Förderzeitraum 2019
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Institute
- Theodor-Boveri-Institut für Biowissenschaften (45)
- Neurologische Klinik und Poliklinik (19)
- Institut für Psychologie (14)
- Kinderklinik und Poliklinik (11)
- Medizinische Klinik und Poliklinik I (11)
- Institut für Hygiene und Mikrobiologie (10)
- Institut für Virologie und Immunbiologie (10)
- Lehrstuhl für Tissue Engineering und Regenerative Medizin (10)
- Pathologisches Institut (9)
- Deutsches Zentrum für Herzinsuffizienz (DZHI) (8)
Sonstige beteiligte Institutionen
To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.
Methylation of the O6-methylguanine DNA methyltransferase (MGMT) promoter has emerged as strong prognostic factor in the therapy of glioblastoma multiforme. It is associated with an improved response to chemotherapy with temozolomide and longer overall survival. MGMT promoter methylation has implications for the clinical course of patients. In recent years, there have been observations of patients changing their MGMT promoter methylation from primary tumor to relapse. Still, data on this topic are scarce. Studies often consist of only few patients and provide rather contrasting results, making it hard to draw a clear conclusion on clinical implications. Here, we summarize the previous publications on this topic, add new cases of changing MGMT status in relapse and finally combine all reports of more than ten patients in a statistical analysis based on the Wilson score interval. MGMT promoter methylation changes are seen in 115 of 476 analyzed patients (24%; CI: 0.21–0.28). We discuss potential reasons like technical issues, intratumoral heterogeneity and selective pressure of therapy. The clinical implications are still ambiguous and do not yet support a change in clinical practice. However, retesting MGMT methylation might be useful for future treatment decisions and we encourage clinical studies to address this topic
Despite histological evidence in various solid tumor entities, available experience with CXCR4-directed diagnostics and endoradiotherapy mainly focuses on hematologic diseases. With the goal of expanding the application of CXCR4 theranostics to solid tumors, we aimed to elucidate the feasibility of CXCR4-targeted imaging in a variety of such neoplasms.
Methods: Nineteen patients with newly diagnosed, treatment-naïve solid tumors including pancreatic adenocarcinoma or neuroendocrine tumor, cholangiocarcinoma, hepatocellular carcinoma, renal cell carcinoma, ovarian cancer, and prostate cancer underwent [\(^{68}\)Ga]Pentixafor PET/CT. CXCR4-mediated uptake was assessed both visually and semi-quantitatively by evaluation of maximum standardized uptake values (SUV\(_{max}\)) of both primary tumors and metastases. With physiologic liver uptake as reference, tumor-to-background ratios (TBR) were calculated. [\(^{68}\)Ga]Pentixafor findings were further compared to immunohistochemistry and [\(^{18}\)F]FDG PET/CT.
Results: On [\(^{68}\)Ga]Pentixafor PET/CT, 10/19 (52.6%) primary tumors were visually detectable with a median SUVmax of 5.4 (range, 1.7–16.0) and a median TBR of 2.6 (range, 0.8–7.4), respectively. The highest level of radiotracer uptake was identified in a patient with cholangiocarcinoma (SUVmax, 16.0; TBR, 7.4). The relatively low uptake on [\(^{68}\)Ga]Pentixafor was also noted in metastases, exhibiting a median SUVmax of 4.5 (range, 2.3–8.8; TBR, 1.7; range, 1.0–4.1). A good correlation between uptake on [\(^{68}\)Ga]Pentixafor and histological derived CXCR4 expression was noted (R = 0.62, P < 0.05). In the 3 patients in whom [\(^{18}\)F]FDG PET/CT was available, [\(^{68}\)Ga]Pentixafor exhibited lower uptake in all lesions.
Conclusions: In this cohort of newly diagnosed, treatment-naïve patients with solid malignancies, CXCR4 expression as detected by [\(^{68}\)Ga]Pentixafor-PET/CT and immunohistochemistry was rather moderate. Thus, CXCR4-directed imaging may not play a major role in the management of solid tumors in the majority of patients.
Circulating MACC1 transcripts in glioblastoma patients predict prognosis and treatment response
(2019)
Glioblastoma multiforme is the most aggressive primary brain tumor of adults, but lacksreliable and liquid biomarkers. We evaluated circulating plasma transcripts of metastasis-associatedin colon cancer-1 (MACC1), a prognostic biomarker for solid cancer entities, for prediction of clinicaloutcome and therapy response in glioblastomas. MACC1 transcripts were significantly higher inpatients compared to controls. Low MACC1 levels clustered together with other prognosticallyfavorable markers. It was associated with patients’ prognosis in conjunction with the isocitratedehydrogenase (IDH) mutation status: IDH1 R132H mutation and low MACC1 was most favorable(median overall survival (OS) not yet reached), IDH1 wildtype and high MACC1 was worst (medianOS 8.1 months), while IDH1 wildtype and low MACC1 was intermediate (median OS 9.1 months).No patients displayed IDH1 R132H mutation and high MACC1. Patients with low MACC1 levelsreceiving standard therapy survived longer (median OS 22.6 months) than patients with high MACC1levels (median OS 8.1 months). Patients not receiving the standard regimen showed the worstprognosis, independent of MACC1 levels (low: 6.8 months, high: 4.4 months). Addition of circulatingMACC1 transcript levels to the existing prognostic workup may improve the accuracy of outcomeprediction and help define more precise risk categories of glioblastoma patients.
Monocytic myeloid-derived suppressor cells (M-MDSCs) and granulocytic MDSCs (G-MDSCs) have been found to be massively induced in TB patients as well in murine Mtb infection models. However, the interaction of mycobacteria with MDSCs and its role in TB infection is not well studied. Here, we investigated the role of Cav-1 for MDSCs infected with Mycobacterium bovis Bacille-Calmette-Guerín (BCG). MDSCs that were generated from murine bone marrow (MDSCs) of wild-type (WT) or Cav1\(^{−/−}\) mice upregulated Cav-1, TLR4 and TLR2 expression after BCG infection on the cell surface. However, Cav-1 deficiency resulted in a selective defect of intracellular TLR2 levels predominantly in the M-MDSC subset. Further analysis indicated no difference in the phagocytosis of BCG by M-MDSCs from WT and Cav1\(^{−/−}\) mice or caveosome formation, but a reduced capacity to up-regulate surface markers, to secrete various cytokines, to induce iNOS and NO production required for suppression of T cell proliferation, whereas Arg-1 was not affected. Among the signaling pathways affected by Cav-1 deficiency, we found lower phosphorylation of the p38 mitogen-activated protein kinase (MAPK). Together, our findings implicate that (i) Cav-1 is dispensable for the internalization of BCG, (ii) vesicular TLR2 signaling in M-MDSCs is a major signaling pathway induced by BCG, (iii) vesicular TLR2 signals are controlled by Cav-1, (iv) vesicular TLR2/Cav-1 signaling is required for T cell suppressor functions.
Gonorrhea is the second most common sexually transmitted infection in the world and is caused by Gram-negative diplococcus Neisseria gonorrhoeae. Since N. gonorrhoeae is a human-specific pathogen, animal infection models are only of limited use. Therefore, a suitable in vitro cell culture model for studying the complete infection including adhesion, transmigration and transport to deeper tissue layers is required. In the present study, we generated three independent 3D tissue models based on porcine small intestinal submucosa (SIS) scaffold by co-culturing human dermal fibroblasts with human colorectal carcinoma, endometrial epithelial, and male uroepithelial cells. Functional analyses such as transepithelial electrical resistance (TEER) and FITC-dextran assay indicated the high barrier integrity of the created monolayer. The histological, immunohistochemical, and ultra-structural analyses showed that the 3D SIS scaffold-based models closely mimic the main characteristics of the site of gonococcal infection in human host including the epithelial monolayer, the underlying connective tissue, mucus production, tight junction, and microvilli formation. We infected the established 3D tissue models with different N. gonorrhoeae strains and derivatives presenting various phenotypes regarding adhesion and invasion. The results indicated that the disruption of tight junctions and increase in interleukin production in response to the infection is strain and cell type-dependent. In addition, the models supported bacterial survival and proved to be better suitable for studying infection over the course of several days in comparison to commonly used Transwell® models. This was primarily due to increased resilience of the SIS scaffold models to infection in terms of changes in permeability, cell destruction and bacterial transmigration. In summary, the SIS scaffold-based 3D tissue models of human mucosal tissues represent promising tools for investigating N. gonorrhoeae infections under close-to-natural conditions.
Both low-level physical saliency and social information, as presented by human heads or bodies, are known to drive gaze behavior in free-viewing tasks. Researchers have previously made use of a great variety of face stimuli, ranging from photographs of real humans to schematic faces, frequently without systematically differentiating between the two. In the current study, we used a Generalized Linear Mixed Model (GLMM) approach to investigate to what extent schematic artificial faces can predict gaze when they are presented alone or in competition with real human faces. Relative differences in predictive power became apparent, while GLMMs suggest substantial effects for real and artificial faces in all conditions. Artificial faces were accordingly less predictive than real human faces but still contributed significantly to gaze allocation. These results help to further our understanding of how social information guides gaze in complex naturalistic scenes.
Metabolic adaptation to the host cell is important for obligate intracellular pathogens such as Chlamydia trachomatis (Ct). Here we infer the flux differences for Ct from proteome and qRT-PCR data by comprehensive pathway modeling. We compare the comparatively inert infectious elementary body (EB) and the active replicative reticulate body (RB) systematically using a genome-scale metabolic model with 321 metabolites and 277 reactions. This did yield 84 extreme pathways based on a published proteomics dataset at three different time points of infection. Validation of predictions was done by quantitative RT-PCR of enzyme mRNA expression at three time points. Ct’s major active pathways are glycolysis, gluconeogenesis, glycerol-phospholipid (GPL) biosynthesis (support from host acetyl-CoA) and pentose phosphate pathway (PPP), while its incomplete TCA and fatty acid biosynthesis are less active. The modeled metabolic pathways are much more active in RB than in EB. Our in silico model suggests that EB and RB utilize folate to generate NAD(P)H using independent pathways. The only low metabolic flux inferred for EB involves mainly carbohydrate metabolism. RB utilizes energy -rich compounds to generate ATP in nucleic acid metabolism. Validation data for the modeling include proteomics experiments (model basis) as well as qRT-PCR confirmation of selected metabolic enzyme mRNA expression differences. The metabolic modeling is made fully available here. Its detailed insights and models on Ct metabolic adaptations during infection are a useful modeling basis for future studies.