Journal: EMBO Molecular Medicine

Article Title: DNA methylation profiling reveals a predominant immune component in breast cancers

doi: 10.1002/emmm.201100801

Figure Lengend Snippet: A. Experimental outline for DNA methylation analysis of 248 breast tissues with the Infinium Methylation Assay. B. Pie chart depicting the number of CpGs differentially methylated between breast tumour and normal samples of the main set, in terms of: (i) CpG location vs. CGI (as defined in Bock et al, ) as well as CpG island shores (as defined in Irizarry et al, ); (ii) CpG location vs. promoter classes (as defined in Weber et al, ; see also of Supporting Information). C. Methylation frequencies of representative CpGs examined by bead array and their correlation with previously reported data (see of Supporting Information for a more detailes table with references). D, E. Validation of the bead array method by conventional Bisulphite Genomic Sequencing (BGS). Panel (D) shows an exemplative analysed locus, CDK3, in 1 normal (N1) and 3 tumour samples (BCs). Red arrows indicate the location of the CpG investigated by the bead array, which seems representative of the surrounding CpGs (see of Supporting Information for further examples). Data representation was done according to (Bock et al, ). Panel (E) shows a significant positive correlation (Spearman's rho = 0.82; p < 0.001) between the Infinium Methylation and BGS data.

Article Snippet: SD and CD designed experiments, performed research and interpreted data; Infinium Methylation Assays were done by SD and EC; Bisulphite genomic sequencing and pyrosequencing were done by SD, EC, MV, RD and PP; JL assisted in analysing bisulphite genomic sequencing data; SD, EC and JL performed experiments on breast epithelial cell lines; GH, NvB and PC isolated ex vivo lymphocytes and provided lymphoid cells; SD, CD, SKS, BHK, MD and StM conducted bioinformatic and statistical analyses.

Techniques: DNA Methylation Assay, Methylation, Biomarker Discovery, Genomic Sequencing

Journal: EMBO Molecular Medicine

Article Title: DNA methylation profiling reveals a predominant immune component in breast cancers

doi: 10.1002/emmm.201100801

Figure Lengend Snippet: A dendrogram (top) and a heatmap (bottom) of the 119 breast cancer (BC) specimens of the main set obtained by performing a hierarchical cluster analysis show two main clusters, I and II. ER status is a main discriminator of the two broad tumour groups (see also of Supporting Information). Box plots of ESR1 module scores show that the genes of the ESR1-positive module (left part) showed higher methylation (red) and lower expression (blue) in cluster I than in cluster II. The opposite was observed for the ESR1-negative module (right part). The ESR1 module has been previously described (Desmedt et al, ). Barcode plots of the ESR1 module (provided by GSEA analysis) showing an anti-correlation of DNA methylation and expression data (see also Table SIX and Supplemental Materials and Methods of Supporting Information). Red and blue bars designate the positions of ESR1 module genes in methylation and expression rankings, respectively. Dotted lines depict the zero.

Article Snippet: SD and CD designed experiments, performed research and interpreted data; Infinium Methylation Assays were done by SD and EC; Bisulphite genomic sequencing and pyrosequencing were done by SD, EC, MV, RD and PP; JL assisted in analysing bisulphite genomic sequencing data; SD, EC and JL performed experiments on breast epithelial cell lines; GH, NvB and PC isolated ex vivo lymphocytes and provided lymphoid cells; SD, CD, SKS, BHK, MD and StM conducted bioinformatic and statistical analyses.

Techniques: Methylation, Expressing, DNA Methylation Assay

Journal: EMBO Molecular Medicine

Article Title: DNA methylation profiling reveals a predominant immune component in breast cancers

doi: 10.1002/emmm.201100801

Figure Lengend Snippet: DNA methylation profiling of the main set identifies six groups of tumours, termed clusters 1–6, displaying differences in terms of ‘expression subtype composition’ and clinical characteristics (see also of Supporting Information). Comparison of the methylation group assigned to each tumour of the main set by the unsupervised cluster analysis and the 86 CpG-classifier established by the nearest centroid classification method (Lusa et al, ; Sorlie et al, ; see also of Supporting Information). Classification of each tumour of the validation set into one of the six methylation groups by means of the 86 CpG-classifier (see also of Supporting Information). Note that the 6 groups obtained for the validation set presented the same ‘expression subtype composition’ and clinical characteristics as the groups obtained for the main set (see also of Supporting Information).

Article Snippet: SD and CD designed experiments, performed research and interpreted data; Infinium Methylation Assays were done by SD and EC; Bisulphite genomic sequencing and pyrosequencing were done by SD, EC, MV, RD and PP; JL assisted in analysing bisulphite genomic sequencing data; SD, EC and JL performed experiments on breast epithelial cell lines; GH, NvB and PC isolated ex vivo lymphocytes and provided lymphoid cells; SD, CD, SKS, BHK, MD and StM conducted bioinformatic and statistical analyses.

Techniques: DNA Methylation Assay, Expressing, Comparison, Methylation, Biomarker Discovery

Journal: EMBO Molecular Medicine

Article Title: DNA methylation profiling reveals a predominant immune component in breast cancers

doi: 10.1002/emmm.201100801

Figure Lengend Snippet: The 86 key CpGs that characterize the 6 methylation-based clusters

Article Snippet: SD and CD designed experiments, performed research and interpreted data; Infinium Methylation Assays were done by SD and EC; Bisulphite genomic sequencing and pyrosequencing were done by SD, EC, MV, RD and PP; JL assisted in analysing bisulphite genomic sequencing data; SD, EC and JL performed experiments on breast epithelial cell lines; GH, NvB and PC isolated ex vivo lymphocytes and provided lymphoid cells; SD, CD, SKS, BHK, MD and StM conducted bioinformatic and statistical analyses.

Techniques: Methylation

Journal: EMBO Molecular Medicine

Article Title: DNA methylation profiling reveals a predominant immune component in breast cancers

doi: 10.1002/emmm.201100801

Figure Lengend Snippet: Comparison of gene expression signatures of several normal mammary epithelial subpopulations (Lim et al, ) with gene expression and DNA methylation profiles of our six DNA methylation-based groups of patients in the main set. A-C. Box plots of MaSC (A), luminal progenitor (B) and luminal mature (C) signature scores for each of the six methylation breast cancer groups, based on their gene expression profiles. Cluster 3 displayed the highest luminal progenitor signature score ( p = 0.001 vs. clusters 2 and 4; p < 0.001 vs. other clusters; (B)), whereas the luminal mature signature score was higher for clusters 1, 4, 5 and 6 ( p < 0.001 for each of these clusters vs. clusters 2 and 3, except for cluster 4 vs. cluster 2 where p = 0.019; (C)). Cluster 2 was not associated with any of the three signatures. D-F. Box plots of MaSC (D), luminal progenitor (E), and luminal mature (F) signature scores for each of the six methylation breast cancer groups, based on their DNA methylation profiles. A strong anti-correlation was observed between gene expression and DNA methylation data for the luminal progenitor and mature signatures (compare (E) with (B) and (F) with (C), respectively) (respective Pearson's coefficients: −0.59, p = 1.10 −9 and −0.70, p = 6.10 −14 ). It was weaker for the MaSC signature (compare (D) with (A); Pearson's coefficient: −0.47, p = 4.10 −6 ).

Article Snippet: SD and CD designed experiments, performed research and interpreted data; Infinium Methylation Assays were done by SD and EC; Bisulphite genomic sequencing and pyrosequencing were done by SD, EC, MV, RD and PP; JL assisted in analysing bisulphite genomic sequencing data; SD, EC and JL performed experiments on breast epithelial cell lines; GH, NvB and PC isolated ex vivo lymphocytes and provided lymphoid cells; SD, CD, SKS, BHK, MD and StM conducted bioinformatic and statistical analyses.

Techniques: Comparison, Gene Expression, DNA Methylation Assay, Methylation

Journal: EMBO Molecular Medicine

Article Title: DNA methylation profiling reveals a predominant immune component in breast cancers

doi: 10.1002/emmm.201100801

Figure Lengend Snippet: Histograms showing the heterogeneity of breast tumours in terms of the number of CpGs differentially methylated compared to normal samples. Differential methylation of genes involved in immunity as revealed by GO analysis, with high hypomethylation content in clusters 2 and 3. Histological patterns of breast tumours displaying no lymphocyte infiltration (1) or both stromal and intratumoural infiltration (2). Panel 3 provides a closer look at the intratumoural infiltration presented in panel 2. Black arrows indicate epithelial cells, whereas green and blue arrows indicate stromal and intratumoural lymphocytes, respectively. Box plots depicting the higher lymphocyte infiltration in main set tumours belonging to clusters 2 and 3 as compared to tumours belonging to other clusters. Box plots illustrating the inverse correlation between LCK and ITGAL methylation and lymphocyte infiltration (Jonckheere–Terpstra test for trends; see also of Supporting Information). Methylation status, assessed by DNA methylation profiling, of immune genes highlighted by GO analysis in breast epithelial cell lines as well as in ex vivo lymphocytes and lymphoid cell lines (see also of Supporting Information).

Article Snippet: SD and CD designed experiments, performed research and interpreted data; Infinium Methylation Assays were done by SD and EC; Bisulphite genomic sequencing and pyrosequencing were done by SD, EC, MV, RD and PP; JL assisted in analysing bisulphite genomic sequencing data; SD, EC and JL performed experiments on breast epithelial cell lines; GH, NvB and PC isolated ex vivo lymphocytes and provided lymphoid cells; SD, CD, SKS, BHK, MD and StM conducted bioinformatic and statistical analyses.

Techniques: Methylation, DNA Methylation Assay, Ex Vivo

Journal: EMBO Molecular Medicine

Article Title: DNA methylation profiling reveals a predominant immune component in breast cancers

doi: 10.1002/emmm.201100801

Figure Lengend Snippet: Pie chart depicting the high proportion of immune genes, and in particular of genes involved in T cell biology, among all the genes that appeared significant prognostic markers (FDR < 0.1) (see of Supporting Information). Box plots illustrating the correlation of methylation (in red) and expression (in blue) status of LAX1 and CD3D with stromal lymphocyte infiltration (Jonckheere–Terpstra test for trends; see also of Supporting Information). Anti-correlation between the methylation and expression status of the 11 prognostic immune markers in breast epithelial cell lines as well as in ex vivo lymphocytes and lymphoid cell lines, as determined by DNA methylation and gene expression profiling. High expression of 11 immune genes is associated with a better clinical. Forest plots showing the log2 hazard ratio (squares) with the 95% confidence interval (bars) of the relapse-free survival analysis. A negative hazard ratio reveals that a high expression level of the indicated variable is associated with a good outcome, and conversely. Immune markers appear significant in a multivariate analysis with all the classical markers used in clinic, as shown for the LAX1 and CD3D genes used as examples (see also of Supporting Information for the complete analysis). n , Number of patients; CI, Confidence Interval. Subtype-specific prognostic value of immune markers for breast cancer. Exemplative Kaplan–Meier curves for different levels of expression of the LAX1 and CD3D genes in each known ‘expression subtype’ (see also of Supporting Information for the detailed continuous univariate survival analysis for each subtype).

Article Snippet: SD and CD designed experiments, performed research and interpreted data; Infinium Methylation Assays were done by SD and EC; Bisulphite genomic sequencing and pyrosequencing were done by SD, EC, MV, RD and PP; JL assisted in analysing bisulphite genomic sequencing data; SD, EC and JL performed experiments on breast epithelial cell lines; GH, NvB and PC isolated ex vivo lymphocytes and provided lymphoid cells; SD, CD, SKS, BHK, MD and StM conducted bioinformatic and statistical analyses.

Techniques: Methylation, Expressing, Ex Vivo, DNA Methylation Assay, Gene Expression