Stratifying triple-negative breast cancer: which definition(s) to use?

Triple-negative breast cancers (TNBC) have increased rates of pathologic complete response following neoadjuvant chemotherapy, yet have poorer prognosis compared with non-TNBC. Known as the triple-negative paradox, this highlights the need to dissect the biologic and clinical heterogeneity within TNBC. In the present issue, Keam and colleagues suggest two subgroups of TNBC exist based on the proliferation-related marker Ki-67, each with differential response and prognosis following neoadjuvant chemotherapy. To place results into context, we review several definitions available under the TNBC umbrella that may stratify TNBC into clinically relevant subgroups

Things change: Women’s and men’s marital disruption dynamics in Italy during a time of social transformations, 1970-2003

We study women’s and men’s marital disruption in Italy between 1970 and 2003. By applying an event-history analysis to the 2003 Italian variant of the Generations and Gender Survey we found that the spread of marital disruption started among middle-highly educated women. Then in recent years it appears that less educated women have also been able to dissolve their unhappy unions. Overall we can see the beginning of a reversed educational gradient from positive to negative. In contrast the trend in men’s marital disruption risk appears as a change over time common to all educational groups, although with persisting educational differentials.determinants, educational differences, event history analysis, gender difference, Italy, marital disruption

Emerging breast cancer epidemic: evidence from Africa

Cancer is an increasingly important public health problem in developing countries, including Africa [1]. As public and professional awareness of the cancer problem has grown, so has interest in the pattern of disease presentation, its epidemiology and treatment outcome. To date, however, there has been limited research about breast cancer in Africa. In the absence of systematic population-based cancer registration, most information has come from small clinical and pathology case series and the bias inherent in these types of studies has influenced current understanding of the pattern and characteristics of breast cancer in Africa. In this communication, we review the evidence for an emerging epidemic of breast cancer in Africa, its risk factors and likely future course. We conclude that, despite limited data, rising incidence of breast cancer is being driven by increasing life expectancy, improved control of infectious diseases, and changing lifestyle, diet, physical activity and obstetric practices. We also review current beliefs about hormone receptor subtypes of breast cancer in Africa and suggest that this is probably not systematically different from the pattern in other populations after adjusting for factors such as age and that the reported differences are related to poor tissue handling and laboratory processing practices

Impact of established prognostic factors and molecular subtype in very young breast cancer patients: pooled analysis of four EORTC randomized controlled trials

Young age at the time of diagnosis of breast cancer is an independent factor of poor prognosis. In many treatment guidelines, the recommendation is to treat young patients with adjuvant chemotherapy regardless of tumor characteristics. However, limited data on prognostic factors are available for young breast cancer patients. The purpose of this study was to determine the prognostic value of established clinical and pathological prognostic factors in young breast cancer patients. Data from four European Organisation for Research and Treatment of Cancer (EORTC) clinical trials were pooled, resulting in a dataset consisting of 9,938 early breast cancer patients with a median follow-up of 11 years. For 549 patients aged less than 40 years at the time of diagnosis, including 341 node negative patients who did not receive chemotherapy, paraffin tumor blocks were processed for immunohistochemistry using a tissue microarray. Cox proportional hazard analysis was applied to assess the association of clinical and pathological factors with overall and distant metastasis free survival. For young patients, tumor size (P = 0.01), nodal status (P = 0.006) and molecular subtype (P = 0.02) were independent prognostic factors for overall survival. In the node negative subgroup, only molecular subtype was a prognostic factor for overall survival (P = 0.02). Young node negative patients bearing luminal A tumors had an overall survival rate of 94% at 10 years' follow-up compared to 72% for patients with basal-type tumors. Molecular subtype is a strong independent prognostic factor in breast cancer patients younger than 40 years of age. These data support the use of established prognostic factors as a diagnostic tool to assess disease outcome and to plan systemic treatment strategies in young breast cancer patient

Phylogenetic Analysis Suggests That Habitat Filtering Is Structuring Marine Bacterial Communities Across the Globe

The phylogenetic structure and community composition were analysed in an existing data set of marine bacterioplankton communities to elucidate the evolutionary and ecological processes dictating the assembly. The communities were sampled from coastal waters at nine locations distributed worldwide and were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes. The analyses show that the local communities are phylogenetically different from each other and that a majority of them are phylogenetically clustered, i.e. the species (operational taxonomic units) were more related to each other than expected by chance. Accordingly, the local communities were assembled non-randomly from the global pool of available bacterioplankton. Further, the phylogenetic structures of the communities were related to the water temperature at the locations. In agreement with similar studies, including both macroorganisms and bacteria, these results suggest that marine bacterial communities are structured by “habitat filtering”, i.e. through non-random colonization and invasion determined by environmental characteristics. Different bacterial types seem to have different ecological niches that dictate their survival in different habitats. Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed. The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes

Knowledge driven decomposition of tumor expression profiles

<p>Abstract</p> <p>Background</p> <p>Tumors have been hypothesized to be the result of a mixture of oncogenic events, some of which will be reflected in the gene expression of the tumor. Based on this hypothesis a variety of data-driven methods have been employed to decompose tumor expression profiles into component profiles, hypothetically linked to these events. Interpretation of the resulting data-driven components is often done by post-hoc comparison to, for instance, functional groupings of genes into gene sets. None of the data-driven methods allow the incorporation of that type of knowledge directly into the decomposition.</p> <p>Results</p> <p>We present a linear model which uses knowledge driven, pre-defined components to perform the decomposition. We solve this decomposition model in a constrained linear least squares fashion. From a variety of options, a lasso-based solution to the model performs best in linking single gene perturbation data to mouse data. Moreover, we show the decomposition of expression profiles from human breast cancer samples into single gene perturbation profiles and gene sets that are linked to the hallmarks of cancer. For these breast cancer samples we were able to discern several links between clinical parameters, and the decomposition weights, providing new insights into the biology of these tumors. Lastly, we show that the order in which the Lasso regularization shrinks the weights, unveils consensus patterns within clinical subgroups of the breast cancer samples.</p> <p>Conclusion</p> <p>The proposed lasso-based constrained least squares decomposition provides a stable and relevant relation between samples and knowledge-based components, and is thus a viable alternative to data-driven methods. In addition, the consensus order of component importance within clinical subgroups provides a better molecular characterization of the subtypes.</p