to favor glycolysis rather than 79
oxidative phosphorylation (the Warburg effect)22. 80
HIFs form a family of transcription factors composed of one of three oxygen-81
labile α subunits HIF-1α, HIF-2α and HIF-3α complexed with a constitutively 82
expressed oxygen-stable β subunit called aryl hydrocarbon receptor nuclear 83
translocator (ARNT). Once the HIF-α:ARNT complex is formed, it translocates to the 84
nucleus and activates the transcription of genes containing hypoxia responsive 85
elements (HRE)23,24. When O2 concentration is below 2% in the extracellular milieu, 86
HIF-α proteins are stable, the complex with ARNT is formed and translocates to the 87
nucleus to initiate transcription of HRE-containing genes. When O2 concentration 88
exceeds 2%-5% in the extracellular milieu, HIF-1α protein can be degraded within 5 89
minutes of formation by the proteasome25 via the combined effects of HIF prolyl 90
hydroxylase domain dioxygenases and the tumor suppressor VHL26,27, preventing the 91
formation of the transcription factor and its translocation to the nucleus. 92
We and others have recently demonstrated that in the normal adult bone 93
marrow (BM), quiescent hematopoietic stem cells (HSCs) are located in poorly 94
perfused areas of the BM28,29. Furthermore a large proportion of the BM extravascular 95
compartment is hypoxic with oxygen concentration below 2%30 and HIF-1α protein 96
accumulates in a proportion of HSC31,32. HIF-1α protein promotes HSC quiescence 97
and increases their self-renewal potential. Indeed conditional deletion of the Hif1a 98
gene causes HSC proliferation and reduces self-renewal potential in serial 99
transplantations31. Conversely, accumulation of the HIF-1 transcriptional complex 100
caused by culture of HSCs in hypoxic conditions33,34, by genetic stabilization 101
follwoing Vhl gene deletion31, or by pharmacological stabilization using prolyl 102
hydroxylase domain enzyme inhibitors35 increases HSC quiescence in vitro and in 103
vivo. 104
In contrast to HIF-1α, HIF-2α expression is more restricted. HIF-2α has been 105
reported to be mostly expressed by lineage negative (Lin-) cells in the adult mouse 106
BM, but was at much lower levels in Lin- Kit+ Sca1+ hematopoietic progenitor and 107
stem cells (HSPCs)31. Furthermore, HIF-2α is not required for the function of adult 108
HSCs in vivo36. HIF-2α is poorly expressed in resting human CD34+ cells in the BM 109
but induced following activation of STAT537. In this work, we show that while 110
normal adult mouse and human BM hematopoietic cells in steady-state have low 111
levels of HIF-2α, it is abundantly expressed by some hematological neoplastic cells 112
such as ALL and AML cells. Functional studies in mouse models of leukemia 113
revealed that HIF-2α expression enhances leukemia cell proliferation in hypoxic 114
conditions in vitro, with accelerated disease progression and reduced mouse survival 115
in vivo suggesting that HIF-2α may increase proliferation of malignant hematopoietic 116
cells by enabling them to overcome the quiescence normally imposed by HIF-1α 117
accumulation in the hypoxic malignant BM. Finally, we find that high HIF-2α 118
expression is associated with favorable subsets of human AML. 119
Cell Cultures 123
Mouse myeloid pre-leukemic cells FDCP1 were cultured in αMEM supplemented 124
with 10% FCS, 2mM L-Glutamine, 1mM sodium pyruvate, 50 i.u./mL penicillin-125
streptomycin and 10ng/mL recombinant mouse GM-CSF unless otherwise stated. For 126
GM-CSF titration, FDCP1 cells transduced with MXIE-HIF2α or empty MXIE vector 127
were seeded at 20,000 / mL in medium described above supplemented with 0–6.25 128
ng/mL purified recombinant mouse GM-CSF (PeproTech) for 48 hours. Live cells 129
were counted with the BioRad TC20 automated cell counter. 130
U937 and HL60 human leukemia cell lines were cultured in RPMI-1640 131
supplemented with 10% FCS, 2mM L-Glutamine, 1mM sodium pyruvate, 15mM 132
HEPES buffer and 50 i.u./mL penicillin-streptomycin. 133
Normoxic cultures were performed in air containing 5% CO2. Hypoxic cultures 134
were maintained in a sealed container containing an Anaerogen anaerobic pouch 135
(Oxoid, Basingstoke, UK) as previously described38. 136
Mouse cell sorting for RNA extraction 138
Bone marrow cell collection and staining for sorting leukocytes, HSPC, endothelial 139
cells, MSC and osteoblasts are described in supplementary methods. 140
Quantitative real-time PCR 142
RNA was reverse transcribed from 1µg of total RNA using iScript according to the 143
manufacturer’s instructions (Australian Biosearch, Australia). qRT-PCR with Taqman 144
probes (labeled 5’with 6-carboxyfluorescein (FAM) and 3’ with blackhole quencher-1 145
(BHQ-1)) for Hif1a, HIF-2α (Epas1), Epo and Oct4 (Pou5f1) were performed 146
following manufacturer’s instructions (ABI systems, Foster City, CA). β2-147
microglobulin was used as housekeeping gene. Oligonucleotide sequences are shown 148
in Supplementary Table 1. Primers were designed to cross intron-exon boundaries so 149
as not to amplify genomic DNA. RNA levels were standardized by parallel qRT-PCR 150
using primers to the house-keeping gene β2-microglobulin. A control PCR from each 151
sample prior to reverse transcription was performed to confirm absence of genomic 152
DNA detection. 153
Western-blotting 155
For quantification of HIF-1α and HIF-2α proteins by Western-blot, BM cells from 156
one femur or 4x106 cultured cells were flushed at harvest with 1mL of urea cell lysis 157
buffer; proteins were separated on an 8% SDS-polyacrylamide gel and following 158
electrotransfer blotted with 1/500 dilution of rabbit anti-mouse/human HIF-1α 159
polyclonal antibody (Novus Biologicals, NB100-132) or anti-mouse/human HIF-2α 160
polyclonal antibody (Novus Biologicals, NB100-122) and a 1/10,000 dilution of 161
IRD800-conjugated donkey F(ab)’2 fragment anti-rabbit IgG as previously 162
described35,39. Proteins were detected and quantified on the Odyssey Infra-Red 163
Imaging System (Li-COR Bioscience) and normalized according to β-actin as 164
previously described39-41. The specificity of the HIF-2α antibody was validated by 165
comparing western-blot of FDCP1 cells that do not express HIF-2α (undetectable by 166
qRT-PCR), to FDCP1 cells retrovirally transduced with human HIF-2α cDNA (Figure 167
3a). 168
Transduction of cell lines and HSCs 170
Retroviral transduction of FDCP1 cells and HSCs from vavBcl2 transgenic mice with 171
human HIF-2α, and lentiviral transduction of HL60 cells with shRNA knocking down 172
human HIF-2α are described in supplementary methods. 173
Transplantations of virally transduced cells 175
Transplantation of retrovirally transduced FDCP1 cell, HSCs from vavBcl2 transgenic 176
mice and knocked-down HL60 cells is described in supplementary methods. 177
Primary human AML samples and Fluidigm Biomark mRNA analysis 179
AML patient cohort 180
A panel of AML patient samples (n=118) was assembled using bone marrow 181
mononuclear cell (MNC) preparations taken at diagnosis with consent via the South 182
Australian Cancer Research Biobank (SACRB) with approval from relevant hospital 183
ethics committees in accordance with the Declaration of Helsinki (Table I). Normal 184
bone marrow samples were obtained using an approved collection process through the 185
Royal Adelaide Hospital. Research ethics approval for this project was obtained 186
through the Royal Adelaide Hospital human ethics committee. Seventy one patients 187
were treated using standard induction and consolidation chemotherapy protocols and 188
included in survival analysis. Briefly, patients under 60 years of age received 189
chemotherapy regimens with idarubicin and high-dose cytarabine, and patients over 190
60 received idarubicin and standard dose cytarabine. Consolidation therapy consisted 191
of high-dose cytarabine alone or standard dose cytarabine with idarubicin. Patients 192
with acute promyelocytic leukaemia were treated with All-trans retinoic acid and 193
were excluded from survival analyses. 194
Fluidigm Biomark mRNA analysis is described in supplementary methods 195
Mutation screening 197
Mutation screening in AML samples is described in supplementary methods 198
Statistical analyses 200
Statistical analyses on mouse models and on AML cohort are described in 201
supplementary methods 202
HIF-1α protein accumulates in leukemic BM 206
We first examined HIF-1α protein expression by western blot in BM cell lysates from 207
three different leukemia models: 1) human B-ALL patient derived xenografts into 208
NOD/SCID mice, 2) mice transplanted with syngeneic mouse HSCs transduced with a 209
retrovirus containing the human MLL-ENL fusion oncogene, and 3) mice transplanted 210
with the mouse myeloid pre-leukemic cell line FDCP1. To minimize potential 211
oxygen-dependent degradation of HIF-α proteins, BM were directly flushed with urea 212
lysis buffer. Consistent with our previous findings35,38, HIF-1α protein was very low 213
to undetectable in the BM of normal mice by western-blot (Figure 1a). However, at 214
the onset of leukemia, BM from all mice bearing human or mouse leukemia had high 215
HIF-1α protein levels, suggesting that the leukemic BM is highly hypoxic42,43 leading 216
to HIF-1α protein accumulation. 217
These findings represent a paradox as HIF-1α has been reported to promote 218
quiescence of normal HSPCs in vitro and in vivo31,33-35 and inhibit their proliferation, 219
possibly by blocking the transcriptional activity of c-myc as reported in renal clear 220
cell carcinoma44 and colorectal carcinoma cells45. In sharp contrast, HIF-2α has been 221
reported to promote the proliferation of human renal clear cell carcinoma44 and 222
embryonic stem cells46. Therefore we investigated whether HIF-2α is expressed in 223
hematological neoplasms. 224
HIF-2α mRNA is abundantly expressed by non-hematopoietic BM stromal cells 226
but only at low levels in hematopoietic cells 227
The mRNA levels of HIF-1α and HIF-2α from mouse central BM (cBM), endosteum, 228
sorted endosteal osteoblasts (OB), endothelial cells, MSC, and BM leukocytes 229
including Lin-KIT+Sca1+ (LKS) HSPCs, Lin-KIT+Sca1- (LKS-) lineage committed 230
HPCs, B220+ B cells, CD3+ T cells, CD11b+ myeloid cells and Gr1+ granulocyte 231
precursors were measured by qRT-PCR (Figure 1b,c). While HIF-1α was 232
constitutively expressed at various levels by all mouse BM cell populations 233
(hematopoietic or stromal), HIF-2α mRNA was preferentially expressed at the 234
endosteum by non-hematopoietic BM stromal cells. Of note, HIF-2α mRNA remained 235
very low in BM lineage-positive leukocytes, HSCs and HPCs in the adult mouse BM 236
in steady-state. Similarly HIF-2α mRNA was very low in normal adult human BM 237
CD34+ HSPCs and CD45+ CD34- leukocytes (Figure 1d). 238
These data were confirmed at the protein level. HIF-2α protein was not detected 239
by western-blot in mouse BM leukocytes or human BM CD45+ MNCs or CD34+ 240
HSPCs (Figure 1e). Of note, culture of normal human BM mononuclear cells or 241
CD34+ cells in hypoxic conditions for 24 hours did not induce HIF-2α expression at 242
the mRNA or protein levels (Figure 1d,e). 243
HIF-2α is expressed in subsets of malignant hematopoietic cells 245
In sharp contrast to normal BM leukocytes, HIF-2α mRNA and protein was 246
abundantly expressed in the BM of moribund NOD/SCID mice engrafted with three 247
distinct B-ALL patient-derived xenografts43,47 as well as in human myeloid leukemia 248
cell lines U937, HL60, THP1 and lymphoid leukemia cell lines ALL1, LK63 and 249
REH (Figure 1e). 250
We next performed an in silico analysis of HIF-2α mRNA expression in 251
hematological neoplasms using the In Silico Transcriptomics Gene Sapiens public 252
database ( Comparisons of hematological neoplasms with 253
normal BM myeloid cells and HSPCs revealed great heterogeneity of HIF-2α 254
expression in B-ALL, T-ALL, myeloma, B and T lymphomas and AML with some 255
samples reaching high values compared to BM HSCs and myeloid progenitors from 256
healthy volunteers (Supplementary Figure 1). Therefore, HIF-2α is highly expressed 257
in subsets of a wide variety of hematological malignancies. 258
These results prompted us to examine in more detail HIF-2α mRNA expression 259
in a local cohort of 118 AML samples taken at diagnosis at the Royal Adelaide 260
Hospital and in 18 BM samples from healthy volunteers (11 MNC and 7 CD34+ 261
purified samples). HIF-2α mRNA was quantified by Fluidigm analysis and 262
normalized relative to HPRT, RPLP0 and HMBS mRNA (Figure 2a). Sample 263
classification by cytogenetic abnormalities revealed that samples with complex 264
karyotypes, inv(16) and t(15;17) translocation had significantly elevated levels of 265
HIF-2α mRNA compared to BM MNC and CD34+ cells isolated from healthy 266
volunteers (Table 1, Figure 2a). Of note although the mean HIF-2α expression was 267
not significantly different between AML BM leukocytes and CD34+ cells and BM 268
MNCs from healthy volunteers, HIF-2α expression in some AML subsets, and in 269
particular the normal karyotype group, was very heterogeneous with some samples 270
reaching very high levels of HIF-2α mRNA, greater than 2-fold the standard deviation 271
above the average of normal controls (Figure 2b). There was no significant 272
association between HIF-2α expression and mutation status in FLT3, NPM1, 273
DNMT3A, IDH1/2 or N/K-RAS genes, with the exception of significantly decreased 274
HIF-2α expression in FLT3-TKD samples relative to FLT3-WT samples 275
(supplementary Figure 2a). There were significant differences between AML subsets 276
according to the FAB classification (ANOVA, p<10-4), with HIF-2α mRNA 277
significantly elevated in M3 and M6 AML compared to normal CD34+ cells (Figure 278
2c). M1 and M2 leukemias were very heterogeneous with some cases showing high 279
HIF-2α mRNA. Likewise, classification according to cytogenetic risk gave significant 280
differences (ANOVA, p=6x10-4) with significantly higher HIF-2α expression in 281
favorable cytogenetic groups compared to healthy MNC and CD34+ cells (Table 1, 282
Figure 2d). Both intermediate and adverse prognosis groups were not significantly 283
different from normal CD34+ cells albeit with a very high heterogeneity and some 284
case reaching high HIF-2α mRNA levels (Figure 2d). 285
To determine if stratifying AML patients by the level of HIF-2α gene 286
expression correlated with outcome in response to treatment we defined altered HIF2-287
α expression groups as any patients with expression above or below 2 standard 288
deviations of the mean in CD34+ cells from healthy individuals (indicated by the grey 289
shaded area in Figure 2a). This identified a large group of patients with high HIF2-α 290
expression (n=29, 25%), however only a small number of patients had low HIF2-α 291
expression (n=7, 5%) so this group was combined into a med-low group for analysis 292
purposes. Statistical analysis of the cohort stratified this way confirmed our previous 293
observation that high HIF-2α expression was associated with t(15;17), inv(16) and 294
favorable risk cytogenetic groups (Table 1). Interestingly we also observed that this 295
group was significantly associated with a lower peripheral white cell count (WCC) at 296
diagnosis (Table 1). To determine effects on outcome to treatment we then selected 297
patients who had received induction chemotherapy (n=71). Univariate analysis of 298
overall survival showed no difference between the two different HIF-2α expression 299
groups (Figure 2e), however patients with higher HIF-2α expression had a trend 300
towards improved disease free survival (Figure 2f, p=0.0672). As we had observed 301
other clinical associations of prognostic relevance with the high HIF-2α expression 302
group, we analyzed this further using multivariate cox-regression analysis with age, 303
WCC and good cytogenetic risk as co-variables. We observed that the effect on 304
disease free survival in the HIF-2α high expression group was not independent of 305
other variables (p=0.564) and only WCC was an independent predictor of disease free 306
survival in this cohort (p<0.0001, Table 2). 307
Ectopic expression of HIF-2α in FDCP1 myeloid pre-leukemia cell line enhances 309
progression to leukemia 310
To better understand the biology of HIF-2α in leukemia cells, we cloned the full-311
length human HIF-2α cDNA into the retroviral expression vector MXIE and 312
ectopically expressed human HIF-2α cDNA in the mouse pre-leukemic GM-CSF-313
dependent cell line FDCP1. FDCP1 cells were chosen as they are one of the few 314
hematopoietic cell lines that we tested that do not express HIF-2α (Figure 3a). 315
Following retroviral transduction, qRT-PCR and western-blotting (Figure 3a,b) 316
were used to confirm ectopic expression of HIF-2α. HIF-2α induction was also 317
confirmed by the up-regulation of erythropoietin (Epo) and oct4 (Pou5f1), two target 318
genes of HIF-2α (Figure 3b). The presence of HIF-2α in FDCP1 cells resulted in a 2-319
fold increase in proliferation, compared to empty MXIE vector controls, whether 320
cultured under hypoxic or normoxic conditions (Figure 3c). Furthermore, ectopic 321
expression of HIF-2α in FDCP1 cells reduced approximately 3 to 10-fold GM-CSF 322
concentrations required for survival and proliferation (Figure 3d). 323
We next transplanted FDCP1 cells transduced with MXIE-HIF2α or empty 324
MXIE vectors into non-irradiated syngeneic DBA/2 recipient mice (n=12 for each 325
group). Without irradiation of the recipients, transplanted FDCP1 cells progressed to 326
leukemia with a 20% penetrance and long latency (over 42 weeks) as previously 327
reported48. In sharp contrast, all recipients (100% penetrance) of HIF-2α transduced 328
FDCP1 cells succumbed to leukemia within 26 weeks with a median survival of 24 329
weeks (p=<0.0001 Log-rank) (Figure 3e). At sacrifice all mice had high leukemia 330
burden (>80% GFP+ cells) in blood, BM and spleens. Therefore HIF-2α expression 331
accelerated progression from a pre-leukemic state to leukemia, most likely by 332
supporting cell proliferation and reducing cytokine dependence. 333
Transduction of HIF-2α into HSC from vavBcl2 transgenic mice accelerates B 335
lymphoma development 336
We then tested the effect of ectopic HIF-2α expression in vavBcl2 transgenic mice, a 337
model of follicular lymphoma49. VavBcl2 transgenic mice overexpress Bcl2 in all 338
hematopoietic cells under the Vav gene promoter, thereby protecting them from 339
apoptosis. Consequently these mice exhibit a pan-leukocytosis with splenomegaly50,51 340
that evolves to follicular lymphomas after a long latency (> 1 year)49. BM cells were 341
isolated from young vavBcl2 transgenic mice (8-9 week old), well before they 342
developed lymphomas, and retrovirally transduced with MXIE-HIF2α or control 343
empty MXIE vectors. We achieved 40% transduction efficiency in both groups (40% 344
BM cells were GFP+ following 48 hours co-culture with packaging cells containing 345
MXIE-HIF2α or empty MXIE retroviral vectors). We then transplanted these 346
transduced BM cells into lethally irradiated wild-type syngeneic C57BL/6 recipients 347
(n=12 per group). 348
Tracking of GFP+ transduced blood leukocytes in live recipients 5 weeks post-349
transplantation, confirmed equivalent levels of retroviral transduction efficiency 350
between the 2 groups with equivalent proportion of GFP+ cells in B220+ B 351
lymphocytes (Figure 4a), myeloid and T cells (not shown). However from 17 weeks 352
onward, the proportion of transduced GFP+ cells in recipients of HIF-2α transduced 353
HSC was significantly above that of recipients of GFP+ HSCs transduced with empty 354
MXIE. In particular, the dominance of transduced GFP+ B cells in recipients of HSCs 355
transduced with HIF-2α was restricted to B220+ B cells (Figure 4b) and was not 356
observed in CD11b+ myeloid cells or CD3+ T lymphocytes (not shown). 357
Furthermore, recipients of HIF-2α transduced vavBcl2 HSC died of lymphoma 358
significantly more rapidly than recipients of vavBcl2 HSC transduced with control 359
MXIE vector (p=0.036 Log-rank) with median survival times of 41.0 and 56.0 weeks 360
respectively (hazard ratio = 2.971, 95% CI 1.068 to 8.26) (Figure 4c). Therefore in 361
both the myeloid pre-leukemia model (FDCP1) and a lymphoma model (vavBcl2 362
transgenic HSCs), ectopic expression of HIF-2α significantly accelerated malignancy 363
progression and reduced animal survival time. 364
HIF-2α knock-down in human myeloid leukemia HL60 prolongs survival of 366
transplanted mice 367
We next knocked-down HIF-2α expression in the human myeloid cell line HL60 with. 368
a lentiviral vector containing shRNA for human HIF-2α and previously validated in 369
multiple myeloma cells52. pFIV-H1-copGFP-HIF2α-scrambled vector was used as 370
control. HIF-2α knock-down was confirmed by Western blot of HL60 whole cell 371
lysates. Knock-down efficiency was 78% compared to scrambled vector control as 372
measured by quantitative western-blot following normalization to β-actin (Figure 373
5a,b). Knock-down of HIF-2α protein expression in HL60 cells halved the rate of 374
proliferation in culture in normoxia in comparison to empty vector and scrambled 375
vector controls (Figure 5c). 376
Knocked-down HL60 cells and controls were transplanted into ten NSG 377
immunodeficient recipient mice. We found that knock-down of HIF-2α in HL60 cells 378
significantly prolonged recipient mouse survival compared to recipients of scrambled 379
vector control lentivirally transduced cells (p=0.027 Log-rank, hazard ratio = 0.192, 380
95%, CI: 0.044 to 0.827) (Figure 5d). Therefore, knock-down of HIF-2α in human 381
myeloid leukemia cell line HL60 prolongs survival of recipient mice. 382
Our functional studies in which HIF-2α protein was ectopically expressed by 385
retroviral transduction demonstrated that HIF-2α expression a) increased myeloid pre-386
leukemia cell proliferation in both normoxic and hypoxic conditions in vitro, b) 387
accelerated disease progression and c) reduced disease latency and animal survival in 388
mouse models of myeloid pre-leukemia and B lymphoma. Conversely knock-down of 389
HIF-2α in the human myeloid leukemic cell line HL60, reduced cell proliferation in 390
vitro, delayed disease progression and prolonged animal survival in vivo. Our results 391
are consistent with previous observations that HIF-2α knock-down in primary human 392
AML cells reduces engraftment in immune-deficient mice41. Our findings are also 393
consistent with observations that HIF-2 transcriptional complex supports proliferation 394
in hypoxic conditions in embryonic stem cells46, renal clear cell carcinoma44,53, and 395
multiple myeloma52 cells. Therefore these congruent findings support the notion that 396
HIF-2 could provide a mechanism by which malignant hematopoietic cells can 397
surmount the HIF-1-mediated suppressive effect on proliferation of normal 398
hematopoietic cells35,44,45 in the hypoxic neoplastic BM. 399
HIF-2α is 60% homologous to HIF-1α. Both these proteins need to bind to 400
their common partner ARNT to translocate to the nucleus and activate the 401
transcription of genes containing HREs. Both these proteins are degraded by the 402
combined action of prolyl hydroxylases and pVHL, albeit with different kinetics 403
depending on the cell type. For instance, while HIF-2α protein was detectable in 404
leukemia cell lines cultured in normoxia (Figures 2 and 4), HIF-1α was not, 405
presumably because HIF-1α protein is more rapidly degraded in normoxia25. Despite 406
HIF-1α and HIF-2α sharing significant homology and a common β subunit, the HIF-1 407
and HIF-2 transcriptional complexes target a unique set of genes and/or regulate 408
overlapping target pathways in an opposing manner. In particular, HIF-1 reprograms 409
cell metabolism from oxidative phosphorylation to glycolysis by enhancing the 410
expression of glucose transporter Glut1, glycolysis enzymes such as lactate 411
dehydrogenase A and phosphoglycerate kinase21, and simultaneously turning off the 412
oxidative phosphorylation pathway21 and increasing mitochondria autophagy through 413
enhanced expression of Bnp321. In addition, HIF-1α blocks proliferation by blocking 414
c-myc44,45 and β-catenin/TCF54 transcription factors and enhancing expression of 415
cyclin kinase inhibitors such as p21Cip1 45. In contrast HIF-2, which has limited effects 416
on metabolic switching to glycolysis53, uniquely increases a) c-myc44 and β-417
catenin/TCF54 transcriptional activities, b) expression of cyclin D1 and cyclin D255, c) 418
expression of transcriptional regulators Oct-4 (Pou5f1)56 and Cited257 which both 419
necessary to maintain stem cells in an undifferentiated state, and d) tyrosine kinase 420
expression and activity such EGF and IGF-1 receptors57 leading to enhanced ERK1/2 421
and Akt activation57. Furthermore, HIF-2 has been recently reported to protect AML 422
cells from apoptosis induced by endoplasmic reticulum stress41. Therefore, in the 423
context of a hypoxic environment, HIF-2 has the potential to further enhance 424
proliferation whereas HIF-1 adjusts cell metabolism to quiescence. 425
Previous studies on the role of HIF-2α in AML did not include statistical 426
analyses on HIF-2α expression in patients and potential effects on disease survival41. 427
We now report that HIF-2α is highly expressed in subsets of B-ALL cells and AML 428
BM samples. In the particular case of AML, HIF-2α mRNA was significantly 429
overexpressed in M3 and M6 AML, or AML with t(15;17), inv(16) or complex 430
karyotypes. The fact that HIF-2α mRNA was elevated in M3 acute promyelocytic 431
leukemia is consistent with our finding that HIF-2α was elevated in the good 432
prognosis group and in the t(15;17) translocation group (generating the PML-RARα 433
fusion oncogene) which is consistent with a recent report showing that PML-RARα 434
induces HIF-2α expression58. Interestingly knockdown of HIF-2α in HL-60 cells (a 435
model of promyelocytic phenotype leukemia - APL) increased survival of xenografted 436
mice (Figure 5d), indicating that induction of HIF-2α could be functionally 437
contributing to growth in this subtype of leukemia. This finding is supported by 438
Coltella et al who also saw increased survival in mice xenografted with HIF-2α 439
knockdown NB4 cells58 (an independent model of APL). 440
We could not find a clear link between HIF-2α expression and mutations in 441
FLT3, NPM1, DNMT3A, IDH1/2 and RAS genes, with the exception of decreased 442
HIF-2α expression in AML with FLT3-TKD mutations (Supplementary Figure 2A). 443
However, it is clear that there is a group of NK patients with high HIF-2α expression 444
(Figure 2b) suggesting that the role of HIF-2 in AML is not restricted to the M3 445
subtype. We also found that high HIF-2α expression was associated with low WCC at 446
diagnosis, a predictor of good survival within AML patients. These results 447
collectively show that HIF-2α mRNA is significantly more highly expressed in AML 448
samples associated with favorable prognosis. Accordingly, high HIF-2α gene 449
expression was associated with a trend to higher and longer disease-free survival but 450
this was not found to be an independent predictor and is most likely due to its 451
association with good outcome cytogenetics such as inv(16) (note that M3 subtype 452
AML was excluded from this survival analysis). It is possible that HIF-2 453
accumulation is contributing to the disease phenotype in these cases by generating a 454
leukemia with fewer quiescent LSC capable of surviving chemotherapy and 455
contributing to relapse. This is supported by our observation of increased proliferative 456
capacity of leukemic cells transduced with HIF-2α and will be important to 457
investigate further in the normal karyotype group with larger patient cohorts. 458
While PML-RARα has recently been reported to up-regulate HIF-2α 459
transcription58, the mechanisms by which HIF-2α mRNA is up-regulated in normal 460
and complex karyotype AML is unknown. Up-regulation of HIF-2α, may in part, be 461
mediated by activated STAT537, however the levels of STAT5 phosphorylation are 462
difficult to reliably assess in cryopreserved AML samples as cellular phosphatase 463
could rapidly dephosphorylate STAT5 upon cell thawing. Therefore, understanding 464
the mechanisms by which different driving mutations in AML up-regulate HIF-2α 465
expression will remain challenging as each mutation / cytogenetic alteration would 466
have to be tested separately for potential effects (direct or indirect) on HIF-2α 467
transcription. 468
In conclusion, our in vivo data in leukemia cell lines transplanted into mice 469
(mouse FDCP1 and human HL60), and spontaneous mouse lymphoma arising from 470
overexpression of a Bcl2 transgene, support the notion that HIF-2 accelerates 471
leukemia and lymphoma progression. In contrast, HIF-2α expression in human AML 472
is associated with favorable prognosis and lower WCC at diagnosis. This apparent 473
contrast between mouse models of leukemia and AML in patients may be in part 474
explained by the complexity of human AML. Indeed, AML is a multiclonal disease in 475
which founding clones can contain up to 7 driving mutations and progressively 476
generate additional clones by accumulating mutations59-61. Adding to the complexity 477
of AML, the different clones contained within individual AML patients have different 478
kinetics, potential and sensitivity to chemotherapy treatments59,62, and acquire 479
additional driving mutations in response to treatment which generates new 480
chemoresistant clones59. Therefore this constantly evolving mosaic of AML clones in 481
AML patients, driven by multiple mutations, may obscure the effect of HIF-2α 482
overexpression. In contrast to the complex heterogeneity of AML clones in patients 483
caused by accumulation of random mutations in HSPCs over the years of human 484
lifespan, mouse models of leukaemia and xenotransplants of human AML cell lines 485
progress rapidly, and are thus likely to be clonally less heterogeneous than primary 486
AML in humans. This may account for the more consistent effect of HIF-2α 487
overexpression or knock-down in mouse models of leukemia. These results further 488
underline the difficulty of predicting in mouse models disease progression and 489
response to treatment of very heterogeneous, multiclonal and complex human 490
malignancies such as AML. 491
The authors have no conflict of interest to declare. 495
The authors have no conflict of interest to declare. This work was supported by 498
Project Grant # 604303 from the National Health and Medical Research Council of 499
Australia (to JPL and IGW) and additional support from the Mater Foundation. JPL 500
and IGW are supported by a Senior Research Fellowship #1044091 and a Career 501
Development Fellowship (#1033736) and FMH was supported by an Australian 502
Based Biomedical Fellowship (#488821) from the National Health and Medical 503
Research Council. 504
CEF, FMH, AB, JP, BN, VB, SM and DP performed the experiments. CEF, FMH, 507
IGW, AB, JP, ACWZ, RDA, IL and JPL designed and planned the experiments, 508
analyzed and discussed the results. DJP provided essential reagents. RDA edited the 509
manuscript; CEF, AB and JPL wrote the manuscript. 510
Supplementary information is available at Leukemia's website. 513
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Figure legends 760
Figure 1. Leukemic BM is hypoxic and HIF-2α is expressed in hematological 762
neoplastic cells but not in normal hematopoietic cells. (a) HIF-1α protein expression 763
in normal and leukemic mouse BM as detected by western-blot with a rabbit anti-764
mouse/human HIF-1α. Each lane is the BM extract of a different mouse. (b) HIF-1α 765
and (c) HIF-2α mRNA expression in sorted mouse BM populations. Data are mean ± 766
SD from 3-6 independent mice sorted separately. (d) HIF-2α mRNA expression in 767
human BM, CD45+, CD34+ human BM cells and BM of moribund NOD/SCID mice 768
engrafted with three distinct B-ALL patient-derived xenografts. Data from normal 769
human BM leukocytes are from each individual donor whereas data from human ALL 770
xenografts are mean±SD of three separate mice for each individual ALL sample. (e) 771
Western-blots with a rabbit anti-HIF-2α on total cell extracts from human BM 772
leukocytes, BM from NOD/SCID mice engrafted with human B-ALL, and cultured 773
human leukemia cell lines. Abbreviations below the blots indicate whether samples 774
are directly from the BM (BM), or were cultured overnight in normoxia (N) or 775
hypoxia (H). 776
Figure 2. HIF-2α mRNA expression is significantly elevated in subsets of AML. (a) 778
HIF-2α mRNA was quantified in 118 AML samples and MNC and CD34+ cells from 779
11 and 7 healthy volunteers respectively. Dotted lines and grey shading indicate 2SD 780
either side of the mean of HIF-2α expression from CD34+ cells. Patients were further 781
classified according to (b) cytogenetic abnormalities, (c) FAB classification and (d) 782
cytogenetic risk. Green symbols represents values from healthy donors, red groups are 783
those which are significantly different from healthy donor BM CD34+ cells. P values 784
are indicated above significantly different subsets. Kaplan Meier plots showing € 785
overall survival and (f) disease free survival of patients with high HIF-2α expression 786
vs med-low. 787
Figure 3. Ectopic expression of HIF-2α accelerates development of myeloid leukemia 789
in mice. (a) HIF-2α protein expression in FDCP1 mouse pre-leukemic cell line 790
transduced with empty MXIE or MXIE- HIF-2α vectors. (b) mRNA expression of 791
HIF-2α, EPO and Oct4 in FDCP1 cells following retroviral transduction with MXIE 792
empty vector or MXIE-HIF2α vector. qRT-PCR data are relative to β2-microglobulin 793
mRNA and represent average ± SD of 3 separate experiments. (c) Cell counts 794
following retroviral transduction with MXIE empty vector or MXIE-HIF2α vector. 795
Cells were seeded at 2x104 / ml in T25 culture flasks and counted after 24 hours in 796
culture in normoxia or hypoxia in the presence of 10ng/mL rmuGM-CSF. Data are 797
means±SD from 4 independent experiments. (d) Live cell counts following GM-CSF 798
titration of FDCP1 cells with MXIE empty vector or MXIE-HIF2α vector. Cells were 799
seeded at 4x104 / ml in 96 well microplates and counted after 3 days in culture in 800
normoxia or hypoxia. Data are from one representative experiment in triplicate out of 801
2 independent experiments. (e) Survival curve following transplantation of transduced 802
FDCP1 cells into 10 syngeneic DBA/2 mice for each group of FDCP1 cells. 803
Figure 4. HIF-2α accelerates development of Bcl2-driven B lymphoma in mice. (a-b) 805
Percentage of GFP+ transduced B cells in wild-type recipients of vavBcl2 transgenic 806
HSCs retrovirally transduced with empty MXIE or MXIE-HIF2α vectors. Each dot 807
represents the result from an individual mouse at 5 weeks and 32 weeks post-808
transplantation respectively. Bars represent the average of each group. (c) Survival 809
curve of wild type mice transplanted with vavBcl2 BM transduced with MXIE empty 810
vector or MXIE-HIF2α vector (12 recipient mice per group). 811
Figure 5. Knock-down of HIF-2α slows leukemia progression in mice transplanted 813
with human myeloid leukemia cell line HL60. Western-blot (a) and quantification (b) 814
of HIF-2α protein in HL60 cells lentivirally transduced with HIF-2α shRNA or 815
scrambled control. Transduced HL60 cells were cultured in normoxia and total 816
protein extract blotted with a rabbit anti-HIF-2α or rabbit anti-β-actin for 817
normalization. Quantification was performed using an infra-red laser detection system 818
(c) Cell counts of HL60 cells lentivirally transduced with HIF-2α shRNA or 819
scrambled control. Cells were seeded at 1.5x105 cells/ml and cultured in normoxia for 820
the indicated times. Data are mean ± SD from 6 separate experiments performed at 821
different times. (d) Survival curve following transplantation of HL60 cells lentivirally 822
transduced with HIF-2α knock-down or scrambled control vector into ten NSG mice. 823
per group. 824
1Standard induction chemotherapy excluding ATRA treatment for APML. 825
2Cytogenetic risk was defined according to Grimwade D, et al. (Blood. 2010; 826
116(3):354-65) 3If a patient displayed more than one cytogenetic abnormality it was 827
included in multiple groups. 4Wilcoxon rank-sum test; 5Fisher's exact test (Fisher's 828
exact test was performed for individual FAB subtypes, cytogenetic abnormalities, and 829
molecular abnormalities); 6Chi-square test. 830
Table I. Distribution of clinical characteristics and genetic lesions according to HIF-
HIF2A expression groups
All cases
HIF2A high
HIF2A med-
low (n=89)
Age, median yrs (range)
66 (18-89)
66 (23-87)
67 (18-89)
Female, No. (%)
54 (46)
10 (35)
44 (44)
Male, No. (%)
64 (54)
19 (65)
45 (46)
WCC x 109/L, median (range)
13.8 (0.36-250)
6.64 (0.36-103)
16.55 (1.12-250)
Blast %, median (range)
63 (13-100)
69 (21-100)
62 (13-100)
De novo AML, No. (%)
101 (88)
24 (83)
77 (90)
Secondary AML, No. (%)
14 (12)
5 (17)
9 (10)
Chemotherapy, No. (%)1
78/110 (71)
15/24 (63)
63/86 (72)
No chemotherapy, No. (%)
33/110 (30)
9/24 (37)
24/86 (28)
Transplant yes, No. (%)
24 (20)
3 (10)
21 (24)
Transplant no, No. (%)
93 (79)
26 (90)
67 (76)
FAB, No. (%)
2 (2)
0 (0)
2 (2)
32 (27)
7 (24)
25 (28)
47 (40)
10 (35)
37 (42)
4 (3)
3 (10)
1 (1)
20 (17)
7 (24)
13 (15)
10 (8)
1 (3)
9 (11)
2 (2)
1 (3)
1 (1)
0 (0)
0 (0)
0 (0)
1 (1)
0 (0)
1 (1)
Cytogenetic risk, No. (%)2,5
< 0.00016
10 (8)
8 (28)
2 (2)
83 (70)
13 (44)
70 (79)
25 (22)
8 (28)
17 (19)
Cytogenetics, No. (%)3,5
Normal karyotype
52 (44)
9 (31)
43 (48)
4 (3)
3 (10)
1 (1)
2 (2)
1 (3)
1 (1)
4 (3)
4 (14)
0 (0)
MLL (11q23)
5 (4)
0 (0)
5 (6)
Trisomy 8
10 (8)
4 (14)
6 (7)
4 (3)
0 (0)
4 (5)
7 (6)
2 (7)
5 (6)
14 (12)
5 (17)
9 (10)
Other abnormality
21 (18)
3 (10)
18 (21)
Mutations, No. (%) 5
22/108 (20)
5/27 (19)
17/81 (21)
7/92 (8)
0/23 (0)
7/69 (10)
23/99 (23)
4/22 (18)
19/77 (25)
10/99 (10)
2/24 (8)
8/75 (11)
22/93 (24)
6/21 (29)
16/72 (22)
10/95 (11)
3/22 (14)
7/73 (10)
Table II. Statistical analysis of overall survival and disease free survival according to
expression levels in AML
Patients in
Total n=71
(% at 5 yrs)
(HR (95% CI), p-value)
14 vs 57
389 vs 384
28 vs 22
0.781 (0.322-1.894), p=0.584
36 vs 35
MNR vs 281
51 vs 8
0.322 (0.151-0.687), p=0.003
54 vs 17
499 vs 196
32 vs 0
< 0.0001
0.252 (0.117-0.538), p< 0.0001
4 vs 67
MNR vs 354
75 vs 20
0.194 (0.023-1.614), p=0.129
14 vs 57
1444 vs 268
38 vs 9
0.763 (0.304-1.913), p=0.564
36 vs 35
499 vs 250
22 vs 9
0.594 (0.313-1.127), p=0.111
54 vs 17
358 vs 159
18 vs 10
< 0.0001
0.195 (0.087-0.435), p< 0.0001
4 vs 67
MNR vs 286
100 vs 8
0.00 (0.00), p= 0.974
For each analysis prognostic variables were assessed individually (median survival
and survival proportion calculated using Kaplan-Meier analysis; univariate analysis
calculated using a Mantel-Cox test) and concurrently (multivariate analysis
calculated using a Cox-regression model). Variables include high vs med-low HIF-
2αmed-low HIF-2sis prognostic variables were assessed individually60 yrs vs
young), WCC at diagnosis (high ≥50x109/L vs low) and cytogenetic risk (favourable
vs all others) HR = hazard ratio, CI = confidence interval, MNR = median not
reached. 1Cytogenetic risk was defined according to Grimwade D, et al. (Blood.
2010; 116(3):354-65)
Mouse cell sorting for RNA extraction
Bone marrow cell collection and staining for sorting leukocytes, HSPC, endothelial cells, MSC and
osteoblasts are described in supplementary methods. Following euthanasia, femurs were collected and
flushed into ice-cold PBS + 2% newborn calf serum (NCS) for cBM cells for RNA preparation. The
empty femurs were then flushed twice more in PBS then with 1mL Trizol (Invitrogen, Carlsbad, CA)
for endosteal RNA preparation as previously described1. RNA was also extracted from the following
FACS sorted BM hematopoietic cell populations: HSPC (LKS), myeloid progenitors (LKS-),
neutrophils (Gr1+F4/80-CD11b+), B-cells (B220+CD11b-) and T-cells (CD3+CD11b-). For stromal and
endothelial cells, partially crushed bones were incubated with type I collagenase (3 mg/mL from
Clostridium histolyticum, Worthington, Lakewood, NJ) for 40 min at 37°C then released cells
depleted for hematopoietic lineage-positive cells (using biotinylated lineage antibodies CD3, CD5,
B220, Ter119, CD11b, Gr1 with SAV-MACS beads and MACS depletion method) before staining
with SAV-FITC, CD45-APCCy7, CD31-APC, CD51-PE and anti-Sca-1-PECY7. The following cell
populations were sorted from viable (7AADneg) cells: BM endothelial cells (CD45-Lin-CD31+), MSC
(CD45-Lin-CD31-CD51+Sca-1+) and osteoblastic cells (CD45-Lin-CD31-CD51+Sca-1-) and RNA
extracted in Trizol.
Viral transduction of cell lines and HSCs
To generate transduced FDCP1 cell lines, full length cDNA encoding wild-type human HIF-2α was
subcloned by PCR from a plasmid vector2 into MND-X-IRES-eGFP (MXIE) bi-cistronic retroviral
vector3, 4 to generate MXIE-HIF2α vector expressing gene of interest together with green fluorescent
protein (GFP). Empty MXIE vector expressing GFP only was used as control. Retroviral particles
were generated after stable transfection and selection of the packaging cell line GP+E86 as previously
described4. FDCP1 cells were co-cultured for 24 hours at a concentration of 100,000/mL on a 30%
confluent layer of 25Gy irradiated GP+E86 cells stably transfected with MXIE-HIF2α or empty
MXIE. Transduced FDCP1 cells were selected by flow cytometry activated cell sorting gating on the
10% brightest green fluorescent protein (GFP)+ cells.
To generate HIF-2α over-expressing HSCs, mice were treated with a single dose of 150mg/kg
5-fluorouracil by retro-orbital injection 5 days prior to harvest. Following treatment, mice were
euthanized by cervical dislocation and BM extracted from femurs, hips, tibias and spine were
harvested in PBS with 10% FCS. BM cells were infected by overnight co-culture at 106/mL on 25Gy
irradiated transfected GP+E86 packaging cells as previously described4.
To generate stable knock-down HL60 cell line, RNA duplexes targeting human HIF- (5’-
GGGGGCTGTGTCTGAGAAGAGT-3’) or a scrambled control (5’-
CCAAGGAGTAAGAGATAAAGGTC-3’) were cloned into the pFIV-H1-copGFP lentiviral vector
(System Biosciences, CA, USA) as previously described5. Transduced cell lines derived from HL60
cells were generated by 2 successive sorts of the brightest 10% of GFP-expressing cells at a 2 week
interval using a FCS Aria cell sorter (BD Biosciences).
Transplantations of virally transduced cells
All experiments were approved by the animal experimentation ethics committee of the University of
Queensland. C57BL/6 mice, DBA/2 and NOD/SCID IL2Rγ-/- (NSG) mice were purchased from the
Australian Resource Centre, Perth Australia. VavBcl2 transgenic mice in C57BL/6 background were
originally donated by Prof. J Adams (WEHI, Melbourne)6. These mice were produced and maintained
by breeding with wild-type C56BL/6 females and pups genotyped by using the PCR primers forward:
AAAACCTCCCACACCTCCCCCTGAA. 106 retrovirally transduced FDCP1 cells were transplanted
into non-irradiated DBA/2 female mice. In other experiments, 5x106 retrovirally transduced BM cells
from 5-fluorouracil treated vavBCl2 transgenic mice were transplanted retro-orbitally into C57BL/6
females after prior irradiation (two 5.5Gy doses at 4 hours apart prior to transplantation) as previously
described4. In other experiments, 2x106 lentivirally transduced HL60 cells were transplanted into NSG
female mice. Following transplantation, mouse health was scored weekly. At the emergence of first
clinical signs of disease, 50µL of blood was drawn from the tail viin at weekly intervals to measure
tumor burden by flow cytometry based on GFP fluorescence.
Transplantation of human B-ALL patient derived xenografts
Three B-ALL patient-derived xenografts ALL#3, ALL#7 and ALL#19 were generously provided by
Dr Richard Lock (Children’s Cancer Institute Australia for Medical Research, Randwick, Australia).
These 3 B-ALL patient-derived xenografts have been exclusively maintained and passaged in vivo in
NOD/SCID mouse recipients and have preserved many of the characteristics of the original patient
leukemia cells such as sensitivity or resistance to particular drugs7. B-ALL cells were transplanted
exactly as described7. When mice exhibited clinical signs of disease, they were euthanized by cervical
dislocation, femurs harvested and flushed with cell urea cell lysis buffer for western-blot, or with PBS
for RNA extraction and qRT-PCR.
Fluidigm gene expression analysis
RNA was extracted from donor and patient material using a routine phenol/chloroform method
(Trizol, Invitrogen). Purified total RNA was converted to cDNA using the QIAGEN Quantitect
Reverse Transcription Kit, and then all of the targeted genes were pre-amplified in a single 14-cycle
PCR reaction for each sample by combining 1.25ul cDNA with the pooled primers and TaqMan Pre-
Amp Mastermix (Fluidigm BioMark™) following conditions outlined in the manufacturer’s protocol.
Finally, quantitative PCR was performed for each primer pair on each sample on a 96.96 Integrated
Fluidics Circuit (IFC) using the EvaGreen detection assay on a Biomark HD system following
standard Fluidigm protocols. Primers were purchased from Sigma-Aldrich (see Supplementary table 2
for primer sequences).
Data were analyzed using Fluidigm Real-Time PCR Analysis v4.0.1 (Fluidigm), and graphed using
Prism v5.04 (GraphPad Software). The HIF- expression for each sample was normalized to the
geometric mean of the expressions of the three housekeeping genes (HMBS, RPLP0, HPRT1).
Samples with cycle thresholds greater than 28 were excluded from the analysis.
Mutation screening
To assess co-occurrence with other common mutations in AML we used a PCR-based fragment
analysis for FLT3-ITD screening and a multiplexed matrix-assisted laser desorption/ionization time-
of- flight genotyping approach (Sequenom MassARRAY Compact System, Sequenom, Inc., San
Diego, CA, USA) for detection of the following mutations: KIT (D816V), DNMT3A (R882C/H),
FLT3 (TKD: D835H/Y//V/E, I836DEL, I836INS), IDH1 (R132C/H/P), IDH2 (R140W/ L/G,
R172W/G/K/M), JAK1 (T478S, V623A), JAK2 (V617F), KRAS (G12D/V/A, G13D/A) and WT1 as
Statistical analyses
For cell cultures or mice, differences between treatment groups were analyzed using a two-tailed t-test
or non-parametric Mann-Whitney depending on distribution normality. Data are presented as mean ±
standard deviation. Survival curve comparisons were performed using the log-rank test. All
calculations were performed using GraphPad Prism 5 software (GraphPad Sofwares, La Jolla, CA). P
values below 0.05 were considered significant.
Differences between the clinical characteristics of AML patient groups were analysed using
the Wilcoxon rank-sum test for continuous variables and the Fisher's exact test or Chi-square test for
categorical variables as indicated. The definition of diagnosis followed recommended criteria9. For
survival analysis eligible patients received standard induction chemotherapy as described above and
survived to first bone marrow biopsy post-treatment (28 days). Overall survival was measured from
date of diagnosis to date of death (failure), last date of contact (censored), or date of transplant
(censored) and all patients were censored at 5 years. Disease free survival was measured from the date
of diagnosis to date of relapse before transplant, date of death from AML, date of transplant
(censored), date of death from unrelated causes (censored), or last date of contact (censored). All
remaining patients were censored at 5 years. Median survival and percentage survival at 5 years were
estimated using the Kaplan-Meier method, and differences between survival distributions were
assessed using univariate and multivariate Cox regression analysis. All statistical analyses were
performed using IBM SPSS Statistics 19.
1 Winkler IG, Sims NA, Pettit AR, Barbier V, Nowlan B, Helwani F, et al. Bone marrow
macrophages maintain hematopoietic stem cell (HSC) niches and their depletion mobilizes
HSCs. Blood 2010; 116: 4815-4828.
2 Bracken CP, Fedele AO, Linke S, Balrak W, Lisy K, Whitelaw ML, et al. Cell-specific
regulation of hypoxia-inducible factor (HIF)-1alpha and HIF-2alpha stabilization and
transactivation in a graded oxygen environment. The Journal of biological chemistry 2006;
281: 22575-22585.
3 Robbins PB, Yu XJ, Skelton DM, Pepper KA, Wasserman RM, Zhu L, et al. Increased
probability of expression from modified retroviral vectors in embryonal stem cells and
embryonal carcinoma cells. Journal of virology 1997; 71: 9466-9474.
4 Shen Y, Winkler IG, Barbier V, Sims NA, Hendy J, Lévesque J-P. Tissue inhibitor of
metalloproteinase-3 (TIMP-3) regulates hematopoiesis and bone formation in vivo. PLoS
ONE 2010; 5: e13086.
5 Martin SK, Diamond P, Williams SA, To LB, Peet DJ, Fujii N, et al. Hypoxia-inducible
factor-2 is a novel regulator of aberrant CXCL12 expression in multiple myeloma plasma
cells. Haematologica 2010; 95: 776-784.
6 Ogilvy S, Metcalf D, Print CG, Bath ML, Harris AW, Adams JM. Constitutive Bcl-2
expression throughout the hematopoietic compartment affects multiple lineages and enhances
progenitor cell survival. Proc Natl Acad Sci U S A 1999; 96: 14943-14948.
7 Liem NLM, Papa RA, Milross CG, Schmid MA, Tajbakhsh M, Choi S, et al. Characterization
of childhood acute lymphoblastic leukemia xenograft models for the preclinical evaluation of
new therapies. Blood 2004; 103: 3905-3914.
8 Diakiw SM, Perugini M, Kok CH, Engler GA, Cummings N, To LB, et al. Methylation of
KLF5 contributes to reduced expression in acute myeloid leukaemia and is associated with
poor overall survival. Br J Haematol 2013; 161: 884-888.
9 Cheson BD, Bennett JM, Kopecky KJ, Buchner T, Willman CL, Estey EH, et al. Revised
recommendations of the International Working Group for Diagnosis, Standardization of
Response Criteria, Treatment Outcomes, and Reporting Standards for Therapeutic Trials in
Acute Myeloid Leukemia. J Clin Oncol 2003; 21: 4642-4649.
Supplementary Table 1: qRT-PCR primer sequences
Mouse Hif1a
Mouse HIF-2α (Epas1)
Human HIF-2α
Mouse Epo
Mouse Oct4 (Pou5f1)
Mouse β2m (B2m)
Mouse β-actin (Actb)
MyelomaPlasma cell
B cell
Supplementary figure 1. In silico analysis of HIF-2αmRNA expression in hematological neoplasms.
Data were retrieved from the In Silico Transcriptomics Gene Sapiens public database and show HIF-2α
mRNA (EPAS1) expression as measured by qRT-PCR on primary samples from 925 B-ALL, 68 T-
ALL, 101 B-CLL, 322 AML, 6 plasma cell leukemia, 102 myeloma, 198 B cell lymphoma, 36
Burkitt’s lymphoma and 43 T cell lymphoma patients. In green are results from 10 healthy BM
myeloid cell and 39 BM HSC donors (
Supplementary Figure 2. HIF-2αmRNA expression by mutation type in AML. HIF-2αmRNA was
quantified in 118 AML samples and MNC and CD34+cells from 11 and 7 healthy volunteers
respectively. Expression in groups was compared by classifying patients according to mutation
status of FLT3 (a), NPM1 (b), DNMT3A (c), N/K-RAS (d) or IDH1/2 (e). P values are indicated
above significantly different subsets (t-test).
... NB4 ( Contr. Globally, elevated levels of HIF-1α have been reported in AML [152][153][154][155], APL [150], Acute Lymphoblastic Leukemia (ALL) [153,156], and Chronic Myelogenous Leukemia (CML) [157,158]. Furthermore, HIF-1α overexpression conditions disease severity and outcome in both AML and Myelodysplastic Syndrome (MDS) [153,[159][160][161]. ...
... NB4 ( Contr. Globally, elevated levels of HIF-1α have been reported in AML [152][153][154][155], APL [150], Acute Lymphoblastic Leukemia (ALL) [153,156], and Chronic Myelogenous Leukemia (CML) [157,158]. Furthermore, HIF-1α overexpression conditions disease severity and outcome in both AML and Myelodysplastic Syndrome (MDS) [153,[159][160][161]. ...
... Globally, elevated levels of HIF-1α have been reported in AML [152][153][154][155], APL [150], Acute Lymphoblastic Leukemia (ALL) [153,156], and Chronic Myelogenous Leukemia (CML) [157,158]. Furthermore, HIF-1α overexpression conditions disease severity and outcome in both AML and Myelodysplastic Syndrome (MDS) [153,[159][160][161]. ...
... Very limited studies are available on the function of HIF1 factors in ALL. So far, it has been shown that HIF-1α is expressed in ALL that reside in the BM [48]. Accordingly, HIF-1α is induced by stroma-mediated AKT/mTOR signaling in pre-B-ALL, and confers resistance to chemotherapy [49]. ...
... An analysis of HIF-1α and YY1 expression levels in ALL was performed using a public data set of microarrays retrieved from the Oncomine and Gene Expression Omnibus databases, derived from a published analysis reported by Andersson, A. et al. [48]. ...
Full-text available
Yin-Yang transcription factor 1 (YY1) is involved in tumor progression, metastasis and has been shown to be elevated in different cancers, including leukemia. The regulatory mechanism underlying YY1 expression in leukemia is still not understood. Bioinformatics analysis reveal three Hypoxia-inducible factor 1-alpha (HIF-1α) putative binding sites in the YY1 promoter region. The regulation of YY1 by HIF-1α in leukemia was analyzed. Mutation of the putative YY1 binding sites in a reporter system containing the HIF-1α promoter region and CHIP analysis confirmed that these sites are important for YY1 regulation. Leukemia cell lines showed that both proteins HIF-1α and YY1 are co-expressed under hypoxia. In addition, the expression of mRNA of YY1 was increased after 3 h of hypoxia conditions and affect several target genes expression. In contrast, chemical inhibition of HIF-1α induces downregulation of YY1 and sensitizes cells to chemotherapeutic drugs. The clinical implications of HIF-1α in the regulation of YY1 were investigated by evaluation of expression of HIF-1α and YY1 in 108 peripheral blood samples and by RT-PCR in 46 bone marrow samples of patients with pediatric acute lymphoblastic leukemia (ALL). We found that the expression of HIF-1α positively correlates with YY1 expression in those patients. This is consistent with bioinformatic analyses of several databases. Our findings demonstrate for the first time that YY1 can be transcriptionally regulated by HIF-1α, and a correlation between HIF-1α expression and YY1 was found in ALL clinical samples. Hence, HIF-1α and YY1 may be possible therapeutic target and/or biomarkers of ALL.
... In patients with T-cell acute lymphoblastic leukemia (T-ALL), HIF-1α is overexpressed, and HIF-1α can promote the activation of Notch1 signaling, increase the expression of cyclin D1, CDK2, p21, MMP2, and MMP9 proteins, thereby leading to cell proliferation, invasion, and resistance [86,87]. Few data are available on the role of HIF-1α in acute B-lymphoblastic leukemia, but it has been demonstrated that HIF-1α expression is induced by leukemic B cells in the bone marrow [88]. ...
Full-text available
Hypoxia-inducible factor-1α (HIF-1α) is widely distributed in human cells, and it can form different signaling pathways with various upstream and downstream proteins, mediate hypoxia signals, regulate cells to produce a series of compensatory responses to hypoxia, and play an important role in the physiological and pathological processes of the body, so it is a focus of biomedical research. In recent years, various types of HIF-1α inhibitors have been designed and synthesized and are expected to become a new class of drugs for the treatment of diseases such as tumors, leukemia, diabetes, and ischemic diseases. This article mainly reviews the structure and functional regulation of HIF-1α, the modes of action of HIF-1α inhibitors, and the application of HIF-1α inhibitors during the treatment of diseases.
... Another regulator of hypoxia, HIF-2, also plays an important role in the survival of primary AML cells. HIF-2-deficiency displays decreased engraftment ability of human AML cells and accelerates AML progression [65,66]. Hypoxia-activated prodrugs designed to be activated in the hypoxic LSC niche are expected to be promising; however, they are not yet successful [67]. ...
The history of human acute myeloid leukemia stem cells (AMLSCs) began in a seminal study performed by Lapidot and Dick, proving that only CD34+CD38- human primary acute myeloid leukemia (AML) cells can repopulate in severe combined immunodeficient mice. The concept of leukemic stem cells (LSCs) has impeded a huge change in the treatment strategy against AML from killing proliferating leukemic cells to eradicating quiescent/dormant LSCs. As next-generation sequencing technologies have developed, multiple and recurrent genetic mutations have been discovered in large cohorts of patients with AML, and the updated understanding of leukemogenesis has improved the old concept of LSC to a revised version of a serial developmental model of LSC; that is, pre-LSCs are generated as seeds by the first hit on epigenetic regulators, and then, leukemia-initiating LSCs emerge from seeds by the second hits on genes involved in transcription and signaling. Dreams for universal and targetable AMLSC biomarker sparing healthy hematopoietic stem cells have weakened after the confrontation of significant heterogeneity of AMLSCs from genomic and immunophenotypic viewpoints. However, there is still hope for effective targets for AMLSCs since there is evidence that grouped gene signatures, such as 17-gene LSC score, and common epigenetic signatures, such as HOXA clusters, independent of various gene mutations, exist. Recently, the LSC niche in the bone marrow has been actively investigated and has expanded our knowledge of the physiology and vulnerability of AMLSCs. Presently, an applicable treatment that always works in AMLSCs is lacking. However, we will find a way, we always have.
... In hematologic malignancies, overexpression of HIF-1α has been reported in acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL) and chronic myeloid leukemia (CML). HIF-2α overexpression has been demonstrated in both AML and ALL (Deeb et al., 2011;Frolova et al., 2012;Zhang et al., 2012;Forristal et al., 2015). Furthermore, roxadustat has been reported to increase the incidence of lung cancer in male mice and breast cancer in female mice compared with that in the control group (Beck et al., 2017). ...
Full-text available
Hypoxia-inducible factor-prolyl hydroxylase inhibitors (HIF-PHIs) emerge as promising agents to treat anemia in chronic kidney disease (CKD) but the major concern is their correlated risk of cancer development and progression. The Wilms’ tumor gene, WT1 , is transcriptionally regulated by HIF and is known to play a crucial role in tumorigenesis and invasiveness of certain types of cancers. From the mechanism of action of HIF–PHIs, to cancer hypoxia and the biological significance of WT1, this review will discuss the link between HIF, WT1, anemia correction, and cancer. We aimed to reveal the research gaps and offer a focused strategy to monitor the development and progression of specific types of cancer when using HIF–PHIs to treat anemia in CKD patients. In addition, to facilitate the long-term use of HIF–PHIs in anemic CKD patients, we will discuss the strategy of WT1 inhibition to reduce the development and progression of cancer.
... In myeloid leukemias, HIF-2 activity is fundamental: (i) it promotes survival of primary AML cells; (ii) down-regulation of HIF-2 decreases engraftment of human AML cells; (iii) and HIF-2 ectopic expression protects AML cells from stress induced apoptosis (He et al. 2013;Forristal et al. 2015). Interestingly in the case CML, HIF-1 was sufficient to maintain LSC activity in a mouse model of this disease even upon inhibition of BCR-ABL with TKI treatment (Ng et al. 2014). ...
The human body requires a constant delivery of fresh blood cells that are needed to maintain body homeostasis. Hematopoiesis is the process that drives the formation of new blood cells from a single stem cell. This is a complex, orchestrated and tightly regulated process that occurs within the bone marrow. When such process is faulty or deregulated, leukemia arises, develops and thrives by subverting normal hematopoiesis and availing the supplies of this rich milieu.In this book chapter we will describe and characterize the bone marrow microenvironment and its key importance for leukemia expansion. The several components of the bone marrow niche, their interaction with the leukemic cells and the cellular pathways activated within the malignant cells will be emphasized. Finally, novel therapeutic strategies to target this sibling interaction will also be discussed.
... HIF-2 alpha protects hematopoietic progenitors as well as AML cells from apoptosis due to endoplasmic reticulum stress [26]. Moreover, it promotes AML progression in mouse models, but HIF-2 alpha is not established as prognostic marker in AML [27]. Further studies demonstrated an accelerated growth of CD318transfected MCF-7 cells in mice compared with mocktransfected controls [28]. ...
Full-text available
Genetic and morphological markers are well-established prognostic factors in acute myeloid leukemia (AML). However, further reliable markers are urgently needed to improve risk stratification in AML. CD318 (CDCP1) is a transmembrane protein which in solid tumors promotes formation of metastasis and correlates with poor survival. Despite its broad expression on hematological precursor cells, its prognostic significance in hematological malignancies so far remains unclear. Here, we evaluated the role of CD318 as novel prognostic marker in AML by immunophenotyping of leukemic blasts. Flow cytometric evaluation of CD318 on leukemic cells in 70 AML patients revealed a substantial expression in 40/70 (57%) of all cases. CD318 surface levels were significantly correlated with overall survival in patients receiving anthracycline-based induction therapy or best available alternative therapy. Using receiver-operating characteristics, we established a cut-off value to define CD318lo and CD318hi expression in both cohorts. Notably, high CD318 expression correlated inversely as prognostic marker in both treatment cohorts: as poor prognostic marker in patients receiving intense therapy, whereas upon palliative care it correlated with better outcome. In conclusion, FACS-based determination of CD318 expression may serve as novel prognostic factor depending on implemented therapy in AML patients.
... [55] In addition, ectopic expression of HIF-2α accelerates leukemic cell proliferation in mouse models, but higher expression of HIF-2α in human leukemia cells is not associated with poor prognosis. [56] ...
Full-text available
Dysregulation of mitochondrial function often precedes malignant transformation of hematopoietic stem cells (HSCs). Mitochondria have a direct role in the maintenance of HSC functions. For example, D-2-hydroxyglutarate, generated due to the activity of mutated mitochondrial isocitrate dehydrogenase (IDH), has been implicated in the pathogenesis of leukemia. Furthermore, disturbances in the fatty acid breakdown and pyruvate oxidation are often seen in leukemic cells. These and other abnormalities expedite leukemogenesis and chemoresistance of leukemic cells. However, it needs to be elucidated whether these aberrations are the result or cause of leukemogenesis. Accordingly, for this review, a search was carried out in PubMed and Google Scholar databases until June 2019 to assess the relationship between metabolic pathways in altered mitochondria and leukemia development. In the present review, an overview of mitochondria-related mechanisms and their abnormalities in leukemia is presented, with mitochondrial pathways and factors, such as mitophagy, intermediary metabolism enzymes, oncometabolites and reactive oxygen species' generation, discussed as potential diagnostic and therapeutic targets in leukemia.
Acute leukemia (AL) is a poor progressive resistant hematological disease, which has different subtypes and immunophenotypic properties according to leukemic blasts. AL is caused by genetic changes and associated with leukemia stem cells (LSCs), which determine its prognosis and endurance. LSCs are thought to be hematopoietic progenitor and stem cell (HPSCs)-like cells that underwent a malignant transformation. In addition to their low number, LSCs have the characteristics of self-renewal, resistance to chemotherapy, and relapse of leukemia. The myeloid ecotropic integration site-1 (MEIS1) protein is a member of the three-amino acid loop extension (TALE) family of homeodomain (HD) proteins that can bind to DNA sequence-specific manner. Studies have shown that overexpression of MEIS1 and associated cofactors involves tumorigenesis of numerous cancers. Historically, increased expression of Meis1 transcript as well as protein has been determined in acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) patients. Moreover, resistance to conventional chemotherapy was observed in leukemic blast samples with high Meis1 content. In this review article, the molecular mechanism of the oncological role of the MEIS1 protein in leukemia and LSC is discussed. In addition, it was suggested that MEIS1 protein could be utilized as a possible treatment target in leukemia with an emphasis on the inhibition of MEIS1, which is overexpressed in LSC.
Acute myeloid leukemia (AML) is a highly aggressive hematological malignancy with complex heterogenous genetic and biological nature. Thus, prognostic prediction and targeted therapies might contribute to better chemotherapeutic response. However, the emergence of multidrug resistance (MDR) markedly impedes chemotherapeutic efficacy and dictates poor prognosis. Therefore, prior evaluation of chemoresistance is of great importance in therapeutic decision making and prognosis. In recent years, preclinical studies on chemoresistance have unveiled a compendium of underlying molecular basis, which facilitated the development of targetable small molecules. Furthermore, routing genomic sequencing has identified various genomic aberrations driving cellular response during the course of therapeutic treatment through adaptive mechanisms of drug resistance, some of which serve as prognostic biomarkers in risk stratification. However, the underlying mechanisms of MDR have challenged the certainty of the prognostic significance of some mutations. This review aims to provide a comprehensive understanding of the role of MDR in therapeutic decision making and prognostic prediction in AML. We present an updated genetic landscape of the predominant mechanisms of drug resistance with novel targeted therapies and potential prognostic biomarkers from preclinical and clinical chemoresistance studies in AML. We particularly highlight the unfolded protein response (UPR) that has emerged as a critical regulatory pathway in chemoresistance of AML with promising therapeutic horizon. Futhermore, we outline the most prevalent mutations associated with mechanisms of chemoresistance and delineate the future directions to improve the current prognostic tools. The molecular analysis of chemoresistance integrated with genetic profiling will facilitate decision making towards personalized prognostic prediction and enhanced therapeutic efficacy.
Full-text available
Many patients with hematological neoplasms fail to mobilize sufficient numbers of hematopoietic stem cells (HSCs) in response to granulocyte colony-stimulating factor (G-CSF) precluding subsequent autologous HSC transplantation. Plerixafor, a specific antagonist of the chemokine receptor CXCR4, can rescue some but not all patients who failed to mobilize with G-CSF alone. These refractory poor mobilizers cannot currently benefit from autologous transplantation. In order to discover alternative targetable pathways to enhance HSC mobilization, we studied the role of hypoxia-inducible factor-1α (HIF1α) and the effect of HIF-1α pharmacological stabilization on HSC mobilization in mice. We demonstrate in mice with HSC-specific conditional deletion of the Hif1a gene, that the oxygen-labile transcription factor HIF-1α is essential to HSC mobilization in response to G-CSF and Plerixafor. Conversely, pharmacological stabilization of HIF-1α with the 4-prolyl hydroxylase inhibitor FG-4497 synergizes with G-CSF and Plerixafor increasing mobilization of reconstituting HSCs 20-fold compared to G-CSF plus Plerixafor, currently the most potent mobilizing combination used in the clinic.Leukemia accepted article preview online, 12 January 2015. doi:10.1038/leu.2015.8.
Full-text available
Next-generation sequencing has been used to infer the clonality of heterogeneous tumor samples. These analyses yield specific predictions-the population frequency of individual clones, their genetic composition, and their evolutionary relationships-which we set out to test by sequencing individual cells from three subjects diagnosed with secondary acute myeloid leukemia, each of whom had been previously characterized by whole genome sequencing of unfractionated tumor samples. Single-cell mutation profiling strongly supported the clonal architecture implied by the analysis of bulk material. In addition, it resolved the clonal assignment of single nucleotide variants that had been initially ambiguous and identified areas of previously unappreciated complexity. Accordingly, we find that many of the key assumptions underlying the analysis of tumor clonality by deep sequencing of unfractionated material are valid. Furthermore, we illustrate a single-cell sequencing strategy for interrogating the clonal relationships among known variants that is cost-effective, scalable, and adaptable to the analysis of both hematopoietic and solid tumors, or any heterogeneous population of cells.
Full-text available
Acute promyelocytic leukemia (APL) is epitomized by the chromosomal translocation t(15;17) and the resulting oncogenic fusion protein PML-RARα. Although acting primarily as a transcriptional repressor, PML-RARα can also exert functions of transcriptional co-activation. Here, we find that PML-RARα stimulates transcription driven by HIF factors, which are critical regulators of adaptive responses to hypoxia and stem cell maintenance. Consistently, HIF-related gene signatures are upregulated in leukemic promyelocytes from APL patients compared to normal promyelocytes. Through in vitro and in vivo studies, we find that PML-RARα exploits a number of HIF-1α-regulated pro-leukemogenic functions that include cell migration, bone marrow (BM) neo-angiogenesis and self-renewal of APL blasts. Furthermore, HIF-1α levels increase upon treatment of APL cells with all-trans retinoic acid (ATRA). As a consequence, inhibiting HIF-1α in APL mouse models delays leukemia progression and exquisitely synergizes with ATRA to eliminate leukemia-initiating cells (LICs).
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Characterization of how the microenvironment, or niche, regulates stem cell activity is central to understanding stem cell biology and to developing strategies for the therapeutic manipulation of stem cells. Low oxygen tension (hypoxia) is commonly thought to be a shared niche characteristic in maintaining quiescence in multiple stem cell types. However, support for the existence of a hypoxic niche has largely come from indirect evidence such as proteomic analysis, expression of Hif-1 (also known as Setd2) and related genes, and staining with surrogate hypoxic markers (for example, pimonidazole). Here we perform direct in vivo measurements of local oxygen tension (pO2) in the bone marrow of live mice. Using two-photon phosphorescence lifetime microscopy, we determined the absolute pO2 of the bone marrow to be quite low (<32 mm Hg) despite very high vascular density. We further uncovered heterogeneities in local pO2, with the lowest pO2 (∼9.9 mm Hg, or 1.3%) found in deeper peri-sinusoidal regions. The endosteal region, by contrast, is less hypoxic as it is perfused with small arteries that are often positive for the marker nestin. These pO2 values change markedly after radiation and chemotherapy, pointing to the role of stress in altering the stem cell metabolic microenvironment.
After intravenous (IV) injection with factor-dependent FDC-P1 cells, irradiated DBA/2 and BALB/c mice developed transplantable leukemias owing to neoplastic transformation of the injected cells in vivo. Increasing the radiation dose shortened the preleukemic latent period, and in female mice the frequency of leukemia development was higher and the latent period shorter than in male mice. In the preleukemic period, the injected FDC-P1 cells rapidly increased in number in hematopoietic organs of irradiated animals, reaching peak levels 3 to 5 weeks after injection; factor-independent transformed cells were not detected before day 45. In unirradiated animals, these events were delayed by several weeks, and long-term survivors did not harbor detectable FDC-P1 cells. FDC-P1 cells sampled from preleukemic mice frequently showed atypical colony formation and reduced cloning efficiency in vitro, suggesting the occurrence of a distinct preleukemic change. U16.6 cells produced leukemia only in irradiated recipients, and the leukemic cells usually remained factor dependent. The two contrasting models should be of value in further analyzing the mechanisms underlying radiation- induced leukemias.
Acute myeloid leukemia (AML) is a heterogeneous group of neoplastic disorders characterized by the proliferation and accumulation of immature myeloid cells in the bone marrow and blood. The World Health Organization classification has changed the criteria for the diagnosis and classification of AML. Cytogenetics, age of the patient, and molecular markers are important prognostic variables. Treatment decisions should be based on risk assessment and biology of the AML.
The relationships between clonal architecture and functional heterogeneity in acute myeloid leukemia (AML) samples are not yet clear. We used targeted sequencing to track AML subclones identified by whole-genome sequencing using a variety of experimental approaches. We found that virtually all AML subclones trafficked from the marrow to the peripheral blood, but some were enriched in specific cell populations. Subclones showed variable engraftment potential in immunodeficient mice. Xenografts were predominantly comprised of a single genetically defined subclone, but there was no predictable relationship between the engrafting subclone and the evolutionary hierarchy of the leukemia. These data demonstrate the importance of integrating genetic and functional data in studies of primary cancer samples, both in xenograft models and in patients.