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Martelotto, L.

Publications and source records attributed to Martelotto, L..

6 recordsLinked to original sources

Autoimmune-like CD8⁺ T Cell Responses Drive Atherosclerotic Plaque Instability and Predict Cardiovascular Events

Background and aimsAtherosclerotic plaque rupture is a major cause of myocardial infarction and stroke. However, the precise drivers of plaque destabilisation remain elusive. We hypothesised that antigen-driven, autoimmune-like T cell responses are central to the destabilisation and rupture of atherosclerotic plaques. MethodsTo dissect T cell responses specifically in unstable compared to stable plaques, we leveraged near-infrared autofluorescence (NIRAF) imaging-guided dissection of human carotid plaques. We also used our tandem stenosis model reflecting plaque instability as seen in patients to differentiate between unstable and stable plaques in mice. To explore T cell involvement, we studied T cell differentiation states and T cell receptor (TCR) repertoires by single-cell multi-omics. Then, testing if antigen-driven CD8+ T cell responses drive plaque instability in mice, we applied a combination of AAV8-PCSK9-induced atherosclerosis, tandem stenosis and TCR transgenic mice. Finally, we leveraged data from the AtheroExpress Biobank Study to link T cell immunity to histology-defined instability and cardiovascular outcomes. ResultsT cell responses in unstable versus stable atherosclerosis were distinct. Unstable human plaques contained highly expanded, autoimmune-like CD8 T cells with markedly increased cytotoxic signatures, reduced exhaustion and distinct clonal repertoires compared to stable regions. Most plaque CD8 T cells exhibited a pronounced tissue-resident transcriptional program. Moreover, the transcriptional signature of these plaque resident T cells was distinct from multiple other human tissues. Autoimmune-like cytotoxic and tissue-resident CD8+ T cell responses were also evident in murine atherosclerosis, where restricting the activation of antigen-driven CD8+ T cells prevented plaque destabilisation. Importantly, analysis of carotid endarterectomy samples from >1000 patients identified that intraplaque cytotoxic CD8 T cell gene signatures strongly correlated with histological instability and predicted future strokes. ConclusionsIntegrated human, murine and clinical analyses demonstrate that autoimmune-like, cytotoxic CD8 T cell responses are central drivers of plaque instability and major cardiovascular events. Targeting pathogenic CD8 T cell responses may thus offer a compelling immunomodulatory strategy to stabilise plaques and reduce the risks of stroke and myocardial infarction. Graphical AbstractO_ST_ABSKey QuestionC_ST_ABSRupture of unstable atherosclerotic plaques is a typical cause of myocardial infarction and stroke. To understand the underlying cause and to prevent plaque rupture, we addressed the central hypothesis that autoimmune-like T cell responses drive plaque destabilisation and rupture. Key FindingsCD8+ T cells are clonally expanded with increased cytotoxic signatures in unstable versus stable plaques (mice and humans) and require antigen recognition to drive plaque instability. Cytotoxic CD8+ T cell signatures in excised plaques correlate with increased future cardiovascular events. Take Home MessageAutoimmune-like adaptive immune reactions, dominated by CD8+ T cells, are a major driver of plaque instability/rupture. Therefore, targeting pathogenic CD8 T cell responses offers a compelling immunomodulatory strategy to stabilise plaques and reduce the risk of myocardial infarction and stroke. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/720043v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@bd83dcorg.highwire.dtl.DTLVardef@1bee3borg.highwire.dtl.DTLVardef@1b56bc0org.highwire.dtl.DTLVardef@1b5176f_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

The Spatial Atlas of Human Anatomy (SAHA): A Multimodal Subcellular-Resolution Reference Across Human Organs

The Spatial Atlas of Human Anatomy (SAHA) represents the first multimodal, subcellular- resolution reference of healthy adult human tissues across multiple organ systems. Integrating spatial transcriptomics, proteomics, and histological features across over 15 million cells from more than 100 donors, SAHA maps conserved and organ-specific cellular niches in gastrointestinal and immune tissues. High-resolution profiling using CosMx SMI, 10x Xenium, RNAscope, GeoMx DSP, and single-nucleus RNA-seq reveals spatially organized cell states, rare adaptive immune populations, and tissue-specific cell-cell interactions and ligand-receptor pairs. Comparative analyses with colorectal cancer and inflammatory bowel disease demonstrate the power of SAHA to detect disease-associated spatial disruptions, including crypt dedifferentiation, perineural invasion, and therapy-resistant immune remodeling. All data are openly accessible through a FAIR-compliant interactive portal to support exploration, benchmarking, and machine learning model training. Through SAHA, we provide a foundational framework for spatial diagnostics and next-generation precision medicine grounded in a comprehensive human tissue atlas, enabling the development of context-aware models that simulate tissue behavior, decode complex pathologies, and accelerate therapeutic innovation at unprecedented scale.

systems biology↗

A Machine Learning One-Class Logistic Regression Model to Predict Stemness in Single Cell Transcriptomics and Spatial Omics Datasets

Cell annotation is a crucial methodological component to interpreting single cell and spatial omics data. These approaches are often biased and manually curated. Here we harness an existing stemness model for assessing oncogenic states to transform its application to single cell and spatial omic datasets. This one-class logistic regression machine learning algorithm is used to extract transcriptomic or proteomic features from non-transformed stem cells to identify dedifferentiated cell states. We found this method identifies single cell states in metastatic tumor cell populations without the requirement of cell annotation. Finally these stemness indices are applicable across a variety of spatial transcriptomic and proteomic technologies for the identification of oncogenic cell types in the tumor microenvironment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC="FIGDIR/small/539461v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@f2973forg.highwire.dtl.DTLVardef@a7aa9corg.highwire.dtl.DTLVardef@1b1ea27org.highwire.dtl.DTLVardef@183b4a5_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

STOmics-GenX: CRISPR based approach to improve cell identity specific gene detection from spatially resolved transcriptomics

The spatial organisation of cells defines the biological functions of tissue ecosystems from development to disease. Recently, an array of technologies have been developed to query gene expression in a spatial context. These include techniques such as employing barcoded oligonucleotides, single-molecule fluorescence in situ hybridization (smFISH), and DNA nanoball (DNB)-patterned arrays. However, resolution and efficiency vary across platforms and technologies. To obtain spatially relevant biological information from spatially resolved transcriptomics, we combined the Stereo-seq workflow with CRISPRclean technology to develop the STOmics-GenX pipeline. STOmics-GenX not only allowed us to reduce genomic, mitochondrial, and ribosomal reads, but also lead to a [~]2.1-fold increase in the number of detected genes when compared to conventional Stereo-seq (STOmics). Additionally, the STOmics-GenX pipeline resulted in an improved detection of cell type specific genes, thereby improving cellular annotations. Most importantly, STOmics-GenX allowed for enhanced detection of clinically relevant biomarkers such as Alpha-fetoprotein (AFP), enabling the identification of two spatially distinct subsets of hepatocytes in hepatocellular carcinoma tissue. Thereby, combining CRISPRclean technology with STOmics not only allowed improved gene detection but also paved the way for spatial precision oncology by improved detection of clinically relevant biomarkers.

molecular biology↗

Fancm regulates meiotic double-strand break repair pathway choice in mammals

Meiotic crossovers are required for accurate chromosome segregation and to produce new allelic combinations. Meiotic crossover numbers are tightly regulated within a narrow range, despite an excess of initiating DNA double-strand breaks. Here, we describe the tumour suppressor FANCM as a meiotic anti-crossover factor in mammals. Crossover analyses with single-gamete and pedigree datasets both reveal a genome-wide increase in crossover frequencies in Fancm-deficient mice. Gametogenesis is heavily perturbed in Fancm loss of function mice, which is consistent with the reproductive defects reported in humans with biallelic FANCM mutations. A portion of the gametogenesis defects can be attributed to the cGAS-STING pathway. Despite the gametogenesis phenotypes in Fancm mutants both sexes were capable of producing offspring. We propose that the anti-crossover function and role in gametogenesis of Fancm are separable and will inform diagnostic pathways for human genomic instability disorders.

genetics↗

Epigenetic reprogramming of plasmacytoid dendritic cells drives type I interferon-dependent differentiation of acute myeloid leukemias for therapeutic benefit

Pharmacological inhibition of epigenetic enzymes can have therapeutic benefit, particularly against hematological malignancies. While these agents can affect tumor cell growth and proliferation, recent studies have demonstrated that pharmacological de-regulation of epigenetic modifiers may additionally mediate anti-tumor immune responses. Here we discovered a novel mechanism of immune regulation through the inhibition of histone deacetylases (HDACs). In a genetically engineered model of t(8;21) AML, leukemia cell differentiation and therapeutic benefit mediated by the HDAC inhibitor panobinostat required activation of the type I interferon (IFN) signaling pathway. Plasmacytoid dendritic cells (pDCs) were identified as the cells producing type I IFN in response to panobinostat, through transcriptional activation of IFN genes concomitant with increased H3K27 acetylation at these loci. Depletion of pDCs abrogated panobinostat-mediated activation of type I IFN signaling in leukemia cells and impaired therapeutic efficacy, while combined treatment of panobinostat and recombinant IFN improved therapeutic outcomes. These discoveries offer a new therapeutic approach for t(8;21) AML and demonstrate that epigenetic rewiring of pDCs enhances anti-tumor immunity, opening the possibility of exploiting this cell type as a new target for immunotherapy.

cancer biology↗