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From the Departments of Molecular Medicine,*
Oncology
and Pathology,
and
Surgery,
Karolinska Hospital, Stockholm,
Sweden; and the Laboratory of Cancer Genetics,
Institute of Medical Technology, University of Tampere and Tampere
University Hospital, Tampere, Finland
| Abstract |
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| Introduction |
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The genetic mechanisms involved in the tumorigenesis of carcinoid tumors are poorly understood. The vast majority of cases are sporadic, although familial cancer syndromes associated with an increased risk of carcinoid tumors are also seen, mainly in multiple endocrine neoplasia type 1 (MEN 1). Most of the carcinoids associated with MEN 1 have been reported to be of foregut origin.4 The gene responsible for MEN 1, MEN1 at 11q13, has recently been cloned and its involvement in the tumorigenesis of sporadic MEN 1-associated tumors has been characterized.5,6 In carcinoids from the lung frequent somatic deletions of the MEN1 region have been demonstrated using loss of heterozygosity (LOH) and comparative genomic hybridization (CGH) analyses,7-12 and in a significant proportion of the cases inactivating MEN1 mutations have also been detected.8 Loss of 11q has also been characterized in a limited number of carcinoids, which were of ileal, duodenal, and gastric origin,7,13 and on 18q in gastrointestinal carcinoids.12
Other frequently detected genetic alterations in carcinoid tumors include losses of 3p, 5q, 9p, 10q, and 13q in lung carcinoids.10,11 The TP53 gene, which is frequently mutated in most human tumors, including gastrointestinal tumors,14 is only rarely mutated in carcinoids,15,16 indicating that TP53 is not important in the tumorigenesis.
To gain a better understanding of the genetic basis of the different types of carcinoid tumors, we have characterized numerical imbalances in a series of midgut carcinoids using CGH, and compared the results to previous findings in carcinoids from the lung.
| Materials and Methods |
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The study includes 18 tumor specimens from 18 patients operated on
for midgut carcinoids at the Karolinska Hospital between 1986 and 1997.
The samples were snap-frozen in liquid nitrogen after surgery and
stored at -70°C until analysis. The histopathological diagnosis and
classification were based on the tumor location, the tumor growth
pattern, on signs of secretory granules as determined by
immunohistochemical analysis of Chromogranin A, and/or a positive
reaction with the Grimelius silver technique, and finally on a positive
reaction for Massons silver staining as a marker of serotonin
production.3
In addition, the size of the primary tumor,
and the presence of metastases to the lymph nodes and the liver were
recorded for each patient (Table 1)
.
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CGH
High molecular weight DNA was isolated from frozen tumor tissues according to standard procedures and used for CGH analyses. CGH was performed essentially as previously described.17 Briefly, tumor DNA samples were labeled with fluorescein isothiocyanate-dUTP (DuPont, Boston, MA) by nick translation, and normal reference DNA was labeled with Texas Red-dUTP (Vysis Inc., Downers Grove, IL). Tumor and reference DNA were then mixed with unlabeled Cot-1 DNA (Life Technologies, Inc., Gaithersburg, MD), denatured, and applied onto slides with denatured metaphases of normal lymphocytes (Vysis Inc.). After hybridization at 37°C for 48 hours, the slides were washed in 0.4x standard saline citrate/0.3% Nonidet P-40 at 74°C for 2 minutes and in 2x standard saline citrate/0.1% Nonidet P-40 at room temperature for 1 minute. After air drying, the slides were counterstained with 4,6-diamidino-2-phenylindole (Vysis Inc.). Two control experiments were performed. In the first, normal male and normal female DNAs were labeled and hybridized to normal metaphases. For the second experiment, DNA from a previously characterized breast cancer cell line (MPE 600, Vysis Inc.) and DNA from a normal female were labeled and hybridized to normal male metaphases.
Ten three-color digital images (4,6-diamidino-2-phenylindole, fluorescein isothiocyanate, and Texas Red fluorescence) were collected from the hybridizations using a Zeiss Axioplan 2 (Carl Zeiss Jena GmbH, Jena, Germany) epifluorescence microscope and Sensys (Photometrics, Tucson, AZ) charge-coupled device camera interfaced to a IPLab Spectrum 10 workstation (Signal Analytics Corporation, Vienna, VA). Green-to-red (g/r) fluorescence ratios <0.8 were considered as losses whereas ratios >1.2 were scored as gains of genetic material. Heterochromatic regions, the short arm of the acrocentric chromosomes, and chromosome Y were not included in the evaluation.
LOH Studies
Matched pairs of blood and tumor DNA samples from nine patients (cases 2, 3, 4, 6, 8, 9, 11, 15, and 18) were genotyped for six polymorphic microsatellite markers including D18S1270, D18S541, D18S858, D16S2624, D16S539, and D16S422. The markers were labeled with fluorescent dyes (ie, HEX, TET, FAM). Fifty ng of DNA was amplified in a 10-µl reaction solution containing 1.0 µl 10x buffer (Finnzyme, Oy), 1 mmol/L MgCl2 (Perkin Elmer, Emeryville, CA), 0.5 µmol/L primer pairs, 0.1 mmol/L dNTPs, and 0.2 µl DNA polymerase (Dynazyme, Finnzyme, Oy). Amplifications were performed using a 10-minute initial denaturation at 95°C, followed by 30 cycles of 30 seconds at 94°C, 30 seconds at 55°C or 60°C, and 30 seconds at 72°C, and a final 5-minute extension at 72°C. The fluorescently labeled PCR products were electrophoresed using 5% polyacrylamide gels (Long Ranger; FMC BioProducts, ME) on an ABI 377 apparatus (Applied Biosystems, Perkin Elmer) and the results were analyzed by Genescan Analysis 3.1 software package (Applied Biosystems, Perkin Elmer). LOH was confirmed when the ratio of allele intensity of the tumor DNA to normal DNA was 50% or less.
Statistical Analyses
Individual chromosome copy number changes of midgut carcinoids and bronchial carcinoids10 were compared using the Fishers exact test, and correlations between CGH aberrations and clinical and histopathological features were analyzed using the Mann-Whitney U test in the StatView 4.5 software. Probabilities of <0.05 were accepted as significant.
| Results |
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DNA samples from all 18 tumor samples were successfully analyzed by
CGH. The chromosomal regions with increased and decreased DNA sequence
copy numbers are illustrated in Figure 1
and detailed for each tumor in Table 2
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The mean number of CGH alterations per tumor was 2.1 ± 1.7,
mean ± SD (range, 0 to 6). Numerical imbalances were detected in
16 of the 18 tumors, and losses were more common than gains. The most
commonly seen losses were detected at 18q22-qter (67%), 11q22-q23
(33%), and 16q21-qter (22%), whereas gains most frequently involved
4p14-qter (22%). High-level amplifications were not detected.
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The four most frequently detected CGH alterations were compared to the
total number of alterations in the individual tumors, and whether they
were detected in primary tumor specimens or in metastases. These
comparisons revealed several significant correlations. The pattern of
CGH alterations in the individual tumors were found to vary depending
on the total number of detected alterations (Table 2)
. Loss of
18q22-qter and loss of 11q22-q23 were both detected as single
aberrations in four and one cases, respectively. However, loss of
16q21-qter and gain of 4p14-qter were only detected in tumors having a
total of two to six alterations (Table 2)
. Furthermore, the total
number of alterations found in the metastases were significantly higher
than in the primary tumors (P = 0.036,
Mann-Whitney). Losses of 18q22-qter and 11q22-q23 were detected both in
primary tumors and metastases without significantly different
frequencies (Table 3)
. However,
significantly different frequencies were seen for loss of 16q21-qter
that were only seen in metastases (P = 0.0016,
Fishers exact test), and gain of 4p14-qter that was present mainly in
metastases (P = 0.044, Fishers exact test)
(Table 3)
. Taken together, the findings would suggest a progression of
numerical imbalances, in which loss of 18q22-qter and 11q22-q23
represent early events in the tumorigenesis, and loss of 16q21-qter and
gain of 4p14-qter are late events associated with metastasizing of
midgut carcinoids.
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| Discussion |
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The four recurrent numerical imbalances detected included losses of 18q22-qter, 11q22-q23, and 16q21-qter, and gains of 4p14-qter. Chromosome 18q, especially the region of 18q12.3-q21.3, is frequently deleted in many types of tumors,18 such as pancreatic and colorectal tumors.19,20 Three tumor suppressor genes located in the 18q12.3-q21.3 region, MADH2/SMAD2 at 18q12.3, MADH4/SMAD4 in 18q21.1, and DCC in 18q21.2, have been evaluated as targets for the frequent deletions, but specific alterations of these genes have only been rarely described.21-23 The minimal region of overlapping deletions detected in midgut carcinoids was mapped to 18q22-qter, which is located immediately distal to the region mentioned above. This would suggest the existence of a yet uncharacterized tumor suppressor gene locus whose inactivation represents a frequent and early event in the development of midgut carcinoids. Interestingly, no 18q losses were detected in two independent CGH studies of lung carcinoids,10,12 whereas this was the most common alteration in midgut carcinoids, indicating that the gene in 18q is specifically involved in the early development of midgut carcinoids but not in carcinoids of the lung.
Loss of 11q22-q23 occurs frequently in both hematological malignancies and in many types of solid tumors, such as breast, lung, cervical, and ovarian carcinoma and melanoma.18 The long arm of chromosome 11 is gene-rich and harbors multiple tumor suppressor genes especially within the region of q22-q23, which thus represent candidate genes for carcinogenesis of midgut carcinoids. The PPP2R1B gene (the serine/threonine protein phosphatase subunit locus), has been shown to be mutated in lung and colon cancer,24 and recently, the SDHD (succinate-ubiquinone oxidoreductase subunit D) gene in 11q23 was demonstrated to be responsible for hereditary paraganglioma.25 The role of the ATM (ataxia telangiectasia mutated) gene in carcinogenesis is still not clear, but it is assumed to function as a tumor suppressor gene, and has been thoroughly studied in breast cancer.26 Other possible candidate genes include CHK1, a protein kinase required for the DNA damage checkpoint,27 LOH11CR2A,28 and DDX10, a putative RNA helicase,29 and ALL-1 (disrupted in acute leukemias)30 that all reside within 11q23.
Homozygous inactivation of the MEN1 tumor suppressor gene in
11q13 by mutation of one allele and loss of the second allele through a
gross deletion, has been observed in a third of sporadic lung
carcinoids.8
Interestingly, loss of 11q in lung carcinoids
was never restricted to the MEN1 gene locus in 11q13, but
always extended distally to the 11q22 region (Figure 2)
. On the
other hand, loss of 11q22-q23 has been seen in lung carcinoids without
loss of 11q13.7,10
This could be interpreted as indicating
that both MEN1 and a more distally located gene on 11q are
involved in lung carcinoids. Furthermore, because the minimal regions
of loss are the same in midgut and lung carcinoids (Figure 2)
,
it is likely that one and the same gene in 11q22-q23 is involved in
both types of tumors.
Carcinogenesis can be regarded as a multistep process, which is associated with the accumulation of genetic alterations,31-33 and this view may also be applied to the development of midgut carcinoids. Consequently, more CGH alterations were seen in the metastatic lesions than in the primary tumors analyzed, and in addition the pattern of CGH alterations varied depending on the total number of detected alterations. Taken together, the findings were suggestive of a progression of numerical imbalances, in which loss of 18q and 11q represent early events, and loss of 16q and gain of 4p are late events associated with the tumor progression. Identification of the exact molecular alterations reflected by these numerical imbalances is likely to bring along an improved understanding of carcinogenesis of midgut carcinoids. Furthermore, these will provide starting points for the development of markers for diagnostic purposes.
| Acknowledgements |
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| Footnotes |
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Supported by the Swedish Cancer Foundation, The Torsten and Ragnar Söderberg Foundations, and the Cancer Society in Stockholm.
Accepted for publication January 23, 2001.
| References |
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