Despite the clinical similarities triple-negative and basal-like breast cancer are not synonymous. Indeed, not all basal-like cancers are negative for estrogen receptor, progesterone receptor and ...HER2 expression while triple-negative also encompasses other cancer types. P53 protein appears heterogeneously expressed in triple-negative breast cancers, suggesting that it may be associated with specific biological subgroups with a different outcome.
We comparatively analyzed p53 expression in triple-negative tumors from two independent breast cancer case series (633 cases from the University of Ferrara and 1076 cases from the University of Nottingham).
In both case series, p53 protein expression was able to subdivide the triple-negative cases into two distinct subsets consistent with a different outcome. In fact, triple-negative patients with a p53 expressing tumor showed worse overall and event-free survival.
The immunohistochemical evaluation of p53 expression may help in taming the currently stormy relationship between pathological (triple-negative tumors) and biological (basal breast cancers) classifications and in selecting patient subgroups with different biological features providing a potentially powerful prognostic contribution in triple-negative breast cancers.
Purpose: Early breast cancer presents with a remarkable heterogeneity of outcomes. Undetected, microscopic lymph node tumor deposits
may account for a significant fraction of this prognostic ...diversity. Thus, we systematically evaluated the presence of lymph
node tumor cell deposits ≤0.2 mm in diameter pN 0(i+) , nanometastases and analyzed their prognostic effect.
Experimental Design: Single-institution, consecutive patients with 8 years of median follow-up ( n = 702) were studied. To maximize chances of detecting micrometastases and nanometastases, whole-axilla dissections were analyzed.
pN 0 cases ( n = 377) were systematically reevaluated by lymph node ( n = 6676) step-sectioning and anticytokeratin immunohistochemical analysis. The risk of first adverse events and of distant
relapse of bona fide pN 0 patients was compared with that of pN 0(i+) , pN 1mi , and pN 1 cases.
Results: Minimal lymph node deposits were revealed in 13% of pN 0 patients. The hazard ratio for all adverse events of pN 0(i+) versus pN 0(i−) was 2.51 ( P = 0.00019). Hazards of pN 1mi and pN 0(i+) cases were not significantly different. A multivariate Cox model showed a hazard ratio of 2.16 for grouped pN 0(i+) /pN 1mi versus pN 0(i−) ( P = 0.0005). Crude cumulative incidence curves for metastatic relapse were also significantly different (Gray's test χ 2 = 5.54, P = 0.019).
Conclusion: Nanometastases are a strong risk factor for disease-free survival and for metastatic relapse. These findings support the
inclusion of procedures for nanometastasis detection in tumor-node-metastasis staging.
We present MadDM v.3.0, a numerical tool to compute particle dark matter observables in generic new physics models. The new version features a comprehensive and automated framework for dark matter ...searches at the interface of collider physics, astrophysics and cosmology and is deployed as a plugin of the MadGraph5_aMC@NLO platform, inheriting most of its features. With respect to the previous version, MadDM v.3.0 can now provide predictions for indirect dark matter signatures in astrophysical environments, such as the annihilation cross section at present time and the energy spectra of prompt photons, cosmic rays and neutrinos resulting from dark matter annihilation. MadDM indirect detection features support both 2→2 and 2→n dark matter annihilation processes. In addition, the ability to compare theoretical predictions with experimental constraints is extended by including the Fermi-LAT likelihood for gamma-ray constraints from dwarf spheroidal galaxies and by providing an interface with the nested sampling algorithm PyMultiNest to perform high dimensional parameter scans efficiently. We validate the code for a wide set of dark matter models by comparing the results from MadDM v.3.0 to existing tools and results in the literature.
SModelS is an automatized tool for the interpretation of simplified model results from the LHC. It allows to decompose models of new physics obeying a Z2 symmetry into simplified model components, ...and to compare these against a large database of experimental results. The first release of SModelS, v1.0, used only cross section upper limit maps provided by the experimental collaborations. In this new release, v1.1, we extend the functionality of SModelS to efficiency maps. This increases the constraining power of the software, as efficiency maps allow to combine contributions to the same signal region from different simplified models. Other new features of version 1.1 include likelihood and χ2 calculations, extended information on the topology coverage, an extended database of experimental results as well as major speed upgrades for both the code and the database. We describe in detail the concepts and procedures used in SModelS v1.1, explaining in particular how upper limits and efficiency map results are dealt with in parallel. Detailed instructions for code usage are also provided.
Program Title: SModelS
Program Files doi:http://dx.doi.org/10.17632/w4nft4459w.1
Licensing provisions: GPLv3
Programming language: Python
Nature of problem: The results for searches for new physics beyond the Standard Model (BSM) at the Large Hadron Collider are often communicated by the experimental collaborations in terms of constraints on so-called simplified models spectra (SMS). Understanding how SMS constraints impact a realistic new physics model, where possibly a multitude of relevant production channels and decay modes are relevant, is a non-trivial task.
Solution method: We exploit the notion of simplified models to constrain full models by “decomposing” them into their SMS components. A database of SMS results obtained from the official results of the ATLAS and CMS collaborations, but in part also from ‘recasting’ the experimental analyses, can be matched against the decomposed model, resulting in a statement to what extent the model at hand is in agreement or contradiction with the experimental results. Further useful information on, e.g., the coverage of the models’ signatures is also provided.
Additional comments including Restrictions and Unusual features: At present, the tool is limited to signatures with missing transverse energy, and only models with a Z2-like symmetry can be tested. Each SMS is defined purely by the vertex structure and the SM final state particles; BSM particles are described only by their masses, production cross sections and branching ratios. Possible differences in signal selection efficiencies arising, e.g., from different production mechanisms or from the spin of the BSM particles, are ignored in this approach. Since only part of the full model can be constrained by SMS results, SModelS will always remain more conservative (though orders of magnitude faster) than “full recasting” approaches.
SModelS is an automatized tool enabling the fast interpretation of simplified model results from the LHC within any model of new physics respecting a Z2 symmetry. With the version 1.2 we announce ...several new features. First, previous versions were restricted to missing energy signatures and assumed prompt decays within each decay chain. SModelSv1.2 considers the lifetime of each Z2-odd particle and appropriately takes into account missing energy, heavy stable charged particle and R-hadron signatures. Second, the current version allows for a combination of signal regions in efficiency map results whenever a covariance matrix is available from the experiment. This is an important step towards fully exploiting the constraining power of efficiency map results. Several other improvements increase the user-friendliness, such as the use of wildcards in the selection of experimental results, and a faster database which can be given as a URL. Finally, smodelsTools provides an interactive plots maker to conveniently visualize the results of a model scan.
Program Title: SModelS
Program Files doi:http://dx.doi.org/10.17632/w4nft4459w.2
Licensing provisions: GPLv3
Programming language: Python3
Journal reference of previous version: Comput. Phys. Commun. 227 (2018) 72
Does the new version supersede the previous version?: Yes
Reasons for the new version: Addition of new features.
Summary of revisions: The most important new features in v1.2 are the combination of signal regions in efficiency map results whenever a covariance matrix is available from the experiment, and the implementation of heavy stable charged particle and R-hadron signatures. Moreover, the database of experimental results can now be given as a URL, and the pickling has been improved to make the database faster. Other improvements include that wildcards are allowed when selecting analyses, datasets or topologies, and that the path to the model file, formerly required to be smodels/sparticles.py, can be specified in the parameters card. For the convenience of the user, we also provide a tool to make interactive plots to visualize the results of a model scan. Finally, the whole code now also runs with Python3, which has become the recommended default, and it can now be installed in its source directory.
Nature of problem: The results for searches for new physics beyond the Standard Model (BSM) at the Large Hadron Collider are often communicated by the experimental collaborations in terms of constraints on so-called simplified models spectra (SMS). Understanding how SMS constraints impact a realistic new physics model, where possibly a multitude of production channels and decay modes are relevant, is a non-trivial task.
Solution method: We exploit the notion of simplified models to constrain full models by “decomposing” them into their SMS components. A database of SMS results obtained from the official results of the ATLAS and CMS collaborations, but in part also from ‘recasting’ the experimental analyses, can be matched against the decomposed model, resulting in a statement to what extent the model at hand is in agreement or contradiction with the experimental results. Further useful information on, e.g., the coverage of the model’s signatures is also provided.
Additional comments including restrictions and unusual features: At present, only models with a Z2-like symmetry can be tested. Each SMS is defined purely by the vertex structure and the final-state particles; initial and intermediate BSM particles are described only by their masses, production cross sections, branching ratios and total widths. Possible differences in signal selection efficiencies arising, e.g., from different production mechanisms or from the spin of the BSM particles, are ignored in this approach. Since only part of the full model can be constrained by SMS results, SModelS will always remain more conservative (though orders of magnitude faster) than “full recasting” approaches.
1 F. Ambrogi et al., “SModelS v1.1 user manual: Improving simplified model constraints with efficiency maps,” Comput. Phys. Commun. 227 (2018) 72 arXiv:1701.06586 hep-ph.
Objective： To analyze the pattern over time （dynamics） of further recurrence and death after ipsilateral breast tumor recurrence （IBTR） in breast cancer patients undergoing breast conserving ...treatment （BCT）. Methods： A total of 338 evaluable patients experiencing IBTR were extracted from a database of 3,293 patients undergoing BCT. The hazard rates for recurrence and mortality throughout 10 years of follow-up after IBTR were assessed and were compared to the analogous estimates associated to the primary treatment. Results： In a time frame with the time origin at the surgical treatment for IBTR, the hazard rate for further recurrence displays a bimodal pattern （peaks at the second and at the sixth year）. Patients receiving mastectomy for IBTR reveal recurrence and mortality dynamics similar to that of node positive （N＋） patients receiving mastectomy as primary surgery, apart from the first two-three years, when IBTR patients do worse. If the patients with time to IBTR longer than 2.5 years are considered, differences disappear. Conclusions： The recurrence and mortality dynamics following IBTR surgical removal is similar to the corresponding dynamics following primary tumor removal. In particular, patients with time to IBTR in excess of 2.5 years behave like N＋ patients following primary tumor removal. Findings may be suitably explained by assuming that the surgical manoeuvre required by IBTR treatment is able to activate a sudden growing phase for tumor foci most of which, as suggested by the systemic model of breast cancer, would have reached the clinical level according to their own dynamics.
Trying to better define Bipolar Disorder (BD) progression, different staging models have been conceptualized, each one emphasizing different aspects of illness. In a previous article we ...retrospectively applied the main staging models to a sample of 100 bipolar patients at four time points over a ten-year observation. In the present study, focusing on Kupka & Hillegers's model, we aimed to assess the transition of the same sample through the different stages of illness and to explore the potential role of clinical variables on the risk of progression.
Multistate Model using the mstate package in R and Markov model with stratified hazards were used for statistical analysis.
A high hazard of transition from stage 2 to 3 emerged, with a probability of staying in stage 2 decreasing to 14 % after 3 years. BD II was significantly associated with transition from stage 1 to 2, whereas the number of lifetime episodes >3 and the elevated predominant polarity with transition from stage 3 to 4.
Our results corroborated the evidence on BD progression and contributed to outline its trajectory over time. Further effort may help to define a standardized staging approach towards ever increasing tailored interventions.
•We retrospectively applied Kupka & Hillegers’s model to a sample of 100 bipolar patients at 4 time-points over 10 years•We assessed the transition across stages and the role of clinical variables on the risk of progression•A high hazard of transition 2→3 emerged, with a probability of staying in stage 2 decreasing to 14% after 3 years•BD II was associated with transition 1→2; > 3 lifetime episodes and elevated predominant polarity with transition 3→4
Abstract
Cell polarity is crucial for the correct structural and functional organization of epithelial tissue. Its disruption can lead to loss of the apicobasal polarity, alteration in the ...intracellular components, misregulation of the pathways involved in cell proliferation and cancer promotion. Very recent in vitro/in vivo findings demonstrated that obesity-associated alterations in tissue adipokines protein level negatively affect epithelial polarity. We performed an in silico study to investigate whether such alterations also occur in surgical samples. We aimed to explore the relationship among the expression of the genes coding for leptin (LEP), adiponectin (ADIPOQ), adipokine receptors (LEPR, ADIPOR1 and ADIPOR2), and a panel of polarity-associated genes in normal tissue from breast reduction mammoplasty, and a series of paired samples of histologically normal (HN) tissue and invasive cancer. Results indicated that, in normal tissue, the expression of adipokines and their receptors negatively correlated with that of the polarity-associated genes and GGT1, which codes for γ-glutamyl transferase (GGT) enzyme, a marker of cell distress and membrane disruption. This negative correlation progressively decreased in HN and cancerous tissue, and loss of correlation between ADIPOR2 and polarity-associated genes appeared the most noticeable alteration. Given the growing role of obesity in breast cancer etiology and the opposite action of leptin and adiponectin in epithelial tissue remodeling, ADIPOR2 loss could be addressed as a key mechanism leading to an unbalanced leptin stimulatory activity, subsequent cell polarity disruption and eventually tumor initiation, a finding that requires to be confirmed also at the protein level and with in vivo models.
Recent in vitro/in vivo findings indicated that obesity-associated alterations in adipokines protein levels negatively affect epithelial cell polarity. Present findings show that this negative correlation occurs also in surgical samples and progressively decreases in normal, histologically normal and cancerous tissue.
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