Close
About
FAQ
Home
Collections
Login
USC Login
Register
0
Selected
Invert selection
Deselect all
Deselect all
Click here to refresh results
Click here to refresh results
USC
/
Digital Library
/
University of Southern California Dissertations and Theses
/
MAO a deficient mice exhibit an altered immune system in the brain and prostate
(USC Thesis Other)
MAO a deficient mice exhibit an altered immune system in the brain and prostate
PDF
Download
Share
Open document
Flip pages
Contact Us
Contact Us
Copy asset link
Request this asset
Transcript (if available)
Content
MAO A DEFICIENT MICE EXHIBIT AN ALTERED IMMUNE SYSTEM IN THE BRAIN
AND PROSTATE
By
Jessica Lapierre
ii
ACKNOWLEDGEMENTS
I would like to take the time to express my thanks and gratitude to the numerous members of my
lab and collaborators who have been integral in the completion of my graduate study. First and
foremost, I would like to thank Dr. Jean C. Shih for opening the doors of her lab to me as well as
opening my eyes to the multifaceted world of MAO. During my time here, I was exposed to a
number of the applications of monoamine oxidase in a variety of fields. I am grateful to Dr. Shih
for her time, energy, and patience in fine tuning my research skills and molding me into a
capable student of science.
Next, I would like to thank Dr. Bogdan Olenyuk for opening up his lab and resources to me as a
collaborator of our lab, in addition to serving on my thesis committee. I am also thankful to Dr.
Curtis Okamoto for taking the time out from his busy schedule to serve on my thesis committee.
I would also like to thank Dr. Jack Lin, Dr. Swati Kushal, and Dr. Chun-Peng Liao for their help
in several stages of my graduate research experience. In particular, I would like to express my
deepest gratitude to Dr. Lauren Geary whose guidance and experience were irreplaceable in the
completion of my project. In addition, I would also like to thank Abbey Kardys for her assistance
in the research of my project.
iii
Finally, I would like thank my family and friends for their continuous support and keeping me
sane throughout the completion of the program.
iv
TABLE OF CONTENTS
Acknowledgements ii
List of Figures vi
Abstract vii
Chapter 1: Introduction 1
Chapter 2: Developmental changes in gene expression of MAO A knockout mice lead to
alterations of the immune system
2.1 Background 7
2.2 Materials and Methods 8
2.3 Results
2.3.1 MAO A knockout mice show differential expression of genes 9
at ages P1 and P7
2.3.2 Immune response related genes and pathways are differentially 10
expressed in MAO A knockout mice
2.3.3 MAO A knockout is predicted to alter NFκB and MEK/ERK 13
pathways in canonical T-cell receptor signaling
2.4 Discussion 14
Chapter 3: Prostate-specific Pten and MAO A double knockout mice display
reduced immune suppression conveying anti-tumor immunity
3.1 Introduction 22
3.2 Materials and Methods 25
3.3 Results
3.3.1 Immunohistochemistry of immune response stimulation cell markers 27
v
3.3.2 Immunohistochemistry of immune suppression cell markers and 28
environment
3.3.3 Characterization of “M2” immunosuppressive macrophages 30
3.4 Discussion 30
Chapter 4: Conclusions 37
Bibliography 38
vi
List of Figures
Figure 2.1 Comparison of genes differentially expressed at ages P1 and P7 in 17
MAO A knockout mice vs WT
Table 2.1 Immune response related genes differentially expressed in P1 18
and P7 MAO A knockout mice
Figure 2.2 MAO A knockout show differences between P1 and P7 in aspects 19
of immune response pathways
Figure 2.3a NFκB and MEK/ERK pathways in canonical T cell receptor 20
signaling are altered at P1 of MAO A knockout mice
Figure 2.3b NFκB and MEK/ERK pathways in canonical T cell receptor 21
signaling are altered at P1 of MAO A knockout mice
Table 3.1 Antibody List 26
Figure 3.1 Immunohistochemistry of anti-tumor immune cell markers 33
in mouse prostate tissue
Figure 3.2 Immunohistochemistry of immune suppression cell markers 34
Figure 3.3 Immunohistochemistry of immune suppression markers in 35
mouse prostate tissue.
Figure 3.4 Multiple antigen staining immunohistochemistry of 36
immunosuppressive M2 macrophages in mouse prostate tissue.
vii
Abstract
Monoamine oxidase A (MAO A) is a mitochondrial bound enzyme which is responsible for the
oxidation of neurotransmitters such as serotonin (5-HT) in the brain and peripheral tissue and
produces hydrogen peroxide, a major source of reactive oxygen species. MAO A knockout (KO)
mice show a significant increase in 5-HT which has been implicated in modulation of immune
system cells. This study will investigate if the immune system is indeed altered in MAO A KO
mice and identify essential gene expression changes during critical developmental stages. We
analyzed Affymetrix GeneChip microarray data available in our lab to identify the differentially
expressed genes (DEGs) from MAO A KO mice brains. We found only 2 genes, MAP3K12 and
TCF7, to be significantly different in adult KO mice which were not relevant to the immune
system. Since we have previously shown that MAO A KO mice have the most significant
increase in serotonin at early postnatal ages postnatal day 1 (P1) and postnatal day 7 (P7), we
examined inflammation and immune stimulation gene changes in the MAO A KO mice at ages
P1 and P7. We found 36 genes at P1 and 22 genes at P7 with fold change >2 or <-2 and false
discovery rate (FDR) <0.05. Among them, CCL1, SPP1, ZEB1, and RAG2 are involved in the
regulation of T cell signaling and differentiation. CRP and LTA4H play roles in inflammation.
These results show that knocking out MAO A in mice leads to early developmental changes in
the immune system of the brain which is compensated in adulthood.
We previously found that when MAO A KO mice were injected with LNCaP prostate cancer
cells subcutaneously that the tumors did not grow. To understand the in vivo function of MAO A
in prostate cancer progression, we generated MAO A/Pten double knockout mice (DKO) and
found that deletion of MAO A in Pten knockout mice delayed prostate cancer formation typically
seen in the Pten KO mouse model of prostate cancer. This animal model is used to study if an
viii
altered immune system from knocking out MAO A is responsible for reduced prostate cancer
growth in the Pten KO mouse model. To study the in vivo effect of knocking out MAO A on the
immune system in a prostate cancer model, we used 9 month old prostate-specific Pten single
knockout and MAO A/ Pten DKO mouse prostate tissue and immunohistochemistry to analyze
the number and types of immune cells recruited to the tumor microenvironment. MAO A KO
and wild type mice prostate tissues were used as controls. We found that the MAO A/Pten DKO
mice tissues had higher staining for CD8
+
cytotoxic T cells which indicates immune stimulation.
Conversely, the Pten knockout mice tissues had the highest markers for immunosuppressive cells
such as FoxP3 for T regulatory cells and CD11b for myeloid-derived suppressor cells as well as
iNOS and arginase-1, markers for immune suppression, in the stroma surrounding the tumors.
When characterizing the macrophage population for M1 versus M2 differentiation, it was
observed that there were more F4/80
+
iNOS
+
cells present in the MAO A/Pten DKO than the Pten
KO. However, there were additional iNOS producing cells in the Pten KO not identified as
F4/80
+
macrophages implying production of iNOS from other immune lineages. These results
suggest that there are alterations in the immune system of MAO A knockout mice which may
explain the delayed prostate cancer formation in MAO A/Pten double knockout mice.
1
CHAPTER 1
Introduction
1.1 MAO A and the immune system
Monoamine oxidases (MAOs) are mitochondrial bound enzymes which catalyze the oxidative
deamination of neurotransmitters. This enzyme is found in two isoforms MAO A and MAO B
which are each responsible for the breakdown of certain substrates. MAO A is seen to have a
higher affinity for serotonin (5-HT) and norepinephrine (NE), while the preferred substrate for
MAO B is phenylethylamine (PEA). Both isoenzymes are capable of degrading dopamine (DA),
tyramine, and tryptamine (Shih et al., 1999). The functions of MAO A in particular have been
widely examined in the context of neurological disorders especially depression and more
recently autism but the enzyme is also expressed in non-neuronal tissue (Bortolato et al., 2013a;
Bortolato et al., 2013b; Youdim et al., 2006).
Irregularities in immune system function have been associated with a number of subpopulations
of major neuropsychotropic conditions such as autism spectrum disorders, schizophrenia, and
obsessive compulsive disorder (Obregon et al., 2012). Such irregularities have been
characterized by disruptions in regulatory T cell populations and altered cytokine expression
levels for example, leading to unnecessary immune activation as a result of exposure to
pathogens or stress (Battistini et al., 2003). Prenatal exposure to maternal pro-inflammatory
cytokines has also been reported to be a mechanism of early developmental disruption seen later
as schizophrenia or autism spectrum disorders (Boulanger, 2009; Derecki et al., 2010).
Alternatively, a similar connection has been shown in individuals with autoimmune disorders
2
such as multiple sclerosis and Grave’s disease having symptoms of depression and other
neuropsychiatric disease (Bunevicius and Prange, 2006).
One of the most researched mechanisms of the immune link to neuropsychiatric disorders lies in
the “tryptophan hypothesis of depression.” Tryptophan is degraded via indoleamine 2,3-
dioxygenase (IDO), a non-specific enzyme for any indole containing compound. It was seen that
tryptophan depletion following its increased breakdown was associated with increased
inflammation and pro-inflammatory cytokines during depression (Maes et al., 1993; Song et al.,
1998). During an enhanced inflammatory state, there is higher IDO activity and breakdown of
tryptophan. Since serotonin is made from tryptophan, depletion of tryptophan causes
serotonergic abnormalities as characterized in a number of neurological disorders such as
depression (Capuron et al., 2002; Maes et al., 2002). This serves as a feedback loop causing the
increase of pro-inflammatory cytokines typical of the depressive state. Since monoamine oxidase
A is the primary enzyme for the degradation of serotonin, it is also a target for modulation in
depression. If it possible for monoamine oxidase A inhibitors to regulate the immune system in
depression, then it is curious to see how MAO A deficiency can also affect the immune system.
1.2. MAO A in Prostate Cancer
Prostate cancer (PCa) is one of the most commonly diagnosed forms of cancer in males as well
as the second leading cause of death from cancer in men (Jemal et al., 2009). Classified as an
adenocarcinoma, prostate cancer begins with a mutation in the prostate gland cells which
normally secrete semen (Gittes, 1991). Prostate cancer is usually diagnosed in men over 65 years
of age with severity depending on a number of factors which determine the prognosis (Westdorp
3
et al., 2014). In general, the severity is determined by the histological grade (Gleason score),
TMN staging, and levels of prostate specific antigen (PSA) (Siegel et al., 2013).
A number of mutations have been attributed to the tumorigenesis of cancer. Loss of function
mutations in tumor suppressor genes or aberrant overexpression mutations in oncogenes are quite
common in a number of cancers including prostate cancer (Mazaris and Tsiotras, 2013).
Frequently modified pathways implicated in prostate cancer include the oncogenes c-Myc and
Bcl-2 as well as the androgen receptor which is highly overexpressed in many prostate cancers
(Hughes et al., 2005; Karan et al., 2003). Tumor suppressor genes often altered in prostate cancer
include p27 and p53 which play roles in regulating the cell cycle, as well as the phosphatase and
tensin homolog protein (PTEN) which is seen in a high percentage of prostate cancers (Hughes
et al., 2005; Sun et al., 1999). All of these genes are currently common highly sought after for
therapeutic targeting; however, other targets contributing to the lethality of prostate cancer are
being researched to better existing therapies and improve outcomes.
We and others have recently found that MAO A is highly overexpressed in high grade (Gleason
grade 4 and 5) prostate cancer tissue which suggests a potential role of the enzyme in prostate
cancer progression (True et al., 2006; Wu et al., 2014). In addition, it was seen that higher levels
of MAO A in prostate cancer patients with Gleason score 4/5 had increased prostate-specific
antigen (PSA) and suggested higher probability for the development of castration resistant
prostate cancer following prostatectomy or androgen deprivation (Peehl et al., 2008). When it
was discovered that MAO A played a role in the tumorigenesis of prostate cancer, our MAO A
knockout mouse model was adapted for the purposes of studying the function of host MAO. We
4
found that when our MAO A knockout mice were subcutaneously injected with various prostate
cancer cell lines, the tumors displayed drastically reduced proliferation and size as well as
extended survival as compared to the WT tumor-bearing mice (unpublished).
Investigations into the role of MAO A in prostate cancer illustrated that when treated with the
MAO A irreversible inhibitor clorgyline, both differentiation as well as mRNA and protein
expression of the androgen receptor (AR) were induced in normal prostatic basal epithelial cells
(Zhao et al., 2009; Zhao et al., 2008). These findings proposed the potential of MAO A being
involved in maintaining an undifferentiated phenotype in high grade primary prostate cancer
(Flamand et al., 2010). In addition, our lab has observed that when tumor-bearing athymic nude
mice were treated with the MAO A irreversible inhibitor antidepressant clorgyline, there was
reduction in tumor burden paralleling the effect seen in the knockout mice (Wu et al., 2014).
Inhibitors such as clorgyline can irreversibly reduce the activity of MAO A in the cancer cells
but it also has downstream effects due to the other physiological roles of the enzyme.
Typically, monoamine oxidase inhibitors such as clorgyline are well established as
antidepressants in the treatment of mood disorders and major depression. A variety of pathways
are seen to be altered in the etiology of depression and with antidepressant treatment, these
pathways are normalized by altering either the synthesis or reuptake of neurotransmitters at the
synapse (Maes et al., 2012). In terms of cancer, a link between antidepressant use and cancer has
been proposed; however, there seems to be contradictory data as well as cancer-
type/antidepressant specificity (Cosgrove et al., 2011). Other selective serotonin reuptake
inhibitors (SSRIs) have also been tested and shown antitumor effects in an assortment of human
5
cancer cell lines (Frick and Rapanelli, 2013). The use of antidepressants as anti-cancer agents has
an effect not only directly on the cancer cells but also on the microenvironment surrounding the
tumor.
1.3 The tumor microenvironment
The earliest ideas on the interplay between tumors and its surrounding microenvironment were
introduced by Stephen Paget with the concept of the “seed and soil” theory (Pienta et al., 2013).
Today it is widely accepted that there is a continuous crosstalk between the tumor and its
environment which contribute to its tumorigenicity by facilitating the growth and potential
malignancy in cancer. The microenvironment is a highly diverse area surrounding the tumor
consisting of vascular endothelial cells, mesenchymal cells such as fibroblasts, soluble factor
such as cytokines and hormones, immune cells, and extracellular matrix (Swartz et al., 2012;
Zhong et al., 2008). Angiogenesis and metastasis, two key hallmarks of cancer, are both
dependent on the surrounding microenvironment (Colotta et al., 2009). As of late, the tumor
microenvironment has been a therapeutic target of increasing interest for a number of cancers.
For example, bevacizumab has been clinically approved to treat a number of cancers through the
targeting of microenvironment secreted VEGF-A which is an important factor in angiogenesis
(Glade-Bender et al., 2003).
During oncogenesis, the host tumor microenvironment is severely altered in order to sustain
tumor growth and encourage metastasis. “Activation” of stromal cells in the tumor
microenvironment causes the secretion of factors which promote angiogenesis, tumor cell
proliferation, and immune suppression (Bohonowych et al., 2014; Qian and Pollard, 2010).
6
Vascular cells are responsible for neovascularization in the cancer environment and increases the
rates of cancer cell proliferation making it a hallmark of cancer (Folkman, 1974). Cancer
associated fibroblasts (CAFs) are taken over by the neighboring cancer cells which begins a
feedback loop through the secretion of growth factors such as transforming growth factor-β
(TGF-β), platelet-derived growth factor, and interleukin (IL)-6 (Kalluri and Zeisberg, 2006).
Activated CAF’s alter the composition of the extracellular matrix which creates a tumor-
promoting inflammatory environment similar to that during wound repair (Haddow, 1972).
Reactive stroma during wound repair leads to the secretion of angiogenic and inflammatory
cytokines which causes the recruitment of immune cells and chronic inflammation conducive to
tumor growth (Bhowmick et al., 2004).
There have been a number of studies researching the molecular and mechanistic pathways of
MAO A involvement in cancer. MAO A’s contributions to reactive oxygen species have already
been found to predispose cancer cells to DNA damage and cause tumor initiation (Shih et al.,
2011). However, based on the interplay between serotonin and immune modulation, it was of
interest to examine the role of MAO A within the tumor microenvironment in terms of the
immune axis within a mouse model. This was done using established MAO A knockout and
PTEN null mouse models and immunohistochemistry.
7
CHAPTER 2
Developmental changes in immune gene expression of MAO A knockout mice
2.1 Background
Monoamine oxidase has an established role in depression and neurological disease. Our lab
discovered a spontaneous nonsense point mutation in exon 8 of the MAO A gene in mice (Scott
et al., 2008). This mutation was analogous to the human disorder Brunner syndrome which is
characterized by complete MAO A deficiency and aggression. This initial finding lead to
subsequent studies on the role of MAO A in autism and other neurological disease in early post-
natal development. MAO A inhibitors have already been established for use as antidepressants
and are currently being explored for other uses.
Antidepressants are seen to act on many pathways including the immune axis due to depression
being a multifactorial and complex disease. As such, the link between the pathogenesis of the
depression and deregulation of the immune system is well established (Pollak and Yirmiya,
2002). Patients with major depression were reported to exhibit elevations in peripheral blood
concentrations of acute phase proteins, chemokines, adhesion molecules, and inflammatory
mediators such as prostaglandins (Bufalino et al., 2013). Neurotransmitters are known to regulate
major immune functions such as lymphocyte activity, proliferation, and the secretion of
cytokines including the selection of differentiated T-helper cell cytokine responses (Elenkov,
2008). It has been reported that low doses of serotonin can act as a stimulus for T-lymphocyte
8
function (Young et al., 1993). Also, Martino et al. collected data illustrating the effects of
neurotransmitters on cytokine production (Martino et al., 2012).
Since antidepressants were seen to have effects on the immune system, it is likely that changes to
the proteins which they target may also be capable to modulating the immune system as well.
We hypothesize that as a result of knocking out MAO A in young mice, the elevated circulating
serotonin levels act as a stimulus for T-lymphocytes and Th1 polarized cytokine production. To
determine this, we used brain microarray to analyze the genomic changes to the immune system
in the mice as a result of knocking out MAO A.
2.2 Methods
RNA was isolated from the brains of MAO A KO mice (n=5) at ages P1 and P7. Affymetrix
GeneChip microarray analysis was performed by Dr. Boris Tabakoff at the University of
Colorado. Partek Genomic Suite was used to perform the statistical analysis of gene expression
between the knockout and the wild-type mice at ages P1 and P7. A fold change cut off of >2 or
<-2 in either P1 or P7 was applied to narrow the results with FDR (false discovery rate) of <0.05.
Partek Genomic Suite (PGS) was used to create a Venn diagram comparing the number of
differentially expressed genes in P1, P7 and in both. Ingenuity Pathways Analysis (IPA) was
used to identify immune response related genes in the data set as well as categorize them into
immune response classifications. The immune categories was translated into heat map form
using Partek Genomic Suite (PGS). To identify any existing associations to cancer, an IPA
search was used to determine if any of the immune response related genes had been associated
9
with prostate cancer or its pathogenesis. In order to explore the signaling pathways of interest,
IPA was used to search the canonical signaling pathways of serotonin signaling as well as T-cell
receptor signaling. The grow function was used to identify established links between the genes of
interest within the two pathways. The Molecule Activity Predictor (MAP) function was used to
predict the downstream effects of the differential gene expression within the signaling pathway.
2.3 Results
2.3.1 Differential expression of genes at ages P1 and P7 in MAO A knockout mice
The gene expression profile in the brains of the MAO A knockout mice was found to be altered
at ages P1 and P7 from the age-matched wild type mice. Figure 2.1 shows the number of genes
that were differentially expressed in P1 versus P7. Initially, the data yielded over 12,000
statistically significant genes showing differential expression in the P1 and P7 analysis groups.
The expansive dataset was condensed using the fold change cutoffs, limiting the list of
differentially expressed genes to those with a fold change greater than 2 or less than -2 in either
P1 or P7, as well as a minimal false discovery rate (FDR) of less than 0.05. The Venn diagram
was created to compare the number of differentially expressed genes in P1 vs P7 possessing a
minimum twofold up-regulation or down-regulation. From this new criteria, the number of
differentially expressed genes was reduced to 395 with 29 of them being common to both P1 and
P7. Comparing P1 and P7 there were 147 and 219 genes which were uniquely differentially
expressed at P1 and P7 respectively. This result shows that knocking out MAO A has an effect
on the downstream gene profile, the extent of which, may be development dependent.
10
2.3.2 Immune response related genes are differentially expressed in MAO A knockout mice
Since the role of serotonin in immune modulation has been established, we hypothesized that the
increased serotonin as a result of knocking out MAO A would have an effect on the expression
of genes related to immune function. Table 1 shows the immune response related genes which
were extracted from the dataset of genes falling within the 2 fold change. With IPA, it was
possible to integrate and overlay the microarray data with known immune response pathways
and functions. By selecting for genes with known associations to immune response according to
IPA annotations, the number of genes of interest was narrowed down to 58 differentially
expressed genes at P1 and P7. The expression criteria identified 36 immune response related
genes out of the 147 genes differentially expressed in P1 and 22 genes out of the 219 DEGs in
P7. It is interesting to note that there were more immune response related genes altered at P1
than P7 because in all of the data, the majority of genes changed were found in P7.
Following the identification of the differentially expressed immune response-related genes, we
examined the immune response processes that these genes may be involved in. The heat maps
seen in Figure 2.2 illustrate the range of fold change intensities for the given immune response
categories. IPA was used to assemble various categories underneath the umbrella term ‘immune
response’ to potentially identify immune response pathways that may be enriched as a
consequence of knocking out MAO in the mice. Searching GO terms in IPA such as ‘cytokines’,
‘inflammation’, ‘chemotaxis’, ‘humoral immunity’ and ‘cell-mediated immunity’ provided gene
lists that fit both the immune response and 2 fold change criteria. The heat maps aided in
11
visualizing trends within the immune response sub-categories which may not have seen. Within
each of the categories, there were genes that played roles in a number of immune response
processes such as inflammation, chemoattraction, and lymphocyte signaling.
Leukotriene A4 hydroxylase (LTA4H: P1=2.017 P7=1.816) is one of the many immune response
related genes which are altered within the microarray. This enzyme is responsible for the
hydrolysis of leukotriene A4 (LTA4) to leukotriene B4, which is a potent chemoattractant and
activator of inflammatory cells when overexpressed (Byrum et al., 1999; Mancini and Evans,
1995; Thunnissen et al., 2001). As such, LTA4H is seen to regulate inflammatory response,
cytokine production, and cell proliferation. C-reactive protein (CRP: P1=0 P7=2.13565) is a
well-established immune response related gene. Found in the blood and plasma, CRP levels are
known to be representative measurements of systemic inflammation (Mold et al., 2002). It serves
a variety of functions as part of the acute phase response with both pro and anti-inflammatory
properties (Clynes et al., 1999; Stein et al., 2000). Osteopontin (SPP1: P1=-2.082 P7=0) is also
known as the early T lymphocyte activation protein and is expressed in a variety of immune cells
including macrophages, dendritic cells, neutrophils, eosinophils, NK cells, NKT cells, and T and
B lymphocytes(Inoue and Shinohara, 2011; Sennels et al., 2008). This protein is a cytokine and
macrophage chemoattractant and has been implicated in the early stage polarization of Th cells
to the Th1 or Th2 phenotype (Baroni et al., 2012). SPP1 is another gene which has been seen to
modulate the inflammatory response.
The recombination activating gene 2 (RAG2: P1=0 P7=2.164) protein product is responsible for
the recombination which is necessary in the production of T-cell receptors and immunoglobulins
12
(Shinkai et al., 1992). Various experiments have identified it as being essential in immune
system function (Noordzij et al., 2002). CCL1 (P1=2.238, P7=0) is a cytokine secreted by
activated T lymphocytes and is one of the many cytokines which plays a role in chemoattraction
(Miller and Krangel, 1992). Being the ligand for the CCR8 cytokine receptor(Garlisi et al., 1999;
Roos et al., 1997), it has been reported that upon triggering of the TCR by CCL1 binding, that Th
polarization is induced (Iellem et al., 2000; Mira et al., 2008; Zingoni et al., 1998). In addition,
CCL1 has been seen to play another role in the recruitment of regulatory T-cells (Butti et al.,
2008). ZEB1 (P1= -1.557, P7=2.260) is a zinc finger protein which encodes the zinc finger E-
box-binding homeobox 1 protein. This transcription factor is responsible for the repression of the
IL-2 gene on T lymphocytes (Williams et al., 1991). Mutant mice have various abnormalities in
thymic T cell development (Takagi et al., 1998).
Some of the genes altered within the microarray played roles in the cellular signaling occurring
within the immune processes. For example, PIK3CD (P1=3.0767 P7=1.508) is a member of the
phosphoinositide 3-kinases which plays a role in signal transduction with various receptors. This
gene is the catalytic subunit of the p110 delta isoform which has been seen to be exclusively
found in leukocytes (Vanhaesebroeck et al., 1997) and occasionally in neurons (Eickholt et al.,
2007). While PI3K signaling is often seen in many pathways, it is of interest that PI3KCD can be
seen in B cell receptor signaling cascades, cytotoxic T lymphocyte function, as well as mast cell
degranulation which all play a role in inflammatory responses(Putz et al., 2012; Tanemura et al.,
2009). Additionally, pathways within T cell signaling such as the MEK/ERK were also altered.
13
2.3.3 NFκB and MEK/ERK pathways in canonical T-cell receptor signaling are altered in MAO
A knockout mice at P1 and P7 as shown by IPA
A number of genes differentially expressed within the MAO A knockout microarray were related
T-cell functionality, differentiation, and receptor activity. As such, it was of interest to see what
mechanisms and pathways linked to T-cells were modified as a result of MAO A knockout. To
determine what immune response signaling pathways may have been altered in the microarray,
IPA was used to single out canonical pathways of interest related to immune signaling. Figure2.3
shows the canonical signaling pathway for T-cell receptor signaling with the fold-changes of the
differentially expressed genes at P1 (A) and P7 (B). The Molecule Activity Predictor (MAP)
function allows for the prediction of activation and inhibition states of the pathway based upon
the differentially expressed genes. This in turn has the potential to encourage or inhibit the
transcription of other immune genes such as the ones seen in the microarray. Figure 2.3A shows
the T-cell receptor signaling pathway genes at P1 which is predicted to lead to activation of the
pathway. Activation of this pathway may result in the production of cytokines specific to Th1 or
Th2 polarization of T-cells. Conversely, Figure 2.3B shows the T-cell receptor signaling
pathway at P7 and is predicted to lead to the inhibition of the pathway. One reason for this could
possibly be a compensatory mechanism to balance out the initial response. Within the pathway,
the MEK/ERK and NFκB signaling pathways are of particular interest due to the existing link to
serotonin levels and T-cell receptor activation (León-Ponte et al., 2007).
14
2.4 Discussion
The versatile roles of monoamine oxidase A in the body have far and reaching effects. Through
the knocking out of MAO A in mice, we have been able to being to estimate how far its reach
extends. Here we have hypothesized how alteration of MAO A expression during early
development leads to changes within the immune system. It has already been shown that
knocking out MAO A in mice has an effect on the behavioral level with a marked increase in
aggression as well as displaying autistic-like behavior (Bortolato et al., 2013a). On the
molecular level, the global genetic effects of knocking out MAO A were seen in the microarray
analysis at ages P1 and P7. With over 12,000 genes being differentially expressed in the MAO A
knockout mice, it can be seen that the early alteration of MAO A levels has an effect on a wide
variety of genes and signaling processes. However, it must be noted that in adult MAO A
knockout mice microarray analysis, only two genes (TCF7 and MAP3K12) were differentially
expressed and considered significant. This suggests that the genetic alterations seen at P1 and P7
were normalized during maturation.
Since monoamine oxidase A is responsible for the degradation of serotonin, knocking out MAO
A will result in elevated serotonin levels in storage and circulation. Being that serotonin can
function as both a neurotransmitter and regulator of immune responses, we analyzed what
immune response-related genes may have been differentially expressed within the MAO A
knockout microarray. We observed over 50 genes with varying connection to immune response
as determined by the Ingenuity Pathway Analysis annotation database. Genes of interest included
CCL1, SPP1, ZEB1, RAG2, CRP and LTA4H. The functions of the genes involved in T cell
15
regulation and signaling each coincided with their differential expression at each age and an
enhance immune response followed by normalization. CCL1 is secreted by activated T
lymphocytes and plays a role in chemoattraction (Miller and Krangel, 1992). One of the key cells
that CCL1 recruit are T regulatory cells which are involved in immune tolerance and immune
suppression (Butti et al., 2008). This follows along with the observed up-regulation of CCL1 at
P7 from the microarray data. RAG2 is responsible for the initiation of V(D)J recombination in B
and T cells during development (Casillas et al., 1995). This gene was seen to be up-regulated at
P7 in the microarray which could be hypothetically supported by the need for increased variation
in B and T cells later in adulthood following the early immune stimulation at P1. ZEB1 is one of
the few genes to be up-regulated at one age and down-regulated in the other. Despite this, its role
in T lymphocyte repression still falls in line with the microarray. ZEB1 being down-regulated in
the microarray data at P1 supports the early immune stimulation hypothesis because its down-
regulation leads to less repression of T lymphocyte IL-2 gene expression which is essential for T
cell activation (Williams et al., 1991). Alternatively, its up-regulation at P7 serves to balance the
previous unrepressed action of IL-2 expression. The genes mediating inflammation also
supported MAO’s potential role in modulating immunity. LTA4H and CRP both take part in
regulating acute inflammation and are also both up-regulated within our microarray data.
Increased inflammation at P1 can also play a part in the early immune challenge following MAO
A knockout.
On a mechanistic level, our results suggested that the knocking out of MAO A in mice led to an
alteration in canonical T-cell receptor signaling due to the stimulatory and inhibitory effects of
serotonin on T-cell function. At P1, MEKKK/JNK, NFκB, and MEK/ERK signaling were all
16
predicted to be activated when overlayed with the differentially expressed gene fold-changes.
This is further supported by Leon-Ponte et al. in their work on serotonin enhancement of T-cell
activation (León-Ponte et al., 2007). They reported that naïve primary T-cells from mice spleens
express serotonin receptors (5-HT7) which were greatly expressed upon T-cell activation as well
as subsequent expression of other 5-HT receptors. In addition, when exogenous 5-HT was added
to the naïve T-cells, there was rapid phosphorylation of ERK and IκBα of the ERK and NFκB
signal transduction pathways which are an essential in the activation and translocation of
transcription factors required for T-cell activation, IL-2 synthesis, and proliferation.
This supports the hypothesis that in early development, serotonin has a simulative effect on
immune processes. At P7, all the signaling pathways in T-cell receptor signaling are predicted to
be inhibited when overlayed with the differentially expressed gene fold-changes. This is opposite
to that of P1 and may be due to compensatory mechanisms. Another explanation for the opposite
prediction of TCR signaling is the extended period of high levels of serotonin may be inhibiting
T-cell activation and proliferation (Young et al., 1993). It has been reported that high levels of
exogenous serotonin may be immunosuppressive and inhibit the lytic function of effector T-cells
and lymphokine –activated killer cells due to serotonin acting as a blocker of K
+
ion channels
involved in the lytic process (Henley and Bellush, 1992; Kut et al., 1992; LeFever et al., 1989).
The immune response related genes differentially expressed at P1 and P7 have the potential to
alter the immune environment during development which may later present itself as an “immune
priming” in adulthood with a number of possible effects.
17
Figure 2.1 Venn diagram comparison of genes differentially expressed at ages P1 and P7 in
MAO A KO mice vs wild type. Statistical analysis using Partek Genomic Suite identified
differentially expressed genes in the MAO A KO vs WT mice (FC >2 or < -2, FDR=0.05) at ages P1
and P7.
18
Table 2.1. Immune response related genes differentially expressed in P1 & P7 MAO A KO
mice. Ingenuity Pathway Analysis was used to identify genes associated with immune response
functions from the established set of statistically significant genes (FC > 2 <-2, FDR<0.05)
obtained from Partek Genomic Suite
19
Figure 2.2.MAO A knockout mice show differences between P1 and P7 in immune response
categories. IPA was used to group the differentially expressed immune response related genes
into general sub-categories. PGS was used to create a genomic heat map to illustrate the range
of expressions. (a) Categories: Cytokine, Inflammation, Chemotaxis (b) Humoral Immune
Response, Cell-Mediated Immune Response
20
Figure 2.3A. NFκB and MEK/ERK pathways in canonical T-cell receptor signaling are altered at
P1 of MAO A knockout mice. Using IPA software, a canonical T-cell receptor signaling pathway
was overlayed with the differentially expressed gene analysis at P1 (A). The Molecule Activity
Predictor (MAP) function was used to predict the downstream effects of differential
expression. (A) At P1, MAP predicts activation of MEKK/JNK, NFκB, and MEK/ERK pathways in
T-cell receptor signaling pathways.
21
Figure 2.3B. NFκB and MEK/ERK pathways in canonical T-cell receptor signaling are altered at
P7 of MAO A knockout mice. Using IPA software, a canonical T-cell receptor signaling pathway
was overlayed with the differentially expressed gene analysis at P7 (B). The Molecule Activity
Predictor (MAP) function was used to predict the downstream effects of differential
expression. At P7, MAP predicts inhibition of the MEKK/JNK, NFATc, NFκB, and MEK/ERK
pathways in T-cell receptor signaling.
22
CHAPTER 3
Prostate-specific PTEN and MAO A double knockout mice display reduced immune suppression
conveying anti-tumor immunity
3.1 Background
The chemokines, cytokines, and interleukins released by the reactive stroma and tumor cells
regulate the recruitment of immune cells and mediate inflammation within the
microenvironment. Innate immune cells such as mast cells, macrophages, granulocytes,
dendritic cells, and natural killer cells are the early inducers of inflammation during immune
challenge (Johansson et al., 2008). Upon interaction with foreign antigens including tumor
antigens, antigen presenting cells such as dendritic cells and macrophages can recruit adaptive
immune response cells such as B cells, cytotoxic CD8
+
T cells, and CD4
+
T helper cells
(Johansson et al., 2008).
It has been accepted that the infiltration of lymphocytes into the tumor microenvironment is an
essential factor in mounting an antitumor effect. Antitumor responses are most often promoted
by natural killer cells, CD8
+
cytotoxic T cells, macrophages and CD4
+
helper T cells; however,
the cytokine profile within the environment determines the effects they may have against the
tumor (Appay et al., 2002; Dunn et al., 2004). T helper cells which serve to prime the CD8
+
T
cells, can differentiate into T helper-1 (Th1) cells and Th2 cells which each produce specific
types of cytokines (Huang et al., 2013). Th1 polarized T-cells secrete cytokines such as IFN-γ,
IL-2, and TNF-β which are involved in the stimulation of the functional activity of cytotoxic
23
cells, natural killer cells, and classically activated macrophages for cell-mediated immunity
(Elenkov, 2008). Th2 cells mainly produce IL-4, IL-5, IL-6, IL-10, and IL-13 which stimulate
mast cells, eosinophils, and the differentiation of B cells into antibody secreting B cells which
comprise humoral immunity (Elenkov, 2008).
Macrophages make up a great number of the immune cells within the tumor microenvironment.
Tumor-associated macrophages are abundant in stroma surrounding tumors mediating
inflammation (Wong et al., 2009). It has been demonstrated that the cytokines which determine
the polarization of T helper cells also leads to differential macrophage programming (Ruffell et
al., 2012). Distinct characterizations of macrophage populations have been identified which play
different roles in the immune system depending on its environment. M1 macrophages are
considered “classically activated” macrophages which are induced by Th1 cytokines such as
IFNγ (Comito et al., 2014). These macrophages possess tumoricidal activity and produce
inflammatory cytokines for the purposes of clearing pathogens, targeting tumors, and activating
the immune response (Bevan, 2006; Edin et al., 2012).
Despite the capability of antitumor immune cells to mount immune responses, tumors have a
number of mechanisms to escape immune action (Adler, 2007; Sadun et al., 2007). Myeloid-
derived suppressor cells (MDSCs) are a heterogeneous subset of innate immune cells which play
a significant role in tumor immune tolerance. Identified by CD11b
+
marker, these cells directly
mediate T cell suppression as well as expand other immunosuppressive cells such as M2
macrophages and T regulatory cells (Lechner et al., 2010; Zhong et al., 2008).
CD4
+
CD25
+
FoxP3
+
T cells are known as T regulatory cells which function to prevent
24
autoimmune disease and exhibit immune tolerance (Zou, 2005). In cancer, these cells are often
recruited to the tumor microenvironment and induce immune suppression by repressing the
activity of cytotoxic T cells through cytotoxic T-lymphocyte antigen 4 (CTLA4) (Johansson et
al., 2008).
Th2 cytokines such as IL-4 and IL-10 direct macrophages toward “alternatively activated” M2
differentiation. In normal tissue, M2 macrophages serve to restore homeostasis in damaged tissue
by promoting tissue repair and angiogenesis as seen in wound healing (Martinez et al., 2009).
However, when Th2 cytokines recruit M2 tumor associated macrophages, they produce factors
that can favor tumor progression such as epidermal growth factor (EGF), fibroblast growth factor
1 (FGF1), vascular endothelial growth factor A (VEGFA), and matrix metallopeptidases
(MMPs) (Edin et al., 2012). In addition, M2 macrophage populations have been shown to
mediate immunosuppression through the direct inhibition of CD8
+
T cell proliferation.
Mechanisms utilized by M2 macrophages and myeloid-derived suppressor cells include the
metabolism of L-arginine through arginase-1 or inducible nitric oxide synthase (iNOS).
Activation of iNOS suppresses T cells through the production of nitric oxide which inhibits
signal transduction. Arginase-1 also degrades L-arginine leading to the formation of reactive
nitrogen and oxygen species (Doedens et al., 2010).
Based on our previous work with MAO A knockout mice and the existing literature, we shall
study the immune cell profiles from 4 experimental mice groups (wild type, MAO A KO, Pten
KO, and MAO A/Pten KO). We expect to see the in vivo effect of knocking out MAO A in the
Pten knockout mouse model of prostate cancer on the immune system in the form of immune cell
25
recruitment into the tumor microenvironment. This data may provide an explanation as to why
knocking out MAO A has the ability to reduce prostate cancer growth.
3.2 Methods and Materials
Generation of prostate-specific PTEN/MAO A double knockout mice
Prostate epithelial cell-specific conditional Pten knockout mice, carrying the Cre transgene and
floxed PTEN alleles were obtained as described by Wang et al.(Wang et al., 2003). The
conditional MAO A/Pten double knockout mouse model was generated by mating female MAO
A
flox/flox
mice with male mice from the conditional Pten knockout model. The breeding scheme
for the experimental mice as well as subsequent genotyping to confirm the presence or lack of
the MAO A and Pten proteins was followed as described by Lin et al. (unpublished). All mice
utilized for these experiments were 9 months old with the exception of one Pten KO mouse (age
6 mos) which showed advanced tumor stage similar to the other 9 month old Pten KO mice.
Immunohistochemical analysis
Dorsolateral prostate tissues were collected from nine month old wild-type, MAO A knockout,
Pten knockout, and Pten/MAO A knockout mice and incubated in buffered zinc formalin
overnight at 4° C then washed twice in PBS for 30 minutes before storing in 70% ethanol.
Tissues were paraffin embedded then cut to 5μm sections onto glass microscope slides. Paraffin
embedded prostate tissue sections were deparaffinized in xylene and rehydrated with ethanol and
water before being entering antigen retrieval in 10 mM sodium citrate buffer, pH 6.0 for 15
minutes at 95° C. Tissues were blocked in 10% normal goat serum in PBS containing 0.3%
26
Triton X-100, pH 7.6 for one hour at room temperature. Tissues were probed with antibodies at
optimized dilutions overnight at 4°. Tissues were washed extensively with PBS, pH 7.6.
Detection was performed using appropriate IgG secondary antibody for 30 minutes at room
temperature, followed by ABC reagent and DAB substrate. Tissues were counterstained with
hematoxylin and visualized by light microscopy.
Procedure for mouse antibody on mouse tissue immunohistochemistry was followed as described
by Vector labs using a mouse on mouse kit. Multiple antigen staining was performed as
recommended by Vector Labs. Vector Blue© and Vector Red© (Burlingame, CA) chromogen
substrates were used for antibody staining. Tissues used for multiple antigen staining were
counterstained with methyl green and visualized by light microscopy. Antibodies were
generously provided as a gift by the laboratory of Dr. Alan Epstein.
Antibody Manufacturer Dilution
CD8 Epstein Lab 1:200
CD11b Epstein Lab 1:200
F4/80 (Cat.# SC71085) Santa Cruz
1:200
1:100 (Multiple Antigen)
FoxP3 (Cat.# AB54501) Abcam 1:400
iNOS (Cat.# AB15323) Abcam
1:200
1:400 (Multiple Antigen)
Arginase-1(Cat.# 610709) BD Biosciences 1:200
Table 3.1. Antibody List. Antibodies and their dilutions for immunohistochemistry are listed.
Statistical analysis
Representative images were taken from each animal group (n=3, 3-5 images per mouse). All data
are presented as mean ± SD. Differences were analyzed by two-tailed t-test with unequal
variance. P values of <0.05 were considered to be statistically significant. ImageJ software was
used for the quantification of images.
27
3.3 Results
3.3.1 Immunohistochemistry of immune stimulatory cell markers
In order to investigate the effects of knocking out MAO A in the Pten knockout prostate cancer
mouse model on the anti-tumor immune response, we performed immunohistochemistry for
markers of CD8
+
cytotoxic T cells and F4/80
+
macrophages. Figure 3.1A shows a comparison of
wild type, MAO A knockout, Pten knockout, and MAO A/Pten double knockout dorsolateral
mouse prostate tissues with staining for these markers. MAO A/Pten double knockout tissue
showed higher positive staining for CD8 than that of the Pten single knockout with 52% more
CD8
+
cells (P<0.005) (Figure 3.1B). No positive staining was seen in the wild type or MAO A
knockout tissues which was expected due to lack of immune challenge. CD8 is a transmembrane
glycoprotein acting as a co-receptor for the T cell receptor (TCR) which binds to major
histocompatibility complex class I proteins. The CD8 receptor is expressed on the surface of
cytotoxic T cells which act as the effectors of adaptive immunity (Gao and Jakobsen, 2000). This
shows that knocking out MAO A in the Pten knockout mouse model of prostate cancer increases
the recruitment of CD8
+
cytotoxic T cells in the tumor stroma.
There was no significant difference in F4/80 positive staining between the MAO A/Pten double
knockout and Pten KO mice prostate tissues (P>0.05) (Figure 3.1C). The wild type and MAO A
knockout tissues showed little to no positive staining for F4/80. F4/80 is the mouse homologue
for the EGF-like module-containing mucin-like hormone receptor-like 1 (Emr1) protein. Emr1 is
a transmembrane protein expressed on the surface of mature macrophages derived from myeloid
lineage (Leenen et al., 1994). F4/80 is the most widely accepted marker of macrophages in mice.
28
These results reveal that knocking out MAO A in the Pten knockout mouse model of prostate
cancer shows no apparent effect on the recruitment of macrophages to the tumor
microenvironment.
3.3.2 Immunohistochemistry of immune suppression cell markers and environment
Immune suppression within the tumor microenvironment is a key characteristic in cancer which
facilitates the progression of the disease. In order to analyze if knocking out MAO A in the Pten
knockout mouse model of prostate cancer can reduce the number of immunosuppressive cells
within the surrounding stroma, immunohistochemistry for markers of FoxP3
+
T regulatory cells
and CD11b
+
myeloid-derived suppressor cells was performed. Figure 3.2A shows the staining
for these markers in the wild type, MAO A knockout, Pten knockout, and MAO A/Pten double
knockout dorsolateral mouse prostate tissue. The MAO A/Pten double knockout showed a 40%
decrease in the number of FoxP3
+
T regulatory cells as compared to the Pten knockout despite
slight background (P<0.05) (Figure 3.2B). The positive staining was most commonly found in
the stromal areas closest to the tumors. Wild type and MAO A KO controls also showed positive
staining for FoxP3; however, this may be due to the small immune cell to stromal cell ratio
within these tissues. FoxP3 is a protein transcription factor which functions as a key regulator in
the development of T regulatory cells. T regulatory cells are CD4
+
CD25
+
; however, FoxP3 is the
most widely used and most specific marker currently available to identify T regulatory cells
(Adler, 2007).
The MAO A/Pten double knockout showed a greater difference for CD11b than FoxP3 with a
78% decrease in CD11b
+
myeloid-derived suppressor cells in the MAO A/Pten double knockout
29
as compared to the Pten knockout (P<0.05) (Figure 3.2C). CD11b, also known as integrin alpha
M, is expressed on many leukocytes such as monocytes, neutrophils, and granulocytes serving to
regulate leukocyte adhesion and migration during inflammatory responses (Stewart et al., 1995).
It is also considered a surface marker for tumor-infiltrating myeloid cells (Priceman et al., 2010),
in particular myeloid-derived suppressor cells with an expression pattern of CD11b
+
CD33
+
(Lechner et al., 2010). This data shows that knocking out MAO A in the Pten knockout mouse
model of prostate cancer can reduce the number of immunosuppressive cells recruited to the
tumor microenvironment.
Cytokines and enzymes present in the tumor microenvironment also contribute to the immune
suppression by converting monocytes present to support tumor growth or by inhibiting T cell
tumoricidal function. Immunohistochemistry was done using markers for inducible nitric oxide
synthase (iNOS) and arginase-1 (arg1) which both facilitate immunosuppression. Figure 3.3A
illustrates the differences between the MAO A/Pten double knockout and Pten knockout mouse
tissues in terms of an immunosuppressive tumor microenvironment environment. The MAO
A/Pten double knockout showed an 80% reduction in iNOS
+
staining as compared to the Pten
knockout indicating a less immunosuppressive environment (P<0.005) (Figure 3.3B). Arginase-1
was also decreased by 75% from the Pten KO to the MAO A/Pten double knockout (P<0.05)
(Figure 3.3C). These results suggest that knocking out MAO A in the Pten knockout mouse
model of prostate cancer leads to a reduction of immune suppression within the tumor
microenvironment.
30
3.3.3 Characterization of “M2” immunosuppressive macrophages
In order to identify whether the immune cells present within the tumor environment were pro-
tumorigenic or anti-tumorigenic, multiple antigen staining was utilized to co-localize markers of
monocytes with iNOS. To determine the reduction of M2 polarized F4/80
+
macrophages present
in the MAO A/Pten double knockout as compared to the Pten knockout prostate cancer model,
F4/80
+
cells were stained by immunohistochemistry with Vector Blue© (Burlingame, CA) and
iNOS
+
cells were stained with Vector Red© (Burlingame, CA) (Figure 3.4A). Co-localization
was seen in purple by histological observation. Our results show that there were 30% more
F4/80
+
iNOS
+
“M2” macrophages in the MAO A/Pten double knockout than the Pten knockout
mouse tissue (P<0.05) (Figure 3.4B). However, there were more iNOS producing cells in the
Pten knockout mouse tissue implying other mechanisms of reduced immune suppression within
the environment.
3.4 Discussion
Our data suggests that knocking out monoamine oxidase A in the Pten knockout mouse model of
prostate cancer alters the immune system leading to an enhanced antitumor response. The MAO
A/Pten double knockout showed higher positive staining for the recruitment of CD8
+
cytotoxic T
cells into the tumor microenvironment. There was no observed difference in macrophage
recruitment between the two groups. Coinciding with that data, we observed that the MAO
A/Pten double knockout prostate tissues displayed less immune suppression based on reduced
positive staining for immunosuppressive cells, such as FoxP3
+
T regulatory cells and CD11b
+
myeloid-derived suppressor cells. In addition, the double knockout mice tissues also displayed
31
less positive staining for two markers of an immune suppressed environment: iNOS and
arginase-1. These findings support the hypothesis that knocking out MAO A can enhance the
antitumor response of the immune system through the reduction of immune suppression allowing
for cytotoxic T cell proliferation and targeting of the tumor cells.
Other researchers have seen that men with prostate cancer who have higher levels of FoxP3
+
T
regulatory cells have dysfunctional CD8
+
cytotoxic T cells and poorer prognosis (Davidsson et
al., 2013). During this experiment, we observed a reduction in the presence of FoxP3
+
T
regulatory cells between the Pten knockout and the MAO A/Pten double knockout; however, the
wild type and MAO A controls also presented positive staining for the immune cell with positive
percentages similar to that of the MAO A/Pten double KO (Wild type P>0.5, MAO A KO
P>0.5). Despite these confounding results, it has been shown that the FoxP3 transcription factor
is expressed in epithelial cells including the prostate during a healthy state (Chen et al., 2008).
This may explain the high positive staining in the wild type and MAO A KO tissues.
Beginning this experiment, we hypothesized that knocking out MAO A in the Pten knockout
mouse model of prostate cancer would reduce the number of M2 polarized macrophages
recruited to the tumor microenvironment. It has been reported that M2-polarized macrophages
synergize with the tumor microenvironment to support cancer progression based upon the
cytokines and growth factors in their environment. Since cytokine-releasing cells have receptors
for neurotransmitters such as the norepinephrine and serotonin receptors, they have been thought
to play a role in decision of Th1 or Th2 differentiation of T-cells (González et al., 2007; Mössner
and Lesch, 1998). Accumulated evidence suggests that serotonin appears to mediate a Th1 shift
32
with previous studies showing that physiological doses of 5HT induce the secretion of Th1
cytokines such as IL-1β, IFN-γ, and IL-12 (Kubera et al., 2005). This implies that serotonin
modulation has the potential to lead to a Th1 shift in CD4
+
T cells which in turn polarizes
macrophages to M1 differentiation and enhances the antitumor immune response (Martino et al.,
2012). However, this is not necessarily what was observed in this experiment. The mechanism
for the observed reduction in immune suppression still needs to be further scrutinized; however,
emerging evidence from the F4/80
+
/iNOS
+
double stain suggest one possible basis for
explanation. Although we observed more cells expressing the F4/80
+
iNOS
+
“M2” phenotype in
the MAO A/Pten double knockout mouse prostate tissue than the Pten knockout, there was a
difference between total iNOS
+
cells, whereby Pten knockout prostate tumor tissues had more
iNOS
+
cells compared to the double knockout. This suggests that the cells contributing to
immune suppression via expression of iNOS in the Pten knockout may be of another myeloid
lineage, most probably myeloid-derived suppressor cells, and the mechanism of reduced immune
suppression in the double knockout comes from a reduction of these cells, rather than infiltration
of F4/80
+
M2 polarized macrophages. Further work needs to be done to clarify this hypothesis
and should involve the co-localization of CD11b and iNOS in the Pten knockout and MAO
A/Pten double knockout mouse prostate tumor tissues.
In conclusion, these studies allowed for investigation into the role of host MAO A in immune
modulation during prostate cancer. Our data suggests that knocking out MAO A can enhance the
antitumor immune response providing a potential explanation of the phenomena of delayed
prostate cancer growth in MAO knockout mice.
33
Figure 3.1. Immunohistochemistry of anti-tumor immune cell markers in mouse prostate
tissue. A. Immunohistochemistry of representative wild type, MAO A KO, Pten KO and MAO
A/Pten double knockout mouse prostate tissue show increased anti-tumor immunity via CD8
+
immune cells and no change in F4/80
+
immune cells in and MAO A/Pten double knockout as
compared to Pten knockout mouse tissue. No significant staining was observed in the wild type
or MAO A knockout tissues. Images at x100 and x400 magnification. Percent positive staining was
quantified from number of B. CD8
+
and C.F4/80
+
cells per total stromal cells. **, P<0.005. NS, not
significant
A
0
10
20
30
40
WT AKO PTEN KO DKO
% Positive Cells
% CD8
+
B.
**
0
5
10
15
20
WT AKO PTEN KO DKO
% Positive Cells
% F4/80
+ C.
NS
34
Figure 3.2. Immunohistochemistry of immunosuppressive immune cell markers in mouse
prostate tissue. A. Immunohistochemistry of representative wild type, MAO A KO, Pten KO and
MAO A/Pten double knockout mouse prostate tissue show increased FoxP3
+
and CD11b
+
staining
for immunosuppressive cells in the Pten KO as compared to MAO A/Pten double knockout mouse
prostate tissue. Images at x100 and x400 magnification. Percent positive staining was quantified
from number of B. FoxP3
+
and C.CD11b
+
cells per total stromal cells. *, P<0.05.
0
10
20
30
40
50
WT AKO PTEN KO DKO
% Positive Cells
% FoxP3
+
0
10
20
30
40
WT AKO PTEN KO DKO
% Positive Cells
% CDllb
+
A.
B.
C.
*
*
35
Figure 3.3. Immunohistochemistry of immune suppression markers in mouse prostate tissue.
A. Immunohistochemistry of representative wild type, MAO A KO, Pten KO and MAO A/Pten
double knockout mouse prostate tissue show decreased iNOS and arginase-1 positive staining in
the MAO A/Pten double knockout as compared to Pten knockout mouse tissue. Images at x100
and x400 magnification. Percent positive staining was quantified from the number of B. iNOS
+
and C.Arginase-1
+
cells per total stromal cells. *, P<0.05, **P<0.005.
A.
0
20
40
60
PTEN KO DKO
% Positive cells
% iNOS
+
0
10
20
30
PTEN KO DKO
% Positive cells
% Arginase-1
B.
C.
**
*
36
Figure 3.4. Multiple antigen staining immunohistochemistry of immunosuppressive M2
macrophages in mouse prostate tissue. A. Pten knockout mouse prostate tissue showed
moderately less cells with positive staining for both F4/80 and iNOS as compared to MAO A/Pten
double knockout mouse tissue. F4/80
+
cells (blue), iNOS (red), co-localized (purple). Serial section
tissues were used to overlap staining locations. Images at x100 and x400 magnification. B.
Percent positive staining was quantified from the ratio of iNOS
+
F4/80
+
cells per total F4/80
+
cells.
C. Cells which were iNOS
+
but F4/80
-
were also observed and quantified from the ratio of iNOS
+
per total iNOS
+
F4/80
+
cells.*, P<0.05, **P<0.005.
0
50
100
150
PTEN KO DKO
% Positive cells
% M2 Macrophages
F4/80
+
iNOS
+
65
70
75
80
85
90
PTEN KO DKO
% Positive cells
% F4/80
-
iNOS
+
A.
B. C.
*
**
37
CHAPTER 4
Conclusions
The immune system is a highly dynamic organism which adapts and changes based on the
environment to reach a status of homeostasis. We have seen that immune processing is altered as
a result knocking out monoamine oxidase A in both the brain and in prostate individually. We
demonstrated in a microarray analysis of MAO A knockout mice brains, that knocking out MAO
A alters immune response genes in early development (Chapter 2). This study was an
introduction into how MAO regulates the immune system on a genetic level. Further studies on
the mechanisms of immune alteration are necessary to determine future applications in
neurological disease and elsewhere.
Chapter 3 illustrated the effect of knocking out MAO A in the conditional Pten knockout mouse
model of prostate cancer on the antitumor immune response. The results suggest that MAO A
deletion in the conditional Pten knockout mouse model of prostate cancer reduces immune
suppression within the tumor microenvironment. Reduction of immunosuppressive cells such as
T regulatory cells and myeloid-derived suppressor cells within the microenvironment allows for
functional antitumor responses from CD8
+
cytotoxic T cells, natural killer cells, and can dissuade
macrophages from differentiating to the immunosuppressive M2 state. This study has potential
implications for targeting immune escape in cancer models. The MAO A inhibitor clorgyline is
presently being examined by our lab as a potential treatment targeting prostate cancer cells.
Further studies are needed to examine if this treatment has the same effect on the immune
response as seen in the MAO A/Pten double knockout mouse model.
38
Bibliography
Adler, A.J. (2007). Mechanisms of T cell tolerance and suppression in cancer mediated by
tumor-associated antigens and hormones. Current cancer drug targets 7, 3-14.
Appay, V., Zaunders, J.J., Papagno, L., Sutton, J., Jaramillo, A., Waters, A., Easterbrook, P.,
Grey, P., Smith, D., McMichael, A.J., et al. (2002). Characterization of CD4(+) CTLs ex vivo. J
Immunol 168, 5954-5958.
Baroni, A., De Filippis, A., Buommino, E., Satriano, R.A., and Cozza, V. (2012). Osteopontin, a
protein with cytokine-like properties: a possible involvement in pemphigus vulgaris. Archives of
dermatological research 304, 237-240.
Battistini, L., Piccio, L., Rossi, B., Bach, S., Galgani, S., Gasperini, C., Ottoboni, L., Ciabini, D.,
Caramia, M.D., Bernardi, G., et al. (2003). CD8+ T cells from patients with acute multiple
sclerosis display selective increase of adhesiveness in brain venules: a critical role for P-selectin
glycoprotein ligand-1. Blood 101, 4775-4782.
Bevan, M.J. (2006). Cross-priming. Nature immunology 7, 363-365.
Bhowmick, N.A., Neilson, E.G., and Moses, H.L. (2004). Stromal fibroblasts in cancer initiation
and progression. Nature 432, 332-337.
Bohonowych, J.E., Hance, M.W., Nolan, K.D., Defee, M., Parsons, C.H., and Isaacs, J.S. (2014).
Extracellular Hsp90 mediates an NF-kappaB dependent inflammatory stromal program:
implications for the prostate tumor microenvironment. The Prostate 74, 395-407.
Bortolato, M., Godar, S.C., Alzghoul, L., Zhang, J., Darling, R.D., Simpson, K.L., Bini, V.,
Chen, K., Wellman, C.L., Lin, R.C., et al. (2013a). Monoamine oxidase A and A/B knockout
mice display autistic-like features. Int J Neuropsychopharmacol 16, 869-888.
39
Bortolato, M., Godar, S.C., Tambaro, S., Li, F.G., Devoto, P., Coba, M.P., Chen, K., and Shih,
J.C. (2013b). Early postnatal inhibition of serotonin synthesis results in long-term reductions of
perseverative behaviors, but not aggression, in MAO A-deficient mice. Neuropharmacology.
Boulanger, L.M. (2009). Immune proteins in brain development and synaptic plasticity. Neuron
64, 93-109.
Bufalino, C., Hepgul, N., Aguglia, E., and Pariante, C.M. (2013). The role of immune genes in
the association between depression and inflammation: a review of recent clinical studies. Brain,
behavior, and immunity 31, 31-47.
Bunevicius, R., and Prange, A.J., Jr. (2006). Psychiatric manifestations of Graves'
hyperthyroidism: pathophysiology and treatment options. CNS drugs 20, 897-909.
Butti, E., Bergami, A., Recchia, A., Brambilla, E., Del Carro, U., Amadio, S., Cattalini, A.,
Esposito, M., Stornaiuolo, A., Comi, G., et al. (2008). IL4 gene delivery to the CNS recruits
regulatory T cells and induces clinical recovery in mouse models of multiple sclerosis. Gene
therapy 15, 504-515.
Byrum, R.S., Goulet, J.L., Snouwaert, J.N., Griffiths, R.J., and Koller, B.H. (1999).
Determination of the contribution of cysteinyl leukotrienes and leukotriene B4 in acute
inflammatory responses using 5-lipoxygenase- and leukotriene A4 hydrolase-deficient mice. J
Immunol 163, 6810-6819.
Capuron, L., Ravaud, A., Neveu, P.J., Miller, A.H., Maes, M., and Dantzer, R. (2002).
Association between decreased serum tryptophan concentrations and depressive symptoms in
cancer patients undergoing cytokine therapy. Molecular psychiatry 7, 468-473.
40
Casillas, A.M., Thompson, A.D., Cheshier, S., Hernandez, S., and Aguilera, R.J. (1995). RAG-1
and RAG-2 gene expression and V(D)J recombinase activity are enhanced by protein
phosphatase 1 and 2A inhibition in lymphocyte cell lines. Molecular immunology 32, 167-175.
Chen, G.Y., Chen, C., Wang, L., Chang, X., Zheng, P., and Liu, Y. (2008). Cutting edge: Broad
expression of the FoxP3 locus in epithelial cells: a caution against early interpretation of fatal
inflammatory diseases following in vivo depletion of FoxP3-expressing cells. J Immunol 180,
5163-5166.
Clynes, R., Maizes, J.S., Guinamard, R., Ono, M., Takai, T., and Ravetch, J.V. (1999).
Modulation of immune complex-induced inflammation in vivo by the coordinate expression of
activation and inhibitory Fc receptors. The Journal of experimental medicine 189, 179-185.
Colotta, F., Allavena, P., Sica, A., Garlanda, C., and Mantovani, A. (2009). Cancer-related
inflammation, the seventh hallmark of cancer: links to genetic instability. Carcinogenesis 30,
1073-1081.
Comito, G., Giannoni, E., Segura, C.P., Barcellos-de-Souza, P., Raspollini, M.R., Baroni, G.,
Lanciotti, M., Serni, S., and Chiarugi, P. (2014). Cancer-associated fibroblasts and M2-polarized
macrophages synergize during prostate carcinoma progression. Oncogene 33, 2423-2431.
Cosgrove, L., Shi, L., Creasey, D., Anaya-McKivergan, M., Myers, J., and Huybrechts, K.
(2011). Antidepressants and breast and ovarian cancer risk: a review of the literature and
researchers' financial associations with industry. PloS one 6.
Davidsson, S., Ohlson, A.L., Andersson, S.O., Fall, K., Meisner, A., Fiorentino, M., Andren, O.,
and Rider, J.R. (2013). CD4 helper T cells, CD8 cytotoxic T cells, and FOXP3(+) regulatory T
cells with respect to lethal prostate cancer. Modern pathology : an official journal of the United
States and Canadian Academy of Pathology, Inc 26, 448-455.
41
Derecki, N.C., Privman, E., and Kipnis, J. (2010). Rett syndrome and other autism spectrum
disorders--brain diseases of immune malfunction? Molecular psychiatry 15, 355-363.
Doedens, A.L., Stockmann, C., Rubinstein, M.P., Liao, D., Zhang, N., DeNardo, D.G., Coussens,
L.M., Karin, M., Goldrath, A.W., and Johnson, R.S. (2010). Macrophage expression of hypoxia-
inducible factor-1 alpha suppresses T-cell function and promotes tumor progression. Cancer
research 70, 7465-7475.
Dunn, G.P., Old, L.J., and Schreiber, R.D. (2004). The immunobiology of cancer
immunosurveillance and immunoediting. Immunity 21, 137-148.
Edin, S., Wikberg, M.L., Dahlin, A.M., Rutegard, J., Oberg, A., Oldenborg, P.A., and Palmqvist,
R. (2012). The distribution of macrophages with a M1 or M2 phenotype in relation to prognosis
and the molecular characteristics of colorectal cancer. PloS one 7, e47045.
Eickholt, B.J., Ahmed, A.I., Davies, M., Papakonstanti, E.A., Pearce, W., Starkey, M.L.,
Bilancio, A., Need, A.C., Smith, A.J., Hall, S.M., et al. (2007). Control of axonal growth and
regeneration of sensory neurons by the p110delta PI 3-kinase. PLoS One 2, e869.
Elenkov, I. (2008). Neurohormonal-cytokine interactions: implications for inflammation,
common human diseases and well-being. Neurochemistry international 52, 40-51.
Flamand, V., Zhao, H., and Peehl, D.M. (2010). Targeting monoamine oxidase A in advanced
prostate cancer. Journal of cancer research and clinical oncology 136, 1761-1771.
Folkman, J. (1974). Tumor angiogensis: role in regulation of tumor growth. The symposium /
The Society for Developmental Biology Society for Developmental Biology Symposium 30, 43-
52.
Frick, L.R., and Rapanelli, M. (2013). Antidepressants: influence on cancer and immunity? Life
sciences 92, 525-532.
42
Gao, G.F., and Jakobsen, B.K. (2000). Molecular interactions of coreceptor CD8 and MHC class
I: the molecular basis for functional coordination with the T-cell receptor. Immunology today 21,
630-636.
Garlisi, C.G., Xiao, H., Tian, F., Hedrick, J.A., Billah, M.M., Egan, R.W., and Umland, S.P.
(1999). The assignment of chemokine-chemokine receptor pairs: TARC and MIP-1 beta are not
ligands for human CC-chemokine receptor 8. European journal of immunology 29, 3210-3215.
Gittes, R.F. (1991). Carcinoma of the prostate. The New England journal of medicine 324, 236-
245.
Glade-Bender, J., Kandel, J.J., and Yamashiro, D.J. (2003). VEGF blocking therapy in the
treatment of cancer. Expert opinion on biological therapy 3, 263-276.
González, A., Fazzino, F., Castillo, M., Mata, S., and Lima, L. (2007). Serotonin, 5-HT1A
serotonin receptors and proliferation of lymphocytes in major depression patients.
Neuroimmunomodulation 14, 8-15.
Haddow, A. (1972). Molecular repair, wound healing, and carcinogenesis: tumor production a
possible overhealing? Advances in cancer research 16, 181-234.
Henley, W., and Bellush, L. (1992). Streptozotocin-induced decreases in serotonin turnover are
prevented by thyroidectomy. Neuroendocrinology 56, 354-363.
Huang, H.W., Tang, J.L., Han, X.H., Peng, Y.P., and Qiu, Y.H. (2013). Lymphocyte-derived
catecholamines induce a shift of Th1/Th2 balance toward Th2 polarization.
Neuroimmunomodulation 20, 1-8.
Hughes, C., Murphy, A., Martin, C., Sheils, O., and O'Leary, J. (2005). Molecular pathology of
prostate cancer. Journal of clinical pathology 58, 673-684.
43
Iellem, A., Colantonio, L., Bhakta, S., Sozzani, S., Mantovani, A., Sinigaglia, F., and
D'Ambrosio, D. (2000). Inhibition by IL-12 and IFN-alpha of I-309 and macrophage-derived
chemokine production upon TCR triggering of human Th1 cells. European journal of
immunology 30, 1030-1039.
Inoue, M., and Shinohara, M.L. (2011). Intracellular osteopontin (iOPN) and immunity.
Immunologic research 49, 160-172.
Jemal, A., Siegel, R., Ward, E., Hao, Y., Xu, J., and Thun, M.J. (2009). Cancer statistics, 2009.
CA: a cancer journal for clinicians 59, 225-249.
Johansson, M., Denardo, D.G., and Coussens, L.M. (2008). Polarized immune responses
differentially regulate cancer development. Immunological reviews 222, 145-154.
Kalluri, R., and Zeisberg, M. (2006). Fibroblasts in cancer. Nature reviews Cancer 6, 392-401.
Karan, D., Lin, M.F., Johansson, S.L., and Batra, S.K. (2003). Current status of the molecular
genetics of human prostatic adenocarcinomas. International journal of cancer Journal
international du cancer 103, 285-293.
Kubera, M., Maes, M., Kenis, G., Kim, Y.-K., and Lasoń, W. (2005). Effects of serotonin and
serotonergic agonists and antagonists on the production of tumor necrosis factor alpha and
interleukin-6. Psychiatry research 134, 251-258.
Kut, J., Young, M., Crayton, J., and Wright, M. (1992). Regulation of murine T-lymphocyte
function by spleen cell-derived and exogenous serotonin. Immunopharmacology and
immunotoxicology 14, 783-796.
Lechner, M.G., Liebertz, D.J., and Epstein, A.L. (2010). Characterization of cytokine-induced
myeloid-derived suppressor cells from normal human peripheral blood mononuclear cells. J
Immunol 185, 2273-2284.
44
Leenen, P.J., de Bruijn, M.F., Voerman, J.S., Campbell, P.A., and van Ewijk, W. (1994).
Markers of mouse macrophage development detected by monoclonal antibodies. Journal of
immunological methods 174, 5-19.
LeFever, A., Liepins, A., and Truitt, R. (1989). Role of K+ ion channels in lymphokine-activated
killer (LAK) cell lytic function. Immunopharmacology and immunotoxicology 11, 571-582.
León-Ponte, M., Ahern, G., and O'Connell, P. (2007). Serotonin provides an accessory signal to
enhance T-cell activation by signaling through the 5-HT7 receptor. Blood 109, 3139-3146.
Maes, M., Fišar, Z., Medina, M., Scapagnini, G., Nowak, G., and Berk, M. (2012). New drug
targets in depression: inflammatory, cell-mediated immune, oxidative and nitrosative stress,
mitochondrial, antioxidant, and neuroprogressive pathways. And new drug candidates--Nrf2
activators and GSK-3 inhibitors. Inflammopharmacology 20, 127-150.
Maes, M., Meltzer, H.Y., Scharpe, S., Bosmans, E., Suy, E., De Meester, I., Calabrese, J., and
Cosyns, P. (1993). Relationships between lower plasma L-tryptophan levels and immune-
inflammatory variables in depression. Psychiatry research 49, 151-165.
Maes, M., Verkerk, R., Bonaccorso, S., Ombelet, W., Bosmans, E., and Scharpe, S. (2002).
Depressive and anxiety symptoms in the early puerperium are related to increased degradation of
tryptophan into kynurenine, a phenomenon which is related to immune activation. Life sciences
71, 1837-1848.
Mancini, J.A., and Evans, J.F. (1995). Cloning and characterization of the human leukotriene A4
hydrolase gene. European journal of biochemistry / FEBS 231, 65-71.
Martinez, F.O., Helming, L., and Gordon, S. (2009). Alternative activation of macrophages: an
immunologic functional perspective. Annual review of immunology 27, 451-483.
45
Martino, M., Rocchi, G., Escelsior, A., and Fornaro, M. (2012). Immunomodulation Mechanism
of Antidepressants: Interactions between Serotonin/Norepinephrine Balance and Th1/Th2
Balance. Current neuropharmacology 10, 97-123.
Mazaris, E., and Tsiotras, A. (2013). Molecular pathways in prostate cancer. Nephro-urology
monthly 5, 792-800.
Miller, M.D., and Krangel, M.S. (1992). The human cytokine I-309 is a monocyte
chemoattractant. Proceedings of the National Academy of Sciences of the United States of
America 89, 2950-2954.
Mira, E., Leon, B., Barber, D.F., Jimenez-Baranda, S., Goya, I., Almonacid, L., Marquez, G.,
Zaballos, A., Martinez, A.C., Stein, J.V., et al. (2008). Statins induce regulatory T cell
recruitment via a CCL1 dependent pathway. J Immunol 181, 3524-3534.
Mold, C., Rodriguez, W., Rodic-Polic, B., and Du Clos, T.W. (2002). C-reactive protein
mediates protection from lipopolysaccharide through interactions with Fc gamma R. J Immunol
169, 7019-7025.
Mössner, R., and Lesch, K. (1998). Role of serotonin in the immune system and in neuroimmune
interactions. Brain, behavior, and immunity 12, 249-271.
Noordzij, J.G., de Bruin-Versteeg, S., Verkaik, N.S., Vossen, J.M., de Groot, R., Bernatowska,
E., Langerak, A.W., van Gent, D.C., and van Dongen, J.J. (2002). The immunophenotypic and
immunogenotypic B-cell differentiation arrest in bone marrow of RAG-deficient SCID patients
corresponds to residual recombination activities of mutated RAG proteins. Blood 100, 2145-
2152.
46
Obregon, D., Parker-Athill, E.C., Tan, J., and Murphy, T. (2012). Psychotropic effects of
antimicrobials and immune modulation by psychotropics: implications for neuroimmune
disorders. Neuropsychiatry 2, 331-343.
Peehl, D.M., Coram, M., Khine, H., Reese, S., Nolley, R., and Zhao, H. (2008). The significance
of monoamine oxidase-A expression in high grade prostate cancer. The Journal of urology 180,
2206-2211.
Pienta, K.J., Robertson, B.A., Coffey, D.S., and Taichman, R.S. (2013). The cancer diaspora:
Metastasis beyond the seed and soil hypothesis. Clinical cancer research : an official journal of
the American Association for Cancer Research 19, 5849-5855.
Pollak, Y., and Yirmiya, R. (2002). Cytokine-induced changes in mood and behaviour:
implications for 'depression due to a general medical condition', immunotherapy and
antidepressive treatment. Int J Neuropsychopharmacol 5, 389-399.
Priceman, S.J., Sung, J.L., Shaposhnik, Z., Burton, J.B., Torres-Collado, A.X., Moughon, D.L.,
Johnson, M., Lusis, A.J., Cohen, D.A., Iruela-Arispe, M.L., et al. (2010). Targeting distinct
tumor-infiltrating myeloid cells by inhibiting CSF-1 receptor: combating tumor evasion of
antiangiogenic therapy. Blood 115, 1461-1471.
Putz, E.M., Prchal-Murphy, M., Simma, O.A., Forster, F., Koenig, X., Stockinger, H., Piekorz,
R.P., Freissmuth, M., Muller, M., Sexl, V., et al. (2012). PI3Kdelta is essential for tumor
clearance mediated by cytotoxic T lymphocytes. PLoS One 7, e40852.
Qian, B.Z., and Pollard, J.W. (2010). Macrophage diversity enhances tumor progression and
metastasis. Cell 141, 39-51.
47
Roos, R.S., Loetscher, M., Legler, D.F., Clark-Lewis, I., Baggiolini, M., and Moser, B. (1997).
Identification of CCR8, the receptor for the human CC chemokine I-309. The Journal of
biological chemistry 272, 17251-17254.
Ruffell, B., Affara, N.I., and Coussens, L.M. (2012). Differential macrophage programming in
the tumor microenvironment. Trends in immunology 33, 119-126.
Sadun, R.E., Sachsman, S.M., Chen, X., Christenson, K.W., Morris, W.Z., Hu, P., and Epstein,
A.L. (2007). Immune signatures of murine and human cancers reveal unique mechanisms of
tumor escape and new targets for cancer immunotherapy. Clinical cancer research : an official
journal of the American Association for Cancer Research 13, 4016-4025.
Scott, A.L., Bortolato, M., Chen, K., and Shih, J.C. (2008). Novel monoamine oxidase A knock
out mice with human-like spontaneous mutation. Neuroreport 19, 739-743.
Sennels, H., Sorensen, S., Ostergaard, M., Knudsen, L., Hansen, M., Skjodt, H., Peters, N.,
Colic, A., Grau, K., and Jacobsen, S. (2008). Circulating levels of osteopontin, osteoprotegerin,
total soluble receptor activator of nuclear factor-kappa B ligand, and high-sensitivity C-reactive
protein in patients with active rheumatoid arthritis randomized to etanercept alone or in
combination with methotrexate. Scandinavian journal of rheumatology 37, 241-247.
Shih, J.C., Chen, K., and Ridd, M.J. (1999). Role of MAO A and B in neurotransmitter
metabolism and behavior. Polish journal of pharmacology 51, 25-29.
Shih, J.C., Wu, J.B., and Chen, K. (2011). Transcriptional regulation and multiple functions of
MAO genes. J Neural Transm 118, 979-986.
Shinkai, Y., Rathbun, G., Lam, K.P., Oltz, E.M., Stewart, V., Mendelsohn, M., Charron, J.,
Datta, M., Young, F., Stall, A.M., et al. (1992). RAG-2-deficient mice lack mature lymphocytes
owing to inability to initiate V(D)J rearrangement. Cell 68, 855-867.
48
Siegel, R., Naishadham, D., and Jemal, A. (2013). Cancer statistics, 2013. CA: a cancer journal
for clinicians 63, 11-30.
Song, C., Lin, A., Bonaccorso, S., Heide, C., Verkerk, R., Kenis, G., Bosmans, E., Scharpe, S.,
Whelan, A., Cosyns, P., et al. (1998). The inflammatory response system and the availability of
plasma tryptophan in patients with primary sleep disorders and major depression. Journal of
affective disorders 49, 211-219.
Stein, M.P., Mold, C., and Du Clos, T.W. (2000). C-reactive protein binding to murine
leukocytes requires Fc gamma receptors. J Immunol 164, 1514-1520.
Stewart, M., Thiel, M., and Hogg, N. (1995). Leukocyte integrins. Current opinion in cell
biology 7, 690-696.
Sun, H., Lesche, R., Li, D.M., Liliental, J., Zhang, H., Gao, J., Gavrilova, N., Mueller, B., Liu,
X., and Wu, H. (1999). PTEN modulates cell cycle progression and cell survival by regulating
phosphatidylinositol 3,4,5,-trisphosphate and Akt/protein kinase B signaling pathway.
Proceedings of the National Academy of Sciences of the United States of America 96, 6199-
6204.
Swartz, M.A., Iida, N., Roberts, E.W., Sangaletti, S., Wong, M.H., Yull, F.E., Coussens, L.M.,
and DeClerck, Y.A. (2012). Tumor microenvironment complexity: emerging roles in cancer
therapy. Cancer research 72, 2473-2480.
Takagi, T., Moribe, H., Kondoh, H., and Higashi, Y. (1998). DeltaEF1, a zinc finger and
homeodomain transcription factor, is required for skeleton patterning in multiple lineages.
Development 125, 21-31.
Tanemura, S., Momose, H., Shimizu, N., Kitagawa, D., Seo, J., Yamasaki, T., Nakagawa, K.,
Kajiho, H., Penninger, J.M., Katada, T., et al. (2009). Blockage by SP600125 of Fcepsilon
49
receptor-induced degranulation and cytokine gene expression in mast cells is mediated through
inhibition of phosphatidylinositol 3-kinase signalling pathway. Journal of biochemistry 145, 345-
354.
Thunnissen, M.M., Nordlund, P., and Haeggstrom, J.Z. (2001). Crystal structure of human
leukotriene A(4) hydrolase, a bifunctional enzyme in inflammation. Nature structural biology 8,
131-135.
True, L., Coleman, I., Hawley, S., Huang, C.Y., Gifford, D., Coleman, R., Beer, T.M., Gelmann,
E., Datta, M., Mostaghel, E., et al. (2006). A molecular correlate to the Gleason grading system
for prostate adenocarcinoma. Proceedings of the National Academy of Sciences of the United
States of America 103, 10991-10996.
Vanhaesebroeck, B., Welham, M.J., Kotani, K., Stein, R., Warne, P.H., Zvelebil, M.J., Higashi,
K., Volinia, S., Downward, J., and Waterfield, M.D. (1997). P110delta, a novel phosphoinositide
3-kinase in leukocytes. Proceedings of the National Academy of Sciences of the United States of
America 94, 4330-4335.
Wang, S., Gao, J., Lei, Q., Rozengurt, N., Pritchard, C., Jiao, J., Thomas, G.V., Li, G., Roy-
Burman, P., Nelson, P.S., et al. (2003). Prostate-specific deletion of the murine Pten tumor
suppressor gene leads to metastatic prostate cancer. Cancer cell 4, 209-221.
Westdorp, H., Skold, A.E., Snijer, B.A., Franik, S., Mulder, S.F., Major, P.P., Foley, R.,
Gerritsen, W.R., and de Vries, I.J. (2014). Immunotherapy for Prostate Cancer: Lessons from
Responses to Tumor-Associated Antigens. Frontiers in immunology 5, 191.
Williams, T.M., Moolten, D., Burlein, J., Romano, J., Bhaerman, R., Godillot, A., Mellon, M.,
Rauscher, F.J., 3rd, and Kant, J.A. (1991). Identification of a zinc finger protein that inhibits IL-2
gene expression. Science 254, 1791-1794.
50
Wong, C.P., Bray, T.M., and Ho, E. (2009). Induction of proinflammatory response in prostate
cancer epithelial cells by activated macrophages. Cancer letters 276, 38-46.
Wu, J.B., Shao, C., Li, X., Li, Q., Hu, P., Shi, C., Li, Y., Chen, Y.T., Yin, F., Liao, C.P., et al.
(2014). Monoamine oxidase A mediates prostate tumorigenesis and cancer metastasis. The
Journal of clinical investigation.
Youdim, M.B., Edmondson, D., and Tipton, K.F. (2006). The therapeutic potential of
monoamine oxidase inhibitors. Nature reviews Neuroscience 7, 295-309.
Young, M., Kut, J., Coogan, M., Wright, M., and Matthews, J. (1993). Stimulation of splenic T-
lymphocyte function by endogenous serotonin and by low-dose exogenous serotonin.
Immunology 80, 395-400.
Zhao, H., Flamand, V., and Peehl, D.M. (2009). Anti-oncogenic and pro-differentiation effects of
clorgyline, a monoamine oxidase A inhibitor, on high grade prostate cancer cells. BMC medical
genomics 2, 55.
Zhao, H., Nolley, R., Chen, Z., Reese, S.W., and Peehl, D.M. (2008). Inhibition of monoamine
oxidase A promotes secretory differentiation in basal prostatic epithelial cells. Differentiation;
research in biological diversity 76, 820-830.
Zhong, L., Roybal, J., Chaerkady, R., Zhang, W., Choi, K., Alvarez, C.A., Tran, H., Creighton,
C.J., Yan, S., Strieter, R.M., et al. (2008). Identification of secreted proteins that mediate cell-
cell interactions in an in vitro model of the lung cancer microenvironment. Cancer research 68,
7237-7245.
Zingoni, A., Soto, H., Hedrick, J.A., Stoppacciaro, A., Storlazzi, C.T., Sinigaglia, F.,
D'Ambrosio, D., O'Garra, A., Robinson, D., Rocchi, M., et al. (1998). The chemokine receptor
CCR8 is preferentially expressed in Th2 but not Th1 cells. J Immunol 161, 547-551.
51
Zou, W. (2005). Immunosuppressive networks in the tumour environment and their therapeutic
relevance. Nature reviews Cancer 5, 263-274.
Abstract (if available)
Abstract
Monoamine oxidase A (MAO A) is a mitochondrial bound enzyme which is responsible for the oxidation of neurotransmitters such as serotonin (5‐HT) in the brain and peripheral tissue and produces hydrogen peroxide, a major source of reactive oxygen species. MAO A knockout (KO) mice show a significant increase in 5‐HT which has been implicated in modulation of immune system cells. This study will investigate if the immune system is indeed altered in MAO A KO mice and identify essential gene expression changes during critical developmental stages. We analyzed Affymetrix GeneChip microarray data available in our lab to identify the differentially expressed genes (DEGs) from MAO A KO mice brains. We found only 2 genes, MAP3K12 and TCF7, to be significantly different in adult KO mice which were not relevant to the immune system. Since we have previously shown that MAO A KO mice have the most significant increase in serotonin at early postnatal ages postnatal day 1 (P1) and postnatal day 7 (P7), we examined inflammation and immune stimulation gene changes in the MAO A KO mice at ages P1 and P7. We found 36 genes at P1 and 22 genes at P7 with fold change >2 or <−2 and false discovery rate (FDR) <0.05. Among them, CCL1, SPP1, ZEB1, and RAG2 are involved in the regulation of T cell signaling and differentiation. CRP and LTA4H play roles in inflammation. These results show that knocking out MAO A in mice leads to early developmental changes in the immune system of the brain which is compensated in adulthood. ❧ We previously found that when MAO A KO mice were injected with LNCaP prostate cancer cells subcutaneously that the tumors did not grow. To understand the in vivo function of MAO A in prostate cancer progression, we generated MAO A/Pten double knockout mice (DKO) and found that deletion of MAO A in Pten knockout mice delayed prostate cancer formation typically seen in the Pten KO mouse model of prostate cancer. This animal model is used to study if an altered immune system from knocking out MAO A is responsible for reduced prostate cancer growth in the Pten KO mouse model. To study the in vivo effect of knocking out MAO A on the immune system in a prostate cancer model, we used 9 month old prostate−specific Pten single knockout and MAO A/ Pten DKO mouse prostate tissue and immunohistochemistry to analyze the number and types of immune cells recruited to the tumor microenvironment. MAO A KO and wild type mice prostate tissues were used as controls. We found that the MAO A/Pten DKO mice tissues had higher staining for CD8⁺ cytotoxic T cells which indicates immune stimulation. Conversely, the Pten knockout mice tissues had the highest markers for immunosuppressive cells such as FoxP3 for T regulatory cells and CD11b for myeloid‐derived suppressor cells as well as iNOS and arginase-1, markers for immune suppression, in the stroma surrounding the tumors. When characterizing the macrophage population for M1 versus M2 differentiation, it was observed that there were more F4/80⁺iNOS⁺ cells present in the MAO A/Pten DKO than the Pten KO. However, there were additional iNOS producing cells in the Pten KO not identified as F4/80⁺ macrophages implying production of iNOS from other immune lineages. These results suggest that there are alterations in the immune system of MAO A knockout mice which may explain the delayed prostate cancer formation in MAO A/Pten double knockout mice.
Linked assets
University of Southern California Dissertations and Theses
Conceptually similar
PDF
Monoamine oxidase and cancer
PDF
Co-expression of monoamine oxidase A and prostate cancer stem cell markers in Pten knockout mice
PDF
NMI (near-infrared dye conjugate MAO A inhibitor) outperformed FDA-approved prostate cancer drugs with a unique mechanism based on bioinformatic analysis of NCI60 screening data
PDF
Role of inflammation in prostate carcinogenesis and prostate cancer growth
PDF
Monoamine oxidase inhibitors regulate tumorigenesis and mitochondrial function in a prostate cancer mouse model
PDF
Potential therapeutic effect of monoamine oxidase (MAO) inhibitor on human neuroblastoma
PDF
Insulin sensitivity in cognition, Alzheimer's disease and brain aging
PDF
Exploration of the roles of cancer stem cells and survivin in the pathogenesis and progression of prostate cancer
PDF
The role of monoamine oxidase in behavioral plasticity
PDF
Monoamine oxidase A inhibitors and androgen receptor antagonists regulate mitochondrial function in prostate cancer cells
PDF
PTEN loss antagonizes aging through promoting regeneration and prevents oxidative stress induced cell death
PDF
Pten regulates beta-cell regeneration intrinsically and independently of development
PDF
Monoamine oxidase (MAO) knock-out mouse models: Tools for studying the molecular basis of aggression, anxiety, autism and cancers
PDF
NMI: a near infrared conjugated MAO-A inhibitor as a novel targeted therapy for colorectal and other cancers
PDF
Regulation of mitochondrial bioenergetics via PTEN (phosphatase and tensin homolog deleted on chromosome 10)/estrogen-related receptor alpha (ERRα) signaling
PDF
The effect of tumor-mediated immune suppression on prostate cancer immunotherapy
PDF
Small molecule modulators of HIF1α signaling
PDF
Application of genome-wide strategies for the mining of secondary metabolite biosynthesis pathways in filamentous fungi
PDF
Study of a novel near-infrared conjugated MAOA inhibitor, NMI, against CNS cancer by NCI60 data analysis
PDF
Differential regulation of monoamine oxidase A and B genes
Asset Metadata
Creator
Lapierre, Jessica
(author)
Core Title
MAO a deficient mice exhibit an altered immune system in the brain and prostate
School
School of Pharmacy
Degree
Master of Science
Degree Program
Molecular Pharmacology and Toxicology
Publication Date
07/14/2015
Defense Date
06/19/2014
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
immune,monoamine oxidase,OAI-PMH Harvest,prostate cancer
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Shih, Jean C. (
committee chair
), Okamoto, Curtis Toshio (
committee member
), Olenyuk, Bogdan (
committee member
)
Creator Email
jlapierre56@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c3-436720
Unique identifier
UC11286951
Identifier
etd-LapierreJe-2666.pdf (filename),usctheses-c3-436720 (legacy record id)
Legacy Identifier
etd-LapierreJe-2666.pdf
Dmrecord
436720
Document Type
Thesis
Format
application/pdf (imt)
Rights
Lapierre, Jessica
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Tags
immune
monoamine oxidase
prostate cancer