The gene expression profile of ... - Wiley Online Library

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Fre´deric Pont et al.

DOI 10.1002/eji.201141870

Eur. J. Immunol. 2012. 42: 228–240

The gene expression profile of phosphoantigen-specific human cd T lymphocytes is a blend of ab T-cell and NKcell signatures Fre´deric Pont1,2,3, Julien Familiades1,2,3, Se´bastien De´jean4, Se´verine Fruchon1,2,3, Delphine Cendron1,2,3, Mary Poupot1,2,3, Re´my Poupot1,2,3, Fatima L’Faqihi-Olive2,5, Nais Prade6, Bernard Ycart7 and Jean-Jacques Fournie´1,2,3 1 2 3 4 5 6 7

INSERM UMR1037, Cancer Research Center of Toulouse, Toulouse, France Universite´ Toulouse III Paul-Sabatier, Toulouse, France ERL 5294 CNRS, BP3028, Hospital Purpan, Toulouse, France Institut de Mathe´matiques, Universite´ Toulouse III Paul-Sabatier, Toulouse, France INSERM UMR1043, Center of Physiopathology of Toulouse Purpan, Toulouse, France Department of Haematology, Hospital Purpan, Toulouse, France Laboratoire Jean Kuntzmann, Universite´ de Grenoble Joseph Fourier and CNRS, Grenoble, France

Global transcriptional technologies have revolutionised the study of lymphoid cell populations, but human cd T lymphocytes specific for phosphoantigens remain far less deeply characterised by these methods despite the great therapeutic potential of these cells. Here we analyse the transcriptome of circulating TCRVc1 cd T cells isolated from healthy individuals, and their relation with those from other lymphoid cell subsets. We report that the gene signature of phosphoantigen-specific TCRVc1 cd T cells is a hybrid of those from ab T and NK cells, with more ‘NK-cell’ genes than ab T cells have and more ‘T-cell’ genes than NK cells. The expression profile of TCRVc1 cd T cells stimulated with phosphoantigen recapitulates their immediate physiological functions: Th1 cytokine, chemokine and cytotoxic activities reflect their high mitotic activity at later time points and do not indicate antigen-presenting functions. Finally, such hallmarks make the transcriptome of cd T cells, whether resting or clonally expanding, clearly distinctive from that of NK/T or peripheral T-cell lymphomas of the cd subtype.

Key words: Gamma-delta . Lymphocyte . Lymphoma . Microarray . Phosphoantigen

Supporting Information available online

Introduction Although the biology of ab T lymphocytes is reasonably well understood, that of gd T lymphocytes remains far less char-

acterised, with development, reactivity and functions that relate to both innate and adaptive immunity. These lymphoid cells express both rearranged antigen receptors and non-rearranged receptors for self-HLA class I or stress signals. In human and nonhuman primates, the peripheral repertoire of the TCR is markedly biased, with most blood gd T cells expressing TCRVg9Vd2 specific

Correspondence: Dr. Jean-Jacques Fournie´ e-mail: [email protected]

These authors contributed equally to this work.

& 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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Molecular immunology

for phosphorylated isoprenoı¨ds (the so-called phosphoantigens) produced by the microbial DOXP and eukaryote mevalonate pathways. Within 4–6 h after activation, TCRVg9Vd21 gd T cells release the pro-inflammatory chemokines MIP-1a, MIP-1b and RANTES, secrete Th1 cytokines IFN-g and TNF-a and kill cancer cells through granzyme, perforin, FasL and TRAIL. In addition, TCRVg9Vg21 gd T cells can take various patterns of differentiation according to the tissue and physiological contexts. These lymphocytes were characterised as Th0 cells [1], Th1 cells [2], T follicular helper cells [3], terminally differentiated Ra cells [4], Treg cells [5], Th17 cells [6] and even as phagocytes [7] or antigen-presenting cells [8]. Furthermore, the cytolytic activity of human gd T lymphocytes may result from activation cascades driven by TCR, NKG2D, CD16, CD160, KIR2DS1, KIR2DS2 and NKp44 and under the negative regulation by inhibitory receptors CD94/NKG2A, KIR2DL1, KIR2DL2 and KIR2DL3 [9]. Thus, TCRVg9Vd21 gd T cells exert NK-like cytotoxic responses against HLA class I-deficient cell targets in addition to T-cell-type cytotoxic responses driven by antigen activation. Together, these features make TCRVg9V21 gd T lymphocytes versatile and attractive candidates for new cancer immunotherapies [10–12]. For these reasons, synthetic analogues of natural phosphoantigens such as bromohydrin pyrophosphate (BrHPP) have been produced and the immune functions mediated by phosphoantigen-activated gd T cells appear promising [13, 14]. Preclinical and clinical studies with BrHPP have shown that phosphoantigens induce a potent and rapid response of the TCRVg9Vd21 gd T lymphocytes in humans and in various species of non-human primate models [15, 16]. The unusual behaviour and high versatility of TCRVg9Vd21 gd T lymphocytes raise several questions on their biology, however. For the design of gd T-cell-based vaccines, are these cells more related to adaptive ab T lymphocytes or to NK cells? From a global pharmacological perspective, what is the transcriptional signature of their activation by phosphoantigens? From a physiopathological standpoint, what differs between freshly activated, normal TCRVg9Vd21 gd T cells, primary cultured cell lines of normal TCRVg9Vd21 gd T cells and peripheral T-cell lymphomas (PTCLs) of gd subtype? To clarify these issues here we report the transcriptomes of highly purified TCRVg9Vd21 gd T cells from healthy individuals and analyse them relative to those of other subsets of human lymphoid cells. These data sets have been deposited at NCBI GEO repository and are freely downloadable under accession number GSE27291.

vised clustering of these transcriptomes formed three main clusters based on differential expression of several thousands of genes. These three clusters were correlated quite well to the cell lineage (B, T, NK cells, R2 5 0.68) and the normal versus cancer status of cell samples (R2 5 0.84). Further subdivision of the clusters I–III created nine groups that encompassed three groups of B cells composing the previous cluster I, five groups in the T and NK cell cluster II, while cluster III comprised two lymphoma groups: PTCLs and NKT cell lymphomas (NKTCLs). Cluster I comprised all the normal B-cell samples, the cluster II encompassed both T and NK cells from normal samples and established cell lines, whereas cluster III encompassed the freshly collected samples of PTCLs and NKTCLs. The T and NK cell cluster II encompassed two branches comprising the cultured cell lines on the first and freshly isolated cells on the other, which subdivided into two subgroups of T cells in one branch and all NK cells plus the CD81 T cells in the other branch. In cluster II, the freshly isolated, resting gd T cells and their counterparts obtained 6 h after activation with the BrHPP phosphoantigen segregated with freshly isolated ab CD41 T cells. After 7 days of activation with BrHPP, however, the TCRVg91 gd T cells clustered primarily with ‘normal gd T cells’ (cluster 7) that were established by 2 weeks culture with zoledronate [17] and then with established cell lines of gd T cells and NK cells (cluster 8). This clustering most likely reflects the mode of action of zoledronate on peripheral blood mononuclear cells, since this aminobisphosphonate is a phosphoantigen-inducing gd T-cell agonist targeting the same TCRVg91 lymphocytes [18]. Of note, additional transcriptomes of freshly isolated monocytes or differentiated macrophages produced in our laboratory [19] clustered outside of the whole lymphoid cell panel involved in this study (data not shown). Cluster III was essentially composed of the primary PTCLs on the one hand and of a more heterogeneous subgroup comprising both cytotoxic ab and gd PTCLs plus the NKTCLs. This sub-clustering we obtained here with entire transcriptomes matched perfectly to the recently depicted clustering of PTCLs and extranodal NK/T-cell lymphomas of nasal type based on 762 differentially expressed genes [20] (Fig. 1). Therefore, the gene signature of normal TCRVg91 gd T lymphocytes overlaps those from both ab cells and NK cells.

Results

Although in the hierarchical clustering, the normal gd TCRVg91 cells were most closely related to normal ab T and NK cells, there were clear differences in their respective gene expression patterns (Fig. 2). Seven thousand eight hundred forty-four genes were differentially (po0.05) expressed by gd TCRVg91 and ab T cells, with 3379 genes up-regulated and 4465 down-regulated by the gd TCRVg91 cells, while 11 264 genes were differentially expressed by gd TCRVg91 and NK cells, with 5617 genes up-regulated and 5646 down-regulated by the gd TCRVg91

The transcriptomes of normal TCRVc91 cd T cells cluster together and next to ab T and NK cells The expression profiles of the 12 TCRVg91 gd T-cell samples were compared with those of normal B, ab and gd T, NK cells and of peripheral T and NKT cell lymphomas (a total of 90 entire transcriptomes obtained on the same platform). The unsuper-


Genes differentially expressed in cd TCRVc91 cells relative to ab T cells and to NK cells

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Figure 1. Unsupervised hierarchical clustering of 90 transcriptomes (20 606 genes) from gd T cells and other lymphoid cell subtypes. Shown are 26 samples of normal B cells of naı¨ve, memory, centroblastic and centrocytic types [52, 53], 6 samples of ab T cells of CD41 and CD81 types [17, 54, 55], 13 samples of NK cells (this study and [55]), 14 samples of TCRVg91 gd T cells (this study and [17]), 6 EBV1 gd T-cell lines from EBV-infected patients [17], 16 peripheral T-cell lymphomas (PTCLs) [21] and 9 NKT cell lymphomas (primary tumours and cell lines) [20].

T cells. Representative genes up-regulated by the gd TCRVg91 cells relative to ab T lymphocytes (as a whole) comprised genes encoding for the cell surface receptors gd TCR, CD94 and NKG2D, which are well-known phenotypic markers of this lineage (Table 1). Indeed, although NKG2D is expressed on most gd TCRVg91 cells, it is also found on a substantial proportion of CD81 ab T cells but barely on the CD41 T cells (unless activated). The 500 genes most significantly up-regulated by normal TCRVg9 gd T cells relative to ab T cells were significantly enriched in genes from several related functional pathways from KEGG, Biocarta and GSEA C2 databases. These pathways comprised cytokine–cytokine receptor interactions (28 genes, p 5 8 10 12), NK cell-mediated cytotoxicity (16 genes, p 5 5.8 10 8), Jak-STAT signalling (12 genes, p 5 2 10 4)


and Th1 cell functions (20 genes, p 5 10 9, geneset GS11 defined de Leval, Rogge and Chtanova) [21]. On the other hand, representative genes up-regulated by normal gd T cells relative to NK cells comprised T-cell specifying genes such as CD3D and TRAT, which encore for the TCR-associated CD3d molecule and the TCR-associated trans-membrane adaptor TRIM1, respectively (Table 1). The 500 genes most significantly up-regulated by gd T cells relative to NK cells comprised genes encoding for cytokine–cytokine receptor interactions (15 genes, p 5 7.8 10 4, KEGG), MAPK signalling (12 genes, po10 2, KEGG), NKT pathway (6 genes, po10 4, Biocarta) and TCR/CTLA4 pathway (5 genes, po10 4, KEGG/ Biocarta, respectively). These results cannot be accounted for by differential culture conditions of the T-cell and NK-cell samples,

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Figure 2. Differential transcriptomes from freshly isolated B, ab T, gd T and NK cells. The most representative genes up-regulated by the gd T cells relative to either ab T cells or NK cells are listed by enriched gene ontology terms.

respectively, since both cell types comprise both resting unstimulated cells and IL-2-activated cells. Hence, the TCRVg9 gd T cells do not have their own unique signature (Fig. 2), since they merge hallmarks of T cells and NK-cells, such as more ‘NK cell’ genes than ab T cells and more ‘T-cell’ genes than NK cells. These results were validated by measuring with RT-qPCR the mRNA expression levels of representative genes from of TCRVg9 gd T cells as compared with those of purified ab T cells and NK cells (n 5 6 independent samples). The expression levels of the KLRK1, KLRC1, KLRC2, KLRC3, KLRC4 and KLRD1 genes were significantly (po0.05) over-expressed by 34-, 58- 66-, 11-, 19- and 66-fold, respectively, by the TCRVg9 gd T cells relative to ab T cells while they over-expressed the CCL3, CCL4 and CCL5 genes by 3-, 6- and 6-fold, respectively. Likewise, the expression levels of the CD28, CD3, ICOS and PERP genes were significantly (po0.05) over-expressed by 7-, 35-, 3- and 12-fold, respectively, by the TCRVg9 gd T cells relative to NK cells (Fig. 3A). A discrepancy between gene expression and phenotypes of killer Ig-type receptors has been reported, however [22], so we asked whether these mRNA expression patterns correlated to their surface phenotype by immunostaining and flow cytometry. For the representative set of cell surface antigens CD3e, CD4, CD8a, CD8b, CD16, CD32, CD64, CD85j, CD94, CTLA4, KIR2DL1, KIR3DL1, KIR2DL3, NKp30, NKp44, NKp46, NKG2A, NKG2D and PD-1, the mRNA level matched with the cell surface phenotype of control TCRVg91 gd T cells (Fig. 3B). This hybrid gene expression profile positions normal human TCRVg91 gd T lymphocytes at the interface of adaptive T lymphocytes and innate NK cells, in good agreement with their physiological development and functions [23].


Molecular signature of phosphoantigen-activated cd T cells The transcription profiles of the four human gd T-cell samples after activation by BrHPP phosphoantigen and culture with IL-2 were compared with those from the same samples before activation. Labelling the purified gd T-cell samples for intracellular Phospho-ZAP70 and flow cytometry indicated that the cell isolation procedure did not activate even a minor rate of the cells prior to stimulation with BrHPP and IL-2, in line with the baseline level of EGR gene expression in the control samples. From the 15 506 genes which expression was detectable in all samples, a total of 2573 genes were significantly modulated (po0.01) 6 h after activation, including 1583 over-expressed genes and 990 down-regulated genes. Six hours after activation, the most overexpressed genes were related to early activation (e.g. EGR2, EGR3) and function of T lymphocytes (e.g. IFNG, LIF, TNFA, LAMP3). At this time point, these cells secreted IFN-g MIP-1a and MIP-1b accordingly [24]. All the genes over-expressed at this early time point corresponded to functional categories from the KEGG’s pathways defined as TCR signalling (14 genes, po0.0009), NK cell cytotoxicity (15 genes, po0.02), Jak-Stat signalling (21 genes, po0.0002), as well as purine and pyrimidine metabolisms (21 and 14 genes, respectively, po0.0009 and o0.0005, respectively; Table 2). Seven days after activation and culture, the expression of a total of 3081 genes was significantly modified including 1835 over-expressed genes and 1246 down-regulated genes. At this time point, most of the over-expressed genes reflected segregation of chromosomes (e.g. KIF15, CENPK, CENPM, CEP55, SPBC25) and cell cycle (AURKB, CDCA8, CDC2, CDC20,

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Table 1. Representative genes up-regulated in TCRVg91 gd T cells

Gene symbol

Name

p-Value

Relative to ab T cells TRA, TRD TRGC2, TRGV2 KLRK1 KLRC1, KLRC2 KLRC3 KLRC4 KLRD1 KLRF1 CD160 KIR3DL2 NKG7 GZMB GNLY TNFSF14 FASLG IL18RAP KSP37 XCL1 XCL2 CCL3 CCL4 CCL5 TBX21

TCR a and TCR d locus TCR g locus NKG2D NKG2A, NKG2C NKG2E NKG2F CD94 NKp80 NK cell activating/inhibitory receptor (By55) Killer cell Ig-like receptor, three domains, long cytoplasmic tail, 2 GMP-17 Granzyme B Granulysin LIGHT, lymphotoxin g Fas ligand Interleukin 18 receptor accessory protein Killer-specific secretory protein of 37 kDa Lymphotactin, SCM-1b Chemokine (C motif) ligand 2 MIP-1a MIP-1b RANTES Tbet transcription factor

4 10 0.005 0.016 7 10 0.002 0.029 0.004 0.012 0.001 0.000 0.017 0.014 0.012 1 10 3 10 2 10 0.040 0.008 0.010 0.009 0.002 0.021 0.01

Relative to NK cells CD28 CD3D TRAT1 ICOS CD5 LAG3 TNFRSF25 TNFSF8 TNFRSF25 IL7R IL21R CXCR6 CCL20 DMN PERP PBX4

CD28 cell surface marker CD3d molecule (CD3-TCR complex) TCR-associated transmembrane adaptor 1, TRIM1 Inducible T-cell costimulator CD5 molecule Lymphocyte-activation gene 3 DR3, LARD, APO-3 CD153 marker (CD30 ligand) DR3, APO-3, LARD Interleukin 7 receptor Interleukin 21 receptor Chemokine (C-X-C motif) receptor 6 MIP-3a Desmuslin (intermediate filament protein) TP53 apoptosis effector Pre-B-cell leukaemia transcription factor 4

1.0 10 6.4 10 3.0 10 3.0 10 2.0 10 1.1 10 3.6 10 2.2 10 9.9 10 1.7 10 10 4 1.6 10 0.009 8.2 10 1.6 10 1.6 10

CDC45L). The other up-regulated genes corresponded to KEGG’s functional categories of purine and pyrimidine metabolisms (49 and 33 genes, po10 18 and o10 15, respectively), regulation of actin cytoskeleton (41 genes, po10 4), cell cycle (49 genes, po10 40), focal adhesion (31 genes, p 5 0.037), MAPK signalling (57 genes, po10 8), Wnt signalling (28 genes, po0.003) and Jak-Stat signalling (28 genes, po0.004; Table 2). These results were confirmed by RT-qPCR of mRNA for representative genes from TCRVg9 gd T cells, by comparing resting and activated TCRVg9 gd T cells (n 5 6 independent samples). After 6 h of activation, the expression levels of TNF-a, IFN-g, LIF, EGR2, CCL3 and CCL4 genes were significantly


Fold change

7

1.56 1.43 1.57 2.73 1.68 1.57 1.59 1.44 1.50 1.38 1.63 1.66 1.56 1.58 1.48 1.66 1.63 1.69 1.58 1.56 1.63 1.47 1.42

5

6 6 6

8 6 7 8 7 5 9 8 10 5

10

8 8 6

1.59 1.24 1.57 1.36 1.50 1.45 1.45 1.36 1.38 1.38 1.37 1.62 1.41 1.87 1.60 1.45

(po0.05) over-expressed by 118-, 433-, 14-, 368-, 230- and 39fold, respectively, whereas those of CCL5 and IL-32 were not changed. After 7 days of activation, the expression levels of IL-32, CDC20 and TOP2A genes were significantly (po0.05) overexpressed by 5-, 17- and 43-fold, respectively, whereas FOXM1 and CCNB1 were almost unchanged (Fig. 3A). Some markers such as CTLA-4 showed good consistency for mRNA and cell surface protein along activation, as both were low in resting controls and strongly increased by activation (Fig. 3B and C). However, the correlate of mRNA expression with cell surface phenotype was more generally lost with activated TCRVg91 gd T cells. KLRK1/NKG2D mRNA expression increased 6 h after acti-

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Figure 3. Validation of transcriptome data. (A) RT-qPCR of representative genes. Result shows the means and SD (n 5 6 replicates from independent donors) for the expression of the indicated genes relative to GAPDH in the specified cell samples. po0.05, one-way paired Student’s t-test. (B) Plot of mean of arbitrary units of mRNA expression (microarray-based) versus mean of fluorescence intensity (FACS-based) for cell surface expression of phenotypic markers on the resting control TCRVg9 gd T cells isolated from (n410) healthy individuals. (C) Divergent changes of cell surface phenotype and mRNA expression (microarray-based) in phosphoantigen-activated TCRVg91 gd T cells for TCR, CD3e, NKG2D, CD94, KIRs, NCRs and other markers of these cells.

vation but returned to baseline by day 7, whereas cell surface NKG2D was strongly increased at this time point. The mRNA expression of the CD28 gene was unchanged by day 7 while CD28 protein decreased at the cell surface, possibly reflecting effector memory maturation. The mRNA for PDCD1 decreased by day 7 while the encoded PD-1 protein strongly increased at the cell membrane (Fig. 3C), as recently reported [25]. Hence, although the mRNA and phenotype of resting TCRVg9 gd T cells were rather matched, activation with phosphoantigen introduced kinetic changes, which generally dissociated this match. The recurrent gene signatures of cytokine/cytokine receptor, JAK/ STAT and MAPK pathways reflected the IL-2-dependent conditions of gd T cell activation with BrHPP. Of note, however, none of the functional associations of the genes up-regulated by activation corresponded to antigen presentation. These experiments demonstrated that the molecular signature of gd T cells activated by phosphoantigens corresponds primarily to cytolytic, cytokine and chemokine activities and further to clonal expansion but not to the professional antigen-presenting functions observed in some culture conditions [8, 26, 27].


Transcriptomes of TCRVc91 cd T-cell lines from healthy individuals or lymphoma patients It was important to determine whether the molecular signature of such cells from EBV-infected patients, which comprise not only BZLF1 but also FGF14, PDCD4, CDK2, HSP90, IL12A and TNFRSF10D [28], did overlap that of normal cells strongly activated by more physiological agonists. The transcription profiles of TCRVg91 gd T-cell lines established from healthy donors (cluster 7) were thus compared with those of cell lines derived from patients with EBV-positive TCRVg91 gd T lymphoproliferative disorders [17] and with the related cell lines SNK6 and SNT7 [20] (cluster 8). The TCRVg91 gd T-cell lines from healthy individuals had up-regulated genes responsible for TCR signalling pathway (po10 8, KEGG), chemokine and cytokine signalling (po10 5, KEGG and Biocarta), cytotoxicity (po10 9, KEGG and Biocarta) and CTLA4 pathways (po5 10 4, Biocarta), cell development, growth and apoptosis (po10 5, GO Biological Process). On the other hand, there was no gene signature overlap with cell lines from lymphoma patients which

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Table 2. Representative genes up-regulated in phosphoantigen-activated TCRVg91 gd T lymphocytes

Fold changea)

Gene symbol

Name

p-Value

6 h after activation IFNG LIF EGR2 EGR3 LAMP3 CCL3 CCL4 IL32 PTGER2 CARD8 TNFRSF9 DPP4 CD96 RAB23 CDK5 BCL2 BTN3A2

Interferon g Leukaemia inhibitory factor Early growth response 2 Early growth response 3 Lysosomal-associated membrane protein 3 MIP-1a MIP-1b Interleukin 32 Prostaglandin E receptor 2 (subtype EP2) Apoptotic protein NDPP1 (CARDINAL) CD137 marker (accessory molecule 4-1BB) CD26 marker (adenosine deaminase complexing protein 2) CD96 molecule (Tactile) RAS oncogene family member Cyclin-dependent kinase 5 B-cell lymphoma 2 Butyrophilin subfamily 3 member A2

5.9 10 2.6 10 6.4 10 1.5 10 8.0 10 6.3 10 4.9 10 8.0 10 1.5 10 3.2 10 7.0 10 3.4 10 2.1 10 1.5 10 6.8 10 4.9 10 4.8 10

3

4.8 10 3.6 10 2.9 10 6.5 10 1.6 10 3.9 10 2.8 10 1.5 10 3.1 10 1.7 10 1.6 10 7.2 10 9.6 10 6.6 10 6.9 10 1.2 10 4.2 10 9.8 10 2.6 10 8.0 10 1.5 10 3.3 10 4.5 10 1.7 10 9.1 10

3

7 days after activation GINS1 GINS complex subunit 1 (Psf1 homolog, actively cycling cell marker) FOXM1 G2/M transition-regulating transcription factor HMMR Hyaluronan-mediated motility receptor (RHAMM) IL32 Interleukin 32 CEP55 Centrosomal protein 55 kDa CENPK Centromere protein K CDC20 CDC20 cell division cycle 20 homolog CDC45L CDC45 cell division cycle 45-like SPBC25 Spindle pole body component 25 homolog AURKB Aurora kinase B CDC2 Cell division cycle 2, G1 to S and G2 to M CENPM Centromere protein M CDCA8 Cell division cycle associated 8 KIF15 Kinesin family member 15 SDC4 Syndecan 4 (amphiglycan, ryudocan) PYCARD PYD and CARD domain containing TOP2A Topoisomerase (DNA) II a 170 kDa CENPH Centromere protein H CCNB2 Cyclin B2 KIF2C Kinesin family member 2C CCNB1 Cyclin B1 TYMS Thymidylate synthetase CCR2 Chemokine (C–C motif) receptor 2 KNTC2 Kinetochore-associated 2 NUSAP1 Nucleolar and spindle-associated protein 1 a)

3 4 3 3 4 3 3 3 3 3 3 3 3 3 4 3

5 4 4 3 6 4 3 4 3 3 3 5 3 3 3 3 3 3 4 4 3 3 4 5

42 31 20 28 24 18 8 18 13 8 19 7 5 5 5 5 5 761 465 436 280 251 204 195 172 126 119 116 98 93 86 65 63 60 58 56 46 45 44 43 43 41

Over resting cells.

over-expressed genes that were rather devoted to the metabolic needs of highly proliferating cells, such as DNA and RNA metabolisms (po10 6, KEGG and GO Biological Process), oxidative phosphorylation (po10 6, KEGG and GO Biological Process), transcription (po2 10 6, KEGG and GO Biological Process) and cell proliferation (po2 10 8, KEGG and GO Biological Process; Table 3).


PTCLs of the gd lineage are rare entities with yet poorly defined oncogenic pathways and biological abnormalities relative to their normal gd T-cell counterparts [20, 29]. Of the 16 PTCLs and 7 NKTCL transcriptomes downloaded for the present meta-analysis, one of these (GD-PTCL_2.GD) corresponded to a lymphoma that was clinically identified as gd PTCLs [20]. This enabled us to compare it by principal component

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Table 3. Representative genes up-regulated by activated cell lines from healthy donors and lymphoma patients

Gene symbol

p-Value

Fold changea)

Up-regulated by cell lines from healthy donors (cluster 7) EGFL6 EGF-like-domain protein 6 (promotes matrix assembly) GIMAP7 Immunity-associated GTPase family member 7 GIMAP8 Immunity-associated GTPase family member 8 GIMAP1 Immunity-associated GTPase family member 1 GIMAP4 Immunity-associated GTPase family member 4 KLRB1 NKRP1A (CD161) KLRC3 NKG2E KLRK1 NKG2D KLRC4 NKG2F KLRC1 NKG2A CCR2 Chemokine (C–C motif) receptor 2 CXCR6 Chemokine (C–X–C motif) receptor 6 CX3CR1 Chemokine (C–X3–C motif) receptor 1 CD300A CD300a, CMRF35H molecule (NK inhibitory receptor p60) CD69 CD69 molecule (lymphocyte activation marker) GNLY Granulysin CRTAM Cytotoxic and regulatory T-cell molecule AMIGO2 Adhesion molecule with Ig-like domain 2 PERP TP53 apoptosis effector P4HA2 Proline 4-hydroxylase, a polypeptide II GSPT2 G1-to-S phase transition 2 SIRPG Signal-regulatory protein g (CD47 molecule)

1.1 10 5 2.7 0 8 1.6 10 10 1.9 10 9 10 4 5.8 10 5 4.6 10 6 10 4 2.9 10 4 0.002 4.0 10 4 2.4 10 5 10 4 2.0 10 3 1.6 10 6 5.8 10 3 3.1 10 3 2.0 10 11 4.7 10 5 9.7 10 4 3.5 10 11 5.8 10 6

2.30 2.29 2.00 1.81 1.77 2.27 1.78 1.66 1.65 1.65 2.12 1.99 1.97 1.73 1.73 1.77 1.66 2.15 2.07 1.65 2.07 1.68

Up-regulated by cell lines from lymphoma patients (cluster 8) DMD Dystrophin (cytoskeleton anchoring to plasma membrane) LPHN2 Latrophilin 2 (exocytosis-regulating receptor) MYO3B Myosin IIIB MMP12 Matrix metallopeptidase 12 (macrophage elastase) IL-9 Interleukin 9 (IL-2/IL-4-independent T-cell growth factor) DDX4 ATP-dependent RNA helicase SOX2OT SOX2 overlapping transcript (non-coding RNA) RBPMS RNA-binding protein with multiple splicing TCF4 Transcription factor 4 CCR7 Chemokine (C–C motif) receptor 7 POU2F3 POU domain. Class 2 transcription factor 3 ENPP2 Ectonucleotide pyrophosphatase (autotaxin)

4.8 10 10 3 4.8 10 0.01 0.02 5.3 10 0.01 4.8 10 7.0 10 8.9 10 0.04 0.01

a)

Name

6

4

4

4 4 5

2.11 2.00 1.90 1.86 1.85 1.78 1.69 1.63 1.60 1.55 1.55 1.48

Fold change of log2-transformed, normalized data.

analysis (PCA) with that of the 12 resting and activated gd T cells. This method determined 38 genes over-expressed by the gd PTCLs which contributed to discriminate it from the healthy gd T cells. These genes (Table 4) were involved in the complement pathways (po10 4, KEGG and Biocarta), cytokine–cytokine receptor signalling (po2 10 7, KEGG and Biocarta), TLR signalling (po10 7, KEGG), chemokine–chemokine receptor and G-protein-coupled signallings (po10 11, from GSEA’s C5). In addition, this gene signature corresponded to the genomic region chr4q21 (po10 6, from GSEA’s C2 positional gene set collection). Accordingly, the CXCL9, CXCL10, CXCL11, CXCL13 and IgJ genes that are over-expressed by the gd PTCLs are all located on chr4q21, so their expression pattern might reflect either genomic amplifications in this gd PTCL, as


recently depicted for unspecified PTCLs and adult T-cell leukaemia/lymphomas [30] or a higher transcriptional activity of this region. These results indicate that gd T-cell lines from NKTLs and PTCLs had molecular signatures of higher metabolic and proliferative activities than in primary gd cell lines from healthy individuals, whereas the profile of gd PTCLs suggested higher chemokine and GPCR gene expression in this malignancy.

Discussion In this study, we show that the gene signature of healthy phosphoantigen-specific human gd T cells mitigates T and NK-like

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Table 4. Representative genes preferentially expressed by the gd PTCL relative to normal gd T cells from healthy donors

Gene symbol

Name

ADAMDEC1 C1QA

ADAM-like decysin 1 Complement component 1, q sub-component, A chain Complement component 1, q sub-component, B chain Complement component 1, q sub-component, C chain MIP-3b 6Ckine CD14 marker NK cell activating/inhibitory receptor (By55) Scavenger receptor CD163 Cystatin C IP-10 I-TAC BCA-1 MIG Ectonucleotide pyrophosphatase/ phosphodiesterase 2 GABA-B receptor, 1 Transmembrane glycoprotein B Ig heavy locus Ig J linker (for Ig a and Igm) C region of Ig k chain Ig l chain C region of Ig l chain CD85, ILT2, LIR1 Lumican TLR4-associated MD-2 protein Lysozyme Serpin peptidase inhibitor, clade G member 1 SPARC-like 1, hevin Transketolase-like 1

C1QB C1QC CCL19 CCL21 CD14 CD160 CD163 CST3 CXCL10 CXCL11 CXCL13 CXCL9 ENPP2 GABBR1 GPNMB IGH IGJ IGKC IGL IGLC LILRB1 LUM LY96 LYZ SERPING1 SPARCL1 TKTL1 a)

Fold change (gd PTCLs versus normal gd T cells)a) 2,7 2,4 2,4 2,5 2,4 2,0 2,4 1,8 2,2 1,8 1,8 2,4 3,2 2,2 2,3 2,2 2,5 2,3 2,2 1,8 1,8 2,0 1,3 3,0 2,3 2,2 2,2 2,5 1,9

Fold change of log2-transformed, normalized data from gd PTCLs relative to normal gd T cells.

patterns which reflect both of their cytolytic, pro-inflammatory and proliferative activities. With activated, established TCRVg91 gd T-cell lines derived from healthy donors, however, these profiles were related to – but distinctive from – those derived from lymphoma patients, which showed exacerbated metabolic and mitotic pathways as well as increased cytokine, chemokine, TLR and GPCR signalling pathway genes. Patterns of gene expression are powerful tools to improve our understanding of the biology of the human gd T lymphocytes, but few studies are currently available on this topic. The first transcriptome studies of murine intra-epithelial gd T lymphocytes


failed to differentiate these cells from their ab counterparts but concluded show an ‘activated yet resting’ profile [31, 32]. Further studies on calf blood gd T lymphocytes, exploiting the crossreactivity of bovine genes with Affymetrix human micro-arrays, depicted a gd T-cell signature hybrid of B and myeloid cells [33, 34] and proposed gd T cells as ancestral to the other lymphoid subsets [35, 36]. An Affymetrix platform-based study of human ab and gd T cells purified from PBMCs by microbeads failed to identify gd T-cell specific transcripts and concluded that ab and gd T cells have fully overlapping profiles [37]. Nevertheless, the transcriptional profiling (using custom microarrays) of established primary cell lines of TCRVg91 gd T cells stimulated with isopentenyl pyrophosphate depicted induction of Fyn-binding protein, immediate early response 3, proinflammatory chemokines, IFN-g, TNF-a, lymphotoxin a and CD25 [38]. Further, Hver 2.1.1 microarray-based study of TCRVg91 gd T cells stimulated with the microbial (E)-4-hydroxy-3-methyl-but-2-enyl-pyrophosphate (HDMAPP) phosphoantigen in the presence of IL-2, IL-4 or IL-21 identified Th1, Th2 cells or follicular dendritic cell (FDC)like polarisations of the TCRVg91 gd T cells, respectively [39]. These studies, however, failed to detect up-regulation of the genes (CD40, CD80, CD86 and HLA-DR) reportedly expressed by TCRVg91 gd T antigen-presenting cells [8]. Finally, a recent Affymetrix (HG U133 plus 2.0) microarray-based microarray study of human gd T cells from cytomegalovirus-infected newborns characterised the signature of TCRVg8/Vd11 cells [40]. These lymphocytes up-regulate the expression of NK receptors (both activating and inhibitory), cytolytic mediators and proinflammatory chemokines and cytokines. Despite their use of different platforms which generally underestimate the differences between gene expression levels, these and the present study are all consistent in showing that in gd T cells, the expression levels of mRNA transcripts correlate quite well to presence of cell surface antigens. The issue of the gd T cells’ relatedness to either B cells, T cells, NK cells or even myeloid-like antigen-presenting cells has been raised in previous studies, but the clustering analysis presented here unambiguously locates these lymphocytes at the interface of T and NK cells. The gd T and NK cell lineages do share some developmental programming, possibly driven by chronic stimulation [41]. Nevertheless, the T-cell transcription factor BCL11b was expressed at the same level in TCRVg91 gd and ab T lymphocytes, which were significantly higher than in NK cells (p 5 0.001), in line with its repressive activity for NK cell-associated genes [42]. That gd T cells expressed more T-cell genes than NK cells and more NK-cell genes than T cells had been reported [37], but this mitigated profile was actually resolved temporally upon activation. Although the molecular signature of resting and early activated TCRVg91 gd T cells were more closely like those of CD41 T cells, those of established and activated TCRVg91 cell lines were mostly like those of NK cells, confirming the functional pleiotropy of cells previously demonstrated for human cells within different conditions [39, 43]. This is also reminiscent of murine gd T cells, where TCRVg11 T lymphocytes with memory-activated phenotype strongly resemble to bona fide NK cells and are referred to as NK-like gd T cells [41, 44]. In addition,

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phosphoantigen-activated TCRVg91 gd T cells up-regulated the expression of IL-21R, a receptor which further interaction with IL-21 enables pre-committed gd T cells to irreversibly trigger their cytotoxic, Th1 and proliferative programming [45], as well as the expression of lymphoid-homing and germinal centre reactions molecules [39]. Within the TCRVg91 cell samples analysed here, no signature for differentiation of Th17 gd T cells such as RORgT, IL-17, IL-23 were observed, as with TCRVg8/Vd11 cells [40]. The phosphoantigen-activated TCRVg91 gd T cells consistently up-regulated the expression of the most of the well-depicted Th1 cytokines, and of several classes of inhibitory molecules such as CTLA4, PD-1 and NK-cell receptors as reported elsewhere [37]. In addition, the expression of BTN3A2 that encodes the inhibitory butyrophilin 3 [46] was increased by activation. Furthermore, gene expression of PTGER2 and the corresponding cell surface phenotype for the EP2 subtype of prostaglandin E2 receptor were strongly up-regulated by activated TCRVg91 gd T cells. Upon binding of PGE2, this receptor mediates a potent AMPc/PKAdependent blockade of activation [47–49]. Neither of the cellsuppressive cytokine TGF-b and its receptors or co-receptors [24] were up-regulated by activation, however. Hence, the gene signature of phosphoantigen-stimulated cells comprised Th1 cytokines but also a whole set of potent negative regulators of activation presumably acting as a normal physiological regulation. In this regard, the gene signature differentiating healthy from pathological gd T cells was informative despite the low number of relevant transcriptomes available. The genes over-expressed by such cancer cells rather reflected the metabolisms and signalling pathways associated with their high proliferation. Not only the signature of these constitutively activated cancer gd T cells did not overlap with that of healthy activated gd T cells, but they lacked the regulatory loops found in healthy antigen-activated cells. Likewise, altered patterns of NK cell receptor expression have recently been reported for non-B-cell lymphomas [17, 50, 51]. In conclusion, this study depicted a hybrid molecular signature for phosphoantigen-specific human TCRVg91 gd T cells, as a blend of the NK cell and ab T-cell signatures. Future studies using these tools will now aim at characterising the pathways induced in TCRVg91 gd T cells lacking these functional activities, such as those encountered in cancer patients.

Materials and methods


gen)] indicated this procedure did not activate the purified cells, unless additional stimuli were provided. These gd T cell samples were purified either before PBMC treatment: ‘gd TCRVg91 control’ samples (n 5 4), or 6 h after stimulation with the TCRVg91-specific agonist BrHPP [13] (500 nM): ‘gd TCRVg91 act 6 h’ samples (n 5 4), or 7 days after PAg stimulation and culture with IL-2 (100 IU/mL): ‘gd TCRVg91 act 7-day’ samples (n 5 4). Cells were cultured in vitro as described [24]. Freshly purified CD3 CD561 NK cells (490%, as checked by flow cytometry) were obtained from PBMC by positive selection from magnetic beads (Miltenyi Biotec, Auburn, CA, USA) according to manufacturer’s instructions. NK cells were then activated with 100 U/mL IL-2 in complete RPMI medium for 2 days before RNA extraction.

Reagents and flow cytometry Flow cytometry for cell surface phenotype of gd T- and NK-cell samples was done as depicted using LSR-II and analysis with the FACS Diva 6.0 (BD Biosciences) or FlowJo (Treestar) softwares [24].

Microarray procedures Total RNA from the specified human gd TCRVg91 or NK cell samples was isolated using TRIzolTM Reagent (Invitrogen Life Technologies, Paisley, UK). The quality of RNA was assessed with Agilent 2100 Bioanalyser (Agilent Technologies, Palo Alto, CA, USA) after denaturation at 701C for 2 min. Microarray analyses were performed using 1–3 mg total RNA as the starting material from human cells, amplified and labelled following the one-Cycle Target Labeling protocol (Affymetrix, Santa Clara, CA, USA). The labelled complementary RNA (cRNA) from these samples was then fragmented and hybridised to Affymetrix GeneChip arrays HG-U133 plus 2.0. The chips were then washed, scanned and analysed with GeneChip Operating Software (Version 1.1, Affymetrix) at the Microarray Core Facility of the Institute of Research on Biotherapy, CHRU-INSERM-UM1 Montpellier (http://irb.chu-montpellier.fr/). Microarray data and procedures were deposited at NCBI GEO data set under accession number GSE27291.

Cells and samples

Gene expression analysis

Whole PBMCs were isolated from four healthy donors (Etablissement Franc- ais du Sang, Toulouse, France) after Ficoll–Hypaque density centrifugation. TCRVg91 cells were purified (498%) from PBMC by cell sorting using clone IMMU510 (BeckmanCoulter-Immunotech, Marseille, France). Control flow cytometry for intracellular phospho-ZAP70 (Y319) and P-ERK1/2 [using, respectively, Ax647-conjugated anti-phospho-ZAP70 and PEconjugated phospho-(T202/Y204) ERK1/2 Abs (BD Pharmin-

The raw data (Affymetrix CEL files) were produced using HG U133-Plus 2.0 platform for the above-depicted 12 samples of highly purified TCRVg91 gd cells (498% purity) and 9 samples of highly purified, IL-2-activated NK cells (CD3 CD561 cells 498%). For comparison purposes, additional raw data files obtained on the same platform were downloaded from the NCBI repository GEO database and Array Express database. These comprised 26 normal B-cell samples: 18 from GSE12195 [52] and


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8 from GSE15271 [53], 6 samples of normal ab T CD41 and CD81 T cells from GSE15659 [54], GSE8059 [55] and GSE13906 [17], 4 samples of normal NK cells with and without IL-2 from GSE8059 [55], 2 samples of normal TCRVg91 gd T-cell lines expanded by 2 weeks of in vitro culture with zoledronate plus IL-2 from GSE13906 [17], 6 samples of malignant gd T cells from GSE13906 [17] which comprised 2 nasal lymphoma and 4 EBV1 gd T-cell lines from EBV-infected patients, 16 PTCLs [21], 7 NKTCLs and 2 NKTCL cell lines [20], both downloaded from Array Express (http://www.ebi.ac.uk/arrayexpress) under accession number E-TABM-791. The raw data from these 90 samples were normalised in batch by the RMA software and the 54 676 probe sets were then reduced to a total of 20 606 genes (HUGO symbols) by using the GSEA collapse function set on maximal probe mode (GSEA, http://www.broadinstitute.org/gsea).

Data mining After log (base 2) transformation, normalisation and collapse, hierarchical clustering of the 90 transcriptomes was based on the 20 606 genes, the Euclidean distance between two transcriptomes and agglomeration by the Ward’s criterion [56]. Implementations were done using the ‘dist’ and ‘hclust’ functions in R (http:// www.R-project.org). The differential transcriptomes from freshly isolated human B, T and NK cells shown in Fig. 2 were represented using dChip (http://www.dchip.org). To identify genes over-expressed by the PTCL_2.GD [20] relative to 12 samples of freshly isolated and purified normal gd T cells, PCA was done with the ‘prcomp’ and ‘biplot’ functions in R. The subspace determined by PCA captures the highest amount of the total data set’s variability which biplot summarises the relationships between genes and samples [57]. Genes differentially expressed between two groups of samples were defined using ANOVA or one-way Student’s t-tests whenever appropriate by using the SigmaStat 12.0 software (Systat Software, Chicago, IL, USA). Text files were generated from the gene lists with one gene name per line; these text files were then uploaded in Autocompare. More than 5000 genes reference lists based on GSEA (http://www.broadinstitute.org/gsea/) pathways and 162 protein lists based on PANTHER pathways (http:// www.pantherdb.org/pathway/) were collected. The differentially expressed gene subsets were analysed for enrichment in functionally related genes among lists downloaded from the gene sets collection. Selective enrichment analysis was computed with the Autocompare freeware that we developed from nwCompare [58] based on one-sided hypergeometric, Bonferroni and Holm tests. Autocompare was developed using the Perl programming language (Perl v5.10.1, http://www.perl.org/) and the R statistical programming language under the Linux operating system (ubuntu 10.04, http://www.ubuntu.com/). Autocompare is available for Linux and Windows (http:// www.ifr150.toulouse.inserm.fn/en/article.asp?id=264) and runs on any operating system with Perl, either as a command line tool or with a graphical interface. As input, it takes any proteomic/


Eur. J. Immunol. 2012. 42: 228–240

genomic data files and performs strings comparisons by line, with any string including protein names, accession numbers or gene chip probesets.

RT-qPCR Specific genes from ab T cells, NK cells or TCRVg1 gd T cells were selected for verification with RT-qPCR. Preference was given to specific functions of each cell type, i.e. cytotoxicity, cytokine/ receptor and proliferation. Briefly, 500 ng of total RNA was reverse transcribed using SuperScriptTM III Reverse Transcriptase (Invitrogen, Carlsbad, CA, USA). Gene-specific primers (Supporting Information S1) were used for qPCR on the LightCyclers 480 Real-Time PCR System (Roche Applied Science, Mannheim, Germany). The quantification of each gene expression was performed using LightCyclers 480 SYBR Green I Master with 4 mL of RT product (1:5 dilution) and primers (3 mM). A cycle threshold (Ct) was assigned at the beginning of the logarithmic phase of PCR amplification, and the difference in the Ct values of the control and experimental samples were used to determine the relative expression of the gene in each sample. GAPDH was used for normalisation as its expression did not significantly change along the different real-time PCR experiments. Statistical analysis was performed with a 5 0.05 in Student’s and Mann–Whitney’s tests whenever appropriate by using SigmaPlot 12.0 software.

Acknowledgements: This work was supported in part by institutional grants from the Institut National de la Sante´ et de la Recherche Me´dicale (INSERM), Universite´ de Toulouse, Centre National de la Recherche Scientifique and by contracts RITUXOP (PAIR LYMPHOME), V9V2TER and TUMOSTRESS from Institut National du Cancer. We thank Ve´ronique Pantesco (Microarray Core Facility of the Institute of Research on Biotherapy, CHRUINSERM-UM1 Montpellier) for the Microarray Core Facility, Philippe Gaulard, Marion Travert, Laurence de Leval and Aure´lien de Reynies for genesets from NK/T-cell lymphoma transcriptomes. We are grateful to Innate Pharma for clinical grade batches of BrHPP and Sanofi (Toulouse, France) for recombinant hIL-2. Conflict of interest: The authors declare no financial or commercial conflict of interest.

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Abbreviations: BrHPP: bromohydrin pyrophosphate NKTCL: NKT cell lymphoma PCA: principal component analysis PTCL: peripheral T-cell lymphoma

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Full correspondence: Dr. Jean-Jacques Fournie´, INSERM UMR1037, Cancer Research Center of Toulouse, 31024 Toulouse, France Fax: 133-56-2745858 e-mail: [email protected] Current address: Dr. Delphine Cendron, Department of Microbiology & Immunology, Vanderbilt University Medical Center, Nashville, TN 37232, USA

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Received: 18/6/2011 Revised: 12/8/2011 Accepted: 26/9/2011 Accepted article online: 4/10/2011

39: 752–762.


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