|Home | About | Journals | Submit | Contact Us | Français|
Cancer-associated thrombocytosis has long been linked to poor clinical outcome, but the underlying mechanism is enigmatic. We hypothesized that platelets promote malignancy and resistance to therapy by dampening host immunity. We herein show that genetic targeting of platelets significantly enhances adoptive T cell therapy of cancer. An unbiased biochemical and structural biology approach established transforming growth factor β (TGFβ) and lactate as the major platelet-derived soluble factors to obliterate CD4+ and CD8+ T cell functions. Moreover, we found that platelets are the dominant source of functional TGFβ systemically as well as in the tumor microenvironment through constitutive expression of TGFβ-docking receptor Glycoprotein A Repetitions Predominant (GARP) rather than secretion of TGFβ per se. Indeed, platelet-specific deletion of GARP-encoding gene Lrrc32 blunted TGFβ activity at the tumor site and potentiated protective immunity against both melanoma and colon cancer. Finally, we found that T cell therapy of cancer can be substantially improved by concurrent treatment with readily available anti-platelet agents. We conclude that platelets constrain T cell immunity though a GARP-TGFβ axis and suggest a combination of immunotherapy and platelet inhibitors as a therapeutic strategy against cancer.
Platelets or thrombocytes play essential roles in hemostasis (1). Increasingly, they have emerged to possess other regulatory functions in physiology such as angiogenesis, wound healing and immunomodulation (2–4). Intriguingly, cancer-associated thrombocytosis is an independent poor prognostic factor in multiple cancer types (5, 6), via enhancing invasiveness of cancer cells (7), promoting cancer motility (4, 8) and inducing epithelial-mesenchymal cell transition (9). Despite knowledge of platelet cross-talk with natural killer (NK) cells (10), neutrophils (11), macrophages (12), dendritic cells (13–15) and T lymphocytes (14), the direct impact of thrombocytes on T cell immunity against cancer and the underlying molecular mechanisms have yet to be fully elucidated.
Platelets are bioactive, anuclear cellular fragments that are shed out of megakaryocytes in the bone marrow vasculature (16). They are the smallest cellular component of the hematopoietic system and are second only to red blood cells in number. Platelets express a number of cell surface receptors for adhesion and aggregation (1, 17), such as glycoprotein (GP) Ib-IX-V complex which serves as a receptor for von Willebrand factor, and GPIIb-IIIa integrin that binds to fibrinogen and fibronectin. They also express other activation receptors, including the thromboxane A2 receptor, ADP receptors P2Y1 and P2Y12, and the protease activated receptors (PAR1 and PAR4), the latter of which can be activated by thrombin (18). Platelets have been found to constitutively expresses a non-signaling TGFβ-docking receptor Glycoprotein A Repetitions Predominant (GARP) (19), encoded by leucine-rich repeat containing protein 32 gene (Lrrc32). The role of GARP is to increase the activation of latent TGFβ and thus its biological function in the close proximity of GARP-expressing cells. The other cells that express GARP are regulatory T (Treg) cells which do so only after activation via T cell receptor (20). Both GP Ib-IX-V complex and GARP depend on a molecular chaperone gp96 for folding and cell surface expression (21, 22). Genetic deletion of Hsp90b1 (encoding gp96) from platelets results in significant thrombocytopenia and impaired platelet function (21). Finally, there are cytoplasmic granules in platelets containing a variety of molecules such as TGFβ, ADP, serotonin and proteases, which are released upon platelet activation and degranulation to exert their functions (23, 24).
The key unresolved questions are how platelets impact the adaptive immunity in cancer and what are the underlying molecular mechanisms for such an action. With regards to TGFβ, it is completely unknown what the physiological function of platelet-specific cell surface GARP-TGFβ is in host immunity. In addition, GARP-TGFβ complex on platelets could be formed intracellularly during the de novo biogenesis, or extracellularly where GARP snatches latent TGFβ (LTGFβ) in the extracellular matrix from non-platelet sources and binds to it. However, it is unclear which source of the GARP-TGFβ complex is critical in regulating the host immunity against cancer in vivo. In this study, we systematically probed the effect of platelets on the effector function of anti-tumor T cells. We also, for the first time, took an unbiased approach to identify platelet-derived soluble immunoregulatory factors in blunting T cell function. This study not only uncovered mechanisms of platelet-mediated T cell suppression, but also demonstrated the validity of the combination therapy of cancer with immunotherapeutics and anti-platelet agents in clinically relevant mouse models.
Using bone marrow chimeric mice, we previously demonstrated that genetic deletion of Hsp90b1 from the hematopoietic system resulted in macrothrombocytopenia coupled with dysfunctional platelets due to the loss of cell surface GPIb-IX-V, the receptor for von Willebrand factor (21). To probe the immunological function of platelets, a megakaryocyte-specific Hsp90b1 knockout (KO) mouse model was generated in this study. As expected, KO mice had significantly lower platelet counts in the blood compared with wild type (WT) mice (Fig. 1A). The dysfunction of platelets was evidenced by prolonged bleeding time (Fig. 1B). Extensive phenotypical analysis showed no obvious abnormalities in other cellular lineages including T and B cells in the hematopoietic system of KO mice (Fig. S1A–1D). The ability of CD8+ and CD4+ cells from the KO mice to produce IFNγ in response to polyclonal activation was also unaffected (Fig. S1E–1F).
Adoptive T cell therapy (ACT) was next used to determine if platelet dysfunction in the host impacts the ability of transferred donor T cells to control cancer. ACT is a process of transferring a large number of pre-activated, antigen-specific T cells for the treatment of established cancers (25). Melanoma was chosen because: (a) Immunotherapy of unresectable melanoma has been increasingly implemented over the past years with encouraging efficacies (26); (b) T cell receptor transgenic mice of both CD4+ (TRP1) and CD8+ (Pmel) lineages (27, 28) against melanoma antigens permit studying tumor-reactive T cells in our mouse models. B16-F1 melanomas were therefore established in C57BL/6 mice after subcutaneous injection on day 0, followed by infusion of ex vivo primed Pmel cells on day 10, along with IL-2-anti-IL-2 antibody complex (29). Transferred Pmel cells had better anti-tumor activity in the Hsp90b1 KO recipients compared with WT ones (Fig. 1C), whereas no difference in tumor growth was observed between the two groups without ACT (Fig. 1D). The improved ACT efficacy in the KO mice was associated with increased production of IFNγ (Fig. 1E) and TNFα (Fig. 1F) by the donor T cells. These results suggest that platelet function in tumor-bearing mice constraints T cell-mediated cancer immunotherapy.
We next focused on understanding the molecular mechanisms of T cell suppression by platelets. Given that platelets are not usually found in the lymphatic system and the T/B cell zone of the lymphoid organs, we reasoned that activated platelets exert their immunosuppressive function via releasing soluble factors. Purified platelets were suspended at 108 platelets/mL (several times lower than physiological platelet concentration) and activated with thrombin to generate platelet releasate (PR). The suppressive capacity was then measured in vitro using a standard polyclonal T cell activation assay (Fig. S2A). Strikingly, soluble factors in platelet releasate, but not platelet microvesicles (MV), completely blocked T cell proliferation, blastogenesis and IFNγ production (Fig. 2 and Fig. S2B–G). The activity of platelet releasate was not species-specific as both mouse (Fig. 2A) and human (Fig. 2B) platelet releasates suppressed the activation and effector function of T cells from either source. Several parameters related to PR-mediated T cell suppression were also examined (Fig. S3A–J). The negative effect of platelet releasate could not be rescued by high dose IL-2 (Fig. S3A). Kinetic studies showed that the inhibitory effect was most pronounced during the first 2 days of T cell activation and was irreversible (Fig. S3B–G). Supernatant from unstimulated platelets had minimal effects (Fig. S3H). Platelet releasate had no direct effect on the proliferation of non-lymphocytes such as fibroblasts and B16-F1 melanoma (Fig. S3I–J). In addition, platelet releasate-treated T cells displayed a naïve phenotype expressing more CD62L and less CD44, programmed death – 1 (PD-1), glucocorticoid-induced tumor-necrosis-factor-receptor-related protein (GITR) and CD25 (Fig. 2C, 2D). Moreover, the presence of platelet releasate during in vitro activation of CD4+ TRP1 transgenic Th17 cells (27) abolished their activity upon adoptive transfer against B16-F10 melanoma (Fig. 3A) and reduced their persistence in the recipient mice (Fig. 3B). Similarly, CD8+ Pmel cells also lost their anti-tumor activity in the adoptive transfer setting after exposure to platelet releasate during ex vivo activation (Fig. 3C) which correlated with poor donor cell persistence (Fig. 3D).
Next, we took an unbiased approach to identify active T cell-suppressive molecule(s) in the platelet releasate. Human PR was fractionated by size-exclusion chromatography, followed by quantifying individual fractions for their suppressive activity. Two major peaks with suppressive activity were resolved (Fig. 4A). Fraction A (>150 kDa) was further sub-fractionated by anion exchange chromatography (Fig. 4B). Comassie blue staining of a reducing SDS-PAGE of the most active sub-fractions showed prominent bands corresponding to 150–250 kDa and 10–50 kDa (Fig. 4B). Mass spectrometry identified these proteins to be mature TGFβ (mTGFβ), latency-associated peptide (LAP), latent TGFβ binding protein 1 (LTBP1) and thrombospondin-1 (TSP1), indicating the presence of a mTGFβ-LAP-LTBP1-TSP1 complex (30). Immunoblot confirmed the existence of mature (12.5 kDa) and latent (44 kDa) TGFβ, LTBP1 (180 kDa) and TSP1 (110–180 kDa) in the whole platelet releasate as well as in Fraction A (Fig. 4B). Neutralizing TGFβ with the combination of an inhibitor for activin receptor-like kinase 5 (ALK5) (also known as type I TGFβ receptor) and anti-TGFβ antibody in fraction A completely rescued T cell function (Fig. 4C). We thus have defined TGFβ as a major T cell suppressive factor in the platelet releasate.
However, blocking TGFβ in the whole mouse PR only partially rescued T cell activity in vitro (Fig. S4), indicating the presence of other TGFβ-independent factors. Furthermore, the activity of fraction B in both human and mouse platelet releasate was heat-stable, proteinase K-resistant and smaller than 1.0 kDa in size (Fig. S5). We then sub-fractionated fraction B by an anion exchange column to obtain sub-fractions B1 through B8, and employed nuclear magnetic resonance (NMR) spectroscopy to delineate the metabolite composition. (Fig. 4D, 4E). Targeted profiling using the Chenomx NMR Suite software identified lactate as the most abundant metabolite (~3.4 mM) in the most suppressive B3 and B4 sub-fractions (Fig. 4E). The immunoregulatory roles of lactate on T cells (31) and macrophages (32) have been reported. The concentration of lactate in the whole platelet releasate was ~5.7 mM. Lactate efficiently suppressed T cell activation with concentrations as low as 2.5 mM (Fig. 4F). Blocking both TGFβ (by a neutralizing antibody) and lactic acid (by inhibiting monocarboxylate transporter I with α-Cyano-4-hydroxycinnamic acid) (32) in the whole human platelet releasate almost completely rescued IFNγ production, CD25 expression and blastogenesis of CD8+ T cells (Fig. S6). We conclude, thus, that the suppressive activity of platelet releasate primarily resides in TGFβ and lactate.
To further address the suppressive components in the platelet releasate, we performed an in vitro Treg induction assay. Splenocytoes were activated with anti-CD3/28 antibody in the presence of PR, TGFβ and lactate for 3 days. Consistent with earlier findings, PR attenuated T cell blastogenesis (Fig. S7A, D) and this was partially recapitulated by each of TGFβ and LA. Importantly, a proportion of CD4+ cells cultured with PR differentiated into the Treg lineage (Fig. S7B, D), and this was accompanied by upregulation of p-Smad 2,3 (Fig. S7C, D). Expectedly, TGFβ, but not LA, also induced Treg differentiation and p-Smad 2,3.
We then investigated whether TGFβ and/or lactic acid (LA) can independently recapitulate the inhibitory effects of platelet releasate on tumor-reactive T cells. B16-F1 melanoma tumors were established in C57BL/6J mice which were subsequently treated with Pmel CD8 T cells, similar to the experiment described in Fig. 3C. T cells were primed ex vivo with hgp100 and IL-12, either in control media (Pmel-12), platelet releasate, TGFβ and/or LA (Fig. S8). T cells primed in the presence of PR or TGFβ (650 pg/mL, the concentration of TGFβ present in PR from 1×108 platelets/mL) failed to control melanoma progression and to persist in peripheral blood (Fig. S8A–C). This poor in vivo persistence is likely explained by the failure of Pmel cells to upregulate receptors of the homeostatic cytokines IL-2 and IL-7 under these conditions (Fig. S8D). Of note, IL-7 is crucial for Pmel cell persistence in vivo in the Pmel tumor model (33). In turn, LA in the priming phase had no effect on the subsequent anti-tumor activity of Pmel T cells. This suggests that platelet-derived TGFβ is likely a more relevant target in immunotherapy.
Platelets not only produce and store high levels of TGFβ intracellularly (34), but also are the only cellular entity known so far that constitutively expresses cell surface docking receptor GARP for TGFβ (19). Thus, platelets may contribute to the systemic levels of TGFβ via active secretion as well as GARP-mediated capturing from other cells or the extracellular matrix (9, 35–37). We next addressed to what extent and how platelets contribute to the physiological TGFβ pool. Baseline sera were obtained from WT mice followed by administration of a platelet depleting antibody. These mice were sequentially bled and serum TGFβ was quantified by ELISA. Depletion of platelets resulted in a complete loss of active and total TGFβ, which rebounded effectively as soon as platelet count recovered (Fig. 5A). These experiments demonstrate that platelets contribute dominantly to the circulating TGFβ level. By comparison, serum lactic acid with or without depletion showed no significant changes (Fig. S9), arguing that platelet-derived TGFβ but not lactic acid is a more relevant immunosuppressive molecule in vivo.
We next addressed the biology of platelet-derived TGFβ in cancer immunity, focusing on the role of platelet GARP in the production of active TGFβ. In addition to platelet-specific Hsp90b1 KO mice, two additional mouse models were generated: One with selective deletion of GARP in platelets (Pf4-cre-Lrrc32flox/flox, or Plt-GARPKO) and another with platelet-restricted knockout of TGFβ1 (Pf4-cre-Tgfb1flox/flox or Plt-Tgfβ1KO) (Fig. 5B). As gp96 is also an obligate chaperone for GARP (22), platelets from neither Plt-gp96KO mice nor Plt-GARPKO mice expressed cell surface GARP-TGFβ complex. Platelets from Plt-Tgfβ1KO mice, however, expressed similar levels of surface GARP-TGFβ1 complex when compared with WT platelets (Fig. 5B–5D), indicating that the GARP-TGFβ1 complex can be formed without autocrine TGFβ1.
The levels of active and latent TGFβ were then measured in the plasma and sera of WT and knockout mice (Fig. 5E, F). In WT mice, active TGFβ was elevated in serum compared to plasma, indicating a role for platelets and/or the coagulation cascade in TGFβ activation (Fig. 5E). Importantly, Plt-gp96KO and Plt-GARPKO mice had very little active TGFβ in their sera, confirming the importance of platelet-intrinsic GARP in converting latent TGFβ to the active form. In contrast, the serum level of active TGFβ in Plt-Tgfβ1KO mice was comparable to that of WT mice (Fig. 5E), indicating that platelets are capable of activating TGFβ from non-platelet sources in a trans fashion. Significantly, the total latent TGFβ level in the serum is only reduced in Plt-Tgfβ1KO mice but not Plt-gp96KO or Plt-GARPKO mice (Fig. 5F). Collectively, these data indicate that platelet-intrinsic GARP is the most important mechanism in the activation of TGFβ systemically. This experiment also categorically confirmed that serum but not plasma level of active TGFβ reflects exclusively platelet activation.
So far we have shown that TGFβ is a major T cell suppressor molecule from platelet releasate and that platelet-specific deletion of gp96 (which functionally deletes GARP) promotes adoptive T cell therapy of cancer. These fortuitous observations suggest that platelet-specific GARP plays critically negative roles in anti-tumor T cell immunity. This hypothesis was next addressed by comparing the efficacy of adoptive T cell therapy of melanoma in WT, Plt-Tgfβ1KO and Plt-GARPKO recipient mice (Fig. 6). B16-F1 melanomas were established in either WT or KO mice, followed by lymphodepletion with Cy on day 9, and the infusion of ex vivo activated Pmel T cells on day 10 (Fig. 6A). Tumors were controlled much more efficiently in the Plt-GARPKO mice compared with WT mice (Fig. 6A). This was associated with enhanced persistence (Fig. 6B) and functionality of Pmel cells in the peripheral blood of Plt-GARPKO mice (Fig. 6CD). In stark contrast, Plt-Tgfβ1KO mice, whose platelets express GARP and remain capable of activating TGFβ, did not have improved control of tumors (Fig. 6D). We next studied the generality of these findings in the MC38 colon carcinoma system given that the growth of this transplantable tumor in syngeneic mice undergoes both CD4 and CD8-mediated immune pressure (38, 39). The growth of MC38 was significantly diminished in Plt-GARPKO mice compared to WT mice (Fig. 7A–7C). The MC38-bearing Plt-GARPKO mice had reduced serum levels of active TGFβ (7D). More importantly, staining for p-Smad2/3 (p-Smad2/3) in MC38 tumor sections demonstrated a remarkable attenuation of TGFβ signaling in MC38 cells in Plt-GARPKO mice (Fig. 7E and 7F). This was associated with reduction of both systemic myeloid-derived suppressor cells (Fig. 7G) and tumor-infiltrating regulatory T cells in Plt-GARPKO mice (Fig. 7H). Taken together, this demonstrates that platelets are the commanding source of TGFβ activity in the tumor microenvironment and they exert potent immunosuppressive effects on anti-tumor immunity via GARP-TGFβ.
To establish the clinical relevance of the suppressive effect of platelets on anti-tumor immunity, we sought to inhibit platelets pharmacologically. The results so far suggest that anti-platelet pharmacological agents can be exploited for enhancing cancer immunotherapy. This intriguing possibility was addressed using Pmel adoptive therapy of B16 melanoma (40–42). B16-F1 melanomas were established in C57BL/6 mice after subcutaneous injection on day 0, followed by lymphodepletion with Cy on day 7, and infusion of ex vivo primed Pmel cells on day 8 (29), along with anti-platelet (AP) agents: aspirin and clopidogrel (43). Aspirin and clopidogrel inhibit platelet activation by blocking cycloxyenase and ADP receptors, respectively. Cy alone failed to control tumors, and the additional AP also had no anti-tumor effects in this model (Fig. 8A, left panel). Melanoma was controlled well with T cells plus Cy for about one month, but most mice eventually relapsed. In contrast, anti-platelet agents plus adoptive T cell transfer were highly effective against B16-F1 with relapse-free survival of most mice beyond 3 months (Fig. 8A, right panel). As a further proof, antigen-specific T cells were sustained at higher numbers in the blood, inguinal lymph nodes (ILNs) and spleens of mice receiving concurrent anti-platelet therapy and ACT (Fig. 8B). Importantly, antiplatelet agents conferred no benefit when the transferred T cells lacked IFNγ (Fig. 8C) or when anti-IFNγ neutralization antibodies were administered (Fig. 8D), demonstrating that the effects of anti-platelet agents were immune-mediated.
The role of platelets in promoting cancer invasion has been previously observed (44, 45). Multiple mechanisms have been attributed to this phenomenon including the promotion of angiogenesis (46) and stimulating epithelial-to-mesenchymal cell transition (9). However, the direct contribution of platelets to anti-cancer immunity has not been well described despite the emerging appreciation of the cross-talk between platelets and the host immunity. The current study uncovers that platelets directly dampen T cell function both in vitro and in vivo. Furthermore, we demonstrated that the platelet releasate suppresses both CD4+ and CD8+ T cells mostly via TGFβ and to a lesser extent through lactate. It is intriguing that both lactate and TGFβ are enriched in the tumor microenvironment, whose source so far has been attributed mostly to cancer cells and other stromal cells (32, 47). This study revealed that platelet-related TGFβ activation contributes dominantly to this immunosuppressive pool in cancer via cell surface TGFβ-docking receptor GARP, a conclusion that was supported by enhanced tumor-specific T cell immunity in mice with platelet-specific deletion of GARP or its critical molecular chaperone gp96.
Platelets are known to respond to tissue injury and infection. Upon activation, platelets self-aggregate and release a variety of soluble factors to promote tissue homeostasis (48). Multiple molecules in the platelet releasate possess immunomodulatory properties (2, 23). To our knowledge, the current study is one of the first efforts to isolate T cell-specific immunomodulators from platelet releasate in an unbiased fashion. We identified TGFβ and lactate to be the major mediators. Platelet contribution to extracellular TGFβ can be accomplished through the release of pre-stored TGFβ in the cytoplasmic granules or via the ability of surface GARP on platelets to snatch and bind TGFβ from non-platelet sources. Our study clearly demonstrates that platelet-intrinsic GARP plays the most dominant role in activating TGFβ and thus likely contributes signficantly to the immunosuppressive molecular hallmarks in the cancer microenvironment. Platelets are known to express GARP constitutively and to upregulate its expression upon activation. The current study is the first to determine the functional significance of platelet-intrinsic GARP in cancer immune tolerance. The other cells that are known to express GARP are Treg cells. Interestingly, we found that conditional deletion of GARP from Treg cells is not as effective as platelet-specific KO of GARP in supporting adoptive T cell therapy (Fig. S10). Future studies are necessary to understand the roles and mechanisms of platelets broadly and the GARP-TGFβ axis specifically in regulating the biology of endogenous T cells in the tumor microenvironment such as differentiation and functionality.
There have been inconsistent reports on the systemic TGFβ level as a reliable biomarker for cancer, inflammation and other conditions (49–51). Consistent with the literature we found that active TGFβ level is low in the plasma, however, after platelet activation and coagulation, serum active TGFβ level increased significantly. It has been unclear where active TGFβ in the serum comes from and what is the underlying mechanism of activation. The current study has resolved these long-standing puzzles. By genetically deleting GARP or TGFβ1 from platelets selectively, we have now reached several important conclusions: (1) Platelet-specific GARP is responsible for TGFβ activation because little active TGFβ can be detected in the sera of mice with platelet-specific deletion of either GARP or gp96; (2) latent TGFβ in the blood (both serum and plasma) is primarily supplied by platelets as revealed by platelet-specific TGFβ1 KO mice and platelet depletion studies; (3) the serum level of active TGFβ depends on the cell surface GARP-TGFβ complex, not the total level of soluble latent TGFβ. Such evidence derived from the fact that even though platelet-specific TGFβ1 KO mice have drastically reduced soluble latent TGFβ1 in the serum, they remain capable of making a comparable level of active TGFβ.
Consistent with the genetic studies, pharmacological platelet inhibitors were found to be effective in potentiating adoptive T cell therapy of melanoma. It is also possible that platelet inhibitors may have other anti-tumor mechanisms such as blocking angiogenesis and immunosuppressive prostaglandins (52), which contribute to their anti-tumor activity. Notwithstanding, our work demonstrated that the anti-platelet agents alone do not have significant anti-tumor activity in our model. Additionally, the improved anti-tumor effect was abolished when IFNγ was removed from the system, demonstrating that platelet inhibition promotes anti-tumor efficacy via an immunologically based mechanism. Given the clinical availability of multiple platelet inhibitors targeting distinct pathways of platelet activation, we hope that our study will catalyze a systematic effort to optimize cancer immunotherapy by simultaneously blocking platelets and immune checkpoint molecules in prospective clinical trials.
Of note, platelets have also been shown to play positive roles in the homing of T cells to sites of inflammation, to mediate a positive feedback loop of T cell recruitment through T cell activation via platelet CD40 (14), and to promote liver cancer induced by dysfunctional liver-directed T cell responses (53). The complexity of the roles of platelets in the tumor microenvironement is also illustrated by a recent finding that platelets can be extensively educated by tumor cells to uptake tumor-associated biomolecules such as RNAs (54). However, our work strongly indicates that the net effect of thrombocytosis in cancer patients is to promote immune evasion of cancer. Physiologically, cancer represents a chronic, non-healing wound, whose progression and metastasis are inevitably accompanied by vascular endothelial damage and local exposure to multiple platelet activators (1, 48). Our study thus suggests that cancer hijacks the tissue-repairing and hemostatic functions of platelets to suppress anti-tumor T cell immunity. A combinational therapy with anti-platelet agents and immunotherapeutical modalities may thus represent a new pardigm for rational treatment of cancer in the future.
Finally, while this study uncovers major suppressive molecules in the platelet releasate in an unbiased approach, such molecules were identified using in vitro experiments, and translated to in vivo models using a hypothesis driven approach. For example, TGFβ was identified as a major suppressive molecule secreted by platelets and this was validated in tumor mouse models. While TGFβ clearly showed to be of biological relevance, it remains possible that in vivo, the PR has a different composition and molecules other than TGFβ could play stronger roles. Furthermore, standard of care immunological therapies for melanoma at this point in time are mostly based on checkpoint inhibition (PD(L)-1 and CTLA-4). Various forms of adoptive T cell transfer have shown very promising results in clinical trials but are still under investigation and not yet standard of care. Our mouse models are based on adoptive T cell transfer and not checkpoint inhibition, so understanding these differences in immunological therapies is important when designing future studies.
In this study, an unbiased approach was used to identify the major T cell suppressors in the platelet releasate. This was achieved by fractionating the releasate as described below, screening for the active fractions, and subsequently identifying the active molecules. Endpoints for in vitro experiments included T cell proliferation, blastogenesis and cytokine production and activation markers. The clinical relevance of the in vitro findings was investigated in vivo. For in vivo experiments, each group contained between 4 and 10 mice; this provided enough power and validity to detect biologically relevant phenomena, while ensuring the use of minimal numbers of mice necessary as per the guidelines of the MUSC Institutional Animal Care and Use Committee. Commercially obtained mice were randomly assigned to different groups in each experiment. For in house-bred, genetically engineered mice, littermates were assigned for comparison groups. Efficacy endpoints for in vivo experiments were tumor size, T cell engraftment and cytokine secretion. Mice were sacrificed when they showed signs of severe, moribund disease. Measurement techniques for in vitro and in vivo experiments are indicated accordingly for each experiment. All experiments were performed at least two times. Numbers of key experiments were indicated in the figure legend. Blinding was not feasible for most of the in vitro experiements, and was not critical as data collection was mostly through objective measures such as flow cytometry. The surgical pathologist scoring IHC stains was blinded to the identity of the samples. For in vivo experiments, researchers were blinded as genetically modifed mice are not readily identifiable as their outer appearances are comparable and they share the same cages. In Figure 3, blinding was maintained for the CD4 Th17 adoptive transfer experiment, but not the CD8 transfer one.
Platelet-specific Hsp90b1 KO mice were generated by crossing Pf4-Cre mice (55) with Hsp90b1flox/flox mice (21, 56). Lrrc32flox/flox mice were obtained from Riken (Japan) (20). Tgfb1flox/flox, Foxp3eGFP-CreERT2, Pmel-1 and TRP-1 mice were purchased from The Jackson Laboratory. Ifng−/− Pmel-1 mice were a gift form Shikhar Mehrotra (MUSC). All animal experiments were conducted under approved protocols by the Institutional Animal Care and Use Committee at MUSC.
Inguinal lymph nodes from tumor-bearing mice were isolated, mashed in cold PBS and filtered. One million cells/well were cultured in 96-well plates for 4 hours in the presence of PMA (500 ng/mL) and Ionomycin (1.5 μg/mL), or human gp100 peptide (Lys-Val-Pro-Arg-Asn-Gln-Asp-Trp-Leu, 25–33) (5 μg/mL) for melanoma-draining lymph nodes. Brefeldin A (BD Biosciences) was added to the cells in all experiments.
Mice were anesthetized and blood was withdrawn to a 5 mL tube containing another 0.5 mL of acid citrate dextrose (ACD) buffer (39 mM citric acid, 75 mM sodium citrate, 135 mM dextrose, 1 μg/mL prostaglandin E1, pH 7.4). Samples were centrifuged for 10 min at 100 g and the upper layer of platelet-rich plasma was collected. Platelets were washed 2x with citrate washing buffer (128 mM NaCl, 11mM glucose, 7.5 mM Na2HPO4, 4.8 mM sodium citrate, 4.3 mM NaH2PO4, 2.4 mM citric acid, 0.35% BSA and 50 ng/mL prostaglandin E1, pH 6.5), then resuspended in RPMI, enumerated by a blood cell counter and diluted to a final concentration of 1×108/mL. Purified platelets were incubated with 1 IU/mL thrombin for 45 min at 37°C, 125 rpm. Stimulated platelets were sedimented by centrifugation for 15 min at 3,200 g and supernatant was collected. Microvesicles were collected by centrifugation at 25,000 g and re-suspension in PBS in the same volume as the original platelet releasate volume.
For human platelet secretome, platelets from healthy donors were obtained from the blood bank at the Medical University of South Carolina, resuspended in ACD buffer at room temperature, followed by activation as above.
Platelet releasate fractionation was carried out using a Pharmacia Akta-fast performance liquid chromatography and columns purchased from GE healthcare. The first fractionation was based on size by loading platelet releasate onto a Superdex 200 column and eluting with PBS or RPMI1640 (Gibco). The active fractions were pooled and dialyzed with phosphate buffer (20 mM, pH 7.2). The resulted material was then loaded onto a diethyl-aminoethyl (DEAE) column, and eluted with a linear gradient of NaCl from 0 to 1 M.
Human platelet releasate was prepared at concentrations of 2×109/mL and fractionated by size exclusion chromatography followed by anion exchange chromatography. Fractions were eluted with sodium phosphate buffer (pH 7.0; 20 mM final concentration) containing sodium 3-trimethylsilyl-2,2,3,3-d4-propionate (TSP; 0.1 mM final concentration) and 10% D2O. NMR data were collected at 298 K on a Bruker Avance III 600 MHz NMR spectrometer (Bruker Biospin Inc) equipped with a 5 mm cryogenically-cooled QCI-inverse probe. Solvent suppression was achieved using the excitation sculpting scheme (57). Typically, 1D-1H NMR spectra with a 7 s recycle delay were acquired with a total of 128 transients in addition to 4 dummy scans. 32,768 real data points were collected across a spectral width of 12 ppm (acquisition time: 2.27 s). Data were zero-filled to twice the original data set size, manually phased and automatically baseline corrected using Topspin 3.1 software (Bruker Biospin Inc., Billerica, MA) and a 1.0 Hz line-broadening apodization was applied prior to spectral analysis. The singlet produced by the known quantity of the TSP methyl groups was used as an internal standard for chemical shift referencing (set to 0 ppm) and for quantification.
Metabolite assignments were established following comparison of chemical shifts and spin-spin couplings with reference spectra as implemented in the Chenomx NMR Suite (Chenomx Inc., Edmonton, AB) profiling software (version 7.72). Specifically, quantification was achieved using the Chenomx 600 MHz metabolite library (version 8). Confirmatory 1D-31P and 2D-1H,13C-multiplicity edited heteronuclear single quantum correlation (HSQC) spectra with adiabatic 13C-inversion, refocusing and decoupling were recorded for selected platelet releasate fractions to enhance metabolite identification by comparison of 13C chemical shifts with the biological magnetic resonance data bank. Concentration of lactic acid was then quantified by an L-lactate assay kit (Eton Bioscience).
CD4+ and CD8+ T cells were purified using magnetic beads to a purity of ≥95%. 1×105 cells were cultured in 96-well plates pre-coated with anti-CD3ε antibody (3 μg/mL), in the presence of IL-2 (100 U/mL) and soluble anti-CD28 (2 μg/mL), together with either media or platelet releasate. On day 3 of culture, T cells were stimulated with PMA (300 ng/mL)/Ionomycin (1 μg/mL) or hgp100 peptide 25–33 (5 μg/mL) for 4 hours in the presence of GolgiPlug (BD Biosciences), followed by staining for relevant markers. TGFβ receptor signaling was blocked using the combination of an ALK5 inhibitor (SB431542, Selleckchem) at 20 μM and anti-TGFβ antibody (R&D Systems, clone MAB1835) at 2 μg/mL. Lactic acid activity was inhibited by blocking the monocarboxylate transporter using α-cyano-4-hydroxycinnamic acid (Sigma, C2020). For CFSE dilution assays, cells were labeled with 5 μM CFSE for 10 minutes at room temperature prior to culture on day 0. Flow cytometry was then performed and the data was analyzed and displayed with FlowJo software. Suppression index by platelet releasate is calculated as: percentage of undivided cells treated with a given fraction of platelet releasate/percentage of undivided cells in the control media.
Treatment of B16-F1 melanoma by adoptive transfer of ex vivo activated Pmel T cells was done as described previously (29). To test the effect of anti-platelet agents on adoptive T cell therapy, clopidogrel was administered by oral gavage 3 days after T cell transfer, and then every 48 hours until day 25. Aspirin was administered through drinking water (150 mg/L) starting 2 days before T cell transfer and was replaced every 48 hours afterwards. For TRP1 Th17 T cell therapy, single-cell suspensions of splenocytes from Rag1−/−TRP1 mice (27) were seeded with irradiated C57BL/6 splenocytes pulsed with TRP1 106–130 peptide (SGHNCGTCRPGWRGAACNQKILTVR; American Peptide). To obtain Th17 polarized cells, recombinant human IL-6 (100 ng/mL, NIH), TGFβ1 (30 ng/mL, Biolegend), IL-1β (10 ng/mL, Shenandoah), anti-IL-4 and anti-IFNγ antibodies (10 μg/mL; BioXCell) were added to the cultures. On the second day of culture, complete medium containing recombinant human IL-2 and IL-23 (40 ng/mL; PeproTech) was added. Where appropriate, human platelet releasate was added at 100% on days 0, 2 and 4. Cells were cultured for 5 days before experimentations. C57BL/6 mice were injected subcutaneously with 4×105 B16-F10 melanoma cells and treated 10 days later with TRP1–specific CD4+ T cells. Recipient mice were lymphodepleted using 5 Gy total body irradiation on the day prior to cell transfer. Tumor growth was measured using calipers and the products of the perpendicular diameters were recorded. In some experiments, IFNγ neutralizing antibody (clone XMG1.2, BioXCell) or isotype control antibody was administered via i.p. injection at 100 μg/mouse every other day starting on day 12 until sacrifice (58). The adoptive T cell transfer experiment with Ifng KO Pmel-1 cells was done identically as above except that Pmel cells were isolated from Ifng KO Pmel-1 mice (59). For some experiments, adoptive transfer was supplemented with exogenous IL-2-anti-IL-2 complexes on days 0, 2, 4, and 6 after transfer in the absence of lymphodepletion (60). Briefly, 1.5 μg of human IL-2 (National Cancer Institute Biological Resources Branch Preclinical Repository) were mixed with 7.5 μg anti–IL-2 mAb (clone 5355, R&D Systems) for 15 minutes at room temperature. Cytokine complexes were administered via I.P. injections.
WT mice were given 1 dose of rabbit anti-mouse thrombocyte polyclonal sera (1:40, Cedar Lane) at 500 μl/mouse I.P. in sterile filtered PBS. Blood was collected at 0, 24, 48, and 72 hours. Serum was harvested via coagulation and centrifugation (12,000g).
Mouse serum or plasma samples were collected by pricking the lateral tail vein. Capture ELISA for TGFβ1 was performed according to manufacturer instructions (Biolegend). Total TGFβ1 was measured following acidic activation using 1M HCl for 10 min at room temperature.
Human samples were isolated from buffy coats (Pennsylvania Plasma). CD8+ T cells were positively enriched from human peripheral blood mononuclear cells (PBMCs), followed by negative isolation of CD4+ T cells using magnetic isolation kits (Invitrogen). Cells were then stimulated with anti-CD3/anti-ICOS beads (Dynal) at 10:1 T cell: bead ratio for 4 days. IL2 (100 IU/mL, NIH) was added to the T cell cultures. Human platelet releasate was added on day 0 and every other day thereafter. Cells were assayed on day 7 for cytokine production and phenotype.
MC38 tumor cells were obtained from Yang-Xin Fu (University of Texas Southwestern Medical Center). WT or Plt-GARPKO mice were injected in the right flank with 1×106 MC38 colon cancer cells. Tumor area was measured with digital caliper kinetically. Tumor infiltrating lymphocytes were isolated from fresh primary tumors by density gradient, after single cell suspensions were made with mechanics and enzymatic digestions (DNase and collagenase).
For p-Smad-2/3 stain on fresh frozen MC38 tumors, 5 μm tumor sections were fixed with 4% paraformaldehyde followed by incubation with 3% H2O2. To minimize nonspecific staining, sections were incubated with the appropriate animal serum for 20 min at room temperature, followed by incubation with primary anti-p-Smad-2/3 antibody (EP823Y; Abcam) overnight at 4°C. Staining with secondary antibodies (Vectastain ABC Kit) was then performed before development using DAB substrate (Vector Labs SK-4100). The staining intensity of p-Smad-2/3 was graded as follows with the sample identity blinded (0: negative; 1: faint; 2: moderate; 3: strong but less intense than 4; and 4: intense).
Two-sided two sample Student’s t-tests were used for all comparisons involving continuous dependent variables and categorical independent variables using Excel software. The variances were compared between groups using an F-test. The Student’s t-test was then implemented assuming equal or unequal variances (i.e., if the F-test p value was less than 0.05, unequal variances were assumed). For tumor curves, two-way repeated measures ANOVA was used. For dose response correlations between continuous dependent and independent variables in Figures 2 and and4,4, Spearman rank-order correlation test was used to determine Rho (ρ). Kaplan-Meier curves were compared using log-rank tests. Error bars represent standard error of the mean. NS denotes statistically non-significant difference.
We received technical help from Yongliang Zhang, Feng Hong, Ephraim Ansa-Addo, Shikhar Mehrotra, Jessica Thaxton, Crystal Morales, Jake Bowers, Samantha Suriano, Colleen Cloud and Thomas Benton. We thank Drs. Yi-Te Hsu, Lauren Ball, Richard Drake and Jacek Bielawski for their initial assistance with platelet releasate fractionation.
FUNDING This work was supported by multiple NIH grants: CA186866, CA188419, AI070603 and AI077283 (to Z.L.), CA175061 and CA208514 (to C.P.), UL1 TR001450 and NIH - NCATS Grant TL1 TR001451 (to C.W.F. and B.P.R.) and Hollings Cancer Center’s Cancer Center Support Grant P30CA138313. A provisional patent application has been filed to target platelets and GARP for cancer immunotherapy.
Supplemental information includes 1 table and 11 figures.
Table S1. Source data for all the figure panels with small n (n<20).
Fig. S1. Pf4CreHsp90b1flox/flox (KO) mice show no noticeable immune dysfunction at baseline.
Fig. S2. Platelet releasate (PR) but not microvesicles (MV) directly suppress T cell proliferation and differentiation in vitro.
Fig. S3. Immune suppression by platelet releasate is independent of TCR signaling and specific to lymphocytes.
Fig. S4. T cell suppressive function of the whole platelet releasate is significantly but not completely neutralized by blocking TGFβ pathway.
Fig. S5. A small molecular weight, heat-stable, proteinase K-resistant T cell suppressive fraction is shared between human and mouse platelet releasate.
Fig. S6: TGFβ and lactic acid (LA) in the platelet releasate are the major suppressors of CD8+ T cell activation.
Fig. S7: TGFβ contained in the platelet releasate drives Foxp3 expression and upregulates p-Smad-2/3.
Fig. S8: TGFβ1, but not lactic acid, abrogates CD8-mediated tumor control.
Fig. S9: Platelet depletion has no effect on serum lactic acid concentration.
Fig. S10: Inducible deletion of GARP from Foxp3+ Treg cells does not improve adoptive T cell therapy of melanoma.
Fig. S11: Sample staining and isotype controls for flow cytometry.
AUTHOR CONTRIBUTIONSZ.L. and S.R. conceived the idea, designed the study and wrote the manuscript. S.R., A.M., B.P.R., B.X.W., M.N.N., C.W.F., C.M.P., M.P.R., M.H. and D.W.B. performed the experiments. Z.L., B.L. and Y.Y. supervised the study. E.G.-M. assisted in data analysis, statistics and interpretation. All authors provided critical comments on the manuscript.
CONFLICTS OF INTEREST
The authors declare no conflicts of interest. GARP