Biology subjects

Van den Eynden, J.

Publications and source records attributed to Van den Eynden, J..

13 recordsLinked to original sources

bioRxiv2026

Predicting subclonal TP53 mutations from tumor spatial transcriptomics data using a graph convolutional neural network

Spatial transcriptomics (ST) has revolutionized our understanding of tumor biology but inherently lacks information on the upstream somatic driver mutations. We developed a spatially-aware graph convolutional neural network (MuT-GCNN) that infers TP53 clones directly from ST data. MuT-GCNN was trained on virtual ST slides with clones simulated from a large collection of existing RNA and matched DNA sequencing data. The model is highly performant with precision and recall values exceeding 95% in most analysed cancer types. It is sensitive for single hit mutations and is primarily informed by the expression of p53 signalling genes in cancer cells. After demonstrating the potential of the model on publicly available squamous cell carcinoma (SCC) data, a direct validation was performed using ST and matched DNA sequencing from serial slices obtained from 4 cutaneous SCC samples. With the increasing availability of ST data and upcoming ST atlases, MuT-GCNN can unveil the location of (sub)clonal alterations in TP53, the most frequently mutated gene in human cancer.

cancer biology↗

bioRxiv2025

Deconvoluting fiber type proportions from human skeletal muscle transcriptomics and proteomics data using FibeRtypeR

Muscle fibers are the dominant, multinucleated cell type in skeletal muscle. In humans, they can be classified as slow (type 1) and fast (type 2) fibers, traditionally based on distinct properties of their contractile machinery. Slow and fast fibers are characterized by shared and specific cellular complexities that are pivotal for their adaptive capacity to exercise or role in metabolic disease progression. In this era of omics research, there is a critical need to accurately infer muscle fiber type proportions from bulk tissue omics datasets, as single-fiber approaches are not feasible in large-scale or retrospective studies. Here we present FibeRtypeR, an easy-to-use web application to accurately estimate fiber type proportions from bulk transcriptomics and proteomics datasets: https://muscleapps.ugent.be. FibeRtypeR exploits transcriptomics and proteomics profiles of 1000 fiber-typed individual human skeletal muscle fibers as a reference dataset and is validated against paired immunohistochemical fiber type determinations in 160 muscle biopsies. We show that FibeRtypeR can be applied to public datasets, illustrating the application potential across a wide range of biological contexts such as aging, disease and exercise training. This new freely accessible computational tool will prove valuable to the skeletal muscle research community. Key pointsO_LIBulk muscle omics datasets lack fiber type specific information C_LIO_LIOur new tool, FibeRtypeR, leverages in-house collected single-fiber profiles allowing for accurate fiber type inference C_LIO_LIFibeRtypeR is methodologically robust across omics technologies and workflows C_LIO_LIWe host FibeRtypeR as an intuitive open-access Shiny app, applicable to new and publicly available transcriptomics and proteomics datasets C_LI

physiology↗

bioRxiv2025

ALK/ATR combination therapy is effective in neuroblastoma mouse tumors driven by MYCN

Summary paragraphOne of the key features of high-risk neuroblastoma (NB) is MYCN-amplification. While MYCN is still regarded as therapeutically challenging despite intensive efforts to find targeting compounds, inhibitors against Anaplastic Lymphoma Kinase (ALK) are now being evaluated among ALK-driven NB patients with promising results. There is a pressing need to find alternative treatment regimens for ALK naive MYCN-amplified patients, as current regimes are accompanied by significant mortality and morbidity. Here we show that genetically removing Alk in the Th-MYCN-driven engineered NB mouse model (GEMM) resulted in decreased tumor penetrance, and survival of Th-MYCN homozygote GEMMs, suggesting that Alk activity contributes to aggressiv e neuroblastoma development in this model. Given the high levels of replication stress induced in Th-MYCN tumors, we employed inhibitors of Ataxia Telangiectasia Rad3 related (ATR), combining ATR and ALK inhibition in a 14-day treatment regime, and comparing with ATR inhibitor monotreatment. Th-MYCN tumor bearing mice that received ATRi/ALKi combination treatment exhibited significantly increased survival compared to ATRi alone, that was sustained over time. Together, our data highlight a potentially effective treatment option for the currently challenging category of MYCN-amplified NB patients lacking ALK mutations.

cancer biology↗

bioRxiv2025

Early initiation of small intestine neuroendocrine tumors

Small intestine neuroendocrine tumor (SI-NET) is normally diagnosed late in life and has several unusual properties, including low proliferation rate, low mutation burden, lack of driver mutations, and frequent multifocality in the form of polyclonal tumor clusters. This sets SI-NET aside from other adult cancers and raises questions about the timeline of initiation and progression. Here, we investigated the evolutionary history of multifocal and unifocal SI-NET using whole genome sequencing data, obtaining timing information on primary tumors, metastases and key genetic events. Despite the late onset, the results indicated that major genetic alterations and the establishment of advanced metastatic tumor cell clones can often be traced back to childhood or adolescence in SINET. This was validated by re-examination of archival CT/MR scans, allowing longitudinal tracking of individual tumors up to 12 years prior. Metastases were detected at a high degree of consistency in the historical imaging data and estimated growth rates suggested several additional decades of tumor expansion. Collectively, our data support that slow growth of advanced lesions over half a century or more may precede SI-NET diagnosis in late adulthood.

cancer biology↗

bioRxiv2024

Spatial transcriptomics exploration of the primary neuroblastoma microenvironment unveils novel paracrine interactions

High-risk neuroblastomas exhibit a high degree of intratumoral heterogeneity. Single-cell RNA sequencing has greatly improved our understanding of these tumors, but the method lacks cellular tissue context and spatial information about local signaling dynamics. To address this gap, we profiled untreated and chemotherapy-treated high-risk neuroblastomas from 2 patients using spatial transcriptomics. We confirmed the transcriptional and cellular heterogeneous nature of the neuroblastoma microenvironment and identified several unique spatial niches and patterns. In one of the treated tumors, a spatially constrained cluster of undifferentiated and 11p-gained cancer cells was identified, surrounded by a rim of macrophages. A signaling interaction between the chemokine CCL18 and its receptor PITPNM3 was predicted between these cells and we experimentally demonstrated that CCL18 increases neuroblastoma cell migration. In the other tumor, we identified a stromal cluster with high transcriptional similarity to the adrenal cortex. These adrenocortical-like cells expressed the ALK ligand ALKAL2 and were predicted to communicate with neighboring ALK expressing cancer cells. We demonstrated a unique developmental pattern of adrenal medulla-specific expression of ALK and adrenocortical-specific expression of ALKAL2, suggesting a role of these signaling interactions in neuroblastoma carcinogenesis.

cancer biology↗

bioRxiv2024

RUVBL1 and RUVBL2 are druggable MYCN regulators in neuroblastoma.

High-risk neuroblastoma is characterized by MYCN amplification and high MYCN or MYC gene expression. These patients have a poor prognosis and there is an urgent need for more effective drugs. While strategies to develop inhibitors that directly target the MYC proteins have remained largely unsuccessful, recent preclinical studies have identified ATR, a key protein of the DNA damage response, as a promising alternative therapeutic target. Here we identified a strong RUVBL1 and RUVBL2 signature in transcriptomics data derived from different MYCN-driven mice tumors treated with ATR inhibitors. The RUVBL proteins form a complex with ATPase activity that has broad cellular functions and we demonstrate that pharmacological inhibition of this protein complex results in a strong reduction of MYC signaling, cell cycle arrest, DNA damage and apoptosis. We confirmed the association with MYCN and identified the RUVBL genes as independent prognosticators in human primary neuroblastoma data.

cancer biology↗

bioRxiv2023

Preclinical exploration of the DNA Damage Response pathway using the interactive neuroblastoma cell line explorer CLEAN.

Neuroblastoma (NB) is the most common cancer in infancy with an urgent need for more efficient targeted therapies. The development of novel (combinatorial) treatment strategies relies on extensive explorations of signaling perturbations in neuroblastoma cell lines, using RNA-Seq or other high throughput technologies (e.g., phosphoproteomics). This typically requires dedicated bioinformatics support, which is not always available. Additionally, while data from published studies are highly valuable and raw data (e.g., fastq files) are nowadays released in public repositories, data processing is time-consuming and again difficult without bioinformatics support. To facilitate NB research, more user-friendly and immediately accessible platforms are needed to explore newly generated as well as existing high throughput data. To make this possible, we developed an interactive data centralization and visualization web application, called CLEAN (the Cell Line Explorer web Application of Neuroblastoma data; https://ccgg.ugent.be/shiny/clean/). By focusing on the regulation of the DNA damage response, a therapeutic target of major interest in neuroblastoma, we demonstrate how CLEAN can be used to gain novel mechanistic insights and identify putative drug targets in neuroblastoma.

cancer biology↗

bioRxiv2023

ALK signalling primes the DNA damage response sensitizing ALK-driven neuroblastoma to ATR inhibition

High-risk neuroblastoma (NB) is a significant clinical challenge. MYCN and ALK, which are often involved in high-risk NB, lead to increased replication stress in cancer cells, suggesting therapeutic strategies. We previously identified an ATR/ALK inhibitor (ATRi/ALKi) combination as such a strategy in two independent genetically modified mouse NB models. Here, we identify an underlying molecular mechanism, in which ALK signalling leads to phosphorylation of ATR and CHK1, supporting an effective DNA damage response. The importance of ALK inhibition is supported by mouse data, in which ATRi monotreatment resulted in a robust initial response, but subsequent relapse, in contrast to a 14-day ALKi/ATRi combination treatment that resulted in a robust and sustained response. Finally, we show that the remarkable response to the 14-day combined ATR/ALK inhibition protocol reflects a robust differentiation response, reprogramming tumour cells to a neuronal/Schwann cell lineage identity. Our results identify a unique ability of ATR inhibition to trigger neuroblastoma differentiation and underscore the importance of further exploring combined ALK/ATR inhibition in NB, particularly in high-risk patient groups with oncogene-induced replication stress.

cancer biology↗

bioRxiv2022

Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data

The Human Leukocyte Antigen (HLA) genes are a group of highly polymorphic genes that are located in the Major Histocompatibility Complex (MHC) region on chromosome 6. The HLA genotype affects the presentability of tumour antigens to the immune system. While knowledge of these genotypes is of utmost importance to study differences in immune responses between cancer patients, gold standard, PCR-derived genotypes are rarely available in large Next Generation Sequencing (NGS) datasets. Therefore, a variety of methods for in silico NGS-based HLA genotyping have been developed, bypassing the need to determine these genotypes with separate experiments. However, there is currently no consensus on the best performing tool. Here, we compiled a list of 13 HLA callers and evaluated their accuracy on three different datasets. Based on these results, best-practice guidelines were constructed, and consensus HLA allele predictions were made for DNA and RNA samples from The Cancer Genome Atlas (TCGA).

bioinformatics↗

bioRxiv2022

A clinically annotated post-mortem approach to study multi-organ somatic mutational clonality in histologically healthy tissues.

Recent research on histologically healthy human tissues identified omnipresent mutational microclones, driven by somatic mutations known to be responsible for carcinogenesis (e.g., in TP53 or NOTCH1). These new insights are fundamentally changing current tumour evolution models, with broad oncological implications. Most studies are based on surgical remnant tissues, which are not available for many organs and rarely in a pan-organ setting (multiple organs from the same individual). Here, we describe an approach based on clinically annotated post-mortem tissues, derived from whole-body donors that are routinely used for educational purposes at human anatomy units. We validated this post-mortem approach using UV-exposed and unexposed epidermal skin tissues and confirm the presence of positively selected NOTCH1/2-, TP53- and FAT1-driven clones. No selection signals were detected in a set of immune genes or housekeeping genes. Additionally, we provide the first evidence for smoking-induced clonal changes in oral epithelia, likely underlying the origin of head and neck carcinogenesis. In conclusion, the whole-body donor-based approach provides a nearly unlimited healthy tissue resource to study mutational clonality and gain fundamental mutagenic insights in the presumed earliest stages of tumour evolution.

genomics↗

bioRxiv2018

Lack of detectable neoantigen depletion in the untreated cancer genome

Somatic mutations in cancer can result in the presentation of mutated peptides on the cell surface, eliciting an immune response. Mutant peptides are presented via HLA molecules and are known as neoantigens. It has been suggested that selection acts against the underlying mutations, leading to neoantigen depletion. Knowing the extent of this specific form of immunoediting may provide fundamental insights into tumour-immune interactions during tumour evolution. Here, we quantified the extent of neoantigen depletion in a wide range of human cancers by studying somatic mutations in the HLA-binding annotated exome, i.e. genomic regions that can be translated into presented peptides. We initially observed reduced non-synonymous mutation rates in presented regions, suggestive of neoantigen depletion. However, when compared to the expected mutation rates from a trinucleotide-based mutational signature model, depletion signals were negligible. This is explained by correlative relationships between the likelihood of mutagenesis in different nucleotide sequences and predicted HLA affinities for corresponding peptides. Our results suggest that signals of immunogenic negative selection are weak or absent in cancer genomics data and that other mechanisms to escape immune responses early during tumour evolution might be more efficient.

genomics↗

bioRxiv2018

Elevated pyrimidine dimer formation at distinct genomic bases underlie promoter mutation hotspots in UV-exposed cancers

Sequencing of whole cancer genomes has revealed an abundance of recurrent mutations in gene-regulatory promoter regions, in particular in melanoma where strong mutation hotspots are observed adjacent to ETS-family transcription factor (TF) binding sites. While sometimes interpreted as functional driver events, these mutations have also been suggested to be due to locally inhibited DNA repair or, alternatively, locally increased propensity for UV damage. Here, we provide evidence that base-specific elevations in the efficacy of UV lesion formation underlie these mutations. First, we find that low-dose UV light induces mutations preferably at a known ETS promoter hotspot in cultured cells even in the absence of global or transcription-coupled nucleotide excision repair (NER), ruling out inhibited repair. Further, by genome-wide mapping of cyclobutane pyrimidine dimers (CPDs) shortly after UV exposure and thus before DNA repair, we find that ETS-related mutation hotspots exhibit a strong base-specific increase in CPD formation frequency. Analysis of a large whole genome cohort illustrates the widespread contribution of this effect to recurrent mutations in melanoma. While inhibited NER underlies a general increase in somatic mutation burden in regulatory regions, we conclude that the most recurrently mutated individual DNA bases arise instead due to locally favorable conditions for UV damage formation, thus explaining a key phenomenon in whole-genome cancer analyses.

cancer biology↗

bioRxiv2017

An antisense RNA capable of modulating the expression of the tumour suppressor microRNA-34a

The microRNA-34a is a well-studied tumor suppressor microRNA (miRNA) and a direct downstream target of TP53 with roles in several pathways associated with oncogenesis, such as proliferation, cellular growth, and differentiation. Due to its broad tumor suppressive activity, it is not surprising that miR34a expression is altered in a wide variety of solid tumors and hematological malignancies. However, the mechanisms by which miR34a is regulated in these cancers is largely unknown. In this study, we find that a long non-coding RNA transcribed antisense to the miR34a host gene, is critical for miR34a expression and mediation of its cellular functions in multiple types of human cancer. We name this long non-coding RNA lncTAM34a, and characterize its ability to facilitate miR34a expression under different types of cellular stress in both TP53 deficient and wild type settings.

cancer biology↗