Tumor Immunotherapy: The mechanism of action of anti-CTLA-4 antibodies requires FcgR-dependant TREG depletion

Ipilimumab is an anti-CTLA-4 antibody used for treatment of metastatic melanoma, one of only two cancer immunotherapeutic drugs approved to date by the FDA.  CTLA-4 is a negative regulatory molecule expressed by activated T cells as well as by negative regulatory T cells (TREGs).  CTLA-4 is related to the T cell co-stimulatory receptor CD28, and acts to suppress T cell function by competing with CD28 for binding to CD80 and CD86 on antigen presenting cells and recruiting inhibitory molecules into the TCR signaling synapse.  Thus, the mechanism of action of Ipilimumab has been presumed to involve releasing anti-tumor effector T cells from CTLA-4-inhibition and/or limiting TREG activity in the tumor and therefore resulting in an increase in the ratio of effector T cells/ TREGs within the tumor.   However, two recent articles demonstrate that Ipilimumab has an additional mechanism of action: FcgR-dependant depletion of intra-tumoral TREGs.

Fcg receptors are a multi-family class of immunoglobulin (IgG)-binding receptors that initiate either activating or inhibitory signals when engaged.  Activating receptors contain cytoplasmic immunoreceptor tyrosine-based activation motifs (ITAM) and activate the FcgR-expressing cell to mediate functions including antibody-dependant cell mediated cytotoxicity (ADCC) and phagocytosis of the antibody-labeled target cell.  FcgRIIB is the single inhibitory Fcg receptor in mice and humans and contains a cytoplasmic immunoreceptor tyrosine-based inhibitory motif (ITIM) which instead downregulates cellular responses.  There are four classes of IgG molecules in both humans and mice, and each bind to different Fcg receptors with varying affinity.  Thus differential affinities of IgG subclasses to functionally different Fcg receptors are thought to mediate the variation in clinical effectiveness of different antibodies targeting the same antigen.

Ipilimumab functions to increase the ratio of effector T cells to TREGS in the tumor microenvironment and has been shown to require binding to both types of T cells for maximal anti-tumor effectiveness.  However, how Ipilimumab differentially modulates these cell types remains to be understood.  A recent study published in The Journal of Experimental Medicine by Simpson et. al sought to clarify the mechanism by which Ipilimumab functions to alter the ratio of effector T cells/ TREGs in a murine tumor model.   Interestingly, the effects of Ipilimumab were found to be tissue-dependant.  In tumors which had high levels of infiltrating CD11b+ macrophages expressing the ADCC-activating FcgRIV, TREGS were selectively depleted in an FcgR-dependant manner, while effector T cells were instead expanded.  In lymph nodes lacking significant levels of these macrophages, frequencies of both effector T cells and TREGS were increased.  Tumor-associated TREGS expressedhigher levels of CTLA-4 than their effector T cell counterparts, or than TREGS present in the lymph node, indicating that higher CTLA-4 expression levels mediate ADCC via macrophages in the tumor.  Furthermore, the presence of FcgRs and hence TREG depletion was required for Ipilimumab’s effects.   Thus is appears that the mechanism of action of Ipilimumab on the effector T cell compartment is two-fold: directly targeting effector T cells to release inhibition via blocking CTLA4 activity, as well as by ADCC-mediated depletion of TREGS.

A second article in the same issue of The Journal of Experimental Medicine by Bulliard et al also explored the role of FcgR engagement on the effects of Ipilimumab as well as an agonistic antibody (DTA-1) targeting the T cell activating receptor GITR (TNFR glucocorticoid-induced TNFR-related protein), which is also expressed on both activated T cells and TREGs.  This study concluded that a major mechanism of action for both antibodies involved engagement of activating FcgRs leading to ADCC-mediated TREG depletion from the tumor.  Even though GITR-activation in effector T cells promotes activities including cytokine production and proliferation, the agonistic properties of this antibody alone were not effective in the absence of activating FcgR engagement.  Thus, even for functionally different (antagonistic versus agonistic) immunotherapeutic antibodies targeting these same T cell populations, FcgR-mediated ADCC of TREGs appears to be a critical mechanism for anti-tumor effects.

These studies highlight several important principles for the field of tumor immunotherapeutics.  Antibody targeting can elicit multiple effects, dependant on expression levels of the target, the isotype of the antibody, and the FcgR-expressing cell types present in the tissue.  Thus knowing the nature of the immune populations present in various types of tumors that are able to mediate ADCC, the FcgRs expressed by these cells, and the expression levels of the target molecule on immune populations that would be ideally targeted for elimination versus activation/inhibition will be critical areas for the forwarding of this field.  Furthermore, as FcgRs are polymorphous in humans, and affect IgG binding affinities, taking these genetic variations into account will be critical in the future of personalized medicine.

Further reading:

Fc-dependent depletion of tumor-infiltrating regulatory T cells co-defines the efficacy of anti-CTLA-4 therapy against melanoma.  Simpson TR, Li F, Montalvo-Ortiz W, Sepulveda MA, Bergerhoff K, Arce F, Roddie C, Henry JY, Yagita H, Wolchok JD, Peggs KS, Ravetch JV, Allison JP, Quezada SA. J Exp Med. 2013 Jul 29.

Activating Fc γ receptors contribute to the antitumor activities of immunoregulatory receptor-targeting antibodies.  Bulliard Y, Jolicoeur R, Windman M, Rue SM, Ettenberg S, Knee DA, Wilson NS, Dranoff G, Brogdon JL. J Exp Med. 2013 Jul 29.

Fcgamma receptors as regulators of immune responses.  Nimmerjahn F, Ravetch JV. Nat Rev Immunol. 2008 Jan;8(1):34-47.

PD-1 re-expression is differentially regulated by IL-12 vs IFNα in CD8 T cells

TUMOR_immunotherapyDownregulation of immune functions following responses to pathogen infections is critical for limiting damage to the host by the immune system.  T cell activity is known to be downregulated by a variety of negative regulatory mechanisms including negative checkpoint regulatory proteins, a family of CD28-related molecules.  PD-1 is one such molecule that is transiently expressed on activated T cells.   The ligands for PD-1 are PD-L1 and PD-L2, members of the B7 family of molecules which are upregulated on antigen presenting cells and tumor cells.  Interaction of PD-1 with its ligand leads to inhibition of TCR-mediated signaling via recruitment of SHP1 and SHP2 phosphatases to the TCR synapse.  In the August 2013 edition of The Journal of Immunology, Gerner et al., demonstrate that CD8 T cells initially activated in the presence of IL-12 and IFNα differentially re-express PD-1 upon antigen restimulation.

Cytokines play roles in regulation of nearly every aspect of immune responses.  The cytokine milieu present during T cell activation directs differentiation into the different functional classes of CD4 T helper or CD8 T cells.  This study sought to determine the differences in anti-tumor CD8 T cell effector functions mediated when T cells are activated in the presence of various cytokines.  IL-12 and IFNα activate both overlapping and distinct gene programs and promote cytotoxic CD8 T cell responses.  Thus, these cytokines were chosen for comparison in this study.

In this system, CD8+ OT-1 cells were activated ex-vivo in the presence of either IL-12 or IFNα, and transferred into B16-OVA tumor-bearing mice.  T cells activated in the presence of IL-12 were found to mediate tumor-growth inhibition significantly better than if they had been activated in the presence of IFNα.  Over time in tumor-bearing mice, transferred IFNα-matured OT-1 cells were observed to decline in number and lost the ability to produce IFNγ ex vivo upon restimulation, indicating these cells may be exhausted.

Because PD-1 is known to be a marker and mediator of T cell exhaustion, PD-1 expression was examined.  Initial induction levels of PD-1 were comparable on OT-1 cells following ex vivo activation with IFNα or IL-12.  Following transfer into tumor-bearing mice, PD-1 levels declined over time on both types of cells isolated from the spleen and on IL-12 matured cells isolated from the tumor.  However, PD-1 expression was high on transferred IFNα-matured cells when isolated from the tumor.  Similar results were seen when cells were transferred into mice that subsequently received an injection of the OVA peptide.  Thus, CD8+ T cells matured in the presence of IFNα appear to re-express significantly higher levels of PD-1 upon antigen restimulation than IL-12 matured T cells.

PD-1 and PD-L1 targeting with inhibitory antibodies have emerged as promising avenues in tumor immunotherapy.  In this study, anti-PD-1 antibody administration had no additional anti-tumor effect in mice that received IL-12-matured T cells, while in mice that received IFNα-matured T cells, anti-PD-1 antibodies led to inhibition of tumor-growth to a level similar to that in mice that had received IL-12-matured T cells.  Thus, the relatively poor ability of IFNα-matured T cells to efficiently inhibit tumor growth appears to be largely due to PD-1 upregulation.  Finally, when T cells were matured with both IL-12 and IFNα, the effect of IL-12 was dominant.

Many questions remain regarding the mechanisms mediating PD-1 re-expression in IFNα vs. IL-12 matured T cells.  However, since IL-12 activity was dominant over IFNα on regulating PD-1 expression, IL-12 administration during immunotherapy regimens may enhance anti-tumor T cell responses by blocking the mechanisms by which IFNα enhances PD-1 re-expression.

Further Reading:

Cutting Edge: IL-12 and Type I IFN Differentially Program CD8 T Cells for Programmed Death 1 Re-expression Levels and Tumor Control.  Gerner MY, Heltemes-Harris LM, Fife BT, Mescher MF. J Immunol. 2013 Aug 1;191(3):1011-5. doi: 10.4049/jimmunol.1300652. Epub 2013 Jun 26.

Upcoming Immunology Conferences: October – December, 2013

I previously posted on Immunology Conferences: July – September, 2013 and 2013 Conferences in Tumor Immunology and Cancer ImmunotherapyThis post lists upcoming Immunology-related conferences from October – December, 2013.

conferencesOctober
Aegean Conference: 6th International Conference on Autoimmunity: Mechanisms & Novel Treatments

October 2 – 7, 2013.

Corfu, Greece

Early registration deadline: July 25, 2013.

Abstract submission deadline: July 25, 2013.

Travel award application deadline: June 30, 2013.

 

IL-1-mediated inflammation and diabetes: From basic science to clinical applications

October 10 – 11, 2013.

Nijmegen, The Netherlands

Abstract submission deadline: August 1, 2013.

 

European Macrophage & Dendritic Cell Society Meeting: Myeloid Cells: Microenvironment, Microorganisms & Metabolism From Basic Science to Clinical Applications

October 10 – 12, 2013.

Erlangen, Germany

 

13th International Workshop on Langerhans Cells

October 10-13, 2013

Royal Tropical Institute, Amsterdam, The Netherlands

Early Registration deadline: August 1, 2013.

Abstract submission deadline: August 19, 2013.

 

The International Symposium on Immunotherapy

October 11-12, 2013

London, UK

Early Registration deadline: August 9, 2013.

Abstract submission deadline: August 9, 2013.

 

46th Annual Meeting of the Society for Leukocyte Biology

October 20-22, 2013

Newport Marriott, Newport, RI, USA

Late Breaking Abstract submission deadline: August 6, 2013.

Online Registration deadline: October 7, 2013.

 

16th Annual New York State Immunology Conference

October 20-23, 2013

Sagamore Resort and Conference Center, Bolton Landing, NY, USA

Abstract submission deadline: July 31, 2013.

Registration deadline: September 6, 2013.

 

Cold Spring Harbor Asia Conference: Tumour Immunology and Immunotherapy

October 28 – November 1, 2013.

Suzhou, China

Abstract submission deadline: August 16, 2013.

Early Registration deadline: August 16, 2013.

 

Keystone Symposium: Advancing Vaccines in the Genomics Era

October 31 – November 4, 2013.

Rio de Janeiro, Brazil

Abstract Deadline: July 30, 2013.

Early Registration Deadline: August 29, 2013.

 

November

The Lancet and Cell: What Will it Take to Achieve an AIDS-free World?

November 3–5, 2013.

San Francisco, California, USA.

Abstract submission deadline: July 26, 2013.

Early Registration Deadline: September 13, 2013.

 

International Primary Immunodeficiencies Congress

November 7–8, 2013.

Lisbon, Portugal

Early Registration deadline: July 19, 2013.

 

Asia Pacific Congress of Allergy, Asthma and Clinical Immunology

November 14–17, 2013.

Taipei City, Taiwan

Abstract Submission Deadline: July 31, 2013.

Early Registration: August 30, 2013.

Registration Deadline: October 25, 2013.

 

Cold Spring Harbor Asia Conference: Bacterial Infection and Host Defence

November 18–22, 2013.

Suzhou, China

Abstract submission deadline: September 6, 2013.

Early Registration Deadline: September 6, 2013.

 

6th Autoimmunity Congress Asia

November 20–22, 2013.

Hong Kong

Abstract Submission Deadline: July 20, 2013.

Early Registration deadline: August 6, 2013.

 

Harnessing Immunity to Prevent and Treat Disease

November 20–23, 2013.

Cold Spring Harbor Laboratory, New York, USA

Abstract submission deadline: September 6, 2013.

 

11th Annual UC Irvine Immunology Fair
November 21–22, 2013.

Irvine, California, USA

Abstract submission deadline: October 19, 2013.

Poster contest deadline: November 2, 2013.

 

December

EMBO Workshop: Complex Systems in Immunology

December 2–4, 2013.

Biopolis, Singapore

Abstract submission deadline: September 1, 2013.

Registration deadline: September 1, 2013.

 

British Society for Immunology Congress

December 2–5, 2013.

Liverpool, UK

Abstract submission deadline: September 6, 2013.

Early Registration deadline: September 30, 2013.

 

Annual Scientific Meeting of the Australasian Society for Immunology

December 2–5, 2013.

Wellington, New Zealand

Abstract submission deadline: September 1, 2013.

Early Registration deadline: September 1, 2013.

 

UK Primary Immunodeficiency Network Forum

December 6–7, 2013.

Liverpool, UK

Abstract submission deadline: September 6, 2013.

Early Registration deadline: September 30, 2013.

 

2013 American Society for Cell Biology Annual Meeting

December 14-18, 2013

New Orleans, LA, USA

Abstract submission deadline (Minisymposium Talk, ePoster Talk, and/or Poster Presentation): July 30, 2013.

Abstract submission deadline (Poster Presentation Only): September 4, 2013.

Early Registration deadline: October 10, 2013.

 

Websites that list upcoming Conferences & Events in Immunology, Tumor Immunology, and Cancer Immunotherapy:

The American Association of Immunologists (AAI) Meetings and Events Calendar

Nature Reviews Immunology’s list of conferences

Cancer Immunity Journal’s List of Conferences

FASEB Scientific Research Conferences Calendar

Using Mass Spectrometry for Mass T cell Epitope Discovery

Time of Flight Mass Cytometry (CyTOF) is a relatively new multiparametric technology that is far outpacing standard fluorescence-based flow cytometry in the number of parameters that can be simultaneously assessed on a single cell.  In CyTOF, rare transition element isotope-conjugated antibodies are used to label cellular antigens of interest, the magnitude of which is then quantitated by a time of flight mass cytometer, as discussed previously. Previous studies assessing 34 cell surface and intracellular proteins by this technology demonstrated the existence of high dimensional complexity in the heterogeneity of human bone marrow and CD8+ T cell populations.  In a July 2013 article in Nature Biotechonology, Newell et al., move CyTOF and the field of immunology another technological step forward by utilizing CyTOF to measure the frequencies of Rotavirus antigen-specific T cells in human peripheral blood mononuclear cells (PBMCs) and jejunal tissue with peptide-MHC tetramers.

In CyTOF, the theoretical maximum number of simultaneously assessable parameters is 100-200 depending on the instrument.  This vastly outnumbers the assessable parameters of standard fluorescence-based flow cytometry.  To date however, only approximately 40 metal ions have been utilized for antibody labeling, and the development of further metal-chelating technologies is awaited in order to utilize the maximum capacity of the CyTOF instrument.  In the current study, the authors circumvent this limitation by using a “bar-coding” methodology in which a variant combination of three out of ten metal ions are used for labeling each tetramer, allowing for up to 120 different metal combinations.

In this study, the authors sought to identify Rotavirus epitopes recognized by human CD8+ T cells in the context of the MHC class I allele, HLA-A*0201.  To date, only two Rotavirus epitopes recognized by T cells have been identified, and little is known about the phenotypic and functional diversity of antigen-specific T cells for any particular pathogen.  The technical difficulties in proper epitope prediction along with the limited number of cells attainable from human blood samples contribute to these issues.  Thus, this method represents a huge leap forward in the potential to identify significantly more antigen-specific T cell epitopes and to extensively classify these cells functionally.  Using an MHC-prediction algorithm, 77 possible Rotavirus peptides were identified that bound to HLA-A*0201.  An additional 32 positive and negative control tetramers were added for a total of 109 labeled tetramers used to stain each sample simultaneously.  This was further combined with 23-27 metal-chelated antibodies specific for cell surface and intracellular antigens to phenotypically characterize the T cells. A specialized Matlab script was used to analyze the high-dimensional data obtained following mass spectrometry of PBMC and jejunal samples.

On average, CD8 T cell populations specific for two Rotavirus-peptides plus 6-7 peptides from other viruses including influenza, EBV, and CMV, were identified on average across PBMCs from the 17 healthy donors analyzed.  These antigen-specific T cell populations were further phenotypically characterized by expression of surface and intracellular markers.   CD8 T cells specific for six Rotavirus epitopes that included the two previously identified epitopes, were recurrently detected in PBMCs from at least two individuals.  Of these, CD8 cells specific for a Rotavirus peptide from the VP3 protein were most common among healthy donor PBMCs and were phenotypically unique, being of the effector memory subtype compared with a central memory phenotype typical of the T cells specific for the other Rotavirus peptides.  VP3-specific T cells were also uniquely present in jejunal tissue obtained from obese patients that had undergone gastric bypass surgeries.  Thus, this methodology discovered at least 4 new Rotavirus peptides as well as unique characteristics of the different antigen-specific CD8 T cell populations.

In summary, this methodology of combining CyTOF technology with tetramer “bar-coding” paves the way for a vast expansion over fluorescent-based flow cytometry techniques for identifying antigen-specific T cell populations.  As vaccine strategies are an ongoing goal for treatment and prevention of infectious diseases and cancer, it is important to not only identify the peptides that can elicit T cell responses, but also functionally characterize these T cells in order to maximally promote desired immune responses.

Further  Reading:

Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization.  Newell EW, Sigal N, Nair N, Kidd BA, Greenberg HB, Davis MM. Nat Biotechnol. 2013 Jul;31(7):623-9. doi: 10.1038/nbt.2593. Epub 2013 Jun 9.

Cracking the code of human T-cell immunity.  Harvey CJ, Wucherpfennig KW. Nat Biotechnol. 2013 Jul 9;31(7):609-10. doi: 10.1038/nbt.2626.

Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity. 2012 Jan 27;36(1):142-52. doi: 10.1016/j.immuni.2012.01.002.

Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum.  Bendall SC, Simonds EF, Qiu P, Amir el-AD, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe’er D, Tanner SD, Nolan GP. Science. 2011 May 6;332(6030):687-96. doi: 10.1126/science.1198704.

Whole Blood Phospho-flow: Direct Ex Vivo Measurement of Signaling in PBMC

I previously discussed phospho-flow cytometry, a method to study intracellular protein phosphorylation events in peripheral blood mononuclear cells (PBMC) at the single cell level.  In standard phospho-flow cytometry protocols, prior to performing assays, PBMCs are first isolated from blood using density gradient centrifugation methods such as Ficoll.  However, there may be times when it is advantageous to study signaling pathways in relatively unmanipulated cells directly ex vivo.  For this, Chow et al. have established a protocol for performing phospho-flow cytometry on PBMCs directly in whole blood.

phospho_flow_cytometry

There are many advantages to isolating and cryopreserving PBMCs with the intention of later studying signaling events by methods including standard phospho-flow cytometry.  In particular, when comparisons are desired between patient groups and healthy controls, there is likely to be less confounding contributions of experimental variability to the results if all of the comparative samples are assayed together.  However, as discussed by Chow et al., pharmacodynamic monitoring as well as evaluation of constitutively activated signaling pathways in PBMCs would be best studied on cells having undergone the least manipulation.  Some signaling pathway responses may be more robust in whole blood PBMCs as well.  For example, I have found in my own assays that signaling responses to IL-6 are strongest in whole blood PBMCs compared with PBMCs following Ficoll or culture in the incubator for any amount of time.  This method can also be used to study bone marrow immune cell signaling as well as expression of intracellular molecules that are exposed by the permeabilization method chosen. In addition, looking at signaling events in murine PBMCs is difficult to do if PBMCs need to be isolated first, given the very small amount of blood that can be obtained from a mouse.  In these cases, anti-coagulated whole blood phospho-flow cytometry should be considered.

Whole blood phospho-flow cytometry is a relatively easy method.  Using 100 ul of whole blood is enough for this assay, and the stimulus (cytokine or other activating signaling molecule) is added directly to the whole blood for the preferred amount of time.  PBMCs are then fixed with formaldehyde and a Triton X-100 based buffer is added to lyse the red blood cells and permeabilize the white blood cells.  This is followed with a few washes and finally the cells can be treated with methanol to unmask phospho-epitopes, similarly to the standard phospho-flow cytometry method by Nolan and colleagues.  Chow et al. include an optional step in which the PBMCs can be stored in a freezing buffer prior to methanol treatment.  However, I have successfully stored PBMCs in 90-100% methanol at -20 or -80 ºC until staining for flow cytometry, similarly to what is done for the standard phospho-flow cytometry method by Nolan and colleagues.

As with all protocols involving treatment of cells with reagents such as methanol or Triton X-100, some epitopes may be lost and thus will not be evaluable if staining is done following these treatments.  Thus, there is an alternate method included in the protocol to stain for some antigens up front.  As a reminder however, some fluorophores are sensitive to methanol, for instance V500, and thus cannot be used to stain PBMCs prior to such treatments.  Finally, in a prior article, Chow et al. (2005), tested different methods of fixation, permeabilization and alcohol unmasking, and I have included the link to that article below as an excellent reference in the case that modulation of the protocol is required for optimal assessment of your antigens of interest.

Further Reading:

Whole blood processing for measurement of signaling proteins by flow cytometry.  Chow S, Hedley D, Shankey TV. Curr Protoc Cytom. 2008 Oct;Chapter 9:Unit 9.27.

Whole blood fixation and permeabilization protocol with red blood cell lysis for flow cytometry of intracellular phosphorylated epitopes in leukocyte subpopulations.  Chow S, Hedley D, Grom P, Magari R, Jacobberger JW, Shankey TV. Cytometry A. 2005 Sep;67(1):4-17.

Single-cell phospho-protein analysis by flow cytometry. Schulz KR, Danna EA, Krutzik PO, Nolan GP.Curr Protoc Immunol. 2012 Feb;Chapter 8:Unit 8.17.1-20.

 

 

GEM T cells: A newly identified class of restricted α-chain TCRα/β T cells

The diversity of the T cell repertoire allows for recognition of a wide diversity of pathogens. During T cell development, T cell receptors (TCRs) undergo genetic rearrangements of their V, D, and J segments, as well as random deletions and nontemplated additions of nucleotides.  Furthermore, major histocompatibility complex (MHC) class I and II molecules are highly polymorphic.  Thus, each person has a unique and highly diverse T cell-MHC repertoire.  In addition, there are two known classes of lymphocytes with restricted diversity of their TCR α-chains, and which bind to the non/rarely polymorphic antigen-presenting molecule families CD1 and MR1.  These are the invariant natural killer T cells (iNKT cells), and the mucosa-associated invariant T cells (MAIT cells), respectively.  In the June issue of Nature Immunology, Van Rhijn et al. identify a new class of T cells with restricted TCR α-chains, termed GEM T cells, that recognize the Mycobacterium tuberculosis (Mtb) lipid glucose monomycolate presented on CD1b.

To study the human TCR repertoire recognizing CD1b, Van Rhijn et al., utilized CD1b tetramers loaded with glucose monomycolate (GMM), to isolate and clone T cells from peripheral blood mononuclear cells (PBMC) of Mtb infected donors.  Two groups of T cell clones with differing avidity for CD1b-GMM were isolated from each patient, differentiated by intermediate (CD1bint) and high (CD1bhi) CD1b tetramer staining intensities.  CD1bint T cells were diverse in their TCR α-chain sequences.  TCR α-chains of CD1bhi T cells however, all utilized the same variable and joining sequences (TRAV1-2, and TRAJ9, respectively) with few nontemplated additions, resulting in a specific complementarity-determining region 3 (CDR3) consensus sequence.  Thus, these were termed “germline-encoded, mycolyl lipid–reactive” (GEM) T cells.  These TCR α-chain sequences furthermore had to be paired with specific TCR β-chain sequences in order to recognize CD1b-GMM complexes.

Other properties of these uniquely identified GEM T cells included expression of CD4 and production of IFNγ and TNFα upon activation, two cytokines important for anti-mycobacterial responses.  GEM T cells expressed various rates of CD161, a marker widely expressed by NKT cells and MAITs, and thus GEM T cells could not be defined by expression of CD161.  In addition, sorting of TRAV1-2+ CD4+ cells from two healthy donors followed by deep sequencing of the TCR α-chain revealed identification of the GEM-specific CDR3 sequence, demonstrating that GEM T cells were present in Mtb uninfected individuals in the naïve T cell repertoire.  However, these cells become clonally expanded in Mtb infected patients, and thus likely to contribute to anti-mycobacterial immune responses.

In conclusion, GEM T cells are a newly identified third class of CD1-recognizing T cells with restricted TCR α-chain sequences.  These cells arise via VDJ recombination, and indicate that special selection mechanisms exist to generate T cells bearing this specific TCR α-chain.  Although what CD1b-self antigen complex could positively select for these cells in the thymus is unknown.  Furthermore, the role these cells play during mycobacterial infections will be an interesting avenue for future studies.

Further Reading:

A conserved human T cell population targets mycobacterial antigens presented by CD1b.  Van Rhijn I, Kasmar A, de Jong A, Gras S, Bhati M, Doorenspleet ME, de Vries N, Godfrey DI, Altman JD, de Jager W, Rossjohn J, Moody DB. Nat Immunol. 2013 Jun 2;14(7):706-13.

A ‘GEM’ of a cell.  Mitchell Kronenberg & Dirk M Zajonc. Nature Immunology 14, 694–695 (2013) doi:10.1038/ni.2644. Published online 18 June 2013.

Tumor Immunotherapies Combine Big for Synergy in Phase I Trials

There are currently two immune cell targeting cancer_immunotherapyimmunotherapeutic agents that have received FDA approval for treatment of various malignancies.  The first approved in 2010 was the autologous dendritic cell vaccine Provenge (Sipuleucel-T) by Dendreon Corporation, for hormone refractory metastatic prostate cancer.  A second immunotherapeutic gaining FDA approval in 2011 for late stage melanoma, was an antibody called Ipilimumab, which inhibits CTLA-4, a major negative regulator of T cell activation.  Antagonists to PD-1 such as Nivolumab and/or PD-L1, another receptor/ligand pair of T cell negative regulators, are expected to join this crowd by 2015.  However, early results from combinatorial immunotherapeutics trials have demonstrated that significant synergy may be achieved by combining several immunotherapeutic modalities. A report in the June edition of The New England Journal of Medicine by Wolchok et al., demonstrates impressive synergistic results with combination therapy of Ipilimumab and Nivolumab in achieving deep and durable tumor regression in patients with advanced metastatic melanoma.

CTLA-4 and PD-1 are negative regulatory immune checkpoint inhibitors expressed on activated T cells and share homology with the TCR co-stimulatory receptor CD28.  CTLA-4 strongly competes with CD28 for binding to CD80 (B7-1) and CD86 (B7-2) on antigen presenting cells thereby limiting CD28-activation signals, and furthermore recruits inhibitory molecules into the TCR signaling synapse.  PD-1 interacts with ligands homologous with the B7 family, PD-L1 (B7H1) and PD-L2 (B7-DC), which are upregulated on tumor and stromal cells and activated antigen presenting cells.  PD-1 interaction with its ligands leads to recruitment of SHP1 and SHP2 phosphatases to the immune synapse, resulting in inhibition of TCR-mediated signaling.  PD-1 and CTLA-4 are considered non-redundant in their functions, and thus blocking both of these has been proposed to have a synergistic effect on T cell function in cancer, which was previously demonstrated in murine tumor models.

In previous clinical trials, Bristol-Myers Squibb’s Ipilimumab (MDX-010, Yervoy, IgG1) with or without a gp100 peptide vaccine extended overall survival of previously treated metastatic melanoma patients by almost 4 months versus gp100 peptide alone.  In a second study, Ipilimumab plus darcarbazine versus darcarbazine alone was tested in previously untreated metastatic melanoma patients.  The addition of Ipilimumab to the darcarbazine regimen extended overall survival by approximately two months, and lent to significantly higher survival rates at 1, 2, and 3 years later.  Bristol-Myers Squibb’s PD-1 blocking antibody (BMS-936558, IgG4) showed significant clinical efficiency in metastatic or advanced non–small-cell lung cancer, melanoma, and renal-cell cancer.

In this dose-escalation phase I trial reported on by Wolchok et al., 53 patients with advanced melanoma were concurrently treated with Ipilimumab and Nivolumab, and 33 patients received sequenced treatment.  Although the primary goal of a phase I trial is to evaluate safety, the clinical responses of the concurrently treated patients were exciting enough to garner much attention.  In the concurrent regimen, 40% of patients had an objective response (modified WHO criteria), and 16 patients had a reduction in their tumor burden by 80% or more at 12 weeks, 5 being complete responses. Not only were responses faster and more pronounced than the previous clinical trials evaluating these inhibitors alone, but in the responding patients, the reduction in tumor burden was quite durable over the course of the study.  Thus, results from phase III clinical trials comparing the combination to the inhibitors alone will be eagerly awaited.  As an interesting note, tumor expression of PD-L1 has been proposed to be an indication of efficacy for Nivolumab.  However, even in patients with PD-L1-negative tumors, responses to this combination regimen were observed.

Despite the strong promise of these inhibitors in combination, adverse events were notably higher than the inhibitors had exhibited alone in previous trials.  Although no treatment-related deaths were reported, 72% of patients exhibited grade 3 or 4 adverse events, 53% of patients exhibited treatment-related grade 3 or 4 adverse events, and 21% of patients discontinued therapy due to treatment-related adverse events.  Adverse events were however manageable with either immunosuppressant or hormone-replacement therapies.

Many different cancer immunotherapeutics are now being tested in clinical trials, including a number of therapies combining immunotherapeutic modalities in the hopes to achieve synergy.  The results from the current trial indicate that anti-tumor T cells are not only present in tumor-bearing patients, but when uninhibited, can lend significantly to tumor-killing.  This is truly an exciting time for cancer immunology.

Further Reading:

Nivolumab plus Ipilimumab in Advanced Melanoma.  Wolchok JD, Kluger H, Callahan MK, Postow MA, Rizvi NA, Lesokhin AM, Segal NH, Ariyan CE, Gordon RA, Reed K, Burke MM, Caldwell A, Kronenberg SA, Agunwamba BU, Zhang X, Lowy I, Inzunza HD, Feely W, Horak CE, Hong Q, Korman AJ, Wigginton JM, Gupta A, Sznol M. N Engl J Med. 2013 Jun 2.

Safety, Activity, and Immune Correlates of Anti–PD-1 Antibody in Cancer. Topalian, S.L. et al. N. Engl. J. Med. 366, 2443–2454 (2012).

Improved Survival with Ipilimumab in Patients with Metastatic Melanoma.  Hodi, F.S. et al. N. Engl. J. Med. 363, 711–723 (2010).

Ipilimumab plus dacarbazine for previously untreated metastatic melanoma.  Robert C, Thomas L, Bondarenko I, O’Day S, M D JW, Garbe C, Lebbe C, Baurain JF, Testori A, Grob JJ, Davidson N, Richards J, Maio M, Hauschild A, Miller WH Jr, Gascon P, Lotem M, Harmankaya K, Ibrahim R, Francis S, Chen TT, Humphrey R, Hoos A, Wolchok JD. N Engl J Med. 2011 Jun 30;364(26):2517-26.

Ipilimumab: an anti-CTLA-4 antibody for metastatic melanoma.  Lipson EJ, Drake CG. Clin Cancer Res. 2011 Nov 15;17(22):6958-62.

Computers meet T cells: in silico identification of mutated tumor antigens targeted by T cells

It is well accepted that T cells can recognize and kill tumors that arise in individuals but that tumor cells escape immune surveillance due to the immunosuppressive tumor microenvironment that renders these T cells dysfunctional is less understood.  Only a relatively small number of antigens that T cells recognize for tumor-killing have been identified, and the methods used to identify these antigens are quite cumbersome.  In a recent article in Nature Medicine, Robbins et al. utilize informatics methods to identify mutated tumor antigens in melanoma patients that allowed effective targeting by anti-tumor T cells.

Genome sequencing T cells

In an effort to identify clinically relevant mutated tumor cell epitopes recognized by T cells, Robbins et al. first performed whole-exome sequencing of tumor cells and matched normal cells from melanoma patients who demonstrated tumor regression following adoptive transfer of autologous tumor infiltrating lymphocytes (TILs).  Mutations in tumor cells that resulted in amino acid changes were identified and then screened using an MHC binding algorithm that predicts high affinity binding of peptide sequences to specific HLA alleles.  Candidate peptides of 9-10 amino acids in length were synthesized and pulsed with specific HLA-expressing target cell lines to load the peptides into the MHC complex.  Peptide-pulsed target cells or autologous tumor cell lines were then cultured with autologous TILs from the same donor and IFN-gamma production was assessed as a read out of T cell activation.

Three metastatic melanoma patients were assessed using this methodology.  The first patient was homozygous for HLA-A*0201, and thus mutated melanoma cell line peptides predicted to bind to the HLA-A*0201 allele were identified by the MHC-binding algorithm.  From this donor, 4 out of 55 candidate peptides elicited IFN-gamma responses from autologous T cells cultured with peptide-pulsed target cells.  Two of these mutated peptides were found to correspond to the casein kinase1α1 protein (CSNK1A1), one peptide was mapped to the growth arrest specific 7 gene (GAS7) gene, and the fourth was a fragment of the HAUS augmin-like complex, subunit 3 (HAUS3) protein.  The wild-type versions of each of these peptides bound very poorly (100-10,000 fold less) or not at all to the HLA and were not recognized by T cells.  Two other donors were assessed for predicted binding of mutated peptides to HLA-A*0101 and HLA-A*1101.  Autologous T cell responses were found to be activated in response to mutated peptides from pleckstrin homology domain containing, family M member 2 (PLEKHM2), protein phosphatase 1 regulatory subunit 3B (PPP1R3B), matrilin 2 (MATN2), and cyclin-dependent kinase 12 (CDK12) genes, but not their wild-type counterparts.  Furthermore, tumor lines were validated to express these mutated proteins.

Finally, the authors compared the reactivity of peripheral blood mononuclear cells (PBMCs) drawn before and after adoptive TIL transfer into two of these patients to determine if anti-tumor reactive T cell clones persisted in vivo.  T cells that recognized the same tumor antigens as the TILs were identified post-adoptive transfer at greater levels than prior to adoptive transfer.  Thus, T cells that recognize mutated tumor epitopes may play a clinically relevant role in mediating tumor regression.  Many questions remain, including a direct demonstration that such tumor-reactive TILs are responsible for mediating the observed tumor regression in these patients, and whether further mutation of these residues might facilitate immune escape later it the course of disease. 

Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells.  Robbins PF, Lu YC, El-Gamil M, Li YF, Gross C, Gartner J, Lin JC, Teer JK, Cliften P, Tycksen E, Samuels Y, Rosenberg SA. Nat Med. 2013 May 5. doi: 10.1038/nm.3161.

NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence.  Nielsen M, Lundegaard C, Blicher T, Lamberth K, Harndahl M, Justesen S, Røder G, Peters B, Sette A, Lund O, Buus S. PLoS One. 2007 Aug 29;2(8):e796.

A bifunctional FoxP3+ regulatory T cell subset converts to pro-inflammatory helper T cells

Recently a number of studies have arisen characterizing Tregulatory cellvarious functional subsets of CD4+ FoxP3+ regulatory T cells (TREGS), as well as their plasticity and ability to differentiate into other TH subtypes.  For instance, TREGS that express RORγt were found to be the specific TREG subset that promotes pro-tumor immune functions in colorectal cancer patients.  In a recent article in Immunity, Sharma et al. identify another TREG subset: FoxP3+ TREGS that loose expression of Eos convert to a pro-inflammatory helper subtype that promotes naïve CD8+ T cells differentiation into potent effectors.

Eos is a transcription factor in the Ikaros family, and acts as an obligate co-repressor in complex with FoxP3 to inhibit expression of FoxP3-repressed genes.  In a quest to understand why TREGS in inflammatory environments were observed to become pro-inflammatory without losing FoxP3 expression, Sharma et al. examined the expression of Eos in FoxP3+ TREGS under inflammatory conditions.

Conversion of FoxP3+ TREGS into an inflammatory phenotype was demonstrated by acquired expression of IL-2, IL-17, and CD40L in the draining lymph nodes of a vaccination site compared with FoxP3+ TREGS at distant lymph nodes that did not gain this function.  In these converted inflammatory FoxP3+ TREGS, expression of Eos was rapidly lost.  IL-6 was required for downregulation of Eos, as TREGS in mice lacking IL-6 did not lose Eos expression under the same conditions.  However, IL-6 alone was insufficient for Eos downregulation, which also required interactions with MHC class II on activated dendritic cells.  Loss of Eos expression was furthermore shown to be required for acquisition of the pro-inflammatory phenotype, as TREGS with forced overexpression of Eos did not undergo this conversion.

Interestingly, not all FoxP3+ TREGS were equivalent in their propensity to lose Eos expression and become pro-inflammatory.  Thymic FoxP3+ TREGS were assessed for stability of Eos under treatment with cyclohexamide. CD38+CD69+CD103 TREGS were “Eos-labile” and specifically lost Eos expression within one hour of cyclohexamide treatment, while CD38CD69CD103+ TREGS maintained Eos expression.  Expression of other markers associated with FoxP3+ TREGS including CD25 and CTLA-4 were equivalent between these two phenotypes highlighting the inability of using these TREG markers to discriminate between these populations.  When these FoxP3+ TREGS were sorted into CD38+CD103and CD38CD103+ subsets and transferred into mice, followed by the vaccination schema, only CD38+CD103 TREGS lost Eos expression and gained CD40L and IL-2 expression. The Eos-labile TREGS do however have characteristic suppressive functions when examined in several models including protection from colitis in a Rag-deficient CD45RBHI effector cell-driven autoimmune colitis model and in vitro suppression of T cell proliferation driven by anti-CD3.

Because the Eos-labile subset was observed in the thymus as part of the natural TREG repertoire, the authors examined the signals required for development of this subset.  Again, IL-6 was required as this subset did not arise in IL-6-/- mice.  Epigenetic analysis of DNA methylation patterns comparing these FoxP3+ TREGS subsets revealed distinctive patterns of methylation yet these subsets were still much more closely related to each other as compared with FoxP3 CD4+ T cells.  Future studies will be needed to determine the nature of these epigenetic differences and which signals are controlled by IL-6.

Interestingly, the authors explored the functional contribution of the Eos-labile pro-inflammatory TREGS subset on CD8+ priming in the vaccination model.  Depletion of TREGS resulted in loss of CD8+ T cell proliferation and granzyme B expression as well as loss of CD86 upregulation on DCs, while adding back just the Eos-labile subset or IL-2 plus CD40-agonist antibodies rescued these defects.  The Eos-labile subset did not however, contribute to reactivation of memory CD4+ T cells, and thus these cells appear to play a specific role in the initial priming stages of naïve T cell activation.  Thus, despite having regulatory activity, these cells are critical in priming CD8+ T cell responses by supplying IL-2 and CD40L signals.

However, indoleamine 2,3-dioxygenase (IDO) was able to block Eos downregulation and acquisition of IL-2, IL-17, and CD40L expression.  Importantly, in a murine tumor vaccination model, blocking IDO was important for FoxP3+ inflammatory TREG induction and acquisition of anti-tumor effector CD8+ T cell responses.  The mechanism of IDO inhibition of Eos downregulation was found to be at least in part, dependent on the antagonization of the IL-6-STAT3 pathway by IDO-mediated production of kynurenine-pathway metabolites which activate the aryl hydrocarbon receptor (AhR).  Interestingly, different AhR ligands have been previously shown to differentially regulate induction of TH17 cells vs. TREGS (Quintana et al.), and kyenurine was a TREG inducing AhR ligand (Mezrich et al.).  Additionally, the contrasting effects of IL-6 and IDO will be an important factor in priming immune cell responses.

Overall, this thorough investigation identified the mechanisms that induce and inhibit this newly defined Eos-labile TREG subset that maintains FoxP3 expression and has typical suppressive TREG activity, yet is critically important in priming effector T cell immune responses.  Future studies will be needed to address how these cells balance regulatory and priming activities as well as the relationships between this subset and the many other TREG subsets described.


An inherently bifunctional subset of foxp3(+) T helper cells is controlled by the transcription factor eos.   Sharma MD, Huang L, Choi JH, Lee EJ, Wilson JM, Lemos H, Pan F, Blazar BR, Pardoll DM, Mellor AL, Shi H, Munn DH. Immunity. 2013 May 23;38(5):998-1012. doi: 10.1016/j.immuni.2013.01.013. Epub 2013 May 16.

Eos, goddess of treg cell reprogramming.  Rieder SA, Shevach EM. Immunity. 2013 May 23;38(5):849-50. doi: 10.1016/j.immuni.2013.05.001.

Control of T(reg) and T(H)17 cell differentiation by the aryl hydrocarbon receptor.  Quintana FJ, Basso AS, Iglesias AH, Korn T, Farez MF, Bettelli E, Caccamo M, Oukka M, Weiner HL. Nature. 2008 May 1;453(7191):65-71. doi: 10.1038/nature06880. Epub 2008 Mar 23.

An interaction between kynurenine and the aryl hydrocarbon receptor can generate regulatory T cells.  Mezrich JD, Fechner JH, Zhang X, Johnson BP, Burlingham WJ, Bradfield CA. J Immunol. 2010 Sep 15;185(6):3190-8. doi: 10.4049/jimmunol.0903670. Epub 2010 Aug 18.

Considerations for measuring cytokine levels in serum or plasma

Changes in circulating cytokine and chemokine levels have been associated with many human diseases, and thus understanding the relationships between these changes and disease is an important area of medical research.  Circulating levels of these proteins or other chemistries are measured from plasma or serum collected from peripheral blood draws.  It is important to note that the methods of sampling and storage of plasma or serum are critical for accurate measurements.  Here are some important considerations when planning to measure the levels of cytokines and chemokines in serum or plasma.

Blood collection tubes are available in a choice of factors and should blood tubesbe selected based on the analysis being done, as different anti-coagulants support different chemistries.  Plasma is collected from blood drawn into tubes containing anticoagulants, including sodium or lithium heparin which act to inhibit thrombin from blood clotting, or sodium citrate or EDTA which chelate calcium ions to prevent coagulation.  Serum collection tubes contain clot activators, however this method does not allow collection of peripheral blood mononuclear cells (PBMCs) from the same vial, which means that oftentimes, plasma will be the product of choice to maximize the value of blood drawn in a minimal number of tubes from study participants and healthy donors.

luminex service 2Following collection, plasma or serum should be cryopreserved at -80º C.  Cytokines and chemokine levels can be measured by Enzyme-linked immunosorbent assay (ELISA).  However, this method is time consuming and allows measurement of only one factor at a time.  Luminex, a bead-based multiplex assay, can measure up to 100 cytokines, chemokines, or other soluble proteins at a time. Thus, for a given disease cohort, multitudes of measurements can be made from a single small sample of serum or plasma.  Notably, many cytokines and chemokines exist in very low levels in peripheral blood, thus for each cytokine or chemokine to be measured it is important to determine if the detection range of the assay used is sufficient for the known range of circulating levels of that protein.  Also, levels of these proteins may differ depending on whether they were measured in serum or plasma collected in various anticoagulants, so determinations should be done using the most similar methodologies as comparisons.

A methodology paper by de Jager et. al, discusses several important considerations for analyzing cytokine levels from serum or plasma by Luminex.  In this paper, due to unmeasurably low levels of many cytokines, to allow for more dynamic determinations, whole blood was spiked with recombinant cytokines, or treated with LPS for a time period to upregulate expression of cytokines, prior to plasma collection, cryopreservation, and Luminex assays.

One comparison made was the difference in profiles of 15 cytokines in serum, versus plasma from the same donors collected in sodium heparin, EDTA, or citrate.  Overall, cytokine levels were similar with a few exceptions, including IL-6 having the lowest values in serum compared with plasma, while CXCL8 was significantly higher in serum.  The authors concluded that plasma collected in sodium heparin allowed the best measurements overall for the cytokines assessed.  The time it takes to process and store samples after blood collection may also influence cytokine levels and should be done as consistently as possible for the most robust comparisons.

Another hugely important factor is sample storage time.  As with all assays, experimental variation should be minimized, and thus it is common to store plasma or serum samples until the entire cohort has been collected and then analyze all of the samples simultaneously.  This also comes into play when changes in cytokine profiles over time are to be measured from serial samples from an individual. The authors measured cytokine levels from sodium heparin plasma stored at -80º C over time, for up to four years.  Several cytokines including IL-13, IL-15, IL-17 and CXCL8 began to be degraded within one year of storage, while levels of IL-1α, IL-1β, IL-5, IL-6, and IL-10 were degraded by over 50% in 2-3 yearsIL-2, IL-4, IL-12 and IL-18 were much more stable, maintaining their initial levels out to 3 years post initial storage.  Thus, depending on the cytokines being analyzed it is critical to keep these issues in mind.  These are the same issues that are faced with storage of recombinant proteins that are used to generate the ELISA or Luminex standard curves or in other cytokine assays.

Stability of cytokines following several rounds of freeze-thawing were also assessed.  Almost all of the cytokines analyzed with the exception of IL-6 and IL-10 were affected by freeze thawing the samples.  Thus, when storing plasma or serum samples, it is important to freeze the samples in multiple aliquots such that additional assays can be performed while avoiding this issue.

In conclusion, handling and storage of serum and plasma samples as well as the choice of serum versus plasma collected in different anti-coagulants are all important factors to consider when planning for studies that will include measurement of circulating cytokines and chemokines.

Further Reading:

Prerequisites for cytokine measurements in clinical trials with multiplex immunoassays.  de Jager W, Bourcier K, Rijkers GT, Prakken BJ, Seyfert-Margolis V. BMC Immunol. 2009 Sep 28;10:52. doi: 10.1186/1471-2172-10-52.