Biology subjects

Perini, G.

Publications and source records attributed to Perini, G..

4 recordsLinked to original sources

bioRxiv2025

MYC/MAX balance dictates cell progenitor fate by altering the HOX program in the Drosophila eye

The transcription factor MYC acts canonically as heterodimer with MAX to promote growth, proliferation, and metabolic adaptation. Although MYC and MAX relative levels are normally kept in balance under physiological conditions, those levels are often dysregulated in many human cancers where MYC is overexpressed and MAX can sometimes be reduced. How altered stoichiometry of MYC/MAX can impact on cell biology is not completely understood. Using the Drosophila eye amenable to genetic modifications, we demonstrate that the relative abundance of the fly MYC ortholog dMyc and its partner dMax affect progenitor cell fate. Elevating the dMyc/dMax ratio--through dMyc or human MYCN overexpression, dMax depletion, or combined manipulations--disrupts photoreceptor differentiation and ectopically induces the thoracic HOX gene Antennapedia within the eye disc. When such a ratio is driven to an extreme degree, the change in cell fate results in eye-to-wing transdetermination. Conversely, restoring dMax levels rescues these phenotypes, demonstrating that stoichiometry, not absolute MYC levels, shapes the response. Transcriptomic profiling reveals global repression of eye-specific regulators (e.g., eyegone and prospero) and ectopic activation of wing determinants (e.g., vestigial and nubbin) while genetic interactions identify the cephalic HOX gene Deformed as a key mediator modulating MYC-dependent identity changes. Our findings uncover MYC/MAX imbalance as a developmental switch that can rewire HOX expression and reprogram progenitor identity, suggesting a conserved mechanism underlying MYC-driven cellular plasticity in cancer.

developmental biology↗

bioRxiv2025

Stress attenuation by the adrenergic-specific lncRNA NESPR prevents cell death in neuroblastoma cells

Neuroblastoma is a pediatric cancer of the sympathetic nervous system characterized by heterogeneous cell states that mirror normal differentiation trajectories. Each state is governed by a core regulatory transcriptional circuitry that reinforces cell identity through an autoregulatory feedforward loop. We identified the long non-coding RNA NESPR as specifically expressed in adrenergic neuroblastoma cells. NESPR expression correlates with high-risk neuroblastoma clinical parameters and poor patient survival. NESPR is located within an insulated gene neighborhood alongside PHOX2B, a master transcription factor of the adrenergic identity. NESPR depletion reduced cell proliferation and increased caspase activity in neuroblastoma cell lines, and NESPR knockout in a neuroblastoma zebrafish model led to reduced tumor penetrance. Subcellular localization revealed NESPR to be a cytosolic long non-coding RNA, suggesting a trans-regulatory function. RNA-sequencing following NESPR depletion revealed a shift from an adrenergic to a mesenchymal cell state, due to proteotoxic stress-induced molecular reprogramming. These findings suggest NESPR as a regulator of neuroblastoma cell identity with potential therapeutic opportunities in high-risk neuroblastoma cases.

genetics↗

bioRxiv2022

Deep Learning for MYC binding site recognition

MotivationThe definition of the genome distribution of the Myc transcription factor is extremely important since it may help predict its transcriptional activity particularly in the context of cancer. Myc is among the most powerful oncogenes involved in the occurrence and development of more than 80% of different types of pediatric and adult cancers. Myc regulates thousands of genes which can be in part different, depending on the type of tissues and tumours. Myc distribution along the genome has been determined experimentally through chromatin immunoprecipitation This approach, although powerful, is very time consuming and cannot be routinely applied to tumours of individual patients. Thus, it becomes of paramount importance to develop in-silico tools that can effectively and rapidly predict its distribution on a given cell genome. New advanced computational tools (DeeperBind) can then be successfully employed to determine the function of Myc in a specific tumour, and may help to devise new directions and approaches to experiments first and personalized and more effective therapeutic treatments for a single patient later on. ResultsThe use of DeeperBind with DeepRAM on Colab platform can effectively predict the binding sites for the MYC factor with an accuracy above 0.96 AUC, when trained with multiple cell lines. The analysis of the filters in DeeperBind trained models shows, besides the consensus sequence CACGTG classically associated to the MYC factor, also the other consensus sequences G/C box or TGGGA, respectively bound by the SP1 and MIZ-1 transcription factors, which are known to mediate the MYC repressive response. Overall, our findings suggest a stronger sinergy between the machine learning tools as DeeperBind and biological experiments, which may reduce the time consuming experiments by providing a direction to guide them.

bioinformatics↗

bioRxiv2020

Different RNA profiles in plasma derived small and large extracellular vesicles of Neurodegenerative diseases patients.

BackgroundIdentifying robust biomarkers is essential for early diagnosis of neurodegenerative diseases (NDs). Large (LEVs) and small extracellular vesicles (SEVs) are extracellular vesicles (EVs) of different sizes and biological functions transported in blood and they may be valid biomarkers for NDs. The aim of our study was to investigate common and different mRNA/miRNA signatures in plasma derived LEVs and SEVs of Alzheimers Disease (AD), Parkinsons disease (PD), Amyotrophic Lateral Sclerosis (ALS) and Fronto-Temporal Dementia (FTD) patients. MethodsLEVs and SEVs were isolated from plasma of patients and healthy volunteers (CTR) by filtration and ultracentrifugation and RNA was extracted. Whole transcriptome and miRNA libraries were carried out by Next Generation Sequencing (NGS). ResultsWe detected different deregulated RNAs in LEVs and SEVs from patients with the same disease. MiRNAs resulted to be the most interesting subpopulation of transcripts transported by plasma derived SEVs since they appeared to discriminate all NDs disease from CTRs and they can provide a signature for each NDs. Common enriched pathways for SEVs were mainly linked to ubiquitin mediated proteolysis and Toll-like receptor signaling pathways and for LEVs to neurotrophin signaling and Glycosphingolipid biosynthesis pathway. ConclusionLEVs and SEVs are involved in different pathways and this might give a specificity to their role in the spreading/protection of the disease. The study of common and different RNAs transported by LEVs and SEVs can be of great interest for biomarker discovery and for pathogenesis studies in neurodegeneration.

neuroscience↗