Fig. 6: The DNA methylation landscape of siNETs. | Nature Communications

Fig. 6: The DNA methylation landscape of siNETs.

From: Comprehensive molecular portrait reveals genetic diversity and distinct molecular subtypes of small intestinal neuroendocrine tumors

Fig. 6

Methylation refines the siNET groups. a Unsupervised k-means consensus clustering was found to be optimal with 4 groups for the top 1,000 most variable CpGs methylation probes (in row: A, B, C and D) and samples (in column, Sample.Methyl.Clust: epithelial-enriched, hypomethylated, unifocal-enriched and FGA-enriched). Clustering method: Ward’s; distance: Euclidean. Recapitulative ssGSEA score of each gene cluster (epithelial, vesicular, mesenchymal and immune), chr18.del and chr4.10.14.gains statuses together with methylation subtypes are indicated as bottom annotations. b Boxplots of the methylation levels (mean beta value) of the 1000 most variants probes (left) and each of the four probe clusters (right: A-D) across the four k-means based methylation clusters (hypomethylated, n = 41; epithelial-enriched, n = 18; unifocal-enriched, n = 26 and FGA-enriched, n = 22). Two-tailed exact p-values were determined by Kruskal-Wallis test. Boxplots: center line = median, box range 25th–75th percentile, minimum/maximum denoted by whiskers. c Barplots for co-occurrence analysis of methylation clusters vs expression clusters, FGA levels, chr18 deletion, chr4.10.14 gains and tumor type (unifocal or multifocal). Significance was determined by two-tailed Fisher’s exact test.

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