1 DEVELOPING TUMOR-ASSOCIATED SOMATIC MUTATIONS AS BIOMARKERS OF CANCER RISK Barbara Parsons...

11

DEVELOPING TUMOR-ASSOCIATED SOMATIC MUTATIONS AS BIOMARKERS OF

CANCER RISK

Barbara Parsons

Division of Genetic and Reproductive Toxicology National Center for Toxicological Research

I count 1, 2, 3, 4 , 5 p53

mutants and…oh…~300,000

wild-type DNA molecules.

ACB-PCR

22

Regulatory Research Need

To determine whether/how quantitative measurement of tumor-associated mutation can be used to improve cancer risk assessment (first steps toward validating the use of tumor-associated somatic mutation as a biomarker for cancer risk).

Research Goal

Albertini et al. (2003) The use of non-tumor data in cancer risk assessment: reflections on butadiene, vinyl chloride and benzene. Regulatory Toxicology and Pharmacology 37: 105-132

“Reliance on animal tumor incidence data with its inherent need to extrapolate to humans introduces considerable uncertainty into the risk assessment process.”

33

EPA’s Cancer risk assessmentguidelines indicate risk assessmentshould be based on an understandingof chemical mode-of-action andkey events in carcinogenesis.

Somatic mutations are considered the earliest biomarkers of chemicaleffect (tumor-associated mutations considered early biomarkers of disease state).

A large literature supports the interpretation that mutation in oncogenes and tumor suppressor genes are key events in carcinogenesis.

Tumor-associated mutations considered more relevant biomarkers of chemical effect than mutations in surrogate reporter genes (hprt, lacI, and Tk).

Advantages of DNA-based measurement of tumor-associated mutations

Primary strategy to improve chemicalrisk assessment: use mechanistic

information to augment bioassay results

• Low dose extrapolation

• Rodent to human extrapolation

44

“Colorectal cancers arise through a gradual series of histological changes - the adenoma-carcinoma sequence-resulting from specific genetic “hits” at a handful of oncogene and tumour suppressor genes.” Fodde et al., Nature Reviews Cancer 1, 55-67 (2001).

Hallmarks of Cancer by Hanahan and Weinberg, Cell 100, 57-70 (2000) indicates several acquired characteristics of tumors can be caused by specific point mutations – Ras and p53.

Data from transgenic p53 and ras rodents accepted in carcinogenicity testing.

At the 2006 EMS meeting, Dr. Channa Keshava indicated EPA weighs oncogene/tumors suppressor gene mutation more heavily than reporter gene mutational data in a weight-of-evidence approach.

Tumor-associated mutations are acceptedas key events in carcinogenesis

55

Allele-specific Competitive Blocker-PCR (ACB-PCR)

UP

Wild-type allele Mutant alleleGGT

Little or no amplification of the wild -type allele

Selective amplification of the mutant allele

UP = upstream primer MSP = mutant-specific primerBP = non-extendable blocker primer ends in dideoxyguanosine

GTT

CCA CAA

UPAGBP ATMSP

UP





GTT

CCA CAA

UPAGBP ATMSP





GTT

CCA CAA

UPAGBP ATMSP

Priming strategy for K-Priming strategy for K-RASRAS codon 12 GGT codon 12 GGT GTT mutation GTT mutation

*

66

Quantifying Mutant Fraction

Isolate genomic DNA from tissue

Synthesize first-round PCR product

(Pfu polymerase)

Aliquot, quantify all unknowns and standards

ACB-PCR of duplicate MF standards, no mutant, no DNA controls, and ~24 unknowns in parallel, per experiment

Polyacrylamide gel electrophoresis, measure

fluorescence, use MF standards to a construct a

standard curve, calculate the MF (ratio of mutant to wild-

type sequence of unknowns, repeat assay 3 times

Exp. 1

Exp. 2

Unknowns10-2 10-3 10-4 10-5 0 no DNA10-1 10-2 10-3 10-4 10-5 0 no DNA10-1

Mutant Fraction

1e-6 1e-5 1e-4 1e-3 1e-2 1e-1 1e+0

Fluorescence (in Pixels)

0

1e+5

2e+5

3e+5

4e+5

5e+5

R2=0.9924

no mutant control

77

Mouse H-Ras codon 61 CAA to AAA mutation

Mouse p53 codon 270 CGT to TGT mutation

Mouse K-RAS codon 12 GGT to TGT mutation

Human K-RAS codon 12 GGT to GTT mutation

Human K-RAS codon 12 GGT to GAT mutation

Rat K-Ras codon 12 GGT to GTT mutation

Rat K-Ras codon 12 GGT to GAT mutation

ACB-PCR assays developed to date

The ACB-PCR methodology has been developed for seven different mutations, each with a sensitivity of 10-5 (i.e., detects 3 mutant DNA molecules among 300,000 wild-type molecules).

Limit of detection 10-5, although the value calculated from the standard curve (values below 10-5) is usually used in statistical analyses.

88

ACB-PCR was used to investigate relationship between DNA adducts, H-Ras codon 61 CAA to AAA mutation, and tumor induction in newborn B6C3F1 and C57BL/6 mice treated with 0.3 mol 4-aminobiphenyl

Tumor data was available from a newborn mouse assay, where tumor induction by 0.3 umol of 4-ABP was scored at 1 year .

B6C3F1 and C57Bl/6 mice were given i.p. injections of 4-ABP (or DMSO vehicle) on postnatal days 8 and 15 days (12 mice per treatment group).

Some animals sacrificed 24 hours after the second dose for liver DNA adduct analyses (Dr. Fred Beland).

Livers were harvested 8 months after treatment - normal by gross pathological examination.

DNA isolated from livers, made 1st round PCR product, then analyzed for H-Ras codon 61 CAA to AAA mutation by ACB-PCR.

“The more we understand about the applied dose metabolism mutation effect continuum, the more confidence we can have in a cancer risk assessment”

Principles for using non-tumor data in cancer risk assessmentAlbertini et al., 2003

99

4-ABP DMSO

Samples 1

-12

Exp 1 Exp 2

Samples 13

-24

Exp 1 Exp 2

10-3 10-4 10-5 0 no DNA4-ABP DMSO

Samples 1

-12

Exp 1 Exp 2

Samples 13

-24

Exp 1 Exp 2

10-3 10-4 10-5 0 no DNA4-ABP DMSO

Samples 1

-12

Exp 1 Exp 2

Samples 13

-24

Exp 1 Exp 2

10-3 10-4 10-5 0 no DNA4-ABP DMSO

Samples 1

-12

Exp 1 Exp 2

Samples 13

-24

Exp 1 Exp 2

10-3 10-4 10-5 0 no DNA

Induction of mutation and correlation with strain susceptibility

4-ABPB6

DMSOB6

4-ABPC57

DMSOC57

10-6

10-5

10-4

10-3

10-2

H-ras

mutant fraction

Treatment

4-ABPB6

DMSOB6

4-ABPC57

DMSOC57

4-ABPB6

DMSOB6

4-ABPC57

DMSOC57

10-6

10-5

10-4

10-3

10-2

10-6

10-5

10-4

10-3

10-2

H-ras

mutant fraction

Treatment

P=0.0515

P=0.0008

Molecular Carcinogenesis 42:193-201 (2005)

7.0 x 10-54-ABPC57BL/6N3.48 - fold5.0 - fold

1.4 x 10-5DMSOC57BL/6N

44.9 x 10-54-ABPB6C3F1

3.46 - fold34.5 - fold1.3 x 10-5DMSOB6C3F1

Change in geometric mean MF

Change in Average MF

with treatment

Average MF

TreatmentMouse Strain

7.0 x 10-54-ABPC57BL/6N3.48 - fold5.0 - fold

1.4 x 10-5DMSOC57BL/6N

44.9 x 10-54-ABPB6C3F1

3.46 - fold34.5 - fold1.3 x 10-5DMSOB6C3F1

Change in geometric mean MF

Change in Average MF

with treatment

Average MF

TreatmentMouse Strain

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Can liver H-Ras MF at 8 monthspredict tumor development at 1 year?

A. 4-ABP-treated mice B. DMSO control mice

4.17 x 10 -3

7.62 x 10 -4

2.55 x 10 -4

6.38 x 10 -5

4.47 x 10 -5

3.83 x 10 -5

2.44 x 10 -5

1.08 x 10 -5

8.45 x 10 -6

2.96 x 10 -6

Rank MF

2.63 x 10 -6

2.38 x 10 -6

1

2

3

10

11

12

7

8

9

4

5

6

Tumor Response

Non-H-ras codon 61 tumors

Micewithouttumors

5.13 x 10 -5

1.91 x 10 -5

1.70 x 10 -5

1.40 x 10 -5

1.19 x 10 -5

1.14 x 10 -5

7.75 x 10 -6

7.11 x 10 -6

6.18 x 10 -6

4.23 x 10 -6

Rank MF

3.54 x 10 -6

2.52 x 10 -6

1

2

3

10

11

12

7

8

9

4

5

6

Tumor Response

H-ras codon 61 tumors

Micewithouttumors

Non-H-ras codon 61 tumors

H-ras codon 61 tumors

Spontaneous H-Ras codon 12 CAA to AAA MF in mouse liver is closer to 10-5 than 10-7 or 10-8 as was expected based on reporter gene MFs.

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Compared the levels of two different K-Ras codon 12 mutations in livers of Big Blue rats treated with N-hydroxy-2-acetylaminofluorene in an attempt to distinguish between chemical-induced induction of de novo mutation vs. chemically-induced amplification of pre-existing mutation.

G T mutation, the predominant mutagenic specificity of N-OH-AAFG A mutation, the most common spontaneous mutation

Tao Chen et al. characterized lacI mutation in six week old Big Blue rats given four i.p. injections of 25 mg/kg N-OH-AAF or the vehicle control at four day intervals. Environmental and Molecular Mutagenesis (2001) 37: 203-214.

Page McKinzie measured theinduction of K-Ras codon 12GGT GTT and GGT GATmutation in liver DNA usingACB-PCR.

“Non-tumor data is critical for determining mechanism/mode of action”


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Comparison of lacI and K-Ras MF measurementssuggests N-OH-AAF may cause amplification of

pre-existing mutation in rat liver

McKinzie et al. (2006) Mutagenesis 21: 391-397

K-Ras

lacIMutation Treatment

Total Mutant

Frequency

Percent of Mutation Spectrum

Mutant Frequency per mutable site

Fold-Increase

G → T Control 26 10x -6 18 0.03 10x -6 N-OH-AAF 407 10x -6 34 0.92 10x -6 30.7

G → A Control 26 10x -6 41 0.07 10x -6 N-OH-AAF 407 10x -6 20 0.53 10x -6 7.6

Mutation Treatment Average MF Fold-

Increase

GGT → GTT Control 50 10X -6 N-OH-AAF 165 10X -6 3.3

GGT → GAT Control 132 0 10X -6 N-OH-AAF 845 0 10X -6 6.4

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Sunlight preferentially induces CT mutation at PyrmeCpG target sites, codon 270 is such a target.

This mutation has a dominant negative phenotype.

The codon 270 CGT to TGT mutation has been found in a significant percentage (20-60%) of mouse SCCs induced by UV-B or SSL.

p53 mutation is viewed as a key causal event in the development of sunlight/UV-B induced squamous cell carcinomas (SCCs) in both mouse and human.

“Non-tumor data can improve the validity of extrapolating from high doses to low doses”


Conducted a dose-response assessment, measuring the induction of p53 codon 270 CGT to TGT mutation by simulated solar light (SSL).

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Phototox center exposure room

Filtered 6.5 kW xenon arc light mimics

terrestrial exposure to sunlight

SKH-1 hairless mice receive sub-toxic doses of 0, 6.85, 13.70, or 20.55 mJ∙CIE/cm2 per day, five days per week (equivalent to 0, 7.5, 15 or 30 minutes of exposure to terrestrial sunlight)

p53 mutation measured in skin after 4, 16, or 28 weeks of exposure.

National Toxicology Program Center for Phototoxicology

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4 Weeks

16 Weeks

28 Weeks

28 Weeks

10-1 10-2 10-3 10-4 10-5 0No DNA

No DNA10-1 10-2 10-3 10-4 10-5 0

Mutant Fraction Standards


Exp 1

Exp 1

Exp 2

Exp 2

mJ•CIE/cm2

mJ•CIE/cm2

0 6.85 13.7 20.55

0 6.85 13.7 20.55

10-1 10-2 10-3 10-4 10-5 0No DNA

No DNA10-1 10-2 10-3 10-4 10-5 0



Exp 1

Exp 1

Exp 2

Exp 2

mJ•CIE/cm2

mJ•CIE/cm2

0 6.85 13.7 20.550 6.85 13.7 20.55

0 6.85 13.7 20.550 6.85 13.713.7 20.5520.55

10-1 10-2 10-3 10-4 10-5 0No DNA

No DNA10-1 10-2 10-3 10-4 10-5 0



Exp 1

Exp 1

Exp 2

Exp 2

mJ•CIE/cm2

mJ•CIE/cm2

0 6.85 13.7 20.55

0 6.85 13.7 20.55

4 Weeks

16 Weeks

28 Weeks

28 Weeks

10-1 10-2 10-3 10-4 10-5 0No DNA

No DNA10-1 10-2 10-3 10-4 10-5 0



Exp 1

Exp 1

Exp 2

Exp 2

mJ•CIE/cm2

mJ•CIE/cm2

0 6.85 13.7 20.55

0 6.85 13.7 20.55

10-1 10-2 10-3 10-4 10-5 0No DNA

No DNA10-1 10-2 10-3 10-4 10-5 0



Exp 1

Exp 1

Exp 2

Exp 2

mJ•CIE/cm2

mJ•CIE/cm2

0 6.85 13.7 20.550 6.85 13.7 20.55

0 6.85 13.7 20.550 6.85 13.713.7 20.5520.55

10-1 10-2 10-3 10-4 10-5 0No DNA

No DNA10-1 10-2 10-3 10-4 10-5 0



Exp 1

Exp 1

Exp 2

Exp 2

mJ•CIE/cm2

mJ•CIE/cm2

0 6.85 13.7 20.55

0 6.85 13.7 20.55

Measured the p53 codon 270 CGT to TGT mutational response induced by 4 different doses of SSL – after three different durations of exposure

1616

Dose-response analysis and measurement of spontaneous p53 MF in skin

Trend, p=0.282

Trend, p<0.001

Trend, p<0.001P = 0.008

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The increase in p53 MF with cumulative dose is highly-significant

P = <0.0001

MF = 10α100.0016*d, where α is the spontaneous MF at a

particular timepoint and d is the dose of SSL in mJ CIE/cm2

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ACB-PCR analysis of 24 SSL-induced lesions

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MF=0.5

p53 MF measurements in skin tumors

All skin tumors have significant levels of p53 codon 270 mutation, but the mutation appears to represent a sub-population of tumor cells.

2020

0.00

0.02

0.04

0.06

0.08

0.10

0.12

p53

Mutant Fraction

Skin28 weeks

n = 6

Tumors32 weeks

n = 24

Comparison of p53 MF in skin and skin tumors

Tumors induced by 32 weeks of exposure at the high dose had significantly more p53 mutation than skin exposed for 28 weeks at the high dose (t-test, P = 0.0006).

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Future research efforts on p53 project

Isolating DNA from replicate needle biopsies from 4 and 7 month animals (medium and high doses).

Trying to use ACB-PCR to characterized the frequency distribution of p53 mutation within skin.

Effort to describe changes in p53 mutant clone size during tumor development.

Hypothesize that p53 mutation is being removed at 7 months but some clones, those on the path to tumor development, must be getting larger

2222

K-RAS mutation is a “key event” in the development of sporadic colon cancer K-RAS mutation has been detected in normal colon and in all stages of colon

cancer development K-RAS mutation causes constitutive

mitogenic signaling. K-RAS mutation induces expression of

VEGF which induces angiogenesis. Detection of K-RAS codon 12 GGT to GTT

mutation in sporadic colonic adeno-carcinoma has been associated withpoor prognosis.

“Endogenous levels of biomarkers can provide information for risk assessment” “Biomarkers must be selected and interpreted in light of what is known about

mechanism of action”


Quantified the levels of K-RAS codon 12 GAT and GTT mutation in the colonic mucosa of human and rat. Determined the levels of K-RAS mutation in human tissues corresponding to pathological stages of colon tumor development, information that may be used to develop mathematical models of carcinogenesis based on oncogene/tumor suppressor gene MFs.

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34%237/6087K-RAS

56%45/802APCAdenocarcinoma

77%10/136K-RAS

45%10/222APCAdenoma

49%43/874K-RAS

3%7/2045APCACF

Mutation Positive

Positive/number screened

Number of Studies

Mutation reported

Lesion

34%237/6087K-RAS

56%45/802APCAdenocarcinoma

77%10/136K-RAS

45%10/222APCAdenoma

49%43/874K-RAS

3%7/2045APCACF

Mutation Positive

Positive/number screened

Number of Studies

Mutation reported

Lesion

Literature review of APC and K-RAS mutation prevalence in sporadic colon cancer

GAT mutation in ~20% of colonic adenocarcinoma

GTT mutation in ~7% of colonic adenocarcinoma

Fodde et al. (2001) Nature Reviews Cancer 1:55-67

2424

Mutation theory and modeling sporadic colon tumor development

Vogelgram

Luebeck and Moolgavkar (2002) PNAS

Assumes clonal amplification after acquiring multiple mutations

2525

ACB-PCR analysis ofhuman colon tissues

Collected fresh tissue from the Central Arkansas Veterans Healthcare System (CAVHS) hospital, as well as fresh-frozen tissues from the Cooperative Human Tissue Network (CHTN).

77 samples analyzed in triplicate for K-RAS codon 12 GAT and GTT mutation (462 data points).

Samples analyzed to date:Normal (individuals w/o colon ca.) 2Tumor distal mucosa (5 or more cm from tumor) 17Tumor proximal mucosa (2 to 5 cm from tumor) 14Tumor margin (normal tumor-adjacent) 10Adenoma 12Adenocarcinoma 21

Additional samples, including ACF remain to be examined.

2626

Exp. 1

Exp. 2

Exp. 1

Exp. 2

10-2 10-3 10-4 10-5 0 no DNA10-1 Mucosa

no DNA Adenoma Carcinoma10-2 10-3 10-4 10-5 010-1 Mucosa

Exp. 1

Exp. 2

Exp. 1

Exp. 2

10-2 10-3 10-4 10-5 0 no DNA10-1 Mucosa

no DNA Adenoma Carcinoma10-2 10-3 10-4 10-5 010-1 Mucosa

K-RAS codon 12 GGT → GTT ACB- ( 1PCR Samples -24)

2727

Nor

mal

Tum

or

dist

al

muc

osa

Tum

or

prox

imal

muc

osa

Ade

nom

a

Tum

or

mar

gin Adenocarcinoma

GAT

GTT

2828

Significant Findings Normal-appearing colon contains a significant level of K-RAS mutation (with

GAT>GTT).

Significant differences in GAT and GTT MF were found in the different tissues (Kruskal-Wallis ANOVA on ranks, P=0.013 and P=0.006) with GAT MF in adenoma and adenocarcinomas significantly higher than in mucosa and GTT MF in adenoma significantly higher than in mucosa and adenocarcinoma.

Many tumors carry bothK-RAS mutations assub-populations.

K-RAS

Mutant Fraction

1e-6

1e-5

1e-4

1e-3

1e-2

1e-1

1e+0

Tumor

-distalMucosa

Tumor

-distalMucosa

Tumor

-proximalMucosa

Tumor Margin

Adenoma

AdenocarcinomaTumor

-proximalMucosa

Tumor Margin

Adenoma

Adenocarcinoma

GTT GAT

17 14 10 12 21 17 14 10 12 21

K-RAS

Mutant Fraction

1e-6

1e-5

1e-4

1e-3

1e-2

1e-1

1e+0

Tumor

-distalMucosa

Tumor

-distalMucosa

Tumor

-proximalMucosa

Tumor Margin

Adenoma

AdenocarcinomaTumor

-proximalMucosa

Tumor Margin

Adenoma

Adenocarcinoma

GTT GAT

17 14 10 12 21 17 14 10 12 21

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Significant Findings

The decrease in K-RAS GTTMF during tumor progressionsuggests that tumors arecomposed of more than oneclone of tumor cells (K-RASmutant and non-K-RAS mutant) and that during progression to adenocarcinoma,K-RAS mutant cells are eitherdying or other clone(s) are proliferating faster.

K-RAS

Mutant Fraction

1e-6

1e-5

1e-4

1e-3

1e-2

1e-1

1e+0

Tumor

-distalMucosa

Tumor

-distalMucosa

Tumor

-proximalMucosa

Tumor Margin

Adenoma

AdenocarcinomaTumor

-proximalMucosa

Tumor Margin

Adenoma

Adenocarcinoma

GTT GAT

17 14 10 12 21 17 14 10 12 21

K-RAS

Mutant Fraction

1e-6

1e-5

1e-4

1e-3

1e-2

1e-1

1e+0

Tumor

-distalMucosa

Tumor

-distalMucosa

Tumor

-proximalMucosa

Tumor Margin

Adenoma

AdenocarcinomaTumor

-proximalMucosa

Tumor Margin

Adenoma

Adenocarcinoma

GTT GAT

17 14 10 12 21 17 14 10 12 21

3030

It is widely accepted that tumors are monoclonal in origin (arise from a single initiated cell). This conclusion is based on studies from the 1970s which showed the same X-chromosome-linked marker was inactivation in all cells of a tumor (colon tumors).

One Renegade Cell (Science Masters) (Paperback) by Robert A. Weinberg (Author)

NCI Teacher’s Guide, “Understanding Cancer”…cancer cells are indigenous cells—abnormal cells that arise from the body's normal tissues. Furthermore, virtually all malignant tumors are monoclonal in origin, that is, derived from a single ancestral cell that somehow underwent conversion from a normal to a cancerous state.

Amazon.com

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Evidence supporting polyclonal tumor origin

76% of adenomas in an XO/XY FAP chimeric woman with average patch size of 1.48 crypts were polyclonal. [Novelli et al., Science 272:1187-1190 (1996)].

Novelli demonstrated that X-inactivation happens early enough in develoment that the human colon has an average patch size of 450 crypts, meaning there is a strong bias for detecting monoclonality. [Novelli et al., PNAS 100:3311-3314 (2003)].

Min+/- heterozygous, ROSA26 chimeric mice also shows high frequency of polyclonal adenomas. [Thliveris et al., PNAS 102:6960 (2005)].

In mouse, active short-range interaction between multiple initiated crypts is responsible for polyclonality of adenomas. Mutant crypts may cause elevated proliferation rate of stem cells in adjacent crypts or interaction between initiated clones may favor tumor survival and development of polyclonal adenomas. [Leedham et al., Cell Proliferation 38: 387 (2005), Thliveris et al., PNAS 102:6960 (2005)].

This issue is currently being re-examined. A recent survey of the literature (since 1997) found 13 reports that conclude tumors are monoclonal and >20 reports with evidence of polyclonality for 10 different tumor types.

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Interpreting Evidence of Tumor Clonality Monoclonal origin

Cannot prove a negative, so reports of monoclonality should be interpreted cautiously. Reports of polyclonality, perhaps, should be given more weight.

Conceptually, the best evidence of polyclonality will be obtained using markers heterogeneously distributed throughout the normal tissue and present as sub-populations within tumors.

Polyclonal origin

Thliveris et al., PNAS 102:6960 (2005).

3333

Comparing spontaneous levels of K-Ras mutation in rat and human colonic mucosa

*Mean age 67 years #38 week-old rats (Page McKinzie)

MUTATIONFREQUENCY IN HUMAN COLON

TUMORS

GEOMETRIC MEAN MF

Human Mucosa* Rat Mucosa#

GAT 20% 8.38 x 10-5 1.3 x 10-3

GTT 7% 6.67 x 10-6 5.0 X 10-5

Colon of a 38 week-old rat has a K-RAS MF 7 to 15 times the of a 67 year-old man

“Endogenous levels of biomarkers can provide information for risk assessment”


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Human Colon Biometry

Colon lengtha = 152 cm (5 feet) Colon widthb = 7.0 ± 2.9 cm Colon area = 152 cm x 7 cm = 1,064 cm2 Crypt densityc = 75 crypts/cm or 5,625 crypts/cm2 Crypt number/colon = colon length x colon width x crypt density Crypt number/colon = 152 cm x 7 cm x 5,625 crypts/mm2/ colon = 5,985,000 crypts/colon Cells/cryptd = 112 cells/crypt Cells/colon = 112 cells/crypt x 5,985,000 crypts/colon = 670,320,000 Cells/colon x K-Ras mutant fractionb = Number of mutant K-Ras cells/colon 670,320,000 x 8.38 x 10-5 (K-Ras GAT) = 56,173 K-Ras GAT mutant cells/human colon 670,320,000 x 6.67 x 10-6 (K-Ras GTT) = 4,471 K-Ras GTT mutant cells/human colon If distributed as individual mutant crypts, then 541 mutant crypts are present at a density of 0.5 mutant crypts/cm2

a. Gray, Henry (1918) Anatomy of the Human Body, 20 th ed. b. Parsons et al., average from 10 pathology reports, unpublished observations. c. Jenkins, D., M. Balsitis, S. Gallivan, M.F. Dixon, H.M. Gilmour, N.A. Shephard, A. Theodossi, and G.T. Williams (1997) J. Clin. Pathol. 50: 93 -105. d. Holt, P.R., N. Arber, B. Halmos, K. Forde, H. Kissileff, K.A. McGlynn, S.F. Moss, K. Fan, K. Yang, and M. Lipkin (2002) Cancer Epidemiology,

Biomarkers & Prevention 11:113 -119.

Rat Colon Biometry

Colon lengtha = 13 cm Colon widthb = 0.6 cm Colon area = 7.8 cm2 Crypt densitya = 188.3 crypts/cm or 35,457 crypts/cm2 Crypt number/colon = colon area x crypt density Crypt number/colon = 7.8 cm2 x 35,457 crypts/cm2/colon = 276,564 crypts/colon Cells/cryptc = 66 cells/crypt Cells/colon = 66 cells/crypt x 276,564 crypts/colon = 18,253,207 Cells/colon x K-Ras mutant fractionb = Number of mutant K-Ras cells/colon 18,253,207 x 1.3 x 10-3 (K-Ras GAT) = 23,729 K-Ras GAT mutant cells/rat colon 18,253,207 x 5.0 x 10-5 (K-Ras GTT) = 913 K-Ras GTT mutant cells/rat colon If distributed as individual mutant crypts, then 373 mutant crypts are present at a density of 47 mutant crypts/cm2

a. Jenab, M. and L.U. Thompson (2000) Carcinogenesis 21:1547-1552. b. McKinzie, P. - unpublished observations c. Ma, Q.-Y, K.E. Williamson, and B.J. Rowlands (2004) Word J. Gastroenterology 10:218-222.

3535

Can we model carcinogenesis based on the frequency and spatial distribution of different tumor-

associated mutations?

Frequency and distribution of mutation relates to frequency of adenoma formation

K-Ras GTT K-Ras GAT APC

Adenoma

Adenocarcinoma

Michael A. Newton, University of Wisconsin Seminar, On Polyclonality of Intestinal Tumors describes the “Random Collision Hypothesis” originally proposed by Armitage http://sprott.physics.wisc.edu/Chaos-Complexity/newton06.pdf

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Summary

Developing oncogene and tumor suppressor gene mutations as biomarkers of cancer risk.

Demonstrated that spontaneous levels of K-Ras and p53 mutation are much higher than expected based on comparisons with neutral reporter gene measurements.

Demonstrated statistically-significant induction of oncogene and tumor suppressor gene mutation using model mutagens (4-ABP, N-OH-AAF, SSL).

ACB-PCR measurements will be useful for establishing chemical mode-of-action (distinguishing de novo mutation from amplification of pre-existing mutation).

Used ACB-PCR to describe the dose response relationship between SSL exposure and induction of p53 codon 270 CGT to TGT MF in mouse skin.

Somatic oncogene and tumor suppressor gene mutations are frequently represented as sub-populations within tumors.

Analysis of K-RAS MF in human and rat colon illustrates how ACB-PCR can be used to inform species extrapolation (better understanding of how the rodent model compares to human).

Quantitative analysis of tumor-associated mutation through the different stages of carcinogenesis can provide a scientific framework for the use of tumor-associated mutation as a metric of cancer risk.

In the future, these measurements may be applied on a case-by-case basis, as part of the weight of evidence approach to cancer risk assessment.

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Pilot dose-response study in collaboration with Jeff Ross (NHEERL/EPA) to measure K-Ras TGT mutation in lung tissue of A/J mice exposed to a range of doses of benzo[a]pyrene (low to tumorigenic doses). Investigating the utility of ACB-PCR in measuring a response at low dose with a short expression time and the relationship between DNA adducts and mutation.

Planning a collaboration with Harvey Clewell (CIIT Centers for Health Research) to measure dose-dependent induction of a p53 mutation in the nasal mucosa of formaldehyde–treated rats. CIIT will collect data on the dose-dependent induction of toxicity-induced cell proliferation. We will learn whether the dose-dependent appearance of p53 mutation coincides with that of formaldehyde-induced cytotoxity and compensatory cell proliferation.

Studies Planned or in Progress

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p53 SSL StudyTracie VerklerRobert DelongchampAlan WarbrittonLetha CouchBarbara MillerPeggy WebbPaul MellickPaul Howard

Rat K-Ras StudiesPage McKinzieRobert DelongchampJohn LatendresseTao Chen

Human K-RAS Study

Kathy MarchantRobert DelongchampPage McKinzieTucker PattersonRalph BroadwaterLaura LampsLawrence Kim

This research was supported by:NCTRNTP Center for Phototoxicology

Martha MooreDirector, Division of Genetic and Reproductive Toxicology

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ReferencesAblertini, R., H. Clewel, M.W. Himmelstein, E. Morinello, S. Olin, J. Preston, L.

Scarano, M.T. Smith, J. Swenberg, R. Tice, and C. Travis (2003) The use of non-tumor data in cancer risk assessment: reflections on butadiene, vinyl chloride, and benzene. Regulatory Toxicology and Pharmacology 37: 105-132.

Chen, T., R.A. Mittelstaedt, S.D. Shelton, S.B. Dass, M.G. Manjanatha, D.A. Casciano, and R.H. Heflich (2001) Gene- and tissue-specificity of mutation in Big Blue rats treated with the hepatocarcinogen N-hydroxy-2-acetylaminofluorene. Environmental and Molecular Mutagenesis 37: 203-214.

Fearon, E.R. and B. Vogelstein (1990) A genetic model for colorectal tumorigenesis. Cell 61: 759-767.

Fodde, R., R. Smits, and H. Clevers (2001) APC, signal transduction and genetic instability in colorectal cancer. Nature Reviews Cancer 1: 55-67.

Hanahan, D., and R.A. Weinberg (2000) The hallmarks of cancer. Cell 100: 57-70.

Leedham, S.J., S. Schier, T. Thliveris, R.B. Halberg, M.A. Newton, and N.A. Wright (2005) From gene mutations to tumours – stem cells in gastrointestinal carcinogenesis. Cell Proliferation 38: 387-405.

Luebeck, E.G., and S.H. Moolgavkar (2002) Multistage carcinogenesis and the incidence of colorectal cancer. PNAS 99: 15095-15100.

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McKinzie, P.B., R.R. Delongchamp, T. Chen, and B.L. Parsons (2006) ACB-PCR Measurement of K-ras codon 12 mutant fractions in livers of Big Blue rats treated with N-hydroxy-2-acetylaminofluorene. Mutagenesis 21: 391-397.

McKinzie, P.B., R. Delongchamp, R.H. Heflich, and B.L. Parsons (2001) Prospects for applying genotypic selection of somatic oncomutation to chemical risk assessment. Mutation Research 489: 47-78.

McKinzie, P.B., and B.L. Parsons (2002) Detection of rare K-ras codon 12 mutations using allele-specific competitive blocker PCR. Mutation Research 517: 209-220.

Newton, M.A (2006) On polyclonality of intestinal tumors. University of Wisconsin. Chaos and Complex Systems April 2006. http://sprott.physics.wisc.edu/Chaos-Complexity/newton06.pdf

Novelli, M.R., J.A. Williamson, I.P.M. Tomlinson, G. Elia, S.V. Hodgson, I.C. Talbot, W.F. Bodmer, N.A. Wright (1996) Polyclonal origin of colonic adenomas in an XO/XY patient with FAP. Science 272: 1187-1190.

Novelli, M., A. Cossu, D. Oukrif, A. Auaglia, S. Lakhani, R. Poulsom, P. Sasieni, P. Carta, M. Contini, A. Pasca, G. Palmieri, W. Bodmer, F. Tanda, and N. Wright (2003) X-inactivation patch size in human female tissue confounds the assessment of tumor clonality. PNAS 100: 3311-3314.

References

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Parsons, B.L., F.A. Beland, L.S. Von Tungeln, R.R. Delongchamp, P. Fu, and R.H. Heflich (2005) Levels of 4-aminobiphenyl-induced somatic H-ras mutation in mouse liver DNA correlate with potential for liver tumor development. Molecular Carcinogenesis 42:193-201.

Parsons, B.L., R.R. Delongchamp, F.A. Beland, R.H. Heflich (2006) Levels of H-ras codon 61 CAAAAA mutation: response to 4-ABP-treatment and Pms2-deficiency. Mutagenesis 21: 29-34.

Parsons, B.L. and R.H. Heflich (1997) Genotypic selection methods for the direct analysis of point mutations. Mutation Research, 387: 97-121.

Parsons, B.L. and R.H. Heflich (1998) Detection of a mouse H-ras codon 61 mutation using a modified allele-specific competitive blocker PCR genotypic selection method. Mutagenesis 13: 581-588.

Parsons, B.L. P.B. McKinzie, and R.H. Heflich (2005) ACB-PCR detection of rare point mutation. In: Molecular Toxicology Protocols (Methods in Molecular Biology Series), P. Keohavong and S. Grant (eds.), Humana Press, Totawa, NJ.

References

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Thilveris, A.T., R.B. Halberg, L. Clipson, W.F. Dove, R. Sullivan, M.K. Washington, S. Standhope, and M.A. Newton (2005) Polyclonality of familial murine adenomas: analyses of mouse chimeras with low tumor multiplicity suggest short-range interactions. PNAS 102: 3960-6965.

Verkler, T.L., L.H. Couch, P.C. Howard, and B.L. Parsons (2005) Quantifying levels of p53 mutation in mouse skin tumors. Environmental and Molecular Mutagenesis 45: 427-43.

References

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Human K-ras MF ResultsHuman K-ras MF Results

K-ras Codon 12 GAT MF K-ras Codon 12 GTT MF Type of Colonic

Tissue

Number of

Samples

Percent Positive Samples

Geometric Mean

Percent Positive Samples

Geometric Mean

Normal Mucosa 2 100 (2/2) 6.39 x 10-5 50 (1/2) 1.01 x 10-5

Tumor-Distal Mucosa 17 100 (17/17) 6.79 x 10-5 24 (4/17) 6.40 x 10-6

Tumor-Proximal Mucosa 14 100 (14/14) 1.13 x 10-4 0 (2/14) 6.61 x 10-6

Tumor-Adjacent Mucosa 10 100 (10/10) 7.87 x 10-5 70 (7/10) 3.95 x 10-5

Adenoma 12 100 (12/12) 1.69 x 10-3 100 (9/12) 6.18 x 10-4

Adenocarcinoma 21 100 (21/21) 1.23 x 10-3 33 (7/21) 2.92 x 10-5

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Next steps:Determine mutant clone size

Perform ACB-PCR “fluctuation test” on mucosa to determine the frequency and size distributions of mutant clones (multiple small biopsies).

Convert this information to number of K-RAS GAT and GTT mutant and wild-type crypts.

Approximate the frequency of APC mutant clones from their abundance relative to K-RAS ACF in the literature (for FAP and sporadic).

Mathematically (?) relate the expected co-occurrence of mutant crypts with the probability of developing K-RAS mutant sporadic colon cancer and determine whether this relationship predicts the increased probability of cancer in FAP patients when the increased number of APC crypts is incorporated.

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Potential implications of polyclonal tumor formation

Mutant clones may contribute transiently to tumor development.

Cannot interpret the most abundant mutation in a tumor as the “initiating” mutation.

Possibility that a few specific mutations are universally involved in the development of a particular tumor type.

Can’t correctly model tumor development without an accurate understanding of the process!

Can’t accurately interpret changes in the frequency of tumor-associated mutations unless their role on the process of carcinogenesis is understood.

Quantitative measurements of tumor-associated mutation provide new opportunities to investigate the earliest events in carcinogenesis.

1 DEVELOPING TUMOR-ASSOCIATED SOMATIC MUTATIONS AS BIOMARKERS OF CANCER RISK Barbara Parsons...

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