Refine
Document Type
- Article (4)
- ZIB-Report (2)
- Poster (1)
Language
- English (7)
Is part of the Bibliography
- no (7)
Institute
Before the onset of sprouting angiogenesis, the endothelium is prepatterned for the positioning of tip and stalk cells. Both cell identities are not static, as endothelial cells (ECs) constantly compete for the tip cell position in a dynamic fashion. Here, we show that both bone morphogenetic protein (BMP) 2 and BMP6 are proangiogenic in vitro and ex vivo and that the BMP type I receptors, activin receptor-like kinase (ALK)3 and ALK2, play crucial and distinct roles in this process. BMP2 activates the expression of tip cell–associated genes, such as DLL4 (delta-like ligand 4) and KDR (kinase insert domain receptor), and p38-heat shock protein 27 (HSP27)–dependent cell migration, thereby generating tip cell competence. Whereas BMP6 also triggers collective cell migration via the p38-HSP27 signaling axis, BMP6 induces in addition SMAD1/5 signaling, thereby promoting the expression of stalk cell–associated genes, such as HES1 (hairy and enhancer of split 1) and FLT1 (fms-like tyrosine kinase 1). Specifically, ALK3 is required for sprouting from HUVEC spheroids, whereas ALK2 represses sprout formation. We demonstrate that expression levels and respective complex formation of BMP type I receptors in ECs determine stalk vs. tip cell identity, thus contributing to endothelial plasticity during sprouting angiogenesis. As antiangiogenic monotherapies that target the VEGF or ALK1 pathways have not fulfilled efficacy objectives in clinical trials, the selective targeting of the ALK2/3 pathways may be an attractive new approach.
Background
We assessed the novel MACC1 gene to further stratify stage II colon cancer patients with proficient mismatch repair (pMMR).
Patients and methods
Four cohorts with 596 patients were analyzed: Charité 1 discovery cohort was assayed for MACC1 mRNA expression and MMR in cryo-preserved tumors. Charité 2 comparison cohort was used to translate MACC1 qRT-PCR analyses to FFPE samples. In the BIOGRID 1 training cohort MACC1 mRNA levels were related to MACC1 protein levels from immunohistochemistry in FFPE sections; also analyzed for MMR. Chemotherapy-naïve pMMR patients were stratified by MACC1 mRNA and protein expression to establish risk groups based on recurrence-free survival (RFS). Risk stratification from BIOGRID 1 was confirmed in the BIOGRID 2 validation cohort. Pooled BIOGRID datasets produced a best effect-size estimate.
Results
In BIOGRID 1, using qRT-PCR and immunohistochemistry for MACC1 detection, pMMR/MACC1-low patients had a lower recurrence probability versus pMMR/MACC1-high patients (5-year RFS of 92% and 67% versus 100% and 68%, respectively). In BIOGRID 2, longer RFS was confirmed for pMMR/MACC1-low versus pMMR/MACC1-high patients (5-year RFS of 100% versus 90%, respectively). In the pooled dataset, 6.5% of patients were pMMR/MACC1-low with no disease recurrence, resulting in a 17% higher 5-year RFS (95% CI (12.6-21.3%)) versus pMMR/MACC1-high patients (P=0.037). Outcomes were similar for pMMR/MACC1-low and deficient MMR (dMMR) patients (5-year RFS of 100% and 96%, respectively).
Conclusions
MACC1 expression stratifies colon cancer patients with unfavorable pMMR status. Stage II colon cancer patients with pMMR/MACC1-low tumors have a similar favorable prognosis to those with dMMR with potential implications for the role of adjuvant therapy.
Background
We assessed the novel MACC1 gene to further stratify stage II colon cancer
patients with proficient mismatch repair (pMMR).
Patients and methods
Four cohorts with 596 patients were analyzed: Charité 1 discovery cohort
was assayed for MACC1 mRNA expression and MMR in cryo-preserved
tumors. Charité 2 comparison cohort was used to translate MACC1 qRT-
PCR analyses to FFPE samples. In the BIOGRID 1 training cohort MACC1
mRNA levels were related to MACC1 protein levels from
immunohistochemistry in FFPE sections; also analyzed for MMR.
Chemotherapy-naïve pMMR patients were stratified by MACC1 mRNA and
protein expression to establish risk groups based on recurrence-free
survival (RFS). Risk stratification from BIOGRID 1 was confirmed in the
BIOGRID 2 validation cohort. Pooled BIOGRID datasets produced a best
effect-size estimate.
Results
In BIOGRID 1, using qRT-PCR and immunohistochemistry for MACC1
detection, pMMR/MACC1-low patients had a lower recurrence probability
versus pMMR/MACC1-high patients (5-year RFS of 92% and 67% versus
100% and 68%, respectively). In BIOGRID 2, longer RFS was confirmed
for pMMR/MACC1-low versus pMMR/MACC1-high patients (5-year RFS of
100% versus 90%, respectively). In the pooled dataset, 6.5% of patients
were pMMR/MACC1-low with no disease recurrence, resulting in a 17%
higher 5-year RFS (95% CI (12.6-21.3%)) versus pMMR/MACC1-high
patients (P=0.037). Outcomes were similar for pMMR/MACC1-low and
deficient MMR (dMMR) patients (5-year RFS of 100% and 96%,
respectively).
Conclusions
MACC1 expression stratifies colon cancer patients with unfavorable pMMR
status. Stage II colon cancer patients with pMMR/MACC1-low tumors have
a similar favorable prognosis to those with dMMR with potential
implications for the role of adjuvant therapy.
The role of titanium surface nanotopography on preosteoblast morphology, adhesion and migration
(2017)
Surface structuring of titanium-based implants with appropriate nanotopographies can significantly modulate their impact on the biological behavior of cells populating these implants. Implant assisted bone tissue repair and regeneration require functional adhesion and expansion of bone progenitors. The surface nanotopography of implant materials used to support bone healing and its effect on cell behavior, in particular cell adhesion, spreading, expansion, and motility, is still not clearly understood. The aim of this study is to investigate preosteoblast proliferation, adhesion, morphology, and migration on different titanium materials with similar surface chemistry, but distinct nanotopographical features. Sonochemical treatment and anodic oxidation were employed to fabricate disordered – mesoporous titania (TMS), and ordered – titania nanotubular (TNT) topographies respectively. The morphological evaluation revealed a surface dependent shape, thickness, and spreading of cells owing to different adherence behavior. Cells were polygonal-shaped and well-spread on glass and TMS, but displayed an elongated fibroblast-like morphology on TNT surfaces. The cells on glass however, were much flatter than on nanostructured surfaces. Both nanostructured surfaces impaired cell adhesion, but TMS was more favorable for cell growth due to its support of cell attachment and spreading in contrast to TNT. Quantitative wound healing assay in combination with live-cell imaging revealed that cells seeded on TMS surfaces migrated in close proximity to neighboring cells and less directed when compared to the migratory behavior on other surfaces. The results indicate distinctly different cell adhesion and migration on ordered and disordered titania nanotopographies, providing important information that could be used in optimizing titanium-based scaffold design to foster bone tissue growth and repair.
The role of titanium surface nanotopography on preosteoblast morphology, adhesion and migration
(2017)
Surface structuring of titanium-based implants with appropriate nanotopographies can significantly modulate their impact on the biological behavior of cells populating these implants. Implant assisted bone tissue repair and regeneration require functional adhesion and expansion of bone progenitors. The surface nanotopography of implant materials used to support bone healing and its effect on cell behavior, in particular cell adhesion, spreading, expansion, and motility, is still not clearly understood. The aim of this study is to investigate preosteoblast proliferation, adhesion, morphology, and migration on different titanium materials with similar surface chemistry, but distinct nanotopographical features. Sonochemical treatment and anodic oxidation were employed to fabricate disordered – mesoporous titania (TMS), and ordered – titania nanotubular (TNT) topographies respectively. The morphological evaluation revealed a surface dependent shape, thickness, and spreading of cells owing to different adherence behavior. Cells were polygonal-shaped and well-spread on glass and TMS, but displayed an elongated fibroblast-like morphology on TNT surfaces. The cells on glass however, were much flatter than on nanostructured surfaces. Both nanostructured surfaces impaired cell adhesion, but TMS was more favorable for cell growth due to its support of cell attachment and spreading in contrast to TNT. Quantitative wound healing assay in combination with live-cell imaging revealed that cells seeded on TMS surfaces migrated in close proximity to neighboring cells and less directed when compared to the migratory behavior on other surfaces. The results indicate distinctly different cell adhesion and migration on ordered and disordered titania nanotopographies, providing important information that could be used in optimizing titanium-based scaffold design to foster bone tissue growth and repair.
In this work, we developed an automatic algorithm to analyze cell migration in chemotaxis assays, based on phase-contrast time-lapse microscopy. While manual approaches are still widely used in recent publications, our algorithm is able to track hundreds of single cells per frame. The extracted paths are analysed with traditional geometrical approaches as well as diffusion-driven Markov state models (MSM). Based on these models, a detailed view on spatial and temporal effects is possible.
Using our new approach on experimental data, we are able to distinguish between directed migration (e.g. towards a VEGF gradient) and random migration without favored direction. A calculation of the committor probabilities reveals that cells of the whole image area are more likely to migrate directly towards the VEGF than away from it during the first four hours. However, in absence of a chemoattractant, cells migrate more likely to their nearest image border. These conclusions are supported by the spatial mean directions.
In a next step, the cell-cell interaction during migration and the migration of cell clusters will be analyzed. Furthermore, we want to observe phenotypical changes during migration based on fluorescence microscopy and machine learning.
The algorithm is part of a collaborative platform which brings the experimental expertise of scientists from life sciences and the analytical knowledge of computer scientists together. This platform is built using web-based technologies with a responsive real-time user interface. All data, including raw and metadata as well as the accompanying results, will be stored in a secure and scalable compute cluster. The compute cluster provides sufficient space and computational power for modern image-based experiments and their analyses. Specific versions of data and results can be tagged to keep immutable records for archival.
Neurons are highly polarized cells that require continuous turnover of membrane proteins at axon terminals to develop, function, and survive. Yet, it is still unclear whether membrane protein degradation requires transport back to the cell body or whether degradation also occurs locally at the axon terminal, where live observation of sorting and degradation has remained a challenge. Here, we report direct observation of two cargo-specific membrane protein degradation mechanisms at axon terminals based on a live-imaging approach in intact Drosophila brains.
We show that different acidification-sensing cargo probes are sorted into distinct classes of degradative ‘‘hub’’ compartments for synaptic vesicle proteins and plasma membrane proteins at axon terminals. Sorting and degradation of the two cargoes in the separate hubs are molecularly distinct. Local sorting of synaptic vesicle proteins for degradation at the axon terminal is, surprisingly, Rab7 independent,
whereas sorting of plasma membrane proteins is Rab7 dependent. The cathepsin-like protease CP1 is specific to synaptic vesicle hubs, and its delivery requires the vesicle SNARE neuronal synaptobrevin. Cargo separation only occurs at the axon terminal, whereas degradative compartments at the cell body are mixed. These data show that at least two local, molecularly distinct pathways sort membrane cargo for degradation specifically at the axon terminal, whereas degradation can occur both at the terminal and en route to the cell body.