Biology subjects

Ticconi, F.

Publications and source records attributed to Ticconi, F..

4 recordsLinked to original sources

bioRxiv2026

Tumors accumulate expanded GATA3-dependent tissue Tregs

Targeting Tregs is a potential strategy to improve cancer therapies. However, which Tregs accumulate in response to tumoral processes, and how tumors affect their phenotype, is poorly understood. Here we show that tumor Tregs are equivalent to effector tissue Tregs in steady state organs. We used a mouse model of intestinal neoplasia to demonstrate that one early event in carcinogenesis is sufficient to induce local accumulation of Tregs resembling human tumor Tregs. Treg accumulation was driven by TCR-dependent oligoclonal expansion of tissue Tregs with an effector Treg phenotype. Treg expansion was independent of CCR8, IL33R and CD137, which were previously linked to tumor Treg. In contrast, GATA3 was required for effector tissue Tregs and for their expansion in response to neoplasia. Our findings identify GATA3-dependent clonal expansion of effector tissue Tregs as a key event in promoting tumor growth. HighlightsO_LIAn early tumorigenic event alone drives accumulation of effector tissue Tregs C_LIO_LITregs in tumors are phenotypically akin to effector tissue Tregs C_LIO_LIThe accumulation of Tregs is driven by TCR-dependent oligoclonal expansion C_LIO_LIGATA3 controls tumor-promoting effector tissue Tregs C_LI

immunology↗

bioRxiv2023

RGT: a toolbox for the integrative analysis of high throughput regulatory genomics data

BackgroundMassive amounts of data are produced by combining next-generation sequencing (NGS) with complex biochemistry techniques to characterize regulatory genomics profiles, such as protein-DNA interaction and chromatin accessibility. Interpretation of such high-throughput data typically requires different computation methods. However, existing tools are usually developed for a specific task, which makes it challenging to analyze the data in an integrative manner. ResultsWe here describe the Regulatory Genomics Toolbox (RGT), a computational library for the integrative analysis of regulatory genomics data. RGT provides different functionalities to handle genomic signals and regions. Based on that, we developed several tools to perform distinct downstream analyses, including the prediction of transcription factor binding sites using ATAC-seq data, identification of differential peaks from ChIP-seq data, and detection of triple helix mediated RNA and DNA interactions, visualization, and finding an association between distinct regulatory factors. ConclusionWe present here RGT; a framework to facilitate the customization of computational methods to analyze genomic data for specific regulatory genomics problems. RGT is a comprehensive and flexible Python package for analyzing high throughput regulatory genomics data and is available at: https://github.com/CostaLab/reg-gen. The documentation is available at: https://reg-gen.readthedocs.io

bioinformatics↗

bioRxiv2021

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell epitope mapping

The current COVID-19 pandemic represents a global challenge. A better understanding of the immune response against SARS-CoV-2 is key to unveil the differences in disease severity and to develop future vaccines targeting novel SARS-CoV-2 variants. Feature barcode technology combined with CITE-seq antibodies and DNA-barcoded peptide-MHC I Dextramer reagents enabled us to identify relevant SARS-CoV-2-derived epitopes and compare epitope-specific CD8+ T cell populations between mild and severe COVID-19. We identified a strong CD8+ T cell response against an S protein-derived epitope. CD8+ effector cells in severe COVID-19 displayed hyperactivation, T cell exhaustion and were missing characteristics of long-lived memory T cells. We identify A*0101 WTAGAAAYY as an immunogenic CD8+ T cell epitope with the ability to drive clonal expansion. We provide an in-depth characterization of the CD8+ T cell-mediated response to SARS-CoV-2 infection which will be relevant for the development of molecular and targeted therapies and potential adjustments of vaccination strategies.

immunology↗

bioRxiv2018

Variants of DNMT3A cause transcript-specific DNA methylation patterns and affect hematopoietic differentiation

The de novo DNA methyltransferase 3A (DNMT3A) plays pivotal roles in hematopoietic differentiation. In this study, we followed the hypothesis that alternative splicing of DNMT3A has characteristic epigenetic and functional sequels. Specific DNMT3A transcripts were either downregulated or overexpressed in human hematopoietic stem and progenitor cells and this resulted in complementary and transcript-specific DNA methylation and gene expression changes. Functional analysis indicated that particularly transcript 2 (coding for DNMT3A2) activates proliferation and induces loss of a primitive immunophenotype, whereas transcript 4 interferes with colony formation of the erythroid lineage. Notably, in acute myeloid leukemia (AML) expression of transcript 2 correlates with its in vitro DNA methylation and gene expression signatures and is associated with overall survival, indicating that DNMT3A variants impact also on malignancies. Our results demonstrate that specific DNMT3A variants have distinct epigenetic and functional impact. Particularly DNMT3A2 triggers hematopoietic differentiation and the corresponding signatures are reflected in AML.

cell biology↗