The most significantly differentially expressed genes between EAC G1 and USC G3.

<p>Performed using data from The Cancer Genome Atlas, listed in order of log2 fold change. The top 10 upregulated and downregulated genes are shown. Log₂ FC, log2 fold-change in gene expression for USC G3 relative to EAC G1; SE, standard error; BH, Benjamini & Hochberg adjusted p-values. ‘Mean’ denotes mean expression for each group based as normalized RNAseq reads.</p

<i>PAX8</i> is differentially expressed between pure and mixed-type tumors.

<p>Normalized relative gene expression, the horizontal line indicates median expression, the box indicates the 25^th and 75^th percentiles of the data and dots represent outlier datapoints.</p

Comparison of p16 gene and protein expression.

<p>(A) Linear regression shows p16 gene and protein expression are highly correlated in USC and EAC components of MT-ECs. Protein expression is denoted at the percentage of cells staining positive plotted against relative, normalized gene expression. (B) P16 protein expression in USC and EAC components of a mixed tumor. 400X magnification.</p

Patient information for samples used in this study.

<p>W, white; H, Hispanic.</p

Epidemiology of ECs (age).

<p>Statistically significant associations are indicated in bold. EAC G1 and USC were used as comparator samples, as indicated, yo, years old.</p

Epidemiology of ECs (ethnicity).

<p>Statistically significant associations are indicated in bold, analyses compared the proportion of EAC, USC and MT-ECs that occur in White or African American Women. Other ethnic groups were excluded from the analyses. EAC G1 and USC were used as comparator samples, as indicated.</p

Linkage disequilibrium between the 92 common variants (MAF>0.05) in HapMap CEPH trios.

<p>Each square represents the correlation (r²) between each pair of SNPs with darker shades representing stronger LD. Tag SNPs are indicated with those SNPs that failed assay design being shown in grey font.</p

Breast and ovarian cancer genotype specific risks for each tSNP by study

<p>1 odds ratio, 2 confidence interval, * compared with common homozygote. Confidence intervals that do not reach or cross 1.00 and P- values<0.05 are in bold type</p

Serous type ovarian cancer genotype specific risks for each tSNP

*<p>compared with common homozygote. Confidence intervals that do not reach or cross 1.00 and P- values<0.05 are in bold type</p

Inherited Variants in Regulatory T Cell Genes and Outcome of Ovarian Cancer

<div><p>Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs) has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL) and sequence-based tagging single nucleotide polymorphisms (tagSNPs) for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p = 2.7×10⁻⁵), LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p = 4.5×10⁻⁴, and rs3753348, p = 9.0×10⁻⁴, respectively), and CD80 (endometrioid, rs13071247, p = 8.0×10⁻⁴). Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p = 0.006). An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p = 8.1×10⁻⁴) among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies.</p> </div