Background: Mammographic density (MD) for age and BMI is a strong risk factor (up to a 6 fold increase across extreme quantiles) for breast cancer. More than 60% of MD variation is estimated to be due to heritable (genetic) factors. Taking two different approaches, this work aimed to determine some of these genetic factors. The recently identified common genetic variants associated with small gradients in breast cancer risk and candidate common genetic variants identified using a genome wide association study (GWAS) of MD extremes were tested for an association with MD. / Methods: Germline DNA extracted from peripheral blood samples from 497 monozygotic (MZ) and 330 dizygotic (DZ) twin pairs, and 634 of their sisters from 903 families were genotyped for 22 independent variants (12 from associations with breast cancer and 10 from GWAS of MD extremes). Mammographic dense area, percent dense area and non-dense area were measured by three observers using a computer thresholding technique. Associations with MD measures adjusted for age, BMI and other determinants were estimated: (a) cross-sectionally using a multivariate normal model for pedigree analysis (P-values reported by Px), and (b) between-sibships and (c) within-sibships using orthogonal transformations of outcomes and exposures. A combined test of association (P-values reported by Pc) was derived using the independent estimates from (b) and (c). The distributions of P-values across variants were tested for a deviation from the uniform distribution (P-values reported by Pu). / Results: For the breast cancer associated common genetic variants tested, for dense area and percent dense area, the distributions of Pc-values deviated from the uniform distribution (both Pu<0.007), providing strong evidence that at least one genetic variant is associated with these MD measures. Consistent with their breast cancer associations, rs3817198 (LSP1) and rs13281615 (8q) were associated with dense area and percent dense area (all Px and Pc<0.05), and rs889312 (MAP3K1), rs2107425 (H19) and rs17468277 (CASP8) were marginally associated with dense area (some Px or Pc <0.05). For the candidate genetic variants from the GWAS of MD extremes the distributions of Pc-values deviated from the uniform distribution for dense area and percent dense area (Pu=0.07 and 0.009). One variant, rs10827227 (NRP1) showed strong evidence for an association with both dense area and percent dense area (Pc<0.009). For both approach, all associations were independent of menopausal status. / Conclusion: At least two common breast cancer susceptibility variants and one common variant identified through a GWAS for MD extremes were associated with MD measures that predict breast cancer. Together these variants explain about 1% of the variation in MD.

Mammographic density (MD), created predominantly by increased stromal tissue, is a major breast cancer risk factor, though little is known about the biological mechanisms mediating it. Tamoxifen prevents breast cancer in a subset of high risk women via mechanisms that appear dependent on reduction of MD. Animal models suggest tamoxifen remodels the mammary stroma to a tumour-inhibitory phenotype. This study aims to analyse the effect of tamoxifen on human breast fibroblast function and identify pro-tumourigenic pathways contributing to density-associated risk. Methods Primary human breast fibroblasts from normal, high risk or breast cancer patients were treated with hydroxytamoxifen (100nM-5μM). Fibroblast function was analysed by measuring: proliferation, expression of stromal proteins fibronectin and collagen 1; effects on TGF-β signalling and up-regulation of myofibroblast marker SMA. Genome wide analysis was performed using RNA-Seq. Significantly deregulated pathways were validated by PCR, western blotting and mass spectrometry. Results Fibroblasts from 23 patients were treated with hydroxytamoxifen. All patients showed reduced proliferation with treatment. 62% of patients showed reduced fibronectin expression. TGF- β-mediated up-regulation of SMA and fibronectin were consistently inhibited by tamoxifen. RNA-Seq analysis revealed down-regulation of Wnt signalling, an established profibrogenic and pro-tumourigenic pathway. In addition, there was significant modulation of many metabolic pathways, including components of the microsomal anti-oestrogen binding site (AEBS). Binding of tamoxifen to the AEBS inhibits cholesterol epoxide hydrolase (ChEH) enzyme activity, promoting an anti-tumourigenic phenotype. The effects of tamoxifen on fibroblasts could be partly replicated using tesmilifene, a commercially available 5 inhibitor of ChEH. Mass spectrometry analysis confirmed an altered cholesterol metabolite profile in tamoxifen treated fibroblasts. Conclusion These data indicate that tamoxifen can directly remodel the mammary stromal microenvironment, generating a less 'reactive' stroma. Thus, tamoxifen impacts on multiple pathways, many independent of the oestrogen receptor, to create a tumourinhibitory microenvironment. This offers exciting potential for patient monitoring and alternative breast cancer prevention strategies.

Background: Vitamin D may be important in the causal pathway to breast cancer (BC) by influencing mammographic breast density (MD). However, previous study results in postmenopausal women are inconsistent. Study objectives were to prospectively examine the relationship between biomarkers of vitamin D (25-OH-D) and percent MD in postmenopausal women at northern latitudes. Potential effect modification by exemestane therapy, calcium or genetic polymorphisms in the vitamin D pathway was also examined. Methods: This study evaluated a sub-cohort of postmenopausal women at elevated BC risk who participated in the NCIC Clinical Trials Group placebo-controlled MAP.3 trial with exemestane. Levels of 25-OH-D were measured using LC-MS/MS from serum samples collected at baseline and year 1, averaged and adjusted for month of collection. Baseline and follow-up (≥ 3 year) percent MD was centrally assessed from film and digital mammograms with Cumulus software. Multivariable linear regression was used to estimate the effect of 25-OH-D on log transformed percent MD at follow-up and on the change in percent MD from baseline. Percent MD was also dichotomized and multivariable logistic regression was used to evaluate 25-OH-D levels between 1) women with lower (<25%) compared with higher (≥25%) percent MD and 2) women with a decrease compared with no change or an increase in percent MD over time. Results: Percent MD was measured for 568 participants with a follow-up mammogram and for 388 participants with a baseline mammogram in the same format as the follow-up. The geometric mean percent MD of the follow-up mammograms was 4.3% and few women (13.4%) had percent MD ≥ 25%. The unadjusted mean 25-OH-D concentration was 36.5 ng/mL (SD=10.6) based on pooled baseline and year one samples. After controlling for age, month of sampling and potential confounders, 25-OH-D was not predictive of log transformed percent MD at follow-up (p=0.36) or with annual mean changes from baseline (p=0.33). Similarly, results from the logistic regression analyses were not statistically significant and no interactions with exemestane, calcium or genetic polymorphisms were detected. Conclusion: No association was observed between vitamin D levels and percent MD at ≥3 year follow-up or change in percent MD from baseline. / Thesis (Ph.D, Community Health & Epidemiology) -- Queen's University, 2014-03-31 11:20:23.963

Background and objectives Evidence suggests that circulating IGF-I levels increase mammographic density (a breast cancer risk factor) and breast cancer risk in premenopausal women. The objective of this thesis was to examine the association of genetic variation at the IGF1 gene with IGF-I concentration, mammographic density, breast cancer risk, and related anthropometric measures in premenopausal women. Methods Three IGF1 CA repeat polymorphisms (at the 5′ and 3′ ends, and in intron 2) were genotyped. A cross-sectional design was used to investigate their associations with IGF-I levels, mammographic density, BMI, weight, and height. Families from registries in Ontario and Australia were used to investigate associations with breast cancer risk and also BMI, weight and height. Results In the cross-sectional study, greater number of copies of the 5′ 19 allele were associated with lower circulating IGF-I levels. Greater number of 3′ 185 alleles were associated with greater percentage breast density, smaller amount of non-dense tissue, and lower BMI. Including BMI in regression models removed the association of the 3′ 185 allele with percentage breast density. In the family based study, nominally significant associations (5′ 21 allele, intron 2 212 allele, intron 2 216 allele) with breast cancer risk were observed, but significance was lost after multiple comparison adjustment. There was a stronger association between the intron 2 216 allele and risk under a recessive model, and 5′ allele groupings of length 18 to 20 and 20 or more repeats produced significant positive and negative associations respectively. These associations were not strongly supported in analyses stratified by registry. Results from the family based study did not support an association between genetic variation at IGF1 with BMI, weight or height. Conclusions No specific IGF1 variant influenced each of circulating IGF-I levels, mammographic density, and breast cancer risk. The failure to replicate the association of the 3′ 185 allele with BMI in the family based study suggests that the association of the 3′ 185 allele with percentage breast density is spurious, since this association was mediated through the relationship with BMI (suggesting IGF-I action on body fat). Evidence for an association between IGF1 and breast cancer risk was limited.

Há muito que se reconhece que a mama não é um orgão estático. Do nascimento à senilidade a mama esta sujeita à variações que vão desde o formato até a composição e arquitetura tecidual. Estas variações são notórias à simples inspeção, palpação, cortes histológicos, dosagens e outros métodos de estudo. Tais variações são decorrentes de fenômenos da esfera endócrina relacionada à vários hormônios envolvidos com o desenvolvimento, tal como: Estrogênios, FSH, LH, TSH, Mineralocorticóides, Prolactina, Progestágenos, Insulina , T3, T4, Glicocorticóides, Hormônio do Crescimento etc. Por outro lado, sabe se também das variações que a mama sofre dentro de apenas um ciclo menstrual decorrentes de fenômenos da esfera endócrina diretamente relacionadas aos hormônios envolvidos com o ciclo menstrual. Por isso, o presente trabalho avalia as implicações cíclicas da mama na qualidade da imagem mamográfica. Para tanto, uma investigação extensiva é feita com exposições radiográficas das mamas de uma cabra a fim de avaliar o perfil das variações de densidade ao longo de um ciclo completo. Inferências dos resultados obtidos são comparadas com algumas mamografias de mulheres , o que comprova a influência e o período em que melhor se pode visibilizar estruturas de interesse no mamograma convencional. / There is known, in long time, that breast is not an static organ. From birth to old age the breast is vulnerable to many variations that come from shape to composition and tissue architecture. This variation is well-know in a single inspection, touching, histological cuts, dosages and many others learning’s methods.These variations come from endocrine phenomenon, connected to many hormones that are involved with the breasts development, as this sequence: Estrogenes, FSH, LH, TSH, T3, T4, Glycocorticoids, Growth’s Hormones and many others. On the other hand, it’s known that the breast’s variations during a menstrual cycle come from endocrine phenomenon with a directly connection to the hormones in this cycle. The present work evaluatetes the breast cycle implications to mammographic images quality. For this pourpose, an extensive investigation is been done by using radiographic exposures of an goat breast in orden to evaluate the image density variation pattern thow a complete cycle. The result can ben inferred to some human mammographics showin the influence and period when structures of interest in convencional mammographicies.

Mammographic density, the amount of radiodense tissue on a mammogram, is a strong risk factor for breast cancer, with properties that could be an asset in screening and prevention programmes. Its use in risk prediction contexts is currently limited, however, mainly due to di culties in measuring and interpreting density. This research investigates rstly, the properties of density as an independent marker of breast cancer risk and secondly, how density should be measured. The rst question was addressed by analysing data from a chemoprevention trial, a trial of hormonal treatment, and a cohort study of women with a family history of breast cancer . Tamoxifen-induced density reduction was observed to be a good predictor of breast cancer risk reduction in high-risk una ected subjects. Density and its changes did not predict risk or treatment outcome in subjects with a primary invasive breast tumour. Finally absolute density predicted risk better than percent density and showed a potential to improve existing risk-prediction models, even in a population at enhanced familial risk of breast cancer. The second part of thesis focuses on density measurement and in particular evaluates two fully-automated volumetric methods, Quantra and Volpara. These two methods are highly correlated and in both cases absolute density (cm3) discriminated cases from controls better than percent density. Finally, we evaluated and compared di erent measurement methods. Our ndings suggested good reliability of the Cumulus and visual assessments. Quantra volumetric estimates appeared negligibly a ected by measurement error, but were less variable than visual bi-dimensional ones, a ecting their ability to discriminate cases from controls. Overall, visual assessments showed the strongest association with breast cancer risk in comparison to computerised methods. Our research supports the hypothesis that density should have a role in personalising screening programs and risk management. Volumetric density measuring methods, though promising, could be improved.

Há muito que se reconhece que a mama não é um orgão estático. Do nascimento à senilidade a mama esta sujeita à variações que vão desde o formato até a composição e arquitetura tecidual. Estas variações são notórias à simples inspeção, palpação, cortes histológicos, dosagens e outros métodos de estudo. Tais variações são decorrentes de fenômenos da esfera endócrina relacionada à vários hormônios envolvidos com o desenvolvimento, tal como: Estrogênios, FSH, LH, TSH, Mineralocorticóides, Prolactina, Progestágenos, Insulina , T3, T4, Glicocorticóides, Hormônio do Crescimento etc. Por outro lado, sabe se também das variações que a mama sofre dentro de apenas um ciclo menstrual decorrentes de fenômenos da esfera endócrina diretamente relacionadas aos hormônios envolvidos com o ciclo menstrual. Por isso, o presente trabalho avalia as implicações cíclicas da mama na qualidade da imagem mamográfica. Para tanto, uma investigação extensiva é feita com exposições radiográficas das mamas de uma cabra a fim de avaliar o perfil das variações de densidade ao longo de um ciclo completo. Inferências dos resultados obtidos são comparadas com algumas mamografias de mulheres , o que comprova a influência e o período em que melhor se pode visibilizar estruturas de interesse no mamograma convencional. / There is known, in long time, that breast is not an static organ. From birth to old age the breast is vulnerable to many variations that come from shape to composition and tissue architecture. This variation is well-know in a single inspection, touching, histological cuts, dosages and many others learning’s methods.These variations come from endocrine phenomenon, connected to many hormones that are involved with the breasts development, as this sequence: Estrogenes, FSH, LH, TSH, T3, T4, Glycocorticoids, Growth’s Hormones and many others. On the other hand, it’s known that the breast’s variations during a menstrual cycle come from endocrine phenomenon with a directly connection to the hormones in this cycle. The present work evaluatetes the breast cycle implications to mammographic images quality. For this pourpose, an extensive investigation is been done by using radiographic exposures of an goat breast in orden to evaluate the image density variation pattern thow a complete cycle. The result can ben inferred to some human mammographics showin the influence and period when structures of interest in convencional mammographicies.

Background and objectives Evidence suggests that circulating IGF-I levels increase mammographic density (a breast cancer risk factor) and breast cancer risk in premenopausal women. The objective of this thesis was to examine the association of genetic variation at the IGF1 gene with IGF-I concentration, mammographic density, breast cancer risk, and related anthropometric measures in premenopausal women. Methods Three IGF1 CA repeat polymorphisms (at the 5′ and 3′ ends, and in intron 2) were genotyped. A cross-sectional design was used to investigate their associations with IGF-I levels, mammographic density, BMI, weight, and height. Families from registries in Ontario and Australia were used to investigate associations with breast cancer risk and also BMI, weight and height. Results In the cross-sectional study, greater number of copies of the 5′ 19 allele were associated with lower circulating IGF-I levels. Greater number of 3′ 185 alleles were associated with greater percentage breast density, smaller amount of non-dense tissue, and lower BMI. Including BMI in regression models removed the association of the 3′ 185 allele with percentage breast density. In the family based study, nominally significant associations (5′ 21 allele, intron 2 212 allele, intron 2 216 allele) with breast cancer risk were observed, but significance was lost after multiple comparison adjustment. There was a stronger association between the intron 2 216 allele and risk under a recessive model, and 5′ allele groupings of length 18 to 20 and 20 or more repeats produced significant positive and negative associations respectively. These associations were not strongly supported in analyses stratified by registry. Results from the family based study did not support an association between genetic variation at IGF1 with BMI, weight or height. Conclusions No specific IGF1 variant influenced each of circulating IGF-I levels, mammographic density, and breast cancer risk. The failure to replicate the association of the 3′ 185 allele with BMI in the family based study suggests that the association of the 3′ 185 allele with percentage breast density is spurious, since this association was mediated through the relationship with BMI (suggesting IGF-I action on body fat). Evidence for an association between IGF1 and breast cancer risk was limited.

Este trabalho apresenta um método computacional que classifica as mamografias no padrão de densidade BI-RADS, visando auxiliar a detecção precoce do câncer de mama, seja essa realizada por análise visual ou por auxílio computadorizado. A classificação das mamografias em bancos padronizados objetiva eliminar conflitos entre laudos mamográficos de diferentes profissionais, bem como quanto à conduta médica a ser seguida. Entretanto, o estabelecimento de bancos feito visualmente e principalmente em períodos diferentes dificulta sua uniformização, proporcionando uma classificação muito subjetiva e relativamente grosseira em conseqüência a grande variação entre e inter observadores. O método desenvolvido permitiu classificar as imagens independentemente da subjetividade própria à observação visual de quem organizou o banco ou da técnica de exposição aos raios X utilizada. Os resultados foram superiores a 92% mesmo para bancos de imagens totalmente diferentes. Esses resultados foram obtidos respeitando-se as possíveis diferenças de interpretações de diversas equipes médicas. Além do estabelecimento de banco de mamografias com limiares entre as composições bem quantificadas, com esta ferramenta, tanto os estagiários poderão ser treinados para classificar as imagens no padrão de densidades do BI-RADS, respeitando as particularidades locais, quanto os resultados dos CAD poderão ser comparados. / This thesis presents a computational method that classifies the mammography into the composition of the breast tissue density patterns described in the BI-RADS protocol, intended to help in the early detection of breast cancer, either if this detection happens to be realized by visual analysis or by computerized support. The classification of the mammography in standardized database intends to eliminate issues between mammography awards of distinct professionals and the correct medical conduct to be followed. However, the determination of database only visually, especially in different periods, difficult it\'s to standardize, causing an extremely subjective classification and relatively superficial in consequence of the large inter-and intraobserver variability. The method allows classifying the images independently of the subjective quality of the visual analysis from who organized the database or from the technique of the exposition to X-ray employed. The results were superior of 92% even to database totally distinct. These results were obtained respecting eventual differences of interpretation from several medical groups. Beside the establishment of mammography database with thresholding between the well quantified categories, this methodology will consent to probationers to be trained for classify the images according to the composition of the breast tissue density patterns described in the BI-RADS, respecting its local particularity. Likewise, with this methodology, the results from CAD would be compared.

Neste trabalho, propõe-se a utilização da técnica Enhanced ICA Misture Model (EICAMM) para a segmentação automática de nódulos mamários em imagens mamográficas digitais. Com o objetivo de compará-la com outros métodos de segmentação encontrados na literatura correlata, como as técnicas Watershed, Self-Organizing Map (SOM), K-Means e Fuzzy C-Means, utiliza-se a métrica Area Overlap Measure (AOM) ou medida de similaridade de Jaccard, para medir a semelhança entre o resultado obtido na segmentação e o recorte efetuado por um especialista (ground truth). Os resultados obtidos mostram um bom desempenho do modelo EICAMM, que foi a única técnica capaz de detectar massas em regiões de interesse de mama densa. Resultados mais precisos produzidos por tal modelo foram aplicados na elaboração de um módulo classificador de nódulos para um esquema CADx (de Computer-aided Diagnosis) em mamografia digital. O módulo utiliza técnicas de extração e seleção de características e técnicas inteligentes, como Redes Neurais Artificiais, para indicar a existência ou não de nódulos em regiões de interesse, bem como avalia seu contorno/margem, forma e densidade, a fim de indicar a pertinência do achado a um caso maligno ou benigno. Para isso, utiliza-se uma base de regras, criada com o auxílio de um especialista e da combinação de diferentes classificações, conhecida como ensemble, para gerar uma única saída. Testes utilizando várias regiões de interesse selecionadas de duas bases de imagens mamográficas disponíveis resultaram numa precisão média de 46,71% na segmentação dos nódulos pela EICAMM (20,72% melhor que a média das demais técnicas comparadas) e um nível de acerto médio de 80,5% na classificação dos nódulos, o que permite considerar o módulo desenvolvido como uma útil ferramenta para auxílio ao diagnóstico desse tipo de estrutura em esquemas CADx. / This work describes the use of a technique called Enhanced ICA Misture Model (EICAMM) for automated segmentation of breast nodules in digital mammography images. Aiming to compare it with other segmentation methods, like Watershed transformation, Self-organizing Map (SOM), K-Means and Fuzzy C-Means, metrics such as Area Overlap Map (AOM) or Jaccard similarity measure are used in order to measure the similarity between the result from the segmentation and the profile determined by a spectialist (ground truth). Results show a good performance for the EICAMM method, the unique able to detect masses in regions of interest from dense breasts. More accurate results from such a model were applied to the development of a nodules classifier module for a CADx scheme in digital mammography. This module uses techniques for features extraction and selection, and intelligent techniques, as artificial neural networks, to determine the existence or not of a nodule, as well as to evaluate its contour/border, shape and radiographic density, in order to point out its pertinency to a malignant or benign case. With this purpose, a rules database known as ensemble, created with help of a specialist and different classifications combination, is used in order to produce only one output. Tests with several regions of interest selected from two available mammographic images databases have resulted in an average accuracy of 46.71% for nodules segmentation by EICAMM (20.72% better than the average of the other compared techniques), as well as an average accuracy of 80.5% in nodules classification, which allows to consider the developed module as an useful tool in aiding the diagnosis of such a structure in CADx schemes.