Mammographic texture resemblance generalizes as an independent risk factor for breast cancer

INTRODUCTION: Breast density has been established as a major risk factor for breast cancer. We have previously demonstrated that mammographic texture resemblance (MTR), recognizing the local texture patterns of the mammogram, is also a risk factor for breast cancer, independent of percent breast density. We examine if these findings generalize to another population. METHODS: Texture patterns were recorded in digitalized pre-diagnosis (3.7 years) film mammograms of a nested case–control study within the Dutch screening program (S1) comprising of 245 breast cancers and 250 matched controls. The patterns were recognized in the same study using cross-validation to form resemblance scores associated with breast cancer. Texture patterns from S1 were examined in an independent nested case–control study within the Mayo Mammography Health Study cohort (S2) of 226 cases and 442 matched controls: mammograms on average 8.5 years prior to diagnosis, risk factor information and percent mammographic density (PD) estimated using Cumulus were available. MTR scores estimated from S1, S2 and S1 + S2 (the latter two as cross-validations) were evaluated in S2. MTR scores were analyzed as both quartiles and continuously for association with breast cancer using odds ratios (OR) and adjusting for known risk factors including age, body mass index (BMI), and hormone usage. RESULTS: The mean ages of S1 and S2 were 58.0 ± 5.7 years and 55.2 ± 10.5 years, respectively. The MTR scores on S1 showed significant capability to discriminate cancers from controls (area under the operator characteristics curve (AUC) = 0.63 ± 0.02, P <0.001), which persisted after adjustment for PD. S2 showed an AUC of 0.63, 0.61, and 0.60 based on PD, MTR scores trained on S2, and MTR scores trained on S1, respectively. When adjusted for PD, MTR scores of S2 trained on S1 showed an association with breast cancer for the highest quartile alone: OR in quartiles of controls as reference; 1.04 (0.59 to 1.81); 0.95 (0.52 to 1.74); 1.84 (1.10 to 3.07) respectively. The combined continuous model with both PD and MTR scores based on S1 had an AUC of 0.66 ± 0.03. CONCLUSIONS: The local texture patterns associated with breast cancer risk in S1 were also an independent risk factor in S2. Additional textures identified in S2 did not significantly improve risk segregation. Hence, the textural patterns that indicated elevated risk persisted under differences in X-ray technology, population demographics, follow-up time and geography

The National Cancer Institute Cohort Consortium : An International Pooling Collaboration of 58 Cohorts from 20 Countries

Cohort studies have been central to the establishment of the known causes of cancer. To dissect cancer etiology in more detail-for instance, for personalized risk prediction and prevention, assessment of risks of subtypes of cancer, and assessment of small elevations in risk-there is a need for analyses of far larger cohort datasets than available in individual existing studies. To address these challenges, the NCI Cohort Consortium was founded in 2001. It brings together 58 cancer epidemiology cohorts from 20 countries to undertake large-scale pooling research. The cohorts in aggregate include over nine million study participants, with biospecimens available for about two million of these. Research in the Consortium is undertaken by >40 working groups focused on specific cancer sites, exposures, or other research areas. More than 180 publications have resulted from the Consortium, mainly on genetic and other cancer epidemiology, with high citation rates. This article describes the foundation of the Consortium; its structure, governance, and methods of working; the participating cohorts; publications; and opportunities. The Consortium welcomes newmembers with cancer-oriented cohorts of 10,000 or more participants and an interest in collaborative research. (C) 2018 AACR.Peer reviewe

The association of mammographic density with risk of contralateral breast cancer and change in density with treatment in the WECARE study.

BACKGROUND: Mammographic density (MD) is an established predictor of risk of a first breast cancer, but the relationship of MD to contralateral breast cancer (CBC) risk is not clear, including the roles of age, mammogram timing, and change with treatment. Multivariable prediction models for CBC risk are needed and MD could contribute to these. METHODS: We conducted a case-control study of MD and CBC risk in phase II of the WECARE study where cases had a CBC diagnosed ≥ 2 years after first diagnosis at age <55 years and controls had unilateral breast cancer (UBC) with similar follow-up time. We retrieved film mammograms of the unaffected breast from two time points, prior to/at the time of the first diagnosis (253 CBC cases, 269 UBC controls) and ≥ 6 months up to 48 months following the first diagnosis (333 CBC cases, 377 UBC controls). Mammograms were digitized and percent MD (%MD) was measured using the thresholding program Cumulus. Odds ratios (OR) and 95% confidence intervals (CI) for association between %MD and CBC, adjusted for age, treatment, and other factors related to CBC, were estimated using logistic regression. Linear regression was used to estimate the association between treatment modality and change in %MD in 467 women with mammograms at both time points. RESULTS: For %MD assessed following diagnosis, there was a statistically significant trend of increasing CBC with increasing %MD (p = 0.03). Lower density (<25%) was associated with reduced risk of CBC compared to 25 to < 50% density (OR 0.69, 95% CI 0.49, 0.98). Similar, but weaker, associations were noted for %MD measurements prior to/at diagnosis. The relationship appeared strongest in women aged < 45 years and non-existent in women aged 50 to 54 years. A decrease of ≥ 10% in %MD between first and second mammogram was associated marginally with reduced risk of CBC (OR 0.63, 95% CI 0.40, 1.01) compared to change of <10%. Both tamoxifen and chemotherapy were associated with statistically significant 3% decreases in %MD (p < 0.01). CONCLUSIONS: Post-diagnosis measures of %MD may be useful to include in CBC risk prediction models with consideration of age at diagnosis. Chemotherapy is associated with reductions in %MD, similar to tamoxifen

Genetic variation in stromal proteins decorin and lumican with breast cancer: investigations in two case-control studies.

INTRODUCTION: The stroma is the supportive framework of biologic tissue in the breast, consisting of various proteins such as the proteoglycans, decorin and lumican. Altered expression of decorin and lumican is associated with breast tumors. We hypothesized that genetic variation in the decorin (DCN) and lumican (LUM) genes may contribute to breast cancer. METHODS: We investigated associations of 14 common polymorphisms in the DCN and LUM genes with 798 breast cancer cases and 843 controls from Mayo Clinic, MN, USA. One polymorphism per gene with the strongest risk association in the Mayo Clinic sample was genotyped in 4,470 breast cancer cases and 4,560 controls from East Anglia, England (Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH)). RESULTS: In the Mayo Clinic sample, six polymorphisms were associated with breast cancer risk (P trend <or= 0.05). The association with LUM rs2268578, evaluated further in SEARCH, was positive, although the odds ratios (OR) were weaker and not statistically significant. ORs were 1.4 (95% confidence interval [CI], 1.1 to 1.8) for heterozygotes and 2.2 (95% CI, 1.1 to 4.3; P2 df = 0.002) for homozygotes in the Mayo Clinic sample, and were 1.1 (95% CI, 0.9 to 1.2) for heterozygotes and 1.4 (95% CI, 1.0 to 2.1; P2 df = 0.13) for homozygotes in the SEARCH sample. In combined analyses, the ORs were 1.1 (95% CI, 1.0 to 1.2) for heterozygotes and 1.6 (95% CI, 1.2 to 2.3; P2 df = 0.005) for homozygotes. Positive associations for this polymorphism were observed for estrogen receptor-positive tumors in both the Mayo Clinic sample (OR for heterozygotes = 1.5, 1.1 to 1.9 and OR for homozygotes = 2.5, 1.2 to 5.3;P2 df = 0.001) and the SEARCH sample (OR for heterozygotes = 1.0, 0.9 to 1.1 and OR for homozygotes = 1.6, 1.0 to 2.5; P2 df = 0.10). In combined analyses, the ORs were 1.1 (95% CI, 0.9 to 1.2) for heterozygotes and 1.9 (95% CI, 1.3 to 2.8; P2 df = 0.001) for homozygotes. CONCLUSIONS: Although LUM rs2268578 was associated with breast cancer in the Mayo Clinic study, particularly estrogen receptor-positive breast cancer, weaker and modest associations were observed in the SEARCH sample. These modest associations will require larger samples to adequately assess the importance of this polymorphism in breast cancer

Mediterranean Diet and Breast Density in the Minnesota Breast Cancer Family Study

Mediterranean populations’ lower breast cancer incidence has been attributed to a traditional Mediterranean diet, but few studies have quantified Mediterranean dietary pattern intake in relation to breast cancer. We examined the association of a Mediterranean diet scale (MDS) with mammographic breast density as a surrogate marker for breast cancer risk. Participants completed a dietary questionnaire and provided screening mammograms for breast density assessment using a computer-assisted method. Among 1,286 women, MDS was not clearly associated with percent density in multivariate linear regression analyses. Because of previous work suggesting dietary effects limited to smokers, we conducted stratified analyses and found MDS and percent density to be significantly, inversely associated among current smokers (β = –1.68, P = 0.002) but not among nonsmokers (β = –0.08, P = 0.72; P for interaction = 0.008). Our results confirm a previous suggestion that selected dietary patterns may be protective primarily in the presence of procarcinogenic compounds such as those found in tobacco smoke

Genetic variation in the estrogen metabolic pathway and mammographic density as an intermediate phenotype of breast cancer

Introduction: Several studies have examined the effect of genetic variants in genes involved in the estrogen metabolic pathway on mammographic density, but the number of loci studied and the sample sizes evaluated have been small and pathways have not been evaluated comprehensively. In this study, we evaluate the association between mammographic density and genetic variants of the estrogen metabolic pathway. Methods: A total of 239 SNPs in 34 estrogen metabolic genes were studied in 1,731 Swedish women who participated in a breast cancer case-control study, of which 891 were cases and 840 were controls. Film mammograms of the medio-lateral oblique view were digitalized and the software Cumulus was used for computer-assisted semi-automated thresholding of mammographic density. Generalized linear models controlling for possible confounders were used to evaluate the effects of SNPs on mammographic density. Results found to be nominally significant were examined in two independent populations. The admixture maximum likelihood-based global test was performed to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three subpathways for androgen synthesis, androgen-to-estrogen conversion and estrogen removal. Results: Genetic variants of genes involved in estrogen metabolism exhibited no appreciable effect on mammographic density. None of the nominally significant findings were validated. In addition, global analyses on the overall estrogen metabolic pathway and its subpathways did not yield statistically significant results. Conclusions: Overall, there is no conclusive evidence that genetic variants in genes involved in the estrogen metabolic pathway are associated with mammographic density in postmenopausal women