Biology subjects

Calura, E.

Publications and source records attributed to Calura, E..

4 recordsLinked to original sources

bioRxiv2024

Dissect mitochondrial activity by transcriptome data with mitology R package

Mitochondria are dynamic organelles that play crucial roles in energy transformation, biosynthesis, and cellular signaling. They actively process biological information, detecting and reacting to both internal and external stimuli. Through intricate physical interactions and diffusion mechanisms within cellular networks, mitochondria integrate diverse inputs and generate signals that finely adjust cellular functions and overall physiology. As a result, the phenotypic expressions of impaired mitochondrial function can exhibit high variability. High-throughput transcriptomic data can capture these changes, but traditional pathway analyses performed on common databases often struggle to specifically detect mitochondrial alterations. This is primarily due to the size of pathways, where the mitochondrial component is typically a small portion of the examined signaling network. To allow a specific exploration of mitochondrial activity through transcriptomic profiles, we developed the mitology R package. We started with a collection of genes whose proteins localize in to the mitochondria, derived from specialized databases like MitoCarta, IMPI, MSeqDR, and from the Gene Ontology database (genes annotated with terms related to mitochondri- in their description). Then, exploiting the mitochondrial gene list, mitology provides ready-to-use implementations of MitoCarta pathways and also a reorganization of general pathway databases, like Reactome and Gene Ontology, with a specific focus on the pathways related to mitochondria activity. Finally, mitology utilizes these mitochondria-focused pathways to conduct mitochondrial pathway analyses, enabling single-sample assessments. Furthermore, we extended the functionality of our package to accommodate classical gene expression data, as well as the newest techniques of single-cell and spatial transcriptomics. Mitology emerges as a novel R package adept at dissecting and unraveling mitochondrial activity, serving as an instrument for conducting targeted mitochondrial studies.

bioinformatics↗

bioRxiv2024

CD300e as a Driver of Immunosuppressive Tumor Microenvironment in Colorectal Cancer

Colorectal cancer (CRC) progression is shaped by the tumor microenvironment, particularly tumor-associated macrophages (TAMs), which often adopt immunosuppressive functions. CD300e, a myeloid receptor involved in immune regulation, has an uncharacterized role in CRC. Here, we show that CD300e is selectively upregulated in tumor-infiltrating monocytes and macrophages, driving a suppressive phenotype marked by impaired antigen presentation. In vitro cocultures of patient-derived tumor organoids and human monocytes revealed that tumor-derived signals induce CD300e expression and promote a protumorigenic macrophage profile. Using CD300e knockout mice in AOM/DSS and MC38 CRC models, we found that CD300e loss reduced tumor burden, enhanced MHC expression on TAMs, and improved T-cell responses. Transcriptomic and functional analyses demonstrated that CD300e-deficient macrophages exhibit increased phagocytosis, upregulated antigen presentation, and greater support for T-cell proliferation and cytotoxicity. Adoptive transfer confirmed that macrophage-intrinsic CD300e expression is sufficient to suppress T-cell function and promote tumor growth. Our findings identify CD300e as a critical regulator of macrophage-mediated immune suppression in CRC and a potential target for reprogramming TAMs to enhance immunotherapy.

cancer biology↗

bioRxiv2024

Atypical chemokine receptor 3 regulates synaptic removal in disease astrocytes

Astrocytes participate in the clearance of obsolete or unwanted neuronal synapses. However, the molecular machinery involved in recognizing these synapses remains unclear, particularly under pathological conditions. Here, we investigated the phagocytic process of astrocytes through individual gene silencing with a druggable gene library. Our study demonstrates that astrocyte- mediated synapse engulfment is regulated by the Atypical chemokine receptor 3 (Ackr3). Mechanistically, we showed that Ackr3 recognizes phosphatidylethanolamine (PE)-bound C-X-C motif chemokine 12 (CXCL12) at synaptic terminals both in vitro and in vivo, thus serving as a novel marker of synaptic dysfunction. Notably, both the receptor and its ligand are upregulated in post- mortem human Alzheimers disease (AD) brains, and AD mouse models. Downregulation of the Ackr3 in AD mice significantly diminishes astrocyte-mediated synaptic elimination, and rescues pathological phenotypes, including synapse loss and cognitive impairment. Overall, this work unveils a novel, possibly targetable mechanism of astrocyte-mediated synaptic engulfment implicated in neurodegenerative disease.

neuroscience↗

bioRxiv2023

signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data

Over the last decade, many studies and some clinical trials have proposed gene expression signatures as a valuable tool for understanding cancer mechanisms, defining subtypes, monitoring patient prognosis, and therapy efficacy. However, technical and biological concerns about reproducibility have been raised. Technical reproducibility is a major concern: we currently lack a computational implementation of the proposed signatures, which would provide detailed signature definition and assure reproducibility, dissemination, and usability of the classifier. Another concern regards intratumor heterogeneity, which has never been addressed when studying these types of biomarkers using bulk transcriptomics. With the aim of providing a tool able to improve the reproducibility and usability of gene expression signatures, we propose signifinder, an R package that provides the infrastructure to collect, implement, and compare expression-based signatures from cancer literature. The included signatures cover a wide range of biological processes from metabolism and programmed cell death, to morphological changes, such as quantification of epithelial or mesenchymal-like status. Collected signatures can score tumor cell characteristics, such as the predicted response to therapy or the survival association, and can quantify microenvironmental information, including hypoxia and immune response activity. signifinder has been used to characterize tumor samples and to investigate intra-tumor heterogeneity, extending its application to single-cell and spatial transcriptomic data. Through these higher-resolution technologies, it has become increasingly apparent that the single-sample score assessment obtained by transcriptional signatures is conditioned by the phenotypic and genetic intratumor heterogeneity of tumor masses. Since the characteristics of the most abundant cell type or clone might not necessarily predict the properties of mixed populations, signature prediction efficacy is lowered, thus impeding effective clinical diagnostics. Through signifinder, we offer general principles for interpreting and comparing transcriptional signatures, as well as suggestions for additional signatures that would allow for more complete and robust data inferences. We consider signifinder a useful tool to pave the way for reproducibility and comparison of transcriptional signatures in oncology.

bioinformatics↗