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Purpose: GOG-0218, a double-blind placebo-controlled phase III trial, compared carboplatin and paclitaxel with placebo, bevacizumab followed by placebo, or bevacizumab followed by bevacizumab in advanced epithelial ovarian cancer (EOC). Results demonstrated significantly improved progression-free survival (PFS), but no overall survival (OS) benefit with bevacizumab. Blood samples were collected for biomarker analyses., Experimental Design: Plasma samples were analyzed via multiplex ELISA technology for seven prespecified biomarkers [IL6, Ang-2, osteopontin (OPN), stromal cell-derived factor-1 (SDF-1), VEGF-D, IL6 receptor (IL6R), and GP130]. The predictive value of each biomarker with respect to PFS and OS was assessed using a protein marker by treatment interaction term within the framework of a Cox proportional hazards model. Prognostic markers were identified using Cox models adjusted for baseline covariates., Results: Baseline samples were available from 751 patients. According to our prespecified analysis plan, IL6 was predictive of a therapeutic advantage with bevacizumab for PFS ( P = 0.007) and OS ( P = 0.003). IL6 and OPN were found to be negative prognostic markers for both PFS and OS ( P < 0.001). Patients with high median IL6 levels (dichotomized at the median) treated with bevacizumab had longer PFS (14.2 vs. 8.7 months) and OS (39.6 vs. 33.1 months) compared with placebo., Conclusions: The inflammatory cytokine IL6 may be predictive of therapeutic benefit from bevacizumab when combined with carboplatin and paclitaxel. Aligning with results observed in patients with renal cancer treated with antiangiogenic therapies, it appears plasma IL6 may also define those patients with EOC more or less likely to benefit from the addition of bevacizumab to standard chemotherapy., (©2020 American Association for Cancer Research.)

Background: Metabolism and excretion of the phytoestrogen enterolactone (ENL), which has been associated with breast cancer risk, may be affected by variation in steroid hormone and xenobiotic-metabolizing genes., Methods: We conducted a randomized, crossover flaxseed intervention study in 252 healthy, postmenopausal women [137 European ancestry (EA) and 115 African ancestry (AA)] from western New York. Participants were randomly assigned to maintain usual diet or consume 10 g/day ground flaxseed for 6 weeks. After a 2-month washout period, participants crossed over to the other diet condition for an additional 6 weeks. Urinary ENL excretion was measured by gas chromatography-mass spectrometry and 70 polymorphisms in 29 genes related to steroid hormone and xenobiotic metabolism were genotyped. Mixed additive genetic models were constructed to examine association of genetic variation with urinary ENL excretion at baseline and after the flaxseed intervention., Results: SNPs in several genes were nominally ( P < 0.05) associated with ENL excretion at baseline and/or after intervention: ESR1, CYP1B1, COMT, CYP3A5, ARPC1A, BCL2L11, SHBG, SLCO1B1 , and ZKSCAN5 . A greater number of SNPs were associated among AA women than among EA women, and no SNPs were associated in both races. No SNP-ENL associations were statistically significant after correction for multiple comparisons., Conclusions: Variation in several genes related to steroid hormone metabolism was associated with lignan excretion at baseline and/or after flaxseed intervention among postmenopausal women., Impact: These findings may contribute to our understanding of the differences observed in urinary ENL excretion among AA and EA women and thus hormone-related breast cancer risk., (©2019 American Association for Cancer Research.)

Background: Mammographic density is a strong risk factor for breast cancer that is heritable and associated with blood levels of growth hormone and insulin-like growth factor-I (IGF-I). We tested single nucleotide polymorphisms (SNP) in pituitary growth hormone (GH1) and growth hormone-releasing hormone receptor (GHRHR) genes for an association with mammographic density, hormones of the growth hormone/IGF-I axis, and anthropometric variables., Methods: Mammograms from 348 women were measured using a computer-assisted method, blood collected, and DNA extracted. The SNPs genotyped were GH1 -57G>T, GH1 -75G >A, and GHRHR A57T. ANOVA and covariance were used to examine associations, adjusted for age, body mass index, ethnicity, and menopausal status, between each SNP and three measures of the mammogram: percent density, total dense area, and total nondense area. Similarly, the SNPs were tested for associations with serum growth hormone, IGF-I, IGFBP3, prolactin, and anthropometric variables., Results: GH1 -57G >T and GH1 -75G >A were both associated with percent density and total nondense area. GH1 -57T homozygotes had 5.2 more mean adjusted percent density than other subjects combined (P = 0.03) and 16.2 cm(2) (14.6%) less nondense area (P = 0.01). GH1 -75A homozygotes had 3.4 more percent density than subjects with at least one G allele (P = 0.04) and also had 32% higher serum growth hormone levels (P = 0.02)., Conclusion: We have found associations between mammographic density and two SNPs in the pituitary growth hormone gene, one of them also associated with serum growth hormone levels. These findings suggest that the GH1 gene may also influence breast cancer risk.

Extensive mammographic density is heritable, strongly associated with increased breast cancer risk, and is influenced by sex hormone exposure. In a cross-sectional study of 181 pre- and 171 postmenopausal women without breast cancer, we examined the relationship of a functional polymorphism in catechol-O-methyltransferase (COMT; VAL-->MET) to mammographic density and other risk factors for breast cancer. We hypothesized that individuals who inherited the low-activity form of COMT (COMT*2 allele) would have higher levels of breast density, presumably because of reduced inactivation/detoxification of catecholestrogens. Subjects were recruited across five categories of breast density. Risk factor information, anthropometric measures, and blood samples were obtained; sex hormone and growth factor levels were measured, and COMT genotypes determined. Mammograms were digitized and measured using a computer-assisted method. After adjustment for age and ethnicity, among pre- but not postmenopausal subjects, each low-activity COMT*2 allele was associated with lower levels of percentage breast density. The statistical significance of this association was lost after further adjustment for serum growth factors [growth hormone, insulin-like growth factor-1 (IGF-1), and insulin-like growth factor binding protein-3 (IGFBP-3)], hormones [follicle-stimulating hormone (FSH) and progesterone], and body size (body mass index and waist:hip ratio). The low-activity COMT*2 allele was also associated, after adjustment for age and ethnicity in premenopausal women, with lower serum levels of IGF-1, higher levels of FSH and progesterone, and with a larger waist:hip ratio, body mass index, and subscapular skinfold. After adjustment for body size, the associations of genotype with IGFBP-3 and FSH were no longer significant. These findings indicate that COMT genotype is associated with several risk factors for breast cancer and suggest that the low-activity COMT*2 allele is associated with a reduced risk of breast cancer among premenopausal women.

There is strong evidence that the risk of breast cancer in populations is influenced by environmental factors. Plasma lipids and lipoproteins are known to be under environmental control and to have epidemiological and/or biological characteristics that suggest they may be relevant to breast cancer risk. The purpose of the study described here was to determine whether plasma lipids, lipoproteins, and the urinary excretion of the mutagen malondialdehyde (MDA) are associated with differences in breast cancer risk. We measured plasma lipids, lipoproteins, and urinary MDA in women without breast cancer but with different degrees of density of the breast parenchyma on mammography, a strong risk factor for breast cancer. Mammograms from 273 premenopausal women were digitized to high spatial resolution by a scanning densitometer, and images were analyzed to quantify the extent of density. The percentage of the breast occupied by mammographic densities was found, after controlling for the effects of age and the Quetelet index of obesity, to be significantly associated with plasma levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglyceride, apoprotein B, and urinary excretion of MDA. A multivariate model comprised of the Quetelet index of obesity, alcohol consumption, apoprotein B, parity, daily MDA excretion, and the skinfold thickness sum accounted for 36% of the variation in breast density. These results suggest that differences in lipid metabolism are associated with differences in breast cancer risk as defined by mammographic densities. These findings are consistent with several other observations that show a relationship between plasma lipids, lipoproteins, and risk factors for breast cancer.

We have examined the relationship between plasma lipids, lipoproteins, and a family history of breast cancer. We measured the plasma lipids and lipoproteins in unaffected female members of the nuclear family of women with familial breast cancer and compared them with those of the female members of the nuclear family of women with sporadic breast cancer. A mean number of 3.3 relatives of mean age 35 years were studied in 23 pairs of familial and sporadic breast cancer families. After adjustment in multivariate analysis for variables that either differed between high and low risk families, or were significantly associated with plasma levels or lipoproteins, statistically significant differences were found in plasma levels of total cholesterol, low density lipoprotein cholesterol, and apoprotein B, all of which were lower in familial breast cancer than in sporadic breast cancer families. These data suggest that inherited factors associated with breast cancer risk may play a role in determining plasma lipid and lipoprotein levels and that lipid regulatory genes should be considered in this context.