Biology subjects

Van Booven, D.

Publications and source records attributed to Van Booven, D..

9 recordsLinked to original sources

bioRxiv2026

Divergent regulation of STING-mediated innate immune responses by CBP and p300

Dysregulation of cGAS-STING pathway contributes to various disorders, including autoimmunity, infectious diseases and cancer. Transcription factors, particularly IRF3 which presumably recruits CBP/p300 as transcription coactivators, drive innate immune responses to STING activation. Here we show that CBP/p300 inhibitors (p300i) boost, not repress as expected, the cGAMP-induced transcription of innate immune genes. Mechanistically, p300i and a CBP/p300 degrader markedly enhance the cGAMP-induced IRF3 phosphorylation and slightly increase NF-{kappa}B activation. Furthermore, cGAMP stimulation increases the presence of p300, not CBP, in the cytoplasm to interrupt interactions between TBK1 and IRF3. Conversely, p300i enhances TBK1-IRF3 interactions, resulting in higher IRF3 phosphorylation. After STING activation, CBP, not p300, is recruited to chromatin along with IRF3 and is coupled with H3K27ac upregulation. At later stages of STING activation, nearly all CBP and p300 are detached from chromatin, which is associated with global histone deacetylation, IRF3 chromatin eviction, and the termination of IRF3-driven transcription programs. p300i robustly enhances IRF3 chromatin engagement which consequently amplifies type 1 interferon responses to STING activation. Together, these findings suggest that CBP, not p300, acts as a transcription coactivator in the nucleus. In contrast, p300, not CBP, is a suppressor of STING signaling in the cytoplasm.

immunology↗

bioRxiv2024

African origin haplotype protective for Alzheimer's disease in APOEϵ4 carriers: exploring potential mechanisms

APOE{varepsilon}4 is the strongest genetic risk factor for Alzheimers disease (AD) with approximately 50% of AD patients carrying at least one APOE{varepsilon}4 allele. Our group identified a protective interaction between APOE{varepsilon}4 with the African-specific A allele of rs10423769, which reduces the AD risk effect of APOE{varepsilon}4 homozygotes by approximately 75%. The protective variant lies 2Mb from APOE in a region of segmental duplications (SD) of chromosome 19 containing a cluster of pregnancy specific beta-1 glycoprotein genes (PSGs) and a long non-coding RNA. Using both short and long read sequencing, we demonstrate that rs10423769_A allele lies within a unique single haplotype inside this region of segmental duplication. We identified the protective haplotype in all African ancestry populations studied, including both West and East Africans, suggesting the variant has an old origin. Long-read sequencing identified both structural and DNA methylation differences between the protective rs10423769_A allele and non-protective haplotypes. An expanded variable number tandem repeat (VNTR) containing multiple MEF2 family transcription factor binding motifs was found associated with the protective haplotype (p-value = 2.9e-10). These findings provide novel insights into the mechanisms of this African-origin protective variant for AD in APOE{varepsilon}4 carriers and supports the importance of including all ancestries in AD research.

genetics↗

bioRxiv2024

Synthetic Genitourinary Image Synthesis via Generative Adversarial Networks: Enhancing AI Diagnostic Precision

In the realm of computational pathology, the scarcity and restricted diversity of genitourinary (GU) tissue datasets pose significant challenges for training robust diagnostic models. This study explores the potential of Generative Adversarial Networks (GANs) to mitigate these limitations by generating high-quality synthetic images of rare or underrepresented GU tissues. We hypothesized that augmenting the training data of computational pathology models with these GAN-generated images, validated through pathologist evaluation and quantitative similarity measures, would significantly enhance model performance in tasks such as tissue classification, segmentation, and disease detection. To test this hypothesis, we employed a GAN model to produce synthetic images of eight different GU tissues. The quality of these images was rigorously assessed using a Relative Inception Score (RIS) of 17.2 {+/-} 0.15 and a Frechet Inception Distance (FID) that stabilized at 120, metrics that reflect the visual and statistical fidelity of the generated images to real histopathological images. Additionally, the synthetic images received an 80% approval rating from board-certified pathologists, further validating their realism and diagnostic utility. We used an alternative Spatial Heterogeneous Recurrence Quantification Analysis (SHRQA) to assess quality in prostate tissue. This allowed us to make a comparison between original and synthetic data in the context of features, which were further validated by the pathologists evaluation. Future work will focus on implementing a deep learning model to evaluate the performance of the augmented datasets in tasks such as tissue classification, segmentation, and disease detection. This will provide a more comprehensive understanding of the utility of GAN-generated synthetic images in enhancing computational pathology workflows. This study not only confirms the feasibility of using GANs for data augmentation in medical image analysis but also highlights the critical role of synthetic data in addressing the challenges of dataset scarcity and imbalance. Future work will focus on refining the generative models to produce even more diverse and complex tissue representations, potentially transforming the landscape of medical diagnostics with AI-driven solutions. CONSENT FOR PUBLICATIONAll authors have provided their consent for publication.

bioengineering↗

bioRxiv2022

Targeting long non-coding RNA NUDT6 enhances smooth muscle cell survival and limits vascular disease progression

Long non-coding RNAs (lncRNAs) orchestrate various biological processes and regulate the development of cardiovascular diseases. Their potential therapeutic benefit to tackle disease progression has recently been extensively explored. Our study investigates the role of lncRNA Nudix Hydrolase 6 (NUDT6) and its antisense target Fibroblast Growth Factor 2 (FGF2) in two vascular pathologies: abdominal aortic aneurysms (AAA) and carotid artery disease. Using tissue samples from both diseases, we detected a substantial increase of NUDT6, whereas FGF2 was downregulated. Targeting Nudt6 in vivo with antisense oligonucleotides in three murine and one porcine animal models of carotid artery disease and AAA limited disease progression. Restoration of FGF2 upon Nudt6 knockdown improved vessel wall morphology and fibrous cap stability. Overexpression of NUDT6 in vitro impaired smooth muscle cell (SMC) migration, while limiting their proliferation and augmenting apoptosis. By employing RNA pulldown followed by mass spectrometry as well as RNA immunoprecipitation, we identified Cysteine and Glycine Rich Protein 1 (CSRP1) as another direct NUDT6 interaction partner, regulating cell motility and SMC differentiation. Overall, the present study identifies NUDT6 as a well-conserved antisense transcript of FGF2. NUDT6 silencing triggers SMC survival and migration and could serve as a novel RNA-based therapeutic strategy in vascular diseases.

molecular biology↗

bioRxiv2022

S-nitrosoglutathione Inhibits the Growth of Androgen-Receptor Dependent and Castration Resistant Prostate Cancer by Modulating FOXM1 Signaling

Castration resistant prostate cancer (CRPC) is an advanced form of prostate cancer associated with loss of androgen receptor activity and resistance to AR-targeted therapies. CRPC is often associated with higher metastasis, invasion, and proliferation. Thus, theres a strong need for additional molecular markers in CRPC, and therapies that target them directly. Transcriptomic profiling of prostate cancer patients revealed an upregulated signature specific to high-grade tumors in cell cycle progression, E2F targets, G2M checkpoint, DNA repair, Aurora Kinase B, and FOXM1 pathway. Validation in a separate cohort of neuroendocrine prostate cancer patients, the most resistant and invasive form of CRPC which lacks AR expression, showed CCP signature as a dominant driver gene set for NEPC. Moreover, high expression of mRNA targets in each of these pathways is associated with poor overall survival in NEPC patients. Gene set variation analysis revealed a strong inverse correlation between AR signaling and CCP.31, set of 31 markers associated with high proliferation, and a positive correlation between CCP.31 and NEPC signature. FOXM1, a prioritized candidate in CCP is shown to be upregulated in CRPC cell lines and human clinical sections of Gleason 9 patients. GSNO, a nitric oxide donor, known for its inhibitory effect on cell proliferation and an effective inhibitor of cell cycle checkpoints, was able to reverse CCP signature both in-vitro and in-vivo. GSNO exhibits a dependence on AR signaling in-vitro by showing mild effect on CRPC clones, but successfully inhibits tumor growth of AR-null CRPC xenografts. FOXM1 is also targeted by GSNO in-vivo and in-vitro models of both CRPC and AD prostate cancer. This establishes an important link between androgen receptor status in prostate cancer and proposes nitric oxide donors as therapeutic intervention. GSNO is effective against AR-null castration resistant prostate cancer. SignificanceNitric oxide donor, S-glutathione-transferase inhibits tumor growth of castration resistant prostate cancer, regardless of androgen receptor expression status by targeting FOXM1, a critical regulator of cell cycle progression. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

cancer biology↗

bioRxiv2022

Generative Adversarial Networks Can Create High Quality Artificial Prostate Cancer Magnetic Resonance Images

PurposeRecent integration of open-source data to machine learning models, especially in the medical field, has opened new doors to study disease progression and/or regression. However, the limitation of using medical data for machine learning approaches is the specificity of data to a particular medical condition. In this context, most recent technologies like generative adversarial networks (GAN) could be used to generate high quality synthetic data that preserves the clinical variability. Materials and MethodsIn this study, we used 139 T2-weighted prostate magnetic resonant images (MRI) from various sources as training data for Single Natural Image GAN (SinGAN), to make a generative model. A deep learning semantic segmentation pipeline trained the model to segment the prostate boundary on 2D MRI slices. Synthetic images with a high-level segmentation boundary of the prostate were filtered and used in the quality control assessment by participating scientists with varying degree of experience (more than 10 years, 1 year, or no experience) to work with MRI images. ResultsThe most experienced participating group correctly identified conventional vs synthetic images with 67% accuracy, the group with 1 year of experience correctly identified the images with 58% accuracy, and group with no prior experience reached 50% accuracy. Nearly half (47%) of the synthetic images were mistakenly evaluated as conventional images. Interestingly, a blinded quality assessment by a board-certified radiologist to differentiate conventional and synthetic images was not significantly different in context of the mean quality of synthetic and conventional images. ConclusionsThis study shows promise that high quality synthetic images from MRI can be generated using GAN. Such an AI model may contribute significantly to various clinical applications which involves supervised machine learning approaches.

bioinformatics↗

bioRxiv2022

Nitric oxide S-nitrosylates CSF1R to augment the action 1 of CSF1R inhibition against castration resistant prostate cancer

During progression of prostate cancer, sustained oxidative overload in cancer cells potentiates the overall tumor microenvironment (TME). Targeting the TME using colony-stimulating factor 1 receptor (CSF1R) inhibition is a promising therapy for castration-resistant prostate cancer (CRPC). However, the therapeutic response to sustained CSF1R blockade therapy (CSF1Ri) is limited as a monotherapy. We postulated that one of the causative agents for reduced efficacy of CSF1Ri and increased oxidation in CRPC is endothelial nitric oxide syntheses (eNOS). Results showed that in high grade PCa human specimens, eNOS is positively correlated with CSF1-CSF1R signaling and remains in an un-coupled state. The uncoupling disables eNOS to generate sufficient Nitric oxide (NO) that are required for inducing effective S-nitrosylation of CSF1R molecule at specific cysteine sites (Cys 224, Cys 278 and Cys 830). Importantly, we found that S-nitrosylation of CSF1R molecule at Cys 224, Cys 278 and Cys 830 sites is necessary for effective inhibition of tumor promoting cytokines (which are downstream of CSF1-CSF1R signaling) by CSF1R blockade. In this context, we studied if exogenous NO treatment could rescue the side effects of eNOS uncoupling. Results showed that exogenous NO treatment (using S-nitrosoglutathione (GSNO)) is effective in not only inducing S-Nitrosylation of CSF1R molecule, but it helps in rescuing the excess oxidation in tumor regions, reducing overall tumor burden, suppresses the tumor promoting cytokines which are ineffectively suppressed by CSF1R blockade. Together these results postulated that NO therapy could act as an effective combinatorial partner with CSF1R blockade against CRPC. In this context, results demonstrated that exogenous NO treatment successfully augment the anti-tumor ability of CSF1Ri in murine models of CRPC. Importantly, the overall tumor reduction was most effective in NO-CSF1Ri therapy compared to NO or CSF1Ri mono therapies. Moreover, Immunophenotyping of tumor grafts showed that the NO-CSF1Ri combination significantly decreased intratumoral percentage of anti-inflammatory macrophages, myeloid derived progenitor cells and increased the percentage of pro-inflammatory macrophages, cytotoxic T lymphocytes, and effector T cells respectively. Together, our study suggests that the NO-CSF1Ri combination has the potential to act as a therapeutic agent that restore control over TME and improve the outcomes of PCa patients.

cancer biology↗

bioRxiv2021

Converging evidence for differential regulatory control of APOEε4 on African versus European haplotypes

INTRODUCTIONThe difference in APOE{varepsilon}4 risk for Alzheimer disease (AD) between different populations is associated with APOE{varepsilon}4 local ancestry (LA). We examined LA SNPs with significant frequency differences between African and European/Japanese APOE{varepsilon}4 haplotypes for areas of differential regulation. METHODSWe performed two enhancer Massively Parallel Reporter Assay (MPRA) approaches, supplemented with single fragment reporter assays. We utilized Capture C analyses to support interactions with the APOE promoter. RESULTSThe TOMM40 intron 2 and 3 region showed increased enhancer activity in the European/Japanese versus African LA haplotypes in astrocytes and microglia. This region overlaps with APOE promoter interactions as assessed by Capture C analysis. Single variant analyses pinpoints rs2075650/rs157581, and rs59007384 as functionally different on these haplotypes. DISCUSSIONBoth differential regulatory function and Capture C data support an intronic region in TOMM40 as contributing to the differential APOE expression between African and European/Japanese LA.

genomics↗

bioRxiv2016

geneXtendeR: R/Bioconductor package for functional annotation of histone modification ChIP-seq data in a 3D genome world

MotivationDifferent ChIP-seq peak callers often produce different output results from the same input. Since different peak callers are known to produce differentially enriched peaks with a large variance in peak length distribution and total peak count, accurately annotating peak lists with their nearest genes can be an arduous process. Functional genomic annotation of histone modification ChIP-seq data can be a particularly challenging task, as chromatin marks that have inherently broad peaks with a diffuse range of signal enrichment (e.g., H3K9me1, H3K27me3) differ significantly from narrow peaks that exhibit a compact and localized enrichment pattern (e.g., H3K4me3, H3K9ac). In addition, varying degrees of tissue-dependent broadness of an epigenetic mark can make it difficult to accurately and reliably link sequencing data to biological function. Thus, there exists an unmet need to develop a software program that can precisely tailor the computational analysis of a ChIP-seq dataset to the specific peak coordinates of the data and its surrounding genomic features.\n\nResultsgeneXtendeR optimizes the functional annotation of ChIP-seq peaks by exploring relative differences in annotating ChIP-seq peak sets to variable-length gene bodies. In contrast to prior techniques, geneXtendeR considers peak annotations beyond just the closest gene, allowing users to investigate peak summary statistics for the first-closest gene, second-closest gene, ..., nth-closest gene whilst ranking the output according to biologically relevant events and iteratively comparing the fidelity of peak-to-gene overlap across a user-defined range of upstream and downstream extensions on the original boundaries of each genes coordinates. We tested geneXtendeR on 547 human transcription factor ChIP-seq ENCODE datasets and 198 human histone modification ChIP-seq ENCODE datasets, providing the analysis results as case studies.\n\nAvailabilityThe geneXtendeR R/Bioconductor package (including detailed introductory vignettes) is available under the GPL-3 Open Source license and is freely available to download from Bioconductor at: https://bioconductor.org/packages/geneXtendeR/\n\nAuthor summarygeneXtendeR makes functional annotation of ChIP-seq data more robust and precise, regardless of peak variability attributable to parameter tuning or peak caller algorithmic differences. Since different ChIP-seq peak callers produce differentially enriched peaks with large variance in peak length distribution and total peak count, annotating peak lists with their nearest genes can often be a noisy process where an adjacent second or third-closest gene may constitute a more viable biological candidate, e.g., during cases of linked genes that are located close to each other. As such, the goal of geneXtendeR is to robustly link differentially enriched peaks with their respective genes, thereby aiding experimental follow-up and validation in designing primers for a set of prospective gene candidates during qPCR.

bioinformatics↗