FACULTY OF MEDICINE & HEALTH SCIENCES

SCHOOL OF MOLECULAR MEDICAL SCIENCES

Bachelor of Medical Sciences Honours Year Project Dissertation

Dissertation Title: An Investigation of C-kit and PDGFR1A receptor Activating Mutations in Colorectal Cancer

Name: Rishi Gulati

Student ID: 4068628

Homebase: Molecular and Cellular Pathology

Academic Year 2009/10

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The work presented in this dissertation by Rishi Gulati is his own work except where

stated in the text. Technical assistance with the project has been acknowledged where

appropriate.

.

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I, Rishi Gulati, understand the nature of plagiarism outlined in the University of

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2

An Investigation of C-kit and PDGF! receptor Activating Mutations

in Colorectal Cancer

Rishi Gulati

Faculty of Medicine and Health Sciences

Department of Clinical Pathology

Queens Medical Centre

Nottingham

Supervisor: Professor Mohammed Ilyas

Bench Supervisors: Dr. Salih Ibrahem

Mr. Darryl Jackson

Dr. Wakkas Fadhil

January 21st, 2009

Year 3 Bachelor of Medical Sciences Honours Project 2009-2010

Summary: 149 words Number of tables: 3

Main text: 4338 words Number of figures: 6

3

Table Of Contents

Abstract..4 1. Introduction.5

a. C-kit..5 b. PDGFRa..6 c. Links between PDGFRa and C-kit.7 d. High-Resolution Melting7

i. Benefits.8 ii. Negatives.8

e. DNA Sequencing.8 2. Materials And Methods10

a. Design of Primers..10 b. Polymerase Chain Reaction10 c. Mutation Detection using HRM Analysis (High-Resolution Amplicon

Melting) .11 d. Melting Curves Analysis12 e. Direct DNA Sequencing.12

i. DNA Purification.12 ii. DNA Concentration Measurement..12 iii. Sequencing..12

f. DNA Sequence Analysis13 3. Results.14

a. C-kit...14 i. Exon 915 ii. Exon 11...15 iii. Exon 13.16 iv. Exon 17.16

b. PDGFRa..16 i. Exon 12.16 ii. Exon 18.17

c. Variations within and Between Samples.18 4. Discussion ...........................19

a. The Project..19 b. HRM.............................20 c. Further Study.21

5. Acknowledgements.23 6. References.24

4

Abstract

Colorectal cancer arises due to mutations in important genes. C-kit and PDGFR1A

are oncogenes that are mutated in a variety of tumours. Mutations of these genes are

mutually exclusive suggesting that they are part of a common pathway. In this study, PCR

followed by High-resolution amplicon melting analysis (HRMAA) was used to screen for

activating C-kit and PDGFR1a mutations in a series of 20 colorectal cancer cell lines.

Primers were designed for known mutation hotspots in mutations in exons 9, 11, 13, and 17

for C-kit and exons 12 and 18 for PDGF1A. HRM analysis revealed aberrant melting of

PCR products in C-kit exon 9, 13, 17 and PDGFR1A exon 12 and 18. However, direct

sequencing of these PCR products showed the presence of polymorphisms but mutations

were not identified. It is therefore unlikely that mutations in these genes play a significant

role in the development of colorectal cancer.

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Introduction

Colorectal cancer is the third most common type of cancer. The World Health

Organisation (WHO) estimates that 945 000 new cases occur yearly, with 492 000

deaths, making it the fourth most frequent cause of cancer deaths worldwide (1). The

genetic basis of cancer was first described by Fearson and Vogelstein as a multi-step

process of genetic alterations involved in the development of a common human

neoplasm, exemplified by the transitional shift to metastatic carcinomas from pre-

existing adenomas (4). Recent studies of the colorectal cancer genome of malignant

tumours suggests that up to 20 genes are mutated during the development of colorectal

cancer (2). It is important to note, however, that it is not solely these individual genes

which determine tumorigenesis, but also the pathways on which they act that leads to

deregulation of cell growth (3). This project looks specifically at two genes, C-kit and

PDGFR!.

C-kit

C-kit is located on the long arm of chromosome 4, between bands q11 and q12.

It consists of 21 exons, 5186 base pairs in length, and encodes a 976 amino acid protein

(ENST00000288135).

C-kit, also called CD117, encodes a transmembrane glycoprotein receptor

tyrosine kinase (5). One known ligand for this receptor is the stem cell factor which

binds to the receptor, causing it to dimerize and become phosphorlyated, activating

downstream signalling pathways involved in cell proliferation, differentiation, survival,

adhesion and chemotaxis. Ligand-independent gain-of-function mutations can also occur

(6). C-KIT is expressed in haematopoietic precursors, mast cells, melanocytes, germ

cells, and interstitial cells of Cajal (ICC) (7).

Gain-of-function mutations can result in c-kit activation independent of ligand,

resulting in neoplastic growth (7). Mutations in exons 9, 11, 13, and 17 have been

reported in hematopoietic cells, small cell lung cancer, and gastrointestinal stromal

tumours (8). Previous data suggests that tumours containing missense mutations in

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exon 11 possibly have a better prognosis than those with deletions or insertions (10).

Also, c-kit activating mutations in exon 9 might characterise a highly malignant tumor

(11). Upregulated C-kit mRNA expression has been detected in the human

adenocarcinoma cell lines HT29 and DLD-1 (9) and protects human colon adenocarinoma

cells against apoptosis and enhance their invasive potential (9). Non tumorigenic

expression has been detected in SK-CO-1. (16).

PDGFR1A

PDGFR1A, (Platelet-Derived Growth Factor Receptor alpha) is located on the long

arm of chromosome 4, on band q12. It consists of 23 exons, 6383 base pairs in length,

and encodes a 1089 amino acid protein (ENST00000257290).

PDGF consists of a family of A, B, C, and D polypeptides which promote cell

migration, proliferation, and survival by binding by disulfide bridges as homodimeric or

heterodimeric tyrosine kinase receptors PDGFR! and PDGFR" (12). The dimer complex

has biological significance as reduction irreversibly inactivates the factor (12). However,

there is interdependibility between the receptors because of their functional redundancy

(13). It is a prerequisite for activation of the kinase (14). PDGFR1A is an important

factor regulating cell proliferation, cell differentiation, cell growth, development and

cancer. The receptor molecule also undergoes conformational change. All three

mechanisms, including dimerization, kinase activation, and conformational change

enable full enzymatic activity directed towards tyrosine residues in the receptor causing

proliferation (14).

PDGF plays a key role in growth and development of placenta and embryo. It is

also responsible for soft tissue healing. Autocrine or paracrine stimulation of PDGFR have

implications for development of disease (14). For example, overexpression of PDGFR1A

is known to cause gastrointestinal stromal tumors and non-small cell lung cancer.

Mutations in PDGF are known to be partial cause to atherosclerosis, pulmonary fibrosis,

angiogenesis, and tumorigenesis. (13)

7

Recent studies relate PDGFR!/" expression with the metastatic behavior of

colorectal cancer. It was shown that 83% PDGFR! compared with 60% PDGFR"

expression appeared in colorectal cancer cell lines. Co-expression occurred in 57% of the

cancer cell lines, and 29% of the samples depicted mono-expression for metastasis (15).

Links Between PDGFR! and C-kit

Mutually exclusive gain-of-function C-kit and PDGFR1A mutations have been

documented in a majority of GISTs. C-kit and PDGFR1A are members of the type III

Tyrosine Kinase Family and have extensive sequence and structural homology (34, 35).

Ligand-binding to a group of cell surface growth factor receptors having tyrosine

kinase function, such as those for C-kit and PDGFR!, activates intracellular downstream

signalling pathways controlling cell-proliferation, adhesion, apoptosis, survival, and

differentiation. These pathways include RTK-GRB2-SOS-RAS-RAF-MEK-ERK, PI3K-AKT,

PLC# and STAT pathways. (36) Some GISTs do not contain c-kit activating mutations but

instead have similar activating mutations in PDGFR! gene. The frequency of GISTs with

PDGFR! activating mutations is about 19% (37). Thus, c-kit and PDGFR! are both

mutually exclusive and alternative.

Imatinib is a drug used to treat cancers produced from C-kit and PDGFR

mutations. It binds to the site of tyrosine kinase activity, and prevents its activity. It is a

competitive inhibitor of the tyrosine kinase. This is dependent on the mutation status of

C-kit and PDGFR (8). However, it warrants further preclinical investigation and clinical

trials, studies show it is a good chemotherapeutic agent in colorectal cancer prevention

(8).

The ability to identify activating C-kit and PDGFR1A mutations in colorectal cancer

will help identify those colorectal tumours that may respond to imatinib. This might yield

prognostic and therapeutic information.

High-Resolution Melting

C-kit and PDGFR! mutations are gain-of-function mutations that can be detected

by HRM (High resolution melting). HRM analysis detects sequence changes in DNA due

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to alterations in the melting behaviour of DNA (which is monitored by the release of a

fluorescent dsDNA binding dye). When compared to a reference sample, an altered

melting curve denotes the possibility of mutation (Figure 1). Heterozygous mutant

amplicon melt curve changes are noticeable because of mismatching that causes

heteroduplex formation. (21)

Figure 1: HRM analysis detects sequences changes between normal and mutatated DNA -

an example shown below.

Benefits

It is a quick, simple, and inexpensive approach using a saturation dye before PCR,

followed by rapid melting analysis of PCR products. Its sensitivity allows heterozygote

detection accuracy to approach 100%, and specificity can be increased by identifying

polymorphisms - although this may be a confounder in mutation detection (21). HRM

does not require fluorescently labelled oligonucleotides or real-time PCR instruments and

is thus a highly useful method for mutation screening.

Negatives

9

HRM analysis depends strongly on good PCR, instruments and dyes. For example,

LCGreen detects heterozygotes better than most other dyes (23). In fact, it is specifically

designed for detecting DNA variants, and the presence of heteroduplexes formed during

PCR. However, homozygote mutations can sometimes be missed due to the absence of

heteroduplex formation and may require mixing with wild type DNA (21). These include

A to T and G to C SNPs (HR-1 Manual). Small insertions and deletions are more difficult

to detect than substitutions (22). The HR-1 instrument is affected by amplicon GC

content for amplicons above 400 bps because of domain melting (24).

DNA Sequencing

C-kit and PDGFR! mutations can be confirmed by DNA sequencing. DNA

sequencing is far more sensitive technique than most modern techniques, and allows

recognition of frameshift and deletion mutations thus it is advantageous in that it

allows detecting specific mutations (21).

This project makes an effort to scan for mutations for C-kit and PDGFR! using

HRM analysis. This was done using appropriate primers, running PCRs, and using 20

colorectal cancer cell lines and correlating it against published data.

10

Materials and Methods

Design of Primers

Primers specific for exons 9,11,13, and 17 for the human c-kit gene, and exons

12,18 for the human PDGFR1A gene were designed in past projects with the use of

Primer3 (Table 2). Their sequences have appeared in previous studies (Table 1, 10).

Polymerase Chain Reaction

A standard polymerase chain reaction consisted of the elements presented in

Table 1.

Table 1: Volumes of

A Standard PCR:

1 reaction

(!L)

Hotshot (2x) 5

Forward 0.4

Reverse 0.4

LC Dye 1

H2O 2.2

DNA 1

TOTAL 10

Each PCR was covered using 10 #L mineral oil to avoid evaporation, which may

lead to change in melting properties. The concentration of magnesium in hotshot was

0.3mM, of primers was 250 nM and quantity of DNA template was 20 ng.

Each PCR was performed on a PEQLAB Advancer Primus 96 thermocycler

(PEQLAB). The initial step was denaturation for 10 minutes at 95 deg. C for denaturation

and enzyme activation. This was followed by 45 cycles that consisted of a denaturation

step at 95 deg. C for 3 seconds, followed by a temperature transition rate of 20 deg.

C/sec to a set annealing temperature. This was 58 deg. C for c-kit 9 and 11, 62 deg. C

for c-kit exon 13 and PDGFRA exons 12 and 18), and 57 deg. C for c-kit exon 17 for 10

seconds. (10,37) This was followed by a temperature transition rate of 2 deg. C to 72

deg. C for 20 seconds, during which elongation occurs (annealing and extension). The

11

samples were momentarily heated to 95 deg. C for heteroduplex formation and brought

to cool to 22 deg. C at a ramp rate of 2.0 deg C/s. They were stored in the PCR machine

at a temperature of 8 deg. C until the machine was stopped manually. All samples were

run in either duplicate or triplicate, depending on the credibility of the results, including

the quality of the amplicon product as determined by the LED fluorescence level, and the

shape of the melt curve from high resolution melting.

Table 2: A summary of the primers sequences used, the PCR products lengths, optimal annealing temperatures, and melting profiles used for each reaction.

Oligonucleotide

Name

Sequence (5' to 3') Length Product

Size

Annealing

Temperature

Exon 9 - F GATGCTCTGCTTCTGTACTG 20 CKIT

Exon 9 - R GCCTAAACATCCCCTTAAATTGG 23

235 58oC

Exon 11 - F CTCTCCAGAGTGCTCTAATGAC 22 CKIT

Exon 11 - R AGCCCCTGTTTCATACTGACC 21

219 58oC

Exon 13 - F CGGCCATGACTGTCGCTGTAA 21 CKIT

Exon 13 - R CTCCAATGGTGCAGGCTCCAA 21

227 62oC

Exon 17 - F TCTCCTCCAACCTAATAGTG 20 CKIT

Exon 17 - R GGACTGTCAAGCAGAGAAT 19

170 57oC

Exon 18 - F GCTACAGATGGCTTGATCCTGAGT 24 PDGFR

a Exon 18 - R AGCCTGACCAGTGAGGGAAGT 21

200 62oC

Exon 12 - F CTGGTGCACTGGGACTTTGGTAAT 24 PDGFR

a Exon 12 - R GTGTGCAAGGGAAAAGGGAGTCT 23

235 62oC

Mutation Detection using HRM Analysis (High-Resolution Amplicon Melting)

After PCR, the PCR products were transferred to the HR-1, a high-resolution DNA

melting analysis instrument (Idaho Technology, Salt Lake City, UT). A melting analysis

was performed.

20 Colorectal cancer cell lines were studied for each exon. These cell lines were:

C125, C32, C80, C84, Caco2, DLD1, GP2D, HCA7, HCT116, HRA-19, HT29, LoVo,

LS1034, RKO, SK-CO-1, SW1116, SW480, SW837, SW948. For each cell line, each exon

was amplified at its optimal annealing temperature using 20 ng of previously extracted

DNA as template. PCR products were subsequently transferred to Roche LightCycler

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glass capillary tubes specific for the HR-1 instrument. They were subject to a melting

profile to generate heteroduplexes and fully base-paired wild types.

Samples were also transferred to the 7500 Fast Real-Time PCR instrument to

confirm potential mutants with wild types. A melting analysis was performed during PCR

in real-time.

Melting Curves Analysis

The melting curve of each reaction, for each particular exon, were created and

compared. The accumulation of melting curves were normalized, based on linear regions

for each curve before and after melting points, and upper fluorescence and lower

baseline values common for all curves. A temperature shift was applied along the X-axis

for a common temperature to cluster the melting curves into groups. As a standard, this

is usually the temperature that heteroduplexes melt.

Difference plots were subsequently produced. Obvious differences in curve shapes

and melting temperatures become visible if they exist.

Derivative plots, which plot the rate of change of fluorescence versus temperature,

display the melting peaks at which the DNA heteroduplexes denature at the greatest rate.

Direct DNA Sequencing

DNA Purification

PCR was usually performed in a final volume of 25 #L, except for exon 13 HT29

and DLD which were performed in 10 #L. The PCR products were purified using the

QIAquick purification kit (by Qiagen). Enzyme contamination of DNA samples can

interfere with subsequent applications. Silica-membrane based purification of the PCR

products using a bind-wash-elute procedure was used to prevent this.

DNA Concentration Measurement

A ThermoScientific NanoDrop Spectrophotometer was used to measure DNA

concentration in 1 #L samples. It was used to measure intensity as a function of

wavelength of light to determine concentration of the samples.

Sequencing

13

The PCR amplicons were sent for DNA sequencing using the appropriate PCR

primers.

DNA sequencing was performed at the DNA sequencing facility at the University

of Nottingham. Previous work indicates a normal melting curve represents a normal DNA

sequence (33). As such, only abnormal curves were evaluated by direct sequencing. DNA

sequencing was performed by the Biopolymer Synthesis and Analysis Unit.

DNA Sequence Analysis

Analysis of the sequence was performed using Finch TV, ensemble.org SNPcheck

v2.0 (http://ngrl.manchester.ac.uk/SNPCheckV2/snpcheck.htm).

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Results

All 20 cell lines were tested for each

exon of each gene using the primers,

annealing temperatures, and melting

thermal profiles listed in table 2.

The first set of PCR products were

run on 2% agarose gels to verify the correct

product size. For this, a 100 bp size ladder

was used (Figure 2).

Figure 2: An example of PCR products separated

on 2% agarose gel. PDGFR1A exon 18 and C-kit

exon 11 primers were used at annealing

temperatures of 58iiC and 62oC respectively to

produce the PCR products.

CKIT

Exon 9 a) b)

c) d) Figure 3: (a) C-kit exon 9 PCR derivative plot for test reaction for 5 cell lines (b) Normalized and

temperature shifted c-kit exon 9 melting curves for 20 cells lines (c) Difference plots for c-kit exon

GP

2D

HC

A7

SK

CO

-1

C8

4

NTC

C1

25

VA

C0

20

HC

A7

C8

0

GP

2D

NTC

PDGFRA C-KIT

DNA LADDER 100 bp

15

9 products normalised against one cell line product (d) Derivative plot for c-kit exon 9 products for

20 cell lines

Exon 9 showed a different melting curve shape for GP2D when compared to other

cell lines (Figure 3). The analysis was repeated twice and the same melting curve was

obtained. There are two melting peaks in the melting curve plot. The presence of two

peaks is explained by CG-rich regions, and thus two melting domains which make them

melt in two parts. GP2D was, as such, sent to be sequenced. Sequencing results showed

GP2D has C to T polymorphism at codon 488 (ACG>ATG, threonine to methionine, SNP

rs56225530).

Exon 11 a) b)

c) d) Figure 4: (a) C-kit exon 11 PCR derivative plot for test reaction for 7 cell lines (b) Normalized and

temperature shifted c-kit exon 11 melting curves for 20 cells lines (c) Difference plots for c-kit exon 11 products normalised against one cell line product (d) Derivative plot for c-kit exon 9 products

for 20 cell lines

There were no differences in melting curve shapes for any cell line in exon 11

(Figure 4).

Exon 13

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A nested PCR of exon 13 was divided into two parts for PCR because a smaller

product size means a greater sensitivity for HRM. A smaller amplicon will have a greater

sensitivity due to the effect of the change on the melting, and improved specificity as

there will be a smaller chance of including SNPs. Exon 13 showed a different melting

curve shape for HT29 and DLD when compared to other cell lines. The analysis was

repeated twice and the same melting curve was obtained. HT29 and DLD were, as such,

sent to be sequenced. Sequencing results showed HT29 showed no evidence of mutation.

DLD also came back as a false-positive sample from DNA sequencing (it did not generate

reliable data).

Exon 17

Exon 17 showed a different melting curve shape for GP2D when compared to

other cell lines. Exon 17 was amplified in one reaction. The analysis was repeated twice

and the same melting curve was obtained. GP2D was, as such, sent to be sequenced.

Sequencing results showed GP2D has C to T polymorphism at codon 798 (ATC>ATT,

isoleucine). This makes it a synonymous polymorphism, and evidently, there is no amino

acid change.

PDGFRA

Exon 12 a) b)

17

c) d) Figure 5: (a) PDGFRa exon 12 PCR derivative plot for test reaction for 5 cell lines (b) Normalized and temperature shifted PDGFRa exon 12 melting curves for 20 cells lines (c) Difference plots for

PDGFRa exon 12 products normalised against one cell line product (d) Derivative plot for PDGFRa exon 12 products for 20 cell lines

Exon 12 showed a different melting curve shape for SK-CO-1 when compared to

other cell lines (Figure 5). Exon 12 was amplified in one reaction. The analysis was

repeated twice and the same melting curve was obtained. SK-CO-1 was consequently

sequenced. Sequencing results showed SK-CO-1 did not have a heteroduplex mutation.

The primers were inserted into In-Silico PCR, which searches a database and returns a

sequence output containing all sequences that lie between and include the primer pair.

This predicted amplicon product was then blasted against the sequence obtained from

DNA sequencing. A homozygous polymorphism became evident at codon 567 (CCA>CCG,

proline). This makes it a synonymous polymorphism, and there is no nucleotide base

change (Figure 6).

Figure 6: Blast analysis compared the output from direct DNA sequencing to the published sequence. For PDGFR1A exon 12, the result from blasting shown below with SNP indicated in blue.

The query sample is the sample from sequencing and the subject sequence is that which is expected.

Exon 18

Exon 18 showed a different melting curve shape for SK-CO-1 and SW837 when

compared to other cell lines. Exon 12 was amplified in two reactions. The analysis was

repeated four times and the same melting curve was obtained. SK-CO-1 and SW837

were, as such, sent to be sequenced. Sequencing results showed SK-CO-1 and SW837

both had a heteroduplex mutation. Sequencing results showed SK-CO-1 has C to T

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polymorphism at codon 824 (GTC>GTT, valine). This makes it a synonymous

polymorphism, and evidently, there is no amino acid change. Sequencing results also

showed SW837 has C to T polymorphism at codon 824 (GTC>GTT, valine). This makes it

a synonymous polymorphism, and evidently, there is no amino acid change.

Table 3: Summary of mutated cell lines using

high-resolution melting and sequencing results

Cell lines

Detected Mutation and Sequencing Result

1 C125*

2 C32

3 C80*

4 C84*

5 Caco2

6 DLD1* Exon 13 -> false positive sample

7 GP2D Exon 9, codon 488, C :T (hetero) Exon 17, codon 798, C:T (hetero)

8 HCA7*

9 HCT116

10 HRA-19

11 HT29 Exon 13 => false positive sample

12 LoVo

13 LS1034*

14 RKO

15 SK-CO-1 Exon 12, codon 567, A:G (homo) Exon 18, codon 824, C:T (hetero)

16 SW1116*

17 SW480*

18 SW837 Exon 18, codon 824, C:T (hetero)

19 SW948

20 VACO10MS*

Variations within and Between Samples

Different melting curves showed normal variation, even between wild types.

Variations can be seen through the difference plots generated. The accepted

fluorescence background noise in the difference plot was agreed to be -2 to 2. This was

the expected up and down variations in each analysis for the wild type cell lines.

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Discussion:

In the present study it was clearly shown that c-kit for exons 9,11,13, and 17 and

PDGFR1A receptor activating mutations in exons 12 and 18 do not exist in colorectal

cancer cell lines.

The Project

High-resolution melting curve analysis was used to screen for exon 9, 11, 13, and

17 in c-kit and exons 12 and 18 for PDGFR1A. Cases showing abnormal melt curves were

subject to direct DNA sequencing. Abnormal melt curves correlated with variations in

DNA sequences. There were no activating mutations in any of these exons.

HRM analysis proved to be a reliable method of detection mutations. This may be

a reason for which, without forming a heteroduplex or being mixed with wild type DNA,

the melt curve of the SK-CO-1 cell line for exon 12 of PDGFR indicated the presence of a

potential mutation, confirmed to be a homozygous SNP.

One false-positive result was obtained from this project for DLD-1 of exon 13 for C-

kit. This can possibly be due to poor DNA quality (25). The C125 cell line for C-kit exon

11 is suspected as poor quality DNA and was not further tested. Concurrent with findings

from Idaho Technologies, this confirms a sensitivity and specificity of more than 98%.

These findings are comparable with other available data, using other screening

techniques (26).

Discrepancies in HT29 were confirmed by validating results with DNA sequencing.

SK-CO-1 and SW837 cell lines had the same polymorphism. The HR-1 machine is not

governed by a defined set of rules for the upper limit of amplicon size that can be

analyzed. It is presumed that product sizes in the range of 100-250 bases can be

routinely analyzed. However, localized regions rich or poor In G:C base pair content can

experience domain melting, which melts at a temperature above that of the remaining

portion of the fragment. Domain melting is most likely to be seen in amplicon PCR

products over 200 bases, but can be seen in fragments as small as 100 bases in length.

A domain melting profile existed for C-kit exon 9, which is 235 bp in length. C-kit exon

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11,13 and PDGFR! exon 12 did not present with domain melting, even though their

amplicons were greater than 200 bps in length.

HRA19, HT29, CACO2 and SK-CO-1, DLD-1 showed abnormal curves on separate

occasions in repeated high-resolution analysis for C-kit exon 13. This can be due to

differences chemical composition, or constituent aberrations that might affect LC Green

binding. Samples showing similar melting patterns had similar changes in DNA sequence

- this was true only for heteroduplex SNPs (27).

HRM

Several screen methods have been described which could be used to screen DNA

isolated from colorectal cancers for activating mutations. However, there are limitations

to each. Single-stranded conformation polymorphism is unable to detect specific

mutations and is deemed unreliable (28). PCR product-length analysis has a likelihood of

missing point mutations (29). Capillary electrophoresis cannot detect point mutations

(30). High performance Liquid Chromatography is considered useful, bar its complexity

and cost. High Resolution melting is a powerful technique to detect mutations,

polymorphisms and epigenetic differences in dsDNA.

High-resolution melting analysis scans for sequence variations in a target gene.

The shape of the melting curve appears as fluorescence as a function of temperature.

In this investigation, high-resolution melting curve analysis was used. As a

standard principle, high-resolution melting is only as effective as the quality of the PCR

amplification product. Determining the best concentration for individual reaction

components, and the best thermal-cycling parameters that will optimise the

amplifications is crucial.

The HR-1 machine is useful in that it allows mutation scanning in fragments of

amplified DNA, which are analysed for homoduplexes and heteroduplexes. Modern

scanning techniques require a separate step to identify heteroduplexes. Melting curve

analysis allows easy detection of heteroduplex mutant alleles because of its low melting

21

temperature. However, homozygotes are more difficult to detect. Furthermore, HRM

cannot discriminate between SNPs and mutations as both represent sequence changes.

The HR-1 instrument requires the PCR products be transferred from the normal

plastic tubes to special capillaries for melting. This limits the usefulness of the

instrument as it increases the chance of contamination. Newer more advanced machines,

(such as the Roche thermal cycler) allow PCR and HRM to be carried out in the same

tube.

It is a lot more labor intensive to analyze multiple exons with several annealing

temperature PCRs, where each PCR has to be run separately according to its optimal

annealing temperature. However this problem will be common to most PCR based

methods.

The 7500 Fast-Real Time machine performs real-time PCR and melt curve

analysis simultaneously. It avoids post-PCR processing and allows fast PCR processing

and melting analysis in real-time. However, it lacks precise temperature control, and

high resolution scanning cannot be performed on this machine. (HR-1 manual)

Further Study

It is understood that some homozygous mutations can only be detected when

heteroduplexes are formed. As such, the SK-CO-1 cell line for C-kit exon 12 should have

been tested by mixing with wild type DNA. It is important to note that HT29 has in the

past, although not for C-kit and PDGFR! genes, remained highly unpredictable. For

example, for the case of P53 mutations, it appears as a homozygous mutant in exon 8

for one study (31) and wild type in another (32). Perhaps this is reason for further study

of this cell line as a determinant of colorectal cancer.

As a final note, a consistent melting profile for genes would have helped in clarity

of analyzing data. This study employed HRM analysis to detect mutations in C-kit and

PDGFR!. It is a useful technique with upto 98% specificity. Real-time PCR is far more

accurate, but lacks temperature control. The purity of the cell lines ensured consistency

of results. C106, COLO201, COLO205, COLO320DM, HCA46, HT55, HuTu80, SW1222,

22

SW620 and VAC05 could also be tested with the specified genes. Other extonic data,

such as that for PDGFR1A exon 14 can also be tested. Without doubt, high-resolution

melting analysis remains a versatile component in detecting gene mutations that are

biologically and clinically important.

C-kit and PDGFR1A have been shown to be up-regulated in colonic tumours, and

these changes in expression seem to be related to some sort of functional effect. The

purpose of this study was to look for aberrant melts to detect mutations in these genes,

but these proved to be SNPs rather than activating mutations for colorectal cancer.

Perhaps there are mutations in other genes upstream that are causing up-regulation of

C-kit and PDGFR1A.

23

Acknowledgements

I thank my supervisors (Clinical Pathology, QMC) including Professor Mohammed Ilyas for

his aura of knowledge, Dr. Salih Ibrahem of course, who is my bench supervisor, Mr. Darryl

Jackson, the one and only, Dr. Wakkas Fadhil, for his motivational speeches, Ms. Karin Kindle for

her expertise in gel electropheresis, Ms. Sonia Ouadi whom I have never met but am thankful for

the DNA sequencing (!) (Biopolymer Synthesis and Analysis Unit), and, on a more serious note, Dr.

Sally Chappell (Clinical Chemistry, QMC) for her help with DNA sequence analysis.

24

References

1. Colorectal Cancer. In: Steward BW, Kleihues P, eds. World Cancer Report. Lyon: IARC Press, 2003: 198202

2. T. Sjoblom, S. Jones, L.D. Wood, D.W. Parsons, J. Lin, T.D. Barber, D. Mandelker, R.J. Leary, J. Ptak, N. Silliman, S. Szabo, P. Buckhaults, C. Farrell, P. Meeh, S.D. Markowitz, J. Willis, D. Dawson, J.K. Willson, A.F. Gazdar, J. Hartigan, L. Wu, C.Liu, G. Parmigiani, B.H. Park, K.E. Bachman, N. Papadopoulos, B. Vogelstein, K.W.

3. Kinzler, V.E. Velculescu, The consensus coding sequences of human breast and 4. colorectal cancers, Science 314 (2006) 268274 5. B. Vogelstein, K.W. Kinzler, Cancer gene and the pathways they control, Nat.Med.

10 (2004) 789799 6. E.R. Fearon, B. Vogelstein, A genetic model for colorectal tumorigenesis, Cell 61 7. (1990) 759767 8. J. Hornick, C. Fletcher. Immunohistochemical Staining for KIT(CD117) in Soft

Tissue Sarcomas Is Very Limited in Distribution. American Journal of Clinical

Pathology 117(2002).

9.O $ scar Fuster, Eva Barraga $ n, Pascual Bolufer, Jose $ Cervera, Maria Jose $ Larra $ yoz,, Antonio Jime $ nez-Velasco, Joaqun Martnez-Lo $ pez, Ana Valencia, Federico Moscardo $ , and Miguel A $ ngel Sanz. Rapid Detection of KIT mutations in Core-binding Factor Acute Myeloid Leukemia Using High-Resolution Melting Analysis. Journal of Molecular Diagnostics. 11(2009) 458-463.

10. C. Willmore, J Holden, L. Zhou, S. Tripp, C. Wittwer, L. Layfield. Detection of c-kit-Activating mutations in Gastrointestinal Stromal Tumors by High-Resolution Amplicon Melting Analysis. American Journal of Clinical Pathology 122 (2004) 206-216.

11. S. Attoub, C. Rivat, S. Rodrigues, S. Van Bocxlaer, M. Bedlin, E. Bruyneel, C.

Louvet, M. Kornprobst, T. Andre, M. Mareel, J. Mester, C. Gespach. The c-kit

Tyrosine Kinase Inhibitor STI571 for Colorectal Cancer Therapy. Cancer Research

62(2002) 4879-4883.

12. Bellone, G., Carbone, A., Sibona, N., Bosco, O., Tibaudi, D., Smirne, C., Martone, T.,

13. Gramigni, C., Camandona, M., Emanuelli, G., and Rodeck, U. Aberrant activation of c-kit protects colon carcinoma cells against apoptosis and enhances their invasive potential. Cancer Res., 61(2001) 2200 2206.

14. Singer S, Rubin BP, Lux ML, et al. Prognostic value of kit mutation type, mitotic activity, and histologic subtype in gastrointestinal stromal tumors. J Clin Oncol. 2002;18:3898- 3905.

15. Heinrich MC, Corless CL, Demetri GD, et al. Kinase mutations and imatinib response in patients with metastatic gastrointestinal stromal tumor. J Clin Oncol. 2003;21:4342- 4349.

16. Heldin CH, Johnsson A, Wennergren S, Wernstedt C, Betsholtz C, Westermark B.

A human osteosarcoma cell line secretes a growth factor structurally related to a

homodimer of PDGF A-chains. Nature. 319(1986) 511-4 .

17. Levitzki A. PDGF receptor kinase inhibitors for the treatment of PDGF driven

diseases. Cytokine Growth Factor Rev. 2004;15:229235

18. Claesson-Welsh, Lena. Platelet-derived Growth Factor Receptor Signals. Journal

of Biological Chemistry. 269(1994) 32023-32026.

19. WEHLER Thomas C. ; FRERICHS Kirsten (1 2) ; GRAF Claudine ; DRESCHER

Daniel (2 3) ; SCHIMANSKI Katrin (2) ; BIESTERFELD Stefan (4) ; BERGER Martin

R. (5) ; KANZLER Stephan (1) ; JUNGINGER Theodor (3) ; GALLE Peter R. (1) ;

MOEHLER Markus (1) ; GOCKEL Ines (2 3) ; SCHIMANSKI Carl C. (1 2).

25

PDGFRa/" expression correlates with the metastatic behavior of human colorectal

cancer: A possible rationale for a molecular targeting strategy. Oncology Reports

19(2008) 697-704.

20. M. Anzano, D. Rieman, W. Prichett, D. Bowen-Pope, R. Greig. Growth Factor

Production by Human Colon Carcinoma Cell Lines. Cancer Research 49 (1989)

2898-2904.

21. Wittwer, Carl. High-Resolution DNA Melting Analysis: Advancements and

Limitations. Human Mutation 30(2009) 857859.

22. van der Stoep N, van Paridon CDM, Janssens T, Krenkova P, Stambergova A,

Macek M, Matthijs G, Bakker E. 2009. Diagnostic guidelines for high resolution

melting curve analysis: an interlaboratory validation of BRCA1 mutation scanning

using the 96- well LightScanner (IT). Human Mutation 30 (2009) 899909.

23. Farrar JS, Reed GH, Wittwer CT. 2009. High resolution melting curve analysis for

molecular diagnositics. In: Patrinos GP, Ansorge W, editors. Molecular Diagnostics,

2nd Ed. Burlington: Elsevier, in press.

24. Reed GH, Wittwer CT. Sensitivity and specificity of single-nucleotide

polymorphism scanning by high-resolution melting analysis. Clinical Chemistry 50

(2004) 17481754.

25. Sheng ZM, Przygodzki RM, OLeary TJ. Rapid screening for kit mutations by

capillary electrophoresis [letter]. Clin Chem.2001;47:1325-1326.

26. R. Yorke, M. Chirala, M. Younes. Journal of Clinical Oncology, 21 (2003) 3885-

3889.

27. Graham, R., Liew, M., Meadows, C.,Lyon, E., and Wittwer, C. T. (2005) Clinical

Chemistry 51(7), 1295-1298

28. Kinoshita K, Isozaki K, Hirota S, et al. Gene mutation and gastrointestinal tumors:

c-kit gene mutation at exon 17 or 13 is very rare in sporadic gastrointestinal

stromal tumors. J Gastroenterol Hepatol. 2003;118:147-150.

29. Sheng ZM, Przygodzki RM, OLeary TJ. Rapid screening for kit mutations by

capillary electrophoresis [letter]. Clin Chem.2001;47:1325-1326.

30. Emile JF, Lemoine A, Bienfait N, et al. Length analysis of polymerase chain

reaction products: a sensitive and reliable technique for the detection of

mutations in kit exon 11 in gastrointestinal stromal tumors. Diagn Mol Pathol.

2002;11:107-112

31. Rodrigues, N. R., Rowan, A., Smith, M. E. F., Kerr, I. B., Bobmer, W. F., Gannon,

J. V., and Lane. D. P. (1990) Proc. Natl. Acad. Sci. 87, 7555-7559

32. Liu, Y., and Bodmer, W. F. (2006) PNAS 103(4), 976981

33. Willmore C, Holden JA, Zhou L, et al. Detection of ckitactivating mutations in

gastrointestinal stromal tumors by high-resolution amplicon melting analysis. Am

J Clin Pathol.2004;122:206-216.

34. Hirota S, Isozaki K, Moriyama Y, et al. Gain-of-function mutations of c-kit in

human gastrointestinal stromal tumors. Science 1998;279:577580.

35. Heinrich MC, Corless CL, Duensing A, et al. PDGFRA activating mutations in

gastrointestinal stromal tumors. Science 2003;299:708710.

36. Gschwind A, Fisher O, Ullrich A. The discovery of receptor tyrosine kinases:

targets for cancer therapy. Nature 4 361-370 (2004)

37. Holden J, Willmore-Payne C, Coppola, et al. High-Resolution Melting Amplicon

Analysis as a Method to Detect c-kit and Platelet-Derived Growth Factor Receptor

!! Activating Mutations in Gastrointestinal Stromal Tumors . Am J Clin

Pathol2007;128:230-238