ALTERATIONS OF MICRORNA EXPRESSION PATTERNS IN

HUMAN CERVICAL CARCINOMA CELLS (CA SKI) TOWARDS

1’S-1’-ACETOXYCHAVICOL ACETATE (ACA) AND

CISPLATIN (CDDP)

PHUAH NEOH HUN

FACULTY OF SCIENCE

UNIVERSITY OF MALAYA

KUALA LUMPUR

2012

ALTERATIONS OF MICRORNA EXPRESSION

PATTERNS IN HUMAN CERVICAL CARCINOMA

CELLS (CA SKI) TOWARDS

1’S-1’-ACETOXYCHAVICOL ACETATE (ACA)

AND CISPLATIN (CDDP)

PHUAH NEOH HUN

DISSERTATION SUBMITTED IN FULFILLMENT OF

THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE

INSTITUTE OF BIOLOGICAL SCIENCES

FACULTY OF SCIENCE

UNIVERSITY OF MALAYA

KUALA LUMPUR

2012

ii

ABSTRACT

The main aims of this study were to investigate the combined effects of a natural

compound 1’S-1’-acetoxychavicol acetate (ACA) with cisplatin (CDDP) on human

cervical carcinoma cells Ca Ski, and to identify microRNAs (miRNAs) asscociated with

response towards ACA and/or CDDP. Data obtained from MTT cell viability assays

indicated that both ACA and CDDP induced dose- and time-dependent cytotoxicity on

Ca Ski cells when used as a standalone agent. The in vitro studies also demonstrated

that ACA potentiates the cytotoxic effects of CDDP when used in combination through

synergistic interactions. The miRNA microarray was used to identify global miRNA

expression profiles on Ca Ski cells following administration of ACA and/or CDDP, and

it was found that 25 miRNAs were differentially expressed in response towards ACA

and/or CDDP with markedly different pattern of miRNA expressions between different

treatment regimens. Three promising miRNA candidates (hsa-miR-138, hsa-miR-210

and hsa-miR-744) which exhibited the highest fold-change in combination

chemotherapy and whose expressions were among those validated by qRT-PCR, were

selected for bioinformatic analyses. The hypothetical pathway model comprising

interaction between candidate miRNAs with their putative target genes indicated that

the cytotoxic effects induced by ACA in combination with CDDP may be regulated by

miRNA expression. Therefore, our study provides a platform for potential therapeutic

approaches in chemotherapy, whereby miRNA expression can be exploited to further

improve efficacy in combination chemotherapy.

iii

ABSTRAK

Tujuan utama penyelidikan ini adalah untuk menyiasat kesan gabungan

kompaun semulajadi 1’S-1’-acetoxychavicol acetate (ACA) dengan cisplatin (CDDP)

ke atas sel-sel karsinoma serviks manusia Ca Ski, serta mengenal pasti miRNA yang

bertindak balas terhadap rawatan ACA dan/atau CDDP. Data yang diperolehi daripada

eksperimen MTT menunjukkan bahawa ACA dan CDDP menyebabkan sitotosik yang

bergantung pada dos dan tempoh rawatan apabila digunakan sebagai ejen ‘standalone’.

Selain itu, kajian in vitro juga menunjukkan bahawa ACA mempotensikan kesan

sitotoksik CDDP melalui hubungan sinergistik apabila digabungkan. MiRNA

microarray digunakan untuk mengenal pasti profil ekspresi global miRNA setelah

dirawat dengan ACA dan/atau CDDP, dan didapati bahawa terdapat sebanyak 25

miRNA yang diekspreskan secara berlainan apabila dirawat dengan ACA dan/atau

CDDP dengan corak ekspresi miRNA yang berbeza antara regimen rawatan yang

berlainan. Tiga calon miRNA yang menjanjikan (hsa-miR-138, hsa-miR-210 and hsa-

miR-744), yang merupakan antara beberapa miRNA yang disahkan ekspresinya dengan

qRT-PCR, dipilih untuk analisis bioinformatik kerana mereka mempamerkan ‘fold-

change’ yang paling tinggi dalam kemoterapi kombinasi. ‘Hypothetical pathway model’

yang melibatkan interaksi miRNA dengan target gen putatif miRNA menunjukkan

bahawa kesan-kesan sitotoksik yang ditunjukkan oleh ACA dan/atau CDDP

berkemungkinan besar disebabkan oleh ekspresi miRNA. Maka, kajian kami

menyediakan satu platform bagi pendekatan terapeutik dalam kemoterapi, dimana

ekspresi miRNA boleh dimanipulasikan untuk meningkatkan efikasi dalam kemoterapi

kombinasi.

iv

ACKNOWLEDGEMENT

First of all, I would like to express my deepest appreciation to my project

supervisor, Associate Professor Dr. Noor Hasima Nagoor, for her support and guidance

in helping me to complete my project successfully.

I am indebted to Dr. Lionel In Lian Aun for his willingness to share his vast

expertise and knowledge with me. I am also thankful to my fellow lab mates from

Cancer Research Laboratory in BGM2 for lending me a helping hand whenever needed,

and also in making this an invaluable experience for me.

I am grateful to Professor Dr. Khalijah Awang and Mr. Mohamad Nurul Azmi

from Centre for Natural Product Research and Drug Discovery (CENAR) for providing

1’S-1’-acetoxychavicol acetate (ACA), without which this research project would not

possible. Special thanks to Oral Cancer Research and Coordinating Centre (OCRCC)

for allowing me to use their software to analyze my microRNA microarray results.

I would like to acknowledge and thank University of Malaya for their generosity

in financing this research project through University of Malaya Postgraduate Research

Grant (PPP) (PS240-2009C and PV044-2011B) and University of Malaya Research

Grant (UMRG) (RG037-10BIO). I am also grateful to University of Malaya for

sponsoring my studies through the University of Malaya Fellowship Scheme.

Last but not least, I would also like to thank my family and friends for their

constant love, care and support throughout this duration as well as everyone else who

has played a part in completion of this research project.

v

TABLE OF CONTENTS

Page No.

Abstract ii

Abstrak iii

Acknowledgement iv

Table of contents v

List of Figures ix

List of Tables ix

List of Abbreviations xii

Chapter 1: Introduction 1

1.1 Study objectives 4

Chapter 2: Literature review 5

2.1 Cancer

2.1.1 Overview 5

2.1.2 Multistep carcinogenesis 6

2.2 Cervical cancer

2.2.1 Overview 8

2.2.2 Cervical cancer subtypes 8

2.2.3 Etiology of cervical cancers 9

2.2.4 Cervical carcinogenesis 10

2.2.5 Grading in cervical cancer 11

2.2.6 Staging of cervical cancer 11

2.2.7 Epidemiology in cervical cancer 12

2.2.8 Human epidermoid cervical carcinoma Ca Ski 13

vi

2.3 Cell cycle

2.3.1 Overview 14

2.3.2 Cell cycle regulation 14

2.3.3 Cell cycle and cancer 17

2.4 Cell death

2.4.1 Overview 19

2.4.2 Apoptosis 19

2.4.3 Apoptosis and cancer 21

2.5 Chemotherapy

2.5.1 Overview 23

2.5.2 Drug resistance 24

2.5.3 Combination therapy 25

2.5.4 Combination analysis 26

2.5.5 Cisplatin 28

2.6 Natural compounds as anti-cancer agents

2.6.1 Overview 30

2.6.2 Plant derived anti-cancer agents 30

2.6.3 1’S-1’-acetoxychavicol acetate 31

2.7 MicroRNAs

2.7.1 Overview 33

2.7.2 Naming conventions for miRNAs 34

2.7.3 Biogenesis of miRNAs 35

2.7.4 MiRNAs and chemotherapy 37

Chapter 3: Materials and methods 38

3.1 1’S-1’-acetoxychavicol acetate (ACA) and cisplatin (CDDP)

3.1.1 1’S-1’-acetoxychavicol acetate (ACA) 38

3.1.2 Cisplatin (CDDP) 38

vii

3.2 Cell cultures

3.2.1 Cell lines and culture conditions 39

3.2.2 Subculturing monolayer cell lines 38

3.2.3 Cryopreservtion of cell lines 40

3.2.4 Thawing of cryopreserved cell lines 41

3.2.5 Cell count 41

3.3 MTT cell viability assays 42

3.4 Total RNA extraction and quality control

3.4.1 Total RNA extraction 43

3.4.2 RNA quality control

3.4.2.1 RNA analysis using UV spectrophotometry 44

3.4.2.2 RNA analysis using Agilent RNA 6000 Nano Kit 45

3.5 MiRNA microarray

3.5.1 FlashTag™

RNA labeling 46

3.5.2 ELOSA quality control assays 47

3.5.3 Hybridization of Affymetrix arrays 48

3.5.4 Washing and staining of Affymetrix arrays 49

3.5.5 Statistical and miRNA expression analysis 49

3.6 Validation of miRNA microarray data

3.6.1 Reverse transcription PCR 50

3.6.2 Real-time PCR amplification and quantitation 50

3.7 Bioinformatic analyses of miRNA gene targets 51

3.8 Statistical analysis 51

Chapter 4: Results 52

4.1 Cytotoxicity assays

4.1.1 Cytotoxic effects of ACA and CDDP on Ca Ski cells 52

4.1.2 Cytotoxic effects of ACA in combination with CDDP on Ca Ski cells 53

viii

4.2 Combination analysis 56

4.3 Normal cells and solvent control

4.3.1 Cytotoxic effects of ACA and CDDP on normal cells 58

4.3.2 Cytotoxic effects of DMSO on various cell lines 60

4.4 RNA quality control 61

4.5 MiRNA expression on Ca Ski cells

4.5.1 MiRNA microarray 62

4.5.2 Validation by qRT-PCR 63

4.5.3 Correlation between miRNA microarray data and qRT-PCR data 65

4.6 Bioinformatic analyses of miRNA gene targets 65

Chapter 5: Discussion 67

5.1 Cytotoxic effects of ACA and/or CDDP 67

5.2 Alterations in miRNAs expression patterns by ACA and/or CDDP 69

5.3 Interaction between candidate miRNAs with their putative target genes 71

5.4 Future research 76

Chapter 6: Conclusion 77

References 78

Appendices 99

Appendix 1: Solutions, formulations and commercial kits 99

Appendix 2: MTT assays on Ca Ski cells for standalone ACA 102

Appendix 3: MTT assays on Ca Ski cells for standalone CDDP 103

Appendix 4: MTT assays on Ca Ski cells for ACA in combination with CDDP 104

Appendix 5: MTT assays on NP69 cells for standalone ACA 105

Appendix 6: MTT assays on NP69 cells for standalone CDDP 105

Appendix 7: MTT assays on NP69 cells for ACA in combination with CDDP 105

Appendix 8: Predicted gene targets using TargetScanHuman v5.2 106

ix

LIST OF FIGURES

Page No.

Figure 2.1 Comparison between cell division in normal cells and cancer

cells

6

Figure 2.2 Multistep carcinogenesis 7

Figure 2.3 Cervical carcinogenesis 10

Figure 2.4 Cell cycle regulation 15

Figure 2.5 Apoptotic pathways 21

Figure 2.6 Mechanisms of drug resistance in cancer cells 25

Figure 2.7 Chemical structure of cisplatin (CDDP) 28

Figure 2.8 Chemical structure of 1’S-1’-acetoxychavicol acetate (ACA) 31

Figure 2.9 Biogenesis of microRNAs 36

Figure 3.1 Chemical structure of 1’S-1’-acetoxychavicol acetate (ACA) 38

Figure 3.2 Chemical structure of cisplatin (CDDP) 38

Figure 4.1 Comparative dose-response curve for standalone ACA on Ca

Ski cells at various concentrations and incubation hours

53

Figure 4.2 Comparative dose-response curve for standalone CDDP on Ca

Ski cells at various concentrations and incubation hours

53

Figure 4.3 Comparative dose-response curve for ACA and CDDP on Ca

Ski cells for different combinations following 24 h exposure

55

Figure 4.4 Isobologram analysis of ACA in combination with CDDP 57

Figure 4.5 Comparative dose-response curve at various concentrations of

standalone ACA (0 - 12.0 µM) and CDDP (0 - 200.0 µM) on

NP69 cells following 24 h exposure.

59

Figure 4.6 Comparative dose-response curve for ACA in combination

with CDDP on NP69 cells following 24 h exposure

59

x

Figure 4.7 Cytotoxic effects of DMSO at 1.2% (v/v) on Ca Ski and NP69

cells following 24 h exposure

60

Figure 4.8 Normalized fold expression for hsa-miR-138, hsa-miR-210,

hsa-miR-224 and hsa-miR-744

64

Figure 4.9 Correlation between miRNA microarray data and qRT-PCR

data

65

Figure 4.10 Pathway model comprising of interaction between candidate

miRNAs with their putative target genes

66

xi

LIST OF TABLES

Page No.

Table 2.1 FIGO staging of cervical carcinomas 12

Table 2.2 Cyclin-dependent kinase inhibitor (CKI) proteins 16

Table 3.1 Summary of experimental setup used in this study indicating

treatment groups with biological replicates

44

Table 3.2 Setup for FlashTag™

RNA labeling 46

Table 3.3 Setup for hybridization solution for ELOSA quality control

assays

48

Table 3.4 Setup for array hybridization cocktail 48

Table 3.5 Summary of washing and staining protocol for each array 49

Table 3.6 PCR setup for reverse transcription PCR 50

Table 3.7 PCR setup for real-time PCR amplification and quantitation 51

Table 4.1 Summary of combination regimens employed for MTT cell

viability assay to evaluate the combined effects of ACA and

CDDP on Ca Ski cells.

55

Table 4.2 Summary of IC50 values for standalone ACA, standalone

CDDP and ACA in combination with CDDP at various

concentrations following 24 h exposure

56

Table 4.3 Combination index analysis of ACA in combination with

CDDP

58

Table 4.4 RNA analysis using UV spectrophotometry 61

Table 4.5 RNA analysis using Agilent RNA 6000 Nano Kit 62

Table 4.6 List of miRNA expression fold-change alterations following the

administration of ACA and/or CDDP on Ca Ski cells over 2 h

63

xii

LIST OF ABBREVIATIONS

3’ UTR Three prime untranslated region

5’ UTR Five prime untranslated region

% Percentage

× Times

°C Degree Celsius

µ Micro

µg Microgram

µg/ml Microgram per militre

µl Microlitre

µM Micromolar

® Registered

(v/v) Volume per volume

(w/v) Weight per volume

A Absorbance

ASR Age-standardized incidence rate

ATP Adenosine triphosphate

Bfl-1/A1 Bcl-2-related protein A1

ACA 1’S-1’-acetoxychavicol acetate

AIF Apoptosis inducing factor

Apaf-1 Apoptotic protease-activating factor-1

ATM Ataxia-telangiectasia-mutated

Bad Bcl-2-agonist death promoter

Bax Bcl-2 associated X protein

Bcl-2 B-cell lymphoma 2

xiii

Bcl-xL B-cell lymphoma-extra large

bp Base pairs

BSA Bovine serum albumin

cAMP Cyclic adenosine monophosphate

CARIF Cancer Research Initiative Foundation

Caspase Cysteine aspartate protease

CaV Voltage-gated calcium channels

CBP CREB-binding protein

CDC Cell-division cycle

CDDP Cisplatin

CDK Cyclin-dependent kinase

cDNA Complimentary deoxyribonucleic acid

CI Combination index

CIN Cervical intraepithelial neoplasia

CKI Cyclin-dependent kinase inhibitor

cm Centimeter

cm2 Centimeter square

CO2 Carbon dioxide

CREB cAMP response element-binding

DAVID Database for Annotation, Visualization and Integrated Discovery

DEPC Diethylpyrocarbonate

dH20 Distilled water

DISC Death-inducing signaling complex

DMEM Dulbecco’s Modified Eagle Medium

DMSO Dimetyl sulfoxide

DNA Deoxyribonucleic acid

xiv

DNase Deoxyribonuclease

dNTP Deoxy-nucleoside-triphosphate

DR Death receptor

Dsh Dishevelled

EDTA Ethylenediaminetetraacetic acid

ELOSA Enzyme Linked Oligosorbent Assay

ERK Extracellular signal-regulated protein kinase

et al And others

FADD Fas-associated death domain

FAK Focal adhesion kinase

FDA Food and Drug Administration

FBS Fetal bovine serum

FIGO Fédération of Internationale de Gynécologic et d’Obstétrique

FLIP FLICE-like inhibitory protein

Fzd Frizzled

g Gravity

g Gram

GSH Glutathione

h Hour

hCG Human chorionic gonadotropin

HCl Hydrochloric acid

HIF Hypoxia-inducible factor

HPV Human papillomavirus

HSV-2 Herpes simplex virus-2

IACR International Agency for Research on Cancer

IAP Inhibitor of apoptotic protein

xv

IC50 50% inhibitory concentration

ICO Institut Català d'Oncologia

IGF Insulin growth factor

IKK IκB kinase

IL-3 Interleukin-3

Inc. Incorporated

JNK c-Jun N-terminal kinases

kDA Kilo Dalton

KEGG Kyoto Encyclopedia of Genes and Genomes

kg Kilogram

KSFM Keratinocyte serum-free medium

LEF Lymphoid enhancer factor

M Molar

MAPK Mitogen-activated protein kinase

MEK MAPK kinase

mg Milligram

mg/ml Milligram per millitre

MgCl2 Magnesium chloride

min Minute

miRNA Micro ribonucleic acid

ml Milliliter

mm Millimetre

mM Millimolar

MnCl2 Manganese chloride

mRNA Messenger ribonucleic acid

MPT Mitochondrial permeability transition

xvi

MTT 3-(4,5-dimethylthiazol-2-γl)-2,5-diphenyl-tetrazoliumbromide

NCI National Cancer Institute

NCR National Cancer Registry

NCX Sodium-calcium exchanger

NF-κB Nuclear factor kappa B

ng Nanogram

nm Nanometer

nM Nanomolar

p53 Protein 53

Pap Papanicolaou

PBS Phosphate buffered saline

PDGF Platelet-derived growth factor

PDGFR Platelet-derived growth factor receptor

pH Potential of hydrogen

PI3K Phosphoinositide 3-kinase

PMCA Plasma membrane Ca2+ ATPase

pRb Retinoblastoma protein

psi Pound force per square inch

r Pearson correlation coefficient

RIN RNA Integrity Number

RIP Receptor interacting protein

RISC RNA-induced silencing complex

RMA Robust Multichip Average

RNA Ribonucleic acid

RNase Ribonuclease

ROC Receptor-operated calcium channels

xvii

rpm Revolutions per minute

rRNA Ribosomal ribonucleic acid

S Svedberg

s Second

SA-HRP Streptavidin-horseradish peroxidase

SD Standard deviation

SDS Sodium dodecyl sulfate

SOS Son of sevenless

SSC Saline sodium citrate

TCF T-cell factor

TGF-β Transforming growth factor-β

™ Trademark

TMB 3,3′,5,5′-Tetramethylbenzidine

TNF Tumor necrosis factor

TNFR Tumor necrosis factor receptor

TRADD Tumor necrosis factor receptor associated death domain

TRAF2 Tumor necrosis factor receptor-associated factor 2

U Unit

USA United States of America

UV Ultraviolet

WHO World Health Organization

WNT Wingless-type MMTV integration site family