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. 2009 Feb 1;69(3):758-64.
doi: 10.1158/0008-5472.CAN-08-2984. Epub 2009 Jan 20.

Large-scale profiling of archival lymph nodes reveals pervasive remodeling of the follicular lymphoma methylome

Affiliations

Large-scale profiling of archival lymph nodes reveals pervasive remodeling of the follicular lymphoma methylome

J Keith Killian et al. Cancer Res. .

Abstract

Emerging technologies allow broad profiling of the cancer genome for differential DNA methylation relative to benign cells. Herein, bisulfite-modified DNA from lymph nodes with either reactive hyperplasia or follicular lymphoma (FL) were analyzed using a commercial C/UpG genotyping assay. Two hundred fifty-nine differentially methylated targets (DMT) distributed among 183 unique genes were identified in FL. Comparison of matched formalin-fixed, paraffin-embedded and frozen surgical pathology replicates showed the complete preservation of the cancer methylome among differently archived tissue specimens. Analysis of the DMT profile is consistent with a pervasive epigenomic remodeling process in FL that affects predominantly nonlymphoid genes.

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Conflict of interest statement

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Figures

Figure 1
Figure 1
Comparison between FFPE and frozen archiving samples and groups for target differential methylation measurement. A, representative correlations ofFFPE and frozen sample array measures for various individuals. Top left, oldest FH sample pair (r = 0.97; 28 mo); top right, oldest FL sample pair (r = 0.98; 22 mo); bottom left, best correlation (r = 0.99); bottom right, worst correlation sample pair (r = 0.95). B, pairwise comparison of target differential methylation significances (P values) between FL and FH for 1,505 targets, as measured separately for FFPE and frozen archive groups (left). Differentially methylated CpG targets show hypermethylation (red, n = 184) and hypomethylation (green, n = 75) in FL relative to reactive hyperplasia (right). C, comparison of FFPE versus frozen archive groups for uniformity of measurement of the identified 259 DMTs in FH (left) and FL (right).
Figure 2
Figure 2
A, dendrogram of unsupervised hierarchical classification of all samples in the study based on 259 DMT profile. Blue, FL; orange, MCD; yellow, lymphoblastoid cell lines; pink, PBL CD4+ T cells; purple, PBL CD8+ T cells; dark blue, PBL B cells; brown, reactive lymph nodes; black, noncancerous lymph node tissue adjacent lymphoma. Gray barbells, matched FFPE and frozen lymph node pairs that cosegregate. B, heatmap of unsupervised hierarchical cluster of 259 DMT β values from above cases. Same color code applies.
Figure 3
Figure 3
Representative COBRA assays for validation of array analyses. PCR primers for each of the eight CpG targets are given in Supplementary Table S4. One half of each PCR product was run on 3% agarose gel neat (−) and the other half after Taq1 restriction digest (+). AIM2, CARD15, CHI3L2, and EPHX1 show hypomethylation in FL samples relative to FH, indicated by diminished Taq1 cutting of PCR product. EPHA7, ETV1, PITX2, and TFAP2C show hypermethylation in FL relative to FH, indicated by greater Taq1 restriction digestion of FL-derived PCR products. These results are in accordance with array measures.
Figure 4
Figure 4
Relative methylation activities of CGI and non-CGI targets for hypermethylated and hypomethylated DMTs. This plot, adjusted for the greater methylation preload of non-CGI targets, reflects a roughly 2-fold greater CGI hypermethylation versus non-CGI hypermethylation, equivalent non-CGI hypomethylation and hypermethylation, and significant deficit of CGI demethylation in FL.

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