Biology subjects

Brugiolo, M.

Publications and source records attributed to Brugiolo, M..

5 recordsLinked to original sources

bioRxiv2026

Splicing of ultraconserved poison exons controls mitotic fidelity and stem cell viability

SR proteins are essential splicing regulators whose expression is controlled in part through poison exons (PEs) -- ultraconserved non-coding exons that trigger nonsense-mediated decay -- yet the biological functions of these elements remain undefined. Here, we show that homozygous deletion of SRSF3-PE or TRA2{beta}-PE is selected against in mouse embryos and human induced pluripotent stem cells (iPSCs), and that conditional PE deletion causes apoptotic death in iPSCs but is tolerated in post-mitotic neurons, revealing a proliferative-state-specific requirement. Mechanistically, PE deletion elevates SR protein levels, triggers widespread splicing dysregulation, and disrupts the correct splicing of a mitotic gene network associated with spindle defects and mitotic errors. These findings establish ultraconserved poison exons as essential regulators of mitotic splicing fidelity and stem cell viability.

molecular biology↗

bioRxiv2025

SpliceDecoder: A High-Throughput Tool for Guiding the Functional Interpretation of Differential Splicing Events

Alternative splicing generates different mRNA isoforms from single genes, generating protein diversity essential for normal development and tissue function. Dysregulation of splicing is implicated in numerous diseases, including cancer, neurodegeneration, diabetes, and rare genetic disorders. Although thousands of spliced isoforms have been identified in disease-relevant contexts, the functional significance of most remains unknown, hindering our understanding of splicing-driven disease mechanisms and limiting therapeutic discovery. A major challenge lies in prioritizing biologically meaningful splicing events identified through short-read RNA sequencing. Existing splicing analysis tools typically rank target events based on splicing change magnitude or gene-level annotation, often without evaluating how resulting isoforms impact protein structure or function. This creates a critical bottleneck in translating splicing data into biological and therapeutic insights. To address this, we developed SpliceDecoder, a computational workflow that predicts how each splicing event or isoform impacts transcript productivity, protein sequence, and functional domains. Each event is assigned a functional effect score to guide evidence-based prioritization. SpliceDecoder facilitates a more informed interpretation of splicing data, reduces reliance on prior knowledge, and enables identification of events with potential biological and clinical relevance. We demonstrate its utility by validating known splicing alterations and identifying novel disease-associated isoform switches across public datasets.

genomics↗

bioRxiv2025

Intron retention regulates STAT2 function and predicts immunotherapy response in lung cancer

Immunotherapy benefits only a subset of lung cancer patients, and the molecular determinants of variable outcomes remain unclear. Using long-read RNA-sequencing we mapped the landscape of alternative RNA splicing in human primary lung adenocarcinomas. We identified over 180,000 full-length mRNA isoforms, more than half of which were novel and many of which occurred in immune-related genes, particularly within the type I interferon response pathway. We discovered retained introns in the STAT2 gene that produce altered protein isoforms that regulate immune signaling and interferon responses. Furthermore, STAT2 intron retention levels predicted patient responses to checkpoint inhibitors. These findings position alternative splicing as a key regulator of tumor immune responses and reveal mRNA splicing alterations as potential biomarkers to identify patients who might respond to cancer immunotherapy.

immunology↗

bioRxiv2023

Cellos: High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology

Three-dimensional (3D) culture models, such as organoids, are flexible systems to interrogate cellular growth and morphology, multicellular spatial architecture, and cell interactions in response to drug treatment. However, new computational methods to segment and analyze 3D models at cellular resolution with sufficiently high throughput are needed to realize these possibilities. Here we report Cellos (Cell and Organoid Segmentation), an accurate, high throughput image analysis pipeline for 3D organoid and nuclear segmentation analysis. Cellos segments organoids in 3D using classical algorithms and segments nuclei using a Stardist-3D convolutional neural network which we trained on a manually annotated dataset of 3,862 cells from 36 organoids confocally imaged at 5 m z-resolution. To evaluate the capabilities of Cellos we then analyzed 74,450 organoids with 1.65 million cells, from multiple experiments on triple negative breast cancer organoids containing clonal mixtures with complex cisplatin sensitivities. Cellos was able to accurately distinguish ratios of distinct fluorescently labelled cell populations in organoids, with <3% deviation from the seeding ratios in each well and was effective for both fluorescently labelled nuclei and independent DAPI stained datasets. Cellos was able to recapitulate traditional luminescence-based drug response quantifications by analyzing 3D images, including parallel analysis of multiple cancer clones in the same well. Moreover, Cellos was able to identify organoid and nuclear morphology feature changes associated with treatment. Finally, Cellos enables 3D analysis of cell spatial relationships, which we used to detect ecological affinity between cancer cells beyond what arises from local cell division or organoid composition. Cellos provides powerful tools to perform high throughput analysis for pharmacological testing and biological investigation of organoids based on 3D imaging.

bioinformatics↗

bioRxiv2021

MYC regulates a pan-cancer network of co-expressed oncogenic splicing factors

MYC is dysregulated in >50% of cancers, but direct targeting of MYC has been clinically unsuccessful. Targeting downstream MYC effector pathways represents an attractive alternative. MYC regulates alternative mRNA splicing, a hallmark of cancer, but the mechanistic links between MYC and the splicing machinery remain underexplored. Here, we identify a network of splicing factors (SFs) co-expressed as SF-modules in MYC-active breast tumors. Of these, one is a pan-cancer SF-module, correlating with MYC-activity across 33 tumor types. In mammary cell models, MYC activation leads to co-upregulation of pan-cancer module SFs and to changes in >4,000 splicing events. In breast cancer organoids, co-overexpression of the pan-cancer SF-module is sufficient to induce splicing events that are also MYC-regulated in patient tumors and to increase organoid size and invasiveness, while its knockdown decreases organoid size. Finally, we uncover a pan-cancer splicing signature of MYC activity which correlates with survival in multiple tumor types. Our findings provide insight into the mechanisms and function of MYC-regulated splicing and for the development of therapeutics for MYC-driven tumors.

cancer biology↗