Biology subjects

van de Werken, H. J. G.

Publications and source records attributed to van de Werken, H. J. G..

8 recordsLinked to original sources

bioRxiv2026

Prime-Target neoantigen vaccination unleashes unprecedented T cell immunity within ''cold'' immunosuppressive tumors

"Cold" immunosuppressive solid tumors are hard-to-treat cancers that are non-responsive to immunotherapies. Their immunosuppressive tumor microenvironment (TME) excludes and inhibits T cells and thereby hampers the therapeutic efficacy of cancer vaccines and immune checkpoint blockade. To overcome this, we employed a "Prime-Target" (P/T) neoantigen vaccination strategy that combines subcutaneous (SQ) and intra-tumor (IT) neopeptide vaccinations to first prime potent systemic neoantigen-specific T cell immunity and then trigger intratumoral T cell recruitment. Using immunotherapy non-responsive murine tumor models with pronounced immunosuppressive TMEs, we demonstrate that P/T neopeptide vaccination resulted in extraordinary tumor control and TME remodeling. P/T vaccination elicited strong systemic anti-tumor responses as well as potent and rapid recruitment of clonal CD4+ Th1 and non-exhausted CD8+ T cells into tumors that carried novel T cell receptors (TCR) and were vaccine neopeptide-specific. Concurrently, P/T vaccination reshaped the TME by decreasing suppressive Treg and M2 macrophages, and dramatically increasing the ratio of effector T cells to Treg and M2 macrophages. Vaccination-induced tumor control was neopeptide-dependent and required concurrent IT administration of both neopeptides and adjuvants. Our study highlights P/T neoantigen vaccination as a promising strategy to overcome T cell exclusion within "cold" immunosuppressive solid tumors and thereby unleash unprecedented anti-tumor immunity.

immunology↗

bioRxiv2025

Cell-Based Immunization Combined with Single-Round Cell Panning Enables Discovery of PSMA-Targeting Nanobodies from Phage Display Libraries

There is a strong need for nanobodies targeting novel cancer-associated antigens to advance radioligand imaging and antibody-based therapeutics. In this study, we investigated whether non-targeted Llama immunization using tumor cells, combined with non-targeted phage display panning on human cell lines, could yield nanobodies specific to Prostate Specific Membrane Antigen (PSMA). Nanobody selection using both classical three round PSMA negative-positive panning and single round panning of cell lines positive or negative for PSMA showed clear enrichment for PSMA binders in both strategies. Using shRNA knockdown, flow cytometry, cell-ELISA, immunohistochemistry and structural modeling and docking, we confirmed the PSMA targeting of selected nanobodies. Two distinct epitopes were predicted to be bound by nanobodies PSMANb9 and A7 (JVZ-007), corroborated by epitope competition assays. These findings support the feasibility of non-targeted immunization and panning strategies for isolating clinically relevant cancer nanobodies.

cancer biology↗

bioRxiv2022

Katdetectr: utilising unsupervised changepoint analysis for robust kataegis detection

BackgroundKataegis refers to the occurrence of regional genomic hypermutation in cancer and is a phenomenon that has been observed in a wide range of malignancies. A kataegis locus constitutes a genomic region with a high mutation rate, i.e., a higher frequency of closely interspersed somatic variants than the overall mutational background. It has been shown that kataegis is of biological significance and possibly clinically relevant. Therefore, an accurate and robust workflow for kataegis detection is paramount. FindingsHere we present Katdetectr, an open-source R/Bioconductor-based package for the robust yet flexible and fast detection of kataegis loci in genomic data. In addition, Katdetectr houses functionalities to characterize and visualize kataegis and provides results in a standardized format useful for subsequent analysis. In brief, Katdetectr imports industry-standard formats (MAF, VCF, and VRanges), determines the intermutation distance of the genomic variants and performs unsupervised changepoint analysis utilizing the Pruned Exact Linear Time search algorithm followed by kataegis calling according to user-defined parameters. We used synthetic data and an a priori labeled pan-cancer dataset of Whole Genome Sequenced malignancies for the performance evaluation of Katdetectr and five publicly available kataegis detection packages. Our performance evaluation shows that Katdetectr is robust regarding tumor mutational burden (TMB) and shows the fastest mean computation time. Additionally, Katdetectr reveals the highest accuracy (0.99, 0.99) and normalized Matthews Correlation Coefficient (0.98, 0.92) of all evaluated tools for both datasets. ConclusionsKatdetectr is a robust workflow for the detection, characterization, and visualization of kataegis and is available on Bioconductor: https://doi.org/doi:10.18129/B9.bioc.katdetectr

bioinformatics↗

bioRxiv2022

Genomic and transcriptomic landscape of advanced renal cell cancer to individualize treatment strategy

BackgroundDifferences in the clinical course and treatment responses in individual patients with advanced renal cell carcinoma (RCC) can largely be explained by the different genomics of this disease. To improve the personalized treatment strategy and survival outcomes for patients with advanced RCC, the genomic make-up in patients with advanced RCC was investigated to identify putative actionable mutations and signatures. MethodsIn this prospective multicenter study (NCT01855477), whole-genome sequencing (WGS) data of locally advanced and metastatic tissue biopsies and matched whole-blood samples were collected from 91 patients with histopathologically confirmed RCC. WGS data were analyzed for small somatic variants, copy-number alterations and structural variants. For a subgroup of patients, RNA sequencing (RNA-Seq) data could be analyzed. RNA-Seq data were clustered on immunogenic and angiogenic gene expression patterns according to a previously developed angio-immunogenic gene signature. ResultsFor papillary and clear cell RCC, putative actionable drug targets were detected by WGS in 100% of the patients. RNA-Seq data of clear cell and papillary RCC were clustered using a previously developed angio-immunogenic gene signature. Analyses of driver mutations and RNA-Seq data revealed clear differences among different RCC subtypes, showing the added value of WGS and RNA-Seq over clinicopathological data. ConclusionsBy improving both histological subtyping and the selection of treatment according to actionable targets and immune signatures, WGS and RNA-Seq may improve therapeutic decision making for most patients with advanced RCC, including patients with non-clear cell RCC for whom no standard treatment is available to data. Prospective clinical trials are needed to evaluate the impact of genomic and transcriptomic diagnostics on survival outcome for advanced RCC patients.

cancer biology↗

bioRxiv2021

Clinical implementation of single-cell RNA sequencing using liver fine needle aspirate tissue sampling and centralized processing captures compartment specific immuno-diversity

Blood samples are frequently collected in human studies of the immune system but poorly represent tissue-resident immunity. Understanding the immunopathogenesis of tissue-restricted diseases, such as chronic hepatitis B, necessitates direct investigation of local immune responses. We developed a workflow that enables frequent, minimally invasive collection of liver fine-needle aspirates in multi-site international studies and centralized single-cell RNA sequencing data generation using the Seq-Well S3 picowell-based technology. All immunological cell types were captured, including liver macrophages, and showed distinct compartmentalization and transcriptional profiles, providing a systematic assessment of the capabilities and limitations of peripheral blood samples when investigating tissue-restricted diseases. The ability to electively sample the liver of chronic viral hepatitis patients and generate high-resolution data will enable multi-site clinical studies to power fundamental and therapeutic discovery.

immunology↗

bioRxiv2021

Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data

Spliced fusion-transcripts are typically identified by RNA-seq without elucidating the causal genomic breakpoints. However, non poly(A)-enriched RNA-seq contains large proportions of intronic reads spanning also genomic breakpoints. Using 1.274 RNA-seq samples, we investigated what additional information is embedded in non poly(A)-enriched RNA-seq data. Here, we present our novel, graph-based, Dr. Disco algorithm that makes use of both intronic and exonic RNA-seq reads to identify not only fusion transcripts but also genomic breakpoints in gene but also in intergenic regions. Dr. Disco identified TMPRSS2-ERG fusions with genomic breakpoints and other transcribed rearrangements from multiple RNA-sequencing cohorts. In breast cancer and glioma samples Dr. Disco identified rearrangement hotspots near CCND1 and MDM2 and could directly associate this with increased expression. A comparison with matched DNA-sequencing revealed that most genomic breakpoints are not, or minimally, transcribed while also revealing highly expressed translocations missed by DNA-seq. By using the full potential of non poly(A)-enriched RNA-seq data, Dr. Disco can reliably identify expressed genomic breakpoints and their transcriptional effects.

bioinformatics↗

bioRxiv2021

Molecular characterization reveals genomic and transcriptomic subtypes of metastatic urothelial carcinoma

BackgroundMolecular characterization of primary urothelial carcinoma (UC) revealed molecular subtypes with different genomic, transcriptomic, and clinicopathological characteristics, which might guide therapeutic decision making. A comprehensive molecular characterization of metastatic UC (mUC), however, is currently lacking in the literature. Because of the lethality of mUC, with few therapeutic options available for patients, a multi-omics characterization of mUC could aid to improve patient selection for new and existing therapies. MethodsTo define the molecular landscape of mUC and to identify potential targets for therapy, we performed whole genome DNA sequencing on fresh-frozen metastatic tumor biopsies of 116 mUC patients, and mRNA sequencing on 90 matched biopsies. ResultsHierarchical clustering based on mutational signatures revealed two major genomic subtypes. The most prevalent subtype (67%) consisted almost exclusively of tumors with high APOBEC mutagenesis. APOBEC mutagenesis was detected in 91% of the samples, and appeared to be an ongoing process in mUC based on analysis of eight patients from whom serial biopsies were obtained during treatment. Contrary to the overall distribution of mutations, APOBEC associated mutations occurred throughout the genome, and independently of predicted accessible or transcribed genomic regions, suggesting that these mutations were generated during replication. Transcriptomic analysis revealed five mRNA-based subtypes: two luminal subtypes (40%), a stroma-rich (24%), basal/squamous (23%), and non-specified subtype (12%). The transcriptomic subtypes were different regarding driver gene alterations (e.g. ELF3 and TSC1), gene amplifications (NECTIN4 and PPARG), pathway activity, and immune cell infiltration. By integrating the genomic and transcriptomic data, potential therapeutic options per transcriptomic subtype and individual patient were proposed. ConclusionsThis study expands our knowledge on the molecular landscape of mUC, and serves as a reference for subtype-oriented and patient-specific research on the etiology of mUC, and for novel drug development. Trial registrationThe mUC cohort studied here is part of the Netherlands nationwide study of the center for personalized cancer treatment consortium (CPCT-02 Biopsy Protocol, NCT01855477), and the Drug Rediscovery Protocol (DRUP Trial, NCT02925234).

cancer biology↗

bioRxiv2019

The genomic landscape of metastatic castration-resistant prostate cancers using whole genome sequencing reveals multiple distinct genotypes with potential clinical impact

Here we present whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 castration-resistant prostate cancer patients. Using hierarchical unsupervised clustering based on genomic aberrations only, we defined eight different clusters. We detected four distinct and potentially clinically relevant genotypes harboring unique genomic features, including: 1) Microsatellite Instability; 2) Homologous Recombination Deficiency (HRD) with enriched genomic deletions and BRCA2 aberrations; 3) tandem duplication phenotype associated with biallelic CDK12 mutations; and 4) a subgroup enriched for chromothripsis events. Our data suggest that classifying patients using WGS characteristics may improve classification of HRD patients. Moreover, we confirmed that important regulators of AR-mediated signaling are located in non-coding regions. Using ChIP sequencing data, we showed that the amplified AR and MYC promoter regions contain open chromatin and bind AR, suggesting a role in AR mediated biology. Thus, high-resolution WGS may be used to improve patient stratification.

cancer biology↗