Background: Methylation-induced silencing of promoter CpG islands in tumor suppressor genes plays an important role in human carcinogenesis. In colorectal cancer, the CpG island methylator phenotype (CIMP) is defined as widespread and elevated levels of DNA methylation and CIMP+ tumors have distinctive clinicopathological and molecular features. In contrast, the existence of a comparable CIMP subtype in gastric cancer (GC) has not been clearly established. To further investigate this issue, in the present study we performed comprehensive DNA methylation profiling of a well-characterised series of primary GC.
Methods: The methylation status of 1,421 autosomal CpG sites located within 768 cancer-related genes was investigated using the Illumina GoldenGate Methylation Panel I assay on DNA extracted from 60 gastric tumors and matched tumor-adjacent gastric tissue pairs. Methylation data was analysed using a recursively partitioned mixture model and investigated for associations with clinicopathological and molecular features including age, Helicobacter pylori status, tumor site, patient survival, microsatellite instability and BRAF and KRAS mutations.
Results: A total of 147 genes were differentially methylated between tumor and matched tumor-adjacent gastric tissue, with HOXA5 and hedgehog signalling being the top-ranked gene and signalling pathway, respectively. Unsupervised clustering of methylation data revealed the existence of 6 subgroups under two main clusters, referred to as L (low methylation; 28% of cases) and H (high methylation; 72%). Female patients were over-represented in the H tumor group compared to L group (36% vs 6%; P = 0.024), however no other significant differences in clinicopathological or molecular features were apparent. CpG sites that were hypermethylated in group H were more frequently located in CpG islands and marked for polycomb occupancy.
Conclusions: High-throughput methylation analysis implicates genes involved in embryonic development and hedgehog signaling in gastric tumorigenesis. GC is comprised of two major methylation subtypes, with the highly methylated group showing some features consistent with a CpG island methylator phenotype.
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http://dx.doi.org/10.1186/1471-230X-14-55 | DOI Listing |
Front Oncol
December 2024
Penn State Hershey Cancer Institute, Pennsylvania State University College of Medicine, Hershey, PA, United States.
Unlabelled: Cladribine indirectly downregulates methylation of DNA, RNA, and histones by blocking the transfer of methyl groups from -adenosyl-methionine. The cladribine and rituximab combination showed a synergetic effect in treating B-cell lymphomas. Bortezomib (Velcade) is a Food and Drug Administration (FDA)-approved proteasome inhibitor for treating mantle cell lymphoma (MCL).
View Article and Find Full Text PDFFront Endocrinol (Lausanne)
December 2024
Rare Disease Research Group, Molecular (Epi) Genetics Laboratory, Bioaraba Health Research Institute, Araba University Hospital, Vitoria-Gasteiz, Spain.
Objective: To identify the genetic cause underlying the methylation defect in a patient with clinical suspicion of PHP1B/iPPSD3.
Design: Imprinting is an epigenetic mechanism that allows the regulation of gene expression. The locus is one of the loci within the genome that is imprinted.
Cancer Metab
December 2024
Department of Obstetrics and Gynecology, First Affiliated Hospital, Shihezi University, Shihezi, China.
BMC Biol
December 2024
Department of Orthodontics, School and Hospital of Stomatology, Liaoning Provincial Key Laboratory of Oral Diseases, China Medical University, Shenyang, 110001, China.
Background: Age-related kidney impairment, characterized by tubular epithelial cell senescence and renal fibrosis, poses a significant global public health threat. Although N6-methyladenosine (m6A) methylation is implicated in various pathological processes, its regulatory mechanism in kidney aging remains unclear.
Methods: An m6A-mRNA epitranscriptomic microarray was performed to identify genes with abnormal m6A modifications in aged human kidney tissues.
Genome Biol
December 2024
Department of Statistics, University of British Columbia, Vancouver, Canada.
Single-cell DNA methylation measurements reveal genome-scale inter-cellular epigenetic heterogeneity, but extreme sparsity and noise challenges rigorous analysis. Previous methods to detect variably methylated regions (VMRs) have relied on predefined regions or sliding windows and report regions insensitive to heterogeneity level present in input. We present vmrseq, a statistical method that overcomes these challenges to detect VMRs with increased accuracy in synthetic benchmarks and improved feature selection in case studies.
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