Identification and characterization of differentially methylated CpG islands in pancreatic carcinoma.
Publication/Presentation Date
12-1-2001
Abstract
To identify CpG islands differentially methylated in pancreatic adenocarcinoma, we used methylated CpG island amplification (MCA) coupled with representational difference analysis. Of 42 CpG islands identified by MCA/representational difference analysis, 7 CpG islands [methylated in carcinoma of the pancreas (MICP)] were differentially methylated in a panel of eight pancreatic cancer cell lines compared with normal pancreas. In a larger panel of 75 pancreatic adenocarcinomas, these 7 MICPs (ppENK, Cyclin G, ZBP, MICP25, 27, 36, and 38) were methylated in 93, 3, 9, 15, 48, 19, and 41% of cancers, respectively, by methylation-specific PCR but not in any of 15 normal pancreata. In pancreatic cancer cell lines, methylation of ppENK, a gene with known growth suppressive properties, was associated with transcriptional silencing that was reversible with 5-aza-2'-deoxycytidine treatment. Relationships between the methylation patterns of pancreatic adenocarcinomas and their clinicopathological features were also determined. Larger pancreatic cancers and those from older patients (P = 0.017) harbored more methylated loci than smaller tumors and those from younger patients (P = 0.017). ppENK, MICP25, and 27 were variably methylated in normal gastric, duodenal, and colonic mucosae. These data indicate that aberrant methylation of ppENK and its transcriptional repression is a common event in pancreatic carcinogenesis.
Volume
61
Issue
23
First Page
8540
Last Page
8546
ISSN
0008-5472
Published In/Presented At
Ueki, T., Toyota, M., Skinner, H., Walter, K. M., Yeo, C. J., Issa, J. P., Hruban, R. H., & Goggins, M. (2001). Identification and characterization of differentially methylated CpG islands in pancreatic carcinoma. Cancer research, 61(23), 8540–8546.
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
11731440
Department(s)
Administration and Leadership
Document Type
Article