Prevention of breast cancer by recapitulation of pregnancy hormone levels

At the present time, the only approved method of breast cancer prevention is use of the selective estrogen receptor modulator (SERM) tamoxifen. Many breast cancers are driven to grow by estrogen, and tamoxifen exploits this by blocking estrogen action at the estrogen receptor. A counter-intuitive and controversial approach to breast cancer prevention is administration of estrogen and progestin at an early age to achieve pregnancy levels. This approach is supported by the fact that breast cancer incidence is halved by early (≤ 20 years of age) full-term pregnancy. Moreover, it has been demonstrated in rodent models that mimicking the hormonal milieu can effectively prevent carcinogen-induced mammary cancer. In this issue of Breast Cancer Research Rajkumar and colleagues use the rodent model to further define the timing and type of hormonal therapy that is effective in preventing mammary carcinogenesis. Clearly, application of this approach in humans may be difficult, but the potential benefit is intriguing

Mortality following development of breast cancer while using oestrogen or oestrogen plus progestin: a computer record-linkage study

The literature on the relationship between breast cancer mortality and postmenopausal oestrogen and combined oestrogen/progestin therapy is seemingly contradictory. This study explored survival after exposure to oestrogen or oestrogen plus progestin at or in the year prior to breast cancer diagnosis. Information on patients first diagnosed with invasive breast cancer between 1993 and 1998 was linked with outpatient pharmacy data from 1992 to 2000. Patients were classified according to use of oestrogen alone or oestrogen plus progestin at or in the year prior to diagnosis. Compared to nonusers, and adjusting for age at diagnosis, race/ethnicity, tumour size and grade, oestrogen receptor status, surgery status, and chemotherapy and hormone therapy for breast cancer treatment, oestrogen plus progestin users had lower all-cause mortality (stage I hazard ratio (HR)=0.69, 95% confidence interval (CI)=0.48–0.99; stage II HR=0.53, 95% CI=0.39–0.72) and breast cancer mortality (stage I HR=0.52, 95% CI=0.26–1.04; stage II HR=0.69, 95% CI=0.48–0.98). Oestrogen users experienced little or no survival benefit for all-cause mortality (stage I HR=1.04, 95% CI=0.77–1.42; stage II HR=0.86, 95% CI=0.65–1.14) or breast cancer mortality (stage I HR=1.23, 95% CI 0.72–2.10; stage II HR=1.01, 95% CI 0.72–1.41). Our findings suggest, relative to nonusers, a lower risk of death from all causes and from breast cancer in patients who were diagnosed with breast cancer while exposed to oestrogen plus progestin, but not in patients exposed to oestrogen only

An overview of menopausal oestrogen–progestin hormone therapy and breast cancer risk

Results from the Women's Health Initiative (WHI) trial support findings from observational studies that oestrogen–progestin therapy (EPT) use is associated with an increase in breast cancer risk. We conducted a meta-analysis using EPT-specific results from the Collaborative Group on Hormonal Factors in Breast Cancer (CGHFBC) pooled analysis and studies published since that report to obtain an overview of EPT use and breast cancer risk. We also assessed risk by histologic subtype of breast cancer, by schedule of the progestin component of EPT, and by recency of use. We estimate that overall, EPT results in a 7.6% increase in breast cancer risk per year of use. The risk was statistically significantly lower in US studies than in European studies – 5.2 vs 7.9%. There was a significantly higher risk for continuous-combined than for sequential EPT use in Scandinavian studies where much higher total doses of progestin were used in continuous-combined than in sequential EPT. We observed no overall difference in risk for lobular vs ductal carcinoma but did observe a slightly higher risk for current vs past EPT use

Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome

Background: Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes. Methods: Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering. Results: Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed. Conclusions: The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer.Peer reviewe

A Method for Efficient Calculation of Diffusion and Reactions of Lipophilic Compounds in Complex Cell Geometry

A general description of effects of toxic compounds in mammalian cells is facing several problems. Firstly, most toxic compounds are hydrophobic and partition phenomena strongly influence their behaviour. Secondly, cells display considerable heterogeneity regarding the presence, activity and distribution of enzymes participating in the metabolism of foreign compounds i.e. bioactivation/biotransformation. Thirdly, cellular architecture varies greatly. Taken together, complexity at several levels has to be addressed to arrive at efficient in silico modelling based on physicochemical properties, metabolic preferences and cell characteristics. In order to understand the cellular behaviour of toxic foreign compounds we have developed a mathematical model that addresses these issues. In order to make the system numerically treatable, methods motivated by homogenization techniques have been applied. These tools reduce the complexity of mathematical models of cell dynamics considerably thus allowing to solve efficiently the partial differential equations in the model numerically on a personal computer. Compared to a compartment model with well-stirred compartments, our model affords a more realistic representation. Numerical results concerning metabolism and chemical solvolysis of a polycyclic aromatic hydrocarbon carcinogen show good agreement with results from measurements in V79 cell culture. The model can easily be extended and refined to include more reactants, and/or more complex reaction chains, enzyme distribution etc, and is therefore suitable for modelling cellular metabolism involving membrane partitioning also at higher levels of complexity

Polymorphisms of genes coding for insulin-like growth factor 1 and its major binding proteins, circulating levels of IGF-I and IGFBP-3 and breast cancer risk: results from the EPIC study

Insulin-like growth factor I (IGF-I) stimulates cell proliferation and can enhance the development of tumours in different organs. Epidemiological studies have shown that an elevated level of circulating IGF-I is associated with increased risk of breast cancer, as well as of other cancers. Most of circulating IGF-I is bound to an acid-labile subunit and to one of six insulin-like growth factor binding proteins (IGFBPs), among which the most important are IGFBP-3 and IGFBP-1. Polymorphisms of the IGF1 gene and of genes encoding for the major IGF-I carriers may predict circulating levels of IGF-I and have an impact on cancer risk. We tested this hypothesis with a case–control study of 807 breast cancer patients and 1588 matched control subjects, nested within the European Prospective Investigation into Cancer and Nutrition. We genotyped 23 common single nucleotide polymorphisms in IGF1, IGFBP1, IGFBP3 and IGFALS, and measured serum levels of IGF-I and IGFBP-3 in samples of cases and controls. We found a weak but significant association of polymorphisms at the 5′ end of the IGF1 gene with breast cancer risk, particularly among women younger than 55 years, and a strong association of polymorphisms located in the 5′ end of IGFBP3 with circulating levels of IGFBP-3, which confirms previous findings. Common genetic variation in these candidate genes does not play a major role in altering breast cancer risk in Caucasians

Hormone-replacement therapy influences gene expression profiles and is associated with breast-cancer prognosis: a cohort study

BACKGROUND: Postmenopausal hormone-replacement therapy (HRT) increases breast-cancer risk. The influence of HRT on the biology of the primary tumor, however, is not well understood. METHODS: We obtained breast-cancer gene expression profiles using Affymetrix human genome U133A arrays. We examined the relationship between HRT-regulated gene profiles, tumor characteristics, and recurrence-free survival in 72 postmenopausal women. RESULTS: HRT use in patients with estrogen receptor (ER) protein positive tumors (n = 72) was associated with an altered regulation of 276 genes. Expression profiles based on these genes clustered ER-positive tumors into two molecular subclasses, one of which was associated with HRT use and had significantly better recurrence free survival despite lower ER levels. A comparison with external data suggested that gene regulation in tumors associated with HRT was negatively correlated with gene regulation induced by short-term estrogen exposure, but positively correlated with the effect of tamoxifen. CONCLUSION: Our findings suggest that post-menopausal HRT use is associated with a distinct gene expression profile related to better recurrence-free survival and lower ER protein levels. Tentatively, HRT-associated gene expression in tumors resembles the effect of tamoxifen exposure on MCF-7 cells

Breast cancer risk associated with different HRT formulations: a register-based case-control study

BACKGROUND: Previous epidemiological studies have inconsistently shown a modestly increased breast cancer risk associated with hormone replacement therapy (HRT). Limited information is available about different formulations – particularly concerning different progestins. METHODS: A case-control study was performed within Germany in collaboration with regional cancer registries and tumor centers. Up to 5 controls were matched breast cancer cases. Conditional logistic regression analysis was applied to estimate crude and adjusted odds ratios (OR) and 95% confidence intervals (95% CI). Stratified analyses were performed to compare the risk of different estrogens, progestins, and combinations. RESULTS: A total of 3593 cases of breast cancer were identified and compared with 9098 controls. The adjusted overall risk estimate for breast cancer (BC) associated with current or past use of HRT was 1.2 (1.1–1.3), and almost identical for lag times from 6 months to 6 years prior to diagnosis. No significant trend of increasing BC risk was found with increasing duration of HRT use, or time since first or last use in aggregate. Many established BC risk factors significantly modified the effect of HRT on BC risk, particularly first-degree family history of BC, higher age, lower education, higher body mass index (BMI), and never having used oral contraceptives (OCs) during lifetime. Whereas the overall risk estimates were stable, the numbers in many of the sub-analyses of HRT formulation groups (estrogens, progestins, and combinations) were too small for strong conclusions. Nevertheless, the BC risk seems not to vary much across HRT formulation subgroups. In particular, no substantial difference in BC risk was observed between HRT containing conjugated equine estrogens (CEE) or medroxyprogesterone acetate (MPA) and other formulations more common in Europe. CONCLUSION: The BC risk of HRT use is rather small. Low risk estimates for BC and a high potential for residual confounding and bias in this observational study do not permit causal conclusions. Apparently, there is not much variation of the BC risk across HRT formulations (estrogens, progestins). However, the small numbers and the overlapping nature of some of the subgroups suggest cautious interpretation