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Methodology of exploring the role of SOX9 in the human HCC stem-like cells

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Methodology of exploring the role of SOX9 in the human HCC stem-like cells

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Methodology of exploring the role of SOX9
in the human HCC stem-like cells

by

Qi Tang

A Thesis Presented to the
FACULTY OF THE USC SCHOOL OF PHARMACY
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(PHARMACEUTICAL SCIENCE)

August 2021

Copyright 2021 Qi Tang
ii

Acknowledgements
First, I would like to express my deepest gratitude to my mentor, Dr. Bangyan L. Stiles, who has
been supporting me during my graduate studies. Her professional advice and continuous support
helped me grow into an individual with critical thinking and independent research capabilities. She
also provided me with a lot of resources and guidance to complete this research. The patience and
care I accepted help me learn deep knowledge for my studying and my life. I am very grateful for
the opportunities that could be a student in USC school of pharmacy. I would also like to thank Dr.
Jean Shih and Dr. Curtis T. Okamoto for their willingness to be members of my committee and
for providing insightful comments and suggestions for my thesis work.
I am very grateful for Taojian Tu, who is a PhD candidate in Dr. Stiles’ lab. He spent his time
telling me basic skills and inspiring me insight ideas when I first joined in the lab. I am also very
appreciated with Lina He who is a technician in Dr. Stiles’ lab that her abundance experience
offering me much advice through my experiments with patience. The sincere thanks give to all
members of our lab, especially Mario Alba, Jingyu Chen, Xinwen Zhang, Yijing Huang and
Xiaoteng Niu.
Last but not the least, I would like to thank my parents and my friends. Their selfless care and
support allow me to complete my studies and research well and enable me to pursue my dreams.

iii

Table of Contents
Acknowledgements ......................................................................................................................... ii
List of Tables ................................................................................................................................... v
List of Figures ............................................................................................................................... vi
Abstract ......................................................................................................................................... vii
Chapter 1: Introduction ................................................................................................................. 1
1.1 Liver cancer background ................................................................................................... 1
1.1.1 Liver cancer epidemiology ............................................................................................ 1
1.2 The Liver cancer stem-like cells (LCSCs) ........................................................................ 3
1.3 Sex-determining region Y-Box9 (SOX9) ........................................................................... 4
1.3.1 What is SOX9? .............................................................................................................. 4
1.3.2 The role of SOX9 in liver disease and HCC .................................................................. 5
Chapter 2: Knocking down SOX9 in attached HCC cells ............................................................ 7
2.1 Introduction ......................................................................................................................... 7
2.2 Results .................................................................................................................................. 9
2.2.1 Analysis HCC cell proliferation by Trypan Blue dye exclusion assay .......................... 9
2.2.2 Analysis HCC cell proliferation by MTT assay .......................................................... 12
2.3 Conclusion ......................................................................................................................... 14
Chapter 3: Knocking down SOX9 in stem-like HCC cells ......................................................... 15
3.1 Introduction ....................................................................................................................... 15
3.2 Results ................................................................................................................................ 15
3.2.1 Sphere forming before transfection ............................................................................. 15
3.2.2 Sphere forming after transfection ................................................................................ 21
3.2.3 Serial sphere forming assay ......................................................................................... 25
3.3 Conclusion ......................................................................................................................... 26
Chapter 4: Overall discussion and future perspective ................................................................ 30
Chapter 5: Methods and Materials .............................................................................................. 32
5.1 Attached HCC Cell Culture ............................................................................................. 32
5.3 Trypan Blue Exclusion Test ............................................................................................. 32
5.4 MTT Assay ........................................................................................................................ 33
5.5 Sphere Passage and Sphere Formation Assay................................................................ 33
5.7 Serial Sphere Forming ...................................................................................................... 34
5.8 RNA Isolation, Reverse Transcription, and RT-qPCR ................................................. 35
5.9 Protein Extract and Western Blot ................................................................................... 36
iv

5.10 Statistical Analysis .......................................................................................................... 37
References .................................................................................................................................... 38

v

List of Tables
Table 1 Primers used for Real-Time PCR .................................................................................... 36

vi

List of Figures
Figure 1 Methodology of knocking down SOX9 in attached HCC cells ....................................... 9
Figure 2 Downregulation of SOX9 in attached Huh7 cells. ......................................................... 10
Figure 3 Downregulation of SOX9 in attached Huh7 cells and analysis of cell proliferation by
the MTT assay............................................................................................................................... 13
Figure 4 Downregulation of SOX9 in stem-like Huh7 cells after sphere-forming (25000
cells/well seeding density). ........................................................................................................... 16
Figure 5 Downregulation of SOX9 in stem-like Huh7 cells after the sphere-forming (50000
cells/well seeding density). ........................................................................................................... 18
Figure 6 Downregulation of SOX9 in stem-like Huh7 cells after the sphere-forming (25000
cells/well seeding density). ........................................................................................................... 20
Figure 7 Downregulation of SOX9 in stem-like Huh7 cells after the sphere-forming (25000
cells/well seeding density). ........................................................................................................... 21
Figure 8 Methodology of knocking down SOX9 in spheres before sphere formation. ................ 23
Figure 9 Downregulation of SOX9 in stem-like Huh7 cells before the sphere-forming. ............. 24
Figure 10 The serial sphere formation assay after downregulation of SOX9 in Huh7 stem-like
cells. .............................................................................................................................................. 26
Figure 11 Flow chart of the optimal methodology for exploring the role of SOX9 in the stem-like
HCC cells ...................................................................................................................................... 27

vii

Abstract

Sex-determining region Y (Sry)-box9 (SOX9) is a transcriptional factor that plays a vital role in
the embryonic development of many tissues and organs. In the liver, SOX9 is known as an early
marker for biliary cells and may play a critical role in the development of liver cancer. In recent
years, SOX9 has received more attention in the field of liver research. SOX9 upregulation is
observed during liver cancer development promoted by chronic injury. Liver injury significantly
stimulates the expansion of tumor-initiating cells (TICs), also known as cancer stem-like cells
(CSCs) and is thought to promote tumorigenesis by inducing TIC/CSC transformation.

The interactions between CSCs and tumor microenvironment (TME) promotes non-CSCs trans-
differentiate into CSCs through providing anti-apoptosis, stemness-maintaining factors, and
matrix components and may influence resistance to therapeutics. Thus, it is critical to understand
the signals that lead to CSCs’ transformation from non-CSCs. The previous studies indicate that
Sox9 may plays an important function in regulating liver CSC stemness. This thesis aims to design
an optical methodology for exploring the role of SOX9 in the human Hepatocellular Carcinoma
(HCC) stem-like cells and highlights that SOX9 plays a vital role in the human liver cancer stem-
like cells (LCSCs) proliferation and HCC progression. Here, we explored the role of SOX9 in
CSC transformation by introducing siRNA targeting SOX9 into the Huh7 human HCC cell lines.
Our work shows that downregulation of SOX9 by siRNA did not significantly affect the cell
growth potential of Huh7 cells in cell proliferation assays. It did attenuate the ability of the Huh7
cells to form spheres in suspension culture, suggesting that SOX9 plays an important role in the
maintaining the stemness of CSCs. In addition, our result shows that knockdown of SOX9
inhibited the ability of CSC self-renewal in the serial sphere cultures. Together, our data
viii

demonstrated a role of SOX9 in CSC transformation and maintenance. Our study here suggests
that SOX9 might be an important LCSCs marker and serve as a potential therapeutic target for
HCC.

Keywords: HCC; SOX9; target therapy; CSCs; liver cancer stem-like cells; siRNA transfection

1

Chapter 1: Introduction
1.1 Liver cancer background
1.1.1 Liver cancer epidemiology
Liver cancer ranks as the sixth most common cancer and the third leading lethal malignant tumor
worldwide (1-3), with over 9 million new cases and 8 million deaths (3, 4), stressing the urgent
need to investigate the mechanism of liver tumors. Asia is the place of highest incidence of this
cancer worldwide, which make up of over 50% of the total cases, followed by Africa, Europe,
North America, Latin America, and the Caribbean (3). In both sexes, the incidence of liver cancer
is rising faster than any other cancer (1, 5). In the U.S., the incidence of liver cancer has more than
tripled since 1980. The mortality rate of this cancer in the United States more than doubled (1). In
most regions, the morbidity and mortality rates of men are 2 to 3 times higher than women (3).
The five-year relative survival rate of this cancer is only 18% (6).
Primary liver cancer includes hepatocellular carcinoma (HCC) accounting for about 75%-85% of
all liver cancers, intrahepatic cholangiocarcinoma (iCCA) accounting for 10%-15%, and the
presence of other rare types (3). The main potential risk factors for HCC progression have been
identified, such as hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, alcohol uptake,
aflatoxin B1 toxicity, and metabolic syndrome and diabetes patients with fatty liver (7). Risk
factors related to iCCA development contain biliary diseases, type II diabetes, and all of the risk
paraments leading to HCC (7). Although the cure rate of new and well-tolerated antiviral therapies
exceeds 90% and therefore has great potential to avoid most of the burden of HCV-related diseases
in the future, there are still many infected people who have not been diagnosed (1). Less than 10%
of new infections are reported, of which approximately 75% to 85% will develop into chronic
2

infections (1). Due to its aggressiveness and adverse consequences, liver cancer remains a major
global public health challenge.
1.1.2 Current therapies for hepatocellular carcinoma (HCC)
The significant complexity of liver cancer poses a challenge for advancing treatment choices for
this aggressive disease (4). Resection and replacement of liver by surgery are the remaining
potential therapies for HCC, although the success of surgery mostly depends on the early detection
of disease and the feasibility of liver transplantation. Only 5% to 15% of patients are suitable for
surgical resection, and most of them are early-stage patients (8).

For more advanced patients in liver cancer, the kinase inhibitor sorafenib is still the most accepted
choice (8). However, only less than a third of patients benefit from treatment, and the drug
resistance appeared within six months after the start of treatment. Long-term use of chemotherapy
drugs, including sorafenib, have other problems such as toxicity and/or drug inefficiency (8). In
recent years, the frontline drug levatinib and the second-line drug including regorafenib, cabotinib
and ramucirumab have been available for HCC patients. However, for unresectable iCCA or
combined HCC-iCCA, no first-line local treatment has been discovered. Compared with
conservative treatment, transarterial chemoembolization (TACE) can increase the 2-year survival
rate of patients with mid-stage HCC by 23% (8). Despite the promising remission rate and survival
in Phase I/II studies, nivolumab, an immune checkpoint inhibitor, was recently listed as a second-
line treatment for HCC (9), therapies for liver cancer patients are remain very limited. As a result,
exploring the initial origin of liver cancer and clarifying the carcinogenic signaling pathways that
3

drive the development of HCC, iCCA and combined HCC-iCCA is necessary to overcome the
obstacles of key therapeutic interventions for the treatment of this group of heterogeneous tumors.
1.2 The Liver cancer stem-like cells (LCSCs)
Liver cancer patients often experience tumor progression, relapse, and distant metastasis. A cell
subset with characteristics of stem cells, called CSCs, can contribute to tumor initiation and growth,
as well as the high rate of metastasis, recurrence, and therapeutic resistance (10-12). CSCs has
similar properties to stem cells such as self-renewal capacity and differentiation ability. CSCs are
also known as tumor-initiating cells (TICs) and were first confirmed by xenotransplantation of
acute myeloid leukemia (AML) cells injecting into SCID mice (13). This experiment showed that
the expression of specific CSCs markers like CD34
+
and

CD38
-
can promote the production of a
large number of colonies forming progenitor cells (10). This finding is proposing a new concept
of CSCs, in which heterogeneity and tumor grade are organized by a cell subset that have the
ability to form CSCs.

CSCs are attributed to possess drug resistance capacity, possibly resulting in tumor recurrence
after therapies. In addition to the capability of reconstituting original tumors, CSCs express high-
levels of drug efflux-related proteins and self-renewal-related genes (12, 14). CSCs also uses
various internal and external mechanisms to evade the multiple effects of drugs (10). They possess
chemical resistance mechanisms including DNA damaged repair pathway activation, and the
ability to undergo epithelial-to-mesenchymal transition (EMT) (10). These intrinsic properties
allow them to resist chemo- and radio-therapy induced cell death. The external chemical resistance
mechanism comprises a signaling pathway involved in EMT, hypoxia and abnormal angiogenesis
(15). In addition, CSCs can reduce cell proliferation when entering a dormant state (the G0 arrest),
4

which allows them to resist chemotherapy, leading to relapse later after chemotherapy has stopped.
In this regard, it may promote the transformation of non-CSCs into CSCs by providing anti-
apoptosis, stem cell maintenance factors and matrix components, thereby affecting the resistance
to treatments. Therefore, the study of how cancer stem cells improve the therapeutic resistance is
a key issue. (10).

The CSCs from HCC are called liver cancer stem cells (LCSCs). LCSCs have specific
characteristics, including the ability to initiate new tumors, chemical resistance, metastasis, and
relapse (10, 16). LCSCs have been shown to be enriched with several CSCs markers, such as CD13
(17), CD133 (18), EpCAM (19, 20), SOX9 (21), OV6 (22), CD44 (23), and CD90 (24). Some
CSC markers like SOX9 play critical roles in sustaining the self-renewal capacity of LCSCs
(11). Compared with the non-CSCs, other cells may be circulating in the body, to promote
metastasis and homing ability. In other words, LCSCs promote tumor development and metastasis
of primary cancer cells to form secondary tumors, resulting in the HCC recurrence (10, 25). In
recent years, more and more studies have focused on the identification of different surface markers
of HCC through cell sorting by fluorescence or magnetics, which can effectively eliminate LCSCs
and achieve the purpose of inhibiting tumor recurrence (10).
1.3 Sex-determining region Y-Box9 (SOX9)
1.3.1 What is SOX9?
Sex-determining region Y (Sry)-box9 (SOX9) is a transcriptional factor that plays a vital in the
embryonic development of many tissues and organs, including the heart, lung, pancreas and the
central nervous system (26). It keeps the target cell within an undifferentiated state during
development (27). In several tissue subtypes, dysregulation of SOX9 expression and high
5

expression of SOX9 leads to tumorigenesis and enhances the ability of cancer cells to metastasize.
(26)

1.3.2 The role of SOX9 in liver disease and HCC
In recent years, SOX9 has attracted more and more attention in the liver research field. In the
developing liver, SOX9 expression was first detected in the original duct structure. The structure
of these primitive ducts is asymmetrical, SOX9
+
bile duct cells are arranged on the portal vein side,
and SOX9
-
hepatoblasts are arranged on the parenchymal side. (28). As the duct structure matures,
the bile duct is completely positive for SOX9 and consists only of bile duct cells, showing radial
symmetry (28). Therefore, SOX9 is considered to be an early marker of liver bile duct cells.

When the chronic injury impairing cell proliferation in the liver, the SOX9
+
cells are responsible
for regenerating liver parenchyma. A previous study from the Stiles’ lab indicates that promoting
SOX9
+
cell activation and proliferation is an indispensable condition for the liver damage, leading
to the development of mixed-lineage liver tumors (29). Liver injury stimulates the expansion of
CSCs significantly.

More and more evidence shows that SOX9 is a liver progenitor cell marker, and that SOX9
expression is associated with CSCs phenotypes (11). In many human liver cancers, SOX9
overexpression has been reported, where high SOX9 expression promoted stem-like cell properties
and induced the CSC pool expansion, resulting in poor patient prognosis (21). Consistently, Notch-
induced suppression of the stemness characteristics of liver CSC leads to a decrease in SOX9
expression by inhibiting its transcription. This is consistent with previous reports that Notch1
6

signal directly regulates SOX9 expression in lung adenocarcinoma (30). Compared with adjacent
tissues, the expression of SOX9 in human HCC samples is increased, and these high SOX9 levels
are related to poor survival (21, 31). Therefore, it is suggested that high expression of SOX9
induces HCC progression.

The SOX9 overexpression in HCC samples indicate that the tumor may originate from the
expansion of SOX9
+
progenitor cells. SOX9 plays a critical role in regulating the stem cell
characteristics in LCSCs, because the decrease of SOX9 expression inhibits LCSCs proliferation
and self-renewal at the same time. As sorafenib remains the most accepted choice for advanced-
stage HCC, a study found that sorafenib therapy expanded the SOX9
+
cells population in HCC cell
lines. SOX9 overexpression in HCC increased drug resistance in vitro and vivo, whereas
downregulation of SOX9 led to inhibition of drug resistance (32). Another study also found that
SOX9 overexpression induces tumor development and self-renewal in non-CSC subpopulations
(21). These results indicate that Sox9 plays a vital role in LCSCs, and this approach can be used
for therapeutic targeting of hepatic CSC.

In this project we hypothesize that SOX9 may play a vital role in transforming liver cancer stem
cells. When SOX9 expression is downregulated, the growth of attached HCC cell lines and LCSCs
will be inhibited. We set out two aims to test this hypothesis. Aim 1 will determine the effect of
knocking down SOX9 on the growth of HCC cells using siRNA to inhibit the expression of SOX9.
To address the role of SOX9 on CSC transformation, aim 2 will determine whether knocking down
SOX9 in HCC can inhibit the sphere forming ability of HCC stem-like cells.

7

Chapter 2: Knocking down SOX9 in attached HCC cells
2.1 Introduction
RNA interference (RNAi) is a natural process through which expression of a targeted gene can be
specific and selective inhibited (33). Small interfering RNA (siRNA) is a widely used methods of
mediating the RNAi effect to knock down gene expression in different types of cells. SiRNA is
a 20-27 nucleotide double stranded RNA (dsRNA) molecule often referred to as “silencing RNA”
(34). Each functional siRNA has a 5' phosphate group and a 3' hydroxyl group. This structure is
contributed from Dicer which is an RNAse III nuclease that can process long dsRNAs and pre-
microRNA into active siRNAs (35, 36). Various transfection methods can be used to introduce
siRNA into cells to specifically knockdown the targeted gene. Once the siRNA enters the cell, it
will combine with other proteins to form an RNA-induced silencing complex (RISC) (37). After
the siRNA binding to the RISC complex, the siRNA will unwound to form a single strand siRNA.
Single strand siRNA can now scan and locate the complementary mRNA and bind to its target
mRNA, thereby inducing mRNA cleavage. Finally, the target mRNA is cleaved by the cell and
recognized as abnormal, which leads to degradation of the mRNA and makes it impossible to
translate the mRNA into amino acids and then into protein (36, 37). Thus, based on sequence
complementarity with an appropriately tailored siRNA, substantially any known gene sequences
can be targeted. This makes siRNAs a vital tool for the gene engineering and verification of drug
targets in the post-genomics field. (36)

Intracellular delivery of siRNA remains a challenge. Transfection is one of most used method for
siRNA delivery which is usually done by liposomes, polymer nanoparticles, and lipid coupling
8

(38, 39). Liposomes are small capsules made of polymers similar to those that make up the cellular
membrane. When formulated with nucleic acids, lipid transfection reagents engage with the cell
membrane and release their cargo into the cells. Lipid based transfection reagents utilize the semi-
permeable feature of cell membranes to transport nucleic acid molecules to the interior of a cell.
The transfection complexes overcome the cell membrane by endocytosis or fusion with the plasma
membrane (38). The advantage of this method includes that it is widely used in most types of cells,
its high efficiency, its reproducibility, and it’s commercially available. Gene silencing by siRNA
in mammalian cells provides a powerful tool for biological study to identify specific gene functions
and expression pathways. The siRNA-induced gene silencing has the therapeutic potential to
improve the treatment of many genetic diseases like cancer and Alzheimer.

To understand the role of SOX9 in liver cancer, we used the Lipofectamine
@
RNAiMAX
transfection reagent (40) purchased from Thermo Fisher to deliver the siRNA to adherent Huh7
cells. Briefly, 0.5-2×10
5
cells/well Huh7 cells were seeded in the 10% FBS supplied DMEM
(Dulbecco’s Modified Eagle’s Medium) in the 24-well plates and allowed to adhere overnight.
SiRNA against SOX9 or scrambled siRNA, as negative controls, were then introduced to the cells
by mixing with Lipofectamine reagent. The cells were incubated with the siRNA-lipid complex
for 24, 48 and 72 h before different cell viability/growth assays were performed. Both the trypan
blue dye exclusion assay and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide
(MTT) assay were performed to determine the effect of knocking down SOX9 on HCC cell
proliferation. (Fig. 1)

9

Figure 1 Methodology of knocking down SOX9 in attached HCC cells
2.2 Results
2.2.1 Analysis HCC cell proliferation by Trypan Blue dye exclusion assay
One way for evaluating cell viability was Trypan Blue dye exclusion assay. Although it was
discovered early on, it is still widely used today. It is based on the principle that with complete and
intact membranes of viable cells, it is possible to extrude Trypan Blue dye and efflux it outside of
the cell. Dead cells absorb Trypan Blue and therefore appear blue owing to their membranes can
no longer control the uptake of macromolecules. The cells need to be in a single cell suspension,
and then a certain volume of cell suspension are visualized and counted under a microscope by
using the hemocytometer or using the automatic counting machines instead (41).
10

Figure 2 Downregulation of SOX9 in attached Huh7 cells.
(A) Cell counting number (cells per well) for SOX9 and the negative control group after 24h,
48h,72h of siRNA transfection. No significant difference was observed between the two groups
(p>0.05). (B) Western blot result shows that the SOX9 siRNA group has a slightly lower SOX9
protein expression level.

For this study, 1.07×10
5
cells/well in a 24-well plate were chosen as our seeding density, and the
Huh7 cells grew overnight. The siRNA-lipid complex was then added to the attached cells. The
Trypan blue dye exclusion assay was carried out to test cell viability after 24-72 hours of
transfection for the SOX9 siRNA group and the negative control (NC) group respectively. After
trypsinization and centrifugation, the cell pellet was resuspended in 5mL serum-free complete
medium. And then, the 0.4% Trypan Blue reagent and the single cell suspension were mixed in a
ratio of 1:1 and a drop of the Trypan Blue/cell mixture was added to a hemocytometer (42). The
viable cells and blue cells were counted separately in the hemocytometer under the
microscope. The number of viable cells were scored as follows:
𝑣𝑖𝑎𝑏𝑙𝑒 𝑐𝑒𝑙𝑙𝑠 𝑛𝑢𝑚𝑏𝑒𝑟 (𝑐𝑒𝑙𝑙𝑠 𝑝𝑒𝑟 𝑤𝑒𝑙𝑙 )
= 𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑖𝑛𝑔 𝑣𝑖𝑎𝑏𝑙𝑒 𝑐𝑒𝑙𝑙𝑠 ÷ 4 × 2(𝑑𝑖𝑙𝑢𝑡𝑒 𝑡𝑖𝑚𝑒𝑠 ) ÷ 0.1𝜇𝐿

11

There were more liver cancer cells growth for the SOX9 siRNA group before 48 h transfection
(Figure 2A). After 48 h transfection, Huh7 was overgrown and many cells died in the siSOX9
group while Huh7 in the control group were still growing, which maybe meant that the seeding
density might be higher than the plate capacity and needed to be reduced in the future. Also, a t-
test had been carried out to validate that there was no significant difference between siRNA for
SOX9 and the control group, due to the huge standard deviation (p>0.05) of the measurements,
indicating that this cell counting result is not convinced. Protein samples have been collected after
counting and western blotting has been done to confirm that SOX9 has been knocked out in the
Huh7 cell line (Figure 2B).

The reason why the Trypan Blue dye exclusion is remain widely used is that it is a simple and
rapid technique. But its problem is that the cell vitality is indirectly determined by the integrity of
the cell membrane (42). Therefore, based on the ability to grow or function, cell viability may be
impaired, even if its membrane integrity is temporarily maintained (42). Conversely, the integrity
of the cell membrane may be abnormal, although the cell may be able to repair itself and survive
completely. Another potential problem is that the described technique is more likely to cause errors
due to the subjectivity of the operator (42). This situation becomes more severe when some cells
congregate together (> 4 cells) and do not separate into a single cell. More peptides should be done,
or we can use the trypsin-EDTA second time and incubate for 2 minutes at RT to break the cell
congregations.

12

2.2.2 Analysis HCC cell proliferation by MTT assay
Indicator dyes that have changes in physical properties because of biochemical events limited to
living cells have been shown to be useful as cell viability markers (43). Among cell proliferation
assays that rely on living cells to convert substrates into chromogenic products, the MTT assay is
still among one of the most versatile assays. The MTT assay involves the reaction of mitochondrial
reductase to convert the water-soluble yellow dye MTT to the purple formazan crystal. Formazan
is then solubilized by DMSO and mixed well by shaker, and then the concentration should be
determined by optical density at 570 nm in a microplate spectrophotometer (44).

Instead of a standard 96-well plate, we seeded the Huh7 cell in the 24-well plate to make sure there
was enough cell lysates for western blotting. Also, we reduced the seeding density to 7.4×10
4

cells/well to avoid cell contact inhibition after 48h growth. The MTT assay was carried out to test
cell viability after 24h, 48h and 72h post-transfection for the two different groups. The results
show that cell viability is higher in the siRNA for SOX9 group than in the control group, and there
is a statistically significant difference between the two groups at all time points (Figure 3A). Cells
for a protein sample collection have been grown at the same time, and a western blot has been
done to confirm that SOX9 has been knocked down in the Huh7 cell line (Figure 3B).

13

Figure 3 Downregulation of SOX9 in attached Huh7 cells and analysis of cell proliferation by the
MTT assay.
(A) The MTT assay results show that the OD value comparison at 570 nm for SOX9 and the
negative control group after 24h, 48h,72h siRNA post-transfection. A significant difference was
observed between the two groups. (* P<0.05, ** P<0.01) (B) Western blot result showing that the
SOX9 siRNA group has a lower SOX9 protein expression level.

The MTT assay is a colorimetric reaction that can easily be performed in the attached single cell
layer in the plates. Cell concentration was determined to be in the range of correlation between the
optical density and the number of viable cells (45). The MTT assay is advantageous because it’s
easy and rapid performance, repeatability of the results and observed similar results in both
vitro and vivo tests (46).

However, it must be considered that the reaction to reduce MTT to MTT-formazan is catalyzed by
mitochondrial succinate dehydrogenase, because this assay depends on mitochondrial respiration
and is used indirectly to measure the cellular energy capacity (45). The decrease in the D-glucose,
NADH or NADPH in the medium may result in a reduce in the production of MTT-formazan. In
cells undergoing apoptosis, since mitochondria may remain intact there may be some reduction in
the early stages of production of MTT. Drug action may also cause changes in mitochondrial
14

activity, thereby affecting the results. The original analysis was modified to improve the uniformity
of dissolved formazan and replaced other tetrazole-based compounds (46).
2.3 Conclusion
All of the above results indicate that knocking out SOX9 in liver cancer cell lines cannot inhibit
the growth of liver cancer cells, which is inconsistent with my hypothesis. However, based on the
disadvantages and problems about the Trypan Blue dye exclusion assay and the MTT assay, we
cannot make a conclusion that decreasing SOX9 expression upregulates the proliferation of HCC
cells. Some experimental parameters should be improved, like seeding density, cell growth time,
times of sample repetition, and times of trial. More experiments should be carried out to determine
the potential relationship between SOX9 expression level and HCC cell proliferation.

15

Chapter 3: Knocking down SOX9 in stem-like HCC cells
3.1 Introduction
As stated, stem-like cells seem to play a vital role in cancer progression. The CSCs may influence
TME, and induce resistance to therapeutics by transforming non-CSCs into CSCs by providing
anti-apoptosis, stemness-maintaining factors, and matrix components. As a result, exploring the
relationship between SOX9 and CSCs is critical (10). To address the role of SOX9 in CSC
transformation, we next evaluated CSC proliferation after knocking down SOX9 in the HCC cell
lines to determine the importance of SOX9 in liver tumorigenesis. Enrichment of CSC
subpopulations from HCC cell lines using the sphere formation assay to assess CSC traits in vitro
(2, 11, 47).

For the sphere-forming assay, Huh7 cells were seeded at 2-5 ×10
4
cells/well, in single cell
suspension, in ultra-low attachment 24-well plates. Usually, the sphere will start to form after 24h
growth under certain seeding density. In sphere formation assays, each sphere is formed from a
single tumor cell with CSC ability, i.e., forming the “tumor” (spheres in this case). Thus, the
number of the spheres indicated how many cells possess the CSC ability in the culture. The sphere
formation efficiency of a culture (number of spheres divided by the number of seeded cells x 100)
is used as a proxy for the self-renewal ability of that culture (48).
3.2 Results
3.2.1 Sphere forming before transfection
Due to the short acting property of siRNA, Huh7 cells were allowed to initiate sphere forming for
24 hours before siRNA-lipid complex is introduced. This protocol allows us to evaluate sphere
16

numbers when the siRNA is still likely active. The same process of siRNA transfection for SOX9
and its negative control were used to introduce the siRNA transfection to spheres of the attached
HCC cell lines.
3.2.1.1 Confirm the seeding density in 24-well low attachment plate

Figure 4 Downregulation of SOX9 in stem-like Huh7 cells after sphere-forming (25000 cells/well
seeding density).
(A) Sphere images for SOX9 and NC siRNA group under the microscope after 24 h, 48 h, 72 h
post-transfection. (B) Sphere proliferation assay shows knocking down SOX9 downregulates the
proliferation of spheres. A significant difference was observed between the two groups. (* means
P value < 0.05) (C) Western blot result shows SOX9 has been knocked down in SOX9 siRNA
group.

17

As the recommended seeding density for siRNA transfection is 2.5-5×10
4
cells/well and the
recommended seeding density for sphere formation assay is 1000-50000 cells/well in the 24-well
plate, about 25000 cells/well Huh7 cells were used for the initial sphere formation assay. After
spheres start forming (about 24 h after cell seeding), the spheres were incubated with the siRNA-
lipid complex as the same process in the attached Huh7 cells. Immunoblotting shows that the
protein expression of SOX9 is lower in the siSOX9 culture than the control culture, confirming
knock down of SOX9 in Huh7 cells after 24 h post-transfection (Fig. 4C). We then quantified the
sphere numbers and imaged the spheres at 24 h, 48 h, and 72 h after transfection (Fig. 4A). The
number of spheres is significantly lower in the siSOX9 cultures vs. controls at all time points,
suggesting that Sox9 knockdown significantly reduced sphere forming efficiency (Fig. 4B). These
findings suggest that the overexpression SOX9 in liver CSCs support self-renewal and
tumorigenicity.

Even though the SuperSignal
@
West Femto Maximum Sensitivity Substrate (49) has been used for
western blot analysis to enhance the detection sensitivity for low-concentration protein samples,
only the protein sample collected after 24 h can be used for SOX9 protein detection. We were not
able to collect enough protein to perform analysis of SOX9 from the 48 and 72 h samples. This is
likely due to samples for 24 h were collected from a larger culture and less wells of cells have been
seeded at the later time point. A 50000 cells/well cell density will be used at the beginning of the
sphere-forming assay for future assays.
Since the seeding density would be increased, Huh7 would take less time to form spheres than
before. Thus, the siRNA transfection was implemented after 12 h cell growth, and sphere counting
and protein extraction should be carried out after 12 h and 24 h post-transfection. Under these
18

conditions, the sphere forming assay shows knocking out SOX9 decreases the number of spheres
in both 12 h and 24 h transfection (Fig. 5B). And the western blot result confirmed that SOX9 has
been knocked down in the SOX9 siRNA group (Fig. 5C). However, we can see that from Fig. 5A
that there are some cell aggregates together exceeding the ideal size which may lead to unexpected
variation when sphere counting. Thus, 25000 cells/well appears to be an ideal seeding density for
Huh7 cells for sphere forming assay. A plate with larger wells (e.g., a 6-well plate) may need to
be used for more accurate results and achieve enough protein samples that can be used to detect
knockdown events.

Figure 5 Downregulation of SOX9 in stem-like Huh7 cells after the sphere-forming (50000
cells/well seeding density).
(A) The sphere images for SOX9 and NC siRNA-treated groups after 12 h and 24 h transfection.
(B) The sphere formation assay shows knocking down SOX9 downregulates the proliferation of
spheres. A significant difference was observed between the two groups. (* means P value < 0.05)
(C) Western blot result shows SOX9 has been knocked down in the SOX9 siRNA group.
19

To further confirm the conclusion that 25000 cells/well seeding density is suitable for our
experiment, a similar transfection assay has been carried out after HCC stem-like cells formation.
We can see from both Fig. 6A and Fig. 6B that there are more spheres formed in the negative
control group before 12 h and the sphere population reversed after 24 h siRNA post-transfection
of the spheres. The sphere number tends to be equal around 24-hour siRNA transformation, and
then there are more spheres formed in the SOX9 siRNA group vs. controls. Those data indicate
that the SOX9 siRNA can only exert its transfection effect within 24 hours, which is inconsistent
with the manufacturer’s manual and previous experimental results (Fig.4). However, we cannot
get a convincing immunoblotting result that there is no SOX9 band can be saw on the membrane,
which shows that SOX9 downregulation in cells cannot be validated (Fig. 6C).

20

Figure 6 Downregulation of SOX9 in stem-like Huh7 cells after the sphere-forming (25000
cells/well seeding density).
(A) The sphere images for SOX9 and NC siRNA-treated groups after 12 h, 24 h and 48 h post-
transfection. (B) The sphere formation assay shows knocking down SOX9 downregulates the
proliferation of spheres before 12 h. A significant difference was observed between the two groups
except 24 h after transfection. (* means P value < 0.05) (C) Western blot result shows no SOX9
has been detected in both groups.

From the previous data, we assumed that the SOX9 siRNA only works for a certain shorter period
during the sphere formation. In this case, we performed the sphere counting assays at serval shorter
time points, including 4 h, 7 h, 12 h and 24 h after siRNA transfection and made sure that we can
get enough protein samples for immunoblotting. Figs. 7A and 7B both show that more spheres
were formed in the control group before 12 h and the sphere numbers tend to be equal after 24 h
siRNA transformation. The western blot result shows the SOX9 protein expression level is slightly
21

lower in the SOX9 knockdown group or basically the same in the two different groups (Fig. 7C),
indicating that siRNA transfection performed in HCC stem-like cells may lead to low transfection
efficacy and abnormal sphere formation.

Figure 7 Downregulation of SOX9 in stem-like Huh7 cells after the sphere-forming (25000
cells/well seeding density).
(A) the sphere images for SOX9 and NC siRNA groups after 4 h, 7 h, 12 h and 24 h post-
transfection. (B) The sphere formation assay shows knocking down SOX9 downregulates the
proliferation of spheres before 12 h. A significant difference was observed between the two groups.
(* means P value < 0.05, *** means P value < 0.001) (C) Western blot result shows a lower SOX9
expression level in SOX9 siRNA and negative control groups before 12h post-transfection and a
opposite result at 24 h post-transfection.

3.2.2 Sphere forming after transfection
The western blotting result from the initial experiment (Fig. 7) shows that the siRNA transfection
efficiency is not high as SOX9 levels are only moderately lower in siSox9 group vs. controls. We
hypothesized that the siRNA-lipid complex may only target the surface of the spheres when
introduced after the initiation of spheres. This will leave the majority of the cells inside the sphere
22

with SOX9 intact. To improve the transfection efficacy, we considered performing the siRNA
transfection before the sphere-forming that may increase the contact surface and SOX9 can be
knocked out in most cells.

To introduce siRNA to Huh7 cells before sphere formation started, Huh7 cells were seeded at
30%-40% confluent in two 100 mm culture plates on the day 0 and allowed to adhere overnight.
The siRNA-lipid complex was then introduced following the manufacturer's manual, respectively,
for SOX9 and negative control groups. Cells were then detached with trypsin-EDTA after a 24-
hour culturing and seeded as single cell suspension in the sphere culture medium, Dulbecco's
Modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F12), in the 24-well ultra-low attachment
plate at 25000 cells/well. Sphere counting and RNA isolation for real-time quantitative PCR (RT-
qPCR) are carried out after the spheres are formed. (Fig. 8)

23

Figure 8 Methodology of knocking down SOX9 in spheres before sphere formation.

Spheres were imaged under an optical microscope for the two groups after 20 h, 40 h and 72 h
after sphere-forming (Fig. 9A). Counting of sphere numbers showed that knocking out SOX9
decreased the numbers of spheres (Fig. 9B). The RT-qPCR result shows SOX9 RNA expression
level is lower than 50% in SOX9 siRNA group after 72 h sphere-forming (Fig. 9C), validating that
SOX9 has been drastically knocked down in the siSOX9 group.

However, although we observed more spheres in the control group than the siSOX9 group in all
time points, only sphere formation at 72 h after sphere-forming shows that downregulation of
SOX9 has a significant effect on inhibiting liver cancer stem-like cell growth. This result may be
24

due to the operation error caused by operator subjectivity when sphere counting and cell counting
before seeding cells, the initial cells in the siSOX9 group may be slightly more than the control
group. Or this situation just indicates that it takes some time for SOX9 to promote self-renewal
capacity of HCC cells. A longer time point of sphere growth should be observed, or a serial sphere
formation should be carried out to validate this hypothesis.

Figure 9 Downregulation of SOX9 in stem-like Huh7 cells before the sphere-forming.
(A) The sphere images for SOX9 and NC siRNA group after 20h, 40h, 72h post-transfection. (B)
The sphere formation assay shows knocking down SOX9 downregulates the proliferation of
spheres. A significant difference was observed between the two groups after 72 h sphere-forming
(* means P value < 0.05). (C) RT-qPCR result shows SOX9 RNA expression level is significantly
lower in the SOX9 siRNA group after 72 h sphere-forming (** means P value < 0.01).

25

3.2.3 Serial sphere forming assay
Based on the two independent approaches, our results indicate that downregulation of SOX9
decreases the stem forming ability of liver cancer cells. The spheres formed are expected to be
enriched for CSCs, and cells within the spheres are expected to have better sphere forming ability.
To further evaluate the self-renewal capacity of LCSCs and explore whether the rate of spheroid
formation increases with time, we observed sphere-forming for three consecutive generations
(Figure 10A). Sphere formation culture was performed as described previously. The single cells
suspension was seeded at 25000 cells/well in the ultra-low attachment plates to form primary
spheres. Primary spheres were centrifuged and disrupted with trypsin-EDTA and pipette to break
into single cells after 3-day growth. And then, seed single cells suspension derived from primary
spheres at 25000 cells/ well for secondary spheres, then seed 25000 cells/well single cells derived
from secondary spheres to form tertiary spheres (11). Sphere counting assays were performed after
72 h of sphere-forming. Results showed that there are obviously less spheres formed in the SOX9
siRNA group vs. control group (Figure 10B), illustrating the potential role of SOX9 in promoting
LCSCs.

Results also showed increases of sphere formation number in the control group after every passage
(Figure 10B), showing that the sphere-forming percentages were enlarged during serial passage.
Fig. 10B shows that the difference of sphere number between the SOX9 knocking down group and
the negative control group. This difference becomes larger with the serial sphere-forming,
indicating that SOX9 can enrich the population of CSCs and promote the self-renewal capacity of
the CSCs. This continuous sphere formation assays confirmed that compared with control cells,
downregulation of the SOX9 in cells decreased the self-renewal capacities.
26

Figure 10 The serial sphere formation assay after downregulation of SOX9 in Huh7 stem-like cells.
(A) The sphere images for the SOX9 and NC siRNA group after 1
st
, 2
nd
and 3
rd
sphere-forming
assay. (B) The sphere formationn assay shows knocking down SOX9 downregulates the
proliferation of spheres. The difference between the two groups becomes larger when more serial
spheres were formed. A significant difference was observed between the two groups. (* means P
value < 0.05, *** means P value < 0.001)

3.3 Conclusion
Downregulation of SOX9 in HCC stem-like cells and serial sphere formation assay both validate
that SOX9 may promote the self-renewal capacity and play an important role in the LCSCs. We
varied different conditions for the sphere formation assay to evaluate the stemness properties of
SOX9. These parameters include the cell seeding density at the beginning, the sequence of steps
in the knockdown vs. sphere formation and the time of sphere-forming. Figure 11 summarizes the
conditions and provides an optimal methodology for exploring the role of SOX9 in sphere HCC
cells. Additional experiments need to be performed following this protocol to confirm the role of
SOX9 in LCSC.

27

Figure 11 Flow chart of the optimal methodology for exploring the role of SOX9 in the stem-like
HCC cells
28

The current protocol in this method utilizes siRNA to knockdown SOX9. Although the simplicity
and transient nature of siRNA manufacturing is very suitable for the treatment of certain diseases,
a major drawback of siRNA-mediated RNAi is that the target inhibition time is short, usually
lasting less than 72 hours in cell culture. Even though this may be sufficient for many applications,
this may have led to the subtle effect observed for sphere formation due to the duration needed for
cells to form spheres. A potential solution for this problem is the use of short hairpin RNA
(shRNA). After the first time application of synthetic siRNAs in cells, the plasmid that can mediate
short RNA molecules into the RNAi pathway were immediately investigated (50). These
molecules, called shRNA, can automatically form hairpin structures, which are identified and
processed by the RNAi mechanism to form active siRNA. It can be clearly seen from early
experiments that shRNA maintains the high-efficiency properties of its synthetic siRNA
counterparts, as validated by effective reporter gene and endogenous gene knockdown (51, 52).
The antibiotic selection markers along with shRNA expression vectors can be integrated to achieve
long-term stability of protein knockdown (50). Using the endogenous processing mechanisms, the
optimized shRNA constructs can also use low copy numbers to achieve high and sustainable
effects, thereby reducing off-target effects (33).

In this way, designing a certain vector to transfer the shRNA into HCC cells to provide a high
effective and stable method to knock down SOX9 may become necessary in the future research
plan.

For assay development, this sphere-forming method is still producing highly variable
results. Human subjectivity as an issue was discussed earlier with trypan blue exclusion assay. A
29

second trypsin-EDTA step to further break the cell congregations can help to reduce the counting
error. An automatic cell counter machine could also be used instead of manual counting by
hemocytometer which can contribute to a more accuracy cell counting result. Another human
subjectivity issue is the size of the spheres. It is difficult to determine that if the spheres are big
enough to count. An added step of using a cell strainer (50 µm) to filter all spheres under standard
size to avoid the variation in cognition of the sphere size. The result of sphere counting could be
more accurate if a cell strainer can be used.
30

Chapter 4: Overall discussion and future perspective
The overexpression of SOX9 in HCC cell samples might reflect that the tumor originated from the
expansion of SOX9
+
stem cells/ TICs. Some studies reported that a Hippo co-activator YAP1 can,
giving stem-like cell characteristics to esophageal cancer cells (53, 54). YAP1 also cooperates with
Slug to determine the status of mammary stem cell (55). CD73 can also upregulate SOX9
expression to maintain CSC properties as a CSC marker (2).

In HCC, exploring protein and RNA expression of more CSC makers after knocking down SOX9
in the HCC cells suggest that SOX9 is important for the HCC stemness-associated phenotype
maintenance. The mRNA expression of serval different CSC markers was reduced after SOX9
downregulation in the HCC cells, including Nanog, Oct4, EpCAM, and c-Myc, while the
expression of mature liver cell markers like albumin and cytokeratin 8 was increased (2, 11). Here,
we validated that SOX9 expression regulates the self-renewal ability of LCSCs, suggesting that
SOX9 may be necessary for maintenance of liver stem-like cell properties and increased the
population of the CSCs, leading to poor prognosis in HCC patients.

To further investigate how CSCs contribute to the self-renewal capacity and tumor initiation, the
cell division type should be studied. Cell division can ensure the self-renewal ability in the process
of cell proliferation involved in the growth of mammalian stem cells, including asymmetric cell
division (ASD) and symmetric cell division (SCD). ASD produces one stem cell and one
differentiated cell to sustain the number of stem cells and tissue homeostasis, while SCD produces
two stem cells to enlarge the population of stem cell for tissue regeneration. A transformation in
division types to support SCD, leading to an exponential growth of CSCs in a variety of tumor
31

types. A previous study showed that the mechanism of increasing the symmetrical split is a
sufficient explanation for the expansion of the CSC pool (56). However, it is not clear how CSCs
use SCD vs. ASD to regulate expansion and support liver tumor. The role of SOX9 in symmetric
and asymmetric cell division needs to be further explored.

Consistently, our results show that knocking down the expression of SOX9 inhibits the
proliferation and self-renewal ability of LCSC, SOX9 plays a vital role in regulating the
characteristics of liver stem-like cells. These results indicate that SOX9 plays a key role in human
HCC stem-like cells and might be a potential therapeutic target for HCC.

32

Chapter 5: Methods and Materials
5.1 Attached HCC Cell Culture
Huh7 cells (Human HCC cell line) was cultured in DMEM (Corning Inc., Corning, NY, USA)
containing 10% Fetal Bovine Serum (VWR International, Radnor, PA, USA) in the attached cell
culture dishes/ plates (Corning Inc., Corning, NY, USA). All hepatocytes grown in a humidified
37°C incubator with 5% CO2 supplied.
5.2 SiRNA Transfection
After cells were seeded onto dishes/ plates, SOX9 siRNAs and control siRNAs were delivered into
cells respectively by using Lipofectamine RNAiMAX transfection reagent (Thermo Fisher
Scientific, Waltham, MA, USA) according to the manufacturer’s instruction. Silencer
®
Select
siRNA against SOX9 and Silencer
®
Select negative control siRNA were purchased from Thermo
Fisher Scientific. The western blot was required to validate the transfection efficacy.
5.3 Trypan Blue Exclusion Test
A single cell suspension was mixed with 0.4% Trypan Blue solution (Thermo Fisher Scientific,
Waltham, MA, USA) (1:1) and then visualized the cell under the microscope to determine whether
cells absorb or exclude dye and counted in the hemocytometer. The viable cells will have a clear
cytoplasm, while the cytoplasm of dead cells will be stained blue. The number of viable cells were
scored as follows:
𝑣𝑖𝑎𝑏𝑙𝑒 𝑐𝑒𝑙𝑙𝑠 𝑛𝑢𝑚𝑏𝑒𝑟 (𝑐𝑒𝑙𝑙𝑠 𝑝𝑒𝑟 𝑤𝑒𝑙𝑙 )
= 𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑖𝑛𝑔 𝑣𝑖𝑎𝑏𝑙𝑒 𝑐𝑒𝑙𝑙𝑠 ÷ 4 × 2(𝑑𝑖𝑙𝑢𝑡𝑒 𝑡𝑖𝑚𝑒𝑠 ) ÷ 0.1𝜇𝐿
33

5.4 MTT Assay
After removing culture medium, 550 µL of the complex of 12 mM MTT (Thermo Fisher Scientific,
Waltham, MA) stock solution and DMEM medium without phenol red were added to each well.
A group of negative control of 550 µL of the MTT medium complex should be added to the empty
wells. After incubating the plate in the 37°C incubator for 3 hours, discarding all medium from the
wells. And then, 500 µL DMSO (Sigma-Aldrich, St Louis, MO) was added to each well to
solubilize the purple formazan and the plates were incubated at 37°C for 10 min to dissolve the
formazan completely. Each sample was remixed and the absorbance at 570 nm was read in the
Bio-Rad Benchmark Plus Microplate Spectrophotometer (Bio-Rad, Irvine, CA).
5.5 Sphere Passage and Sphere Formation Assay
The single cell suspension was obtained from the attached HCC cells by using trypsin-EDTA.
25000-10000 cells/well were seeded to the ultra-low attachment 24-well plate (Corning Inc.,
Corning, NY) in the Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 DMEM/F12
medium (Thermo Fisher Scientific, Waltham, MA) to form spheres. The spheres were collected
by centrifuge under 100 - 200 x g for 5 minutes, then broke the spheres with trypsin-EDTA and
pipette was used to disrupt mechanically. The cells were then centrifuged to remove the trypsin-
EDTA and add trypsin-EDTA second time to form single cells. After centrifuged, re-suspended
the single cells in DMEM/F12 medium and seed them to the ultra-low attachment 24-well plate at
25000 cells/well (500 μl) to re-form spheres. The spheres should be passed every 5-8 days to avoid
the spheres grow than 100 μm diameter and form a dark core. All hepatocytes grown in a
humidified 37°C incubator with 5% CO2 supplied.

34

5.6 Sphere Image and Counting
The spheres were observed under an optical microscope and imaged by Canon PowerShot A620
digital camera under 4× optical zoom in.

The spheres were harvested from one well of a 24-well plate and transferred to a 2mL tube. The
well was rinsed with 500 𝜇 L of DMEM/F12 and the rinsing solution was combined with the
collected suspension. Centrifuged the suspension at low speed, approximately 100 - 200 x g for 5
minutes. The supernatant was then discarded carefully, ensuring not to disturb the sphere pellet.
The spheres were resuspended to a final volume of 125 μL with DMEM/F-12. Using a fine-tipped
marker, one well of a 96-well plate was divided into quadrants by drawing a plus sign on the
underside of the well. The quadrants would be helpful to keep track of which spheres have been
counted. 50 μL of the sphere suspension was then added to the well and viewed the spheres under
the microscope. The spheres were counted in each quadrant using a hand-tally counter. To ensure
accuracy of the total sphere count, counted at least 50 spheres in the well. The Sphere
Concentration was calculated by dividing the Sphere Count by the Counting Volume (e.g., 50 µL).
The Total Sphere Count was calculated by multiplying the Sphere Concentration by the Total
Volume (e.g., 125 µL). The number of spheres were scored as follows:
Total Sphere number (per well) = Sphere Count/Counting Volume (μL) x Total Volume
5.7 Serial Sphere Forming
At first, cells were seeded at 25000 cells/well in the ultra-low attachment plates to form primary
spheres. Primary spheres were centrifuged and disrupted with trypsin-EDTA and peptide to break
into single cells after 3-day growth. And then, the single cells suspension were seeded derived
from primary spheres at 25000 cells/ well for secondary spheres, then 25000 cells/well single cells
35

were seeded derived from secondary spheres to form tertiary spheres. Sphere counting assays were
performed after 72h sphere-forming for each serial.
5.8 RNA Isolation, Reverse Transcription, and RT-qPCR
Total RNA was extracted from hepatocyte cell lysate by using Trizol reagent (Invitrogen, Carlsbad,
CA, USA). After cells were collected to the 1.5mL tubes from spheres by centrifuging and using
trypsin-EDTA to separate the single cell, 1mL Trizol was added directly to the tubes, followed
with vortex and incubation for 10 minutes at room temperature (RT). 200 𝜇 L Chloroform was then
added to isolate RNA from cell lysates following vortex and incubation for 15 minutes at RT. After
centrifuging at 12000×g at 4°C for 15min, the upper aqueous phase which is colorless was
transferred to the new tubes. 0.5mL Isopropyl alcohol were added to precipitate the RNA from the
aqueous phase. Incubated 15 minutes at RT and then centrifuged the tubes at 12000×g at 4°C for
10min to discard the supernatant completely. The RNA pellets were washed with 0.5mL 75%
ethanol in the DEPC water twice.
RNA concentrations were measured by NanoDrop
TM
1000 Spectrophotometer (Thermo Fisher,
Waltham, MA). Reverse transcription was performed by M-MLV reverse transcriptase system
(Promega, Madison, WI). The real-time Polymerase chain reaction was achieved by
StepOnePlus
TM
Real- Time PCR System (Thermo Fisher, Waltham, MA) and quantified with the
help of SYBR Green qPCR Master Mix (Thermo Fisher, Waltham, MA; Bioland, Paramount, CA).
The relative gene expression was calculated with delta Ct and GAPDH was used as an internal
control. The primers for specific genes are listed on the table shown below (Table 1).

36

Table 1 Primers used for Real-Time PCR
Gene Primer Probe Sequence
SOX9
Forward GTGCAAGCTGGCAAAGTTGA
Reverse TGCTCAGTTCACCGATGTCC
GapDH
Forward GTCGGTGTGAACGGATTTGG
Reverse GACTCCACGACATACTCAGC

5.9 Protein Extract and Western Blot
Cells from 100 mm dishes were collected with a cell lysis buffer and a cell scraper, while cells
from 24-well plates were collected with trypsin-EDTA and centrifuges. Cell lysates were harvested
in cell lysis buffer (50 mM Tris [pH 7.4], 150 mM NaCl, 1 mM EDTA, 1% NP-40, 0.1% sodium
dodecyl sulfate, 1mM sodium deoxycholate, 0.1 M sodium pyrophosphate, 0.33M b
glycerophosphate, 1 M sodium fluoride, 0.1 M sodium metavanadate Na3VO4, 50 μM micro
cysteine, 100 mM phenylmethyl sulfonyl fluoride), supplemented with protease inhibitor cocktail
(MedChemExpress, Monmouth Junction, NJ).
The colorimetric DC
TM
(detergent compatible) protein assay (Bioland, Paramount, CA) was used
to quantify protein concentration. Cell lysates with equal amounts of protein mixed with
5× protein loading dye were subjected to a 10% Tris-glycine SDS-PAGE, and then transferred
from the SDS-gel to a PVDF (polyvinylidene difluoride) membrane (Bioland, Paramount, CA).
PVDF membranes were blocked with 5% nonfat milk dissolved in phosphate buffered saline,
supplemented with 0.1% Tween-20 (PBST) and then probed with primary antibodies against
SOX9 (Cell Signaling Technology, Danvers, MA) and GAPDH (Cell Signaling Technology,
Danvers, MA), as a control gene for quantification, at 4°C overnight. After washing with PBST,
the membrane was incubated with HRP (horseradish peroxidase)-linked secondary antibodies (GE
37

healthcare Chicago IL). Signals were detected using HRP substrate enhanced chemiluminescence
solutions (Thermo Fisher Waltham, MA). SuperSignal™ West Femto Maximum Sensitivity
Substrate (Thermo Fisher Waltham, MA) was used for low femtogram protein level detection
following manufacturer’s instructions.
5.10 Statistical Analysis
Data are presented as mean ± the standard error of the mean (SEM). Student’s t test was used to
analyze differences between two individual groups, and one-way ANOVA test with multiple
comparisons was used for testing differences among three or more groups. Two-tailed p values
less than 0.05 was considered as statistically significant.

38

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Abstract (if available)

Abstract Sex-determining region Y (Sry)-box9 (SOX9) is a transcriptional factor that plays a vital role in the embryonic development of many tissues and organs. In the liver, SOX9 is known as an early marker for biliary cells and may play a critical role in the development of liver cancer. In recent years, SOX9 has received more attention in the field of liver research. SOX9 upregulation is observed during liver cancer development promoted by chronic injury. Liver injury significantly stimulates the expansion of tumor-initiating cells (TICs), also known as cancer stem-like cells (CSCs) and is thought to promote tumorigenesis by inducing TIC/CSC transformation. ? The interactions between CSCs and tumor microenvironment (TME) promotes non-CSCs trans-differentiate into CSCs through providing anti-apoptosis, stemness-maintaining factors, and matrix components and may influence resistance to therapeutics. Thus, it is critical to understand the signals that lead to CSCs? transformation from non-CSCs. The previous studies indicate that Sox9 may plays an important function in regulating liver CSC stemness. This thesis aims to design an optical methodology for exploring the role of SOX9 in the human Hepatocellular Carcinoma (HCC) stem-like cells and highlights that SOX9 plays a vital role in the human liver cancer stem-like cells (LCSCs) proliferation and HCC progression. Here, we explored the role of SOX9 in CSC transformation by introducing siRNA targeting SOX9 into the Huh7 human HCC cell lines. Our work shows that downregulation of SOX9 by siRNA did not significantly affect the cell growth potential of Huh7 cells in cell proliferation assays. It did attenuate the ability of the Huh7 cells to form spheres in suspension culture, suggesting that SOX9 plays an important role in the maintaining the stemness of CSCs. In addition, our result shows that knockdown of SOX9 inhibited the ability of CSC self-renewal in the serial sphere cultures. Together, our data demonstrated a role of SOX9 in CSC transformation and maintenance. Our study here suggests that SOX9 might be an important LCSCs marker and serve as a potential therapeutic target for HCC.

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Asset Metadata

Creator Tang, Qi (author)

Core Title Methodology of exploring the role of SOX9 in the human HCC stem-like cells

School School of Pharmacy

Degree Master of Science

Degree Program Pharmaceutical Sciences

Degree Conferral Date 2021-08

Publication Date 07/24/2021

Defense Date 07/21/2021

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

Tag CSCs,HCC,liver cancer stem-like cells,OAI-PMH Harvest,siRNA transfection,SOX9,target therapy

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Stiles, Bangyan (committee chair), Okamoto, Curtis (committee member), Shih, Jean (committee member)

Creator Email qit@usc.edu,tangqi96@hotmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC15619737

Unique identifier UC15619737

Legacy Identifier etd-TangQi-9824

Document Type Thesis

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Rights Tang, Qi

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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