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Laboratory of Molecular Carcinogenesis [R. J. C. S., L. M. M., J. A. T.] and Epidemiology Branch [J. A. H., J. A. T.], and Laboratory of Experimental Pathology [J. F., P. S., G. P. F.], National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709; Departments of Environmental and Occupational Health [J. A. H., P. E. T.] and Biostatistics [R. H. Z.], Rollins School of Public Health, Emory University, Atlanta, Georgia 30322; Department of Epidemiology and Biostatistics, University of California-San Francisco School of Medicine, San Francisco, California 34143 [E. A. H., P. M. B.]; and Centers for Disease Control, National Center for Environmental Health, Atlanta, Georgia 30322 [J. W. B.]
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Abstract |
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Mutations in K-ras codon 12 were found in 46 (75%) of
61 pancreatic cancers. A prior diagnosis of diabetes was significantly
associated with K-ras negative tumors
(P = 0.002, Fisher’s exact test). The absence of
this mutation was also associated with increased serum levels of DDE,
although this association was not statistically significant
(P = 0.16, Wilcoxon’s test). There was no
difference in polychlorinated biphenyl levels between the
K-ras wild-type and mutant groups. Immunohistochemical
staining for p53 protein did not differ by patient characteristics or
clinical history, but significant associations were found with poor
glandular differentiation (P = 0.002,
2 trend test), severe nuclear atypia
(P = 0.0007, 2 trend test), and high
tumor grade (P = 0.004, 2 trend
test). Our results are suggestive of the presence of
K-ras codon 12 mutation-independent tumorigenesis
pathways in patients with prior diabetes and possibly in patients with
higher serum levels of DDE. Our results also support a role for the p53
tumor suppressor protein in the maintenance of genomic integrity.
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Introduction |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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The causes of pancreatic cancer remain unknown, but there are several factors that increase the risk for the development of the disease (for reviews, see Refs. 2, 3, 4 ). Two risk factors have been firmly established: tobacco smoking and diabetes mellitus. Between one-fourth and one-half of the pancreas cancer cases can be attributed to cigarette smoking; several cohort and case-control studies have found an increased risk of 2- to 3-fold (5 , 6) . A meta-analysis of 20 case-control and cohort studies demonstrated that a history of diabetes mellitus preceding the diagnosis of pancreatic cancer by more than 1 year is associated with a 2-fold increased risk for pancreatic cancer (4) . This risk factor had not been appreciated until recently, mainly because diabetes can be one of the symptoms associated with pancreatic cancer.
Dietary and environmental factors are suspected to influence pancreatic cancer risk; however, the results remain inconclusive (for review, see Ref. 2 ). Coffee consumption was initially reported to increase pancreatic cancer risk by a factor of 2–3 (7) , but subsequent studies have failed to reproduce this finding (2 , 8) . Some studies have reported an increased risk with high consumption of meat and low consumption of fruit, whereas low-to-moderate consumption of alcoholic beverages does not appear to be associated with an increased risk for pancreatic cancer (2) .
Organochlorines are major environmental pollutants and include DDT3 and PCB compounds. DDT was widely used as a pesticide, whereas PCBs are a group of chemically related synthetic compounds used for a variety of industrial and commercial purposes. Although DDT and PCBs were removed from the United States market in the 1970s, residual exposure continues because of the environmental persistence of these compounds. Exposure to DDT (and its metabolite DDE) and PCBs occurs in occupational and environmental settings, either directly or through food or other environmental sources. An increased risk for pancreatic cancer has been reported among individuals occupationally exposed to DDT and other organochlorine chemicals (for reviews, see Refs. 9 and 10 ). Elevated risks for pancreatic cancer were reported for DDT manufacturers (11) , and to a lesser extent for workers potentially exposed to PCBs (12) . Because organochlorines are lipophilic and resistant to further metabolism, serum levels of DDE and PCBs can be used as a surrogate measure of long-term exposure (13) . To date, there has been only one report on the possible associations of organochlorine exposure with genetic alterations in pancreatic cancer (14) .
Activating point mutations in codon 12 of K-ras are among the most common oncogene alterations in human adenocarcinomas, especially in pancreatic carcinoma (for reviews, see Refs. 15, 16, 17 ). In the earliest report, more than 90% of pancreatic carcinomas were shown to harbor K-ras codon 12 mutations (18) , whereas more recent and larger studies have indicated a prevalence of about 75% (19 , 20) . K-ras is one of a family of three ras oncogenes that also includes the Harvey- and N-ras oncogenes. The ras oncogenes encode for closely related GTP-binding proteins that can acquire transforming potential when altered in one of the critical positions at codons 12, 13, or 61. Under normal circumstances, ras proteins are involved in growth signal transduction within the cell, similarly to "second messenger" G-proteins (for review, see Ref. 21 ). Cancer-associated point mutations occur almost exclusively in codon 12 of the K-ras oncogene.
Inactivation of the p53 tumor suppressor gene is very common in almost all human cancers (for review, see Ref. 22 ). Normal p53 protein functions in cell cycle regulation, in maintenance of genomic stability, and in controlled cell death (apoptosis). A mutated p53 protein is capable of inactivating the normal function of p53 in the cell, even in the presence of the normal (wild-type) protein. Most inactivating mutations in p53 consist of single-point mutations in evolutionarily conserved domains that change the amino acid composition of the resulting p53 protein. The majority of inactivating mutations in p53 lead to an increased stability of the p53 protein. Under normal conditions, p53 protein levels in the cell nucleus are not detectable by standard protein immunohistochemistry, but in cells with mutated p53, the accumulation of p53 protein is easily detectable. Inactivation of the p53 tumor suppressor gene is common in pancreatic carcinoma and is found in 50–70% of cases (23, 24, 25) .
The molecular analysis of pancreatic cancer is complicated by its infiltrative growth and by strong desmoplastic and inflammatory responses from the host. Because of these features, it can be very difficult to obtain tumor cell preparations that are pure enough for molecular analyses. One approach to obtaining pure tumor DNA is to culture primary tumors as xenografts in nude mice, but this approach requires living cells and is difficult and time-consuming (25) . A recent technical development, LCM, has improved the isolation of near-pure tumor cell populations (26) . LCM has been successful in the isolation of DNA and RNA from a variety of tissue specimens (27) . The small surface area of microdissection makes LCM much more precise than manual microdissection using a needle or surgical blade.
For the present investigation, we used a case-case approach to test the hypothesis that known risk factors for pancreatic carcinoma are associated with characteristic molecular defects in the tumors. This information may lead to a better understanding of the molecular pathways that are present in pancreatic carcinogenesis.
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Materials and Methods |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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At the start of this substudy, information on a total of 321 eligible patients was available from the San Francisco Bay Area, whereas 53 patients were enrolled from the UCSF pathology records. A total of 91 patients had surgical tumor material available for study, of which 78 were from the Bay Area and 13 were from UCSF pathology records. In 18 of these patients, formalin-fixed paraffin-embedded tumor samples could not be obtained, mainly because of hospital refusal. For an additional six patients, the archival samples that were obtained contained insufficient tumor material for analysis, resulting in a total of 67 patients for whom all information and tumor material were available for study. An additional six specimens were excluded from the analysis because of histopathology other than pancreatic ductal carcinoma (three cystadenocarcinomas, two cystadenomas, one small cell tumor with neuroendocrine features). Thus, a total of 61 patients had sufficient material available for molecular analysis.
Pathological Review and Grading of Pancreas Tumors.
The microscopic slides from all 61 cases were reviewed independently by
a clinical pathologist (G. P. F.), without knowledge of the
submitting diagnosis. Tumors were graded as outlined in the Armed
Forces Institute of Pathology Atlas on Tumors of the Pancreas
(29)
, including glandular differentiation, number of
mitoses per 10 high power microscopic fields (x100), and nuclear
atypia. The extent of mucin production by the tumor was not deemed to
be easily evaluable and was not included among the grading factors.
Each of the three factors was assessed independently and scored from 1
to 3. The three scores were added to provide a total score that ranged
from 3 to 9. Grade I carcinomas had scores of 3 or 4, Grade II had
scores of 5–7, and Grade III had scores of 8 or 9. With tumors
exhibiting variations in degree of differentiation, grading was based
on the more poorly differentiated area if this area was 5 mm or larger.
Tumors were also designated as Grade III if the entire tumor exhibited
poorly differentiated architecture regardless of the total score, or if
two of the grading factors were in the highest score category
regardless of the score of the third factor. These modifications were
used in four tumors that had a disparity between a low mitotic count
and an otherwise poorly differentiated tumor and that had limited
material available for review. Information on the origin and stage of
the tumors was extracted from the original pathology reports. Of the 61
carcinomas included in this study, 59 were identified as ductal
adenocarcinoma of the pancreas (3 were located in the tail of the
pancreas), and 2 tumors were diagnosed as carcinoma of the ampulla of
Vater. In all except 4 cases, sufficient staging information was
available from the original pathology report. Staging classification
was performed according to the most recent pancreatic cancer
classification system by the American Joint Committee for Cancer
(30)
.
LCM.
LCM works by examination of a standard 5-µm section under the LCM
microscope and by bringing a plastic cap in direct contact with the
cells of interest. Activation of the LCM infra-red laser briefly melts
the thermoplastic ethylene vinyl polymer on the cap surface, which
causes cells to adhere to the cap for removal from the slide. The
selection of optimum areas of tumor for microdissection was based on
several factors. These included the absence of intermixed or
immediately adjacent benign pancreatic acinar, ductal, or islet tissue,
the absence of marked inflammation or hemorrhage, and the presence of
glandular or solid tumor tissue that appeared to be representative of
the tumor in the material available. The areas chosen for
microdissection were outlined in ink on the glass slides and matched to
the same area on consecutive weakly stained slides used for
microdissection. Sections were cut at 5 µm. LCM was performed with a
30-µm laser beam, firing approximately 500 laser hits at an amplitude
of 50 mW for 50 milliseconds. The polymer caps with the microdissected
cells were then transferred to a 0.5-ml microcentrifuge tube containing
50 µl of DNA lysis buffer [10 mM TRIS (pH 8.0), 0.2%
Tween 20, and 100 µg/ml proteinase K]. The tubes were then inverted
and incubated for 18–24 h at 56°C. Before PCR, the proteinase was
inactivated by incubation at 95°C for 10 min.
After LCM, the glass slides with the microdissected tissue were coverslipped and examined with the light microscope to determine the accuracy and effectiveness of the microdissection. In those cases in which the tumor was missed or was dissected along with benign tissue, the microdissection was repeated. This evaluation of the microdissected slides, and the consequent decision to repeat the dissection or not, was carried out independently and without knowledge of the molecular analysis of the original microdissected sample.
Analysis of K-ras Mutations.
K-ras mutations were determined by a previously described
method using a semi-nested PCR approach followed by mutation enrichment
(31)
. DNA sequence analysis was performed to determine the
precise nucleotide change in codon 12 of K-ras
(32)
. Briefly, 5 µl of the DNA preparation, equivalent
to one-tenth of the sample, was used for a first round of PCR
amplification. PCR-I was carried out using primer A (5'-GAA AAT GAC TGA
ATA TAA ACT TGT GGT AGT TGG ACC T-3') and primer D (5'-TCA TGA AAA TGG
TCA GAG AAA CC-3') in a total volume of 25 µl for 35 cycles. To
enrich for mutant K-ras codon 12 sequences, 10 µl of PCR-I
was then used for digestion by the restriction endonuclease MvaI
(Boehringer Mannheim, Indianapolis, IN). MvaI specifically cuts the
wild-type K-ras sequence but not any sequences that are
mutant at codon 12 of K-ras. For each sample, a second round
of PCR amplification was then carried out using the PCR-I product
(which was unenriched for mutant sequences), and in a separate tube,
with the MvaI-digested PCR-I product (which was enriched for mutant
sequences). PCR-II was performed with primers A and B (5'-TCA AAG AAT
GGT CCT GGA CC-3') in a total volume of 50 µl for 15 cycles. Other
PCR parameters and conditions were as described previously (31
, 32) . The unenriched and mutant-enriched PCR-II products were
then subjected to digestion with MvaI followed by agarose gel
electrophoresis to distinguish between wild-type and codon 12 mutant
K-ras. Samples were considered mutant when the unenriched
PCR product showed a visible mutant signal that we estimated
corresponded to a mutant contribution of at least 10% of the original
LCM microdissected sample. To determine the specific nucleotide change
at codon 12 of K-ras, mutant samples were subjected to
automated DNA sequence analysis. For this purpose, the mutant-enriched
PCR-II product was purified using QIAquick columns (Qiagen, Valencia,
CA), used for DNA cycle sequencing with the ABI Prism dRhodamine
terminator cycle sequencing kit (Perkin-Elmer Applied Biosystems,
Foster City, CA).
Immunohistochemistry for p53 Tumor Suppressor Protein.
Immunohistochemical staining for p53 was carried out with monoclonal
antibody Bp-53–11 using the NexES automated staining system (Ventana
Medical Systems, Tucson, AZ) according to instructions by the
manufacturer. Five-µm tissue sections were collected on positively
charged slides, deparaffinized with xylene, and rehydrated in ethanol
series. Antigen retrieval was performed by boiling the samples for 5
min in 0.1 M citrate buffer [0.1 M citric acid monohydrate
and 0.1 M sodium citrate (pH 6.0)]. Final detection was
performed with a standard biotin-avidin detection kit (Ventana Medical
Systems). In the large majority of the cases, immunohistochemical
staining for p53 was intense and localized in the nucleus of about
80–90% of the tumor cells. A minimum of 10% of the tumor cells had
to demonstrate nuclear staining to be counted as p53
immunohistochemistry-positive.
Environmental Exposures.
A detailed in-person interview was conducted in the subject’s home or
at a place convenient to the subject to obtain information on
environmental exposures (diet, smoking history, and coffee consumption)
and medical history along with demographic factors. No proxy interviews
were conducted. Self-reported information on cigarette smoking was
obtained for age of first smoking, number of years smoked, and number
of cigarettes per day (for each period of smoking). Intervals that
reflected a change in the smoking pattern were also assessed to obtain
a more accurate measure of lifetime cigarette smoking. Coffee
consumption in the year prior to diagnosis was obtained via a
semiquantitative food frequency questionnaire. Cut points in the
distribution of coffee consumption were selected based on the
distribution in the sample.
Blood Sampling and Analysis.
For patients enrolled between October 1, 1996, and October 1, 1998,
nonfasting blood samples were obtained about 3 months postdiagnosis and
were used for chemical analysis of organochlorines. These serum samples
were analyzed for organochlorines as described previously
(33)
. Briefly, each sample was extracted by solid phase
extraction and then analyzed on two separate gas chromatographs with
electron capture detection. Samples were adjusted for recovery of the
solid phase extraction method using the values reported in Ref.
33
. Results in ng/ml serum were obtained for
p,p'-DDE, p,p'-DDT, and 11
PCB congeners. Serum specimens were analyzed for cholesterol and
triglycerides using enzymatic methods. Lipid-corrected organochlorine
levels were created by dividing the recovery-adjusted estimates by the
lipid content of the serum sample. The use of lipid-corrected values
has been shown to account for differences in lipophilic chemical levels
between fasting and nonfasting samples (13)
. The sum of
all PCB congener values measured was used as a measure for total PCBs
level. A detailed analysis of organochlorine levels in this patient
population, including a discussion on possible effects of body size
changes, has been published previously (28)
.
Statistical Analysis.
Data analysis consisted of descriptive statistics using
2 test, 2 test for
trend, and Fisher’s exact test. Comparisons of normally distributed
data, such as pack-years, were performed using Student’s t
test. Comparisons of non-normally distributed data, such as
organochlorine levels, were performed using Wilcoxon’s rank test. The
statistical analyses were performed using SAS/STAT statistical software
(SAS Institute, Cary, NC). All of the tests were two-sided and a value
of P < 0.05 was considered statistically significant.
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Results |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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. None of these parameters varied significantly between the overall
study and this subgroup, although cases with tumor material available
were more likely to be female and to drink less coffee.
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. For each of these patients, neoplastic tissue was obtained and serial
5-µm sections were made from the formalin-fixed, paraffin-embedded
tumor blocks. Serial sections were used for standard H&E staining, for
immunohistochemistry, and for molecular analyses. Because surgical
specimens of pancreatic cancer may only contain a minority of tumor
cells, we used LCM to dissect the malignant cells away from stromal and
inflammatory cells (26
, 27)
.
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. A standard H&E-stained tumor section is shown in Fig. 1A
,
and the same tumor area is shown in Fig. 1B
as seen with the
LCM microscope. Ductal patterns are clearly visible in this field,
although more subtle morphological features may be difficult to
distinguish. The next two panels (Fig. 1, C and D)
depict an example of the LCM slide after microdissection
and the corresponding microdissected tumor material. In this study,
capture was usually near complete, although in individual cases, a
smaller fraction of the targeted cells was transferred to the cap.
Examination of the caps after overnight incubation with DNA isolation
buffer indicated complete digestion of cellular material (not shown).
For each tumor sample, approximately 500 laser hits were performed. On
average, about 5 cells are removed per laser hit, resulting in an
estimated yield of 2500 cells per sample. The equivalent of 125 cells
(which should contain 250 copies of the K-ras oncogene) was
used for PCR amplification. To verify that there was sufficient
amplifiable DNA present in these samples, K-ras PCR analysis
was performed on 5-fold serial dilutions of representative tumor
samples and were compared with dilutions of known amounts of placenta
DNA. Fig. 2
shows 5-fold serial dilutions of 0.4 ng of placenta DNA (equivalent to
about 250 gene copies), which gives a signal down to a dilution of
about 1 gene copy, but not at lower dilution (last 3 lanes
for placenta DNA). Microdissected DNA amplifies at an approximately
equivalent dilution, indicating that each microliter of the LCM DNA
preparation yields a sufficiently large number of gene copies to allow
adequate tumor representation.
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K-ras Codon 12 Mutational Analysis.
An example of the initial screen for K-ras codon 12 point
mutations is shown in Fig. 2B
. Aliquots of both the
unenriched and mutant-enriched PCR-II product are digested with MvaI to
yield a wild-type K-ras DNA fragment of 111 bp and a mutant
fragment of 147 bp. The original wild-type:mutant ratio is represented
in the unenriched lanes, whereas an almost pure mutant DNA population
can often be achieved in the mutant-enriched lanes. The latter property
makes these PCR preparations amenable for automated sequence analysis
(32)
. Fig. 3
demonstrates DNA sequence analysis of four different tumors. Of the
total of 61 pancreatic cancers, 46 (75%) had a mutant K-ras
codon 12 sequence, whereas 15 (25%) of the tumors had the normal
"GGT" sequence at codon 12. The distribution of activating
mutations was: 25 (54%) "GAT," 14 (30%) "GTT," 6 (13%)
"CGT," and 1 (2%) "TGT."
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. There was no significant difference with respect to
age-at-diagnosis, sex, or race. Patients with a self-reported history
of diabetes more than 1 year prior to cancer diagnosis had a
significantly lower frequency of K-ras mutations than
patients who did not have this diagnosis (Fisher’s exact test:
P = 0.002). The mean time between diagnosis of diabetes
and pancreatic cancer diagnosis was 9.1 years (range, 2–21 years) for
all patients with a diagnosis of diabetes more than 1 year prior to the
pancreatic cancer diagnosis.
The following histopathological features of the tumors were determined:
glandular differentiation, nuclear atypia, and mitotic index. The
combination of these three factors resulted in a score for tumor grade
(I through III). In addition, staging information was obtained from the
pathology records. K-ras mutational status was not
associated with any of these factors, although there was some evidence
for a higher incidence of K-ras mutations with increasing
tumor stage (P = 0.08, 2 test
for trend).
The analysis of the relationship between environmental exposures and
K-ras codon 12 point mutations is shown in Table 3
. There was no significant difference between K-ras positive
and negative tumors with respect to smoking history for the following
comparisons: ever versus never smoker, nonsmoker
versus current smoker, average pack-years, or duration of
smoking. Coffee consumption was analyzed for caffeinated,
decaffeinated, and total coffee consumption. No significant differences
were found with respect to K-ras mutation and coffee
consumption. Patients with K-ras positive tumors tended to
have lower serum levels of DDE, but this difference did not reach
statistical significance. Median serum DDE levels were 1951 ng/g lipid
versus 1287 ng/g lipid in patients with K-ras
negative and K-ras positive tumors, respectively
(P = 0.16, Wilcoxon’s test). There was no difference
between the K-ras negative and positive groups with respect
to median levels of total PCBs (P = 0.34, Wilcoxon’s
test). With the present sample size, the minimum detectable difference
was 1758 ng/g lipid for DDE (versus 664 ng/g lipid observed)
and 285 ng/g lipid for PCBs (versus 18 ng/g lipid observed),
at 80% power and with a 0.05 significance level.
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. Staining for p53 was always limited to the nucleus of histologically
abnormal cells. A comparison of patient characteristics and p53
immunohistochemical results is shown in Table 4
. There was no statistically significant difference between the
p53-negative and positive groups with respect to age-at-diagnosis, sex,
race, or prior history of diabetes. A strong association between p53
immunohistochemical staining and glandular differentiation
(P = 0.002, 2 test for trend)
and nuclear atypia (P = 0.0007,
2 test for trend) was observed, but p53
staining was not associated with mitotic activity of the tumors.
The composite of these three parameters, tumor grade, was also
associated with p53 immunohistochemical staining (P =
0.0038, 2 test for trend). There was an
indication of heterogeneity in p53 staining by tumor stage
(P = 0.01, Fisher’s exact test); however, there was no
evidence of a trend toward higher stage (P = 0.88,
2 test for trend).
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1 cups per day. In the p53 negative
group, these numbers were 14 and 10, respectively (P =
0.396, Fisher’s exact test). Median serum levels of DDE and PCBs were
not significantly different between the p53 negative and positive
groups. DDE levels were 1618 versus 1993 ng/g lipid and PCBs
were 420 versus 491 ng/g lipid in the p53 positive
(n = 12) and negative (n = 10) groups,
respectively. There was some evidence of an association between K-ras codon 12 mutations and p53 staining. Twenty-two tumors were mutant for both K-ras and p53, 9 were wild-type for both, 15 tumors were K-ras wild-type but p53 mutant, and 3 tumors were K-ras mutant but p53 wild-type (P = 0.051, Fisher’s exact test).
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Discussion |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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K-ras and p53 Alterations.
Mutations in codon 12 of the K-ras oncogene are very
frequent in pancreatic cancer. Previous reports have indicated that
between 70 and 90% of the tumors harbor such mutations (18
, 19)
. In this study, 75% of the tumors harbored K-ras
codon 12 mutations. The majority of these mutations were attributable
to replacement of the normal GGT sequence by either GAT or GTT
(replacing glycine with either aspartic acid or valine). The
distribution of the different mutations in codon 12 of K-ras
is remarkably similar to that reported in a pooled analysis of 13
separate studies (17)
.
Immunohistochemical staining patterns for p53 were found in about 50% of the pancreas cancers in this study, which is in agreement with previously reported frequencies (19 , 25 , 34) . In general, p53 staining is associated with inactivation of the gene as determined by DNA sequence analysis, but differences between the two methods exist. Analysis by immunohistochemistry has the advantage that all of the mutations that result in a stabilized protein can be detected, even if they occur outside exons 5 through 8 to which most sequencing efforts are limited. Previous studies have shown that K-ras codon 12 mutations and p53 tumor suppressor gene alterations occur independently of each other (34) . Our data are in general agreement with this, although there was some evidence of an association between K-ras mutations and p53 accumulation. In this study, mutations in codon 12 of K-ras or p53 staining did not cluster in any particular patient group: associations with age-at-diagnosis, sex, or race have not been reported previously and are absent in this study as well.
K-ras and Diabetes Mellitus.
One striking observation was the relative absence of K-ras
mutations in pancreatic tumors from patients with a self-reported
diagnosis of diabetes mellitus more than 1 year prior to the diagnosis
of pancreatic cancer. The two patients who had K-ras
mutation positive tumors reported diabetes 2 and 4 years prior to their
pancreatic cancer diagnosis, respectively, whereas the six
K-ras mutation negative cases had a minimum of 4 years
between the reported onset of diabetes and the pancreatic cancer
diagnosis. Our assessment of diabetes was based on a self-reported
diagnosis, which was previously shown to be in good agreement with
information obtained from medical records of pancreatic cancer patients
(35)
. The first question regarding diabetes was: "Were
you ever diagnosed as having diabetes, or sugar diabetes that lasted
for one year or longer?," and was followed up with 9 additional
questions regarding the specifics of the diagnosis. Given that all
patients were asked the same question, all were pancreatic cancer
cases, and none were aware of the K-ras status of the
cancer, we do not expect any classification bias.
It is interesting to note that diabetes mellitus is a well-established risk factor for pancreatic cancer. A meta-analysis of 20 case-control and cohort studies demonstrated a relative risk of about 2 for patients with diabetes mellitus (4) . In our study, pancreatitis is unlikely to be a confounder because none of the diabetic patients had a history of chronic or acute pancreatitis. The biology underlying an association of diabetes with pancreas cancer remains poorly understood. A possible factor might be the exposure of the pancreas to the growth-promoting effects of high levels of insulin in certain cases (36) .
The close association of diabetes with a wild-type K-ras result is suggestive of a distinct tumorigenesis pathway in these patients. Indeed, evidence for separate tumor pathways has been proposed for pancreatic cancer in a recent report by Goggins et al. (37) . A small minority of tumors exhibit microsatellite instability (RER phenotype) which is caused by defects in DNA mismatch repair capacity. The RER phenotype tumors were associated with the absence of K-ras codon 12 mutations, poor histological differentiation, a syncytial growth pattern in which cell borders are not well defined, and a better prognosis. Of the eight pancreatic cancers from patients who had a previous diagnosis of diabetes in this study, only one appeared to fit the criteria for the RER phenotype. It can, thus, be hypothesized that pancreatic cancers arising in patients with a long-standing history of diabetes may have a different genetic profile than those that are not associated with diabetes, and that these tumors are different from those with the RER phenotype. It would be of interest to determine whether such differences are reflected in tumor behavior and, eventually, patient outcome. Additional studies will be needed to study this specific question. Additional tumor characteristics (differentiation, mitotic index, nuclear atypia, and grade) did not appear to differ between those from diabetic patients or from non-diabetic patients, although the numbers for these comparisons are small.
Tumor Characteristics.
Associations between K-ras mutational status and tumor grade
and stage have generally been absent in pancreatic cancer (13
, 17) , although we did find a weak trend toward a higher frequency
of K-ras mutations with increasing stage. Because our study
consisted only of surgical cases, we must assume a selection for lower
tumor stage, which may limit generalizability to more advanced cancers.
However, the frequency and pattern of K-ras mutations
observed in this study are consistent with previously reported series.
None of the tumor grade criteria (glandular differentiation, nuclear
atypia, and mitotic index) or the combined measure of these parameters
were statistically different between the K-ras positive and
negative groups. These findings are in agreement with results from
previous studies (19
, 37
, 38)
.
When p53 staining was considered, a completely different picture in
relation to histopathological features emerged. There were significant
trends between increasing p53 positivity and both decreasing glandular
differentiation and increasing nuclear atypia. Several studies on
pancreatic cancer have shown a relationship between p53mutations and nuclear aneuploidy and poor differentiation
(25
, 38) . A possible explanation for the association
between p53 inactivation and nuclear abnormalities is the proposed role
of the p53 tumor suppressor protein in the maintenance of genomic
integrity (39)
. According to this scenario, inactivation
of p53 leads to increased accumulation of additional chromosomal
abnormalities, including those that lead to deletion of the p53locus itself (40)
. Accumulation of p53 protein was
also more frequently found in higher stage tumors, although none of the
five stage IV tumors in this study stained for p53. Some reports have
indicated a similar association of p53 positivity with higher-stage
tumors, and there are indications that p53 inactivation may
be associated with poor survival in pancreatic cancer (25
, 38)
. Staining for p53 was not different between patients with or
without a previous diagnosis of diabetes or for the other patient
characteristics (Table 4)
.
Environmental Exposures.
Although the occurrence of K-ras mutations is linked to
smoking in tumor types such as lung cancer (41)
, such a
relationship appears to be absent in this study. One previous report
indicated a difference in K-ras mutation prevalence between
ever- and never-smokers in pancreatic cancer, but there was no
association with the number of pack-years smoked (19)
.
Other studies have failed to show an association with smoking
(25)
. In light of the modest increased risk of pancreatic
cancer with smoking, the effect on K-ras mutational pattern
is probably small.
An association between coffee drinking and pancreatic cancer was proposed in some early studies, but nearly all subsequent studies have failed to document such an increased risk (reviewed in Ref. 2 ). Recently, it was reported that coffee consumption was significantly higher in patients with K-ras positive tumors than in patients with K-ras negative tumors (42) . However, our study did not find any clear relation between K-ras mutational pattern or p53 staining and coffee drinking. This was true for caffeinated coffee, decaffeinated coffee and total coffee drinking habits. Our data do not suggest an influence of coffee consumption on the pattern of K-ras mutations or p53 inactivation in pancreatic cancer. However, it may be a limitation that our questionnaire asked about average total coffee consumption habits during the year prior to diagnosis, which may not capture the etiologically relevant exposure period.
Information linking organochlorine exposure and cancer is largely based
on animal research and less so on epidemiological studies in humans
(9
, 10)
. In rodents, DDT and DDE have a possible mutagenic
effect, whereas PCBs can act as tumor promoters. The United States
Environmental Protection Agency has classified both DDT and PCBs
as probable human carcinogens (43
, 44)
. Occupational
exposure to technical grade DDT was associated with an increased risk
for pancreatic cancer in one study (11)
, whereas other
studies have been too small to detect effects on specific cancer types
(10)
. We did not find an association between serum DDE
levels and pancreatic cancer risk in the larger case-control study from
which the specimens reported here were obtained (28)
,
whereas a different case-control study reported elevated
organochlorines among pancreatic cancer cases (14)
. The
limitations found with DDE apply to studies of occupational exposures
to PCBs as well: only one of eight cohorts has demonstrated an elevated
risk for pancreatic cancer (10
, 12)
, although we observed
a significant dose-response relationship for total PCBs in the larger
case-control study (28)
. Our data suggest a possible link
between DDE exposure and the absence of K-ras mutations
(P = 0.16, Wilcoxon’s test). This result would argue
against a role of DDT as a mutagen acting in the K-ras
pathway of pancreatic cancer tumorigenesis. There was also no
difference in PCB levels between the K-ras wild-type and
mutant groups. Although serum organochlorine levels were available only
for a limited subset of patients, which limited the power of our
comparisons, the measurements in this study were comparable with those
found in the larger ongoing case-control study from which our specimens
were derived (see Table 1
).
LCM.
LCM is a powerful tool for targeting specific cell populations
(45)
. This is especially important for the molecular
analysis of pancreatic cancer cells, among which small nests of tumor
cells are frequently surrounded by abundant nonneoplastic reactive
tissue. With only minor purification steps, LCM preparations yield DNA
that is highly enriched for tumor and is of sufficient quality for
multiple PCR analyses. This enrichment is particularly important for
molecular analyses that require pure tumor cell populations such as
analyses for sequence changes or for loss of heterozygosity. However,
in some cases, it was difficult to locate the cells of interest under
the LCM view, especially in the absence of larger architectural
structures in the section. It was also clear that a fraction of the
tissue adheres nonspecifically to the cap, even when the laser was not
activated to melt the polymer. These cells were not expected to
contribute significantly to the final DNA preparation, however, and
this was shown in several experiments using serial dilutions in the
K-ras PCR. These experiments also showed that the DNA
preparations contained sufficient numbers of gene copies to be
representative of the tumor. A minimum of 250 K-ras gene
copies were calculated to be present at the start of each PCR assay,
which should give sufficient representation of any abnormal sequences
present in the tumor. Representation is an important aspect when using
formalin-fixed tissue, which may degrade DNA and increase the risk of
false-positive results (46)
.
In conclusion, we have assessed K-ras oncogene mutations and p53 protein accumulation in a population-based sample of pancreatic cancers to investigate the hypothesis that these genetic alterations may be associated with known or postulated risk factors for pancreatic cancer. One of the main findings was that activation of the K-ras oncogene, the most commonly mutated oncogene in pancreatic cancer, was rare in tumors obtained from patients with a history of diabetes. Additional studies will be needed to determine whether this reflects a separate pathway of tumorigenesis in these patients. Although previous reports have identified increased risk for pancreas cancer associated with cigarette smoking, possibly coffee consumption, and organochlorine levels in serum, these factors were not associated with either K-ras or p53 accumulation in the present study. In addition, strong evidence was found for a relationship between p53 accumulation and nuclear abnormalities, consistent with a role of p53 in the maintenance of genomic integrity.
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Acknowledgments |
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Footnotes |
|---|
1 This work was supported in part by Grant EDT-101
from the American Cancer Society and NIH Grant R01-CA59706 from the
National Cancer Institute. 
2 To whom requests for reprints should be
addressed, at Epidemiology Branch, National Institute of Environmental
Health Sciences, Maildrop A3–05, P. O. Box 12233, Research Triangle
Park, NC 27709. E-mail: taylor{at}niehs.nih.gov
3 The abbreviations used are: DDT,
dichlorodiphenyltrichloroethane; DDE,
dichlorodiphenyltrichloroethylene; PCB, polychlorinated biphenyl; LCM,
laser capture microdissection; UCSF, University of California at San
Francisco.
Received 3/ 8/00; revised 7/26/00; accepted 9/ 6/00.
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250 gene copies) in 5-fold steps down to less than 1 copy
per reaction. On the right (Lanes
17–24), 5-fold dilutions of a representative tumor sample
starting from 5 µl (1/20 of the LCM preparation) per reaction are
shown. In the left part of the gel (Lanes
1–8), 5-fold serial dilutions of one of several LCM
preparations from caps that only touched the tissue without any
activation of the laser are shown. The assay can detect as low as 1
gene copy using 35 + 15 PCR cycles. In B, the equivalent
of approximately 250 gene copies (1/20 of the LCM preparation) was
amplified from seven microdissected pancreas cancer cases and digested
with MvaI. The top band, the undigested mutant
K-ras sequence (147 bp); the lower band,
the digested wild-type K-ras band (111 bp). The
left lane (odd numbers) for each sample
is unenriched for mutant K-ras and, therefore,
corresponds to the original wild-type:mutant ratio in the tumor,
whereas the right lane (even
numbers) was enriched for mutants at codon 12 of
K-ras. The sample in Lanes 5 and
6 was wild-type for K-ras, whereas all
other samples had mutant signals that enriched after MvaI digestion.
Lanes 15 and 16, 17 and
18, and 19 and 20 are cap
only and PCR-I water and PCR-II water only controls, respectively.
M lanes, loaded with MspI-digested pUC18
as a size marker.
