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Graduate Theses and Dissertations Graduate School
January 2018 Novel Role of Histone Deacetylase 11 (HDAC11) in Regulating Normal and Malignant Hematopoiesis Jie Chen University of South Florida, [email protected]
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Scholar Commons Citation Chen, Jie, "Novel Role of Histone Deacetylase 11 (HDAC11) in Regulating Normal and Malignant Hematopoiesis" (2018). Graduate Theses and Dissertations. https://scholarcommons.usf.edu/etd/7608
This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Novel Role of Histone Deacetylase 11 (HDAC11) in Regulating Normal and
Malignant Hematopoiesis
by
Jie Chen
A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Cell Biology, Microbiology and Molecular Biology College of Arts and Sciences University of South Florida
Major Professor: Eduardo M. Sotomayor, M.D. Co-Major Professor: Javier Pinilla Ibarz, M.D., Ph.D. Sheng Wei, M.D. Kenneth Wright, Ph.D.
Date of Approval: Dec 21, 2017
Keywords: Neutrophils, Myeloid-derived suppressor cells, CD8+ T cells, C/EBPbeta,
Copyright © 2017, Jie Chen
Table of Contents
List of Figures ...... v
Abstract ...... vii
Chapter 1: Background ...... 1 1.1 Cancer ...... 1 1.1.1 Cancer and host immune cyctem...... 2 1.1.2 Hematopoiesis and abnormal myelopoiesis ...... 4 1.1.3 Current approaches for cancer immunotherapy ...... 6 1.2 Tumor microenvironment ...... 7 1.2.1 Tumor infiltrated T lymphocytes ...... 8 1.2.2 Tumor-derived suppressor cells ...... 9 1.2.2.1 The origin of MDSCs ...... 10 1.2.2.2 MDSCs expansion ...... 11 1.2.2.3 Subsets of MDSCs ...... 11 1.2.2.4 Mechanisms regulating MDSCs biology ...... 12 1.2.2.5 Clinical evaluation of MDSCs ...... 15 1.2.2.6 Targeting MDSCs in Cancer ...... 16 1.2.3 Tumor associated macrophages ...... 17 1.2.4 Other cellular and non-cellular components in the tumor microenvironment ...... 18 1.2.5 Strategies of targeting the tumor microenvironment ...... 19 1.3 Histone deacetylases ...... 22
i 1.3.1 Classification of HDACs ...... 22 1.3.2 HDAC11 ...... 23 1.3.2.1 HDAC11 in APCs ...... 25 1.3.2.2 HDAC11 in T lymphocytes ...... 26 1.3.2.3 HDAC11 in cancer ...... 27 1.3.2.4 Other functions of HDAC11 ...... 27 1.3.3 Other HDACs ...... 28 1.3.4 HDAC inhibitors ...... 29
Chapter 2: Essential Role for Histone Deacetylase 11 (HDAC11) in Neutrophil Biology ...... 33 2.1 List of abbreviation ...... 33 2.2 Abstract ...... 35 2.3 Introduction ...... 36 2.4 Material and methods ...... 39 2.4.1 Mice and cell lines ...... 39 2.4.2 Quantitative reverse transcriptase-polymerase chain reaction (qRT- PCR) ...... 39 2.4.3 Flow cytometry ...... 40 2.4.4 Immunoblotting ...... 41 2.4.5 Harvesting and in vitro culturing of mouse peritoneal neutrophils ... 41 2.4.6 Migration assay analysis ...... 42 2.4.7 Chromatin immunoprecipitation ...... 42 2.4.8 Phagocytosis assay ...... 43 2.4.9 Incucyte real-time microscopy analysis ...... 44 2.4.10 Cytometric bead array ...... 44 2.4.11 Sepsis model ...... 45 2.4.12 RACE analysis ...... 45
ii 2.4.13 Statistical Analysis ...... 45 2.5 Results...... 45 2.5.1 HDAC11 is differentially expressed in various stages of myeloid differentiation...... 45 2.5.2 Expression of HDAC11 is significantly increased in leukemic cells upon differentiation ...... 48 2.5.3 Lack of HDAC11 markedly increases the expression of pro- inflammatory cytokines ...... 49 2.5.4 Neutrophils isolated from mice lacking HDAC11 demonstrate much higher migratory and phagocytic capacity ...... 53 2.5.5 HDAC11KO mice are more susceptible to LPS induced sepsis when compared to C57BL/6 wild-type counterpart ...... 56 2.5.6 HDAC11KO mice show bone marrow hypercellularity with granulocytic expansion and splenomegaly due to increased extramedullay hematopoiesis ...... 58 2.6 Discussion ...... 61
Chapter 3: HDAC11 Function as a Transcriptional Regulator in Immature Myeloid Cells (IMCs) to Myeloid-derived Suppressor Cells (MDSCs) transition ...... 67 3.1 List of abbreviation ...... 67 3.2 Abstract ...... 68 3.3 Introduction ...... 69 3.4 Material and methods ...... 72 3.4.1 Mice and cell line ...... 72 3.4.2 Genotyping ...... 73 3.4.3 In Vivo tumor model ...... 74 3.4.4 Splenic and tumor infiltrated MDSCs isolation ...... 74 3.4.5 BM-derived MDSCs generation ...... 75 3.4.6 Arginase activity assay ...... 75 3.4.7 NO production assay ...... 76 3.4.8 ROS production ...... 76
iii 3.4.9 Quantitative real-time pCR (qRT-PCR) ...... 77 3.4.10 Flow cytometry analysis and cell sorting ...... 77 3.4.11 Western blotting analysis ...... 78 3.4.12 Adoptive Cell Therapy ...... 78 3.4.13 Chromatin immunoprecipitation (ChIP) ...... 79 3.4.14 Statistics ...... 80 3.5 Results...... 80 3.5.1 C/EBPβ is necessary for bone marrow-derived and tumor-induce MDSCs ...... 80 3.5.2 Elevated level of C/EBPβ contributes to the up-regulation of enzymes involved with MDSC suppression in HDAC11KO mice .. 83 3.5.3 HDAC11 deletion promotes MDSCs suppressive activity through increased arginase activity and NO production ...... 85 3.5.4 HDAC11 negatively regulates C/EBPβ expression by interacting with the promoter region of this transcription factor ...... 89 3.5.5 Mice with HDAC11 deletion in myeloid compartment displayed enhanced tumor progression compared to total knockout mice .... 90 3.5.6 HDAC11 plays a contradictory role in regulating MDSCs and T cells in the tumor microenvironment ...... 92 3.6 Discussion ...... 94
Chapter 4: Conclusion and Future Directions ...... 99
List of references ...... 104
Appendices ...... 114
iv
List of Figures
Figure 2.1 HDAC11 message is differentially expressed in various stages of myelopoiesis ...... 47
Figure 2.2 Expression of HDAC11 in acute promyelocytic leukemia samples (APL) and functional consequences of its manipulation in this model ...... 49
Figure 2.3 ...... 51
Figure 2.4 Phenotypic consequences of HDAC11 deficient peritoneal neutrophils ..... 53
Figure 2.5 Enhanced migratory and phagocytic capacity of HDAC11KO neutrophils . 55
Figure 2.6 Septic shock experiment comparing HDAC11KO mice and C56BL/6 mice 58
Figure 2.7 Observation of splenomegaly as well as Hypercellularity with granulocytic expansion in BM of HDAC11KO mice ...... 60
Figure 2.8 ...... 65
Figure 3.1 C/EBPβ expression is up-regulated in MDSCs with HDAC11 deletion ...... 82
Figure 3.2 C/EBPβ is involved with the suppressive activity of MDSCs lacking HDAC11 ...... 84
v Figure 3.3 Enzymes involved in the suppressive pathways employed by BM-derived MDSCs with HDAC11 deletion ...... 86
Figure 3.4 Enzymes involved in the suppressive pathways employed by HDAC11KO MDSCs in vivo ...... 88
Figure 3.5 HDAC 11 regulates C/EBPβ expression in MDSCs ...... 90
Figure 3.6 Mice lacking HDAC11 in the myeloid compartment demonstrate a more enhanced tumor growth pattern than HDAC11 total knockout ...... 91
Figure 3.7 The antitumor efficacy by adoptive transfer of HDAC11KO T cells can be diminished by MDSCs lacking HDAC11 ...... 93
vi
Abstract
During hematopoiesis, multilineage progenitor cells and the precursors are
committed to individual hematopoietic lineages. In normal myelopoiesis, the immature
myeloid cells (IMCs) differentiate into macrophages, neutrophils or dendritic cells.
However, under tumor burden, these IMCs differentiate into myeloid derived suppressor
cells (MDSCs) result in an up-regulation of immune suppressive factors and pro-tumor
effect. The development of normal or malignant is tightly controlled by endogenous
signals such as transcription factors and epigenetic regulations. HDAC11 is the newest
identified members of the histone deacetylase (HDAC) family. Previous study in our
group had identified HDAC11 as a negative regulator of interleukin 10 (IL-10) production
in antigen-presenting cells (APCs). However, the mechanisms of HDAC11 in regulating
myeloid cells differentiation and function remained unclear.
We have uncovered for the first time that in the absence of HDAC11, upon LPS
stimulation, neutrophils isolated form mice displays an over-production of pro-
inflammatory cytokines such as TNF-alpha and IL-6. Strikingly, these HDAC11KO neutrophils showed a significantly higher migratory and phagocytosis activity, resulting from an overexpression of the migratory receptor and cytokine CXCR/L2. We have performed Chromatin Immunoprecipitation (ChIP) analysis on the neutrophils and discovered that HDAC11 was recruited to the promoter regulatory region of these genes we have identified. This part of data will be discussed mainly in chapter 2.
vii Not only does HDAC11 plays a crucial role in the neutrophil function, our group have also found out that lacking of HDAC11 result in an increased suppressive activity of the Myeloid-derived Suppressor Cells (MDSCs). The previous publication of our group had shown that the tumor bearing mice experienced a much more aggressive growth pattern in the HDAC11 KO mice compare with C57BL/6 wild type control.
MDSCs isolated from mice lacking HDAC11 appeared to gain increased capability to suppress the function of antigen-specific CD8+ T cells in vitro. Followed by this initial study, in chapter 3, we observed an up-regulation of both expression and enzymatic activity of arginase 1 and Nos2, two enzymes that are crucial in regulating MDSCs suppressive function. The aberrant enzymatic activity of Arg1 and Nos2 in HDAC11KO
MDSCs is possibly result from an over-expression of the lineage-specific transcription factor C/EBPβ, which is previously proved to be essential for the differentiation of functional MDSCs. Furthermore, our ChIP data confirmed that HDAC11 may play as an negative regulator of C/EBPβ. Recently, our lab had demonstrated that T cells lacking
HDAC11 gained a hyperactive phenotype and anti-tumor effect, indicating that HDAC11 may play a dual role in the host immune system. We further performed an adoptive transfer therapy to C57BL/6 tumor bearing mice. Our data showed that the additional administration of HDAC11KO MDSCs could eliminate, at least partially, the anti-tumor effect by adoptive transfer of HDAC11KO T cells.
Taken together, we have uncovered a previously unknown role for HDAC11 as a transcriptional regulator in the myeloid cells differentiation and function. Based on our data and previous work from our lab, we propose a dual role of HDAC11 played in the host immune system. In the absence of HDAC11, host defenders such as neutrophils
viii and T cells are functionally more aggressive against intruders such as pathogen and cancer. However, the immune suppressors such as MDSCs became more suppressive.
The contradictory role HDAC11 played in the immune system may provide some insights for the assessment of the pharmacological value of HDAC11 and contribute to the development of novel immunotherapeutic strategies.
ix
Chapter 1: Background
1.1 Cancer
Cancer is the second leading cause of death in the United States and a major
health problem worldwide. There are 1,688,780 new estimated cancer cases and 600,
920 estimated cancer death in the United States in 2017. Prostate, lung & bronchus and
colon & rectum are the top three types of cancer incidence in male with estimated
incidence rate of 19%, 14% and 9% respectively. In women, breast cancer consist 30%
of projected cancer incidence along with other two leading cause lung and colon cancer.
In both sex, lung cancer appears to be the top projected cause of death in 2017 [1].
Overall, both cancer incidence and death rate are slowly decreasing since 2004 and 5-
year survival rate has increased by 20%, possibly benefit from the development of
treatments, introduction of cancer screening and more access to medical care among
all population [1]. However, the efficacy of current therapeutic strategies is limited by the
unresponsiveness and resistance from patients after treatment. The complexity of tumorigenesis remains a huge challenge to the development of therapeutics.
In their paper published in 2000, Hanahan and Weinberg proposed a model for six features that were shared by most even all human cancers: sustained proliferative signaling, evasion of growth suppression, ability to metastasize, replicative immortality,
1 ability to induce angiogenesis and resistance to cell death [2]. With new knowledge
gained by current developments in the cancer research field, this model was further re-
defined by Yousef Ahmed Fouad and Carmen Asnei with seven hallmarks by combining
a few common features together and adding three new hallmarks: metabolic rewriting,
an abetting microenvironment and immune modulation [3]. Interestingly, many recent
studies provide evidences indicting that many mechanisms for tumorigenesis are
shared among different hallmarks. Finding over-lapping areas cross cancer types can
benefit the development of cancer therapies in a long run.
1.1.1 Cancer and host immune system
The host immune response, which has been studied extensively for the past few
decades, can be broadly categorized as innate immunity and adaptive immunity. It is
well accepted that the adaptive immunity relies on the innate immunity during the
initiation and development of adaptive effector mechanisms. Upon pathogen recognition, cellular mediator for the innate immunity such as macrophages, neutrophils and nature killer cells migrate toward the location of infection and produce high level of cytokines and chemokines to direct the killing or phagocytosis of infected cells. The antigens
recognized by antigen-presenting cells such as macrophages and dendritic cells will
then be presented to the key components for adaptive immunity and direct the clonal
expansion of antigen-specific effector cells selected by receptor gene rearrangement [4,
5].
2 In both cancer patients and tumor bearing animal models, it is widely observed
the host immune system often silenced when encounter tumors. The theory of cancer
immune surveillance was accepted with the observation of the defensive machinery in
the host body that was associated with immune mediated rejection of tumors in mouse
models. However, despite the immune surveillance tumor maintained its capability of
continuous development. The phenomenon of cancer immunoediting, which includes
three stages as elimination, equilibrium and escape, can best summarize the interaction
between tumor and host immune system. The elimination phase can best describe the
process of host immune response against cancer: by recognition of tumor cells, the
innate immune cell undergoing maturation and migration followed by the presentation of
tumor antigen and priming of cytotoxic T lymphocytes, which triggers the homing of
these T cells to tumor site and directs the killing of tumor cells. The continuous
elimination of tumor cells can then trigger the tumor cells evolution by the selection of
cells with reduced immunogenicity and increased resistance. This process defines the
second phase: equilibrium. The final step of tumor immunoediting is involved with the
evasion of immune surveillance and elimination and eventually results in tumor
"escape" (reviewed in [6]).
During the phase of selection, tumor cells are undergoing multiple genetic and
epigenetic alterations toward a "suitable" phenotype that could potentially survive the
immune attack. Mechanisms generated by tumor cells include 1) reduced antigen recognition by alter either tumor cell surface marker expression or the effector T cells, 2) induce immunological ignorance and tolerance through tumor secreted immunosuppressive factors or recruitment of immunosuppressive cells such as myeloid-
3 derived suppressor cells and tumor associated macrophages, 3) reduce
cytokine/chemokine mediated cell death [3].
In order to evade the immune surveillance and promote its progression, tumor
cells generate multiple mechanisms to "build" or "re-edit" the local microenvironment
they were growing in. The tumor microenvironment provides physical support, nutrition
and chemical signals for the tumor growth. However, large amount of immune cells and
non-immune cells are recruited to the TMEs as well. Large amount of literatures had
reported the infiltration of T cells, myeloid cells and cancer-associated fibroblasts in the microenvironment. The crosstalk between these cells and tumor cells can significantly impact the effectiveness of cancer therapy. The infiltration of antigen-specific effector T cells in the TMEs could potentially provide immune defense against cancer and present as a good prognostic marker. However, the anti-tumor function of those T cells is often suppressed by either tumor cells or other immunosuppressive cells recruited by the tumor. The reprogramming of immunosuppressive factors in the TMEs will be discussed later in this chapter.
1.1.2 Hematopoiesis and abnormal myelopoiesis
Hematopoiesis plays a crucial role in the immune system in humans. The hematopoietic stem cells (HSCs) are responsible for the production of all lineages of blood cells at a daily basis. Upon stimulation with different kind of signals such as growth factor and cytokines, HSCs undergoes multiple steps of differentiation and commitment and eventually give rise to multiple lineages of cells. In the bone marrow,
4 common myeloid progenitor cells (CMPs) will be further differentiated into
Megakaryoblast, Proerythroblast, master cells and Myeloblasts, whereas common
lymphoied progenitor cells (CLPs) will be further differentiated into B, T lymphocytes
and lymphoid dendritic cells. The Myeloblasts will eventually give rise to
monocytes/macrophages, neutrophils, dendritic cells, basophils and eosinophils. At
steady state, hematopoiesis is strictly regulated by different genetic and epigenetic
modulations to maintain homeostasis of the host immune system. However, under
pathological conditions such as infection, HSCs will undergoing expansion and induce
the production of different kinds of blood cells to replace the cells that are "consumed"
during innate and adaptive immune responses.
During tumorigenesis, abnormal myelopoiesis could occur in response to a
persistent signal of growth factors (such as GM-CSF, G-CSF and M-CSF) produced by tumor cells or tumor induced inflammation [7]. As a result, large amount of immature myeloid cells will enter the blood stream and migrate to the sites of demand. As previously discussed, tumor cells can develop multiple mechanisms to evade immune surveillance such as induced immunosuppressive pathways. During this tumor induced emergency myelopoiesis, once being released to the blood, the immature myeloid cells will differentiated into functional suppressive MDSCs and enter the tumor microenvironment [8-10]. Moreover, besides growth factors listed above, cytokines such as IL-1β can also induce increased hematopoiesis in the bone marrow in tumor bearing mice, possibly through the release of increased level of serum IMCs induced by IL-1β
[11]. Interestingly, recent studies had demonstrated that tumor induced abnormal
myelopoiesis can be mediated by HDAC inhibition. Besides the direct cytotoxic effect of
5 HDAC inhibitors on cancer cells, HDACi has been shown to induce the cytotoxic activity of CD8+ T cells against cancer. However, administration of HDACi in vitro result in an enhanced bone marrow proliferation and functional MDSCs expansion [12]. To date, the mechanism of HDAC inhibition affect myelopoiesis is not fully understood yet. In chapter two and three of this dissertation, questions regarding to mechanistic role of HDAC11, the newest member of the HDAC family, in hematopoiesis under pathological conditions such as infection and cancer will be further addressed.
1.1.3 Current approaches for cancer immunotherapy
Currently many different types of immunotherapy are used to treat cancer. (1)
The monoclonal antibodies. Some mABs are designed to bind to specific surface receptors and function as an agonist or antagonist, which can potentially cause an immune response that eliminates cancer cells. Other types of mABs may bind to the surface of cancer cells and direct immune recognition or the delivery of a cytotoxic agent [13]. (2) Cytokine treatment. The infusion of cytokines such as interferons and interleukins could potentially induce the proliferation and responses of the immune cells.
However, it also proved to be associated with various side effects and limited clinical outcomes. (3) Adoptive cell transfer. T cells isolated from the tumor have the potential to recognize tumor cells and are actively against them. Ex vivo expansion of those tumor- specific T cells and re-introduce to the patients can restore the anti-tumor immune response in many cases. The T cells from patients can also be genetically modified before re-infuse into the patients. More recently, CAR-T cell therapy has been approved
6 by the Food and Drug Administration (FDA) in treatment of ALL. (4) Vaccine treatment.
Cancer vaccines such as polypeptide based, whole cell, or viral vector can work against cancer by induce the responses by host immune system.
One challenge for modern cancer immunotherapy such as adoptive T cell transfer is to overcome the immunosuppressive microenvironment modulated by tumors.
The suppressive feather of the TMEs is associated with multiple factors such as cancer types and disease stages, as the host immune system is possibly compromised with advanced disease. Targeting the suppressive cells/factors in the TMEs or giving the treatment at an earlier stage might provide a better outcome in combination with these therapies.
1.2 Tumor microenvironment
Cancer cells are the crucial components to form a malignant tumor. But the malignant phenotype of cancer cells cannot be achieved without the surrounding cells in the local environment where primary or metastasis tumor mass was formed. Together with tumor cells, the non-malignant cells such as lymphocytes, myeloid cells, fibroblasts, along with the extracellular matrix, blood vessels and other supporting structures composed tumor microenvironment [14]. The infiltrated non-malignant cells in the tumor microenvironment displayed a dynamic and tumor promoting function during the initiation, progression and metastasis of many solid tumors [15]. Both tumor cells themselves and infiltrated immune cells can release a wide range of different cytokines, chemokines and growth factors which can contribute to the tumorigenesis, recruitment
7 of immune cells, as well as suppression of T cell function. The cross talk in between
tumor cells and infiltrated cellular and non-cellular components in the microenvironment
formed a dynamic network and brought huge challenge for therapeutic targeting the
tumor microenvironment.
1.2.1 Tumor infiltrated T lymphocytes
Studies had documented evidence of many different T lymphocyte populations
infiltration in tumors and the draining lymphoid organs. The prognostic significance of
those tumor infiltrated T cells is in debate considering the functional diversity of this
heterogeneous population of T cells when interacting with tumor cells or other cellular
components in the tumor microenvironment.
Higher number of infiltration of cytotoxic CD8+ memory T cell which have the
capability to recognize antigen and kill tumor cells are generally correlate with good
prognostic [16]. CD4+ T helper 1 cells (Th1, produce IL-2 and IFN-γ), which support
CD8+ T cell function, are also considered as good prognostic when largely infiltrated in
the tumors [16]. On the contrary, CD4+ T helper 2 cells (Th2, produce cytokine such as
IL-4, IL-13 and IL-5)) and immnosuppressive regulatory T cells (Tregs express surface marker Foxp3 and CD25) in the tumor microenvironment are believed to be tumor promoting [16, 17]. Additionally, higher number of Tregs in the blood of diffuse large B- cell lymphoma is associated with poor prognostic, but Tregs can be tumor suppressive in Hodgkin's lymphoma patients [18-20].
8 However, multiple mechanisms had been identified to discharge Cytotoxic T
cell's anti-tumor function in the microenvironment. The key effectors that contribute to the immune dysfunction include tumor cells, suppressive immune cells and stromal cells. Tumor cells often over-express or down-regulate certain cytokines to manipulate
immune responses. For instance, over-expression of CCL2 in colorectal cancer result in increased recruitment of tumor associated macrophages that contribute to cancer progression [21]. Enhanced secretion of chemokine ligand CCL22 by breast cancer is associated with the infiltration of regulatory T cells [22, 23]. Lacking expression of
CCL2, CCL3 CXCL5, CXCL10 in metastatic melanoma can forbid antigen-specific T cell infiltration [23, 24]. Besides chemokines, tumor cells can up-regulate checkpoint proteins such as cytotoxic T lymphocyte antigen-4 (CTLA-4) and programed cell death-
1 (PD-1) on tumor infiltrated T cells, which are originally part of the normal suppressive mechanism during immune response, result in down-regulation of those T cell response and exhaustion [25].
1.2.2 Myeloid-derived suppressor cells
Myeloid-derived suppressor cells are defined as a heterogeneous population of inhibitory immune cells that are expanded result from abnormal myelopoiesis and neutrophilia in various cancers in murine models and humans [26]. MDSCs were first observed in the 1980s and were called "nature suppressor cells" characterized with its inhibitory ability to T cell proliferation and cytotoxic T cell generation. They were soon discovered in multiple cancer types such as head and neck, as well as murine animal
9 model bearing spontaneous and transplanted tumors [27, 28]. Researchers had
struggled how to term this special population of cells and until 2007 the terminology of
"myeloid-derived suppressor cells (MDSCs)" was finally accepted [29].
1.2.2.1 The origin of MDSCs
Based on currently knowledge, MDSCs are believed to originate from the bone marrow in both human and mouse (a small amount of MDSCs are believed to originate from spleen in mouse). They are derived from the hematopoietic stem cells to the common myeloid progenitor and the granulocyte/macrophage progenitor cells. During steady state hematopoiesis, these GMP cells usually further commit to granulocytes and macrophages. However, under pathological conditions such as cancer progression
(sometimes infection), the GMPs will further differentiated into MDSCs in bone marrow, blood, lymph nodes, spleen, tumor site and metastasis, with an expansion of more than
20% of total cells [30]. Originally, MDSCs are defined as cell express surface marker
CD11b and Gr-1 (Ly6G/Ly6C). However, during normal hematopoiesis, CD11b+Gr-1+
cells constitute 20 to 30% of total cells in the bone marrow and 2 to 3% in the spleen.
The surface markers are not exclusively expressed on MDSCs, which make it
necessary to include the functional characterization as part of the strategy to identify
this special population.
10 1.2.2.2 MDSCs expansion
Several growth factors were demonstrated to affect the MDSC expansion:
granulocyte-macrophage colony-stimulating factor (GM-CSF), granulocyte colony- stimulating factor (G-CSF) and macrophage colony-stimulating factor (M-CSF). During myelopoiesis at steady state, GM-CSF, G-CSF and M-CSF are believed to play a crucial role in the maturation, proliferation, recruitment and survival of granulocytes and monocytes. When treated with GM-CSF and/or G-CSF in vitro, bone marrow precursor cells acquired a similar surface phenotype and function to MDSCs induced by cancer
[31, 32]. Thus, it is not surprising that the high secretion of GM-CSF and G-CSF from cancer cells is associated with MDSCs expansion and infiltration. Long-term exposure of high level of GM-CSF and G-CSF produced by cancer cells affect the generation, maintenance and survival of MDSCs in cancer patients [33]. However, there's no evidence showing that short administration of GM-CSF to patients has the same effect
[34].
1.2.2.3 Subsets of MDSCs
Recently, two major subsets of MDSCs have been identified based on their morphology and surface markers expression: monocytic MDSC (M-MDSC) and granulocytic MDSC (G-MDSC, also called polymorphonuclear PMN-MDSC) [35, 36]. In mice, M-MDSCs are characterized as CD11b+Ly6G-Ly6Chigh while G-MDSCs as
CD11b+Ly6G+Ly6Clow [36-38]. However, in cancer patients, the definition of phenotype
of human MDSCs is unclear. By far human M-MDSCs are defined as
11 CD11b+CD14+CD33+HLA-DR-/lowCo-receptor-/low and G-MDSCs as
CD11b+CD15+CD33+Lin-HLA-DR-/low expressing cells [8, 39].
Functionally, M-MDSCs are believed to be highly immunosuppressive in both
antigen specific and non-specific manner, whereas G-MDSCs' immunosuppressive
effect is moderate and its promotion to T cell tolerance is antigen-specific. Monocytic
MDSCs express high level of both immunosuppressive enzymes arginase and inducible
oxide synthetase (iNOS), but could not produce high level of reactive oxygen species
(ROS). On the contrary, granulocytic MDSCs are capable of the expression of high level
of arginase and the production of high level of ROS, but fail to express iNOS [26, 40].
Besides increased expression of Gr-1 surface marker on both populations, M-MDSCs express high level of IL-4 receptor alpha (IL-4α) compare with G-MDSCs [41]. However, the low intensity of IL-4α on and its inconsistent expression pattern on in different cancer hosts forbid it to become a good surface marker to distinguish the subsets of
MDSCs [42, 43].
1.2.2.4 Mechanisms regulating MDSCs biology
Two major questions regarding MDSCs biology are: 1), what is the mechanism(s) that regulates MDSC generation and expansion; 2), what controls their tumor promoting function. Recent studies had established multiple signal pathways that were regulating
MDSC expansion and function. The transcription factors involved with those pathways often overlap or have impact on each other and formed a complicated signal network that benefit MDSCs suppressive capability.
12 The signal transducer and activator of transcription (STAT) family had been
demonstrated to play an important role in different mechanisms. Activation of STAT3
can directly promote proliferation; prevent cell apoptosis and differentiation in MDSCs,
through over-expression of Bcl-xL, c-myc and cyclin D1 [30]. Another pathway STAT3
involved with is the calcium-binding pro-inflammatory protein S100A8 and S100A9 [44].
Upregulation of S100A8 and S100A9 by STAT3 result in MDSCs accumulation in mice
[9, 44]. Activation of STAT3 was also proven to directly relate with up-regulation of ROS
production in MDSCs, possibly through up-regulation of the NADPH oxidase (Nox2)
components P47phox and gp91phox [9]. Notable, there's new evidence showing that
STAT3 activation result in an up-regulation of transcription factor CCAAT-enhancer- binding protein beta (C/EBPβ), in responding to G-CSF in vitro [31]. C/EBPβ plays a
crucial role in the differentiation and immunosuppressive function of BM-derived and
tumor-induced MDSCs. Mice lacking C/EBP-β in the bone marrow compartment
appeared to lose the ability to differentiate from IMCs into pathologically active MDSCs, possibly through a reduction of arginase 1 and Nos2 proteins expression [31]. In addition to STAT3, other members of the STAT family had shown to be associated with
MDSCs function. In response to IL-1β or IFN-γ, STAT1 can up-regulate iNOS and arginase activity, leading to a functionally more suppressive MDSCs phenotype [45, 46].
Some studies reviewed that STAT5 and STAT6 played a crucial role to MDSC survival
and function through multiple pathways.
One mechanism of the suppressive function in MDSCs is mediated by Arginine
metabolism. Arginine is a non-essential amino acid for adult human and its metabolism
is largely associated with immune response. L-Arginine deprivation has no effect on
13 primary T cells at steady state, from both mouse and human. Once activated in L-
Arginine free culture medium, T cells appeared to have decreased expression of CD3ζ
chain and down-regulation of NFκB-p65 and Jak-3, as well as a reduced proliferation
and inability of IFN-γ production [47, 48]. Arginine can be metabolized by a few
enzymes such as arginase, nitric oxide synthase (NOS), arginine:glycine
amidinotransferase (AGAT) and arginine decarboxylase. In MDSCs, higher expression
of Arg1 and Nos2 are often detected among different subsets that are related with
MDSCs to T cell suppression. There are two isoforms of arginase, Arg1 and Arg2.
Arginase 1 mainly expresses in myeloid cells and hepatocytes. Arginase 2 can be found
in tissues such as kidney, brain and small intestine [48]. Arg1 can convert L-arginine to
urea and L-ornithine, whereas Nos2 can generate nitrite oxide (NO) and L-citrulline
when utilize L-arginine. Increased NO production by MDSCs infiltrated into tumors is associated with T cell suppression through interfering T cell and APC communication, inhibit T cell signaling downstream of IL-2R and induce T cell apoptosis [49-51]. Up-
regulation of Arg1 and Nos2 in MDSCs are mediated through different signal pathways.
Activation of STAT6 and up-regulation of transcription factor C/EBPβ and STAT3 are
associated with increased Arg1 expression in MDSCs. Additionally, multiple cytokines
and growth factors such as IL-4, IL-10, IL-13, TGF-β and GM-CSF can induce the
expression of Arg1 as well [48]. Moreover, Nos2 production can be induced in response
to IFN-γ, TNF-α and IL-1β as mentioned before.
In addition to up-regulation of Arg1 and Nos2, increased expression of NOX2, the
catalytic subunit of NADPH oxidase can result in increased level of ROS in granulocytic
14 MDSCs, mediating T cell inhibition through downregulating CD3ζ chain expression, reducing cytokine production and impairment of the differentiation of MDSCs [52].
Besides directly suppress T cell function, MDSCs was found to induce the development of CD4+CD25+Foxp3+ Tregs in a colon carcinoma mouse model [53].
Additionally, a few inhibitory methods that are used to reduce MDSCs function were found to contribute to reduce Treg function and expansion [54, 55].
1.2.2.5 Clinical evaluations of MDSCs
The important role of MDSCs has been acknowledged for tumor initiation, progression and immune evasion. However, in clinic, the expansion of MDSCs has been correlated with advanced stages in multiple cancer types such as head and neck squamous cell carcinoma, none small cell lung cancer (NSCLC), hepatocellular carcinoma (HCC), bladder cancer, pancreatic cancer and hematological malignancies such as non-Hodgkin lymphoma (reviewed in [56]). Moreover, besides tumor progression stages, MDSCs level also correlates with patient response to therapy and surgery. Clinical data reviewed that circulating MDSCs level in the blood could serve as a predictive and prognosis marker. An example is in stage IV breast or colorectal cancer patients, high circulating MDSCs number is associated with poor prognosis (reviewed in
[56]). Higher number of blood circulating MDSCs at baseline prior to chemotherapy also correlated with a shorter overall survival (reviewed in [56]).
15 1.2.2.6 Targeting MDSCs in cancer
The functional characterization and clinical correlation study reviewed MDSCs as
an important factor in cancer in general and reflect them as a potential target for
therapeutic approaches. The fact that MDSC is primarily correlate with T cell
suppression indicate the potential to directly target this population or as adjuvant with
current immunotherapy. As reviewed by many researchers, blocking MDSCs
generation, recruitment or suppressive function, as well as converting MDSCs to APCs
could be beneficial as potential therapeutics. One in vivo study using nitroaspirin (NCX-
4016) had observed restoration of T cell responsiveness and enhanced efficacy of
cancer vaccination, possibly through inhibition of Arg1 and iNos activity [57].
Administration of all-trans retinoic acid (ATRA) or vitamin D3 result in differentiation of
MDSCs toward matured myeloid cells thus improve the efficacy of anti-tumor vaccination [58]. Some earlier generations of chemotherapeutic agents such as 5-
Fluorouracyl showed to affect monocytic MDSCs apoptosis in animal models [59, 60].
Inhibition of CSF1/CSF1R by using CSF1R antagonist and anti-CSF1R mAB (RG7155) affects monocytic MDSCs differentiation and recruitment in some clinical trials [61].
Although increasing therapeutics have been designed to target MDSCs through
different pathways, more investigation should be dedicated to assess the safety,
effectiveness and side effects of the new agents before entering clinical trial. Moreover,
the complexity of the signal pathways regulating MDSCs function brings huge challenge
to targeted therapeutics. A better understanding of the network mediating MDSCs
biology will likely to benefit cancer treatment in a long run.
16
1.2.3 Tumor associate macrophages
Tumor associate macrophages (TAMs) are a major leukocyte population
infiltrated in tumors. Depend on the microenvironment; macrophages could acquire
different phenotypes associated with different functions. Classically activated
macrophages (M1 macrophages) and alternatively activated macrophages (M2
macrophages) are often considered to be the two major polarized phenotypes of
macrophages. M1/M2 macrophages are driven from different cytokines. IFN-γ or LPS
can induce M1 macrophages that are generally considered to be pro-inflammatory. M2
macrophages can be polarized in response to IL-4 and IL-13 and are characterized with
anti-inflammatory phenotype. Tumor associated macrophages are usually linked with
M2 macrophages. However, the transcription profile of TAMs is quite distinct from both
phenotypes [62, 63].
Unlike regular macrophages, which have the potential to eliminate tumor cells, tumor associate macrophages are one of the major contributors to many stages of tumor progression. The pro-tumorigenic effect of TAMs is largely reflected on their
involvement with tumor cell migration, invasion and metastases. The
immunosuppressive effects of TAMs and MDSCs are overlapping in many manners. For
instance, both TAMs and MDSCs can suppress T cell function in an antigen-specific
and non-specific manner. TAMs and MDSCs can both induce CD4+CD25+Tregs
generation and recruitment [64, 65]. Similar to MDSCs, TAMs shared high enzymatic
activity for L-arginine consumption that deploys one of the most powerful suppressive
17 features in regulating T cell response and proliferation [66]. In addition to immune suppression, TAMs and MDSCs both played a crucial role in promoting tumor angiogenesis by secreting VEGF, CXCL8/IL-8 in response to hypoxia [56].
1.2.4 Other cellular and non-cellular components in the tumor
microenvironment
Besides T lymphocytes and suppressive myeloid cells, other types of immune cells can be found at the invasive margin of some tumors and/or draining lymph nodes as well. The infiltration of natural killer cells (NK cells) and natural killer T cells (NKT cells) can be found in some cancer types and are associated with a good prognosis
[67]. Dendritic cells (DCs) and tumor associated neutrophils (TANs) are also reported to infiltrate tumors. However, the primary function of DCs and TANs that are related with antigen processing and presenting are usually defective. Instead, when interact with malignant cells or local microenvironment, they appear to promote tumor progression by suppressing T cell response or enhancing tumor growth and angiogenesis. In addition, the infiltration of B cells in medullary ductal breast cancer and high-grade serous ovarian cancer was associated with good prognosis [68, 69]. However, their function can be switched to tumor promotion by inhibit tumor specific cytotoxic T cell response
[70].
Other cellular or non-cellular components in the tumor microenvironment had been shown to play crucial roles in cancer progression. Myofibroblasts in TME, also known as cancer-associated fibroblasts (CAFs), are associated with promotion of
18 cancer cells growth and survival, maintaining the immune suppressive
microenvironment as well as inducing epithelial-mesenchymal transition (EMT) through secretion of growth factors and chemokines [71]. Adipose cells and tissue are associated with secretion of large amount of cytokine, chemokine and hormone-like
factors to support and maintain a pro-inflammatory microenvironment, contributing to
tumor progression and immunosuppression. In addition, the non-cellular components in
TMEs, extracellular matrix (ECM), contain cytokines and growth factors secreted by
tumor cells and stromal, which contribute to tumor growth and recruitment of
immunosuppressive cells [71]. ECM also provides a physical scaffold for all cells in the
tumor microenvironment, helping maintain tumor homeostasis.
1.2.5 Strategies of targeting the tumor microenvironment
The cellular and non-cellular components of the tumor microenvironment permit
and promote tumor progression in many different aspects and a lot of them were found
over-lapping during the cross talk between each other. Therapeutic strategies can be
developed to target both cellular and non-cellular components in the TMEs.
(1) Targeting immune cells. Chronic inflammation induced by tumor infiltrated
macrophages, neutrophils and master cells is usually associated with cancer
progression. Depend on the polarization phenotype, immune cells can exert
either anti- or pro-tumor effect. The presence of M1 macrophages, N1
neutrophils, Th1 CD4+ helper T cells and cytotoxic CD8+ T cells sometimes
indicate a good prognostic or favorable to immune therapy. However, these
19 immune cells possess potential anti-tumor effect that is often found to be suppressed through different pathways. On the other hand, cells with immunosuppressive phenotype such as tumor associated macrophages,
MDSCs and regulatory T cells either promote tumor progression directly or suppress immune response. Thus, targeted therapeutics could be considered based on the unique function of a particular cell type. For instance, blocking the recruitment or reprograming suppressive cells in the TMEs may potentially reduce the pro-tumor effect and induce immune response against tumor cells.
The cytotoxic CD8+ T cells present in the tumor is often not sufficient enough against tumor cells. Additional adoptive transfer of antigen-specific CD8+ T cells was proved to have positive effects on some patients. However, the over-all suppressive microenvironment those T cells encountered may potentially affect the anti-tumor response. Adding a suppressor cell blockade may potential benefit the effect for the adoptive transfer therapy. Anti-inflammatory drug have been found to reduce tumor incidence and could potential serve as an anti- tumor agent, however, its side effects and specificity remains questionable.
(2) Targeting none-immune cells in the TMEs. Cancer associated fibroblasts
(CAFs) are involved with tumor progression and metastasis by providing support to tumor cell growth and cell-cell interaction in TMEs, induce angiogenesis and the presence of CAFs usually associated with poor prognosis in many cancers. Extensive cross talk between tumor cells, CAFs and immune cells in the TMEs was observed among different cancers, indicating that CAFs possessed a therapeutic value. Although a few clinical studies had failed to
20 either achieve clinical benefits or end up reducing survival rate, further understanding will contribute to the development of targeted therapy against
CAFs.
(3) Targeting non-cellular component in the TMEs. The extracellular matrix in
TMEs facilitates support for the interaction between cancer cells and host cells.
In addition to the physical network, ECM creates an environment contains different chemical signal with the ability to regulate the oxygen level, pH value and interstitial pressure for the TMEs [72] that affects tumor progression, which may provide multiple potential targets for cancer therapy.
(4) Targeting angiogenesis. Extensive interests and developments on tumor angiogenesis during the past 40 years contribute to the development of therapeutics targeting this specific hallmark of cancer. Many clinical trials have been conducted using different kind of agents such as anti-VEGF antibody and antiangiogenetic tyrosine kinase inhibitors. However, the feedback of antiangiogenetic drugs turned to be modest with a lower responding rate [73], possibly through tumor dependent or independent resistance. Alternative strategies proposed by cancer researchers are using antiangiogenic drugs as adjuvant therapies in combination with other therapies such as chemotherapy, conduct trials for patients at early stage of tumor development and developing therapeutics against VEGF-independent angiogenic factors (reviewed in [72])
21 1.3 Histone deacetylases
In eukaryotes, DNA is tightly compacted with an octamer of four histones (2
H2A/H2B dimers and a H3/H4 tetramer) to form the nucleosome, subunit of chromatin.
This highly dynamic protein-DNA complex prevents the accessibility of transcription factors in resting cells whereas made available through chromatin remodeling during post-transcriptional regulation. Epigenetic modification, including DNA methylation, phosphorylation, ubiquination and acetylation, could alter the chromatin architecture thus influence the transcriptional regulation. Although DNA methylation is well studied, acetylation of histones had gained increasing amount of interest for scientific investigators in recent years.
Two groups of enzymes have been recognized to modify histone acetylation status based on their function. Histone acetyltransferase (HATs), function as epigenetic writers, transfer acetyl group to lysine residues on histones (and other acetyl-lysine containing proteins) and allow accessibility of transcription machinery to a “relaxed” chromatin structure and up-regulate a particular gene expression. On the contrary, the epigenetic eraser histone deacetylases (HDACs) remove acetyl group from histone tails, form a condensed chromatin and make it unfavorable to DNA binding proteins and repress transcription [74, 75].
1.3.1 Classification of HDACs
Presently in humans, there are eighteen known HDACs so far with differences in amino acid sequence, enzymatic domain structure and tissue specific expression
22 pattern. Besides the nicotinamide-adenine-dinucleotide (NAD+)-dependent sirtuins, eleven out of these eighteen zin-dependent HDACs were found with conserved deacetylase domain and divided into four classes: class I HDACs (including HDAC1,
HDAC2, HDAC3 and HDAC8); class II (HDACs 4, 5, 6, 7 and 9) and class IV with a sole member HDAC11. Class II HDACs were further divided into two sub-classes: class IIa includes HDAC 4, 5, 7 and 9; class IIb includes HDAC6 and HDAC10 which both have two catylytic sites. Class I, IIa, IIb and IV HDACs are grouped as classical HDACs [76,
77].
The predominant localization of almost all HDACs was found to be the nuclear through a nuclear localization signal (NSL) or the co-localization with other proteins.
Class I HDACs are mostly found exclusively in the nucleus except for HDAC3, which contains both a nuclear import and export signal. HDAC11 is primarily located in the nucleus, however, using co-immunoprecipitation, both endogenous and over-expressed
HDAC11 can be detected in the cytoplasm when associated with HDAC6 [78, 79]. Class
II HDACs can shuttle in and out of the nucleus, either induced by certain signal or depend on the splice variants [76].
1.3.2 HDAC11
Histone deacetylase 11 was first cloned and identified in 2002 by Gao and colleagues. The molecular weight of HDAC11 is 39 kDa with a total sequence of 347 amino acid consisting nine exons and eight introns [79]. In humans, HDAC11 protein is encoded on chromatin 3p25.2 whereas on chromatin 6 in mouse [79]. As the smallest
23 member in the HDAC family, HDAC11 contains all blocks of conservative sequence in its catalytic domain that are identified to be important for the enzymatic activity for deacetylase function among other HDACs [79]. Phylogenetic analysis had reviewed
HDAC11 is more closely related to class I HDACs and the prokaryotic AcuC protein than class II HDACs [79]. However, HDAC11 shared an extremely low similarity of its structure to class I, II and III HDACs and was granted with its own class, class IV [79].
The expression of HDAC11 characterized in various tissues and cancer cell lines. Northern blotting and mRNA analysis from Gao, et al reviewed that HDAC11 expression was highly tissue specific, with a higher expressing signature in brain, heart, skeletal muscle, kidney and testis, suggesting that its function may be tissue specific
[79]. Higher level of HDAC11 was also detected in several human malignant cell lines such as rhabdomyosarcoma muscle tumor cell line [79]. An in vitro deacetylase activity assay using FLAG-HDAC11 showed that HDAC11 possessed catalytic activity shared by other family members, but in a much lower manner [79]. However, using a synthetic peptide in vitro to measure the activity might not reflect the true deacetylase ability of endogenous HDAC11.
Using same FLAG-HDAC11 over-expression model, Gao's group identified a physical association between HDAC6 and HDAC11 293 cells [79]. Both calss I and II
HDACs had been previously proved to function in protein complexes including transcription repressors and other proteins from the HDAC family. However, besides
HDAC6, no evidence indicates that HDAC11 is physically involved with other HDAC family members. HDAC11 was previously found to localize in the nucleus. However, recent study detected the interaction of HDAC6 and HDAC11 in both cytoplasmic and
24 nuclear compartment in murine and human macrophage or promonocytic cell lines,
through the N-terminal domain of HDAC11 and C-terminal domain of HDAC6 [78].
1.3.2.1 HDAC11 in APCs
The functional role of HDAC11 in immune cells was largely undefined until
Villagra in our group first found out that this molecule played as a transcription repressor of IL-10 expression in macrophages. In response to LPS, macrophages with HDAC11 over-expression result in decreased IL-10 expression, possibly through alteration of the phosphorylation of histone H3 in the proximal region of IL-10 promoter [80]. Further investigation by the authors showed that HDAC6 and HDAC11 played opposing roles in regulating IL-10 expression in APCs. The authors had demonstrated that over- expression of HDAC6 results in an increased IL-10 production in macrophages [78].
Interestingly, the physical interacted HDACs were found to be recruited to the same region in the IL-10 promoter, suggesting the opposite role of HDAC6 and HDAC11 played in regulation IL-10 expression might related with their dynamic interaction under stimulation [78].
Recently, another group had demonstrated that HDAC11 up-regulation result in a down-regulation of IL-10 in Kupffer cells isolated from alcohol-fed mice, possibly through alcohol metabolites (ALDH) and NF-κB pathways [81]. Furthermore, decreased
IL-10 production was observed in dendritic cells when HDAC11 was knocked down using shRNA.
25 1.3.2.2 HDAC11 in T lymphocytes
The functional role of HDAC11 in T lymphocytes was characterized by two recent
publications. Woods and Woan from our group had previously observed an increased
effector function by T cells lacking HDAC11. Using a HDAC11 knockout mouse model,
the authors found that in the absence of HDAC11, CD8+ T cells displayed increased
proliferation rate and surface expression of effector molecules such as granzyme B and
perforin [82]. Both HDAC11KO CD4+ and CD8+ T cells produced higher level of proinflammatory cytokines in both antigen dependent and independent manner. In addition, HDAC11KO T cells were less susceptible to tolerance induction and experience less suppression from Tregs [82]. Furthermore, in vivo study demonstrated an enhanced anti-tumor effect of T cells lacking HDAC11 through adoptive transfer therapy [82]. One proposed mechanism by the authors was HDAC11 mediate the hyperactive phenotype of T cells through alteration of chromatin structure in the promoter region of transcription factors Eomes and Tbet. Using Chromatin-
immunoprecipitation, the presence of HDAC11 in both promoters of Eomes and Tbet
was determined, along with a decreased acetylation signature of histone 3 in both
promoters in resting WT T cells [82]. Meanwhile, another study demonstrated that
deletion or pharmacologic targeting of HDAC11 using a HDAC11 inhibitor (JB3-22) could enhance the suppressive function of Foxp3+ Tregs and promotes Treg-dependent
allograft survival [83].
26 1.3.2.3 HDAC11 in cancer
Upon its identification, aberrant up-regulation of HDAC11 has been reported in a few cancer cell lines including rhabdomyosarcoma (SJRH30), colorectal carcinoma
(HCT116), urinary bladder carcinoma (T24), non-small cell lung carcinoma (H1299) and oxteosarcoma (SJSA-1) [79]. Recently, another report pointed out that HDAC11 depletion by siRNA in HCT-116 colon, PC-3 prostate, MCF-7 breast and SK-OV-3 ovarian cell lines resulted in induced apoptosis and reduced metabolic activity of the cancer cells, however, such effects could not be reflected on normal cells [84]. Knocking down of HDAC11 in Hodgkin's lymphoma cell lines result in a significant enhanced surface expression of OX40L, which is essential for T cell activation and memory formation when engage with OX40 receptor B [85]. Additionally, a higher expression of
HDAC11 that observed in pituitary tumor tissue, which appears to be correlated with down-regulation of tumor suppressor P53, possible through the deacetylation of HEY1
[86]. Another study in neuroblastoma demonstrated that HDAC11 deletion triggered cell death through apoptotic programs [87].
1.3.2.4 Other functions of HDAC11
Earlier studies showed that HDAC11 control DNA replication. Through binding
Cdt1 during S-phase, HDAC11 deacetylates this molecule and inhibits its ability to induce chromatin unfolding thereby limits DNA replication [88]. A recent study had
demonstrated that HDAC11 can deacetylase Cdc25, a key regulator of cell cycle, via
direct protein-protein interaction [89].
27 In addition, expression of HDAC11 was observed at the highest level in mouse oligodendrocytes and its expression was increased during brain maturation after birth
[90]. One study by Liu et al had demonstrated that using HDAC inhibitor (TSA) or silencing HDAC11 expression by siRNA result in an increased histone 3 lysine 9 and lysine 14 (H3K9/K14) acetylation within the myelin basic protein (MBP) and proteolipid protein (PLP) gene promoters in the oligodendrocyte cells, leading to an abruption of their maturation and development [91].
Furthermore, HDAC11 has also been found to be involved in the regulation of myc gene along with vitamin D3 [92]. Interestingly, another recent study found out that
Vitamin D3 could induce the binding rate of Vitamin D receptor (VDR) and HDAC11 to the promoter loci of tight junction protein genes, result in the repressing of gene expression and the dysfunction of epithelial barrier [93].
Although attention and knowledge of HDAC11 is expanding during the past two decades, the full functional signature of HDAC11 still needs to be further defined. More understanding of the mechanistic role HDAC11 played in cancer and other diseases will contribute to further explore its potential as therapeutic targeting in those fields.
1.3.3 Other HDACs
HDAC1, 2, 3, 5, 6, 7 and 10 can be detected in all tissues whereas HDAC8 and 9 are mostly expressed in tumor tissues and cells. However, HDAC4 expression is non- detectable in somatic tissues but can be found in embryonic muscle tissue, which indicate that this HDAC is not essential [74].
28 HDAC 1 and 2 only display enzymatic activity within protein complexes such as
Sin3, nucleosome remodeling and deacetylating (NuRD) complex. Multiple cytokines,
transcription factors and growth factors are found to be downstream targets of HDAC1,
2 and 3. Class II HDACs possessed diverse functions among the family. Among all the
class II members, HDAC6 is the most studied and one of the two HDACs contained two deacetylase domains. HDAC6 was found to regulate various pathways related with autoimmune disease and cancer, which made it attractive pharmacological targets.
A typical characteristic of human cancer is the aberrant regulation of DNA methylation and histone modification, especially histone acetylation. It is not surprising that HDACs are believed to play an important role in cancer progression. Increased
HDAC activity is observed in many cancers possibly through recruitment of HDACs to specific promoters of tumor suppressor genes. Moreover, up-regulation of HDACs expression is observed in many cancers. For instance, HDAC1 overexpression is found in breast, colon, gastric, and prostate cancer [94-97], whereas HDAC2 is over- expressed in cervical, colorectal, and gastric cancer [98, 99]. HDAC3 up-regulation is reported in colon cancer and HDAC6 in breast cancer [95, 100]. These findings indicate that HDACs could be potential targets for cancer treatment.
1.3.4 HDAC inhibitors
HDAC inhibitors (HDACi) are most considered as promising cancer therapeutics along with its crucial role in treating immunological diseases such as viral infection and neurological disorder [101]. Besides the ability to inhibit the enzymatic activity of
29 HDACs, HDAC inhibitors also have the potential to target non-histone proteins in order
to inhibit angiogenesis, cell proliferation and also stimulate cell-cycle arrest [102, 103].
Based on the chemical structure, the HDAC inhibitors can be classified into hydroxamic
acid, benzamides, aliphatic acid and cyclic peptides, electrophilic ketones and
miscellaneous compounds [104].
In the past, the most commonly known HDAC inhibitors usually target multiple
HDACs. This can bring challenges to identify whether the effect of those inhibitors is
due to inhibition of a particular HDAC activity or in combination of multiple HDACs.
Moreover, several HDACs are believed to interact or depend on each other to achieve a
biological outcome, which suggest that even a putative specific HDAC inhibitor could
potentially develop broader effect than anticipated. Currently, HDACi is observed to
regulate various cellular or molecular effects in antitumor, immunological and
neurological responses.
A lot of questions remained unanswered in regarding to the direct anti-tumor effect of HDAC inhibitors. However, it is generally acknowledged that HDACis directly
effect on tumor cell through multiple pathways such as: 1) induced cell death through
induction of apoptosis, enhanced production of ROS, accumulation of DNA damage, 2)
induced cell cycle arrest, 3) induced senescence, 4) reversal of differentiation blocked
by fusion protein in AMLs, 5) induction of autophagy and 6) enhanced tumour
immunogenicity such as antigen-presenting capacity (reviewed in [75]). A few HDAC
inhibitors have been approved for cancer therapy by the US Food and Drug
Administration (FDA) in recent few years, namely suberoylanilide hydroxamic acid
30 (SAHA, 2006), romidepsin (2009) and belinostat (Beleoda1, 2014), in treatment of T-cell
lymphoma[105, 106] [107].
Many studies demonstrated that HDACs expression and function influence the
immune response under multiple pathological conditions including cancer. Considering
the wide spectrum impact of HDACis on different aspects when used as an oncology
drug, it could potentially achieve its best effect if a particular HDACi could target tumor
cells and induce anti-tumor immune response simultaneously. A few recent studies
have shown enhanced tumor antigenicity after treatment with HDAC inhibitor. For
instance, acute myeloid leukemia (AML), human neuroblastoma and mouse
plasmacytoma cells treated with HDACis such as TSA, trapoxin A or sodium butyrate
result in an up-regulation of MHC class I and MHC class II proteins, CD40, CD80, CD86
as well as adhesion molecule-1 (ICAM1) [108, 109]. Moreover, HDACi such as TSA,
SAHA and sodium butyrate has been shown to induce the expression of MHC class I
related chain A (MICA) and chain B (MICB), which are ligands for natural killer group 2
member D activating receptor on NK, CD8+ T cells, result in increased tumor-targeted
destruction [110, 111]. Additionally, TSA can induce the proliferation of cytotoxic CD8+
T cell and NK cells through enhanced expression of MHC class II and CD40 on B16
melanoma cells [112]. The antitumor immunity by HDACi SAHA could also result in decreased serum level of pro-inflammatory cytokines such as TNF-α, IL-1 and IFN-γ in an allogeneic GVHD model [113].
New HDACi compounds have been developed rapidly during the past few years.
However, the mechanisms for HDAC inhibitors to augment tumor rejection through either direct target or immunomodulatory effect are not fully understood by far. As for
31 the newest identified member of the HDAC family, only a handful of inhibitors have been reported to target HDAC11 with an unknown specificity feature. Recent work from our group and other laboratory had uncovered a novel regulatory role of T cell function by
HDAC11, implicated its potential therapeutic value. However, an earlier study from our lab demonstrated an opposite role of HDAC11 by enhancing the suppressive ability of
MDSCs, result in a pro-tumor effect. Given the complexity of the immunomodulatory role played by HDAC11, the next two chapters of this dissertation will be dedicated to present our recent work on how HDAC11 regulating immune response under different pathological conditions.
32
Chapter 2: Essential Role for Histone Deacetylase 11 (HDAC11) in Neutrophil
Biology1
2.1 List of Abbreviation
APCs: Antigen Presenting Cells
APL: Acute Promyelocytic Leukemia
ATCC: American Type Culture Collection
ATRA: All Trans-Retinoic Acid
CBA: Cytometric Bead Arra
CBC: Complete Blood Count
ChIP: Chromatin Immunoprecipitation
CXCL2: Chemokine (C-X-C motif) Ligand 2, Also known as Macrophage Inflammatory
Protein 2-alpha (MIP2-a)
CXCR2: Chemokine (C-X-C motif) Receptor 2, also known as Interleukin 8 Receptor
Beta (IL8Rb)
1 This chapter has been previously published (Chen J, Sahakian E et al. J Leukoc Biol. 2017 Aug; 102(2):475-486.) and utilized with permission from the publisher.
33 DCs: Dendritic Cells
E. coli: Escherichia Coli
eGFP: Enhanced Green Florescent Protein
FBS: Fetal Bovine Serum
HDACs: Histone Deacetylases
HDAC11: Histone Deacetylase 11
HDAC11KO: HDAC11 Knock-out
IL-1b: Interleukin-1 beta
IL-6: Interleukin-6
IP: Intraperitoneally
LPS: Lipopolysaccharides
mABs: Monoclonal Antibodies
MDSCs: Myeloid-derived Suppressor Cells
MGAL: Murine Genetic Analysis Laboratory
MIP2: Macrophage Inflammatory Protein 2-alpha (MIP2-a)
MPO: Myeloperoxidase
mRNA: Messenger RNA
34 NETs: Neutrophil Extracellular Traps
PBS: Phosphate Buffered Saline
PNs: Peritoneal Neutrophils qRT-PCR: Quantitative Reverse Transcriptase-polymerase Chain Reaction
RACE: Rapid Amplification of cDNA Ends
RFP: Red Fluorescent Protein
TNF-alpha: Tumor Necrosis Factor Alpha
WT: Wild-type
2.2 Abstract
Epigenetic changes in chromatin structure have been recently associated with the deregulated expression of critical genes in normal and malignant processes.
HDAC11, the newest member of the histone deacetylase family of enzymes, functions as a negative regulator of IL-10 expression in antigen presenting cells (APCs) as previously described by our lab. However, at the present time its role in other hematopoietic cells, specifically in neutrophils, has not been fully explored. In this report for the first time we present a novel physiological role for HDAC11, as a multifaceted regulator of neutrophils. Thus far, we have been able to demonstrate a lineage- restricted over-expression of HDAC11 in neutrophils and committed neutrophil precursors (promyelocytes). Additionally, we show that HDAC11 appears to associate
35 with the transcription machinery, possibly regulating the expression of inflammatory and
migratory genes in neutrophils. Given the prevalence of neutrophils in the peripheral
circulation, and their central role in the first line of defense, our results highlight a unique
and novel role for HDAC11. Considering the emergence of new selective HDAC11
inhibitors, we believe that our findings will have significant implications in wide range of
diseases spanning malignancies, autoimmunity, and inflammation.
2.3 Introduction
In humans, the predominant circulating leukocytes—neutrophils, are known to be
produced at immense numbers, through sequences of increasingly differentiated
precursor myeloid progenitors in the bone marrow (BM), before entering the
bloodstream and account for 50-70% of the entire circulating population [114-117].
During granulopoiesis neutrophils are produced at the rate of 1 x 1011 each day with a
significant increase within hours during infections [118], and in patients with various
cancer [119, 120] and therefore more than half of the BM is devoted to the production of
these cells at steady state [121]. Neutrophils play a pivotal and well-defined role in the host defense where they eradicate invading microorganisms [122], and even though they have been labeled short-lived, new in vivo deuterium labeling analysis has revealed that these cells may have a circulatory life span of up to 5 days [123].
Moreover, it is known that neutrophils can influence the immune response by way of communicating with dendritic cells (DCs), macrophages [124, 125] as well as B cells
[126] and T cells [127]. In fact an accumulating series of evidence also suggests that
36 neutrophils have the potential to gain phenotypic as well as functional properties
classically assigned to APCs [128, 129], and in the presence of cancer appose tumor
progression [114, 130] conversely given the appropriate signals, regulate tumor growth
[131-134]. These antagonistic populations of neutrophils referred to as N1—tumor inhibiting and N2—tumor promoting, probably exist as a dynamic array of activation states, rather than only two distinct populations [130, 135]. Additionally, neutrophils can form structures called NETs (neutrophils extracellular traps) which are involved in a process called NETosis—a contributor of innate immunity and induced or stimulated by infection, inflammation, trauma, cytokine production, activated platelets, autoantibodies and pathogens [136-140]. In recent years, NETosis has been identified as an additional
pathway of programmed cells death [141] during which nuclear chromatin relaxes and
forms fibrous web-like structures composed of DNA and histone associated granular
proteins [138, 142]. Therefore, it is of no surprise that these cells can also damage cells
and tissues of self (host), highlighting the importance of regulating genes functionally
responsible for these pathological occurrences [143, 144]. Regulation of neutrophil
function and differentiation in particular genes involved in the inflammatory responses
and chronic diseases, are mostly regulated at the transcriptional levels [145]; and subsequently an identification of factors involved in these processes would offer significant insight into the molecular mechanisms governing functional outcome. For number of years, regulation of normal and malignant hematopoiesis by epigenetic factors has shown to be an area of significant interest [146, 147]. Epigenetic changes in chromatin structure have been associated with the deregulation of critical genes in normal as well as malignant hematopoiesis [148, 149]. Histone deacetylases (HDACs)
37 alter chromatin by deacetylation of histone tails, resulting in transcriptionally inactive
chromatin [150]. HDAC inhibitors have also been identified to alter cytokine production profile [151], ultimately influencing the fate and expansion of hematopoietic cells [148,
152]. However, presently the exact role of specific HDACs in regulation of
hematopoietic processes is yet to be elucidated. Moreover, it has been demonstrated
that cytokine production by myeloid cells is regulated by changes in the acetylation
status of specific gene promoters [153, 154]. HDAC11 has been described as a negative regulator of IL-10 expression in myeloid cells [80]. Also, it has been shown that
lack of HDAC11 increases the suppressive capacity of myeloid derived suppressor cell
(MDSC) [155]. HDAC11, the most recently identified HDAC, is the sole member of the
Class IV HDAC sub-family [79]. The functional role of HDAC11 remains poorly
characterized. Initially it was believed that HDAC11 had a limited tissue expression
restricted to kidney, heart, brain, skeletal muscle, and testis [79]; but it has recently
been documented to also be expressed in hematopoietic cells, where it plays an integral
role in the regulation of immune tolerance through its action in antigen presenting cells,
However at the present time, its regulatory role in myeloid differentiation and specifically
neutrophil function is yet to be characterized. In this manuscript, we reveal a previously
unknown role of HDAC11 which may involve the regulation of neutrophil function. Here
we demonstrate that expression of HDAC11 correlates with neutrophil maturation,
migration, and phagocytic function. We also show that HDAC11 may be involved in the
transcriptional machinery of IL-6, TNF-alpha, and CXCR2/CXCL2.
38 2.4 Material and Methods
2.4.1 Mice and cell lines: C57BL/6 wild-type mice were purchased from Charles
River laboratories, Tg-HDAC11-eGFP reporter mice [156] were provided by Nathaniel
Heintz through the Mutant Mouse Regional Centers, and HDAC11KO kindly supplied by
Merck and obtained from Dr. Seto’s lab respectively. All strains of mice were housed in
the same designated room at the animal facility (Stabile Research-Moffitt Cancer
Center), were kept in pathogen-free condition, and handled in accordance with the
requirements of the Guideline for Animal Experiments. HL60 acute promyelocytic
leukemia (APL) cell line was purchased from American Type Culture Collection (ATCC)
and cultured and maintained in RPMI with 10% FBS, at 5%CO2 and 37°C. Aging
HDAC11KO and C57BL/6 wild-type mice were housed in the same room, under
identical conditions (mentioned above) for 18 months (n=5/group and strain).
2.4.2 Quantitative Reverse Transcriptase-Polymerase Chain Reaction (qRT-
PCR): Total RNA was prepared from centrifugally pelleted and pre-sorted cells (RNeasy mini columns and RNAse free DNAse, Qiagen, Valencia, CA). cDNA was prepared using iScript cDNA Synthesis Kit (Bio-Rad) and qRT-PCR reactions were conducted using the SYBR green two-step qRT-PCR (Bio-Rad) with transcript-specific primers
(Supplied upon request) and cDNA from samples as templates. qRT-PCR amplification reactions were resolved on CFX iCycler (Bio-Rad) and fold changes were quantified (2 -
C t ) [157]. Primers used TNF-alpha Forward (CCGATGGGTTGTACCTTGTC)
39 Reverse (AGATAGCAAATCGGCTGACG), IL-6 Forward
CCGGAGAGGAGACTTCACAG) Reverse (TCCACGTTTCCCAGAGAAC), 18s Forward
(GTAACCCGTTGAACCCCATT) Reverse (CCGTCCAATCGGTAGTAGCG), CXCL2
Forward (TCCAGAGCTTGAGCGTGACG) Reverse (TTCAGGGTCAAGGCAAACTT),
CXCR2 Forward (TCTGCTACGGGTTCACACTG) Reverse
(ACAAGGACGACAGCGAAGAT).
2.4.3 Flow Cytometry: Flow cytometric analysis of bone marrow aspirates was performed using fluorochrome-labeled monoclonal antibodies (mAbs; anti-CD3, -CD4, -
CD8, -CD19, -NK1.1, -CD11b, -Ly6G, -CD45, -CD117, -CD127, -CD11C, -Ly6G)
Becton Dickinson, San Jose, CA and eBiosciences, San Diego, CA) and the vitality dye
4',6-diamidino-2-phenylindole (DAPI, Sigma). Data was acquired on an LSRII cytometer (Beckman Coulter), at least 10,000 events, of the smallest population of interest, were collected using an LSR II (BD) and subsequently analyzed using Kaluza
(BD) and FlowJo software 10.0.07r2 (TreeStar). Annexin V Flow cytometry was performed utilizing BD’s LSRII flow cytometer using purified peritoneal neutrophils from wild-type C57/BL6 and HDAC11KO mice. A FITC conjugated Annexin V antibody and the DNA dye Propidium Iodide were used in conjunction with FACS buffer containing and Ca/Mg. Gates were created for the analysis of Apoptotic, Viable and Dead cells from total cells. Data was collected to a limit of 10,000 events of the population of interest.
40 2.4.4 Immunoblotting: The cells were lysed in a lysis-buffer containing 50 mM
Tris, 280 mM NaCl, HCL PH 8.0, 0.5% Igepal, 5 mM MgCl2, 10% glycerol and 10X
protease inhibitor (Roche), phosphatase inhibitor (Santa Cruz Biotechnology). Next ,
lysates were sonicated for 8 min (on ice---for 2 cycles of 30s on, 30s rest) and then mixed with 4× gel loading buffer and boiled for 10 min. Samples were then resolved on
10% gels and transferred to nitrocellulose membranes. Membranes were blocked with
5% milk-PBS-Tween. Bands were detected by scanning blots with an LI-COR Odyssey imaging system. Anti-GAPDH (68795) was purchased from Sigma Aldrich. Anti-b-actin
(sc-47778) was purchased from Santa Cruz Biotechnology. Anti-HDAC11 (3611P-100)
was purchased from BioVision Incorporated.
2.4.5 Harvesting and in vitro culturing of mouse peritoneal neutrophils:
C57BL/6 wild-type or HDAC11KO mice (8 weeks old, female) were injected
intraperitoneally (ip) with 1 mL sterile 5% Thioglycollate solution (BD). Mice were
euthanized and peritoneal cavity was flushed immediately. The cavity was flushed with
10 mL ice-cold RPMI-1640 medium (HyClone). Cells from the initial wash were pelleted
and neutrophils were positively selected using biotin anti-mouse Ly-6G antibody
(127604, Biolegend) and Mouse Biotin Selection Kit (EasySep, Stemcell Technologies).
The peritoneal neutrophils were cultured in 6-well (5 × 106 cell/mL) plates, in complete
RPMI-1640 medium in presence of 10% fetal bovine serum (HyClone) and 1% Penicillin
Streptomycin (Corning), stimulated with 2.5 µg/mL Lipopolysaccharides (LPS) (L2880,
Sigma). The purity of the peritoneal neutrophils was about 90% after selection.
41 2.4.6 Migration assay analysis: Medium (25 µL) (control Medium) containing serum-free medium or chemokine MIP2 (10 µg/mL) was loaded into the lower chambers of Transwell system. 50 µL of cells suspension (1×106/mL or 2×106 /mL) in 10 % FBS
RPMI 1640 medium was added to the upper compartment of the chemotaxis chamber.
The two compartments were separated by a 5-µM pore size polycarbonate filter.
Spontaneous migration was determined as the movement of cells toward the control
medium.
2.4.7 Chromatin Immunoprecipitation: Mouse peritoneal neutrophils (PNs)
(3×107) were cross-linked with 1% formaldehyde (F8775-25ML, Sigma) for 10 minutes
at room temperature. Then the cross-linking was stopped by 0.125 M glycine for 10
minutes at room temperature. The cells were washed twice with PBS and proceed with
sample preparation. The cell pellet was lysed by 1 mL of lyse buffer (50 mM HEPES pH
7.8, 3 mM MgCl2, 20 mM KCl, 0.25% Triton X-100, 0.5% NP-40) on ice for 10 minutes.
The cell lysate was transferred to a “Dounce Homogenizer” and 25 strokes were applied using the loose pestle A. The cell pellet was washed once with 1 mL wash buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA, 200 mM NaCl). The pellet was resuspended in 600 uL sonication buffer (50 mM HEPES pH 7.8, 140 mM NaCl, 1 mM EDTA, 0.5% SDS,
1% Triton X-100). The samples were sonicated and centrifuged for 10 minutes. The lysate was diluted at 1:10 to dilution buffer I (50 mM HEPES pH 7.8, 140 mM NaCl,
1mM EDTA, 1% Triton X-100), pre-cleared using Protein A Agarose beads (16-156,
Millipore), incubated with rabbit anti-HDAC-11 antibody cocktail (3611P, BioVision and
H4539-200UL, Sigma) on a rotator at 4°C overnight. Biotin-conjugated normal rabbit
IgG-B (SC-2763, Santa Cruz Biotechnology) was added at the same amount of rabbit
42 anti-HDAC-11 antibody cocktail in parallel of each sample and incubated on a rotator at
4°C overnight. Then 50 µL protein A Agarose beads was applied to each sample and incubated at 4°C for 4 hours. The beads were then washed twice each with dilution buffer I, dilution buffer II (50 mM HEPES pH 7.8, 500 mM NaCl, 1 mM EDTA, 1% Triton
X-100), LiCL buffer (20 mM Tris-HCl pH 8.0, 250 mM LiCl, 1 mM EDTA, 0.5% Triton X-
100), and TE buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA). Then the beads were eluted
in 100 µl elution buffer (50 mM Tris-HCl pH 8.0, 1 mM EDTA, 1% SDS) and incubated
at 65°C for 15 minutes and the immunocomplexes were collected in the soluble fraction.
NaCl was added to a final concentration 200 mM and the crosslinking was reverted by
incubating at 65°C for overnight. Then RNAse A (158922, Qiagen) was added to 20
µg/mL to each sample and incubated at 37°C for 30 minutes. Proteinase K (EO0491,
Thermo Scientific) was then added at 100 µg/mL and incubated at 42°C for 2 hours.
DNA was purified by using QIAquick PCR Purification Kit (28104, Qiagen) and purified
DNA was eluted in 100 µL TE buffer for analysis by qRT-PCR. 2 µL of DNA was used
for each qRT-PCR reaction. The following PCR primers were used: TNF alpha Forward
(CTCGGAAAACTTCCTTGGTG), TNF alpha Reverse
(CGATGGAGAAGAAACCGAGA), IL-6 Forward (TCTGCAGAGTGAAGAAGCTGA), IL6
Reverse (GATTCCAGGCTGAAAGTAGGC), CXCL2 (MIP-2) Forward
(GGCTAGAACTGAGGGCTAC), CXCL2 (MIP-2) Reverse
(ACATCCATTCTTGTCCCACTG), CXCR2 Forward (CCTCTGACTCCCACACATCT),
CXCR2 Reverse (GCTTGCTGTGCTTTTGGTTT).
2.4.8 Phagocytosis assay: Upon euthanasia, 1mL of blood was obtained from an experimental mouse via cardiac puncture with a heparinized syringe. Blood was
43 centrifuged at 2,000 RPM for 2 minutes in a microcentrifuge tube and Sera was
aspirated and added to a single tube of lyophilized pHrodo Red E. coli BioParticles (Life
technologies). The BioParticles were vortexed and then incubated for 30 minutes in a
37ºC water bath for optimal opsoninization. BioParticles were centrifuged at 2,000 RPM
for 2 minutes and washed twice with PBS (pH 7.4) w/o Ca and Mg and resuspended in
2 mL of RPMI with 10% FBS. Purified neutrophils were resuspended at 1 x 106 cells per
mL and plated at 100 µL per well, in quadruplicate, in a 96 well flat bottom TC treated
plate per mouse. BioParticles were added to the plate immediately before being placed
into Incucyte High Throughput Live Cell Microscope System for detection of red
fluorescent protein (RFP) expression.
2.4.9 Incucyte real-time microscopy analysis: Cells in a 96 well plate were
imaged through a 10× objective lens at 5 minute intervals for 3 hours using the Incucyte
Zoom HD live cell imaging system (Essen Bioscience, Michigan, USA). The system is
located in a 37ºC /5% CO2 cell culture incubator to maintain proper incubation
conditions. Analysis was performed using the default red fluorescence processing
definition within the Incucyte Zoom 2014B software. The number of red cells and
confluency of red fluorescence was extracted from the images and export the excel
format.
2.4.10 Cytometric Bead Array: This assay involves measurement of secreted cytokines in the media by flow cytometry. Briefly, 100 µL of supernatant from cells
stimulated with or without LPS were collected as specific time-points and IL-6 and TNF-
alpha levels were measured following manufactures recommended protocol CBA kitTM;
(BD Biosciences, San Jose, Ca).
44 2.4.11 Sepsis model: C57BL/6 wild-type and HDAC11KO mice were injected
with 15 mg/Kg of LPS (L4391-1MG Sigma) via tail vein (TV) in 100 µL volume and
observed for signs of sepsis (abnormal posture/positioning, partial paralysis, failure to
respond to stimuli, head tilt, circling, impaired locomotion, non-purposeful movement,
hypoactivity, hyperactivity, restlessness, self-trauma, aggressiveness, isolation from
cage mates, shallow, rapid and/or labored breathing, cyanosis, piloerection, matted hair
coat, lack of inquisitiveness, hunched posture and/or vocalizations) 3 times daily.
2.4.12 RACE analysis: This experiment was out-sourced to murine genetic analysis laboratory, mouse biology program at University of California, Davis. Detailed protocol will be provided upon request.
2.4.13 Statistical Analysis: Unless otherwise specified, the statistical significance between values was determined by student’s t test. Data were expressed as the mean ± SD. Probability values of p ≤ 0.05 were considered significant.
2.5 Results
2.5.1 HDAC11 is differentially expressed in various stages of myeloid
differentiation
It has previously been reported that HDAC11 is a negative regulator of IL-10 production in myeloid cells. Here, we examined the expression of HDAC11 in myelopoiesis. To follow the dynamic changes in HDAC11 transcriptional activation, we utilized HDAC11 promoter-driven eGFP reporter mice (Tg-HDAC11-eGFP) [156], where
45 eGFP expression is indicative of HDAC11 transcription. Using multiparameter flow
cytometric analysis, as seen in Figure 2.1A, in the bone marrow compartment, we were
able to determine that expression of HDAC11 is markedly increased in promyelocytes
when compared to earlier progenitors and further amplified in the neutrophils when
compared to myeloblasts. Interestingly, expression eGFP and consequently of
HDAC11 in monocytes was negligible when compared to promyelocytes and
neutrophils (Figure 2.1A). The lymphocytes also show a moderate expression of
HDAC11 transcript. Expression of HDAC11 protein was confirmed by immunoblotting
analysis in flow-sorted monocytes, promyelocytes and neutrophils (Figure 2.1B top
panel). Quantitative mRNA analysis confirmed our findings by demonstrating an
increase in the expression HDAC11 message (fold changes are normalized to the 18s
house-keeping gene for each sample) and further validated the Tg-HDAC11-eGFP
reporter mouse model (Figure 2.1B lower panel) used in our experiments. Additionally,
we further validated these results by quantifying the mRNA expression of eGFP in the
same samples and were able to demonstrate that expression of HDAC11 is
concomitant with the expression of eGFP message (Figure 2.1C). To ensure that our
data was not an artifact of the eGFP reporter mouse model, we flow-sorted monocytes, promyelocytes, neutrophils, and lymphocytes from a C57BL/6 wild-type mouse and examined the expression of HDAC11 message (Figure 2.1D). The results confirmed our
previous findings in the Tg-HDAC11-eGFP reporter mouse and consequently the
neutrophil population expressed significantly higher levels of HDAC11 when compared
to the rest of the sub-populations. Next, we purchased source leukocytes (OneBlood,
Florida Blood bank) collected from volunteer normal donors and isolated (flow-sorted
46 cell populations) monocytes and neutrophils. Quantification of HDAC11 expression
observed in this figure show parallel results mirroring what we had previously seen in
our murine models where neutrophils had higher expression of HDAC11 message
(Figure 2.1E lower panel). Immunoblotting analysis confirmed the expression of
HDAC11 in the neutrophils when compared to the monocyte population (Figure 2.1E top
panel).
Figure 2.1 HDAC11 message is differentially expressed in various stages of myelopoiesis. (A) Dynamic visualization of HDAC11 message using HDAC11-eGFP transgenic mouse in myeloid compartments. Bone marrow was extracted from Tg- HDAC11-eGFP (As well as CD57B/6 mice as control- non-eGFP expressing cells; gray histogram markings) and cells were labeled (as indicated above) with specific cell surface markers for identification of each population. HDAC11 expression was determined by flow cytometry analysis of eGFP reporter gene expression, where the
47 expression of eGFP protein corresponds to the activation of HDAC11 transcriptional machinery. (Representative presentation from 2 individual experiments) (B) Monocytes, promyelocytes, and neutrophils from Tg-HDAC11-eGFP mouse bone marrow cells were sorted using FACS-Aria (BD) device with 99% purity. Cells were lysed using TriZoL reagent (Invitrogen) as well as RIPA buffer (Cell Signaling) and RNA as well as protein was extracted respectively. Immunoblotting was performed using 10% SDS gel and image was resolved using Dura ECL reagent (Pierce) (Top image) and qRT-PCR analysis was performed using HDAC11 primers (bottom graph). Sorted cell populations were also morphologically confirmed (Lower panel). (C) Co-expression of HDAC11 message and eGFP message was confirmed by qRT-PCR using eGFP primers. (Error bars = S.E.M; data representative of 3 individual experiments n=3) (D) Monocytes, promyelocytes, neutrophils, B-cells, and T cells were sorted from C57BL/6 wild-type mouse bone marrow cells using FACS-Aria (BD) device with 98% purity. Cells were lysed using TriZoL reagent (Invitrogen) and RNA was extracted. qRT-PCR analysis was performed using HDAC11 primer. This was done to confirm HDAC11 expression profile in a non-transgenic setting. (Error bars = S.E.M; data representative figure from 3 individual experiments n=3). (E) Four normal human donor peripheral blood source leukocyte samples (Purchased from OneBlood Florida) were sorted for monocytic and neutrophylic populations using FACS-Aria (BD) device with 96% purity and then examined for the expression of HDAC11 message using qRT-PCR analysis and the fold change between neutrophils and monocytes were normalized to the lowest expressing monocytic population. (Error bars = S.E.M, n=4) Note: In figures B, C, D, and E sub- populations were compared and normalized to monocytes (Since they have the lowest expression of HDAC11).
2.5.2 Expression of HDAC11 is significantly increased in leukemic cells
upon differentiation
Utilizing HL60 acute promyelocytic leukemia (APL) cell line model and upon in vitro maturation and differentiation of these cells using all trans-retinoic acid (ATRA) stimulation, we observed an increase in the expression of HDAC11 message (Figure
2.2A bottom) and protein (Figure 2.2A top) as demonstrated. These differentiated HL60 cells also exhibited neutrophil-like segmentation and over-expression of maturation markers such as CD11b, and myeloperoxidase (MPO) (Figure 2.2B).
48 Figure 2.2 Expression of HDAC11 in acute promyelocytic leukemia samples (APL) and functional consequences of its manipulation in this model. (A) HL60 cells were treated with All Trans Retinoic Acid (ATRA) for 72hrs and the expression of HDAC11 message was measured by qRT-PCR and the differentiation of HL60 cells to granulocytic-like cells were examined by morphological analysis (Left) Error bars = S.E.M; (Representative figure from 3 individual experiments) . (B) The differentiation of HL60 cells to granulocytic-like cells were examined using Myeloperoxidase (MPO-a marker for cell’s gain of granularity) (Top) as well as CD11b expression (Bottom). (Representative figure from 3 individual experiments).
2.5.3 Lack of HDAC11 markedly increases the expression of pro-
inflammatory cytokines
HDAC11 is restricted mainly to the nucleus, and its expression appears to be tissue specific with higher expression in brain, heart, testis, and skeletal muscle [79],
however its precise function in myeloid compartment and specifically in the neutrophils
49 is yet to be elucidated. In the previous experiments, we utilized germ-line HDAC11
knock-out mice (HDAC11KO) (Merck Pharmaceutical). HDAC11KO (C57BL/6
background) mice were developed using Lox/CRE technology to remove a floxed exon
3, a portion of the histone deacetylase catalytic region. In our Figure 2.3A, we
demonstrate our method of positively genotyping the HDAC11KO mice. Since these
mice will still transcribe a truncated mRNA sequence (excluding exon3), and to further
validate this mouse model, we designed a special HDAC11 primer set that was within
the excised exon3 region of HDAC11 gene. As seen in supplementary figure,
HDAC11KO mice have no amplified HDAC11 amplicons demonstrated by qRT-PCR
analysis when compared to C57BL/6 wild-type counterparts (Figure 2.3B). Also,
immunoblotting analysis suggested that the expression of HDAC11 is absent in cells
isolated from HDAC11KO mice (Figure 2.3C). Taking a step further, we sent samples
from two C57BL/6 wild-type and two HDACK11KO mice to Murine Genetic Analysis
Laboratory (MGAL), Mouse Biology Program at University of California, Davis for Rapid
Amplification of cDNA ends (RACE-Seq). The data confirmed that the HDAC11KO mice are devoid of exon3 on the HDAC11 gene sequence.
Recently, it has been demonstrated that epigenetic factors such as HDACs have
been known to affect regulation of genes involved in inflammatory responses [158].
Subsequently, we decided to investigate whether lack of HDAC11 had any functional
consequences in the neutrophil population. To do this, we isolated peritoneal
neutrophils (PNs) from both HDAC11KO as well as C57BL/6 wild-type mice; 18 hours
post 5% thioglycollate injection. In vitro, cells were treated with 2.5 µg/mL of
50
Figure 2.3 (A) Schematic representation of HDAC11KO mouse development and genotyping methods for proper identification of mouse colony. (B) qRT-PCR analysis of HDAC11 expression (using exon3-designed primers) in brain and spleen of C57BL/6 wild-type and HDAC 11KO mice (n=3). (C) Expression of HDAC11 protein in brain and testes of C57BL/6 wild-type and HDAC 11KO mouse. lipopolysaccharide (LPS) for 2 and 4 hours and the samples were analyzed for TNF-
alpha and IL-6 message and protein expression. Results revealed that in the absence of
HDAC11, neutrophils became more inflammatory as seen by the mRNA expression
level of TNF-alpha and IL-6 at every time-point (Figure 2.4A). These findings were
further confirmed by cytometric bead array (CBA) protein analysis where both cytokines
51 showed higher level of expression when compared to the C57BL/6 wild-type
counterparts (Figure 2.4B). We were also interested to see whether lack of functional
HDAC11 changed the normal distribution of hematological cells in the peripheral blood.
Briefly we collected peripheral blood from HDAC11KO as well as their normal
counterparts C57BL/6 wild-type mice (sub-mandibular blood collection) and performed a
complete blood count (CBC) analysis. Surprisingly, both cohorts—HDAC11KO as well
as the C57BL/6 wild-type control mice had relatively similar monocytic and granulocytic
blood count profile (Figure 2.4C). To our knowledge thus far, there has been no report of HDAC11 binding directly to DNA and consequently, there are no direct downstream genes that can be signature indicators of this interaction. In experiments for this section we also interrogated the possibility of HDAC11 being involved in transcriptional regulation of these molecules. Briefly, PNs isolated from C57BL/6 wild-type mice were
treated with 2.5 µg/mL of LPS for 3.5 hours (the concentration and the time point for
these experiments were determined by dose titration and time course analysis in
preceding experiments) and then the cells were processed for Chromatin
immunoprecipitation (ChIP) assay. In Figure 2.4D, ChIP data suggests that HDAC11
may be recruited to the TNF-alpha and IL-6 transcriptional complex. To demonstrate
that this observation was specific to HDAC11 being possibly recruited to the promoter
region of TNF-alpha and IL-6, we performed a similar ChIP analysis in mice using
HDAC11KO PNs which showed no recruitment of HDAC11 to the promoter regions of
TNF-alpha and IL-6 interpreted by no change in the enrichment ratio when comparing
LPS stimulated samples to the non-stimulated controls (Figure 2.4E).
52 Figure 2.4 Phenotypic consequences of HDAC11 deficient peritoneal neutrophils. (A) Peritoneal neutrophils (PNs) from C57BL/6 wild-type and HDAC11KO mice were collected post thyoglycolate injection (5% at 18hrs). The cells were treated with 2.5 µg/mL of LPS for 2, and 4hrs. Expression of inflammatory genes TNF-alpha and IL-6 were measured by qRT-PCR. (B) Protein concentrations for TNF-alpha and IL-6 were measured by cytometric bead array (CBA) analysis. (C) Complete blood count from C57BL/6 wild-type and HDAC11KO (n=6 per group). (D) The recruitment of HDAC11 protein to chromatin fragments of TNF-alpha and IL-6 promoters were analyzed using the PfaffI method [157] and are presented relative to input before immunoprecipitation and the enrichment ratio was normalized to the IgG control (PNs isolated from C57BL/6 wild-type) (E) PNs isolated from HDAC11KO mice were used in another ChIP assay as negative control. (NT = No LPS incubation). (Error bars = S.E.M; data presented for each graph is a representative figure from 2 individual experiments).
2.5.4 Neutrophils isolated from mice lacking HDAC11 demonstrate much
higher migratory and phagocytic capacity
53 The hallmark of neutrophils in the innate immune system is their capacity to
migrate to the site of tissue injury and/or infection. In order to interrogate migratory
capacity of neutrophils lacking HDAC11, we isolated peritoneal neutrophils (as
mentioned in Figure 2.4) and performed a migration assay. Briefly, in this assay
isolated neutrophils were loaded in the upper compartment of the chemotaxis chamber,
and the serum-free media or chemokine CXCL2-(MIP-2—IL-8 homologue) (10 µg/mL) was loaded into the lower chambers of a transwell system, and the assay was concluded by detection and calculation of migratory neutrophils. The data suggests that neutrophils isolated from the HDAC11KO mice have a significantly higher migratory capacity towards a bait chemokine MIP-2 when compared to the wild-type counterpart
(Figure 2.5A). Next we compared the expression of migratory receptor/chemokines such as CXCR2 (Homologue of IL-8 receptor beta) /CXCL2, in HDAC11KO and
C57BL/6 wild-type mice. In Figure 2.5B we demonstrate a higher endogenous expression of mRNA for these molecules in neutrophils lacking HDAC11. Flow cytometry analysis confirmed a significant increase in the protein level of CXCR2 on
HDAC11KO neutrophils when compared to the C57B/6 wild-type mice (Figure 2.5C), however the changes in the CXCL2 protein levels were not significant (data not shown).
Furthermore we assessed the phagocytic ability of C57BL/6 wild-type versus
HDAC11KO mouse PNs. Briefly, equal number of PNs from C57BL/6 wild-type and
HDAC11KO mice were co-cultured with E. coli BioParticles loaded with a pH sensitive fluorescent dye. Using live microscopy, we were able to (in real-time) monitor phagocytic capacity of PNs from each mice. Data ascertained from these experiments demonstrated that PNs from the HDAC11KO mice were functionally more potent
54 Figure 2.5 Enhanced migratory and phagocytic capacity of HDAC11KO neutrophils. (A) Migration assay analysis between C57BL/6 wild-type and HDAC11KO PNs utilizing the Transwell system and 2 x 106 per sample. Expression of migratory genes were analyzed in PNs isolated from the WT and HDAC11KO mice using qRT-PCR analysis (Data generated from 4 individual experiments) **p-value < 0.01, * p-value < 0.05. (B) mRNA expression of CXCL2 and CXCR2 were analyzed in both C57BL/6 wild-type and HDAC11KO mice at steady state. (Representative figure from 2 individual experiments). (C) Expression of surface CXCR2 protein on neutrophils from HDAC11KO vs C47BL/6 wild-type mice. (D) Phagocytic ability of PNs isolated from both C57BL/6 wild-type and HDAC11KO mice were analyzed in the presence of E. coli Bio-Particles loaded with a pH sensitive fluorescent dye and analyzed as a measure of cell engulfment and lysis in real-time (RFP measurement by microscopy). (Error bars = S.E.M; statistical analysis was done using two-way ANOVA **p-value < 0.01, * p-value < 0.05. Data presented is a representative figure from 2 individual experiments). (E) The recruitment of HDAC11
55 protein to chromatin fragments of CXCL2 and CXCR2 promoters was analyzed in the presence and absence of LPS stimulation. (F) PNs from HDAC11KO mice were used in another ChIP assay as negative control. The values obtained for these ChIP experiments were analyzed using the PfaffI method [157] and are presented relative to input before immunoprecipitation and the enrichment ratio was normalized to the IgG control. (Error bars = S.E.M; representative figure from 2 individual experiments, three animals were used for each experiment).
(Figure 2.5D). Given our findings discussed in the above experiments, it was deemed necessary to determine if there HDAC11 was being recruited to the promoters of
CXCR2 and CXCL2. Given our presented data so far, we predict that HDAC11 may be a negative regulator of genes involved in migratory response. To examine this hypothesis, we performed a ChIP analysis. Briefly, PNs from C57BL/6 wild-type mice were treated with 2.5 µg/mL of LPS for 3.5 hours and then the cells were processed for
ChIP assay. The data indicates that there is recruitment of HDAC11 to the promoter regions of CXCR2 and CXCL2 (Figure 2.5E). To demonstrate that this observation was specific to HDAC11, we performed a similar ChIP analysis using HDAC11KO PNs which showed no change in the enrichment ratio when comparing LPS stimulated samples to the non-stimulated controls. The observed recruitment of HDAC11 to the promoter regions is not defined as a direct biding of HDAC11 to the promoter regions however, the interrogation of this possibility requires additional and in depth promoter binding analysis in the future.
2.5.5 HDAC11KO mice are more susceptible to LPS induced sepsis when
compared to C57BL/6 wild-type counterpart
Sepsis in humans, defined as severe inflammation in the presence of infection, is a common syndrome that kills thousands of patients each year [159]. To study this
56 physiological response, murine models have been established and validated. For instance, in intoxication models mice are inoculated with proinflammatory compounds(noninfections) such as lipopolisaccharides (LPS) [160]. Of note, mice are extremely resilient to most types of inflammation when compared to humans, but at high doses of LPS within the range of 1-25 mg/kg (1000-10000 X the dose that will cause septic shock in humans), mice experience severe inflammatory response and eventually succumb to sepsis [161, 162]. Given our observations thus far, it appears that
HDAC11KO PNs, at steady state, have a higher innate inflammatory nature when compared to the C57BL/6 wild-type mice. Therefore, we sought to investigate whether there was a difference between the time of inflammatory onset, leading to eventual sepsis and death (post LPS inoculation), when comparing HDAC11KO and C57BL/6 wild-type mice. Briefly, a cohort of HDAC11KO and age matched C57BL/6 wild-type mice (n=8 in each group), were injected with LPS at 15 mg/kg via tail vein. Mice were monitored 3 times in 24hrs. As seen in Figure 2.6, although all mice post LPS inoculation showed signs of fatigue and sluggish movements, HDAC11KO mice expired within the first 48hrs of the experiment while the remaining C57BL/6 wild-type mice fully recovered and were ultimately euthanized at 72hr time-point to mark the termination of the experiment.
57 Figure 2.6 Septic shock experiment comparing HDAC11KO mice and C56BL/6 mice. A cohort (n=8) of HDAC11KO and C57BL/6 mice were injected with 15 mg/kg of LPS via tail vein. Survival graph representing both groups in time-line up to 72 hours. (Data presented is a representative figure from 2 individual experiments).
2.5.6 HDAC11KO mice show bone marrow hypercellularity with
granulocytic expansion and splenomegaly due to increased extramedullary
hematopoiesis
58 Emergency granulopoiesis is defined as a well-coordinated de novo production of
neutrophils due to increased myeloid progenitor cells proliferating in the bone marrow,
signaled by and during severe infection. The ultimate goal of this physiological
occurrence is to increase the neutrophil output during an innate immune response. In
order to see whether HDAC11KO mice had a more robust production of neutrophils, we
injected (i.p.) a cohort of HDAC11KO and C57BL/6 wild-type mice with Freund’s
complete adjuvant (Thermo Scientific) and assessed the expression of granular cells by
flow cytometry. Flow cytometery analysis revealed a moderate increase of granular
cells in the spleen of the HDAC11KO mice when compared to the C57BL/6 wild-type mice however this difference was not significant. Immunohistochemisty (IHC) and H&E staining of bone marrow cells from the same mice demonstrated extensive hypercelullarity which did not allow decisive identification and quantification of granular cells (data not shown). However, when we compared spleen sections from aging
(18months old) HDAC11KO and C57BL/6 wild-type mice, we observed that the
HDAC11KO spleens had increased extramedullary hematopoiesis resulting in an expanded red pulp (figure 2.7A). In addition, sections from femoral bones revealed a marked bone marrow hypercellularity on aging HDAC11KO mice, mostly due to an expansion of maturing neutrophils (figure 2.7B).
59 Figure 2.7 Observation of splenomegaly as well as Hypercellularity with granulocytic expansion in BM of HDAC11KO mice. (A) Representative sections of spleens (H&E stain) harvested from aged C57BL/6 wild-type (top) and HDAC11 KO (bottom) mice showing a marked expansion of the red pulp (left, x40), due to replacement of the mostly lymphocytic red pulp cellularity observed on C57BL/6 wild-type mice with mostly trilinegae extramedullary hematopoiesis on the HDAC11KO mice (right, x400). (B) Representative sections of femurs (H&E stain) harvested from aged C57BL/6 wild-type (top) and HDAC11 KO (bottom) mice showing a marked increase in the bone marrow cellularity on HDAC11KO mice compared to WT mice (left, x20), mostly due to an expansion on maturing neutrophils (right, x200). (n=5 per group)
60 2.6 Discussion
In myelopoiesis, lineage-specific transcription factors C/EBPα, C/EBPε, PU.1,
and AML1 cooperatively interact with specific DNA sequence response elements to
initiate transcription of genes involved in differentiation [121, 163-165]. More recently, epigenetic mechanisms such as chromatin modification by acetylation/deacetylation of histone tails have been shown to contribute to the regulation of gene expression and determination of cell population specificity [166, 167]. Conversely, it has been demonstrated that the deregulation of epigenetic mechanisms cause genetic alterations which consequently leads to manifestation of diseases such as cancer and autoimmunity [102, 168]. More specifically, epigenetic modulations have been reports in number of cellular processes involved in neutrophil development and functions
(reviewed in [147]) including NETosis [169].
In this report, the interrogation of the transcriptional activity of HDAC11 in myeloid and lymphoid cells, utilizing a HDAC11 promoter-driven eGFP reporter mouse model, combined with utilization of lineage-specific markers with multiparametric flow cytometry analysis demonstrated a significant over-expression of HDAC11 in neutrophils, when compared to monocytes (Figure 2.1A). Moreover, analysis of hematopoietic cells isolated from the bone marrow of the Tg-HDAC11-eGFP mice revealed an over-expression of HDAC11 at the promyelocyte stage of neutrophil differentiation and with a significant increase in the neutrophils. Monocytes showed low to undetectable expression of HDAC11 (Figure 2.1B & C). Additionally, our results utilizing flow-sorted leukocyte subpopulations from C57BL/6 wild-type mouse bone marrow, further confirmed and demonstrated a higher level of HDAC11 expression in
61 promyelocytes and neutrophils compared to monocytes and lymphoid subsets (Figure
2.1D). Equally, flow-sorted monocytes and neutrophils from normal human donors’ source leukocytes showed higher levels of HDAC11 expression in neutrophils, as compared to monocyte population (Figure 2.1E). These findings are of interest because they suggest that HDAC11 may be a factor during myelopoiesis and consequently play a role in the fate of neutrophils. Epigenetic mechanisms such as histone modifications play a key role in the control of multiple normal biological processes including hematopoiesis as well as alterations leading to many diseases such as autoimmunity and cancer [170, 171]. Understanding the role of each specific HDAC in the context of the immune system, in different malignancies, will facilitate selective cancer immunotherapeutic modalities. Therefore we further examined HDAC11 in a cancer model to determine whether this lineage-specific overexpression also applied to malignancies using HL60 acute promyelocytic leukemia (APL) human cell line. Our findings supported what we had seen in normal processes. Upon in vitro ATRA induced differentiation and maturation of APL cells, expression of HDAC11 is increased exponentially (Figure 2.2A). Concurrently the expression MPO and CD11b (markers of granularization and) were increased (Figure 2.2B) during maturation of APL cells. The exploration of the physiologic role of HDAC11 overexpression in neutrophils, utilizing a model of germline-HDAC11KO mice demonstrated that purified neutrophils lacking
HDAC11 displayed an apparent overproduction of TNF-alpha and IL-6 upon stimulation with LPS both at message and protein levels, as compared to their C57BL/6 wild-type counterparts (Figure 2.4A & B). Our assessment of these collective data suggests that
HDAC11 may be playing the role of a check-point molecule; where it possibly controls
62 the activation of neutrophils. Moreover, subsequent data suggests that HDAC11 may
be associated with the transcriptional machinery of inflammatory molecules TNF-alpha and IL-6 as seen by HDAC11-chromatin binding which was demonstrated by ChIP analysis (Figure 2.4D & E). Recently, Stammler, et al reported that HDAC11 inhibition increases IL-1b in dendritic cells and macrophages through promoting nonanonical caspase-8-dependent pathway [172]. In our experiments, ChIP analysis revealed that
HDAC11 –chromatin binding is distinctive to TNF-alpha and IL-6 and no binding was observed for IL-1b (IL-1b data not sown). Markedly, migration assay analysis also demonstrated that neutrophils isolated from HDAC11KO mice exhibit a significantly higher migratory rate as well as increased phagocytic activity when compared to the
C57BL/6 wild-type mice (Figure 2.5A). This observation is highlighted by qRT-PCR analysis that showed HDAC11KO mice demonstrate an endogenous over-expression of
CXCR2 and CXCL2 genes (Figure 2.5B & C). Moreover, ChIP analysis results suggest that HDAC11 may also be recruited to the transcription complex, regulating the transcription machinery of CXCR2 and CXCL2 (Figure 2.5E & F). Recently published data suggests that HDAC11 has functional network protein association with number of biological processes including gene expression [173], therefore highlighting the possibility of its involvement in regulating transcription which is yet to be determined.
Typically, occurrence of severe sepsis also known as septic shock is fatal from complications of infection, usually caused by dysregulated inflammatory and immune responses. The onset of sepsis is generally due to a robust innate immune response, through enhanced granulopoiesis in the bone marrow and generation of exuberant number of neutrophils, and consequently a massive production of pro-inflammatory
63 cytokines [174]. Sepsis remains a serious health issue and therefore identification of factors contributing to it is of great interest. Thus far, numerous studies have labeled pan-HDAC inhibitors fundamentally as negative regulators of gene expression for acute immune receptors and pathways in innate immune cells [175, 176]. However oversimplifying this statement cannot be generally correct since HDAC inhibitors depending on tissue type and time of treatment, can have alternative effects on gene expression. Consequently, numerous investigators are now focusing on selective HDAC inhibitors to narrow the target of interest. In regards to HDAC11, our observations suggest that this HDAC maybe a gatekeeper of inflammatory response in neutrophils. In fact, in a murine sepsis model, we were able to show that HDAC11KO mice succumb to sepsis much faster than the C57BL/6 wild-type counterparts (Figure 2.6) suggesting the
possible presence of pre-primed neutrophils in HDAC11KO mice. Additionally, CellTiter-
Blue® viability assay demonstrated a modest decrease in the number of neutrophils
(isolated from the BM) extracted from HDAC11KO mice in the absence of stimulation
when compared to the C57BL/6 wild-type counterpart however, a significant decrease in
the viability of neutrophils isolated from the HDAC11KO mice was observed when these
cells were stimulated with GM-CSF, compared to C57BL/6 wild-type counterparts
(Figure 2.8). Moreover, in aging HDAC11KO mouse experiment we observed
noticeable increase in the bone marrow cellularity when compared to age-matched
C57BL/6 wild-type controls mice, which is mostly due to an expansion of maturing neutrophils (Figure 2.7). This is indicative of what we have demonstrated—signifying the likelihood of an essential role for HDAC11 in neutrophil biology.
64
Figure 2.8 BM cells from the femurs of age-matched WT (C57BL/6) and/or HDAC11KO (C57BL/6) mice (n=4/ mouse strain) were extracted and neutrophils from these samples were isolated using the StemCell™ EasySep magnetic selection kit. Each sample was plated at equal numbers in triplicates in a 96-well plate. Cells were then treated (or not in the control groups) with 50ng/ml of mouse GM-CSF for 9 hours. Next CellTiter-Blue® reagent was added to each well and incubated at 37C for 1 hour following by the measurement of fluorescent signal at 560(20)Ex/590(10)Em using a BioTek Cytation 3 plate reader. (Data is a representative graph from 2 independent experiments).
In recent years, the role of neutrophils has significantly expanded from front-line
combatants of infection to endowment of anti-tumor immunity [177, 178]. In contrast,
recent evidence suggests a novel pro-tumor function for these cells [124, 179],
suggesting complex and opposing roles of neutrophils in a tumor setting. Such
observations continue to highlight the importance of identifying factors that may play
65 essential roles in neutrophil activation and function. In conclusion, our data suggests
that HDAC11 appears to have a dual function in neutrophils biology; 1) HDAC11 is increased as neutrophils differentiate and mature, and 2) decrease in HDAC11 correlates with functional activity of neutrophils. Our studies reveal that HDAC11 plays a
role in neutrophil chemokine and cytokine biology and function. Given the multifaceted
function of neutrophils, the key findings described here will potentially lead to targeted
epigenetic therapies to influence diseases involving neutrophils.
66
Chapter 3: HDAC11 Function as a Transcriptional Regulator in Immature Myeloid
Cells (IMCs) to Myeloid-derived Suppressor Cells (MDSCs) transition
3.1 List of Abbreviation
APCs: Antigen Presenting Cells
ATCC: American Type Culture Collection
C/EBPβ: CCAAT-enhancer-binding protein beta
ChIP: Chromatin Immunoprecipitation
DCs: Dendritic Cells
FBS: Fetal Bovine Serum
HDACs: Histone Deacetylases
HDAC11: Histone Deacetylase 11
HDAC11KO: HDAC11 Knock-out
IL-1b: Interleukin-1 beta
IL-6: Interleukin-6
IMCs: Immature Myeloid Cells
67 iNOS: Inducible Nitric Oxide Synthetase
IP: Intraperitoneally
IV: Intravenous
LPS: Lipopolysaccharides
MDSCs: Myeloid-derived Suppressor Cells mRNA: Messenger RNA
NO: Nitric Oxide
PBS: Phosphate Buffered Saline qRT-PCR: Quantitative Reverse Transcriptase-polymerase Chain Reaction
WT: Wild-type
3.2 Abstract
Myeloid-derived suppressor cells constitute a heterogeneous population of immature myeloid cells derived from bone marrow and possess the ability to negatively regulate both innate and adaptive immunity in the tumor microenvironment in large scale solid tumor settings. Previous work in our lab had demonstrated that MDSCs lacking histone deacetylase 11 (HDAC11), a newly identified member of the HDAC family, revealed an increase in suppressive ability against CD8+ T cell cytotoxicity.
However, the mechanisms of HDAC11 that contribute to the suppressive function of
68 MDSCs remain unclear. In this study, we have evaluated a number of factors implicated in MDSCs-mediated immune suppression, such as arginase activity, NO and ROS production. Our data suggest that arginase activity and NO production is significantly higher in HDAC11 knockout MDSCs when compared with C57BL/6 wild type control.
Acquisition of this elevated suppressive function in HDAC11 KO MDSCs is possibly mediated through an up-regulation of transcription factor CCAAT-enhancer-binding protein beta (C/EBPβ). Also, we observed a markedly higher expression of C/EBPβ in
CD11b+ Gr1+ from HDAC11 KO animals under tumor challenge as well as at steady state. Additionally, our data showed that HDAC11 was recruited to the promoter region of C/EBPβ in wild-type MDSCs, suggesting that HDAC11 serves as a negative regulator of C/EBPβ.
3.3 Introduction
In both cancer patients and tumor bearing animals, the presence and progression of tumors often contribute to the development of immune dysfunction which introduces challenges and negative feedbacks to the development of immunotherapeutic strategies. Multiple cell types have been identified to regulate tumor mediated immune evasion and immunosuppression, including regulatory T cells [180], tumor associated macrophages and MDSCs . As one of the major cell populations that infiltrated into the tumor site, MDSCs are believed to involve largely with the unresponsiveness of antigen specific CD8+ T cells in the tumor microenvironment [181].
Recently, two major subsets of MDSCs have been identified based on their morphology
69 and surface markers expression: monocytic MDSC (M-MDSC) and granulocytic MDSC
(G-MDSC, also called polymorphonuclear PMN-MDSC) [35, 36]. In mice, MDSCs are
recognized as cells that express Gr-1+CD11b+ phenotype and further M-MDSCs are
characterized as CD11b+Ly6G-Ly6Chigh while G-MDSCs are characterized as
CD11b+Ly6G+Ly6Clow [36-38]. However, in cancer patients, the phenotype of human
MDSCs remains unclear. So far, human M-MDSCs are defined as
CD11b+CD14+CD33+HLA-DR-/lowCo-receptor-/low and while G-MDSCs as
CD11b+CD15+CD33+Lin-HLA-DR-/low expressing cells [8, 39].
MDSCs display a wide range of mechanisms to restrain the function of antigen
specific and non-specific T lymphocytes in vitro. They express high levels of
immunosuppressive enzyme arginase and NO/nitric oxide synthetase (iNOS), as well as
reactive oxygen species (ROS) [38, 42, 162, 182, 183]. A recent study has revealed several transcription factors that are activated by GM-CSF, IL-6 and other cytokines or growth factors, which regulate MDSC differentiation and function. Marigo and colleagues had recently provided new insight demonstrating that the transcription factor
CCAAT-enhancer-binding protein beta (C/EBPβ) plays a crucial role in the differentiation and immunosuppressive function of BM-derived and tumor-induced
MDSCs [31]. Of note, mice lacking C/EBPβ in the bone marrow compartment lose the ability to differentiate from IMCs into pathologically active MDSCs, possibly through a reduction of arginase 1 and Nos2 proteins [31].
A growing knowledge of epigenetic modification has been shown to regulate hematopoiesis under different pathological conditions such as infection and cancer
[146, 184]. HDAC11, the newest member of the HDAC family, was first identified in
70 2002 as a 39 kDa enzyme and the only class IV HDAC [79]. Northern analyses and
real-time PCR data from Gao and colleagues had confirmed a high expression level of
HDAC11 in brain, testis, some types of B-cell lymphomas and leukemias in humans respectively [79]. The functional role of HDAC11 played in the immune system was
unclear until Villagra et al first uncovered that this HDAC serves as a negative regulator
of IL-10 expression in macrophages [80]. Neutrophils lacking HDAC11 displayed a
functionally more active phenotype as well as enhanced migratory and phagocytic
capacity [185]. Moreover, data published by Woods and colleagues showed that down-
regulation of HDAC11 was required for T cell activation. This has further been
confirmed with a hyper-proliferative and responsive phenotype of HDAC11 Knockout T
cells [82]. These studies hinted at a positive feedback of innate and adaptive immune
response in a system devoid of functional HDAC11 protein. Although adoptive transfer of HDAC11KO T cells had significantly delayed tumor progression in a murine syngeneic lymphoma model [82], inoculation of murine thymoma or pancreatic cancer
cells to HDAC11 total KO mice demonstrated enhanced tumor growth kinetics when
compared with wild-type [155], hinting a hidden mechanistic role of HDAC11 in the
immunosuppressive compartments in cancer. Notably, Sahakian had uncovered that in
responding to antigen-specific OVA peptide, IFN-γ production from OT-1 CD8+ T cells
was significantly decreased when co-cultured with HDAC11KO MDSCs when compared
with Wild-type MDSCs [155], indicating that HDAC11KO MDSCs are functionally more
suppressive. However, the mechanism of HDAC11 in MDSCs expansion and function
remains to be elucidated. Here for the first time, we demonstrate a previously unknown
mechanistic role of HDAC11 as a transcriptional regulator of C/EBPβ in MDSCs.
71 Indeed, in the absence of this epigenetic checkpoint of C/EBPβ gene expression, the fully suppressive potential of MDSCs was fully unleashed. A better understanding of this novel role of HDAC11 in myeloid biology will ultimately lead to targeted epigenetic therapies to manipulate the suppressive abilities of these immunoregulatory cells.
3.4 Material and methods
3.4.1 Mice and cell line: C57BL/6 and B6-Lyz2tm1(cre)lfoIJ mice were purchased from The Jackson Laboratory. HDAC11 knockout mice were supplied by Merck
Research Laboratory and obtained from Dr. Seto’s laboratory at The George
Washington University Cancer Center. The HDAC11KO mice were on a C57BL/6 background and were generated by targeted deletion of floxed exon 3 of the HDAC11 gene. HDAC11 myeloid cell conditional knockout (HDAC11 KO LyZ-Cre) mice were generated by breeding B6-Lyz2tm1(cre)lfoIJ transgenic mice with HDAC11 flox/flox mice for greater than 10 generations. The third exon of HDAC11 gene, flanked by LoxP sites, is excised only in myeloid cells expressing the lysozyme 2 gene (Lyz2) which drive the expression of cre-recombinase. All mice were housed in pathogen-free conditions in the same designated room of the animal facility at H. Lee Moffitt cancer center and The
George Washington University. All animal studies were performed according to the guideline of approved protocols by the Institutional Animal Care and Use Committee
(IACUC) at the University of South Florida and The George Washington University.
EL-4 murine thymoma was purchased from ATCC and cultured and maintained in Dulbecco’s modified Eagle’s medium (DMEM, Corning) supplemented with 4 mM L-
72 glutamine, 4500 mg/L glucose, 1mM sodium pyruvate, 1500 mg/L sodium bicarbonate,
10% horse serum (ATCC), 100 U/mL penicillin and 100 µg/mL streptomycin. Cell line
was grown under humidified conditions at 5% CO2 and 37ºC. Cells were frozen at early passages (less than 6) in 95% culture medium + 5% DMSO and were used within 30 days of recovering.
3.4.2 Genotyping: To identify the genotypes of HDAC11KO, HDAC11 flox/flox and Lyz-CreHDAC11 conditional KO mice, total genome DNA was isolated and a polymerase chain reaction (PCR) experiment was performed with specific forward and reverse primers.
Briefly, approximately 0.5 cm of tail snips was obtained from each mouse and
then digested overnight in a lysis buffer containing 10 mM Tris-HCl (PH 8.0), 50 mM
NaCl, 25 mM EDTA, 0.5% SDS and 10 mg/mL proteinase K at 55 ºC. 6M NaCl was added to each sample followed by 15 seconds of vortexing then 30 minutes of centrifugation at 13,000 g at room temperature. The supernatant was transferred to a new conical tube containing 100% ethanol and DNA precipitated by inverting the tube.
After spinning down at 13,000 g for 10 minutes, DNA pellets were washed once with
75% ethanol and then resuspended in Tris-EDTA buffer. DNA concentration and quality was determined.
Primer sequences used for each strain are as follows: HDAC11KO Forward
(TGCTGCCTGTGAGCCACTGC), Reverse (CCTTGGAATAGCATCTCAGG). HDAC11-
flox Forward (TGCTGCCTGTGAGCCACTGC), Reverse
(AGAATGGCTGTCTCCCTAAG). Lyz-Cre set 1) WT (TTACAGTCGGCCAGGCTGAC),
73 Common (CTTGGGCTGCCAGAATTTCTC). LyZ-Cre set 2) Mutant
(CCCAGAAATGCCAGATTACG), Common (CTTGGGCTGCCAGAATTTCTC). For
each 25 µL PCR reaction, we used 0.5 µM of forward or reverse primer, 2.6 mM MgCl2,
0.26 mM dNTPs, 0.75U taq polymerase and 50 ng of DNA was used and product size was resolved on a 1.5% acrylamide gel containing SYBR safe DNA Gel Stain
(Invitrogen).
3.4.3 In Vivo tumor model: For in vivo tumor studies, 0.25×106 EL-4 cells were
injected subcutaneously into the right flank of female mice that were 8 weeks old.
Tumor volume was measured starting around Day 8 after injection or at the time when
tumors were palpable.
3.4.4 Splenic and tumor infiltrated MDSCs isolation: Mouse spleens or
tumors were harvested under sterile conditions on Day 21 after subcutaneous injection.
Total splenocytes were obtained by mashing mouse spleens through a 70 µm sterile cell strainer (Fisher Scientific). Mouse tumor tissue was cut into small pieces followed by incubation with tumor dissociation solution (RPMI-1640 supplemented with 10%
FBS, 0.25 mg/mL Collagenase D and 60 U/mL DNase I) for 30 minutes at 37 ºC. The disassociated tumor cells were collected by straining through a 70 µm sterile cell strainer. Red blood cells from spleen and tumor cells were lysed by incubating with ACK lysis buffer (Gibco) for 3 minutes at room temperature. Cells were washed twice with
PBS subsequently. MDSCs were further purified by magnetic bead isolation. Briefly, cells obtained from spleens or tumors were incubated with biotinylated anti-Gr-1
antibody (Invitrogen) followed by streptavidin microbeads (Miltenyi) for 15 minutes each
74 on ice. Gr-1+ MDSCs were isolated on LD columns (Miltenyi) according to the
manufacturer’s instruction.
3.4.5 BM-derived MDSCs generation: Mouse bone marrow aspirate was
removed from the tibias and femurs by flushing with ice-cold PBS and RBCs were
removed using ACK lysis buffer. To obtain bone marrow derived MDSCs, 5×106 bone
marrow cells were plated into 100 mm diameter tissue culture dishes in 10 mL RPMI-
1640 medium supplemented with 10% FBS, 100 U/mL penicillin, 100 µg/mL
streptomycin, 10 mM HEPES (Corning), 50 uM 2-mercaptoethanol (gibco), 40 ng/mL
mouse recombinant GM-CSF (Peprotech Inc) and 40 ng/mL mouse recombinant G-CSF
(Peprotech Inc). Cells were maintained in a humidified atmosphere with 5% CO2 at 37
ºC for 4 days. Fresh medium was replaced from cultured cells at Day 3 [31]. Gr-1+
MDSCs were purified by using magnetic bead isolation for each day as previously
described.
3.4.6 Arginase activity assay: To determine arginase activity, an arginase activity assay kit was used according to the manufacturer’s instructions (Sigma-Aldrich).
Briefly, 1×106 freshly isolated MDSCs were lysed in 100 µL lysis buffer containing 10
mM Tris-HCl (pH 7.4), 0.4% (w/v) Triton X-100 (Fisher), 1 µM pepstatin (Sigma-Aldrich)
A and 1 µM leupeptin (Sigma-Aldrich) for 10 minutes on ice. Cell lysate was collected by
centrifugation at 13,000 g for 10 minutes at 4 ºC. 40 µL of cell lysate was added to each
of two wells of a 96 well plate, one each serving for reaction well and blank well. 50 µL
of 1mM urea was added to the late serving for standard. 10 µL of 5× substrate buffer (8
µL arginase buffer + 2 µL Mn solution) was then added to each sample reaction well
and the plate was incubated for 120 minutes at 37 ºC. To stop the arginase reaction,
75 200 µL of urea reagent (100 µL reagent A + 100 µL reagent B) was added to each well
and 10 µL of 5× substrate buffer was added to sample blank wells. The plate was
incubated for 45 minutes at room temperature and urea concentration was defined by
measuring the absorbance at 430 nM using a microplate reader (Bio-Rad). One unit of
arginase activity is defined as the amount of enzyme that catalyzes the formation of 1
µmole of L-arginine to ornithine and urea per minute.
3.4.7 NO production assay: To detect nitrite production, 0.5 × 106 freshly
isolated MDSCs were cultured in a 96 well plate with 150 µL RPMI-1640 medium
supplemented with 10% FBS and 10 ng/mL mouse recombinant GM-CSF for 24 hours
in the presence or absence of 100 ng/mL mouse recombinant IFN-γ. 100 µL of culture supernatant were mixed with equal volume of Greiss reagent containing 1% (100 mg) sulfanilamide (Sigma-Aldrich), 0.1% (10 mg) N-(1-naphthyl)ethylenediamine (Sigma-
Aldrich) and 5% (0.5 mL) H3P04 (Fisher). After incubation for 10 minutes at room
temperature, the absorbance was measured at 550 nm using a microplate reader.
Nitrite concentration was measured by comparing the absorbance values for the
samples to a standard curve generated by 8 serial dilutions of 0.25 mM sodium nitrite
(Sigma-Aldrich).
3.4.8 ROS production: Oxidation-sensitive dye DCFDA (Invitrogen) was used to measure reactive oxygen species production by MDSCs. 2 to 3 ×106 freshly isolated
BM-derived MDSCs, splenocytes or MDSC-infiltrated tumor tissue digestions collected
from tumor bearing mice were labeled with flow antibodies against surface markers as
following: CD11b (M1/70, BD Biosciences), Ly6G (1A8, BD Biosciences) and Ly6C (AL-
21, BD Biosciences) for 20 minutes at 4ºC. Cells were then incubated in 500 µL serum
76 free RPMI-1640 medium with 3 µM DCFDA for 30 minutes in dark at 37ºC, in the
presence or absence of 300 nM PMA (Sigma-Aldrich). The cells were analyzed using
flow cytometry.
3.4.9 Quantitative Real-time PCR (qRT-PCR): Total messenger RNA was
extracted using Trizol (Invitrogen) according to manufacturer’s instruction. cDNA was
synthesized from 1 µg of mRNA for each sample by using iScript cDNA synthesis kit
(Bio-Rad). To detect gene expression, qRT-PCR was performed using a SYBR Green
two-step system. Primers targeting specific genes were designed or purchased as follows: Murine C/EBPα Forward (CCCACTCAGCTTACAACAGG), Murine C/EBPα
Reverse (GCTGGCGACATACAGTACAC). Murine C/EBPβ Forward
(ACACGTGTAACTGTCAGCCG), Murine C/EBPβ Reverse
(GCTCGAAACGGAAAAGGTTC). Murine HDAC11 Forward
(AGAGAAGCTGCTGTCCGATG), Murine HDAC11 Reverse
(AGGACCACTTCAGCTCGTTG). Murine 18s rRNA (QT 02448075, QuantiTech Primer
Assay, Qiagen).
3.4.10 Flow cytometry analysis and cell sorting: For flow cytometric analysis,
cells were stained with fluorochrome-labeled monoclonal antibodies (mAbs; anti-CD11b,
-Ly6G, -Ly6G, BD Biosciences) for 20 minutes at 4ºC and washed for 2 times with
FACS buffer. The vitality dye 4', 6-diamidino-2-phenylindole (DAPI, 50 ng/mL, Sigma)
was added to cells before analysis. Data was acquired on FACSCelesta flow cytometer
(BD Biosciences), at least 10,000 events, of the smallest population of interest,
subsequently analyzed using FlowJo software 10.2.
77 3.4.11 Western blotting analysis: Approximately 5 to 10 ×106 MDSCs were lysed in RIPA buffer containing 50 mM Tris-HCl (pH. 8.0), 150 mM NaCl, 0.5% Sodium
Deoxycholate, 0.1% SDS, 1% Triton X-100 with freshly added protease inhibitor
(Sigma-Aldrich), phosphatase inhibitor (Santa Cruz Biotechnology). The cell lysates were left on ice for 30 minutes followed by 2 cycles of sonication (8 min 30s on/30s off for each cycle. The lysates were then mixed with 2× gel loading buffer and boiled for 10 minutes. Samples were then resolved on 4 to 10% SDS-PAGE gels (Bio-Rad) and transferred to nitrocellulose membranes. Membranes were blocked with buffer containing 5% milk and 0.05% Tween-20 (Sigma-Aldrich) and probed with appropriate primary antibodies overnight at 4ºC. Membranes were then washed three times with wash buffer and incubated with secondary antibody for one hour at room temperature.
Bands were visualized by chemiluminescence detection on Azure Biosystem. To confirm equal loading, anti-GAPDH (Sigma Aldrich) was used for each experiment. Anti-
C/EBPβ, anti-Arginase and anti-iNOS antibodies were purchased from abcam.
3.4.12 Adoptive Cell Therapy: In this model, female C57BL/6 and HDAC11KO
mice (7 to 8 weeks old) were injected with 0.25×106 EL4 cells subcutaneously into
shaved right flanks on Day 0. A mixture of MDSCs (5×106/mouse) and CD3+ T cells
(5×106/mouse) from was intravenously injected to the animals on Day 0 and Day 7 upon
EL4 tumor inoculation, as described previously [186]. Briefly, on day of adoptive
transfer, spleens were harvested from C57BL/6 and HDAC11KO EL4 bearing mice. WT
or HDAC11KO MDSCs were labeled with biotinylated anti-Gr-1 antibody and streptavidin magnetic beads and positively selected on a LD column. Meanwhile, lymph
78 nodes and spleens from naïve C57BL/6 and HDAC11KO mice were harvested and
single cell suspensions was obtained after being lysed for red blood cells. CD3+T cells
were purified using a negative selection kit (EasySep, STEMCELL technology). Both
MDSCs and T cells were washed twice with ice cold PBS and re-suspended in HBSS at
a concentration of 5×106 cells/150 µL for I.V. injection.
3.4.13 Chromatin Immunoprecipitation (ChIP): Mouse MDSCs (20×106) were
cross-linked with 1% formaldehyde (Sigma-Aldrich) for 10 minutes at room temperature.
The cross-linking was then stopped with 0.125 M glycine for 10 minutes at room
temperature. The cells were washed twice with PBS and proceed with sample
preparation. The cell pellet was lysed by 1 mL of lyse buffer (50 mM HEPES pH 7.8, 3
mM MgCl2, 20 mM KCl, 0.25% Triton X-100, 0.5% NP-40) on ice for 10 minutes. The cell lysate was then transferred to a “Dounce Homogenizer” and 20 strokes were applied using the loose pestle A. The cell pellet was washed once with 1 mL wash buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA, 200 mM NaCl) and resuspended in 300 µL sonication buffer (50 mM HEPES pH 7.8, 140 mM NaCl, 1 mM EDTA, 0.5% SDS, 1%
Triton X-100). 8 sonication cycles (8 minutes of 30s on/off) were applied to the samples
followed by centrifugation for 10 minutes at 4ºC. The lysate was diluted at 1:10 with
dilution buffer I (50 mM HEPES pH 7.8, 140 mM NaCl, 1mM EDTA, 1% Triton X-100),
pre-cleared using Protein A Agarose beads (Millipore), and incubated with rabbit anti-
HDAC-11 antibody cocktail (BioVision and Sigma-Aldrich) on a rotator at 4°C overnight.
Biotin-conjugated normal rabbit IgG-B (Santa Cruz Biotechnology) was added at the
same amount of rabbit anti-HDAC-11 antibody cocktail in parallel of each sample and
incubated on a rotator at 4°C overnight. 50 µL protein A Agarose beads was then
79 applied to each sample and incubated at 4°C for 4 hours. The beads were then washed
twice each with dilution buffer I, dilution buffer II (50 mM HEPES pH 7.8, 500 mM NaCl,
1 mM EDTA, 1% Triton X-100), LiCL buffer (20 mM Tris-HCl pH 8.0, 250 mM LiCl, 1
mM EDTA, 0.5% Triton X-100), and TE buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA).
Afterwards, beads were eluted in 100 µl elution buffer (50 mM Tris-HCl pH 8.0, 1 mM
EDTA, 1% SDS) and incubated at 65°C for 15 minutes and the immunocomplexes were collected in the soluble fraction. NaCl was added to a final concentration of 200 mM and the crosslinking was reverted by incubating at 65°C for overnight. RNAse A (Qiagen) was added to 20 µg/mL to each sample and incubated at 37°C for 30 minutes.
Proteinase K (Thermo Scientific) was then added at 100 µg/mL and incubated at 42°C for 2 hours. DNA was purified by using QIAquick PCR Purification Kit (Qiagen) and purified DNA was eluted in 100 µL TE buffer for analysis by qRT-PCR. 4 µL of DNA was used for each qRT-PCR reaction. The following PCR primers were used: C/EBPβ
Forward (ATGCACACAGGCAAGTTTCA), C/EBPβ Reverse
(TCTCTCAGGCCTCAGTTTCC).
3.4.14 Statistics: Statistical analyses were performed using student’s t test. Data expressed as the mean ± SD. Probability values of p ≤ 0.05 were considered significant.
3.5 Results
3.5.1 C/EBPβ is necessary for bone marrow-derived and tumor-induced
MDSCs.
80 Previously in our group, we have demonstrated that when compared with naive
myeloid cells, HDAC11 expression was significantly reduced in the myeloid-derived
suppressor cells in response to tumor challenge. Without HDAC11, MDSCs are
functionally more suppressive by implicating antigen-specific CD8+ T cell
unresponsiveness in vitro [155]. However, the mechanism underlying this functional
characteristic remains uninvestigated. C/EBP transcription factor family is largely
involved during myelopoiesis. C/EBPα is a "master regulator" of granulopoiesis at steady-state, whereas C/EBPβ is required for emergency granulopoiesis in response to cytokines and infection [187]. It wasn't until 2010, Marigo and colleagues had first
uncovered the crucial role of C/EBPβ in regulating the immunosuppressive activity of
MDSCs in tumor bearing host. Complete deletion of C/EBPβ resulted in full abrogation
of MDSCs on antigen specific CD8+ T cells, possibly through reduction of expression
and reduced enzymatic activity of arginase 1 and nitric oxide synthase 2, two enzymes
that have previously been described as major contributors to the inhibitory ability of
MDSCs [31, 182].
To determine whether or not C/EBPβ is involved with the elevated suppressive
activity of HDAC11KO MDSCs, we assessed the gene expression profile of C/EBPβ in
WT or HDAC11KO MDSCs. We isolated CD11b+Ly6G+Ly6Clow and CD11b+Ly6G-
Ly6Chigh cells from spleens of naive and tumor-bearing C57BL/6 WT animals (Figure
3.1A). C/EBPβ mRNA is barely detectable in immature myeloid cells from naive mice.
Interestingly, both CD11b+Ly6G+Ly6Clow granulocytic-MDSCs and CD11b+Ly6G-
Ly6Chigh monocytic-MDSCs from tumor bearers showed an elevated C/EBPβ mRNA
expression compared with IMCs sharing the same surface phenotype from naive mice,
81
Figure 3.1 C/EBPβ expression is up-regulated in MDSCs with HDAC11 deletion. (A) In Naïve and EL4 tumor bearing C57BL/5 mice, splenic monocytes (Ly6G+Ly6Chigh cells in naïve mice) and monocytic MDSCs (Ly6G+Ly6Chigh cells in tumor bearing mice), as well as splenic neutrophils (Ly6G+Ly6Clow cells in naïve mice) and granulocytic MDSCs (Ly6G+Ly6Clow cells in tumor bearing mice) were flow sorted. C/EBPβ expression was further assessed by qRT-PCR. (B) Ly6G+Ly6Clow Monocytes and Ly6G-Ly6Chigh neutrophils were flow sorted from the bone marrow of C57BL/6 mice and HDACKO mice. The expression of C/EBPβ profile were analyzed using qRT-PCR . (C) Gr-1+ bone marrow derived-myeloid cells (day o) and –MDSCs (day 4) were isolated using biotinylated anti-Gr-1 antibody and magnetic beads. C/EBPβ mRNA expression was determined by qRT-PCR. Error bars = S.E.M. Data presented for each graph is a representative figure from 2 individual experiments, 3 animals were used for each experiment. Asterisk indicates statistical significance: *P<0.05, **P<0.01, ***P<0.001.
82 suggesting that up-regulation of C/EBPβ is required during the transition of immature
myeloid cells to MDSCs. We then flow-sorted CD11b+Ly6G+Ly6Clow and CD11b+Ly6G-
Ly6Chigh cells from WT and HDAC11KO bone marrow (Figure 3.1B). To our surprise, we
have found out that at steady state, C/EBPβ level was significantly higher for both
Ly6G+ and Ly6C+ IMCs lacking HDAC11. To further confirm this, we isolated BM-
derived Gr-1+ MDSCs and found up-regulated mRNA expression of C/EBPβ in
HDAC11KO MDSCs. Given Marigo's data that C/EBPβ-deleted myeloid cells failed to
generate functional MDSCs in vivo, we hypothesize that HDAC11KO myeloid cells are
more suitable for MDSC generation with its abnormally high level of C/EBPβ.
3.5.2 Elevated level of C/EBPβ contributes to the up-regulation of enzymes
involved with MDSC suppression in HDAC11KO mice.
We next evaluated whether up-regulation of C/EBPβ in HDAC11KO MDSCs
might control suppressive immunoregulatory pathways. We isolated bone marrow cells
from WT and HDAC11KO mice followed by a treatment with 40 ng/mL of GM-CSF and
G-CSF for up to four days in vitro. Gr-1+ cells were then purified after 72 and 96 hours
and immunoblottings of targets of interest were performed (Figure 3.2A). We found that
consistent with our mRNA result, C/EBPβ protein was not detectable in Gr-1+ bone
marrow cells at day 0 of harvest. On both day 3 and day 4, an increased C/EBPβ
protein level was observed in HDAC11KO MDSCs along with an over-expression of
arginase 1 (Arg1) and nitric oxide synthase 2 (Nos2). The data was further confirmed in
splenic-MDSCs and tumor infiltrated-MDSCs isolated from WT and HDAC11 KO tumor-
83
Figure 3.2 C/EBPβ is involved with the suppressive activity of MDSCs lacking HDAC11. (A) Immunoblots of C/EBPβ, Arginase 1 and NOS2 in Gr-1+ MDSCs isolated from WT and HDAC11KO mice fresh bone marrow (indicated as day 0) and BM cells treated with GM-CSF and G-CSF for 72 and 96 hours (day 3 and day 4). (B) Immunoblots of C/EBPβ in Gr-1+ MDSCs isolated from spleens and tumors of WT or HDAC11KO mice bearing EL4 tumor at Day 21. LAP*, LAP and LIP indicate three isoforms of C/EBPβ protein.
84 bearing mice. As shown in Figure 3.2B, C/EBPβ, in the absence of HDAC11, Arg1 and
Nos2 protein level were increased in both splenic- and tumor infiltrated- MDSCs.
Interestingly, C/EBPβ and Nos2 displayed a stronger expression profile in MDSCs isolated from tumor site, where as Arg1 level seems to be similar in between these two sources. Earlier studies had pointed out the transcriptional regulation by C/EBPβ of
Arg1 and Nos2 genes [188-190]. In Marigo's recent work, loss of C/EBPβ results in a reduction to near complete depletion of both Arg1 and Nos2 protein in MDSCs [31].
With these observations, we believe that the loss of HDAC11 is associated with the up- regulation of Arg1 and Nos2 through transcription factor C/EBPβ.
3.5.3 HDAC11 deletion promotes MDSCs suppressive activity through
increased arginase activity and NO production.
Previous studies had demonstrated that arginase activity, NO and ROS production were the main effectors of MDSC's suppressive function. Up-regulation of Arginase 1 activity results in rapid uptake of L-arginine from the tumor microenvironment which contributes to the loss of the CD3ζ chain and prevents T cell proliferation [48, 162, 182]. Increased
NO synthase expression can facilitate MDSCs to produce more NO and suppress T cell function through down-regulated downstream pathways of IL-2 receptor [162, 191].
Hyperproduction of reactive oxygen species (ROS) such as hydrogen peroxide and peroxynitrite can induce T cell apoptosis [42]. In our earlier finding, MDSCs devoid of
HDAC11 can prevent IFN-γ production in antigen- specific CD8+ OTI T cells in responding to OVA peptide. HDAC11 deficient mice displayed an enhanced tumor
85 growth pattern which indicates a more suppressive microenvironment in those tumor
bearing animals when compared with WT.
To further compare the suppressive functional activity of WT and HDAC11KO
MDSCs, we performed arginase activity and NO production assays (Figure 3.3 and
Figure 3.4). Bone marrow cells were collected from WT and HDAC11KO mice followed by GM-CSF and G-CSF treatment for four days. Gr-1+ cells were isolated at each day
Figure 3.3 Enzymes involved in the suppressive pathways employed by BM-derived MDSCs with HDAC11 deletion. (A) Gr-1+ MDSCs were isolated from bone marrow and treated with GM-CSF and G-CSF for 24, 48, 72 and 96 hours (day 1, 2, 3 and 4). The enzymatic activity of Arginase was evaluated from cell lysate as previously described. (B) Bone marrow-derived Gr-1+ MDSCs from WT or HDAC11KO mice were also plated in complete RPMI-1640 medium containing GM-CSF, with or without IFN-γ for 24 hours. Cell supernatants were collected and assayed for NO production to determine Nos2 activity. Error bar = S.E.M. Asterisk indicates statistical significance: *P<0.05, **P<0.01, ***P<0.001.
86 and arginase activity evaluated from cell lysate. Accordingly, arginase activity was
significantly increased in HDAC11KO MDSCs on both day 3 and 4 (Figure 3.3A). After
24 hours of IFN-γ stimulation, NO production was measured from culture medium.
HDAC11KO MDSCs facilitated significant increase of NO than WT on day 3 and day 4
(Figure 3.3B).
Next we performed similar experiments in splenic- and tumor infiltrated-MDSCs
(Figure 3.4). Interestingly, splenic-MDSCs isolated from WT or HDAC11KO tumor bearing mice showed a similar (arginase activity) or moderately increased (NO production, not significant) activity from both enzymes (Figure 3.4A and 3.4B). However, upon entry into the tumor site, HDAC11KO MDSCs displayed a dramatic increase in arginase activity and NO production, indicating abnormal activity from both enzymes in cells depleted of HDAC11 (Figure 3.4A and 3.4B). Cytokines such as GM-CSF, G-CSF and IL-6 produced by tumor are some of the main factors that promote the suppressive function and differentiation of MDSCs [43, 192]. Given our previous observation that
C/EBPβ protein levels are significantly higher in tumor infiltrated-MDSCs than in splenic-
MDSCs, we believe that in response to cytokines such as GM-CSF and G-CSF, up- regulation of C/EBPβ in HDAC11KO MDSCs facilitates their ultra suppressiveness in the tumor microenvironment.
87
Figure 3.4 Enzymes involved in the suppressive pathways employed by HDAC11KO MDSCs in vivo. (A) Gr-1+ MDSCs were isolated from spleens and tumors of C57BL/6 WT or HDAC11KO mice bearing EL4 tumors at day 21. The enzymatic activity of Arginase was evaluated from cell lysate as previously described. (B) Gr-1+ MDSCs from WT or HDAC11KO tumor bearers were also plated in complete RPMI-1640 medium containing GM-CSF, with or without IFN-γ for 24 hours. Cell supernatants were collected and assayed for NO production to determine Nos2 activity. Tumors were collected on day 21 after EL4 inoculation. Cells were stimulated with or without PMA in RPMI medium for 30 minutes then labeled with anti-CD11b, anti-Ly6G and anti-Ly6C antibodies. ROS was measured in G-MDSCs (C) and M-MDSCs (D) population by labeling cells with DCFDA. Mean florescence intensity (MFI) is shown in each indicated
88 figure. Error bar = S.E.M. Asterisk indicates statistical significance: *P<0.05, **P<0.01, ***P<0.001.
3.5.4 HDAC11 negatively regulates C/EBPβ expression by interacting with
the promoter region of this transcription factor.
Given our presented data so far, we hypothesize that HDAC11 could be a
negative regulator of C/EBPβ. The higher mRNA expression of C/EBPβ in HDAC11KO
immature myeloid cells may indicate that those IMCs are ready to differentiate into
functional suppressive MDSCs when recruited into the tumor microenvironment. To
further elaborate the mechanism of how HDAC11 regulates C/EBPβ, we performed
chromatin-immunoprecipitation analysis. Gr-1+ MDSCs isolated from C57BL/6 WT and
HDAC11KO tumor-bearing mice were cultured in medium for 3 hours with or without
LPS. ChIP data suggest that HDAC11 was present on the promoter region of C/EBPβ in
WT MDSCs (Figure 3.5A), with an enrichment ratio at least 2.5 fold higher than
HDAC11KO MDSCs (Figure 3.5B) which serves as a negative control. These data
suggest that HDAC11 could alter the expression of C/EBPβ through chromatin
remodeling or simply function as a transcription factor. Unlike other HDACs, there has
been no literature reporting on HDAC11’s ability to bind to DNA directly or, coupled with
other proteins, to directly facilitate transcription initiation or regulation. At this point we
could not fully answer the question of how HDAC11 negatively regulates C/EBPβ. A
more in-depth study is required to fully understand the mechanism.
89
Figure 3.5. HDAC 11 regulates C/EBPβ expression in MDSCs. MDSCs were purified from C57BL/6 mice and HDACKO mice for Chromatin-immunoprecipitation. ChIP studies showed the presence of HDAC11 protein to the promoter region of C/EBPβ in C57BL/6 mice MDSCs (A) but not MDSCs from HDAC11 KO mice (B). Error bars = S.E.M. Asterisk indicates statistical significance: *P<0.05, **P<0.01, ***P<0.001.
3.5.5 Mice with HDAC11 deletion in myeloid compartment displayed
enhanced tumor progression compared to total knockout mice.
Our previous work demonstrated an enhanced tumor progression pattern in
HDAC11KO tumor bearers. Woods and Woan in our lab had found out that T cells possessed a hyper reactive phenotype and enhanced anti-tumor efficacy in vivo [82]. In
their study, FCmuMCL tumor bearing mice established a significant delay in tumor
growth and reduced tumor volume when adoptively transferred with HDAC11KO T cells
[82]. We thought the HDAC11 total knockout mouse might not serve as the best model
to study MDSCs function in vivo. Taking that into consideration, we decided to establish
a mouse model with a linage-specific HDAC11 knockout in the myeloid compartment
only. In Figure 3.6, our in vivo experiment show that upon EL4 tumor challenge, mice
90 with HDAC11 myeloid-lineage conditional knockout displayed enhanced tumor growth
when compared with HDAC11 total knockout and WT mice, possibly resulting from the
absence of HDAC11KO T cells in the tumor microenvironment. However, tumor grew larger in HDAC11 total knockout mice compared with WT mice, indicating that although the hyperactive HDAC11KO T cells could function against tumor progression, but when encountered with HDAC11KO MDSCs, at least in this model, their anti-tumor capability were limited.
Figure 3.6 Mice lacking HDAC11 in the myeloid compartment demonstrate a more enhanced tumor growth pattern than HDAC11 total knock out. 0.25×106 EL4 cells were subcutaneously injected to C57BL/6 mice, HDAC11KO mice and HDAC11KO Cre-LyZ mice (n=5 per group) for up to 19 days. Tumor volume was measured for every 3 days after the initiation of tumors. The tumor growth pattern was analyzed to compare HDAC11 total KO mice with mice lacking HDAC11 in the myeloid compartment (HDAC11 KO Cre-LyZ), HDAC11 KO mice with C57BL/6 WT mice and HDAC11KO
91 Cre-LyZ with C56BL/6 mice. (Error bar = S.E.M). Asterisk indicates statistical significance between WT and HDAC11 KO, WT and HDAC11 KO Cre-LyZ, HDAC11KO and HDAC11KO Cre-LyZ tumor bearing mice: *P<0.05, **P<0.01, ***P<0.001.
3.5.6 HDAC11 plays a contradictory role in regulating MDSCs and T cells in
the tumor microenvironment.
To further investigate the contradictory role of HDAC11 plays in MDSCs and T
cells, we performed an in vivo experiment where we adoptively transferred a single cell
type or a mixture of MDSCs and T cells (from WT or HDAC11KO) to C57BL/6 EL4
tumor bearers. Briefly, on day 0, 9 groups of C57BL/6 mice were inoculated with EL4
tumor cells subcutaneously. Two adoptive transfers of MDSCs and/or T cells were given
to indicated mice on day 0 and day 7. In figure 3.7A, we found out that adoptive
transfer of HDAC11KOT cells into EL4 tumor bearing mice can significantly reduce
tumor progression than mice receiving WT T cells. Notably, tumor volume of mice
receiving HDAC11KO MDSCs alone is significantly larger than mice that received WT
MDSCs, which is expected given the enhanced suppressive phenotype of those cells
(Figure 3.7B). Additional transfer of HDAC11KO T cells significantly reduced both
MDSC-promoted tumor growth in mice receiving WT MDSCs or HDAC11KO MDSCs
(Figure 3.7C, 3.7D). However, the anti-tumor effect by HDAC11KO T cells was affected
when they encounter HDAC11KO MDSCs in the tumor microenvironment (Figure 3.7E,
3.7F).
92
Figure 3.7 The antitumor efficacy by adoptive transfer of HDAC11KO T cells can be diminished by MDSCs lacking HDAC11. 0.25 × 106 EL4 cells were subcutaneously injected to 9 groups of C57BL/6 mice on day 0 (n=5 per group). On day 0 and day 7, mice were given WT MDSCs, H11KO MDSCs, WT T cells, H11KO T cells alone or a mixture of WT or 11KO MDSCs with naive WT or 11KO T cells intravenously. For each mouse receiving adoptive transfer, 5 × 106 MDSCs or T cells were used. One group of mice receiving only EL4 tumor cells served as No i.v control. Tumor volume was measured for every 2 days after the initiation of tumors. The tumor growth pattern was analyzed in comparison with (A) C57BL/6 tumor-bearing mice with adoptive transfer of
93 C57BL/6 WT T cells alone, HDAC11KO T cell alone and No i.v control, (B) C57BL/6 tumor-bearing mice with adoptive transfer of WT MDSCs alone, HDAC11KO MDSCs alone and No i.v control, (C) C57BL/6 tumor-bearing mice with adoptive transfer of WT MDSCs alone, WT MDSCs + WT T cells, WT MDSCs + HDAC11 KO T cells and No i.v control, (D) C57BL/6 tumor-bearing mice with adoptive transfer of HDAC11KO MDSCs alone, HDAC11KO MDSCs + WT T cells, HDAC11KO MDSCs + HDAC11KO T cells and No i.v control. (E) C57BL/6 tumor-bearing mice with adoptive transfer of WT MDSCs + WT T cells, HDAC11KO MDSCs + WT T cells, WT T cells alone. (F) C57BL/6 tumor-bearing mice with adoptive transfer of WT MDSCs + HDAC11KO T cells, HDAC11KO MDSCs + HDAC11KO T cells, HDAC11KO T cells alone. (Error bar = S.E.M). Asterisk indicates statistical significance: *P<0.05, **P<0.01, ***P<0.001.
3.6 Discussion
Myeloid-derived suppressor cells represent a heterogeneous population of
immature myeloid cells that are recruited to the tumor microenvironment where they
differentiate into immunosuppressive cells. As one of the main mechanisms that
facilitate the immune evasion of cancer, MDSCs have garnered a great deal of interest
from scientific investigators and were believed to be a potent target for therapeutic
approaches against cancer. Here we showed for the first time that among all the
HDACs known, through negative regulation of C/EBPβ, HDAC11, the newest member
of this family of enzymes, promotes the suppressive function of MDSCs in mouse
model.
C/EBPβ had been recently demonstrated to control emergency granulopoiesis
induced by cytokines such as GM-CSF or infection [187]. It is the discovery of C/EBPβ
deletion could mostly eliminate MDSC suppressive activity until investigators first
associate this molecule with MDSC development and biological function [31]. Previously
we have found out that in the absence of HDAC11, MDSCs display an enhanced
suppressive phenotype against antigen-specific CD8+ T cell function and promote tumor
94 progression [155]. However, little is known regarding the C/EBPβ expression profile in
MDSCs devoid of HDAC11. In our study, we observed an increased C/EBPβ level in
HDAC11KO BM-derived MDSCs compared with WT. C/EBPβ is generally not
detectable in myeloid cells at steady state. To our surprise however, we detected a
markedly higher expression of C/EBP-β mRNA in both CD11b+Ly6G+Ly6Clow and
CD11b+Ly6G-Ly6Chigh compartments at steady state in HDAC11KO vs WT control,
indicating a possibility of HDAC11KO myeloid cells being primed and ready to
differentiate into functional MDSCs (Figure 3.1). Additionally, in the absence of
HDAC11, we have detected an increased protein level of C/EBPβ in in vitro cultured
BM-derived MDSCs, as well as splenic and tumor-infiltrated MDSCs from our in vivo
tumor model when compared with WT (Figure 3.2). Moreover, ChIP analysis results
suggest that HDAC11 was recruited to the promoter region of C/EBPβ, indicating a
direct or indirect transcriptional machinery involved with HDAC11 (Figure 3.5). Along with that, two enzymes known to be associated with C/EBPβ, arginase 1 and nitric oxide
synthase 2 showed increased protein level in HDAC11KO MDSCs compare with WT
(Figure 3.2). In MDSCs, arginase activity, NO and ROS production are the main
effectors to suppress T cell function. We next assessed enzymatic activity analysis for
those factors. Our data suggest that in the absence of HDAC11, in vitro GM-CSF and
G-CSF induced MDSCs displayed a higher arginase activity and NO production (Figure
3.3). Similarly, tumor-infiltrated HDAC11KO MDSCs had a dramatic increase of both
Arg1 activity and NO, but not ROS production (Figure 3.4). However, both arginase activity and NO level were at a similar level in the splenic-MDSCs from tumor bearing mice. Both Arg1 and iNOS use L-arginine as a substrate and the uptake of L-arginine
95 from the tumor microenvironment can suppress T cell function through multiple
pathways [48, 193, 194]. Taken together, our data suggest that through arginine
metabolism regulated by C/EBPβ-induced enzyme Arg1 and Nos2, HDAC11KO MDSCs
function more suppressive in the tumor microenvironment.
In addition to having increased suppressive phenotypes in HDAC11KO MDSCs,
studies have shown that T cells lacking HDAC11 had enhanced effector function
against tumor [82]. Our observation in HDAC11 myeloid-lineage conditional knockout provides evidence to support this finding. In solid tumor, the microenvironment consist of a heterogeneous population of tumor cells, stromal cells, fibroblasts and a mixture of different immune cells such as T cells, MDSCs, tumor associated macrophages and regulatory T cells. Deletion of HDAC11 in the knockout mouse will inevitably affect all cell types and will bring an uncertainty in how to interoperate our data. Using the
HDAC11 Cre-LyZ conditional knockout model allow us to investigate the suppressive function of MDSCs without interference from HDAC11KO T cells. When challenged with tumor, the HDAC11 Cre-LyZ mice indeed showed a dramatic increase in tumor progression compared with total knockout mice (Figure 3.6). This finding provides evidence to allow us to further investigate the contradictory role HDAC11 played in the tumor microenvironment.
In our in vivo study, tumor progression in C57BL/6 tumor bearing mice receiving
HDAC11KO T cells was significantly reduced than mice receiving WT T cells, whereas adoptive transfer of HDAC11KO MDSCs alone could promote tumor growth (Figure
3.7A, 3.7B). Additional transfer of HDAC11KO T cells could significantly reduce both
MDSC-promoted tumor growth in mice receiving WT MDSCs or HDAC11KO MDSCs
96 (Figure 3.7C, 3.7D). However, the anti-tumor effect by HDAC11KO T cells was affected
and reduced when co-existing with HDAC11KO MDSCs. When encountered with both
HDAC11KO and WT T cells, WT MDSCs appeared to have a milder suppression
(Figure 3.7E, 3.7F). Based on our data, we hypothesize that to gain a full anti-tumor effect from T cells by HDAC11 inhibition, it is necessary to eliminate MDSC function or infiltration.
A growing body of evidence has demonstrated that targeting HDAC11 could be a potent therapeutics against in multiple cancer cell lines or across different cancer types
[84, 87, 195]. There are a few HDAC11 inhibitors commercially available and hopefully more will be generated with a higher specificity. Inhibition of HDAC11 activity either as stand-alone or in combination with other therapies will inevitably target the host immune system and tumor cells simultaneously. With its potent ability to target cancer cells directly, the additional effect on T cell function could boost the anti-tumor capability of the drugs. However, this effect could be potentially jeopardized by the benefit of
HDAC11 inhibition to MDSCs. In addition to HDAC11 inhibition blockade of MDSC infiltration or elimination of its function could potentially provide a better outcome as a new therapeutic approach. Growing interest has focused on MDSC inhibition in cancer patients. Targeting GM-CSF signaling or CSF-R blockade could potentially benefit chemotherapy and reverse resistance to immunotherapy in vitro [196, 197]. Inhibiting
MDSC NO production through Nrf2 degradation by RTA 408, which is currently being evaluated in clinical trials, benefits the outcome of treatment with its anti-cancer and anti-inflammatory activity [198]. C/EBPβ could also serve as a potential target in
97 reducing MDSCs function as a few inhibitors are available but need to be further evaluated [199, 200].
Taken together, these studies have allowed us to identify HDAC11 as a novel regulator of the tolerogenic and immunosuppressive microenvironment induced by cancer. The dual role of HDAC11 in regulating MDSCs suppressive function and T cell anti-tumor effect reflects the complexity of its function and sheds lights on the therapeutic potential of this novel molecule.
98
Chapter 4: Conclusions and Future Directions.
HDAC11 was first discovered and cloned in 2002 and was characterized as a
small protein with 39 kDa molecule weight and expressed largely different among
different tissues [79]. It shared limited similarity with other HDACs in its family, and was
thus given its own class as Class IV HDACs. Unlike other HDACs in its family, little is
known of HDAC11's function among the scientific community. HDAC11 has the
potential to regulate DNA replication through manipulation of chromatin structures and
alter chromatin accessibility to transcription in a few genes such as cdt1, cdc25A and
oligodendrocyte specific genes MBP and PLP genes [91, 201, 202]. Recently, HDAC11
depletion is believed to cause cancer cell death and inhibit the metabolic activities in a
few cancer cell lines, including colon, prostate, breast and ovarian lines by using a
catalytically impaired variant of HDAC11 [84]. Other HDACs have been shown to
demonstrate an effect on both cancer cells and the host immune system. However, the regulatory role of HDAC11 on the immune system is still undergoing investigation. In order to assess the capability of HDAC11 as a potential therapeutic, a better understanding of its function is urgently needed.
Knocking out HDAC11 in the mouse model is not lethal, at least in the C57BL/6 background. Extensive studies in our group have illuminated a unique role of HDAC11 in the immune system. In our observations, in other experiments performed in the
99 laboratory outside of this thesis, there is no difference in the size of major organs such
as the brain, spleen, liver, thymus and heart from HDAC11KO mouse. In addition,
lymph nodes appear to be slightly larger in the knockout. HDAC11KO animals also
share relatively similar blood counts for monocytes, granulocytes, white blood cells and
lymphocytes, whereas colony forming assay results showed a slight increase of CFU-M,
CFU-G, CFU-GM colonies with a dramatic increase of the CFU-PreB colony (data not
shown in this dissertation). In Chapter 2 we have reviewed the evidence that aging
HDAC11KO mice (18 months old) demonstrated BM hypercellularity with granulocytic
expansion and splenomegaly, possibly resulting from increased extramedullary
hematopoiesis. Additionally, a significant decrease in the viability of neutrophils isolated
from the HDAC11KO mice bone marrow was observed when these cells were
stimulated with GM-CSF compared to WT control, indicating that HDAC11KO
neutrophils have an even shorter life span in response to stimulation. So far we have
uncovered no evidence regarding the long-term survival for HDAC11KO MDSCs.
Using the HDAC11-eGFP transgenic mouse model, previous members in our lab
were able to visually identify the HDAC11 gene expression profile in immune cells. Their
data suggest that HDAC11 expresses at a higher level in the neutrophils/granulocytes,
but remains low in the macrophages/monocytes. Activation of both CD4+ and CD8+ T cells required a decreased expression of HDAC11. While differentiated into MDSCs,
HDAC11 signal was lost compared with immature myeloid cells express the same
surface marker as MDSCs. Tumors can promote multiple mechanisms to induce
immune dysfunction in both mouse and human. The unique expression profile of
100 HDAC11 drove researchers in our group to further investigate the role of this molecule
in different lineage immune cells.
Villagra demonstrated that HDAC11 regulates the chromatin accessibility for
transcriptional regulation in the promoter region of IL-10 in macrophages [80]. Woods
found out that deletion of HDAC11 permits a hyper active phenotype in T cells with an
upregulation of transcription factor T-bet and Eomes [82]. Huang from the Hancock lab
discovered an increased expression of Foxp3 and TGF-β, along with increased
suppressive function in Foxp3+ Tregs [83]. Sahakian published work in identifying
HDAC11KO MDSCs that possessed an enhanced ability to suppress T cell function and promote tumor progression [155]. This dissertation discussed the influence of HDAC11
in neutrophil biology, as well as its role in regulating MDSC function through
transcriptional regulation of C/EBPβ. In collaboration with Sahakian, we found out that
neutrophils lacking HDAC11 gained migratory and phagocytic ability, with an increased
cytokine production profile (TNF-α, IL-6 and IL-1β, data for IL-1β cytokine production is
not listed in this dissertation). Furthermore, the deletion of HDAC11 seems to grant
neutrophils a more active phenotype upon infection. The continuous work carried on
from this MDSCs study was discussed previously in chapter 3. We found out that the
ultra suppressive phenotype of MDSCs lacking HDAC11 was possibly regulated
through transcription factor C/EBPβ, which was proven to be associated with MDSC
suppressive factor Arg1 and Nos2. With an increased level of Arg1 and Nos2, L-
arginine metabolism was increased in HDAC11KO MDSCs, granting those cells
enhanced suppression.
101 Taken all together, we believe that HDAC11 plays a dual yet contradictory role in
the host immune system. Without HDAC11's participation, under pathological conditions
such as cancer or infection, the "immune defenders" such as neutrophils, APCs and T
cells become functionally more active against pathogen or tumor invasion. On the
contrary, "immune suppressors" such as MDSCs become more suppressive.
These findings led us to believe that when targeting HDAC11 as a potential
cancer treatment, the effect of its inhibition on both cancer cells and the immune system
should be taken into consideration to assess its safety and effectiveness. With an
increasing interest in the development of effective HDAC11 inhibitors, more in-depth
investigation should be performed to gain a better understanding of the mechanisms of
HDAC11 that affect the immune system. Data from us and other investigators suggest
that HDAC11 regulates a broad range of genes in different cell types. HDAC11 down-
regulates cytokines such as IL-10, IL-6, TNF-α and IL-1β in matured myeloid cells, while
repressing the expression of transcription factors such as T-bet, Eomes in T cells,
Foxp3 in Tregs and C/EBPβ in MDSCs. Neutrophils lacking HDAC11 displayed a higher
level of migration related genes such as MIP2 and CXCR2. Chromatin immunoprecipitation analysis showed the presence of HDAC11 in the promoters of multiple genes listed above, indicating the potential mechanism of HDAC11 in chromatin remodeling within those genes. Unfortunately, there is no further evidence to help us explain how HDAC11 regulate those genes. Data from Woods and myself did point out that total histone 3 in T cells and Lysine 27 on histone 3 in neutrophils (figure not included in this dissertation) demonstrated an increased acetylation status when lacking HDAC11. However, more experiments in the promoters should be performed to
102 help us understand the true mechanism. Secondly, most members in the HDAC family
are known to function as a protein complex. Villagra had discovered that in APCs,
HDAC11 and HDAC6 could interact in the cytosolic and nuclear compartment [78].
Further investigation of how these two HDACs interact as well as other proteins
potentially associated with this regulatory complex will certainly help us unveil the
secrets of HDAC11. HDAC11 is predominately localized in the nucleus with a limited amount of protein detectable in the cytosolic compartment. It will be necessary to find out the mechanism of how HDAC11 is shuttling in and out of the nucleus in response to
stimulation, which will provide a better insight into its function in immune cells. Last but
not least, more experiments should be designed and performed to identify other
possible pathways for MDSCs function under HDAC11 inhibition. Despite the critical
role of C/EBPβ in regulating MDSC function, multiple pathways have been uncovered in
the past contributing to this suppressive cell type. For instance, STAT3 was shown to
enhance MDSC proliferation through up-regulation of cell cycle related genes such as
Bcl-x1, cyclin D1 and survivin, as well as S100A8 and S100A9 [9, 203, 204]. A better
understanding of the complete regulatory role of HDAC11 in MDSCs could provide
more potential therapeutic targets in combination with HDAC11 inhibition.
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