Scatterplot representation of marker discovery process and ROC curves.

<p>A (top figure: HM27, bottom figure: HM450), scatterplots of the highest PBL β-value (β-PBL_H) of 10 (HM27) and 2 (HM450) healthy control samples (X-axis) against the associated 10th percentile of CRC tumor β-values (β-CRC₁₀) on the Y-axis. The blue dots represent the eliminated probes (HM27: n = 23,049; HM450: n = 367,833) and the red dots (HM27: n = 695; HM450: n = 30,207) represent the retained probes with a β-CRC₁₀>β-PBL_H or a β-PBL_H<0.2. B, scatterplots of the mean normal colon tissue β-value (β-NC_M) for the retained probes from Panel A (X-axis) against the associated β-CRC₁₀ (Y-axis). The red dots (HM27: n = 512; HM450: n = 28,428) represent the eliminated probes, the green dots represent the retained probes (HM27: n = 183; HM450: n = 1779) with a β-CRC₁₀>β-NC_M or a β-NC_M<0.2. C, scatterplots of the retained probes from Panel B (green) displayed by the difference between β-CRC₁₀ and β-PBL_H (X-axis) against the associated β-CRC₁₀ (Y-axis). The dots within the yellow square are the probes selected for additional filtering against other types of cancer. The white arrows point out the probes of the two candidate markers. D, ROC curves for the probes used in the multiplex reaction based on methylation β-values of 335 independent colorectal cancer samples and 23 independent matched normal colorectal tissue samples (the DNA methylation data of these samples were not used in the marker discovery pipeline). The dark grey color is the area under the curve.</p

Overview of samples and data sets used for biomarker discovery.

*<p>normal samples were obtained from surgical specimens of CRC patients, at least 10 cm from the tumor margins.</p>**<p>these samples were among the samples run on the HM27 platform.</p

Schematic representation of colorectal cancer marker discovery and verification pipeline.

<p>We used DNA methylation data from the Infinium HumanMethylation27 Beadchip (HM27) and HumanMethylation450 Beadchip (HM450) Infinium platforms to screen 27,578 (HM27) and 482,421 (HM450) CpG loci for their methylation status in CRC samples, PBL samples from healthy subjects, paired normal colorectal tissue samples (NC) and 15 other types of cancer (OC). We used a stepwise approach eliminating probes that failed in any of the samples, probes that contained SNPs or repeat sequences, probes with a highest PBL β-value (β-PBL_H) or a mean normal colon tissue β-value (β-NC_M) higher than the associated 10th percentile of CRC tumor β-values (β-CRC₁₀) or higher than 0.2 in any of the PBL or NC samples (Infinium panel). The remaining probes were ranked based on the difference between β-CRC₁₀ and β-PBL_H and the top 25 were selected from both datasets (HM27 and HM450) for filtering against OC samples. Probes with a mean OC β-value higher than the associated mean CRC β-value (β-CRC_M) were eliminated. A total of 15 MethyLight reactions (markers) were designed for 10 probes and tested in a sequence of verification steps (MethyLight panel). Markers were eliminated if their performance was suboptimal in controls such as <i>in vitro</i> methylated <i>Sss</i>1 DNA, PBL and plasma samples from healthy controls and CRC tumor tissues. Markers were also eliminated if they failed to detect CRC methylated DNA in pooled plasma and serum from CRC patients. Two markers met all the selection criteria and were advanced in the pipeline for further verification on individual patient samples. (*Probes that failed in any of the samples, as well as those that included SNPs and repeat sequences; **Other cancer types used in this study are summarized in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050266#pone-0050266-t001" target="_blank">Table 1</a>, ***M.<i>Sss</i>I treated DNA).</p

Clinical characteristics of CRC patients and controls used for plasma and serum analysis.

<p>Clinical characteristics of CRC patients and controls used for plasma and serum analysis.</p

DNA methylation β-values of THBD and C9orf50 in various types of samples.

<p>Jitter plots representing Infinium-based DNA methylation β-values of <i>THBD</i> (left panel) and <i>C9orf50</i> (right panel) in 335 independent CRC tumors, matched normal colon tissues, a variety of other cancer types and PBL from healthy individuals. The specific number of samples for each tissue type is described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050266#pone-0050266-t001" target="_blank">Table 1</a>.</p

Genome-wide association studies identify four ER negative-specific breast cancer risk loci

<p>Estrogen receptor (ER)-negative tumors represent 20-30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry. The etiology and clinical behavior of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition. To identify susceptibility loci specific to ER-negative disease, we combined in a metaanalysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P= 2.1 x 10(-12) and LGR6, P = 1.4 x 10(-8)), 2p24.1 (P = 4.6 x 10(-8)) and 16q12.2 (FTO, P = 4.0 x 10(-8)), were associated with ER-negative but not ER-positive breast cancer (P> 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.</p>