Investigate gene expression responses of a regenerative

Investigate gene expression responses of a regenerative rat liver model using a partial

hepatectomy method

Thomas Jefferson University of Graduate Studies Masters of Cell & Developmental Biology

Tracee L. Popielarczyk April 11, 2011

Thesis Advisor: Amy G. Aslamkhan, Ph.D.

Committtee Members: Gerald B. Grunwald, Ph.D.

James J. Monroe, Ph.D.

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Table of Contents Acknowledgements ........................................................................................................... 5 Abstract …………………………………………………………………………………. 6 Introduction....................................................................................................................... 7

Liver Injury and Regeneration ........................................................................................ 8 Regenerative Liver Model in the Adult Rat.................................................................. 10 2AAF Selects for Oval Cells......................................................................................... 11 Partial Hepatectomy...................................................................................................... 12 Research Aims .............................................................................................................. 13 Rat Drug Induced Liver Injury Comparisons ............................................................... 13

Materials and Methods................................................................................................... 14 Animal Handling........................................................................................................... 14 Surgery and Tissue Collection for Study 1 ................................................................... 15 Surgery and Tissue Collection for Study 2 ................................................................... 16 Histopathology.............................................................................................................. 17 RNA Preparation........................................................................................................... 17 RT-PCR Analysis ......................................................................................................... 18 Taqman Assay............................................................................................................... 18 Pathway Analysis.......................................................................................................... 22

Results .............................................................................................................................. 23 Histopathology for Study 1........................................................................................... 23 TaqCard Data for Study 1 ............................................................................................. 23 Pathway Analysis for Study 1....................................................................................... 25 Histopathology for Study 2........................................................................................... 26 TaqCard Data for Study 2 ............................................................................................. 27 Pathway Analysis for Study 2....................................................................................... 23

Discussion......................................................................................................................... 30 Histopathology.............................................................................................................. 31 Proliferation .................................................................................................................. 31 Liver Cell Population.................................................................................................... 32 Apoptosis ...................................................................................................................... 33 2AAF Effects ................................................................................................................ 34 Sham-Operation Effects................................................................................................ 34 Pathway Analysis.......................................................................................................... 35

Concluding Remarks ...................................................................................................... 46 Illustrations

Figure 1: Summary of animal models and their modes for inducing liver regeneration ....................................................................................................................................... 11 Figure 2: Flowchart summarizing the experimental process from administration of 2AAF through pathway analysis................................................................................... 15 Figure 3. Representative liver sections from Study 2 were formalin-fixed, paraffin-embedded and stained with hematoylin-eosin .............................................................. 27 Figure 4. Study 1(A) and Study 2 (B) proliferation pathway maps that represent a process in the cell cycle: transition and termination of DNA replication..................... 37

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Figure 5. Study 1 (A) and Study 2 (B) proliferation pathway maps that represent a process in the cell cycle: development thrombopoietin-regulated cell processes......... 39 Figure 6. Study 1 (A) and Study 2 (B) proliferation pathway maps that represent a process in the cell cycle: chromosome condensation in prometaphase ........................ 41 Figure 7. Study 1 (A) and Study 2 (B) proliferation pathway maps that represent a process in the cell cycle: role of APC in cell cycle regulation. .................................... 43 Figure 8. Study 1(A) and Study 2 (B) proliferation pathway maps that represent a process in the cell cycle: ESR1 regulation of G1/S transition. ..................................... 45

Tables

Table 1. Summary of transcriptomic sample set generated from previous 5 studies consisting of animals treated with Compounds A-E..................................................... 14 Table 2. The sample name and sample description of the RQ values calculated in Study 1 (2AAF implantation). ...................................................................................... 16 Table 3. The sample number, sample name, and sample description of the RQ values calculated in Study 2 (without 2AAF implantation)..................................................... 17 Table 4. Rat Liver Cell Population TaqCard including mature biliary markers, mature hepatocyte markers, oval cell/progenitor markers, Kupffer markers, fibroblast markers, and markers for metabolism and normalization............................................................ 20 Table 5. Rat Liver Proliferation Pathway TaqCard including proliferation markers, growth markers, and housekeeping markers................................................................. 21 Table 6. Rat Apoptosis Pathway TaqCard including apoptosis and housekeeping markers.......................................................................................................................... 22 Table 7: Study 1 Rat Liver Cell Population TaqCard including mature biliary markers, mature hepatocyte markers, oval cell/progenitor markers, Kupffer markers, fibroblast markers, and markers for metabolism and normalization............................................. 24 Table 8: Study 1 Rat Liver Proliferation Pathway TaqCard including proliferation markers, growth markers, and housekeeping markers.................................................. 25 Table 9: Top 5 differential expression pathways from MetaCore analysis of proliferation TaqCard data in Study 1 and Study 2 ...................................................... 26 Table 10: Study 2 Rat Liver Cell Population TaqCard including mature biliary markers, mature hepatocyte markers, oval cell/progenitor markers, Kupffer markers, fibroblast markers, and markers for metabolism and normalization. ........................... 28 Table 11: Study 2 Rat Liver Proliferation Pathway TaqCard including proliferation markers, growth markers, and housekeeping marker. .................................................. 29 Table 12: Study 2 Apoptosis TaqCard including apoptosis and housekeeping markers........................................................................................................................................ 30

Appendices Appendix 1. GeneGo MetaCore Analysis Key Legend............................................... 48 Appendix 2. Cell Cycle: Transition and termination of DNA replication pathway description..................................................................................................................... 48 Appendix 3. Development: Thrombopoietin-regulated cell processes pathway description..................................................................................................................... 49 Appendix 4. Cell Cycle: Chromosome condensation in prometaphase pathway description..................................................................................................................... 49

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Appendix 5. Cell Cycle: Role of APC in cell cycle regulation pathway description .. 50 Appendix 6. Cell Cycle: ESR1 regulation of the G1/S transition pathway description ....................................................................................................................................... 51 Reference List.................................................................................................................. 52

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Acknowledgements The research was supported by Merck & Co., Inc., West Point, Pennsylvania, U.S.A. I would

like to thank Amy Aslamkhan, James Monroe, and Gerald Grunwald for serving on my thesis

committee, Matthew Kuhls, Kim Bleicher and Adam Meacham for their guidance and

training in laboratory techniques, Wendy Bailey and Ethan Xu for their critical scientific

support in gene expression analysis, Thomas Forest for histopathology guidance, Adam

Meacham for photographs and LAR, Merck & Co., Inc. for their in vivo technical

contributions.

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Abstract

Characterization of transcriptional changes after partial hepatectomy (PH) may

provide an understanding of the underlying biological processes involved in

compensatory growth and regeneration of liver mass after drug induced liver injury

(DILI). Development of this type of model would prove useful as a model for assessment

of potential drug induced liver injury that induces a compensatory proliferative response.

In this project, we developed a surgical regeneration model (70% partial hepatectomy) in

liver of male Sprague Dawley rats. Individual gene markers associated with a

regenerative response in liver were evaluated in the partial hepatectomy model and

compared to five previous studies where compounds induced histopathological changes

indicative of proliferative and or regenerative responses in the liver to DILI. The liver

cell population and apoptosis biomarkers exhibited no apparent robust changes, while

many of the proliferation markers were up-regulated. In two studies, pathway enrichment

analysis using GeneGo MetaCore revealed that regulatory pathways related to cell

proliferation were differentially expressed in response to partial hepatectomy.

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Introduction

The liver is a common target for drug induced injury in both preclinical as well as

clinical development (Xu et al. 2008b). While both in vivo testing in preclinical species

and in vitro testing in hepatocyte culture models are the current screens to evaluate the

potential for drug induced liver injury (DILI), the prevalence of DILI in the clinic still

remains a common cause of drug attrition (Olson et al. 2000). More work is needed to

establish the underlying biological processes that impact susceptibility to DILI. One

preclinical screening strategy is to assess mechanistic transcriptomic biomarkers in

samples from animals affected with different manifestations of liver injury (Boone et al.

2005). Gene expression data serves as an important early indicator of toxicity because it

is detectable before clinical chemistry, histopathology, or clinical observations (Gerrish

and Malarkey 2007).

One critical biological process impacted in liver injury is compensatory growth

and regeneration. A regenerating liver does not undergo the same processes as a

developing liver, it is more similar to later stages of liver development (Otu et al. 2007).

Moreover, the outcome and progression of DILI is more adverse when compensatory

processes do not ensue (Mehendale 2005). Furthermore, a regenerative biomarker liver

signal in preclinical studies, in the absence of other findings, may provide evidence of

potential DILI liability down the line (Huby and Tugwood 2005). Using a surgical

regenerative liver model (partial hepatectomy), the proposed work will test the hypothesis

that the transcriptomic pathways resulting from a surgical regenerative partial

hepatectomy model will produce the same proliferative gene responses as a previous

DILI study set that was anchored in histological response. By comparison, the apoptosis

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gene transcriptomic pathway gene markers are not expected to produce a response since

this was employed as a "specificity" check.

Liver regeneration research has progressed over the years since the nineteenth

century. In 1931, Higgins and Anderson reported a procedure for a partial hepatectomy

in the rat and paved the way for reproducible quantitative studies. The rat is an ideal

animal model for liver regeneration in that the excision of the two prominent lobes

removes ~68% of the organ consistently, and rapid regeneration robustly ensues. Another

breakthrough was by Brues and colleagues in 1936 with their studies on regenerating

livers, demonstrating that the liver starts to increase in mass after only a few hours and

profound increases in cell number occur after a day in tandem with an increased rate of

DNA synthesis (Fitz 2002).

The impact of this experiment to the existing knowledge is to gain a better

understanding of compensatory regeneration of liver by characterizing the transcriptomic

pathway response to both surgical and drug induced modes of liver injury in the rat.

Overall, the model's greatest purpose is that it will add to the knowledge of integration

and regulation of gene transcription networks that result in the restoration of liver mass.

This work could potentially be beneficial to the health industry as a whole, as the liver is

one of the organs which manifest pathologies that lead to a number of mortalities

worldwide (Piscaglia et al. 2003).

Liver Injury and Regeneration

The liver functions in metabolic homeostasis in the body, including the storage,

synthesis, metabolism, and redistribution of carbohydrates, fats, and vitamins, and is the

main detoxifying organ. Furthermore, the liver has the ability to regenerate after damage.

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A normal liver consists of at least fifteen different cell types characterized as either

parenchymal cells or nonparenchymal cells. Parenchymal cells include hepatocytes that

make up the majority of the liver mass, while nonparachymal cells include sinusoidal

endothelial cells, Kupffer cells, hepatic stellate cells, and biliary cells. Hepatic

parenchymal cells are more numerous and have the most apparent functional impact.

However, nonparenchymal cells also aid in liver function and can alter parenchymal

transcript and protein profiles, including cytokines and chemokines (Mehendale 2005).

The specific cells which are activated following different manifestations of liver

injury are first hepatocytes, followed by endothelial cells, Kupffer cells, and hepatic

stellate cells. Endothelial cells are found lining the intrahepatic circulatory vessels or

sinusoids of the liver that provide a large surface area for oxygen and nutrients. Kupffer

cells are found in the sinusoids and play a role in phagocytosis and synthesis of cytokines

(Mehendale 2005). They may also have an influence on hepatocyte proliferation (Klaunig

et al. 2007). Cytokines, along with chemokines, contribute to the overall liver protein

expression profile in liver injury and inflammation (Mehendale 2005). Lymphocytes are

found within the hepatic tissue to help combat infection. Hepatic stellate cells have

several key functions including production of extracellular matrix (Klaunig et al. 2007).

The 70% partial hepatectomy is the most common method for studying liver

regeneration because removing more than 80% reportedly leads to liver regeneration

failure and mortality (Cao et al. 2009). Liver regenerative models are widely used to

study the cell cycle because a large percentage of the liver's total cell population consists

of the hepatocytes which will undergo proliferation in a synchronized manner (Chen et

al. 2010;Fukuhara et al. 2003). The cell cycle consists of four phases, including G1, S,

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G2, and M phase. The G1 phase prepares the cell for DNA synthesis in the S phase. The

G2 phase prepares the cell for mitosis (Assy and Minuk 1997). It is rare for hepatocytes

in a normal adult rat liver to undergo cell division, and here they remain in the G0 phase

of the cell cycle. After a hepatectomy, hepatocytes are activated and enter the S phase of

the cell cycle. It has been noted that DNA synthesis increases in hepatocytes after 12

hours and peaks at around 24 hours, while nonparenchymal cells peak around 2-4 days

depending on the specific cell type (Muriel 2007). DNA synthesis and expression of

cyclins may also be affected by circadian rythyms (Fausto, Campbell, and Riehle

2006;Khan and Mudan 2007). The liver mass will increase after 3 days and is complete

5-7 days (Muriel 2007). Several studies have observed the completion of liver

regeneration by day 7, however, it has also been reported to take up to 10 days for

complete liver regeneration in rodents.

Regenerative Liver Model in the Adult Rat It is important to validate in vitro studies with in vivo studies. Various animal

models for studying liver regeneration are available, as summarized in Figure 1 (Palmes

and Spiegel 2004). In this study we focused on the surgical model, using a partial

hepatectomy method. Specifically, one popular method is the 2-acetylaminofluorene

(2AAF)/partial hepatectomy method which activates a progenitor cell population, known

as oval cells. Oval cells are small cells with oval shaped nuclei that are recruited for liver

regeneration when hepatocytes fail to proliferate (Shupe et al. 2008).

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Figure 1: Summary of animal models and their modes for inducing liver regeneration.

2AAF Selects for Oval Cells

The first line of defense against liver injury is the involvement of hepatocytes. The

second line of defense against liver injury occurs when hepatocytes can not regenerate

the liver (Riehle et al. 2011). Administration of 2AAF inhibits the proliferation of

hepatocytes and promotes oval cell differentiation into hepatocytes to regenerate liver

mass lost from damage. This process works because hepatocytes can metabolize 2AAF

to its metabolite, N-hydroxyl, which interferes with the cyclin D1 pathway (Shupe et al.

2008). N-acetylation is a major route of biotransformation for xenobiotics containing an

aromatic amine which is converted to an aromatic amide. N-acetyltransferases can

activate aromatic amines if they are first N-hydroxylated by cytochrome P450. Many

xenobiotics are sulfated after a hydroxyl group is exposed. 2AAF undergoes sulfonation

to produce the tumorigenic metabolites of nitrenium and carbonium ions that can bind to

DNA (Parkinson and Ogilvie 2010). Preventing hepatocyte proliferation in 2AAF selects

for oval cells which begins the regeneration process because neither biliary epithelial

cells nor oval cells are capable of converting 2AAF to its toxic metabolite (Oh, Hatch,

and Petersen 2002;Shupe et al. 2008).

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Partial Hepatectomy Partial hepatectomy in rodents induces liver regeneration and causes DNA synthesis

to be initiated in the remaining liver cells. In one particular protocol, the partial

hepatectomy involves removal of both the median and left lateral lobes from an

anesthetized rat (Shupe et al. 2008). After 5-7 days, the structure of the rat liver is

restored; however, the remaining lobules are temporarily over-sized, but return to normal

size lobules (Kara et al. 2009;Palmes and Spiegel 2004;Song et al. 2010).

Cytokines, hormones, growth factors, and transcription factors are involved in liver

regeneration (Arai et al. 2003). The two processes involved include; i.) hypertrophy,

which is defined as an increase in cell size or protein content and ii.) hyperplasia, which

is defined as an increase in cell number. However, these two processes can take place

independently of each other. Liver regeneration is primarily a process of compensatory

hyperplasia governed by functional stressors on the liver (Palmes and Spiegel 2004).

The liver is unique as an organ in that it modulates its mass according to functional

requirements. Moreover, the liver only proliferates under conditions of functional

deficiency, and it undergoes apoptosis under functional excess. Hepatocytes are normally

quiescent, but are the first cell population to proliferate when induced (Kara et al.

2009;Baker et al. 2001). About 90-95% of the total hepatocytes of the liver will re-enter

the proliferating phase within the first 40 hours and show a limitless capacity (Guo et al.

2006;Su et al. 2002).

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Research Aims

The areas I hope to address in this project include

1.) Determine how the gene responses to the proliferation markers in our study

compare to the data from a previous DILI study set.

2.) Determine gene responses in liver cell population markers in this study.

3.) Apoptosis markers will be used as a "specificity" check.

Rat Drug Induced Liver Injury Comparisons

For this study, a transcriptomic sample set that was previously generated from

proprietary compounds (labeled Compound A-E) and genes (labeled Gene A-M) were

included for comparison to the surgical partial hepatectomy results. In brief, the

proprietary compounds had been administered by oral gavage to female rats for seven

days at doses ranging from 10 to 750 mg/kg/day. At the time of necropsy, an

approximately 5 mm liver sample was collected, placed in a polycon and frozen on dry

ice. These samples were then stored at -70 ºC until processed. An adjacent liver sample

was collected in 10% neutral buffered formalin (NBF) for histopathological examination

by a board certified veterinary pathologist. Pooled control liver samples were compared

to study liver samples (coded by animals #1-3) with histopathological diagnoses of bile

duct hyperplasia and increased mitotic activity.

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Table 1. Summary of transcriptomic sample set generated from previous 5 studies consisting of animals treated with Compounds A-E.

Liver Bile

Duc

t:Hyp

erpl

asia

Mito

tic A

ctiv

ity In

crea

sed

Gene A Gene B Gene C Gene D Gene E Gene F Gene G Gene H Gene I Gene J Gene K Gene L Gene MControls Control Liver 1 0 0 1.67 1.13 1.55 0.89 0.82 0.97 0.55 2.30 1.20 0.70 0.94 1.05 0.95

Control Liver 2 0 0 0.36 0.46 0.23 1.84 1.02 1.37 0.35 0.20 0.50 0.98 0.58 1.41 2.86Control Liver 3 0 0 2.68 1.63 4.10 1.43 1.51 1.21 4.45 2.13 3.31 3.09 2.15 2.42 2.62Control Liver 4 0 0 1.65 0.88 1.29 0.47 0.87 1.13 1.94 2.21 0.76 0.86 1.24 0.80 1.23Control Liver 5 0 0 1.02 0.95 1.21 0.91 0.97 1.28 0.99 1.23 0.37 1.16 1.14 1.42 1.03Control Liver 6 0 0 0.72 1.23 0.83 0.89 0.98 0.94 1.07 1.45 1.53 1.12 1.18 1.20 0.35Control Liver 7 0 0 0.65 1.19 0.49 1.02 0.87 0.54 0.53 0.53 0.99 0.59 0.45 0.77 0.66Control Liver 8 0 0 0.77 0.96 1.09 1.08 1.09 0.85 1.09 0.50 1.16 0.72 1.13 0.27 0.48

Compound A Liver 1 1 0 30.85 2.77 3.89 2.75 0.95 1.15 16.52 4.55 3.41 3.85 2.95 2.38 2.67Liver 2 2 0 19.04 12.99 30.64 9.60 2.54 7.87 25.00 23.86 21.48 20.49 22.99 6.14 15.90

Compound B Liver 1 0 0 1.21 0.84 1.58 1.90 0.73 1.31 1.80 1.68 0.88 0.40 1.62 1.85 0.74Liver 2 0 0 0.91 1.04 0.04 2.14 0.82 2.37 0.85 0.66 0.34 0.17 0.35 1.27 0.32Liver 3 0 0 3.92 10.26 5.37 8.73 4.96 10.32 7.61 1.43 1.85 8.40 10.86 3.40 1.55

Compound C Liver 1 0 0 1.75 1.17 1.96 2.04 0.83 1.56 1.68 1.63 1.55 0.62 1.63 1.33 1.74Liver 2 0 0 0.77 0.25 0.21 2.05 1.26 1.24 0.56 0.57 0.66 0.24 0.30 1.25 0.67Liver 3 0 0 0.24 0.30 0.34 0.52 0.94 0.65 0.50 1.19 1.04 0.70 0.42 0.80 0.80

Compound D Liver 1 2 0 1.99 1.26 1.19 1.63 1.05 0.53 2.95 1.19 0.63 1.22 1.60 0.61 0.79Liver 2 3 0 15.50 10.12 16.12 8.41 2.09 5.56 15.30 19.20 16.50 19.43 16.30 5.31 10.36Liver 3 3 0 1.34 0.50 1.07 1.07 1.38 1.16 0.77 0.15 1.10 0.01 0.42 5.59 0.41

Compound E Liver 1 0 2 8.06 10.00 17.55 7.62 3.58 4.44 14.63 18.37 15.87 12.03 21.33 3.98 16.47Liver 2 0 1 5.17 6.02 8.52 3.20 1.19 4.95 7.66 5.43 7.06 4.60 6.63 1.60 3.41Liver 3 0 1 5.58 4.02 8.54 3.73 1.96 3.94 8.88 7.02 4.93 5.57 10.70 2.91 3.66

Materials and Methods

Animal Handling

Male Sprague Dawley rats between 6-20 weeks, purchased from Charles River

Laboratories (Wilmington, MA). Animals were housed individually in covered animal

boxes. The climate controlled rooms had alternating 12 hr light-dark cycles and the rats

were fed ad-lib a certified rodent diet (PMI international) with a constant supply of water.

Animals were dosed with 21 day time-release 2AAF pellets, starting 7 days before the

partial hepatectomy surgery. 2AAF pellets (75 mg) were acquired from Innovative

Research of America (Sarasota, Florida). The 2AAF time release pellets were implanted

in the abdomen of the three animals designated to the treatment group. The partial

hepatectomy surgery involved removing both the median and left lobes of the liver from

treated and control animals. Note in Figure 1 that administration of 2AAF for treated

animals and no administration of 2AAF for control animals was the first step in the study.

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Figure 2: Flowchart summarizing the experimental process from administration of 2AAF

through pathway analysis.

± 2AAF Treatment

Pre-/Post-HepatectomyTissue Collection

Histopathology RNA Isolation

TaqMan Analysis

Pathway Analysis

± 2AAF Treatment

Pre-/Post-HepatectomyTissue Collection

Histopathology RNA Isolation

TaqMan Analysis

Pathway Analysis

Surgery and Tissue Collection for Study 1

For the partial hepatectomy surgery, each rat had the median and left lobes of the

liver removed, which is ~70% of the livers mass. An approximate 5 mm section was

taken from the hilar region of each of the extracted lobes, one section each on dry ice for

RNA isolation and for section each for fixation in 10% NBF for histopathological

examination.

Animals were anesthetized, exsanguinated, and the liver removed at 4, 7, and 11

days. An approximate 5 mm section was taken from the hilar region of each of the

extracted lobes, one sample for each freezing and fixation in 10% NBF for

histopathological examination.

In this 2AAF/partial hepatectomy procedure, each rat serves as its own control

with samples being taken before and after the partial hepatectomy surgery. Note that

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Figure 2 shows that both control and treated animals undergo a partial hepatectomy

where liver samples are collected before and at the time of surgery for the next steps of

RNA isolation and histopathological examination.

Table 2: The sample name and sample description of the RQ values calculated in Study 1 (2AAF implantation).

Sample Name Sample Description

Rat #1 No 2AAF 11 days post hepatectomy No 2AAF pre hepatectomy

Rat #2 2AAF 4 days post hepatectomy 2AAF pre hepatectomy



Surgery and Tissue Collection for Study 2

For the partial hepatectomy surgery, the rat had the median and left lobes of the

liver removed. An approximate 5 mm section was taken from the hilar region of each of

the extracted lobes, one section each on dry ice for RNA isolation and for section each

for fixation in 10% NBF for pathohistological examination. For the sham-operation, rats

were treated similar to those undergoing partial hepatectomy surgery, except that no

lobes were extracted.

On Day 7, all animals were exsanguinated and an approximate 5 mm section was

taken from the hilar region of each of the remaining lobes, one section stored at -70 ºC

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until processed for RNA isolation and one section for fixation in 10% NBF for

histopathological examination.

Table 3: The sample number, sample name, and sample description of the RQ values calculated in Study 2 (without 2AAF implantation). Sample Number Sample Name Sample Description

1 Rat #1 Day 7 post hepatectomy




5 Rat #5 Sham-operated



8 Control Day 0 pre hepatectomy

Histopathology

After fixation in 10% NBF, the control and treated liver samples were embedded

in paraffin, sectioned, and stained with hematoxylin and eosin. Histopathological

examination of the liver tissues was performed by a board certified veterinary pathologist

(Figure 2).

RNA Preparation

RNA was isolated from control and treated liver tissues (Figure 2) using the

QIAGEN RNeasy kit (QIAGEN Inc. Valencia, CA). Approximately 100 mg of tissue for

each sample was treated with Trizol, homogenized, and the remainder of the procedure

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was performed using the manufacturer's procedure. The RNA was quantified using 2µl of

the isolated RNA by the Nanodrop® ND-1000 Spectrophotometer (NanoDrop

Technologies, Inc., Wlimington, DE).

RT-PCR Analysis

The isolated RNA was diluted to 2.5 µl (100ng/ µl) and combined with 5µl RT

Buffer, 11 µl MgCl, 10µl DNTPS, 2.5µl random hexamers, 1µl RNAse Inhibitor, 1.25 µl

Multiscribe Reverse Transcriptase enzyme, and 16.75 µl nuclease free H2O (TaqMan

Reagent Kit, Applied Biosciences, Foster City, CA). Reverse transcriptase was performed

at 25˚C for 10 min, 48˚C for 30 min, 95˚C for 5 min to 4˚C by the GeneAmp® PCR

System 9700 (Applied Biosystems, Inc.).

Gene expression of total liver RNA isolated from hepatectomy and non-

hepatectomy rats was evaluated using RT-PCR. cDNA was synthesized from total RNA

with Reverse transcriptase and Micro Fluidic cards (TaqCards) containing an established

panel of liver biomarker sequences were used to measure gene levels. The ABI Prism®

7900HT Sequence Detection System (SDS 2.1 software) was used to quantify gene

expression levels. The data were normalized with 18S rRNA.

TaqMan Assay

Amplification of cDNA was carried out using the Rat Liver Cell Population

(Table 4), the Proliferation (Table 5), and the Apoptosis TaqCards (Table 6) from

Applied Biosystems (ABI). Each well contained 22 µl cDNA, 33 µl nuclease free H2O,

and 55 µl TaqMan Universal PCR Master Mix. Figure 2 show the TaqMan assay as the

last step before pathway analysis.

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The TaqCards contain two housekeeping genes, including 18S and GADPH, for

normalization of gene expression levels (Wang and Xu 2010). The 18S gene is

commonly used as it is a basic component of all eukaryotic cells. It is an rRNA gene

sequence that is easy to access because of its highly conservative regions, which allow it

to be a universal primer. GADPH is considered a housekeeping gene and is used because

it is frequently expressed at abundant levels in both tissue and cells.

Data was analyzed in Microsoft Excel using the comparative CT method. The

comparative CT method is a quantitative approach to compare the CT values of samples of

interest to a calibrator sample. Both CT values are normalized against the housekeeping

gene(s). Since the study designs were different for these two studies, Study 1 resulted in a

comparison of post heapatectomy to pre hepatectomy animals and Study 2 compared the

hepatectomy to sham-operation animals for our final fold change. This fold change is

known as the relative quantification (RQ) value. Using this method, pre-set thresholds

could be used that included any values greater than 2.0 are up-regulated and any values

less than 0.5 are down-regulated. An additional threshold was set for up-regulation with

values greater than 5.0.

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Table 4. Rat Liver Cell Population TaqCard including mature biliary markers, mature hepatocyte markers, oval cell/progenitor markers, Kupffer markers, fibroblast markers, and markers for metabolism and normalization.

Category # GeneMature biliary 1 Gene A

2 Gene B3 Gene C4 Gene D5 Gene E6 Gene F

Mature hepatocyte 7 Gene G8 Gene H9 Gene I10 Gene J11 Gene K12 Gene L

Oval Cell/Progenitor 14 Gene M15 Gene N16 Gene O17 Gene P

Kupffer 18 Gene Q19 Gene R

Fibroblast 20 Gene SMetabolism 21 Gene T

22 Gene UHousekeeping 23 GADPH

24 18SrRNA

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Table 5. Rat Liver Proliferation Pathway TaqCard including proliferation markers, growth markers, and housekeeping markers.

Category # GeneProliferation 1 Gene A

2 Gene B3 Gene C4 Gene D5 Gene E6 Gene F7 Gene G8 Gene H9 Gene I10 Gene J11 Gene K12 Gene L13 Gene M

Polyamine 14 Gene N(Other) 15 Gene O

16 Gene P17 Gene Q18 Gene R19 Gene S20 Gene T21 Gene U

Growth 22 Gene VHousekeeping 23 GAPDH

24 18SrRNA

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Table 6. Rat Apoptosis Pathway TaqCard including apoptosis and housekeeping markers.

Category # GeneApoptosis 1 Gene A

2 Gene B3 Gene C4 Gene D5 Gene E6 Gene F7 Gene G8 Gene H9 Gene I10 Gene J11 Gene K12 Gene L13 Gene M14 Gene N15 Gene O16 Gene P17 Gene Q18 Gene R19 Gene S20 Gene T21 Gene U22 Gene V

Housekeeping 23 GAPDH24 18SrRNA

Pathway Analysis

The proliferation TaqCard data was loaded into GeneGo MetaCore to visualize

the enrichment of differentially expressed pathways (Figure 2). Ranking of relevant

pathways was based on hypergeometric p values (Xu et al. 2008a). We further examined

the member gene expression profiles of the top five pathways for the proliferation

TaqCard.

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Results

Histopathology for Study 1

Liver tissue was collected pre- and post hepatectomy from days 0, 4, 7, and 11.

Images were similar to those of Study 2 and exhibited no distinct changes, therefore, data

for this study was not shown.

TaqCard Data for Study 1

Table 7 shows that there were no robust changes seen in the markers for the different

liver cell populations. The changes were not consistent within the category or within or

across rats #1-4 and all changes were only slightly above or below the pre-set thresholds.

Table 8 shows that there were more robust changes seen in the markers for cell

proliferation. The up-regulation of markers were more consistent and of a greater degree

across the proliferation category and across rats #1-4. The up-regulated changes of

interest are seen in Genes A-D, Genes F-M, and Gene U.

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Table 7: Study 1 Rat Liver Cell Population TaqCard including mature biliary markers, mature hepatocyte markers, oval cell/progenitor markers, Kupffer markers, fibroblast markers, and markers for metabolism and normalization. [RQ values ≤ 0.5 are shaded in light blue (down-regulated) and values ≥ 2.0 are shaded in light pink (up- regulated).] Category Marker Rat #1 Rat #2 Rat #3 Rat #4Mature biliary Gene A 0.95 0.54 3.41 0.50

Gene B 2.15 0.23 1.73 0.45Gene C 1.13 0.56 0.22 0.36Gene D 1.48 2.08 0.56 0.61Gene E 1.85 0.28 0.60 0.75Gene F 1.38 0.96 1.02 1.40

Mature hepatocyte Gene G 0.98 0.77 0.85 0.98Gene H 1.14 1.25 0.49 0.55Gene I 0.97 0.48 0.45 0.61Gene J 0.73 0.52 0.22 0.32Gene K 0.65 0.28 0.44 0.36Gene L 1.15 0.52 0.59 0.73Gene M 0.75 0.65 0.41 0.82Gene N 1.68 0.58 0.94 0.98

Oval Cell/Progenitor Gene O 2.34 0.40 2.33 0.91Gene P 1.66 0.70 0.42 0.62Gene Q 2.28 1.64 0.15 2.97

Kupffer Gene R 1.42 0.83 1.36 1.49Fibroblast Gene S 1.60 0.74 0.66 0.96Metabolism Gene T 0.46 0.69 0.45 0.85

Gene U 0.52 0.33 0.76 0.42Housekeeping GADPH 0.89 0.55 0.74 0.76

24

Table 8: Study 1 Rat Liver Proliferation Pathway TaqCard including proliferation markers, growth markers, and housekeeping markers. [RQ values ≤ 0.5 are shaded in blue (down-regulated), values 2.0-5.0 are shaded in pink (up-regulated), and values ≥ 5.0 are shaded in red (greater degree of up- regulation ).] Category Marker Rat #1 Rat #2 Rat #3 Rat #4Proliferation Gene A 3.24 6.96 15.17 18.33

Gene B 4.49 3.49 7.57 7.70Gene C 2.40 4.82 46.56 17.82Gene D 2.01 1.96 2.36 6.04Gene E 0.95 1.52 0.48 2.38Gene F 3.20 2.91 2.43 2.92Gene G 4.21 6.98 5.94 18.44Gene H 2.05 5.13 26.09 13.91Gene I 1.98 7.09 15.56 21.36Gene J 1.71 5.73 8.35 11.27Gene K 1.91 4.51 6.27 17.01Gene L 3.17 2.10 3.00 6.39Gene M 2.83 3.44 11.79 18.88

Proliferation Gene N 0.15 0.30 0.77 0.61(other) Gene O 1.13 0.56 0.61 0.57

Gene P 0.54 0.04 0.06 0.72Gene Q 1.13 1.44 0.49 1.36Gene R 1.03 1.56 1.15 1.06Gene S 0.98 1.05 0.46 0.75Gene T 1.11 2.05 0.94 1.51Gene U 2.20 9.87 10.85 14.58

Growth Gene V 0.97 1.24 0.42 1.29Housekeeping GADPH 0.81 1.52 0.43 1.05

Pathway Analysis for Study 1

In Study 1, with 22 markers for proliferation, the top five pathways are shown in

Table 9. The top ranked pathway was the cell transition and termination of DNA

replication, followed by the development thrombopoietin-regulated cell processes

pathway, each consisting of five of the markers measured on the cell proliferation

TaqCard, shown in Table 8. The remaining pathways included chromosome condensation

in prometaphase, role of APC in cell cycle regulation, and ESR1 regulation in G1/S

transition.

25

Table 9: Top 5 differential expression pathways from MetaCore analysis of proliferation TaqCard data in Study 1 and Study 2. Pathway Maps of Proliferation Markers

Rank Ratio Genes

Cell cycle: Transition and termination of DNA replication

1 5/28

Gene C Gene KGene NGene U

Development: Thrombopoietin-regulated cell processes

2 5/45

Gene B Gene C Gene NGene OGene P

Cell cycle: Chromosome condensation in prometaphase

3 4/21

Gene AGene C Gene KGene U

Cell cycle: Role of APC in cell cycle regulation

4 4/32

Gene AGene C Gene F Gene U

Cell cycle: ESR1 regulation of G1/S transition

5 4/33

Gene C Gene NGene OGene P

Histopathology for Study 2

In Study 2, liver tissue was collected pre- and post hepatectomy from Day 7 and

sham animals. These images, shown in Figure 7, focus at a low magnitude on the

periportal area and at a higher magnitude to focus in on the main parts of the portal triad,

consisting of the portal vein, the hepatic artery and the bile duct. The pre hepatectomy

Rat #1 served as the control and showed normal cells in the periportal area and portal

triad. Sham rat #5 and hepatectomy rat #7 were similar to control rat #1 with no distinct

changes. The remaining data was not shown as they were all similar and all changes were

most likely due to animal variability.

26

Figure 3. Representative liver sections from Study 2 were formalin-fixed, paraffin-embedded and stained with hematoylin-eosin.

A.) Control rat liver tissue at 20X. B.) Control rat liver tissue at 40X. C.) Sham rat liver tissue at 20X. D.) Sham rat liver tissue at 40X. E.) Hepatectomy rat liver tissue at 20X. F.) Hepatectomy rat liver tissue at 40X.

TaqCard Data for Study 2

Table 10 shows that there were no consistent robust changes seen in the markers for

liver cell populations. The changes were not consistent within the category or across rats

#1-4 and most changes were only slightly above or below the thresholds. The changes

that were seen to a greater degree were still inconsistent with the data as a whole.

Table 11 shows that there were more robust changes seen in the markers for cell

proliferation. The up-regulation of markers was more consistent and of a greater degree

across the proliferation category and across rats #1-4. The up-regulated changes of

interest are seen in Genes A, C, G, K-M, and Gene U. Table 12 shows that there were

few robust changes seen in the markers for apoptosis. The changes were not consistent

27

within the category or within or across Rats #1-4, except for Gene G. All other changes

were only slightly above or below the thresholds.

Table 10: Study 2 Rat Liver Cell Population TaqCard including mature biliary markers, mature hepatocyte markers, oval cell/progenitor markers, Kupffer markers, fibroblast markers, and markers for metabolism and normalization. [RQ values ≤ 0.5 are shaded in light blue (down-regulated), values 2.0-5.0 are shaded in pink (up-regulated), and values ≥ 2.0 are shaded in red (greater degree of up- regulation).] Category Marker Rat #1 Rat #2 Rat #3 Rat #4Mature Biliary Gene A 1.89 4.43 NV 6.53

Gene B 7.36 0.77 1.79 2.77Gene C 2.07 0.09 0.85 0.18Gene D 7.40 1.85 1.63 2.03Gene E 1.60 0.67 0.87 0.76Gene F 2.63 1.92 1.18 1.72

Mature Hepatocyte Gene G 2.42 0.82 1.17 0.95Gene H 2.37 1.29 0.99 1.29Gene I 1.92 0.71 0.99 0.72Gene J 2.91 1.64 1.99 1.82Gene K 1.80 0.82 0.77 0.37Gene L 2.43 1.08 1.03 1.04Gene M 1.58 0.67 0.85 0.51Gene N 2.27 1.01 1.51 0.90

Oval Cell/Progenitor Gene O 21.79 3.65 1.89 5.02Gene P 3.52 1.50 1.74 1.50Gene Q 2.02 0.15 0.37 0.28

Kupffer Gene R 4.17 2.08 1.39 1.83Fibroblast Gene S 1.96 1.17 0.84 1.17Metabolism Gene T 2.25 1.20 0.81 0.97

Gene U 1.97 0.64 0.66 0.97Housekeeping GAPDH 2.29 1.05 1.08 1.05 NV = no value.

28

Table 11: Study 2 Rat Liver Proliferation Pathway TaqCard including proliferation markers, growth markers, and housekeeping marker. [RQ values ≤ 0.5 are shaded in blue (down-regulated), values 2.0-5.0 are shaded in pink (up-regulated), and values ≥ 2.0 are shaded in red (greater degree of up-regulation).] Category Marker Rat #1 Rat #2 Rat #3 Rat #4Proliferation Gene A 7.29 5.90 2.30 4.90

Gene B 2.61 1.61 1.61 1.66Gene C 10.46 5.58 3.16 5.71Gene D 3.13 2.82 2.74 1.15Gene E 1.47 0.71 1.12 1.34Gene F 1.42 0.75 1.47 2.31Gene G 9.07 7.64 3.29 5.95Gene H 5.47 4.70 1.98 2.34Gene I 7.49 2.03 1.97 4.49Gene J 5.81 3.09 1.32 3.98Gene K 7.33 5.35 2.17 4.42Gene L 11.53 8.53 5.27 6.70Gene M 8.76 5.28 2.48 4.05

Proliferation Gene N 1.71 0.38 1.08 1.06(other) Gene O 0.86 1.60 1.34 2.45

Gene P 0.54 1.80 2.45 4.57Gene Q 1.96 1.86 3.40 3.59Gene R 1.77 1.23 1.78 2.38Gene S 1.69 1.67 2.52 1.90Gene T 1.23 1.26 3.19 3.30Gene U 5.11 3.49 2.12 3.49

Growth Gene V 2.03 1.51 1.72 2.43Housekeeping GADPH 2.60 1.55 2.20 2.67

29

Table 12: Study 2 Apoptosis TaqCard including apoptosis and housekeeping markers. [RQ values ≤ 0.5 are shaded in blue (down-regulated), values 2.0-5.0 are shaded in pink (up-regulated), and values ≥ 2.0 are shaded in red (greater degree of up- regulation).] .

Category Marker Rat #1 Rat #2 Rat #3 Rat #4Apoptosis Gene A 1.95 1.33 1.43 2.54

Gene B 2.50 1.45 1.73 2.89Gene C 1.75 0.95 0.93 2.22Gene D 0.59 0.23 1.49 0.28Gene E 1.09 1.66 1.16 1.32Gene F 0.73 2.17 0.62 2.07Gene G 4.23 2.54 4.21 6.33Gene H 0.27 1.76 0.38 1.85Gene I 1.40 1.65 1.30 2.17Gene J 1.49 1.66 1.58 1.67Gene K 1.42 1.14 1.72 1.97Gene L 1.16 1.46 1.12 1.38Gene M 2.67 2.15 1.97 2.41Gene N 1.14 1.19 1.04 1.64Gene O 1.57 1.34 1.02 1.60Gene P 1.68 1.69 1.72 1.90Gene Q 2.11 2.60 1.84 2.07Gene R 1.79 1.59 1.16 1.76Gene S 1.69 2.06 1.27 1.63Gene T 2.68 1.34 1.17 1.79Gene U 1.26 1.29 1.45 1.11Gene V 1.30 1.15 1.84 1.06

Housekeeping GAPDH 1.42 1.01 1.20 1.26 Pathway Analysis for Study 2

In Study 2, with 22 markers for proliferation, the top five pathways are shown in

Table 9, as is Study 1. The top ranked pathways were the cell transition and termination

of DNA replication, followed by the development thrombopoietin-regulated cell

processes pathway, each consisting of five of the markers measured on the cell

proliferation TaqCard, shown in Table 11. The remaining pathways included

chromosome condensation in prometaphase, role of APC in cell cycle regulation, and

ESR1 regulation in G1/S transition.

30

Discussion Histopathology

When comparing the treated liver tissue from Study 1 and the hepatectomy liver

tissue from Study 2, to the control animals, there were no distinct differences with only

subtle sample variation that was most likely due to animal variability. This lack of

response my be consistent with the reported kinetic histological response of the liver,

where the time frame (post 7 days) we assessed has been reported to be a "recovery"

phase. Moreover, the literature explains that, in general, hepatocyte proliferation begins

in the periportal region and progresses to the pericentral region of the lobule (Palmes and

Spiegel 2004). Kara et al. found that at 8, 16, and 24 hours post hepatectomy, tissue

specimens showed hyperchromatic hepatocytes swollen with prominent nucleoli and

nuclear vascuolization in the periportal area. Also, at 2 and 3 days post hepatectomy,

numerous mitotic figures were present, and began to decrease until day 6 when the

parenchymal architecture had recovered (Guo et al. 2006). While we did not observe

distinct changes such as hepatocyte proliferation and the presence of mitotic figures, if

we were to look at earlier time-points post hepatectomy, we may see more remarkable

changes.

Proliferation

Since this hepatectomy model induces a proliferative response, it was expected

that there would be an overall increase in the proliferation markers. There were multiple

genes that were up-regulated in both studies, including Genes A, C, G, K-M, and U.

Many studies have divided the processes of liver regeneration into phases. One study in

particular, defines four phases of liver regeneration as i.) initiation phase during 0.5-4

31

hours post hepatectomy, ii.) G0 to G1 transition during 4-6 hours post hepatectomy, iii.)

cell proliferation phase during 6-66 hours post hepatectomy, and iv.) cell differentiation

and structure-functional reorganization phase during 66-168 hours post hepatectomy (Qin

et al. 2006;Wang et al. 2009). According to these phases, proliferation should be

complete by day 3. We observed robust changes in proliferation, shown also in many

other studies; however, our data is from samples taken at a later phase of liver

regeneration. A number of studies have demonstrated increased DNA synthesis and

hepatocytes occurring within 48 hours of hepatectomy, followed by smaller, yet

significant increases in hepatocyte mitosis (Ochoa et al. 2010). Koniaris et al. also

explained that proliferation is proportional to the degree of injury and with greater than a

50% resection a second wave of mitosis is less distinct, but can be expected to peak at 3-5

days (Koniaris et al. 2003). Since we were still noticing changes at day 7, in the absence

of a histomorphological change, maybe there were additional proliferation gene

responses lagging after the initial proliferation phase. Perhaps we would see the same

changes, but even more pronounced with liver samples from earlier time-points.

Liver Cell Population

We assessed trends in the liver cell population markers. As seen in both Study 1

and Study 2, there were no robust changes seen in the markers for the different liver cell

populations. These changes were not consistent between animals and all changes were

only slightly above or below the pre-set thresholds. Almost immediately after surgery,

cytokines and growth factors stimulate activation of transcription factors and genes

responsible for stimulating normally quiescent hepatocytes and non parenchymal cells

(White et al. 2005). Most changes occur very early in the period post hepatectomy.

32

Fukuhara et al. data showed that of the genes up-regulated more then twofold after partial

hepatectomy, several were expressed at the 6 hour and 12-18 hour time-points, while

fewer were expressed at the 24 hour and 48-72 hour time-points and only one gene was

reported at the one week time-point (Fukuhara et al. 2003). Our observations correlate

with this study in that we had some similar genes and also saw only slight changes at the

one week time-point. We could expect that more of our cell population genes would be

expressed with liver samples from earlier timepoints.

Apoptosis

While we did expect changes in proliferation, the purpose of the apoptosis markers is

to test for specificity. We observed few changes in the markers for apoptosis (Table 12).

The changes were not consistent within the category or within or across rats #1-4. All

other changes were only slightly above or below the thresholds. In a study by

Michalopoulus, it was thought that apoptosis was seen as a possible mechanism to correct

an "over-shooting of the regenerative response" (Michalopoulos 2007). Many studies

have reported that rat liver mass is restored 5-7 days post hepatectomy (Taub 2004).

Koniaris explains that total liver mass is controlled by promitotic and apoptotic

mechanisms and in both human and animal liver transplants, a smaller liver will grow to

a size proportional to its larger host and that a larger liver will undergo apoptosis to reach

a size proportional to the smaller host (Koniaris et al. 2003). Perhaps, by day 7, the livers

had reached their necessary size and apoptosis had ceased by this point. It may be

possible to see changes in these markers if samples were collected at an earlier time-

point. Nevertheless, apoptosis may be generally insignificant for liver regeneration.

33

2AAF Effects

In Study 1, the administration of 2AAF before the partial hepatectomy surgery,

seemed to have little to no effect on hepatocyte proliferation. The cell population data

(Table 7) shows no significant difference between rat #1 and rats #2-4, in the markers of

the mature hepatocytes. The proliferation data (Table 8) clearly shows robust gene

expression for proliferation across rats #1-4. Cimica et al. used 2AAF in a time-course

study and found evidence suggesting that 2AAF was effective in inhibiting hepatocyte

proliferation because liver mass was not significantly recovered until day 11, instead of

the usual 7 days after partial hepatectomy (Cimica et al. 2005). We did not achieve the

same results with the 2AAF and this was one reason for performing another study

without the administration of 2AAF, and also to limit the number of variables affecting

the liver regeneration in this model. Perhaps, the administration of 2AAF can be re-

addressed in future studies.

Sham-Operation Effects

In Study 2, sham animals were included to distinguish between the effects of the

hepatectomy and surgery-related changes. Sham surgery is a known exogenous priming

stimulus. They are conducted to eliminate responses caused by surgery alone (Su et al.

2002). Shams were included because variables including surgical stress, handling of the

liver, anesthesia, and administration of drugs will trigger a wave of DNA synthesis in the

liver (Palmes and Spiegel 2004). Sham-operated animals showed genes that were up- or

down-regulated, particularly up-regulation of proliferation Genes A and B and down-

regulation of apoptosis Gene D. Perhaps, the differences in gene expression in sham-

operated animals can also be explained by testing error or biological variability

34

(Juskeviciute, Vadigepalli, and Hoek 2008). All three sham animals did not always

express the same level of gene expression within the pre-set threshold limits, but were

relatively close and so may be due to the biological variability.

Pathway Analysis

The pathways shown in Figure 4 are the pathway maps for the pathway ranked

first for both studies. They represent a process in the cell cycle in which the DNA

replication transition is controlled. The four genes from the proliferation TaqCard that

function in this pathway include Genes C, K, N, and U, as shown in Table 9. These genes

were also a subset of the genes that expressed up-regulation on the TaqCard from the

proliferation and proliferation (other) categories. For Study 1, shown in Figure 4A, Gene

C appears to increase in rat #3, but then decreases again in rat #4, showing that the

greatest change in this gene occurs 7-11 days post hepatectomy. In genes K, N, and U,

there is a slight increase over time for rats #1-4. For Study 2, shown in Figure 4B, these

are replicates, but are showing some variability. Gene K is noted twice since GeneGo

MetaCore analysis represents the potential for different mRNA isoforms of this gene.

This pathway involves the control of DNA replication and whether the cell cycle

progresses from G1 to the S phase. In general, these four genes are involved in DNA

synthesis of the leading strand and Okazaki fragments, relaxation of the supercoiled

DNA, and control of phosphorylation of DNA polymerases. These genes overlapped and

appeared in other top ranked pathways, as shown in Table 9. Gene C is also involved in

the pathways of thrombopoietin-regulated cell processes, chromosome condensation in

prometaphase, the role of APC in cell cycle regulation, and ESR1 regulation of the G1/S

transition. Gene K is involved in the chromosome condensation in prometaphase. Gene N

35

is involved in the pathways of thrombopoietin-regulated cell processes and ESR1

regulation of the G1/S transition. Gene U is involved in the pathways of chromosome

condensation in prometaphase and the role of APC in cell regulation (2000).

36

Figure 4. Study 1(A) and Study 2 (B) proliferation pathway maps that represent a process in the cell cycle: transition and termination of DNA replication. (See Appendix 2 for pathway description.)

37


second for both studies. They represent a process in the cell cycle of thrombopoietin-

regulated cell processes. The five genes from the proliferation TaqCard that function in

this pathway include Genes B, C, N, O, and P. These genes were also a subset of the

genes that expressed up-regulation on the TaqCard from the proliferation and

proliferation (other) categories. For Study 1, shown in Figure 5A, all genes seem

relatively consistent across rats #1-4. For Study 2, shown in Figure 5B, all these are

replicates and are again relatively consistent.

This pathway involves processes regulated by thrombopoietin, a hormone

produced by the liver involved in biological effects on a broad spectrum of hematopoietic

progenitor cells. In general, these five genes are involved in regulation of the cell cycle

and the anti-apoptotic processes. Some of these genes also overlapped and appeared in

other top ranked pathways, as shown in Table 9. Genes N, O, and P are also involved in

ESR1 regulation of the G1/S transition (2000).

38

Figure 5. Study 1 (A) and Study 2 (B) proliferation pathway map that represents a process in the development: thrombopoietin-regulated cell processes. (See Appendix 3 for pathway description.)

39

40

The pathways shown in Figure 6 are the pathway maps for the pathway ranked third

for both studies. They represent a process in the cell cycle in which chromosome

condensation in prometaphase occurs. The four genes from the proliferation TaqCard that

function in this pathway include Genes A, C, K, and U, as shown in Table 9. These genes

were also a subset of the genes that expressed up-regulation on the TaqCard from the

proliferation and proliferation (other) categories. For Study 1, shown in Figure 6A, all

genes were relatively consistent across rats #1-4. For Study 2, shown in Figure 6B, all

these are replicates and are again relatively consistent.

This pathway involves the process of chromosome condensation. In general, these

four genes are involved in activation of the condensing complex, binding of histone H3,

and phosphorylation of Ser10. One of these genes, Gene U, as shown in Table 9, also

overlapped and appeared in another top ranked pathway, the role of APC in cell cycle

regulation (2000).

Figure 6. Study 1 (A) and Study 2 (B) proliferation pathway map that represents a process in the cell cycle: chromosome condensation in prometaphase. (See Appendix 4 for pathway description.)

41

42


fourth for both studies. They represent a process involving the role of APC in cell cycle

regulation. The four genes from the proliferation TaqCard that function in this pathway

include Genes A, C, F, and U, as shown in Table 9. These genes were also a subset of the

genes that expressed up-regulation on the TaqCard from the proliferation and

proliferation (other) categories. For Study 1, shown in Figure 7A, all genes were

relatively consistent across rats #1-4. For Study 2, shown in Figure 7B, all these are

replicates and again are relatively consistent.

This pathway involves degradation of different regulatory proteins in the

ubiquitin-dependent pathway. Generally, these four genes are involved in

phosphorylation of APC, degradation, and mitotic spindle assembly checkpoints (2000).

Figure 7. Study 1 (A) and Study 2 (B) proliferation pathway map that represents a process in the cell cycle: role of APC in cell cycle regulation. (See Appendix 5 for pathway description.)

43

The pathways shown in Figure 8 are the pathway maps for the pathway ranked as

fifth for both studies. They represent a process in the cell cycle of ESR1 regulation of

G1/S transition. These four genes from the proliferation TaqCard that function in this

pathway include Genes C, N, O and P, as shown in Table 9. Gene P is noted twice since

GeneGo Metacore analysis represents the potential for different mRNA isoforms of this

gene. These genes were also a subset of the genes that expressed up-regulation on the

TaqCard from the proliferation and proliferation (other) categories. For Study 1, shown in

Figure 8A, all genes were relatively consistent across rats #1-4. For Study 2, shown in

Figure 8B, all these are replicates and again are relatively consistent except for Gene C,

rat #1.

This pathway involves estradiol and the process of inducing proliferation of

estrogen receptor-positive cells. In general, these four genes are proto-oncogenes and

transcription factors that are involved in the G1/S transition of the mitotic cell cycle

(2000).

44

Figure 8. Study 1(A) and 2 (B) proliferation pathway maps that represents a process in the cell cycle: ESR1 regulation of G1/S transition. (See Appendix 6 for pathway description.)

45

Concluding Remarks

Though the partial hepatectomy method is widely used to study liver regeneration,

these studies are unique in that we can compare a subset of this signature to liver

signatures from animals that succumbed to DILI. Expectedly, we discovered that results

from our surgical model did exhibit similar proliferative gene responses as a previous

DILI data set, but an absence of proliferation features in histomorphology. Differential

kinetics could explain the difference between gene expression and histological changes.

While both the processes of liver regeneration and DILI are complex, the histologic

findings in DILI can reflect multiple pathological processes (Ennulat et al. 2010). The

surgical partial hepatectomy model is a potential alternative model to DILI studies for

studying liver regeneration in the absence of other findings. Additional biomarkers of

liver cell populations showed no apparent changes in this study. As we expected,

apoptosis pathway changes were not robustly induced and, therefore, was effective as a

"specificity" check. By assessing mechanistic transcriptomic biomarkers in samples from

different manifestations of liver injury, we can establish the underlying biological

processes that impact susceptibility to DILI. Using rat gene expression data to assess

potential DILI will lead to developing a valid and more sensitive model for preclinical

safety.

Further studies are needed to continue adding to our knowledge of gene

transcription networks in restoration of liver mass. In particular, studies that further

investigate liver cell population and proliferation biomarkers at earlier time-points would

be helpful to study the variation between the cell types during liver regeneration. Other

pathways, besides apoptosis, of the rat liver can be studied for additional biomarker

46

changes. Since our samples were taken at a later phase in liver regeneration, it would also

be helpful to use time-points that capture the changes and processes occurring at time of

termination of liver regeneration to understand how the processes cease as well as

progress.

47

APPENDIX 1: GeneGo MetaCore Analysis Key Legend.

APPENDIX 2: Cell cycle: Transition and termination of DNA replication pathway description. DNA replication begins in early S phase. DNA polymerase alpha/primase synthesizes

RNA/DNA hybrid on the newly unwound DNA. The two parental strands are replicated

differently due to the anti-parallel nature of DNA. The leading strand is replicated

continuously by DNA polymerase alpha/primase and delta, while the lagging strand is

replicated discontinuously. As the helicase unwinds DNA, DNA polymerase

alpha/primase and delta synthesize the Okazaki fragments which are matured by

removal of the RNA primers and connected by DNA ligase I. The topology of a DNA

48

molecule changes as it is unwound by topoisomerases. Termination occurs when two

opposing replication forks meet and the nascent DNA from the two forks is ligated

together. Reduplication of DNA is completed in late S phase (2000).

APPENDIX 3: Development: Thrombopoietin-regulated cell processes pathway description. Thrombopoietin is a hormone involved in biological effects on a broad spectrum of

hematopoietic progenitor cells. It supports stem cell survival/expansion and is a key

physiological regulator of steady-state megakaryocytopoiesis. Thrombopoietin is

produced by the liver, kidney, marrow stroma and other tissues. Binding of

Thrombopoietin with its receptor Myeloproliferative leukemia virus oncogene (c-Mpl)

leads to receptor homodimerization and subsequent activation of Janus kinase 2 (JAK2).

inducing phosphorylation of Myeloproliferative leukemia virus oncogene (c-Mpl) itself

and recruitment of signaling proteins to the receptor. Activation of H-Ras is followed by

recruitment of V-raf-1 murine leukemia viral oncogene homolog 1 (c-Raf-1) and

activation of Mitogen-activated protein kinase kinase (MEK) and Mitogen-activated

protein kinase (Erk). Furthermore, Thrombopoietin stimulation leads to an activation of

Phosphoinositide-3-kinase (PI3K) pathway (2000).

APPENDIX 4: Cell cycle: Chromosome condensation in prometaphase pathway description. Chromosome condensation is a highly ordered process in which the two sister chromatids

are sorted out and compacted. Condensin complex is one of the most abundant

components of mitotic chromosome condensation distributed throughout the chromosome

arms. The complex consists of two structural maintenance of chromosomes (SMC)

49

subunits and three non-SMC subunits. Condensin complex gains the ability to introduce

positive supercoils into DNA. The two critical steps in cell reproduction are

to duplicate the DNA content of chromosomes and to segregate them into two daughter

cells. The linkage between duplicated chromosomes is established during S phase

(cohesion), it persists during their dramatic structural changes in prometaphase

(condensation), and is finally dissolved at the metaphase- anaphase transition

(separation). Condensin complex also converts the form of nicked circular DNA.

Condensin complex is co-localized with phosphorylated Histone H3 during the early

stage of the mitotic chromosome condensation (2000).

APPENDIX 5: Cell cycle: Role of APC in cell cycle regulation pathway description.

Cell division progression is governed by degradation of different regulatory proteins in

the ubiquitin-dependent pathway. In this pathway, a polyubiquitin chain gets attached to a

protein substrate by an ubiquitin-ligase, which targets it for degradation by the 26S

proteasome. Anaphase-promoting complex (APC) is a one of ubiquitin ligases, which

plays a key role in the cell APC is mainly required to induce progression and exit from

mitosis by inducing proteolysis of different cell cycle regulators. Phosphorylation of APC

is one of the mechanisms used by the cell to modulate APC. APC also induces

degradation of several factors that are essential for spindle-pole separation and spindle

disassembly. Three different APC substrates control DNA replication: ORC1, CDC18L,

and Geminin. This control is carried out by formation of the prereplication complex at the

replication origins during S phase (2000).

50

APPENDIX 6: Cell cycle: ESR1 regulation of the G1/S transition pathway description. Estradiol induces proliferation of estrogen receptor-positive cells. ESR1 (nuclear)

activated by Estradiol acts like as ligand-dependent transcription factor and promotes

G1/S transition through several pathways. First, ESR1 (nuclear) activates transcription of

Cyclin D1 by a variety mechanisms. ESR1 (nuclear) can activate transcription of Cyclin

D1 acting as co-activator c-Jun/ c-Fos or regulate transcription of c-Jun and c-Fos. ESR1

(nuclear) may also activate transcription of Cyclin D1, allowing Cyclin D1 to bind ESR1

(nuclear) and activate transcription of ESR1 (nuclear) -responsible genes including its

own gene (2000).

51

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Investigate gene expression responses of a regenerative