Impact of Sample Heterogeneity on Methylation Analysis


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Abstract

The recent emergence of high-throughput arrays for methylation analysis has made the influence of tumor content on the interpretation of methylation levels increasingly pertinent. However, to what degree does tumor content have an influence, and what degree of tumor content makes a specimen acceptable for accurate analysis remains unclear. Taking a systematic approach, we analyzed 98 unselected formalin-fixed and paraffin-embedded gastric tumors and matched normal tissue samples using the Illumina GoldenGate methylation assay. Unsupervised hierarchical clustering showed 2 separate clusters with a significant difference in average tumor content levels. The probes identified to be significantly differentially methylated between the tumors and normals also differed according to the tumor content of the samples included, with the sensitivity of identifying the “top” candidate probes significantly reduced when including samples below 70% tumor content. We also tested whether the removal of the probes featuring single nucleotide polymorphisms and/or DNA repetitive elements, reportedly present in GoldenGate arrays, would significantly affect the study's findings, and found little change in the results with their omission. Our findings suggest that tumor content significantly influences the interpretation of methylation levels and candidate gene identification, and that 70% tumor content may be a suitable threshold for selecting samples for methylation studies.

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