Ex vivo expanded cord blood CD4 T lymphocytes exhibit a distinct expression profile of cytokine-related genes from those of peripheral blood origin

Abstract

With an increase in the importance of umbilical cord blood (CB) as an alternative source of haematopoietic progenitors for allogenic transplantation, donor lymphocyte infusion (DLI) with donor CB-derived activated CD4⁺ T cells in the unrelated CB transplantation setting is expected to be of increased usefulness as a direct approach for improving post-transplant immune function. To clarify the characteristics of activated CD4⁺ T cells derived from CB, we investigated their mRNA expression profiles and compared them with those of peripheral blood (PB)-derived activated CD4⁺ T cells. Based on the results of a DNA microarray analysis and quantitative real-time reverse transcriptase–polymerase chain reaction (RT-PCR), a relatively high level of forkhead box protein 3 (Foxp3) gene expression and a relatively low level of interleukin (IL)-17 gene expression were revealed to be significant features of the gene expression profile of CB-derived activated CD4⁺ T cells. Flow cytometric analysis further revealed protein expression of Foxp3 in a portion of CB-derived activated CD4⁺ T cells. The low level of retinoic acid receptor-related orphan receptor γ isoform t (RORγt) gene expression in CB-derived activated CD4⁺ T cells was speculated to be responsible for the low level of IL-17 gene expression. Our data indicate a difference in gene expression between CD4⁺ T cells from CB and those from PB. The findings of Foxp3 expression, a characteristic of regulatory T cells, and a low level of IL-17 gene expression suggest that CB-derived CD4⁺ T cells may be a more appropriate source for DLI.

Introduction

Donor lymphocyte infusion (DLI) is a direct and useful approach for improving post-transplant immune function. DLI has been shown to exert a graft-versus-leukaemia (GVL) effect and has emerged as an effective strategy for the treatment of patients with leukaemia, especially chronic myelogenous leukaemia, who have relapsed after unrelated haematopoietic stem cell transplantation (HSCT).¹ In addition, DLI has been successfully used for some life-threatening viral infections, including Epstein–Barr virus and cytomegalovirus infections after HSCT.²

Although DLI frequently results in significant acute and/or chronic graft-versus-host disease (GVHD), several groups have demonstrated that depletion of CD8 T cells from DLIs efficiently reduces the incidence and severity of GVHD while maintaining GVL activity.^3,4 Therefore, selective CD4 DLI is expected to provide an effective and low-toxicity therapeutic strategy for improving post-transplant immune function. Actually, selective CD4 DLI based on a recently established method for ex vivo T-cell expansion using anti-CD3 monoclonal antibody and interleukin (IL)-2 is now becoming established as a routine therapeutic means of resolving post-transplant immunological problems in Japan.⁵

The importance of umbilical cord blood (CB) as an alternative source of haematopoietic progenitors for allogenic transplantation, mainly in patients lacking a human leucocyte antigen (HLA)-matched marrow donor, has increased in recent years. Because of the naïve nature of CB lymphocytes, the incidence and severity of GVHD are reduced in comparison with the allogenic transplant setting. In addition, CB is rich in primitive CD16⁻ CD56⁺ natural killer (NK) cells, which possess significant proliferative and cytotoxic capacities, and so have a substantial GVL effect.⁶

In contrast, a major disadvantage of CB transplantation is the low yield of stem cells, resulting in higher rates of engraftment failure and slower engraftment compared with bone marrow transplantation. In addition, it was generally thought to be difficult to perform DLI after CB transplantation using donor peripheral blood (PB), with the exception of transplantations from siblings. However, the above-described method for the ex vivo expansion of activated T cells can produce a sufficient amount of cells for therapy using the CB cell residues in an infused bag, which has solved this problem and made it possible to perform DLI with donor CB-derived activated CD4⁺ T cells in the unrelated CB transplantation setting.⁵ It has also been reported that CB-derived T cells can be expanded ex vivo while retaining the naïve and/or central memory phenotype and polyclonal T-cell receptor (TCR) diversity,⁷ and thus potential utilization for adoptive cellular immunotherapy post-CB transplantation has been suggested.⁸

There are functional differences between CB and PB lymphocytes, although the details remain unclear. In an attempt to clarify the differences in characteristics between activated CD4⁺ T cells derived from CB and those derived from PB, we investigated gene expression profiles. In this paper we present evidence that CB-derived CD4⁺ T cells are distinct from PB-derived CD4⁺ T cells in terms of gene expression.

Materials and methods

Cell culture and preparation

CB was distributed by the Tokyo Cord Blood Bank (Tokyo, Japan). The CB was originally collected and stored for stem cell transplantation. Stocks that were inappropriate for transplantation because they contained too few cells were distributed for research use with informed consent, with the permission of the ethics committee of the bank. In addition, all of the experiments in this study using distributed CB were performed with the approval of the local ethics committee. The mononuclear cells were isolated by Ficoll-Paque centrifugation and cultured in the presence of an anti-CD3 monoclonal antibody and interleukin (IL)-2 using TLY Culture Kit 25 (Lymphotec Inc., Tokyo, Japan) as described previously.⁵ Although several different methods for T-cell stimulation have been reported, this method is currently being used clinically in Japan. Thus we selected this method in this study. After 14 days of culture, CD4⁺ cells were isolated using a magnetic-activated cell sorting (MACS) system (Miltenyi Biotec, Bergisch Gladbach, Germany) according to the manufacturer’s instructions. As a control, mononuclear cells isolated from the peripheral blood of healthy volunteers were similar examined.

Polymerase chain reaction (PCR)

Total RNA was extracted from cells using an RNeasy kit (Qiagen, Valencia, CA) and reverse-transcribed using a First-Strand cDNA synthesis kit (GE Healthcare Bio-Science Corp., Little Chalfont, Buckinghamshire, UK) according to the manufacturer’s instructions. Using cDNA synthesized from 150 ng of total RNA as a template for one amplification, real-time reverse transcriptase (RT)-PCR was performed using SYBR® Green PCR master mix, TaqMan® Universal PCR master mix and TaqMan® gene expression assays (Applied Biosystems, Foster City, CA), and an inventoried assay carried out on an ABI PRISM® 7900HT sequence detection system (Applied Biosystems) according to the instructions provided. Either the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene or the β-actin gene was used as an internal control for normalization. The sequences of gene-specific primers for real-time RT-PCR are listed in Table 1.

Table 1.

The sequences of gene-specific primers for reverse transcriptase–polymerase chain reaction (RT-PCR) and real-time RT-PCR used in this study

Primer	Sequence
IL-4 forward	CACAGGCACAAGCAGCTGAT
IL-4 reverse	CCTTCACAGGACAGGAATTCAAG
IL-6 forward	GTAGCCGCCCCACACAGA
IL-6 reverse	CCGTCGAGGATGTACCGAAT
IL-10 forward	GCCAAGCCTTGTCTGAGATGA
IL-10 reverse	CTTGATGTCTGGGTCTTGGTTCT
IL-17 forward	GACTCCTGGGAAGACCTCATTG
IL-17 reverse	TGTGATTCCTGCCTTCACTATGG
IL-17F forward	GCTTGACATTGGCATCATCAA
IL-17F reverse	GGAGCGGCTCTCGATGTTAC
IL-23 forward	GAGCCTTCTCTGCTCCCTGATAG
IL-23 reverse	AGTTGGCTGAGGCCCAGTAG
IL-23R forward	AACAACAGCTCGGCTTTGGTATA
IL-23R reverse	GGGACATTCAGCAGTGCAGTAC
IFNG forward	CATCCAAGTGATGGCTGAACTG
IFNG reverse	TCGAAACAGCATCTGACTCCTTT
GM-CSF forward	CAGCCCTGGAGCATGTG
GM-CSF reverse	CATCTCAGCAGCAGTGTCTCTACr
RORγt forward	TGGGCATGTCCCGAGATG
RORγt reverse	GCAGGCTGTCCCTCTGCTT
STAT-3 forward	GGAGGAGGCATTCGGAAAGT
STAT-3 reverse	GCGCTACCTGGGTCAGCTT
FOXP3 forward	GAGAAGCTGAGTGCCATGCA
FOXP3 reverse	GCCACAGATGAAGCCTTGGT

IL, interleukin; IFNG, interferon γ; FOXP3, forkhead box protein 3; GM-CSF, granulocyte–macrophage colony-stimulating factor; RORγt, retinoic acid receptor-related orphan receptor γ isoform t; STAT, signal transducer and activator of transcription.

DNA microarray analysis

The microarray analysis was performed as previously described.⁹ Total RNA isolated from cells was reverse-transcribed and labelled using One-Cycle Target Labeling and Control Reagents as instructed by the manufacturer (Affymetrix, Santa Clara, CA). The labelled probes were hybridized to a Human Genome U133 Plus 2·0 Array (Affymetrix). The arrays were used in a single experiment and analysed with genechip operating software 1.2 (Affymetrix). Background subtraction and normalization were performed using genespring gx 7.3 software (Agilent Technologies, Santa Clara, CA). The signal intensity was pre-normalized based on the positive control genes (GAPDH and β-actin) for all measurements on that chip. To account for differences in detection efficiency between spots, the pre-normalized signal intensity of each gene was normalized to the median of pre-normalized measurements for that gene. The data were filtered as follows. (i) Genes that were scored as absent in all samples were eliminated. (ii) Genes with a signal intensity of < 90 were eliminated. (iii) Genes that exhibited increased (fold-change > 2) or decreased (fold-change > 2) expression in CB-derived CD4⁺ T cells compared with PB-derived CD4⁺ T cells were selected by comparing the mean value of signal intensities in each condition.

Immunofluorescence study

After periods of cultivation, cells were collected and stained with fluorescence-labelled monoclonal antibodies and analysed by flow cytometry (FC500; Beckman/Coulter, Fullerton, CA). A four-colour immunofluorescence study was performed with a combination of fluorescein isothiocyanate (FITC)-conjugated anti-CD3, phycoerythrin (PE)-conjugated anti- forkhead box protein 3 (Foxp3), phycoerythrin-cyanine-5 (PC5)-conjugated anti-CD4 and PC7-conjugated anti-CD8 (Beckman/Coulter). After staining of cell surface antigens, cells were permeabilized with IntraPrep (Dako, Glostrup, Denmark) and intracellular antigen (Foxp3) was further stained.

Statistical analysis

The statistical analysis was performed using a Student’s t-test and a P-value < 0·05 was considered to be statistically significant.

Results

Expression profiles of activated CD4⁺ T cells derived from human CB and PB

To compare the gene expression patterns of CB-derived CD4⁺ cells and PB-derived CD4⁺ cells, we performed DNA microarray analysis using the Affymetrix Human Genome U133 Plus 2·0 Array. After background subtraction, comparison of the gene expression profiles of two independent CB-derived CD4⁺ samples and PB-derived CD4⁺ samples was performed using a gene cluster analysis. The genes differentially expressed (fold-change > 2) between the activated CD4⁺ T cells derived from CB and those derived from PB were selected, and 396 probes were found to exhibit higher levels of expression in CB-derived CD4⁺ samples while 131 probes exhibited higher levels in PB-derived CD4⁺ samples. Parts of the data are summarized and presented in Fig. 1a and Tables 2–4.

Figure 1.

Comparison of the gene expression profiles of cord blood (CB)- and peripheral blood (PB)-derived CD4⁺ T cells. Hierarchical clustering of results from a microarray analysis for CB- and PB-derived CD4⁺ T cells is indicated. (a) A total of 529 genes characterizing CD4⁺ T cells (396 genes for CB-derived CD4⁺ T cells and 131 genes for PB-derived CD4⁺ T cells) were used to create the gene tree. The gene list is presented in Tables 3 and 4. (b) Genes related to T-cell development (40 genes for CB-derived CD4⁺ T cells and 26 genes for PB-derived CD4⁺ T cells) are presented. The arrows indicate the expression pattern of T-cell lineage-specific genes including inducible T-cell co-stimulator (ICOS), granulocyte-macrophage colony-stimulating factor (GM-CSF) and forkhead box protein 3 (FOXP3).

Table 2.

The microarray results for T-cell-related genes

Table 4.

Genes up-regulated in CD4⁺ T cells from peripheral blood (PB)

		Fold change
Affi ID	Gene abbreviation	CB 1	CB 2	PB 1	PB 2	Gene name
Apoptosis
1553681_a_at	PRF1	0·66	0·51	1·41	1·34	Perforin 1 (pore-forming protein)
B- and T-cell development
224499_s_at	AICDA	0·06	0·44	1·56	3·47	Activation-induced cytidine deaminase
205495_s_at	GNLY	0·40	0·51	1·49	6·34	Granulysin
217478_s_at	HLA-DMA	0·67	0·39	1·33	1·35	Major histocompatibility complex, class II, DM alpha
203932_at	HLA-DMB	0·64	0·31	2·02	1·36	Major histocompatibility complex, class II, DM beta
211991_s_at	HLA-DPA1	0·50	0·14	1·54	1·50	Major histocompatibility complex, class II, DP alpha 1
212671_s_at	HLA-DQA1	0·44	0·23	1·56	2·56	Major histocompatibility complex, class II, DQ alpha 1
211656_x_at	HLA-DQB1	0·63	0·48	1·37	7·07	Major histocompatibility complex, class II, DQ beta 1
210982_s_at	HLA-DRA	0·58	0·37	1·50	1·42	Major histocompatibility complex, class II, DR alpha
208306_x_at	HLA-DRB1	0·51	0·24	1·49	1·61	Major histocompatibility complex, class II, DR beta 3
204670_x_at	HLA-DRB5	0·63	0·22	1·47	1·37	Major histocompatibility complex, class II, DR beta 5
211634_x_at	IGHV1-69	0·69	0·77	1·23	1·99	Immunoglobulin heavy variable 1–69
211645_x_at	IgK	0·15	0·49	1·51	6·62	Immunoglobulin kappa light chain (IGKV)
221651_x_at	IGKC	0·46	0·68	1·32	5·57	Immunoglobulin kappa constant
215379_x_at	IGLC2	0·62	0·41	1·38	4·26	Immunoglobulin lambda joining 2
209031_at	IGSF4	0·50	0·03	2·33	1·50	Immunoglobulin superfamily, member 4
205686_s_at	CD86	0·70	0·23	1·30	1·39	CD86 antigen (CD28 antigen ligand 2, B7-2 antigen)
204698_at	ISG20	0·68	0·49	1·32	1·64	Interferon stimulated exonuclease gene, 20 kDa
213915_at	NKG7	0·72	0·42	1·28	2·31	Natural killer cell group 7 sequence
Cell growth and maintenance
201334_s_at	ARHGEF12	0·74	0·50	1·26	1·96	Rho guanine nucleotide exchange factor (GEF) 12
230292_at	CHC1L	0·70	0·56	1·30	2·02	Regulator of chromosome condensation (RCC1)
205081_at	CRIP1	0·56	0·73	1·27	1·75	Cysteine-rich protein 1 (intestinal)
31874_at	GAS2L1	0·77	0·52	1·23	2·35	Growth arrest-specific 2 like 1
202364_at	MXI1	0·43	0·73	1·27	1·44	MAX interactor 1
219304_s_at	PDGFD	0·65	0·71	1·29	3·68	Platelet-derived growth factor D
213397_x_at	RNASE4	0·64	0·46	1·36	2·21	Ribonuclease, RNase A family, 4
213566_at	RNASE6	0·69	0·39	1·49	1·31	Ribonuclease, RNase A family, k6
219077_s_at	WWOX	0·40	0·78	1·25	1·22	WW domain containing oxidoreductase
Cytokine and chemokine
207861_at	CCL22	0·76	0·52	1·24	2·47	Chemokine (C–C motif) ligand 22
238750_at	CCL28	0·74	0·45	1·26	1·41	Chemokine (C–C motif) ligand 28
1555759_a_at	CCL5	0·71	0·23	1·29	1·92	Chemokine (C–C motif) ligand 5
208304_at	CCR3	0·50	0·12	1·50	2·35	Chemokine (C–C motif) receptor 3
205898_at	CX3CR1	0·30	0·20	1·70	4·16	Chemokine (C–X3–C motif) receptor 1
204533_at	CXCL10	0·80	0·16	1·20	2·53	Chemokine (C–X–C motif) ligand 10
219255_x_at	IL-17RB	0·73	0·04	1·27	1·29	Interleukin 17 receptor B
206148_at	IL-3RA	0·60	0·54	2·46	1·40	Interleukin 3 receptor, alpha (low affnity)
226333_at	IL-6R	0·22	0·79	1·21	2·43	Interleukin-6 receptor
206693_at	IL-7	0·09	0·54	1·46	5·86	Interleukin-7
Signal transduction
204497_at	ADCY9	0·76	0·40	1·24	2·40	Adenylate cyclase 9
206170_at	ADRB2	0·58	0·35	1·42	3·97	Adrenergic, beta-2-, receptor, surface
202096_s_at	BZRP	0·50	0·54	1·59	1·46	Benzodiazapine receptor (peripheral)
230464_at	EDG8	0·04	0·09	1·91	2·42	Endothelial differentiation, sphingolipid G-protein-coupled receptor 8
223423_at	GPR160	0·54	0·68	1·40	1·32	G protein-coupled receptor 160
227769_at	GPR27	0·07	0·08	1·92	244	G protein in-coupled receptor 27
210095_s_at	IGFBP3	0·27	0·20	1·73	5·25	Insulin-like growth factor binding protein 3
38671_at	PLXND1	0·08	0·65	1·35	2·57	Plexin D1
226101_at	PRKCE	0·56	0·43	1·72	1·44	Protein kinase C. epsilon
232629_at	PROK2	0·01	0·13	1·87	2·09	Prokineticin 2
203329_at	PTPRM	0·36	0·62	1·38	1·93	Protein tyrosine phosphatase, receptor type, M
204731_at	TGFBR3	0·78	0·55	1·22	2·04	Transforming growth factor, beta receptor III (betaglycan, 300 kDa)
Transcription
203129_s_at	KIF5C	0·67	0·09	1·33	3·43	Kinesin family member 5C
213906_at	MYBL1	0·75	0·51	1·25	3·63	V-myb myeloblastosis viral oncogene homologue (avian)-like 1
209815_at	PTCH	0·59	0·27	1·41	4·17	Patched homologue (Drosophila)
213891_s_at	TCF4	0·74	0·65	2·06	1·26	Transcription factor 4
238520_at	TRERFI	0·70	0·77	1·23	2·30	Transcriptional regulating factor 1
203603_s_at	ZFHX1B	0·74	0·61	1·26	3·63	Zinc finger homobox 1b
213218_at	ZNF187	0·74	0·69	1·26	1·76	Zinc finger protein 187
221123_x_at	ZNF395	0·38	0·71	1·63	1·29	Zinc finger protein 395

Among these genes, those closely correlated to T-cell function and development were selected (Fig. 1b). The genes exhibiting higher levels of expression in CB-derived CD4⁺ samples included those encoding cell cycle regulators, including cyclin-dependent kinase (CDKN)2A and 2B, transcriptional regulators and signal transduction factors (Tables 2 and 3). The genes for cytokines, chemokines and their receptors such as Interferon γ (IFNG), granulocyte-macrophage colony-stimulating factor (GM-CSF) and for T-cell transcriptional regulators (FOXP3) as well as the genes related to T-cell development including CD28, cytotoxic T lymphocyte antigen-4 (CTLA4) and inducible T-cell co-stimulator (ICOS) were also found among the genes exhibiting higher levels of expression in CB-derived CD4⁺ samples (Fig. 1b). The factors reported to be essential for negative selection in CD4⁺ CD8⁺ thymocytes such as BCL2-like 11 (BIM)¹⁰ as well as other apoptotic regulators were also found among the genes exhibiting higher expression levels in CB-derived CD4⁺ samples.

Table 3.

Genes up-regulated in CD4⁺ T cells from cord blood samples 1 and 2 (CB 1 and CB 2, respectively)

		Fold change
Affi ID	Gene abbreviation	CB 1	CB 2	PB 1	PB 2	Gene name
Apoptosis
1555372_at	BimL	1·39	1·52	0·61	0·42	BCL2-like 11 (apoptosis facilitator)
237837_at	BCL2	1·27	1·32	0·49	0·73	B-cell CLL/lymphoma 2
205681_at	BCL2A1	1·91	1·53	0·39	0·47	BCL2-related protein A1
1558143_a_at	BCL2L11	1·68	1·74	0·32	0·32	BGL2-like 11 (apoptosis facilitator)
228311_at	BCL6B	1·36	3·39	0·64	0·26	B-cell CLL/lymphoma 6, member B (zinc finger protein)
215037_s_at	BCLX	2·56	1·27	0·73	0·56	BCL2-like 1
224414_s_at	CARD6	2·65	1·34	0·56	0·66	Caspase recruitment domain family, member 6
201631_s_at	IER3	1·62	2·95	0·38	0·31	Immediate early response 3
218000_s_at	PHLDA1	2·34	1·21	0·53	0·79	Pleckstrin homology-like domain, family A, member 1
209803_s_at	PHLDA2	2·87	1·32	0·31	0·68	Pleckstrin homology-like domain, family A. member 2
203063_at	PPMIF	1·26	1·53	0·74	0·64	Protein phosphatase IF (PP2C domain containing)
205214_at	STK17B	1·78	1·26	0·74	0·71	Serine/threonine kinase 17b (apoptosis-inducing)
217853_at	TENS1	1·63	6·00	0·04	0·37	Tensin 1
B- and T-cell development
211861_x_at	CD28	1·35	1·41	0·49	0·65	CD28 antigen(Tp44)
207892_at	CD40LG	3·67	1·32	0·45	0·68	C040 ligand (TNF superfamily, member 5, hyper-IgM syndrome)
206914_at	CRTAM	2·76	1·60	0·40	0·36	Class I MHC-restricted T-cell-associated molecule
210557_x_at	CSF1	3·79	1·22	0·78	0·70	Colony-stimulating factor 1 (macrophage)
210229_s_at	CSF2	1·28	2·67	0·69	0·72	Colony-stimulating factor 2 (granulocyte–macrophage)
205159_at	CSF2RB	2·33	1·60	0·18	0·40	Colony-stimulating factor 2 receptor
231794_at	CTLA4	1·39	1·26	0·74	0·44	Cytotoxic T-lymphocyte-associated protein 4
204232_at	FCER1G	1·63	2·14	0·28	0·37	Fc fragment of IgE, high affinity 1, receptor for; gamma polypeptide
210439_at	ICOS	1·38	1·34	0·57	0·66	Inducible T-cell costimulator
210354_at	IFNG	1·48	1·92	0·46	0·52	Human mRNA for HuIFN -gamma interferon
230536_at	PBX4	1·48	1·26	0·50	0·74	Pre-B-cell leukaemia transcription factor 4
215540_at	TCRA	1·25	1·87	0·67	0·75	T-cell antigen receptor alpha
234440_al	TCRD	7·51	1·48	0·50	0·52	Human T-cell receptor delta-chain
Cell growth and maintenance
213497_at	ABTB2	2·06	1·34	0·66	0·63	Ankyrin repeat and BTB (POZ) domain containing 2
201236_s_at	BTG2	1·60	1·23	0·60	0·77	BTG family, member 2
235287_at	CDK6	1·50	1·32	0·44	0·68	Cyclin-dependent kinase 6
209644_x_at	CDKN2A	2·90	1·21	0·67	0·79	Cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4)
236313_at	CDKN2B	3·24	1·28	0·58	0·72	Cyclin-dependent kinase inhibitor 2B (p15, inhibits CDK4)
241984_at	CHES1	1·38	1·34	0·66	0·63	Checkpoint suppressor 1
202552_s_at	CRIM1	1·94	1·39	0·32	0·61	Cysteine-rich transmembrane BMP regulator 1 (chordin-like)
204844_at	ENPEP	1·64	1·75	0·09	0·36	Glutamyl aminopeptidase (aminopeptidase A)
205418_at	FES	1·39	1·80	0·61	0·25	Feline sarcoma oncogene
228572_at	GRB2	4·69	1·21	0·79	0·78	Growth factor receptor-bound protein 2
207688_s_at	INHBC	1·46	1·25	0·51	0·75	Inhibin, beta C
209744_x_at	ITCH	1·30	1·47	0·63	0·70	Itchy homolog E3 ubiquitin protein ligase (mouse)
201548_s_at	JARID1B	1·27	1·92	0·73	0·46	Jumonji, AT-rich interactive domain IB (RBP2-like)
203297_s_at	JARID2	1·42	1·28	0·54	0·72	Jumonji, AT-rich interactive domain 2
41387_r_at	JMJD3	1·82	1·24	0·76	0·65	Jumonji domain containing 3
205569_at	LAMP3	2·32	1·24	0·76	0·50	Lysosomal-associated membrane protein 3
214039_s_at	LAPTM4B	1·41	1·49	0·49	0·59	Lysosomal-associated protein transmembrane 4 beta
205857_x_at	MSH3	1·79	1·28	0·58	0·72	MutS homolog 3 (E. coli)
209550_at	NDN	3·42	1·38	0·17	0·62	Necdin homolog (mouse)
207943_x_at	PLAGL1	1·37	1·43	0·57	0·63	Pleiomorphic adenoma gene-like 1
204748_at	PTGS2	1·65	1·78	0·14	0·35	Prostaglandin-endoperoxide synthase 2
201482_at	QSCN6	1·32	1·23	0·38	0·77	Quiescin Q6
203743_s_at	TDG	1·47	1·23	0·54	0·77	Thymine-DNA glycosylase
204227_s_at	TK2	2·12	1·26	0·56	0·74	Thymidine kinase 2, mitochondrial
Cytokines and chemokines
207533_at	CCL1	1·67	1·48	0·52	0·49	Chemokine (C-C motif) ligand 1
205099_s_at	CCR1	4·70	1·21	0·61	0·79	Chemokine (C-C motif) receptor 1
207681_at	CXCR3	1·51	1·33	0·41	0·67	Chemokine (C-X-C motif) receptor 3
211469_s_at	CXCR6	1·58	1·95	0·32	0·42	Chemokine (C-X-C motif) receptor 6
206613_at	IL-18R1	2·32	1·38	0·61	0·62	Interleukin-18 receptor 1
207072_at	IL-18RAP	2·16	1·44	0·46	0·56	Interleukin-18 receptor accessory protein
212657_s_at	IL-1RN	1·44	3·12	0·56	0·37	Interleukin 1 receptor
206341_at	IL-2RA	1·52	1·27	0·73	0·66	Interleukin-2 receptor alpha
202859_x_at	IL-8	1·31	3·75	0·38	0·69	Interleukin-8
202643_s_at	TNFAIP3	1·61	1·25	0·67	0·75	Tumour necrosis factor, alpha-induced protein 3
202687_s_at	TNFSF10	2·83	1·23	0·67	0·77	Tumour necrosis factor (ligand) superfamily member 10
205599_at	TRAF1	2·25	1·32	0·68	0·61	Tumour necrosis factor receptor-associated factor 1
202871_at	TRAF4	1·43	1·58	0·57	0·48	Tumour necrosis factor receptor-associated factor 4
206366_x_at	XCL1	1·24	2·66	0·46	0·76	Chemokine (C motif) ligand 1
Signal transduction
210538_s_at	AIP1	1·35	1·54	0·65	0·61	Baculoviral IAP repeat-containing 3
209369_at	ANXA3	1·39	6·82	0·61	0·05	Annexin A3
1554343_a_at	BRDG1	1·45	1·67	0·52	0·55	BCR downstream signalling 1
225946_at	C12orf2	3·20	1·77	0·23	0·23	Ras association (RaIGDS/AF-6) domain family 8
204392_at	CAMK1	1·26	1·62	0·74	0·54	Calcium/calmodulin-dependent protein kinase I
231042_s_at	CAMK2D	1·31	1·63	0·25	0·69	Calcium/calmodulin-dependent protein kinase (CaM kinase) II delta
205692_s_at	CD38	1·37	1·29	0·71	0·48	CD38 antigen (p45)
231747_at	CYSLTR1	3·16	1·45	0·55	0·43	Cysteinyl leukotriene receptor 1
211272_s_at	DGKA	1·43	1·23	0·77	0·54	Diacylglycerol kinase alpha 80 kDa
200762_at	DPYSL2	1·35	1·40	0·37	0·65	Dihydropyrimtdinase-like 2
208370_s_at	DSCR1	1·23	1·90	0·63	0·77	Down syndrome critical region gene 1
204794_at	DUSP2	1·55	2·57	0·39	0·45	Dual specificity phosphatase 2
204015_s_at	DUSP4	1·35	2·66	0·65	0·39	Dual specificity phosphatase 4
211333_s_at	FASLG	1·20	1·37	0·49	0·80	Fas ligand (TNF superfamily, member 6)
211535_s_at	FGFR1	1·23	2·79	0·70	0·77	Fibroblast growth factor receptor 1
224148_at	FYB	1·50	1·21	0·45	0·79	FYN binding protein (FYB-120/130)
209304_x_at	GADD45B	1·55	1·29	0·65	0·71	Growth arrest and DNA-damage-inducible beta
234284_at	GNG8	1·50	3·16	0·50	0·35	Guanine nucleotide binding protein (G protein), gamma 8
224285_at	GPR174	1·91	1·42	0·56	0·58	G protein-coupled receptor 174
223767_at	GPR84	4·41	1·44	0·05	0·56	G protein-coupled receptor 84
211555_s_at	GUCY1B3	1·66	1·73	0·34	0·03	Guanylate cyclase 1, soluble, beta 3
38037_at	HBEGF	1·54	1·36	0·55	0·64	Heparin-binding EGF-like growth factor
203820_s_at	IMP-3	1·83	2·18	0·17	0·17	IGF-II-mRNA-binding protein 3
203006_at	INPP5A	1·40	1·86	0·60	0·52	Inositol polyphosphate-5-phosphatase, 40 kDa
231779_at	IRAK2	1·93	1·46	0·46	0·54	Interleukin-1 receptor associated kinase 2
32137_at	JAG2	1·58	1·29	0·71	0·64	Jagged 2
203904_x_at	KAI1	1·65	1·59	0·41	0·25	CD82 antigen
235252_at	KSR	1·72	1·56	0·43	0·44	Kinase suppressor of ras 1
210948_s_at	LEF1	1·21	1·64	0·41	0·79	Hypothetical protein LOC641518
203236_s_at	LGALS9	1·48	1·27	0·73	0·51	Lectin, galactoside-binding, soluble, 9 (galectin 9)
220253_s_at	LRP12	1·27	1·30	0·31	0·73	Low-density lipoprotein-related protein 12
206637_at	P2RY14	1·32	1·48	0·39	0·68	Purinergic receptor P2Y, G-protein coupled, 14
210837_s_at	PDE4D	1·35	1·31	0·62	0·69	Phosphodiesterase 4D, cAMP-specific
206726_at	PGDS	6·45	1·40	0·60	0·43	Prostaglandin D2 synthase, haematopoietic
210617_at	PHEX	1·53	4·08	0·21	0·47	Phosphate regulating endopeptidase homologue, X-linked
206370_at	PIK3CG	1·23	1·32	0·50	0·77	Phosphoinositide-3-kinase, catalytic, gamma polypeptide
205632_s_at	PIP5K1B	1·32	1·42	0·64	0·68	Phosphalidylinositol-4-phosphate 5-kinase, type 1 beta
215195_at	PRKCA	2·17	1·36	0·64	0·61	Protein kinase C, alpha
210832_x_at	PTGER3	4·44	1·47	0·07	0·53	Prostaglandin E receptor 3 (subtype EP3)
1553535_a_at	RANGAP1	1·58	1·39	0·58	0·61	Ran GTPase activating protein 1
234344_at	RAP2C	1·75	1·26	0·46	0·74	RAP2C, member of RAS oncogene family
223809_at	RGS18	2·12	1·67	0·15	0·33	Regulator of G-protein signalling 18
209882_at	RIT1	1·74	1·32	0·63	0·68	Ras-like without CAAX 1
209451_at	TANK	1·34	1·20	0·42	0·80	TRAF family member-associated NFKB activator
204924_at	TLR2	1·60	2·52	0·36	0·40	Toll-like receptor 2
217979_at	TM4SF13	1·21	2·47	0·30	0·79	Tetraspanin 13
209263_x_at	TM4SF7	2·05	1·41	0·58	0·59	Tetraspanin 4
Transcription
1566989_at	ARID1B	1·42	1·27	0·09	0·73	AT-rich interactive domain 1B (SWIl-like)
203973_s_at	CEBPD	3·06	1·51	0·33	0·49	CCAAT/enhancer binding protein (C/EBP), delta
221598_s_at	CRSP8	1·60	1·29	0·71	0·68	Cofactor required for Spl transcriptional activation, subunit 8, 34 kDa
205249_at	EGR2	1·33	4·27	0·67	0·60	Early growth response 2 (Krox-20 homologue, Drosophila)
206115_at	EGR3	1·31	6·15	0·69	0·48	Early growth response 3
201328_at	ETS2	1·57	1·72	0·43	0·40	V-ets erythroblastosis virus E26 oncogene homologue 2 (avian)
218810_at	FLJ23231	2·13	1·37	0·63	0·63	Zinc finger CCCH-type containing 12A
209189_at	FOS	21·56	1·31	0·13	0·69	V-fos FBJ murine osteosarcoma viral oncogene homologue
223408_s_at	FOXK2	2·26	1·22	0·48	0·78	Forkhead box K2
202723_s_at	FOXO1A	1·47	1·27	0·57	0·73	Forkhead box O1A (rhabdomyosarcoma)
224211_at	FOXP3	1·62	1·41	0·59	0·23	Forkhead box P3
207156_at	HIST1H2AG	1·73	1·30	0·41	0·70	Histone 1, H2ag
220042_x_at	HIVEP3	1·26	1·65	0·74	0·56	Human immunodeficiency virus type I enhancer binding protein 3
207826_s_at	ID3	1·34	8·64	0·60	0·66	Inhibitor of DNA binding 3, dominant negative helix-loop-hetix protein
204549_at	IKBKE	2·33	1·29	0·71	0·66	Inhibitor of kappa light polypeptide gene enhancer in B cells
219878_s_at	KLF13	1·89	1·26	0·34	0·74	Kruppel-like factor 13
207667_s_at	MAP2K3	1·33	1·28	0·72	0·57	Mitogen-activated protein kinase kinase 3
201502_s_at	NFKBIA	2·31	1·29	0·71	0·57	Nuclear factor of κ light polypeptide gene enhancer in B cells inhibitor
222105_s_at	NKIRAS2	1·84	1·21	0·69	0·79	NFKB inhibitor interacting Ras-like 2
204622_x_at	NR4A2	1·35	4·31	0·65	0·63	Nuclear receptor subfamily 4, group A, member 2
207978_s_at	NR4A3	1·33	3·53	0·62	0·67	Nuclear receptor subfamily 4, group A, member 3
202600_s_at	NRIPI	1·86	1·39	0·26	0·61	Nuclear receptor interacting protein 1
216841_s_at	SOD2	1·25	1·73	0·36	0·75	Superoxide dismutase 2, mitochondrial
201416_at	SOX4	1·53	2·21	0·47	0·38	SRY (sex determining region Y)-box 4
223635_s_at	SSBP3	2·12	1·25	0·75	0·62	Single-stranded DNA binding protein 3
206506_s_at	SUPT3H	1·47	1·31	0·57	0·69	Suppressor of Ty 3 homologue (S. cerevisiae)
221618_s_at	TAF9L	1·25	1·49	0·47	0·75	TAF9-like RNA polymerase II
203177_x_at	TFAM	1·63	1·23	0·77	0·57	Transcription factor A, mitochondrial
213943_at	TWIST1	1·89	3·14	0·04	0·11	Twist homologue 1 (acrocephalosyndactyly 3; Saethre-Chotzen syndrome)
219836_at	ZBED2	1·33	4·76	0·67	0·21	Zinc finger, BED-type containing 2
211965_at	ZFP36L1	2·02	1·47	0·29	0·53	Zinc finger protein 36, C3H type-like 1
230760_at	ZFY	1·41	1·25	0·75	0·02	Zinc finger protein, Y-linked
228854_at	ZNF145	3·26	1·21	0·40	0·79	Transcribed locus
235121_at	ZNF542	2·68	1·33	0·63	0·67	Zinc finger protein 542

The genes with a higher level of expression in the PB-derived CD4⁺ T cells included those encoding transcriptional regulators, signal transduction factors, major histocompatibility complex (MHC) class II molecules (HLADMA, HLADMB, HLADPA1, HLADQB1, HLADRA, HLADRB1 and HLADRB5), and cytokines, chemokines and their receptors (IL-7, IL-17RB), as well as genes that characterize the T-cell lineage (CD29, CD86) (Fig. 1b, Tables 2, 4).

Notably, microarray studies showed that the expression of several regulatory T cell (Treg)-related genes was significantly higher in the CB-derived T cells. Foxp3 is an important T-cell transcription factor and is considered to be a marker of Tregs. Cytotoxic T-lymphocyte antigen-4 (CTLA-4) and ICOS, which belong to the CD28 family of receptors and play a crucial role in the activation of T cells, were reported to be highly expressed in activated Tregs.^11,12 All of the above genes were expressed at higher levels in the CB-derived CD4 T cells (Fig. 1).

The microarray results for major genes related to the development of the T-cell lineage, including those not appeared in Fig. 1, are summarized in Table 2. As shown in Table 2, the expression of T-cell lineage master regulator genes, such as TBX21, GATA3 and MAF, and T cell-related cytokines, such as IL-4, IL-5, IL-13, IL-22 and TGFB1, revealed no significant difference between CB-derived CD4⁺ cells and PB-derived CD4⁺ cells. However, other T cell-related genes, including IL-2, IL-6, IL-9, IL-10 and IL-17, were eliminated from the list in the course of background subtraction because the signal intensity of each gene was low (< 90 as raw data) in all of the samples.

Differences in the expression patterns of T-cell lineage-specific genes between CB-derived and PB-derived CD4⁺ T cells

To further confirm the characteristic gene expression in CB- and PB-derived CD4⁺ T cells, we performed a real-time RT-PCR analysis. Consistent with the microarray data, when the mRNA levels of the genes related to the T helper type 1 (Th1) and Th2 phenotypes were examined, higher levels of GM-CSF and IFNG were observed in CB-derived T cells, while IL-4 revealed no significant tendency (Fig. 2). We also examined IL-6 and IL-10 and no significant tendency was observed either in the expression of these genes (Fig. 2).

Figure 2.

Quantitative polymerase chain reaction (PCR) analysis of the genes related to the T helper type 1 (Th1) and Th2 phenotypes. The expression of the genes indicated was examined by real-time reverse transcriptase (RT)-PCR using the same sample specimens as in Fig 1. Data are normalized to the mRNA level in PB 1 which is arbitrarily set to 1. The signal intensity was normalized using that of a control housekeeping gene [the human glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene]. Data are relative values with the standard deviation (SD) for triplicate wells.

Next we examined the expression of the genes related to Tregs and observed a higher level of Foxp3, but lower levels of retinoic acid receptor-related orphan receptor γ isoform t (RORγt); and IL-17F, in CB-derived T cells (Fig. 3). In contrast, there was no significant tendency in the expression of genes encoding signal transducer and activator of transcription 3 (STAT-3), IL-23 and IL-23 receptors. In the case of the IL-17 gene, clear amplification was detected in PB-derived T cells whereas no amplification was observed in the samples of CB-derived T cells (data not shown).

Figure 3.

Quantitative polymerase chain reaction (PCR) analysis of the forkhead box protein 3 gene (FOXP3) and the genes related to the secretion of interleukin (IL)-17. The expression of the genes indicated was examined as in Fig 2. Data are normalized to the mRNA level in peripheral blood sample 1 (PB 1) as in Fig.2. The signal intensity was normalized using that of a control housekeeping gene [the human glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene]. Data are relative values with the standard deviation for triplicate wells.

To further investigate whether increased expression of the FOXP3 gene is a general feature of CB-derived CD4⁺ T cells, we tested four samples of CB-derived CD4⁺ T cells by real-time RT-PCR analysis and compared the results with those for equivalent numbers of PB-derived samples. As shown in Fig. 4, two CB-derived samples (CB 4 and 5, at 2 weeks) revealed significantly increased gene expression of FOXP3 when compared with PB-derived samples, whereas the remaining two samples (CB 3 and 6; termed ‘additional’ samples below) did not. We also tested FOXP3 gene expression at an earlier time-point in the same samples and observed no significant increase of FOXP3 gene expression in CB-derived CD4⁺ T cells at 1 week (Fig. 4). When the data were analysed statistically, expression of the FOXP3 gene was found to be significantly higher in CB-derived CD4⁺ T cells in comparison with equivalent PB-derived CD4⁺ T cells at both 1 week (P<0·05) and 2 weeks (P<0·05) (Fig. 4).

Figure 4.

Quantitative polymerase chain reaction (PCR) analysis of the forkhead box protein 3 gene (FOXP3) in additional samples. Additional peripheral blood (PB) and cord blood (CB) samples were prepared and RNAs were extracted at 1 and 2 weeks. The expression of the FOXP3 gene was examined as in Fig. 2. Data are normalized to the mRNA level in the sample of PB 3 at 1 week, which is arbitrarily set to 1. The signal intensity was normalized using that of a control housekeeping gene (the human β-actin gene). Data are relative values with the standard deviation for triplicate wells. The data were analysed statistically and FOXP3 gene expression in CB-derived CD4⁺ T cells was found to be significantly higher in comparison with equivalent PB-derived CD4⁺ T cells at both 1 week (P<0·05) and 2 weeks (P<0·05).

Next we assessed the expression of the Foxp3 protein in CB-derived CD4⁺ T cells. When the same samples as described above were examined by flow cytometry using a specific antibody, the Foxp3 protein was certainly detected in a portion of cells in all of four CB-derived samples while not detected in any of the PB-derived samples tested (Fig. 5). Inconsistent with the results of real-time RT-PCR, expression level of Foxp3 proteins was higher in CB-derived CD4⁺ T cells at 1 week than at 2 weeks.

Figure 5.

Protein expression of forkhead box protein 3 (Foxp3) in activated CD4⁺ T cells. The protein expression of Foxp3 in same sample specimens as in Fig. 4 was examined by flow cytometry. The CD4 versus Foxp3 cytogram of the population gated with CD3⁺ and CD4⁺ in each sample is presented.

To investigate whether increased expression of the IL-17 gene is a general feature of PB-derived CD4⁺ T cells, we also tested IL-17 gene expression in the above-described additional samples by real-time RT-PCR analysis. As shown in Fig. 6, all of four PB-derived CD4⁺ T-cell samples revealed significantly increased gene expression of IL-17 when compared with the CB-derived samples at 1 week. At 2 weeks, however, IL-17 gene expression in PB-derived CD4⁺ T cells was diminished while some of the CB-derived CD4⁺ T cells (such as sample CB 4) exhibited increased IL-17 gene expression. When the data were analysed statistically, expression of the IL-17 gene was found to be significantly higher in PB-derived CD4⁺ T cells in comparison with equivalent CB-derived CD4⁺ T cells at 1 week (P < 0·05) but not at 2 weeks (Fig. 6).

Figure 6.

Quantitative polymerase chain reaction (PCR) analysis of interleukin (IL)-17 in additional samples. The expression of the IL-17 gene in the same sample specimens as in Fig. 4 was examined and presented as in Fig 2. The data were analysed statistically and IL-17 gene expression in peripheral blood (PB)-derived CD4⁺ T cells was found to be significantly higher in comparison with equivalent CB-derived CD4⁺ T cells at 1 week (P<0·05) but not at 2 weeks.

Discussion

Although it is generally believed that there are functional differences between CB and PB lymphocytes, the details are obscure. For instance, Azuma et al.¹³ reported that the phenotype and function of expanded CB lymphocytes were essentially equivalent to those of expanded PB lymphocytes when evaluated in in vitro experiments. In the present study, however, we have shown that CB-derived CD4⁺ T cells revealed a distinct expression profile of genes important for the function of particular T-cell subsets compared with PB-derived CD4⁺ T cells.

CD4⁺ T cells can be classified into distinct subsets, including effector CD4⁺ cells and Tregs, according to their functional characteristics as well as differentiation profiles.^14–16 Typically, effector CD4⁺ T cells have been further divided into two distinct lineages on the basis of their cytokine production profiles, namely Th1 and Th2. Th1 cells producing cytokines such as IL-2, IFN-γ and GM-CSF have evolved to enhance the eradication of intracellular pathogens and are thought to be potent activators of cell-mediated immunity. In contrast, Th2 cells secreting cytokines such as IL-4, IL-5, IL-6, IL-9 and IL-13 have evolved to enhance the elimination of parasitic infections and are thought to be potent activators of B-cell immunoglobulin E production, eosinophil recruitment, and mucosal expulsion. Th1-type responses to self or commensal floral antigens can promote tissue destruction and chronic inflammation, whereas dysregulated Th2-type responses can cause allergy and asthma. The development of Th1 is specified by the transcription factor T-bet (also known as Tbx-21) and master regulators of Th2 differentiation are GATA-3 and c-maf.

As shown in Fig. 2 and Table 2, the gene expression profiles of CB- and PB-derived CD4⁺ T cells revealed no significant differences regarding cytokines related to the definition of Th1 and Th2, with the exceptions of IFN-γ and GM-CSF. The mRNA levels of IFN-γ and GM-CSF tended to be higher in CB-derived CD4⁺ T cells than in PB-derived CD4⁺ T cells. The mRNA expression of the transcription factors T-bet, GATA-3 and c-maf, which regulate Th1 and Th2 cell differentiation, did not differ significantly between CB- and PB-derived CD4⁺ T cells.

In addition to Th1 and Th2 cells, IL-17 (also known as IL-17A)-producing T lymphocytes have been recently shown to comprise a distinct third subset of T helper cells, termed Th17 cells, in the mouse immune system. Th17 cells exhibit pro-inflammatory characteristics and act as major contributors to autoimmune disease. A number of experiments using animal models support a significant role for IL-17 in the response to allografts.^14,16,17 There is as yet no direct evidence for the existence of discrete Th17 cells in humans, although helper T cells secreting IL-17 have clearly been detected in the human immune system.¹⁸ Several studies have shown a correlation between allograft rejection and IL-17. For example, IL-17 levels are elevated in human renal allografts during subclinical rejection and there are detectable mRNA levels in the urinary mononuclear cell sediments of these patients.^19,20 In human lung organ transplantation, IL-17 levels have also been reported to be elevated during acute rejection.²¹ Interestingly, in this study, most of the PB-derived CD4⁺ T-cell samples expressed higher levels of IL-17 mRNA than the CB-derived CD4⁺ T-cell samples, suggesting that PB-derived CD4⁺ T cells frequently include potent IL-17-secreting T cells.

Th17 cells expand independently of T-bet or STAT-1. Ivanov et al.²² have shown that the orphan nuclear receptor RORγt is the key transcription factor orchestrating the differentiation of the effector lineage. RORγt induces transcription of the gene encoding IL-17 in naïve CD4⁺ T helper cells and is required for its expression in response to IL-6 and transforming growth factor (TGF)-β, the cytokines known to induce IL-17 expression. IL-23 is also involved in Th17 cell differentiation, but naïve T cells do not have the IL-23 receptor and are relatively refractory to IL-23 stimulation.^23,24 Although IL-23 seems to be an essential survival factor for Th17 cells, it is not required during their differentiation. It has been suggested that IL-23R expression is up-regulated on RORγt⁺ Th17 cells in an IL-6-dependent manner. IL-23 may therefore function subsequent to IL-6/TGF-β-induced commitment to the Th17 lineage to promote cell survival and expansion and, potentially, the continued expression of IL-17 and other cytokines that characterize the Th17 phenotype. As presented in Fig. 3, the expression of the RORγt gene was significantly weaker in CB-derived CD4⁺ T cells, whereas the expression of genes encoding IL-23 and the IL-23 receptor did not differ significantly between the CD4⁺ T cells. Based on the above findings of others, it is possible that the low-level expression of the RORγt gene in CB-derived CD4⁺ T cells is responsible for the absence of IL-17 mRNA expression in those cells.

Tregs are another functional subset of T cells having anti-inflammatory properties and can cause quiescence of autoimmune diseases and prolongation of transplant function. In vitro, Tregs have the ability to inhibit the proliferation and production of cytokines by responder (CD4⁺ CD25⁻ and CD8⁺) T cells subjected to polyclonal stimuli, as well as to down-regulate the responses of CD8⁺ T cells, NK cells and CD4⁺ cells to specific antigens.^25,26 These predicates translate in vivo to a great number of functions other than the maintenance of tolerance to self-components (prevention of autoimmune disease), such as the ability to prevent transplant rejection. Indeed, donor-specific Tregs can prevent allograft rejection in some models of murine transplant tolerance through a predominant effect on indirect alloresponses.

Foxp3 is thought to be responsible for the development of the Treg population and can act as a phenotypic marker of this fraction.²⁷ Tregs constitutively express CTLA-4 and there are suggestions that signalling through this pathway may be important for their function, as antibodies to CTLA-4 can inhibit Treg-mediated suppression.²⁸ As shown above, most of the CB-derived CD4⁺ T cells were found to express either the FOXP3 gene or the Foxp3 protein at higher levels compared with PB-derived CD4⁺ T cells, suggesting that CB-derived CD4⁺ T cells frequently include a potent Treg population.

As described above, IL-17 mRNA was more detectable in PB-derived CD4⁺ cells while FOXP3 mRNA expression was higher in CB-derived CD4⁺ cells. Post-transcriptional regulation, as well as differences in mRNA and protein turnover rates, can cause discrepancies between mRNA and protein expression and thus the differences observed in the mRNA expression do not necessary directly indicate those in protein expression.²⁹ Indeed, we observed some discrepancy between the levels of mRNA and protein with regard to Foxp3 expression in CB-derived CD4⁺ T cells, as presented above. Nevertheless, changes in mRNA expression are mediated by the alteration of transcriptional regulation, and thus should indicate the differentiation ability of the cells. Therefore, our data indicate that CB-derived CD4⁺ T cells tend frequently to include potent Tregs, while PB-derived CD4⁺ T cells tend to include potent IL-17-secreting cells. As described above, DLI with donor CB-derived activated CD4⁺ T cells is currently becoming established as a routine therapeutic strategy in Japan. It has been proposed that the skewing of responses towards Th17 or Th1 cells and away from Tregs may be responsible for the development and/or progression of autoimmune diseases or acute transplant rejection, and it may thus also be speculated that CB-derived CD4⁺ T cells are more appropriate for DLI than PB-derived CD4⁺ T cells.

However, our data also indicate the presence of individual, donor-dependent variations in the characteristics of activated CD4⁺ T cells derived from CB and PB. Moreover, activated CD4⁺ T cells do not consist of a single population and should include several distinct functional subsets of CD4⁺ T cells. Therefore, it is important to clarify the characteristics of activated CD4⁺ T cells in each preparation to predict the therapeutic effect of DLI in each clinical case.

In summary, our findings demonstrate a difference in gene expression between activated CD4⁺ T cells derived from CB and those derived from PB. The higher level of FOXP3 gene expression and the lower level of IL-17 gene expression in CB-derived CD4⁺ T cells may indicate that these cells have potential as immunomodulators in DLI therapy. Further detailed analysis should reveal the advantages of activated CD4⁺ T cells from CB in DLI.

Glossary

Abbreviations:

BIM

BCL2-like 11

CB

cord blood

CTLA-4

cytotoxic T-lymphocyte antigen-4

CDKN

cyclin-dependent kinase inhibitor

DLI

donor lymphocyte infusion

Foxp3

forkhead box protein 3

GAPDH

glyceraldehyde-3-phosphate dehydrogenase

GM-CSF

granulocyte–macrophage colony-stimulating factor

GVHD

graft-versus-host disease

GVL

graft-versus-leukaemia

HSCT

haematopoietic stem cell transplantation

ICOS

inducible T-cell co-stimulator

IFNG

interferon γ

IL

interleukin

PB

peripheral blood

RORγt

retinoic acid receptor-related orphan receptor γ isoform t

RT

reverse transcriptase

TCR

T-cell receptor

Th

T helper cell

Treg

regulatory T cell

Disclosures

No competing personal or financial interests exist for any of the authors in relation to this manuscript.