Enroth et al. BMC Cancer 2011, 11:450 http://www.biomedcentral.com/1471-2407/11/450 Methods Patient material Normal colon mucosa [13] and tumor samples were obtained from two patients diagnosed with CRC at Uppsala University Hospital (Sweden). Immediately upon surgery, the removed material was kept on ice. Samples from the normal colon mucosa were taken at least 15 cm from the localized tumor, while the tumor sample was collected without containing parts of the normal mucosa. A gastrointestinal pathologist per- formed sample collection and tumor evaluation. The patients did not receive any anticancer treatment before surgery. All patients treated for CRC in Uppsala are registered in the Swedish Colorectal Cancer Registry. When admitted to the hospital they are asked to partici- pate in that registry and also informed that biopsies will be saved in a biobank. After having read the information the informed consent is verbally obtained. Linked to this we have an ethical approval to perform studies like this, #2006/077. ChIP and ChIP-chip ChIP on patient samples and HT29 cells were per- formed as previously described [13,54]. DNA amplifica- tion, fragmentation, labelling and hybridizations of ChIP and input DNAs were performed according to Affyme- trix recommendations and basically as previously described [13], using Affymetrix GeneChip Human Pro- moter 1.0 arrays, which cover approximately from 7.5 kb upstream to 2.45 kb downstream of transcription start sites for over 25,500 human promoters. Raw array data has been deposited in ArrayExpress under acces- sion number E-TABM-533 Data analysis pipeline Affymetrix Tiling Analysis SDK revision 4 was used to quantile normalize each pair of replicate ChIP measure- ments together with the two input measurements and adjusted to have a median intensity of 200 [55,56]. Replicates were combined using a sliding window of 301 bp (bandwidth = 150) assigning the median value of the replicates in the window to the center probe. From this point, all analysis was carried out using custom scripts in R [57]. Log2-ratios of merged ChIP measurements over merged input measurements were used for further analysis. Enriched regions were defined using a Z-score based sliding window approach. For each probe on the array, a Z-score was calculated from the average of log2-ratios of probes within a window of 150 base pairs centred on the probe against the distribution of log2- ratios on the array. Enriched regions were defined from enriched probes (Z-score >= 6) using the following criteria; (i) at least 2 Page 11 of 13 enriched probes within the region, (ii) each enriched probe must be flanked on both sides by existing mea- surements within 110 base pairs (iii) the maximum gap between enriched probes within a region is 110 base pairs. Regions were prolonged with probes positioned within 75 base pairs of the probes defining the tails of the regions. Finally, regions were merged if the shortest distance was less than 1000 base pairs. Bivalent regions were defined as regions sharing at least three probes between H3K4me3 and H3K27me3 regions out of which at least two were enriched. Regions classified as having changed their methylation status (’transitions’) between normal and tumor where required to have at least three probes in common out of which two needed to be commonly labelled as enriched in the different states. In addition to this we required a Z- score of at least 3 between the normal and tumor in the non-changed methylation status ensuring that we are not selecting regions immediately on opposite sides of the chosen cut-off, i.e. clearly separating changes invol- ving bivalent marks to single marks from instances where a single mark is changed to another single mark. Gene Annotation We associated enriched regions to UCSC knownGene transcripts if; (i) the regions were intragenic and posi- tioned within 2.5 kb downstream of TSS or (ii) inter- genic and positioned within 2.5 kb upstream of TSS but not associated to any other transcript through intragenic positioning. This window size (+/- 2.5 kb) was chosen based on the distribution of both H3K4me3 and H3K27me3 signals around transcription start sites. We defined transcripts to be marked by H3K4me3 if asso- ciated with at least one H3K4me3 region and no H3K27me3 region. The same was done for H3K27me3 associated transcripts. Transcripts associated with both H3K4me3 regions and H3K27me3 regions but not with bivalent regions were called semi-bivalent. Gene Ontology (GO) analysis GO terms were tested using a one-sided Fishers exact test. P-values were corrected for multiple hypotheses testing using Bonferroni correction. The hierarchical clustering was done using Euclidean distances and the Ward agglomeration method. All analysis was done using R [57] Microarray Gene expression data sets Microarray genes expression data sets were downloaded from Gene Expression Omnibus (GEO) public reposi- tories. Expression data was obtained and analyzed using GEOquery and the ‘limma’ Bioconductor package in R [57]. Expression data from paired tumor and normal