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Keywords:

  • leukaemia;
  • genetic signature;
  • tyrosine kinase;
  • apoptosis;
  • signalling pathway;
  • transcriptome

Summary

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Authors’ contributions
  8. Conflict of interest statement
  9. References
  10. Supporting Information

This study compared the gene expression profiles of primary leukaemic cells from infants versus children with acute lymphoblastic leukaemia (ALL). Our analyses provided unprecedented evidence that remarkably different pathognomonic transcriptomes dominate the biology of infant versus paediatric high risk ALL. The genetic signature of infant ALL is characterized by concomitant overexpression of mitogenic and anti-apoptotic genes, some of which have been associated with early relapse in ALL. Our study demonstrated that primary leukaemia cells from infant ALL patients expressed significantly higher levels of genes for cytokines that mediate their biological effects through stimulation of the JAK-STAT signal transduction pathway including interleukin 1a, interleukin 1b, interleukin 2, and interleukin 7. We further showed that the JAK/STAT signalling pathway is constitutively active in CD10 infant ALL cells and treatment with a JAK3 inhibitor or a pan-JAK kinase inhibitor effectively triggered their apoptosis. These findings identified JAK3 as an attractive molecular target for disrupting the constitutively deregulated anti-apoptotic STAT3 and STAT5 signalling pathways in infant ALL cells.

Infants with B-precursor acute lymphoblastic leukaemia (ALL), representing approximately 5% of all paediatric ALL cases, continue to have a disappointingly poor treatment outcome with less than 50% 5-year survival despite intensive chemotherapy and supralethal radiochemotherapy in the context of stem cell transplantation (SCT) (Hilden et al, 2006; Reaman et al, 1999). Infants with CD10 antigen negative pro-B ALL and very young infants less than 6 months of age have a particularly poor prognosis (Hilden et al, 2006; Reaman et al, 1999). Early bone marrow relapse and toxicity of intensive very high dose systemic chemotherapy are the leading causes of treatment failure for infants with ALL (Hilden et al, 2006; Reaman et al, 1999).

The purpose of the present study was to compare the gene expression profiles of primary leukaemic cells from infants with ALL to those of primary leukaemic cells taken from children with ALL. Our analyses provided unprecedented evidence that remarkably different pathognomonic transcriptomes dominate the biology of infant versus paediatric high risk B-precursor ALL. The unique anti-apoptotic and pro-mitogenic gene expression profile of infant ALL cells prompted the hypothesis that a complex network of multiple overlapping but non-redundant signalling pathways, including constitutively active JAK3/STAT3 and JAK3/STAT5 pathways, contribute to their survival and proliferation. Disruption of this network by inhibiting JAK3 kinase with small molecule inhibitors induced apoptosis in CD10 infant pro-B ALL cells.

Materials and methods

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Authors’ contributions
  8. Conflict of interest statement
  9. References
  10. Supporting Information

Patients

Surplus leukaemia cells isolated from bone marrow specimens of 31 infants with newly diagnosed ALL, who were treated on the Children’s Cancer Group (CCG) Infant ALL Protocols (Hilden et al, 2006; Reaman et al, 1999) and 23 children with newly diagnosed high risk ALL, who were treated on a CCG High Risk ALL Protocol (Eligibility: age ≥10 years or age 1–9 years with presenting white blood cell count (WBC) ≥ 50 × 109/l) (Seibel et al, 2008) as well as seven children with newly diagnosed standard risk ALL, who were treated on a CCG Standard Risk ALL protocol (Eligibility: age 1–10 years and WBC < 50 × 109/l) (Matloub et al, 2006) were used for gene expression profiling, confocal microscopy, JAK3 kinase expression and phosphorylation, and/or apoptosis assays with approval of the Parker Hughes Institute Institutional Review Board under the exemption category (45 CFR Part 46.101; Category #4: Existing Data, Records Review, and Secondary Use of Pathologic Specimens) in accordance with US Department of Health and Human Services guidelines.

Gene expression profiling using atlas human cDNA expression arrays

Expression profiling of leukaemia cells for 588 genes was performed using the Atlas Human cDNA Expression arrays from Clontech Laboratories Inc. (Mountain View, CA, USA) according to the manufacturer’s specification using previously detailed standard procedures (Table I, Table II, Fig. I-III, Appendix S1, Table SI–Table SIX, Fig. SI, Fig. SII). Genes that showed the most consistent differences in expression between patient groups, the greatest fold change and most significant t-tests in the signature were cross-referenced to the Oncomine™ Research Data Base (http://www.oncomine.org/), a compendium of more than 392 studies represented by 28880 gene expression arrays for 41 different cancers (Rhodes et al, 2007) (Appendix S1, Table SVI).

Table I.   Gene expression profiles of infant ALL cells versus paediatric ALL cells.
Array IDGenebank#Gene symbolInfant ALL/paediatric ALL (fold-difference)T-test (P-value)Cluster order
Upregulated in infant ALL
 Oncogenes, tumour suppressors, cell cycle control proteins
  A7hL29222CLK12·34·2 × 10−221
  A1aV00568MYC2·32·2 × 10−210
  A3iL25080RHOA1·71·1 × 10−227
  A4gX51521EZR1·63·0 × 10−228
  A2cU01134FLT11·54·4 × 10−225
 Ion channels and transport, intracellular signal transduction modulators and effectors, stress response
  B1nM18391EPHA12·68·0 × 10−313
  B6eX80692MAPK61·53·8 × 10−226
 Apoptosis, DNA synthesis, repair and recombination
  C5lL07541RFC33·11·5 × 10−312
  C6hM87339RFC43·01·9 × 10−417
  C7cU07418MLH12·01·2 × 10−218
  C5aU60520CASP82·01·4 × 10−211
 Transcription factors, general DNA binding proteins
  D3aD26155SMARCA23·67·4 × 10−69
  D5eM93255FLI12·32·4 × 10−320
  D3bD28118VEZF12·28·2 × 10−322
  D5fM96824NUCB11·86·4 × 10−323
  D3eL11672ZNF911·73·1 × 10−224
  D6aU04847SMARCB11·62·6 × 10−219
 Receptors, cell surface antigens, cell adhesion molecules
  E1aM29366ERBB34·03·4 × 10−48
  E2bM73482NMBR2·69·8 × 10−414
 Cell-cell communication molecules (Growth factors, cytokines, chemokines, interleukins,  hormones)
  F4jX06233S100A96·71·6 × 10−71
  F4lX06374PDGFA4·82·7 × 10−63
  F4kX06234S100A83·72·5 × 10−42
  F5kA14844IL22·53·7 × 10−44
  F1mM37435CSF12·22·7 × 10−215
  F5mK02770IL1B2·12·3 × 10−316
  F5jJ04156IL71·93·4 × 10−35
  F5lX02851IL1A1·91·1 × 10−26
  F5iX01992IFNG1·51·2 × 10−27
Downregulated in infant ALL
 Oncogenes, tumour suppressors, cell cycle control proteins
  A4mU57456SMAD10·55·9 × 10−353
  A5bU18422TFDP20·54·1 × 10−342
  A1cM15024MYB0·53·9 × 10−250
  A1kL07868ERBB40·54·9 × 10−255
  A7gL29220CLK30·55·5 × 10−330
  A6hD13639CCND20·63·2 × 10−336
  A7mM81934CDC25B0·62·0 × 10−240
  A6eM92287CCND30·62·0 × 10−247
  A5iM28882MCAM0·64·8 × 10−235
 Ion channels and transport, intracellular signal transduction modulators and effectors, stress response
  B3eL22075GNA130·52·5 × 10−331
  B7nX76648GLRX0·51·6 × 10−251
  B4gU02081NET10·52·3 × 10−352
  B4fM36430GNB10·61·7 × 10−241
  B7iD49547DNAJB10·62·4 × 10−254
  B3fL24959CAMK40·62·7 × 10−239
  B6jX14454IRF10·74·9 × 10−229
 Apoptosis, DNA synthesis, repair and recombination
  C6cM32865XRCC60·59·4 × 10−349
  C3hU18321DAP30·61·1 × 10−248
  C7fM60974GADD45A0·62·2 × 10−246
 Transcription factors, DNA binding proteins
  D3jL34587TCEB10·56·2 × 10−334
  D5hM97287SATB10·62·9 × 10−238
  D4kM76766GTF2B0·61·7 × 10−233
  D3lM16937HOXB70·64·6 × 10−232
 Receptors, cell surface antigens, cell adhesion molecules
  E6mL12002ITGA40·51·1 × 10−237
  E7eX06256ITGA50·62·4 × 10−245
 Cell-cell communication molecules (growth factors, cytokines, chemokines, interleukins, hormones)
  F2aD16431HDGF0·48·2 × 10−543
  F4fM96956TDGF1///TDGF30·58·8 × 10−344
Table II.   Signature transcriptome of infant ALL cells.
Array IDGenebank#Gene symbolFold-difference (infant ALL/paediatric ALL)T-test (P-value)
F4jX06233S100A96·71·6 × 10−7
F4lX06374PDGFA4·82·7 × 10−6
E1aM29366ERBB34·03·4 × 10−4
F4kX06234S100A83·72·5 × 10−4
D3aD26155SMARCA23·67·4 × 10−6
C5lL07541RFC33·11·5 × 10−3
C6hM87339RFC43·01·9 × 10−4
F5kA14844IL22·53·7 × 10−4
image

Figure 1.  Gene Expression Profiles of Infant ALL Cells. A T-test was performed on log transformed, normalized expression values for 588 genes on the Clontech Array. Mean centred, standardized values for significantly affected genes (rows) across the 61 patients (columns) were subjected to hierarchical clustering, showing genes that were upregulated in infant ALL (n = 31) and those that had higher expression values in paediatric ALL (n = 30). The heat map represents the colour-coded expression value reported as standard deviation units (SD) relative to the average expression levels across 61 samples (Panel A). Differentially expressed genes (t-test unequal variance, P < 0·05, fold-difference greater than 1·5) were also identified for infants (N = 7) versus paediatric patients (N = 20) with CD10+ ALL. Fifteen common genes that were up-regulated in the total pool of infants from comparison in ‘A’ and the CD10+ subset were represented in the cluster figure (Panel B) joined across patients using the average linkage method for standardized values. For both cluster figures A and B, expression values were analyzed first by joining pairs of genes (in rows) closest in the average SD units values (average distance linkage) and then connecting larger groups of genes using the branching structure, whereby larger branch lengths represent larger differences in expression profiles. The dendrogram depicts the similarity of expression pattern for gene sets (identified by gene symbols) across the two patient groupings.

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image

Figure 2.  Gene expression profiles of infant B-precursor leukaemia (BPL) cells. We identified 37 differentially expressed genes using a t-test (two sample, 2-tailed, P < 0·05) for infant BPL (N = 21) and high risk paediatric BPL (N = 16). These significantly affected genes (rows) were expressed as mean centred, standardized values and clustered using the average distance metric to identify co-expressed genes (Panel A). Gene expression profiles were also compared for subset of CD10+ infant BPL patients (N = 5) versus CD10+ paediatric BPL patients (N = 17 that included 5 standard risk and 12 high risk patients) resulting in 14 genes and 27 genes up-regulated in infant BPL and paediatric BPL patients, respectively. Fourteen genes were found to be common in the comparisons of infant BPL and the subset of CD10+ patients with paediatric patients. Differential expression of this gene set was represented in the cluster figure (Panel B) using standardized values for gene expression across patients.

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image

Figure 3.  Targeting constitutively active JAK3/STAT pathway in infant pro-B ALL cells. (A) JAK3 expression in primary leukaemic cells from six infant pro-B ALL patients and two CD10+CD19+CD7 infant B-precursor ALL (BPALL) patients were examined by Western blot analysis of whole cell lysates. (B) Expression and subcellular localization of JAK3, STAT3, and STAT5 was examined in primary leukaemic cells from five infants with pro-B ALL (see also Fig S2) using confocal microscopy. Representative confocal images obtained on primary leukaemic cells from INF-Pro-B #5 in (A) are depicted as examples. (C) The effects of the JAK3 inhibitor WHI-P131 on constitutive activity of JAK3 kinase in primary leukaemic cells from three infants with pro-B ALL (INF-Pro-B#’s 1–3 from Panel A) was examined by APT Western blot analysis in cold kinase assays. (D) The ability of the JAK inhibitors WHI-P131 and AG-490 (as well as the BTK inhibitor LFM-A13 that was included as a control) to induce apoptosis in primary leukaemic cells from six infants with pro-B ALL (INF-Pro-B ALL#’s 1–6 from Panel A) was examined using in vitro TUNEL assays. **P < 0·0001.

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Reagents and antibodies

The antibodies against JAK3, STAT3, and STAT5 used in these studies were obtained from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA, USA). JAK3 inhibitor WHI-P131 (Sudbeck et al, 1999) and BTK/PLK1 inhibitor LFM-A13 (Mahajan et al, 1999) were synthesized according to previously published procedures. JAK1,2,3 inhibitor AG-490 was included as a control (Sigma-Aldrich, St. Louis, MO, USA).

Western blot analysis, confocal microscopy, and apoptosis assays

Primary leukaemia cells from five infants with pro-B ALL were examined for expression of JAK3, STAT3, and STAT5 by confocal microscopy. Anti-JAK3 and anti-phosphotyrosine (APT) Western blot analyses of JAK3 immune complexes were performed using previously published procedures (Sudbeck et al, 1999). Two-colour TdT-mediated dUTP nick-end labelling (TUNEL) assays and confocal microscopy (Narla et al, 2000) were used to determine the percentage of apoptotic cells after treatment with WHI-P131, AG-490 or LFM-A13 (each kinase inhibitor was used at 100 μmol/l final concentration) compared to vehicle control on leukaemia cells obtained from six infants with pro-B ALL.

Results

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Authors’ contributions
  8. Conflict of interest statement
  9. References
  10. Supporting Information

Differences in gene expression profiles of primary leukaemic cells from infants versus children with newly diagnosed ALL

We compared the gene expression profiles of primary leukaemic cells from 31 infants (age < 1 year) with newly diagnosed ALL with those of 30 children (age ≥ 1 year) with newly diagnosed high risk or standard risk ALL using Atlas Human cDNA Expression Arrays. Eighteen genes showed greater than twofold higher expression levels (change of 1 log unit) in infant leukaemia cells versus childhood leukaemia cells (Table I). Of these 18 genes, 10 exhibited greater than 2·5-fold higher expression levels in infant leukaemia cells, including S100A9 (fold-difference = 6·7), PDGFA (fold-difference = 4·8), ERBB3 (fold-difference = 4·0), S100A8 (fold-difference = 3·7), SMARCA2 (fold-difference = 3·6), RFC3 (fold-difference = 3·1), RFC4 (fold-difference = 3·0), NMBR (fold-difference = 2·6), EPHA1 (fold-difference = 2·6), and IL2 (fold-difference = 2·5). The one-dimensional hierarchic cluster shown in Fig 1A depicts a set of three genes (top three rows) that were closely clustered together and were amongst the genes with the highest expression levels in infant leukaemia cells and exhibited the most significant differences in expression compared to childhood ALL cells (P < 0·00001 for S100A9, PDGFA, SMARCA2). We next sought to identify the discriminating genes for which the greatest proportion of infant ALL patients had expression values greater than 90% power of detection and alpha of 5%. After application of t-tests, cluster analysis and the chi-square tests, eight signature genes were identified that best discriminated infant ALL cells from childhood ALL cells: S100A9, PDGFA, ERBB3, S100A8, SMARCA2, RFC3, RFC4 and IL2 (Table II). Each one of these differentially expressed genes showed greater than 2·5-fold higher expression levels in infant versus childhood leukaemia cells.

We next compared the gene expression profiles of primary leukaemia cells from CD10+ infants (N = 7) with the gene expression profiles of primary leukaemic cells from CD10+ paediatric ALL patients (N = 20) (Fig 1B). There was a significant overlap between the genes that were upregulated in infant versus paediatric ALL cases (Table I) and the genes that were upregulated in CD10+ infant versus CD10+ paediatric ALL cases (Table SI) (Fishers Exact test, 2-tailed, P < 0·0001). Of the eight signature genes identified in the infant versus paediatric ALL comparison, 4 (viz.: S100A9, S100A8, PDGF and RFC3) were expressed at significantly higher levels in primary leukaemic cells from CD10+ infant ALL versus CD10+ paediatric ALL patients as well (Table SII). Since the CD10+ subset of infant ALL is usually negative for MLL gene rearrangements (MLL-R), these genes are highly unlikely to be related to MLL-R.

Differences in gene expression profiles of primary leukaemic cells from infants versus children with newly diagnosed B-precursor ALL

We next compared the gene expression profiles of primary leukaemic cells from 21 infant and 16 high-risk paediatric ALL patients with a CD19+CD10+/−CD7 B-precursor immunophenotype. In this subset of 37 B-precursor ALL patients, 37 genes showed differential expression (15 expressed at higher levels and 22 expressed at lower levels in infant ALL cells versus childhood ALL cells) with a P-value less than 0·05; 16 genes showed expression differences associated with a P-value less than 0·01 [T-test, true discovery rate (TDR) = 62·5%] (Fig 2A, Appendix S1, Table SII). Highly significant differences in expression (P < 0·001) were observed with four genes (TDR = 85%): three genes were expressed at higher levels in infant B-precursor ALL (S100A8, S100A9 and PDGFA) and one gene was expressed at higher levels in childhood high risk B-precursor ALL (MAPK8). Two genes, S100A8 and S100A9, which were also among the eight genes identified as the best discriminators of infant versus childhood ALL, were associated with both (i) the greatest number of patients with true positive scores for expression values outside the range of the 90% power calculation and (ii) the lowest proportion of patients with false positive scores. For the most consistent gene, S100A9, 24 patients (65%) showed differences that were true positive scores and only two patients were categorized as false positive (χ2 = 19·6, df = 2, P < 0·0001).

Of the 15 genes showing higher expression levels in infant B-precursor ALL cells, one gene showed greater than eightfold higher expression (S100A9), three genes showed greater than fourfold higher expression levels (S100A8, PDGFA, ERBB3) and seven genes showed greater than twofold higher expression levels (Table SII).

Notably, the comparison of the CD10+ infant B-precursor ALL cases to CD10+ paediatric high risk B-precursor ALL cases revealed that the three genes that showed the most significant differences in expression (P < 0·001) in the infant versus paediatric ALL B-precursor ALL comparison (viz.: S100A8, S100A9 and PDGFA) were expressed at much higher levels in leukaemia cells from CD10+ infant B-precursor ALL patients, with S100A9 exhibiting a 19·1-fold higher expression, S100A8 a 9·2-fold higher expression, and PDGFA an 8·3-fold higher expression (Fig 2B, Appendix S1, Table SIII). Similar results were obtained in a comparison of infant CD10+ B-precursor ALL versus paediatric (high risk + standard risk) CD10+ B-precursor ALL, with S100A9 exhibiting a 18·7-fold higher expression, S100A8 a 10·2-fold higher expression, and PDGFA a 10·6-fold higher expression in infant leukaemia cells (Appendix S1, Table SIV). These findings for the B-precursor subsets confirm and extend those obtained in the CD10+ infant versus CD10+ paediatric ALL comparisons, as shown in Table SI. When the CD10 infant pro-B ALL cases were compared to CD10 high risk paediatric pro-B ALL cases, most of the signature genes that were upregulated in infant versus paediatric ALL cases or their B-precursor subsets were no longer discriminating except for S100A9, which showed a 5·5-fold higher expression level in infants (Appendix S1, Fig S1, Table SV). It is therefore possible that the majority of the signature genes are expressed at higher levels at earliest stages of human B-cell ontogeny and their overexpression in infant leukaemia cells is a reflection of the higher representation of the immature pro-B immunophenotype in infant B-precursor ALL. Gene expression profiles of prognostically distinct subsets of infant ALL patients are detailed in S1, Table SVII-Table SIX.

Constitutive activation of JAK/STAT pathway and JAK3-inhibition induced apoptosis of primary leukaemic cells from infants with CD10 ALL

As leukaemic cells from CD10 infant pro-B ALL patients expressed JAK3 gene at higher levels than CD10+ infant B-precursor ALL cells (2·4 fold higher expression level, P = 0·012), we examined the expression levels of JAK3 kinase as a potential molecular target for this poor risk subset of infant ALL. JAK3 kinase protein was abundantly expressed in infant pro-B ALL cells, as documented by Western blot analysis (Fig 3A) as well as confocal microscopy (Fig 3B). Confocal microscopy revealed a predominantly nuclear localization of STAT3 and STAT5 proteins in these cells, consistent with a constitutive activation of the JAK3/STAT3/STAT5 signalling pathway (Fig 3C). Treatment of infant pro-B ALL cells with the JAK3 inhibitor WHI-P131 reduced the kinase activity of native JAK3, as shown by decreased autophosphorylation of JAK3 in kinase assays (Fig 3C). Treatment with WHI-P131 or the pan-JAK inhibitor AG-490 (but not the BTK inhibitor LFM-A13) induced apoptosis in primary leukaemic cells from six of six infants with pro-B ALL (Fig 3D). The analysis of variance (anova) model explained 98% of the variation in the apoptotic response (Grand Mean of the response = 50%, Root Mean Square = 6·8%, F3,20 = 338, P < 0·0001). Treatment with WHI-P131 (93%, P < 0·0001) and AG-490 (96%, P < 0·0001) showed significant induction of apoptosis in contrast to LFM-A13 (P = 0·96) using Dunnett’s post hoc test compared to the control values.

Discussion

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Authors’ contributions
  8. Conflict of interest statement
  9. References
  10. Supporting Information

Leukaemic B-cell precursors from ALL patients have been previously reported to constitutively express functional receptors for interleukin 1 (Uckun et al, 1989), interleukin 2 (Touw et al, 1985), and interleukin 7 (Uckun et al, 1991). Therefore, constitutive activation of the genes for one or more of the cytokines may lead to an apoptosis-resistant phenotype as well as an autocrine stimulation of the proliferative activity of leukaemic B-cell precursors. IL-7 activates the anti-apoptotic transcription factors STAT1, STAT3 and STAT5 in B-cell precursors and promotes their proliferation (Uckun et al, 1991; Van der Plas et al, 1996). Forced overexpression of IL-7 in transgenic mice or administration of exogenous IL-7 leads to an increase of the B-cell precursor pool (Morrissey et al, 1991). Nakayama et al (2009) recently reported that constitutive activation of JAK3/STAT5 signalling pathway in B-cell precursors by autocrine IL-7 production in the absence of BLNK protein, a direct inhibitor of JAK3 that functions as a tumour suppressor, causes B-precursor leukaemia in mice. Inhibition of IL-7 receptor signalling or JAK3/STAT5 activity resulted in apoptosis of B-precursor ALL cells (Nakayama et al, 2009). Our current study provided unprecedented evidence that primary leukaemia cells from infant ALL patients express significantly higher levels of multiple genes for anti-apoptotic and mitogenic cytokines that mediate their biological effects through stimulation of the JAK-STAT signal transduction pathway including interleukin 1a, interleukin 1b, interleukin 2, and interleukin 7. We further showed that the JAK/STAT signalling pathway is constitutively active in CD10 infant ALL cells and treatment with the JAK3 inhibitor WHI-P131 or the pan-JAK inhibitor AG-490 triggers their apoptosis. These findings demonstrate that JAK3 is an attractive molecular target for disrupting the constitutively degulated anti-apoptotic STAT3 and STAT5 signalling pathway in infant ALL cells.

Our comparative analysis of the gene expression profiles of primary leukaemic cells from infants with ALL versus those taken from children with ALL provided evidence that remarkably different pathognomonic transcriptomes dominate the biology of infant versus paediatric high risk B-precursor ALL. In particular, we identified eight signature genes that best discriminated infant ALL from childhood ALL cells: S100A8, S100A9, RFC3, RFC4, PDGFA, ERBB3, and IL2. The known biological functions of the protein products of these differentially expressed genes prompt the hypothesis that they are likely contributors to the apoptosis-resistance and high proliferative activity of infant leukaemia cells. S100A8 [also termed myeloid related protein (MRP)8] and S100A9 (MRP14) exist mainly as a S100A8/S100A9 heterodimer (termed calprotectin), which binds to and acts as an endogenous activator of toll-like receptor 4 (TLR4) (Ehrchen et al, 2009). S100A8/S100A9 tetramers have been shown to promote tubulin polymerization and bundle microtubules leading to stabilization of tubulin filaments (Leukert et al, 2006). Increased co-expression of S100A8 and S100A9 proteins synergistically promote cell survival by exhibiting marked anti-apoptotic activity (Nemeth et al, 2009). Increased expression of S100A8 and S100A9 have been associated with steroid resistance (Holleman et al, 2004) and relapse in childhood ALL (Bhojwani et al, 2006). The markedly enhanced expression of S100A8 and S100A9 in infant ALL suggests that S100 proteins may play an important role in leukemogenesis and/or adverse clinical course of ALL during infancy. Likewise, the SWI/SNF chromatin remodelling complexes, that play a critical role in the regulation of gene expression during lymphopoiesis (Wang et al, 1996), have been implicated in carcinogenesis as well as leukemogenesis (Klochendler-Yeivin et al, 2002; Park et al, 2009; Nie et al, 2003). MLL gene may cause altered chromatin remodelling and transcription by licencing histone acetylases and SWI/SNF-like helicases (Redner et al, 1999), and MLL-R may cause abnormal derepression of MLL-regulated genes by aberrant recruitment of SWI/SNF complexes (Rozenblatt-Rosen et al, 1998). In the present study, infant leukaemia cells showed 3·2-fold higher expression levels for the SNF-like SMARCA2 gene than leukaemic cells from children with high risk ALL. Notably, four studies (Yeoh et al, 2002; Ross et al, 2003; Fine et al, 2004; Tsutsumi et al, 2003) showed over expression of SMARCA2 in MLL-R+ ALL cells. Replication factor C (RFC) plays an important role in exonuclease 1-independent mismatch repair, an important DNA repair pathway responsible for correction of DNA replication errors (Kadyrov et al, 2009) as well as resistance to apoptosis (Arai et al, 2009). Increased expression of RFC3 and RFC4 has been associated with early relapse in childhood ALL (Bhojwani et al, 2006). The observed high level expression of RFC3 and RFC4 in infant leukaemia cells is a likely contributor of their resistance to apoptosis-promoting agents and high incidence of early relapse in infant ALL. Leukaemia cell lines derived from B-precursor ALL patients have been shown to express PDGFA gene and secrete PDGF A-chain (Tsai et al, 1994). The significance of the high level PDGF gene expression in infant ALL cells that was documented in the present study is not known, but it prompts the hypothesis that inhibitors of the PDGF-MAPK pathway may affect the proliferation and survival of infant ALL cells. Future studies will aim at deciphering the molecular mechanisms of cooperation between the protein products of the differentially expressed infant ALL signature genes and other putative leukemogenic proteins. Further evaluation of these proteins as potential molecular targets may provide the basis for therapeutic innovation against infant ALL.

Acknowledgements

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Authors’ contributions
  8. Conflict of interest statement
  9. References
  10. Supporting Information

The authors thank the members of the Uckun Lab from Parker Hughes Institute for providing the PTK inhibitors, technical assistance, and immunoprecipitations/immunoblotting, and confocal microscopy. This work funded by Parker Hughes Trust and Hughes Chair in Molecular Oncology at Parker Hughes Institute (to FMU).

Authors’ contributions

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Authors’ contributions
  8. Conflict of interest statement
  9. References
  10. Supporting Information

F.M.U and S.Q designed and performed research, analyzed data, and wrote the paper.

References

  1. Top of page
  2. Summary
  3. Materials and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Authors’ contributions
  8. Conflict of interest statement
  9. References
  10. 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. Authors’ contributions
  8. Conflict of interest statement
  9. References
  10. Supporting Information

Appendix S1. Gene Expression Profiling and Statistical Analyses.

Figure S1. Gene Expression Profiles of Infant Pro-B ALL Cells.

Figure S2. Expression of JAK3, STAT3, and STAT5 in Infant Pro-B ALL Cells.

Table S1. Gene Expression Profiles of CD10+ Infant ALL Cells vs. Pediatric ALL Cells.

Table S2. Gene Expression Profiles of Infant vs. Pediatric High Risk B-precursor Leukemia Cells.

Table S3. Gene Expression Profiles of Infant vs. Pediatric CD10+ High Risk B-precursor Leukemia Cells.

Table S4. Gene Expression Profile of Infant vs. Pediatric CD10+ B-precursor Leukemia Cells.

Table S5. Gene Expression Profiles of Infant vs. High Risk Pediatric Pro-B ALL Cells.

Table S6. Meta-Analysis of the Infant ALL Gene Expression Signature Using the Oncomine Database.

Table S7. Gene Expression Profiles of CD10+ vs. CD10 Infant ALL Cells.

Table S8. Gene Expression Profiles of Infant Pro-B ALL Cells.

Table S9. Gene Expression Profiles of Leukemic Cells from Very Young Infants with ALL.

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