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Pro-inflammatory Kupffer cells secrete CXCL5 to promote liver cancer

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Pro-inflammatory Kupffer cells secrete CXCL5 to promote liver cancer

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Content Pro-inflammatory Kupffer cells secrete CXCL5 to promote liver cancer
By
Taojian Tu
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PHARMACEUTICAL SCIENCES)
August 2022
Copyright 2022 Taojian Tu
ii

Dedication

To my parents
Dr. Jiasheng Tu and Jianmei Wu

iii

Acknowledgements
I would like to thank my advisors Dr. Bangyan Stiles and Dr. Curtis Okamoto.
Mechanistic science discoveries are very difficult, but their unconditional support and
guidance helped me through the process. They encouraged and supported me to try new
methods and think out of the box. Dr. Stiles also patiently helped me with writing and
presentation skills, which won me quite a few best poster awards in conferences. Their
efforts have established my confidence in my scientific abilities.
My sincere thanks go to Dr. Lina He, who is much more than the lab manager of
the Stiles lab. She guides and helps everyone in their experiments, I wouldn’t have been
able to isolate liver macrophages without her help and suggestions. The other previous
and current members of the Stiles lab helped tremendously. Joshua Chen and Jingyu
Chen guided me as senior students. Handan Hong, Mario Alba, Qi Tang and Lulu Chen
contributed to this project directly. Dr. Anh Tan Truong was my best friend in the Okamoto
lab, he helped with my experiments and made lab life more enjoyable.
Special acknowledgements to my committee member Dr. Jianmin Xie who has
given me valuable advice on inflammation studies. Dr. Meisam Razaviyayn and Dr. Sze-
chuan Suen and Peng Dai helped with the bioinformatics, especially the regression
analysis. Dr. Stan Louie and the Louie lab (Hua Pei, Eugene Zhou, Isaac Asante and
others) helped me establish my fundamental skills when I first came to USC, and
continued to help and support me through my PhD.
iv

My most heartfelt thanks to my family. My father Dr. Jiasheng Tu is my role model
and my initial inspiration to do science. My mother Jianmei Wu has taken care of my life
for years and she cooked everyday for me to ensure my nutrition for the last 2 years of
my PhD. My brother Nick Tu and my wife Yang Su has been my emotional support with
their optimism and sense of humor. And that’s just the tip of the iceberg of my family’s
support for me.

v

Table of Contents
Dedication .................................................................................................................................................... ii
Acknowledgements ................................................................................................................................... iii
List of Tables ............................................................................................................................................. vii
List of Figures .......................................................................................................................................... viii
Abstract ....................................................................................................................................................... ix
Chapter 1 ................................................................................................................................................... 11
Background and Introduction ................................................................................................................. 11
1.1 Liver Cancer, Epidemiology and Treatments ............................................................................ 11
1.1.1 Epidemiology and Etiology.................................................................................................... 11
1.1.2 Treatment and therapy ............................................................................................................ 3
1.2 Liver inflammation and HCC .......................................................................................................... 5
1.2.1 Inflammatory system in the Healthy Liver ............................................................................ 5
1.2.2 Innate and adaptive defense against gut bacteria—involvement of PAMP .................... 7
1.2.3 Activation of Kupffer Cells during Inflammation-Involvement of DAMP ........................... 9
1.2.4 Liver inflammation promotes HCC ....................................................................................... 11
1.3 Chemokines in the regulation of liver inflammatory response ................................................ 11
1.4 Hypothesis ...................................................................................................................................... 20
Chapter 2 ................................................................................................................................................... 21
CXCL5 is associated with HCC progression ........................................................................................ 21
2.1 Introduction ..................................................................................................................................... 21
2.2 Results ............................................................................................................................................ 22
2.3 Discussion....................................................................................................................................... 29
Chapter 3 ................................................................................................................................................... 32
Liver macrophages are the cellular source of hepatic CXCL5 .......................................................... 32
3.1 Introduction ..................................................................................................................................... 32
3.2 Results ............................................................................................................................................ 34
3.3 Discussion....................................................................................................................................... 47
Chapter 4 ................................................................................................................................................... 50
CXCL5 is expressed by HCC associated proinflammatory Kupffer cells ........................................ 50
4.1 Introduction ..................................................................................................................................... 50
4.2 Results ............................................................................................................................................ 53
4.3 Discussion....................................................................................................................................... 70
vi

Chapter 5 ................................................................................................................................................... 74
CXCL5 promotes HCC growth ............................................................................................................... 74
5.1 Introduction ..................................................................................................................................... 74
5.2 Results ............................................................................................................................................ 76
5.3 Discussion....................................................................................................................................... 81
Chapter 6 ................................................................................................................................................... 84
Perspective ................................................................................................................................................ 84
Chapter 7 ................................................................................................................................................... 86
Method Development ............................................................................................................................... 86
7.1 Liver macrophage isolation .......................................................................................................... 86
7.1.1 Digestion of the Liver ............................................................................................................. 86
7.1.2 Separation of non-parenchymal cells from hepatocytes .................................................. 87
7.1.3 Separation of macrophages from non-parenchymal cells ............................................... 87
7.2 Intracellular flow cytometry ........................................................................................................... 88
Chapter 8 ................................................................................................................................................... 91
Materials and Methods ............................................................................................................................ 91
Bibliography .............................................................................................................................................. 97

vii

List of Tables
Table 1: CXC and CC chemokines and their receptors, functions and reported cellular
source. .......................................................................................................................... 12
Table 2: HCC datasets from GEO database ................................................................. 23
Table 3: CXCL5 expression correlates with macrophage marker F4/80. ...................... 36
Table 4: Macrophage marker CD64 correlates with CXCL5 expression. ...................... 37

viii

List of Figures
Figure 1: A schematic diagram of liver structure. .................................................................................. 6
Figure 2: Activation of Kupffer cell during chronic liver diseases. ...................................................... 9
Figure 3: Chemokine expressions in HCC patients. ........................................................................... 25
Figure 4: CXCL5 is highly expressed in liver tumors. ......................................................................... 27
Figure 5: CXCL5 negatively impacts patient survival. ........................................................................ 28
Figure 6: Macrophages are solely responsible for CXCL5 expression. ........................................... 38
Figure 7: Pearson correlation in human HCC tumors. ....................................................................... 39
Figure 8: Immunostaining of human HCC tumors shows colocalization of CXCL5 and CD68. ... 41
Figure 9: Disease progression in Pten null mice. ................................................................................ 42
Figure 10: Flow cytometry analysis of liver immune cell population. ............................................... 44
Figure 11: Immunostaining of liver macrophages in wild type vs Pten null mice. .......................... 45
Figure 12: CXCL5 expression increase gradually during HCC development in Pten null mice. . 46
Figure 13: Flow cytometry identifies macrophages as the cellular source of CXCL5. .................. 54
Figure 14: CD64high macrophages express the highest levels of CXCL5. .................................... 55
Figure 15: Macrophages, but not hepatocytes, are the main source of hepatic CXCL5. ............. 57
Figure 16: Pten null livers are pro-inflammatory. ................................................................................ 58
Figure 17: Human HCC is associated with pro-inflammatory macrophages. ................................. 59
Figure 18: LPS stimulate CXCL5 expression in liver macrophages. ............................................... 60
Figure 19: LPS does not stimulate CXCL5 expression in peritoneal macrophages and
macrophage cell lines. ............................................................................................................................. 61
Figure 20: LPS stimulated the secretion of CXCL5 in liver macrophages. ..................................... 62
Figure 21: HMGB1 induced CXCL5 expression in liver macrophages. ........................................... 63
Figure 22: Liver hepatocellular carcinoma associated macrophages express high levels of
CXCL5. ...................................................................................................................................................... 64
Figure 23: CXCL5 expression in LPS treated Kupffer cells. .............................................................. 65
Figure 24: CXCL5 is expressed in Kupffer cells in Pten null mice. .................................................. 66
Figure 25: Kupffer cells are the major cellular source of hepatic CXCL5. ....................................... 67
Figure 26:CD64high Kupffer cells are the highest producers of CXCL5. ........................................ 69
Figure 27: CXCL5 treatment increased hepatocyte viability. ............................................................ 77
Figure 28: CXCR2 blockade reduced hepatocyte viability................................................................. 78
Figure 29: CXCL5 induced HepG2 cell proliferation through CXCR2. ............................................ 79
Figure 30: CXCL5 shows strong correlation with liver tumor proliferation. ..................................... 80
Figure 31: Intracellular flow cytometry workflow.................................................................................. 90

ix

Abstract
Inflammation is a hallmark of liver cancer development. It drives the tumorigenic
cycle of liver injury and regeneration. Here, I studied the key chemokines involved in liver
cancer progression through analysis of CXC and CC chemokine expressions in human
hepatocellular carcinoma (HCC), and its further characterization in the Pten null mouse
model. We found that CXCL5 was the only chemokine consistently upregulated in human
HCC with different etiologies compared to healthy livers. Further bioinformatic analysis
showed that the CXCL5 increase is closely associated with liver macrophages.
We hypothesized that CXCL5 expression was induced by pathogenic stimulations
that are common to chronic liver diseases, and these stimulations induced CXCL5
expression in liver macrophages. To test that, we used the Pten null mouse model that
recapitulates NAFLD-NASH-HCC progression. Concurrent increase of hepatic CXCL5
expression and macrophage population is observed during HCC development in Pten null
mice. Intracellular flow cytometry and immunofluorescent staining demonstrated that
Kupffer cells are the predominant CXCL5 high expressing cells in the liver.
Mechanistically, chronic liver diseases and inflammation leads to increased intestinal
permeability which elevates hepatic LPS concentration. We found that LPS stimulation
leads to CXCL5 upregulation uniquely in liver macrophages, but not in peritoneal
x

macrophages or Raw264.7 macrophages. Mass spectrometry confirmed that there is an
increase of CXCL5 secretion in LPS treated vs non-treated liver macrophages. CXCL5
binding to CXCR2 promotes HCC tumor cells proliferation.
Together, we showed that CXCL5 expression is strongly associated with HCC.
During chronic liver inflammation, liver-gut axis promotes HCC development through
Kupffer cell-specific LPS-induced CXCL5 overexpression. Secreted CXCL5 drives HCC
tumor growth. Further studies on LPS and Kupffer cell interactions might provide new
drug targets to reduce HCC incidence in patients with chronic liver disease.

xi

Chapter 1
Background and Introduction

1.1 Liver Cancer, Epidemiology and Treatments
Liver cancer is consisted of primarily hepatocellular carcinoma (HCC) and
intrahepatic cholangiocarcinoma (iCCA). Hepatocellular carcinoma (HCC) is the most
common and accounts for 75-85% of all liver cancers whereas iCCA accounts for 10 to
15% of all liver cancers[1]. In 2020, liver cancer is the 6
th
most common cancer worldwide,
and it is the 3
rd
leading cause of cancer deaths. It is the 5
th
most common and 2
nd
leading
cause of cancer deaths in male[1].

1.1.1 Epidemiology and Etiology
The majority of HCC emerges in livers with chronic liver diseases. The major cause
of HCC is attributed to HBV (Hepatitis B Virus) which is associated with 33% of HCC
worldwide. HCV (Hepatitis C Virus) is responsible for 21% of HCC[2]. HBV and HCV
promotes liver cirrhosis[3, 4]. The risk of HCC development increased by 7.7-fold in
cirrhotic HBV livers and 6-fold in cirrhotic HCV livers compared to non-cirrhotic chronic
viral infections[3, 5]. Alcohol consumption contributes to 30% of worldwide HCC, other
causes accounts for 16% of HCC tumors[2]. Non-alcoholic fatty liver disease (NAFLD) is
another contributing factor for HCC. The proportion of NAFLD related HCC shows
substantial heterogeneity among different studies; this is partly due to how NAFLD was
2

defined in the studies. NAFLD was commonly determined using ICD-9 codes 571.8, ‘other
chronic nonalcoholic liver disease’ or 571.9, ‘unspecified chronic liver disease without
alcohol’. These criteria are inaccurate and might include other diseases[6]. In one study,
nearly 60% of HCC in the US were attributed to NAFLD[7]. In studies with histological or
metabolic evidence of NAFLD, Mittal, et al., discovered that 8% of the US veterans
developed HCC owing to NAFLD between 2005 and 2010; Wong, et al., found increasing
ratio of NASH related HCC (0% in 2002, 4% in 2007 and 6% in 2012) among patients
who received liver transplantation due to primary HCC[8]; Dyson, et al., in UK Newcastle-
upon-Tyne hospitals, showed that 35% of their HCC cases were due to NAFLD in 2010;
they also observed a dramatic increase of NAFLD related HCC from 2000 to 2010[4]. It
is worth noting that these percentages might be underestimating NAFLD related HCC
because many HCC patients diagnosed with cryptogenic cirrhosis (not caused by virus
or alcohol) likely have undiagnosed NAFLD[8].
The development of vaccines against HBV and therapies against HCV have
significantly impacted HCC development. HBV vaccines has proven to be effective in
reducing HCC occurrence in young patients. In a Taiwanese cohort, the rate of HCC
decreased from 0.92 per 10
5
person-years in unvaccinated subjects to 0.23 per 10
5

person-years in vaccinated subjects[9]. Although there are no effective HCV vaccines yet,
direct-acting antivirals (DAA) are able to induce sustained virological response (SVR) and
significantly lowers the chances of getting HCC: 0.90 (with SVR) vs 3.45 (without SVR)
HCC per 100 person-years[10]. However, patients who have cirrhosis or severe fibrosis
due to chronic HCV infection should still be aware of HCC risks (more than 2%/year) even
after HCV eradication as these conditions are irreversible[11].
3

Another important disease that contributes to HCC is non-alcoholic fatty liver
diseases (NAFLD). This is partly due to the global pandemic of obesity and diabetes,
approximately 25% of the global population suffers from NAFLD[12]. It is projected that
NAFLD related HCC will increase exponentially in future years[13]. A meta-analysis
showed that NAFLD contributed to 9.77% of global HCC before 2000, however, after
2010 NAFLD leads to 16.97% of global HCC[14]. Importantly, patients with NAFLD
related HCC suffer from late diagnosis. Only 32.8% NAFLD patients have surveillance for
liver tumors before the diagnosis of HCC, while 55.7% of patients were on surveillance
for liver tumors before diagnosis of HCC secondary to other causes. Patients with NAFLD
was more likely to develop HCC without cirrhosis than HBV.
More than 38% of NAFLD related HCC patients did not have cirrhosis, while only
14.6% of HCC attributed to other causes (HBV, HCV, alcoholism) were absent of
underlying cirrhosis[14]. This is interesting because cirrhosis is the primary risk factor for
HCC. Overall, metabolic disorders have shown great associations with HCC
developments. The population attributable fraction (PAF) reflects the contribution of a risk
factor to HCC occurrence in a population. Among 10,708 HCC patients, the PAF of
metabolic disorders (32%) ranked as the number 1 HCC risk factor, followed by HCV
(20.5%), alcohol (13.4%), smoking (9%), HBV (4.3%), and genetic disorders (1.5%)[15].

1.1.2 Treatment and therapy
The only curative treatment for liver cancer is resection followed by transplantation.
However, only early stage patients are eligible for this treatment. For advanced HCC, the
4

first line treatment for has been sorafenib and lenvatinib since 2007. Sorafenib and
lenvatinib are two broadly-targeting tyrosine kinase inhibitors (TKIs) that target Raf-1, B-
Raf, VEGFR and PDGFRβ[16]. However, Sorafenib treatment only extended overall
median survival by 3 months to 10.7 months, as compared to 7.9 months in the placebo
group[17].
Mutations in tumor cells drive the expression of novel self-antigens or neoantigens,
these neoantigens can spark adaptive immune reactions against tumors[18]. In the
nineteenth century, physician Busch reported tumor regression after the patient had
superficial skin infections (erysipelas)[19]. More studies confirmed that activated
immunity can suppress or eliminate tumors[20, 21]. Immune checkpoints such as CTLA-
4 and PD-1 receptors are expressed on T-cells, they act as coinhibitory signals to
maintain immune tolerance. They are utilized by tumors to evade immunity[22]. Leach et
al. showed that blocking CTLA-4 potentiates immune response against tumors[23]. With
the success of immune checkpoint inhibitors (ICIs) in the treatment of melanoma[24, 25],
nivolumab (PD-1 inhibitor) was tested in treating unresectable HCC. Even though
nivolumab doesn’t significantly improve the overall survival compared to sorafenib, it did
improve the objective response rate and complete response rate[26]. To further
potentiate the immune response, atezolizumab (PD-L1 inhibitor) was tested in
combination with bevacizumab (VEGF inhibitor). This treatment was compared to
sorafenib, the results showed that the addition of bevacizumab significantly improved
overall survival, progression free survival and objective response rate(27.3% vs
11.9%)[27]. In 2020, the Food and Drug Administration (FDA) approved atezolizumab
and bevacizumab as an initial treatment for patients with liver cancer that has spread or
5

that can’t be treated with surgery. Clinical trials are ongoing to test the efficacy of the
combinational therapy with ICIs and TKIs.

1.2 Liver inflammation and HCC
The immune checkpoint inhibitors aim to establish a favorable environment for T
cell activation and sustained anti-tumor response. Inflammation plays a key role in
regulating T cell function. It is critical to study key changes and immune cell crosstalk in
liver inflammation during HCC development.

1.2.1 Inflammatory system in the Healthy Liver
The liver is mainly composed of hepatocytes, biliary lineage cells and endothelial
cells, hepatic stellate cells, Kupffer cells and other immune cells. Among them,
hepatocytes are the major functional units by metabolizing components from the gut and
blood circulation, and in synthesizing and secreting bile acids. Bile acids are secreted into
bile canaliculus formed by two or more hepatocytes on their apical membrane, while
uptake from the blood occurs on their basolateral side facing the space of Disse (Figure
1).

6

One of the key components in liver immune response is the macrophage.
Macrophages are known as versatile immune cells that can alter their phenotypes
between pro-inflammatory and anti-inflammatory macrophages, traditionally termed M1
(pro-inflammatory) and M2 (anti-inflammatory) macrophages[28]. Relative quantity of M1
vs M2 macrophages and the inflammatory mediators that they produce determine the
outcomes of liver inflammation, this is shown by comparing alcohol feeding in BALB/c
mice vs C57BL6/J mice: Alcohol feeding did not induce differential immune cell infiltration:
it promoted M1 macrophages in the C57BL6 mice; in contrast, it promoted M2
macrophages in the BALB/c mice. As a result, C57BL6 mice developed steatosis and
liver injury, while BALB/c mice were resistant[29].
Liver macrophages consists of 2 populations, the local proliferating Kupffer cells
and the infiltrating monocyte derived macrophages[30]. Kupffer cells are the first
responders in liver immune system. Kupffer cells are the largest tissue resident
Figure 1: A schematic diagram of liver structure. The liver sinusoids are separated from the hepatocytes by the space
of Disse. The porous or fenestrated liver sinusoids in combination with the slow blood flow allows better molecule
exchange between the space of Disse and the sinusoidal lumen. External molecules/drugs are metabolized by
hepatocytes, some of them are secreted into the bile canaliculus located in between the hepatocytes. Kupffer cells
are located within the sinusoids to monitor pathogens.
7

macrophage population in the body. They critically affect the liver immune response. For
example, resting state Kupffer cells and inflammatory Kupffer cells induce different T-cell
responses. Antigen presentation by Kupffer cells induced binding between the Kupffer
cells and the antigen-specific CD4
+
T-cells. In healthy livers, Kupffer cells, but not
monocyte derived macrophages, induced immune-suppressive regulatory T-cell marker
FoxP3 and anti-inflammatory cytokine IL-10 in these antigen specific CD4
+
T-cells[31].
During liver inflammation, Kupffer cells expressed reduced tolerogenic PDL-1 but
increased immunogenic CD80. In inflamed livers, Kupffer cells failed to suppress T-cell
activation[31].

1.2.2 Innate and adaptive defense against gut bacteria—involvement of PAMP
Seventy-five percent of the liver blood supply comes from the gut through the portal
vein; thus, the liver is exposed to endotoxins and antigens from the gut microbiome, also
known as Pathogen Associated Molecular Patterns (PAMPs)[32]. To prevent constant
inflammation, the liver has developed a unique immune response that tolerates but also
eliminates the pathogens. In healthy individuals, Kupffer cells are located within the liver
sinusoids and monitor pathogens in the blood. Different from monocyte derived
macrophages, mature Kupffer cells are highly effective in binding and clearing E. coli in
the blood[33].
However, it was reported that there is increased intestinal permeability (leaky gut)
in patients with chronic liver diseases, especially NAFLD. A meta-analysis showed that
39.1% NAFLD patients had increased intestinal permeability as compared to 6.8% in
8

healthy individuals, the percentage of leaky gut further increased to 49.2% in NASH
patients[34]. Increased intestinal permeability allows more bacterial endotoxin into the
liver through portal vein, one of the most important endotoxins is lipopolysaccharide (LPS),
a potent ligand for Toll-like receptor 4 (TLR4). When exposed to LPS and fatty acids,
hepatocytes go through pyroptosis and release proinflammatory cytokine IL-1β[35].
Kupffer cells interact with LPS in 2 ways: on one hand, Kupffer cells detoxify and
clear LPS from the liver blood flow and store them in phagocytic vacuoles[36]. On the
other hand, Kupffer cells release various pro-inflammatory cytokines including IL-1β[37],
IL-6[38], TNFα[39] upon LPS stimulation. In Raw264.7 murine macrophages and
peritoneal macrophages, LPS binds to the cell surface CD14 or soluble CD14 in the
serum to initiate downstream signaling. Compared to Raw264.7 and peritoneal
macrophages, Kupffer cells express substantially lower levels of CD14 and the interaction
between Kupffer cells and LPS was not dependent on CD14[40, 41]. These studies
suggested a unique LPS pathway in Kupffer cells, which is likely due to the constant
exposure to endotoxins from the gut and the need to maintain liver homeostasis (Figure
2).
9

1.2.3 Activation of Kupffer Cells during Inflammation-Involvement of DAMP
Kupffer cells not only recognize molecules from invading microorganisms, but they
also survey for endogenous host cell debris and signals released by apoptotic or necrotic
cell. These signals released from dying cells are called Damage Associated Molecular
Patterns (DAMPs), they include proteins such as high mobility group box protein 1
(HMGB1), S100 proteins and heat shock proteins, and non-protein molecules such as
uric acid and mitochondrial DNAs[42, 43] (Figure 2). The immune system reacts to these
signals similar to external wounds which are usually followed by pathogens invasions and
infections, thus DAMPs trigger the activation of immune defense. Kupffer cells express
scavenger and pattern recognition receptors such as Toll-like Receptors (TLRs), NOD-
like receptors (NLRs) and Receptor for Advanced Glycation Endproducts (RAGE)[44].
Figure 2: Activation of Kupffer cell during chronic liver diseases. Kupffer cells can be activated by gut derived
endotoxins including lipopolysaccharide and damaged hepatocytes derived damage associated molecular patterns
including high mobility group box protein 1.
10

Activation of these receptors reverses the immune-suppressive liver environment
and escalate liver injury[45]. This is supported by studies on disrupted TLR4 signaling: 1)
TLR4 knockout prevents liver damage in alcoholic liver disease[46]; 2) Loss of function
mutations in toll-like receptor adaptor protein TIRAP reduces liver fibrosis in NAFLD[47].
TLR4 is highly expressed on Kupffer cells[48]. During fatty liver diseases, free palmitic
acids induce the overexpression and secretion of HMGB1 from hepatocytes. HMGB1 can
bind and activate TLR4 receptors on Kupffer cells and induce the release of
proinflammatory cytokines such as TNFα and IL-6[49]. Similarly, during HFD feeding,
hepatocytes release mitochondrial DNAs which stimulate Kupffer cells TLR9 receptors
and subsequent TNFα secretion. Cholesterol laden lipid droplets formed within
hepatocytes can also activate Kupffer cells through direct contact, this promote IL-1b
secretion in these Kupffer cells[50].
In fatty liver diseases, ballooned hepatocytes (swelled and rounded hepatocytes
typically appearing in hepatitis due to damaged membranes) produce Hedgehog ligands,
and they can promote macrophage accumulation and pro-inflammatory cytokine release.
This is partly mediated by OPN since Hedgehog signaling in hepatocytes leads to OPN
secretion. OPN can recruit macrophages and promote inflammation[51]. Hepatocytes
release extracellular vesicles in response to palmitate and its metabolite, lysophophatidyl
choline (LPC). These vesicles express Trail ligands to bind to Death Receptor 5 (DR5)
on macrophages, which will induce the generation of pro-inflammatory macrophages and
the production of IL-1β and IL-6[52].

11

1.2.4 Liver inflammation promotes HCC
Proinflammatory cytokines promote HCC development. IL-6 promotes the transition from
pre-cancerous progenitor cells to cancer stem cells[53]. TNFα further facilitates cancer
cells’ self-renewal. Moreover, TNFα downregulates MSH2 (the mismatch repair (MMR)
protein that prevents DNA mutation) expression via NF-κB-mediated miR-21 expression
in hepatocytes. Thus, TNFα increases hepatocytes’ mutagenesis and carcinogenesis.
Additionally, pro-inflammatory cytokines including TNFα and IL-10 increases the
expression of PD-L1 on macrophages. These macrophages suppress CD8
+
T-cells to
promote tumor progression[54]. On the contrary, metformin treatment of fatty liver disease
reduces pro-inflammatory macrophages, and this leads to an increased T-cell population
in the liver and inhibits HCC development[55].

1.3 Chemokines in the regulation of liver inflammatory response
Chemokines are released by Kupffer cells, liver sinusoidal endothelial cells and hepatic
stellate cells to recruit infiltrating immune cells. There are 2 major groups of chemokines:
CC and CXC, this is based on the amino acid sequence between the 2 cysteines closest
to the N-terminus. In CC chemokines, the second cysteine is placed immediately
following the first cysteine, while CXC chemokines have a variable amino acid between
them. CC chemokines are known for their ability to recruit monocytes and lymphocytes,
while CXC chemokines are potent neutrophil attractants and can promote
angiogenesis[56].
12

Kupffer cells in particular act as the sensor of pathogen invasion and tissue
damage. Upon binding of PAMPs or DAMPs, Kupffer cells release CCL2 to recruit
monocytes and CXCL1, CXCL2 and CXCL8 to recruit neutrophils[57]. These chemokines
have redundant functions and share receptors while each receptor also binds to a
multitude of ligands (Table 1).

Table 1: CXC and CC chemokines and their receptors, functions and reported cellular source.
Chemokine Receptor Chemotaxis function Function and cellular source in the liver
CXCL1 CXCR2 Recruit neutrophil[58] Contributes to cirrhosis in HCV and
alcoholic liver diseases[59, 60]
CXCL2 CXCR2 Recruit neutrophil[61] Secreted by hepatocytes to recruit
neutrophils[61]
CXCL3 CXCR2 Recruit neutrophil[62]
CXCL4 CXCR3 Promote monocyte
infiltration and
differentiation into
macrophages[63]
Produced by platelets, and promote
proliferation and chemokine expression
of hepatic stellate cells[64]
CXCL5 CXCR2 Promote neutrophil
migration in vitro[65]
Produced by hepatic stellate cells, liver
sinusoidal endothelial cells and Kupffer
cells in healthy livers[66], and promote
liver cancer cell metastasis[67]. CXCL5
over-expression in HCC cells promoted
xenograft tumor formation[67]
13

CXCL6 CXCR1 & 2 Recruit neutrophils[68] CXCL6 stimulates Kupffer cell secretion of
TGFβ to promote fibrosis[69]. Contrarily,
another study showed that CXCL6 inhibits
COL1 secretion in hepatic stellate cells,
instead it promotes hepatocyte
proliferation[70]
CXCL7 CXCR2 Recruit neutrophils[71] Expressed by hepatic stellate cells to
recruit neutrophils[71].
CXCL8 CXCR1&2 Recruit neutrophils and
monocytes[72]
Recruits neutrophils in cholestatic liver
cirrhosis, it also recruits monocytes in
non-cholestatic liver cirrhosis[72].
CXCL9 CXCR3 Recruit T cells[73] Produced by hepatocytes[74, 75].
Reduces liver neo-angiogenesis and
fibrosis[76]
CXCL10 CXCR3 Recruit T-cells and plasma
cells[77]
Produced by hepatocytes[74, 75].
Promote liver fibrosis[78].
CXCL11 CXCR3 Recruit T cells[79] Produced by hepatocytes[74, 75].
CXCL12 CXCR4 Recruit MDSC[80]. Produced by liver sinusoidal endothelial
cells[81].
CXCL13 CXCR5 Recruit CXCR5+ T-
cells[82].
Recruit CXCR5+ T-cells to promote
antiviral response in chronic HBV
infection[82]. Mainly produced by
14

Kupffer cells during disease
conditions[83].

CXCL14 Not Identified Assist T cell recruitment
through binding to CXCR4,
CXCR5 and CCR7
allosterically to enhance
the sensitivity of these
receptors to their
ligands[84].
Inhibits HCC growth[85]

CXCL15 Not Identified Recruit neutrophils into
the lung airspace[86].

Mostly expressed in the lung, not
expressed in the adult liver[86].
CXCL16 CXCR6 Recruit T cells and
monocytes through low
affinity with ccr1,2,5[87]
Expressed by hepatocytes[88]
CXCL17 CXCR8[89] Recruit monocytes[89]. Mediates bacterial membrane disruption
in the lung[90]
CCL1 CCR8 Recruit Th2 cells[91] Attract and activate Th2 cells in HCC[91].
CCL2 CCR2 Recruit macrophages[92] Secreted by senescent hepatocytes,
recruit pro-inflammatory monocyte-
derived macrophages in HCC[92].
CCL3 CCR1&5 Recruit macrophages[93] Recruit macrophages in HCC[93]
15

CCL4 CCR5 Recruit T cells[94] Promote infiltration of γδ T cells in
HCC[95].
CCL5 CCR1&3&5 Recruit a wide range of
immune cells including T
cells, monocytes, NK cells,
and DCs[96].
Recruit and activate a wide range of
immune cells including T cells,
monocytes, NK cells, and DCs to promote
HCC[96]. Secreted by damaged
hepatocytes and Kupffer cells[96, 97]
CCL6 CCR1 Recruit monocyte-derived
macrophages[98]

CCL7 CCR1&2 Recruit monocytes[99] Secreted by tumor-associated
neutrophils and fibroblast, lead to the
accumulation of macrophages in liver[87]
CCL8 CCR2 Recruit TH2 cells[100]
CCL9 CCR1 Recruit CD4 T cells[101]
CCL10 Former name for CCL9, no
longer in use

CCL11 CCR3 Recruit eosinophils[102]
CCL12 CCR2 Recruit fibrocytes[103]
CCL13 CCR1, 2&3 Recruit eosinophils,
basophils, monocytes,
macrophages, immature
dendritic cells, and T
cells[104]

16

CCL14 CCR1, 3&5 Recruit monocyte[105] Inhibit HCC tumor cell growth[106]
CCL15 CCR1 Recruit monocytes[107] Recruit monocytes which are educated
by HCC tumors to express immune
checkpoints and facilitate tumor immune
escape[107]
CCL16 CCR1, 2&5 Recruits T cells and
monocytes through low
affinity with ccr1,2,5[87]

Expressed by hepatocytes[88]
CCL17 CCR4 Recruit Tregs[108]

CCL18 CCR8 Recruit CD4+ CD25+ T
cells[109]

CCL19 CCR7 Recruit T cells through
CCR7 [110]

CCL20 CCR6 Recruit CCR6+ Th17
cells[111]
Produced by hepatic stellate cells and
macrophages[112, 113], stimulate
fibrosis gene expression in HSCs[113].
CCL21 CCR7 Recruit NK cells through
CCR7[114] and activated T
cells[115]

17

CCL22 CCR4 Recruit T cells[116] Recruit Tregs to HCC[116]
CCL23 CCR1 Recruit resting T cells and
monocytes[117]
Reduce HCC cells proliferation through
inhibition of Akt activation, and increase
CD8+ T-cells[118]
CCL24 CCR3 Recruit eosinophils and
basophils[119]
Directly stimulates hepatic stellate cells
α-SMA expression and Collagen 1α
secretion to promote liver fibrosis.
Produced by liver macrophages,
hepatocytes as well as endothelial
cells[120].
CCL25 CCR11 Mainly expressed by liver
sinusoidal endothelial cells
to recruit CCR9+ T
cells[121]
Mainly expressed by liver sinusoidal
endothelial cells to recruit CCR9+ T
cells[121]
CCL26 CCR3, CX3CR1 Recruit eosinophils
through CCR3[122],
recruit CD16+ NK cells
through CX3CR1[123]

CCL27 CCR10 Recruit CCR10+ CD4/CD8+
T-cells[124]

CCL28 CCR3&10 Recruit regulatory T-cells
through CCR10[125]
Recruit CCR10+ Treg to inflamed liver,
mainly produced by cholangiocytes[125].

18

Initially, these chemokines were found to recruit neutrophils or monocytes[126]. A
subgroup of chemokines was named Neutrophil Activating Chemokines (NACs) due to
their ability to attract neutrophils. NACs included CXCL1,2,3,5,6,7,8 in humans. They bind
to CXCR1 or CXCR2 or to both. The chemokines can bind to receptors either as a
monomer or a homodimer[127]. This redundancy in receptor binding complicated the
interpretation for the functions of these chemokines. In the liver, studies have shown that
CXCR2 ligands might be involved in controlling hepatocyte proliferation, where high
concentration of CXCR2 ligands inhibit hepatocyte proliferation and low concentration of
CXCR2 ligands promote hepatocyte proliferation[128].
CXCL5, also known as ENA-78 (epithelial neutrophil-activating peptide 78),
preferentially binds to CXCR2 [129]. Although CXCL1, 2, 7, 8 can also bind to CXCR2,
their structures are different from CXCL5. CXCL5 is more flexible compared to CXCL8,
which might affect its binding with CXCR2. More specifically, CXCL5 N- terminal tail is
longer than that of the other CXCR2 ligands, and cleaving the N-terminal tail results in a
truncated CXCL5 (ENA-70) with a higher affinity for CXCR2[130]. CXCL5 contributes to
neutrophil accumulation in the lung during LPS challenge[131]. Uniquely, CXCL5 binds
to Duffy Antigen Receptor for Chemokines (DARC) with much higher affinity compared to
CXCL1 and CXCL2. DARC is expressed on the surface of erythrocytes and endothelial
cells. It acts as a trap for chemokines in the blood, and this maintains a low concentration
of chemokines in the plasma and a chemokine gradient that directs circulating immune
cells to inflamed tissues. In certain conditions such as E. Coli pneumonia, deletion of
CXCL5 allows more CXCL1 and CXCL2 to be bound to DARC, and this creates a more
significant gradient that directs more neutrophils to the lung[132].
19

CXCL5 is associated with chronic hepatitis and HCC development. CXCL1,
CXCL5, CXCL6 and CXCL8 expression gradually increased during alcoholic hepatitis
progression[133]. CXCL5, but not other NACs, was significantly upregulated in NASH
associated lobular inflammation[134]. Hepatic CXCL5 expression was higher in patients
with severe fibrosis and cirrhosis compared to patients without fibrosis, while CXCL5
plasma concentration decreased in patients with cirrhotic livers[66]. Multivariate Cox
analysis of TCGA data identified that among 110 differentially expressed genes that were
associated with HCC overall survival, CXCL5 and IL18RAP were the only 2 genes that
predicts prognosis independently[135].
The cellular source of CXCL5 seems to be diverse in different organs. In the lung,
CXCL5 is exclusively produced by residential alveolar epithelial type II (AEII) cells, but
not alveolar epithelial type I-like (AEI) cells or alveolar macrophages or neutrophils[131].
In the adipose tissues, CXCL5 is produced by the macrophages from the stromal vascular
fraction, but not by mature adipocytes[136]. In the heart, CXCL5 is only expressed by
resident myocardial cells, while CXCL1 and CXCL2 is only expressed by infiltrating
immune cells[137]. The cellular source of CXCL5 in the liver is not clear. One study
isolated different liver cell types and detected CXCL5 mRNA expression in hepatic stellate
cells, endothelial cells and Kupffer cells, but not hepatocytes[66], Other studies have
shown that CXCL5 is highly expressed by ICC and HCC cancer cell lines[65, 138].

20

1.4 Hypothesis
Chemokines are important mediators of inflammation. In addition to driving
immune cell infiltration, chemokines also regulate angiogenesis and tissue
regeneration[139]. One of the potent inducers of inflammation and chemokine
expressions is pathogen associated molecular patterns (PAMPs) from the gut, which is
frequently elevated during HCC due to increased intestinal permeability and altered gut
microbiota[140]. Hepatocellular carcinoma was dramatically reduced by sterilization of
the gut, this revealed a central role of PAMPs in promoting liver carcinogenesis[141].
However key links between HCC and PAMP stimulation has not been identified. Previous
studies have demonstrated tumor promoting roles of various chemokines[142, 143], but
the relationship between hepatocellular carcinoma (HCC) development and chemokine
expression is largely unknown. We performed bioinformatics analysis and found a
prominent association between CXCL5 over-expression and HCC with different etiologies.
We hypothesized that PAMPs stimulate Kupffer cells to produce CXCL5 which promotes
the expansion of liver tumor cells.
21

Chapter 2
CXCL5 is associated with HCC progression
2.1 Introduction
Inflammatory cytokines are known to promote liver regeneration in various models
including partial hepatectomy[144]. In chronic liver diseases, inflammatory cytokines
promote cell proliferation and activate HCC progenitor cells[53, 145]. While cytokines are
known to play diverse roles including mediating tissue regeneration[146], remodeling[147]
and cancer cell death[147, 148], chemokines were recently reported for various roles
beside immune cell recruitment, particularly in their roles in cancer progression. CXCL1
over-expression promotes HCC cell proliferation in vitro and in xenograft models[142,
149]. CXCL3 has also been shown to promote HCC cell stemness and proliferation in
vitro[143]. Knockdown of CXCR6, the receptor of CXCL16, reduced HCC cell proliferation
and migration[150]. Conversely, overexpression of CXCL2 and CXCL14 promote tumor
cell apoptosis and exhibit anti-tumor properties[85, 151].
In addition, some chemokines can promote tumor angiogenesis. The ability of
chemokine angiogenesis relies on the ELR motif, a conserved Glu-Leu-Arg motif that is
required for binding to CXCR2[152]. The NAC family chemokines promote angiogenesis
by binding to CXCR2 expressed on endothelial cells to induce their chemotaxis[139]. On
the other hand, CXCL4 and CXCL14, 2 chemokines that do not contain the ELR motif,
inhibit angiogenesis[153, 154].
These studies demonstrate that chemokines directly regulate cancer expansion
independently of their immune functions. However, most of the studies on HCC-related
22

chemokines only included a small group of patients, so it is not clear which chemokines
are clinically relevant in a majority of HCC patients.

2.2 Results
We explored the cytokine and chemokine signatures in liver cancer cross different
etiologies in liver cancer dataset available in the GEO database
(https://www.ncbi.nlm.nih.gov/geo/) (Table 2).
23

For this analysis, we set our inclusion criteria to be datasets that contain at least
30 HCC tumor tissues. We analyzed all CXC and CC ligands/chemokines (Table 1) in
each dataset to identify chemokines that are upregulated in tumors compared to their
expression in peri-tumor normal tissues or healthy controls. Out of the genes that encodes
for these chemokines, significantly upregulated genes (P<0.05) from each dataset are
included to generate the Venn diagram shown in Figure 3A. The relative expression of
CXCL5 was 7.9AU (Arbitrary Units of fluorescence intensity measured by microarray
analysis) in alcoholic HCC tissues compared to 5.7AU in healthy livers (p-value<0.0001).
Table 2: HCC datasets from GEO database
24

In HCV patients, CXCL5 expression was 7.5AU in HCC tumors and 5.7AU in healthy
controls (p-value<0.05). CXCL5 expression was also significantly higher in NASH-
associated HCC tissues compared to healthy livers (24.5AU vs 17.3AU, p<0.05). In the
HBV dataset, significantly higher CXCL5 expression was observed in the tumor tissues
compared to tumor adjacent normal tissues (0.23AU vs 0.11AU, p<0.05). (Figure 3B). A
higher CXCL5 expression is also observed when compared with healthy samples though
not reaching significant likely due to the low samples size for the healthy patient samples
(n=6). (Figure 3C). Together, these analyses show that expression of CXCL5 mRNA is
uniquely upregulated in all HCC tumors compared to non-tumor control tissues regardless
of etiology.
25

Figure 3: Chemokine expressions in HCC patients. A) Venn diagram of significantly upregulated chemokines in different
HCC datasets; B) CXCL5 expression dot plots from the datasets included in the Venn diagram. From Left to right: 1. CXCL5
in Hepatitis B Virus related HCC, Y axis is in log scale to accommodate large inter-individual variations; 2. CXCL5 in Non-
alcoholic Steatohepatitis (NASH) associated HCC; 3. CXCL5 in HCC attributed to alcoholic liver diseases; 4. CXCL5 in
Hepatitis C Virus induced HCC.

26

To validate this observation, we examined HCC and CC samples collected from
two patient cohorts. The samples are from liver cancer patients of mixed etiology that
include Hepatitis B, Hepatitis C and non-virally related HCC and CC. We compared the
expression of CXCL5 in tumors vs. nontumor healthy donor tissues. Our data shows that
CXCL5 expression is significant higher in tumor vs. healthy samples (Fig 4A). In addition,
we performed immunoblotting analysis for CXCL5 in a subset of the patient samples. Our
data showed that protein expression of CXCL5 is also higher in tumor vs. nontumor
samples, although patient-to-patient variation exists (Figure 4B).
We hypothesize that the observed variation for protein expression is likely due the
fact that CXCL5 is a secreted protein and thus not always confined to the tumor region.
Immunohistochemical staining showed that CXCL5 is highly produced by cells that reside
in the tumor stroma versus the tumor cells. Tumor cells are marked by proliferation
marker Ki67 staining. Almost all of the CXCL5 positive staining are observed in the non-
proliferating (Ki67 negative) cells (white arrows) in HCC tissues (Figure 4C). These
CXCL5 positive cells have smaller nucleus that are similar to the situation with immune
cells, a finding consistent with a immune cellular origin for CXCL5.
27

20µm 20µm
Figure 4: CXCL5 is highly expressed in liver tumors. A) Liver cancer patients CXCL5 mRNA expression was
analyzed with qPCR, n=5 in healthy group, n=29 in liver cancer group, p<0.05; B) HCC patients CXCL5 protein
expression analyzed with western blots; C) HCC patient tissues IHC stained for CXCL5 (green) and Ki67 (red).
28

Together, our analysis identified CXCL5 as a molecule that is highly expressed in
liver cancer specimens and supports a potential role of CXCL5 in liver cancer
development. A protumor effect of CXCL5 is further demonstrated with analysis of TCGA
data showing that patients with high CXCL5 expression (highest quartile of patients) had
a significantly lower HCC survival rate compared to patients with low CXCL5 expression
(lowest quartile of patients) (Figure 5).
Figure 5: CXCL5 negatively impacts patient survival. Total survival time of the CXCL5 high expression group
was compared with that of the CXCL5 low expression group using the Kaplan-Meier survival curve. The dotted
lines indicate the 95% confidence interval.
29

2.3 Discussion
Inflammation is a hallmark of liver cancer development. Inflammation is initiated by
the secretion of chemokines. In this study, we screened for chemokines that were
upregulated in liver cancers to identify key links between inflammation and tumor
progression. Our analysis of the GSE datasets showed that CXCL5 was consistently
upregulated in the tumor area and tumor adjacent tissues compared to healthy controls.
CXCL5 was the only chemokine upregulated in all common HCC etiologies including HBV,
HCV, alcoholic liver diseases and non-alcoholic fatty liver diseases. In human HCC
tissues, the expression of CXCL5 was seen in immune cells but not proliferating tumor
cells. Our findings suggest that immune cell derived CXCL5 is upregulated in cancerous
livers and promotes HCC progression.
CXCL5 has been reported to play supportive roles in several carcinomas and to
facilitate their metastasis: breast cancer[155], prostate cancer[156], colorectal
cancer[157], pancreatic cancer[158], and, liver cancer[65]. These studies suggest that
CXCL5 can play threemajor roles in tumor progression: 1. promote neutrophils or MDSCs
(myeloid derived suppressor cells) infiltration; 2. stimulate tumor proliferation; 3. facilitate
metastasis. In these studies, CXCL5 is mainly expressed by tumor cells. In HCC, CXCL5
expression is much higher in HCC cell lines with greater metastatic potential[65].
Overexpression of CXCL5 in these cells activates the PI3K-Akt pathway to promote
cancer cell growth and survival. CXCL5 knockdown dramatically reduces HCC metastasis
to the lung (100% metastasized in the control group versus 25% in the CXCL5 knockdown
group)[65]. Previous studies showed that CXCL5 is overexpressed in both hepatocellular
30

carcinoma as well as in intrahepatic cholangiocarcinoma[138, 159]. CXCL5 expression is
closely associated with HCC progression. It is shown that recurrent HCC tumors express
higher levels of CXCL5 compared to non-recurrent tumors[65]. Consistent with these
previous discoveries, our data here identify CXCL5 as the unique chemokine that is
upregulated in liver cancers regardless of etiology. Supporting our analysis, Wang, et al.,
analyzed the tumor microenvironment including stromal cells and immune cell-related
gene expression, and they calculated stromal and immune scores using the ESTIMATE
algorithm (https://rdrr.io/rforge/estimate/) for HCC tissues in the TCGA dataset. They
screened for differentially expressed genes (DEGs) comparing stromal score (high versus
low tumors) and immune score (high versus low tumors). Among those 830 DEGs, they
found 110 genes impacted HCC survival. Within the 110 genes, multivariate COX
regression analysis showed that CXCL5 and IL18RAP were the only two independent
prognositic factors of HCC. Different from IL18RAP, they used the STRING (https://string-
db.org/) tools to predict protein-protein interactions and found that CXCL5 is one of the
genes with the highest degree of interactions with other HCC related nodules[135].
Our analysis also indicated that CXCL5 is produced in the tumor stroma and is
likely associated with immune cells. These data are consistent with analysis using TCGA
data where CXCL5 expression was not induced in HCC tumors when compared to tumor
adjacent tissues (data not shown). Similarly, in the GEO datasets that we analyzed,
CXCL5 expression is higher in HCC adjacent tissues compared to healthy livers.
Particularly in alcoholic and HCV patients, HCC surrounding liver expressed significantly
higher levels of CXCL5 compared to healthy livers. There was a trend of CXCL5
upregulation (p=0.097) in NASH related HCC adjacent tissues compared to healthy livers.
31

Overall, our analysis of multiple GEO datasets indicates that CXCL5 is upregulated in
cancerous livers compared to healthy livers. Analysis of TCGA data indeed showed that
HCC patients with high CXCL5 expression had lower survival rate, supporting a role of
upregulated CXCL5 in liver cancer progression.

32

Chapter 3
Liver macrophages are the cellular source of hepatic CXCL5

3.1 Introduction
Liver is mainly composed of hepatocytes and biliary lineage cells together with
endothelial cells, hepatic stellate cells, macrophages and other immune cells.
Hepatocytes are the major component of the liver parenchyma and is the main metabolic
and detoxification machinery of the human body. Like other epithelia, hepatocytes are
situated at the interface between the organism exterior and the inside milieu, where they
mediate the vectorial exchange of macromolecules between external and internal spaces.
They are involved in two counter-current flow systems: the uptake, metabolism and
secretion of sinusoidal blood components, and the synthesis and secretion of the bile into
the bile canaliculus. Bile canaliculi merge and form the bile duct.
Metabolic functions in the liver are not exclusive to the hepatocytes. Macrophages
are also involved in the maintenance of iron and cholesterol homeostasis[160]. Although
hepatocytes are the main iron storing cells in the body, the liver relies on macrophages
to phagocytose aged red blood cells to recycle iron[161]. Similarly, through phagocytosis,
macrophages can acquire lipoprotein from dying cells and digest them in the lysosome to
form free cholesterol and fatty acids. Macrophage cholesterol can be disposed in 2 ways:
1. Efflux of cholesterol by forming HDL (high density lipoprotein) 2. Re-esterification of
the cholesterols, and store them in cytosolic lipid droplets.
As Non-alcoholic Fatty Liver Disease (NAFLD) continue to rise, macrophage-
mediated regulation of lipid homeostasis has become a hot research topic. It has been
33

shown that the progression of NAFLD is closely associated with macrophages[162]. The
precise roles of macrophages in NAFLD are still largely unknown[163]. Most studies in
this area have focused on the role of macrophage induced liver inflammation, where a
pro-inflammatory environment facilitates liver damage[164]. Other studies have shown
that macrophages can alter their metabolic phenotypes, and pro-inflammatory
macrophages can up-regulate their fatty acid synthesis pathway[165], while anti-
inflammatory macrophages can upregulate their fatty acid oxidation pathways[166].
The liver macrophages are composed of mainly 2 populations: the monocyte
derived macrophages and the liver resident Kupffer cells. Because monocytes can
differentiate into macrophages, macrophage specific markers such as F4/80, CD64 and
MSR1 were used to distinguish them. F4/80 is a pan macrophage marker in mouse.
MSR1 and CD64 are expressed by both mouse and human liver macrophages and their
expression is induced in chronic liver diseases[167, 168]. Different from macrophages,
monocytes uniquely express CCR2 and Ly6C.
The liver also has a unique adaptive immune system. Due to the fenestration of
the liver sinusoidal endothelial cells and the lack of basement membrane, T cells passing
through the liver sinusoids can be activated by direct interactions with hepatocellular
antigens. However, interaction between CD4+ T cells and the predominant liver antigen
presenting cells, the liver sinusoidal endothelial cells and the liver resident Kupffer cells,
results in the expansion of regulatory T-cells and immune suppression[31, 169].
Intriguingly, in polyinosinic-polycytidylic acid (poly I:C), CCl4 or Methionine-Choline-
deficient diet induces liver inflammation, and T-cells can be effectively activated by
Kupffer cells[31, 170]. Overall, the liver microenvironment is shaped by complex and
34

delicate interactions between its parenchymal cells, endothelial cells and various immune
cells. In this chapter, we looked into which of the liver cells are the cellular origin of
CXCL5.
3.2 Results
To identify the cellular source of CXCL5, we first examined the correlation between
CXCL5 expression and cell-type specific markers using GEO datasets. We collected 15
GEO datasets incorporating 587 samples, and ranked the genes per sample to obtain a
ranking dataset. The ranking dataset was normalized by subtracting the mean value of
each sample so the resultant mean was 0 and scaling the variance to 1. We performed
OLS (ordinary least squares) regression, Lasso and graphic Lasso regression analysis
on a set of inflammatory cytokines and macrophage and monocytes markers in the
ranking datasets (Tables 3). Our analysis showed that, of the independent variables
examined, only F4/80 (a macrophage marker) and Timd4 (a Kupffer cell marker) were
significantly predictive of CXCL5 in all three analyses. Interestingly, the monocyte
markers CCR2 and Ly6C made negligible contributions to predict CXCL5 in both Lasso
regression and OLS analyses. To validate the accuracy of our analysis, we included other
members of the neutrophil activating chemokine family, specifically CXCL1, CXCL2 and
CXCL3. We compared our bioinformatics results on these chemokines to published
experimental results: Previous studies suggested that CXCL2 is produced by hepatocytes
as well as by macrophages[61, 171]. Macrophages produce CXCL2 in response to TLR2
stimulation but not TLR4 stimulation [172]. In comparison, CXCL1 was mainly produced
by hepatocytes and hepatic stellate cells, lesser produced by macrophages[173, 174].
Our analysis is consistent with published experimental results: CXCL1 did not correlate
35

with F4/80 in any of the regression analysis (Lasso coefficient=0), while 2 out of 3
regressions suggested CXCL2 correlation with F4/80 (Lasso coefficient=-0.011).
36

Table 3: CXCL5 expression correlates with macrophage marker F4/80. Table 3.1: OLS regression analysis, each
row is calculated using the top row of genes as the independent variables, and the gene in the left column as the
dependent variable; Table 3.2: Lasso regression analysis, independent and dependent variables are the same as
in Table 3.1; Table 3.3: Summary of all three regression analysis, the integer (0,1,2 or 3) records the number of
methods that suggested association between the two genes. 3 means that three methods all suggested correlation
between such two genes; 0 suggests that no method supported relationship between these two genes.

37

To further consolidate our analysis, we used a different set of genes, mainly cell-
type specific marker genes, and analyzed their correlation with CXCL5 expression using
Lasso (Table 4). We found that a macrophage marker CD64 contributed the most to
CXCL5 expression. This further confirmed the close relationship between macrophages
and CXCL5.
In addition, we performed sub-expression analysis of CXCL5 with different cell type
markers in TCGA human HCC datasets using the GEPIA2021 online tool
(http://gepia2021.cancer-pku.cn/)[175]. In this analysis, EPIC deconvolution method was
used to determine the proportion of each cell type. This method established the reference
genes expression profile (including the expression of tens of thousands of genes in each
cell type) of the major cell types. The total tissue expression of the reference genes should
equal to the sum of the individual cell type expression multiplied by its proportion. The
proportion of each cell type was inferred using least-square regression[176]. This analysis
demonstrates that CXCL5 expression is exclusively associated with macrophages in liver
hepatocellular carcinoma samples (Fig 6).
Table 4: Macrophage marker CD64 correlates with CXCL5 expression. Genes listed on the top row were used as
independent variables to regress on CXCL5. The first column are the weights set for Lasso regression. A larger weight
will eliminate more genes from possible relationship with CXCL5. Table was split into 2, all genes from 2 tables were
used together as independent variables.

38

The mRNA expression level was measured by TPM (transcripts per million). The
median TPM of macrophages from HCC tumors, HCC tumor adjacent normal tissues and
healthy livers were 9174 (Q1=2115, Q3=41677), 23043 (Q1=15761, Q3=52978) and
1758 (Q1=636, Q3=6183) respectively, while CXCL5 expression was not detected in
other cell types. Macrophage associated CXCL5 expression was significantly higher in
HCC tumor tissues compared to healthy livers (p-value<0.0001), and in HCC surrounding
normal tissue compared to healthy livers (p-value<0.0001). We further investigated the
association of CXCL5 expression with that of specific macrophage population markers
using TCGA data. Our results show that the expression of CXCL5 positively correlated
with those of two macrophage markers: CD64 (Figure 7A) and macrophage scavenger
receptor 1 (MSR1) (Figure 7B).
CD64 is preferentially expressed by proinflammatory macrophages whereas
MSR1 promotes pro-inflammatory macrophages by engaging in macrophage lipid
uptake. Our data indicated that CXCL5 correlates with pro-inflammatory macrophage
Figure 6: Macrophages are solely responsible for CXCL5 expression. Macrophage was exclusively associated with
hepatic CXCL5 expression based on EPIC deconvolution of TCGA data.
39

marker genes (MSR1 and CD64) expressions (R=0.32 p<0.0001 and R=0.42 p=0
respectively), whereas CD19, a B cell specific marker, and albumin (ALB), a hepatocyte
marker, showed no correlation with CXCL5 (R=-0.0027 p=0.96 and R=-0.062 p=0.23
respectively).
Figure 7: Pearson correlation in human HCC tumors. CXCL5 expression correlated with A) CD64 (p<0.0001) and B)
MSR1 (p<0.0001); CXCL5 did not correlate with C) CD19 (p=0.96) or D) ALB expression (p=0.23).
40

We also confirmed these observations in patient samples using
immunohistochemistry (Figure 8). CD68 is a macrophage marker that labels various
macrophage populations in the liver[160]. We show here that CXCL5 colocalized with
human macrophage marker CD68 (as indicated by the yellow staining which is the result
of green CXCL5 and red CD68 colocalization) in HCC samples. CXCL5 is localized
mainly within the macrophages, but we also see macrophage enriched areas where
CXCL5 seems to be secreted in between the cells. Together, these data suggest that
macrophages are the cellular source for CXCL5 in the liver.

41

To further confirm that hepatic macrophages are the cellular origin of CXCL5, we
utilized a liver tumor model where a tumor suppressor gene Pten is deleted (Pten
loxP/loxP
;
Alb-Cre
+
, Pten null) (Figure 9).

Figure 8: Immunostaining of human HCC tumors shows colocalization of CXCL5 and CD68. CXCL5 was stained
in green, CD68 was stained in red, nuclei were stained with DAPI in blue.
30µm 30µm
30µm
30µm
42

Figure 9: Disease progression in Pten null mice. Development of liver disease in wild type (Con) vs Pten null (Mut)
mice: Pten null mice sequentially develop steatosis (top) to fibrosis (middle) to liver cancer (bottom).

43

Immunostaining showed that PTEN protein loss occurred in 40 to 50% of HCC
cases[177, 178]. PTEN loss of function mutation including missense mutation V255A was
observed in a subset of HCC patients[179]. In addition, genetic alteration of PI3K/AKT
pathway was identified in 51% of HCC cases[180]. These studies validated the clinical
relevance of Pten-null HCC model. PTEN is a dual-specific protein and lipid phosphatase,
it is most known for its role in antagonizing the phosphoinositide 3-kinases (PI3Ks)
function. While PI3K converts membrane lipid PI(4,5)P2 to PI(3,4,5)P3, PTEN
dephosphorylates PI(3,4,5)P3 at the 3’ position of the inositol ring to generate PI(4,5)P2.
Membrane PI(3,4,5)P3 is required for the activation of Akt by binding to its PH domain
and bringing Akt to the cytosolic membrane. Thus, PTEN is a negative regulator of the
PI3K-Akt pathway[181]. Since the PI3K-Akt pathway mediates cell growth, cell survival
and the insulin signaling, PTEN is a tumor suppressor as well as a metabolic regulator.
Liver specific deletion of PTEN promotes increased de novo lipogenesis in hepatocytes
which results in liver steatosis and injury[182]. Removal of the tumor suppressor PTEN
also allows consistent onset of liver cancer[183, 184]. This model recapitulates clinical
features of NASH associated HCC development where the mice developed steatosis at
an early age (1 month)[185]. By 12 months of age, 100% of the mice developed
spontaneous liver tumors. In this model, we reported previously that inflammation is
induced concurrently with the progression from steatosis to cancer[186]. In the 9 months
old Pten null (PM) mice, we observed a robust increase of the macrophage population as
compared to the wild type (WT) mice (Figure 10).
44

Macrophages accounted for 49 + 1.4% of total liver immune cells in the Pten null
livers, while they only accounted for 37.5 + 3.2% of total liver immune cells in the wild
type livers. Consistent with flow cytometry analysis in these mice, total macrophages
Figure 10: Flow cytometry analysis of liver immune cell population. Top: Pie chart of immune cell populations,
population percentages + standard error mean were labeled; Bottom: Dot plot of individual immune cell
populations.
45

(marked by F4/80) and Kupffer cells (marked by Clec4f) are dramatically increased in the
Pten null mouse livers (Figure 11).
Figure 11: Immunostaining of liver macrophages in wild type vs Pten null mice. F4/80 was stained in
red, Clec4f was stained in green, nuclei were stained with DAPI in blue.

30µm 30µm
30µm 30µm
46

Concurrent with the notion that the macrophage is the potential source for CXCL5,
we observed a progressive increase of CXCL5 expression in the Pten null livers as tumors
develop (Fig 12).
At 6 months of age, there is a trend of CXCL5 increasing in Pten null (PM) livers,
and CXCL5 expression in PM livers was 1.5-fold of that in wild type (WT) livers (p=0.08).
In 9-month-old PM mice, liver CXCL5 expression was 2.5-fold as high as it was in age
matched WT mice (p=0.02). By 12 months of age, CXCL5 expression was 92-fold higher
in Pten null livers than that in wild type livers (p=0.0024). This is consistent with our
analysis of human HCC datasets which showed that CXCL5 was elevated in human HCC
livers compared to healthy livers. The concurrent increase of the liver macrophage
population and CXCL5 expression further support that CXCL5 is produced by
macrophages.
Figure 12: CXCL5 expression increase gradually during HCC development in Pten null mice. Hepatic
expression of CXCL5 in wild-type vs Pten null mice measured by qPCR. 6M: n=7, p=0.083; 9M: n=10, p<0.05;
12M: n=6, p<0.01.
47

3.3 Discussion
Chemokines are usually produced by various cell types. CXCL5 belongs to the
neutrophil activating chemokine family, but other members from that family, namely
CXCL1 and CXCL2, has been shown to be produced by hepatocytes, macrophages and
hepatic stellate cells in different conditions[171, 174]. By using RNAseq or microarray
data, different algorithms are able to predict the immune/stromal cell composition in the
tissue[176]. In this study, we predicted the cellular source of cytokines/chemokines based
on regression analysis with cell type marker genes and verified the results using
immunofluorescent staining and flow cytometry (Chapter 4). Our analysis showed that
CXCL5 is strongly associated with macrophage markers such as F4/80 and CD64 in mice,
and human macrophage markers such as MSR1 and CD64 in human HCC datasets. We
utilized a Pten null mouse model to further examine CXCL5 expression experimentally.
Similar to what we found in human HCC, this model exhibited CXCL5 upregulation during
HCC development. Our results indicated that CXCL5 is increasingly produced by the
expanding liver macrophage population during liver cancer progression.
Using RNAseq and microarray data, different algorithms had been developed to
predict the immune/stromal cell composition in the liver[176]. We used bioinformatics to
analyze these markers and tested the association of macrophages and CXCL5. A
combination of OLS and Lasso regression showed that the macrophage marker F4/80
contributed the most to CXCL5 expression, while monocyte markers CCR2 and Ly6C had
little contribution to CXCL5. Lasso regression with an extensive list of macrophage,
monocytes, neutrophils, endothelial cells and hepatocytes marker genes further identified
48

CD64 as the top contributor to CXCL5 hepatic expression. Due to the heterogeneity of
the liver macrophage population, not all macrophage markers correlated with CXCL5,
suggesting that a subset of macrophages was responsible for CXCL5 production. The
contribution of subpopulations of macrophages to CXCL5 production is further explored
later in Chapter 4.
CXCL5 belongs to the neutrophil activating chemokine family, which are commonly
upregulated in liver inflammation. The neutrophil activating chemokines includes CXCL1,
2, 3, 5, 6, 7 and 8 in humans. They recruit neutrophils to inflamed tissues to exert
antibacterial functions including phagocytosis and production of reactive oxygen species
(ROS). In human NASH patients, CXCL1 and CXCL8 are frequently upregulated in
hepatocytes and result in neutrophil infiltration[187]. However the strong association
revealed by our regression analysis was not a result of concurrent increase of various
chemokines production and macrophage infiltration during liver inflammation. The
macrophage marker F4/80 showed no association with the expression of CXCL1 which
is commonly upregulated during hepatic inflammation[188, 189]. Interestingly, other
members of the neutrophil activating chemokine family (CXCL1, CXCL2, CXCL3) showed
very weak or no correlation with CXCL5, while CXCL2 and CXCL3 strongly correlated
with CXCL1. This also suggested a unique cellular origin of CXCL5 compared to the other
neutrophil activating chemokines.
Despite the increased CXCL5 expression, we found that the neutrophil population
did not increase in the liver. This is further confirmed by our microarray analysis of 9-
month-old Pten null mice compared to wild type mice (publicly available in GSE70501),
49

where neutrophil specific marker Mrgpra2 expression was slightly reduced in Pten null
compared to wild type mice(p=0.389, data not shown)[190]. In contrast, the macrophage
marker F4/80 and Kupffer cell marker Clec4f expression increased significantly in Pten
null compared to wild type mice by 3.3 fold (p<0.001) and 0.8-fold (p<0.05) respectively
(data not shown). Consistently, in another NAFLD HCC model, the neutrophil population
did not increase in mice fed with DEN plus the ALIOS (American lifestyle induced obesity
syndrome) diet[191]. Similar to our results, the ALIOS diet induced NASH also showed
an increase in liver inflammation and in the macrophage population[192].
Previous studies detected CXCL5 expression in multiple HCC cell lines, they
suggested that CXCL5 was mainly produced by liver cancer cells. However, through
bioinformatics analysis and IHC staining of human HCC tissues, we found that CXCL5 is
mainly expressed by liver macrophages.

50

Chapter 4
CXCL5 is expressed by HCC associated proinflammatory Kupffer
cells
4.1 Introduction
Liver macrophages are an extremely diverse population. Functionally, macrophages can
alter their immune responses depending on the microenvironment. In vitro murine BMDM
(bone marrow derived macrophage) treatment with LPS and IFNγ induces pro-
inflammatory macrophages that are characterized by the upregulation of cytokines
including IL-1β, IL-6 and IL-12. Macrophages with this phenotype were named M1
macrophages. M1 macrophages also upregulated neutrophil activating chemokines
including CXCL1, CXCL2 and CXCL3, but not CXCL5. Interestingly, in vivo stimulation of
peritoneal macrophages with LPS did not induce the neutrophil activating chemokines. In
vitro stimulation of BMDM with IL-4 induces anti-inflammatory macrophages that are
characterized by upregulation of MRC1 (CD206)[193]. These anti-inflammatory
macrophages were termed M2 macrophages. In human, studies on tumor associated
macrophages identified HLA-DR (human leukocyte antigen-DR), NOS2/iNOS (inducible
nitric oxide synthase) phosphorylated STAT1 and CD64 as M1 markers. Tumor
associated M2 macrophages are characterized by high expression of CD206, CD204 and
CD163. CD68 is expressed by both M1 and M2 macrophages[194, 195]. Biochemically,
M1 and M2 macrophages both catalyze the cleavage of arginine. M1 macrophages
express high levels of iNOS to convert arginine into NO which inhibits cell growth, M2
macrophages express high levels of Arginase to convert arginine into ornithine which
promotes cell survival. Recent studies have shown a much more complicated spectrum
of macrophage phenotypes compared to the M1/M2 paradigm, in vivo, macrophages
51

usually express a combination of M1 and M2 markers. However, M1 and M2 are still
commonly used as simpler terms for pro-inflammatory (tissue damage) and anti-
inflammatory (tissue repair) macrophages[196].
In terms of cellular origin, there are two populations of macrophages residing in the liver:
monocyte derived macrophages (infiltrating macrophages) and the embryonic yolk sack
derived Kupffer cells (liver resident macrophages)[33]. Transcriptional factors including
ID3 and LXRα control the tissue specific development of Kupffer cells[197, 198]. The
unique identity of Kupffer cells is dependent on the niche created by liver sinusoidal
endothelial cells (LSECs), hepatic stellate cells (HSCs) and hepatocytes. While Kupffer
cells reside within the liver sinusoids, they extend themselves into the space of Disse to
form close contact with HSC and hepatocytes. Kupffer cell’s expression of ID3 and LXRα
are induced by hepatocytes and LSEC respectively, while HSC secrete BMP9 (bone
morphogenetic protein 9) to further stimulate the expression of Kupffer cell specific
markers such as Clec4f and CD38[199].
The intestinal tract and liver are closely connected both anatomically and physiologically.
Therefore, the gut microbiota and their metabolites play important roles in the
homeostasis of the liver. In recent years, several studies suggest that excessive intake of
a high-fat diet can lead to the compositional changes of gut microbiota[200]. This change
results in increased gram-negative bacilli in the intestinal microflora which is the main
source of endotoxins including LPS[201]. In fatty liver disease, intestinal barrier
dysfunction (leaky gut) leads to increased microbe-associated molecular patterns
(MAMPs) and metabolites of bacteria or even the translocation of the bacteria themselves
52

can occur into the liver through the portal vein[202]. This allows an elevated amount of
lipopolysaccharide (LPS), a characteristic molecule produced by most Gram-negative
bacteria, translocate into the liver[203]. In healthy conditions, Kupffer cells and
hepatocytes can clear the LPS produced by gut microbiota since only a small amount of
LPS can penetrate the barrier, which cannot cause significant clinical inflammation[204].
However, in chronic liver diseases such as NAFLD (non-alcoholic fatty liver disease)
/NASH (non-alcoholic steatohepatitis), the excessive LPS, which cannot be cleared by
Kupffer cells and hepatocytes, can trigger inflammation. The precise mechanism of
NAFLD/NASH associated leaky gut is still unclear, but it was shown that the intestinal
mucosa from obese mice have an altered tight junction protein localization which causes
increased intestinal epithelial permeability[205]. Studies in MCD (methionine choline
deficient) diet fed mice have shown that the initial phase of liver damage indicated by
increased serum ALT precedes increased intestinal permeability, suggesting that
disrupted liver homeostasis induces the leakiness of the gut[34].
Experimentally, mouse liver macrophages are identified through a few markers: infiltrating
macrophages (monocyte derived macrophages) are CD11b
high
F4/80
intermediate
Clec4f
-
,
while the Kupffer cells are CD11b
intermediate
F4/80
high
Clec4f
+
. In many studies, F4/80 and
CD11b were sufficient to differentiate between Kupffer cells and infiltrating macrophages.
Clec4f is expressed by most Kupffer cells and is unique to Kupffer cells. There are
emerging new markers for Kupffer cells such as Vsig4, Timd4 and Folr2, but whether
these markers label the majority of Kupffer cell population has not been tested.

53

4.2 Results
In the Pten null liver, intracellular flow cytometry analysis of non-parenchymal cells
(Fig 13A) isolated from the 9-month-old livers identified a subpopulation of F4/80 and
CD11b positive macrophages (circled cells, Fig 13A). The histogram (Figure 13B) is
based on the fluorescence intensity of the CXCL5 antibody staining in liver non-
parenchymal cells (blue peaks, Fig 13B). The red peaks in the histogram are the circled
macrophage population from Figure 13A. The 2 red peaks indicated that the expression
of CXCL5 splits the macrophages into 2 populations. The red peak (macrophages) on the
right is at the right end of the blue peaks (liver non-parenchymal cells), suggesting that
these macrophages have the highest expression of CXCL5 within the liver non-
parenchymal cells. Similarly, the non-parenchymal cells (blue peaks) show a small peak
on the right side of the main peak, and a comparison with the main peak shows that this
small peak consists of the CXCL5 high expressing cells. The macrophage peak on the
right almost completely occupies the small peak of the non-parenchymal cells, which
suggests that the majority of the CXCL5 high expressing liver non-parenchymal cells are
these macrophages.

54

Figure 13: Flow cytometry identifies macrophages as the cellular source of CXCL5. A) Intracellular flow cytometry
analysis of liver non-parenchymal cells, circled are CD11b+ F4/80+ macrophages; B) Histogram of PE fluorescence.
Blue peak: Some liver non-parenchymal cells were fixed, permeabilized and stained with primary CXCL5 antibody
and PE-conjugated secondary antibody. Out of them, Gated macrophages (Figure 13A circled) were shown in red
peaks. Yellow peak: Some liver non-parenchymal cells were fixed, permeabilized and stained with only PE-
conjugated secondary antibody.
55

We further identified the CD64
high
macrophages (Fig 14A population 1) among the
F4/80
+
CD11b
+
population to be the CXCL5 high-expressing cells whereas the CD64
low

macrophages (Fig 14A population 2) express lower levels of CXCL5 (Fig 14B).
Figure 14: CD64high macrophages express the highest levels of CXCL5. A) Gated macrophages can be further
separated into 2 populations based on CD64 expression level: CD64high (population 1) and CD64low (population 2).
B) Histogram of CXCL5 expression measured by PE fluorescence. CD64
high
macrophages (population 1) are shown
in the red peak and CD64
low
macrophages (population 2) are shown in the blue peak.

56

Since this analysis only included liver non-parenchymal cells, we also compared
CXCL5 expression in hepatocytes and macrophages by comparing the MFI (mean
fluorescence intensity) of CXCL5 in hepatocytes vs. macrophages (Figure 15). MFI is
usually normalized in 2 ways: 1) subtraction method: positive population MFI subtracted
from negative population MFI (Figure 15A); 2) division method: positive population MFI
divided by negative population MFI (Figure 15B). The negative population is to measure
non-specific binding and auto-fluorescence. For hepatocytes, the positive population are
the permeabilized hepatocytes stained with primary CXCL5 antibody and fluorescent
secondary antibody, the negative population is the permeabilized hepatocytes stained
with only fluorescent secondary antibody. For macrophages, we used CD64
low

macrophages as the negative population and CD64
high
macrophages as the positive
populations, all macrophages were permeabilized and stained with primary CXCL5
antibody and fluorescent secondary antibody. Macrophages showed 4-fold (p<0.001) and
10.5-fold (p<0.05) increase of CXCL5 MFI compared to hepatocytes using the subtraction
method and the division method, respectively. Together, our data showed that CXCL5 is
expressed in CD64 high-expressing macrophages.

57

Consistent with the upregulation of CXCL5, more CD64
high
macrophages are
observed in the tumor-bearing Pten null (PM) livers vs. controls (WT) (Fig 16A). In addition,
expression analysis found a 3-fold higher expression of CD64 (p<0.05) in PM tumor livers
compared to WT livers (Fig 16B). Together, these data indicated a pro-inflammatory
environment in the livers of the Pten null mice. In addition, proteomic analysis using mass
spectrometry in 9-month-old Pten null and wild type livers also showed increased M1
polarization in Pten null livers (Fig 16C). IPA (Ingenuity Pathway Analysis) showed that
in Pten null livers, genes associated with macrophage M1 polarization including PRKCSH,
LCN2, PDK1 and AHSG increased to 1.14, 1.44, 1.09, 1.14 folds of that in wild type livers.
Figure 15: Macrophages, but not hepatocytes, are the main source of hepatic CXCL5. A) CXCL5 MFI was calculated
by positive population MFI subtracted by negative population, n=3, p<0.001 MFI; B) CXCL5 MFI was calculated by
positive population MFI divided by negative population MFI, n=3, p<0.05.
58

We further analyzed the hepatocellular carcinoma (HCC) data available on TCGA.
Figure 16: Pten null livers are pro-inflammatory. A) Percentage of CD64high macrophages in liver infiltrating
macrophages, n=3, p<0.01; B) mRNA expression of CD64 in PM and WT livers analyzed by qPCR, n=6, p<0.05; C)
IPA (Ingenuity Pathway Analysis) based on the proteomics data of Pten null and wild type livers.
59

Consistent with a M1 macrophage phenotype, this analysis showed that expression of
M2 macrophage markers including CD163 (p<0.0001) and MRC1 (p<0.01) is significantly
lower in tumors compared to tumor adjacent healthy tissues (Figure 17A). On the other
hand, expression of M1 macrophage markers such as CD64 (p<0.05) and NOS2
(p<0.0001) is significantly increased (Figure 17B). NOS2 expression increased by over
2-fold in tumor samples compared to tumor surrounding normal samples. Together, these
data show that liver cancer may be characterized by a pro-inflammatory
microenvironment with increased M1-like macrophages.

Figure 17: Human HCC is associated with pro-inflammatory macrophages. A) M2 macrophage marker expressions in
tumor adjacent normal liver tissues vs HCC tumor samples. B) M1 macrophage marker expressions in tumor
adjacent normal liver tissues vs HCC tumor samples.
60

A primary inducer for M1 proinflammatory macrophage and the expression of
CD64 is the bacterial toxin lipopolysaccharide (LPS), a pathogen associated molecular
pattern (PAMP)[206] proteins. In the Pten null mice, it has been shown that LPS is
significantly increased in the portal vein compared to the wild type mice[207]. To
determine if LPS induced the production of CXCL5 in the liver macrophages, we isolated
and treated primary liver macrophages with 100ng/ml LPS for 24 hours (Fig 18).
Peritoneal macrophages and the murine macrophage cell line Raw264.7 were also used
as controls (Figure 19). Expression analysis showed that LPS treatment induced dramatic
CXCL5 upregulation by 20-fold in the macrophages from wild type (WT) livers. The
CXCL5 induction decreased to 9-fold in 12-month old Pten null (PM) livers which
developed HCC tumors. This decrease may be due to the increased infiltrating
macrophages in the liver during tumor development, which do not up-regulate CXCL5 in
response to LPS. In the peritoneal macrophages or the murine macrophage cell line
Raw264,7 cells, however, no changes were observed, consistent with earlier studies
where CXCL5 expression was found induced by LPS in mouse fibroblasts but not
peritoneal macrophages or macrophage cell lines, Raw264.7 and J774A.1 [208, 209].
Figure 18: LPS stimulate CXCL5 expression in liver macrophages. LPS induced CXCL5 mRNA expression in liver
primary macrophages from wild type, 9-month Pten null mice and 12-month Pten null mice. WT: n=3, p<0.01; 9M
PM: n=3, p<0.01; 12M PM: n=3, p<0.05.
61

Additionally, we performed mass spectrometry analysis to assess the secretomes
of liver macrophages treated with or without LPS. Our data indicate that secreted CXCL5
from LPS treated liver macrophages were 2.15 fold of that from untreated liver
macrophages (p<0.05) (Fig 20). In addition to CXCL5, we also observed induction of
several other chemokines from macrophages treated with LPS including CXCL2, CXCL3,
CCL2, CCL5, and CCL9. In contrast, Galectin-3, whose expression is associated with
anti-inflammatory macrophages, did not increase after LPS treatment.
Consistent with our regression analysis of GEO mouse liver transcriptomics data
where CXCL2 and CXCL3, but not CXCL1, correlate with the macrophage marker F4/80
(Table 3), CXCL1 was not detected in the liver macrophage secretome, while secreted
Figure 19: LPS does not stimulate CXCL5 expression in peritoneal macrophages and macrophage cell lines. LPS
induced CXCL5 expression was measured in mice peritoneal macrophages and murine macrophage cell line Raw
264.7 cells. Lines were used to connect peritoneal macrophages (control and LPS treated) from the same mice.
Peritoneal macrophages: n=3, p=0.63; Raw264.7: n=3, p=0.61.
62

CXCL2 and CXCL3 increased to 1.87 and 2.35 fold in LPS treated compared to untreated
liver macrophages. As a positive control, the classical M1 macrophage proinflammatory
cytokine TNF (tumor necrosis factor) was dramatically increased by 3.38 fold in LPS
treated liver macrophages. CXCL16, an IFNγ induced M1 cytokine [193] was not
significantly induced. These results suggest that liver macrophages produce chemokines,
particularly CXCL5 in response to LPS stimulation and that this is likely a unique feature
of liver macrophages.
LPS induces macrophage cytokine production via binding to its cell surface
receptor TLR4. To test whether other TLR4 ligands can also induce CXCL5, we treated
isolated liver macrophages with HMGB1, a common DAMP released by damaged
Figure 20: LPS stimulated the secretion of CXCL5 in liver macrophages. Mass spectrometry analysis of LPS
induced mice primary macrophages secretome. Detected cytokines and chemokines are plotted; n=3 for all
chemokines and cytokines; CXCL2: p<0.01; CXCL3: p<0.05; CXCL3: p<0.05; CXCL5: p<0.05; CXCL16: p=0.25;
CCL2: p<0.01; CCL5: p<0.05; CCL7: p<0.05, CCL9: p=0.074; IL1: p<0.05; TNF: p<0.01; Galectin-3: p=0.85.
63

hepatocytes. We compared the expression of CXCL5 induced by HMGB1 to that of TNFα,
a well-established downstream target of HMGB1 in macrophages. Compared to vehicle
treatment, HMBG1 induced a higher fold change in the expression of CXCL5 (3.6 fold of
that in untreated) than it did for TNFα (1.18 fold of that in untreated), suggesting that
CXCL5 is a robust downstream target of HMGB1 and TLR4 in macrophages (Fig 21).
The induction of CXCL5 in liver but not peritoneal or other macrophages suggest
a uniqueness of liver macrophages. This unique upregulation of CXCL5 by liver
macrophages is also observed in TCGA data analysis where HCC associated
macrophages showed higher expression of CXCL5 compared to other tumor-associated
macrophages (Fig 22). Liver macrophages consist of monocyte derived macrophages
and liver resident Kupffer cells. As monocyte derived macrophages are present in most
tissues while the Kupffer cells are specific to the liver, we hypothesized that this unique
property of liver macrophages to produce CXCL5 in response to LPS that we observed
in liver macrophages is a feature of the Kupffer cells. Supporting this hypothesis, MSR1,
which we showed to be strongly correlated with CXCL5 expression (Fig 7), was shown to
be preferentially expressed in Kupffer cells compared to monocyte derived
macrophages[167].
Figure 21: HMGB1 induced CXCL5 expression in liver macrophages. HMGB1 induced CXCL5 (left) and TNFα (right)
expression. Data represents liver macrophages isolated from 4 mice: M(1), M(2), M(3) and M(4). P<0.05 in all groups
when comparing CXCL5 expression between control and HMGB1 treated; Other than M(2),TNFα expression did not
significantly differ between control and HMGB1 treated.
64

To investigate whether CXCL5 expression is associated with the Kupffer cells, we
performed immunostaining of CXCL5 and Clec4f in LPS treated liver primary macrophage
cultures, and it showed that CXCL5 colocalizes with Clec4f indicating that the Kupffer
cells populations among the isolated macrophages are the source for LPS induced
CXCL5 secretion and upregulation (Fig 23). Co-staining of CXCL5 and Clec4f in the 12-
month-old Pten null livers showed that CXCL5 is almost exclusively associated with
Kupffer cells, further supporting a Kupffer cell origin of CXCL5 in liver cancer (Fig 24, See
next page).

Figure 22: Liver hepatocellular carcinoma associated macrophages express high levels of CXCL5. Macrophage
expression of CXCL5 in major cancers: Prostate Adenocarcinoma (PRAD), Pancreatic Adenocarcinoma (PAAD),
Colon Adenocarcinoma (COAD), Lung Adenocarcinoma (LUAD) and Liver Hepatocellular Carcinoma (LIHC).
Analyzed using GEPIA2021 (http://gepia2021.cancer-pku.cn). p<0.0001 comparing liver cancer associated
macrophages to tumor associated macrophages from other tissues.
65

Figure 23: CXCL5 expression in LPS treated Kupffer cells. Immunostaining of CXCL5 (green) and
Clec4f (red) in LPS treated liver macrophages. Nuclei were stained with DAPI (blue).
66

10µm
Figure 24: CXCL5 is expressed in Kupffer cells in Pten null mice. Immunostaining of CXCL5 (red) and Clec4f (green)
in 12M Pten null livers. Nuclei were stained with DAPI (blue).
67

Finally, using flow cytometry, we confirmed that Clec4f high Kupffer cells are the
cells that showed highest expression of CXCL5 among the immune cells (Figure 25).
Kupffer cells (red peak in Figure 25B) was located at the right end of the blue peaks
Figure 25: Kupffer cells are the major cellular source of hepatic CXCL5. A) Intracellular flow cytometry analysis
of liver non-parenchymal cells: circled are CD11b+ Clec4f+ Kupffer cells; B) Histogram of PE fluorescence. Blue
peak: liver non-parenchymal cells were fixed, permeabilized and stained with primary CXCL5 antibody and PE-
conjugated secondary antibody. Out of them, Gated Kupffer cells (Figure 25A circled) were shown in red peaks.
68

representing liver non-parenchymal cells. This showed the Kupffer cells exhibit the
highest fluorescent staining from the anti-CXCL5 antibody within the liver non-
parenchymal cells. In addition, the small blue peak on the right side of the main blue peak
represents the CXCL5 high expressing liver non-parenchymal cells. Kupffer cells (red
peak) occupied the majority of the small blue peaks, suggesting that most of the CXCL5
high expressing liver non-parenchymal cells may be indeed Kupffer cells.
We confirmed that CD64
high
Kupffer cells are the highest producers of CXCL5
(Figure 26).
69

Figure 26:CD64high Kupffer cells are the highest producers of CXCL5. A) Gated Kupffer cells can be further
separated into 2 populations based on CD64 expression level: CD64high and CD64low. B) Histogram of CXCL5
expression measured by PE fluorescence. CD64
high
Kupffer cells are shown in the red peak and CD64
low
Kupffer
cells are shown in the blue peak.
70

4.3 Discussion
Macrophage heterogeneity has been emphasized in recent studies[210, 211].
However functional characterization of distinct macrophage populations in vivo is still
needed, especially in liver cancers where the macrophage may play critical roles[207]. In
this study, we found that during liver cancer development, CXCL5, an HCC associated
chemokine, is almost exclusively expressed by CD64
high
Kupffer cells. Furthermore, LPS
uniquely induced CXCL5 expression in Kupffer cells but not in other macrophages
including peritoneal macrophages and Raw264.7 macrophage cell line.
We explored the accuracy of cellular source prediction based on regression
analysis of the cell type marker expression and the target protein (gene) expression in
Chapter 3. Our data in this chapter showed that the prediction was accurate. CXCL5 was
predicted to be associated with F4/80 expressing macrophages, but not Ly6C expressing
monocytes and monocyte derived macrophages (Figure 3.2). Indeed, our experimental
data support that macrophages, particularly Kupffer cells, are the cellular source of
CXCL5. Kupffer cells express higher levels of F4/80 and lower levels of Ly6C compared
to infiltrating macrophages. This accuracy was contributed by our method of combining
several datasets into a large dataset which increases the sample count. In addition, we
compared the strength of multiple regression analysis, and our results showed that Lasso
regression, which identified F4/80 and Timd4 as the only two contributing factor in CXCL5
expression, is more stringent and precise compared to OLS regression (Figure 3.1) and
Pearson correlation (data not shown).
71

There is ongoing debate regarding proinflammatory (M1-like) vs anti-inflammatory
(M2-like) macrophages. Which one is more detrimental for HCC patients? Our data as
well as TCGA data suggested that NOS2 and CD64 high (M1-like) macrophages are
increased while CD163 and CD206 high (M2-like) macrophages are drastically reduced
during HCC. Previous research suggested that M2 macrophages provide tumor immune
escape through immune suppression[212]. However, other studies showed that M1, but
not M2, induces tumor immune escape. Pro-inflammatory macrophages secrete
cytokines such as TNFα and IL-10 to induce PD-L1 expression on monocytes[54]. PD-L1
high macrophages from human HCC tumors expressed much higher levels of
proinflammatory cytokines (such as IL-1β, IL-6 and TNFα) compared to PD-L1 low
macrophages. Blocking IL-1β or TNFα reduced PD-L1 expression by 50% in HCC
associated macrophages[213].
Importantly, a subpopulation of Kupffer cells from HCC bearing livers expressed
the highest level of inflammatory cytokines as well as the highest level of PD-L1 and some
anti-inflammatory macrophage markers[214]. This suggests that tumor associated
macrophages cannot be clearly classified as pro-inflammatory (M1) or anti-inflammatory
(M2), they usually display a mixed phenotype. But pro-inflammatory cytokines are
commonly over-expressed by these tumor associated macrophages and this production
may play an important role in tumor development.
Increased gut bacteria derived endotoxins (endotoxemia) is a common issue in
patients with chronic liver diseases, especially in liver cirrhosis and NAFLD[215, 216].
About 40% of liver cirrhosis patients suffer from endotoxemia, the plasma LPS
72

concentration positively correlates with the severity of liver dysfunction[215, 217]. NAFLD
patients also have higher serum LPS concentration and hepatocellular LPS compared to
healthy controls[216]. LPS is one of the main PAMP for liver macrophages and stimulates
the proinflammatory cytokine production and M1 phenotypes in liver resident and
infiltrating macrophages. Stimulation of macrophages by LPS leads to increased total
macrophages and M1 macrophages, but decreased M2 macrophages[216]. This is
consistent with our findings in a NASH-HCC model and observations made using TCGA
dataset. In the liver specific Pten deletion mice, a previous study showed an increase in
LPS concentration in the portal vein. LPS concentration was lowered by treating PTEN
null mice with antibiotics, and a reduced HCC tumor incidence and size was also
observed after treatment[207]. LPS binds to and activates TLR4. Inhibition of TLR4
prevented HCC development in PTEN null mice[218]. With the increased global NAFLD
patient population and increased HCC cases attributable to NAFLD, increased LPS and
endotoxins are affecting more and more patients. Though LPS promotes liver
inflammation through the TLR4 pathway, there lacks insight on how that leads to HCC
development and druggable targets.
Interaction between LPS and macrophages has been previously reported.
However, most of these studies utilized macrophage cell lines or peritoneal macrophages
which are easy to acquire. Precise response of liver macrophages especially Kupffer cells
to LPS has not been fully explored. Multiple studies showed that fibroblasts but not
macrophages produced CXCL5 in response to LPS. While CCL2 was induced in LPS
treated macrophages (including peritoneal macrophages, Raw264.7 and J774A.1
macrophage cell lines), CXCL5 mRNA was only induced in Swiss 3T3 fibroblasts but not
73

in any of the macrophages. Intraperitoneal injection of LPS also did not induce CXCL5
induction in murine peritoneal macrophages[209]. Another study compared CXCL1,
CXCL2 and CXCL5 secretion in the mouse corneal fibroblast cell line MK/T-1 and primary
peritoneal macrophages and neutrophils. ELISA analysis of the cell culture supernatants
showed that CXCL1 was highly induced by LPS in fibroblasts, CXCL2 was induced in
macrophages and neutrophils but not in fibroblasts, CXCL5 was only induced in
fibroblasts but not in neutrophils or macrophages[208].
Unlike other macrophages in the body, Kupffer cells are faced with increased
concentrations of LPS constantly. Previous studies suggested that Kupffer cells, unlike
Raw264.7 and peritoneal macrophages, react to LPS independent of CD14[40]. Kupffer
cells likely respond to LPS in a unique way to maintain liver homeostasis as well as to
clear potential microbiome threats. We found that Kupffer cells react to LPS differently
compared to peritoneal macrophages and Raw264.7 macrophages, Kupffer cells
uniquely over-express CXCL5 in response to LPS. This was confirmed by qPCR as well
as mass spectrometry analysis of Kupffer cell secretome. Indeed, our
immunohistochemistry staining and flow cytometry analysis showed that CXCL5 is
produced by F4/80
high
Clec4f
+
CD64
high
Kupffer cells. We think that CXCL5 is part of a
Kupffer cell unique repertoire and may play an important role in liver diseases especially
HCC.

74

Chapter 5
CXCL5 promotes HCC growth
5.1 Introduction
The cellular receptor for CXCL5 is C-X-C receptor 2 (CXCR2). CXCL5 shares this
receptor with other CXCL members that belong to the family of neutrophil activating
chemokines (NAC). The NAC chemokines, except CXCL6, including CXCL1, 2, 3, 5, 7,
8 share a conserved Glu-Leu-Arg domain. This domain allows these NACs to bind to and
activate CXCR2 through the ELR (single letter amino acid code) motif [152]. As a G
protein-coupled receptor (GPCR), binding to chemokine ligands results in: 1. The GTP-
bound Gα-subunit inhibits adenylyl cyclase which leads to decreased cAMP levels and
PKA activation; 2. Gα-subunit can also activate Ras and induce its binding with PI3K
catalytic subunit to activate the PI3K-Akt pathway; 3. The Gβγ-complex is able to activate
phospholipase C (PLC). PLC hydrolyzes the membrane phosphatidylinositol 4,5-
bisphosphate (PIP2) into the second messenger inositol trisphosphate (IP3) and
diacylglycerol (DAG). DAG activates PKC while IP3 stimulates the release of Ca
2+
from
the endoplasmic reticulum[219]. Specifically, CXCR2 is found coupled to PLC-β2 through
the PDZ scaffold protein Na+/H+ exchanger regulatory factor-1 (NHERF1). This
macromolecular complex mediates calcium mobilization and neutrophil chemotaxis[220],
dictating the function of CXCR2 binding NAC chemokines on neutrophil activation.
Beyond its role on neutrophil chemotaxis, CXCR2 also appears to play roles in
tumor growth[65, 142, 143, 149, 151]. In prostate cancer, development of castration-
resistance in androgen deprivation therapy is associated with the proliferation of
neuroendocrine cells which do not express androgen receptors. Instead of androgen
75

receptors, neuroendocrine cells over-express CXCR2 and proliferate in response to
CXCL8. On the other hand, CXCR2 inhibition suppressed the expansion of
neuroendocrine cells and inhibited tumor growth[221]. Similarly, in ovarian cancer, tumors
resistant to sorafenib treatment over-express CXCL8. Blockade of CXCR2 reduced tumor
cell proliferation and cancer stem cell properties. Combination of sorafenib and CXCR2
inhibition effectively reduced tumor growth compared to sorafenib alone[222].
In the liver, the function of CXCR2 is complex likely due to the crosstalk of multiple
cell types that differentially respond to CXCR2 ligand binding signal. The concentration
and types of the ligand may also be a factor that dictate response. In HCC cells, CXCL3
and CXCL5 have been found to activate mitogenic signaling including the PI3K-Akt and
Erk1/2 pathways[65, 143]. Consistently, inhibition of CXCR2 attenuated liver
regeneration in a partial hepatectomy model [223]. In hepatocytes, high concentrations
of CXCL2 induces hepatocyte cell death, whereas lower concentrations promotes
hepatocytes’ proliferation[128]. However, inhibition of CXCR2 directly promotes
hepatocytes’ proliferation during ischemia/reperfusion and bile duct ligation induced liver
injury that involves inflammation[224, 225]. Neutrophils are not involved during this
process. Thus, the induction of CXCL5 in the tumor livers may play a tumor promotion
role or is a response of the liver attempting to attenuate tumor growth. In this chapter, we
explore the role of CXCL5 on tumor cell growth and survival.

76

5.2 Results
To explore the effect of CXCL5 on tumor cell growth, we first performed the MTT
assay using several normal and tumor hepatocyte cell lines. Our data shows that CXCL5
promoted mouse hepatocytes viability in a dose dependent manner, suggesting a
mitogenic or cell death preventive role of CXCL5 on hepatocytes. In both wild-type and
Pten-deleted mouse hepatocytes, CXCL5 dose-dependently induced MTT indexes.
Especially at 10ng/ml, CXCL5 incubation for 24 hours increased wild type hepatocytes
MTT absorbance by over 20%, the increase reached 48% at 10000 cells per well. We
didn’t observe cytotoxic effects of CXCL5, however treatment with 100ng/ml CXCL5 for
48 hours showed reduced MTT indexes compared to 10ng/ml CXCL5 (Figure 5.1B). This
indicated a potential cytotoxic effect at higher CXCL5 concentrations. These data suggest
that the tumor associated CXCL5 over-expression can promote tumor growth (Figure 27).
77

CXCL5 binds to CXCR2 receptor to induce neutrophils’ migration. To address
whether CXCR2 activation promotes hepatocytes viability, we treated mouse hepatocytes
with different concentrations of CXCL5 with or without the CXCR2-specific inhibitor Azd-
Figure 27: CXCL5 treatment increased hepatocyte viability. MTT assay with mouse hepatocytes at different cell
densities treated with various concentrations of CXCL5. Inside the parentheses are the tag number of the mice from
which the hepatocytes were isolated from. A) MTT with wild type (644) immortalized hepatocytes incubated for 24hrs
with CXCL5. p<0.01 at all cell densities when comparing 1 or 10 or 100ng/ml CXCL5 treated group to control
(untreated) group. B) MTT with wild type (644) immortalized hepatocytes incubated for 48hrs with CXCL5. p<0.05 at
all cell densities when comparing 1ng/ml CXCL5 treated group to control (untreated) group; p<0.01 at 10000cells/well
when comparing 10 or 100ng/ml CXCL5 treated group to control (untreated) group. C) MTT with wild type (3798)
immortalized hepatocytes incubated for 24hrs with CXCL5. p<0.05 at all cell densities when comparing 10 or
100ng/ml CXCL5 treated group to control (untreated) group; p<0.05 at 20000 or 30000cells/well when comparing
1ng/ml CXCL5 treated group to control (untreated) group. D) MTT with Pten null (3798) immortalized hepatocytes
incubated for 24hrs with CXCL5. p<0.05 at all cell densities when comparing 100ng/ml CXCL5 treated group to
control (untreated) group; p<0.05 at 10000cells/well when comparing 1 or 10 or 100ng/ml CXCL5 treated group to
control (untreated) group.
78

5069. Our MTT results showed that the CXCR2 inhibitor Azd-5069 significantly
attenuated hepatocytes expansion induced by CXCL5 treatment (Figure 28).

Figure 28: CXCR2 blockade reduced hepatocyte viability. MTT assay with mouse hepatocytes treated with or without
CXCL5 and CXCR2 inhibitor Azd5069. Inside the parentheses are the tag number of the mice from which the
hepatocytes were isolated from. A) CXCL5 and Azd5069 treatment of wild type (644) hepatocytes. p<0.05 when
comparing 1 or 10ng/ml CXCL5 treated hepatocytes to 0ng/ml CXCL5 treated hepatocytes; p<0.05 at all CXCL5
concentrations when comparing hepatocytes treated without Azd5069 to hepatocytes treated with Azd5069. B)
CXCL5 and Azd5069 treatment of wild type (3798) hepatocytes. p<0.05 at 0.1 and 10ng/ml CXCL5 when comparing
hepatocytes treated without Azd5069 to hepatocytes treated with Azd5069.
79

To investigate whether CXCL5 induces cell proliferation or prevents cell death in
HCC tumor cells, we have performed the BrdU incorporation assay in human HepG2 cells,
which shows that CXCL5 increases human HCC tumor cells proliferation (Fig 6C).
Seventy four percent of the cells in the CXCL5 treated cultures were found to be BrdU
positive compared to 13% in the vehicle treated cells. Treatment with Azd5069 blocked
CXCR2 signaling and reduced BrdU positive cells to 17.8% (Fig 29).
Figure 29: CXCL5 induced HepG2 cell proliferation through CXCR2. A) Representative image of HepG2 cells
incubated with only BrdU for 14hrs; B) Representative image of HepG2 cells incubated with BrdU and CXCL5 for
14hrs; C) Representative image of HepG2 cells incubated with BrdU and CXCL5 and Azd-5069 for 14hrs; D)
Quantification of BrdU incorporation. n=3, p<0.05 when comparing CXCL5 treatment group to control group or
Azd5069 treated group.

80

CXCL5 induces proliferation of liver cancer cells was further verified in TCGA HCC
data, where a correlation between CXCL5 expression and MKI67 (gene of the
proliferation marker Ki67) expression is high in tumor tissues (r=0.36) (Figure 30A) but
low in tumor surrounding normal tissue (r=-0.077) (Figure 30B).

Figure 30: CXCL5 shows strong correlation with liver tumor proliferation. Pearson correlation of CXC ligands with
MKI67 in human HCC tissues. A) CXCL5 correlation with MKI67 in HCC tumors; B) CXCL5 correlation with MKI67 in
HCC tumor adjacent normal tissues; C) CXCL1 correlation with MKI67 in HCC tumors; D) CXCL2 correlation with
MKI67 in HCC tumors.

81

Among the neutrophil activating chemokines, including CXCL1 (r=0.12, Figure
30C), CXCL2 (r=-0.048, Figure 5.2D), CXCL3 (r=0.18), CXCL6 (r=0.11), CXCL7 (r=-
0.033) and CXCL8 (r=0.18), CXCL5 shows the highest correlation (r=0.36). Furthermore,
the strong correlation only exists in tumor tissues but not tumor adjacent normal tissues,
suggesting a specific association between CXCL5 and tumor cell proliferation.

5.3 Discussion
CXCL5 is associated with many roles in promoting tumor progression, such as
angiogenesis[226], metastasis[227] and tumor immune escape[228]. In this chapter, we
focus on the role of CXCL5 in tumor cell proliferation. Our results show that CXCL5
promotes hepatocyte proliferation and survival. We further investigated the role of
CXCR2 in CXCL5 regulated cell growth and survival. Our data suggest that CXCL5
promotes hepatocyte proliferation via binding to the CXCR2 receptors.
Our results on CXCL5 inducing hepatocyte proliferation are comparable to a
previous report on CXCL2. In the CXCL2 study, they measured LDH (lactate
dehydrogenase) release as the marker for hepatocytes cell death, and their data
showed that a 24-hour incubation with CXCL2 protected 20 to 30% of hepatocytes from
apoptosis at 1 and 10ng/ml respectively, while it induced hepatocytes’ cell death at
1000 and 10000ng/ml. There was no effect at 100ng/ml suggesting a balance between
mitogenic and apoptotic effects[224]. We measured CXCL5 induced hepatocytes’
proliferation with the MTT assay and found that 1 and 10ng/ml indeed induced
hepatocyte proliferation. In particular, 10ng/ml CXCL5 increased MTT indexes by 36%
82

to 48% at 10000 cells/well. However, we found that a 24-hour incubation at 100ng/ml
still induced significant hepatocytes proliferation and increased MTT absorbance by
45% to 52% at 10000 cells/well. These data suggest that a high concentration of
CXCL5 is less cytotoxic compared to CXCL2. In addition, analysis of HCC tumors from
TCGA showed a strong correlation between CXCL5 and the proliferation marker Ki67
expression, but not with other neutrophil activating chemokines. Overall, our results
suggest that CXCL5 is very potent in inducing tumor cells proliferation and has low
cytotoxicity at high concentrations.
CXCR2 is a cell surface protein that is more accessible to drugs, There are small
molecules and orally available drugs that can inhibit CXCR2. Recent studies exploring
the inhibition of CXCR2 showed that CXCR2 plays a multifaceted role in promoting tumor
progression. In some cases, CXCR2 signaling is responsible for tumor cell proliferation,
while other studies showed that CXCR2 mediates immune crosstalk and contributes to
tumor immune escape. In prostate cancer, development of castration-resistance in
androgen deprivation therapy is associated with the proliferation of neuroendocrine cells
which do not express androgen receptors. These neuroendocrine cells were found to
over-express CXCR2 and proliferate in response to CXCL8, a well characterized ligand
for CXCR2. In these models, the CXCR2 inhibitor navarixin suppressed the expansion
of neuroendocrine cells and inhibited tumor growth[221]. Furthermore, CXCR2 blockade
was also shown to increase the efficacy of anti PD-L1 therapy in pancreatic cancers and
HCC[191, 229]. CXCR2 inhibition also increases intratumoral CD8
+
T-cells. This effect
was dependent on the recruitment of myeloid cells, in particular dendritic cells, through
CCR receptors. Thus, it was suggested that CXCR2 mediates the crosstalk between
83

myeloid cells and T cells[191]. Contrary to the role of CXCR2 activation on promoting
neutrophil activation and chemotaxis, the CXCR2 inhibitor Azd5069 in combination with
anti-PDL1 therapy dramatically increased neutrophil accumulation at the tumor site.
Interestingly, the infiltrated neutrophils displayed anti-tumor characteristics, suggesting
the CXCR2 inhibition likely led to alterations of the inflammatory tumor microenvironment,
resulting in reprograming of the infiltrated neutrophils[191]. These studies demonstrate
that targeting the CXCL5-CXCR2 signal might be an effective therapy against HCC
immune suppression. Our study further shows that inhibition of CXCR2 suppresses tumor
growth through direct interaction with HCC tumor cells.
As a ligand for CXCR2, CXCL5 was originally characterized for its function to drive
neutrophil chemotaxis. In Chapter 2, we show that HCC tumors are frequently associated
with a CXCL5 high expressing microenvironment. The elevated CXCL5 concentration
helps tumors thrive and results in recurrent HCC[65]. We identified CXCL5 as a critical
chemokine in HCC. Consistent with the effect of CXCL5 on the induction of a mitogenic
signaling pathway, our data suggest a role of CXCL5 in tumor cell growth and survival.

84

Chapter 6
Perspective
From the mononuclear phagocyte system where all macrophages are differentiated from
monocytes and the bone marrow[230], to the recognition of prenatal yolk sac derived
tissue resident macrophages[210]; from the classical M1 vs M2 macrophage phenotype
distinction[231], to the 23 different liver macrophage clusters identified by CITE-seq
analysis[211], the appreciation of macrophage heterogeneity has dramatically improved
in the past 50 years. However, a detailed link between different macrophage populations
and disease progression is still lacking. Previous studies have identified Kupffer cell
specific markers such as Clec4f, Vsig4 and Timd4, and unique transcriptional factors such
as ID3 and LXRα that contributes to Kupffer cell specific identity[197, 198]. Nonetheless,
questions like, “what’s the functional relevance of Kupffer cells in HCC, is it the same as
for infiltrating macrophages?” have yet to be answered. In this work, we investigate the
chemokines and identify a strong association between CXCL5 and HCC progression. We
show that Kupffer cells are the predominant origin of liver CXCL5. We are the first to
report that Kupffer cells, but not other macrophages, uniquely over-express CXCL5 in
response to LPS.
LPS is frequently elevated in chronic liver diseases, and the Kupffer cells are the major
responders to LPS[232]. Studies in mice showed that the gut microbiota plays a critical
role in driving HCC progression, this is confirmed in Pten null mice where antibiotics
caused tumor suppression [207]. In DEN and CCl4 induced HCC, TLR4 deletion or gut
sterilization (either through antibiotics or transferring to a germ-free environment)
85

dramatically reduced tumor incidence and tumor size. 12-week administration of low-dose
non-toxic LPS significantly increased tumor count and size in DEN and CCl4 models[141].
We show here that LPS induces the unique overexpression of CXCL5 in liver resident
Kupffer cells, but not other macrophages. We further revealed the pro-inflammatory
microenvironment associated with HCC in both human and our mice. Stimulation of LPS
results in the enrichment of a subpopulation of Kupffer cells characterized by high CD64
and CXCL5 expression. This response of Kupffer cells to LPS likely contributes to the
strong association between CXCL5 and HCC. Our results identified CXCL5 as a common
mediator of LPS promoted HCC development.
CXC ligands (CXCLs) are known for their redundancy, and multiple ligands bind to the
same receptor. Correspondingly, there is a complex system of chemokine activity
regulation, the association between these regulations and diseases is largely unknown.
CXCLs activities are regulated by matrix metalloproteinases. MMP-12 cleaves the ELR
motif of CXCL1,2,3,5,8 to abrogate their activities[233]. MMP-9 differentially cleaves
and regulates CXCL5 and CXCL6. MMP-9 cleavage of CXCL6 results in no change in
its activity. In contrast, MMP-9 cleaves CXCL5 at multiple positions, and can result in
potentiation or inactivation of CXCL5[234]. In the case of mouse CXCL5, MMP-2 and
MMP-9 mediated cleavage is essential for CXCL5 induced neutrophil chemotaxis[235].
We show that out of all the chemokines, CXCL5 over-expression is prominently
associated with HCC. Anti-inflammatory macrophages in the liver express high levels of
MMP-12 which can deactivate CXCL5[160]. However our findings suggest that a pro-
inflammatory environment and M1-like macrophages are associated with HCC, and this
86

likely reduces the expression of MMP-12 by liver macrophages, which will help maintain
the tumor promoting activities of CXCL5.
Chapter 7
Method Development
We developed several methods to accomplish this project including the isolation
of liver macrophages and intracellular flow cytometry to explore the identity of cells that
express and produce CXCL5.
7.1 Liver macrophage isolation
7.1.1 Digestion of the Liver
To test our hypothesis that CXCL5 is produced by liver macrophages, we isolated
liver primary macrophages as cultured macrophage cell lines and peritoneal
macrophages that do not produce CXCL5 in response to treatment. To do this, we further
developed the liver cell isolation protocol. Mouse liver was perfused with PBS followed by
collagenase type IV (50mg collagenase in 100ml Hanks' Balanced Salt Solution). The
hepatic-cardio vein is cannulated to allow maximum contact and digestion of liver
connective tissues by collagenase.
The liver? filled with liver cells suspension in the collagenase solution is then
collected for further separation of different cell populations. The digested livers were
filtered through a 100µm pore size cell strainer to remove the debris.
87

7.1.2 Separation of non-parenchymal cells from hepatocytes
To remove hepatocytes, centrifugation 5 min at 50 x g or 30min (what g force?) of
natural sedimentation (1 x g) is performed. The larger hepatocytes will settle to the
bottom with these two different approaches. The supernatant is further centrifuged at 900
x g for 10mins at 4°C to pellet the non-parenchymal cells. The pelleted non-parenchymal
cells are then collected in 10ml of RPMI supplemented with 10% fetal bovine serum (FBS).
7.1.3 Separation of macrophages from non-parenchymal cells
To further separate macrophages from the other non-parenchymal cells, a Percoll
gradient 25/50% (SIP) is needed. The 25/50% Percoll gradient is gently added to the non-
parenchymal cell suspension. Centrifuge at 850 x g for 15 min without acceleration or
brake allows the cells to be distributed to the different gradient fractions. The enriched
macrophage fraction can be found within the 25% SIP fraction close to the 25/50% SIP
interface, while the dead cells floats near the top of the 25% SIP.
Percoll gradient recipe
• Stock Isotonic Percoll (SIP) solution: For a final volume of 50ml, add 5ml of 10x
PBS to 45ml of Percoll.
• 25% SIP solution: For a final volume of 40ml, add 30ml of 1x PBS to 10ml of SIP
solution.
• 50% SIP solution: For a final volume of 30ml, add 15ml of 1x PBS to 15ml of SIP
solution.
Percoll gradient protocol
88

In a 50ml falcon tube, add 15ml of 50%SIP solution at the bottom of the tube, tilt the tube
to almost 90
o
, slowly add 20ml of 25% SIP solution on the side wall of the tube without
touching the surface of the 50% SIP solution. Keep the tip of the pipette just above the
surface to avoid splashing and mixing.
Percoll cell extraction protocol
Using a 10 ml serological pipette, aspirate about 15 ml of the enriched macrophage
cell fraction. Transfer cells into a centrifuge tube containing 30 ml of RPMI supplemented
with 10% FBS. Mix gently and centrifuge at 1,350 x g for 15 min at 4 °C to pellet cells.
Discard the supernatant and resuspend cells in 5-10 ml of pre-warmed RPMI
supplemented with 10% FBS. Count cells (hemocytometer) and measure the viability
using trypan blue staining. Plate cells, incubate in CO2 incubator for 60mins, then gently
wash the cells with PBS and add fresh media to remove the non-adherent cells.

7.2 Intracellular flow cytometry
To determine the cell type that produce CXCL5, we developed the flow cytometry
methods to measure intracellular CXCL5 protein expression (Figure 7.2). Isolation of the
hepatocytes and the non-parenchymal cells is the same as for liver macrophage isolation
(See Chapter 7.1). Before subjecting to flow cytometry, the isolated non-parenchymal
cells are resuspended in 10mL RBC lysis buffer, resuspend cells by pipetting and
incubate on ice for 15mins with occasional mixing. We then perform a cell count to assess
the approximate recovery of non-parenchymal cells (in RBC lysis buffer) and hepatocytes
89

(in FACS buffer: 2% FBS in PBS) in the isolates before subjecting the cells to flow
cytometry. Aliquots of approximately 2X10
6
cells (in each tube) are allocated for
intracellular staining. The cells were then centrifuged at 300 x g for 5 min. and
resuspended in fixing solution. For each 2X10
6
cells, we resuspend and fix them in 200ul
2.5% formaldehyde solution (20µl 25% formaldehyde + 180µl FACS buffer) at room
temperature. After incubating/fixing for 5 min, add another 200ul 2.5% formaldehyde
solution, resuspend the cells and incubate for 10 more min to ensure sufficient fixing.
Wash the cells twice with FACS buffer. For each 2X10
6
cells, resuspend and permeabilize
them with 200ul 0.1% Tween-20 in FACS buffer at room temperature for 5 min. Then add
another 200ul 0.1% Tween-20 in FACS buffer, resuspend the cells and incubate at room
temperature for 10 more mins. Centrifuge (300g for 5mins) and gently remove the
supernatant. For each 2X10
6
cells, resuspend and stain the intracellular antigen (CXCL5)
with primary antibody (diluted in 200ul 0.1% Tween-20 FACS buffer) for 30 min at room
temperature. Wash the cells twice with FACS buffer. For each 2X10
6
cells, resuspend
and stain with secondary fluorescence-labeled antibody (diluted in 200ul 0.1% Tween-20
FACS buffer) for 30 min at room temperature in the dark. Wash the cells twice with FACS
buffer. For each 2X10
6
cells, resuspend and stain the extracellular antigens with diluted
primary antibody (diluted in 200ul FACS buffer) for 30 min at room temperature in the
dark (This is only if the antibodies can bind to fixed extracellular antigens, if fixation
prevents the binding with the antibody, move this step before the fixation). Wash the cells
twice with FACS buffer. Resuspend the cells in 500μL FACS buffer. At least 30,000 liver
immune cells are subjected to flow cytometric analysis on a flow cytometer (BD
FACSVerse). Experimental data were analyzed using FlowJo software.
90

Figure 31: Intracellular flow cytometry workflow.
91

Chapter 8
Materials and Methods
8.1 Bioinformatics
GEO data were extracted using the R package GEOquery. If one gene has multiple
probes in the dataset, then the probe with the highest expression readings was used.
TCGA analysis were performed using GEPIA (http://gepia.cancer-pku.cn/), GEPIA2021
(http://gepia2021.cancer-pku.cn/) and UALCAN (http://ualcan.path.uab.edu/) online
portal[175, 236].
8.2 Proteomics and Ingenuity Pathway Analysis
To analyze secreted chemokines from LPS treated liver macrophages, we isolated
mouse liver macrophages (See Chapter 7.1) from 3 Pten null mice and treated them
with or without 100ng/ml LPS for 24 hours in RPMI supplemented with 0.1% FBS. Cell
culture supernatants were collected and analyzed using mass spectrometry.
8.2.1 Mass spectrometry analysis
Macrophage secretomes were isolated as well as liver tissues and processed using
bottom-up global proteomic workflow as seen in Cohn et al
1
. Following the TMT labeling
and clean-up, samples were then fractionated using Pierce High pH Reverse-Phase
Fractionation Kit per manufacturer’s protocol (Thermo Fischer Scientific, Waltham, MA,
USA). Samples were then dried and reconstituted in water/acetonitrile/FA (15μL,
98/2/0.1, v/v/v), and aliquots (5μL) were injected onto a reverse-phase nanobore HPLC
column (AcuTech Scientific, C18, 1.8μm particle size, 360μm × 20cm, 150μm ID, San
Diego), equilibrated in same solvent, and eluted (500 nL/min) with an increasing organic
92

gradient(acetonitrile/water/FA, 98/2/0.1, v/v/v: min/% ; 0/0, 5/3, 18/7, 74/12, 144/24,
153/27, 162/40, 164/80, 174/80, 176/0, 180/0) using an Eksigent NanoLC-2D system
(Sciex, Framingham, MA, USA). The effluent from the column was directed to a
nanospray ionization source connected to a hybrid quadrupole-Orbitrap mass
spectrometer (Q Exactive Plus, Thermo Fisher Scientific, Waltham, MA, USA), acquiring
mass spectra in a data-dependent mode alternating between a full scan (350–1700 m/z,
automated gain control (AGC) target 3 × 10
6
, 50 ms maximum injection time, FWHM
resolution 70,000 at 200 m/z) and up to 15 MS/MS scans (quadrupole isolation of
charge states 2–7, isolation window 0.7 m/z) with previously optimized fragmentation
conditions (normalized collision energy of 32, dynamic exclusion of 30s, AGC target 1 ×
10
5
, 100ms maximum injection time, FWHM resolution 35,000 at 200 m/z)[237].
8.2.2 Proteomic Data Processing
Raw mass spectra data were processed using Proteome Discoverer (Version 2.4,
Thermo Scientific, Waltham, MA, USA) via a SEQUEST-HT search against the UniProt
mus musculus-reviewed protein database. Measurements of protein abundances were
then acquired and normalized to total protein amount. Decoy database searching was
utilized in order to identify high confidence tryptic peptides [FDR < 1%]. Median
abundance values for all biological replicates were used to generate abundance ratios
and perform differential analysis on each protein.
8.2.3 Ingenuity Pathway Analysis
Proteome discoverer results were exported into excel and formatted for upload into
ingenuity pathway. Data was uploaded utilizing uniport identification codes and
93

abundance ratios. Ingenuity pathway core analysis was then performed on the dataset
utilizing Qiagen IPA (QIAGEN Inc., https://digitalinsights.qiagen.com/IPA)[238].
Macrophage polarization was added to new pathway and analysis was overlayed
to determine trends.
8.3 Immunofluorescence staining
Immunofluorescence staining were performed as reported previously[184]. Briefly,
Formalin-Fixed Paraffin-Embedded (FFPE) tissue was baked and deparaffinized.
Antigen retrieval was done in a microwavable pressure cooker. After blocking with 10%
goat serum in PBS, slides were incubated at 4
o
C overnight with primary antibodies: anti-
mouse F4/80-, anti-mouse Clec4f (Biolegend), anti-mouse LIX (R&D systems), anti-
human CD68 (?), anti-human CXCL5 (R&D systems), anti-human Ki67-PE (Biolegend)
and then stained at room temperature for 1 hour with secondary antibodies: anti-rat IgG-
PE (Biolegend), anti-goat IgG-AlexaFluor488 (Biolegend). Images were taken using a
Zeiss fluorescent microscope.
8.4 Cell culture
Mouse hepatocytes were cultured in DMEM supplemented with 10% FBS, insulin and
epidermal growth factor (EGF).
HepG2 cells were cultured in DMEM supplemented with 10% FBS.
Macrophages (Raw264.7, peritoneal macrophages and liver macrophages) were
cultured in RPMI supplemented with 0.1% FBS for the secretome analysis.
94

For qPCR analysis of LPS induced CXCL5 expression, liver macrophages were
cultured in RPMI supplemented with 10% FBS.
8.5 Quantitative polymerase chain reaction (qPCR)
Quantitative polymerase chain reaction (qPCR) was performed as reported before[239].
Briefly, RNA was collected using Trizol reagent (Thermo Fisher). Reverse transcription
was performed using M-MLV reverse transcriptase (Promega). qPCR was performed
using PowerUp SYBR Green Master Mix (Thermo Fisher).
8.6 Extracellular flow cytometry
Flow cytometry was performed as described previously[184]. Liver non-parenchymal
cells were isolated (See Chapter 7.1) and stained with fluorescently labeled antibodies:
anti-mouse CD45-PE (Biolegend), anti-mouse/human CD11b-FITC (Biolegend), anti-
mouse F4/80-APC (Biolegend), anti-mouse Ly6G-PerCP (Biolegend), anti-mouse
CD64-BV421 (Biolegend), anti-mouse CD3-FITC (Biolegend), anti-mouse CD19-APC
(Biolegend), anti-mouse NK1.1-PE-Cy7 (Biolegend), anti-mouse Clec4f-AlexaFluor647
(Biolegend). Stained cells were analyzed using BD FACSVerse, and data were further
analyzed using FlowJo.
8.7 Modified Tricine-SDS-PAGE
Tricine-SDS-PAGE was performed according to a previous protocol[240]. We overlayed
a 4% gel (stacking gel) on top of the 10% gel (separating gel). Electrophoresis was
95

done at 30V until the sample has completely entered the stacking gel, followed by 50V
until the samples entered separating gel, then 80V until stopped.
In the regular western blot procedure, the blotting step is followed by the blocking step.
In this procedure for small chemokines, extra experimental procedures were added
between the blotting and the blocking step to prevent small proteins getting washed off
the membrane[241]. Additionally, BSA (bovine serum albumin) was used instead of milk
during the whole process, because milk reduces/blocks the detection.
After electrophoresis, the gel was blotted to PVDF membranes using a wet transfer
system. Transfer buffer used was 25 mM Tris-HCl at pH 8.3, 192 mM glycine, 20%
methanol. The blotted membrane was briefly washed in TBS-T (50 mM Tris-HCl at pH
7.4, 150 mM NaCl, 0.1% Tween-20) and submerged in blocking buffer (5% BSA in TBS-
T) for 5 min. After a 3-min washing step with PBS-T (phosphate buffered saline with
0.1% Tween-20), the membrane was incubated in 0.4% paraformaldehyde solution in
PBS-T for 15 min. The membrane was briefly washed 3 times with PBS-T. Antigen
retrieval was done by immersing the membrane in citrate retrieval buffer (10 mM citric
acid at pH 6.0, 1 mM EDTA, 0.05% Tween-20). and microwaved for 10 min at 600 W
after boiling (takes about 7mins at high power to reach boiling). Allow the retrieval
solution to cool to room temperature, the membrane was incubated with quenching
buffer (200 mM glycine in TPBS) for 10 min. Proceed to blocking with 5% BSA in TBS-T
and follow the regular western blot protocol. Primary antibody: anti-human CXCL5 (R&D
systems), secondary antibody: anti-goat IgG-HRP (R&D systems).
8.8 Animals
96

Liver-specific deletion of Pten (Pten
loxP/loxP
; Alb-Cre
+
, Pten null) were reported
previously[182]. Control animals are Pten
loxP/loxP
; Alb-Cre
-
. Experiments were conducted
according to IACUC guidelines of the University of Southern California.
8.9 Human liver samples
Patient samples were collected from multiple hospitals with diverse etiologies. All
patient information was removed, and all experiments were conducted according to IRB
guidelines of University of Southern California.

97

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Abstract (if available)

Abstract Inflammation is a hallmark of liver cancer development. It drives the tumorigenic cycle of liver injury and regeneration. Here, I studied the key chemokines involved in liver cancer progression through analysis of CXC and CC chemokine expressions in human hepatocellular carcinoma (HCC), and its further characterization in the Pten null mouse model. We found that CXCL5 was the only chemokine consistently upregulated in human HCC with different etiologies compared to healthy livers. Further bioinformatic analysis showed that the CXCL5 increase is closely associated with liver macrophages.
We hypothesized that CXCL5 expression was induced by pathogenic stimulations that are common to chronic liver diseases, and these stimulations induced CXCL5 expression in liver macrophages. To test that, we used the Pten null mouse model that recapitulates NAFLD-NASH-HCC progression. Concurrent increase of hepatic CXCL5 expression and macrophage population is observed during HCC development in Pten null mice. Intracellular flow cytometry and immunofluorescent staining demonstrated that Kupffer cells are the predominant CXCL5 high expressing cells in the liver. Mechanistically, chronic liver diseases and inflammation leads to increased intestinal permeability which elevates hepatic LPS concentration. We found that LPS stimulation leads to CXCL5 upregulation uniquely in liver macrophages, but not in peritoneal macrophages or Raw264.7 macrophages. Mass spectrometry confirmed that there is an increase of CXCL5 secretion in LPS treated vs non-treated liver macrophages. CXCL5 binding to CXCR2 promotes HCC tumor cells proliferation.
Together, we showed that CXCL5 expression is strongly associated with HCC. During chronic liver inflammation, liver-gut axis promotes HCC development through Kupffer cell-specific LPS-induced CXCL5 overexpression. Secreted CXCL5 drives HCC tumor growth. Further studies on LPS and Kupffer cell interactions might provide new drug targets to reduce HCC incidence in patients with chronic liver disease.

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Asset Metadata

Creator Tu, Taojian (author)

Core Title Pro-inflammatory Kupffer cells secrete CXCL5 to promote liver cancer

School School of Pharmacy

Degree Doctor of Philosophy

Degree Program Pharmaceutical Sciences

Degree Conferral Date 2022-08

Publication Date 01/27/2023

Defense Date 06/17/2022

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag cancer,chemokines,CXCL5,gut,Inflammation,Kupffer cells,liver,LPS,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Stiles, Bangyan (committee chair), Okamoto, Curtis (committee member), Xie, Jianming (committee member)

Creator Email taojiant@usc.edu,taojiantu@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC111375428

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Source 20220728-usctheses-batch-962 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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