Fausto SESSA Anatomia Patologica
Epigenetic profiles of gastroenteropancreatic neuroendocrine neoplams.
Insights into the pathogenetic mechanisms with potential clinical impact.
Abstract
Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are a heteogenous group of
neoplasms characterized by different morphologic, clinical, and biological features. Their
pathogenesis is largely unknown, in spite of several studies performed in the last years. Particularly,
little is known about the pathogenetic role of epigenetic mechanisms, indeed, very few studies have
been published about DNA hypermethylation in these tumors with a limited number of genes
analyzed. Moreover, there is no information about distinct hypermethylation profiles of GEP-NENs
and there are not studies on this topic analyzing large series of NETs with different clinicopathologic features and adequate follow-up period. For these reasons, the main aim of the present
project is that of analyzing the methylation profile of a large series of GEP-NENs and to correlate it
with tumor grading and staging, functional status, and patients’ prognosis. 415 cases (300 well
differentiated and 115 poorly differentiated NENs) will be enrolled. Each case will be
morphologically revaluated and the MS-MLPA technique will be used to perform promoter
methylation analysis of 34 different tumor suppressor genes. Quantitative RT-PCR analysis and
immunohistochemistry will be use to evaluate the mRNA levels and expression of proteins codified
by the genes examined in the methylation study. Finally, all findings will be correlated with clinicopathological features.
State of art and rationale of the study
GEP-NENs are a heterogeneous group of neoplasms characterized by different morphologic,
molecular, and clinical features (1). Their diagnosis is currently much more common than in the
past probably reflecting a more awareness of this disease. Despite a better diagnostic ability and the
recently proposed classification (2), the correct prognostic stratification of patients often remains
difficult, especially for the assessment of malignant potential of well to moderately differentiated
neuroendocrine tumors (NETs).
On the basis of morphology, NETs can be separated from poorly differentiated neuroendocrine
carcinomas (NECs) (2). This distinction is particularly important for the different therapeutic
approach (3) and the different genetic and pathogenetic characteristics (4). NECs are high grade
carcinomas associated with poor patients’ survival. Although in the last years a few studies have
clarified the pathogenetic role of some genes (5), genetic and epigenetic mechanisms involved in
NEC development and progression are largely unknown. NETs follow a relatively indolent course
and may occur sporadically or in the setting of well defined inherited diseases. The genetic
alterations involved in the onset and progression of sporadic forms are poorly understood, although
in recent years several studies have been carried out to identify specific molecular markers with
potential diagnostic and/or prognostic value (6). To date, little is known about the role of epigenetic
mechanisms in the onset of GEP-NENs. Very few studies have been published about DNA
hypermethylation in these tumors with a limited number of genes analyzed (7) and there is no
information about distinct hypermethylation profiles of NENs. Moreover, there are not studies on
this topic analyzing large series of NENs with different clinicopathological features and adequate
follow-up period.
The rationale for a project aimed in defining the role and the frequency of DNA methylation in
GEP-NENs is based on the large amounts of data gathered in recent years about the importance of
CpG island methylation in GEP adenocarcinomas (8). Our recent studies have shown that DNA
methylation as well as CIMP are present in colorectal adenocarcinomas and in NECs with very
similar frequencies (around 25-30% of cases) (9,10) and hypermethylation of specific genes may
mark the early steps of neoplastic transformation in this site. Furthermore, we have recently
preliminary demonstrated that an extensive DNA methylation characterizes a subset of pancreatic
NETs and that positive associations may be observed between the presence of hypermethylation of
specific genes (DAPK1, TIMP3, PAX5, PTEN, THBS1, HIC1, TP73) and tumor aggressiveness
(11).
Objectives
It seems clear that a better understanding of the role of gene methylation in GEP-NENs may
have important diagnostic and clinical implications. The aims of the present study are: 1) to stratify
patients into different prognostic groups with biologically different neoplasms and 2) to identify
tumors potentially responsive to classes of drugs designed to inhibit either DNA methylation or
histone deacetylation, such as 5-azacytidine inactivating DNA methyltransferase and inhibitors of
histone deacetylases. At least some of these drugs are in current clinical practice and many more are
in the clinical trials pipeline (12).
Methodology
The study will have five main steps:
1. Enrolling and morphological characterization of tumors.
In this step 415 cases (300 differentiated NETs e 115 NECs) present in the files of the
Department of Pathology of the Ospedale di Circolo-Fondazione Macchi at Varese from 1980 to
2010 will be enrolled and reclassified using the criteria proposed by the WHO (3). For each case, all
available clinical information including patients’ survival will be collected. The series will be
composed of the following tumor types: 40 gastric NETs, 70 ileal NETs, 50 appendiceal NETs, 50
colorectal NETs, 90 pancreatic NETs, 12 esophageal NECs, 41 gastric NECs, 56 intestinal NECs (6
duodenal and 50 colonic), 3 NECs of the gallbladder, and 3 pancreatic NECs.
2. Analysis of methylation profile using the MS-MLPA technique.
The SALSA MS-MLPA ME001 Tumor suppressor-1 Kit and SALSA MS-MLPA ME002
Tumor suppressor-2 Kit (MRC-Holland, Amsterdam, The Netherlands) will be used to perform
promoter methylation analysis on all tumors included in the study. MS-MLPA will be executed as
described by the manufacturer and data analysis will be carried out using Coffalyser Software v. 8
(MRC Holland). Aberrant methylation will be scored as a categorical variable using a specific
Methylation Ratio (MR) for each gene (9,10).
3. Quantitative RT-PCR (qRT-PCR) to analyze the expression levels of genes examined in the
methylation study
Tumor RNA samples will be extracted from FFIP tissues and reverse transcribed according to
the protocols previously optimized in our lab (9). qRT-PCR will be used to test a condition of
haplo-insufficiency or complete loss of expression for the subset of genes exhibiting promoter
methylation. The analysis of transcripts will be carried out using TaqMan assays (inventoried
Taqman® MGB gene expression assays, Applied Biosystems) and the instrument ABI-PRISM 7000
Sequence Detection System and RQ software (Applied Biosystems). The most suitable reference
genes for this analysis will be chosen among a set of housekeeping genes known to be constitutively
expressed across a wide range of biological conditions and tissues (HPRT1, β2PGK1, ACTB, Applied Biosystems). The data analysis of qRT-PCR will be performed according to
the method of comparative quantification (user Bulletin # 2, Applied Biosystems).
4. Immunohistochemical study to evaluate the expression of proteins codified by gene underwent
methylation analysis
The avidin-biotin-peroxidase method will be used to study immunohistochemically all enrolled
tumors as previously reported (10). The antibodies directed against the following antigens will be
employed:
a) Proteins codified by genes examined using the MS-MLPA technique;
b) Antigens needed for tumor classification such as Ki67, serotonin, gastrin, ghrelin, somatostatin,
glicentin, insulin, glucagon, pancreatic polypeptide, calcitonin, neutoensin, VIP, PYY, CDX2,
and TTF1.
This immunohistochemical technique is routinely used in our laboratory and it has been well
standardized as demonstrated by several papers published in these years by the researches involved
in this project.
5.Data analysis and correlation of the clinico-pathological features with DNA methylation status
and gene silencing.
DNA methylation status will be correlated with tumor grading and staging, with the functional
profiles and location as well as with tumor recurrence and patient survival. The statistical analysis
for association and correlation will be performed using Fisher’s exact test, 2 test, ANOVA and the
independent sample t test. Kaplan-Meier curves for univariate survival analysis and the Cox
proportional hazards model for multivariate survival analysis will be calculated. Furthermore, we
will evaluate the possibility of applying unsupervised hierarchical clustering in order to distinguish
specific methylation patterns to be correlated with all the clinicopathological features (R statistical
package). The expression levels of transcripts and proteins will be compared with the gene
methylation status and all the results will be correlated with the clinical-pathological features.
References
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11. Mod Pathol 26(Suppl 2):137A,2013
12. J Natl Cancer Inst 97:1498-506,2005