Refine
Year of publication
Document Type
- Article (20)
- Part of a Book (1)
- Preprint (1)
Language
- English (22) (remove)
Has Fulltext
- yes (22)
Is part of the Bibliography
- no (22)
Keywords
- breast cancer (4)
- brain metastases (2)
- Absolute quantification (1)
- Artificial Intelligence (1)
- Atherosclerosis (1)
- BPTF (1)
- Biodiversity Data (1)
- Biomonitoring (1)
- Botanical Collections (1)
- Breast cancer (1)
Institute
Introduction: Current prognostic gene expression profiles for breast cancer mainly reflect proliferation status and are most useful in ER-positive cancers. Triple negative breast cancers (TNBC) are clinically heterogeneous and prognostic markers and biology-based therapies are needed to better treat this disease.
Methods: We assembled Affymetrix gene expression data for 579 TNBC and performed unsupervised analysis to define metagenes that distinguish molecular subsets within TNBC. We used n = 394 cases for discovery and n = 185 cases for validation. Sixteen metagenes emerged that identified basal-like, apocrine and claudin-low molecular subtypes, or reflected various non-neoplastic cell populations, including immune cells, blood, adipocytes, stroma, angiogenesis and inflammation within the cancer. The expressions of these metagenes were correlated with survival and multivariate analysis was performed, including routine clinical and pathological variables.
Results: Seventy-three percent of TNBC displayed basal-like molecular subtype that correlated with high histological grade and younger age. Survival of basal-like TNBC was not different from non basal-like TNBC. High expression of immune cell metagenes was associated with good and high expression of inflammation and angiogenesis-related metagenes were associated with poor prognosis. A ratio of high B-cell and low IL-8 metagenes identified 32% of TNBC with good prognosis (hazard ratio (HR) 0.37, 95% CI 0.22 to 0.61; P < 0.001) and was the only significant predictor in multivariate analysis including routine clinicopathological variables.
Conclusions: We describe a ratio of high B-cell presence and low IL-8 activity as a powerful new prognostic marker for TNBC. Inhibition of the IL-8 pathway also represents an attractive novel therapeutic target for this disease.
Plants, fungi and algae are important components of global biodiversity and are fundamental to all ecosystems. They are the basis for human well-being, providing food, materials and medicines. Specimens of all three groups of organisms are accommodated in herbaria, where they are commonly referred to as botanical specimens.The large number of specimens in herbaria provides an ample, permanent and continuously improving knowledge base on these organisms and an indispensable source for the analysis of the distribution of species in space and time critical for current and future research relating to global biodiversity. In order to make full use of this resource, a research infrastructure has to be built that grants comprehensive and free access to the information in herbaria and botanical collections in general. This can be achieved through digitization of the botanical objects and associated data.The botanical research community can count on a long-standing tradition of collaboration among institutions and individuals. It agreed on data standards and standard services even before the advent of computerization and information networking, an example being the Index Herbariorum as a global registry of herbaria helping towards the unique identification of specimens cited in the literature.In the spirit of this collaborative history, 51 representatives from 30 institutions advocate to start the digitization of botanical collections with the overall wall-to-wall digitization of the flat objects stored in German herbaria. Germany has 70 herbaria holding almost 23 million specimens according to a national survey carried out in 2019. 87% of these specimens are not yet digitized. Experiences from other countries like France, the Netherlands, Finland, the US and Australia show that herbaria can be comprehensively and cost-efficiently digitized in a relatively short time due to established workflows and protocols for the high-throughput digitization of flat objects.Most of the herbaria are part of a university (34), fewer belong to municipal museums (10) or state museums (8), six herbaria belong to institutions also supported by federal funds such as Leibniz institutes, and four belong to non-governmental organizations. A common data infrastructure must therefore integrate different kinds of institutions.Making full use of the data gained by digitization requires the set-up of a digital infrastructure for storage, archiving, content indexing and networking as well as standardized access for the scientific use of digital objects. A standards-based portfolio of technical components has already been developed and successfully tested by the Biodiversity Informatics Community over the last two decades, comprising among others access protocols, collection databases, portals, tools for semantic enrichment and annotation, international networking, storage and archiving in accordance with international standards. This was achieved through the funding by national and international programs and initiatives, which also paved the road for the German contribution to the Global Biodiversity Information Facility (GBIF).Herbaria constitute a large part of the German botanical collections that also comprise living collections in botanical gardens and seed banks, DNA- and tissue samples, specimens preserved in fluids or on microscope slides and more. Once the herbaria are digitized, these resources can be integrated, adding to the value of the overall research infrastructure. The community has agreed on tasks that are shared between the herbaria, as the German GBIF model already successfully demonstrates.We have compiled nine scientific use cases of immediate societal relevance for an integrated infrastructure of botanical collections. They address accelerated biodiversity discovery and research, biomonitoring and conservation planning, biodiversity modelling, the generation of trait information, automated image recognition by artificial intelligence, automated pathogen detection, contextualization by interlinking objects, enabling provenance research, as well as education, outreach and citizen science.We propose to start this initiative now in order to valorize German botanical collections as a vital part of a worldwide biodiversity data pool.
Purpose: The PELICAN trial evaluates for the first time efficacy and safety of pegylated liposomal doxorubicin (PLD) versus capecitabine as first-line treatment of metastatic breast cancer (MBC).
Methods: This randomized, phase III, open-label, multicenter trial enrolled first-line MBC patients who were ineligible for endocrine or trastuzumab therapy. Cumulative adjuvant anthracyclines of 360 mg/m2 doxorubicin or equivalent were allowed. Left ventricular ejection fraction of >50 % was required. Patients received PLD 50 mg/m2 every 28 days or capecitabine 1250 mg/m2 twice daily for 14 days every 21 days. The primary endpoint was time-to-disease progression (TTP).
Results: 210 patients were randomized (n = 105, PLD and n = 105, capecitabine). Adjuvant anthracyclines were given to 37 % (PLD) and 36 % (capecitabine) of patients. No significant difference was observed in TTP [HR = 1.21 (95 % confidence interval, 0.838–1.750)]. Median TTP was 6.0 months for both PLD and capecitabine. Comparing patients with or without prior anthracyclines, no significant difference in TTP was observed in the PLD arm (log-rank P = 0.64). For PLD versus capecitabine, respectively, overall survival (median, 23.3 months vs. 26.8 months) and time-to-treatment failure (median, 4.6 months vs. 3.7 months) were not statistically significantly different. Compared to PLD, patients on capecitabine experienced more serious adverse events (P = 0.015) and more cardiac events among patients who had prior anthracycline exposure (18 vs. 8 %; P = 0.31).
Conclusion: Both PLD and capecitabine are effective first-line agents for MBC.
Parkinson’s disease (PD) is a neurodegenerative disorder frequent at old age characterized by atrophy of the nigrostriatal projection. Overexpression and A53T-mutation of the presynaptic, vesicle-associated chaperone alpha-synuclein are known to cause early-onset autosomal dominant PD. We previously generated mice with transgenic overexpression of human A53T-alpha-synuclein (A53T-SNCA) in dopaminergic substantia nigra neurons as a model of early PD. To elucidate the early and late effects of A53T-alpha-synuclein on the proteome of dopaminergic nerve terminals in the striatum, we now investigated expression profiles of young and old mice using two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE) and mass spectrometry. In total, 15 proteins were upregulated and 2 downregulated. Mice before the onset of motor anomalies showed an upregulation of the spot containing 14-3-3 proteins, in particular the epsilon isoform, as well as altered levels of chaperones, vesicle trafficking and bioenergetics proteins. In old mice, the persistent upregulation of 14-3-3 proteins was aggravated by an increase of glial fibrillary acidic protein (GFAP) suggesting astrogliosis due to initial neurodegeneration. Independent immunoblots corroborated GFAP upregulation and 14-3-3 upregulation for the epsilon isoform, and also detected significant eta and gamma changes. Only for 14-3-3 epsilon a corresponding mRNA increase was observed in midbrain, suggesting it is transcribed in dopaminergic perikarya and accumulates as protein in presynapses, together with A53T-SNCA. 14-3-3 proteins associate with alpha-synuclein in vitro and in pathognomonic Lewy bodies of PD brains. They act as chaperones in signaling, dopamine synthesis and stress response. Thus, their early dysregulation probably reflects a response to alpha-synuclein toxicity.
Electronic supplementary material: The online version of this article (doi:10.1007/s00702-011-0717-3) contains supplementary material, which is available to authorized users.
Oncologic therapy is currently undergoing significant changes. A number of innovative targeted medications currently in clinical development have raised high expectations. With that in mind, discussions about terms such as "clinical benefit" and "clinical relevance" are highly topical. This also applies to further developments in the field of adjuvant systemic therapies for early-stage breast cancer. As the treatment aim is curative, assessment of the clinical benefit of adjuvant therapies must be largely based on efficacy outcomes. The focus must be on improving disease-free survival rates and lowering the risk of recurrence. Because of the current low mortality rates, statements about overall survival rates are only possible after very long observation periods. Consequently, new drugs in adjuvant therapies should be considered as offering a clinical benefit, if they reduce the risk of recurrence below current low levels of risk. The evidence for established adjuvant therapy standards in early-stage breast cancer can be used as objective criteria for comparison. This review article considers the requirements for clinical benefit of new adjuvant therapies for early breast cancer, based on examples from adjuvant endocrine therapy, adjuvant polychemotherapy and adjuvant anti-HER2 therapy.
Characteristics and clinical outcome of breast cancer patients with asymptomatic brain metastases
(2020)
Simple Summary: The prognosis for patients with breast cancer that has spread to the brain is poor, and survival for these women hasn’t improved over the last few decades. We do not currently test for asymptomatic brain metastases in breast cancer patients, although this does happen in some other types of cancer. In this study we wanted to find out more about breast cancer that has spread to the brain and in particular to see whether there might be any advantage to spotting brain metastases before the development of neurological symptoms. Overall, our results suggest that women could be better off if their brain metastases are diagnosed before they begin to cause symptoms. We now need to carry out a clinical trial to see what happens if we screen high-risk breast cancer patients for brain metastases. This will verify whether doing so could increase survival, symptom control or quality of life.
Abstract: Background: Brain metastases (BM) have become a major challenge in patients with metastatic breast cancer. Methods: The aim of this analysis was to characterize patients with asymptomatic BM (n = 580) in the overall cohort of 2589 patients with BM from our Brain Metastases in Breast Cancer Network Germany (BMBC) registry. Results: Compared to symptomatic patients, asymptomatic patients were slightly younger at diagnosis (median age: 55.5 vs. 57.0 years, p = 0.01), had a better performance status at diagnosis (Karnofsky index 80–100%: 68.4% vs. 57%, p < 0.001), a lower number of BM (>1 BM: 56% vs. 70%, p = 0.027), and a slightly smaller diameter of BM (median: 1.5 vs. 2.2 cm, p < 0.001). Asymptomatic patients were more likely to have extracranial metastases (86.7% vs. 81.5%, p = 0.003) but were less likely to have leptomeningeal metastasis (6.3% vs. 10.9%, p < 0.001). Asymptomatic patients underwent less intensive BM therapy but had a longer median overall survival (statistically significant for a cohort of HER2-positive patients) compared to symptomatic patients (10.4 vs. 6.9 months, p < 0.001). Conclusions: These analyses show a trend that asymptomatic patients have less severe metastatic brain disease and despite less intensive local BM therapy still have a better outcome (statistically significant for a cohort of HER2-positive patients) than patients who present with symptomatic BM, although a lead time bias of the earlier diagnosis cannot be ruled out. Our analysis is of clinical relevance in the context of potential trials examining the benefit of early detection and treatment of BM.
Heterogenous subtypes of breast cancer need to be analyzed separately. Pooling of datasets can provide reasonable sample sizes but dataset bias is an important concern. We assembled a combined dataset of 579 Affymetrix microarrays from triple negative breast cancer (TNBC) in Gene Expression Omnibus (GEO) series GSE31519. We developed a method for selecting comparable datasets and to control for the amount of dataset bias of individual probesets.