Introduction
Tregs play a key role in the regulation of self-tolerance and the maintenance of tissue homeostasis. Several human diseases such as autoimmune and immunodeficient conditions, chronic infections, and cancer have been associated with alterations in Treg numbers or function, and these alterations may contribute to disease progression and impact patient survival [
1‐
3]. In cancer patients, it is well established that accumulation of Tregs is associated with tumor progression, poor prognosis, and the suppression of anti-tumor immune effector functions. Treg-mediated immunosuppression is therefore considered a major obstacle for successful cancer immunotherapy [
4‐
6]. Given their potential to affect the outcome of immunotherapy trials, Tregs are being studied extensively in this context. The multitude of Treg definitions in the reported studies and the lack of functional Treg testing in immunomonitoring of clinical trials, however, make correct interpretation of data and comparisons between studies difficult, especially since knowledge of overlap between the identified Treg populations is missing and the methods to detect these cells differ per laboratory. As a result, blurred pictures emerge with respect to associations between clinical outcome and Tregs [
7]. So far, Tregs have been identified through a number of different (combinations of) markers including CD4
pos, Foxp3
pos/hi, CD25
pos/hi, CD127
neg/low, CTLA-4
pos, CD45RA
pos/neg, Helios
pos, CD39
pos, and CD73
pos/neg using several different gating strategies [
8‐
15]. The latter may form an important addition to misinterpretation of data sets since differences in gating strategies were found to be the biggest source for interassay variation in flow cytometry-based intracellular cytokine staining (ICS) assays [
16,
17]. Similarly, a lack of adequate controls to guide the settings of gates may add another level of complexity to the analysis of Tregs.
To address these issues, the CIP organized a workshop on October 29, 2013 on the detection and functional testing of Tregs. This workshop, which hosted 40 researchers from seven countries in Europe and the USA, brought together leading experts in the field to (1) understand the state of the art of Treg research and to (2) define the most appropriate assays/markers to measure, quantify, and functionally assess Tregs within patient samples. As it became apparent during the workshop that a multitude of markers and combinations thereof is currently being used by the participants, a rationally composed ranking list of “Treg markers” was generated by the participants in the follow-up of the meeting. The preparation of this Treg marker list, subsequent data interpretation of the experiments performed at the LUMC, and subsequent discussions about and approval of the final conclusions were done through a series of circulating emails. Subsequently, the proposed Treg markers were tested in order to get insight into the overlap/differences between the most frequently used Treg definitions and their utility for Treg detection in various human tissues. This led to a context-dependent [i.e., peripheral blood/tumor/lymph node (LN)] essential marker set and robust gating strategy for the analysis of Tregs by flow cytometry.
Conclusion and discussion
The unambiguous enumeration of Tregs by flow cytometry is hampered by (a) the inability to directly measure their function and (b) the absence of an exclusive, highly specific marker. Reaching consensus on an essential marker set for Treg enumeration with the currently available markers involves a number of considerations. First, the essential marker set should be able to identify a population of cells that in addition to the essential Treg-defining markers also express other Treg-associated markers but do not produce IFNγ and IL-2 [
12,
13,
26]. Secondly, as there are currently three Treg definitions used in the field [
8‐
12,
26], the cell population identified should be highly specific and include at least the same population of Tregs by all three definitions. Third, the proposed marker set should allow for robust, undisputable, and context (tissue)-independent gating since differences in gating strategies have been found to be the biggest source for interassay variation in flow cytometry-based assays [
16,
17]. Fourth, if possible, one should be able to assess their functionality.
Based on the data presented here and taking into account the above-mentioned considerations, we consider the use of the CD3, CD4, CD25, CD127, and Foxp3 markers as the minimally required markers to define human Tregs. We showed that this combination of markers allows for robust and undisputable gating of Tregs in the context of HD- and cancer patient-derived peripheral blood as well as TDLN and tumor samples (Supplementary figure 2 and Fig.
3). Although the latter also holds true for Foxp3
posHelios
pos def.2 Tregs (Supplementary figure 3 and Fig.
3), Treg measurement based solely on Foxp3 and Helios resulted in a ~25 % underestimation of the number of def.1 Tregs through exclusion of CD25
posCD127
low cells within the Foxp3
posHelios
neg population in all tested tissues/compartments (supplementary figure 4 and 9). These observations were in line with findings from others, reporting that Helios expression was restricted to a subpopulation (approximately 70 %) of human Foxp3
pos T(reg) cells [
12,
13,
26]. Treg enumeration based on Foxp3 and CD45RA (def.3) yielded distinctive aTreg and nTreg populations in HD- and cancer patient-derived peripheral blood and TDLN, with high CD25, CTLA-4, and Ki67 expression levels in the aTreg and lower expression levels of these markers in the nTreg populations (Supplementary figure 6 and figure 1 and 3). Yet, in line with findings from others [
12], the largest population of CD25
posCD127
lowFoxp3
pos (def.1; supplementary figure 6c) or Foxp3
posHelios
pos (def.2; supplementary figure 6e) populations was found in the so-called non-Treg population of Foxp3
intCD45RA
neg cells. While the population of Tregs based on definitions 1 or 2 may contain small fractions on non-Tregs, the measurement of Tregs based solely on Foxp3 and CD45RA (def.3) will lead to a ~60–70 % underestimation of Tregs. Importantly, def.3 Treg gating could not be done in a robust and undisputable fashion in tumor samples. Although not unexpected and observed before [
8], the absence of the Foxp3
intCD45RA
pos T cell population in tumor samples precluded robust def.3 aTreg and nTreg gatings in this context. Notably, the apparent absence of naïve T cells at tumor effector sites and the preferential recruitment of activated Tregs or accumulation of locally activated Tregs does confirm the validity of the defined respective activated and naïve Treg definitions within definition 3 [
8,
11]. Of note, this observation clearly emphasizes the need for validating/assessing the suitability of the flow cytometry panels in the intended context/tissue.
As shown, we used CD3
posCD4
neg (i.e., CD8
pos) and CD3
neg cells to define the limits of the positive (CD25, CD127, Helios, and CD45RA) gates as this has been described to form a more reliable gating strategy than using isotype control antibodies or FMO controls [
23]. Omission of CD3 and CD8 antibodies from the essential marker set does affect our gating strategy resulting in less reliable/more disputable CD25, CD127, Helios, and CD45RA gating, and thus affecting the reliability of our results (data not shown). Furthermore, this gating strategy results in objective CD25
pos gating rather than subjective CD25
high gating, the latter being very important for harmonized and comparative Treg analysis.
There are a number of Treg-associated markers which we consider to be of interest, yet optional to the required minimal panel. Based on our data, we highly recommend extending the minimally required antibody panel to include Ki67 and CD45RA as they provide additional information on the Treg activation status (Table
2). Indeed, the addition of CD45RA and Ki67 to the marker panel proved very informative in that no def.1, def.2, or def.3 Tregs were associated with worse survival of ovarian cancer patients but only the pretreatment frequencies of activated Foxp3
posCD45RA
neg and Ki67
pos def.1 Tregs (Fig.
4). The measurement of activated Ki67
pos Tregs has also been advocated by others [
36,
37]. In one study, renal cell cancer patients undergoing multipeptide vaccination and cyclophosphamide treatment showed a significant reduction in the number of circulation Ki67
pos Tregs and a trend toward prolonged OS following therapy [
37]. Of note, as Ki67
pos def.1 Treg detection was also feasible in TDLN and tumor samples (not shown), this strategy may also be useful to identify activated Tregs within def.1 Tregs in tumor samples, thereby circumventing the need for the subjective gating on Foxp3
hi versus Foxp3
int cells. While the activation markers CD39 and CTLA-4 [
27,
28,
38,
39] have been described as functional markers to identify activated Tregs, they do not provide additional information to a panel over CD45RA and Ki67 and the minimally required antibody set. Helios may be of interest for identifying Tregs in autoimmunity such as SLE since these patients’ conventional T cells display high levels of CD25 resulting in overlap with Tregs [
12]. In a recent trial where patients displayed a strong antigen-specific CD4
pos T cell response to vaccination, we did not observe such problems for identifying Tregs using the currently proposed markers (EM Dijkgraaf et al. submitted for publication). Based on our data, omission of CD25 as a marker is not recommended as this resulted in the identification of less pure Treg populations (Supplementary figure 10).
Table 2
Proposed marker set
1 | CD3 | Directly ex vivo | Cell surface | Essential | |
2 | CD4 | Directly ex vivo | Cell surface | Essential | |
3 | CD25 | Directly ex vivo | Cell surface | Essential | |
4 | Foxp3 | Directly ex vivo | Intranuclear | Essential | |
5 | CD127 | Directly ex vivo; low/absent | Cell surface | Essential | |
6 | Ki67 | Directly ex vivo | Intranuclear | Highly recommended | In recently activated/proliferating Tregs |
7 | CD45RA | Directly ex vivo | Cell surface | Highly recommended | Discriminates between naïve and TCR-triggered Tregs |
8 | CTLA4 | Directly ex vivo | Intracellular | Optional | On (previously) activated Tregs |
9 | Helios | Directly ex vivo | Intranuclear | Optional | Superior to CD25/CD127 in autoimmune conditions (such as SLE) |
10 | CD39 | Directly ex vivo | Cell surface | Optional | Present on suppressive Tregs |
11 | LAP/GARP | Upon activation (>24 h) on PBMC/directly ex vivo on TIL | Intracellular | Optional | On activated Tregs |
In addition, there remains a number of markers, not tested in this study, which may offer benefits to identify specific subsets of Tregs. CD147 is a cell surface marker that is accessible directly ex vivo and can also be used to identify an activated and highly suppressive Treg subset [
36,
40,
41]. Furthermore, LAP (membrane-bound active form of TGF-β) and GARP (membrane-anchoring molecule involved in latent TGF-β binding) may be particularly interesting in defining TGF-β-associated and activated Tregs in tumor samples [
39,
42‐
45]. Moreover, the chemokine receptors CCR6, CXCR3, CCR4, and CCR10 were found to be useful for the identification of phenotypical and functional distinct subsets of human Foxp3+ Tregs [
46].
In summary, consensus was reached concerning the use of an essential marker set comprising antibodies to CD3, CD4, CD25, CD127, Foxp3, Ki67, and CD45RA and a corresponding robust gating strategy for the analysis of Tregs in human samples. This set will be used in proficiency panels to harmonize the phenotypic analysis of Tregs within laboratories participating in the CIP.
Acknowledgments
We would like to acknowledge Dr. David Murdoch for his thoughtful criticisms. Saskia J.A.M. Santegoets and Sjoerd H. van der Burg were supported by a grant from the Wallace H. Coulter Foundation (Miami, Florida, USA, awarded to Sjoerd H. van der Burg, Cedrik M. Britten, and Cecile Gouttefangeas). Eveline M. Dijkgraaf and Judith R. Kroep were supported by a grant from the Bontius stichting. Cecile Gouttefangeas was supported by the Wallace Coulter Foundation and the Deutsche Forschungsgemeinschaft SFB 685/Z5. Kjetil Taskén was supported by the Norwegian Cancer Society, Research Council of Norway, and Kristian Gerhard Jebsen Foundation. Awen Gallimore was supported by the Wellcome Trust (Grant Number 086983/Z/08/Z). Andrew Godkin was supported by a grant from Cancer Research Wales. Alexander Scheffold was supported by grants from the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 633, and Sonderforschungsbereich 650. Hans J.P.M. Koenen was supported by a grant from the Nijmegen Institute for Infection, Inflammation, and Immunity (Grant Number 151692). Ethan Shevach is supported by the Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institute of Health (DIR/NIAID/NIH). Janet Staats was supported by the Duke University Center for AIDS Research (CFAR), an National Institute of Health funded program (5P30 AI064518). Marij J.P Welters was supported by a grant from the Dutch Cancer Society (Grant number 2009-4400). Theresa L. Whiteside was supported by a grant from the National Institute of Health (Grant number R01-CA168628).