scispace - formally typeset
Search or ask a question
Author

Tobias Bäuerle

Bio: Tobias Bäuerle is an academic researcher from University of Erlangen-Nuremberg. The author has contributed to research in topics: Bone metastasis & Magnetic resonance imaging. The author has an hindex of 34, co-authored 155 publications receiving 4504 citations. Previous affiliations of Tobias Bäuerle include Fred Hutchinson Cancer Research Center & German Cancer Research Center.


Papers
More filters
Journal ArticleDOI
TL;DR: It is shown that primary human luminal breast cancer CTCs contain MICs that give rise to bone, lung and liver metastases in mice, and functional circulating MICs and associated markers are described to aid the design of better tools to diagnose and treat metastatic breast cancer.
Abstract: It has been hypothesized that carcinoma metastasis is initiated by a subpopulation of circulating tumor cells (CTCs) found in the blood of patients. However, although the presence of CTCs is an indicator of poor prognosis in several carcinoma entities, the existence and phenotype of metastasis-initiating cells (MICs) among CTCs has not been experimentally demonstrated. Here we developed a xenograft assay and used it to show that primary human luminal breast cancer CTCs contain MICs that give rise to bone, lung and liver metastases in mice. These MIC-containing CTC populations expressed EPCAM, CD44, CD47 and MET. In a small cohort of patients with metastases, the number of EPCAM(+)CD44(+)CD47(+)MET(+) CTCs, but not of bulk EPCAM(+) CTCs, correlated with lower overall survival and increased number of metastasic sites. These data describe functional circulating MICs and associated markers, which may aid the design of better tools to diagnose and treat metastatic breast cancer.

930 citations

Journal ArticleDOI
TL;DR: Use of wb-MRI for risk stratification of patients with asymptomatic multiple myeloma is recommended and the presence per se of FLs and a number of greater than one FL were the strongest adverse prognostic factors for progression into sMM in multivariate analysis.
Abstract: Purpose With whole-body magnetic resonance imaging (wb-MRI), almost the whole bone marrow compartment can be examined in patients with monoclonal plasma cell disease. Focal lesions (FLs) detected by spinal MRI have been of prognostic significance in symptomatic multiple myeloma (sMM). In this study, we investigated the prognostic significance of FLs in wb-MRI in patients with asymptomatic multiple myeloma (aMM). Patients and Methods Wb-MRI was performed in 149 patients with aMM. The prognostic significance of the presence and absence, as well as the number, of FLs for progression into sMM was analyzed. Results FLs were present in 28% of patients. The presence per se of FLs and a number of greater than one FL were the strongest adverse prognostic factors for progression into sMM (P < .001) in multivariate analysis. A diffuse infiltration pattern in MRI, a monoclonal protein of 40 g/L or greater, and a plasma cell infiltration in bone marrow of 20% or greater were other adverse prognostic factors for progre...

325 citations

Journal ArticleDOI
07 Aug 2019-Nature
TL;DR: Analysis of macrophage subsets within joints reveals a population of CX3CR1+ tissue-resident macrophages that form a tight-junction-mediated barrier at the synovial lining, protecting the joint from the invasion of inflammatory cells.
Abstract: Macrophages are considered to contribute to chronic inflammatory diseases such as rheumatoid arthritis1. However, both the exact origin and the role of macrophages in inflammatory joint disease remain unclear. Here we use fate-mapping approaches in conjunction with three-dimensional light-sheet fluorescence microscopy and single-cell RNA sequencing to perform a comprehensive spatiotemporal analysis of the composition, origin and differentiation of subsets of macrophages within healthy and inflamed joints, and study the roles of these macrophages during arthritis. We find that dynamic membrane-like structures, consisting of a distinct population of CX3CR1+ tissue-resident macrophages, form an internal immunological barrier at the synovial lining and physically seclude the joint. These barrier-forming macrophages display features that are otherwise typical of epithelial cells, and maintain their numbers through a pool of locally proliferating CX3CR1− mononuclear cells that are embedded into the synovial tissue. Unlike recruited monocyte-derived macrophages, which actively contribute to joint inflammation, these epithelial-like CX3CR1+ lining macrophages restrict the inflammatory reaction by providing a tight-junction-mediated shield for intra-articular structures. Our data reveal an unexpected functional diversification among synovial macrophages and have important implications for the general role of macrophages in health and disease. Analysis of macrophage subsets within joints reveals a population of CX3CR1+ tissue-resident macrophages that form a tight-junction-mediated barrier at the synovial lining, protecting the joint from the invasion of inflammatory cells.

311 citations

Journal ArticleDOI
05 Apr 2019-Science
TL;DR: It is found that a mere motility change of the individuals in response to the visual perception of their peers induces group formation and cohesion and is relevant not only for the self-organization of living systems, but also for the design of robust and scalable autonomous systems.
Abstract: Group formation in living systems typically results from a delicate balance of repulsive, aligning, and attractive interactions. We found that a mere motility change of the individuals in response to the visual perception of their peers induces group formation and cohesion. We tested this principle in a real system of active particles whose motilities are controlled by an external feedback loop. For narrow fields of view, individuals gathered into cohesive nonpolarized groups without requiring active reorientations. For wider fields of view, cohesion could be achieved by lowering the response threshold. We expect this motility-induced cohesion mechanism to be relevant not only for the self-organization of living systems, but also for the design of robust and scalable autonomous systems.

182 citations

Journal ArticleDOI
TL;DR: Potentially, medication directed at inhibiting microglia activation within the first day after stroke could stabilize blood vessels in the penumbra, increase blood flow, and serve as a valuable treatment for patients suffering from ischemic stroke.
Abstract: The contribution of microglia to ischemic cortical stroke is of particular therapeutic interest because of the impact on the survival of brain tissue in the ischemic penumbra, a region that is potentially salvable upon a brain infarct. Whether or not tissue in the penumbra survives critically depends on blood flow and vessel perfusion. To study the role of microglia in cortical stroke and blood vessel stability, CX3CR1+/GFP mice were subjected to transient middle cerebral artery occlusion and then microglia were investigated using time-lapse two-photon microscopy in vivo. Soon after reperfusion, microglia became activated in the stroke penumbra and started to expand cellular protrusions towards adjacent blood vessels. All microglia in the penumbra were found associated with blood vessels within 24 h post reperfusion and partially fully engulfed them. In the same time frame blood vessels became permissive for blood serum components. Migration assays in vitro showed that blood serum proteins leaking into the tissue provided molecular cues leading to the recruitment of microglia to blood vessels and to their activation. Subsequently, these perivascular microglia started to eat up endothelial cells by phagocytosis, which caused an activation of the local endothelium and contributed to the disintegration of blood vessels with an eventual break down of the blood brain barrier. Loss-of-microglia-function studies using CX3CR1GFP/GFP mice displayed a decrease in stroke size and a reduction in the extravasation of contrast agent into the brain penumbra as measured by MRI. Potentially, medication directed at inhibiting microglia activation within the first day after stroke could stabilize blood vessels in the penumbra, increase blood flow, and serve as a valuable treatment for patients suffering from ischemic stroke.

178 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
TL;DR: Novel engineering approaches are discussed that capitalize on the growing understanding of tumour biology and nano–bio interactions to develop more effective nanotherapeutics for cancer patients.
Abstract: The intrinsic limits of conventional cancer therapies prompted the development and application of various nanotechnologies for more effective and safer cancer treatment, herein referred to as cancer nanomedicine. Considerable technological success has been achieved in this field, but the main obstacles to nanomedicine becoming a new paradigm in cancer therapy stem from the complexities and heterogeneity of tumour biology, an incomplete understanding of nano-bio interactions and the challenges regarding chemistry, manufacturing and controls required for clinical translation and commercialization. This Review highlights the progress, challenges and opportunities in cancer nanomedicine and discusses novel engineering approaches that capitalize on our growing understanding of tumour biology and nano-bio interactions to develop more effective nanotherapeutics for cancer patients.

3,800 citations

Journal ArticleDOI
19 Nov 2015-Nature
TL;DR: It is demonstrated that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells.
Abstract: Ever since Stephen Paget's 1889 hypothesis, metastatic organotropism has remained one of cancer's greatest mysteries. Here we demonstrate that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis. Targeting the integrins α6β4 and αvβ5 decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. Finally, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis.

3,399 citations

Journal ArticleDOI
TL;DR: The disease definition of multiple myeloma is updated to include validated biomarkers in addition to existing requirements of attributable CRAB features (hypercalcaemia, renal failure, anaemia, and bone lesions), and specific metrics that new biomarkers should meet for inclusion in the disease definition are provided.
Abstract: This International Myeloma Working Group consensus updates the disease defi nition of multiple myeloma to include validated biomarkers in addition to existing requirements of attributable CRAB features (hypercalcaemia, renal failure, anaemia, and bone lesions). These changes are based on the identifi cation of biomarkers associated with near inevitable development of CRAB features in patients who would otherwise be regarded as having smouldering multiple myeloma. A delay in application of the label of multiple myeloma and postponement of therapy could be detrimental to these patients. In addition to this change, we clarify and update the underlying laboratory and radiographic variables that fulfi l the criteria for the presence of myeloma-defi ning CRAB features, and the histological and monoclonal protein requirements for the disease diagnosis. Finally, we provide specifi c metrics that new biomarkers should meet for inclusion in the disease defi nition. The International Myeloma Working Group recommends the implementation of these criteria in routine practice and in future clinical trials, and recommends that future studies analyse any diff erences in outcome that might occur as a result of the new disease defi nition.

3,049 citations

Journal ArticleDOI
09 Feb 2017-Cell
TL;DR: The cellular and molecular mechanisms involved in metastasis are summarized, with a focus on carcinomas where the most is known, and the general principles of metastasis that have begun to emerge are highlighted.

1,930 citations