Clinical details of the 19 <i>HOXB13</i> missense mutation G84E carriers (rs138213197), their male relatives and their mothers at baseline, sufficient to calculate the penetrance estimates.^*

*<p>B, brother; F, father; HB, half-brother; MU, maternal uncle; MGF, maternal grandfather; PU, paternal uncle; PGF, paternal grandfather; S, son.</p><p>Observation time began at date of birth and ended at the earliest of the following: date of diagnosis of prostate cancer, date at death, or 31 Dec 2011. Carrier status: + carrier, (+) obligate carrier, − non-carrier, ? unknown carrier status.</p

Penetrance (age-specific cumulative risk) (solid line), and 95% confidence limits intervals (dashed lines), of prostate cancer for carriers of the HOXB13 missense mutation G84E (rs138213197) by selected years of birth.

<p>Penetrance (age-specific cumulative risk) (solid line), and 95% confidence limits intervals (dashed lines), of prostate cancer for carriers of the HOXB13 missense mutation G84E (rs138213197) by selected years of birth.</p

Penetrance (age-specific cumulative risk) and 95% confidence intervals of prostate cancer for carriers of the <i>HOXB13</i> missense mutation G84E (rs138213197) by selected years of birth.

<p>Penetrance (age-specific cumulative risk) and 95% confidence intervals of prostate cancer for carriers of the <i>HOXB13</i> missense mutation G84E (rs138213197) by selected years of birth.</p

Comparison of average blood and tumor-derived DNA methylation across a panel of tumor suppressor genes.

<p>Plotted β-values at CpG probes across defined genomic regions. Red line indicates average β-value for blood-derived DNA samples. Blue line indicates average β-values for tumor-derived DNA samples. * indicates significant statistical difference (p<0.01). Error bars are plotted Standard Error of Mean. Gene region schematics denote [CGI (CpG Island), TSS (Transcriptional Start Site)].</p

DNA methylation at the <i>PALB2</i> promoter region.

<p>Plotted β-values for each sample at each CpG probe across <i>PALB2</i> (chr16:23,649,887 –chr16:23,653,182). Red line indicates average β -value for blood-derived DNA samples. Blue line indicates average β-value for tumor-derived DNA samples. * indicates significant statistical difference (p<0.01). Solid black bars indicate regions previously screened for methylation. Gene region schematic denotes [CGI (CpG Island), TSS (Transcriptional Start Site)].</p

Sample tumor DNA methylation at the <i>MLH1</i> promoter region.

<p>Plotted β-values for each sample at each CpG probe across <i>MLH1</i> (chr3:37,033,277 –chr3:37,082,650). Solid black line indicates average β-values for blood-derived DNA. Dotted black line indicates average β-values for tumor-derived DNA. Schematic of four <i>MLH1</i> promoter regions previously defined by Deng <i>et al</i>, base pair number is in relation to the start codon (ATG) Regions. * highlights tumor-derived DNA samples showing increased <i>MLH1</i> methylation. Gene region schematic denotes [CGI (CpG Island), TSS (Transcriptional Start Site)]</p

Sample tumor DNA methylation across a panel of tumor suppressor genes.

<p>Plotted β-values at CpG probes across defined genomic regions. Each colored line indicates β-values for an individual tumor-derived DNA sample. Solid black line indicates average β-values for blood-derived DNA. Dotted black line indicates average β-values for tumor-derived DNA. Gene region schematics denote [CGI (CpG Island), TSS (Transcriptional Start Site)].</p

Causes of blood methylomic variation for middle-aged women measured by the HumanMethylation450 array

<p>To address the limitations in current classic twin/family research on the genetic and/or environmental causes of human methylomic variation, we measured blood DNA methylation for 479 women (mean age 56 years) including 66 monozygotic (MZ), 66 dizygotic (DZ) twin pairs and 215 sisters of twins, and 11 random technical duplicates using the HumanMethylation450 array. For each methylation site, we estimated the correlation for pairs of duplicates, MZ twins, DZ twins, and siblings, fitted variance component models by assuming the variation is explained by genetic factors, by shared and individual environmental factors, and by independent measurement error, and assessed the best fitting model. We found that the average (standard deviation) correlations for duplicate, MZ, DZ, and sibling pairs were 0.10 (0.35), 0.07 (0.21), -0.01 (0.14) and -0.04 (0.07). At the genome-wide significance level of 10⁻⁷, 93.3% of sites had no familial correlation, and 5.6%, 0.1%, and 0.2% of sites were correlated for MZ, DZ, and sibling pairs. For 86.4%, 6.9%, and 7.1% of sites, the best fitting model included measurement error only, a genetic component, and at least one environmental component. For the 13.6% of sites influenced by genetic and/or environmental factors, the average proportion of variance explained by environmental factors was greater than that explained by genetic factors (0.41 vs. 0.37, <i>P</i> value <10⁻¹⁵). Our results are consistent with, for middle-aged woman, blood methylomic variation measured by the HumanMethylation450 array being largely explained by measurement error, and more influenced by environmental factors than by genetic factors.</p

<em>RAD51</em> and Breast Cancer Susceptibility: No Evidence for Rare Variant Association in the Breast Cancer Family Registry Study

<div><h3>Background</h3><p>Although inherited breast cancer has been associated with germline mutations in genes that are functionally involved in the DNA homologous recombination repair (HRR) pathway, including <em>BRCA1</em>, <em>BRCA2</em>, <em>TP53</em>, <em>ATM</em>, <em>BRIP1</em>, <em>CHEK2</em> and <em>PALB2,</em> about 70% of breast cancer heritability remains unexplained. Because of their critical functions in maintaining genome integrity and already well-established associations with breast cancer susceptibility, it is likely that additional genes involved in the HRR pathway harbor sequence variants associated with increased risk of breast cancer. <em>RAD51</em> plays a central biological function in DNA repair and despite the fact that rare, likely dysfunctional variants in three of its five paralogs, <em>RAD51C, RAD51D,</em> and <em>XRCC2,</em> have been associated with breast and/or ovarian cancer risk, no population-based case-control mutation screening data are available for the <em>RAD51</em> gene. We thus postulated that <em>RAD51</em> could harbor rare germline mutations that confer increased risk of breast cancer.</p> <h3>Methodology/Principal Findings</h3><p>We screened the coding exons and proximal splice junction regions of the gene for germline sequence variation in 1,330 early-onset breast cancer cases and 1,123 controls from the Breast Cancer Family Registry, using the same population-based sampling and analytical strategy that we developed for assessment of rare sequence variants in <em>ATM</em> and <em>CHEK2.</em> In total, 12 distinct very rare or private variants were characterized in <em>RAD51</em>, with 10 cases (0.75%) and 9 controls (0.80%) carrying such a variant. Variants were either likely neutral missense substitutions (3), silent substitutions (4) or non-coding substitutions (5) that were predicted to have little effect on efficiency of the splicing machinery.</p> <h3>Conclusion</h3><p>Altogether, our data suggest that <em>RAD51</em> tolerates so little dysfunctional sequence variation that rare variants in the gene contribute little, if anything, to breast cancer susceptibility.</p> </div

Summary of results from reported studies on <i>PIK3CA</i> mutation in colorectal carcinoma and various associations with molecular and pathological characteristics.

<p>Summary of results from reported studies on <i>PIK3CA</i> mutation in colorectal carcinoma and various associations with molecular and pathological characteristics.</p