Abstract
Purpose
We compared the gene expression profile of peripheral blood CD34+ cells and granulocytes in subjects with chronic myeloid leukemia (CML), with the accent on signaling pathways affected by BCR-ABL oncogene.
Methods
The microarray analyses have been performed in circulating CD34+ cells and granulocytes from peripheral blood of 7 subjects with CML and 7 healthy donors. All studied BCR-ABL positive CML patients were in chronic phase, with mean value of 2012±SD of CD34+ cells/μl in peripheral blood.
Results
The gene expression profile was more prominent in CML CD34+ cells (3553 genes) compared to granulocytes (2701 genes). The 41 and 39 genes were significantly upregulated in CML CD34+ cells (HINT1, TXN, SERBP1) and granulocytes, respectively. BCR-ABL oncogene activated PI3K/AKT and MAPK signaling through significant upregulation of PTPN11, CDK4/6, MYC and reduction of E2F1, KRAS, NFKBIA gene expression in CD34+ cells. Among genes linked to inhibition of cellular proliferation by BCR-ABL inhibitor Imatinib, the FOS and STAT1 demonstrated significantly decreased expression in CML.
Conclusion
Presence of BCR-ABL fusion gene doubled the expression quantity of genes involved in the regulation of cell cycle, proliferation and apoptosis of CD34+ cells. These results determined the modified genes in PI3K/AKT and MAPK signaling of CML subjects.
Keywords: CD34+ cells, granulocytes, chronic myeloid leukemia, microarray analysis
Introduction
Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder that originates from an abnormal pluripotent bone marrow hematopoietic stem cell, characterized by various biological and clinical features [1]. The main molecular marker of CML is the BCR-ABL fusion gene generation as a result of a t(9;22)(q34;q11) translocation [2]. It has been shown that distribution of malignant cells in CML is not induced by the neoplastic stem cell, but by the lineage-committed progenitor cells [3]. During the chronic phase CML, pool of circulated CD34+ cells demonstrate an increase in the proportion of megakaryocyte-erythroid progenitors, whereas the proportion of hematopoietic stem cells and granulocyte-macrophage progenitors usually decrease [4]. The gene expression profiles of quiescent bone marrow leukemic and peripheral blood CD34+ cells of untreated CML subjects, demonstrate no significant difference, compared to normal CD34+ cells [4,5]. The sedentary CML CD34+ cells are more similar to their dividing counterparts than quiescent normal cells are to theirs [6].
In patients with CML, mitogenic signaling pathways such as rat sarcoma viral oncogenes homolog (RAS) / mitogen-activated protein kinase (MAPK) pathway, the Janus kinase (JAK) / signal transducer and activator of transcription (STAT) pathway, phosphoinositide-3 kinase (PI3K) / AKT pathway and the MYC pathway are usually constitutively activated, in addition to deregulation of proliferation, apoptosis and release of progenitors from bone marrow [7]. The following cellular processes are dysregulated by the BCR-ABL oncoprotein: RAS/MAPK signaling that activates proliferation, and PI3K/AKT signaling that activates apoptosis. It has been shown that most components of the MAPK and PI3K/AKT pathways and some genes of the alternative JNK and p38 MAPK pathways are upregulated in primary CML CD34+ cells [4]. A wide range of genes are identified as being dependent on BCR-ABL1-mediated signaling, including genes involved in signal transduction of JAK/STAT, MAPK, and TGF-β. BCR-ABL1 activates several genes involved in negative feedback regulation that indirectly suppress the tumor promoting effects exerted by BCR-ABL1 [8].
Previous microarray analyses of CML subjects has been performed on selected CD34+ cells or mononuclear cells [9–12]. In our study we combined gene expression analyses of selected CD34+ cells and granulocytes to determine persistent and transient gene expression in MAPK, PI3K/AKT and TGF-β pathways, influenced by BCR-ABL, during cell maturation. Gene expression patterns reflect BCR-ABL-induced functional modifications such as cell-cycle, apoptosis and proliferation. This observation highlights the difference in gene expression between CD34+ cells of CML and control subjects, with the accent on genes that direct the pathogenic course of malignancy.
Material and methods
Isolation of CD34+ cells and granulocytes from the peripheral blood of CML subjects
Informed consent was obtained from 7 de novo subjects with CML included in the study. All subjects had signed the consent form approved by the local ethical committee. All studied de novo CML subjects were subject to 10 ml of peripheral blood draw on one occasion, collected in 10% sodium citrate. The maximum time interval between venepucture and arrival in the laboratory was 2 hours. Each 20 ml of diluted blood (1:1 with Ca2+/ Mg2+- free PBS) was then layered gently on the top of 10 ml lymphocyte separation medium (LSM, PAA Laboratories GmbH, Pasching, Austria). After centrifugation (400 g, 30 min, 20°C), the interface containing mononuclear cells was collected and washed with PBS. The CD34+ cells were isolated from the collected mononuclear cells using a positive immunomagnetic separation (Super Macs II, Miltenyi Biotec, Bergisch Gladbach, Germany). Control CD34+ cells were also isolated by positive immunomagnetic separation from 7 leukapheresis products of healthy donors (4 females, 3 males). The pellet formed during centrifugation with LSM was comprised mostly of erythrocytes and granulocytes that migrated through the gradient. Contaminating erythrocytes were removed by using lysing solution (0.15 M NH4Cl, 0.1 mM Na2EDTA, 12 mM NaHCO3). High quality of purified granulocytes was confirmed by cytospine preparations and Wright-Giemsa staining. The viable CD34+ cell and granulocyte counts were performed by trypan-blue exclusion technique (BioWhittaker). The purity of recovered cells was determined by flow cytometry using PE-anti-CD34 mAb (BD Biosciences, San Jose, CA, USA) and was over 80% in samples used for microarray analysis. Karyotype analyses confirmed the Philadelphia chromosome aberrations t(9:22)(q34:q11) in all examined CML subjects.
Isolation of total RNA
We use the RNeasy protocol for isolation of total RNA from CD34+ cells and granulocytes according to the manufacturer’s instructions (Qiagen GmbH, Hilden, Germany). Concentration and integrity of total RNA was assessed using NanoDrop spectrophotometer (Thermo Fisher Scientific Inc., Wilmington, Delaware, USA) and Agilent 2100 Bioanalyzer Software (Agilent Technologies, Waldbronn, Germany) comparing the ratio of 28S and 18S RNA peaks to ensure that there is minimal degradation of the RNA sample.
Microarray analysis
The human oligo probe set is purchased from Operon Human genome Array-Ready Oligo Set Version 4.0 (Eurofins MWG Operon, Huntsville, AL, USA) which contains 35.035 oligonucleotides probes, representing approximately 25.100 unique genes. The human version 4.0 is constructed based on the Ensemble human database build (NCBI-35c), with a full coverage on NCBI human Refseq dataset. We have followed the MIAME (minimum information about a microarray experiment) guidelines for the data presentation. Oligonucleotides were diluted in 150mM sodium phosphate, pH 8.5, at 20μM concentration for printing. Also, our prior experience with these primary cell cultures includes quantitative PCR with housekeeping genes (S16 and HPRT) to establish similar efficiency of cDNA synthesis and PCR (data not shown). In microarray studies, for determination of broad gene expression in CD34+ cells, we analyzed 7 CML subjects in chronic phase (1 female and 7 males, average age 60) and 7 healthy subjects (4 females and 3 males, average age 48). For determination of gene expression in granulocytes we used 2 CML subjects (1 female and 1 male, average age 58) in chronic phase and 4 healthy subjects (2 females and 2 males, average age 51), that matched subjects used for isolation of CD34+ cells.
Amplification of mRNA
We isolated a low quantity of CD34+ cells (~2×106 cells) that correspond to low mRNA levels insufficient for microarray analysis, so we performed the amplification of total RNA using the Amino Allyl MessageAmp™ II aRNA Amplification kit (Life Technologies Corp., Carlsbad, CA, US). This amplification protocol was performed both in CD34+ cells and granulocytes, for parallel studies, according to the manufacturer’s instructions. We used 0.5 μg of total RNA from CML subjects for amplification. Briefly, 11 μl of total RNA was mixed with 1 μl of T7 dT primer and incubated at 70°C for 5 minutes and quickly chilled for 3 minutes. Then, 8 μl Reverse Transcription Master Mix (10X First Strand Buffer, dNTP Mix, Rnase inhibitor, ArrayScript) were added and incubated for 2 hours at 42°C and quickly chilled. We added 80 μl Second Strand Master Mix (10X Second Strand Buffer, dNTP Mix, DNA polymerase, Rnase H) and incubated for 2 hours at 16°C. cDNA was purified by 250μl cDNA Binding buffer and the mixture applied to the cDNA filter cartridge. After discharging the flow-through, 500 μl of washing buffer was added to the column, and centrifuged for 1 minute at 10.000 rpm. cDNA was diluted with 18 μl of 55°C preheated nuclease free water, mixed with 26 μl of in vitro transcription (IVT) Master Mix (aaUTP, ATP, CTP, GTP mix, UTP solution, 10X reaction buffer, T7 enzyme mix) and after 14 hours incubation at 37°C we added 60 μl of nuclease free water. Amino allyl-modified antisense RNA (aRNA) was purified with aRNA Binding buffer and ethanol, applied to the cDNA filter column and quantified by NanoDrop spectrophotometer (Thermo Fisher Scientific Inc.). Vacuum dried 3 μg of aRNA was resuspended in 9 μl Coupling buffer, mixed with 11 μl Cy5 dye resuspended in DMSO and incubated 45 minutes at room temperature (RT) in the dark. After incubation, labeled aRNA was purified and eluted with 10 μl preheated nuclease free water by centrifugation.
Probe preparation
Total human universal RNA (HuURNA) isolated from a collection of adult human tissues to represent a broad range of expressed genes from both male and female donors (BD Biosciences, Palo Alto, CA) served as a universal reference control in the competitive hybridization. All examined CML and healthy control samples are hybridized against HuURNA. Briefly, 5 μg of HuURNA was incubated at 70°C for 5 minutes along with 1 μl of aminoallyl-oligo dT primer and quickly chilled for 3 minutes. Then, 2 μl 10X first strand buffer, 1.5 μl SSII enzyme (Stratagene, La Jolla, CA), 1.5 μl 20X aminoallyl dUTP and 2 μl of 0.1M DTT were added and incubated for 90 minutes at 42°C. After incubation, volume of the reaction mixture was raised to 60 μl with 40 μl of DEPC water. cDNA was purified by the MinElute column (Qiagen) where 300 μl of Binding buffer PB was added to the coupled cDNA, and the mixture applied to the MinElute column, and centrifuged for 1 minute at 10.000 rpm. After discharging the flow-through, 500 μl of washing buffer PE was added to the column, and centrifuged for 1 minute at 10.000 rpm. The flow-through was discharged and the washing repeated. Then the columns were placed into a fresh eppendorf tube and 10 μl elution buffer added to the membrane, incubated for 1 minute at RT, centrifuged for 1 minute at 10.000 rpm and probe collected. The probe was dried in speed-vac for 20 minutes. Finally, cDNA diluted in 10 μl of 2X coupling buffer were mixed with 10 μl of Cy3 dye (GE Healthcare Bio-Sciences Corp., Piscataway, NJ), diluted in DMSO, and incubated at RT in dark for 90 minutes. After incubation, the volume was raised to 60 μl by 40 μl DEPC water and then cDNA was purified by the MinElute column and eluted with 10 μl elution buffer by centrifugation. Eluted cDNA probe and aRNA were combined in final volume of 20 μl for hybridization.
Hybridization
For hybridization, the mixture of cDNA probe and aRNA was preheated at 100°C for 2 minutes and centrifuged for 1 minute at 10.000 rpm. 20 μl of preheated (42°C) Ambion hybridization buffer (20x SSC and 10% SDS) is mixed with hybridization mixture. Total volume of the hybridization mixture was added on the array in slide and covered with cover slip. Slides were placed in MAUI hybridization chamber (BioMicro Systems, Inc., Salt Lake City, UT, USA) and incubated overnight at 42°C. Slides were then washed each in 1x SSC and 0.1x SSC and spin-dried.
Data Filtration, normalization and analysis
Microarray slides were scanned in both Cy3 (532nm) and Cy5 (635nm) channels using Axon GenePix 4000B scanner (Axon Instruments, Inc., Foster City, CA) with a 10-micron resolution. Scanned microarray images were exported as TIFF files to GenePix Pro 3.0 software for image analysis. The raw images were collected at 16-bit/pixel resolutions with 0 to 65,535 count dynamic range. The area surrounding each spot image was used to calculate a local background and subtracted from each spot before the Cy5:Cy3 ratio calculation. The average of the total Cy3 and Cy5 signal gave a ratio that was used to normalize the signals. Each microarray experiment was globally normalized to make the median value of the log2-ratio equal to zero. The Loess normalization process corrects for dye bias, photo multiplier tube voltage imbalance and variations between channels in the amounts of the hybridized labeled cDNA probes. The data files representing the differentially expressed genes were then created. For advanced data analysis, gpr and jpeg files were imported into microarray database and normalized by software tools provided by NIH Center for Information Technology (http://nciarray.nci.nih.gov/). Spots with confidence interval of 99% (≥ 2 fold) with fluorescence intensity of at least 150 for both channels and 30 μm spot size were considered as good quality spots for analysis. The complete results of our microarray experiments are available in the gene expression omnibus database (http://www.ncbi.nlm.nih.gov/geo; accession no.GSE55976) according to MIAME standards.
Statistical analysis
For microarray data management and analysis, we used NCI/CIT microArray database (mAdb) system. The one way ANOVA was applied using mAdb software for measurement of statistical significance in gene expression in CML. For mAdb hierarchical clustering we used uncentered correlation that applies a modified Pearson correlation equation. It is basically the same as the standard Pearson correlation function, except that it assumes the means are 0.
Results
Comparison of gene expression between CML subjects and controls in CD34+ cells and granulocytes
The t(9;22)(q34;q11) translocation was present in all CML subjects, with average of 2012 CD34+ cells / μl (SD±3158) and 56 × 109 / L granulocytes (SD±44) in peripheral blood. In controls, the average number was 3.1±1.4 CD34+ cells / μl, but through leukapheresis we separated 5.7 × 105 CD34+ cells per control subject. Within CML and control subjects the average correlation was high: CML −0.89; Controls −0.88 (Supplemental Table 1). Also, the average correlation coefficient was even higher among granulocytes: Controls – 0.93; CML – 0.94. Using Venn diagram we compared the total gene expression in CD34+ cells from control and CML subjects before and after 50 % filtration (Figure 1 A, B). The total gene expression in CD34+ CML cells revealed 6457 genes, while after filtration of 50 % the total gene expression was reduced to 3553 genes determined by microarray analysis (Figure 1 A, B). Before filtration, the total gene expression in granulocyte revealed 3947 genes, while after 50 % filtration this number declined to 2701 genes (Figure 1 C, D). Therefore, the total gene expression was almost doubled in CD34+ CML cells compared to granulocytes after 50 % filtration (Figure 1). The 64 genes overexpressed, more than 2-fold, exclusively in CML CD34+ cells are presented in Table 1. Among them, the genes with most prominent expression were DEFA1/3 and MPO (Table 1). Genes overexpressed exclusively in CML granulocytes more than 2 fold were lectin galactoside-binding soluble 16 (LGALS16), hyperpolarization activated cyclic nucleotide gated potassium channel 3 (HCN3), chemokine (C-C motif) ligand 13 (CCL13), hect domain and RLD 2 pseudogene 4 (HERC2P4), SRSF protein kinase 1 (SRPK1), tripartite motif containing 69 (TRIM69), G-protein signaling modulator 1 (GPSM1) and natriuretic peptide receptor 2 (NPR2).
Figure 1. Microarray study of gene expression in CD34+ cells and granulocytes from peripheral blood.
(A): The Venn diagram shows similarity of total gene expression between CML (N=7) and control (N=7) CD34+ cells. (B): The Venn diagram shows similarity of gene expression between CML and control CD34+ cells after 50 % filtration (C): The Venn diagram shows similarity of gene expression between CML and control granulocytes. (D): The Venn diagram shows similarity of gene expression between CML and control granulocytes after 50 % filtration.
Table 1.
Genes overexpressed exclusively in CML CD34+ cells more than 2 fold.
| Gene symbol | Description | Mean | SD |
|---|---|---|---|
| DEFA3 | defensin, alpha 3, neutrophil-specific | 6.38 | 0.30 |
| DEFA1 | defensin, alpha 1 | 6.35 | 0.30 |
| MPO | myeloperoxidase | 4.63 | 1.39 |
| HSH2D | hematopoietic SH2 domain containing | 3.96 | 0.24 |
| FBXO4 | F-box protein 4 | 3.65 | 0.47 |
| MLLT3 | myeloid/lymphoid or mixed-lineage leukemia | 3.47 | 0.42 |
| SRSF7 | serine/arginine-rich splicing factor 7 | 3.47 | 0.40 |
| CHST13 | carbohydrate (chondroitin 4) sulfotransferase 13 | 3.18 | 0.43 |
| ZNF180 | zinc finger protein 180 | 3.10 | 0.38 |
| LIMS1 | LIM and senescent cell antigen-like domains 1 | 2.96 | 0.34 |
| KCNH2 | potassium voltage-gated channel, subfamily H | 2.94 | 1.12 |
| PLAC8 | placenta-specific 8 | 2.90 | 0.79 |
| TRMT2B | tRNA methyltransferase 2 homolog B | 2.86 | 0.39 |
| HTRA3 | HtrA serine peptidase 3 | 2.84 | 0.95 |
| GFI1 | growth factor independent 1 transcription repressor | 2.83 | 1.10 |
| PHF14 | PHD finger protein 14 | 2.80 | 0.25 |
| USP38 | ubiquitin specific peptidase 38 | 2.79 | 0.30 |
| CASP6 | caspase 6, apoptosis-related cysteine peptidase | 2.73 | 0.25 |
| SLC39A8 | solute carrier family 39 (zinc transporter), member 8 | 2.72 | 0.57 |
| ERLIN1 | ER lipid raft associated 1 | 2.61 | 0.20 |
| CD33 | CD33 molecule | 2.59 | 0.56 |
| N4BP2L2 | NEDD4 binding protein 2-like 2 | 2.57 | 0.41 |
| CREB3L4 | cAMP responsive element binding protein 3-like 4 | 2.55 | 0.34 |
| RARRES3 | retinoic acid receptor responder | 2.52 | 0.44 |
| CASP3 | caspase 3, apoptosis-related cysteine peptidase | 2.52 | 0.59 |
| ASB8 | ankyrin repeat and SOCS box containing 8 | 2.51 | 0.33 |
| CPT2 | carnitine palmitoyltransferase 2 | 2.49 | 0.43 |
| MAGEH1 | melanoma antigen family H, 1 | 2.48 | 0.77 |
| SBNO1 | strawberry notch homolog 1 | 2.48 | 0.37 |
| CRBN | cereblon | 2.47 | 0.47 |
| TMEM69 | transmembrane protein 69 | 2.45 | 0.33 |
| KLF6 | Kruppel-like factor 6 | 2.43 | 0.35 |
| LSM10 | LSM10, U7 small nuclear RNA associated | 2.43 | 1.57 |
| DCUN1D1 | DCN1, defective in cullin neddylation 1, domain cont 1 | 2.37 | 0.33 |
| FAM175A | family with sequence similarity 175, member A | 2.36 | 0.36 |
| FBXW9 | F-box and WD repeat domain containing 9 | 2.34 | 0.79 |
| EEF1A1 | eukaryotic translation elongation factor 1 alpha 1 | 2.32 | 0.45 |
| EED | embryonic ectoderm development | 2.32 | 0.42 |
| AFF3 | AF4/FMR2 family, member 3 | 2.28 | 0.39 |
| OIP5 | Opa interacting protein 5 | 2.26 | 0.60 |
| THEM4 | thioesterase superfamily member 4 | 2.23 | 0.29 |
| UBE2V2 | ubiquitin-conjugating enzyme E2 variant 2 | 2.19 | 0.27 |
| MRPL19 | mitochondrial ribosomal protein L19 | 2.18 | 0.12 |
| XK | X-linked Kx blood group (McLeod syndrome) | 2.18 | 0.95 |
| ISY1 | ISY1 splicing factor homolog | 2.17 | 0.21 |
| MINPP1 | multiple inositol-polyphosphate phosphatase 1 | 2.16 | 0.53 |
| USP48 | ubiquitin specific peptidase 48 | 2.16 | 0.33 |
| PXMP2 | peroxisomal membrane protein 2, 22kDa | 2.14 | 0.39 |
| BCCIP | BRCA2 and CDKN1A interacting protein | 2.11 | 0.31 |
| ARMCX1 | armadillo repeat containing, X-linked 1 | 2.10 | 0.39 |
| CHEK1 | checkpoint kinase 1 | 2.08 | 0.53 |
| BDH2 | 3-hydroxybutyrate dehydrogenase, type 2 | 2.06 | 0.13 |
| SP100 | SP100 nuclear antigen | 2.06 | 0.07 |
| RNFT1 | ring finger protein, transmembrane 1 | 2.04 | 0.31 |
| SFXN4 | sideroflexin 4 | 2.04 | 0.23 |
| WDR5 | WD repeat domain 5 | 2.03 | 0.39 |
| WDR18 | WD repeat domain 18 | 2.03 | 0.35 |
| RNPC3 | RNA-binding region | 2.03 | 0.22 |
| CD3EAP | CD3e molecule, epsilon associated protein | 2.03 | 0.47 |
| BTN3A2 | butyrophilin, subfamily 3, member A2 | 2.02 | 0.60 |
| TMEM216 | transmembrane protein 216 | 2.02 | 0.49 |
| ETNK1 | ethanolamine kinase 1 | 2.01 | 0.30 |
| RPL34 | ribosomal protein L34 | 2.01 | 0.58 |
| ALKBH2 | alkB, alkylation repair homolog 2 | 2.00 | 0.23 |
Determination of significantly expressed genes in CD34+ cells and granulocytes of CML compared to control subjects
We previously mentioned that CML and control CD34+ cells shared 3553 common genes using Venn diagram (Figure 1 B). We compared these common genes by Student’s t-test, and defined the significantly upregulated 41 genes in CML versus control CD34+ cells (p<0.05) (Table 2). The most significantly upregulated genes, in favor of CD34+ CML cells, were HINT1, TXN, SERBP1 and RPL6 (Table 2). On the other hand, the most significantly downregulated genes in CML versus control CD34+ cells, with more than 2.5 fold difference in gene expression, were KCNQ1OT1, FREM2, PPP1R3F and MLLT4 (Table 3). Also, Student’s t-test determined significant genes, presented by hierarchical clustering to describe their relation (Figure 2). We also showed that granulocytes of CML subjects significantly expressed 39 genes in comparison to control subjects (Supplemental Table 2).
Table 2.
Significantly upregulated genes in CML versus control CD34+ cells, with more than 2 fold difference in gene expression.
| Symbol | Gene description | p value | Mean differ | Mean Contr | SD | Mean CML | SD |
|---|---|---|---|---|---|---|---|
| HINT1 | histidine triad nucleotide binding protein 1 | 2.5E-07 | 2.25 | 0.68 | 0.39 | 2.93 | 0.32 |
| TXN | thioredoxin | 2.1E-06 | 2.06 | −0.84 | 0.38 | 1.22 | 0.44 |
| SERBP1 | SERPINE1 mRNA binding protein 1 | 4.5E-06 | 2.10 | −0.09 | 0.34 | 1.93 | 0.39 |
| RPL6 | ribosomal protein L6 | 6.5E-06 | 2.15 | −1.08 | 0.44 | 1.07 | 0.42 |
| RPLP0 | ribosomal protein, large, P0 | 1.1E-05 | 2.49 | −1.72 | 0.49 | 0.77 | 0.46 |
| HSPA8 | heat shock 70kDa protein 8 | 1.1E-05 | 2.14 | −1.26 | 0.45 | 0.88 | 0.32 |
| RPS18 | ribosomal protein S18 | 1.2E-05 | 2.60 | −0.05 | 0.46 | 2.54 | 0.49 |
| GCSH | glycine cleavage system protein H | 1.4E-05 | 2.38 | −1.19 | 0.25 | 1.19 | 0.30 |
| H2AFZ | H2A histone family, member Z | 1.7E-05 | 2.03 | −1.47 | 0.42 | 0.56 | 0.40 |
| H2AFV | H2A histone family, member V | 1.8E-05 | 2.21 | 0.56 | 0.54 | 2.77 | 0.58 |
| C1QBP | Complement component 1, q subcomp. binding protein | 1.8E-05 | 2.54 | −1.56 | 0.40 | 0.98 | 0.53 |
| RPS12 | Ribosomal protein S12 | 2.0E-05 | 2.13 | −1.09 | 0.36 | 1.04 | 0.48 |
| HNRNPA1 | heterogeneous nuclear ribonucleoprotein A1 | 3.4E-05 | 2.21 | 0.94 | 0.58 | 3.16 | 0.34 |
| RPLP1 | Ribosomal protein, large, P1 | 5.5E-05 | 2.20 | −1.12 | 0.44 | 1.08 | 0.48 |
| HIST1H4C | histone cluster 1, H4c | 6.2E-05 | 2.47 | 0.06 | 0.49 | 2.78 | 0.69 |
| PPA1 | pyrophosphatase (inorganic) 1 | 6.5E-05 | 2.16 | −0.66 | 0.46 | 1.50 | 0.53 |
| NDUFA8 | NADH dehydrogenase 1α subcomplex, 8, 19kDa | 6.5E-05 | 2.41 | 0.01 | 0.17 | 2.27 | 0.39 |
| METTL5 | methyltransferase like 5 | 7.1E-05 | 2.05 | −0.50 | 0.18 | 1.36 | 0.32 |
| TFDP1 | transcription factor Dp-1 | 7.3E-05 | 2.19 | −0.31 | 0.24 | 1.94 | 0.49 |
| EEF1B2 | eukaryotic translation elongation factor 1β2 | 7.6E-05 | 2.27 | 0.12 | 0.65 | 2.39 | 0.35 |
| HMGN2 | high mobility group nucleosomal bind domain 2 | 8.8E-05 | 2.41 | −1.06 | 0.29 | 1.35 | 0.58 |
| RPL6 | ribosomal protein L6 | 0.0002 | 2.00 | 0.39 | 0.69 | 2.39 | 0.56 |
| RPL7 | ribosomal protein L7 | 0.0003 | 2.00 | 0.13 | 0.60 | 2.13 | 0.55 |
| DEK | DEK oncogene | 0.0003 | 2.06 | −0.30 | 0.60 | 1.76 | 0.51 |
| SNRPE | small nuclear ribonucleoprotein polypept E | 0.0003 | 2.10 | −0.99 | 0.54 | 1.11 | 0.25 |
| RPL26 | ribosomal protein L26 | 0.0004 | 2.04 | −1.09 | 0.69 | 0.95 | 0.30 |
| NUCB2 | nucleobindin 2 | 0.0004 | 2.27 | −0.38 | 0.10 | 1.63 | 0.42 |
| RPSAP58 | Ribosomal protein SA pseudogene 58 | 0.0005 | 2.06 | −1.23 | 0.63 | 0.83 | 0.20 |
| TMEM14B | transmembrane protein 14B | 0.0006 | 2.14 | −0.89 | 0.68 | 1.25 | 0.41 |
| MRPL1 | mitochondrial ribosomal protein L1 | 0.0006 | 2.25 | 0.97 | 0.12 | 2.90 | 0.41 |
| RPS3A | ribosomal protein S3A | 0.0009 | 2.11 | −0.78 | 0.96 | 1.33 | 0.28 |
| TTC27 | tetratricopeptide repeat domain 27 | 0.0016 | 2.19 | 0.97 | 0.28 | 3.08 | 0.52 |
| CCT2 | chaperonin containing TCP1, subunit 2 | 0.0017 | 2.13 | 0.23 | 0.62 | 2.17 | 0.46 |
| FABP5 | fatty acid binding protein 5 | 0.0017 | 2.14 | −0.37 | 0.22 | 1.69 | 0.53 |
| RPS2 | ribosomal protein S2 | 0.0026 | 2.40 | −0.32 | 1.25 | 2.08 | 0.43 |
| RPS3A | ribosomal protein S3A | 0.0030 | 2.08 | −0.07 | 0.94 | 2.01 | 0.50 |
| SOCS2 | suppressor of cytokine signaling 2 | 0.0030 | 2.07 | 1.10 | 0.34 | 2.96 | 0.58 |
| MCM5 | minichromosome maintenance complex comp 5 | 0.0032 | 2.04 | 0.37 | 0.11 | 2.55 | 0.29 |
| RPS3A | ribosomal protein S3A | 0.0047 | 2.79 | 0.68 | 1.67 | 3.47 | 0.70 |
| BRP44 | brain protein 44 | 0.0060 | 2.12 | 0.71 | 0.14 | 2.52 | 0.59 |
| RPL7 | ribosomal protein L7 | 0.0065 | 2.04 | 0.25 | 1.16 | 2.29 | 0.40 |
Table 3.
Significantly downregulated genes in CML versus control CD34+ cells, with more than 2.5 fold difference in gene expression.
| Symbol | Gene description | p value | Mean differ | Mean Contr | SD | Mean CML | SD |
|---|---|---|---|---|---|---|---|
| KCNQ1OT1 | KCNQ1 opposite strand/antisense | 5.3E-05 | 3.71 | 3.63 | 0.42 | −0.08 | 0.61 |
| FREM2 | FRAS1 related extracellular matrix protein 2 | 0.0002 | 3.66 | 3.22 | 0.79 | −0.43 | 0.88 |
| PPP1R3F | Protein phosphatase 1, regul. subunit 3F | 0.0003 | 3.60 | 4.35 | 0.67 | 0.75 | 0.67 |
| MLLT4 | Myeloid/lymphoid mixed-lineage leukemia | 0.0004 | 3.56 | 3.88 | 0.73 | 0.32 | 0.96 |
| ASTN2 | astrotactin 2 | 0.0001 | 3.45 | 4.05 | 0.61 | 0.60 | 0.79 |
| BNIP3L | BCL2/adenovirus E1B interact protein 3-like | 0.0002 | 3.41 | 2.85 | 0.88 | −0.56 | 0.72 |
| CDRT1 | CMT1A duplicated region | 0.0055 | 3.40 | 2.51 | 1.04 | −0.94 | 1.79 |
| HSP90AB2P | heat shock protein 90kDa alpha | 0.0002 | 3.24 | 3.70 | 0.61 | 0.46 | 0.85 |
| PGM5P2 | phosphoglucomutase 5 pseudogene 2 | 0.0001 | 3.23 | 3.39 | 0.66 | 0.16 | 0.65 |
| ORC4 | origin recognition complex, sub 4 | 0.0002 | 3.21 | 3.55 | 0.68 | 0.34 | 0.80 |
| MIPOL1 | Mirror-image polydactyly 1 | 0.0004 | 3.17 | 2.90 | 0.98 | −0.27 | 0.87 |
| LRP6 | low density lipoprotein receptor-related protein 6 | 0.0010 | 3.16 | 1.98 | 0.78 | −1.18 | 1.14 |
| SERPINB9 | serpin peptidase inhibitor, clade B | 0.0004 | 3.07 | 2.86 | 0.76 | −0.21 | 0.47 |
| CFLAR | CASP8 and FADD-like apoptosis regulator | 0.0021 | 2.95 | 2.19 | 0.92 | −0.86 | 0.94 |
| MALAT1 | metastasis associated lung adenocarcinoma | 0.0061 | 2.79 | 1.85 | 2.01 | −0.86 | 1.80 |
| PRR20A | proline rich 20A | 0.0019 | 2.75 | 2.81 | 0.84 | 0.07 | 0.55 |
| CDKN2B | cyclin-dependent kinase inhibitor 2B | 0.0022 | 2.72 | 1.04 | 0.63 | −1.66 | 0.96 |
| UGT2B15 | UDP glucuronosyltransferase 2 family B15 | 0.0003 | 2.71 | 1.88 | 0.64 | −0.83 | 0.54 |
| CCDC144B | coiled-coil domain containing 144B | 0.0087 | 2.69 | 3.19 | 0.41 | 0.55 | 0.72 |
| RFX4 | Regulatory factor X, 4 | 2.5E-05 | 2.60 | 1.48 | 0.49 | −1.12 | 0.52 |
| ID2 | inhibitor of DNA binding 2 | 0.0006 | 2.60 | 1.69 | 0.39 | −0.78 | 0.66 |
| GZMM | granzyme M (lymphocyte met-ase 1) | 0.0018 | 2.55 | 0.25 | 0.43 | −2.31 | 0.44 |
| ZNF215 | Zinc finger protein 215 | 0.0001 | 2.55 | 1.33 | 0.47 | −1.22 | 0.65 |
| SLC19A3 | solute carrier family 19, member 3 | 0.0003 | 2.51 | 2.26 | 0.66 | −0.25 | 0.52 |
Figure 2. Hierarchical clustering of genes expressed in CML and control CD34+ cells.
Hierarchical clustering of statistically significant different (p<0.05) gene expression, between CML and control CD34+ cells, determined by Student’s t-test. The color indicates the relative fold expression of each gene: red indicates increased expression, green negative expression, black not changed expression, while gray stands for absent expression per each examined sample. The total gene expression of CML and control CD34+ cells is also clustered (upper image), representing similarities among examined cells. The genes and arrays correlations are uncentered. The gene description is provided in Table 3.
Signaling pathways and related gene expression affected by CML
Significantly upregulated expression of E2F1, NFKBIA, TGFBR2 and KRAS in control subjects versus CML subjects was determined (Figure 3A, Table 4), while significantly upregulated genes in CML subjects were PTPN11, CTBP2, CDK4, CDK6 and MYC in CD34+ cells (Figure 3B, Table 4). The genes expressed only in CML subjects, in comparison to control (absent or sporadic), were E2F3, NFKB1 and MAPK1 (Figure 3C, Table 4). Regarding imatinib inhibition related genes, the FOS and STAT1 genes were significantly decreased (p<0.01) in CML compared to control subjects (Figure 3D). PI3K/AKT and MAPK signaling pathways, affected by BCR-ABL mutation, promoted the CD34+ cells proliferation and survival, while TGF-β signaling affected a growth of CD34+ cells (Figure 4). Significantly upregulated genes were PTPN11, CDK4/6 and MYC, while KRAS, NFKBIA, and FOS were downregulated in CD34+ cells (Figure 4, Table 4). RUNX1 gene expression was upregulated both in CD34+ cells and granulocytes of CML and controls (Table 4, Supplemental Table 2). RAF1 gene expression, as part of MAPK signaling pathway, was upregulated both in CD34+ cells and granulocytes of CML subjects (Table 4, Supplemental Table 2).
Figure 3. BCR-ABL activated gene expression profile in CD34+ cells of CML.
(A): Upregulated genes in controls. (B): Upregulated genes in CML. (C): Genes expressed only in CML. (D): Inhibition of cellular proliferation after Imatinib therapy.
Table 4.
BCR-ABL activated signaling pathway related genes in CD34+ cells of CML and healthy controls origin.
| Symbol | Gene description | p value | Mean differ | Mean Contr | SD | Mean CML | SD |
|---|---|---|---|---|---|---|---|
| AKT2 | v-akt murine thymoma viral oncogene homolog 2 | 0.87 | 0.18 | 0.55 | 0.68 | ||
| CBL | Cbl proto-oncogene, E3 ubiquitin protein ligase | 0.52 | 0.43 | 0.34 | 0.42 | ||
| CDK4 | cyclin-dependent kinase 4 | 0.02 | −1.58 | −1.06 | 0.29 | 0.08 | 0.50 |
| CDK6 | cyclin-dependent kinase 6 | 0.003 | −1.42 | 0.42 | 0.63 | 1.88 | 0.47 |
| CDKN1A | cyclin-dependent kinase inhibitor 1A | 2.66 | 0.69 | ||||
| CDKN1B | cyclin-dependent kinase inhibitor 1B | 0.87 | 0.9 | 1.23 | 0.31 | ||
| CRK | v-crk sarcoma virus CT10 oncogene homolog | 1.5 | 0 | −0.08 | 0.42 | ||
| CTBP1 | C-terminal binding protein 1 | −0.42 | 0 | 0.23 | 1.09 | ||
| CTBP2 | C-terminal binding protein 2 | 0.007 | −1.08 | 0.03 | 0.31 | 1.01 | 0.27 |
| E2F1 | E2F transcription factor 1 | 0.03 | 2.00 | 0.19 | 0.69 | −2.18 | 0.44 |
| E2F3 | E2F transcription factor 3 | 0.65 | 0 | 1.06 | 0.74 | ||
| FOS | FBJ murine osteosarcoma viral oncogene homolog | 0.007 | 1.79 | 2.46 | 0.87 | 0.42 | 1.16 |
| GRB2 | growth factor receptor-bound protein 2 | 1.8 | 0.19 | ||||
| HDAC1 | histone deacetylase 1 | 0.26 | 0.21 | ||||
| HDAC2 | histone deacetylase 2 | −0.5 | 0.14 | ||||
| KRAS | v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog | 0.003 | 1.06 | 1.4 | 0.51 | 0.34 | 0.31 |
| MAP2K1 | mitogen-activated protein kinase kinase 1 | 0.8 | 0 | 0.46 | 0.57 | ||
| MAPK1 | mitogen-activated protein kinase 1 | 0.64 | 0.18 | ||||
| MYC | v-myc myelocytomatosis viral oncogene homolog | 0.018 | −2.93 | −2.0 | 0.27 | 0.29 | 0.85 |
| NFKB1 | nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 | 0.57 | 0 | 0.97 | 0.30 | ||
| NFKBIA | nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, α | 0.02 | 1.95 | 4.31 | 0.72 | 2.36 | 1.21 |
| PIK3CB | phosphoinositide-3-kinase, catalytic, β polypeptide | 1.18 | 0.13 | ||||
| PIK3R1 | phosphoinositide-3-kinase, regulatory subunit 1 | 0.72 | 0 | 1.34 | 0.02 | ||
| PTPN11 | protein tyrosine phosphatase, non-receptor type 11 | 0.04 | −1.14 | 0.45 | 0.46 | 1.46 | 0.43 |
| RAF1 | v-raf-1 murine leukemia viral oncogene homolog 1 | 2.06 | 0 | 1.66 | 0.32 | ||
| RUNX1 | runt-related transcription factor 1 | 4.47 | 1.1 | 4.15 | 0.56 | ||
| STAT1 | signal transducer and activator of transcription 1 | 0.003 | 1.30 | 3.6 | 0.55 | 2.22 | 0.36 |
| STAT5A | signal transducer and activator of transcription 5A | 1.32 | 0.24 | 1.10 | 0.57 | ||
| TGFBR1 | transforming growth factor, β receptor 1 | 0.6 | 0.23 | ||||
| TGFBR2 | transforming growth factor, β receptor II | 0.023 | 0.48 | 1.67 | 0.18 | 1.20 | 0.14 |
Figure 4. BCR-ABL activated signaling pathways in CD34+ cells of CML origin.
(+p) phosphorylation; → stimulation, ⊥ inhibition; dotted lines define gene function; bolded gene symbols in empty boxes represent downregulated genes, while in gray boxes represent upregulated genes in CML vs. controls (corresponding to Table 4). Non bolded gene symbols in empty boxes represent unexpressed or sporadically expressed genes. Red bolded gene symbols represent significantly different genes in CML vs. controls.
Discussion
The results of microarray study showed that the total gene expression of CD34+ cells and granulocytes revealed 3553 and 2701 genes, respectively in CML. The genes with the most prominent expression in CD34+ cells were DEFA1/3, MPO, HSH2D, FBXO4, MLLT3, SRSF7, CHST13 and ZNF180, with induction more than 3 times. The genes overexpressed exclusively in CML granulocytes were LGALS16, HCN3, CCL13, HERC2P4, SRPK1, TRIM69, GPSM1 and NPR2. Significantly downregulated genes in CML CD34+ cells, with more than 2.5 fold difference in gene expression, were KCNQ1OT1, FREM2, PPP1R3F and MLLT4. PI3K/AKT and MAPK signaling pathways related genes were affected by BCR-ABL mutation, as well as TGF-β signaling. The significant difference was observed for NFKBIA and CDK4/6 genes in PI3K/AKT activated signaling for cell proliferation, for PTPN11, KRAS and FOS genes in MAPK signaling, and for TGFβR1/2 and CTBP2 genes within TGF-β signaling in CD34+ cells of CML subjects.
Previous microarray studies of chronic phase CML subjects analyzed mononuclear cells in bone marrow [1,11,13] and peripheral blood [14], as well as CD34+ progenitors in bone marrow [4,5,15] and peripheral blood [6,9,10]. Also, comparative microarray analyses were performed in blast phase CML subjects [9–11]. We combined simultaneous microarray analyses of CD34+ cells and granulocytes from peripheral blood of chronic phase CML subjects. Comparing the controls and CML CD34+ cells we found that 64 genes were overexpressed exclusively in CML CD34+ cells more than 2 fold. Their products are involved in regulation of different cellular functions including cell cycle (WDR5, WDR18), apoptosis (CASP3, CASP6), tumor suppression (ARMCX1), and regulation of transcription (ZNF180). Expanded microarray analysis of granulocytes revealed a significant difference in expression pattern of 39 genes between CML and healthy donors. In contrast to presented DEFA1 and DEFA3 upregulated gene expression in CD34+ cells of chronic phase CML subjects, genes responsible for anti-pathogen response (DEFA1, DEFA3, DEFA4) were downregulated in blast phase CML cells [13].
The largest difference between chronic phase CML subjects and normal donors were obvious in CD34+ cells, including downregulation of genes encoding inhibitors of cell proliferation in chronic phase CML [15]. Among genes linked to inhibition of cellular proliferation by Gleevec: STAT1 and FOS had significantly decreased expression in CML, whereas MAP2K1 and RAF1 had very similar level of expression in CML and controls. The following genes CDK4, CDK6, MYC, CTBP2, and PTPN11 had increased expression and NFKBIA, E2F1, KRAS and TGFBR2 genes had reduced expression in CML-associated genes of CD34+ cells. Extracellular-regulated kinase (ERK) was significantly upregulated in primary BCR-ABL-positive cells (MAPK1). Regarding genes involved in the PI3K pathway, its substrate AKT and the downstream molecules NFκB and Bcl-xl were significantly upregulated in CML CD34+ cells [4]. According to our data, AKT and Bcl-xl had decreased expression while NFKB1 had increased expression in CML CD34+ cells, but no significant difference was observed. Moreover, the upregulation has been reported in CD34+ compartment of proteins within the STAT pathway and MYC, and downregulation of MDM2, MEK, AKT and NFκB proteins [16]. It has been reported that the BCR-ABL adapter protein CRKL has also been upregulated in CML CD34+ cells, but not in our results at mRNA level. Within the TGFβ signaling pathway, other report has shown that TGFβ1 itself as well as SMAD2 and SMAD4 were significantly upregulated in CML CD34+ cells, in contrast to our results [4].
The bone marrow CD34+ cells expressed 9 cell cycle driving genes at particularly higher levels than circulating CD34+ cells [17]. According to those results cycling activity of bone marrow CD34+ cells was higher than in peripheral blood CD34+ cells. We found a significant downregulation of FOS in CML CD34+ cells. FOS had a role in growth suppression and apoptosis of many cell types. Therefore, down regulation of FOS might be liable for increased proliferation of CML CD34+ cells [5]. In accordance to our results, the upregulation of CDK4 gene expression has been reported n CML, as a gene involved in cell cycle [13]. Upregulation of the E2F1 transcription factor lead to a molecular mechanism that initiated the proliferation of hematopoietic stem and progenitor cells [17]. The cell cycle–initiating transcription factor E2F1, that promoted cell cycle progression, showed higher expression in bone marrow CD34+ cells than in peripheral blood CD34+ cells [18]. In our study, E2F1 gene expression was downregulated in CML CD34+ cell compared to control CD34+ cells.
Results of this study highlighted the difference in gene expression between primitive and mature cells of CML and control subjects, with the accent on the CD34+ cells that direct the pathogenic course of malignancy. Presence of BCR-ABL fusion gene significantly modified the observed genes in PI3K/AKT, MAPK and TGF-β signaling pathways, enhancing its influence on CD34+ cells proliferation, apoptosis and cell growth.
Supplementary Material
Acknowledgments
This research was supported by Intramural Research Program of Alan N. Schechter at the National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, and by a grant from the Serbian Ministry of Education and Science [No. 175053].
Footnotes
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