Biology subjects

Lijnzaad, P.

Publications and source records attributed to Lijnzaad, P..

10 recordsLinked to original sources

bioRxiv2025

Mechanisms of dexamethasone-induced bone toxicity in developing bone: a single-cell perspective

AbstractGlucocorticoids, such as dexamethasone, are essential for treating severe childhood conditions, including cancer, organ transplantation, and inflammatory disorders. However, their long-term use can impair bone development, posing risks to pediatric bone health, which is vital for lifelong skeletal integrity. A mechanistic insight on how glucocorticoids negatively impact bone could improve decision-making in patient care to improve the quality of life for pediatric cancer patients and survivors. In this study, we aimed to elucidate the molecular mechanisms underlying dexamethasone-induced bone toxicity in developing bones using single-cell transcriptomics. We treated skeletally immature C57BL/6JRj mice with dexamethasone for 28 days, and assessed the bone architecture with micro-computed tomography, and characterized bone and bone marrow cells from the femurs using single-cell RNA sequencing. Our findings revealed a marked reduction in osteoblast and chondrocyte cell populations and impaired function of pre-osteoblasts. Additionally, dexamethasone adversely affected B cell subsets, significantly depleting early B cell progenitors while allowing some further developed immature B cells to persist. These cellular changes were accompanied by reduced longitudinal bone growth, compromised bone architecture, and increased bone fragility at the highest doses of dexamethasone. Interestingly, unlike observations in adults, dexamethasone did not enhance osteoclast activity in our model. Overall, our study suggests that the adverse effects of dexamethasone on bone development are primarily due to its impact on osteoblastic, chondroblastic and B cell lineages, disrupting the critical signaling crosstalk between the cells necessary for bone development and hematopoiesis. Layman summaryGlucocorticoids, like dexamethasone, are vital for treating severe childhood illnesses but can harm bone development when used long-term. This study investigated how dexamethasone affects bone health in young mice. Using advanced techniques, we found that dexamethasone reduced key bone-building cells (osteoblasts and chondrocytes) and weakened their function. It also disrupted immune cell development in the bone marrow, especially early B cells. These changes led to weaker, more fragile bones without increasing bone breakdown, unlike in adults. The findings highlight the need to carefully balance treatment benefits and risks for children to protect their bone health and overall well-being.

cancer biology↗

bioRxiv2023

An engineered tumor organoid model reveals cellular identity and signaling trajectories underlying translocation RCC.

Translocation renal cell carcinoma (tRCC) is a rare, aggressive type of kidney cancer primarily occurring in children. They are genetically defined by translocations involving MiT/TFE gene family members, TFE3 or, in rare cases, TFEB. The biology underlying tRCC development remains poorly understood, partly due to the lack of representative experimental models. Here, we utilized human kidney organoids, or tubuloids, to engineer a tRCC model by expression of one of the most common MiT/TFE fusions, SFPQ-TFE3. Fusion expressing tubuloids adopt a tRCC-like phenotype and gene expression signature in vitro and grow as clear cell RCC upon xenotransplantation in mice. Genome-wide binding analysis reveals that SFPQ-TFE3 reprograms gene expression signatures by aberrant, gain-of-function genome-wide DNA binding. Combining these analyses with single-cell mRNA readouts reveals an epithelium-to-mesenchymal differentiation trajectory underlying tRCC transformation, potentially caused by deregulated Wnt signaling. Our study demonstrates that SFPQ-TFE3 expression is sufficient to transform kidney epithelial cells into tRCC and defines the trajectories underlying malignant transformation, thereby facilitating the development of new therapeutic interventions.

cancer biology↗

bioRxiv2023

Multi-dimensional profiling of hepatoblastomas and patient-derived tumor organoids uncovers tumor subpopulations with divergent WNT activation profiles and identifies pan-hepatoblastoma drug sensitivities

Hepatoblastoma, the most prevalent pediatric liver cancer, almost always carries a WNT-activating CTNNB1 mutation, yet exhibits notable molecular heterogeneity. To characterize this heterogeneity and identify novel targeted therapies, we performed comprehensive analysis of hepatoblastomas and tumor-derived organoids using single-cell RNA-seq, spatial transcriptomics, single-cell ATAC-seq and high throughput drug profiling. We identified two distinct tumor epithelial signatures: hepatic fetal-like and WNT-high embryonal-like signatures, displaying divergent WNT signaling patterns. The liver-specific WNT targets were enriched in the fetal-like group, while the embryonal-like group was enriched in canonical WNT target genes. Gene regulatory network analysis revealed enrichment of regulons related to hepatic function such as bile acid, lipid and xenobiotic metabolism in the fetal-like subgroup but not in the embryonal-like subgroup. In addition, the dichotomous expression pattern of the transcription factors HNF4A and LEF1 allowed for a clear distinction between the fetal- and embryonal-like tumors. We also performed high-throughput drug screening using patient-derived tumor organoids and identified sensitivity to multiple inhibitor classes, most notably HDAC inhibitors. Intriguingly, embryonal-like tumor organoids, but not fetal-like tumor organoids, were sensitive to FGFR inhibitor treatments, suggesting a dependency on FGFR signaling. In summary, our data uncover the molecular and drug sensitivity landscapes of hepatoblastoma and pave the way for the development of targeted therapies.

cancer biology↗

bioRxiv2022

Integrative analysis of neuroblastoma by single-cell RNA sequencing identifies the NECTIN2-TIGIT axis as a target for immunotherapy

Pediatric patients with high-risk neuroblastoma have poor survival rates and urgently need more effective treatment options with less side effects. As novel and improved immunotherapies may fill this need, we dissected the immunoregulatory interactions in neuroblastoma by single-cell RNA-sequencing of 25 tumors (10 pre- and 15 post-chemotherapy, including 5 pairs) to identify strategies for optimizing immunotherapy efficacy. Neuroblastomas were infiltrated by NK, T and B cells, and immunosuppressive myeloid populations. NK cells showed reduced cytotoxicity and T cells had a dysfunctional profile. Interaction analysis revealed a vast immunoregulatory network and identified NECTIN2-TIGIT as a crucial immune checkpoint. Combined blockade of TIGIT and PD-L1 significantly reduced neuroblastoma growth, with complete responses in vivo. Moreover, addition of TIGIT blockade to standard relapse treatment in a chemotherapy-resistant Th-ALKF1174L/MYCN 129/SvJ syngeneic model significantly improved survival. Concluding, our integrative analysis of neuroblastomas vast immunoregulatory network provides novel targets and a rationale for immunotherapeutic combination strategies.

cancer biology↗

bioRxiv2021

Cdk8 directly regulates glycolysis via phosphorylation of Gcr2

CDK8 encodes an evolutionarily conserved Mediator complex kinase subunit that functions in general and context-specific transcription regulation by phosphorylating core components of the transcription machinery and gene-specific transcription factors. To better understand the role Cdk8 in transcription regulation, we performed high-resolution gene expression time course analysis following nuclear depletion of Cdk8. Focusing on the earliest gene expression alterations revealed dysregulation of genes encoding glycolysis enzymes, suggesting a functional link to Gcr1 and Gcr2, key transcriptional activators of these genes. Consistently, we found that nuclear depletion of Cdk8 altered the mRNA levels of glycolysis genes as well as the promoter occupancy of Gcr2, but not Gcr1. Examination of the Gcr2 protein sequence revealed a putative Cdk8 phosphorylation site at serine 365, which we confirmed using in vitro and in vivo assays. Importantly, phospho-mutant GCR2 recapitulated the growth and gene expression defects of the GCR2 deletion mutant, effects not observed with a phospho mimetic mutant. As such, our work highlights Gcr2 as a new Cdk8 substrate, revealing that its phosphorylation is critical for the activation of genes encoding glycolysis enzymes.

molecular biology↗

bioRxiv2020

Tumor to normal single cell mRNA comparisons reveal a pan-neuroblastoma cancer cell

Neuroblastoma is an embryonal childhood cancer that arises from aberrant development of the neural crest, mostly within the fetal adrenal medulla. It is not established what developmental processes neuroblastoma cancer cells represent. Here, we sought to reveal the phenotype of neuroblastoma cancer cells by comparing cancer (n=16,591) with fetal adrenal single cell transcriptomes (n=57,972). Our principal finding was that the neuroblastoma cancer cell resembled fetal sympathoblasts, but no other fetal adrenal cell type. The sympathoblastic state was a universal feature of neuroblastoma cells, transcending cell cluster diversity, individual patients and clinical phenotypes. We substantiated our findings in 652 neuroblastoma bulk transcriptomes and by integrating canonical features of the neuroblastoma genome with transcriptional signals. Overall, our observations indicate that there exists a pan-neuroblastoma cancer cell state which may be an attractive target for novel therapeutic avenues.

cancer biology↗

bioRxiv2020

Genome-wide off-rates reveal how DNA binding dynamics shape transcription factor function

Protein-DNA interactions are dynamic and these dynamics are an important aspect of chromatin-associated processes such as transcription or replication. Due to a lack of methods to study on- and off-rates across entire genomes, protein-DNA interaction dynamics have not been studied extensively. Here we determine in vivo off-rates for the Saccharomyces cerevisiae chromatin organising factor Abf1, at 191 sites simultaneously across the yeast genome. Average Abf1 residence times span a wide-range, varying between 4.5 and 37 minutes. Sites with different off-rates are associated with different functional characteristics. This includes their transcriptional dependency on Abf1, nucleosome positioning and the size of the nucleosome-free region, as well as the ability to roadblock RNA polymerase II for termination. The results show how off-rates contribute to transcription factor function and that DIVORSEQ (Determining In Vivo Off-Rates by SEQuencing) is a meaningful way of investigating protein-DNA binding dynamics genome-wide.

molecular biology↗

bioRxiv2019

CHETAH: a selective, hierarchical cell type identification method for single-cell RNA sequencing

Cell type identification is essential for single-cell RNA sequencing (scRNA-seq) studies that are currently transforming the life sciences. CHETAH (CHaracterization of cEll Types Aided by Hierarchical clustering) is an accurate cell type identification algorithm that is rapid and selective, including the possibility of intermediate or unassigned categories. Evidence for assignment is based on a classification tree of previously available scRNA-seq reference data and includes a confidence score based on the variance in gene expression per cell type. For cell types represented in the reference data, CHETAHs accuracy is as good as existing methods. Its specificity is superior when cells of an unknown type are encountered, such as malignant cells in tumor samples which it pinpoints as intermediate or unassigned. Although designed for tumor samples in particular, the use of unassigned and intermediate types is also valuable in other exploratory studies. This is exemplified in pancreas datasets where CHETAH highlights cell populations not well represented in the reference dataset, including cells with profiles that lie on a continuum between that of acinar and ductal cell types. Having the possibility of unassigned and intermediate cell types is pivotal for preventing misclassification and can yield important biological information for previously unexplored tissues.

bioinformatics↗

bioRxiv2018

The ability of transcription factors to differentially regulate gene expression is a crucial component of the mechanism underlying inversion, a frequently observed genetic interaction pattern

Genetic interactions, a phenomenon whereby combinations of mutations lead to unexpected effects, reflect how cellular processes are wired and play an important role in complex genetic diseases. Understanding the molecular basis of genetic interactions is crucial for deciphering pathway organization as well as understanding the relationship between genetic variation and disease. Several putative molecular mechanisms have been linked to different genetic interaction types. However, differences in genetic interaction patterns and their underlying mechanisms have not yet been compared systematically between different functional gene classes. Here, differences in the occurrence and types of genetic interactions are compared for two classes, gene-specific transcription factors (GSTFs) and signaling genes (kinases and phosphatases). Genome-wide gene expression data for 63 single and double deletion mutants in bakers yeast reveals that the two most common genetic interaction patterns are buffering and inversion. Buffering is typically associated with redundancy and is well understood. In inversion, genes show opposite behavior in the double mutant compared to the corresponding single mutants. The underlying mechanism is poorly understood. Although both classes show buffering and inversion patterns, the prevalence of inversion is much stronger in GSTFs. To decipher potential mechanisms, a Petri Net modeling approach was employed, where genes are represented as nodes and relationships between genes as edges. This allowed over 9 million possible three and four node models to be exhaustively enumerated. The models show that a quantitative difference in interaction strength is a strict requirement for obtaining inversion. In addition, this difference is frequently accompanied with a second gene that shows buffering. Taken together, these results provide a mechanistic explanation for inversion. Furthermore, the ability of transcription factors to differentially regulate expression of their targets provides a likely explanation why inversion is more prevalent for GSTFs compared to kinases and phosphatases.\n\nAuthor SummaryThe relationship between genotype and phenotype is one of the major challenges in biology. While many previous studies have identified genes involved in complex genetic diseases, there is still a gap between genotype and phenotype. One of the difficulties in filling this gap has been attributed to genetic interactions. Large-scale studies have revealed that genetic interactions are widespread in model organisms such as bakers yeast. Several molecular mechanisms have been proposed for different genetic interaction types. However, differences in occurrence and underlying molecular mechanism of genetic interactions have not yet been compared between gene classes of different function. Here, we compared genetic interaction patterns identified using gene expression profiling for two classes of genes: gene specific transcription factors and signaling related genes. We modelled all possible molecular networks to unravel putative molecular differences underlying different genetic interaction patterns. Our study proposes a new mechanistic explanation for a certain genetic interaction pattern that is more strongly associated with transcription factors compared to signaling related genes. Overall, our findings and the computational methodologies implemented here can be valuable for understanding the molecular mechanisms underlying genetic interactions.

genetics↗

bioRxiv2018

Sharq, a versatile preprocessing and QC pipeline for Single Cell RNA-seq

Despite the meteoric rise of single cell RNA-seq, only a few preprocessing pipelines exist that are able to perform all steps from the original fastq files to a gene expression table ready for further analysis. Here we present Sharq, a versatile preprocessing pipeline designed to work with plate-based 3-end protocols that include Unique Molecular Identifiers (UMIs). Sharq performs stringent step-wise trimming of reads, assigns them to features according to a flexible hierarchical model, and uses the barcode and UMI information to avoid amplification biases and produce gene expression tables. Additionally, Sharq provides an extensive plate diagnostics report for quality control and troubleshooting, including that of spatial artefacts. The diagnostics report includes measures of the quality of the individual plate wells as well as a robust assessment which of them contain material from live cells. Collectively, the innovative approaches presented here provide a valuable tool for processing and quality control of single cell RNA-seq data.

bioinformatics↗