Leukemia (2006) 20, 1028–1034 & 2006 Nature Publishing Group All rights reserved 0887-6924/06 $30.00 www.nature.com/leu ORIGINAL ARTICLE

Gene expression profiling of CD34 þ cells identifies a molecular signature of chronic myeloid leukemia blast crisis

C Zheng1,LLi2, M Haak2, B Brors3, O Frank1, M Giehl1, A Fabarius1, M Schatz1, A Weisser1, C Lorentz1, N Gretz2, R Hehlmann1, A Hochhaus1 and W Seifarth1

1III. Medizinische Universita¨tsklinik, Fakulta¨tfu¨r Klinische Medizin Mannheim der Ruprecht-Karls-Universita¨t Heidelberg, Mannheim, Germany; 2Zentrum fu¨r Medizinische Forschung (ZMF), Fakulta¨tfu¨r Klinische Medizin Mannheim der Ruprecht-Karls-Universita¨t Heidelberg, Mannheim, Germany and 3Division Intelligente Bioinformatik Systeme, DKFZ - German Cancer Research Center, Heidelberg, Germany

Despite recent success in the treatment of early-stage disease, genesis of CML.1 Chronic myeloid leukemia in blastic phase is blastic phase (BP) of chronic myeloid leukemia (CML) that is the transition of CML in chronic phase (CP) or accelerated phase characterized by rapid expansion of therapy-refractory and (AP) to an acute leukemia, characterized by rapid extramedullar differentiation-arrested blasts, remains a therapeutic challenge. 4 4 The development of resistance upon continuous administration expansion ( 30% blasts in or 50% in of imatinib mesylate is associated with poor prognosis pointing peripheral ) of a population of myeloid or lymphoid to the need for alternative therapeutic strategies and a better differentiation-arrested progenitor cells. These cells show understanding of the molecular mechanisms underlying dis- enhanced proliferation and survival which is associated with ease progression. To identify transcriptional signatures that resistance to chemotherapy and poor prognosis.2–4 may explain pathological characteristics and aggressive beha- The mechanisms responsible for transition into BP are still vior of BP blasts, we performed comparative gene expression incompletely understood. However, recent advances in leuke- profiling on CD34 þ Ph þ cells purified from patients with untreated newly diagnosed chronic phase CML (CP, n ¼ 11) and mia biology and emerging data about imatinib- from patients in BP (n ¼ 9) using Affymetrix oligonucleotide resistant CML and BCR-ABL-driven genomic instability have led arrays. Supervised microarray data analysis revealed 114 to the formulation of a plausible mechanistic model of CML À4 differentially expressed genes (Po10 ), 34 genes displaying blast crisis. One assumption of this model is that BCR-ABL is more than two-fold transcriptional changes when comparing CP and BP groups. While 24 of these genes were down- directly or indirectly responsible for progressive genomic regulated, 10 genes, especially suppressor of cytokine signal- instability or epigenetic changes, which occur at the CML stem ling 2 (SOCS2), CAMPATH-1 antigen (CD52), and four human and/or progenitor cell level and contributes to the emergence of leukocyte antigen-related genes were strongly overexpressed increasingly malignant and imatinib-resistant cell clones. The in BP. Expression of selected genes was validated by real-time- degree of genomic instability is proportional to the level of BCR- polymerase chain reaction and flow cytometry. Our data ABL kinase activity.5–8 Second, ABL-targeted therapy does not suggest the existence of a common gene expression profile of CML-BP and provide new insight into the molecular eradicate CML stem cells that may serve as reservoirs for occult phenotype of blasts associated with disease progression and CML progression. The detection of BCR-ABL-positive CD34 þ high malignancy. cells in patients with complete cytogenetic response (CCR) Leukemia (2006) 20, 1028–1034. doi:10.1038/sj.leu.2404227; under imatinib treatment demonstrates that the drug rather published online 13 April 2006 inhibits proliferation of CML primitive precursors than to induce Keywords: CML; blast crisis; microarray; expression profiling; apoptosis. Thus, the proliferative advantage of BCR-ABL- CD52 positive progenitors is restricted, but residual tumor cells will not be eliminated by the drug.4,9,10 Together, both phenomena conspire resulting in an acquired loss of hematopoietic cell differentiation leading to the highly aggressive, acute leukemic phenotype of CML-BP. Introduction To elucidate molecular mechanisms of CML pathogenesis, microarray approaches have been successfully used to charac- Chronic myeloid leukemia (CML) is a clonal myeloproliferative terize normal and BCR-ABL-positive primary CD34 þ hemato- disorder of hematopoietic stem cells and is characterized by the poietic stem and progenitor cells derived from CML patients or genomic reciprocal translocation t(9;22)(q34;q11), which results corresponding in vitro model systems.11–15 A large body of in the formation of the Philadelphia (Ph) . As a information has been established regarding BCR-ABL-modu- consequence, the bcr gene on chromosome 22 is fused to the lated expression of genes which are involved in regulation of abl gene on chromosome 9, resulting in a novel chimeric bcr- chromosome/DNA dynamics, apoptosis, adhesion, in altered abl gene. The encoded BCR-ABL oncoprotein is a constitutively DNA repair or duration of CML-CP.14,16 activated tyrosine kinase and plays a key role in the patho- Therefore, we considered the microarray technique promising for identification of transcriptional signatures of disease progres- Correspondence: Dr W Seifarth, III. Medizinische Universita¨tsklinik, sion that may lead to the prospect of new treatments based on Fakulta¨tfu¨r Klinische Medizin Mannheim der Ruprecht-Karls-Uni- the improved understanding of the molecular pathogenesis of  versita¨t Heidelberg, Wiesbadener Stra e 7-11, 68305 Mannheim, BCR-ABL-positive CML-BP. For the first time, we examined Germany. E-mail: [email protected] highly enriched CD34 þ hematopoietic stem and progenitor Received 22 November 2005; revised 16 February 2006; accepted 3 cells from patients in CML-BP by means of Affymetrix HG- March 2006; published online 13 April 2006 U133A oligonucleotide arrays targeting 14 500 human genes. Molecular phenotype of CML-BP CD34 þ cells C Zheng et al 1029 Comparison with CP-derived tumor cells revealed a distinct BP- validation, where an inner three-fold cross-validation loop was related gene expression signature and novel aspects associated used to optimize the parameters of the kernel function by grid with CML progression. Moreover, some differentially expressed search, and an outer 10-fold cross-validation loop was used to genes of potential prognostic and therapeutic value were determine classification accuracy.21 A discriminative gene identified. expression pattern was obtained by using recursive feature elimination together with support vector machines.22 The classifier with the best classification accuracy as determined Materials and methods by 10-fold cross-validation is chosen, which provides a selection of genes with high discriminative power. In our Samples and purification of CD34 þ cells analysis, a classifier based on 512 genes showed highest After informed consent, 20 ml of peripheral blood (PB) was classification accuracy. Heatmaps were constructed using harvested from 20 bcr-abl-positive CML patients, 11 from z-transformed gene expression values, that is measurements untreated patients in CML-CP at diagnosis and nine from were scaled to have gene-wise zero mean and gene-wise unit patients in CML-BP. Cytogenetically, all patients had more than variance. Columns (samples) and rows (probe sets) of the gene 95% Ph chromosome-positive metaphases and diagnosis ‘blast expression matrix were reordered by hierarchical clustering crisis’ was characterized by 430 and 450% blasts plus using an Euclidean distance metric and the complete linkage promyelocytes in PB and bone marrow, respectively. In contrast algorithm. All calculations were performed using R and to CP patients, six of nine BP patients had additional Bioconductor software.23,24 In particular, we used R version chromosomal aberrations as given in Supplementary Table 1. 2.1.0, and the packages Affy version 1.6.7, vsn version 1.6.3, Eleven patients were female and nine were male. Median age e1071 version 1.5-8, and MCRestimate version 1.2.6. was 51 years (range 21–73) for newly diagnosed CP patients and 64 years (range 54–81) for patients in BP. Six BP patients had myeloid, three had mixed myeloid/lymphoid blasts. PB mono- Quantitative real-time polymerase chain reaction) nuclear cells were purified by Ficoll-Hypaque (GE Healthcare For confirmation of microarray results, quantitative real-time Bio-Sciences, Freiburg, Germany) density gradient centrifuga- polymerase chain reaction (QRT-PCR) (LightCycler, Roche, tion. CD34 þ cells were positively selected using the midiMACS Mannheim, Germany) was performed for all samples employing immunomagnetic separation system (Miltenyi Biotec, Bergisch specific primer pairs and hybridization probes for a panel of Gladbach, Germany). Purities of CML CD34 þ cells ranged selected genes (suppressor of cytokine signalling 2 (SOCS2), between 90 and 99% (data not shown). CAMPATH-1 antigen (CD52), CD74, CD34, GAPDH). Trans- cripts of the housekeeping gene glycerol aldehyde 3 phosphate dehydrogenase served as internal control for relative quantifica- RNA isolation and oligonucleotide microarray tion. Total RNA (2 mg) was reverse transcribed using the hybridization Omniscript Kit (Qiagen, Hilden, Germany). Reverse transcribed Total RNA was extracted from CD34 þ cells with the RNeasy RNA (200 ng) was assayed in a total volume of 20 ml PCR mix Mini Kit (Qiagen, Hilden, Germany) and quality assayed using (LightCycler Fast-Start DNA MasterPlus Hybridization Probes, an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA, USA). Roche) containing 10 pmol of each primer and 0.3 pmol of each Hybridization probe preparation and HG-U133A microarray fluorescent probe. Primer and hybridization probes are given in processing were performed according to the standard protocols Table 1. Amplification was performed using a 10-min denatura- available from Affymetrix (Santa Clara, CA, USA). Detailed tion step at 951C, followed by 45 cycles of 30 s denaturation at information about experimental settings and raw data have been 951C, 30 s primer annealing at 541C(CD52, CD74, CD34, submitted to ArrayExpress, a public repository for microarray SOCS2) and 551C(GAPDH) and a polymerization step at 721C data and are available under accession number E-MEXP-480 for 45 s. For each QRT-PCR run a standard curve using serial (http://www.ebi.ac.uk/arrayexpress). cDNA dilutions was constructed and the relative number of target molecules of each sample was calculated by reference to this curve. The crossing points of curves were determined by the Microarray data analysis and statistical procedures LightCycler 3.5 software. All samples were analyzed in duplicate Raw microarray data from Affymetrix CEL files were normalized and for corroboration, amplicons were visualized on 1.5% using the method of Huber et al.17 After normalization, probes agarose gels after ethidium bromide staining (data not shown). from one probe set are summarized using the median polish function resulting in one value per probe set which is scaled to 18 be on a log2 scale. This method has proven to be superior to Flow cytometry Affymetrix Microarray Suite methods in comparative studies CD34 þ bcr-abl-positive hematopoietic stem and progenitor (http://affycomp.biostat.jhsph.edu). Analysis of variance (ANO- cells from six patients included in the microarray experiments VA) analysis was performed using SAS software package were subjected to flow cytometric analysis of CD marker MicroArray Solutions version 1.3 (SAS Institute GmbH, Heidel- expression. About 1 Â 106 cells were stained with FITC- and PE- berg, Germany). Loglinear mixed models were fitted for values labeled antibody conjugates. These were anti-CD52-FITC (clone of perfect-matches,19 where stage of disease (CP or BP), type of 3H1532, BioMol, Hamburg, Germany), anti-CD74-FITC (clone fusion transcript (b2a2, b3a2), gender (female, male) and all By2, Santa Cruz Biotechnology, Santa Cruz, CA USA), anti- their possible interaction terms were considered to be with CD13-PE (clone L138) and anti-CD19-PE (clone 4G7, both from constant effects and the chip ID with random effect. Gene Becton Dickinson, Pharmingen, Germany). Samples were annotation was obtained through the Affymetrix NetAffx web prepared using a two-color staining method including a final site (http://www.affymetrix.com/analysis/index.affx). To test for fixation step in 1% paraformaldehyde. After gating, the robustness of microarray data, we used support vector machines percentage of CD52 þ and CD74 þ cells was measured in the (SVM) with a linear kernel function for supervised learning.20 CD13 þ /CD19 þ cell fractions. All analyses were performed on Classification accuracies were determined by nested cross- a FACScan flow cytometer (Becton Dickinson).

Leukemia Molecular phenotype of CML-BP CD34 þ cells C Zheng et al 1030 Table 1 Primer pairs and hybridization probes for quantitative real-time PCR (QRT-PCR) on selected genes

Symbol Position Oligonucleotide sequence (50-30) Accession no

SOCS2 Forward GCTCGGTCAGACAGGATGG NM_003877 Reverse TCGATTCGAAGATTAGTTGGTCC Probe1 AGAGGCACCAGAAGGAACTTTCTTGATT-FL Probe2 LCR640-GAGATAGCTCGCATTCAGACTACCTACTAACAAT-PH

CD52 Forward CCTGGTTATGGTACAGATACAAACTG NM_001803 Reverse CTGAGACGTGTCACCTCAACT Probe1 GGATGCTGAGGGGCTGCTGGTT-FL Probe2 LCR640-GGCTGGTGTCGTTTTGTCCTGAGAGT-PH

CD74 Forward GGAGAACCTGAGACACCTTAAGAA NM_004355 Reverse GGTCCTCCAGTTCCAGTGA Probe1 CCTGCTCATTTCAAACAGGAGCCA-FL Probe2 LCR640-TGGTGCATCCAGCTCTCAAAGACCT-PH

CD34 Forward TGCTGGGGCCCAGGTAT NM_001773 Reverse CCGAGGTGACCAGTGCA Probe1 GCTTTTTCATAAGTTGGAGTTTGCTGGA-FL Probe2 LCR640-TTCTGTTCTGTTGGCCAAGACCAG-PH

GAPDH Forward GAAGGTGAAGGTCGGAGTC J02642 Reverse GAAGATGGTGATGGGATTTC Probe1 AGGGGTCATTGATGGCAACAATATCCA-FL Probe2 LCR640-TTTACCAGAGTTAAAAGCAGCCCTGGTG-PH Oligonucleotide modifications: FL, Fluorescein; LCR640, Lightcycler Red 640; PH, Phosphate.

Results identified as the top most altered transcripts in CD34 þ Ph þ tumor cells derived from CML-BP, confirming the robustness of The molecular signature of CML-BP compared our microarray data and the existence of a common gene to CML-CP expression signature in CML-BP. In this study, gene expression profiles of highly enriched bcr-abl- positive CD34 þ stem and progenitor cells from PB of 11 patients with untreated CML in CP were compared with those of Corroboration of microarray data by QRT-PCR nine patients in BP. Affymetrix HG-U133A oligonucleotide- To validate the data obtained by Affymetrix oligonucleotide based gene chips were used featuring probe sets for expression arrays, the transcript levels of SOCS2, CD52, CD74, and CD34 level analysis of 18 400 transcripts and variants, including were comparatively analyzed in CD34 þ bcr-abl-positive cells 14 500 well-characterized human genes. from all patients under investigation. Quantitative real-time PCR Application of loglinear mixed models fitted for values of confirmed that all four genes were differentially expressed perfect-matches (repeated measures ANOVA, Po10À4 Bonfer- (Figure 2a). Except for SOCS2, the relative expression differ- roni correction), revealed 114 differentially expressed genes ences were even more striking compared to the preceding (listed in Supplementary Table 2), 34 genes displaying more microarray experiments. For example, while CD52 transcript than twofold transcriptional changes when comparing CP and levels were increased 2.8-fold in microarray analysis (myeloid BP groups, as visualized by volcano plotting (Figure 1a). As BP vs CP), a mean fold change of 4.6 was observed in the shown in Table 2, 10 genes were overexpressed in BP patients corresponding QRT-PCR experiments. Comparing BP samples to including the SOCS2, CD52 (the CAMPATH-1 antigen), four myeloid/lymphoid mixed type CP only, an eight-fold and over immune response-related genes (HLA-DRA, HLA-DRB, HLA- 10-fold increase was observed in microarray and QRT-PCR DPA, CD74), and the CD34. Moreover, 24 analysis, respectively, confirming higher CD52 expression in genes were downregulated in BP and included the myeloid lymphoid than in myeloid blasts (7.6- vs 4.6-fold relative lineage marker myeloperoxidase (MPO), the transcription increase compared to CP) as observed by others.25 Consistent factors JUNB, FOS, FOSB, KIf4, C/EBPB; the cell cycle results were also obtained for SOCS2, CD34 and CD74, the regulation gene G0S2; the signal transduction receptor PLAUR; latter showing a 4.8-fold higher expression in lymphoid than in the Calcium binding S100P and S100A12; the myeloid blasts (2.8- vs 13.4-fold increase comparing myeloid apoptosis-related gene Lipocalin2 and others. To approve (m-BP) to myeloid/lymphoid BP (m/l-BP). Thus, our microarray robustness of data generated from ANOVA, support vector data were thoroughly confirmed by QRT-PCR. machine classification (SVM) was performed revealing 512 genes as the most accurate classifier for discrimination between CML-CP and BP diagnostic groups. A clustered display (heat CD52 and CD74 flow cytometry analysis map) of the data is shown in Figure 1b and demonstrates a clear- Differential gene expression of CD52 and CD74 was examined cut discrimination between CP and BP samples despite by flow cytometry of CD34 þ bcr-abl-positive cells from six additional karyotypic alterations in six of nine CML-BP samples patients, corresponding to two specimens each from CP, under investigation (Supplementary Table 1). Irrespective to the myeloid BP, and myeloid/lymphoid mixed-type BP, respec- type of algorithm (SVM, ANOVA), the same gene IDs were tively. Fluorochrome-conjugated antibodies directed against

Leukemia Molecular phenotype of CML-BP CD34 þ cells C Zheng et al 1031 lymphoid and myeloid cells of the same representative patient were compared (Figure 2b, m/l-BP). Similar FACS results were obtained for CD74 surface showing 1.9-fold (m-BP vs CP) and 4.6-fold (m/l-BP vs CP) increased expression levels. All these findings were in line with the preceding microarray and QRT-PCR data (Figure 2a).

Discussion

Clinically, responsiveness to antileukemic treatment makes up the major difference between CP and BP of CML. On molecular level, the malignant evolution of the relatively benign CP to the very aggressive BP is associated with major changes in phenotype and genotype of leukemic cells, which is reflected by differences in the gene expression profile. In this study, we compared gene expression profiles from newly diagnosed CP (n ¼ 11) and BP (n ¼ 9) patient groups to identify transcriptional signatures associated with disease progression and to investigate pathomechanisms that may be useful for identification of novel therapeutic targets potentially useful for therapy of CML advanced stages. To rule out one important limitation of microarray technology – the heterogeneity of patient samples – only highly enriched fractions of bcr-abl-positive CD34 þ progenitor and stem cells, all derived from PB samples were used in this study. All samples of CML patients in CP, recruited at time of diagnosis, were taken before start of treatment. In contrast, BP patients had prodromal therapy regimens including both interferon-alpha and imatinib. For validation of microarray results, additional methods were applied. Genes of interest were further analyzed on transcriptional and protein levels by QRT- PCR and flow cytometry, respectively. Having used different algorithms for validation of microarray data, we identified a consistent CML-BP-specific gene expres- sion profile irrespective to the cytogenetic heterogeneity of our CML-BP samples. This signature is distinct from that of CP and features 34 known genes with more than twofold transcriptional changes, which may have impact on malignant progression toward BP. While some of these genes that are functionally Figure 1 Graphical display of comparative gene profiling data. related to cell cycle regulation, transcription, intracellular Results of ANOVA are shown as Volcano plot (a). The negative log - 10 signalling, adhesion, and immune response have already been transformed p-values are plotted against log2 fold change. Comparison of BP (n ¼ 9) vs CP (n ¼ 11) gene expression profiles revealed 114 reported by others and, thus, are confirmed in accordance with known genes featuring P-values o10À4 (marked by horizontal line in previous reports as related to CML malignant transformation, red) and fold changes 42 (limits shown by vertical lines in grey). other genes are novel in this context. These provide new insight Twenty-four of these genes (e.g. myeloperoxidase (MPO)) were into the molecular phenotype of therapy-resistant and differ- downregulated in BP (upper left area of the plot), 10 genes including entiation-arrested CML-BP blasts. suppressor of cytokine signalling 2 (SOCS2) and CAMPATH-1 antigen SOCS2 displayed the most increase in transcript level in our (CD52) were overexpressed in BP (upper right area). See Table 2 and Supplementary Table 2 for gene lists. Heatmap of gene expression study. Suppressor of cytokine signalling is involved in Ras and values (b) in 20 samples derived from CD34 þ Ph þ tumor cells PI-3 kinase signal transduction cascades via binding to the IGF-1 purified from patients in Chronic myeloid leukemia in chronic phase receptor and has been reported to be overexpressed in a bcr-abl- (CML-CP) (n ¼ 11) and in BP (n ¼ 9). Red denotes high, blue low dependent manner in CML blasts of advanced stages. It has been expression compared to the mean. The colored bar above the heatmap suggested that SOCS2 is part of a defective negative feedback refers to the CP (green) or BP (pink) group. The gene expression is loop that is unable to control the growth-promoting effects of shown for the 512 genes with the highest discriminatory power as 26 obtained by recursive feature elimination analysis. BCR-ABL in blast crisis. Thus, the BCR-ABL-induced upregu- lation well explains the more than threefold increase of SOCS2 transcript levels in BC blasts in our study confirming the previous findings of Schultheis and co-workers. At the opposite end of the list, MPO was identified as the gene four different surface molecules were employed: antiCD52, with the most decreased transcript levels in BP patients. As MPO antiCD74, antiCD13 (myeloid marker), antiCD19 (lymphoid is highly reputated as specific myeloid-lineage marker, this marker). Compared to CD34 þ bcr-abl-positive cells from CP, observation seems unexpected, being not in keeping with the CD52 expression was 5- and 7.3-fold higher on corresponding myeloproliferative nature of CML. However, our microarray cells from m-BP and myeloid/lymphoid mixed-type BP, respec- data confirm recent reports about MPO deficiency as an intrinsic tively (Figure 2b). This confirms the QRT-PCR data indicating property of blasts of all phases of CML, a phenomenon that preferential expression of CD52 on lymphoid blasts when obviously reflects the perturbation of myelopoiesis in CML.27

Leukemia Molecular phenotype of CML-BP CD34 þ cells C Zheng et al 1032 Table 2 Genes (n ¼ 34) that distinguish CP and BP stages of CML (Po10À4), sorted by fold change (42oro0.5)

Gene symbol Description Àlog10 (P-value) Fold change Transcript ID

SOCS2 Suppressor of cytokine signaling 2 6.2530 3.3449 NM_003877 CDW52 CD52 antigen (CAMPATH-1 antigen) 8.1554 3.2894 NM_001803 HLA-DRB1 Major histocompatibility complex, class II, DR beta 1 4.8959 2.8763 NM_002124 HLA-DRA Major histocompatibility complex, class II, DR alpha 4.3082 2.8328 NM_019111 HLA-DPA1 Major histocompatibility complex, class II, DP alpha 1 4.0166 2.8004 NM_033554 CD74 CD74 antigen (invariant polypeptide of MHC, class II antigen-associated) 5.0667 2.5665 NM_004355 ARL6IP5 ADP-ribosylation-like factor 6 interacting protein 5 4.0050 2.2060 NM_006407 TRIM22 Tripartite motif-containing 22 5.2440 2.1824 NM_006074 CD34 CD34 antigen 4.5438 2.1700 NM_001773 GIMAP6 GTPase, IMAP family member 6 6.9169 2.0969 NM_024711 MAD MAX dimerization protein 1 4.0080 0.4942 NM_002357 APOBEC3A Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A 4.2079 0.4574 NM_145699 FTH1 ferritin, heavy polypeptide 1 4.6874 0.4566 NM_002032 PLAUR Plasminogen activator, 4.2273 0.4381 NM_001005376 SAT Spermidine/spermine N1-acetyltransferase 4.5646 0.4263 NM_002970 CEBPB CCAAT/enhancer binding protein (C/EBP), beta 4.0394 0.4173 NM_005194 JUNB Jun B proto-oncogene 4.7928 0.3882 NM_002229 FOSB FBJ murine osteosarcoma viral oncogene homolog B 4.6902 0.3692 NM_006732 C5R1 Complement component 5 receptor 1 (C5a ligand) 4.1127 0.3671 NM_001736 FCER1G Fc fragment of IgE, high affinity I, receptor for; gamma polypeptide 4.7605 0.3642 NM_004106 KLF4 Kruppel-like factor 4 (gut) 4.6343 0.3538 NM_004235 CSTA Cystatin A (stefin A) 4.0943 0.3222 NM_005213 ZFP36 Zinc finger protein 36, C3H type, homolog (mouse) 5.0225 0.3104 NM_003407 RNASE3 Ribonuclease, RNase A family, 3 (eosinophil cationic protein) 5.2937 0.2917 NM_002935 PRTN3 Proteinase 3 (serine proteinase, neutrophil, Wegener granulomatosis antigen) 5.5335 0.2784 NM_002777 S100P S100 calcium binding protein P 4.0904 0.2366 NM_005980 FOS V-fos FBJ murine osteosarcoma viral oncogene homolog 5.1133 0.2343 NM_005252 IL8 Interleukin 8 4.7036 0.2281 NM_000584 S100A12 S100 calcium binding protein A12 (calgranulin C) 4.3704 0.2059 NM_005621 RNASE2 Ribonuclease, RNase A family, 2 (liver, eosinophil-derived neurotoxin) 5.7315 0.2045 NM_002934 LCN2 Lipocalin 2 (oncogene 24p3) 4.1990 0.1960 NM_005564 LTF Lactotransferrin 5.4481 0.1784 NM_002343 G0S2 Putative lymphocyte G0/G1 switch gene 5.3802 0.1650 NM_015714 MPO Myeloperoxidase 7.3186 0.1433 NM_000250

Figure 2 Corroboration of microarray data by QRT-PCR (a). Bars indicate increased levels (fold change) of suppressor of cytokine signalling 2 (SOCS2), CAMPATH-1 antigen (CD52), CD74, and CD34 transcripts in CD34 þ bcr-abl-positive cells from BP (n ¼ 9) compared to corresponding tumor cells from CP (n ¼ 11) for all specimens tested in microarray and QRT-PCR experiments. For CD52 and CD74, fold changes are given separately for m-BP (n ¼ 6) and m/l-BP (n ¼ 3) samples. (b) Flow cytometry analysis shows distribution of CD52 and CD74 proteins on CD34 þ bcr- abl-positive tumor cells. Representative plots show gating of the CD34 þ progenitor cell population, CD52 and CD74 distribution on tumor cells from CP, and on CD13 þ (myeloid) and CD19 þ (lymphoid) tumor cells from m-BP and mixed type m/l-BP, respectively.

Elevated transcript and protein levels were observed for CD52 and hematopoietic stem cells.30,31 The unexpected upregulation in CML-BP. Originally described as a human leukocyte of CD52 in CML-BP blasts suggests that CD52 presentation may differentiation antigen, CD52 is a small glycosylphosphatidy- be a marker of blastic transformation. Altered expression linositol (GPI)-anchored of unknown function with patterns of CD52 proteins have been found in various human a mature peptide comprising 12 amino acids only.28,29 While cancers when compared to corresponding normal cells. For abundantly present on the surface of most normal and malignant example, membrane-bound CD52 antigen is strongly expressed PB lymphocytes, monocytes, and macrophages, it has been by many B-cell and some T-cell malignancies, and a minority of shown to be absent from most myeloid cells, platelets, erythroid myeloid leukemias.31,32 This concurs with our findings of

Leukemia Molecular phenotype of CML-BP CD34 þ cells C Zheng et al 1033 preferential CD52 expression in lymphoid compared to myeloid potential therapeutic role of induction of C/EBPbeta expression blasts within a single representative patient. The ectopic in acute phase of CML. expression of CD52 protein on a significant proportion of BP Furthermore, we observed BP-related transcriptional down- myeloid blasts may be of major clinical importance as CD52 regulation of lipocalin (LCN2), the G0/G1 switch gene G0S2, may serve as a novel target for alemtuzumab (Campath-1H, and the differentiation- and anti-pathogen response-related anti-CD52), a recombinant humanized mAB that has been genes S100A12 and S100P. Although dysregulated genes in proven very effective in treatment of B-cell chronic lymphocytic BP cells obtained from bone marrow have been reported as leukemia (B-CLL) and other lymphoproliferative disor- different from those detected in PB leukemia blasts, our data ders.25,33,34 We consider CD52 as a useful marker of disease about these transcripts concur with a previous microarray study progression and as potential target of future combinatorial reporting on bone marrow-derived BP blasts in comparison to therapies for CML advanced stages. appropriate healthy donor samples.14 However, we found no Interestingly, CD34 þ Ph þ PB blasts from CML-BP displayed overlap with listed genes therein when bone marrow samples of elevated levels of MHC class II complex-related genes CML-CP were compared to CML-BP samples. This discrepancy HLA-DRB1, HLA-DRA, HLA-DPA1, and CD74. While in the gene expression profiles may be explained by the use of a coordinated expression and proper processing of these poly- more homogenous cell population in our study. peptides are crucial for efficiency of professional antigen presenting cells, silencing or aberrant expression of MHC class I and class II molecules has been reported to be associated Conclusion with high-grade malignancy and impairment of immunosurveil- lance.35,36 Recently, elevated transcript levels of HLA-DRA, Our microarray-based study identifies a common gene expres- HLA-DRB but a lack of mature HLA-DR beta chains has been sion profile of CML-BP. The transcriptional signature confirms unexpectedly found in ovarian and other cancers. Since in several previous findings about the biology of CML and adds parallel, high levels of CD74 expression in both the cytoplasm more genes to the list of potential gene products that contribute and plasma membrane of ovarian tumor cells were detected, to disease progression and evolution of malignant blastic it was argued that overexpression of the chaperone CD74 that phenotypes. Moreover, novel properties of malignant blasts is essential for HLA-DR trafficking and antigen loading may such as overexpression of CD52 cell surface protein were contribute to the observed lack of mature MHC molecules.36–38 discovered. We believe that this work expands our knowledge The same proposed pathomechanism may play a role in about CML-BP and provides support for development of future CML-BP as we detected up to 4.6-fold elevated CD74 protein therapies of CML advanced stages. levels in CD34 þ Ph þ BP blasts pointing to aberrant post- translational processing of HLA polypeptides. This may explain Acknowledgements the abnormal phenotypes in CML. Owing to the elevated levels of CD74 protein on BP blasts compared to We are grateful to Alex D Greenwood (GSF-Gesellschaft fu¨r those from CP, this surface protein may be useful as marker of Umwelt und Gesundheit, Mu¨nchen, Germany) for critically disease progression and could be of potential interest for future reading the manuscript. This work was financially supported by therapies of BP. Grant R03/09 of the Deutsche Jose´ Carreras Leuka¨mie-Stiftung, þ Although uniform fractions of highly purified CD34 tumor Mu¨nchen, Germany, and by funds of the European Leukemia Net cells have been used in this study, cells from BP show elevated (ELN), contract no. LSHC-CT-2004-503216. levels of CD34 transcripts (2.2-fold increase). CD34, a highly glycosylated type I membrane protein, is a marker of early hematopoietic progenitor cells and a putative adhesion mole- References cule with essential functions in early hematopoiesis. 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