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Codato, R.

Publications and source records attributed to Codato, R..

3 recordsLinked to original sources

Identification of non-covalent inhibitors for the atypical peroxiredoxin PRDX5 as a therapeutic strategy in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is an aggressive asbestos-linked cancer with limited therapeutic options and a dismal 5-year survival rate of [~]5%. While aberrant production of reactive oxygen and nitrogen species (ROS/RNS) is a hallmark of MPM, targeted approaches to exploit these redox vulnerabilities remain scarce. Here, using the MOSAIC multimodal cancer patient atlas, we identify Peroxiredoxin 5 (PRDX5) as being significantly upregulated in the epithelioid subtype of MPM. We show that MPM cells exhibit enhanced resistance to nitrosative and oxidative stress compared to healthy mesothelial cells, a phenotype correlated with basal PRDX5 expression. Next, utilising a machine learning guided discovery pipeline, we identified three putative allosteric pockets in PRDX5 and conducted a virtual screen of 3.6 million compounds. High-throughput biochemical validation of 452 candidates yielded 36 non-covalent hits, including sub-micromolar inhibitors. These findings establish PRDX5 as a novel, subtype specific therapeutic target in MPM and provide a chemical framework for the development of next-generation redox-modulating oncology treatments.

cancer biology↗

Deciphering Cellular Ecosystems Driving Tumor Progression and Immune Escape from Spatial Transcriptomics and Single-Cell with COMPOTES

Cell-cell communication is central to understanding the complex interactions within the tumor microenvironment. However, current methods fail to identify recurrent communication patterns across patient cohorts from spatial transcriptomics, as they are often limited to single samples or lack essential spatial context. Yet this is essential for understanding how local environments influence cell phenotype and states, and shape the entire cellular ecosystem. We introduce a machine-learning approach that models local, spatially aware ligand-receptor interactions and uses matrix factorization to extract global multicellular programs from large cohorts representing the complex biology of cancer. Applied to a multimodal muscle-invasive bladder cancer cohort of 146 patients, it uncovered 45 communication programs defined by distinct ligand-receptor pairs and cellular niches. In particular, we identified a conserved immune program linked to stalled anti-tumor immunity and a program linking KMT2D loss-of-function mutations with early-stage (T2) tumors, intense proliferation and a favorable response to neoadjuvant chemotherapy.

bioinformatics↗

The SMYD3 methyltransferase promotes myogenesis by activating the myogenin regulatory network

The coordinated expression of myogenic regulatory factors, including MyoD and myogenin, orchestrates the steps of skeletal muscle development, from myoblast proliferation and cell-cycle exit, to myoblast fusion and myotubes maturation. Yet, it remains unclear how key transcription factors and epigenetic enzymes cooperate to guide myogenic differentiation. Proteins of the SMYD (SET and MYND domain-containing) methyltransferase family participate in cardiac and skeletal myogenesis during development in zebrafish, Drosophila and mice. Here, we show that the mammalian SMYD3 methyltransferase coordinates skeletal muscle differentiation in vitro. Overexpression of SMYD3 in myoblasts promoted muscle differentiation and myoblasts fusion. Conversely, silencing of endogenous SMYD3 or its pharmacological inhibition impaired muscle differentiation. Genome-wide transcriptomic analysis of murine myoblasts, with silenced or overexpressed SMYD3, revealed that SMYD3 impacts skeletal muscle differentiation by targeting the key muscle regulatory factor myogenin. The role of SMYD3 in the regulation of skeletal muscle differentiation and myotube formation, partially via the myogenin transcriptional network, highlights the importance of methyltransferases in mammalian myogenesis.

cell biology↗