p53 Mutations and Occupational Exposures in a Surgical Series of

Transcription

p53 Mutations and Occupational Exposures in a Surgical Series of
Vol. 5, 997-/O()3.
p53
!)eeember
Cancer
/996
Mutations
and
Occupational
Exposures
Lung
Epidemiology
Branch
IL. C. H.. N. E. Cl,
Laboratory
of Pathology
IL. A. LI, and Laboratory
of Human
Carcinogenesis
ID. G. G.. W. P. B..
C. C. HI, National
Cancer
Institute.
National
Institutes
of Health,
Bethesda,
Maryland
20892:
Department
of Pulmonary
and Mediastinal
Pathology,
Armed
Forces
Institute
of Pathology.
Washington.
D. C. 20306
ID. G. G., W. D. TI;
and Mayo Clinic.
Rochester.
Minnesota
55905
lJ. J.. T. V. C.. H. T.. V. T..
P. P.1
Abstract
p53 mutations
are frequent
in malignant
lung tumors.
Of
88 surgically
treated
lung cancers
from cigarette
smokers
previously
evaluated
for p53 mutations,
45 tumors
(51.1%)
had mutations
in exons 5-8 (D. G. Guinee,
Jr. et
a!., Carcinogenesis
(Lond.),
16: 993-1002,
1995).
We
report
here the examination
of 13 occupational
exposures
and 13 high-risk
occupations
in relation
to these p5.3
mutations.
Two molecular
abnormalities
were associated
with occupational
exposures:
(a) G:C-T:A
transversions
on the coding
(nontranscribed)
strand
(n = 13) were
associated
with chromate
exposure
and employment
in
the metal
industry
(P < 0.05) and marginally
associated
with nickel exposure
(P
0.056);
and (b) G:C-*A:T
transitions
at non-CpG
sites (n
9) were associated
with
work in the petrochemical
industry
(P
0.05). No
association
was found
between
p5.3 mutations
and gender,
cigarette
pack-years,
tumor
histology,
age at diagnosis,
or
family
history
of lung cancer.
Because
all three chromateexposed
subjects
had large cell carcinomas
exhibiting
G:
C-”T:A
coding-strand
transversions,
follow-up
of a
cohort
with this exposure
should
clarify
the association
with the p53 gene.
Introduction
Lung cancer
is the leading
cause of cancer
death in the United
States
( I ). Epidemiological
studies
have linked
several
environmental
agents
to lung cancer,
including
tobacco
smoke,
asbestos,
ionizing
radiation,
metals,
polycyclic
aromatic
hydrocarbons,
and chloromethyl
ethers
(2). Whereas
an estimated
85% of lung cancer
deaths
may be attributable
to cigarette
smoking
( 1 ), other
factors
contribute
independent
effects
as
well as possible
synergistic
effects
with cigarette
smoke.
Received
The costs
4/ I 6/96: revised
8/2 1/96: accepted
of publication
of this article
were
8/26/96.
defrayed
in part
by the
payment
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Biomarkers
Series
& Prevention
of
Cancers
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Donald
G. Guinee,
Jr., William
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James
Jett, Thomas
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and Neil E. Caporaso’
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Epidemiology,
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must therefore
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At the molecular
level, mutation
of the p53 gene is the
most frequent
somatic
genetic
alteration
found
in malignant
lung tumors
(3). The prevalence
of p53 mutations
is considerably lower in adenocarcinomas
(33%) than in other histological
types of lung cancers
(60-70%
of small cell, large cell, and
squamous
cell carcinomas;
reviewed
in Ref. 3). The p53 protein
regulates
gene transcription
(4) and is thought
to play a role in
many fundamental
cellular
activities
including
cell cycle control, DNA
repair
and synthesis,
cell differentiation,
genomic
plasticity,
and apoptosis
(5).
Mutations
may be classified
as transitions
or transversions.
Transitions
involve
a change
from one purine [adenine
(A) and
guanine
(G)] to another
or from one pyrimidine
[cytosine
(C)
and thymine
(T)j to another.
G:C-”A:T
transitions
(the notation refers to a G to A change
in which a G:C pair is replaced
by an A:T pair after one round
of DNA replication)
may be
further
classified
according
to whether
they occur at CpG sites
(DNA sequences
in which a cytosine
is followed
by a guanine
in the 5’-3’
direction).
The cytosines
in a CpG dinucleotide
are frequently
methylated,
which
predisposes
to spontaneous
deamination
of 5-methylcytosine
to thymidine:
this spontaneous deamination
is generally
unrelated
to environmental
exposures (6,7). Transversions
involve
the replacement
of a purine
with a pyrimidine
or replacement
of a pyrimidine
with a purine.
The mutational
spectrum
of a gene consists
of the type and
distribution
of mutations
within
a target sequence.
Mutational
spectrum
analysis
has shown
that patterns
of mutations
can
reflect etiological
agents or processes
(3). Presently,
five environmental
agents
have been linked to human
cancers
and have
characteristic
p53 mutational
spectra:
(a) hepatocellular
carcinomas associated
with aflatoxin
B1 exposure
contain
a predictable mutation
at codon
249, AGG-*AGT,
resulting
in the
substitution
of serine for arginine
(8, 9): (b) sunlight-associated
skin cancers
have mutations
at dipyrimidine
sites that are usually G:C-”A:T
transitions
and also exhibit
characteristic
CC:
TT-TT:AA
mutations
(10);
(c) hepatic
angiosarcomas
associated
with vinyl chloride
exposure
have frequent
mutations
almost
exclusively
at A:T bp ( 1 1 ). This is consistent
with the
mutational
activity
of the vinyl chloride
monomer,
and it contrasts with relatively
infrequent
G:C-”A:T
mutations
in sporadic angiosarcomas
(12); (d) p53 mutation
in oral cancers
correlates
with a patient’s
tobacco
and alcohol
consumption
(13); and (e) the mutational
spectrum
of lung cancers
is dommated
by G:C-”T:A
transversions
with a coding
(nontranscribed)
strand
bias that account
for 40% of all mutations
(3).
This spectrum
can be explained
by DNA adducts
formed
by
polycyclic
aromatic
hydrocarbons
and preferential
repair of the
noncoding
(transcribed)
strand (3). Several
investigators
report
a dose-response
relationship
between
smoking
history
and the
prevalence
of p53 mutations
(14, 15).
Previously,
a series
of lung malignancies
was examined
for p.53 mutations,
and the mutational
spectrum
was reported
( 16). The goal of the present
study was to determine
whether
Downloaded from cebp.aacrjournals.org on October 19, 2016. © 1996 American Association for Cancer Research.
997
998
p53
Mutations
and
Occupational
Exposures
in Lung
occupational
factors
are associated
with the
tations
among
smokers.
In
particular,
G:C-”A:T
mutations
were studied
because
ularly
susceptible
to attack
by electrophilic
G:C-”T:A
and G:C-A:T
changes
are the
lung cancers,
accounting
for 40% and 24%
respectively
(3).
Cancer
observed
p53 muG:C-T:A
and
guanine
is particspecies,
and
most common
in
of p53 mutations,
Table
I
Characteristics
of subjects
and
their
tumors
and
No.
Percent
Male
50
56.8
Female
38
43.2
87
98.9
I
1.1
Hispanic
Age
Study
Population.
Patients
with primary
lung cancer
were
identified
through
the Thoracic
Surgery
Department
at the
Mayo
Clinic
in Rochester,
Minnesota
in 1991-1992
before
resection.
A total of 107 patients
meeting
the following
eligibility criteria
were enrolled
in the study:
(a) no cancer
diagnoses
in the year preceding
lung cancer
diagnosis;
(b) no
chemotherapy
or radiation
treatment
to the trunk before
specimen collection:
(e) lung tumor histology
other than lymphoma;
(d) mental
competence;
(e) able to comprehend
and communicate with study staff using the English
language;
(f) at least
three pieces
of tumor
tissue and three pieces
of normal
lung
available
at resection;
and (g) 15 cc of blood available
for study.
All subjects
provided
informed
consent
for participation
in the
study.
Five patients
who had never smoked
at least I 00 cigarettes
(“nonsmokers”)
were excluded
from the analysis
because
of
potential
etiological
differences
between
their tumors
and those
that occurred
in smokers.
p.53 sequence
data were not available
for 13 patients
and occupational
exposure
data were not available for I patient.
resulting
in a final sample
size of 88.
Covariate
Data.
Information
regarding
tumor
stage was abstracted
from the patient’s
medical
record.
Malignancies
were
classified
using the Tumors-Nodes-Metastasis
Staging
System
for lung cancer
(17).
A 30-mm
questionnaire
was administered
to each patient
after surgery
by a nurse or respiratory
therapist.
The questionnaire
included
items
regarding
demographics,
tobacco
use,
medical
history,
occupational
history,
residential
history,
and
family medical
history.
Within
the occupational
history
section,
subjects
were asked about lifetime
exposures
to 13 occupational
hazards
and past or present
employment
in I 3 industries.
These
occupational
exposures
and industries
were chosen
because
they are putative
lung cancer
risk factors
or because
they were
common
in the Mayo Clinic referral
area. A complete
occupational history
was elicited
that included
all jobs held for at least
six months,
job titles, activities
or duties,
name and address
of
company
or organization,
the type of business
or products
made, years of employment,
and number
of hours worked
per
week.
No attempt
was made to verify the self-reported
information
provided
at interview.
Genomic
DNA Extraction,
Amplification,
and Sequencing.
p53 mutations
in exons 5-8 were previously
determined
(16);
a brief description
of the methodology
used is presented
here.
p53-specific
intron primers
were used in the PCR to generate
a
538-bp
fragment
encompassing
exons
5 and 6 and a 660-bp
fragment
encompassing
exons 7 and 8. In rare cases in which
the DNA did not amplify
with this procedure,
individual
exons
were amplified
using
nested
primers
(18). Gel-purified
PCR
88)
Race
Methods
Specimen
Collection.
Specimen
collection
procedures
have
been described
previously
( 16). In brief, three pieces of tumor
and three pieces of adjacent
nonmalignant
tissue were collected
from each patient
at the time of resection
and snap-frozen
within
1 h. Tissues
were stored at -70#{176}Cbefore
DNA extraction and PCR. Formalin-fixed
paraffin-embedded
blocks
were
collected
for histological
review.
=
Gender
White
Materials
(n
at diagnosis
Mean
(yrs)
65.5
± SD
Range
Tumor
± 9.4
35-81
-
histology
Adenocarcinoma
42
47.7
25
28.4
carcinoma
20
22.7
carcinoma
I
1.1
Squamous
cell
Large
cell
Small
cell
Tumor
stage
carcinoma
at diagnosis
40
45.5
II
16
18.2
lilA
23
26.1
IIIB
4
4.5
IV
3
3.4
Unknown
2
2.3
No
75
85.2
Yes
13
14.8
At least
one
Cigarette
parent
or sibling
with
lung
cancer
pack-years
Males
Mean
± SlY’
60.8
±
39.5
0.5-166.9
Range
Females
Mean
46.7
± SD
“
P
<
0.05
± 22.5
0.8-103.0
Range
(males
versus
females).
products
were sequenced
by a modification
of the dideoxy
chain-termination
method
of Sanger
et a!. (19). Both strands
of
each
exon
were
sequenced
to identify
putative
mutations.
Germ-line
mutations
were excluded
by repeat amplification
and
sequencing
of genomic
DNA isolated
from paired
nonneoplastic lung tissue.
Data
Analysis.
Univariate
analyses
were performed
for the
following
variables:
gender,
age at diagnosis,
tumor histology,
history
of lung cancer
in at least one parent or sibling,
lifetime
smoking
dose expressed
as cigarette
pack-years,
and 26 occupational
factors.
Associations
between
these factors
and p53
mutations
were evaluated
using
Fisher’s
exact
test (20) as
determined
by the SAS (2 1) procedure
PROC
FREQ
on a
mainframe
computer
or by an exact trend test (22) for factors
with more than two levels.
Associations
were considered
statistically
significant
if the two-tailed
P was less than 0.05.
Student’s
t tests,
implemented
through
the SAS
procedure
PROC ITEST,
were used to compare
mean values for selected
variables.
Results
Selected
characteristics
of the 88 subjects
and their tumors
are
presented
in Table 1 . Both genders
were well represented
in this
series, which was predominantly
if not entirely
Caucasian
(one
subject
described
his race as Hispanic
and did not indicate
if he
was Caucasian
or African-American).
When classified
by histology,
47.7%
of the tumors
were
adenocarcinomas,
28.4%
were squamous
cell carcinomas,
22.7%
were large cell carcinomas,
and I . 1% were small cell carcinomas.
Reflecting
the
Downloaded from cebp.aacrjournals.org on October 19, 2016. © 1996 American Association for Cancer Research.
Cancer
Table
2
Numbers
and
Type
G.C
of mutations
of mutation
found
.
in 88 lung
On
strand
noncoding
No.
%ofall
.
mutations
strand
13
27.7
3
6.4
A:T
-“
At CpG
site
4
8.5
9
19.1
G:C-’C:G
3
6.4
A:T-sT:A
3
6.4
4
8.5
At non-CpG
A:T
site
G:C
-“
I
A:T-+C:G
Deletions
and
Total
of mutations
no.
insertions
No.
of tumors
with
at least
one p53
No.
of tumors
with
no p53
mutations
mutation”
2.1
7
14.9
47
100.0
45
43
489b
One tumor
had two G:C -. T:A mutations
(one on the coding
on the noncoding
strand);
one tumor
had a G:C -“ T:A mutation
strand
and a G:C -‘ A:T mutation
at a non-CpG
site.
S Percentage
of all tumors.
“
malignancies
T:A
-“
On coding
G:C
types
51.1”
strand
and one
on the coding
eligibility
requirement
of resectability,
tumors
tended
to be
diagnosed
at early stages,
with 79 (90.0%)
classified
as Stage I,
II, or lIlA. All subjects
smoked
for at least six months.
Average
cigarette
pack-years
differed
by gender.
Men reported
an average of 60.8 cigarette
pack-years
compared
with 46.7 cigarette
pack-years
for women;
however,
the range for both sexes was
wide.
p53 mutations
were found in 45 of 88 tumors
(51 .1%). The
mutational
spectrum
for the entire tumor series (n
107) has
been described
in detail previously
(16); those found in the 88
tumors
included
in the present
analysis
are summarized
in
Table
2. The most common
type of mutation,
a G:C-T:A
transversion,
was found in 16 (34.1%)
tumors.
Thirteen
of these
I 6 transversions
were on the coding
strand.
Thirteen
tumors
(27.6%)
exhibited
G:C-A:T
transitions,
nine of which were at
non-CpG
sites. Other
base changes,
deletions,
and insertions
were less frequently
observed.
Subjects
provided
information
about
13 occupational
exposures
and a history
of employment
in 13 industries
(Table 3).
Of the I 3 exposures,
agricultural
pesticides
or herbicides,
reported
by 2 1 subjects,
were the most common.
Exposures
to
crude petroleum
refining,
radiation,
asbestos,
coke oven gases,
and dyes were each reported
by at least five subjects.
All other
exposures
were less common.
When asked about employment
in 13 industries,
10 subjects
reported
a history
of employment
in the construction
industry,
and 10 subjects
reported
holding
jobs in the metal refining,
manufacturing,
plating,
or polishing
industries.
None of the other industries
surveyed
were reported
by more than four subjects.
The relationship
of G:C-*T:A
transversions
on the coding
strand
to various
factors
is shown
in Table 3. No association
was found
between
this type of p53 mutation
and gender,
cigarette
pack-years,
age at diagnosis,
tumor
histology,
or
family
history
of lung cancer.
Of the occupational
exposures,
chromate
exposure
was significantly
associated
with
G:C-”T:A
coding
strand mutations
(P < 0.05). An association
between
occupational
exposure
to nickel
and G:C-*T:A
coding-strand
transversions
was also found (P = 0.056).
A history
of employment
in the metal refining,
manufacturing,
polishing,
or plating
industries
was also positively
associated
with this
type of mutation
(P
0.037).
Limiting
the analyses
to males
did not appreciably
alter the findings
(data not shown).
Epidemiology,
Biomarkers
& Prevention
Of 10 subjects
who reported
working
in the metal industry,
1 reported
chromate
exposure,
1 reported
nickel exposure,
and
2 reported
both chromate
and nickel exposures.
Thus, of three
chromate-exposed
subjects,
only one was not exposed
to nickel,
and of three nickel-exposed
subjects,
only one did not report
exposure
to chromates.
Table
4 presents
the mutational
features, tumor
histologies,
and specific
metal exposures
for the
metal
industry-exposed
subjects.
All three chromate-exposed
subjects
had large cell carcinomas
with G:C-*T:A
transversions on the coding
strand.
The work histories
of the metal industry-exposed
subjects
were further
examined.
For 37 years before
being diagnosed
with lung cancer,
Subject
10 worked
in the custom
manufacturing
of kitchen
appliances.
Subject
29 worked
a total of 42
years in manufacturing,
18 years of which involved
aluminum
welding
and exposure
to coal, and 24 years of which he served
as manager
for several
aircraft
manufacturing
companies.
He
was diagnosed
with lung cancer
26 years
after his welding
exposure
began.
Subject
3 1 was employed
for 45 years as a
welder
and also engaged
for 38 years in part-time
construction
work involving
cement.
He was diagnosed
with lung cancer 51
years after beginning
welding
work. Subject
88 worked
8 years
as a welder;
she began this job 28 years before being diagnosed
with lung cancer.
Subject
103 performed
a variety
of activities
at a gray iron foundry
for 23 years; he developed
lung cancer
37 years after he started
working
there. Subject
106 was employed
as a dyemaker
during
the 28 years preceding
his lung
cancer diagnosis.
Subject
107 was a welder for 27 years, having
begun
this job 28 years before
developing
lung cancer.
There
was no further
information
pertaining
to employment
in the
metal industry
for Subjects
65 and 66.
G:C-”A:T
transitions
at non-CpG
sites were also exammed for associations
with potential
risk factors
(Table 3). Gender, cigarette
pack-years,
age at diagnosis,
tumor histology,
and
family history
of lung cancer were not associated
with this type
of mutation.
Of the occupational
factors,
a history
of employment in the petrochemical
industry
was positively
associated
with G:C-A:T
transitions
at non-CpG
sites (P
0.05). One of
the subjects
who reported
working
in the petrochemical
industry was employed
as a truck driver for an oil refinery;
the work
histories
of the other three subjects
who reported
work in the
petrochemical
industry
did not provide
any further
information
about their jobs.
The mutations
observed
in this series of malignancies
have
been described
in detail elsewhere
( 16). In Table 5, the mutational features
of the 13 G:C’-T:A
coding
strand transversions
and the 9 G:C-’A:T
transitions
at non-CpG
sites studied
in the
present
report
are presented
together
with the subjects’
occupational
exposures
and tumor histologies.
The majority
of the
changes
were
missense
mutations;
the resultant
amino
acid
substitutions
are indicated.
Several
subjects
reported
exposure
to more than one of the occupational
factors that were surveyed.
Discussion
Chromium
and nickel compounds
have been implicated
in the
etiology
of lung cancer
(23). The present
study extends
previous findings
by providing
evidence
that such metals
may be
related
to a specific
type of mutation,
G:C-*T:A
transversions,
in the p53 gene. This is consistent
with Chen and Thilly’s
(24)
observation
of K,Cr2O7-induced
mutational
hotspots
involving
G:C bp in the hypoxanthine
guanine
phosphoribosv!
transferase gene and the G:C-T:A
transversions
in the K-ras gene in
nickel-induced
renal
sarcomas
in the rat reported
by Higinbotham
et a!. (25). An A:T-G:C
transition
in the p53 gene has
Downloaded from cebp.aacrjournals.org on October 19, 2016. © 1996 American Association for Cancer Research.
999
1000
p53
Mutations
Table
and
3
Occupational
Associations
Exposures
of putative
risk
in Lung
factors
with
Cancer
pSi
G:C
-“
T:A coding
strand
transversion
among
88 lung cancer patients
G:C
No. with
factor (%)
No. with
mutation
-“
T:A
coding
strand
% of G:C -“
mutations
Gender
and
transversions
T:A
G:C
-“
A:T
G:C
,,
No. with
mutation
transition
-“
A:T
mutations
transitions
Female
Cigarette
2
22.2
3
33.3
3
33.3
‘,
22.2
I 5.4
2
22.2
53.8
38 (43.2)
6
46.2
0.569
2
I 5.4
31.6-47.5
23 (26.1)
3
23.1
47.6-68.3
21 (23.9)
5
38.5
1.5
22 (25.0)
3
23.1
68.4-166.9
at diagnosis
>0.900
I 1.1
0.758
(yrs)
55
>0.900
I 1 (12.5)
2
56-65
31 (35.2)
5
38.5
.,
22.2
>65
46 (52.3)
6
46.2
5
55.6
4
44.4
5
55.6
histology
Other
I parent
or sibling
diagnosed
Yes
with
lung
42 (47.7)
4
30.8
46 (52.3)
9
69.2
cancer
>0.900
13 (14.8)
75 (85.2)
No
Occupational
.,
II
>0.900
15.4
1 1.1
84.6
8
88.9
exposures
Smelting
process
85 (96.6)
No
petroleum
12
92.3
8
88.9
2
22.2
7
77.8
2
22.2
7
77.8
0.156
5 (5.7)
83 (94.3)
No
I 1.1
7.7
refining
Yes
Agricultural
0.279
0.385
3 (3.4)
Yes
Crude
0.731
0.236
Adenocarcinoma
2
II
I 5.4
84.6
pest/herbicides
0.080
0.177
Yes
21 (23.9)
No
67 (76.1)
7.7
12
92.3
>0.900
0.156
Radiation
Yes
5 (5.7)
No
83 (94.3)
2
II
0.425
I 5.4
I 1.1
84.6
8
88.9
0
0.0
0.003
Chromates
Yes
3 (3.4)
85 (96.6)
No
3
23.1
10
76.9
Nickel
>0.900
9
100.0
0.056
Yes
3(3.4)
No
85 (96.6)
Hematite
or iron
2
II
I 5.4
84.6
ore
>0.900
0
0.0
9
100.0
0.275
Yes
2(2.3)
No
86 (97.7)
0.195
1 1.1
7.7
12
92.3
Asbestos
8
88.9
0.163
Yes
No
10 (11.4)
3
23.1
78 (88.6)
10
76.9
tars
>0.900
11.1
8
88.9
0.385
Yes
3 (3.4)
85 (96.6)
No
0.279
7.7
12
I 1.1
92.3
Chromium”
8
88.9
0
0.0
9
100.0
0
0.0
9
100.0
0.388
Yes
3(3.5)
No
84 (96.5)
7.7
12
92.3
Uranium
>0.900
>0.900
Yes
No
Coke
sites
A:T
0.289
77.8
7
22 (25.0)
Coal
sites
at non-CpG
% of G:C -“
mutations
7
50 (56.8)
pack-years
0.5-3
Tumor
at non-CpG
>0.900
Male
Age
mutations
oven
Yes
No
I (1.1)
0
0.0
87 (98.9)
13
100.0
gases
>0.900
6(6.8)
82 (93.2)
No
0.487
I 1.1
7.7
12
8
92.3
Dyes
Yes
>0.900
88.9
>0.900
6(6.8)
0.487
I 1.1
7.7
82 (93.2)
12
92.3
Yes
1 (1.1)
0
No
87 (98.9)
13
8
88.9
0.0
0
0.0
100.0
9
100.0
Industries
Shipbuilding
>0.900
>0.900
Downloaded from cebp.aacrjournals.org on October 19, 2016. © 1996 American Association for Cancer Research.
Cancer
Table
3
(cont’d.)-Associations
of putative
risk
factors
with
p53
G:C
sites
G:C
No. with
factor (%)
-“
T:A
-“
among
T:A
No. with
mutation
coding
strand
88 lung
coding
transversion
cancer
strand
% of G:C -“
mutations
transversions
T:A
10(11.4)
2
No
78 (88.6)
II
I (1.1)
No
87 (98.9)
1
7.7
12
92.3
3 (3.4)
0
0.0
No
85 (96.6)
13
100.0
at non-CpG
A:T
transitions
at non-CpG
% of G:C mutations
sites
A:T
1
11.1
8
88.9
0
0.0
9
00.0
1
I 1.1
8
88.9
2
22.2
7
77.8
1
1 1.1
8
88.9
2
22.2
7
77.7
0
0.0
>0.900
0.279
0.102
No
4 (4.5)
2
15.4
84(95.5)
II
84.6
chemicals
0.050
>0.900
Yes
3 (3.4)
0
0.0
No
85 (96.6)
13
100.0
Metal
0.279
0.037
Yes
No
Sugar
10 ( I I .4)
4
30.8
78 (88.6)
9
69.2
cane
0.270
>0.900
Yes
I (I. I)
No
87 (98.9)
0
0.0
13
100.0
Mining
>0.900
9
100.0
0
0.0
9
100.0
0.148
Yes
I (I. I)
No
87 (98.9)
I
7.7
12
92.3
Insulation
I ( I. I )
No
87 (98.9)
Asbestos
0
0.0
13
100.0
No
9
2(2.3)
1
7.7
100.0
86(97.7)
12
92.3
>0.900
0
manufacturing
0.0
9
100.0
0
0.0
9
00.0
>0.900
Yes
I ( I.I)
No
87 (98.9)
0
0.0
13
100.0
Demolition
>0.900
>0.900
Yes
1 ( 1. I )
No
87 (98.9)
test
used
exposure
for cigarette
unknown
Table
no.
for
4
pack-years
and
1 subject;
analysis
Mutational
Chromate
features,
exposure
0.0
0
0.0
13
100.0
9
100.0
age at diagnosis;
based
tumor
Nickel
Fisher’s
exact
test
used
for all other
histology,
and
chromate
and
exposure
nickel
Mutation
exposures
29
Yes
Yes
G:C
31
No
No
None
65
No
No
G:C
66
No
No
None
88
Yes
No
G:C
91
No
No
None
103”
No
Yes
G:C
-“
A:T
CpG
106
Yes
Yes
G:C
-“
T:A
coding
strand
107
No
No
G:C
-“
T:A
coding
strand
G:C
-“
A:T
non-CpG
103 was
found
after
publication
worked
-‘
T:A
coding
strand
A:T
non-CpG
Codon
site
249
Codon
T:A
coding
strand
143
Codon
249
site
and
histology
Large
cell
carcinoma
Adenocarcinoma
Large
cell
carcinoma
Large
cell
carcinoma
cell
carcinoma
Codon
248
Squamous
cell
carcinoma
Codon
245
Large
carcinoma
Codon
160
Adenocarcinoma
Codon
161
-
site
Tumor
Adenocarcinoma
-
industry
Adenocarcinoma
-“
in the metal
location
-
of Ref.
observed
by Maehle
et a!. (26) in human
renal epithelial
treated
with nickel.
The mechanism(s)
by which
metals
exert
their carcinogenic
effects
may involve
oxidative
damage
resulting
in DNA
base modifications,
cross-linking
of DNA
with proteins
and/or
adjacent
DNA
bases,
DNA
cleavage,
who
Mutation
None
Subject
in subjects
type
No
from
factors.
on 87 subjects.
No
in the tumor
>0.900
0
10
mutation
0.0
0.275
Yes
Cement
>0.900
0
manufacturing
trend
>0.900
>0.900
Yes
been
cells
mutations
>0.900
84.6
Yes
Other
The
transition
>0.900
Yes
“
A:T
0.148
Yes
Subject
-“
No. with
mutation
15.4
Petrochemicals
Exact
-‘
& Prevention
0.638
Yes
Wood/paper
Chromium
G:C
,
Fishing
S
and G:C
Blomarkers
patients
Construction
“
mutations
Epidemiology,
Squamous
cell
1.
and/or depurination
(reviewed
in Ref. 27). The role of particular
metals
(e.g., nickel
versus chromates)
could not be resolved
in
the present
study because
coexposure
was more common
than
single exposure.
In contrast
to recent work by Wang et a!. (28),
we did not observe
an increased
frequency
of G:C-+T:A
trans-
Downloaded from cebp.aacrjournals.org on October 19, 2016. © 1996 American Association for Cancer Research.
/00/
/()02
p53
Mutations
5
Table
and
Occupational
Muiational
features,
Exposures
tumor
in Lung
histologies.
and
Cancer
occupational
exposures
associated
transitions
at non-CpG
G:C
Subject
no .
-_____________________________
Codon
or
.
.
splice
site
Base
Mutation
class
chance
,,
the G:C
9)”
strand
s
T:A
coding
strand
transversions
(n
Tumor
.
histology
Occupational
,
Asbestos;
asbestos
.
AGG
> ATG
mis
Arg
> Met
sq cell
I 58
CGC
>
CTC
mis
Arg
> Leu
adenoca
-
14
245
GGC
>
GTC
mis
Gly
> Val
adenoca
22
298
GAG
>
TAG
non
Glu
> Ter
sq cell
29
249
AGG
>
AGT
mis
Arg
> 5cr
Ig cell
Radiation;
>
GT
spl
-
sq cell
Crude
petroleum
petrochemical
7 3 splice
site
GG
manufacturing
-
chromates;
nickel:
coke
oven
gases;
refining;
construction
md.; mining
md.
158
CGC
>
CTC
mis
Arg
>
Leu
adenoca
-
71
266
GGA
>
GTA
mis
Gly
> Val
sq cell
-
80
294
GAG
>
TAG
non
Glu
> Ter
Ig cell
88
249
AGG
>
AGT
mis
Arg
>
5cr
lg cell
md.;
metal
158
CGC
>
CTC
mis
Arg
> Leu
sq cell
245
GGC
>
GTC
mis
Gly
>
Val
Ig cell
Smelting
process;
agricultural
herb/pesticides:
chromates;
nickel;
hematite
or iron ore;
tars; chromium;
dyes; metal md.
107
161)
ATG
>
All’
mis
Met
> lie
adenoca
Crude
petroleum
petrochemical
Codon
.
splice
or
.
site
Base
change
Mutation
class
,,
transitions
-
at non-CpG
Amino
acid
change
Tumor
.
histology
refining;
asbestos;
md.; metal md.
.
Occupational
,,
275
TGT
> TAT
mis
Cys
> Tyr
adenoca
167
CAG
>
TAG
non
GIn
> Ter
Ig cell
Agricultural
pest/herbicides;
oven gases
38
193
CAT
> TAT
mis
His > Tyr
adenoca
Wood/paper
65
143
GTG
>
ATG
mis
Val
>
Met
adenoca
Smelting
process;
pest/herbicides;
petrochemical
69
179
CAT
> TAT
mis
His
> Tyr
sq cell
-
72
242
TGC
> TAC
mis
Cys
> Tyr
Ig cell
-
97
245
GGC
> AGC
mis
Gly
> 5cr
adenoca
102
159
GCC
> GTC
mis
Ala > Val
sq cell
Crude
107
161
GCC
> GTC
mis
Ala
adenoca
Construction
features
mis.
have been
missense:
previously
reported
non, nonsense:
spl.
(16),
splice
md.;
b
-
hematite
or iron
ore;
coke
md.
crude
petroleum
refining;
agricultural
radiation;
coal tars; dyes;
md.; other chemical
md.; metal
md.
-
petroleum
except
for those in the tumors
from Subjects
71, 98, and 102.
site; sq cell, squamous
cell carcinoma;
adenoca,
adenocarcinoma;
versions
in the p53 gene in lung cancer
patients
occupationally
exposed
to asbestos,
despite
the relatively
high prevalence
of
this exposure
(10 of 88 patients,
I 1.4%) in the present
study.
A limitation
of this study is the use of self-reported
occupational
exposure
data, which may introduce
misclassification.
However,
when patients’
complete
occupational
histories
were
evaluated
for consistency
with self-classification
as “exposed”,
subjects
who reported
an exposure
also reported
a job title or
duty that is known
or suspected
to involve
that exposure.
In
addition,
among
patients
who reported
work in the metal
industry,
the age at lung cancer
diagnosis
(mean
=
61.3 years;
range
=
35-75
years)
and the number
of years between
first
occupational
exposure
and tumor
development
are similar
to
those reported
in other studies
(29, 30), providing
further
support for the use of self’-reported
occupational
data in this study
as a surrogate
measure
of exposure.
Only hexavalent
chromium
compounds
have been established
as carcinogens
(23);
the
effect found in this study was specific
for chromates.
The distribution
of histological
types of lung cancer
in
chromate-exposed
persons
is not consistent
in the literature.
All
three chromate-exposed
persons
in our study
had large cell
carcinomas.
In contrast,
squamous
cell carcinomas
predominated in three previous
reports
of lung malignancies
in chromate- or nickel-exposed
persons
(31-33).
However,
Abe et a!.
construction
factors
37
Mutational
Abbreviations:
radiation;
asbestos;
coal
sites
25
> Val
md.
md.;
md.
98
A:T
metal
fishing
-
Chromates;
106
-“
A:T
-
md.
50
G:C
G:C
S
factors
174
Exon
13) and
transversions
Amino
acid
change
5
Subject
no .
“
coding
(,i
II
48
“
T:A
-
with
sites
refining;
md.;
asbestos;
petrochemical
lg cell,
large
md.;
cell
metal
carcinoma;
md.
md.,
industry.
(33) reported
that small cell carcinomas
(n = 5) occurred
in
employees
who worked
exclusively
in those parts of the chromate manufacturing
process
involving
exposure
to hexavalent
chromate
dusts.
The role of chance
must be considered
in interpreting
the
statistically
significant
associations
in this study because
a large
number
of comparisons
were made, and some exposures
were
present
in only a small number
of subjects.
The small sample
size also prevented
multivariate
adjustment
when
examining
the relationship
of occupational
exposures
to p53 mutations.
However,
there was no association
between
p53 mutations
and
several
potential
confounders
(gender,
cigarette
pack-years,
age
at diagnosis,
tumor histology,
and family
history
of lung cancer). In contrast
to previous
work (14, 15), we failed to observe
a significant
association
between
cigarette
pack-years
or other
measures
of smoking
duration
and intensity
(data not shown)
and G:C-t’T:A
transversion
mutations
in this study. However,
a weak trend may be present,
i.e. I 9.3% of tumors
from subjects
with less than the median
number
of pack-years
versus
30.8%
of tumors
from subjects
with greater
than the median
number
of
pack-years
exhibited
G:C-*A:T
mutations.
It is noteworthy
that all three chromate-exposed
persons
had large cell carcinomas
and G:C-”T:A
transversions
on the
Downloaded from cebp.aacrjournals.org on October 19, 2016. © 1996 American Association for Cancer Research.
Cancer
coding
strand.
occupationally
This finding
warrants
exposed
cohort.
follow-up
in a larger,
16. Guinee,
Cawley,
H.,
Abbondanzo,
Harris,
C. C.
tions,
anti-p53
Acknowledgments
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p53 mutations and occupational exposures in a surgical series
of lung cancers.
L C Harty, D G Guinee, Jr, W D Travis, et al.
Cancer Epidemiol Biomarkers Prev 1996;5:997-1003.
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