Abstract
BackgroundDue to the heterogeneity of cancer, identifying differentially methylated (DM) CpG sites between a set of cancer samples and a set of normal samples cannot tell us which patients have methylation aberrations in a particular DM CpG site.MethodsWe firstly showed that the relative methylation-level orderings (RMOs) of CpG sites within individual normal lung tissues are highly stable but widely disrupted in lung adenocarcinoma tissues. This finding provides the basis of using the RankComp algorithm, previously developed for differential gene expression analysis at the individual level, to identify DM CpG sites in each cancer tissue compared with its own normal state. Briefly, through comparing with the highly stable normal RMOs predetermined in a large collection of samples for normal lung tissues, the algorithm finds those CpG sites whose hyper- or hypo-methylations may lead to the disrupted RMOs of CpG site pairs within a disease sample based on Fisher’s exact test.ResultsEvaluated in 59 lung adenocarcinoma tissues with paired adjacent normal tissues, RankComp reached an average precision of 94.26% for individual-level DM CpG sites. Then, after identifying DM CpG sites in each of the 539 lung adenocarcinoma samples from TCGA, we found five and 44 CpG sites hypermethylated and hypomethylated in above 90% of the disease samples, respectively. These findings were validated in 140 publicly available and eight additionally measured paired cancer-normal samples. Gene expression analysis revealed that four of the five genes, HOXA9, TAL1, ATP8A2, ENG and SPARCL1, each harboring one of the five frequently hypermethylated CpG sites within its promoters, were also frequently down-regulated in lung adenocarcinoma.ConclusionsThe common DNA methylation aberrations in lung adenocarcinoma tissues may be important for lung adenocarcinoma diagnosis and therapy.
Highlights
Due to the heterogeneity of cancer, identifying differentially methylated (DM) CpG sites between a set of cancer samples and a set of normal samples cannot tell us which patients have methylation aberrations in a particular DM CpG site
Stable relative methylation-level orderings (RMOs) of CpG sites in normal lung tissues are widely disrupted in cancer tissues We collected a total of 355 samples for normal lung tissues, including 79 samples derived from three datasets assayed by the 27K array and 276 samples derived from two datasets assayed by the 450K array (Table 1)
90.62% of the stable CpG site pairs in the shorter list were included in the longer list and 99.75% of the overlapped CpG site pairs had the same RMOs in the two sets of the normal lung tissue samples
Summary
Due to the heterogeneity of cancer, identifying differentially methylated (DM) CpG sites between a set of cancer samples and a set of normal samples cannot tell us which patients have methylation aberrations in a particular DM CpG site. A novel computational tool is needed to detect which patients have methylation aberrations in a particular CpG site. To tackle this difficulty, some previous works discretized DNA methylation states of CpG sites in a cancer sample through comparing with the average methylation level in a set of normal samples [12, 13]. Because the DNA methylation levels of CpG sites vary across individuals in a healthy population, this approach may be affected by biological variations
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