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Comparison of CpG Island Methylator Phenotype (CIMP) Frequency in Colon Cancer Using Different Probe- and Gene-Specific Scoring Alternatives on Recommended Multi-Gene Panels
Authors:Marianne Berg  Hanne R Hagland  Kjetil S?reide
Institution:1. Department of Gastrointestinal Surgery, Stavanger University Hospital, Stavanger, Norway.; 2. Centre of Organelle Research, University of Stavanger, Stavanger, Norway.; 3. Department of Clinical Medicine, University of Bergen, Bergen, Norway.; Howard University, United States of America,
Abstract:

Background

In colorectal cancer a distinct subgroup of tumours demonstrate the CpG island methylator phenotype (CIMP). However, a consensus of how to score CIMP is not reached, and variation in definition may influence the reported CIMP prevalence in tumours. Thus, we sought to compare currently suggested definitions and cut-offs for methylation markers and how they influence CIMP classification in colon cancer.

Methods

Methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA), with subsequent fragment analysis, was used to investigate methylation of tumour samples. In total, 31 CpG sites, located in 8 different genes (RUNX3, MLH1, NEUROG1, CDKN2A, IGF2, CRABP1, SOCS1 and CACNA1G) were investigated in 64 distinct colon cancers and 2 colon cancer cell lines. The Ogino gene panel includes all 8 genes, in addition to the Weisenberger panel of which only 5 of the 8 genes included were investigated. In total, 18 alternative combinations of scoring of CIMP positivity on probe-, gene-, and panel-level were analysed and compared.

Results

For 47 samples (71%), the CIMP status was constant and independent of criteria used for scoring; 34 samples were constantly scored as CIMP negative, and 13 (20%) consistently scored as CIMP positive. Only four of 31 probes (13%) investigated showed no difference in the numbers of positive samples using the different cut-offs. Within the panels a trend was observed that increasing the gene-level stringency resulted in a larger difference in CIMP positive samples than increasing the probe-level stringency. A significant difference between positive samples using ‘the most stringent’ as compared to ‘the least stringent’ criteria (20% vs 46%, respectively; p<0.005) was demonstrated.

Conclusions

A statistical significant variation in the frequency of CIMP depending on the cut-offs and genes included in a panel was found, with twice as many positives samples by least compared to most stringent definition used.
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