DNA methylation profiling reveals common signatures of tumorigenesis and defines epigenetic prognostic subtypes of canine Diffuse Large B-cell Lymphoma

Abstract

Epigenetic deregulation is a hallmark of cancer characterized by frequent acquisition of new DNA methylation in CpG islands. To gain insight into the methylation changes of canine DLBCL, we investigated the DNA methylome in primary DLBCLs in comparison with control lymph nodes by genome-wide CpG microarray. We identified 1,194 target loci showing different methylation levels in tumors compared with controls. The hypermethylated CpG loci included promoter, 5'-UTRs, upstream and exonic regions. Interestingly, targets of polycomb repressive complex in stem cells were mostly affected suggesting that DLBCL shares a stem cell-like epigenetic pattern. Functional analysis highlighted biological processes strongly related to embryonic development, tissue morphogenesis and cellular differentiation, including HOX, BMP and WNT. In addition, the analysis of epigenetic patterns and genome-wide methylation variability identified cDLBCL subgroups. Some of these epigenetic subtypes showed a concordance with the clinical outcome supporting the hypothesis that the accumulation of aberrant epigenetic changes results in a more aggressive behavior of the tumor. Collectively, our results suggest an important role of DNA methylation in DLBCL where aberrancies in transcription factors were frequently observed, suggesting an involvement during tumorigenesis. These findings warrant further investigation to improve cDLBCL prognostic classification and provide new insights on tumor aggressiveness.

Figure 1

Genomic distribution of differentially methylated sequences in cDLBCLs versus control lymph nodes. (A) Percentages of hyper- and hypo-methylated probes across CpG regions and CDS. Corresponding sequence counts are reported in each barplot. (B) Distribution of hyper- and hypo-methylated features across different genomic locations. Percentages with respect to the corresponding total number of hyper- and hypo-methylated sequences are reported. Sequence counts allow repetitions, since a sequence can overlap more than one genomic location. Asterisks (*) indicate enriched genomic locations, according to Fisher’s Exact test (Supplementary File 1).

Figure 2

PPI sub-networks from differentially methylated genes belonging to the enriched GO terms and KEGG pathways. The thickness of network edges correlates with the confidential score provided by STRING database: the thicker is the edge, the higher is the confidence score of the interaction.

Figure 3

Heatmap of the 138 CpG sequences highly correlated with the first principal component. Methylation levels were centered and scaled by sequence.

Figure 4

Survival outcomes in patient cohort. Kaplan-Maier curves for LSS according to cDLBCL subgroups defined by PCA and hierarchical clustering on methylation patterns.