Biology subjects

Mosca, E.

Publications and source records attributed to Mosca, E..

8 recordsLinked to original sources

bioRxiv2026

Proteome analysis reveals common players between the physiological neurodegeneration of the ascidian Ciona intestinalis and the pathological neurodegeneration in humans

Tunicates, including ascidians, are recognized as the true sister group of vertebrates and are emerging as models to study the development and degeneration of central nervous system (CNS). Ascidian larvae have the typical chordate body plan that includes a dorsal neural tube. During their metamorphosis, a deep tissue reorganization takes place, with some tissues that degenerate while others develop to become functional during the adult life. The larval CNS also degenerates and most neurons disappear, making room for the formation of adult CNS. The genome of the ascidian Ciona intestinalis has been sequenced and annotated, with several CNS specific genes that have been characterized, revealing specification mechanisms shared with humans. These features make ascidian metamorphosis a good model to study the mechanisms underlying physiological CNS degeneration and to compare them to the pathological conditions typical of neurodegenerative diseases. In order to shed light on the molecular determinants of C. intestinalis metamorphosis and neurodegeneration, we analyzed the proteome at three stages of development: swimming larva (SwL, Hotta stage 28), settled larva (SetL, Hotta stage 32) and metamorphosing larva (MetL, Hotta stage 34). A total of 405 modulated proteins were identified by mass spectrometry by comparing the three stages. Enrichment and network analysis showed the involvement of several processes/pathways, including autophagy and mTOR pathway, and actin cytoskeleton organization and remodeling among the most significant ones. This study elucidates molecular pathways underlying ascidian metamorphosis and highlights shared mechanisms between physiological neurodegeneration in ascidians and pathological neurodegeneration in humans.

neuroscience↗

bioRxiv2025

The two sides of resistance: aggressiveness and mitotic instability as the Achilles heel of Osimertinib-resistant NSCLC

Non-small cell lung cancer (NSCLC) represents majority of lung cancer cases and remains a leading cause of cancer mortality worldwide. Tumors carrying activating mutations in the epidermal growth factor receptor (EGFR) are highly sensitive to EGFR tyrosine kinase inhibitors (TKIs), with third-generation inhibitors such as Osimertinib now established as standard of care. However, acquired resistance to Osimertinib inevitably develops, involving both genetic and non-genetic mechanisms, the latter playing a major role in sustaining cellular plasticity and promoting tumor aggressiveness. Among regulators of adaptive programs, the Polycomb protein BMI1 has emerged as a key factor driving stemness, epithelial-to-mesenchymal transition (EMT), and therapy resistance in multiple cancers, yet its role in Osimertinib resistance remains poorly defined. Here, we show that Osimertinib-resistant H1975 cells, which display greater aggressiveness than their parental counterparts, are enriched in BMI1 target genes and mitotic cell-cycle pathways, establishing a dependency on microtubule dynamics and mitotic control. Functionally, BMI1 drives migration, invasiveness, and tumor progression in resistant cells. This mitotic dependency creates a therapeutic vulnerability that can be exploited with Unesbulin (PTC596), a BMI1 inhibitor that destabilizes microtubules and induces mitotic catastrophe, thereby effectively suppressing tumor growth in vitro and in vivo. Our findings establish BMI1 as a central mediator of Osimertinib resistance and provide a mechanistic and therapeutic rationale for targeting BMI1 and mitotic weaknesses in refractory EGFR-mutant NSCLC.

cancer biology↗

bioRxiv2025

Deciphering the Role of Acetate in Metabolic Adaptation and Drug Resistance in Non-Small Cell Lung Cancer

Resistance to targeted therapies remains a major challenge in EGFR-mutant non-small cell lung cancer (NSCLC). Here, we describe a novel metabolic adaptation in osimertinib-resistant cells characterized by elevated acetate levels and activation of an unconventional pyruvate-acetaldehyde-acetate (PAA) shunt. Integrated transcriptomic, exometabolomic, and functional analyses reveal suppression of canonical metabolic pathways and upregulation of ALDH2 and ALDH7A1, which mediate the NADP+-dependent oxidation of acetaldehyde to acetate, generating NADPH. This shift supports reducing power essential for biosynthesis and redox balance under conditions of oxidative pentose phosphate inhibition. These metabolic changes promote endurance in resistant cells and rewire the interplay between glycolysis, the pentose phosphate pathway, and the tricarboxylic acid cycle, offering a de novo bypass for anaplerosis and bioenergetics. Systematic metabolite profiling revealed distinct transcriptomic and metabolic signatures distinguishing resistant from parental cells. Together, these findings depict a unique, resistance-driven adaptive metabolic shift, and uncover potential therapeutic vulnerabilities in osimertinib-resistant NSCLC.

biochemistry↗

bioRxiv2025

Reprogramming of Osimertinib-Resistant EGFR-mutant NSCLC: The Pyruvate-Acetaldehyde-Acetate Pathway As a Key Driver of Resistance

Osimertinib (Osi) resistance remains a significant challenge in EGFR mutant non-small-cell lung cancer (NSCLC). This study investigates the metabolic reprogramming associated with Osi resistance, identifying key metabolic vulnerabilities that may be targeted for therapeutic intervention. Employing the EGFR-mutant H1975 parental (Par) cell line and its Osi-resistant (OsiR) counterpart, we integrated transcriptomics, metabolomics, nuclear and mitochondrial genomics, functional assays and bioanalytical techniques, as well as advanced 3D imaging to comprehensively define the resistant phenotype. We found that OsiR cells exhibit mitochondrial dysfunction, including impaired oxidative phosphorylation (OXPHOS), mitochondrial DNA mutations, and altered mitochondrial gene expression. To describe this systems-level characterization, we introduce the concept of mitochondromics, a comprehensive profiling of mitochondrial genomic, transcriptomic, structural, and functional changes contributing to therapeutic resistance. Metabolomic profiling revealed a significant accumulation of glycolytic intermediates (lactate, pyruvate, acetate, and acetaldehyde) in the extracellular medium, indicating a shift toward glycolysis and activation of alternative metabolic pathways, including the Warburg effect. Notably, we identified the pyruvate-acetaldehyde-acetate (PAA) pathway as a functionally repurposed metabolic route that facilitates NADPH production, which is critical for antioxidant defense and anabolic processes in OsiR cells. Additionally, although the pentose phosphate pathway (PPP) is not the primary source of NADPH in OsiR cells, it plays a supporting role in biosynthesis, contributing to the production of amino acids, nucleotides, and vitamins. Altered expression of enzymes involved in glycolysis, the TCA cycle, and both oxidative and non-oxidative arms of the PPP further supports an adaptive metabolic network promoting cell growth and resistance to Osi. This study reveals a complex metabolic reprogramming in Osi-resistant EGFR-mutant NSCLC, where a newly identified role for the PAA pathway, alongside integrated mitochondromic alterations emerges as key driver of resistance. These insights uncover potential metabolic vulnerabilities of Osi-resistant tumors and provide a foundation for developing therapeutic strategies to counteract resistance and improve osimertinib efficacy. Targeting these metabolic pathways may offer promising avenues for overcoming resistance in clinical settings.

cancer biology↗

bioRxiv2025

In vitro and in vivo Antiviral Activity of the Acyclic Nucleoside Phosphonate Prodrug LAVR-289 against Poxvirus and African Swine Fever Virus Replication

Poxviruses are double-stranded DNA viruses including relevant zoonotic pathogens with high morbidity. Although African swine fever virus (ASFV) belongs to the Asfarviridae family and is not strictly classified as a member of the Poxviridae, both fall within the same class of Pokkesviricetes that replicate in the cytoplasm, and some poxviruses pose potential biological warfare threats. Among compounds targeting these viruses, acyclic nucleoside phosphonate prodrugs are nucleoside analogues inhibitors of viral DNA polymerases that have been identified as promising agents. However, some limitations related to their toxicity and the rapid emergence of resistance highlight the need for new antiviral molecules. In this study, the new nucleoside analogue LAVR-289 was shown to effectively inhibit the viral replication by intervening early in the viral replication step, targeting a specific domain of the poxvirus DNA polymerase. Using monkeypox virus models, the subcutaneous or oral administration of LAVR-289 demonstrates protective efficacy in infected animal models without toxicity or behavioral modification. The stability in vivo, long shelf-life and efficacy make LAVR-289 a promising candidate for further development and stockpiling as a medical countermeasure against dsDNA virus outbreaks. Its broad-spectrum efficacy is a real asset in a context of recurrent viral epidemics, risk of bioterrorism and emergence of resistance strains in the population. HighlightsO_LILAVR-289 is a unique acyclic nucleoside phosphonate prodrug targeting viral DNA polymerases. C_LIO_LILAVR-289 displays antiviral activity against dsDNA viruses, ASFV and poxviruses. C_LIO_LIFirst report of in vivo evaluation of LAVR-289 against MPXV by subcutaneous and oral administration. C_LIO_LILAVR-289 reduces clinical signs and increase survival in animal models. C_LI

microbiology↗

bioRxiv2024

MargheRita: an R package for LC-MS/MS SWATH metabolomics data analysis and confident metabolite identification based on a spectral library of reference standards

In the field of untargeted metabolomics, the deployment of high-resolution mass spectrometry technologies generates an immense volume of complex metabolite signals. This data density necessitates sophisticated computational frameworks for post-acquisition processing and the integration of specialized databases for accurate metabolite identification. Currently, many web-based data processing solutions offer fragmented workflows, covering only specific stages of the analysis and frequently requiring researchers to migrate data across multiple, often incompatible, platforms. To address these challenges, we introduced margheRita, an R package designed to streamline the workflow for untargeted metabolomic profiling. Developed to work seamlessly with MS-DIAL output, margheRita provides a comprehensive pipeline for liquid chromatography-tandem mass spectrometry (LC-MS/MS) data. This tool is particularly effective for Data-Independent Acquisition (DIA) experiments, where the high-resolution acquisition of all MS/MS spectra demands rigorous and integrated processing capabilities. A key innovation of margheRita is its ability to significantly enhance fragment matching accuracy. It achieves this by utilizing an original, curated high-quality spectral library from authentic reference standards. This library includes data acquired in both positive and negative ionization polarities using various chromatographic columns, ensuring high versatility. By bridging the gap between initial MS-DIAL processing and final biological insights, margheRita offers a holistic solution from metabolite identification to the functional interpretation of complex biological datasets.

bioinformatics↗

bioRxiv2023

Cross-talk quantification in molecular networks with application to pathway-pathway and cell-cell interactions.

Disease phenotypes can be described as the consequence of interactions among molecular processes that are altered beyond resilience. Here, we address the challenge of assessing the possible alteration of intra- and inter-cellular molecular interactions among gene sets, which are intended to represent processes and or cellular phenotypes. We present an approach, designated as "Ulisse", which complements the existing methods of enrichment analysis and cell-cell communication analysis. It can be applied to a gene list as well as multiple ranked gene lists, typically derived in the context of omics or multi-omics studies. The approach highlights the presence of alterations in those components that control the interactions between processes or cells. Crosstalk quantification is supported by two null models. Further, the approach provides an additional way of identifying the genes associated with the phenotype. As a proof-of-concept, we applied Ulisse to study the alteration of pathway crosstalks and cell-cell communications in triple negative breast cancer samples, based on single-cell RNA sequencing. In conclusion, our work supports the usefulness of crosstalk analysis as an additional instrument in the "toolkit" of biomedical research for translating complex biological data into actionable insights.

bioinformatics↗

bioRxiv2022

scMuffin: an R package for resolving solid tumor heterogeneity from single-cell expression data

INTRODUCTIONSingle-cell (SC) gene expression analysis is crucial to dissect the complex cellular heterogeneity of solid tumors, which is one of the main obstacles for the development of effective cancer treatments. Such tumors typically contain a mixture of cells with aberrant genomic and transcriptomic profiles affecting specific sub-populations that might have a pivotal role in cancer progression, whose identification eludes bulk RNA-sequencing approaches. We presentscMuffin, an R package that enables the characterization of cell identity in solid tumors on the basis of a various and complementary analyses on SC gene expression data. RESULTSscMuffin provides a series of functions to calculate qualitative and quantitative scores, such as: expression of marker sets for normal and tumor conditions, pathway activity, cell state trajectories, CNVs, transcriptional complexity and proliferation state. Thus, scMuffin facilitates the combination of various evidences that can be used to distinguish normal and tumoral cells, define cell identities, cluster cells in different ways, link genomic aberrations to phenotypes and identify subtle differences between cell subtypes or cell states. We analysed public SC expression datasets of human high-grade gliomas as a proof-of-concept to show the value of scMuffin and illustrate its user interface. Nevertheless, these analyses lead to interesting findings, which suggest that some chromosomal amplifications might underlie the invasive tumor phenotype and the presence of cells that possess tumor initiating cells characteristics. CONCLUSIONSThe analyses offered by scMuffin and the results achieved in the case study show that our tool helps addressing the main challenges in the bioinformatics analysis of SC expression data from solid tumors.

bioinformatics↗