Biology subjects

Gaggi, G.

Publications and source records attributed to Gaggi, G..

3 recordsLinked to original sources

bioRxiv2025

Small activating RNA AW1-51 (CEBPA-51) elicits targeted DNA demethylation to promote gene activation

Small activating RNAs are short double-stranded RNAs designed to upregulate transcription of target genes. By this virtue, they can be used to restore expression of genes frequently silenced in cancer. AW1-51 (also referred to as CEBPA-51), the first small activating RNA therapeutic to enter clinical evaluation, has demonstrated biological activity and safety in Phase II trials for hepatocellular carcinoma, both as monotherapy and in combination with sorafenib, and in Phase 1a/1b in combination with pembrolizumab for patients with advanced solid tumors. It targets the master regulator CCAAT enhancer-binding protein alpha, abnormally silenced by DNA methylation in a wide range of hematological and non-hematological malignancies. However, the molecular events enabling this mechanism are only partially elucidated. In this study, we uncovered the molecular basis for AW1-51-induced transcriptional reactivation of CCAAT enhancer-binding protein alpha demonstrating that by directly promoting DNA demethylation of its promoter restores its expression, protein synthesis, and consequently cell differentiation. These findings unveil AW1-51 as a prototype for RNA-based precision medicine enabling conditional expression of CCAAT enhancer-binding protein alpha in diseases characterized by aberrant gene silencing and extending its potential therapeutic impact beyond cancer.

molecular biology↗

bioRxiv2023

Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls

Parkinsons disease (PD) is the second most common neurodegenerative disease and is characterized by the loss of midbrain dopaminergic neurons. Endocrine disruptors (EDs) are active substances that interfere with hormonal signaling. Among EDs, bisphenols (BPs) and perfluoroalkyls (PFs) are chemicals leached from plastics and other household products, and humans are unavoidably exposed to these xenobiotics. Data from animal studies suggest that ED exposure may play a role in PD, but data about the effect of BPs and PFs on human models of the nervous system are lacking. Previous studies demonstrated that machine learning (ML) applied to microscopy data can classify different cell phenotypes based on image features. In this study, the effect of BPs and PFs at different concentrations within the real-life exposure range (0.01, 0.1, 1, and 2 M) on the phenotypic profile of human stem cell-derived midbrain dopaminergic neurons (mDANs) was analyzed. Cells exposed for 72 hours to the xenobiotics were stained with neuronal markers and evaluated using high content microscopy yielding 126 different phenotypic features. Two different ML models (XGBoost and LightGBM) were trained to classify ED-treated versus control mDANs. ED-treated mDANs were identified with high accuracy (0.92). Assessment of the phenotypic feature contribution to the classification showed that EDs induced a significant increase of alpha-synuclein (Syn) and tyrosine hydroxylase (TH) staining intensity within the neurons. Moreover, microtubule-associated protein 2 (MAP2) neurite length and branching were significantly diminished in treated neurons. Our study shows that human mDANs are adversely impacted by exposure to EDs, causing their phenotype to shift and exhibit more characteristics of PD. Importantly, ML-supported high-content imaging can identify concrete but subtle subcellular phenotypic changes that can be easily overlooked by visual inspection alone and that define EDs effects in mDANs, thus enabling further pathological characterization in the future.

neuroscience↗

bioRxiv2020

Human USP18 is regulated by miRNAs via the 3'UTR, a sequence duplicated in lincRNA genes residing in chr22q11.21

Ubiquitin-specific peptidase 18 (USP18) acts as gatekeeper of type I interferon (IFN) responses by binding to the IFN receptor subunit IFNAR2 and preventing activation of the downstream JAK/STAT pathway. In any given cell type, the level of USP18 is a key determinant of the output of interferon-stimulated transcripts. How the baseline level of USP18 is finely tuned in different cell types remains ill defined. Here we explored post-transcriptional regulation of USP18 by microRNAs (miRNAs) and identified four miRNAs (miR-24-3p, miR-191-5p, miR-423-5p and miR-532-3p) that efficiently target USP18 through binding to the 3UTR. Among these, three miRNAs are particularly enriched in circulating monocytes which exhibit low baseline USP18. Intriguingly, the USP18 3UTR sequence is duplicated in human and chimpanzee genomes. In human, we found several copies of the 3UTR that are embedded in long intergenic non-coding (linc) RNA genes residing in chr22q11.21 and exhibiting a tissue-specific expression pattern. Interestingly, one of these lincRNAs (here named linc-UR-B1) is uniquely and highly expressed in testis. RNA-seq data analyses from testicular cell subsets revealed a positive correlation between linc-UR-B1 and USP18 expression in spermatocytes and spermatids. Overall, our findings uncover a set of miRNAs and lincRNAs, which may be part of a network evolved to fine-tune baseline USP18, particularly in cell types where IFN responsiveness needs to be tightly controlled. SIGNIFICANT STATEMENTUSP18 is a non-redundant negative feedback regulator of type I IFN signaling and a key determinant of cell responsiveness to IFN. How baseline USP18 is set in different human cell types is ill defined. We identified three microRNAs that restrain USP18 level notably in primary monocytes through binding the 3UTR. We found several copies of the USP18 3UTR embedded in long intergenic non-coding (linc) RNAs which reside in a complex region of human chromosome 22. These lincRNAs are expressed in a tissue-specific manner. We describe one lincRNA expressed only in testis, and most notably in germ cells. Correlative analyses suggest that microRNAs and lincRNAs may form a network controlling baseline USP18 and IFN responsiveness.

immunology↗