Effectiveness of EGFR/HER2-targeted drugs is influenced by the downstream interaction shifts of PTPIP51 in HER2-amplified breast cancer cells

Breast cancer is the most common female cancerous disease and the second most cause of cancer death in women. About 20-30% of these tumors exhibit an amplification of the HER2/ErbB2 receptor, which is coupled to a more aggressive and invasive growth of the cancer cells. Recently developed tyrosine kinase inhibitors and therapeutic antibodies targeting the HER2 receptor improved the overall survival time compared with sole radio- and chemotherapy. Upcoming resistances against the HER2-targeted therapy make a better understanding of the receptor associated downstream pathways an absolute need. In earlier studies, we showed the involvement of Protein Tyrosine Phosphatase Interacting Protein 51 (PTPIP51) in the mitogen-activated protein kinase (MAPK) pathway. The MAPK pathway is one of the most frequently overactivated pathways in HER2-amplified breast cancer cells. This study is aimed to elucidate the effects of four different TKIs on the interactome of PTPIP51, namely with the receptors EGFR and HER2, 14-3-3/Raf1 (MAPK pathway), its regulating enzymes, and the mitochondria-associated interaction partners in HER2 breast cancer cell lines (SK-BR3 and BT474) by using the Duolink proximity ligation assay, immunoblotting and knockdown of PTPIP51. Inhibition of both EGFR and HER2/ErbB2R shifted PTPIP51 into the MAPK pathway, but left the mitochondria-associated interactome of PTPIP51 unattended. Exclusively inhibiting HER2/ErbB2 by Mubritinib did not affect the interaction of PTPIP51 with the MAPK signaling. Selective inhibition of HER2 induced great alterations of mitochondria-associated interactions of PTPIP51, which ultimately led to the most-effective reduction of cell viability of SK-BR3 cells of all tested TKIs. The results clearly reveal the importance of knowing the exact mechanisms of the inhibitors affecting receptor tyrosine kinases in order to develop more efficient anti-HER2-targeted therapies

New Techniques for Clustering Complex Objects

The tremendous amount of data produced nowadays in various application domains such as molecular biology or geography can only be fully exploited by efficient and effective data mining tools. One of the primary data mining tasks is clustering, which is the task of partitioning points of a data set into distinct groups (clusters) such that two points from one cluster are similar to each other whereas two points from distinct clusters are not. Due to modern database technology, e.g.object relational databases, a huge amount of complex objects from scientific, engineering or multimedia applications is stored in database systems. Modelling such complex data often results in very high-dimensional vector data ("feature vectors"). In the context of clustering, this causes a lot of fundamental problems, commonly subsumed under the term "Curse of Dimensionality". As a result, traditional clustering algorithms often fail to generate meaningful results, because in such high-dimensional feature spaces data does not cluster anymore. But usually, there are clusters embedded in lower dimensional subspaces, i.e. meaningful clusters can be found if only a certain subset of features is regarded for clustering. The subset of features may even be different for varying clusters. In this thesis, we present original extensions and enhancements of the density-based clustering notion to cope with high-dimensional data. In particular, we propose an algorithm called SUBCLU (density-connected Subspace Clustering) that extends DBSCAN (Density-Based Spatial Clustering of Applications with Noise) to the problem of subspace clustering. SUBCLU efficiently computes all clusters of arbitrary shape and size that would have been found if DBSCAN were applied to all possible subspaces of the feature space. Two subspace selection techniques called RIS (Ranking Interesting Subspaces) and SURFING (SUbspaces Relevant For clusterING) are proposed. They do not compute the subspace clusters directly, but generate a list of subspaces ranked by their clustering characteristics. A hierarchical clustering algorithm can be applied to these interesting subspaces in order to compute a hierarchical (subspace) clustering. In addition, we propose the algorithm 4C (Computing Correlation Connected Clusters) that extends the concepts of DBSCAN to compute density-based correlation clusters. 4C searches for groups of objects which exhibit an arbitrary but uniform correlation. Often, the traditional approach of modelling data as high-dimensional feature vectors is no longer able to capture the intuitive notion of similarity between complex objects. Thus, objects like chemical compounds, CAD drawings, XML data or color images are often modelled by using more complex representations like graphs or trees. If a metric distance function like the edit distance for graphs and trees is used as similarity measure, traditional clustering approaches like density-based clustering are applicable to those data. However, we face the problem that a single distance calculation can be very expensive. As clustering performs a lot of distance calculations, approaches like filter and refinement and metric indices get important. The second part of this thesis deals with special approaches for clustering in application domains with complex similarity models. We show, how appropriate filters can be used to enhance the performance of query processing and, thus, clustering of hierarchical objects. Furthermore, we describe how the two paradigms of filtering and metric indexing can be combined. As complex objects can often be represented by using different similarity models, a new clustering approach is presented that is able to cluster objects that provide several different complex representations

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Crosstalks of the PTPIP51 interactome revealed in Her2 amplified breast cancer cells by the novel small molecule LDC3/Dynarrestin.

LDC3/Dynarrestin, an aminothiazole derivative, is a recently developed small molecule, which binds protein tyrosine phosphatase interacting protein 51 (PTPIP51). PTPIP51 interacts with various proteins regulating different signaling pathways leading to proliferation and migration. Her2 positive breast cancer cells (SKBR3) express high levels of PTPIP51. Therefore, we investigated the effects of LDC3/Dynarrestin on PTPIP51 and its interactome with 12 different proteins of various signal pathways including the interaction with dynein in SKBR3 cells. The localization and semi-quantification of PTPIP51 protein and the Tyr176 phosphorylated PTPIP51 protein were evaluated. Protein-protein-interactions were assessed by Duolink proximity ligation assays. Interactions and the activation of signal transduction hubs were examined with immunoblots. LDC3/Dynarrestin led to an increased PTPIP51 tyrosine 176 phosphorylation status while the overall amount of PTPIP51 remained unaffected. These findings are paralleled by an enhanced interaction of PTPIP51 with its crucial kinase c-Src and a reduced interaction with the counteracting phosphatase PTP1B. Furthermore, the treatment results in a significantly augmented interaction of PTPIP51/14-3-3β and PTPIP51/Raf1, the link to the MAPK pathway. Under the influence of LDC3/Dynarrestin, the activity of the MAPK pathway rose in a concentration-dependent manner as indicated by RTK assays and immunoblots. The novel small molecule stabilizes the RelA/IκB/PTPIP51 interactome and can abolish the effects caused by TNFα stimulation. Moreover, LDC3/Dynarrestin completely blocked the Akt signaling, which is essential for tumor growth. The data were compared to the recently described interactome of PTPIP51 in LDC3/Dynarrestin treated non-cancerous keratinocyte cells (HaCaT). Differences were identified exclusively for the mitochondrial-associated ER-membranes (MAM) interactions and phospho-regulation related interactome of PTPIP51.LDC3/Dynarrestin gives the opportunity/possibility to influence the MAPK signaling, NFkB signaling and probably calcium homeostasis in breast cancer cells by affecting the PTPIP51 interactome

PTPIP51—A New RelA-tionship with the NFκB Signaling Pathway

The present study shows a new connection of protein tyrosine phosphatase interacting protein 51 (PTPIP51) to the nuclear factor κB (NFκB) signalling pathway. PTPIP51 mRNA and protein expression is regulated by RelA. If bound to the PTPIP51 promoter, RelA repress the mRNA and protein expression of PTPIP51. The parallel treatment with pyrrolidine dithiocarbamate (PDTC) reversed the suppression of PTPIP51 protein expression induced by TNFα. Using the intensity correlation analysis PTPIP51 verified a co-localization with RelA, which is also regulated by TNFα administration. Moreover, the direct interaction of PTPIP51 and RelA was established using the DuoLink proximity ligation assay. IκBα, the known inhibitor of RelA, also interacted with PTPIP51. This hints to the fact that in un-stimulated conditions PTPIP51 forms a complex with RelA and IκBα. The PTPIP51/RelA/IκBα complex is modulated by TNFα. Interestingly, the impact on the mitogen activated protein kinase pathway was negligible except in highest TNFα concentration. Here, PTPIP51 and Raf-1 interactions were slightly repressed. The newly established relationship of PTPIP51 and the NFκB signaling pathway provides the basis for a possible therapeutic impact

der Justus-Liebig-Universität Gießen vorgelegt von

gewidmet Für meine MutterKämpfende Ferkel in einer Sau-Ferkel-Gruppenhaltung (Foto: Birger Puppe, FBN Dummerstorf)...Es gibt nicht zwei in derselben Gesellschaft lebende Hennen, die nicht genau wissen, wer von ihnen „über “ und wer „unter “ ihnen ist... Es erwies sich bei den verschiedensten Experimenten, dass die Neigung zur sozialen Gliederung den Hühnern im Blute liegt... THORLEIF SCHJELDERUPP-EBBE, 192