Analysis of gene expression in normal and neoplastic keratinocytes

(1)

ANALYSIS OF GENE EXPRESSION IN NORMAL

AND NEOPLASTIC KERATINOCYTES

RYAN O’SHAUGHNESSY

UNIVERSITY COLLEGE LONDON

AND

IMPERIAL CANCER RESEARCH FUND

Thesis presented for the degree of

Doctor of Philosophy

In the University of London

September 2000

Internal Supervisor: Dr Fiona M Watt

(2)

ProQuest Number: U643597

INFORMATION TO ALL USERS

The quality of this reproduction is dependent upon the quality of the copy submitted.

In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed,

a note will indicate the deletion.

uest.

ProQuest U643597

Published by ProQuest LLC(2016). Copyright of the Dissertation is held by the Author.

This work is protected against unauthorized copying under Title 17, United States Code. Microform Edition © ProQuest LLC.

ProQuest LLC

789 East Eisenhower Parkway P.O. Box 1346

(3)

Abstract

The epidermis is a constantly renewing tissue. Cells in the basal layer of the epidermis

terminally differentiate and are shed as dead squames. The cells responsible for

controlling this constant renewal are known as stem cells. Alterations of these stem cells

can lead to neoplasms such as basal cell carcinoma. I used differential hybridisation, a

technique that allows the analysis of changes in expression of a large number of genes

simultaneously, to find differences in gene expression between basal cell carcinoma

tissue and normal skin. Two genes, MRP-14 and 8, were found to be upregulated in basal

cell carcinoma. Consistent with the link between expression of these genes and

hyperplasia, the epidermis over the basal cell carcinoma expressed high levels of these

genes.

Improvements I made in the differential hybridisation method allowed elucidation of the

differences between stem cells and cells with lower proliferative potential in vitro.

Careful analysis revealed no changes in gene expression greater then two fold. One gene,

the epidermal fatty acid binding protein, E-FABP, showed higher levels in transit cells.

Antibody studies revealed E-FABP expression is reduced in the regions of the epidermis

thought to house the stem cells.

Finally the expression of a potential marker of stem cells, the melanoma specific

chondroitin proteoglycan, MCSP, was examined in vitro and in vivo. Antibody studies

revealed expression of the protein only above the dermal papillae of cross sections of

epidermis. Fluorescence activated cell sorting revealed a population of basal

kératinocytes that are both MS CP positive and express high levels of the (31 integrin, a

(4)

Chapter 1 Introduction

1.1 Overview 18

1.2 Differential Gene Expression analyses 18

1.2.1 A Brief History of Arrays 19

1.2.2 Performing an Array Hybridisation 21

1.2.3 Analysis of Differential Hybridisation Data 25

1.2.4 Confirmation of Differential Gene Expression 27

1.2.5 Other Methods of Determining Differential Gene Expression 27

1.2.6 Towards Functional Genomics - The Future of Array Hybridisation 30

1.3 The Epidermis 31

1.3.1 The Basal Layer, Basement Membrane and Integrins 33

1.3.2 The Spinous Layer 34

1.3.3 The Granular Layer 34

1.3.4 The Comified Layer 34

1.4 Two Cancers of the Epidermis: BCC and SCC 35

1.4.1 Basal Cell Carcinoma 35

1.4.2 Genetic Predispositions to BCC 37

1.4.3 Squamous Cell Carcinoma 39

1.5 Keratinocyte Stem Cells 42

(5)

1.5.3 Other Integrins as Stem Cell Markers 45

1.5.4 Other Potential Markers of Stem Cells 46

1.5.5 Stem Cell Patterning 48

1.5.6 Whole Mount Staining of Human Epidermis 49

1.5.7 Control of Stem Cell Fate 49

1.6 Aims 55

Chapter 2 Materials and Methods

2.1 Molecular Biology 56

2.1.1 Materials and Solutions 56

2.1.2 Agarose Gel Electrophoresis 59

2.1.3 Vectors, Plasmid Preparation and Restriction digestion 59

2.1.4 Subcloning Techniques 59

2.1.5 Transformation of Plasmid DNA 60

2.1.6 Sequencing 60

2.1.7 Southern Blotting and Hybridisation 60

2.1.8 Northern Blotting and Hybridisation 62

2.1.9 RT-PCR 63

2.1.10 In Situ Hybridisation 64

2.2 Differential Hybridisation 65

2.2.1 Arrayed cDNA Library Filters 65

2.2.2 Hybridisation of Arrayed Keratinocyte Filters 65

2.2.3 Hybridisation of Arrayed Unigene Filters 66

2.3 Cell Culture 67

2.3.2 General Culture Conditions 69

2.3.3 Freezing and Thawing of Cell Stocks 69

2.3.4 Culture of J2-3T3 and J2-puro 70

(6)

2.3.7 Clonogenicity Assays 72

2.4 Immunostaining 74

2.4.2 Antibodies 75

2.4.3 Immunofluorescence Staining of Frozen Sections 76

2.4.4 Immunohistochemical Staining of Paraffin Sections 77

2.4.5 Immunofluorescence Staining of Cultured Kératinocytes 77

2.4.6 BrdU Incorporation and Nuclear counterstaining 78

2.4.7 Immunostaining of Wholemount Epidermis 78

2.5 Flow Cytometry 80

2.5.2 FACS Analysis of MCSP and pi Integrin 80

2.5.3 FACS Analysis of E-FABP 80

2.5.4 Sorting of Producer Cells and Kératinocytes Expressing GFP 81

2.5.5 Sorting to Enrich for Stem and Transit Amplifying Cells 81

2.5.6 Staining and Sorting of kératinocytes expressing pi Integrin and MCSP 81

2.6 SDS-PAGE Electrophoresis and Western Blotting 83

2.6.2 Preparation of SDS-PAGE gels 84

2.6.3 Extraction of Triton Soluble Proteins and Measurement of Protein

Concentration 85

2.6.4 SDS-PAGE Electrophoresis 85

2.6.5 Western Blotting 86

Chapter 3 Detection of differentially expressed genes in Basal Cell

Carcinoma and Skin samples

3.1 Introduction 87

(7)

3.4 Evaluation of the Hybridisations 89

3.5 Determination of Differentially Expressed Genes 90

3.6 MRP-8 and MRP-14 mRNA are Overexpressed in BCC Samples 93

3.7 Expression of MRP-14 protein in Epithélia and Cultured Kératinocytes 93

3.8 Distribution of MRP-8 and MRP-14 Transcripts 94

3.9 Discussion 95

Chapter 4 The Epidermal Fatty Acid Binding Protein, a Novel Transit

Amplifying Cell Marker Revealed by cDNA Array Hybridisation

4.1 Introduction 107

4.2 Unigene Filter Construction 107

4.3 Differential Hybridisation 108

4.4 Results of the Differential Hybridisation 109

4.5 Expression of E-FABP in Other Tissues, Epidermis and

Cultured Kératinocytes 111

4.6 Construction of Producer Cells Overexpressing E-FABP 113

4.7 Analysis of Kératinocytes Overexpressing E-FABP 114

4.8 Discussion 115

Chapter 5 The Melanoma Chondroitin Sulphate Proteoglycan, A

Potential Stem Cell Marker in Human Epidermis

5.1 Introduction 128

5.2 Structure and Possible Functions 128

5.3 Expression of MCSP m v/vo 129

5.4 Expression of MCSP in Cultured Kératinocytes and WholeMount

Epidermis 130

5.5 FACS Analyses of MCSP expression 131

5.6 Clonogenic Properties of MCSP Positive Cells 131

(8)

Chapter 6 Final Discussion

6.1 Markers of BCC and Stem Cells 143

6.2 Activation of the Hedgehog Pathway in BCC Formation 143

6.3 Limitations of Differential Hybridisations on Arrays 144

6.4 Further Work 145

6.5 The Future 148

(9)

List of Figures

Figure 1.1 Differential hybridisation experiments 23

Figure 1.2 Histogram and scatter plot 26

Figure 1.3 The human epidermis 32

Figure 1.4 BCC and SCC 36

Figure 1.5 The patched pathway in humans 38

Figure 1.6 Populations of the interfollicular keratinocyte lineage 43

Figure 1.7 Stem and transit amplifying cell markers 47

Figure 1.8 Stem cell patterning in the epidermis 50

Figure 1.9 Factors that determine stem cell fate 54

Figure 3.1 Overview of the Xdigitise program 98

Figure 3.1 Demonstration of the principle of the Cgen analysis program

using a mock-up of hybridisation results 99

Figure 3.3 Cgen analyses 100

Figure 3.4 Results of the analysis of the normalised hybridisations 101

Figure 3.5 Confirmation of the differential expression of MRP-8 and

MRP-14 by RT-PCR 102

Figure 3.6 Immunohistochemistry of BCCs 103

Figure 3.7 Immunhistochemistry of SCC and normal squamous epithelia 104

Figure 3.8 Immunofluorescence studies on epidermis and cultured

kératinocytes 105

Figure 3.9 In situ hybridisation 106

Figure 4.1 FACS profiles for the separation of basal cells 118

Figure 4.2 Hybridisation of the Unigene filters 119

Figure 4.3 Cgen profiles of stem cell versus transit amplifying cell

comparisons 121

Figure 4.4 Northern hybridisation analyses 122

Figure 4.5 Immunofluorescence staining of kératinocytes 124

(10)

Figure 4.8 Analyses of infected kératinocytes 127

Figure 5.1 Primary structure of MCSP 135

Figure 5.2 MCSP expression in breast epidermis 136

Figure 5.3 MCSP expression at other body sites 137

Figure 5.4 MCSP expression in the hair follicle 138

Figure 5.5 MCSP expression in cultured kératinocytes 139

Figure 5.6 Immunostaining of wholemount epidermis 140

Figure 5.7 FACS analysis of double stained kératinocytes 141

(11)

List of Tables

Table 1.1 Comparison of array hybridisation methods 24

Table 3.1 Differentially expressed genes 92

Table 4.1 Analysis of candidate genes

Table 4.2 Analysis of E-FABP negative nuclei

110

112

(12)

Abbreviations

18S 18 Svedburgs

20mer Oligonucleotide containing 20 bases

2D 2-Dimensional

Ack-1 Human activated p21cdc42Hs kinase

AMV Avian myeloblastosis virus

AP Ammonium persulphate

BCA Bicinchoninic acid

BCC Basal cell carcinoma

BSA Bovine serum albumen

bFGF Basic fibroblast growth factor

bp base pairs

BrdU 5-Bromodioxy Uridine

C-FABP Cutaneous fatty acid binding protein (E-FABP)

CD Cluster of differentiation antigen

Cdc42 Homo sapiens cell division cycle 42 (GTP-binding protein, 25kD)

cDNA Copy DNA

CGAP Cancer Genome Anatomy Project

CNS Central Nervous System

C0S2 Costal 2

CRN A Copy RNA

dXTP Deoxythymidine triphosphate

DAB 3,3-diaminobenzedene tetrahydrochloride

dATP Deoyadenosine triphosphate

DCS Donor Calf Serum

dCTP Deoxycytidine triphosphate

DEPC Diethylpyrocarbonate

dGTP deoxyguanosine triphosphate

DICE Difference Gel Electrophoresis

DMEM Dulbecco’s modification of Eagles medium

DMSG Dimethyl Sulphoxide

DNA Deoxyribonucleic acid

DNTPs Deoxynucleoside triphophates

(13)

DP Dermal Papilla

DTT Dithiothreitol

E-FABP Epidermal Fatty Acid Binding Protein

ECL Enhanced chemiluminescence

EDTA Ethyldiaminotetraacetic acid, disodium salt

EST Expressed Sequence Tag

FABP Fatty acid binding protein

FACS Fluorecence Activated Cell Sorter

FCS Foetal Calf Serum

FITC Fluorescein isothiocyanate

FSG Fish skin gelatin

Fu Fused

GFP Green Fluorescent Protein

GLI Human homologues of Drosophila Cubitus Interruptus

HEPES N-[2-hydroxyethyl]piperazine-N’-[2-ethanesulphonic acid]

HRP Horseradish peroxidase

ICRF Imperial Cancer Research Fund

IFN Interferon

IMAGE Integrated Molecular Analysis of Genomes and their Expression

1RES Internal ribosomal entry site

LamG Laminin G - D omain of the laminin protein

LB Luria Burtani

LRC Label retaining cell

MARK Mitogen protein kinase

MAPKKl Mitogen protein kinase kinase 1

MCSP Melanoma Chondroitin Sulphate Proteoglycan

MOPS 3-[N-Morpholino]propane-sulfonic acid

mRNA Messenger Ribonucleic acid

MRP-14 Homo sapiens migration inhibitory factor-related protein 14

MRP-8 Homo sapiens migration inhibitory factor-related protein 8

NaOAC Sodium Acetate

(14)

NG2 Mouse and rat homologues of the Melanoma Chondrotin Sulphate

Proteoglycan

NH4OAC Ammonium Acetate

OD Optical Density

plSOcas Homo sapiens Crk-associated substrate plSOCas

PAGE Polyacrylamide gel electrophoresis

PB Permeablilisation buffer

PBS Phosphate buffered saline

PB ST PBS/Tween

PCR Polymerase chain reaction

PDGF Platelet derived growth factor

PE Phycoerythrin

PMSF Phenylmethanesulphonyl fluoride

PTCH Human homologue of Drosophila patched

PVDF polyvinylidene fluoride

RDA Representation difference analysis

RNA Ribonucleic acid

RR Rete ridge

rRNA Ribosomal ribonucleic acid

RT Reverse transcriptase

RT-PCR Reverse transcription - polymerase chain reaction

RZPD German centre for the human genome project

SlOO 100% soluble in ammonium sulphate

SAGE Serial analysis of genomes and their expression

SCC Squamous cell carcinoma

SDS Sodium dodecyl sulphate

SHH Sonic hedgehog, a homologue of Drosophila hedgehog

SMOH Human homologue of Drosophila smoothened

SSC Salt sodium citrate buffer

SSSRC Salt sodium sarcosyl citrate buffer

Su (Fu) Suppressor of Fused

TAE Tris-acetate-EDTA buffer

TBE Tris-borate-EDTA buffer

(15)

TEMED N,N.N’ ,N’ -tetramethylethylenediamine

TM Transmembrane domain

(16)

To Mum and Dad

(17)

Acknowledgements

I was lucky enough to have two supervisors during my four years at the ICRF. The

greatest of thanks go to Anna-Maria and Fiona, for allowing me to learn what I have in

both laboratories, and for making me realise that I wanted to pursue a career in science.

Thanks for both for your patience and understanding. Lab life was made easier by the

many discussions and re-enactments of scenes from Star Wars in the Frischauf Lab, and

the constant denigration of West Ham in the Watt Lab. Without me asking inane

questions to Brian, Lisa, Steph, Thomas, Kirsten, Fritz and Sanjiv, I wouldn’t be where I

am now. The tradition of inane questioning continued when I was lucky enough to work

in the Watt lab. Thanks to all of you (over 20 at the last count!) for bearing with my first

tentative steps in cell biology. Although huge apologies for the mould! - Maybe one day

in the future I’ll get my Clonogenicity assays to work, and it’ll all be down to you guys!

I.C.R.F is a great place to make friends (and drink beer), and thanks goes out to the large

number people I have met and coerced into going to the George - Robin, Mat, Liz, Brian,

Shauny, Matt, Maria, Bryony, Steph, Jenny, and more recently, Josie, Ceri, Anna, and ....

(the list continues - oh I did drink quite a lot didn’t I!). A special shout goes out to my

fellow Essex-ites, Richard (never believe him- he is you know) and Becky. I’m sure that

the science we discussed and the beer (or whisky and cokes) we drank there was of the

highest calibre.

I.C.R.F have great laboratory services staff, without them, some of my thesis wouldn’t be

possible. Thanks go to all the members of the FACS laboratory, for their constant

patience with clumping kératinocytes, Histopathology, for the help with sections,

immunohistochemistry, and in situs, and the members of the equipment park for extended

loans of Phosphorlmagers!

Finally thanks to my family and friends who have had to bear with me through all this

(18)

Publications

O'Shaughnessy, R.F.L., Seery, J.P., Cells, J.E., Frischauf, A-M. and Watt, F.M. - E-

FABP, a novel marker of human epidermal transit amplifying cells revealed by 2D

protein gel electrophoresis and cDNA array hybridisation - In Press, FEES letters

(19)

Chapter 1 Introduction

1.1 Overview

The expression of candidate genes differentially expressed in normal and neoplastic

kératinocytes, or in kératinocytes in different stages of development could be assessed

one at a time in considerable detail. Using the intrinsically non-biased technique of

differential hybridisation, the expression of thousands of genes can be analysed

simultaneously, in a non-hypothesis driven manner. The goal of this thesis is to discover

new candidate genes involved the mechanisms of differentiation in interfollicular

epidermis and tumourigenesis in basal cell carcinoma.

1.2 Differential Gene Expression Analyses

No single cell type expresses all the genes present in a genome of an organism. At a very

basic level, liver cells express liver genes; brain cells express brain genes and so on.

What makes a brain cell a brain cell and a liver cell a liver cell? Different genes are

expressed in different cell types and the levels of expression of particular genes vary. The

panoply of different transcripts is referred to as the transcriptome, whereas the assortment

of different gene products is the proteome. Differences in the transcriptome and proteome

(the expressed genome) are what causes different cell types to have different phenotypes

and to form different tissues. The expressed genome also varies during the differentiation

of a tissue, for example kératinocytes that are destined to become terminally

differentiated squames produce proteins that are not present in the basal layer of the

epidermis. Variation is also observed in pathological conditions, a good example of this

being tumourigenesis.

Hybridisation of n orthem blots, nalysis of western blots, and more recently PCR of

cDNA with gene specific primers (RT-PCR) allow discovery single differences in the

expressed genome between two conditions. Analysis of the expressed genome by these

(20)

Chapter 1 Introduction

differences in the many thousands of genes in the expressed genome could be analysed

simultaneously. This is what differential gene expression analyses aim to achieve. It can

be likened to performing a Northern hybridisation for thousands of genes simultaneously,

or performing a Western blot for thousands of protein products simultaneously. Looking

at differences in the expressed genome between, for example, a normal cell line, and a

cell line derived from a tumour would give information on which pathways have been

altered in the tumour cell line (for example see DeRisi et al., 1996). The current term for

this is functional genomics, literally the determination of function through differences in

gene expression. The final goal of functional genomics is the tracking of differences in

the expressed genome within a species tissue by tissue, time-point by time-point, disease

by disease and condition by condition.

Although there are alternative methods to analyse the transcriptome, and these will be

discussed later, the current method of choice is the hybridisation of cDNA arrays. A

cDNA array is a number of cDNAs (from 1 to 40,000+) that have been spotted onto a

support, historically this has been a nylon filter but more recently has become a glass

slide. A probe is synthesised from RNA obtained from the tissue or cell line under test

and this is hybridised to the array. This provides an indication of what cDNAs present on

the array are actually present in the probe. If another hybridisation is performed with

another probe derived from a tissue or cell line, differences in expression of the genes

present on the array is possible by comparing the signal intensities between

hybridisations for the same spot on an array, which corresponds to a particular gene. Of

course by this method it is impossible to determine gene expression differences for genes

that are not present on the filter. The principles necessary have been known for over 25

years. However only in the last ten years with the continued development of array

technologies has the implementation been possible.

1.2.1 A Brief History of Arrays

Over 25 years ago, Edwin Southern’s discovery that labelled nucleic acid molecules

could be hybridised to immobilised nucleic acids (Southern, 1975) effectively lead to the

first array hybridisations. In these times before PCR, Northern blotting was the only way

(21)

to detect differences in the level of transcripts. Dot and slot blots were the next step, and

the first attempt to immobilise a number of genes of choice on a filter and interrogate

them with a probe. The combination of the dot blot and the ability to construct cDNA

libraries was required to allow the arraying of cDNA so there was a 1:1 relationship

between the hybridisation signal and the clones analysed (Gress et a l, 1992; Gress et a l,

1996). Attempts to quantify signal intensities and differences thereof between different

samples can be made with these filters, and one such attempt is described in Chapter 3,

the comparison of 2 BCC samples and 1 skin sample. At this time (Early-Mid 1990’s)

bacterial colonies were spotted onto nylon filters (Southern, 1975; Gress et al., 1992;

Gress et al.„ 1996). The nuts and bolts of the technology were present, but quantification

of signals was complicated by the variable amount of DNA present in a bacterial colony

and the fact that bacterial debris contributed to non-specific variation in hybridisation

signals.

Improvement were made in the technology. Better gene representation was possible as a

result of the huge amount of data being generated from the sequencing of cDNA ends

(ESTs) (For example see Boguski and Schuler, 1995 and Lennon et a l, 1996). Selecting

specific cDNAs from the huge numbers available also provided the arrays with non

redundancy, that is the representation of each gene only once. Using cDNA rather than

colonies allowed easier contol of the quantity of DNA present on each spot, and

drastically reduced the variation in DNA content on the spot, allowing for more precise

quantification of hybridisation signals

Stanford University, in the laboratory of Patrick Brown, was where the next advance

originated, with the discovery that cDNAs could be immobilised on a non-porous support

such as glass. Up to 10,000 cDNAs could be spotted on a microscope slide (Schena et a l,

1995). The ability to use two differently fluorescently labelled probes on the same

microarray (the term for arrays on chips) abrogated the need to normalise data. This

approach coupled with confocal microscopic analysis of the microarray has been

successfully used by a number of laboratories, and has been marketed by a large number

of companies. Both chips and chip readers are commonplace now. The most recent

(22)

allowed by in situ oligonucleotide synthesis, a method pioneered by Lipshutz and Fodor,

founders of Affymatrix.Inc. This allows 300,000 gene specific oligonucleotides

(corresponding to 15,000 genes) to be arrayed on a single chip (Lipshutz et a l, 1999).

Experimental chips now exceed 1,000,000 oligonucleotides (Lipshutz et al., 1999).

However for most researchers the cost of setting up an arraying facility or buying ready

made microarrays are still prohibitive, but the costs will fall as the demand for global

expression data increases.

1.2.2 Performing an Array Hybridisation

All array hybridisation methods involve the hybridisation of a complex probe from tissue

samples or cell lines to an array target either a large nylon filter (macroarray) or a smaller

glass support (microarray) (Figure 1.1). The probe in question is normally reverse-

transcribed from the mRNA and either labelled in the reverse-transcription reaction or the

synthesised cDNA is labelled. The probe is labelled radioactive nucleotides (typically

with or ” P labelled) or fluorescently labelled nucleotides. This “complex probe”

(Oettgen et a l, 1997) is a representative sample of the transcripts present in a particular

mRNA population. The probe is hybridised to the target in a volume appropriate for the

array being used i.e. tens to hundreds of microlitres for microarrays, and 10-30 ml for

macroarrays.

The hybridisation is performed in a large excess of the target i.e. the DNA spotted onto

the array. Only under these conditions will the hybridisation signal on a spot vary in a

linear fashion with the abundance of the transcript in the probe. To give an idea of

numbers, the typical nylon filter spot has 50ng of DNA (Nguyen et a l, 1995). An

abundant mRNA species (1/1000 relative abundance) when labelled corresponds to

approximately 1 ng when lug of mRNA is labelled. This is 50 times less than the amount

of DNA on the spot. Even then only a small fraction of this probe will hybridise to the

cognate target. This is in stark contrast to normal Southern and Northern hybridisation,

where the probe is in huge excess, and the signal is dependent upon the amount of

available target. In complex probe hybridisations, the signals are dependent on the probe

concentration, the length of hybridisation time and the DNA on each spot. These

(23)

hybridisation conditions are therefore not optimal and less complex DNA species, repeat

sequences, and polyA or polyT tracts will hybridise more readily. These events have to

be taken into consideration when the hybridisation is analysed (Nguyen et al.,, 1995;

Bernard gr a/., 1996).

As discussed previously, the signal on a spot is mostly dependent on the concentration of

the probe. Simply increasing the amount of probe present in the hybridisation can

increase the sensitivity of any hybridisation; the ability to detect low signals above the

background signal present over the whole array, assuming the background does not vary

as a result. However as the biological material is normally the limiting factor in any

expression analysis, this is not really possible. Sensitivity can be described in two ways:

the minimal number of transcripts per cell that can produce a discernible signal on a spot

(the detection limit) or the minimal number of mRNA molecules of a given species that

can detected (Bertucci et a l, 1999). Detection methods are important determinants in

sensitivity, as is the amount of DNA on per target. Radioactive detection is more

sensitive than fluorimetric detection (Bertucci et al., 1999), and Nylon arrays have more

DNA per target than microarrays. In fact the minimum detectable sample is

approximately the same for both techniques. In addition smaller amount of sample can be

(24)

Cell Line Tissue Tum our

PREPARATION _{cDNA Libraries}

HYBRIDISATION

TARGET Array of 1 0 0 0 to 2 0 0 0 0 genes PROBE

Complex probe

1000-20000

d ifferent RNA species

2 Colour Fluorescence Radioactive

Detection

ANALYSIS OF D A TA

Data aquisition and Normalisation

Identification of differentially expressed genes

Bioinformatic or further analysis

I

RESULT

Figure 1.1 Differential Hybridisation Experiments. All experiments involve three steps. Firstly the preparation of resources, which includes mRNA extraction from the test and references tissue and selection of cDNAs for array construction. Secondly, the a probe is synthesised from the mRNAs and hybridised to the array target. Signals are analysed automatically and changes in signals are then determined.

(25)

Nylon Filters Microarrays

(Schena et al.„ 1995)

Oligonucleotide chips

(Lockhart et a l, 1996)

Target cDNA clones

(Colonies or PCR

products)

cDNA clones as PCR

products

Normally 20mer

oligonucleotides

Format Up 30,000 spots on

a 22x22 nylon filter

(B. Korn - Pers.

Comm.)

Up to 6400 spots on a

1.8x 1.8 cm glass

slide

64,000

oligonucleotides on

1.28x1.28 cm glass

chip

Sample 25 mg Total, 1 pg

mRNA

2 pg mRNA 10 pg mRNA

Label 33p _Fluorescence _Fluorescence

Hybridisation

Volume

10-40 ml 2-10 pi 200 pi

Detection limit 1/20,000 1/ 100,000 1/300,000

Minimum

sample amount

25 X10^ molecules 20 X 10^ molecules 30 X 10^ molecules

Table 1.1 Comparison of Array Hybridisation Methods: Adapted from Bertucci

et aL, 1999

Detection limit is the minimal relative abundance of a particular mRNA species that can actually be detected as a signal on a spot. Minimal sample amount is the smallest number of a single species of transcripts that can produce a signal. Ipg of mRNA is approximately 10^ transcripts, assuming a 1.7kb average transcript size (Bertucci et al.,

(26)

1.2.3 Analysis of Differential Hybridisation Data

Although performing the hybridisations is relatively trivial, what is far from trivial is the

analysis of the hybridisation results. Short of manually scoring every signal, the only way

that meaningful data can be obtained is by automated analysis. The hybridised filter is

normally analysed from an image derived from a high resolution imaging plate system

(for example the Phosphorlmager plates used in this thesis), and the results from

microarray hybridisations are normally analysed from a confocal microscopic image. The

result is a list of co-ordinates and signal intensities. The interpretation of these data can

be a problem. Data is typically normalised to allow easy comparison between different

hybridisations. Some way of determining the minimum difference in expression that can

be detected is necessary to reduce the number of false positives (differences in signals

that are not due to differences in expression). In addition the minimal detectable signal

above background levels has to be determined.

A good way of determining these criteria is by the plotting of data on a scatter plot and a

histogram respectively. Plotting the intensities as a histogram will show a distribution

around a peak value. Normally this peak value is regarded as the background value. All

signals below this value will be assigned this value for quantitation purposes (Figure 1.2).

In addition, differences in signal are only regarded as valid if one or other of the signals is

significantly above this background value, typically double the background value.

Blindly evaluating signal differences of spots that are of a background value is a major

source of false positives. Plotting two sets of signal intensities against each other will

always produce the same result, a cloud of data points that vary around the line of no

differential expression (that is identical signals in both hybridisations). Points that lie

outside of this main cloud correspond to signals that differ by a larger amount than is due

to random variation. These are regarded as due to potentially differentially expressed

genes (Figure 1.2)

(27)

800(r

7 0 0 0

6000-n 4 0 0 0 -3 0 0 0 2000

-1000

-B

80 100 120 140 160 180 200 220 ^ 4 ^ ^ 6 T ^ 8 ^ ^ i ^ 3 2 ^ ^ 0 " " 3 6 ^ ^ 8 0 " ^ W

Signal intensity

4 . 0 3 . 0 3 . 6

3 . 2

2 . 4

2 . 2

2 . 0

2 .9 2 .7

Figure 1.2 Histogram and Scatter Plot A. The range of signal intensities in a hybridisation can be shown as a histogram. The modal value is taken to be the background value. B. A scatter plot comparing two hybridisations, in this case, HT 1080 cells induced for six hours with IFN-gamma (y-axis), versus uninduced cells (x-axis). Guanylate binding protein (Red spots) is up-regulated in the induced cells, shown by being away from the cloud of unchanged signals.

(28)

1.2.4 Confirmation of Differential Gene fi.\pression

Gene expression differences are normally confirmed, typically by Northern hybridisation

or RT-PCR. This is necessary for several reasons. The first and most important of these is

the elimination of remaining false positives. Secondly confirmation that the observed

expression change is observed in other samples of the same condition (same kind of

tumour or a related cell line), gives weight to the finding. Tumours are good example of

the need to do these sorts of analyses as, for example, different classes of melanoma can

be identified on the basis of the genes that are differentially expressed in them (Bittner et

a l, 2000). When these confirmation steps are overlooked (Lee et aL, 1999) the results of

the analysis should be regarded with some scepticism. The only exception to this would

be where the results are in line with previously published findings, an example of this

would be the expression of keratins in different classes of breast tumours (Pérou et a l,

2000)

1.2.5 Other methods of determining differential gene expression

Differential hybridisation is not the only way to detect different levels amounts of

transcripts between two populations. Powerful though differential hybridisation clearly is,

it cannot provide the whole picture of differential gene expression as yet (although many

of the large companies that have bought into the technology would like you to think so).

Differential hybridisation currently fails at trying to find differences in expression in very

rare transcripts, and contrary to popular belief, the actual expression differences are hard

to quantify exactly. The other approachs open to most laboratories can only ever address

one of these problems well. PCR based approaches are the best way to determine

differential gene expression in rare transcripts, whereas cDNA sequencing projects are

better suited for more precise quantitation. Although analysis of changes in the transcript

population are reflected in the protein products, looking at the proteome can also allow

the detection of more subtle, yet just as significant changes such as post translational

modifications. Proteomics utilising 2D gel electrophoresis has been around for much

longer than array hybridisation, but only recently has it become a particularly powerful

tool in expression analyses (Cells et al., 1991)

(29)

PCR based technologies -cDNA subtraction

If knowing the approximate differences in expression of genes is not important, and the

only information desired is discovery of genes that are either absent or present from one

or other of the transcripts under test, then PCR approaches are powerful ways to detect

differences in even extremely rare transcripts. Without going into a huge amount of

detail, cDNA subtraction involves the hybridisation of the cDNA under test, the tester,

with a large excess of a reference cDNA, the driver. cDNAs that are present in the tester

but not in the driver do not hybridise. This first step is known as cDNA subtraction

(Hedrick et aL, 1984). Only the non-hybridised tester cDNA can be amplified. This

process can be iterated (in a variation of cDNA subtraction known as Representational

Difference Analysis or RDA - Lysitsyn et aL, 1993) until a number of PCR products

corresponding to genes present in the tester but not in the driver are seen. These products

have to be characterised, which involves not a small amount of work, but the whole

transcriptome has been analysed for differences, not just the representation on a cDNA

array.

cDNA sequencing and SAGE

If manpower and expense are not problems, then probably the most comprehensive way

of finding out what genes are differentially expressed between two mRNA populations is

to make cDNA libraries out of each and sequence tens of thousands of clones from both

libraries (examples Lennon et a/., 1996; Konishi et aL, 1994 in cultured kératinocytes).

Then all that is needed is to count the number of times a particular gene is sequenced in

both libraries to determine expression differences. Absolute quantitation is assured and

the sensitivity of the approach is only limited by the amount of clones sequenced.

l.M. A.G.E, the integrated molecular analysis of genomes and their expression (Lennon et

aL, 1996) is a huge attempt at this and now tens of millions of 5’ and 3’ ends of cDNAs

from hundreds of different libraries have been sequenced. But it has taken nearly a

decade so far. Indeed the Unigene database, an attempt to collate the l.M.A.G.E.

(30)

1995), is the basis of the genes that are spotted on the filters used in chapter 4 (B.Kom -

personal communication)

Recently a method has been devised to do the same as above, but for far less effort. The

reasoning goes that if only 9 bp is required for a unique gene sequence that will be only

present once in the human genome (Velculescu et aL, 1995), why sequence 500bp to

ascertain the identity of a gene in a cDNA sequencing project? Instead ligate together,

with spacers, these 9bp tags and sequence them all at once. This technique, known as

serial analysis of gene expression or SAGE is complicated, involving the digestion of

cDNAs at known locations brought about by the use of two restriction enzymes, the

ligation of the resulting identifying “tags” in concatomers, and their subsequent

sequencing and analysis (Velculescu et aL, 1995). The amount of each tag present is

counted and compared with the tags from the other cDNA population. The data is easy to

quantify and differential expression can be measured exactly. This technique has been

used with some success in determining gene expression differences in colorectal cancer

compared to normal tissue, and very recently has revealed that tumour neovasculature

expresses different genes to normal endothelia (Zhang et aL, 1997; St. Croix et aL, 2000),

validating the approach in small amounts of starting tissue.

Proteomics approaches

There is no need to look at differences in the transcriptome at all. Differences in

transcription will lead to differences in the translated gene products. Also there are many

post translational modifications that would not be apparent in cDNA based approaches.

Phosphorlyation, and glycosylation are just two of these modifications that could

modulate function. Conceptually proteomics is simple. Perform two identical 2D gel

electrophoreses with the two extracts under test (typically size separation on one axis

after isoelectric focusing on the second axis). Visualise the proteins as thousands of dots,

and look for dots that are different between the two, either in size (i.e. differential

expression), or position (normally due to post-translational modification).

(31)

The problems arise when trying to determine the identity of the protein of interest. This

involves microseqencing normally directly from the spot of interest. However in certain

tissues this has been made easier by the efforts of laboratories such as that of Julio Celis,

who is systematically characterising for example, all the proteins in normal human

kératinocytes and their positions in terms of their size in kilodaltons, and their isoelectric

points (Celis et al., 1991). This database (http://biobase.dk/cgi-bin/celis) has been used to

compare normal and psoriatic kératinocytes (Madsen et aL, 1992), and more recently has

been used to address the stem cell versus transit amplifying cell problem discussed in

Chapters 4 and 5 (O’Shaughnessy et aL, in press). Improvements have been made in the

technology. Difference gel eletrophoresis (DICE - Unlu et aL, 1997) allows two

differently fluorescently labelled extracts to be electrophoresed on the same

polyacyrlamide gel. In this way both the differences in expression and post-translational

modification are easier to detect.

1.2.6 Towards Functional Genomics - The Future of Array Hybridisation

In organisms where the whole genome has been sequenced, i.e yeast, differential

hybridisation is functional genomics. Comparing the expression profiles of a database of

known yeast mutants with the expression profile of an unknown yeast mutant makes

possible the detemination of probable functions of the product of the unknown mutated

gene (Hughes et aL, 2000). The global changes in gene expression in processes such as

cell division can also be analysed (Cho et aL, 1998). True functional genomics cannot be

performed as yet on human expression studies as the whole genome is not as yet

characterised. In addition on a practical level, it is unlikely in the very near future,that

there will be the ability to represent the whole human genome on a chip, as is the case

with yeast. However, attempts are being made to collate expression data in parallel

comparisons of tumour tissue versus normal tissue as a part of the cancer genome

anatomy project (CGAP)(Strausberg et a l, 1997; Cole et aL, 1999; Krizman et a l, 1999).

The true power of differential hybridsation in combatting diseases such as cancer will be

manifest in the ability to track and understand the progression of all tumours from the

earliest premalignant lesion right up to metastasis on the basis of their gene expression

(32)

1.3 The Epidermis

The epidermis is a good model tissue for examining problems in tumorigenesis and

development. Skin carcinogenesis in mouse is one of the major nv^;^contributing to the

understanding of the multi step nature of carcinogenesis in general (Yuspa., 1994). The

discovery that the epidermis requires stem cells active throughout life, that kératinocytes

undergo a well known program of terminal differentiation and that stem cells are

maintained in culture make the epidermis and kératinocytes an attractive model system in

which to analyse the properties of stem cells and their committed progenitors (Watt.,

1998; Watt., 2000)

The skin is the outermost layer of the human body and is made of three layers, the

innermost subcutaneous fat, the dermis, and the othermost layer, the epidermis. The main

role of the skin is to protect the rest of the body from water loss, infection and the

environment. The epidermis is the layer that plays the largest role, as it provides an

impermeable barrier to the outside by virtue of the outermost layer of the epidermis,

which produces anucleate, proteinaceous flattened cells called squames. Squames are

constantly sloughed off the surface of the skin, so to maintain its protective role, the

epidermis must be able to produce more squames. This is achieved with an actively

dividing layer of cells, the basal layer. These cells eventually terminally differentiate,

leaving the basal layer to eventually form squames (Holbrook., 1994).

In humans, the thickness of the epidermis varies, with regions where the epidermis is thin

overlying the dermal papilla, and regions where the epidermis is thicker, projecting

further into the dermis, that are known as rete ridges (Figure 1.3). In the epidermis of the

palm and sole (palmoplanter epidermis), there are two sorts of rete ridges, the shallow

rete ridges similar to those seen in non palmoplantar epidermis, and deep rete ridges. The

epidermis is arranged into four histologically distinct layers, the basal layer, the spinous

layer, the granular and the comified layer. The main cell of the epidermis is the

leratinocyte. The major constituent of kératinocytes is keratin. Keratin forms an

intermediate filament skeleton, which provides resistance to shearing forces (Odland.,

1991). Different keratins are expressed in different layers of the epidermis, and act as

(33)

DP

RR

I Epidermis

Dermis

Fat

B

S h e d S q u a m e s

Comified Layer

Granular Layer

Spinous Layer

Basal Layer

K e r a t o h y a lin G r a n u le s

Terminal Differentiation

Actively Dividing

Basement Membrane

H e m id e s m o s o m e s

D e s m o s o m e s

Figure 13 The Human Epidermis. A. Gross structure of the human skin. The three layers of the skin are shown. The basement membrane, is shown as a blue line. The arrangement of dermal papillae and rete ridges in non-palmoplantar epidermis is shown. B. The layers of the epidermis and some of the stmctures.

DP - Dermal Papilla, RR - Rete Ridge

(34)

Specific markers for the layers (Stoler et al.,1988; reviewed in Fuchs., 1988). Other cells

are present in the epidermis and these are the melanocytes that provide the skin with

pigment (Jimbo et a l, 1991), the Langerhans cells, which are the epidermal antigen

presenting cells (Hauser et a l , 1991) and the Merkel cells which are required for hair

follicle development as well as electro-mechanical signal transduction (Munger et a l,

1991).

1.3.1 The Basal Layer, Basement Membrane and Integrins

The basal layer of the epidermis is the only actively dividing layer of the epidermis. Stem

cells that are present in the basal layer give rise to committed progenitors that eventually

leave the basal layer and terminally differentiate (Watt., 1998). There are several known

markers specific to the basal layer. Keratins 5 and 14 are the keratins that form the

intermediate filament skeleton in basal cells (Stoler et a l, 1988). The basal kératinocytes

express adhesion molecules called integrins, which allow them to attach to the basement

membrane which divides the epidermis from the dermis (Hynes., 1992; reviewed in Watt

and Hertle., 1993). The basement membrane consists of extracellular matrix componants

secreted by both the kératinocytes and the dermal fibroblasts, including laminins,

fibronectin and collagen (Burgeson and Christiano., 1997), The basement membrane

contains microfibrils which connect the dermis to the epidermis via structures called

hemidesmosomes (Jones et a l, 1998). There are three major integrins, consisting of a

and P subunits, expressed by the basal kératinocytes which can adhere to these

extracellular matrix componants. a 2pi integrin can adhere to laminin, fibronectin and

collagen, while aSpl and a6p4 integrins can adhere to laminin 5, with a6p4 being one of

the major components of the hemidesmosomes (Watt and Hertle 1993; Jones et al, 1998).

Integrins are important not only for adhesion, but also the modulation of growth and

proliferation (Hynes., 1992: Zhu et a l, 1999). Because of this they are attractive as

potential markers of the stem cell. This is discussed the section Keratinoyte stem cells.

(35)

1.3.2 The Spinous Layer

This 4-8 cell thick layer contains cells that are terminally differentiating. The cells are

more flattened and contain more keratin than the cells of the basal layer. The first well

known markers of terminal differentiation, keratins 1 and 10 are expressed in this layer in

hair bearing skin, whereas keratins 1,2 and 9 are expressed in palmoplantar epidermis

(Morely and Lane., 1994). The uppermost cells of this layer express some of the

constituents of the comified envelope of the squames, such as involucrin and proline rich

proteins such as comifin (Simon., 1994)

1.3.3 The Granular Layer

This 2-3 cell thick layer is named for the presence of keratohyalin granules, containing

profilaggrin and loricrin, whose function is thought to be the aggregation of keratin

filaments (Holbrook., 1994). These cells produce lipids that contribute to the barrier

function of the com ified layer (Lampe et al., 1983; reviewed in Nemes and

Steinert.,1999).

1.3.4 The Comified Layer

This is the outermost layer of the epidermis. It functions as an impermeable barrier to the

environment. The cells of this layer are the squames described earlier. Squames are large

but very thin cells with no organelles. The cytoplasm is packed full of keratins, and is

surrounded by a 12nm thick insoluble comified envelope, which consists of covalently

(36)

1.4 Two cancers of the epidermis: BCC and SCC

1.4.1 Basal Cell Carcinoma

Basal cell carcinoma (BCC) is a tumour derived from the basal layer of the epidermis. As

yet no clear precursor lesion has been detected (Miller, 1991a; Miller, 1991b; Preston and

Stem, 1992). In general, BCC begins as small invasive areas of the epidermis growing

downward into the dermis, but with an intact basement membrane. In later stages of the

carcinoma, small tumour nests bud away from the epidermis above and tend to be

associated with a mononuclear infiltrate. These nests are characterised by their outermost

cell layer having a pallisade-like appearance reminiscent of the basal layer of the

epidermis from which the tumour had originated (Miller, 1991a; Miller, 1991b; Preston

and Stem, 1992 and Figure 1.4)

There are few genes whose expression is diagnostic of BCC. In general genes that are

expressed in the basal layer of the epidermis, or in the proliferative cells of the hair

follicle, are also expressed in BCC. In particular expression of cytokeratins is observed.

The basal keratins, 5 and 14, and the hair follicle-derived keratins, 15 and 17, are

expressed in all BCCs (Stoler et a l, 1988). Other proteins that are typically upregulated

in BCC include, but are not restricted to, integrin subunits and the transferrin receptor

(Gatter et a l , 1984; Peltonen et a l, 1989). Conversely, markers of the suprabasal

epidermis are generally absent in BCC tumour nests. For example, involucrin, a markers

of terminal differentiation was negative in all tumours analysed (Murphy et a l, 1984;

Said et a l, 1984; Sumitomo et a l, 1986). Collagen IV, a basement membrane component

is present around all tumour nests suggesting an intact basement membrane (Barsky et

a l, 1987; Kallioinen el a l , 1984). The bullous pemphigoid antigen (BPAG), a

component of hemidesmosomes, has a reduced expression in BCC, consistent with a

reduced number of hemidesmosomes (Stanley et a l, 1982). However, too date, there is

no antibody that specifically marks BCC.

Cell cycle time for BCC cells and normal kératinocytes are not markedly different

(Weinstein and Frost, 1970), however the DNA synthesis phase (S-phase) is twice as

(37)

Carcinoma

Squamous Cell Carcimoma

Normal Skin

Figure 1.4 BCC and SCC. Arrows point to invasive regions of the SCC beneath the hyperproliferative epidermis. Bai 200 pm

(38)

long in BCC cells (Heenen et a l, 1973). The DNA content is almost the same as normal

diploid cells, with the most common genetic lesion being the loss of all or parts of

chromosome 9 (Quinn et a l, 1994). In general, amplification of oncogenes is not

observed, however, amplification of c-Myc and mutations in K-ras have been observed in

some BCCs (van der Schroeff et a l, 1990).

BCCs rarely metastasise, one reason for this possibly being that, according to Pinkus, the

BCC is a stroma-dependent tumour (Pinkus., 1959). This is borne out by the fact that

transplanted tumours are unable to survive without their accompanying stroma (Pinkus.,

1965) and that attempts to culture BCCs have always caused a degree of differentiation

(Flaxman and Van Scott, 1968; Flaxman, 1972; Kubilus et a l, 1980). This suggests that

the maintenance of the BCC phenotype requires factors from the surrounding stroma.

1.4.2 Genetic predispositions to BCC

Recently major advances in the understanding of BCC development has come from the

study of genodermatoses, or genetically inherited skin abnormalities that lead to a higher

incidence of BCC in the affected individual. These diseases include Xeroderma

Pigmentosum (Robbins et a l, 1988), Bazex Syndrome, which causes hypotrichosis

(reduced hair growth) as well as BCC (Viksnins and Berlin, 1977), and most importantly.

Nevoid Basal Cell Carcinoma Syndrome, or Gorlin Syndrome (Gorlin, 1987). Gorlin

Syndrome is an autosomal dominant disorder, which manifests as multiple BCCs,

palmoplantar pits, which are indicative of aberrant keratin synthesis, and developmental

abnormalities that include bifid ribs (Gorlin, 1987). The gene responsible for this disorder

has recently been cloned, providing insight into tumour development, not only in BCC,

but also other common cancers. The gene mutated in Gorlin syndrome is the human

homologue of the Drosophila segment polarity gene, patch ed, PTCH, part of the

hegdehog signalling pathway (Hahn et a l, 1996a; Hahn et a l, 1996b; Johnson et a l,

1996 and Figure 1.5).

PTCH is found on chromosome 9, the most common altered chromosome in BCC (Quinn

et a l, 1994). Analysis of some of the members of the PTCH pathway has revealed its

(39)

PTCH

II

SMOH

G Protein

Signalling

Su(FuV

GLI activates

transcnption

of target genes

including PTCH

(40)

importance in the development of BCC. Mutations in PTCH and smoothened (SMOH)

have been observed in sporadic tumours, with the possibility that point mutations in some

cases were sufficient to impair function. Out of 37 tumours examined, 14 had mutations

in PTCH, most of which were premature stops and frameshifts, however there were 4

point mutations and a single in-frame deletion. These were found either on the first

extracellular loop on one intracellular loop or at the carboxyl terminus (Gailani et a l,

1996). In SMOH point mutations were often observed (Reifenberger et a l, 1998). Two

point mutations in SMOH were found in 3 out of 47 BCCs, one in the seventh

transmembrane domain and a second in the cytoplasmic tail. Some of these mutations

allowed SMOH to act as a cooperative oncogene with adenovirus E l A, transforming rat

fibroblasts (Xie et a l, 1998). Expressing one of the SMOH mutants in the basal layer of

the epidermis of mice lead to the development of BCC like features (Xie et a l, 1998).

Ectopic expression of some of the patched pathway members in the epidermis can lead to

BCC. Expressing SHH under the control of the keratin 14 promoter in mice produces

BCC-like lesions (Oro et a l, 1997). Human kératinocytes expressing SKH by retroviral

transduction when grafted onto SCID mice, produce epidermis with BCC-like features

(Fan et a l, 1997). Injection of GUI mRNA into Xenopus skin leads to BCC-like lesions

(Dahmane et a l, 1997). Mice overexpressing G lil under the control of the keratin 5

promoter develop spontaneous BCCs as well as other epidermal tumours, that are not

dependent on the mutation of Ras or p53 (Nilsson et a/.,2000). Recently mice that are

hemizygous for Patched display medulloblastomas, another of the tumours indicative of

the genetic abnormality (Zurawel et a l, 2000; Gorlin, 1987).

1.4.3 Squamous Cell Carcinoma

SCC is another neoplasm that arises from the basal layer of the epidermis (Figure 1.4).

Like BCC, the main causitive agent is again chronic sun exposure. Unlike BCC, they

appear to progress through precursor lesions. A possible candidate precursor lesion is

actinic keratosis, scaly skin caused by sun exposure (Marks, 1990). It is thought that

around 3% of these lesions go on to become SCCs in situ, and subsequently become

malignant (Marks et a l, 1988). SCCs appear to acquire multiple mutations in multiple

(41)

genes in a similar fashion to the multistep carcinogenesis model proposed by Vogelstein

(Vogelstein and Kinzler, 1993). In mice, SCCs that are produced by chemical

carcinogenesis progress through hyperproliferate papillomas, onto invasive and in some

cases metastatic tumours (Yuspa., 1986; Yuspa., 1994)

Carcinogenesis in the mouse begins with tumour promotion, typically a genetic mutation

that is phenotypically silent. The promoted cells undergo clonal expansion, which

eventually gives rise to papillomas. The c-Ras gene is frequently heterozygous in these

papillomas (For example Balmain et a l, 1984). The papilloma progresses, acquiring

more genetic hits and chromosomal abnormalilites, until malignant conversion can take

place. In carcinomas both copies of the c-Ras gene are typically hit (Quintalla et a l,

1986; Bianchi et al., 1990). Other genes typically altered on the way to carcinoma

include members of the TGF family, protein kinase C, with later hits including changes in

expression of integrins, and proteases, both of which promote invasion of malignant

keratinoytes (Reviewed in Yuspa., 1994).

Human SCC appears to progess along similar pathways. Typically multiple genetic hits

that include Ras and p53 (Field et a l, 1992). Indeed p53 mutations are seen in pre

malignant kératinocytes, typically C-T and CC-TT transitions associated with damage

from ultraviolet light, and are clonally expanded in sun exposed areas, awaiting further

mutations in other genes (Jonason et al., 1996). There is greater variation in genetic

content in SCCs compared to BCCs with the loss and amplification of chromosomes

(Quinn et al.„ 1994), as well as the mutation and amplification of classical oncogenes

(i.e. Ras) (Field et al., 1992). This suggests that the origin of BCC and SCC are very

different.

SCCs tend to exhibit regions that differentiate, so they tend to express high levels of

proteins normally expressed in the suprabasal epidermis. The expression of proteins that

display variation in BCC, for example, integrins, may have diagnostic potential in SCC of

the oral cavity, where reduction in the levels of integrin expression, particularly the pi

and a6p4 integrins correlate with poor prognosis. (Bagutti et a l, 1998). Routinely,

(42)

(Suminami et a l, 1998). These appear to act through the degradation of proteins involved

in apoptosis and inflammation (Suminami et al., 1998).

(43)

1.5 Kératinocyte Stem Cells

There is a requirement for the epidermis to be able to repopulate as there is constant

shedding of squames from the surface of the epidermis (Holbrook., 1994). When the

epidermis is injured, new epidermis has to be produced during wound healing

(Holbrook., 1994). Repopulation and turnover are possible due to the presence of a

population of stem cells that can give rise to both the epidermis itself, and its adnexa, the

hair follicle and the sebacous gland (Odland., 1991). Evidence for keratinocyte stem cells

was first accumulated in the mouse, where only 10% of the basal cells were able to

reconstruct normal epidermis after severe irradiation (Withers., 1967; Rotten and

Hendry., 1973). As approximately 60% of the basal cells are actively cycling Withers.,

1967; Rotten and Hendry., 1973), this subdivides the basal layer into 3 putative

compartments, actively dividing cells that can reconstruct injured epidermis (stem cells),

actively dividing cells that cannot reconstruct epidermis (transit amplifying cells), and

non-dividing cells (committed progenitors). By inference therefore, stem cells have an

unlimited potential for cell division, and little likelihood of differentiation. Transit cells

on the other hand only divide a limited number of times and have a higher likelihood of

terminal differentiation (Figure 1.6). Understanding the properties of stem and transit

amplifying cells has involved the use of in vivo and in vitro models as well as newer

novel approaches such as whole mount epidermal staining (Jensen et al., 1999). What

follows is a summary of the knowledge accrued so far.

1.5.1 Keratinocyte Cell Culture

For many years, the culture of human kératinocytes by established methods (Rheinwald

1989) has been used to produce epidermal sheet for grafting onto bums (Gallico et al.,

1984; Compton et al., 1998). The fact that these grafts persist for long periods of time

proves that epidermal stem cells are retained in cell culture. When kératinocytes are

cultured on a layer of mitotically inactive 3T3 cells at clonal density, that is a single cell

gives rise to a colony of kératinocytes, then only 20-40% of cells plated typically give

(44)

Basal I Suprabasal |

Committed to

Stem Transit Terminal Terminally

Amplifying Differentiation Differentiating

C

Unlimited

5-6 Times

Actively Dividing _Post-Mitotic

Proliferative Abortive

I Colonies | Colonies | No Colony Forming Ability [

Figure 1.6 Populations of the interfoUicular keratinocyte lineage

(45)

types, those that are large and proliferative (typically containing thousands of cells), and

those that are small (normally 32 cells or less), with all the cells producing markers of

terminal differentiation, such as involucrin (Adams and Watt., 1989; Jones and Watt.,

1993). These colonies are known as abortive colonies. It is assumed that the founders of

proliferative colonies have the characteristics of stem cells, whereas the founders of

abortive colonies have the characteristics of transit amplifying cells (Jones and Watt.,

1993; demonstrated also in Gandarillas and Watt., 1997; Zhu and Watt., 1999; Zhu ef a l,

1999; Lowell et al., 2000)

One essential characteristic of stem cells is their ability to divide effectively limitlessly.

The ability of the cells of a proliferative colony to themselves found proliferative

colonies is a more stringent assay for a stem cell (Barrandon and Green., 1987; Rochat et

al., 1994). Three types of colony founder were observed using this approach. A founder

that produced little or no secondary colonies and the cells of the colonies were all

expressing terminal differentiation markers (a terminal colony) was referred to as a

paraclone. Founders producing no terminal colonies were referred to as holoclones.

Founders with intermediate qualities were meroclones. How do these three classifications

compare with the abortive/proliferative classifications? Holoclones, paraclones and

meroclones can all produce proliferative colonies but have different proliferative

potential (Barrandon and Green., 1987). Most if not all of the secondary colonies of a

paraclone have the properties of abortive colonies. However the number of divisions a

paraclone can undergo prior to terminal differentiation are significantly greater than the

number of divisions of a cell that produces an abortive colony, and so are unlikely to be

the transit amplifying cells as described above. Cells move from being holoclones,

through meroclone and paraclone to transit amplifying cells then they terminally

differentiate. The hope is that finding new markers will allow the better characterisation

of this continuum of proliferative potential.

1.5.2 pi Integrin as a Stem Cell Marker

Adhesion receptors are attractive candidates for stem cell markers as they have the ability

Analysis of gene expression in normal and neoplastic keratinocytes