Molecular epidemiology studies on risk factors for breast cancer and disease aggressiveness

Breast cancer is a heterogeneous disease. Aggressive subtypes are characterized by faster growth rates, increased capability to invade and metastasize, leading to poorer clinical outcomes. In this thesis, we use a molecular epidemiology approach to investigate the association between risk factors and aggressive breast cancer defined by tumor characteristics, intrinsic subtypes, mode of detection, and survival. Using a variety of methods, we analyzed data from well-characterized breast cancer cohorts in Sweden, genome-wide association studies, and gene expression profiling of tumors. In Paper I, we found that breast cancer genetic load, defined by rare deleterious variants in 31 breast cancer genes, and unlike common variants, is positively associated with unfavorable tumor characteristics, patient survival, and mode of detection. In Paper II, we observed that women with low breast cancer risk defined by the Tyrer-Cuzick risk score were more likely to develop aggressive tumors. We computed a low-risk gene expression profile that was consistently associated with worse prognosis. In addition, our analysis showed that increased proliferation rather than estrogen status underlie this association. In Paper III, we examined gene expression profiles in a subset of aggressive breast cancer tumors, known as interval cancers. By taking mammographic density and intrinsic PAM50 subtypes into account, we found an interval cancer gene expression profile to be associated with immune subtypes in breast cancer, particularly those involving interferon response. In Paper IV, we show that breast cancer has a shared immune-related genetic component with celiac disease, an autoimmune disorder. In consistency with previous epidemiological findings, we found that a higher genetic load for celiac disease was associated with lower breast cancer risk. Overall, this thesis aims to provide scientific evidence towards a better understanding of the factors underlying the development of aggressive breast cancers that could shed light on the design of better preventative strategies aimed at lowering disease mortalit

Epidemiological studies on breast cancer risk factors and screening

This thesis aims to enhance cancer prevention by investigating the factors and outcomes associated with false-positive (FP) mammography recalls, as well as understanding the association between breast cancer risk factors of women and cancer risk among their relatives. Specifically, four studies were conducted using data from Swedish national registers, the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort, and the Linné-Bröst1 (Libro-1) cohort. In Study I, we characterized factors associated with FP mammography recalls, comparing women with a FP recall to those who were not recalled and to those who had a true-positive recall (screen-detected cancer). We found that several mammographic and non-mammographic factors, as well as high breast cancer risk scores, were associated with having a FP recall. However, these factors were either equally or more strongly associated with having a truepositive recall. In Study II, using a matched-cohort design, we examined the risk of subsequent breast cancer among women with a FP mammography recall. We observed a long-term increased breast cancer risk after a FP recall, compared with women who were not recalled. The elevated breast cancer risk differed by age and mammographic density at the matching mammography. In addition, the increased risk for breast cancer diagnosed on the ipsilateral side to the FP recall decreased over time and was highest within the first four years of follow-up. In Study III, we investigated whether specific breast cancer risk factors in women were associated with their sisters' breast cancer incidence. We found that for women with high breast cancer risk prediction scores, benign breast disease (BBD), and high mammographic density, there was an increased risk of breast cancer for their sisters. In Study IV, we investigated the associations of both carriership of protein-truncating variants (PTV) in eight genes and breast cancer polygenic risk scores (PRS) in women, with the risk of cancers in their first-degree relatives. We observed an elevated breast cancer risk among female relatives of women with PTVs, and among those with high breast cancer PRS. Additionally, we found a slightly elevated risk of cancers related to hereditary breast and ovarian cancer syndrome (HBOC)—other than breast cancer—among relatives of women with either high PRS or PTVs in the studied genes. In summary, this thesis provides valuable information for both screening processes and genetic counseling. Although none of the studied factors are viable for interventions aimed at reducing FP recalls—due to the risk of simultaneously missing tumors—our results may aid in tailoring individualized surveillance plans for women with a FP recall. Additionally, our results suggest that women’s breast density and breast cancer risk scores—information that will be available at screening—may be useful for estimating the breast cancer risk in their sisters. Furthermore, PTVs in non-BRCA genes might offer insights into cancer aggregation in families. Overall, this thesis advances evidence-based cancer prevention in the era of precision medicine

Heritability of mammographic breast density, density change, microcalcifications, and masses

Background: Mammographic features influence breast cancer risk and are used in risk prediction models. Understanding how genetics influence mammographic features is important since the mechanisms through which they are associated with breast cancer are not well known. Methods: Mammographic screening history and detailed questionnaire data for 56,820 women from the KARMA prospective cohort study were used. The heritability of mammographic features such as dense area (MD), microcalcifications, masses, and density change (MDC – cm2/year) were estimated using 1,940 sister pairs. We investigated the association between a genetic predisposition to breast cancer and mammographic features, among women with family history of breast cancer information (N=49,674) and a polygenic risk score (PRS, N=9,365). Results: Heritability was estimated at 58% (95% CI: 48%, 67%) for MD, 23% (2%, 45%) for microcalcifications, and 13% (1%, 25%) for masses. The estimated heritability for MDC was essentially null (2%, 95% CI: -8%, 12%). The association between a genetic predisposition to breast cancer (using PRS) and MD and microcalcifications was positive, while for masses this was borderline significant. In addition, for MDC, having a family history of breast cancer was associated with slightly greater MD reduction. Conclusions: We confirmed previous findings of heritability in MD, and also found heritability of the number of microcalcifications and masses at baseline. Since these features are associated with breast cancer risk, and can improve detecting women at short-term risk of breast cancer, further investigation of common loci associated with mammographic features is warranted to better understand the etiology of breast cancer.Swedish Research Council, 2018-02547Swedish Cancer Society, CAN 19 0266Stockholm County Council, LS 1211-1594Swedish Research Council, 70867902Accepte

Breast cancer genetic risk profile is differentially associated with interval and screen-detected breast cancers

Background: Polygenic risk profiles computed from multiple common susceptibility alleles for breast cancer have been shown to identify women at different levels of breast cancer risk. We evaluated whether this genetic risk stratification can also be applied to discriminate between screen-detected and interval cancers, which are usually associated with clinicopathological and survival differences. Patients and methods: A 77-SNP polygenic risk score (PRS) was constructed for breast cancer overall and by estrogen-receptor (ER) status. PRS was inspected as a continuous (per standard deviation increment) variable in a case-only design. Modification of the PRS by mammographic density was evaluated by fitting an additional interaction term. Results: PRS weighted by breast cancer overall estimates was found to be differentially associated with 1,865 screen-detected and 782 interval cancers in the LIBRO-1 study (age-adjusted ORperSD [95% confidence interval]=0.91 [0.83-0.99], p=0.023). The association was found to be more significant for PRS weighted by ER-positive breast cancer estimates (ORperSD=0.90 [0.82-0.98], p=0.011). This result was corroborated by two independent studies (combined ORperSD=0.87 [0.76-1.00], p=0.058) with no evidence of heterogeneity. When enriched for “true” interval cancers among nondense breasts, the difference in the association with PRS in screen-detected and interval cancers became more pronounced (ORperSD=0.74 [0.62-0.89], p=0.001), with a significant interaction effect between PRS and mammographic density (pinteraction=0.017). Conclusion: To our knowledge, this is the first report looking into the genetic differences between screendetected and interval cancers. It is an affirmation that the two types of breast cancer may have unique underlying biology.Swedish Research CouncilSwedish Cancer SocietyStockholm County CouncilBreast Cancer Theme Centre Consortium (BRECT)Accepte

Risk assessment and prevention of breast cancer

One woman in eight develops breast cancer during her lifetime in the Western world. Measures are warranted to reduce mortality and to prevent breast cancer. Mammography screening reduces mortality by early detection. However, approximately one fourth of the women who develop breast cancer are diagnosed within two years after a negative screen. There is a need to identify the short-term risk of these women to better guide clinical followup. Another drawback of mammography screening is that it focuses on early detection only and not on breast cancer prevention. Today, it is known that women attending screening can be stratified into high and low risk of breast cancer. Women at high risk could be offered preventive measures such as low-dose tamoxifen to reduce breast cancer incidence. Women at low risk do not benefit from screening and could be offered less frequent screening. In study I, we developed and validated the mammographic density measurement tool STRATUS to enable mammogram resources at hospitals for large scale epidemiological studies on risk, masking, and therapy response in relation to breast cancer. STRATUS showed similar measurement results on different types of mammograms at different hospitals. Longitudinal studies on mammographic density could also be analysed more accurate with less nonbiological variability. In study II, we developed and validated a short-term risk model based on mammographic features (mammographic density, microcalcifications, masses) and differences in occurrences of mammographic features between left and right breasts. The model could optionally be expanded with lifestyle factors, family history of breast cancer, and genetic determinants. Based on the results, we showed that among women with a negative mammography screen, the short-term risk tool was suitable to identify women that developed breast cancer before or at next screening. We also showed that traditional long-term risk models were less suitable to identify the women who in a short time-period after risk assessment were diagnosed with breast cancer. In study III, we performed a phase II trial to identify the lowest dose of tamoxifen that could reduce mammographic density, an early marker for reduced breast cancer risk, to the same extent as standard 20 mg dose but cause less side-effects. We identified 2.5 mg tamoxifen to be non-inferior for reducing mammographic density. The women who used 2.5 mg tamoxifen also reported approximately 50% less severe vasomotor side-effects. In study IV, we investigated the use of low-dose tamoxifen for an additional clinical use case to increase screening sensitivity through its effect on reducing mammographic density. It was shown that 24% of the interval cancers have a potential to be detected at prior screen. In conclusion, tools were developed for assessing mammographic density and breast cancer risk. In addition, two low-dose tamoxifen concepts were developed for breast cancer prevention and improved screening sensitivity. Clinical prospective validation is further needed for the risk assessment tool and the low-dose tamoxifen concepts for the use in breast cancer prevention and for reducing breast cancer mortality

Volumetric mammographic density: heritability and association with breast cancer susceptibility loci.

BACKGROUND: Mammographic density is a strong heritable trait, but data on its genetic component are limited to area-based and qualitative measures. We studied the heritability of volumetric mammographic density ascertained by a fully-automated method and the association with breast cancer susceptibility loci. METHODS: Heritability of volumetric mammographic density was estimated with a variance component model in a sib-pair sample (N pairs = 955) of a Swedish screening based cohort. Associations with 82 established breast cancer loci were assessed in an independent sample of the same cohort (N = 4025 unrelated women) using linear models, adjusting for age, body mass index, and menopausal status. All tests were two-sided, except for heritability analyses where one-sided tests were used. RESULTS: After multivariable adjustment, heritability estimates (standard error) for percent dense volume, absolute dense volume, and absolute nondense volume were 0.63 (0.06) and 0.43 (0.06) and 0.61 (0.06), respectively (all P < .001). Percent and absolute dense volume were associated with rs10995190 (ZNF365; P = 9.0 × 10(-6) and 8.9 × 10(-7), respectively) and rs9485372 (TAB2; P = 1.8 × 10(-5) and 1.8 × 10(-3), respectively). We also observed associations of rs9383938 (ESR1) and rs2046210 (ESR1) with the absolute dense volume (P = 2.6 × 10(-4) and 4.6 × 10(-4), respectively), and rs6001930 (MLK1) and rs17356907 (NTN4) with the absolute nondense volume (P = 6.7 × 10(-6) and 8.4 × 10(-5), respectively). CONCLUSIONS: Our results support the high heritability of mammographic density, though estimates are weaker for absolute than percent dense volume. We also demonstrate that the shared genetic component with breast cancer is not restricted to dense tissues only.This work was supported by the Swedish Research Council (grant no. 521-2011- 3187) and Swedish Cancer Society (grant no. CAN 2013/469). The KARolinska MAmmography project for risk prediction of breast cancer study was supported by Märit and Hans Rausing’s Initiative Against Breast Cancer and the Cancer and Risk Prediction Center CRisP (http://ki.se/en/meb/crisp), a Linneus Centre (Contract ID 70867902) financed by the Swedish Research Council. KH is supported by the Swedish Research Counsil (grant no. 521-2011-3205) and JL is a UNESCO-L’OREAL International Fellow.This is the accepted manuscript. The final version is available from OUP at http://dx.doi.org/10.1093/jnci/dju33

Evaluation of the current knowledge limitations in breast cancer research: a gap analysis

BACKGROUND A gap analysis was conducted to determine which areas of breast cancer research, if targeted by researchers and funding bodies, could produce the greatest impact on patients. METHODS Fifty-six Breast Cancer Campaign grant holders and prominent UK breast cancer researchers participated in a gap analysis of current breast cancer research. Before, during and following the meeting, groups in seven key research areas participated in cycles of presentation, literature review and discussion. Summary papers were prepared by each group and collated into this position paper highlighting the research gaps, with recommendations for action. RESULTS Gaps were identified in all seven themes. General barriers to progress were lack of financial and practical resources, and poor collaboration between disciplines. Critical gaps in each theme included: (1) genetics (knowledge of genetic changes, their effects and interactions); (2) initiation of breast cancer (how developmental signalling pathways cause ductal elongation and branching at the cellular level and influence stem cell dynamics, and how their disruption initiates tumour formation); (3) progression of breast cancer (deciphering the intracellular and extracellular regulators of early progression, tumour growth, angiogenesis and metastasis); (4) therapies and targets (understanding who develops advanced disease); (5) disease markers (incorporating intelligent trial design into all studies to ensure new treatments are tested in patient groups stratified using biomarkers); (6) prevention (strategies to prevent oestrogen-receptor negative tumours and the long-term effects of chemoprevention for oestrogen-receptor positive tumours); (7) psychosocial aspects of cancer (the use of appropriate psychosocial interventions, and the personal impact of all stages of the disease among patients from a range of ethnic and demographic backgrounds). CONCLUSION Through recommendations to address these gaps with future research, the long-term benefits to patients will include: better estimation of risk in families with breast cancer and strategies to reduce risk; better prediction of drug response and patient prognosis; improved tailoring of treatments to patient subgroups and development of new therapeutic approaches; earlier initiation of treatment; more effective use of resources for screening populations; and an enhanced experience for people with or at risk of breast cancer and their families. The challenge to funding bodies and researchers in all disciplines is to focus on these gaps and to drive advances in knowledge into improvements in patient care

CYP2D6-polymorphism and effect of adjuvant tamoxifen in breast cancer patients

Adjuvant tamoxifen at the standard dose of 20 mg daily for five to ten years reduces the risk for relapse and mortality in hormone sensitive breast cancer. The effect however varies and no early marker of poor response is yet available. Varying activation of tamoxifen due to polymorphism in the CYP2D6 gene has been suggested to influence the effect of the treatment, but data are inconsistent. Our previous study in a smaller cohort of tamoxifen treated early breast cancer diagnosed 1998-2000 indicated a poorer prognosis in premenopausal patients with reduced CYP2D6 activity. The overall aim of this thesis was to investigate various aspects of tamoxifen treatment to facilitate improved personalized endocrine treatment strategies in early breast cancer, with individualized tamoxifen dosing, to improve quality of life, adherence and prognosis. In study I we investigated the correlation between CYP2D6 genotype and tamoxifen metabolite levels in plasma, focusing on reduced function CYP2D6 variants (n=118). We also explored the relationship between endoxifen levels and adverse effects to tamoxifen. The degree of side effects to tamoxifen appeared to be dependent on endoxifen concentration. We found a distinct correlation between CYP2D6 activity and plasma concentrations of endoxifen. The effect of reduced function variants, in particular CYP2D6*41, on endoxifen formation was greater than anticipated. Markedly reduced endoxifen concentrations were seen in all homozygous carriers of CYP2D6 no function variants and in those with two reduced activity alleles. The fraction of patients with poor tamoxifen activation might thus be larger than expected. This may be important information for future genotype-based tamoxifen dosing. Although the clinical relevance of the proposed target level of endoxifen at around 5.9 ng/mL needs to be evaluated, it is concerning that a third of our study patients had endoxifen concentrations below this level with tamoxifen at the current standard dose. This underlines the importance of further work to define a target concentration of endoxifen for clinical benefit. In study II we investigated the effect of CYP2D6 activity and other systemic adjuvant therapy on mammographic density (MD) change (n=699) in tamoxifen treated patients. As expected, MD declined during follow up, with a more prominent decrease in the premenopausal subgroup. Other systemic adjuvant treatment did not further extend density decline in this tamoxifen treated cohort. Density reduction appeared to persist after tamoxifen was stopped. Importantly, the previously proposed correlation between CYP2D6 activity and density change in patients with adjuvant tamoxifen could not be confirmed in this cohort with modern complex systemic adjuvant treatment. More data is needed to ascertain whether mammographic density change may be used as a marker of the desired effect of adjuvant tamoxifen. In study III we compared information from patient records to data from the National Prescribed Drug Register in Sweden on adherence to adjuvant endocrine treatment (n=1235). We also investigated the association between CYP2D6-activity, menopausal status, the patients’ risk for relapse and adherence. Consistency, i.e. agreement, between the two sources of adherence data was good, 86%, when including medication with an aromatase inhibitor (AI) after tamoxifen. In those with at least 4.5 years follow up, adherence to adjuvant tamoxifen was reasonable, 72% and increased to 82%, when including subsequent AIs, based on prescription refill data. Adherence was not found to vary by menopausal status or recurrence risk. Unexpectedly, adherence to tamoxifen was lower in CYP2D6 poor metabolizers, despite data proposing a reduced risk of adverse effects in this group. In study IV we aimed to validate our previous findings in a larger material in a more modern setting (n=1105), with tamoxifen treated patients operated between 2006-2014, who could also be subject to improved multimodal adjuvant therapy compared to the patients in our older study and to determine if the effect of CYP2D6 genotype is affected by menopausal status. Compared with our previous study, fewer patients, 12%, had a relapse and only 4% died from breast cancer under the 11-year follow-up. In summary, no obvious correlation between poor CYP2D6 activity and a worse prognosis was found in this material, accounting for adherence to tamoxifen and CYP2D6 inhibitors. A correlation between low CYP2D6 activity and a poorer prognosis in premenopausal tamoxifen treated early breast cancer was thus not confirmed. Breast cancer treatment has steadily improved over time. A possible negative effect of poor CYP2D6 activity on clinical outcome in tamoxifen treated patients is therefore likely marginal in a clinical setting with access to multimodal postoperative breast cancer treatment. Although our results do not support CYP2D6 testing for patients with adjuvant tamoxifen in a multimodal clinical setting, we cannot exclude that CYP2D6 genotyping might still be of value in selected groups, such as in in a low resource setting, where many patients, including those at higher risk of relapse, receive tamoxifen monotherapy. Therapeutic drug monitoring of tamoxifen to secure sufficient plasma levels of endoxifen for clinical efficacy and to avoid excess drug exposure associated with severe side effects might also be relevant in the future. In conclusion, this thesis contributes to the knowledge on CYP2D6 polymorphism and the effect of postoperative tamoxifen in a multimodal setting, the correlation between CYP2D6 genotype and tamoxifen metabolites, which is important for future dose titration studies of tamoxifen, the effect of systemic adjuvant treatment on density change in tamoxifen treated patients as well as adherence to adjuvant endocrine treatment, with focus on tamoxifen. There is a need for improved management of side effects to tamoxifen treatment, to optimize quality of life and adherence. Therapeutic drug monitoring of tamoxifen might be an approach. More work on predictive markers and early evaluation of response to tamoxifen is warranted

유방 촬영술 영상 자료의 딥러닝 적용을 통한 유방암 위험도 평가 : 유방 치밀도 자동 평가 방법 기반

학위논문(석사)--서울대학교 대학원 :보건대학원 보건학과,2019. 8. 성주헌.Introduction : Mammographic density adjusted for age and body mass index (BMI) is the most predictive marker of breast cancer after familial causes and genetic markers. The aim of this study was to develop deep learning (DL) algorithm to assess mammographic density. Methods : Total 2464 participants (834 cases and 1630 controls) were collected from Asan Medical Center and Samsung Medical Center, Korea. Cranio-caudal view mammographic images were obtained using full-field digital mammography system. Mammographic densities were measured using CUMULUS software. The resulting DL algorithm was tested on a held-out test set of 493 women. Agreement on DL and expert was assessed with correlation coefficient and weighted κ statistics. Risk associations of DL measures were evaluated with area under curve (AUC) and odds per adjusted standard deviation (OPERA). Results : The DL model showed very good agreement with expert for both percent density and dense area (r = 0.94 - 0.96 and κ = 0.89 - 0.91). Risk associations of DL measures were comparable to manual measures of expert. DL measures adjusted for age and BMI showed strong risk associations with breast cancer (OPERA = 1.51 - 1.63 and AUC = 0.61 - 0.64). Conclusions : DL model can be used to measure mammographic density which is a strong risk factor of breast cancer. This study showed the potential of DL algorithm as a mammogram-based risk prediction model in breast cancer screening test.유방 내 유방 실질 조직의 양을 반영하는 유방 밀도는 맘모그램에서 나타나는 밝은 부분으로 정의되며, 유방암의 강력한 위험인자로 널리 알려져 있다. 하지만 유방 밀도는 측정하는데 시간과 비용이 많이 든다는 단점으로 인해 유방암 검진 과정에서 제한적으로 사용돼 왔다. 본 연구의 목적은 유방암 검진에서 유방암 예측 모형에 포함해 활용할 수 있는 딥러닝 기반 유방 밀도 측정치를 개발하는 것이다. 본 연구는 아산 병원과 삼성 서울병원의 유방암 검진 자료로부터 수집된 총 2464 명의 참여자 (환자: 834 명, 대조군 : 1630 명) 를 대상으로 수행되었다. 환자의 경우 병변이 발생한 유방의 반대쪽 유방, 대조군의 경우 임의로 고른 유방을 대상으로 유방 밀도 측정에 5년 이상의 경력을 가진 전문가가 CUMULUS 프로그램을 활용하여 유방 밀도 (치밀 유방 부위, cm2 및 치밀도 백분율, %) 를 측정하였다. 이 전문가 측정치를 훈련 데이터로 하여 완전 합성곱 신경망 (Fully Convolutional Network) 기반 딥러닝 모델을 구축하였고, 이를 테스트 데이터에 대해 적용해 전문가 측정치와의 일치도 및 유방암 예측력을 평가하였다. 딥러닝 모델은 전문가와 높은 일치도 (r = 0.94 - 0.96, weighted κ = 0.89 – 0.91) 를 보였다. 또한 나이와 BMI를 보정한 딥러닝 기반 측정치의 유방암 예측력을 평가한 결과, 딥러닝 모델이 전문가와 비슷한 수준의 예측력을 갖는다는 것을 확인하였다 (전문가, AUC = 0.62 – 0.63, 딥러닝 모델, AUC = 0.61 – 0.64). 본 연구는 딥러닝이 현재의 노동 집약적인 유방 밀도 측정법을 보완할 수 있는 가능성을 보여주었다. 이는 비용-효율적인 방법으로 유방 밀도 측정치를 유방암 예측 모형에 포함시킬 수 있는 기회를 제공한다. 이러한 맘모그램 기반 유방암 위험도 예측 모형이 유방암 검진 과정에 적용된다면 보다 정밀한 유방암 위험도 평가를 통해 효과적으로 유방암 고위험군을 선별할 수 있으며, 고위험군에 대한 맞춤형 예방 전략이 적용된다면 장기적으로 유방암 조기 발견 및 사망률 감소에 기여할 수 있을 것으로 기대한다.1 Introduction 1 2 Materials and Methods 3 2.1 Data collection 3 2.2 Measurement of mammographic density 4 2.3 Development of DL model 6 2.3.1 Establishing ground truth 6 2.3.2 Image preprocessing 6 2.3.3 Establishing DL model 6 2.3.4 Estimation of mammographic density 11 2.4 Statistical methods 14 2.4.1 Agreement statistics 14 2.4.2 Evaluation of risk association 15 3 Results 16 3.1 Characteristics of study participants 16 3.2 Agreement of DL model 17 3.3 Breast cancer risk profiles 21 4 Discussion 24 Bibliography 26 초록 29Maste

Determinants and influence of mammographic features on breast cancer risk

Mammographic density and mammographic microcalcifications are the key imaging features in mammography examination. Mammographic density is known as a strong risk factor for breast cancer and is the radiographic appearance of epithelial and fibrous tissue which appears white on a mammogram. While, the dark part of a mammogram represents the fatty tissue. Mammographic microcalcifications appear as small deposits of calcium and they are one of the earliest sign of breast cancer. Malignant microcalcifications are seen in both in situ and invasive lesions. In this thesis we used the data from the prospective KARMA cohort to study the association between established breast cancer risk factors with mammographic density change over time (Study I), to examine the association between annual mammographic density change and risk of breast cancer (Study II), to investigate the association between established risk factors for breast cancer and microcalcification clusters and their asymmetry (Study III), and finally to elucidate the association between microcalcification clusters, their asymmetry, and risk of overall and subtype specific breast cancer (Study IV). The lifestyle and reproductive factors were assessed using web-based questionnaires. Average mammographic density and total microcalcification clusters were measured using a Computer Aided Detection system (CAD) and the STRATUS method, respectively. In Study I, the average yearly dense area change was -1.0 cm . Body mass index (BMI) and physical activity were statistically associated with density change. Beside age, lean and physically active women had the largest decrease in mammographic density per year. In Study II, overall, 563 women were diagnosed with breast cancer and annual mammographic density change did not seem to influence the risk of breast cancer. Furthermore, density change does not seem to modify the association between baseline density and risk of breast cancer. In Study III, age, mammographic density, genetic factors related to breast cancer, having more children, longer duration of breast-feeding were significantly associated with increased risk of presence of microcalcification clusters. In Study IV, 676 women were diagnosed with breast cancer. Further, women with 33 microcalcification clusters had 2 times higher risk of breast cancer compared to women with no clusters. Microcalcification clusters were associated with both in situ and invasive breast cancer. Finally, during postmenopausal period, microcalcification clusters influence risk of breast cancer to the similar extend as baseline mammographic density. In conclusion, we have identified novel determinants of mammographic density changes and potential predictors of suspicious mammographic microcalcification clusters. Further, our results suggested that annual mammographic density change does not influence breast cancer risk, while presence of suspicious microcalcification clusters was strongly associated with breast cancer risk