Transcript Lecture Slides

CANCER MOLECULAR EPIDEMIOLOGY
Epidemiology 242
2009
NUMBERS OF PAPERS/YEAR PUBLISHED
WITH SUBJECT WORDS “MOLECULAR
EPIDEMIOLOGY” USING PUBMED SEARCH
EVOLUTION OF EPIDEMIOLOGY IN
HISTORY
 Systematic
collection and analysis of vital
statistics
 Defined triad of agent-host-vector for both
infectious and chronic disease
 Refine exposure assessment such as jobexposure matrix, dietary and nutritional
analysis
 Defined study design such as case-control
and cohort study
 Use of the advance of statistical and
computational capacities (MLE, Logistic
regression, poission regression)
EVOLUTION OF EPIDEMIOLOGY
Now, it is the time to add biological variables
(physiologic, cellular, subcellular, molecular
levels), which can be assayed by technically
powerful biological methods
 Molecular epidemiology is the use of these
biological markers in epidemiology research.

EPIDEMIOLOGY AND MOLECULAR SCIENCES
EPIDEMIOLOGY

Health effects in
grouped people
Observation and
inference of
association between
variables
 Macro

MOLECULAR SCIENCES
Assessment of the
individual at the
component level
 Experimental proof of
cause and effects


Micro
MOLECULAR EPIDEMIOLOGY AND
TRADITIONAL EPIDEMIOLOGY
These capacities provide additional tool for
epidemiologists studying questions on etiology,
prevention and control of diseases
 Although molecular epidemiology can be viewed
as an evolution step of epidemiology, it generally
dose not represent a shift in the basic paradigm
of epidemiology

TRADITIONAL
MOLECULAR
Association
 High exposure and
single outcome
 Prevention through
control of exposure is
feasible without
understanding
cellular process

Mechanisms
 Smaller and mixed
exposures;
multicausal
 Intervention through
cellular process has
the need to
understand
mechanisms of the
process

BASICS OF MOLECULAR EPIDEMIOLOGY

The term of molecular epidemiology indicates the
incorporation of molecular, cellular, and other
biological measurements into epidemiologic
studies
MOLECULAR EPIDEMIOLOGY
studies
utilizing biological
markers of exposure, disease
and susceptibility
studies which apply current
and future generations of
biomarkers in epidemiologic
research.
FUNCTIONAL DEFINITION OF
MOLECULAR EPIDEMIOLOGY

The use of biologic markers or biologic
measurements in epidemiologic research.
Biological markers (or biomarkers) generally
include biochemical, molecular, genetic,
immunologic, or physiologic signals of events in
biologic system.
MOLECULAR EPIDEMIOLOGY


The goal of molecular epidemiology is to
supplement and integrate, not to replace, existing
methods
Molecular epidemiology can be utilized to
enhance capacity of epidemiology to understand
disease in terms of the interaction of the
environment and heredity.
CAPACITIES OF MOLECULAR
EPIDEMIOLOGY
Identification of Exposure at the smaller scale
 Identification of events earlier in the nature
history of disease
 Evaluation of gene-environment interaction
 In addition, it can be used to reduce
misclassification, to indicate mechanisms, and
enhance risk assessment

STUDY OF BLACK BOX
The concept of a continuum of events between
exposure and disease provide opportunities
 To ensure that epidemiologic research has a
biological basis for hypothesis
 To provide the analysis to test these ideas
 To generate new epidemiological methods to deal
with new challenges
Cancer Epidemiol Biomarkers Prev 2007;16(10). October 2007
MEASUREMENT OF BIOMARKERS
Biomarkers can be measured
quantitatively or
qualitatively by biochemical,
immunochemical, cytogentic,
molecular and genetic
techniques.
MATERIALS FOR BIOMARKER
MEASUREMENT
Biomarkers can be measured
in human biological
materials including normal
and tumor tissues, blood and
urine sample, etc.. Their
biological nature can be
DNA, RNA, and protein, etc.
STUDY QUESTIONS: EXPOSURE MARKERS
 How
reliable are the exposure data
obtained by questionnaire and what type
of misclassification bias result?
 How are the carcinogens metabolized?
What are the dynamics and distribution of
carcinogen metabolization?
 What is the concentration of carcinogens
in peripheral blood? What is the exposure
level in the target tissue? Can we employ
the exposure markers measured in
peripheral blood to predict the
concentrations of exposure at the target
tissue?
EXPOSURE MEASUREMENTS
The powerful tools of molecular biology,
analytical chemistry, and related disciplines
allow measure smaller amounts of exposures
(10-18 -10-21)
Reconstruct past exposure doses using
molecular measurements (biologic dosimetry)
EXPOSURE BIOMARKERS
Mutagenesis vol. 24,117–125, 2009
EXPOSURE MARKERS: DNA ADDUCTS
 Exposure
markers are a group of
biomarkers, which can indicate the
environmental exposures and can be
measured in tumor tissues, or blood or
urine specimens.
 The presence or concentration of specific
environmental carcinogens or other
agents can be measured in biological
specimens, for example, blood levels of
cotinine, polycyclic aromatic hydrocarbon
(PAH) -DNA adducts, 4-aminobiphenyl (4ABP) hemoglobin adducts.
EXPOSURE MARKERS: DNA ADDUCTS

exposure markers measure biological effective
dose, that is, the amount of carcinogens bound to
DNA in the target tissue such as DNA-adducts,
or surrogate measurements which can represent
the exposure levels of the target tissue such as
hemoglobin adducts
EXPOSURE MARKERS
 Aromatic
Amines and 4-ABP DNAAdducts. The human bladder carcinogens
2-naphtylamine and 4-aminobiphenyl, as
well as the suspected carcinogen otoluidine, are present in tobacco and
certain occupational exposures. DNA
adducts of 4-aminobiphenyl were found in
tumor samples from smokers indicating
that this agent may account for some of
the carcinogenicity of tobacco smoke
EXPOSURE MARKERS
 Polycyclic
Aromatic Hydrocarbons (PAH)
and PAH DNA-Adducts. PAHs are
produced by incomplete combustion of
organic materials and the sources of
environmental PAH include industrial
and domestic furnaces, gasoline and diesel
engines and tobacco smoke. PAHs are
carcinogens requiring metabolic activation
to react with cellular macromolecules, the
initial step in tumorigenesis
P32
postlabel
ing
LIMITATIONS OF EXPOSURE MARKERS
 These
markers have to be measured in
biological materials, which requires the
collection of biological specimens;
 Some of exposure markers such as
hemoglobin-adducts and blood level of
cotinine only represent the current
exposure status;
 The costs for measurement of exposure
markers are generally more expensive
than that of questionnaire data.
STUDY QUESTIONS: SUSCEPTIBILITY
GENES



Which gene or enzymes are involved?
Is there any metabolic phenotype related to the
risk of cancer?
Are there any high risk individuals who are
susceptible to cancer and how can we identify
them?
SUSCEPTIBILITY MARKERS
Susceptibility markers represent a group of
tumor markers, which may make an individual
susceptible to cancer.
 These markers may be genetically inherited or
determined.
 They are independent of environmental
exposures.

SUSCEPTIBILITY MARKERS

Tumor susceptibility markers such as P450s,
GSTs, and NATs, act in enzymatic pathways
related to metabolizing and eliminating
carcinogens.
SUSCEPTIBILITY MARKERS
 The
phase I enzymes such as p450
enzyme superfamily metabolize exogenous
or endogenous agents or carcinogens to
intermediates, which can result in DNA
damages and act as risk factors for cancer.
 The phase II enzymes such as glutathione
S-transferase (GST) system are dealing
with detoxification of oxygenated
intermediates by conjugation process,
acting as a protective factors for cancer.
Case 1
Case 2
Case 3
Case 4
Case 5
GST T1
beta-globin
GST M1
Figure. GSTM1 and GSTT1 genotyping from buccal cell DNA.
Case 5 is null for the GSTT1 genotype. Case 2 is null for the
GSTM1 genotype
Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Case 7 Case 8
ile/val
ile/val
ile/ile
val/val
ile/val
ile/ile
Figure. GSTP1 polymorphism
ile/val
ile/ile
14 13
12
11 10
9
8
7
6
5
4
3
PCR P450 2E1 after Using Pst1 RFLP
2
1
Case 1 Case 2 Case 3 Case 4
Case 5
Arg/Arg
Arg/Pro
Arg/Arg
Pro/Pro
Arg/Arg
Figure. P53 polymorphism at codon 72 from buccal cell DNA.
Interactions between smoking and GST M1
(odds ratios* and 95% confidence intervals)
5.29
(1.81, 15.4)
6
5
2.79
(0.97, 7.99)
4
3
2
1.00
1.13
(0.32, 3.95)
1
0
Never/
Positive
Never/ Null Ever/ Positive
Ever/ Null
*Adjusted for age, sex, race, and level of education
ISSUES IN GWAS STUDIES
False positive (multiple comparison)
 False negative (very small p-value)
 Population stratification
 Gene-Environmental Interaction

BACKGROUND
 In
2006 and 2007 GWAS studies identified
associations between SNPs in the 8q24 region
and prostate cancer among Icelandic, Swedish,
European American, African American, and
the Multiethnic Cohort populations.
RESEARCH QUESTIONS: GENETIC AND
MOLECULAR ALTERATIONS



What kinds of damages do the carcinogens make,
and is the damage specific?
Does the DNA repair capacity affect risk and how
can we measure it?
Is there any gene-gene interaction and is there
any gene-environment interaction?
IDENTIFICATION OF EARLIER EVENTS


Identification of the patients at a very early stage
- for better treatment and prognosis to improve
the survival of cancer
Identification of pre-malignant lesions - for
intervention and early treatment to reduce the
incidence of cancer
EARLY BIOLOGICAL RESPONSE: MOLECULAR
GENETIC ALTERATIONS

Molecular genetic markers are defined as a group
of markers which can be induced by certain
carcinogens or by some intermediate end-point
EARLY BIOLOGICAL RESPONSE: MOLECULAR
GENETIC ALTERATIONS

cytogenetic markers such as chromosome
abnormalities by karyotyping;

oncogenes such as RAS family;

tumor suppressor genes such as TP53 and p16
genes.
P53 GENE MUTATIONS

TP53 Mutations as DNA Fingerprints of
Environmental Exposures. The wide range of
involvement of TP53 in human tumors and the
broad spectrum of mutations make this gene a
good candidate for molecular epidemiological
studies
Case 607 Exon 8
1
2
Case 644 Exon 7
1
3
Wild Type
Mutant
G A T C G A T C
A
C/G
Arg
Thr
A
C/G
A
Codon 280
3
Wild Type Mutant
G A T C G A T C
A
G
A
A
2
C
G
A/G
C
G
G
Gly
Ser
A/G
G
C
Codon 244
Figure 8-1. IHC Analysis of p53, p21, and mdm2
Case 1
Case 2
Case 3
(unmethylated)
(unmethylated)
(methylated)
Figure 11. GST P1 methylation from lung cancer tissue.
(U=unmethylated, M=methylated) Case 3 is unmethylated.
AGE AND TP53 MUTATIONS
Age
<50
P53+
No. (%)
6 (8.7)
P53No. (%)
11 (10.0)
Total
No. (%)
17 (9.5)
50-59
16 (23.2)
18 (16.4)
34 (19.0)
60+
47 (68.1)
81 (73.6)
128 (71.5)
GENDER AND TP53 MUTATIONS
Gender
TP53+
No (%)
TP53No (%)
Total
No (%)
Male
47 (71.2)
89 (81.7)
136 (77.7)
Female
19 (28.8)
20 (18.4)
39 (22.3)
RACE AND TP53 MUTATIONS
Race
TP53+
No (%)
TP53No (%)
Total
No. (%)
White
60 (87.0)
100 (90.9)
160 (89.4)
10 (9.1)
19 (10.6)
Non-White 9 (13.0)
EDUCATION AND TP53 MUTATIONS
Education
(years)
<12
TP53+
No. (%)
2 (2.9)
TP53No. (%)
4 (3.6)
Total
No. (%)
6 (3.4)
12-16
58 (84.1)
76 (69.1)
134 (74.9)
>16
9 (13.0)
30 (27.3)
39 (21.8)
TP53 MUTATIONS IN BLADDER CANCER
BP changes
Transitions
GC AT
(at CpG)
ATGC
Transversions
GCTA
GCCG
ATTA
ATCG
Deletion/Insert.
Reported, n=200 Current study
41.0%
14.0%
10.0%
37.5%
12.5%
15.0%
13.0%
19.0%
3.0%
2.0%
12.0%
12.5%
10.0%
0.0%
2.5%
10.0%
SMOKING AND TP53 MUTATIONS IN
BLADDER CANCER
Smoking TP53+
TP53-
OR
No
8
24
1.00
Yes
58
83
6.27
Adjusted for age, gender, and education
95%CI
1.29-30.2
CIGARETTES/DAY AND TP53 MUTATIONS IN
BLADDER CANCER
Cig/day
TP53+
TP53-
OR
No
8
24
1.00
1-20
8
21
2.07
0.22-19.9
21-40
36
47
5.50
1.08-28.2
>40
17
18
10.4
1.90-56.8
Trend
P=0.003
Adjusted for age, gender, and education
95%CI
YEARS OF SMOKING AND TP53 MUTATIONS
IN BLADDER CANCER
Years of TP53+
smoking
No
8
TP53-
OR
24
1.00
1-20
5
10
5.64
0.82-38.7
21-40
42
58
6.45
1.24-33.4
>40
14
18
6.20
1.17-32.8
Trend
P=0.041
Adjusted for age, gender and education
95%CI
REDUCTION OF MISCLASSIFICATIONS
 Better
classification of exposures by using
markers of internal and biological
effective doses.
 More
homogeneous disease grouping by
using marker of effect such as specific
mutations.
 Reduced
misclassification may lead to
increased validity and precision of point
estimates
INDICATION OF MECHANISMS


Test association between mechanistic events in a
defined continuum
Knowledge of the mechanisms can guide future
research and intervention applications
VARIABILITY AND EFFECT
MODIFICATION


Individual variability of susceptibility may be
related to host factors such as genetic factors
Effect modification can be evaluated between
genetic susceptibility markers and exposure on
the risk of cancer
ENHANCED INDIVIDUAL AND GROUP RISK
ASSESSMENT


Providing more person-specific information
allowing extrapolation of risk from one group to
another, from animal species to humans, and
from one group to individuals
EXAMPLE: SMOKING AND LUNG
CANCER
Internal Dose (ID). The amount of a xenobiotic
substance or its metabolites found in a biologic
medium: e.g., Serum cotinine as an indicator of
nicotine.
 Biologic Effective Dose (BED). The integration of
exposure and effect modification by the host: e.g.,
DNA adducts of PAH in lung tissue.

EXAMPLE: SMOKING AND LUNG
CANCER

Early Biologic Effect (or biological response) are
biological or biochemical changes in target cells
or tissues that result from the action of the
chemical and are thought to be a step in the
pathologic process toward disease, e.g., tumor
suppressor gene TP53 mutations in lung cancer.