Poster abstracts
Poster number 77 submitted by Brian Giacopelli
Epigenetic classification of CLL using the novel Bisulfite-iPLEX technique
Brian J. Giacopelli (Molecular, Cellular, and Developmental Biology), Yue-Zhong Wu (Comprehensive Cancer Center, The Ohio State University), John C. Byrd (Department of Internal Medicine, Division of Hematology, The Ohio State University), Christopher C. Oakes (Department of Internal Medicine, Division of Hematology, The Ohio State University)
Abstract:
Subclassification of tumor samples using epigenetic patterns is an emerging and powerful approach to predict clinical outcomes and improve therapy selection. Current technology for analyzing DNA methylation ranges from global assays, which provide a large amount of data but at a high cost per sample, to targeted assays, which cost less per sample but focus on a single small region of DNA. To simultaneously address numerous genomic regions in a high-throughput and cost efficient manner, a new approach was needed. We developed a novel method for analyzing the methylation status of multiple CpGs named Bisulfite-iPLEX (Bs-iPLEX) using the MassARRAY system (Agena Biosciences) which utilizes a MALDI-TOF mass spectrometer to analyze oligonucleotides. This method is capable of screening up to 30 individual CpGs multiplexed in a single well in 384 samples simultaneously. Here we demonstrate that the Bs-iPLEX is a highly accurate, reproducible, and efficient tool for measuring DNA methylation.
As an application of the Bs-iPLEX, we designed a panel of targeted CpGs to profile the epigenetic pattern of chronic lymphocytic leukemia (CLL) patients. CLL is a clinically heterogeneous disease which can be classified into three subgroups based on their epigenetic profile defined by genome-wide DNA methylation patterns using 450K arrays (Illumina). Our multiplexed panel accurately classifies CLL patient subgroups using a greatly reduced number of CpGs (20 CpGs) defferentially methylated among CLL patients. We initially evaluated the accuracy of the panel using a set of 96 patient samples of known subgrouping. We further validated with a set of an additional 96 patient samples. We conclude that the Bs-iPLEX is an efficient and accurate technique for assaying the DNA methylation profile of patient samples, and can effectively be used to classify CLL patients with potential clinical utility.
Keywords: Epigenetics, Cancer