Biology subjects

Ceccarelli, F.

Publications and source records attributed to Ceccarelli, F..

9 recordsLinked to original sources

bioRxiv2025

Transposable Elements and Homotypic Niches Drive Immune Dynamics and Resistance in Melanoma Epigenetic-based immunotherapy

Melanoma plasticity drives immune evasion and therapy resistance through dynamic cell-state transitions beyond genetic alterations. Epigenetic remodeling critically influences such processes, yet its role in reshaping the tumor ecosystem under therapeutic pressure remains unresolved. Here, we profiled longitudinal biopsies from melanoma patients treated in the phase Ib NIBIT-M4 epi-immunotherapy clinical trial (NCT02608437), testing the combination of a DNMT1 inhibitor with anti-CTLA4 using single-cell multiome and high-resolution spatial transcriptomics. Integrated analyses resolved seven malignant meta-programs, including a rare Wnt/{beta}-catenin-driven melanocytic state and a de-differentiated neural crest-like state enriched in non-responders. Spatial modeling revealed that homotypic clustering stabilizes resistant programs, with neural crest-like cells forming compact, centrally localized niches, whereas Wnt/{beta}-catenin subpopulations displayed a bimodal architecture, either cohesive clusters sustained by adhesion or dispersed, transcriptionally plastic cells. Responders exhibited progressive enrichment of an antigen presentation/interferon program and coordinated remodeling of the tumor microenvironment with T and B cell expansion, whereas tumors from non-responder patients maintained stable composition of neural crest-like clusters. Epigenetic therapy reactivated transposable elements, providing both regulatory signals that prime innate immunity within microenvironment and generating antigens that drive immunoediting and immunogenicity of Antigen presentation/interferon cell states in responders. Finally, NFATC2 emerged as a master regulator of neural crests-like transcriptional phenotypes and promoter of resistance to therapeutic interventions in melanoma patients. NFATC2 perturbation was able to shift tumor cells towards more differentiated and immunogenic states. These findings reveal how epigenetic-based immunotherapy reshapes melanoma ecosystems, provide mechanistic insights into how multiple transcriptional programs promote tumor plasticity and resistance to both combinatorial therapies and immune checkpoint blockade, identify spatial clustering as a principle stabilizing resistant niches, and highlight {beta}-catenin and NFATC2 as actionable vulnerabilities to overcome resistance.

genomics↗

bioRxiv2025

OmniPath: integrated knowledgebase for multi-omics analysis

Analysis and interpretation of omics data largely benefit from the use of prior knowledge. However, this knowledge is fragmented across resources and often is not directly accessible for analytical methods. We developed OmniPath (https://omnipathdb.org/), a database combining diverse molecular knowledge from 168 resources. It covers causal protein-protein, gene regulatory, miRNA, and enzyme-PTM (post-translational modification) interactions, cell-cell communication, protein complexes, and information about the function, localization, structure, and many other aspects of biomolecules. It prioritizes literature curated data, and complements it with predictions and large scale databases. To enable interactive browsing of this large corpus of knowledge, we developed OmniPath Explorer, which also includes a large language model (LLM) agent that has direct access to the database. Python and R/Bioconductor client packages and a Cytoscape plugin create easy access to customized prior knowledge for omics analysis environments, such as scverse. OmniPath can be broadly used for the analysis of bulk, single-cell and spatial multi-omics data, especially for mechanistic and causal modeling. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/675512v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@17c2b6borg.highwire.dtl.DTLVardef@1069835org.highwire.dtl.DTLVardef@1f2ce76org.highwire.dtl.DTLVardef@1d0b34f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Topography Aware Optimal Transport for Alignment of Spatial Omics Data

Understanding the spatial organization of tissues is essential for uncovering cellular communication, developmental processes, and disease mechanisms. Recent advances in spatial omics technologies have provided unprecedented insight into tissue spatial organization, but challenges remain in aligning spatial slices and integrating complementary single-cell and spatial data. Here, we propose TOAST (Topography-aware Optimal Alignment of Spatially-resolved Tissues), a novel OT-based framework that extends the classical Fused Gromov-Wasserstein (FGW) objective to more comprehensively model the heterogeneity of local molecular interactions. By introducing spatial coherence, quantified through the entropy of local neighborhoods, and neighborhood consistency, which preserves the expression profiles of neighboring spots, TOASTs objective function significantly improves the alignment of spatially resolved tissue slices and the mapping between single-cell and spatial data. Through comprehensive evaluations on both simulated and real-world datasets, including human brain cortex Visium data, Axolotl brain Stereo-seq data, mouse embryo seqFISH data, and Imaging Mass Cytometry from multiple cancer types, we demonstrate that our method consistently outperforms traditional FGW and other OT-based alignment methods. Specifically, TOAST improves the accuracy of spatial slice alignment, better preserves cell type compositions, recovers lineage trajectories in developmental brain data, and reconstructs spatial relationships in spatial transcriptomics mouse embryo data. By integrating spatial constraints into OT, our framework provides a principled approach to enhance the biological interpretability of spatially resolved omics data and facilitate multimodal data integration.

bioinformatics↗

bioRxiv2024

Dynamic Attentional Control Through Mixed Prefrontal Cortex Resources

Spatial attention can be either involuntarily drawn to salient, unexpected events (exogenous attention) or voluntarily directed (endogenous attention). Evidence suggests a link of both forms of attention to the (oculo)motor system. We investigated the role of the prefrontal cortex (PFC) in this relationship using a task that spatially dissociated attention from motor planning in two monkeys. PFC units flexibly encoded either the attended location or motor target, with some showing overlapping coding. Endogenous attention promotes an early engagement of these shared resources, producing two key effects: (1) it prevents interference between motor and attention systems, and (2) it regulates the extent of the exogenous shifts for attentional capture, with stronger shifts occurring when endogenous attention is weak. Overall, we show that there are separate attention and motor systems, each of which can flexibly draw on some "overlapping" resources based on environmental and internal demands.

neuroscience↗

bioRxiv2024

Out of the single-neuron straitjacket: neurons within assemblies change selectivity and their reconfiguration underlies dynamic coding

We investigated cell assemblies in the frontal cortex of macaques during two discrimination tasks. Focusing on the period of goal-action transformation, we extracted spikes fired during assembly activation from the full neural activity and showed that the contribution of a neuron to assembly coding, when it coordinates with other assembly neurons, differs from its coding in isolation. Neurons with their flexible participation to multiple assemblies contributed to the encoding of new information not encoded by the neurons alone. Even non-discriminative neurons acquired selectivity as part of the collective activity of the assemblies. Thus, neurons in their assemblies process distinct information for various purposes as a chess simul master, playing on multiple chessboards. The reconfiguration of the participation of the neurons into different assemblies in the goal-action transformation process translated into a dynamic form of coding, whereas minimal reconfiguration was associated with the static goal coding of the memory period.

neuroscience↗

bioRxiv2024

History bias and its perturbation of the stimulus representation in the macaque prefrontal cortex.

Multiple history biases affect our representation of magnitudes, such as time, distance, and size. It is not clear whether the previous stimuli interfere with the discrimination process from the moment of stimulus presentation, during working memory retention, or even later during the decision-making phase. We used a spatial discrimination task involving two stimuli of different magnitudes, presented sequentially at various distances from the center. The monkeys task was to select the farthest of them. We showed that the previous stimulus magnitude generated a contraction bias effect, but only when its stimulus features differed from those of the current stimulus. In this case, at the neural level we also observed that the decoding of the stimulus magnitude achieved the highest accuracy when it matched the magnitude of the preceding stimulus for which the decoder was trained. This indicates that past stimuli can affect magnitude processing already during the stimulus presentation, even before the decision process. Interestingly, this effect manifested when the trace of the previous stimulus magnitude reactivated in the second part of the stimulus presentation after an "activity-silent" period.

neuroscience↗

bioRxiv2022

Integrated optical device for Structured Illumination Microscopy

Structured Illumination Microscopy (SIM) is a key technology for high resolution and super-resolution imaging of biological cells and molecules. The spread of portable and easy-to-align SIM systems requires the development of novel methods to generate a light pattern and to shift it across the field of view of the microscope. Here we show a miniaturized chip that incorporates optical waveguides, splitters, and phase shifters, to generate a 2D structured illumination pattern suitable for SIM microscopy. The chip creates three point-sources, coherent and controlled in phase, without the need for further alignment. Placed in the pupil of a microscopes objective, the three sources generate a hexagonal illumination pattern on the sample, which is spatially translated thanks to thermal phase shifters. We validate and use the chip, upgrading a commercial inverted fluorescence microscope to a SIM setup and we image biological sample slides, extending the resolution of the microscope.

cell biology↗

bioRxiv2020

Converting networks to predictive logic models from perturbation signalling data with CellNOpt

MotivationThe molecular changes induced by perturbations such as drugs and ligands are highly informative of the intracellular wiring. Our capacity to generate large data-sets is increasing steadily as new experimental approaches are developed. A useful way to extract mechanistic insight from the data is by integrating them with a prior knowledge network of signalling to obtain dynamic models. Logic models scale better with network size than alternative kinetic models, while keeping the interpretation of the model simple, making them particularly suitable for large datasets. ResultsCellNOpt is a collection of Bioconductor R packages for building logic models from perturbation data and prior knowledge of signalling networks. We have recently developed new components and refined the existing ones. These updates include (i) an Integer Linear Programming (ILP) formulation which guarantees efficient optimisation for Boolean models, (ii) a probabilistic logic implementation for semi-quantitative datasets and (iii) the integration of MaBoSS, a stochastic Boolean simulator. Furthermore, we introduce Dynamic-Feeder, a tool to identify missing links not present in the prior knowledge. We have also implemented systematic post-hoc analyses to highlight the key components and parameters of our models. Finally, we provide an R-Shiny tool to run CellNOpt interactively. AvailabilityR-package(s): https://github.com/saezlab/cellnopt Contactjulio.saez@bioquant.uni-heidelberg.de Supplementary informationSupplemental Text.

bioinformatics↗

bioRxiv2018

A functional landscape of chronic kidney disease entities from public transcriptomic data

To develop efficient therapies and identify novel early biomarkers for chronic kidney disease an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in CKD origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for nine kidney disease entities that account for a majority of CKD worldwide. We included data from five distinct studies and compared glomerular gene expression profiles to that of non-tumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms and conditions, that we mitigated with a bespoke stringent procedure. This allowed us to perform a global transcriptome-based delineation of different kidney disease entities, obtaining a landscape of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. Furthermore, we derived functional insights by inferring activity of signaling pathways and transcription factors from the collected gene expression data, and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating e.g. that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in RPGN whereas not expressed in control kidney tissue. These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities, that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate this, we provide our results as a free interactive web application: https://saezlab.shinyapps.io/ckd_landscape/. Translational StatementChronic kidney disease is a combination of entities with different etiologies. We integrate and analyse transcriptomics analysis of glomerular from different entities to dissect their different pathophysiology, what might help to identify novel entity-specific therapeutic targets.

pathology↗