Brinton, Louise A.

Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3′ gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97–1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03–1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed (p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa (r = 0.51, p = 1.7 × 10−28), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.

Abstract Background: Pelvic inflammatory disease (PID) has been associated with ovarian cancer and Chlamydia trachomatis (chlamydia) is the leading cause of PID in the developed world. Primary infection with chlamydia is often asymptomatic and may persist for several months/years, thus ascertainment of PID in epidemiologic studies is challenging due to pervasive misclassification and under-reporting. To improve our understanding of the role of chlamydia and other infectious agents in developing ovarian cancer, we evaluated serologic markers of infection with incident ovarian cancer using a staged approach in two independent populations. Methods: Studies included: 1) a case-control study conducted in Poland of 278 ovarian cancer cases diagnosed from 2000 to 2003 and age- and study site-matched controls (n=556) and 2) a nested case-control study from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial including 160 women who eventually developed ovarian cancer and 159 matched controls. We calculated odds ratios (OR) and 95% confidence intervals (CI) for the association between serologic marker titers and ovarian cancer risk using logistic regression adjusted for matching factors and potential confounders. We evaluated laboratory cutpoints indicative of prior chlamydia infection and tested more stringent marker thresholds, identified in Poland and applied in PLCO, that could be relevant for a PID-like infection. Results: In the Polish study, positivity for the chlamydia plasmid-encoded Pgp3 protein was associated with increased ovarian cancer risk [OR (95% CI): 1.63 (1.20-2.22)]; when a positive result was redefined at a higher titer, ovarian cancer risk increased [cutpoint 2: 2.00 (1.38-2.89); cutpoint 3 (max OR): 2.19 (1.29-3.73)]. All other chlamydia markers measured were associated with increased risk at the more stringent positivity threshold in Poland. In the prospective PLCO study, Pgp3 was associated with elevated risk at the laboratory cutpoint [1.43 (0.78-2.63)]; using higher thresholds, Pgp3 was associated with increased ovarian cancer risk [cutpoint 2: 2.25 (1.07-4.71); cutpoint 3: 2.53 (0.63-10.08)]. In both studies, markers of other infections (i.e., Mycoplasma genitalium, herpes simplex virus-2, human papillomavirus, herpes simplex virus-1, polyomavirus, hepatitis B, hepatitis C, Epstein Barr virus, cytomegalovirus) measured were not associated with risk. Conclusions: In two independent populations, the gold standard serologic marker of prior/current chlamydia infection (Pgp3) was associated with a doubling in ovarian cancer risk, whereas markers of other infectious agents were unrelated. Although these findings need to be replicated, they suggest potential ovarian cancer risk reduction through targeted treatment of chlamydia infections. Citation Format: Britton Trabert, Tim Waterboer, Sally B. Coburn, Louise A. Brinton, Mark E. Sherman, Jolanta Lissowska, Beata Peplonska, Patricia Hartge, Michael Pawlita, Nicolas Wentzensen. Serologic markers of infectious agents and ovarian cancer: Markers of prior Chlamydia trachomatis infection associated with increased ovarian cancer risk in two independent populations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4942.

Lesser degrees of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini/TDLU, are associated with elevated breast cancer risk. In rodent models, the insulin‐like growth factor (IGF) system regulates involution of the mammary gland. We examined associations of circulating IGF measures with TDLU involution in normal breast tissues among women without precancerous lesions. Among 715 Caucasian and 283 African American (AA) women who donated normal breast tissue samples to the Komen Tissue Bank between 2009 and 2012 (75% premenopausal), serum concentrations of IGF‐I and binding protein (IGFBP)‐3 were quantified using enzyme‐linked immunosorbent assay. Hematoxilyn and eosin‐stained tissue sections were assessed for numbers of TDLUs (“TDLU count”). Zero‐inflated Poisson regression models with a robust variance estimator were used to estimate relative risks (RRs) for association of IGF measures (tertiles) with TDLU count by race and menopausal status, adjusting for potential confounders. AA (vs. Caucasian) women had higher age‐adjusted mean levels of serum IGF‐I (137 vs. 131 ng/mL, p = 0.07) and lower levels of IGFBP‐3 (4165 vs. 4684 ng/mL, p < 0.0001). Postmenopausal IGFBP‐3 was inversely associated with TDLU count among AA (RRT3vs.T1 = 0.49, 95% CI = 0.28–0.84, p‐trend = 0.04) and Caucasian (RRT3vs.T1=0.64, 95% CI = 0.42–0.98, p‐trend = 0.04) women. In premenopausal women, higher IGF‐I:IGFBP‐3 ratios were associated with higher TDLU count in Caucasian (RRT3vs.T1=1.33, 95% CI = 1.02–1.75, p‐trend = 0.04), but not in AA (RRT3vs.T1=0.65, 95% CI = 0.42–1.00, p‐trend = 0.05), women. Our data suggest a role of the IGF system, particularly IGFBP‐3, in TDLU involution of the normal breast, a breast cancer risk factor, among Caucasian and AA women.

Abstract Background: High percent mammographic density (MD), which reflects the relative fibroglandular tissue content of the breast, is one of the strongest breast cancer risk factors; however, the pathologic mediators of this risk are unknown. We hypothesize that analysis of breast tissue sections using deep learning approaches may characterize histologic features that underpin risk associated with high MD. Methods: Non-targeted H&E stained breast tissue sections of diagnostic image-guided breast biopsies were evaluated among 588 women enrolled following an abnormal mammogram in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project (2007-2010). Overall volumetric percent MD for the biopsied breast and localized volumetric percent MD surrounding the biopsy site were determined for each participant. A deep convolutional neural network (CNN) model was trained to identify and quantitatively assess breast epithelial, stroma and fat tissue and their organizational and spatial arrangements. Least absolute shrinkage and selection operator (Lasso) regression was used to determine relationships between MD measures and pathological features. To ensure reliability of the model, a cross-validation strategy was employed to build and assess the performance of the fitted model. Finally, Spearman correlation coefficients were estimated to test the association between the predicted density values by each model (predicting overall or localized MD) and the actual MD measurements. We report the average and standard deviation (SD) of the correlation coefficients. Results: In an independent validation set, the CNN model was 95.5% accurate in classifying epithelial, stromal and fat tissue. The mean (SD) correlations between the predicted model and the actual measurements for overall and localized MD were 0.70 (0.06) and 0.65 (0.06) respectively. The amount of stroma identified (normalized to tissue area) had the highest selection probability (P-value) by the Lasso model and thus the strongest positive relationship with MD (P-value &gt;0.9 for each MD measurement). In contrast, the amount of normalized epithelial tissue was not related to MD (P-value=0.01 for each MD measurement). No association was observed for the total normalized fat area with MD (P-value &lt;0.31 for each MD measurement). In addition, the number of distributed epithelial regions was positively associated, whereas the distance between epithelial regions was inversely associated with overall MD (P-value &lt;0.87 and 0.62, respectively). Conclusions: These results show that greater stromal tissue amount and spatial distribution patterns of epithelial regions, rather than total epithelial amounts, had the strongest relationships with elevated MD. Future work will determine the relationship of these MD features with biopsy diagnosis. Citation Format: Maeve Mullooly, Babak Ehteshami Bejnordi, Maya Palakal, Pamela M. Vacek, Donald L. Weaver, John A. Shepherd, Bo Fan, Amir Pasha Mahmoudzadeh, Jeff Wang, Jason M. Johnson, Sally D. Herschorn, Brian L. Sprague, Ruth M. Pfeiffer, Louise A. Brinton, Mark E. Sherman, Andrew Beck, Gretchen L. Gierach. Application of convolutional neural networks to breast biopsies to uncover tissue correlates of mammographic breast density [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4235. doi:10.1158/1538-7445.AM2017-4235

Terminal duct lobular units (TDLUs) are the predominant source of future breast cancers, and lack of TDLU involution (higher TDLU counts, higher acini count per TDLU and the product of the two) is a breast cancer risk factor. Numerous breast cancer susceptibility single nucleotide polymorphisms (SNPs) have been identified, but whether they are associated with TDLU involution is unknown. In a pooled analysis of 872 women from two studies, we investigated 62 established breast cancer SNPs and relationships with TDLU involution. Poisson regression models with robust variance were used to calculate adjusted per‐allele relative risks (with the non‐breast cancer risk allele as the referent) and 95% confidence intervals between TDLU measures and each SNP. All statistical tests were two‐sided; P < 0.05 was considered statistically significant. Overall, 36 SNPs (58.1%) were related to higher TDLU counts although this was not statistically significant (p = 0.25). Six of the 62 SNPs (9.7%) were nominally associated with at least one TDLU measure: rs616488 (PEX14), rs11242675 (FOXQ1) and rs6001930 (MKL1) were associated with higher TDLU count (p = 0.047, 0.045 and 0.031, respectively); rs1353747 (PDE4D) and rs6472903 (8q21.11) were associated with higher acini count per TDLU (p = 0.007 and 0.027, respectively); and rs1353747 (PDE4D) and rs204247 (RANBP9) were associated with the product of TDLU and acini counts (p = 0.024 and 0.017, respectively). Our findings suggest breast cancer SNPs may not strongly influence TDLU involution. Agnostic genome‐wide association studies of TDLU involution may provide new insights on its biologic underpinnings and breast cancer susceptibility.

Telomeres cap chromosome ends, protecting them from degradation, double‐strand breaks, and end‐to‐end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset‐based meta‐analyses of 204,993 directly‐measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene‐level p value cutoffs ≤3.08 × 10−5). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere‐related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.