Biology subjects

Wojnicki, K.

Publications and source records attributed to Wojnicki, K..

5 recordsLinked to original sources

bioRxiv2024

Integrin blocking peptide reverses immunosuppression in experimental gliomas and improves anti-PD-1 therapy outcome

Immune checkpoint inhibitors (ICI) presented clinical benefits in many cancer patients but invariably fail in glioblastoma (GBM), the most common and deadly primary brain tumor. Lack of ICI efficacy in GBM is attributed to the accumulation of immunosuppressive myeloid cells that create the "cold" tumor microenvironment (TME) impeding infiltration and activation of effector T cells. We developed a designer RGD peptide that hindered glioma-instigated, integrin-mediated pro-tumoral reprogramming of myeloid cells and blocked microglia-dependent invasion of human and mouse glioma cells in co-cultures in vitro. Intratumorally-delivered RGD alone did not reduce glioma growth in syngeneic mice but prevented the emergence of immunosuppressive myeloid cells and led to peritumoral blood vessels normalization. Furthermore, combining RGD with immunotherapy using PD-1 blockade reduced tumor growth, led to upsurge of proliferating, interferon-{gamma} producing CD8+T cells and depleted regulatory T cells. Transcriptomic profiles of myeloid cells were altered by the combined treatment, consistently with the restored "hot" inflammatory TME and boosted immunotherapy responses. RGD modified the phenotypes of myeloid cells in human gliomas in nude mice. Thus, combining the integrin blockade with ICI reinvigorates antitumor immunity and paves the way to improve immunotherapy outcomes in GBM.

cancer biology↗

bioRxiv2023

Deep Learning Glioma Grading with the Tumor Microenvironment Analysis Protocol for A Comprehensive Learning, Discovering, and Quantifying Microenvironmental Features

Gliomas are primary brain tumors that arise from neural stem cells or glial precursors. Diagnosis of glioma is based on histological evaluation of pathological cell features and molecular markers. Gliomas are infiltrated by myeloid cells that accumulate preferentially in malignant tumors and their abundance inversely correlates with survival, which is of interest for cancer immunotherapies. To avoid time-consuming and laborious manual examination of the images, a deep learning approach for automatic multiclass classification of tumor grades was proposed. Importantly, as an alternative way of investigating characteristics of brain tumor grades, we implemented a protocol for learning, discovering, and quantifying tumor microenvironment elements on our glioma dataset. Using only single-stained biopsies we derived characteristic differentiating tumor microenvironment phenotypic neighborhoods. A challenge of the study was given by a small sample size of human leukocyte antigen stained on glioma tissue microarrays dataset - 203 images from 5 classes - and imbalanced data distribution. This has been addressed by image augmentation of the underrepresented classes. For this glioma multiclass classification task, a residual neural network architecture has been adapted. On the validation set the average accuracy was 0.72 when the model was trained from scratch, and 0.85 with the pre-trained model. Moreover, the tumor microenvironment analysis suggested a relevant role of the myeloid cells and their accumulation to characterize glioma grades. This promising approach can be used as an additional diagnostic tool to improve assessment during intra-operative examination or sub-typing tissues for treatment selection, despite the challenges caused by the difficult dataset. We present here the distributions and visualizations of extracted tumor inter-dependencies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/544739v2_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@a85f48org.highwire.dtl.DTLVardef@7a49forg.highwire.dtl.DTLVardef@1c8df75org.highwire.dtl.DTLVardef@c6bad7_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIResearch highlight 1: We demonstrate that the ResNet-18 architecture with simple data augmentation trained in 10-fold cross-validation performs the multiclass classification relatively well even with a small imbalanced dataset with a high degree of similarities between classes. C_LIO_LIResearch highlight 2: After supervised subtyping of the tumor, we investigated the usefulness of the protocol for discovery and learning tumor microenvironment elements for the same task. The protocol designed for deriving new biomarkers based on multiplex stained histological samples proved the ability to detect features characteristic of malignant tumors based only on single target stained tissue microarrays. We propose further studies on this topic can help in formulating specific criteria for improvements in diagnosis of gliomas, allowing to avoid the necessity of conducting advanced histopathological analysis or complementing genetic testing of tumor samples. C_LI

bioinformatics↗

bioRxiv2023

H2A.Z histone variants facilitate HDACi-dependent removal of H3.3K27M mutant protein in paediatric high-grade glioma cells

Diffuse intrinsic pontine gliomas (DIPG) are deadly paediatric brain tumours, non-resectable due to brainstem localisation and diffusive growth. Patients with DIPG have a dismal prognosis of 9-12 months of survival with no effective therapy. Over 80% of DIPGs harbour a mutation in histone 3 (H3.3 or H3.1) resulting in a lysine to methionine substitution (H3K27M). H3K27M causes global epigenetic alterations (a loss of H3K27 trimethylation and an increase in H3K27 acetylation) resulting in aberrant gene expression. To date, no therapeutic strategy exists to suppress the levels of oncogenic H3K27M. We show that pan-HDAC inhibitors (HDACi) lead to the temporary but significant reduction in the H3.3K27M protein (up to 80%) in multiple glioma cell lines expressing the H3.3K27M histone variant, without changes in the H3F3A mRNA expression. The H3.3K27M occupancy at the chromatin is greatly reduced upon HDACi (SB939) treatment, as shown by ChIPseq analysis. H3.3K27M loss is most striking at SB939-upregulated genes suggesting the role in repression of these genes. In addition, genes previously reported as H3K27M-dependent become downregulated in response to SB939 treatment. We discover that the SB939-mediated loss of H3.3K27M is partially blocked by a lysosomal inhibitor, chloroquine. Moreover, the loss of H3.3K27M is facilitated by co-occurrence of H2A.Z, as evidenced by the knock-down of H2A.Z histone isoforms. ChIPseq analysis confirms the occupancy of H3.3K27M and H2A.Z at the same SB939-inducible genes. Altogether, we provide new insight into disease-specific mechanism of HDAC inhibition and demonstrate pharmacological modulation of the oncogenic H3.3K27M protein levels. These findings open a new possibility to directly target the H3.3K27M oncohistone, which may be exploited in future therapies.

cancer biology↗

bioRxiv2022

Regulatory networks driving expression of genes critical for glioblastoma are controlled by the transcription factor c-Jun and the pre-existing epigenetic modifications.

BackgroundGlioblastoma (GBM, WHO grade IV) is an aggressive, primary brain tumor. Despite gross surgery and forceful radio- and chemotherapy, survival of GBM patients did not improve over decades. Several studies reported transcription deregulation in GBMs but regulatory mechanisms driving overexpression of GBM-specific genes remain largely unknown. Transcription in open chromatin regions is directed by transcription factors (TFs) that bind to specific motifs, recruit co-activators/repressors and the transcriptional machinery. Identification of GBM-related TFs-gene regulatory networks may reveal new and targetable mechanisms of gliomagenesis. ResultsWe predicted TFs-regulated networks in GBMs in silico and intersected them with putative TF binding sites identified in the accessible chromatin in human glioma cells and GBM patient samples. The Cancer Genome Atlas and Glioma Atlas datasets (DNA methylation, H3K27 acetylation, transcriptomic profiles) were explored to elucidate TFs-gene regulatory networks and effects of the epigenetic background. In contrast to the majority of tumors, c-Jun expression was higher in GBMs than in normal brain and c-Jun binding sites were found in multiple genes overexpressed in GBMs such as VIM, FOSL2 or UPP1. Binding of c-Jun to the VIM gene promoter is stronger in GBM cells than in cells derived from benign glioma as evidenced by gel shift and supershift assays. Regulatory regions of a majority of the c-Jun targets have distinct DNA methylation in GBMs suggesting the contribution of DNA methylation to the c-Jun-dependent regulation. ConclusionsWe identified distinct TFs-gene networks in GBMs compared to benign gliomas, a predominant role of c-Jun in controlling genes driving gliomagenesis and a modulatory role of DNA methylation.

cancer biology↗

bioRxiv2019

Single-cell RNA sequencing reveals functional heterogeneity and sex differences of glioma-associated brain macrophages

Microglia are resident myeloid cells in the central nervous system (CNS) that control homeostasis and protect CNS from damage and infections. Microglia and peripheral myeloid cells accumulate and adapt tumor supporting roles in human glioblastomas that show prevalence in men. Cell heterogeneity and functional phenotypes of myeloid subpopulations in gliomas remain elusive. Single-cell RNA sequencing (scRNA-seq) of CD11b+ myeloid cells in naive and GL261 glioma-bearing mice revealed distinct profiles of microglia, infiltrating monocytes/macrophages and CNS border-associated macrophages. We demonstrated an unforeseen molecular heterogeneity among myeloid cells in naive and glioma-bearing brains, validated selected marker proteins and showed distinct spatial distribution of identified subsets in experimental gliomas. We found higher expression of MHCII encoding genes in glioma-activated male microglia, which was corroborated in bulk and scRNA-seq data from human diffuse gliomas. Sex-specific gene expression in glioma-activated microglia may be relevant to sex differences in incidence and outcomes of glioma patients.

cancer biology↗