ARTICLE IN PRESS

Experimental Hematology 2008;-:-–-

Molecular profiling of candidate humanhematopoietic stem cells derived from human embryonic stem cells

Farbod Shojaeia,b and Pablo Menendeza,c

aRobarts Research Institute; bUniversity of Western Ontario,

London, ON, Canada; cBanco Andaluz de Celulas Madre/University of Granada, Granada, Spain

(Received 16 March 2008; revised 5 May 2008; accepted 2 June 2008)

Offprint requests to

Bioedicas, Parque Tec

Granada 18100, Spain

0301-472X/08 $–see

doi: 10.1016/j.exph

Objective. Human embryonic stem cells (hESCs) have been differentiated into CD45+ hema-topoietic cells in vitro. A subset of hESC–derived CD45+ cells coexpresses CD34 and show pro-genitor function in colony–forming units assays. These hESC–derived hematopoietic stem(HSC), or progenitor cells, display, however, distinct functional properties, including poor re-population ability; impaired differentiation; and lack of homing when compared to HSCsfrom fetal blood (FB) or cord blood. Whether these differences are cell–autonomous or drivenby their microenvironment remains to be elucidated.

Materials and Methods. Here, to gain insight into the molecular determinants accounting forthese functional differences, a gene–expression profiling comparing candidate hESC–HSCs vsFB–derived HSCs (FB–HSCs) was conducted.

Results. Only 2.4% of differentially expressed transcripts were common for FB–HSCs andcandidate hESC–HSCs, suggesting a completely different molecular signature for HSCs iso-lated from two different in utero ontogeny stages. Several key hematopoietic transcription fac-tors, apoptosis and cycle regulators, and cell aggregation and homing genes may contribute toexplain the functional differences between hESC–HSCs and FB–HSCs. Importantly, compo-nents of Notch and Wnt signaling pathways involved in HSC self–renewal and hematopoieticspecification were significantly underexpressed in candidate hESC–HSCs.

Conclusion. Our study provides a platform to understand the molecular basis underlyinghESC–HSCs functional properties. Future studies are needed to address the functional roleof the transcripts identified here, eventually leading to identification of intrinsic determinantsand cytokines driving physiological specification of hESCs into definitive HSCs. � 2008ISEH - Society for Hematology and Stem Cells. Published by Elsevier Inc.

Hematopoietic stem cells (HSCs) are responsible for main-taining the homeostasis of the hematopoietic systemthroughout the life of an individual via two fundamentaland unique properties: 1) their ability to self–renew to gen-erate new HSCs upon mitotic division, and 2) their capacityto differentiate toward downstream progenitors (hematopoi-etic progenitor cells [HPCs]) that eventually give rise tomature hematopoietic cells [1]. Although much informationhas been gained during the last decade, the molecularmechanisms regulating these properties in human HSCshave yet to be fully understood [2]. In vivo xenotransplan-tation studies of human hematopoietic cells into nonobese

: Farbod Shojaei, Ph.D., Instituto de Investigaciones

nologico de la Salud, Avenida del Conocimiento s/n,

.; E-mail: farbodshojaei@hotmail.com

front matter. Copyright � 2008 ISEH - Society for Hemat

em.2008.06.001

diabetic/severe combined immunodeficient (NOD/SCID)mice have demonstrated that Lin�CD34þCD38� cells areenriched for somatic HSCs and are capable of reconstitut-ing the hematopoietic system, whereas the HPC population(Lin�CD34þCD38þ) lacks reconstitution capacity in thesame recipients [3,4].

Recent studies have indicated the ability of human embry-onic stem cells (hESCs) to differentiate into hematopoieticcells in the presence of hematopoietic cytokines and bonemorphogenetic protein (BMP)–4 [5] and also in a coculturesystem in the presence of stromal cells [6]. These hESC–derived hematopoietic cells express CD45 and are capableof generating colonies in colony–forming unit (CFU) assays.Further investigations showed that hESC–derived CD45þ

cells are capable of extremely low–level reconstitution inNOD/SCID mice upon intra–bone marrow injection [7,8].However, compared to their somatic counterparts, the

ology and Stem Cells. Published by Elsevier Inc.

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hESC–derived CD45þ cells show distinct characteristics, in-cluding lack of proper homing to the bone marrow upon in-travenous transplantation and very low level of engraftmentin the recipients upon intra–bone marrow injection. Whetherthese differences are cell–autonomous or initiated by the sur-rounding microenvironment remains to be elucidated.

Here, based on expression of CD45, CD34, and CD38 asconventional markers identifying somatic human HSCs(CD45þCD34þCD38�) and HPCs (CD45þCD34þCD38þ)[3], subsets of hESC–derived CD45þCD34þCD38� (hereaf-ter candidate hESC–HSCs) and CD45þCD34þ CD38þ

(hereafter hESC–HPCs) cells were fluorescein–activatedcell sorting (FACS)–isolated. Next, the gene–expression pro-file in candidate hESC–HSCs was evaluated in comparisonwith fetal blood (FB) CD45þCD34þCD38� cells (hereafterFB–HSCs), which represent in utero HSCs at later ontogenystage that were previously shown to be enriched in HSCactivity and in vivo engraftment potential [9].

Analysis of key developmental signaling pathways in-volved in regulating somatic HSC cell fate, including Notch[10], Wnt [11,12], BMPs [13], and Sonic hedgehog (Shh)[14], revealed that, in contrast to BMPs and Shh,components of Notch and Wnt signaling pathways are sig-nificantly underexpressed in candidate hESC–HSCs, em-phasizing the importance of both Notch and Wntsignaling pathways also in HSC cell–fate specificationwithin the human embryo. The current study provides fur-ther insights into the mechanisms underlying human em-bryonic hematopoietic specification and identifies keycomponents of the Notch and Wnt signaling pathways ascrucial components for derivation of definitive HSCs fromhESCs. This may also support recent studies suggestingthat mutations in key components of Notch and Wnt signal-ing pathways can be early or initiating events in acute in-fant/childhood leukemia arising prenatally (embryonic orfetal stage), possibly controlling the embryonic specifica-tion toward normal vs leukemic hematopoiesis [15].

Materials and methods

Human FB cellsSamples (n 5 12) of human FB from early gestation (18–20 weeks)were obtained in conjunction with local ethical and biohazard au-thorities of the University of Western Ontario and London HealthSciences Center as described [16]. FB samples were diluted (1:4)with a–minimal essential medium (GibcoBRL, Grand Island, NY,USA) or phosphate–buffered saline (PBS), and mononuclear cells(MNCs) were isolated as described previously [17].

Cell purification from FBLin� cells were isolated from FB using a cocktail of microbead–conjugated monoclonal antibodies (Stem Cell Technologies,Vancouver, British Columbia, Canada) including CD2, CD3,CD14, CD16, CD19, CD24, CD41, CD56, CD66b, and glyco-phorin A, to remove mature hematopoietic cells. Next, the Lin�

population was stained with 7–amino–actinomycin D to exclude

dead cells and anti–human CD45–allophycocyanin, anti–humanCD34–fluorescein isothiocyanate and anti–human CD38–phycoer-ythrin (all from Becton Dickinson, San Jose, CA, USA) antibodiesto isolate the subsets: CD45þCD34þCD38� (HSCs) andCD45þCD34þCD38þ (HPCs). Stained cells were sorted usinga FACSVantage SE (Becton Dickinson) using the sorting gates il-lustrated in Figure 1.

Human ESC culture, embryoid bodyformation, and hematopoietic differentiationApproval for use of established human ESC lines was obtainedfrom the Stem Cell Oversight Committee of the Canadian Instituteof Health Research. CD45þ cells were derived from the hESC lineH9 as described previously [5]. Briefly, karyotypically normal un-differentiated hESCs were maintained in six–well Matrigel (BDBioscience, Bedford, MA, USA)–coated plates in mouse embry-onic fibroblast–conditioned medium [5] supplemented with 8 ng/mL human basic fibroblast growth factor (Invitrogen, Burlington,Ontario, Canada). Culture medium was changed daily and cellswere split weekly using collagenase IV (200 U/mL; Invitrogen).

For embryoid body (EB) formation, collagenase IV–treated cellswere detached from the Matrigel and were transferred to six–welllow attachment plates for overnight incubation in differentiationmedium consisting of knockout Dulbecco ’s modified Eagle ’s me-dium supplemented with 20% non–heat–inactivated fetal bovine se-rum (HyClone, Logan, UT, USA), 1 mM L–glutamine, 0.1 mMb–mercaptoethanol, and 1% nonessential amino acids. On the follow-ing day, cells were treated with fresh medium containing several he-matopoietic growth factors, including stem cell factor (300 ng/mL;Amgen, Thousand Oaks, CA, USA), Flt3 ligand (300 ng/mL; R&DSystems, Minneapolis, MN, USA), interleukin (IL)–3 (10 ng/mL;R&D Systems), IL–6 (10 ng/mL; R&D System), granulocyte col-ony–stimulating factor (50 ng/mL; Amgen), and BMP–4 (50 ng/mL; R&D Systems). EBs were cultured for 15 days and the mediawas changed every 3 days.

Flow cytometric analysisAt day 15 of culture, EBs were dissociated using collagenase B(Roche Diagnostic, Montreal, Quebec, Canada) for 2 hours at37�C followed by 10 minutes incubation at 37�C with Enzyme–free Cell Dissociation Buffer (Invitrogen). Single cell suspensionwas obtained by gentle pipetting and passage through a 70–mmcell strainer (BD Bioscience, Palo Alto, CA, USA) and the disso-ciated cells were stained with anti–CD45– fluorescein isothiocya-nate, anti–CD34–allophycocyanin, anti–CD38–phycoerythrinantibodies and 7–amino–actinomycin D. The CD45þCD34þ

CD38� and CD45þCD34þCD38þ populations were isolated usingthe sorting gates illustrated in Figure 1A. After sorting, around50,000 and 100,000 sorted cells derived from hEBs and FB, re-spectively, were collected for gene–expression studies. A FACS-Calibur machine equipped with the CellQuest software was usedfor both data acquisition and analysis (BD Bioscience). Post–sort purity was constantly O95%.

CFU assaysHuman clonogenic progenitor assays (Fig. 2) were performed byplating 1000 FB–Lin– or hESC–derived CD45þCD34þCD38þ orCD45þCD34þCD38� cell subsets into methylcellulose H4230(Stem Cell Technologies) supplemented with recombinant humangrowth factors: 50 ng/mL stem cell factor, 3 U/mL erythropoietin,

Figure 1. Isolation of CD45þCD34þCD38� (hematopoietic stem cells [HSCs]) and CD45þCD34þCD38þ (hematopoietic progenitor cells [HPCs]) cell sub-

sets from human embryonic stem cell (hESC) and fetal blood (FB). (A) Hematopoietic cells (CD45þ) were differentiated from hESCs as explained in Ma-

terial and Methods section. The CD45þ fraction was then further divided into two populations, CD34þCD38� and CD34þCD38þ cells. The purity post–sort

was O90%. (B) The Lin� population was isolated from FB using a cocktail of antibodies to remove mature hematopoietic cells. The CD45þCD34þCD38�

and CD45þCD34þCD38þ subsets were then fluorescein–activated cell sorting–isolated, using fluorochrome–conjugated antibodies, and post–sort analysis

also confirmed high purity constantly (O90%) in the sorted population.

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10 ng/mL granulocyte–macrophage colony–stimulating factor, and10 ng/mL IL–3. Cells were incubated at 37�C in a 5% CO2 humid-ified atmosphere and colonies counted at day 14 of CFU assay usingstandard morphological criteria [5,16].

Total RNA extraction and amplificationTotal RNA from each sample was extracted using the RNeasy kit(Qiagen, Valencia, CA, USA) along with on–column DNaseI diges-tion to minimize genomic DNA contamination. Total RNA fromeach replicate was amplified using Message Amp aRNA kit (Am-bion, Austin, TX, USA) as described previously [18]. Briefly,cDNA was synthesized from total RNA using poly dT primers fol-lowed by second–strand cDNA synthesis. The double strandedcDNA was used as a template for in vitro transcription reaction togenerate antisense RNA (aRNA). Biotin–16–UTP (Roche Diagnos-tics, Montreal, Quebec, Canada) and Biotin–11–CTP (Perkin El-mer, USA) nucleotides were incorporated to the newlysynthesized RNA during in vitro transcription. Aliquots of aRNAas well as fragmented RNA were analyzed on Bioanalyzer (AgilentTechnologies, Santa Clara, CA, USA), performed at the London Re-

gional Genomic Center (Robarts Research Institute, London, On-tario, Canada), as well as analyzed on a spectrophotometer(Fischer Scientific, Boston, MA, USA) to ensure the quality andquantity of amplified RNA. For chip hybridization, 20 mg amplifiedRNA underwent fragmentation reaction using fragmentation buffer(Tris pH 8.0, 3.2% MgOAc, 4.9%KOAc) followed by incubation at94�C for 35 minutes.

Microarray experiments and data analysisThe microarray experiments were done in duplicate using two sep-arate sample preparations. Human genome microarray chip(U133) (Affymetrix, Palo Alto, CA, USA) consisting of two gen-echip arrays (A and B) that consisted of approximately 33,000 hu-man genes were used for array hybridization by the standardprotocol provided by the Affymetrix Company. Array hybridiza-tion, washing and data acquisition were performed at the LondonRegional Genomic Center. The gene expression data was normal-ized (Fig. 3) (against undifferentiated hESCs per chip, using the50th percentile of measurements taken from that chip and pergene, by dividing the mean of the signal intensity from each

Figure 2. In vitro functional colony–forming unit (CFU) assay in fetal blood (FB)–and human embryonic stem cell (hESC)–derived CD45þCD34þCD38� vs

CD45þCD34þCD38þ. (A) In vitro clonogenic efficiency of both FB–derived and hESC–derived CD45þCD34þCD38� and CD45þCD34þCD38þ cell sub-

sets. The clonogenic efficiency in FB–derived CD34þCD38� hematopoietic stem cells (HSCs) is 37% and in FB–derived CD34þCD38þ hematopoietic pro-

genitor cells (HPCs) is 32%. CFU capacity in hESC–derived HSCs and HPCs is significantly lower: CD34þCD38� HSCs (2.1%) and CD34þCD38þ HPCs

(0.9%). (B) Representative images of hESC–derived hematopoietic multilineage colonies.

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gene in the selected sample by the mean of the signal intensity ofthe same gene in the control sample, using algorithms in Gene-Spring 6.0. Genes that were significantly (p ! 0.05) differentiallyexpressed (relatively over– or underexpressed more than twofold)in each comparison and were flag present in the replicates wereselected for further analysis. The genes differentially expressedwere functionally categorized to different groups, using the geneontology program built in GeneSpring 6.0 and the literature searchand were clustered in groups with high correlation of expressionusing hierarchical clustering method [19]. Microarray data waspartially validated by polymerase chain reaction (PCR) (Fig. 4).

PCRIn order to randomly validate some of the significant genes foundin the microarray datasheet, expression of frizzled (FZD) 3, 5, 7,and 8 was confirmed/evaluated in conventional PCR using the fol-lowing primers designed by means of the Primer3 program (http://frodo.wi.mit.edu/cgi–bin/primer3/primer3_www.cgi): FZD3F: 50

GCTGGAGAACCAACTGAAGG 30, FZD3R: 50 TGAAATAGCGAGCAAATGACA 30; FZD5F: 50 GGCAACCAGAACCTGAACTC 30, FZD5R: 50 TGTAGAGCAGCGTGAAGATG 30; FZD7F: 50

ACATCGCCTACAACCAGACC 30, FZD7R: 50 CTCGCACAGAGAACGACAC 30; FZD8F: 50 GCTTCGTGTCCCTGTTCC 30,FZD8R: 50 CGGTTGTGCTGCTCGTAG 30; HES1F: 50 GAGCACAGAAAGTCATCAAAGC 30, HES1R: 50 TCCAGAATGTCCGCCTTC 30; b–ActinF: 50 GATCCACATCTGCTGGAAGG 30, b–ActinR: 50 AAGTGTGACGTTGACATCCG 30. PCR conditionsconsisted of primary denaturation at 95�C for 10 minutes followedby 30 cycles of amplifications (consist of 95�C for 30 seconds,60�C for 45 seconds, and 72�C for 2 minutes) and final extensionat 72�C for 10 minutes. The amplified products were fractionatedthrough 2% agarose gel and were sequenced to verify the presenceof the expected PCR product (Fig. 4).

Results

Gene expression experimental strategydesigned for studying the molecular determinantsunderlying the biology of ‘‘candidate’’hESC–HSCsTwo hematopoietic cell subsets were derived from hESC cul-tures and FACS–isolated after 15 days of EB differentiation:

Figure 3. Gene–expression strategy developed for studying the molecular determinants underlying the biology of candidate human embryonic stem cell

(hESC)–hematopoietic stem cells (HSCs). Like somatic HSCs, the candidate hESC–HSCs are considered to be a more primitive population compared to

hESC–HPCs. (A) In all populations of interest (FB–HSCs, FB–HPCs, candidate hESC–HSC, and hESC–HPCs) gene expression was normalized against un-

differentiated hESCs (UhESCs). (B) Comparison of candidate hESC–HSCs and FB–HSCs to their corresponding progenitor counterparts identifies genes

differentially expressed in each HSC population. (C) Venn diagram identifies genes uniquely expressed in either candidate hESC–HSCs or FB–HSCs as

well as 79 genes common for both in utero ontogeny stages of HSCs: hESC and FB.

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hESC–HSCs (CD45þCD34þCD38�) and hESC–HPCs(CD45þCD34þCD38þ) [5] (Fig. 1A). Phenotypicallymatched identical subsets from FB were isolated and usedas corresponding populations for comparison purposes:FB–HSCs (CD45þCD34þCD38�) and FB–HPCs (CD45þ

CD34þCD38þ) (Fig. 1B). To further characterize hemato-poietic potential of HSCs and HPCs isolated from FB andhESCs, we assessed the in vitro clonogenic efficiency ofboth FB–derived and hESC–derived CD45þCD34þ

CD38� and CD45þCD34þCD38þ cell subsets. As it isshown in Figure 2, the clonogenic efficiency in FB–derivedCD34þCD38� HSCs (37%) and CD34þCD38þ HPCs(32%) is significantly higher than in hESC–derivedCD34þCD38� HSCs (2.1%) and CD34þCD38þ HPCs(0.9%). More importantly, in both tissues the CD34þCD38�

HSC subset was always more enriched in CFU potential thanthe CD34þCD38þ HPC population. This CFU functionaldata indicates that the onset of CD38 expression marks theloss of CFU potential, strengthening the value of our compar-ison between these sorted populations.

To gain further insights into the molecular determinantsunderlying cellular behavior of candidate hESC–HSCs, wedeveloped the gene expression strategy illustrated in Fig-ure 3. We compared the gene–expression profile between1) ‘‘candidate’’ hESC–HSCs vs the hESC–HPCs and 2)FB–HSCs vs FB–HPCs (Fig. 3A). All gene–expressiondata were normalized against undifferentiated hESCs.This strategy compares genes differentially expressed incandidate hESC–HSCs and FB–HSCs (Fig. 3B), leadingto identification of specific genes that are uniquely ex-pressed in the either population (Fig. 3C). Functional clas-sification of unique genes will help to explain, at least inpart, some of the distinct cellular characteristics/in vitroand in vivo cell behavior observed for the ‘‘candidate’’hESC–HSCs. Analysis of microarray data identified 768and 2468 genes differentially expressed in FB–HSCs and‘‘candidate’’ hESC–HSCs, respectively, compared to theircorresponding progenitor populations. However, usingVenn diagram, only 97 of those genes were common be-tween ‘‘candidate’’ hESC–HSCs and FB–HSCs, suggesting

Figure 4. Endpoint polymerase chain reaction (PCR) amplification to as-

sess expression of frizzled (FZD) 3, 5, 7, 8, and HES1 in candidate human

embryonic stem cell (hESC)–hematopoietic stem cells (HSCs) and fetal

blood (FB)–HSCs. Using PCR, expression of the above transcripts was

evaluated in candidate hESC–HSCs and FB–HSCs. PCR products were

run on 2% agarose gel to investigate the presence of the expected ampli-

cons. b–actin was used as an internal control and cDNA from fetal tissue

was used as positive control.

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a clearly distinct gene–expression profile between HSCs inthese two ontogeny stages of human development in utero.Given the aim of the study, genes differentially expressed inthe candidate hESC–HSCs are discussed in detail, whereasthe list of genes differentially expressed in FB–HSCs isavailable in Supplemental Table 1

Identification of differentially expressedgenes specific for candidate hESC–HSCsAnalysis of genes differentially expressed in candidatehESC–HSCs compared to hESC–HPCs revealed a distinctpattern of gene expression (Table 1). Differentially ex-pressed genes were grouped according to their functionalrole (Table 1). In contrast with somatic cells, hESC–HSCs have been shown to fail to reconstitute intravenouslytransplanted recipient mice because of cellular aggregationcausing fatal emboli formation [8]. Our molecular analysesrevealed overexpression of several adhesion molecules,such as NINJ2 [20], CD47 [21], CD62 [22], and ICAM1[23], which may explain, at least in part, the molecular ba-sis for the cellular aggregation previously observed in vivo[8,23]. Furthermore, underexpression of N–cadherin and

the chemokine CXCR4, which play key roles in cell anchor-age and homing of HSCs to the bone marrow (BM), respec-tively [24], may explain as well the reported lack of properhoming to BM of candidate hESC–HSCs upon intravenoustransplantation [8].

Analysis of cell–cycle regulators show overexpression ofseveral cell–cycle inducers, such as CDC42 [24], CDC27[25], CyclinD3 [26], and CDK4 [27], suggesting a potentialcycling status of these hESC–HSCs. Within the Hox familygenes, it is worth noting that HoxB4, a gene previously im-plicated in self–renewal of somatic HSCs and mESC–HSCswas not differentially expressed, confirming our previouslyreported data that shows its lack of effect on hESC–HSCsengraftment ability [8]. In contrast, HoxA13 shows a 21–fold–less expression in hESC–HSCs as compared to theircounterpart progenitors, indicating a potential role forHoxA13 in the hierarchical organization of embryonic he-matopoietic development. Analysis of cell surface receptorsindicates overexpression of several receptors associated tocell death, such as BID [28] and MADD [29] that mighthelp to explain the increased rate of cell death [8] inhESC–derived hematopoietic cells in culture.

Among transcription factors, multiple genes crucial foronset and progression of hematopoiesis were differentiallyexpressed (Table 1). Overexpression of hematopoietic tran-scription factors, such as RUNX3, TAL1, VAV1, LMO2,AML–1, and c–myc, along with downregulation of GATA–6, TBX3, and MLL, provides informative molecular cluessupporting our previous studies reporting the inability toproperly differentiate hESCs into definitive HSCs with en-graftment ability.

The transforming growth factor (TGF)–b signaling path-way has a well–established role in inhibition of hemopoie-sis. We have recently reported that TGF–b1 maintains theundifferentiated stage of hESC cultures, whereas inhibitionof the TGF–b pathway promotes differentiation [30]. Inter-estingly, the fact that several members of TGF–b family,such as Smad2, TGFbRIP, and MADR2 are overexpressedin candidate hESC–HSC may partially explain the low levelof prospective and reproducible differentiation of hESCsinto definitive HSCs capable of engrafting immunodeficientanimals [8,31].

This gene expression profiling study revealed importantinsights into developmental signaling pathways known tobe involved in HSC fate determination such as Notch[10], Wnt [11,12], BMP [13], and Shh [14]. In contrast toBMP and Shh pathways, which were similarly expressedamong the cell subsets under study, several componentsof both Notch (HEY1, HEY2, NOTCH4, and HERP1) andWnt (sFRP1, FZD7, FZD10, and Wnt5a) signaling path-ways, known to enhance the repopulation capacity of hu-man and mouse HSCs, were barely expressed in hESC–HSCs, suggesting a role of these developmental signalingpathways in generation of definitive HSCs from hESCs.Given the significance of Wnt and Notch pathways in

Table 1. Annotation of genes that are differentially expressed and unique in candidate hESC–HSCs as compared to hESC–HPCs

Gene ontology GenBank accession number Commonname Gene description O/U DES

Adhesion molecules

NM_016533 NINJ2 Ninjurin 2 mRNA O 4.72

BG230614 CD47 CD47 antigen (integrin–associated signal transducer) O 4.20

AF299343 CD164 CD164 antigen, sialomucin O 3.32

NM_003005 Selectin P Selectin P (granule membrane protein 140kD) O 3.14

AI608725 ICAM1 Intercellular adhesion molecule 1 O 3.10

NM_000584 IL8 Interleukin 8 O 2.85

BC005930 CD58 CD58 antigen, (lymphocyte function–associated antigen 3) O 2.62

AF022375 VEGF Vascular endothelial growth factor U 2.05

NM_006727 CDH10 Cadherin 10, type 2 U 2.14

AF348491 CXCR4 Chemokine receptor CXCR4 U 5.03

NM_018934 PCDHB14 Protocadherin b 14 U 6.85

M34064 N–cadherin N–cadherin cadherin 2, type 1 U 27.02

Apoptosis Regulators

NM_001188 BAK1 BCL2–antagonistkiller 1 O 3.89

AF005775 Clarp Caspase–like apoptosis regulatory protein 2 O 2.36

Cell Cycle Regulators

R37664 CDC42 Cell division cycle 42 O 5.03

AI203880 CDC27 Cell division cycle 27 O 4.38

NM_001760 CCND3 Cyclin D3 O 4.15

NM_006286 TFDP2 Transcription factor Dp–2 (E2F dimerization partner 2) O 2.88

NM_000075 CDK4 Cyclin–dependent kinase 4 O 2.67

AI767436 CDC2L1 Cell division cycle 2–like 1 O 2.53

NM_003981 PRC1 Protein regulator of cytokinesis 1 O 2.41

NM_005792 MPHOSPH6 M–phase phosphoprotein 6 O 2.37

X06130 RCC1 Rell cycle gene RCC1 O 2.23

AI343459 CDC25A Cell division cycle 25A O 2.21

X98258 MPP9 M–phase phosphoprotein 9 O 2.05

BG476661 CDC34 Cell –division cycle 34 O 2.08

R78668 CDKN1C Cyclin–dependent kinase inhibitor 1C (p57, Kip2) U 2.23

Cytokines

NM_015986 CREME9 Cytokine receptor–like molecule 9 O 2.02

Hox family

NM_018952 HOXB6 Homeo box B6 O 2.65

Z21533 HEX HEX gene encoding hematopoietically expressed homeobox O 2.24

NM_004503 HOXC6 Homeo box C6 U 3.55

BG289306 HOXA13 Homeo box A13 U 21.48

Notch pathway

AI743713 NOTCH4 Notch (Drosophila) homolog 4 U 2.32

NM_012259 HEY2 Hairy enhancer–of–split related with YRPW motif 2 U 4.79

AF232238 HERP1 HES–related repressor protein 1 U 9.78

NM_012258 HEY1 Hairy enhancer–of–split related with YRPW motif 1 U 21.27

Receptors

NM_001196 BID BH3 interacting domain death agonist O 3.17

AB002356 MADD MAP–kinase activating death domain O 3.08

X16323 HGF Hepatocyte growth factor O 2.37

BE620457 NRP1 Neuropilin 1 O 2.68

NM_000142 FGFR3 Fibroblast growth factor receptor 3 U 6.08

Transcription factors

NM_004350 RUNX3 Runt–related transcription factor 3 O 4.76

X51990 TAL–1 T–cell acute lymphocytic leukemia 1 O 3.77

NM_005428 VAV1 Vav 1 oncogene O 4.05

NM_005574 LMO2 LIM domain only 2 (rhombotin–like 1) O 2.59

D89788 AML1 Acute myeloid leukemia 1 O 2.58

NM_005354 JUND Jun D proto–oncogene O 2.44

NM_001450 FHL2 Four and a half LIM domains 2 O 2.14

NM_001755 CBFB Core–binding factor, b O 2.30

NM_001674 ATF3 Activating transcription factor 3 O 2.98

U19969 TF8 transcription factor 8 (represses interleukin–2 expression) O 2.93

BC002712 c–myc c–myc avian myelocytomatosis viral related oncogene O 2.72

AI347136 TERF1 Telomeric repeat binding factor O 2.35

(continued)

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Table 1 (continued )

Gene ontology GenBank accession number Commonname Gene description O/U DES

NM_004556 NFKBIE Nuclear factor of k light gene enhancer in B–cells inhibitor e O 2.33

D26156 SWISNF Transcriptional activator hSNF2b O 2.33

N22468 MEF2C MADS box transcription enhancer factor 2 O 2.31

NM_003472 DEK DEK oncogene (DNA binding) O 2.18

NM_001207 BTF3 Basic transcription factor 3 O 2.17

AI361227 NFE2L1 Nuclear factor (erythroid–derived 2)–like 1 O 2.14

BC004973 STAT6 Signal transducer and activator of transcription 6, interleukin–4 induced O 2.12

NM_005335 HCLS1 Hematopoietic cell–specific Lyn substrate 1 O 2.05

D87811 GATA–6 GATA–binding protein 6 U 4.76

NM_004821 HAND1 Heart and neural crest derivatives helix–loop–helix transcription factor U 5.92

AI806338 TBX3 T–box 3 (ulnar mammary syndrome) U 7.14

AV681807 ERBB3 V–erb–b2 avian erythroblastic leukemia viral U 16.70

AB016898 MLL Myeloidlymphoid or mixed–lineage leukemia U 19.67

TGF–b pathway

NM_005901 Smad2 MAD (mothers against decapentaplegic, Drosophila) homolog 2 O 3.23

U65019 MADR2 MAD–related protein 2 (MADR2) O 2.71

U36764 TGFBRIP TGF–b receptor interacting protein 1 O 2.21

Wnt pathway

AI332407 SFRP1 Secreted frizzled–related protein 1 U 2.33

NM_003507 FZD7 Frizzled (Drosophila) homolog 7 U 5.87

NM_007197 FZD10 Frizzled (Drosophila) homolog 10 U 8.85

AI968085 WNT5A Wingless–type MMTV integration site family, member 5A U 16.31

Genes are grouped according to functional classification.

DES 5 differential expression score; O 5 relatively overexpressed; TGF 5 transforming growth factor; U 5 relatively underexpressed.

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HSC fate determination, the expression of several FZD re-ceptors and HES1 was further validated in candidatehESC–HSCs and FB–HSCs by endpoint reverse transcrip-tase PCR (Fig. 4). Absence of FZD receptors in candidatehESC–HSCs implies an inability of Wnt ligands to signalthrough and activate the canonical Wnt pathway in thiscell population, evidencing poor hematopoietic specifica-tion and subsequent reconstitution capacity in vivo [8].FZD 3, 5, 7, and 8 receptors were only detected in FB–HSCs, but not in hESC–HSCs, further confirming a defectin Wnt signaling pathway in candidate hESC–HSCs. Also,according to the gene expression data, HES1 is expressed inboth cell populations, although show slightly lower expres-sion level in hESC–HSCs as compared to FB–HSCs. Takentogether, among the 2468 genes differentially expressed inhESC–HSCs, it deserves especial attention a variety ofcomponents of Notch and Wnt signaling pathways, whichare significantly low–expressed in candidate hESC–HSCs,supporting a key role for these pathways in embryonic he-matopoietic cell–fate specification and possibly HSCs self–renewal.

Universally expressed common genesin both FB–HSCs and candidate hESC–HSCsGene–expression Venn diagram analysis (Fig. 3C) identi-fied 79 genes commonly expressed in HSCs derived fromboth ontogeny stages: FB and hESCs. A brief list of these79 transcripts is shown in Table 2. Among these 79transcripts, the pattern of expression varied between theseontogeny stages (Table 2). Some genes were either

relatively underexpressed or overexpressed in both FB–HSCs and hESC–HSCs, whereas other genes, even beingcommonly expressed in both cell subsets, showed an oppo-site pattern of expression between FB–HSCs and hESC–HSCs as compared to their corresponding progenitor coun-terparts. For instance, CD9, which is expressed during thedifferentiation process from HSCs to HPCs [31,32], is rel-atively overexpressed in candidate hESC–HSCs, but barelyexpressed in FB–HSCs, suggesting that the former cell pop-ulation might contain more committed cells. In contrast,MPL gene is relatively overexpressed in both FB–HSCsand hESC–HSCs, highlighting its functional role throughsignal transduction in both embryonic and fetal hematopoi-etic cells, facilitating hematopoietic specification fromESCs [33]. Overexpression of the apoptosis–related tumornecrosis factor receptor TNFRSF1B [34] in candidatehESC–HSCs suggests that this population may be moreprone to apoptosis than FB–HSCs, which present lowerlevels of TNFRSF1B. Similarly, our data also shows overex-pression and underexpression of PROCR (protein C recep-tor) in FB–HSC and candidate hESC–HSC populations,respectively. Given the role of protein C in inhibiting apo-ptosis through blockade of p53 [35], this may explain theincreased resistance of FB–HSCs to cell death in compari-son to candidate hESC–HSCs. Low expression of TEK inhESC–HSCs offers further insights into the propensity ofcandidate hESC–HSCs to undergo apoptosis as a recentstudy demonstrated the significance of TEK tyrosine kinasein maintaining the quiescent status and resistance of HSCsto cell death [36]. Finally, overexpresion of HES1 in both

Table 2. List of common genes differentially expressed in both candidate hESC–HSCs and FB–HSCs in comparison to their progenitor counterparts

Genbankaccession number Common name Description

Expression in

FB–HSCs

Expressionin

candidatehESC–HSCs

U84895 T4A15 Transmembrane 4 superfamily A15 homolog U U

NM_001769 CD9 CD9 antigen (p24) U O

NM_000250 MPO Myeloperoxidase U U

NM_005373 MPL Myeloproliferative leukemia virus oncogene O O

NM_006910 RBBP6 Retinoblastoma–binding protein 6 U O

NM_001066 TNFRSF1B Tumor necrosis factor receptor superfamily, 1B U O

BE973687 HES–1 Hairy enhancer of split O O

U77914 Jagged–1 Soluble protein Jagged U U

NM_006404 PROCR Protein C receptor, endothelial O U

AI333232 RAB18 RAB18, member of RAS oncogene U O

NM_002922 RGS1 Regulator of G–protein signaling 1 O O

NM_000459 TEK TEK tyrosine kinase, endothelial O U

NM_002777 PRTN3 Proteinase 3 U U

NM_007173 SPUVE Protease, serine, 23 U U

NM_004094 EIF2S1 Eukaryotic translation initiation factor 2 O O

BF516289 EIF4EL3 Eukaryotic translation initiation factor 4E–like 3 O O

FB 5 fetal blood; hESC 5 human embryonic stem cells; HSC 5 hematopoietic stem cells; O 5 relatively overexpressed; U 5 relatively underexpressed.

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FB–HSCs and hESC–HSCs further confirms an importantrole for the Notch pathway [10] in cell fate determinationof both early stages of human hematopoietic development.

Clustering analysis ofgenes enriched in candidate hESC–HSCsHierarchical clustering [19] was applied to the genes differ-entially expressed in candidate hESC–HSCs to evaluate co-hort of gene expression (Fig. 5). Interestingly, clusters I andII contain several adhesion molecules, cell–cycle regula-tors, and apoptotic genes. For example, NINJ2 [20],CDC42 [24], and ATF3 [37] in cluster I and CD47 [21],RAB5C [38], and BID [28] in cluster II showed a close pro-file of expression. Cluster III also contains cell–cycle in-ducers, such as CDC25A [39] and CD62, which isinvolved in cell aggregation [22]. In cluster IV, higher ex-pression of ICAM1, which is involved in cell adhesionand aggregation [23], and MADD, which encodes a deathdomain protein [29], were noticeable (Fig. 5). Coregulationof several cell–cycle genes and apoptotic inducers (Table 2)may provide new molecular insights into the vulnerabilityof candidate hESC–HSCs to undergo cell death as they tra-verse the cell cycle. In addition, the presence in the sameclusters of genes encoding adhesion molecules associatedwith cell aggregation and apoptotic inducers links togetherthe processes of cell aggregation and cell death in candidatehESC–HSCs. Interestingly, vascular endothelial growthfactor (VEGF) and CXCR4 show a high correlation profileof expression as compared to cluster V. This is consistentwith other studies explaining cross–talks between VEGFand CXCR4 [40,41]. VEGF regulates CXCR4 expressionin breast carcinoma cells leading to migration of cancercells toward the gradient of SDF1 [40]. This raises a ques-tion about factors regulating both VEGF and CXCR4

expression in candidate hESC–HSCs. Finally, cluster VIcontains most of the underexpressed genes includingWnt5A, FZD7, FZD10, and SFRP1, suggesting a cohortof gene expression for the components of Wnt pathway incandidate hESC–HSCs.

DiscussionThe molecular determinants and signaling pathways under-lying the self–renewal and multilineage differentiation ofhuman somatic HSCs in different stages of mammalian de-velopment have been studied extensively [42,56]. However,recent studies describing the derivation of hematopoieticcells from hESCs have shown that hESC–derived hemato-poietic cells display distinct cellular behavior with impairedmultilineage potential and barely engraftment ability ascompared to somatic HSCs [5,43]. Potential explanationsfor these distinct biological features of candidate hESC–HSCs may lie in the lack of appropriate culture conditions,resulting in 1) generation of hematopoietic cells still retain-ing ES cell properties or 2) derivation of hematopoieticcells that have developed beyond the HSC hierarchicalstage (i.e., downstream committed progenitors) with theconcomitant loss of ‘‘stemness’’ features.

Here, in order to gain further insights into the molecularbasis underlying the in vitro and in vivo biology of candidatehESC–HSCs, we investigated, for the first time, the gene–expression profile in the CD45þCD34þCD38� cell popula-tion derived from two human prenatal ontogeny stages: hESCsand human FB. We chose FB–HSCs as they represent the on-togenically closest HSC population to the embryonic stage[9,17]. Analysis of differentially expressed genes identifieda variety of transcripts potentially responsible for cell aggre-gation, such as NINJ2 [20], CD47 [21], and CD62 [22] in the

Figure 5. Gene tree analysis to evaluate the cohort of gene expression in the candidate human embryonic stem cell (hESC)–hematopoietic stem cell (HSC)

population. Standard correlation was applied to the genes differentially expressed in ‘‘candidate’’ hESC–HSCs (explained in Table 2). Data were normalized

against undifferentiated hESCs per chip and per gene (explained in Materials and Methods). Genes that were significantly (p ! 0.05) differentially expressed

(more than twofold) and were flag present in the three replicates, were selected for gene tree analysis. Standard correlation (Pearson correlation around one)

was applied to cluster the data with a separation ratio of 1 and minimum distance of 0.001.

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candidate hESC–HSCs, which may explain, at least in part,the emboli formation previously reported upon intravenousinjection in NOD/SCID mice [8]. In addition, the lower ex-pression of N–cadherin and CXCR4 in candidate hESC–HSCs may help to explain the lack of proper homing to theBM after intravenous injection. Overexpression of CXCR4using cytokines such as IL–2, IL–4, IL–7, and IL–15 may fa-cilitate the homing capacity of these cells to the appropriateniches in the BM [44]. We additionally suggest that thehigh–level expression of genes encoding several cell–cycle in-ducers, such as CDC42, CDC27, CyclinD3 may also contrib-ute to the active cycling status of candidate hESC–HSCs,which is commonly associated to loss of self–renewal upontraversing the cell cycle [45,46]. Furthermore, the increasedsensitivity that candidate hESC–HSCs seem to have to apo-ptosis is supported by the high expression levels of severalgenes encoding death domain receptors, such as BID [28]and MADD [29], the apoptosis–related receptor TNFRSF1B[34] and the relatively underexpression of PROCR [35], a po-tent apoptosis inhibitor that acts through p53 pathway [35].

With respect to leukemogenesis, there are different typesof childhood acute leukemia, wherein clinically significantmanifestations arise in utero [47–49]. The mechanisms oftransformation are not amenable to analysis with patientsamples because cancer is studied once the transformationevents have already occurred. On the other hand, manymouse models for childhood cancer have fallen short inachieving the goal of illuminating the human disease be-cause they do not recapitulate key aspects of the actual hu-man disease, indicating that the mouse model is missingessential ingredients of oncogenesis present in the humanembryo/fetus [47,48,50]. Recent studies indicate that can-cer may arise at the level of stem cells, and that many sig-naling pathways essential for normal development (i.e.,BMPs, Shh, Notch, and Wnt) may also be involved in can-cer progression, suggesting a link between embryonic cellsand cancer cells [5,51,52]. Notch pathway is known to beinvolved in acute lymphoblastic leukemia through activa-tion of several transcriptional programs, including c–Myc[53,54].

Because of the importance of these developmental sig-naling pathways in regulating cell fate specification, andalso their emerging role in leukemia, we evaluated thesepathways in detail. Interestingly, several members of theWnt pathway, including ligands and FZD receptors, werefound barely expressed in candidate hESC–HSCs. Thelack of proper growth factors in culture further supportsa role for a stroma layer in the specification of definitive he-matopoietic cells from hESCs [55]. Accordingly, very re-cent studies [6,55] demonstrated derivation of HSC fromhESCs in the presence of S17 stromal cells. These hESC–derived hematopoietic cells were capable of repopulatingand multilineage differentiation in primary as well assecondary recipients in a variety of hosts, includingNOD/SCID mice [6] and fetal sheep [55].

Also, several components of Notch pathway (HEY1,HEY2, NOTCH4, and HERP1), known to enhance the repo-pulation capacity of human and mouse HSCs, were barelyexpressed in hESC–HSCs, suggesting a role of this devel-opmental signaling pathway in the generation of definitiveHSCs from hESCs. This data may also support recent stud-ies suggesting that mutations in key components of Notchsignaling pathways can be early or initiating events in acuteinfant/childhood leukemia arising prenatally, possibly con-trolling the embryonic specification towards normal vs leu-kemic hematopoiesis [15].

Overall, the current study suggests that despite ‘‘candidate’’hESC-HSCs are phenotypically committed to the hematopoi-etic cell fate, their intrinsic properties, influenced by the cul-ture condition, is distinct and defective compared to de novosomatic HSCs isolated from in utero stage of ontogeny. Thegene expression profile may become instrumental in betterunderstand the molecular basis underlying hESC–derivedHSC behavior and cellular properties, which clearly differfrom their somatic FB–HSCs. Future studies will be neededto address the functional role of the key genes identified hereand for identification of novel cytokines/growth factors driv-ing physiological specification of hESCs into definitive HSCs.

AcknowledgmentsP.M. was supported by the Canadian Institutes of Health Research.We would like to thank Ms. Dagna Sheerer for FACS sorting andstaff at London Regional Genomic Centre at Robarts Research In-stitute for assisting with the microarray experiments.

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Supplementary information associated with this article canbe found in the online version, at doi:10.1016/j.exphem.2008.06.001.