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PubMed2025

Widespread release of translational repression across Plasmodium's host-to-vector transmission event.

Malaria parasites must respond quickly to environmental changes, including during their transmission between mammalian and mosquito hosts. Therefore, female gametocytes proactively produce and translationally repress mRNAs that encode essential proteins that the zygote requires to establish a new infection. While the release of translational repression of individual mRNAs has been documented, the details of the global release of translational repression have not. Moreover, changes in the spatial arrangement and composition of the DOZI/CITH/ALBA complex that contribute to translational control are also not known. Therefore, we have conducted the first quantitative, comparative transcriptomics and DIA-MS proteomics of Plasmodium parasites across the host-to-vector transmission event to document the global release of translational repression. Using female gametocytes and zygotes of P. yoelii, we found that ~200 transcripts are released for translation soon after fertilization, including those encoding essential functions. Moreover, we identified that many transcripts remain repressed beyond this point. TurboID-based proximity proteomics of the DOZI/CITH/ALBA regulatory complex revealed substantial spatial and/or compositional changes across this transmission event, which are consistent with recent, paradigm-shifting models of translational control. Together, these data provide a model for the essential translational control mechanisms that promote Plasmodium's efficient transmission from mammalian host to mosquito vector.

Animals↗
PubMed2026

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗
PubMed2026

CRISPR-Enabled functional genomics in hPSCs-derived neural models for autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a genetically heterogeneous neurodevelopmental condition in which hundreds of individually rare risk variants converge on a small number of shared biological pathways, including synaptic scaffolding, chromatin remodeling, excitation-inhibition balance, and cellular energy metabolism. Translating this genetic heterogeneity into mechanistic insight requires experimental systems capable of interrogating individual gene functions in human-relevant neural contexts at scale. CRISPR-enabled functional genomics in human pluripotent stem cell (hPSC)-derived neural models, spanning neural progenitors, cortical and inhibitory neurons, astrocytes, microglia, and brain organoids, provides precisely this capability. By integrating pooled perturbation screens with multimodal readouts including single-cell and spatial transcriptomics, chromatin accessibility profiling, proximity labeling proteomics, multi-electrode array electrophysiology, and metabolic flux analysis, these platforms enable systematic, causal mapping of ASD gene function at system resolution. Early applications have already revealed convergent mechanisms: BAF complex disruption expands the ventral progenitor pool and biases its fate toward oligodendrocyte and interneuron lineages; ADNP loss impairs microglial synaptic pruning through altered endocytic trafficking; and mTOR pathway dysregulation in PTEN- and TSC2-perturbed models links genetic risk directly to metabolic and mitochondrial dysfunction. Computational frameworks including MIMOSCA and SCEPTRE enable causal network reconstruction and pseudotime inference from these datasets, moving the field from gene lists toward pathway-level models of ASD pathobiology. Translational applications leverage isogenic iPSC panels and variant-level base and prime editing to stratify ASD variants by functional impact, informing gene therapy design for haploinsufficient targets such as CHD8 and SCN2A via AAV or antisense oligonucleotide delivery. Remaining challenges, including model developmental immaturity, batch variability, and the difficulty of modeling polygenic risk, are addressed by a roadmap integrating spatial perturbomics, AI-driven causal inference, and population-scale standardized biobanks. This review synthesizes the current state of CRISPR-based functional genomics in human stem cell neural models as a coherent experimental framework for converting ASD genetic associations into mechanistic understanding and therapeutic opportunity.

Humans↗
PubMed2026

Omics in optic neuropathies: From molecular landscapes to personalized therapeutics.

Optic neuropathies comprise a heterogeneous group of disorders involving transient or permanent injury to retinal ganglion cells (RGCs) and their axons. Clinically, these neurodegenerative conditions manifest as dyschromatopsia, decreased visual acuity, and visual field defects, and in severe cases may ultimately lead to blindness and disability. The marked heterogeneity across disease subtypes, incompletely understood etiologies, and complex pathogenic mechanisms pose substantial challenges to precise diagnosis and effective treatment. Recent advances in omics technologies - including genomics, transcriptomics, proteomics, metabolomics, lipidomics, single-cell and spatial sequencing, and integrative multi-omics approaches - have ushered optic nerve degenerative disease research into an era of high-resolution comprehensive investigation. In this review, we summarize representative applications of omics approaches to elucidate genetic alterations, signaling dysregulation, metabolic reprogramming, and immune responses in optic neuropathies. We further discuss the emerging potential of multi-omics in identifying early diagnostic biomarkers and informing individualized therapeutic strategies. Finally, we provide a forward-looking perspective on the future trajectory of omics technologies and their prospects in both fundamental research and clinical translation, with the overarching aim of accelerating the bench-to-bedside transition in this critical eye disease field.

biomarkers↗
PubMed2005

Genetic isolation of transport signals directing cell surface expression.

Membrane proteins represent approximately 30% of the proteome in both prokaryotes and eukaryotes. The spatial localization of membrane-bound proteins is often determined by specific sequence motifs that may be regulated in response to physiological changes, such as protein interactions and receptor signalling. Identification of signalling motifs is therefore important for understanding membrane protein expression, function and transport mechanisms. We report a genetic isolation of novel motifs that confer surface expression. Further characterization showed that SWTY, one class of these isolated motifs with homology to previously reported forward transport motifs, has the ability to both override the RKR endoplasmic reticulum localization signal and potentiate steady-state surface expression. The genetically isolated SWTY motif is functionally interchangeable with a known motif in cardiac potassium channels and an identified motif in an HIV coreceptor, and operates by recruiting 14-3-3 proteins. This study expands the repertoire of and enables a screening method for membrane trafficking signals.

14-3-3 Proteins↗
PubMed2003

Analysis of protein interactions using fluorescence technologies.

Biophotonics techniques, especially those involving fluorescence, are widely used in proteomics to characterize the in vitro interactions between proteins in high-throughput mode. On the other hand, fluorescence-based imaging studies often show that protein activity is regulated through large protein complexes that transiently form at specific sites in the cell. One could therefore argue that a systematic functional analysis of the human proteome requires technologies that are capable of time and spatially resolved, multiplexed analysis of protein interactions within cells.

Fluorescence Resonance Energy Transfer↗
PubMed2026

Proteomics as a theranostic compass in BCR::ABL1-negative myeloproliferative neoplasms: Integrating biomarker discovery with therapeutic stratification.

Classic BCR::ABL1-negative myeloproliferative neoplasms (MPNs)-polycythaemia vera, essential thrombocythaemia, and primary myelofibrosis-are clonal haematopoietic stem cell disorders with marked heterogeneity in clinical phenotype, disease trajectory, and therapeutic response. Genomic stratification by driver and cooperating mutations only partially accounts for this variability, leaving gaps in predicting thrombotic risk, fibrotic progression, leukaemic transformation, and treatment benefit. Proteomics bridges this gap by providing function-proximal readouts of protein abundance, post-translational modifications, pathway activity, and intercellular signalling that genomics and transcriptomics cannot capture, positioning it as a theranostic platform in which the same molecular readouts simultaneously inform diagnostic stratification and therapeutic decision-making. We propose a five-stage translational framework spanning from discovery-scale mass spectrometry and affinity-based plasma profiling to targeted validation, multicentre standardisation, and machine learning-integrated clinical panels. Proteomic evidence is synthesised across the following four disease axes: clonal fitness in haematopoietic stem and progenitor cells; bone marrow microenvironmental remodelling and fibrosis; chronic inflammation and thrombosis; and leukaemic transformation. We further describe how phosphoproteomics reveals resistance mechanisms to JAK inhibitors, including AXL-MAPK bypass and PP2A-autophagy-mediated tolerance, and how protein-level biomarkers (BCL2-BCL-XL, RAS-ERK, CAMK2G, and ROCK1/2) can guide individualised therapeutic selection. Affinity-based platforms (Olink PEA and SomaScan) and spatially resolved technologies (CODEX and single-cell proteomics) complement discovery proteomics. At present, however, this evidence base is constrained by small and heterogeneous cohorts, limited cross-platform reproducibility, and a scarcity of independent external validation for candidate protein panels. Realising this vision will require multicentre standardisation, analytically validated panel assays, and prospective clinical studies that translate molecular findings into decision-grade tools for patients with MPNs.

Humans↗
PubMed2006

Analyzing proteome topology and function by automated multidimensional fluorescence microscopy.

Temporal and spatial regulation of proteins contributes to function. We describe a multidimensional microscopic robot technology for high-throughput protein colocalization studies that runs cycles of fluorescence tagging, imaging and bleaching in situ. This technology combines three advances: a fluorescence technique capable of mapping hundreds of different proteins in one tissue section or cell sample; a method selecting the most prominent combinatorial molecular patterns by representing the data as binary vectors; and a system for imaging the distribution of these protein clusters in a so-called toponome map. By analyzing many cell and tissue types, we show that this approach reveals rules of hierarchical protein network organization, in which the frequency distribution of different protein clusters obeys Zipf's law, and state-specific lead proteins appear to control protein network topology and function. The technology may facilitate the development of diagnostics and targeted therapies.

Dermatitis, Atopic↗
PubMed2026

Spatial multiomics in biomedical research: advances beyond transcriptomics.

Coordinated changes in gene expression, epigenetic regulation, protein and metabolic activities together drive disease progression and determine clinical outcomes. While spatially resolved transcriptomics has been widely adopted across biomedical fields, it offers an incomplete picture limited to transcriptomic levels. Here, we survey the latest developments in spatial multiomics technologies, with particular emphasis on platforms that extend beyond conventional transcriptomics and profile genomics, epigenomics, proteomics, or metabolomics within intact tissues. These approaches are rapidly becoming commercialized, and here we highlight major technical breakthroughs, enhanced sample compatibility, emerging applications, and computational tools for data analysis. This Review aims to equip researchers with a clear understanding of the current technological landscape and to accelerate the adoption of spatial multiomics methods in biomedical research.

Humans↗
PubMed2026

Multimodal Analysis Reveals Aberrant Expression of SUMO2 and Its Significant Association With Key Mechanisms of Metabolic Pathways in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. However, the role of small ubiquitin-like modifier 2 (SUMO2), a core member of the small ubiquitin-like modifier (SUMO) family, regarding its expression patterns and metabolism-related functions in HCC remains inadequately understood. METHODS: A multidimensional analytical framework was applied, integrating immunohistochemistry (153 HCC vs. 21 non-HCC samples), proteomics (159 paired samples), bulk transcriptomics (3240 HCC vs. 2267 non-HCC samples), single-cell RNA sequencing (RNA-seq) (10 HCC vs. 8 non-HCC samples), spatial transcriptomics, and external CRISPR/Cas9 functional genomics data. Systematic analyses included standardized mean difference (SMD), pathway enrichment, pseudotime trajectory inference, in silico knockout, cell-cell communication, metabolic flux scoring, immune infiltration, clinical correlation, drug sensitivity prediction, and molecular docking. RESULTS: At the protein level, immunohistochemistry (nuclear positivity) and external proteomic data collectively demonstrated consistent SUMO2 overexpression in HCC. Consistent upregulation was also observed at the mRNA level across large-scale cohorts. Single-cell RNA-seq and spatial transcriptomics localized SUMO2 enrichment to malignant hepatocytes and tumor-dominant regions. CRISPR-mediated SUMO2 knockout suppressed proliferation in multiple HCC cell lines. Mechanistically, high SUMO2 expression was significantly associated with metabolic reprogramming involving glycolysis/gluconeogenesis, pyruvate metabolism, and the tricarboxylic acid cycle. SUMO2-high malignant hepatocyte subpopulations exhibited enhanced activity of the macrophage migration inhibitory factor signaling axis and enhanced iron-sensor interactions. Further, the immune infiltration analysis revealed a negative correlation between SUMO2 expression and M1 macrophages and a positive correlation between follicular helper T cells and regulatory T cells. Clinically, elevated SUMO2 levels were found to be associated with adverse prognostic features. Furthermore, high SUMO2 expression was associated with increased sensitivity to dasatinib, and molecular docking simulations predicted potential binding between SUMO2 and dasatinib, with a Vina score of -8.5 kcal/mol. CONCLUSIONS: SUMO2 is aberrantly expressed at the protein, mRNA, single-cell, and spatial transcriptomic levels in HCC and is significantly associated with metabolic reprogramming and altered migration inhibitory factor (MIF)-mediated intercellular communication, suggesting its potential as a novel biomarker for diagnosis and treatment.

Humans↗
PubMed2006

Novel approaches for understanding the mechanisms of wound repair.

Mechanisms that drive wound repair are complex and have challenged wound-healing investigators for many years. In this review, we present four examples of new tools that are being utilized to discover events that drive wound repair and regeneration. Laser capture microdissection facilitates the focused collection of tissue for purposes of genomic or proteomic analysis from specific cell populations within the wound bed. Tissue profiling and protein imaging by matrix-assisted laser desorption ionization mass spectrometry are two proteomic-based tools that permit rapid analysis with spatial orientation and relative abundance of hundreds to thousands of molecules from intact tissues. Another approach uses an in vivo porcine model to harness a strategy of adenoviral-driven receptor overexpression. This biological model closely mimics the human setting and permits transient stimulation along a specific cytokine pathway to tip the balance in favor of accelerated repair. The advent of new approaches that collect cell samples from within their in vivo circumstance while preserving discrete cellular localizations is likely to move the field of wound repair forward.

Adenoviridae↗
PubMed2026

DeepPlaque: a scalable multimodal platform for Aβ pathology and cell analysis in Alzheimer's disease.

Histological analysis is essential for understanding disease pathology and the microenvironment, particularly in Alzheimer's disease (AD), characterized by beta-amyloid (Aβ) plaques that exist as diffuse, fibrillar, and core species, with distinct toxicity levels. However, accurate classification of Aβ plaque types in postmortem brain tissues and profiling of surrounding cells present significant challenges. To address these challenges, we developed "DeepPlaque", an integrated system featuring "PlaqueNet", a deep learning model for automated classification of Aβ plaque species from diverse imaging platforms. DeepPlaque includes automated workflows for cellular phenotyping and proteomic profiling through targeted laser microdissection. PlaqueNet achieves expert-level accuracy (AUC > 90%) in classifying the 3 major Aβ plaque species, supporting consistent and large-scale annotation. By integrating spatial cellular phenotyping with laser microdissection, DeepPlaque enables high-throughput proteomic analysis of Aβ plaque niches, revealing that microglia are more abundant around core and fibrillar Aβ plaques, with increased expression of apolipoprotein E and amyloid precursor protein in core Aβ plaques. This customizable platform enhances the molecular and cellular characterization of Aβ plaque-associated environments, providing critical insights into AD pathology.

Alzheimer Disease↗
PubMed2026

Pathogenic role of serpin B3-positive neutrophils in reinforcing thrombus stiffening during ischemic stroke.

The contribution of immune cells to thrombus architecture and mechanical properties in acute ischemic stroke (AIS) remains poorly understood. Using 3-dimensional imaging and multiplex staining, we mapped immune cells in human stroke thrombi and identified neutrophils as the dominant population. Analysis of 19 thrombi confirmed their positive correlation with collagen, increased stiffness, and poorer clinical outcomes. To preserve spatial context, we developed a laser capture-based proteomic workflow and analyzed thrombus neutrophils from 34 patients with AIS stratified by 90-day outcomes, followed by validation in an independent cohort of 22 patients. Proteomic analysis revealed serpin B3 as a neutrophil-enriched protein strongly correlated with poor prognosis. In murine models of ferric chloride-induced carotid artery thrombosis and middle cerebral artery occlusion, experiments using wild-type, neutrophil-depleted, and Serpinb3a knockout mice demonstrated that neutrophil-derived serpin B3 promotes early thrombus formation, enhances collagen deposition, and contributes to progressive thrombus stiffening. Mechanistically, serpin B3 secreted by neutrophils amplifies thrombus stiffness through upregulation of transforming growth factor β1, neutrophil extracellular traps, and COL1A1. Targeted Serpinb3a knockdown delayed vascular occlusion, improved thrombolysis efficiency, and resulted in better neurological recovery. Collectively, these findings identify a neutrophil-driven mechanism underlying thrombus stiffening and establish SERPINB3 as both a prognostic biomarker and a promising therapeutic target in AIS. This project has been registered with the Chinese Clinical Trial Registration Platform (https://www.chictr.org.cn/index.html) and has successfully passed the review process (registration number: ChiCTR2300077911).

Animals↗
PubMed2026

Comprehensive transcriptomics and proteomics analysis of neointima formation in human saphenous vein: implications for bypass graft disease.

Human saphenous veins (SVs) are widely used as grafts in coronary artery bypass (CABG) surgery but often fail due to neointima formation. Little is known, however, regarding the cellular, transcriptomic, and proteomic dynamics of neointima formation in human veins. Here, we performed transcriptomics and proteomics analysis in an ex vivo tissue culture model of neointima formation in human SVs procured for CABG surgery. Histological examination demonstrated significant elastin degradation and neointima formation (indicated by increased neointima area and neointima-to-media ratio) in SVs subjected to tissue culture. Analysis of data from 72 patients suggests that the progression of SV remodeling and neointima formation differs according to sex and body mass index, which is negatively associated with neointima formation in males only. RNA sequencing demonstrated upregulation of proinflammatory and proliferation-related genes during neointima formation and identified novel processes, including increased cellular stress and DNA damage responses, reflecting tissue trauma associated with vein harvesting. Proteomic analysis identified upregulated extracellular matrix-related and coagulation/thrombosis proteins and downregulated metabolic proteins. Spatial transcriptomics, used to infer regionally enriched gene expression, suggested dynamic alterations in fibroblast and vascular smooth muscle cell (VSMC) states during neointima formation. Specifically, we identified the emergence of HES1+ and matrix metalloproteinase 2- and 14-positive (MMP2+/MMP14+) expression in VSMCs and fibroblasts, respectively, during neointima formation. Furthermore, our data suggest that MIR647, identified through screening, maintains VSMC contractile gene expression. Our findings suggest dynamic transcriptomic and proteomic changes during neointima formation in human veins and provide useful mechanistic information for the pathogenesis of SV graft disease.NEW & NOTEWORTHY Using multiomics and spatial transcriptomics, we uncover dynamic molecular and cellular changes driving neointima proliferation in human saphenous veins, the most common conduit for bypass surgery. Our study highlights sex- and body mass index-associated differences, novel fibroblast and smooth muscle cell states, and a role for microRNA-647 in preserving vascular contractile phenotype. These findings provide new insight into the mechanisms of vein graft failure and may guide future strategies to improve coronary bypass outcomes.

Humans↗
PubMed2006

Microfluidic protein detection through genetically engineered bacterial cells.

Protein microarray technology, in which a large number of capture ligands are spatially arrayed at a high density, presents an attractive method for high-throughput proteomic analysis. Toward this end, we demonstrate the first cell-based protein detection in a microsystem, wherein Escherichia coli cells are genetically engineered to express the desired capture proteins on the membrane surface and are spatially arrayed as sensing elements in a microfluidic device. An E. coli clone expressing peptide ligands with high affinity and high specificity for target molecules was isolated a priori. Then these cells were electrokinetically immobilized on gold electrodes using dielectrophoresis, thus allowing each sensor element to be electrically addressable. Flow cytometry and subsequent fluorescence analysis verified the highly specific capture and detection of target molecules by the bacteria. Finally, through the coexpression of peptide-based capture ligands on the cell surface and fluorescent protein in the cytoplasm, we demonstrate an effective means of directly linking the fluorescence intensity to the density of capture ligands.

Escherichia coli↗
PubMed2025

Tribus: semi-automated discovery of cell identities and phenotypes from multiplexed imaging and proteomic data.

MOTIVATION: Multiplexed imaging and single-cell analysis are increasingly applied to investigate the tissue spatial ecosystems in cancer and other complex diseases. Accurate single-cell phenotyping based on marker combinations is a critical but challenging task due to (i) low reproducibility across experiments with manual thresholding, and, (ii) labor-intensive ground-truth expert annotation required for learning-based methods. RESULTS: We developed Tribus, an interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. We demonstrated that Tribus recovers fine-grained cell types, matching the gold standard annotations by human experts. Additionally, Tribus can target ambiguous populations and discover phenotypically distinct cell subtypes. Through benchmarking against three similar methods in four public datasets with ground truth labels, we show that Tribus outperforms other methods in accuracy and computational efficiency, reducing runtime by an order of magnitude. Finally, we demonstrate the performance of Tribus in rapid and precise cell phenotyping with two large in-house whole-slide imaging datasets. AVAILABILITY AND IMPLEMENTATION: Tribus is available at https://github.com/farkkilab/tribus as an open-source Python package.

Proteomics↗
PubMed2005

The future of post-genomic biology at the proteomic level: an outlook.

Drug discovery and early-stage drugs and biomarkers development is a continuous adaptation and maturation process. The cycle of changes based on new findings is coupled with shifts in research priorities and make this part of pharmaceutical research a challenging endeavour. Over the last years, the emphasis on genomics has shifted to proteomics, the science of understanding how proteins translate gene information into function, and metabonomics, the science of small metabolites that are further apart from genomic projects. Proteomics describes the analysis of the protein complement of a biological sample with respect to temporal and spatial resolution. This technology is based on separation of complex protein mixtures by 2D gel-electrophoresis, in gel digest and mass spectrometric analysis of the protein fragments. Proteomics has been recently flanked by peptidomics, a new research direction aimed at the comprehensive analysis of small (1-20 kDa) polypeptides, thus covering the gap between proteomics and metabonomics. The refinement of peptidomics is based on an essential paradigm related to modularity and diversity. Peptides are a paramount example of how one single gene can release multiple functionalities. We can expect fast progress in understanding protein and peptide networks from a systems biology approach ending in the discovery of new peptide targets. However, the way from a complex sample to potential diagnostic and therapeutic targets will depend on technological developments and from the ability to discriminate true disease-related signals from false positive and negative signals, and the way from target discovery to target validation will not be short.

Aged↗
PubMed2002

Proteome analysis of nuclear matrix proteins during apoptotic chromatin condensation.

The nuclear matrix (NM) is considered a proteinaceous scaffold spatially organizing the interphase nucleus, the integrity of which is affected during apoptosis. Caspase-mediated degradation of NM proteins, such as nuclear lamins, precedes apoptotic chromatin condensation (ACC). Nevertheless, other NM proteins remain unaffected, which most likely maintain a remaining nuclear structure devoid of chromatin. We, therefore, screened various types of apoptotic cells for changes of the nuclear matrix proteome during the process of apoptotic ACC. Expectedly, we observed fundamental alterations of known chromatin-associated proteins, comprising both degradation and translocation to the cytosol. Importantly, a consistent set of abundant NM proteins, some (e.g. hNMP 200) of which displaying structural features, remained unaffected during apoptosis and might therefore represent constituents of an elementary scaffold. In addition, proteins involved in DNA replication and DNA repair were found accumulated in the NM fraction before cells became irreversibly committed to ACC, a time point characterized in detail by inhibitor studies with orthovanadate. In general, protein alterations of a consistent set of NM proteins (67 of which were identified), were reproducibly detectable in Fas-induced Jurkat cells, in UV-light treated U937 cells and also in staurosporine-treated HeLa cells. Our data indicate that substantial alterations of proteins linking chromatin to an elementary nuclear protein scaffold might play an intriguing role for the process of ACC.

Apoptosis↗