Biology subjects

Chiodi, A.

Publications and source records attributed to Chiodi, A..

9 recordsLinked to original sources

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

Tectonic setting shapes microbial biosynthetic potential across global geothermal environments

Microbial communities in geothermal environments constitute an underexplored reservoir of biosynthetic gene clusters with significant biotechnological potential. Here, we investigate the secondary metabolite potential of 219 microbial communities across marine and continental geothermal field sites, encompassing broad environmental gradients in temperature (4.7{degrees}C to 93.5{degrees}C), pH (0.85 to 10.3), and tectonic setting, including volcanic arcs, backarcs, divergent margins at on-axis mid-ocean ridges, post-subduction extensional arcs, and paleo-convergent intraplate plume systems. We identified 9,019 putative new biosynthetic gene cluster families, mostly lacking similarity to known biosynthetic gene clusters. Volcanic arc systems consistently exhibit the highest diversity of biosynthetic repertoires, whereas intraplate plume systems showed a greater representation of terpene-associated gene cluster families. In contrast, divergent margin systems were primarily characterized by nonribosomal peptide synthetases and ribosomally synthesized and post-translationally modified peptides pathways, together accounting for a large fraction of their predicted biosynthetic diversity. These findings suggest that tectonic context could be associated with large-scale patterns in microbial biosynthetic potential and provide a geobiological framework for guiding natural product discovery in geothermal ecosystems.

microbiology↗

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↗

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↗

bioRxiv2023

Complex organic matter degradation by secondary consumers in chemolithoautotrophy-based subsurface geothermal ecosystems

Microbial communities in terrestrial geothermal systems often contain chemolithoautotrophs with well-characterized distributions and metabolic capabilities. However, the extent to which organic matter produced by these chemolithoautotrophs supports heterotrophs remains largely unknown. Here we compared the abundance and activity of peptidases and carbohydrate active enzymes (CAZymes) that are predicted to be extracellular identified in metagenomic assemblies from 63 springs in the Central American and the Andean convergent margin (Argentinian backarc of the Central Volcanic Zone), as well as the plume-influenced spreading center in Iceland. All assemblies contain two orders of magnitude more peptidases than CAZymes, suggesting that the microorganisms more often use proteins for their carbon and/or nitrogen acquisition instead of complex sugars. The CAZy families in highest abundance are GH23 and CBM50, and the most abundant peptidase families are M23 and C26, all four of which degrade peptidoglycan found in bacterial cells. This implies that the heterotrophic community relies on autochthonous dead cell biomass, rather than allochthonous plant matter, for organic material. Enzymes involved in the degradation of cyanobacterial- and algal-derived compounds are in lower abundance at every site, with volcanic sites having more enzymes degrading cyanobacterial compounds and non-volcanic sites having more enzymes degrading algal compounds. Activity assays showed that many of these enzyme classes are active in these samples. High temperature sites (> 80{degrees}C) had similar extracellular carbon-degrading enzymes regardless of their province, suggesting a less well-developed population of secondary consumers at these sites, possibly connected with the limited extent of the subsurface biosphere in these high temperature sites. We conclude that in < 80{degrees}C springs, chemolithoautotrophic production supports heterotrophs capable of degrading a wide range of organic compounds that do not vary by geological province, even though the taxonomic and respiratory repertoire of chemolithoautotrophs and heterotrophs differ greatly across these regions.

biochemistry↗

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↗

bioRxiv2022

Dealing with the promise of metabarcoding in mega-event biomonitoring: EXPO2015 unedited data

As human activities on our planet persist, causing widespread and irreversible environmental degradation, the need to biomonitor ecosystems has never been more pressing. These circumstances have required a renewal in monitoring techniques, encouraged by necessity to develop more rapid and accurate tools which will support timely observations of ecosystem structure and function. The World Exposition (from now EXPO2015) hosted in Milan from May to October 2015 was a global event that could be categorized as a mega-event, which can be defined as an acute environmental stressor, possibly generating biodiversity alteration and disturbance. During the six months of EXPO2015, exhibitors from more than 135 countries and 22 million visitors insisted on a 1.1 million square meters area. Faced with such a massive event, we explore the potential of DNA metabarcoding using three molecular markers to improve the understanding of anthropogenic impacts in the area, both considering air and water monitoring. Furthermore, we explore the effectiveness of the taxonomy assignment phase considering different taxonomic levels of analysis and the use of data mining approaches to predict sample origin. Unless the degree of taxa identification still remains open, our results showed that DNA metabarcoding is a powerful genomic-based tool to monitor biodiversity at the microscale, allowing us to capture exact fingerprints of specific event sites and to explore in a comprehensive manner the eukaryotic community alteration. With this work, we aim to disentangle and overcome the crucial issues related to the generalization of DNA metabarcoding in order to support future applications.

molecular biology↗

bioRxiv2020

Identification of variable sites in Sars-CoV-2 and their abundance profiles in time

The SARS-CoV-2 pandemic that we are currently experiencing is exerting a massive toll both in human lives and economic impact. One of the challenges we must face is to try to understand if and how different variants of the virus emerge and change their frequency in time. Such information can be extremely valuable as it may indicate shifts in aggressiveness, and it could provide useful information to trace the spread of the virus in the population. In this work we identified and traced over time 7 amino acid variants that are present with high frequency in Italy and Europe, but that were absent or present at very low frequencies during the first stages of the epidemic in China and the initial reports in Europe. The analysis of these variants helps defining 6 phylogenetic clades that are currently spreading throughout the world with changes in frequency that are sometimes very fast and dramatic. In the absence of conclusive data at the time of writing, we discuss whether the spread of the variants may be due to a prominent founder effect or if it indicates an adaptive advantage.

bioinformatics↗