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Epidemiology and Prevention |
Departments of Medicine [E. L. C., S. A. K., D. A. W., W. J. F., C. A. J., J. R. H., D. A. O., J. C. W.] and Surgery, [S. G. D.]; Medical College of Ohio, Toledo, Ohio 43699-0008 Surgery Departments of Medicine and Environmental Medicine, University of Rochester School of Medicine, Rochester, New York 14642 [M. F., M. U.]; and Department of Toxicology and Center for Environmental Health Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 [W. G. T.]
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ABSTRACT |
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INTRODUCTION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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particles that generate reactive oxygen products as they encounter the
cells. NBECs also are exposed through inhaled cigarette smoke or urban
air pollution to PAHs. These procarcinogens may be metabolically
activated in the cytoplasm and subsequently damage nuclear DNA. Damage
to NBECs and adjacent structures from oxidants and/or activated
carcinogens may result in a variety of pulmonary disorders, including
bronchogenic carcinoma, pulmonary fibrosis, chronic bronchitis, and
emphysema (5
, 8)
. NBECs express several enzymes, including GSTs and glutathione peroxidases, that are capable of preventing or reducing injury from reactive oxidants or carcinogens. The GST enzymes conjugate reactive chemical groups, including reactive oxygen species and diol-epoxide ultimate carcinogens, to glutathione and thereby prevent them from binding to and damaging DNA (9) . There are several classes of GSTs, including one microsomal class (mGST) and four cytosolic classes: GSTA, GSTM, GSTP, and GSTT (10 , 11) . In addition, a human homologue of rat GSTK1 has been reported (12) . Each GST enzyme has substrate specificity, but there is considerable overlap (for review, see Ref. 13 ). For example, diol-epoxides derived from PAH procarcinogens are metabolized by GSTP1 and GSTM1–3 (14) . Other substrates for the cytosolic GSTs include steroids, alkenals, and quinones (for review, see Ref. 9 ). In contrast to the cytosolic GST enzymes, mGST has very little specificity for epoxides (15) . However, mGST has activity against a broad range of other substrates, including styrene-7–8-oxide (16) , 1-chloro-2,4-dinitrobenzene, and cumene hydroperoxide (17) . Further, various halogenated alkynes and alkenes are metabolized preferentially by mGST compared to the cytosolic forms (13 , 18) .
The glutathione peroxidase enzymes catalyze the inactivation of peroxides (including hydrogen peroxide and lipid peroxides) using reduced glutathione as a cofactor (19) . Several enzymes have glutathione peroxidase activity, including GSHPx (19) , GSHPxA (a secreted form; Ref. 20 ), mGST (21) , GSTA (22) , and GSTM3 (23) .
Both intertissue and interindividual variation in the expression of GST and glutathione peroxidase genes have been reported (14 , 24, 25, 26, 27) . In addition, the expression of some GST and glutathione peroxidase genes is altered in carcinoma tissues (14 , 20 , 24 , 25 , 28 , 29) . Because there is intertissue variation in the expression of these genes, it is important to measure expression specifically in the progenitor cell for bronchogenic carcinoma, the bronchial epithelial cell. There is very little information presently available regarding quantitative levels of GST or glutathione peroxidase gene expression in primary NBECs relative to primary bronchogenic carcinoma tissue.
Interindividual variation in GST enzyme gene expression may translate into variation in risk for bronchogenic carcinoma. For example, in some epidemiological studies, GSTM1 null individuals have an increased risk (30 , 31) . However, the results of other studies are contradictory (32) . One hypothesis to explain these different results is that because the multiple GST and glutathione peroxidase enzymes have a broad substrate overlap, a decrease in the expression level of one GST or glutathione peroxidase may be compensated for by increased expression of another. Thus, the expression patterns for multiple relevant GST and glutathione peroxidase enzymes may be more closely associated with risk than the expression of each individual gene. Consequently, studies that do not control for expression of all relevant genes may generate data that are difficult to interpret. We recently have developed a method for gene expression measurement by quantitative RT-PCR that allows simultaneous expression measurement of many genes on the small specimens obtained by bronchoscopic brush biopsy (33) . In this study, we simultaneously measured the mRNA expression of mGST, GSTM3, GSTT1, GSTP1, GSHPx, and GSHPxA and the combined expression of GSTM1,2,4,5 (due to high levels of homology, it was not possible to identify primers specific to each GSTM isoenzyme) in the primary NBECs of 23 non-lung cancer patients, primary NBECs from 11 lung cancer patients, and in cultured NBECs from eight non-lung cancer patients.
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MATERIALS AND METHODS |
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Samples.
Primary NBECs were obtained by bronchial brush biopsy as
previously reported (34
, 35)
. This group of individuals
without lung cancer consisted of healthy volunteers from a university
setting, individuals undergoing diagnostic bronchoscopy, and three
organ donors. The lungs of the donors did not meet criteria for
transplantation due to COPD (subjects 54 and 62) or asthma (subject
55). Two of the subjects (57 and 71) had bronchoscopy at the time of
thoracotomy for resection of adenocarcinoma of the colon that had
metastasized to the lung. Subjects 59 and 63–66 had bronchoscopy due
to persistent hemoptysis or change in character of chronic cough, and
no endobronchial mucosal lesions were observed. Samples from lung
cancer patients were obtained via bronchoscopic bronchial brushing at
the time of surgery as previously reported (36)
or
brushing of surgically resected samples (subjects 74 and 75; Table 1
). Samples that were evaluated in previous studies (34
, 35)
have the same subject numbers in this study. Samples acquired since the
time of those publications are numbered in order of acquisition. Cells
were recovered from the bronchial brush into ice-cold 0.9% NaCl
solution and pelleted. Informed consent was obtained from each patient.
Demographic data are presented in Table 1
.
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RNA Extraction and Reverse Transcription.
Excess NaCl solution/media was removed, and the cells were
lysed in TriReagent. Total RNA was extracted according to the
TriReagent Manufacturer Protocol (37)
. Following
extraction, mRNAs were reverse-transcribed using M-MLV reverse
transcriptase and an oligo dT primer as previously reported
(34)
.
Quantitative RT-PCR.
Gene expression was determined using quantitative
competitive RT-PCR (33, 34, 35
, 38)
. PCR reactions were cycled
35 times in a Rapidcycler (Idaho Technology, Idaho Falls, Idaho) in the
presence of two types of controls. First, a house-keeping gene
(ß-actin) was coamplified along with the target genes to control for
the amount of cDNA included in the reaction. Second, known amounts of
cDNA CTs were included for both the target and the house-keeping gene
to control for the loss of predictable exponential amplification with
increasing cycles (38
, 39)
. In these experiments, the
concentration of the CTs in each PCR reaction was
10-14 M for ß-actin and varied for
each of the other genes. CTs were synthesized according to previously
described methods (33
, 40)
. Primers for synthesizing CTs
and for amplification of NT and CT sequences were chosen using Oligo
software (National Biosciences, Inc., Plymouth, MN). After careful
assessment of the sequences, we were not able to identify primers that
would amplify GSTM1 without amplifying GSTM2,4,5. Therefore, cDNA from
all four isogenes were amplified with the same primers. Sequences for
mGST (GenBank accession no. J03746), GSTM3 (J05459), GSTM1,2,4,5
(J03817, M63509, M96234, L02321), GSTT1 (X79389), GSHPx (Y00433),
GSHPxA (D00632), and GSTP1 (X06547) were retrieved from GenBank. Table 2
lists primer sequences and product lengths for both NT and CT PCR
products. Primers for ß-actin have been reported previously
(34)
.
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The amount of cDNA loaded for each sample was determined
by comparing the density of the PCR product band for ß-actin NT cDNA
to the PCR product band for ß-actin CT cDNA. Quantification of
expression of the target genes was determined in the following way.
First, the ratio of target gene NT:CT product was calculated. Because
the starting target gene CT concentration was known and the relative
amplification efficiencies for the NT and CT cDNAs were known (see
below), the starting target gene NT cDNA concentration could be
determined. Second, the calculated number of target gene NT molecules
was divided by the calculated number of ß-actin NT molecules to
correct for loading differences. Gene expression values are reported in
Tables 3
,4
, and 5
.
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2 analysis was conducted for
each gene or gene expression index using a range of cutoff values to
determine their sensitivity and specificity as a test for separating
cancer patients from non-lung cancer patients (Table 6)
. To determine statistically significant (P < 0.05) interindividual variation in gene expression levels among
primary NBECs from non-lung cancer patients and primary NBECs
from lung cancer patients and compare this variation with
interindividual variation in cultured NBECs, a one-factor ANOVA was
used. All statistical analyses were conducted using SAS version 6.11
(SAS Institute, Cary, NC).
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, Table 4
, and Table 5
, three or more
replicate measurements were made for 218, and an SD is
provided. Of the remaining 62 gene expression means reported, duplicate
measurements were obtained for 48, and a range is provided. There was
sufficient cDNA for only one measurement for 14 gene expression values. |
RESULTS |
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, Table 4
, and Table 5
). This is similar to the
reproducibility observed in other gene expression studies using the
same method (33)
.
Comparison of Primary NBECs from Individuals with or without
Bronchogenic Carcinoma
Individual Gene Expression Values.
GSTM3, GSTP1, and GSHPx were expressed at significantly
lower levels (P = 0.02, 0.01, and 0.01,
respectively) in primary NBECs from bronchogenic carcinoma patients
compared to primary NBECs from individuals without bronchogenic
carcinoma (bold font in Table 4
). Of these genes, GSHPx was the
individual gene with the best sensitivity (80% for a value of 70–90
mRNA/103 ß-actin mRNA; Table 6
). However, a
value that was 
90% sensitive had poor specificity (Fig. 2A)
.
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Gene Expression Indices.
Indices comprising expression values of multiple genes
were formed by multiplying expression values of different combinations
of genes together. Rather than assessing every possible combination of
genes, 25 indices comprising the 5 genes that individually demonstrated
the greatest difference between groups (GSP1, GSHPxA, GSTM3, mGST, and
GSHPx; Table 6
) were assessed. Index values were reported as
molecules/103 molecules of ß-actin and were
calculated as in the following example: (GSTM3
molecules/103 molecules of ß-actin x GSTP1 molecules/103 molecules of
ß-actin x mGST molecules/103
molecules of ß-actin) = GSTM3 x GSTP1 x mGST molecules/109
molecules of ß-actin/106 molecules of
ß-actin = index molecules/103
molecules of ß-actin.
For two indices that each comprised three genes (GSTP1 x GSHPx x GSTM3; GSTP1 x mGST x GSHPx), it was possible to identify cutoff
values with sensitivities 90% and specificities >70% (Table 6
;
Fig. 2, B and C
). These indices both included
GSTP1 and GSHPx and varied only with respect to the third gene (either
mGST or GSTM3). For an index that included all four of these genes
(mGST x GSTM3 x GSHPx x GSTP1), a range of cutoff values (3.2 x 10-5 - 3.5 x 10-5 molecules/103
molecules of ß-actin) had a sensitivity of 100%. However, the
specificity of this index was only 62% (Table 6)
. Reducing the
cutoff value to 2.0 x 10-5
molecules/103 molecules of ß-actin
decreased the sensitivity to 90% but did not improve the
specificity (Fig. 2D)
. In addition, for an index
comprising five genes (mGST x GSTM3 x GSHPx x GSHPxA x GSTP1), a range of
cutoff values (3.0 x 10-9 - 1.0 x 10-8
molecules/103 molecules of ß-actin) had a
sensitivity of 90% and a specificity of 76% (Table 6
; Fig. 2E
).
Correlation with Age, Gender, and Smoking
Age.
Pearson’s correlation was used to test the relationship
of age to the expression of each gene and the level of each gene
expression index. First, the test was run on all patients. Only GSHPx
was significantly associated (negatively correlated) with age
(P = 0.018). To avoid bias caused by the
relatively low representation of older individuals in the non-lung
cancer group (mean age among non-lung cancer and lung cancer patients
was 39 and 69 years, respectively), the test also was run separately on
the lung cancer patients and the non-lung cancer patients. There was no
significant association within either the non-lung cancer or the lung
cancer group between age and GSHPx. GSHPx gene expression also was
assessed separately on samples from individuals aged 45–65 years. In
this group, the mean age among nine non-lung cancer and four lung
cancer individuals was 54 and 55 years, respectively. As with the
entire group, the mean level of GSHPx expression among the cancer cases
(35.9 molecules/103 molecules of ß-actin) was
significantly lower (P = 0.01) than the mean
GSHPx expression among non-lung cancer cases (122
molecules/103 molecules of ß-actin).
Smoking History.
A Pearson’s correlation was used to assess relationships
between smoking history and gene expression. This test was run once on
all patients, once on present and former smokers only, once on present
smokers only, and once on former smokers only. No correlation between
expression of any gene or gene expression index studied here with
smoking history (in pack-years) was observed among patients of any
group.
Gender.
Among the primary NBECs from lung cancer and non-lung cancer
patients combined, no differences in gene expression or any gene
expression index were found due to gender.
Interindividual Variation in Gene Expression
Primary NBECs.
There was significant (P < 0.05)
interindividual variation in primary NBEC expression of each of the
genes (Table 3
and Table 4
). The value of mGST in NBECs from subject 21 was
excluded from statistical analysis because it was an outlier (Table 3)
.
Interpretation of this result is included in the discussion.
Cultured NBECs.
In an effort to test whether the interindividual
variation in expression observed in primary NBECs was based on
hereditary differences or environmental factors, gene expression was
measured in cultured NBECs from eight different individuals with no
history of lung cancer. In this model, all of the cultures were
maintained under the exact same conditions. This should allow
hereditary differences in constitutive gene expression to predominate.
In these eight different NBEC cultures, the mean level of expression
for each antioxidant gene studied was lower than that observed
among primary NBEC samples. In addition, although significant
interindividual variation among cultured NBECs was observed for GSHPx,
GSTM3, and mGST, it was less than that observed in primary NBECs
(Table 3
, Table 4
, and Table 5
). Further, there was no significant interindividual
variation in the expression of GSTM1,2,4,5, GSTT1, GSHPxA, or GSTP1
among cultured NBECs (Table 5)
.
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DISCUSSION |
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may be responsible for the increased carcinogenicity of
the PAH benzo(a)pyrene (41)
. GSTP1 was
expressed at a higher level in NBECs from non-lung cancer patients than
any other gene studied here. Recently described polymorphisms in the
coding region of GSTP1 have a strong association with increased risk
for neoplasia (42
, 43)
and will be important to assess in
future studies along with GSTP1 gene expression levels.
Although 
50% of Caucasians lack GSTM1 expression due to a
null allele, NBECs from all 34 patients in this study expressed one or
more of these GSTM isoforms (Table 3
and Table 4
). Because all of the GSTM
isoforms have substrate overlap, it is possible that risk for
bronchogenic carcinoma is not related to GSTM1 expression alone but
also to relative gene expression levels of all GSTM isoforms in NBECs.
Non-cancer subjects 21 and 54 had mGST levels three logs
and 10-fold greater, respectively, than in any of the other subjects.
Such wide fluctuation in gene expression was not observed for any of
the other genes. It is possible that a small segment of the population
is capable of expressing very high levels of mGST either constitutively
or upon exposure to certain xenobiotics. Because mGST has peroxidase
activity (21)
and because it was expressed at lower levels
in the NBECs of lung cancer patients in this study (Table 3
and Table 4
), it
would be expected that such a high level of expression would protect
the cellular DNA from oxidant damage and therefore lower cancer risk.
The reason that mGST expression is not significantly different in the
two groups, although there is a 5-fold difference in the means, is that
the subject 54 value confers such a high SD. If both subjects 21 and 54
are excluded from analysis, mean mGST expression is significantly lower
(P < 0.05) in the samples from cancer
patients.
Although we did not measure protein and/or enzyme levels in this study, mRNA levels and enzyme activities for some of the measured genes and other xenobiotic metabolism enzyme genes are known to be closely related. For example, Moscow et al. (44) reported in 1988 that GSTP1 enzyme activity and mRNA levels are highly correlated in several human breast cancer cell lines. We have reported previously that CYP1A1 and NADPH oxidoreductase activities are correlated with mRNA levels in lymphoblastoid cell lines (35) . CYP1A1 mRNA and enzyme activities also have been correlated in rat liver tissue (45) . Further, manganese superoxide dismutase activity correlates with protein and mRNA levels in fibroblasts (46) .
Gene Expression Indices May Better Identify Individuals at Risk for
Bronchogenic Carcinoma.
An important feature of the method used in this study is that
it allows expression values of multiple different genes to be combined
into indices. Such index values may then be used to rank cell or tissue
samples. Data from this study support the hypothesis that such
gene expression indices generally will correlate better than expression
of any single gene or isozyme with phenotype. For the best
index identified (mGST x GSTM3 x GSHPx x GSHPxA x GSTP1) at a value that
provided a sensitivity of 90%, the specificity was 76% (Table 6)
.
Because 5–10% of smokers get lung cancer, it is reasonable to
hypothesize that at least 5–10% of the people in the general
population have a genetic predisposition to bronchogenic carcinoma.
Thus, of the four individuals without bronchogenic carcinoma who had
index values below the cutoff value, one to two of them could be
expected to be at high risk for bronchogenic carcinoma if they smoked.
The manner in which gene expression values are combined into indices will depend in part on the weight given each gene. In this study, indices were calculated by multiplying gene expression values together so that each gene expression value included had equal weight. The key assumption made for the method chosen was that, at the mean level of expression measured in NBECs, each of the genes studied contributed equally to protection of NBECs from oxidant and/or carcinogen damage. Philosophically, this assumption is supported by the expectation that the optimal level of expression for the function of each gene would be selected for through evolution. Using the same method of combining gene expression values into indices in a previous study of bronchial epithelial cells, it was possible to identify a gene expression index that was highly correlated with bronchogenic carcinoma by empirically combining multiple cell cycle gene expression values (36) . In another manuscript,4 an index of methotrexate metabolism gene expression values better identified sensitive childhood leukemias from resistant leukemias. These findings combined with the study reported here suggest the general applicability of this method for combining individual gene expression values into indices to better define the mechanisms underlying cellular phenotype.
Environmental Exposures Affect Antioxidant Gene Expression.
The observed interindividual variation in the expression of
GST and GSHPx enzyme genes in primary NBECs (Table 3
and Table 4
) may result
from several different factors, including variation in constitutive
level of gene expression, variation in the inducible level of gene
expression and variation in inhalational exposure to exogenous
oxidants, and xenobiotics in the form of cigarette smoke, occupational,
or environmental pollutants. Although no significant relationship
between antioxidant gene expression and present smoking or amount of
past smoking (in pack-years) was observed, it remains possible that the
interindividual variation in gene expression observed in this study
could be due to variation in exposure to xenobiotics and/or oxidants
from sources other than cigarette smoke.
Lower mean antioxidant gene expression and interindividual variation in expression among the cultured cells support the hypothesis that the variation observed among the primary NBECs was at least in part due to environmental rather than hereditary causes. Further, it is possible that hereditary differences caused variation in inducible as well as constitutive levels of the genes tested. Thus, the NBECs of cancer patients may express lower levels of GSTM3, GSHPx, and GSTP1 due to the inheritance of particular polymorphisms in the regulatory regions of these genes or of the transcription factors that bind to them.
Summary.
Although the risk of bronchogenic carcinoma is strongly
associated with cigarette smoking, only 5–10% of heavy smokers are
affected. This suggests that there is interindividual variation in
endogenous risk factors. There is an urgent need to identify an
effective marker for the 5–10% of these individuals at risk. The data
presented here support the hypothesis that a low level of antioxidant
gene expression in NBECs is associated with increased risk for
bronchogenic carcinoma. Analysis in NBEC samples of the indices
provided in Table 6
, particularly, GSTP1 x GSHPx x GSTM3; mGST x GSTM3 x GSHPx x GSHPxA x GSTP1; and
GSTP1 x mGST x GSHPx, may be useful for
this purpose.
Conclusions that may be drawn from the data presented are limited in two ways. First, the numbers are relatively small, which limits the statistical power of the study. Second, the indices were identified empirically and thus are models that will require further testing to validate them.
Although the indices were derived from gene expression measurements in NBECs obtained through bronchoscopy, an investigation of hereditary differences responsible for interindividual variation in NBEC expression of GSTP1, GSTM3, and GSHPx should lead to the development of biomarkers assessable in blood samples. It will be possible to assess peripheral blood lymphocyte DNA for polymorphisms in the regulatory region of these genes that are associated with high or low expression. If such polymorphisms are identified, it will be important to control for them in future epidemiological studies. Individuals identified to be at increased risk may be suitable candidates for lung cancer chemoprevention studies and/or screening programs that employ regular chest X-rays and/or sputum cytology analysis.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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1 Supported by Grants NIEHS R01 05719, NIEHS P01
01640, NIEHS R01 02679, and NHLBI R01 HL51701 and a grant from Gene
Express, Inc. 
2 To whom requests for reprints should be
addressed, at Medical College of Ohio, Division of Pulmonary and
Critical Care Medicine, Department of Medicine, 3000 Arlington Avenue,
Toledo, OH 43699-0008. Phone: (419) 383-3543; Fax: (419) 383-6244;
E-mail: jwilley{at}mco.edu
3 The abbreviations used are: NBEC, normal
bronchial epithelial cell; PAH, polycyclic aromatic hydrocarbon; GST,
glutathione transferase; RT-PCR, reverse transcription-PCR; COPD,
chronic obstructive pulmonary disease; CT, competitive template; NT,
native template.
4 Rots et al., submitted for
publication.
Received 8/18/99. Accepted 1/19/00.
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