Biology subjects

Boerries, M.

Publications and source records attributed to Boerries, M..

23 records · Page 2Linked to original sources

bioRxiv2021

Spatially confined sub-tumor microenvironments orchestrate pancreatic cancer pathobiology

Pancreatic ductal adenocarcinoma (PDAC) remains resistant to most treatments and demonstrates a complex pathobiology. Here, we deconvolute regional heterogeneity in the human PDAC tumor microenvironment (TME), a long-standing obstacle, to define precise stromal contributions to PDAC progression. Large scale integration of histology-guided multiOMICs with clinical data sets and functional in vitro models uncovers two microenvironmental programs in PDAC that were anchored in fibroblast differentiation states. These sub-tumor microenvironments (subTMEs) co-occurred intratumorally and were spatially confined, producing patient-specific cellular and molecular heterogeneity associated with shortened patient survival. Each subTME was uniquely structured to support discrete aspects of tumor biology: reactive regions rich in activated fibroblast communities were immune-hot and promoted aggressive tumor progression while deserted regions enriched in extracellular matrix supported tumor differentiation yet were markedly chemoprotective. In conclusion, PDAC regional heterogeneity derives from biologically distinct reactive and protective TME elements with a defined, active role in PDAC progression. Graphical Abstract & Key findings O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=191 SRC="FIGDIR/small/431890v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@17adabdorg.highwire.dtl.DTLVardef@aee778org.highwire.dtl.DTLVardef@deae00org.highwire.dtl.DTLVardef@1718272_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIPDAC regional heterogeneity originates in sub-tumor microenvironments (subTMEs) C_LIO_LISubTMEs exhibit distinct immune phenotypes and CAF differentiation states C_LIO_LIDifferent subTMEs are either tumor-promoting or chemoprotective C_LIO_LIIntratumoral subTME co-occurrence links stromal heterogeneity to patient outcome C_LI

cancer biology↗

bioRxiv2020

Canonical TGFβ signaling induces collective invasion in colorectal carcinogenesis through a Snail1- and Zeb1-independent partial EMT

Local invasion is the initial step towards metastasis, the main cause of cancer mortality. In human colorectal cancer (CRC), malignant cells predominantly invade as cohesive collectives, and may undergo partial epithelial-mesenchymal transition (pEMT) at the invasive front. How this particular mode of stromal infiltration is generated is unknown. Here we investigated the impact of oncogenic transformation and the microenvironment on tumor cell invasion using genetically engineered organoids as CRC models. We found that inactivation of the Apc tumor suppressor combined with expression of oncogenic KrasG12D and dominant negative Trp53R172H did not cell-autonomously induce invasion in vitro. However, oncogenic transformation primed organoids for activation of a collective invasion program upon exposure to the prototypical microenvironmental factor TGF{beta}1. Execution of this program co-depended on a permissive extracellular matrix which was further actively remodeled by invading organoids. Although organoids shed some epithelial properties particularly at the invasive edge, TGF{beta}1-stimulated organoids largely maintained epithelial gene expression while additionally implementing a mesenchymal transcription pattern, resulting in a pEMT phenotype that did not progress to a fully mesenchymal state. Induction of this stable pEMT required canonical, Smad4-mediated TGF{beta} signaling, whereas the EMT master regulators Snail1 and Zeb1 were dispensable. Gene expression profiling provided further evidence for pEMT of TGF{beta}1-treated organoids and showed that their transcriptomes resemble those of human poor prognosis CMS4 cancers which likewise exhibit pEMT features. We propose that collective invasion in colorectal carcinogenesis is triggered by microenvironmental stimuli through activation of a novel, transcription-mediated form of non-progressive pEMT independently of classical EMT regulators.

cancer biology↗

bioRxiv2020

CD20 as a gatekeeper of the resting stage of human B cells

CD20 is a B cell specific membrane protein and a target of therapeutic antibodies such as rituximab (RTX)1. In spite of the prominent usage of anti-CD20 antibodies in the clinic little is known about the biological function of CD202. Here we show that CD20 controls the nanoscale organization of receptors on the surface of resting B lymphocytes. A CRISPR/Cas-based ablation of CD20 in Ramos B cells results in a relocalisation of the IgM B cell antigen receptor (IgM-BCR) and the co-receptor CD19. The resulting IgM-BCR/CD19 signaling synapse leads to transient B cell activation followed by plasma cell differentiation. Similarly to CD20-deficient Ramos cells, naive human B cells treated with rituximab in vitro or isolated from patients during rituximab administration display hallmarks of transient activation characterized by the formation of the IgM-BCR/CD19 signaling synapse, followed by CD19 and IgM-BCR downregulation. Moreover, increased expression of specific plasma cell genes can be observed after rituximab treatment in relapsed CLL patients. In summary we identify CD20 as a gatekeeper of the resting state on human B cells and demonstrate that a disruption of the nanoscale organization of the B cell surface via CD20 deletion or anti-CD20 treatment profoundly alters B cell fate.

immunology↗

bioRxiv2020

Lineage and Spatial Mapping of Glioblastoma-associated Immunity

The diversity of molecular states and cellular plasticity of immune cells in the glioblastoma environment is still poorly understood. Here, we performed scRNA sequencing of the immune compartment and mapped potential cellular interactions leading to an immunosuppressive microenvironment and dysfunction of T cells. Through inferring the dynamic adaptation during T cell activation, we identified three different terminal states with unique transcriptional programs. Modeling of driver genes for terminal T cell fate identified IL-10 signaling alterations in a subpopulation of HAVCR2(+) T cells. To explore in depth cellular interactions, we established an in-silico model by the integration of spatial transcriptomic and scRNA-sequencing, and identified a subset of HMOX1+ myeloid cells defined by IL10 release leading to T cell exhaustion. We found a spatial overlap between HMOX(+) myeloid and HAVCR2(+) T cells, suggesting that myeloid-lymphoid interaction causes immunosuppression present in tumor regions with enriched mesenchymal gene expression. Using human neocortical GBM model, coupled with patient-derived T cells, we confirmed that the functional interaction between myeloid and lymphoid cells, leads to a dysfunctional state of T cells. This IL-10 driven T cell exhaustion was found to be rescued by JAK/STAT inhibition. A comprehensive understanding of the cellular states and plasticity of lymphoid cells in GBM will aid towards successful immunotherapeutic approaches.

cancer biology↗

bioRxiv2019

Image-derived Models of Cell Organization Changes During Differentiation of PC12 Cells

Cellular differentiation is a complex process requiring the coordination of many cellular components. PC12 cells are a popular model system to study changes driving and accompanying neuronal differentiation. While significant attention has been paid to changes in transcriptional regulation and protein signaling, much less is known about the changes in cell organization that accompany PC12 differentiation. Fluorescence microscopy can provide extensive information about this, although photobleaching and phototoxicity frequently limit the ability to continuously observe changes in single cells over the many days that differentiation occurs. Here we describe a generative model of differentiation-associated changes in cell and nuclear shape and their relationship to mitochondrial distribution constructed from images of different cells at discrete time points. We show that our spherical harmonic-based model can accurately represent cell and nuclear shapes by measuring reconstruction errors. We then learn a regression model that relates cell and nuclear shape and mitochondrial distribution and observe that the predictive accuracy generally increases during differentiation. Most importantly, we propose a method, based on cell matching and linear interpolation in the shape space, to model the dynamics of cell differentiation using only static images. Without any prior knowledge, the method produces a realistic shape evolution process.\n\nAuthor Summary\n\nCellular differentiation is an important process that is challenging to study due to the number of organizational changes it includes and the different time scales over which it occurs. Fluorescent microscopy is widely used to study cell dynamics and differentiation, but photobleaching and phototoxicity often make it infeasible to continuously observe a single cell undergoing differentiation for several days. In this work, we described a method to model aspects of the dynamics of PC12 cell differentiation without continuous imaging. We constructed accurate representations of cell and nuclear shapes and quantified the relationships between shapes and mitochondrial distributions. We used these to construct a generative model and combined it with a matching process to infer likely sequences of the changes in single cells undergoing differentiation.

cell biology↗