Biology subjects

Snijder, B.

Publications and source records attributed to Snijder, B..

13 recordsLinked to original sources

bioRxiv2026

An RFX-driven ciliogenic cell state defines ex vivo FGFR-inhibitor sensitivity in colorectal cancer

Genomic stratification leaves most patients with colorectal cancer (CRC) without opportunities for targeted therapy. Seeking tumour state-linked drug sensitivities, we combined image-based ex vivo drug profiling with matched transcriptomics in 127 prospectively collected patient biopsies across CRC stages and molecular subtypes. Network-level integration identified a ciliogenic cell state defined by upregulation of cilia related genes with selective sensitivity to the FGFR inhibitor erdafitinib. This ciliogenic signature was associated with poor progression-free survival (hazard ratio 2.28; adjusted p=0.0098), even in early-stage colorectal cancer. Furthermore, knockdown of the transcriptional regulators RFX2 and RFX3, upstream of the ciliogenic cell state, attenuated erdafitinib sensitivity. Orthogonal bulk and single-cell analyses across normal, primary and metastatic tissues contextualised the ciliogenic programme along a transition from canonical epithelial states towards fetal and non-canonical tumour states, concomitant with Wnt-related remodelling, FGFR1/FGFR2 upregulation, and loss of intestinal epithelial identity. Together, these findings define a tumour-intrinsic ciliogenic cell state as a feature of CRC progression, revealing a patient-stratified repurposing opportunity for targeted therapy beyond the current CRC treatment paradigms.

cancer biology↗

bioRxiv2026

Clone-level multi-modal prediction of tumour drug response

Tumour heterogeneity presents a major challenge for precision oncology, as genetically and phenotypically distinct tumour clones may respond differently to therapy. To address this, we introduce scClone2DR, a probabilistic multi-modal framework that predicts drug responses at the level of individual tumour clones by integrating single-cell DNA and RNA sequencing with ex-vivo drug-screening data. In simulations, scClone2DR substantially outperforms alternatives in recovering true drug-effects and clonal sensitivities. Applied to 60 melanoma and 21 acute myeloid leukaemia patient samples, the method identifies heterogeneous clonal responses, yields biologically meaningful feature rankings, highlights clones that may be resistant to treatment, and improves the prediction of clinical outcomes compared to models ignoring clonal structure. These results demonstrate that modelling tumour evolution and clonal diversity is crucial for accurate drug-response prediction and provides a foundation for more effective, clone-aware precision oncology.

cancer biology↗

bioRxiv2025

Single-cell phenomics through integrated imaging and molecular profiling

Single-cell technologies such as transcriptomics, microscopy, and flow cytometry have revolutionized the study of cellular identity and function. While each of these technologies is powerful on its own, their full potential lies in their integration, enabling multimodal profiling of the same cell and revealing how distinct modalities influence one another. Here, we introduce IRIS (Interconnected Robotic Imaging and Single cell transcriptomics), a deterministic single-cell platform technology that seamlessly couples high-resolution microscopy with droplet-based single-cell RNA sequencing. IRIS enables precise cell positioning, multimode imaging across brightfield and fluorescent channels, and subsequent molecular capture from the same cell, directly linking high-resolution morphological features to matched transcriptomes. We validate IRIS by recovering cell cycle progression states and transcriptional programmes associated with canonical morphologies and demonstrate its discovery power by molecularly resolving two nuclear-ER architectures within naive CD8+ T cells, each defined by distinct gene expression profiles and functional markers. IRIS establishes an integrative single-cell phenomics framework, opening new avenues for dissecting how cellular form relates to molecular state and function.

immunology↗

bioRxiv2023

Enhancing anti-EGFRvIII CAR T cell therapy against glioblastoma with a paracrine SIRPγ-derived CD47 blocker

A major challenge for chimeric antigen receptor (CAR) T cell therapy against glioblastoma (GBM) is its immunosuppressive tumor microenvironment (TME), which is densely populated and supported by protumoral glioma-associated microglia and macrophages (GAMs). Targeting of CD47, a "dont-eat-me" signal overexpressed by tumor cells, disrupts the CD47-SIRP axis and induces GAM phagocytic function. However, antibody-mediated CD47 blockade monotherapy is associated with toxicity and low bioavailability in solid tumors. To overcome these limitations, we combined local CAR T cell therapy with paracrine GAM modulation for more effective elimination of GBM. To this end, we engineered a new CAR T cell against epidermal growth factor receptor variant III (EGFRvIII) that constitutively secretes a SIRP{gamma}-related protein (SGRP) with high affinity to CD47. Anti-EGFRvIII-SGRP CAR T cells eliminated EGFRvIII+ GBM in a dose-dependent manner in vitro and eradicated orthotopically xenografted EGFRvIII-mosaic GBM by locoregional application in vivo. This resulted in significant tumor-free long-term survival, followed by partial tumor control upon tumor re-challenge. The combination of anti-CD47 antibodies with anti-EGFRvIII CAR T cells failed to achieve a similar therapeutic effect, underscoring the importance of sustained paracrine GAM modulation. Multidimensional brain immunofluorescence microscopy and in-depth spectral flow cytometry on GBM-xenografted brains showed that anti-EGFRvIII-SGRP CAR T cells accelerated GBM clearance, increased CD68+ cell trafficking to tumor scar sites, and induced myeloid-mediated tumor cell uptake. Additionally, in a peripheral lymphoma mouse xenograft model, anti-CD19-SGRP CAR T cells had superior efficacy compared to conventional anti-CD19 CAR T cells. Validation on human GBM explants revealed that anti-EGFRvIII-SGRP CAR T cells had similar tumor-killing capacity to anti-EGFRvIII CAR monotherapy, but showed a slight improvement in maintenance of tumor-infiltrated CD14+ myeloid cells. Thus, local anti-EGFRvIII-SGRP CAR T cell therapy combines the potent antitumor effect of engineered T cells with the modulation of the surrounding innate immune TME, resulting in the additive elimination of bystander EGFRvIII- tumor cells in a manner that overcomes major mechanisms of CAR T cell therapy resistance, including tumor innate immune suppression and antigen escape.

cancer biology↗

bioRxiv2023

Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.

neuroscience↗

bioRxiv2023

Self-supervised vision transformers accurately decode cellular state heterogeneity

Characterising cellular phenotypic heterogeneity is essential to understand the relationship between the molecular and morphological determinants of cellular state. Here we report that publicly available self-supervised vision transformers (ss-ViTs) accurately elucidate phenotypic stem cell heterogeneity out-of-the-box. Moreover, we introduce scDINO, an adapted ss-ViT trained on five-channel automated microscopy data, attaining excellent performance in delineating peripheral blood immune cell identity. Thus, ss-ViTs represent a leap forward in the unsupervised analysis of phenotypic heterogeneity.

systems biology↗

bioRxiv2022

The Siglec-sialic acid-axis is a target for innate immunotherapy of glioblastoma

Glioblastoma (GBM) is the most aggressive form of primary brain tumor, for which effective therapies are urgently needed. Cancer cells are capable of evading clearance by phagocytes such as microglia and monocyte-derived cells through engaging tolerogenic programs. Here, we found that high level of Siglec-9 expression correlates with reduced survival in GBM patients. Using conditional knockouts of Siglec-E, the murine functional homologue of Siglec-9, together with single-cell RNA sequencing, we demonstrated significant pro-phagocytosis effects in microglia and monocyte-derived cells in the absence of Siglec-E. Loss of Siglec-E on monocyte-derived cells enhances antigen cross-presentation and production of pro-inflammatory cytokines, resulting in more efficient T cell priming. This bridging of innate and adaptive responses delays tumor growth and results in prolonged survival. Further, we showed synergistic activity of Siglec-E blockade in combinatorial immunotherapies and demonstrate its translational potential against GBM.

cancer biology↗

bioRxiv2022

ROS induction as a strategy to target persister cancer cells with low metabolic activity in NRAS mutated melanoma

Metabolic reprogramming is an emerging hallmark of resistance to cancer therapy but may generate vulnerabilities that can be targeted with small molecules. Multi-omics analysis revealed that NRAS-mutated melanoma cells with a mesenchymal transcriptional profile adopt a quiescent metabolic program to resist cellular stress response induced by MEK-inhibitor resistance. However, as a result of elevated baseline ROS levels, these cells become highly sensitive to ROS induction. In vivo xenograft experiments and single-cell RNA sequencing demonstrated that intra-tumor heterogeneity requires the combination of a ROS-inducer and a MEK-inhibitor to target both tumor growth and metastasis. By ex vivo pharmacoscopy of 62 human metastatic melanomas, we found that MEK-inhibitor resistant tumors significantly benefitted from the combination therapy. Finally, we profiled 486 cancer cell lines and revealed that oxidative stress responses and translational suppression are biomarkers of ROS-inducer sensitivity, independent of cancer indication. These findings link transcriptional plasticity to a metabolic phenotype that can be inhibited by ROS-inducers in melanoma and other cancers. Statement of SignificanceTargeted-therapy resistance in cancer arises from genetic selection and both transcriptional and metabolic adaptation. We show that metabolic reprogramming sensitizes resistant cells to ROS-induction in combination with pathway inhibitors. Predictive biomarkers of metabolic sensitivity to ROS-inducing agents were identified in many cancer entities, highlighting the generalizability of this treatment approach. Graphical summary O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

cancer biology↗

bioRxiv2022

Targeting tumour-intrinsic neural vulnerabilities of glioblastoma

Glioblastoma is the most common yet deadliest primary brain cancer1. The neural behavior of glioblastoma, including the formation of synaptic circuitry and tumour microtubes, is increasingly understood to be pivotal for disease manifestation2-9. Nonetheless, the few approved treatments for glioblastoma target its oncological nature, while its neural vulnerabilities remain incompletely mapped and clinically unexploited. Here, we systematically survey the neural molecular dependencies and cellular heterogeneity across glioblastoma patients and diverse model systems. In 27 surgical patient samples, we identify cancer cell morphologies indicative of poor prognosis, and discover repurposable neuroactive drugs with anti-glioblastoma efficacy by image-based drug screening. Glioblastoma cells exhibit functional dependencies on highly expressed neuroactive drug targets, while interpretable molecular machine learning (COSTAR) reveals their downstream convergence on AP-1-driven tumour suppression. This drug-target connectivity signature is confirmed by accurate in silico drug screening on >1 million compounds, as well as by multi-omic profiling of glioblastoma drug responses. Thus, Ca2+-driven AP-1 pathway induction represents a tumour-intrinsic vulnerability at the intersection of oncogenesis and neural activity-dependent signaling. Opportunities for clinical translation of this neural vulnerability are epitomized by the antidepressant Vortioxetine synergizing with current standard of care treatments in vivo. Together, the results presented here provide a mechanistic foundation and conceptual framework for the treatment of glioblastoma based on its neural origins.

cancer biology↗

bioRxiv2021

Multiplexed high-throughput immune cell imaging reveals molecular health-associated phenotypes

Phenotypic plasticity is essential to the immune system, yet the factors that shape it are not fully understood. Here, we comprehensively analyze immune cell phenotypes including morphology across human cohorts by single-round multiplexed immunofluorescence, automated microscopy, and deep learning. Using the uncertainty of convolutional neural networks to cluster the phenotypes of 8 distinct immune cell subsets, we find that the resulting maps are influenced by donor age, gender, and blood pressure, revealing distinct polarization and activation-associated phenotypes across immune cell classes. We further associate T-cell morphology to transcriptional state based on their joint donor variability, and validate an inflammation-associated polarized T-cell morphology, and an age-associated loss of mitochondria in CD4+ T-cells. Taken together, we show that immune cell phenotypes reflect both molecular and personal health information, opening new perspectives into the deep immune phenotyping of individual people in health and disease.

systems biology↗

bioRxiv2021

Epithelial-mesenchymal transition is the main driver of intrinsic metabolism in cancer cell lines

A fundamental feature of cancer cells is genomic heterogeneity. It is a main driver of phenotypic differences, including the response to drugs, and therefore a key factor in therapy selection. Motivated by the increasing role attributed to metabolic reprogramming in tumor development, we wondered how genomic heterogeneity affects metabolic phenotype. To this end, we profiled the intracellular metabolome of 180 cancer cell lines grown in similar conditions to exclude environmental factors. For each cell line, we estimate activity for 49 pathways across the whole metabolic network. Upon clustering of activity data, we found a convergence into only two major metabolic types. These were further characterized by 13C-flux analysis, lipidomics, and analysis of sensitivity to perturbations. These experiments revealed differences in lipid, mitochondrial, and carbohydrate metabolism between the two major types. Finally, a thorough integration of our metabolic data with multiple omics data revealed a strong association with markers of epithelial-mesenchymal transition (EMT). Our analysis indicates that in absence of variations imposed by the microenvironment, the metabolism of cancer cell lines falls into only two major classes despite genetic heterogeneity.

systems biology↗

bioRxiv2020

Light-mediated discovery of surfaceome nanoscale organization and intercellular receptor interaction networks

Delineating the molecular nanoscale organization of the surfaceome is pre-requisite for understanding cellular signaling. Technologies for mapping the spatial relationships of cell surface receptors and their extracellular signaling synapses would open up theranostic opportunities and the possibility to engineer extracellular signaling. Here, we developed an optoproteomic technology termed LUX-MS that exploits singlet oxygen generators (SOG) for the light-triggered identification of acute protein interactions on living cells. Using SOG-coupled antibodies, small molecule-drugs, biologics and intact viral particles, we show that not only ligand-receptor interactions can be decoded across organisms, but also the surfaceome receptor nanoscale organization ligands engage in with direct implications for drug action. Furthermore, investigation of functional immunosynapses revealed that intercellular signaling inbetween APCs and CD8+ T cells can be mapped now providing insights into T cell activation with spatiotemporal resolution. LUX-MS based decoding of surfaceome signaling architectures provides unprecedented molecular insights for the rational development of theranostic strategies.

systems biology↗

bioRxiv2019

Critical Nodes of Virus-Host Interaction Revealed Through an Integrated Network Analysis

Viruses are one of the major causes of various acute and chronic infectious diseases and thus a major contributor to the global burden of disease. Several studies have shown how viruses have evolved to hijack basic cellular pathways and evade innate immune response by modulating key host factors and signalling pathways. A collective view of these multiple studies could advance our understanding of viral evasion mechanisms and provide new therapeutic perspectives for the treatment of viral diseases. Here, we performed an integrative meta-analysis to elucidate the 17 different host-virus interactomes. Network and bioinformatics analyses showed how viruses with small genomes efficiently achieve the maximal effect by targeting multifunctional and highly connected host proteins with a high occurrence of disordered regions. We also identified the core cellular process subnetworks that are targeted by all the viruses. Integration with functional RNA interference (RNAi) datasets showed that a large proportion of the targets are required for viral replication. Furthermore, we performed an interactome-informed drug re-purposing screen and identified novel activities for broad-spectrum antiviral agents against hepatitis C virus and human metapneumovirus. Altogether, these orthogonal datasets could serve as a platform for hypothesis generation and follow-up studies to broaden our understanding of the viral evasion landscape.

immunology↗