Biology subjects

Krijgsveld, J.

Publications and source records attributed to Krijgsveld, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Oncogenic fusions induce an extensive cancer-restricted cryptic proteome in Ewing sarcoma

How tumors generate a cryptic "dark" proteome absent from healthy tissues, and whether it can be reversibly activated, remains unclear. In Ewing sarcoma, all tumors are driven by EWSR1::ETS fusions, making it a tractable model to study dark proteome activation. Integrating matched transcriptomes, translatomes and proteomes from 48 patient tumors with long-read RNA sequencing, single-cell Ribo-seq, proteomics and immunopeptidomics in cell line models, we show that EWSR1::FLI1 acts as a reversible switch recurrently inducing hundreds of cancer-specific neoproteins. Many arise from canonical coding regions via intragenic transcription start sites, generating truncated or out-of-frame neoproteins. We uncover a fusion-dependent increase in ribosomal readthrough into poly(A) tails, generating a stable 80-amino-acid TRPM4 neoprotein that, despite lacking a stop codon, is the most abundant tumor-specific microprotein across patients. Proteomic, immunopeptidomic, and immunofluorescence analyses validate neoproteins as tumor-restricted antigens, revealing a therapeutically actionable cancer dark proteome controlled by one oncogenic fusion.

cancer biology↗

bioRxiv2026

Multi-omics profiling reveals MAGEL2-driven defects in human corticogenesis shared across Prader-Willi and Schaaf-Yang syndromes.

The human cortex acquires its advanced cognitive capacity through tightly regulated developmental programs, disruption of which underlies neurodevelopmental disorders such as Schaaf-Yang syndrome (SYS) and Prader-Willi syndrome (PWS). While SYS results from pathogenic variants in the imprinted gene MAGEL2, PWS arises from chromosomal deletions, imprinting defects or uniparental disomy encompassing the MAGEL2 locus. However, the contribution of MAGEL2 to disease pathogenesis and human corticogenesis is not fully understood. Here, we performed integrated transcriptomic, proteomic, and ubiquitinomic profiling of cortical neurons derived from CRISPR/Cas9-engineered isogenic human pluripotent stem cells (hiPSC) modeling SYS and PWS. Beyond PWS-specific signatures including dysregulated ribosomal processes, we identified MAGEL2-dependent defects shared across both disorders. These include reduced progenitor proliferation, accelerated neuronal maturation, impaired migration and adhesion, as well as abnormal synaptic development, collectively linking PWS and SYS at the level of cortical development. Notably, these phenotypes partially overlap with those observed in other neurodevelopmental disorders, suggesting that MAGEL2 governs core pathways broadly vulnerable in disease. Together, our findings establish MAGEL2 as a key regulator of human cortical development, provide a unifying mechanistic framework for SYS and PWS, accessible via a web-based platform.

neuroscience↗

bioRxiv2026

CRISPR screens establish regulatory maps of immunosuppressive surface molecules in cancer

Cancer cells can evade immune surveillance by triggering inhibitory checkpoint responses in tumor-associated T cells through the expression of immunosuppressive surface molecules. While therapeutic blockade of such receptors has emerged as a pillar of cancer therapy, tumor cell-intrinsic mechanisms controlling their expression remain incompletely understood. Fluorescence-activated cell sorting (FACS)-based genetic screens can be used to decipher regulatory pathways, but conventional screening approaches are biased towards regulators that are dispensable for cancer cell proliferation and survival. Here, we used a tetracycline-inducible Cas9 system enabling fully time-controllable CRISPR-based mutagenesis to gain a more comprehensive and comparative survey of regulators controlling the expression of four major immunosuppressive surface molecules, PD-L1 (CD274), CD47, CD276 and HLA-E, as well as CD151, a candidate surface target associated with tumor growth and invasion. As a prominent hit, our screens identify the membrane-trafficking factor DNAJC13 as a regulator of PD-L1 and CD276. Among DNAJC13-controlled surface proteins, we identify other known and proposed immune-checkpoint molecules. Based on this function, suppression of DNAJC13 strongly increases the sensitivity of human cancer cells to T-cell attack in vitro and prolongs survival of mice bearing pancreatic tumors. Together, our study establishes regulatory maps of major immune-modulatory surface molecules and identifies DNAJC13 as a potential target for the coordinated inhibition of multiple immunosuppressive signals.

molecular biology↗

bioRxiv2026

Inflammatory injury drives CIN and STING loss in polyploidpancreatic acinar cells

Epidemiological studies link pancreatic inflammation to increased cancer risks with elevated levels of chromosomal instability (CIN), yet the underlying cause remains unclear. The exocrine pancreas and lactating mammary gland harbor polyploid cells to boost secretory efficiency. Using organoid and in vivo models of pancreatic injury, we show that polyploid acinar cells contribute to regeneration via acinar-to-ductal metaplasia. The metaplasia induced cell size reduction is associated with crowding and spindle misorientation, leading to mitotic errors such as lagging chromosomes, chromatin bridges, and micronuclei. Micronucleated cells are not always eliminated or arrested in the cell cycle but can continue to proliferate and expand. Polyploid cells in post-lactational mammary gland organoids equally exhibited proliferation-related CIN. Single-cell proteomics of acinar cells shows STING1 loss and increased ATR levels in polyploid cells, enabling continued proliferation. These findings uncover physiological links between polyploidy, tissue repair, and CIN, offering new insights into cancer risks after tissue remodeling.

cell biology↗

bioRxiv2025

Exploration of oncogenic cooperation between germline variation and somatic mutation in prostate cancer progression

Prostate carcinoma (PCa) is the most common cancer of men, associated with a still unresolved issue of accurate risk-stratification. While recent advances in omics technologies have provided clues as to how molecular changes shape the onset and progression of PCa, it remains largely unclear whether germline variants and somatic mutations cooperate to contribute to PCa progression and outcome. Thus, we explored whether oncogenic cooperation between regulatory germline variants and somatic driver mutations can help explain why some PCa patients develop a more aggressive phenotype, which may have implications for risk-adapted medical treatment. Here, by employing an integrative functional genomics approach, we identified receptor-type protein-tyrosine phosphatase kappa (PTPRK) as a TMPRSS2::ERG (TE)-modulated gene associated with PCa progression whose expression is controlled by cooperation of the TE-fusion with a regulatory single nucleotide polymorphism (SNP). Analysis of available clinically annotated patient cohorts demonstrated that PTPRK is overexpressed in TE-positive PCa tumors and associated with higher Gleason scores and metastatic disease. TE knockdown in PCa cell lines reduced PTPRK expression, while ectopic overexpression of the fusion in TE-negative PCa cell lines and prostatic epithelium cells induced its expression. Functionally, PTPRK silencing inhibited cellular proliferation, cell cycle progression, and clonogenic growth of PCa cells, which was mirrored by dysregulation of corresponding gene and protein signatures in global transcriptomic and phospho-proteomic analyses after PTPRK knockdown. Analysis of TE ChIP-Seq and Hi-C data from PCa cells highlighted a proximal TE-bound DNA element whose TE-dependent enhancer activity was validated in reporter assays and which could be abrogated by a regulatory SNP. Collectively, our results provide evidence of how exploration of oncogenic cooperation may help to identify novel biomarkers and potentially druggable pathways and highlight the role of the regulatory genome in PCa progression.

cancer biology↗

bioRxiv2025

A bone marrow stromal secretome screen identifies semaphorin 3A as a regulator of hematopoiesis

Bone marrow mesenchymal stromal cells (MSCs) are a major source of secreted factors that control hematopoietic stem and progenitor cell (HSPC) function. We previously reported the generation of revitalized MSCs (rMSCs), which more effectively support HSPCs in culture. In a secretome screen using rMSCs, we identified semaphorin 3A (SEM3A) as a secreted factor upregulated as part of a pro-inflammatory signature that may contribute to HSPC expansion by rMSCs. We show that recombinant SEM3A acts directly on HSPCs to inhibit their cycling ex vivo. Analysis of a SEM3A loss of function mutation in vivo revealed hematopoietic progenitor expansion and accelerated recovery after myeloablation, consistent with a role for SEM3A in regulating HSPCs at steady state and during hematopoietic stress. This work highlights proteomic screening using rMSCs as a method to identify novel secreted niche factors and uncovers a novel role for SEM3A in controlling HSPC proliferation in stress hematopoiesis. SummaryBorger et al. characterize the secretome of revitalized bone marrow stromal cells and identify a novel role of the protein semaphorin 3A in regulating hematopoietic stem and progenitor cell proliferation in steady state and stress conditions.

cell biology↗

bioRxiv2025

MEK inhibition induces AXIN1 loss in colorectal cancer by mTOR associated suppression of protein synthesis

AXIN1 is a central regulatory hub of many oncogenic pathways in colorectal cancer (CRC). As the main scaffold protein and least abundant component of the beta-catenin destruction complex, changes in AXIN1 levels affect Wnt signaling output. We show that targeting the Ras-MAPK pathway by MEK1/2 inhibitors induces AXIN1 loss across a panel of CRC cell lines and patient-derived organoids. GSK3B inhibition similarly reduced AXIN1 levels, yet by distinct mechanisms. MEK1/2 causes a reduction of AXIN1 transcript levels, but neither affects protein stability nor post-translational modifications of AXIN1. In contrast, GSK3B inhibition induces rapid AXIN1 degradation. Prevention of AXIN1 loss by co-treatment with tankyrase inhibitors was much stronger for GSK3B than for MEK1/2 inhibition. Using isogenic CRC cell lines and murine intestinal organoids, we show that APC truncations strongly reduce basal AXIN1 levels, but do not alter dynamics of AXIN1 loss upon MEK1/2 inhibition. Polysome profiling and Ribo-Seq revealed that MEK1/2 inhibition reduces global protein synthesis via an mTOR dependent pathway. This translational repression is sufficient to cause significant AXIN1 loss, as treatment with mTOR inhibitors phenocopies the effect of MEK1/2 inhibitors. Our study demonstrates that AXIN1 protein homeostasis is critically controlled by Ras-MAPK signaling at the level of protein synthesis, and that MEK1/2 inhibitors cause AXIN1 loss by translational repression.

cancer biology↗

bioRxiv2025

Nucleotide insufficiency induced by p53 deficiency leads to replication stress driving genomic instability

P53 prevents DNA damage by inducing repair processes, cell cycle arrest or apoptosis. P53 loss leads to replication stress and genomic instability, yet the mechanisms underlying these effects and their contribution to catastrophic genomic events such as chromothripsis remain poorly understood. Using patient-derived fibroblasts with germline p53 variants, that spontaneously undergo chromothripsis, and p53-downregulated fibroblasts, we discovered that p53 loss leads to aberrant transcriptional upregulation, increasing nucleotide consumption while simultaneously decreasing nucleotide biosynthesis. This imbalance in production and consumption results in insufficient nucleotide pools, leading to replication stress and genomic instability, which are rescued by nucleoside supplementation or transcription normalization. The replication stress triggers telomere dysfunction, micronuclei formation, and ultimately chromothripsis. Emerging dominant chromothriptic clones exhibit normal DNA replication, telomere stabilization, and ecDNA, highlighting critical features for clonal selection. Hence, p53 coordinates transcription and nucleotide pools, crucial for maintaining genomic stability and preventing early cancer development.

cancer biology↗

bioRxiv2024

Oxytocin Gαi signaling-induced amygdala astrocytes processes retraction shapes behavioral stress response

Anticipated reactions to stressful situations are vital for the survival and well-being of organisms, and abnormal reactions are involved in stress-related disorders. The neuropeptide oxytocin is a key modulator ensuring well-adapted stress responses. Oxytocin acts on both neurons and astrocytes, but the molecular and cellular mechanisms mediating stress response remain poorly understood. Here, we focus on the amygdala, a crucial hub that integrates and processes sensory information through oxytocin- dependent mechanisms. Using an acute stress paradigm in mice, genetic and pharmacological manipulations combined with proteomic, morphological, electrophysiological and behavioral approaches, we reveal that oxytocinergic modulation of the freezing response to stress is mediated by transient Gi-dependent retraction of astrocytic processes, followed by enhanced neuronal sensitivity to extracellular potassium in the amygdala. Our findings elucidate a pivotal role for astrocytes morphology- dependent modulation of brain circuits that is required for proper anticipated behavioral response to stressful situations.

neuroscience↗

bioRxiv2024

Super-enhancer-driven CACNA2D2 is an EWSR1::WT1 signature gene encoding a diagnostic marker for desmoplastic small round cell tumor (DSRCT)

Desmoplastic small round cell tumor (DSRCT) is a highly aggressive cancer predominantly occurring in male adolescents and young adults. The lack of a comprehensive understanding on the biology of the disease is paralleled by its dismal survival rates (5-20%). To overcome this challenge, we first identified and prioritized urgently needed resources for clinicians and researchers. Thus, we established genome-wide single-cell RNA-sequencing and bulk proteomic data of in vitro and in vivo-generated knockdown models of the pathognomonic DSRCT fusion oncoprotein (EWSR1::WT1) and combined them with an original systems-biology-based pipeline including patient data and the largest histology collection of DSRCTs and morphological mimics available to date. These novel tools were enriched with curated public datasets including patient- and cell line-derived ChIP-seq, bulk and single-cell RNA-seq studies resulting in a multi-model and multi-omic toolbox for discovery analyses. As a proof of concept, our approach revealed the alpha-2/delta subunit of the voltage-dependent calcium channel complex, CACNA2D2, as a highly overexpressed, super-enhancer driven, direct target of EWSR1::WT1. Single-cell and bulk-level analyses of patient samples and xenografted cell lines highlighted CACNA2D2 as a critical component of our newly established EWSR1::WT1 oncogenic signature, that can be employed to robustly identify DSRCT in reference sets. Finally, we show that CACNA2D2 is a highly sensitive and specific single biomarker for fast, simple, and cost-efficient diagnosis of DSRCT. Collectively, we establish a large-scale multi-omics dataset for this devastating disease and provide a blueprint of how such toolbox can be used to identify new and clinically relevant diagnostic markers, which may significantly reduce misdiagnoses, and thus improve patient care.

cancer biology↗

bioRxiv2024

Unbiased functional genetic screens reveal essential RNA modifications in human cancer and drug resistance

RNA modification pathways are mis-regulated in multiple types of human cancer. To comprehensively identify cancer-relevant RNA modifications and their regulators, we screened all 150 annotated human RNA modifying proteins across 18 different normal and cancer cell lines using a CRISPR-based genetic knockout system. Fifty RNA modifying proteins were essential for survival of at least one cell type. A third of these essential genes were amplified in 38 different human primary cancer types and potentially drive cancer growth. Unexpectedly, the number of essential genes per cell line varied considerably, and this variation was not due to tissue of origin. Instead, we found that cancer cell-specific mitochondrial metabolic plasticity was responsible for the unique requirement of certain RNA modifications. For example, leukemia cells with high intrinsic drug tolerance required mitochondrial flexibility to survive treatment with the anti-leukemic drugs cytarabine and venetoclax. Synthetic lethality screens revealed that drug-resistance is abolished by deleting the mitochondrial methyltransferase TRMT5, which is responsible for the formation of N1-methylguanosine (m1G) in the tRNA anticodon loop. In summary, our study identifies cancer-relevant RNA modifying enzymes, and reveals a novel promising drug target for therapy-resistant acute myeloid leukemia.

cell biology↗

bioRxiv2024

An organoid platform reveals MEK-PARP co-targeting to enhance radiation response in rectal cancer

Locally advanced rectal cancer is usually treated by neoadjuvant chemoradiotherapy. However, tumor response rates to this treatment vary greatly. Thus, most patients do not reach a complete remission and have to undergo tumor resection. In the present study, we introduce a patient-derived rectal cancer organoid platform that reflects clinical radiosensitivity and use this to screen 1596 drug-radiation combinations. We identify inhibitors of RAS-MAPK signaling, especially MEK inhibitors, strongly synergizing with radiation response. Mechanistically, MEK inhibitors suppressed radiation-induced activation of RAS-MAPK signaling, and selectively downregulated the homologous recombination DNA repair pathway component RAD51, thereby achieving radio-enhancement. Through testing drug-drug-radiation combinations in organoids and cell lines, we identified synergism between PARP and MEK inhibitors to further enhance the effect of radiation. Our data support clinical testing of combined MEK and PARP inhibition with radiotherapy in locally advanced rectal cancers. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/597640v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1d77d62org.highwire.dtl.DTLVardef@68b928org.highwire.dtl.DTLVardef@154142eorg.highwire.dtl.DTLVardef@f8f462_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Isolation of proteins on chromatin (iPOC) reveals signaling pathway-dependent alterations in the DNA-bound proteome

Signaling pathways often convergence on transcription factors (TFs) and other DNA-binding proteins (DBPs) that regulate chromatin structure and gene expression, thereby governing a broad range of essential cellular functions. However, the repertoire of DBPs is incompletely understood even for the best-characterized pathways. Here, we optimized a strategy for the isolation of Proteins on Chromatin (iPOC) exploiting tagged nucleoside analogues to label the DNA and capture associated proteins, thus enabling the comprehensive, sensitive, and unbiased characterization of the DNA-bound proteome. We then applied iPOC to investigate chromatome changes upon perturbation of the cancer-relevant PI3K/AKT/mTOR pathway. Our results show distinct dynamics of the DNA-bound proteome upon selective inhibition of PI3K, AKT, or mTOR, and we provide evidence how this signaling cascade regulates the DNA-bound status of SUZ12, thereby modulating H3K27me3 levels. Collectively, iPOC is a powerful approach to study the composition of the DNA-bound proteome operating downstream of signaling cascades, thereby both expanding our knowledge of the mechanism of action of the pathway, and unveiling novel chromatin modulators that can potentially be targeted pharmacologically.

molecular biology↗

bioRxiv2024

Deep learning-based proteomics enables accurate classification of bulk and single-cell samples

Proteins are the main drivers of cell function and disease, making their analysis a powerful technique to characterize determinants of cell identity and to identify biomarkers. Current proteomic technology has the breadth to profile thousands of proteins and even the sensitivity to access single cells, however limitations in throughput restrict its application, e.g. not allowing classification of samples according to biological or clinical status in large sample cohorts. Therefore, we developed a deep learning-based approach for the analysis of mass spectrometric (MS) data, assigning proteomic profiles to sample identity. Specifically, we designed an architecture referred to as Proformer, and show that it is superior to convolutional neural network-driven architectures, is explainable, and demonstrates robustness towards batch-effects. Based on its tabular approach, we highlight the integration of all four dimensions of proteomic measurements (retention time, mass-to-charge, intensity and ion mobility), and demonstrate enhanced sample discrimination involving a treatment with IFN-{gamma}, despite its subtle effect on the cells proteome. In addition, the Proformer is not restricted to proteomic depth, and can classify cells by cell type and their differentiation status even using single-cell proteomic data. Collectively, this work presents a novel deep learning-based model for rapid classification of proteomic data, with important future implications to enhance patient stratification, early detection and single-cell analysis.

bioinformatics↗

bioRxiv2024

Degradome analysis to identify direct protein substrates of small-molecule degraders

Targeted protein degradation (TPD) has emerged as a powerful strategy to selectively eliminate cellular proteins using small-molecule degraders, offering therapeutic promise for targeting proteins that are otherwise undruggable. However, a remaining challenge is to unambiguously identify primary TPD targets that are distinct from secondary downstream effects in the proteome. Here we introduce an approach that combines stable isotope labeling and click-chemistry for selective quantification of protein degradation by mass spectrometry, excluding confounding effects of altered transcription and translation induced by target depletion. We show that the approach efficiently operates at the time scale of TPD (hours) and we demonstrate its utility by analyzing the Cyclin K degraders dCeMM2 and dCeMM4, which induce widespread transcriptional downregulation, and the GSPT1 degrader CC-885, an inhibitor of protein translation. Additionally, we apply it to characterize compound 1, a previously uncharacterized degrader, and identify the zinc-finger protein FIZ1 as a degraded target.

biochemistry↗

bioRxiv2024

Enhanced feature matching in single-cell proteomics characterizes response to IFN-gamma and reveals co-existence of different cell states

Proteome analysis by data-independent acquisition (DIA) has become a powerful approach to obtain deep proteome coverage, and has gained recent traction for label-free analysis of single cells. However, optimal experimental design for DIA-based single-cell proteomics has not been fully explored, and performance metrics of subsequent data analysis tools remain to be evaluated. Therefore, we here present DIA-ME, a data analysis strategy that exploits the co-analysis of low-input samples with a so-called matching enhancer (ME) of higher input, to increase sensitivity, proteome coverage, and data completeness. We evaluate the matching specificity of DIA-ME by a two-proteome model, and demonstrate that false discovery and false transfer are maintained at low levels when using DIA-NN software, while preserving quantification accuracy. We apply DIA-ME to investigate the proteome response of U-2 OS cells to interferon gamma (IFN-{gamma}) in single cells, and recapitulate the time-resolved induction of IFN-{gamma} response proteins as observed in bulk material. Moreover, we observe co- and anti-correlating patterns of protein expression within the same cell, indicating mutually exclusive protein modules and the co-existence of different cell states. Collectively our data show that DIA-ME is a powerful, scalable, and easy-to- implement strategy for single-cell proteomics.

systems biology↗

bioRxiv2023

A single-sample workflow for joint metabolomic and proteomic analysis of clinical specimens

Understanding the interplay of the proteome and the metabolome aids in understanding cellular phenotypes. To enable more robust inferences from such multi-omics analyses, combining proteomic and metabolomic datasets from the same sample provides major benefits by reducing technical variation between extracts during the pre-analytical phase, decreasing sample variation due to varying cellular content between aliquots, and limiting the required sample amount. We evaluated the advantages, practicality and feasibility of a single-sample workflow for combined proteome and metabolome analysis. In the workflow, termed MTBE-SP3, we combined a fully automated protein lysis and extraction protocol (autoSP3) with a semi-automated biphasic 75% EtOH/MTBE extraction for quantification of polar/non-polar metabolites. Additionally, we compared the resulting proteome of various biological matrices (FFPE tissue, fresh-frozen tissue, plasma, serum and cells) between autoSP3 and MTBE-SP3. Our analysis revealed that the single-sample workflow provided similar results to those obtained from autoSP3 alone, with an 85-98% overlap of proteins detected across the different biological matrices. Additionally, it provides distinct advantages by decreasing (tissue) heterogeneity by retrieving metabolomics and proteomic data from the identical biological material, and limiting the total amount of required material. Lastly, we applied MTBE-SP3 to a lung adenocarcinoma cohort of 10 patients. Integrating the metabolic and proteomic alterations between tumour and non-tumour adjacent tissue yielded consistent data independent of the method used. This revealed mitochondrial dysfunction in tumor tissue through deregulation of OGDH, SDH family enzymes and PKM. In summary, MTBE-SP3 enables the facile and confident parallel measurement of proteins and metabolites obtained from the same sample. This workflow is particularly applicable for studies with limited sample availability and offers the potential to enhance the integration of metabolomic and proteomic datasets.

cancer biology↗

bioRxiv2023

An integrated workflow for quantitative analysis of the newly synthesized proteome

The analysis of proteins that are newly synthesized upon a cellular perturbation can provide detailed insight in the proteomic response that is elicited by specific cues. This can be investigated by pulse-labeling of cells with clickable and stable-isotope-coded amino acids for enrichment and mass spectrometric characterization of newly synthesized proteins (NSPs), however convoluted protocols prohibit their routine application. Here we optimized multiple steps in sample preparation, mass spectrometry and data analysis, and integrated them in a semi-automated workflow for the quantitative analysis of the newly synthesized proteome (QuaNPA). Reduced input requirements and data-independent acquisition (DIA) enabled analysis of triple-SILAC-labeled NSP samples, with enhanced throughput while featuring high quantitative accuracy. We applied QuaNPA to investigate the time-resolved cellular response to interferon-gamma (IFNg), observing rapid induction of known and novel targets 2h after IFNg treatment. QuaNPA provides a powerful approach for large-scale investigation of NSPs to gain insight in complex cellular processes.

systems biology↗