• refractory anaemia with ring sideroblasts;
  • gene expression profiling;
  • pathway analyses;
  • ABCB7;
  • MFN2


  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Refractory anaemia with ring sideroblasts (RARS) is characterized by anaemia, erythroid apoptosis, cytochrome c release and mitochondrial ferritin accumulation. Granulocyte-colony-stimulating factor (G-CSF) inhibits the first three of these features in vitro and in vivo. To dissect the molecular mechanisms underlying the RARS phenotype and anti-apoptotic effects of G-CSF, erythroblasts generated from normal (NBM) and RARS marrow CD34+ cells were cultured ±G-CSF and subjected to gene expression analysis (GEP). Several erythropoiesis-associated genes that were deregulated in RARS CD34+ cells showed normal expression in erythroblasts, underscoring the importance of differentiation-specific GEP. RARS erythroblasts showed a marked deregulation of several pathways including apoptosis, DNA damage repair, mitochondrial function and the JAK/Stat pathway. ABCB7, transporting iron from mitochondria to cytosol and associated with inherited ring sideroblast formation was severely suppressed and expression decreased with differentiation, while increasing in NBM cultures. The same pattern was observed for the mitochondrial integrity gene MFN2. Other downregulated key genes included STAT5B, HSPA5, FANCC and the negative apoptosis regulator MAP3K7. Methylation status of key downregulated genes was normal. The mitochondrial pathway including MFN2 was significantly modified by G-CSF, and several heat shock protein genes were upregulated, as evidence of anti-apoptotic protection of erythropoiesis. By contrast, G-CSF had no effect on iron-transport or erythropoiesis-associated genes.

Myelodysplastic syndromes (MDS) are clonal haematological disorders characterized by defects in the haemopoietic stem cell compartment resulting in failure of one or more of the cell lineages. The World Health Organization (WHO) subtype refractory anaemia with ring sideroblasts (RARS) presents with isolated anaemia, hyperplastic ineffective erythropoesis, hypochromic erythrocytes, and presence of mitochondrial accumulation of mitochondrial ferritin in erythroblasts. According to the WHO classification, RARS and refractory cytopenia with multilineage dysplasia and ring sideroblasts (RCMD-RS) are defined by the presence of more than 15% ringed sideroblasts and <5% myeloblasts in bone marrow with an isolated erythroid versus a multilinage dysplasia, respectively (Jaffe et al, 2001; Swerdlow et al, 2008). The risk of transformation to acute myeloid leukaemia from RARS is very low, and from (RCMD-RS) around 9% (Germing et al, 2000).

We have previously shown that mitochondria in RARS erythroblasts constitutively release cytochrome c from the mitochondrial intermembrane space (Cazzola et al, 2003; Tehranchi et al, 2003, 2005). The molecular basis for the abnormal iron accumulation, defect mitochondrial function and ineffective haem biosynthesis in RARS remains unknown. We recently identified the ABCB7 gene as a candidate gene for sideroblast formation in RARS because of its low expression levels in CD34+ RARS cells, and by the analogy of RARS with the hereditary syndrome X-linked sideroblastic anaemia with ataxia (XLSA-A), in which ABCB7 is mutated (Boultwood et al, 2008). However, no mutations have been detected in acquired RARS (Steensma et al, 2007; Boultwood et al, 2008).

Chronic transfusion need of RARS (Bennett et al, 1982; Greenberg et al, 1997) may respond to treatment with Erythropoietin (Epo) alone or in combination with granulocyte colony-stimulating factor (G-CSF). The synergistic effect of the addition of G-CSF is more pronounced in RARS than in other subgroups of low-risk MDS (Hellstrom-Lindberg et al, 1998; Jadersten et al, 2005). In a series of studies we showed that G-CSF strongly inhibited apoptosis in differentiating RARS erythroblasts in vitro as well as in vivo, through a marked inhibition of mitochondrial cytochrome c release and subsequent decrease in caspase-9 and caspase-3 activity (Schmidt-Mende et al, 2001; Tehranchi et al, 2003, 2005). By contrast, G-CSF did not affect the accumulation of mitochondrial ferritin at any measured time point of differentiation (Tehranchi et al, 2005).

There are several reports on gene expression profiling of purified CD34+ fractions obtained from the bone marrow of patients with MDS (Hofmann et al, 2002; Chen et al, 2004; Sternberg et al, 2005; Pellagatti et al, 2006). We recently demonstrated that the expression profile of MDS CD34+ cells, particularly RARS cells, show similarities to γ-interferon (IFN-γ)-induced gene expression in CD34+ cells from healthy individuals. Moreover, altered expressions of haem biosynthesis and mitochondrial genes were reported (Pellagatti et al, 2006). The CD34 compartment of MDS bone marrow is, however, heterogeneous and may reflect a different mix of progenitors depending on marrow blast percentage and degree of erythroid hypo vs. hyperplasia. To specifically address the abnormalities in differentiating erythroblasts we performed gene expression profiling on cultured RARS and normal erythroid progenitors at an intermediate maturation level, with a specific focus on genes involved in erythropoiesis, apoptosis, iron metabolism/transport and mitochondrial function. We also analysed the effects of G-CSF on gene expression to further understand its anti-apoptotic role in RARS erythropoiesis.

Materials and methods

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information


The diagnostic procedure was performed according to the WHO 2008 classification (Swerdlow et al, 2008) and routines reported by the Nordic MDS Group (Jadersten et al, 2005). Informed consent was obtained from patients and controls, and the study followed the guidelines of the ethical committee for research at Karolinska Institute and the Declaration of Helsinki. Seven patients with either RARS (n = 3) or refractory cytopenia with multilineage dysplasia and ringed sideroblasts (RCMD-RS) (n = 4) with a median age of 75 years were included. Four were transfusion-dependent and three had a stable anaemia at the time of sampling. There were no major differences in clinical presentation between the two WHO subgroups. Five patients had a normal karyotype, one 46XY,del(13q) and one had 46,XY[23]/47,XY,+8[2]. Bone marrow (NBM) samples from six healthy individuals (four females and two males) with a median age of 54 years were used as controls. In addition, a larger cohort of RARS and RCMD-RS (n = 19) and normal controls (n = 10) were assessed for methylation status of identified candidate genes.

CD34+ cell separation and erythroblast cultivation

Bone marrow mononuclear cells were isolated by using Lymphoprep (Axis-Shield, Oslo, Norway) density gradient within 1 h from aspiration, and CD34+ cells were positively selected using a magnetic-activated cell sorting (MACS) labelling system (Miltenyi Biotec, Bergisch Gladbach, Germany) according to the manufacturers’ protocols. The purity of CD34+cells isolated with this system was assessed at regular intervals and shown to be above 95% (Tehranchi et al, 2003). Following separation, CD34+ cells were cultured (0·1 × 106/ml) for 14 d in Iscove’s medium supplemented with 15% BIT9500 serum substitute (containing bovine serum albumin, bovine pancreatic insulin and iron/saturated human transferrin and recombinant human interleukin (rh-IL)-3 (10 ng/ml), rh-IL-6 (10 ng/ml), rh-stem cell factor (rh-SCF; 25 ng/ml), 1% penicillin and streptomycin and 1%l-glutamine. Epo (2 iu/ml) was added to the medium at day 7, and fresh medium supplemented as above (plus Epo) was added at day 9 and 11. We used cells obtained at day 7 of culture, in order to compare gene expression profiling with previous extensive cell biological studies on this cell cohort. Phenotype and erythroid maturation of cells was, as previously validated and reported, analysed at day 4, 7 and 14 using CD36 and glycophorin A (GpA) antibodies. At day 4, 42% of cells were CD34+ CD36, while 24% were CD34+ CD36+ and 12% were positive only for CD36 (median values). At day 7, 22% were CD34+ CD36, 14% were CD34+ CD36+, 26% CD36+ and 5% CD36+ GpA+. At day 14, the median percentages of CD36+ and GpA+ cells were 92% and 77%, respectively (Tehranchi et al, 2003, 2005).

At day 7, an aliquot of cells were treated with 100 ng/ml G-CSF (Neupogen; Amgen, Twelve Oaks, CA, USA) for 4 h, e.g. the same concentration and exposure time that were used in previous experiments (Tehranchi et al, 2003, 2005).

Total RNA extraction

Total RNA from cultured erythroid progenitors at day 7 (untreated and G-CSF-treated cells from RARS patients and healthy controls) was extracted using TRIZOL (Invitrogen, Paisley, UK) following the protocol supplied by the manufacturer. RNA yields were determined spectrophotometrically at 260 nm and RNA integrity assayed using Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA, USA).

HUMARA analysis

Clonality of cultured erythroblasts was evaluated through the study of the X-Chromosome Inactivation Pattern (XCIP) by both DNA methylation and differential allelic expression analysis of the HUMARA (human androgen receptor) gene after 7 d of culture. DNA methylation status analysis was performed as previously described (Tonon et al, 1998). The expression clonality assay was based on a nested primer RT-PCR as reported by Busque et al (1994). Amplified bands were subjected to density analysis by Molecular Imager FX software (Bio-Rad laboratories, Hercules, CA, USA).

Affymetrix experiments

Extracted total RNA (50 ng for each sample) was amplified and labelled with the 2-Cycle cDNA Synthesis and the 2-Cycle Target Labelling and Control Reagent packages (Affymetrix, Santa Clara, CA, USA) following the manufacturer’s recommendations. Labelled fragmented cRNA (10 μg) was hybridized to oligonucleotide probes on an Affymetrix Human Genome U133 Plus 2.0 GeneChip, containing 54 675 probe sets representing approximately 39 000 human genes. Hybridization occurred for 16 h at 45°C with constant rotation at 60 rpm. Washing was carried out in accordance with the manufacturer’s instruction on the GeneChip Fluidics Station 450, and the arrays were scanned using a GeneChip Scanner 3000 (Affymetrix).

Data analysis

Scanned GeneChip images were processed using GeneChip Operating Software (GCOS). Data analysis was performed by GeneSpring 7.3 (Agilent Technologies). Quality control was performed within the GCOS software after scaling the signal intensities of all arrays to a target of 100. Scale factors, background levels, percentage of present calls, 3′/5′GAPDH ratio and intensities of spike hybridization controls were within the acceptable range for all samples. Affymetrix CEL files were uploaded and pre-processed using Robust MultiChip Analysis (RMA) (Irizarry et al, 2003). Differentially expressed genes (t-test, P < 0·05, Benjamini–Hochberg multiple testing correction) between conditions were identified using GeneSpring and used for pathway analysis using Ingenuity 5.0. Hierarchical clustering was performed with GeneSpring software using Pearson correlation.

Quantitative real-time RT-PCR

For confirmation of microarray results, real-time quantitative polymerase chain reaction (QRT-PCR) was performed for selected genes. We selected the five most deregulated probe sets in patients compared to normal erythroblasts (sorted according to P-value) including NSMCE4A, UQCC, ABCB7, ITFG1 and DNAJA2 as well as five genes with potential role in RARS pathogenesis or potential mechanism of G-CSF effect including MAP3K7, MFN2, HSPA1B, FANCC and FOXO3.

The expression level of the housekeeping gene GAPDH was used to normalize for differences in input cDNA. RT- PCR was carried out using TaqMan gene expression pre-synthesized reagents and master mix (Applied Biosystems, Foster City, CA, USA) in 7500 Real-Time PCR system (Applied Biosystems). The expression ratio was calculated using the ΔΔCT method (Livak & Schmittgen, 2001).

Western blotting

Cells were lysed with lysis buffer (Complete Lysis-M; Roche, Mannheim, Germany). Total protein concentration was determined using the BCA Protein Assay kit (Uptima-Interchim, Montluçon, France). Twenty-five micrograms of total protein was separated on a 7·5–10% acrylamide gel and transferred to nitrocellulose membrane. Membranes were probed with antibodies that recognize HSPA1B (Abcam, Cambridge, UK), MFN2 (Abcam) and GAPDH (Abcam). After incubation with appropriate secondary antibodies, specific proteins were detected using enhanced chemiluminesence reagents (Amersham Bioscience, GE Healthcare, Uppsala, Sweden).

DNA extraction and bisulfite modification

Genomic DNA was extracted from myeloid cell fractions from 19 patents and 10 healthy individuals using Gene Elute mammalian genomic extraction kit (Sigma, St Louis, MO, USA) according to the manufacturer’s instructions. Bisulfite modification of genomic DNA was carried out using EZ DNA methylation Gold™ kit (ZYMO research, Orange, CA, USA) following standard protocol. Epi-Tect® PCR control DNA set (Qiagen, Solna, Sweden) was used as methylated and unmethylated DNA controls for all PCR reactions.

Melting curve analysis-Methylation assay (MCA-Meth)

MCA-Meth was performed as described by Lorente et al (2008). Briefly, 20 ng of bisulfite-modified DNA was amplified in a total volume of 20 μl PCR mix, containing 10 μl of 2× SYBR Green master mix (Applied Biosystems) and 5 pmol of forward and reverse primers. Primers for ABCB7, MFN2, FANCC and FOXO3 were designed using Methprimer software (Li & Dahiya, 2002).

The cycling program was 95°C for 10 min, following by 40 cycles of 30 s at 94°C, 30 s at corresponding annealing temperatures (Table SI) and 30 s at 72°C. Melting curve analysis was performed from 60 to 95°C. Both amplification reaction and melting curve analysis were carried out using an ABI 7500 FAST real time PCR system (Applied Biosystems).


  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

RARS erythroblasts are clonal

We investigated the clonality of cultured day 7 erythroblasts from five female patients with RARS through X-chromosome inactivation pattern, using both DNA methylation- and allelic expression-based approaches. At day 7, all samples showed a skewed XCIP (corrected allelic ratios: 4·28, 5·62, 8·19 and complete inactivation of one allele in two cases), indicative of a clonal erythroid progenitor population. Three of these were also analysed at the start of culture (CD34+ cells), and all showed skewed XCIP (corrected allelic ratios: 18·41 and complete inactivation of one allele in two cases) (data not shown).

Differentially expressed genes in RARS and normal erythroblasts

Six thousand two hundred and twenty-eight probe sets were significantly different between day 7 RARS and normal erythroblasts. From these, 3960 probe sets were up- and 2268 probe sets were downregulated. Table I shows the 10 most up- and downregulated probe sets, sorted according to P-value, in RARS compared to normal erythroblasts (category A). Table I also lists deregulated genes specifically involved in iron metabolism, haematopoiesis and apoptosis (category B), even if they did not fall within the top 10 genes, as well as marking the genes significantly altered by G-CSF. Genes included in both categories or affected by G-CSF were of particular interest. In addition the 50 most deregulated probe sets, sorted only according to P-value, are presented in Table SII. The most deregulated gene in RARS compared to normal erythroblasts was NSMCE4A, which was downregulated. NSMCE4A mutant yeast displays genome instability and hypersensitivity to DNA damage (Hu et al, 2005). PCR confirmed deregulation of 9 of the 10 selected genes (selected data shown in Figs 1–3).

Table I.   List of upregulated (a) and downregulated (b) probe sets in RARS erythroblasts compared to normal erythroblasts. Thumbnail image of

Figure 1. ABCB7 expression level in intermediate (day 7) erythroblasts by (A) microarray analysis and (B) RT-PCR (seven RARS and six normal samples); (C) ABCB7 expression level in differentiating RARS and normal erythroblasts, with ABCB7 expression normalized to that of day 0 healthy controls (results shown as mean ± SD) (three RARS and normal samples); (D) Analysis of ABCB7 promoter methylation by MCA-Meth. Melting temperature of the amplified fragment (274 bp) was determined as described in materials and methods. Results from 19 RARS patients and 10 healthy donors plus unmethylated, 50% methylated and 100% methylated controls are presented. Female samples from RARS as well as normal bone marrow showed both unmethylated and methylated peaks.

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Figure 2.  (A) MFN2 expression level by microarray analysis in intermediate (day 7) RARS and normal erythroblasts ± G-CSF (seven RARS and six normal samples); (B) MFN2 expression level in differentiating RARS and normal erythroblasts, with MFN2 expression normalized to that of day 0 healthy controls (results shown as mean ± SD) (three RARS and normal samples); (C) MFN2 protein level in representative RARS and normal cultures, with and without G-CSF treatment (2 RARS and normal samples); (D) MFN2 expression level by RT-PCR in day 7 RARS erythroblasts ± G-CSF (seven RARS and six normal samples). (E) Analysis of MFN2 promoter methylation by MCA-Meth. Melting temperature of the amplified fragment (183 bp) was determined by 7500F real time PCR system. Results from 19 RARS patients and 10 healthy donors are presented. Methylation was not observed in either group. The two methylated peaks are 50% and 100% methylated DNA controls.

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Figure 3. HSPA1B expression level by (A) microarray and (B) RT-PCR in intermediate (day 7) RARS and normal erythroblasts ± G-CSF (seven RARS and six normal samples); (C) HSPA1B protein level in two representative RARS cultures, with and without G-CSF treatment.

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Deregulation of genes involved in cellular iron metabolism and mitochondrial function increases during differentiation

We previously showed that ABCB7 expression, mutated in XLSA/A and involved in maturation of cytosolic Fe/S proteins, is inversely correlated to the percentage of ring sideroblasts in MDS marrow smears (Boultwood et al, 2008). Here we showed that ABCB7 was suppressed throughout erythroid maturation in RARS, and that the suppression was more pronounced in mature erythroblasts, in contrast to the increasing expression over time in normal erythroblast cultures (Fig 1C).

Another key downregulated mitochondrial gene was mitofusin 2 (MFN2), involved in mitochondrial membrane integrity (Sugioka et al, 2004). A corresponding decrease of the protein was shown (Fig 2C). MFN2 expression during culture followed the pattern of ABCB7, and increased 2–3-fold during normal erythroid differentiation, while decreasing in the RARS cultures (Fig 2B).

In addition, Sideroflexin 1 (Sfxn1), mutated in flexed-tail (f/f) mice with siderocytic anaemia, and PGRMC1, encoding a haem binding protein, were also downregulated in RARS erythroblasts.

Erythropoiesis-related genes are not overexpressed in RARS erythroblasts

Next, we compared expression profiling from a recent study using RARS CD34+ cells (Pellagatti et al, 2006) with the GEP results obtained from intermediate RARS erythroblasts in the present study. The expression level of all haem biosynthesis pathway enzymes was normal in RARS erythroblasts, except aminolevulinic acid synthase 2 (ALAS2), the first enzyme in the haem biosynthetic pathway (Table I, category B). RARS erythroblasts showed a moderate overexpression of ALAS2, however at a much lower magnitude than RARS CD34+ cells (1·37-fold vs. 12·77-fold). Interestingly, other genes also involved in the haem pathway and erythropoiesis, including ALAD, FECH, GATA1 and EPOR, were upregulated in CD34+ cells but showed normal expression levels in RARS erythroblasts. This indicates that part of the overexpression observed in CD34+ cells may be due to an enrichment of early erythroid cells in that fraction. Downregulated genes in the erythropoiesis group included FOXO3, a transcription factor regulating oxidative stress in erythropoiesis and FANCC, a key mutated gene in Fanconi anaemia.

Genes involved in cell survival and apoptosis

The expression of pro and anti-apoptotic genes in RARS erythroblasts constituted a complex pattern. MAP3K7, an important negative regulator of apoptosis (Tang et al, 2008) was one of the most downregulated genes in RARS erythroblasts. By contrast, two members of the heat shock protein 70 family, HSPA1B and HSPA9 genes, showed moderate overexpression, which may indicate their involvement in protection of erythroid cells survival in RARS. HSPA1B encodes an inducible HSP70 which regulates haematopoiesis and protects GATA-1 from caspase-3 cleavage, while, HSPA9B encodes an anti-apoptotic protein that is a mediator of Epo signalling (Ohtsuka et al, 2007; Ribeil et al, 2007).

A key finding of the report by Pellagatti et al (2006) was the upregulation of several interferon-induced genes that may be responsible for enhancement of apoptosis in erythroid progenitors, hence in ineffective erythropoiesis in RARS. Deregulation of several interferon induced genes including IRF2, IRF6, IRF2BP2, TOR1AIP2, IFNA17, AEN and ISG20L2 were observed also in RARS erythroblasts.

Pathway analysis of RARS compared to normal erythroblasts

Functional classification revealed 25 significantly deregulated pathways in RARS compared to normal erythroblasts (P < 0·01), the top 10 being listed in Table II, A. RARS erythroblasts showed a marked deregulation of several important pathways for haematopoiesis and cell cycle control, including integrin, PI3K/AKT and VEGF signalling, protein ubiquitination, apoptosis, DNA damage checkpoint regulation, mitochondrial function, and the JAK/Stat pathway.

Table II.   Pathway analysis.
PathwaysP-valueSelection of the involved genes
A. The 10 most deregulated pathways in day 7 RARS erythroblasts compared to normal erythroblasts
  Integrin signalling5·37E-0669 genes including MAP2K4, RAP2B, RAC2, RAF1, MAP3K11, ARHGAP26, MAPK1, PIK3R1, HRAS, TLN1
  PI3K/AKT signalling1·78E-0543 genes including GAB2, RAF1, PIK3CA, JAK1, YWHAH, MAPK1, PPP2CA, PIK3R1, ILK, HRAS
  B Cell receptor signalling4·27E-0552 genes including MAP2K4, RAF1, FCGR2C, GAB2, RAC2, MAP3K11, MAPK1, NFATC3, PIK3R1, HRAS
  Actin cytoskeleton signalling4·90E-0569 genes including RAC2, RAF1, PFN1, MAPK1, DIAPH3, PIK3R1, HRAS, ARHGEF1, LIMK2, MYH11
  Protein ubiquitination pathway6·31E-0564 genes including UBE2H, USP45, PSMA3, UBE2A, PSMA7, UBE3B, UBR2, UBE2D2, USP20, UBE2V2
  JAK/Stat signalling1·66E-0426 genes including RAF1, SOCS1, SOCS3, PIK3CA, PIAS2, JAK1, MAPK1, PIK3R1, HRAS, MAP2K2, STAT5B, SOS1
  VEGF signalling1·70E-0433 genes including RAF1, EIF2S2, PIK3CA, PTK2B, MAPK1, PIK3R1, EIF1, HRAS, EIF2S1, EIF2B2
  Insulin receptor signalling2·57E-0444 genes including PRKACB, PPP1CC, SOCS3, FYN, RAF1, PIK3CA, JAK1, MAPK1, PIK3R1, LIPE
  Apoptosis signalling5·25E-0432 genes including MAP2K4, RAF1, MAPK1, HRAS, MAP4K4, DFFA, BCL2, ACIN1, CASP6, IKBKB
  Cell Cycle: G2/M DNA damage  checkpoint regulation7·24E-0418 genes including CDKN2A, TP53, PRKDC, UBB, YWHAE, YWHAB, WEE1, PTPMT1, CUL1, YWHAZ
B. The 10 most deregulated pathways in day 7 RARS erythroblasts after G-CSF treatment (P < 0·05)
  Biosynthesis of steroids2·69E-07SQLE, FDFT1, DHCR7, EBP, IDI1, MVK, PDSS2, LSS, HMGCR, SC5DL
  Hypoxia signalling2·69E-03VEGFA, UBB, NFKBIA, UBE2D3, HIF1A, UBE2L6, UBE2E1, PTEN, ARNT
  Endoplasmic reticulum stress pathway6·76E-03CASP9, ERN1, MAP3K5, HSPA5
  Toll-like receptor signalling1·70E-02ECSIT, TLR4, NFKBIA, CD14, EIF2AK2, IRAK2
  IL-10 signalling1·74E-02IL1R2, NFKBIA, BLVRA, IL10RA, BLVRB, CD14, FCGR2B
  Propanoate metabolism1·74E-02ACSL3, ACAT2, ACACB, DHCR24, ABAT, ACSS1, ALDH6A1
  LXR/RXR activation2·63E-02IL1R2, TLR4, CD14, ABCG1, HMGCR, MMP9, ABCA1
  Acute phase response signalling3·47E-02ECSIT, TCF4, RRAS, NOLC1, SOCS2, SERPINF1, MAP3K5, TCF3, NFKBIA, RIPK1, SOS1, SERPINE1, IL1RAP
  Inositol phosphate metabolism3·47E-02PAK1, INPP4B, SGK1, PDIA3, CSNK1A1, CDK6, LIMK2, IP6K2, EIF2AK2, PI4KA, PTEN
  Pyruvate metabolism3·55E-02ACSL3, AKR1A1, ACAT2, ACACB, DLAT, ACSS1, ACOT9
C. The only two deregulated pathways in day 7 normal erythroblasts after G-CSF treatment (P < 0·05)
  SAPK/JNK signalling2·51E-02FADD, RIPK1, ZAK
  Galactose metabolism4·17E-02GLA, GALT

The JAK/Stat signalling pathway mediates cellular responses to growth factors, however, Epo receptor (EpoR) and G-CSF receptor activate distinct but overlapping sets of signalling molecules within the pathway. While Stat5 activation is essential for signalling through the EpoR, it is not necessary for the terminal erythroid differentiation induced by G-CSF (Millot et al, 2001). Interestingly, STAT5B was dramatically down regulated in RARS erythroblasts, which could explain why RARS patients benefit from the addition of G-CSF to EPO treatment. The deregulation of protein ubiquitination pathway, which targets abnormal or short-lived proteins for degradation, might reflect an abnormal protein synthesis in RARS.

Potential mechanisms behind the anti-apoptotic effects of G-CSF in RARS

One thousand hundred and fifty-three probe-sets were significantly different (P < 0·05) between G-CSF treated and untreated RARS erythroblasts. The 10 most up and downregulated genes, sorted according to P-value are shown in Table SIII. The influence of G-CSF treatment on probe sets categorized as A or B is also shown in Table I.

Only 163 probe-sets were differentially expressed in treated and untreated normal erythroblasts, which is in line with the very moderate effect of G-CSF on normal erythroblasts shown in our previous cell biological studies (Tehranchi et al, 2003, 2005). G-CSF had no effect on the expression of ABCB7, or erythropoiesis-associated genes. The slight overexpression of ALAS2 was normalized by G-CSF. Importantly, several genes, which in RARS were altered in a direction of enhanced apoptosis, were reverted back to the normal range by G-CSF. The reduced MFN2 expression was reverted to normal range (confirmed by RT-PCR and Western blotting) (Fig 2). However, the expression level of MAP3K7, a negative regulator of apoptosis and downregulated in RARS erythroblasts, was not altered by G-CSF.

The expression level of HSPA9, which was slightly upregulated in RARS, further increased after G-CSF treatment. HSPA9 inhibits apoptosis via the inactivation of P53 (Kaul et al, 2000) and its loss in zebra fish recapitulates the ineffective haematopoiesis of the myelodysplastic syndrome including anaemia and dysplasia (Craven et al, 2005). G-CSF also significantly enhanced the expression and protein level of HSPA1B in RARS (Fig 3).

Pathway analysis of RARS erythroblasts after G-CSF treatment

Pathway analysis revealed 17 significantly deregulated pathways in G-CSF treated and un-treated RARS erythroblasts (P < 0·05), listed in Table II, B. Interestingly, the ‘mitochondrial dysfunction’ pathway, one of the main deregulated pathways in RARS erythroblasts, was significantly modulated after G-CSF treatment (P = 0·04). Caspase-9, which is increased in RARS was downregulated by G-CSF (Tehranchi et al, 2003).

G-CSF also reverted the endoplasmic reticulum stress (ERS) pathway, which is triggered by the accumulation of unfolded proteins in the endoplasmic reticulum (ER), towards the normal pattern. For instance, HSPA5, an ER associated member of HSP70 family and shown to inhibit cytochrome c release and apoptosis, was upregulated. Moreover, G-CSF overexpressed several genes in the ‘NRF2-mediated Oxidative Stress Response pathway’ involved in protein folding, including DNAJB9, DNAJB11, DNAJB6, DNAJC7 and HERPUD1 (Table II, B). As a reflection of the minor cellular effects of G-CSF on normal erythroblasts, only two pathways were deregulated in normal erythroblasts after G-CSF treatment (Table II, C).

Methylation analysis

In order to investigate whether downregulation of key genes was caused by hypermethylation, methylation status was determined by MCA-Meth (Lorente et al, 2008). The MFN2, FANCC and FOXO3 genes were not methylated in the RARS samples. Regarding ABCB7, there was 50% methylation in females (both RARS and control), which is in line with the fact that one allele of ABCB7 is inactivated because of its location on chromosome X (Fig 1D). Hence, DNA methylation was not a significant cause of low mRNA expression. Methylation status of MFN2 in RARS samples is shown in Fig 2E.


  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Gene expression profiling of MDS CD34+cells showed that RARS patients constitute a relatively homogenous group with IFN-γ-induced gene expression, and altered expression of haem biosynthesis and mitochondrial genes (Pellagatti et al, 2006). However, the CD34+ compartment may reflect different cell mixes in different MDS subtypes as MDS progenitors may retain the CD34 antigen longer than normal progenitors (Kanter-Lewensohn et al, 1996). Considering the typical morphology of RARS, it is likely that mRNA from the CD34+ subtype mirrors a higher proportion of erythroblasts compared to e.g. 5q- syndrome CD34+ cells. To address this problem, we used cultured erythroblasts for the microarray analyses using a well-validated culture method (Tehranchi et al, 2003, 2005). Interestingly, several genes involved in erythropoiesis and significantly overexpressed in RARS CD34+ cells showed normal or nearly normal expression in erythroblasts. By contrast, the suppressed expression of ABCB7 and MFN2 genes in RARS erythroblasts was reinforced during erythroid differentiation.

The severely reduced ABCB7 expression in mature erythroblasts deserves more consideration (Boultwood et al, 2008). ABCB7 is required for maturation of cytosolic Fe–S proteins, such as iron regulatory protein 1, which regulates protein levels of the major iron homeostasis genes (Cairo & Recalcati, 2007). Hence, disruption of Fe-S cluster biogenesis pathways can result in maladaptive changes in iron metabolism. ABCB7 silencing in HeLa cells causes an iron-deficient phenotype with mitochondrial iron overload (Cavadini et al, 2007). In normal erythroblast cultures ABCB7 expression increased in parallel with haemoglobinisation, but intriguingly, it decreased gradually from day 0 to day 14 in RARS, supporting a critical role of ABCB7 in aberrant iron accumulation also in acquired RARS.

The single most downregulated gene in RARS was NSMCE4A, which is involved in DNA damage repair and hence may be associated with DNA instability in RARS (Hu et al, 2005; Novotna et al, 2008). Moreover, FANCC, a key mutated gene in Fanconi anaemia and involved in DNA damage repair and apoptosis inhibition in haematopoietic cells exposed to IFN-γ (Pang et al, 2001), was also markedly suppressed, which may explain the similarities of MDS CD34+ and IFN-γ -induced normal CD34+ cells (Pellagatti et al, 2006). Finally, apoptosis of RARS erythroblasts was paralleled by MAP3K7 down regulation. MAP3K7 deletion leads to a massive haematopoietic cells apoptosis in mice (Tang et al, 2008).

Several pathways showed deregulation in RARS compared to normal erythroblasts, including mitochondrial function, apoptosis and JAK/Stat signalling, all key mediators of functional erythropoiesis. Deregulation of JAK/Stat signalling pathway, particularly Stat5 down regulation, is in line with the impaired response to Epo in RARS patients (Hoefsloot et al, 1997). However, RARS erythroblasts are able to undergo terminal differentiation induced by G-CSF because of the dispensable role of Stat5b in G-CSF-R signalling (Millot et al, 2001). This may be a relevant explanation for the particularly good synergistic in vivo and in vitro effects of G-CSF and Epo on the anaemia and erythroid apoptosis in RARS (Tehranchi et al, 2003, 2005; Jadersten et al, 2005).

G-CSF has virtually no effect on normal erythroblasts and haemoglobin of normal individuals, which was reflected by its very moderate effects on normal gene expression. To further address the anti-apoptotic role of G-CSF in RARS cells we assessed those genes whose expression was returned to the normal range by G-CSF. Interestingly, the expression of several anti-apoptotic genes, such as BCL2 and BCL2L1, was normal in RARS and unaffected by G-CSF (Tehranchi et al, 2003) and neither did G-CSF affect MAP3K7.

Instead, G-CSF restored MFN2 gene and protein expression and had also a significant effect on the whole mitochondria pathway in RARS cells. MFN2 participates in the mitochondrial pathway and its silencing leads to enhanced apoptosis in HeLa cells (Sugioka et al, 2004) and reduced mitochondrial membrane potential (Bach et al, 2003). The reduced MFN2 expression in RARS erythroblasts may therefore link to cytochrome c release in these cells and G-CSF-induced re-expression of MFN2 to the inhibitory effect of the growth factor on cytochrome c release and erythroid apoptosis (Tehranchi et al, 2003). Furthermore, G-CSF upregulated HSPA1B, a member of the HSP70 family, which was recently shown to protect GATA-1 from caspase-3-mediated proteolysis during differentiation (Ribeil et al, 2007). This may constitute another potential mechanism for G-CSF, which inhibits caspase-3 activation in RARS cells (Schmidt-Mende et al, 2001). HSPA9, another member of the HSP70 family, had a similar response pattern to G-CSF. HSPA9 inhibits P53 function (Wadhwa et al, 1998) and is also involved in Epo signalling (Ohtsuka et al, 2007).

The endoplasmic reticulum stress (ERS) pathway is activated in response to an accumulation of unfolded proteins in the endoplasmic reticulum (ER) and protects cells against different types of stress (Zhang & Kaufman, 2006). Interestingly, the ERS pathway was modified by G-CSF, which might be a survival mechanism, particularly because several genes involved in protein folding, including DNAJB9, DNAJB11, DNAJB6, DNAJC7 and HERPUD1, were upregulated by G-CSF. In addition, HSPA5, an ER associated member of the HSP70 family, was upregulated by G-CSF. HSPA5 overexpression is associated with inhibition of cytochrome c release and apoptosis (Shu et al, 2008).

In contrast to its anti-apoptotic effects, G-CSF does not seem to affect sideroblast formation or mitochondrial iron accumulation, as shown by the ABCB7 results and unaffected accumulation of mitochondrial ferritin (Tehranchi et al, 2005). Interestingly, RARS erythrocytes from patients responding to growth factors develop a more abnormal phenotype with increased cell size and hypochromatic cytosol, which supports this interpretation (Ljung et al, 2004). We therefore suggest that G-CSF promotes erythroblast survival until the erythrocyte stage, despite impaired cellular function.

Our data shows the strength of assessing gene expression during differentiation. Through this technique and by assessing the G-CSF effects, we have identified a number of candidate genes involved in mitochondrial iron accumulation and cytochrome c release for further investigation. The stable clinical course of WHO RARS may suggest its monogenetic – or oligogenetic nature. In the absence of ABCB7 mutations or hypermethylation, we hypothesize that upstream mechanisms with impact on cellular iron transport may be involved in RARS pathogenesis.


  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

This work was supported by grants from the Swedish Cancer Society (contract 08 0601), and through a strategic grant for Centrum For Experimental Haematology (EHL and AG), the Medical Research Council (contract 70293801), the Cancer Society in Stockholm (EHL), Leukaemia Research Fund of the UK (JB, AP, JW), and Fondazione IRCCS Policlinico San Matteo, Pavia, (M.C). M.K is supported with a post doc grant from Karolinska Institute.


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  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Table SI. List of the oligonucleotides used for methylation analysis.

Table SII. List of the 50 most deregulated probe sets in RARS erythroblasts compared to normal erythroblasts, sorted according to P-value.

Table SIII. The 10 most significantly up/downregulated probe sets in G-CSF-treated RARS erythroblasts versus untreated RARS erythroblast.

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BJH_8174_sm_SIII.xls25KSupporting info item

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