Secondhand smoke, obesity, and risk of type II diabetes among California teachers

PURPOSE

To examine if secondhand smoke (SHS) is associated with elevated risk of type II diabetes among California teachers. We also aim to determine if overall and central obesity are mediators or effect modifiers of this association.

METHODS

Using data from the California Teachers Study, conducted in 1995-2013 in California public schools, we obtained information on SHS exposure among 39,887 lifetime nonsmokers. The association between SHS and incident diabetes after 17 years of follow-up was assessed using Cox regression models. The mediation and modification effects of BMI and waist circumference on this association were tested.

RESULTS

At baseline, 70.2% of the nonsmokers reported exposure to SHS. Higher intensity, duration, and intensity-years of exposure to SHS were associated with higher multivariate adjusted risk of incident diabetes in a dose-response manner (hazard ratio = 1.28; 95% confidence interval, 1.11-1.48 for highest quartile vs. lowest quartile of exposure; P = .001 for trend). Participant's waist circumference (measured 2 years after baseline) could explain greater than 50% of the association between SHS and diabetes.

CONCLUSIONS

SHS exposure is associated with increased risk of type II diabetes among nonsmokers of California teachers with obesity being a potentially important mediator but not an effect modifier for this association.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Laminin 332 expression and prognosis in breast cancer

The purpose of this study was to determine the distribution of and potential significance of laminin 332 (LM332) in breast cancer. Specimens from a population-based cohort (N = 297) from 1994 to 1995 were stained for estrogen receptor (ER), progesterone receptor (PgR), HER2 and the LM332 β3 chain. Seventy-five tumors were LM332-positive and 222 were negative. LM332 β3 stained 16.0% of ER and/or PgR-positive tumors and 73.2% of triple-negative breast cancers (TNBC). Immunoblotting revealed LM332 in TNBC and HER2-positive samples, but not in an ER-positive breast carcinoma or a phyllodes tumor. After 20 years, 172 patients were alive, 43 had died of breast cancer and 82 of other causes. Patients with LM332-positive tumors had significantly worse 5 (P < .0001) and 10-year (P < .05) overall and breast cancer specific survival. Among patients with LM332 β3-expressing and ER/PgR-negative carcinomas, 10-year survival was significantly reduced (P < .0450). In a multivariate analysis LM332-positive patients had significant hazard ratios of 3.9 with 95% confidence intervals (CI) of 2.0-7.7 and 2.2 with 95% CI of 1.3-3.8 for 5 and 10-year overall survival, respectively. Because tumor cell motility is required for metastasis, the effect of LM332 on MDA-MB-231 migration was determined using siRNA. Knockdown of LM332-specific β3 and γ2 chains reduced motility without affecting viability. Our observation that LM332 in breast carcinoma is associated with decreased survival provides evidence that LM332 may have a role in the aggressive phenotype of some breast cancers.

Diet Quality Scores Inversely Associated with Postmenopausal Breast Cancer Risk Are Not Associated with Premenopausal Breast Cancer Risk in the California Teachers Study

Background

Evidence for the association between diet and breast cancer risk is inconsistent Thus, research that compares indexes of overall diet quality may provide new insight.

Objective

We examined the association between diet quality indexes and pre- and postmenopausal breast cancer risk in a large prospective cohort.

Methods

This was a prospective analysis of 96,959 women, aged 22-104 y, in the California Teachers Study cohort (1995-2011). Diet quality was characterized by 4 different indexes. Specifically, we examined Alternate Mediterranean Diet (aMED), Alternative Healthy Eating Index-2010 (AHEI-2010), Dietary Approaches to Stop Hypertension (DASH), and Paleolithic index (PALEO) scores with the risk of developing breast cancer. We used multivariable Cox proportional hazards regression models to derive HRs and 95% CIs for breast cancer risk.

Results

In the analysis of 42,517 women at risk of premenopausal breast cancer, there was no association between any of the indexes and incident breast cancer (346 cases). In the analysis of 54,442 women at risk of postmenopausal breast cancer at baseline, higher AHEI-2010, aMED, and DASH scores were inversely associated with incident breast cancer (3523 incident cases). Respectively, HRs (95% CIs) comparing quintile 5 to quintile 1 (reference) for AHEI-2010, aMED, and DASH indexes were 0.87 (0.78, 0.97; P-trend = 0.004), 0.91 (0.82, 1.02; P-trend = 0.03), and 0.89 (0.80, 1.00; P-trend = 0.03). The PALEO score was not associated with postmenopausal breast cancer (HR for quintile 5 compared with quintile 1: 1.05; 95% CI: 0.94, 1.17).

Conclusions

Diet quality indexes that emphasize intake of whole grains, vegetables, fruits, legumes, and nuts and seeds and de-emphasize red and processed meats and sugar-sweetened beverages were modestly associated with a lower risk of incident postmenopausal breast cancer risk. However, they were not associated with premenopausal breast cancer, and the PALEO score was not associated with cancer risk regardless of menopausal status.

rs495139 in the TYMS-ENOSF1 Region and Risk of Ovarian Carcinoma of Mucinous Histology

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.

Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations.

Perception matters: Stressful life events increase breast cancer risk

OBJECTIVE

The relationship between psychological stress and breast cancer risk is unclear. The present study sought to understand how stressfulness appraisal of salient Life Events (LEs) influences breast cancer risk.

METHODS

A case-control design was used and included 664 female cases identified through the Cancer Surveillance Program of Orange County, CA and 203 female population-based controls. A LE questionnaire determined if events occurred prior to breast cancer diagnosis and if these events were considered to be stressful or not. Multivariate unconditional logistic regression was used to calculate ORs while adjusting for known breast cancer covariates.

RESULTS

Cumulative adverse LEs perceived as stressful were associated with increased breast cancer risk in a dose response fashion (OR = 1.63, 95% CI = 1.00-2.66, P_trend = 0.045). Conversely, events perceived as non-stressful did not have a significant impact on breast cancer risk. Previous personal illness was directly related to increased breast cancer risk, whether perceived as stressful (OR = 2.84, 95% CI = 1.96-4.11) or non-stressful (OR = 3.47, 95% CI = 1.34-8.94). Abortion and relocation were observed to have a protective effect on breast cancer risk only when reported as stressful (OR = 0.54, 95% CI = 0.32-0.92; OR = 0.63, 95% CI = 0.43-0.93, respectively). Pre/Peri-menopausal women who were nulliparous or who had their first child at ≥30 years of age were especially prone to the effects of appraised stress on increased breast cancer risk.

CONCLUSIONS

This study underscores the importance of stressfulness appraisal when determining the effect of major LEs on breast cancer risk. Our results support incorporating assessments of perceived stressfulness in future epidemiological investigation of this topic.

A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10-6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

Breast Cancer Characteristics in Middle Eastern Women Immigrants Compared With Non-Hispanic White Women in California

Background

Emerging evidence has indicated that Middle Eastern (ME) immigrants might be more likely to be diagnosed with breast cancer at advanced stage, yet have better overall survival than nonimmigrant non-Hispanic whites (NHW). This study aims to analyze the association between ME immigration status and breast cancer stage at diagnosis and survival.

Methods

Using the California Cancer Registry, a total of 343 876 women diagnosed with primary in situ or invasive breast cancers were identified during 1988–2013. Multinomial logistic regression models were fitted to evaluate the risk of in situ and nonlocalized breast cancer stage in comparison with localized breast cancer among first-generation ME immigrants, second- or subsequent-generation ME immigrants, and NHW. Cox proportional hazard models were applied to calculate hazard ratios (HRs) with their 95% confidence intervals (CIs) for breast cancer mortality among the three population groups with invasive primary breast cancer.

Results

First-generation ME immigrants had higher odds of being diagnosed with a nonlocalized stage (vs localized) than NHW (odds ratio [OR] = 1.17, 95% CI = 1.09 to 1.26). Second- or subsequent-generation ME immigrants also had higher odds of being diagnosed with a nonlocalized stage (vs localized) than NHW (OR = 1.31, 95% CI = 1.20 to 1.43). First-generation ME immigrants were 11% less likely to die from breast cancer than NHW (HR = 0.89, 95% CI = 0.82 to 0.97).

Conclusions

First-generation ME immigrants had higher breast cancer survival despite being diagnosed at a nonlocalized breast cancer stage at diagnosis when compared with NHW. Screening interventions tailored to this ME immigrant group need to be implemented.

Adult height is associated with increased risk of ovarian cancer: a Mendelian randomisation study

BACKGROUND

Observational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias.

METHODS

We pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis.

RESULTS

Greater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours.

CONCLUSIONS

Women with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.

Racial/ethnic differences in the epidemiology of ovarian cancer: a pooled analysis of 12 case-control studies

Background

Ovarian cancer incidence differs substantially by race/ethnicity, but the reasons for this are not well understood. Data were pooled from the African American Cancer Epidemiology Study (AACES) and 11 case-control studies in the Ovarian Cancer Association Consortium (OCAC) to examine racial/ethnic differences in epidemiological characteristics with suspected involvement in epithelial ovarian cancer (EOC) aetiology.

Methods

We used multivariable logistic regression to estimate associations for 17 reproductive, hormonal and lifestyle characteristics and EOC risk by race/ethnicity among 10 924 women with invasive EOC (8918 Non-Hispanic Whites, 433 Hispanics, 911 Blacks, 662 Asian/Pacific Islanders) and 16 150 controls (13 619 Non-Hispanic Whites, 533 Hispanics, 1233 Blacks, 765 Asian/Pacific Islanders). Likelihood ratio tests were used to evaluate heterogeneity in the risk factor associations by race/ethnicity.

Results

We observed statistically significant racial/ethnic heterogeneity for hysterectomy and EOC risk (P = 0.008), where the largest odds ratio (OR) was observed in Black women [OR = 1.64, 95% confidence interval (CI) = 1.34-2.02] compared with other racial/ethnic groups. Although not statistically significant, the associations for parity, first-degree family history of ovarian or breast cancer, and endometriosis varied by race/ethnicity. Asian/Pacific Islanders had the greatest magnitude of association for parity (≥3 births: OR = 0.38, 95% CI = 0.28-0.54), and Black women had the largest ORs for family history (OR = 1.77, 95% CI = 1.42-2.21) and endometriosis (OR = 2.42, 95% CI = 1.65-3.55).

Conclusions

Although racial/ethnic heterogeneity was observed for hysterectomy, our findings support the validity of EOC risk factors across all racial/ethnic groups, and further suggest that any racial/ethnic population with a higher prevalence of a modifiable risk factor should be targeted to disseminate information about prevention.

Identification of a gene expression signature predicting survival in oral cavity squamous cell carcinoma using Monte Carlo cross validation

OBJECTIVES

This study aims to identify a robust signature that performs well in predicting overall survival across tumor phenotypes and treatment strata, and validates the application of Monte Carlo cross validation (MCCV) as a means of identifying molecular signatures when utilizing small and highly heterogeneous datasets.

MATERIALS AND METHODS

RNA sequence gene expression data for 264 patient tumors were acquired from The Cancer Genome Atlas (TCGA). 100 iterations of Monte Carlo cross validation were applied to differential expression and Cox model validation. The association between the gene signature risk score and overall survival was measured using Kaplan-Meier survival curves, univariate, and multivariable Cox regression analyses.

RESULTS

Pathway analysis findings indicate that ligand-gated ion channel pathways are the most significantly enriched with the genes in the aggregated signature. The aggregated signature described in this study is predictive of overall survival in oral cancer patients across demographic and treatment strata.

CONCLUSION

This study reinforces previous findings supporting the role of ion channel gating, interleukin, calcitonin receptor, and keratinization pathways in tumor progression and treatment response in oral cancer. These results strengthen the argument that differential expression of genes within these pathways reduces tumor susceptibility to treatment. Conducting differential gene expression (DGE) with Monte Carlo cross validation, as this study describes, offers a potential solution to decreasing the variability in DGE results across future studies that are reliant upon highly heterogeneous datasets. This improves the ability of studies reliant upon similarly structured datasets to reach results that are reproducible.

Abstract P3-09-07: Breast cancer risk assessment in a multiethnic patient population

The United States Preventive Services Task Force recommends that women who are at increased risk for breast cancer and at low risk for adverse medication effects should be offered risk-reducing medications, such as tamoxifen or raloxifene, by their clinicians. In addition, the National Comprehensive Cancer Network recommends risk counseling for women with a 5-year risk of ≥1.7% as calculated by the NCI-developed Breast Cancer Risk Assessment Tool (BCRAT, based on the Gail model) or other risk model. Thus, breast cancer risk assessment is important for the identification of women at "high risk" who should be offered risk counseling and potentially intervention. The Athena Breast Health Network, which has served &gt;120,000 breast screening patients across California and the midwest, has integrated breast cancer risk assessment into its clinical breast screening programs. The goal of our study was to characterize breast cancer risk for &gt;10,000 mammography patients in the University of California Irvine Athena Breast Health Network, overall and by race/ethnicity, using several different risk models, including the BCRAT, BCSC, and IBIS models. Our cohort was comprised of 47% non-Hispanic White, 13% non-Hispanic Asian, 38% Hispanic, and 2% women of other race/ethnicities. Using data collected from electronic medical records and self-completed questionnaires, we determined that, as expected, non-Hispanic White and Asian women had higher breast cancer risk scores than Hispanic women for all risk models (5-year risks = 1.51-1.68% and 1.22-1.40% vs. 0.95-1.05%, respectively). In addition, when women were categorized as "increased risk" according to a given risk model if their 5-year risk score was ≥1.7%, the percentages of women at "increased risk" were higher in White women (26.5–42.2%) than in Asian (15.8–28.6%) and Hispanic (6.2–10.7%) women. However, the correlations between risk models were low to moderate in our cohort, overall (Pearson's r = 0.47-0.62) and especially for Asian women (Pearson's r = 0.29-0.49). Our results indicate that using only one risk model in a clinical breast cancer risk assessment program to identify "high risk" women would miss a significant proportion of women who would have been considered "high risk" according to another risk model. Conversely, some women who are identified as "high risk" according to one model may not need risk counseling and intervention since they are not considered "high risk" according to two other models. As our cohort expands and incident breast cancers occur, we will be able to determine which risk model or combination of risk models will have the highest discriminatory accuracy for predicting breast cancer risk in women of different race/ethnicities, which will enable our risk assessment programs to have a more targeted approach to risk counseling and intervention.

Citation Format: Park HL, Columbus A, Athena Breast Health Network Investigators and Advocate Partners, Kelly R, Alvarez A, Goodman D, Larsen K, Ziogas A, Anton-Culver H. Breast cancer risk assessment in a multiethnic patient population [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-09-07.

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.

Polycystic Ovary Syndrome, Oligomenorrhea, and Risk of Ovarian Cancer Histotypes: Evidence from the Ovarian Cancer Association Consortium

Background: Polycystic ovary syndrome (PCOS), and one of its distinguishing characteristics, oligomenorrhea, have both been associated with ovarian cancer risk in some but not all studies. However, these associations have been rarely examined by ovarian cancer histotypes, which may explain the lack of clear associations reported in previous studies.Methods: We analyzed data from 14 case-control studies including 16,594 women with invasive ovarian cancer (n = 13,719) or borderline ovarian disease (n = 2,875) and 17,718 controls. Adjusted study-specific ORs were calculated using logistic regression and combined using random-effects meta-analysis. Pooled histotype-specific ORs were calculated using polytomous logistic regression.Results: Women reporting menstrual cycle length >35 days had decreased risk of invasive ovarian cancer compared with women reporting cycle length ≤35 days [OR = 0.70; 95% confidence interval (CI) = 0.58-0.84]. Decreased risk of invasive ovarian cancer was also observed among women who reported irregular menstrual cycles compared with women with regular cycles (OR = 0.83; 95% CI = 0.76-0.89). No significant association was observed between self-reported PCOS and invasive ovarian cancer risk (OR = 0.87; 95% CI = 0.65-1.15). There was a decreased risk of all individual invasive histotypes for women with menstrual cycle length >35 days, but no association with serous borderline tumors (Pheterogeneity = 0.006). Similarly, we observed decreased risks of most invasive histotypes among women with irregular cycles, but an increased risk of borderline serous and mucinous tumors (Pheterogeneity < 0.0001).Conclusions: Our results suggest that menstrual cycle characteristics influence ovarian cancer risk differentially based on histotype.Impact: These results highlight the importance of examining ovarian cancer risk factors associations by histologic subtype. Cancer Epidemiol Biomarkers Prev; 27(2); 174-82. ©2017 AACR.

A Case-Control Study of the Genetic Variability in Reactive Oxygen Species-Metabolizing Enzymes in Melanoma Risk

Recent studies have shown that ultraviolet (UV)-induced chemiexcitation of melanin fragments leads to DNA damage; and chemiexcitation of melanin fragments requires reactive oxygen species (ROS), as ROS excite an electron in the melanin fragments. In addition, ROS also cause DNA damages on their own. We hypothesized that ROS producing and metabolizing enzymes were major contributors in UV-driven melanomas. In this case-control study of 349 participants, we genotyped 23 prioritized single nucleotide polymorphisms (SNPs) in nicotinamide adenine dinucleotide phosphate (NADPH) oxidases 1 and 4 (NOX1 and NOX4, respectively), CYBA, RAC1, superoxide dismutases (SOD1, SOD2, and SOD3) and catalase (CAT), and analyzed their associated melanoma risk. Five SNPs, namely rs1049255 (CYBA), rs4673 (CYBA), rs10951982 (RAC1), rs8031 (SOD2), and rs2536512 (SOD3), exhibited significant genotypic frequency differences between melanoma cases and healthy controls. In simple logistic regression, RAC1 rs10951982 (odds ratio (OR) 8.98, 95% confidence interval (CI): 5.08 to 16.44; p < 0.001) reached universal significance (p = 0.002) and the minor alleles were associated with increased risk of melanoma. In contrast, minor alleles in SOD2 rs8031 (OR 0.16, 95% CI: 0.06 to 0.39; p < 0.001) and SOD3 rs2536512 (OR 0.08, 95% CI: 0.01 to 0.31; p = 0.001) were associated with reduced risk of melanoma. In multivariate logistic regression, RAC1 rs10951982 (OR 6.15, 95% CI: 2.98 to 13.41; p < 0.001) remained significantly associated with increased risk of melanoma. Our results highlighted the importance of RAC1, SOD2, and SOD3 variants in the risk of melanoma.

Age-dependent interaction between sex and geographic ultraviolet index in melanoma risk

BACKGROUND

Ultraviolet (UV) exposure may not affect melanoma development equally in different sexes and ages. Whether and how these factors interact with each other in relation to melanoma risk is unknown.

OBJECTIVE

This study attempts to estimate interactions among UV index (UVI), sex, and age in melanoma risk.

METHODS

Melanoma incidence data were collected from 42 cancer registries. Geographic UVI was collected from local satellite stations. Negative binomial regression models were used to estimate the impact of each risk factor and their interactions.

RESULTS

Sex, UVI, and age, as well as interactions between any 2 of these factors, were significantly associated with melanoma risk. In younger age groups, female sex is an independent risk factor for melanoma that is not affected by ambient UV exposure. In older age groups, however, female sex interacts with UV exposure as a risk factor, exhibiting a protective effect. The switching age category is 45 to 49, which correlates with dramatic hormonal changes.

LIMITATIONS

The interaction between sex and UVI is measured at an ecologic level.

CONCLUSIONS

The interaction between sex and UVI is age dependent. Female sex is an independent risk factor for early-onset melanoma, but female sex also protects against UV-associated melanoma in older age groups.

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Negative Valence Life Events Promote Breast Cancer Development

BACKGROUND

The influence of stress on breast cancer risk remains unknown. The goal of the present study was to determine the effect of stress in the form of salient positive and negative valence life events (LEs) on primary invasive breast cancer risk. We hypothesized that salient negative LEs would increase breast cancer risk and salient positive LEs would attenuate this increased risk.

PATIENTS AND METHODS

We used a case-control design with 664 cases identified through the Cancer Surveillance Program of Orange County and 203 population-based controls. Participants completed a risk factor questionnaire, which included a LE section. Fourteen salient LEs of positive or negative valence were used to quantify stress exposure. A baseline model was constructed, and odds ratios (ORs) were calculated using multivariate unconditional logistic regression.

RESULTS

Negative LEs were associated with increased breast cancer risk. The OR for ≥ 4 negative LEs showed a 2.81-fold increase in breast cancer risk (OR, 2.81; 95% confidence interval [CI], 1.47-5.36). A significant dose-response relationship between lifetime negative valence LEs and breast cancer risk was found. Previous personal illness increased breast cancer risk by 3.6-fold (OR, 3.60; 95% CI, 2.50-5.20). In contrast, abortion was associated with a 45% decrease in breast cancer risk (OR, 0.55; 95% CI, 0.34-0.89). Salient positive LEs did not have a significant effect on breast cancer risk. However, they seemed to buffer the adverse effect of salient negative LEs on breast cancer risk.

CONCLUSION

The findings from the present study support the role of salient negative LEs in promoting breast cancer development, with a possible buffering effect of salient positive LEs.

Association analysis identifies 65 new breast cancer risk loci

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Nonparametric Adjustment for Measurement Error in Time-to-Event Data: Application to Risk Prediction Models

Mismeasured time to event data used as a predictor in risk prediction models will lead to inaccurate predictions. This arises in the context of self-reported family history, a time to event predictor often measured with error, used in Mendelian risk prediction models. Using validation data, we propose a method to adjust for this type of error. We estimate the measurement error process using a nonparametric smoothed Kaplan-Meier estimator, and use Monte Carlo integration to implement the adjustment. We apply our method to simulated data in the context of both Mendelian and multivariate survival prediction models. Simulations are evaluated using measures of mean squared error of prediction (MSEP), area under the response operating characteristics curve (ROC-AUC), and the ratio of observed to expected number of events. These results show that our method mitigates the effects of measurement error mainly by improving calibration and total accuracy. We illustrate our method in the context of Mendelian risk prediction models focusing on misreporting of breast cancer, fitting the measurement error model on data from the University of California at Irvine, and applying our method to counselees from the Cancer Genetics Network. We show that our method improves overall calibration, especially in low risk deciles.

Genome-Wide Testing of Exonic Variants and Breast Cancer Risk in the California Teachers Study

Background: Few studies have focused on the relationship of exonic variation with breast cancer and subtypes defined by tumor markers: estrogen receptor (ER), progesterone receptor (PR), and HER2.Methods: We genotyped 1,764 breast cancer patients and 1,400 controls from the California Teachers Study cohort using the Infinium HumanExome Beadchip. Individual variant and gene-based analyses were conducted for overall breast cancer and by individual tumor marker subtype.Results: No exonic variants or gene-based analyses were statistically significantly associated with breast cancer overall or by ER-, PR-, or HER2-defined subtype.Conclusions: We did not detect any novel statistically significant exonic variants with overall breast cancer risk or by subtype.Impact: Exonic variants in the exome chip may not be associated with overall breast cancer or subtype susceptibility. Cancer Epidemiol Biomarkers Prev; 26(9); 1462-5. ©2017 AACR.

History of Comorbidities and Survival of Ovarian Cancer Patients, Results from the Ovarian Cancer Association Consortium

Background: Comorbidities can affect survival of ovarian cancer patients by influencing treatment efficacy. However, little evidence exists on the association between individual concurrent comorbidities and prognosis in ovarian cancer patients.Methods: Among patients diagnosed with invasive ovarian carcinoma who participated in 23 studies included in the Ovarian Cancer Association Consortium, we explored associations between histories of endometriosis; asthma; depression; osteoporosis; and autoimmune, gallbladder, kidney, liver, and neurological diseases and overall and progression-free survival. Using Cox proportional hazards regression models adjusted for age at diagnosis, stage of disease, histology, and study site, we estimated pooled HRs and 95% confidence intervals to assess associations between each comorbidity and ovarian cancer outcomes.Results: None of the comorbidities were associated with ovarian cancer outcome in the overall sample nor in strata defined by histologic subtype, weight status, age at diagnosis, or stage of disease (local/regional vs. advanced).Conclusions: Histories of endometriosis; asthma; depression; osteoporosis; and autoimmune, gallbladder, kidney, liver, or neurologic diseases were not associated with ovarian cancer overall or progression-free survival.Impact: These previously diagnosed chronic diseases do not appear to affect ovarian cancer prognosis. Cancer Epidemiol Biomarkers Prev; 26(9); 1470-3. ©2017 AACR.