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The cAMP Response Element Binding Protein, CREB, is a transcription factor that regulates cell proliferation, differentiation, and survival in several model systems, including neuronal and hematopoietic cells. We demonstrated that CREB is overexpressed in acute myeloid and leukemia cells compared to normal hematopoietic stem cells. CREB knockdown inhibits leukemic cell proliferation in vitro and in vivo, but does not affect long-term hematopoietic reconstitution.
Methods
To understand downstream pathways regulating CREB, we performed expression profiling with RNA from the K562 myeloid leukemia cell line transduced with CREB shRNA.
Results
By combining our expression data from CREB knockdown cells with prior ChIP data on CREB binding we were able to identify a list of putative CREB regulated genes. We performed extensive analyses on the top genes in this list as high confidence CREB targets. We found that this list is enriched for genes involved in cancer, and unexpectedly, highly enriched for histone genes. Furthermore, histone genes regulated by CREB were more likely to be specifically expressed in hematopoietic lineages. Decreased expression of specific histone genes was validated in K562, TF-1, and primary AML cells transduced with CREB shRNA.
Conclusion
We have identified a high confidence list of CREB targets in K562 cells. These genes allow us to begin to understand the mechanisms by which CREB contributes to acute leukemia. We speculate that regulation of histone genes may play an important role by possibly altering the regulation of DNA replication during the cell cycle.
The online version of this article (doi:10.1186/1471-2407-8-264) contains supplementary material, which is available to authorized users.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
MP and SFN analyzed the microarray data, performed the statistical analysis, and drafted the manuscript. JCC, JC, DJ, and JT performed the real-time PCR experiments. KMS supervised the experiments and wrote the manuscript. All authors read and approved the final manuscript.
Background
Several proto-oncogenes have been demonstrated to be deregulated in human cancer. In particular, the development of the hematologic malignancies such as leukemia, is associated with aberrant expression or function of proto-oncogenes such as c-myc, evi-1, and c-abl. Many translocations with cytogenetic abnormalities that characterize leukemias involve rearrangement of transcription factors, including AML-ETO and Nup98-hox. Some of these leukemia-associated fusion proteins predict prognosis, e.g. t(8,21), t(15,17), and inv(16) are associated with a good prognosis in acute myeloid leukemia (AML) [1]. Approximately 50% of adult patients have been noted to have specific cytogenetic abnormalities. The overall survival of patients with AML is less than 50%. Since half of the patients diagnosed with AML have normal cytogenetic profiles, it is critical to understand the molecular pathways leading to leukemogenesis.
We identified that the cyclic AMP Response Element Binding Protein (CREB) was overexpressed in the majority of bone marrow samples from patients with acute leukemia [2, 3]. CREB is a leucine zipper transcription factor that is a member of the ATF/CREB family of proteins [4‐6]. This transcription factor regulates proliferation, differentiation, and survival in a number of cell types, including neuronal and hematopoietic cells [4, 5]. CREB has been shown to be critical in memory and hippocampal development in mice [7, 8]. We previously described that CREB is phosphorylated at serine 133 downstream of signaling by the hematopoietic growth factor, Granulocyte Macrophage-Colony Stimulating Factor (GM-CSF) in myeloid cells [9‐11]. We further demonstrated that CREB phosphorylation results from the activation of the Mitogen Activated Protein Kinase (MAPK) and pp90 Ribosomal S6 Kinase (pp90RSK) pathways in response to GM-CSF stimulation [9].
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To understand the role of CREB in normal and neoplastichematopoiesis we investigated the expression of CREB in primary cells from patients with acute lymphoblastic (ALL) and myeloid leukemia and found that CREB was overexpressed in the majority of leukemia cells from patients with ALL and AML at the protein and mRNA levels [2, 3, 12]. Furthermore, overexpression of CREB was associated with a worse prognosis. We created CREB transgenic mice that overexpressed CREB in myeloid cells. These mice developed enlarged spleens, high monocyte count, and preleukemia (myeloproliferative disease) after one year. Bone marrow progenitor cells from CREB transgenic mice had increased proliferative capacity and were hypersensitive to growth factors compared to normal hematopoietic stems cells (HSCs). Overexpression of CREB in myeloid leukemia cell lines resulted in increased proliferation, survival, and numbers of cells in S phase [12]. Known target genes of CREB include the cyclins A1 and D [4, 5, 12, 13]. Both of these genes were upregulated in CREB overexpressing cells from mice and human cell lines [4, 5]. Thus, CREB is a critical regulator of leukemic proliferation and survival, at least in part, through its downstream target genes.
CREB target genes have been published on the website developed by Marc Montminy http://natural.salk.edu/CREB/ based on ChIP chip data [14]. Additional CREB target genes were described by Impey et al. [15]. In their studies, serial analysis of chromatin occupancy (SACO) was performed by combining chromatin immunoprecipitation (ChIP) with a modification of Serial Analysis of Gene Expression (SAGE). Using a SACO library derived from rat PC12 cells, approximately 41,000 genomic signature tags (GSTs) were identified that mapped to unique genomic loci. CREB binding was confirmed for all loci supported by multiple GSTs. Of the 6302 loci identified by multiple GSTs, 40% were within 2 kb of the transcriptional start of an annotated gene, 49% were within 1 kb of a CpG island, and 72% were within 1 kb of a putative cAMP-response element (CRE). A large fraction of the SACO loci delineated bidirectional promoters and novel antisense transcripts [15]. These studies suggest that CREB binds many promoters, but only a fraction of the associated genes are activated in any specific lineage. We therefore set out to measure the functional targets of CREB in a hematopoietic model system.
Since CREB is overexpressed in bone marrow cells from patients with acute leukemia compared to normal HSCs, this provides a potential target for leukemia therapy. To this end, we stably transduced myeloid leukemia cells with CREB shRNAlentivirus[16]. CREB knockdown by 80% resulted in decreased proliferation and differentiation of both normal myeloid cells and leukemia cells in vitro and in vivo [16]. However, downregulation of CREB did not affect short-term or long-term engraftment of normal HSCs in bone marrow transplantation assays [16]. To understand the pathways downstream of CREB, we investigated genes that were differentially regulated in CREB shRNA transduced cells. In this paper, we report expression profiling of genes that were differentially regulated in CREB knockdown K562 myeloid leukemia cells and could be potential targets for development of new therapies for acute leukemia.
Methods
Cell lines
The following human leukemia cell lines were transduced with shRNAs: K562 (Iscoves + 10% FCS) and TF-1 (RPMI + 10%FCS + rhGM-CSF. Cells were cultured at 37°C, 5% CO2 and split every 3 to 4 days. Primary AML bone marrow samples were processed as previously described [12]. All human samples were obtained with approval from the Institutional Review Board and consents were signed, according to the Helsinki protocol.
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shRNA sequence design and constructs
The CREB specific shRNA sequences were selected and validated based on accepted parameters established by Tuschl et al. [17‐19]http://www.rockefeller.edu/labheads/tuschl/sirna.html; CREB shRNA-1, CREB shRNA-2, CREB shRNA-3. Controls included empty vector, luciferaseshRNA, and scrambled shRNA. shRNA sequences are: CREB shRNA-1(5'GCAAATGACAGTTCAAGCCC3'), shRNA-2 (5'GTACAGCTGGCTAACAATGG3'), shRNA-3 (5'GAGAGAGGTCCGTCTAATG3'), LuciferaseshRNA (5'GCCATTCTATCCTCTAGAGGA3'), Scramble shRNA (5'GGACGAACCTGCTGAGATAT3'). Short-hairpin sequences were synthesized as oligonucleotides and annealed according to standard protocol. Annealed shRNAs were then subcloned into pSICO-R shRNA vectors from the Jacks laboratory at MIT [20]. The second generation SIN vector HIV-CSCG was used to produce human shRNA vectors [21].
Microarray analysis
Total RNA (10 μg) was extracted from K562 cells transduced with vector alone or CREB shRNA was submitted to the UCLA DNA Microarray Facility. RNA samples were labeled and hybridized by standard protocol to Affymetrix Gene Chip Human Genome U133+ Array Set HG-U133A array. Gene expression values were calculated using the MAS5 software. The expression values are quantile normalized across all arrays. We obtained the expression profiles for a control set and CREB downregulated K562 cells. A t-test is performed between the two groups to identify significantly differentially regulated genes. The analysis was performed using Matlab (Mathworks, Inc.). We find a significant number of differentially expressed genes, which are either direct or indirect targets of CREB.
To further characterize the data we have aligned CREB binding data from chromatin immunoprecipitation studies with our expression data. The chromatin immunoprecipitation data was obtained from the website http://natural.salk.edu/CREB/[14]. To identify genes that are most significantly bound by CREB and differentially expressed in our knockdown experiment we first filtered genes by their fold change (greater than 1.5 or less than 0.7). Finally, we ranked genes according to the product of the binding and expression P value (jerry_bind_data.xls) (see Additional file 1).
We characterize these genes using three types of analyses: Ingenuity Pathway Analysis (IPA), Gene Ontology term enrichment analysis and tissue distribution. For the former analysis, we used the Ingenuity Pathways Analysis tool on the lists of significant downregulated genes. We then identified functions that were overrepresented among these genes. For the second, we used the DAVID website http://david.abcc.ncifcrf.gov/home.jsp to identify Gene Ontology terms that were enriched in the list.
Finally, we compute the tissue distribution of the 200 genes we identified as functional CREB targets. The tissue specific expression profiles of each gene are obtained from HG_U133A/GNF1H and GNF1M Tissue Atlas Datasets.[22]. We first compute the logarithm of the ratio of the expression intensity of each gene in each tissue, divided by its average intensity across all tissues. We then perform hierarchical clustering of both the genes and the tissues.
Quantitative Real-time PCR
K562 transduced with CREBshRNA(5 × 106) were lysed in Trizol and stored at -80°C prior to RNA extraction. RNA extraction was performed according to a standard protocol supplied by the manufacturer (Invitrogen) and pellets were resuspended in RNAse free water. The cDNA was transcribed with a Superscript RT III based-protocol. DNAse treatment was not performed due to the selection of intron-spanning primers. Quantitative real-time PCR was performed with the SyberGreen reagent (Bio-Rad) in triplicates and analyzed by the standard curve method standardized to the housekeeping gene beta actin[23, 24].
Results and discussion
Since CREB has pleiotropic effects on cell function and potentially activates several genes in hematopoietic and leukemia cells, we performed microarray analysis with total RNA isolated from K562 chronic myeloid leukemia cells transduced with CREB or control shRNA. The comparison of transcriptional profiles in wild type and CREB shRNA transduced K562 cells revealed a large number of differentially expressed genes (see Additional file 2). Among these genes, some are direct targets of CREB, while others are indirect targets. To infer which of these genes was potentially directly regulated by CREB, we combined the expression data with the ChIP-chip data of CREB bound promoters as demonstrated by Marc Montminy[14]. As was previously observed CREB binding sites are highly conserved across different tissues. However, these sites are activated by cAMP in a tissues specific manner. Therefore by combining these two datasets we attempted to uncover the functional CREB sites in hematopoietic tissues.
Our hypothesis for discovering functional CREB sites in hematopoietic cells is that if a gene is found to be differentially expressed in the CREB shRNA K562 transduced cells, and bound by CREB it is likely to be a direct target. To identify these genes we developed a metric that accounts for both the significance of the expression change and binding data for each gene (described in detail in Methods).
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Since CREB has been described as both a transcriptional activator (when phosphorylated) and a repressor, we were interested in genes that were both up and downregulated in CREB shRNA transduced cells. The resulting rank ordered list allows us to sort genes by their likelihood of being functional CREB targets in K562 cells. It is difficult to determine, however, where to draw a threshold between the true and false targets. We have decided to restrict our analysis to the top several hundred targets that had both significant changes in expression and binding, as we deemed these to be highly enriched for true versus false targets. However, we do not claim that these are the only functional CREB targets in K562 cells, as the exact number of true targets is difficult to determine. The top down and upregulated genes revealed by this analysis are listed in Tables 1 and 2, and the full list is found in the supplementary materials.
Table 1
Potential CREB target genes.
Gene Name
Fold Change
CREB binding
CREB site
Gene Name
Fold Change
CREB binding
CREB site
DKFZP434G222
0.551725
3.883395
ht h
HSPC056
0.44548
1.892546
ht h
ABCG2
0.479066
2.244422
ht h
HSU79303
0.573524
1.812829
ht
ALDH2
0.5604
1.989872
none
ILVBL
0.675128
1.893295
ht h
ALDH7A1
0.62012
2.051646
h
KIAA0103
0.682528
2.620283
ht h
ALS2CR19
0.46208
1.788188
ht
HSU79303
0.573524
1.812829
ht
ANC_2H01
0.659044
1.991467
ht h
ILVBL
0.675128
1.893295
ht h
ANG
0.693535
3.287977
ht
KIAA0103
0.682528
2.620283
ht h
APLP2
0.636685
1.219917
h
KIAA0141
0.689536
3.479426
h
APPL
0.668234
1.391059
h
KIAA0408
0.595271
3.603389
none
ARFD1
0.524897
2.336962
ht
KIAA0494
0.67838
5.420821
F
BCL2L11
0.589894
3.191337
H h
KLF5
0.553523
2.062499
H
BECN1
0.600243
1.151217
H h
KNSL8
0.468603
7.854334
HT ft
BMX
0.315984
1.072006
none
KPNA5
0.562667
2.859517
none
C20orf133
0.635849
2.420642
h
LANCL1
0.647544
1.020319
none
C6orf67
0.610619
2.665053
h
LOC51668
0.500097
1.062053
ht h
CA2
0.592202
1.082939
ht
LOC51762
0.599397
3.307553
ht h
CALB2
0.671562
1.894443
h
LYPLA3
0.664078
2.379015
HT h
CCDC2
0.533032
1.529166
none
MAF
0.597194
2.383458
FT
CENPE
0.306986
3.736367
FT ht
MAPKAPK5
0.699356
2.053184
FH
CGI-77
0.664435
4.334985
H ht h
MDM2
0.468991
2.523732
none
CLDN18
0.566707
4.30699
ht h
MGC15419
0.617252
3.032433
h
CNN1
0.670957
1.150221
F ht h
MPHOSPH1
0.423771
3.535138
ht h
CREB1
0.382751
1.816762
HT H ht h
MSH2
0.592302
3.203985
h
CSPG6
0.573523
3.082765
h
MVD
0.632896
3.854905
ht h
CUL5
0.683117
2.073118
H ht h
MYL4
0.69963
1.010099
h
DBP
0.67969
2.805267
ft ht
NEFL
0.343403
2.413823
HT h
DES
0.521516
1.509794
ht h
NFKBIL1
0.695019
4.072353
ht
DIS3
0.692573
3.837304
HT ht
NIPSNAP1
0.679129
1.215594
h
DNCI1
0.673721
2.195167
none
NOX3
0.455479
2.60292
h
DNMT3A
0.679821
1.035348
h
NR4A3
0.543361
5.002146
HT H h
DSIPI
0.40458
2.546212
HT
NUDT5
0.673003
2.561752
h
DUSP19
0.674195
2.225933
none
NUMB
0.675667
1.014954
HT ht
EIF2S1
0.631867
1.075696
H ht h
PDE6B
0.66696
2.699363
h
EIF2S2
0.644661
3.313634
ht h
PEX12
0.694707
6.199684
h
ESRRBL1
0.67914
4.633352
FH h
PFDN4
0.507631
2.196535
none
FBXO22
0.688756
2.206273
ht
PHC1
0.672187
1.053985
HT
FECH
0.516446
1.045191
h
PKD2L2
0.513894
2.249593
h
FECH
0.658471
1.045191
h
PLAA
0.603854
9.235476
none
FLJ10853
0.622952
3.981514
H ht
PPP1R2
0.568734
2.04019
ft
FLJ10858
0.668758
1.523113
none
PRDX3
0.615229
1.847784
none
FLJ10904
0.54026
1.085341
none
PSAT1
0.47554
2.492965
ht
FLJ11011
0.610253
3.387879
ht h
PSMAL/GCP
0.68221
1.341117
none
FLJ11342
0.683482
2.617474
ht
PTGS2
0.684401
3.057276
ht h
FLJ11712
0.62618
2.776373
ht
RAB31
0.698664
1.12667
ht
FLJ13491
0.633125
3.268155
none
RB1CC1
0.533475
1.390318
none
FLJ20130
0.640787
2.766588
h
RFC3
0.577787
6.745001
FH ht
FLJ20331
0.681859
8.752576
H
RHEB
0.682202
3.47317
HT H h
FLJ20333
0.690542
1.946262
ht h
RNASE4
0.436168
2.975774
ht h
FLJ20509
0.691949
1.96435
none
SARS2
0.692149
5.455469
H h
FLJ23233
0.471676
1.517415
none
SBBI26
0.683312
6.75719
H
FOXD1
0.593522
5.160553
HT ht
SDP35
0.502432
2.320591
h
GCAT
0.656744
2.122675
ht h
SERPINI1
0.31594
3.277692
ht
GCHFR
0.676365
2.188753
ht h
SHMT1
0.658252
1.127084
ht h
GFI1B
0.671179
0.999255
h
SILV
0.662805
2.130617
H
GMPR
0.672975
1.149663
ht
SLC11A2
0.684325
1.842417
none
GOLGA4
0.567882
2.939327
ht h
SLC22A5
0.657746
1.64513
none
GPNMB
0.410992
1.004344
none
SLC27A6
0.547039
1.029816
ht
GRHPR
0.68706
2.454475
H ht
SLC2A4
0.507466
2.273185
ht h
H2BFS
0.591569
2.358423
ht
SLC39A8
0.201136
1.004832
none
HBE1
0.639376
0.947159
h
SLC4A7
0.532067
1.262531
ht
HDGFRP3
0.65013
1.208322
none
SMARCA1
0.519982
1.056916
HT ht
HDGFRP3
0.668211
1.208322
none
SMC2L1
0.596288
2.916083
ht h
HEXA
0.54467
2.622927
none
SRI
0.671893
0.826457
ht
HIST1H1C
0.590374
1.983514
h
STK16
0.680797
6.555535
H h
HIST1H2AD
0.66909
4.768013
ht h
SULT1C2
0.599235
3.511947
f h
HIST1H2AI
0.542518
2.801688
H ht h
SURB7
0.498245
1.598812
ht
HIST1H2AJ
0.696531
3.066865
ft ht h
SYN1
0.696375
3.016534
F h
HIST1H2AL
0.602018
2.600144
FHT ht h
TAF1A
0.589389
2.689618
none
HIST1H2BB
0.590821
1.782458
ht h
TBC1D7
0.692755
1.281463
ht
HIST1H2BD
0.674855
3.111055
HT ht h
TCTE1L
0.368312
2.475611
ht
HIST1H2BE
0.546621
2.34815
ht
TFDP2
0.670657
1.016413
ht
HIST1H2BF
0.543665
1.985466
ht
TGDS
0.67197
1.523411
none
HIST1H2BH
0.617917
2.04185
none
THRB
0.670555
2.256453
H ht h
HIST1H2BI
0.585897
1.443622
ht
TMEM14A
0.656093
1.175355
ht h
HIST1H2BJ
0.493823
5.335159
HT ht h
TOM1
0.64031
3.221137
h
HIST1H2BM
0.687469
3.533372
ft ht h
TXN2
0.689274
1.893339
H ht h
HIST1H2BO
0.618862
4.014214
ht h
UBE2B
0.663194
3.652863
H ht h
HIST1H3B
0.556438
4.260113
ft ht
VRK1
0.650583
1.000406
h
HIST1H3H
0.641946
2.647758
H ht h
WASPIP
0.572355
1.01892
none
HIST1H4E
0.608257
2.458831
FT h
WDHD1
0.624889
4.984045
H ht h
HIST1H4I
0.612088
2.068983
ht
WWOX
0.671866
1.882778
h
HIST2H2AA
0.560962
4.032876
ht
ZNF134
0.677481
2.726853
ht h
HLA-DRA
0.365141
3.086303
ht h
ZNF222
0.5618
4.09755
ht h
HLXB9
0.667926
1.006593
none
ZNF230
0.410725
3.76825
ht h
HS2ST1
0.694429
1.032562
ht h
ZNF235
0.38371
2.959812
none
HSBP1
0.671929
1.891961
ht h
Top down-regulated genes that show significant CREB binding and changes in expression in the CREB knockdown cells. The detailed criteria for selecting these genes are described in the methods section. For each grouping of genes, from left to right, column 1 shows the gene symbols, column 2 the ratio of the expression change in wild type versus knockdown, column 3 the CREB binding ratio and column 4 the presence of CREB binding motifs. The key for column 4 is as follows: F is a full CREB motif (TGACGCTA) that is conserved from human to mouse, while f is not conserved, H is a conserved CREB half motif (TGACG or CGTCA), while h is not conserved, and T is the conserved presence of a TATA motif less than 300 base pairs downstream of the CREB motif, while t is not conserved.
Table 2
Potential CREB target genes.
Gene Name
Fold Change
CREB binding
CREB site
Gene Name
Fold Change
CREB binding
CREB site
ACOX1
2.110674
2.911283
H ht
LDLR
1.678587
1.525499
ht
ADAT1
1.410234
3.769574
ht f h
LGALS3BP
2.131291
3.615437
none
APEH
1.400261
2.527266
h
LIM
1.696177
1.097432
none
APPBP2
1.486616
2.151867
H ht h
LIM
1.849989
1.097432
none
ARHB
2.758453
2.77377
H ht
LRRFIP1
1.941595
1.122307
h
ATP6V1A
1.446867
3.016595
HT ht h
METAP2
1.916632
2.635425
ht
BCL6
1.640646
6.084626
HT ht
METTL2
1.593867
3.474639
none
BDKRB2
1.600927
2.601219
none
MGC2731
1.588545
2.80081
HT h
BTN3A2
1.465264
3.426679
ht
MGC4054
1.502743
2.777966
ht
C20orf12
1.511854
3.12999
h
MOCS3
1.796255
5.213295
none
C20orf121
1.456022
3.532969
H
MRPS10
1.410471
1.834794
ht f
C20orf172
1.463616
4.659037
H h
NCOA3
1.495237
2.715807
ht
C20orf23
1.528396
2.622103
none
NDRG1
2.030896
2.312257
ht h
CD44
9.531947
1.335178
ht h
NEDF
1.567662
4.268912
ft ht
CDH12
3.296441
1.178959
none
NPR2L
1.618864
6.397355
ht h
CDKAL1
1.735322
3.445022
none
ODZ1
1.448279
2.310975
ht
CDKN1A
2.216725
1.778747
H ht h
OPA3
1.474233
7.631458
FHT ht h
CELSR3
1.546375
3.175919
H ht
OTC
1.693003
4.881484
ht
CENPF
1.415064
2.654622
ht
PAFAH2
1.67217
4.584628
none
CHRNB1
1.55045
1.412576
H h
PAFAH2
1.631066
4.584628
none
CLECSF2
1.747573
1.251667
none
PHC3
1.42261
1.747154
ht
CML2
1.47905
3.427882
ht
PHLDA1
3.92008
2.003171
h
COL15A1
2.56792
1.394566
none
PLAT
1.668223
1.95203
none
CREM
1.793497
3.67068
H
PLEKHB2
1.568395
4.611748
f
CRKL
1.690269
3.051845
H h
PPARGC1
2.268458
2.972107
HT F ht h
CSMD1
1.647116
1.61907
ht
PPFIBP1
1.852526
2.550633
ht h
CTMP
1.548763
3.386235
none
PPP1R10
1.870902
2.447557
H h
DBT
1.518604
4.292329
none
PPP1R3B
1.693114
1.622596
h
DCLRE1C
1.41992
3.010944
none
PSMAL/GCP
1.506527
2.707076
none
DDOST
1.582101
2.508459
ht
RAB7L1
1.638378
1.15364
ht h
DDX3X
1.817009
3.42975
none
RABL2B
1.486054
2.496157
h
DEGS
1.488221
1.464348
none
RASSF1
1.431271
4.04395
none
DIAPH1
1.412484
2.96506
none
RBL1
1.529652
2.451247
h
DUSP1
1.578824
2.102797
FT HT ht h
REL
1.944847
1.143935
H h
EGR2
5.148023
2.036633
HT ht h
RHOBTB3
1.63057
2.813465
none
EIF5
1.422558
4.208549
ht h
RIOK3
1.40951
2.008376
none
ELK1
1.405171
4.088789
ht
RNASE6PL
1.561704
2.252099
ht
ENC1
1.957151
1.549567
h
RNF32
1.954396
1.603905
H ht
F2R
1.804785
1.098488
ht h
SAS
1.768493
7.735178
HT ht h
FAM13A1
1.780869
2.014276
none
SERPINB9
2.244605
1.418097
ht h
FAT
2.00051
1.816506
F ht
SFPQ
1.477265
3.428149
ht
FKBP14
1.78994
3.042488
ht
SHARP
1.558516
1.078188
H ht
FLJ10781
1.463332
1.113364
ht h
SLC31A1
1.491104
3.803168
FH ht
FLJ10803
1.726196
2.63943
ht
SLC35E3
1.716026
1.969928
ht
FLJ11029
1.422001
3.085667
ht h
SLC38A2
1.497716
1.914154
H ht
FLJ11151
2.413055
1.840398
h
SLC39A6
1.477678
3.119807
h
FLJ20507
1.730068
2.922871
H ht h
SMA3
1.414595
2.654203
ht
FOSL1
2.220086
1.929543
HT ht h
SMARCF1
1.537978
1.046929
none
FRSB
1.423607
2.982919
ht
SNAP29
1.521481
2.454502
h
FXC1
1.423019
5.02095
HT H ht
SON
1.42477
4.933417
H
GALNS
1.772331
2.592543
h
SPG4
1.413533
3.160161
none
GCA
1.690161
2.92801
H h
SUFU
1.661693
2.275704
ht h
GTF2H3
1.593421
10.587057
H
TAP1
1.435113
3.105625
H h
GYS1
1.418699
2.559154
h
TIGD6
1.772719
3.636168
h
HBS1L
1.475369
3.891767
ht
TIMP1
1.791155
1.848154
HT h
HIP1
1.537214
2.114631
ht h
TNFRSF21
1.498482
2.635088
ht
HLA-C
1.429002
3.2916
h
TP53AP1
1.527339
3.493111
ht h
HSPG2
1.708361
1.453039
none
TPM4
2.201468
1.33368
H ht
ICAM1
2.20462
1.198603
ht h
TRIM26
1.400065
6.12308
ht
ID1
1.521685
2.3068
FT ht
TSSC3
1.879281
2.01021
H ht h
IDS
1.508286
1.1848
h
TTF1
1.513382
3.461645
ht h
IER5
1.66867
2.847755
HT ht
TUBA3
1.481437
2.500545
none
IL10RA
1.64246
2.830231
f
U2AF1L1
2.758542
3.548509
ht
IL10RB
1.410005
1.192048
ht h
U5-116KD
2.223148
2.779884
h
IL1R1
1.812093
1.329947
ht
USP2
2.35423
3.920336
HT H h
IL6
1.980266
1.460112
HT ht
VPS4B
1.474465
6.693871
H ht
IL6ST
1.54702
3.418269
none
YME1L1
1.441837
1.843132
F ht h
INPP1
2.071508
1.550135
ht h
ZFP37
1.572207
4.659572
ht h
ITGA5
2.028008
1.315131
none
ZNF142
1.50914
3.028386
h
JM4
1.606813
2.392743
HT h
ZNF155
1.69746
4.195939
none
KIAA0266
1.504796
2.986155
none
ZNF189
1.625836
4.104303
ht h
KIF14
1.453888
4.181899
none
ZNF221
1.777122
3.569536
none
KIF3B
1.623133
1.560467
none
ZNF324
1.488601
4.205703
h
LCMT2
1.587221
2.338943
H ht h
Top up-regulated genes that show significant CREB binding and changes in expression in the CREB knockdown cells. The detailed criteria for selecting these genes are described in the methods section. The column descriptions are the same as in Table 1.
Genes within the downregulated list were BECLIN 1, UBE2B. Both these genes have a cAMP responsive element binding site(s) in their promoters. These genes were selected for further validation because they are known to be involved in autophagy/apoptosis (BECLIN 1), cell cycle/DNA repair (UBE2B) [25‐28]. Quantitative real time-polymerase chain reaction (qRT-PCR) with mRNA from AML cell lines (K562 and TF-1) and primary leukemic blasts from a patient with M4-AML was performed. UBE2B expression was significantly reduced in CREB shRNA transduced TF-1 and K562 myeloid leukemia cells compared to controls (Figure 1, p < 0.05). BECLIN and UBE2B were downregulated in primary AML cells transduced with CREB shRNA (Figure 1, p < 0.05).
Figure 1
Expression of potential target genes downstream of CREB in myeloid leukemia cells. Primers specific for the UBE2B, BECLIN1, and CREB genes were generated and utilized for quantitative real-time PCR by SyberGreen method (Bio-Rad Inc.) Relative gene expression normalized to the housekeeping gene actin is shown for the following transduced cells: (A) K562 myeloid leukemia cells, (B) TF-1 myeloid leukemia cells, and (C) Human AML-M4 blasts.
Having confirmed the validity of our microarray results in these two test cases we set out to characterize the function of the complete list of CREB target genes using two annotation schemes. The first utilizes the annotation contained in the Ingenuity Pathway Analysis software (IPA). This analysis showed that there is a significant enrichment for cell cycle (P < 1e-3) and cancer (P < 1e-3) genes. The full list of genes associated with cancer is shown in Table 3. Many of these genes regulate cell cycle, signaling, DNA repair, or metabolism, which are consistent with previously published results [5, 15]. Furthermore, the role of CREB in the pathogenesis of leukemias has also been described in the literature [2, 3, 12, 29].
Table 3
The subset of CREB target genes associated with cancer according to Ingenuity Pathways Analysis.
Column 1 is the gene name, column 2 the localization, column 3 is a description of the protein function and column 4 are compounds that target the protein.
IPA also allows us to study CREB target genes in the context of protein-protein interactions networks. A network for downregulated genes interacting with CREB is shown in Figure 2, with a subset of the downregulated targets shown in grey, while other genes not in the target list that interact with these, shown in white. Here we see that there is prior literature supporting our analysis that CREB1 regulates PTGS2 (COX2), NR4A3 and TOM1, as depicted by the blue lines. Interestingly, COX2 is an important drug target, and suggests that commonly used COX2 inhibitors may provide a target for acute leukemia.
Figure 2
A network depicting interactions between direct CREB targets (shown in grey) and proteins that these interact with (shown in white). PTGS2, NR4A3 and TOM1 are direct CREB targets whose regulation by CREB was previously described in the literature (clue lines). PTGS2 (COX2) emerges as a central player in this network, and is thus implicated as a potential regulator of leukemias.
The second analysis that we performed used the terms from Gene Ontology to identify common characteristics among the top K562 CREB targets. Here we find the striking and unexpected result that ten percent of the downregulated targets code for histone genes (P < 1e-10, Table 4). We also performed an analysis of the top upregulated genes but did not find any significant GO terms. Although there is some prior literature indicating that CREB or CREB-related pathways may play a role in regulating histone modifications primarily through the histone acetylase CREB Binding Protein (CBP)[5, 30, 31], the fact that CREB directly regulates the transcription of histone genes in these cells is unexpected.
Table 4
Gene Ontology terms that are enriched among the top CREB targets.
Category
Term
Count
%
PValue
GOTERM_CC_ALL
nucleosome
11
6.88%
6.22E-10
GOTERM_CC_ALL
chromosome
17
10.62%
2.39E-09
GOTERM_BP_ALL
nucleosome assembly
11
6.88%
6.60E-09
GOTERM_CC_ALL
chromatin
13
8.12%
7.56E-09
GOTERM_BP_ALL
chromatin assembly
11
6.88%
1.66E-08
GOTERM_BP_ALL
protein complex assembly
15
9.38%
2.19E-07
GOTERM_BP_ALL
chromatin assembly or disassembly
11
6.88%
3.84E-07
GOTERM_BP_ALL
chromosome organization and biogenesis
15
9.38%
5.56E-07
GOTERM_BP_ALL
chromosome organization and biogenesis (sensu Eukaryota)
14
8.75%
1.63E-06
GOTERM_CC_ALL
membrane-bound organelle
75
46.88%
1.93E-06
GOTERM_CC_ALL
intracellular membrane-bound organelle
74
46.25%
4.63E-06
GOTERM_CC_ALL
organelle
83
51.88%
5.39E-06
GOTERM_MF_ALL
DNA binding
38
23.75%
6.17E-06
GOTERM_BP_ALL
cellular physiological process
118
73.75%
8.86E-06
GOTERM_BP_ALL
establishment and/or maintenance of chromatin architecture
12
7.50%
1.02E-05
GOTERM_CC_ALL
intracellular organelle
82
51.25%
1.28E-05
GOTERM_BP_ALL
DNA packaging
12
7.50%
1.38E-05
GOTERM_BP_ALL
organelle organization and biogenesis
22
13.75%
1.59E-05
GOTERM_CC_ALL
nucleus
56
35.00%
2.46E-05
GOTERM_BP_ALL
DNA metabolism
19
11.88%
2.63E-05
Column 1 is the ontology used (BP is biological process, CC is cellular localization and MF is molecular function), column 2 is the term, column 3 is the number of genes in the target list associated wit the term, column 4 is the percentage of genes in the target list associated with the term and column 5 is the P value for observing this number genes associated with the term.
To further validate the hypothesis that CREB is an activator of these 20 histone genes, we utilized previously published analyses of the gene promoters to identify consensus CREB binding sequences. The results shown in Table 1 demonstrate that nearly all the histone genes contain CREB half sites along with a TATA box in the vicinity of these. Thus three lines of evidence support the assignment of these 20 histone genes as CREB targets in K562 cells: expression, binding and sequence based.
We examined the distribution of expression of these 20 histone genes across human tissues. The expression data were obtained from the GNF body atlas. We were able to extract expression profiles for 81 histone genes contained in the human genome. Fifteen of these overlapped with the 20 histone CREB targets. We show the expression of all 81 histone genes in Figure 3, where the identity of the 15 CREB target genes is shown in the last row. We see that the 15 genes are clustered into two groups containing more than one gene, with a third group consisting of a single histone HIST1H1C. One of the groups contains histones that are broadly expressed across human tissues, and particularly in all hematopoietic tissues. The second group is instead expressed in a very narrow range of tissues including K562 cells, bone marrow, prostate and thymus.
Figure 3
The tissue specific expression of histone genes. Each row of the figure represents a tissue from the GNF Body Atlas (see methods). We show only the top 30 tissues with highest variance of expression of histone genes. Each column represents a histone gene. We use hierarchical clustering to order the rows and columns according to their similarity. Red indicates that the gene is over expressed relative to its mean expression levels across all tissues, and green that it is under expressed. The histone genes that we identify as direct targets of CREB are shown in red in the last row of the figure. We see that many of these are only expressed in a small subset of rapidly dividing tissues along with K562 cells.
We examined the expression of three histones that are putative targets of CREB by real time PCR with mRNA from K562, TF-1, and primary cells from patients with AML. The three histones selected were based on our microarray analyses. Our results demonstrated a statistically significant decrease in histonesHIST1H2Bj, HIST1H3B, and HIST2H2AA in K562 and TF-1 cells (Figure 4). Interestingly, in primary cells from a patient with AML, only HIST1H3B and HIST2H2AA, but not HIST1H2BJ expression was decreased with CREB knockdown. These results suggest that histones are differentially expressed in AML and that specific histones are potential targets of CREB. This analysis supports the hypothesis that CREB regulates a subset of histone genes that are normally expressed in a small set of rapidly dividing tissues. These genes are presumably aberrantly activated in K562 and other leukemia cells, and could potentially contribute to the malignant phenotype.
Figure 4
Expression of target histone genes is decreased in CREB knockdown myeloid leukemia cells. Primers specific for HIST1H2BJ, HIST1H3B, and HIST2H2AA were generated and utilized for quantitative real-time PCR by the SYBR Green method (Applied Biosystems). Relative gene expression normalized to the housekeeping gene actin is shown for the following transduced cells: (A) K562 myeloid leukemia cells, (B) TF-1 myeloid leukemia cells, and (C) primary AML cells.
We have identified a high confidence list of CREB target genes in K562 myeloid leukemia cells. Several important CREB target genes that function in DNA repair, signaling, oncogenesis, and autophagy were identified. These genes provide potential mechanisms by which CREB contributes to the pathogenesis of acute leukemia. Expression of the genes beclin-1 and ube2b was found to be decreased in myeloid leukemia cell lines and primary AML cells in which CREB was downregulated. In addition, we speculate that CREB may have more global effects on transcription, primarily through the regulation of histone genes thereby altering the regulation of DNA replication during the cell cycle.
Acknowledgements
We would like to thank Nori Kasahara and the Core Vector Laboratory for assistance with the CREB shRNA lentivirus. This work was supported by National Institutes of Health grants HL75826 (K.M.S.), HL83077 (K.M.S.), F32HL085013 (J.C.), American Cancer Society grant RSG-99-081-01-LIB (K.M.S.), and Department of Defense grant CM050077 (K.M.S.). Microarray experimentation was supported by the UCLA NHLBI Shared Microarray Resource grant R01HL72367 (S.F.N.). K.M.S. is a scholar of the Leukemia and Lymphoma Society.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
MP and SFN analyzed the microarray data, performed the statistical analysis, and drafted the manuscript. JCC, JC, DJ, and JT performed the real-time PCR experiments. KMS supervised the experiments and wrote the manuscript. All authors read and approved the final manuscript.
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