Biology subjects

Pinna, G.

Publications and source records attributed to Pinna, G..

7 recordsLinked to original sources

bioRxiv2025

Medial preoptic area FoxO1 controls metabolic adaptation in a sexually dimorphic manner

The medial preoptic area (MPOA) of the hypothalamus is essential for metabolic adaptation to environmental challenges, though the molecular mechanisms underlying this process remain poorly understood. Here, we investigate the role of Forkhead transcription factor O1 (FoxO1), a key mediator of stress adaptation, in MPOA-dependent metabolic responses to temperature and nutritional changes. Our findings reveal sex-specific responses to both nutritional and temperature challenges. In female mice, but not males, a high-fat diet (HFD) challenge decreased FoxO1 expression in the MPOA. Specific deletion of FoxO1 in MPOA neurons (FoxO1-KOMPOA) had no effect on body weight under normal chow-fed conditions but protected females from HFD-induced obesity (DIO). These protected females exhibited increased lean mass, decreased fat mass, enhanced thermogenesis, increased energy expenditure, and reduced food intake under HFD conditions. They also showed enhanced cold-induced heat production at 6{degrees}C, though this effect vanished at thermoneutrality (30{degrees}C). The protection against DIO was abolished by ovariectomy (OVX) and was not restored by 17{beta}-estradiol supplementation, suggesting an estrogen-independent mechanism. Conversely, constitutive activation of FoxO1 in MPOA neurons (FoxO1-CAMPOA) increased DIO susceptibility in both sexes. Together, these findings demonstrate that FoxO1MPOA plays a crucial role in coordinating metabolic adaptation to nutritional and temperature challenges specifically in female mice.

physiology↗

bioRxiv2024

G-quadruplex ligand RHPS4 compromises cellular radio-resistance by blocking the increase in mitochondrial mass and activity induced by ionising irradiation.

A major challenge in radiotherapy is to enhance tumor cell sensitivity to radiation while minimizing damage to healthy tissues. Ionising radiation (IR) induces mitochondrial DNA (mtDNA) alterations that can impair mitochondrial function and cell survival. Since mitochondria play a key role in tumor cell proliferation, they represent a promising therapeutic target for cancer treatment. In this study, we characterized the impact of different IR sources on mitochondrial function in radioresistant cancer cells. Our findings revealed several adaptive responses that may contribute to radioresistance, including increased mtDNA content, mitochondrial mass, enhanced activity, and hyperfusion of the mitochondrial network. Notably, the use of mitochondrial-targeted G-quadruplex (G4) ligands, which block mtDNA replication and transcription, disrupted these responses, reducing cancer cell survival in an mtDNA-dependent manner. These results demonstrate that mitochondrial adaptations contribute to radioresistance and highlight mitochondria as a novel target for the radiosensitizing effects of G4-ligands, extending their potential beyond telomere destabilization.

cell biology↗

bioRxiv2024

Prefrontal 5α-reductase 2 mediates male-specific acute stress response

A key response to acute stress is the increased brain synthesis of the neurosteroid allopregnanolone (AP). While the rate-limiting step of this reaction is catalyzed by 5-reductase (5R), the role of its two primary isoenzymes, 5R1 and 5R2, in stress reactivity remains unclear. Here, we found that acute stress led to increased levels of 5R2, but not 5R1, in the medial prefrontal cortex (mPFC) of male, but not female, rats. Downregulation of 5R2 in the mPFC significantly reduced stress response in males, and similar sexual dimorphic effects were observed in a novel line of 5R2 knockout rats. Notably, 5R1 regulated baseline AP synthesis, while 5R2 enabled AP production under stress. Acute AP administration restored stress response in 5R2 knockdown rats. Single-nucleus transcriptomics showed that 5R2 enabled stress-induced protein translation in neurons and glia. These results highlight the crucial role of 5R2 in mediating sex-specific differences in acute stress reactivity.

neuroscience↗

bioRxiv2022

Combination drug screen targeting glioblastoma core vulnerabilities reveals pharmacological synergisms

Synergistic drug combinations are an attractive anticancer strategy but prove challenging to identify. Here we present a stepwise approach consisting in revealing core cancer vulnerabilities and exploiting them through drug combination screen to uncover synergistic treatments for glioblastoma patients. MethodsWe established an innovative method, based on high-throughput screening, target deconvolution and functional genomics, to reveal core vulnerabilities in glioblastoma. Combination drug screen targeting these vulnerabilities was then designed to unveil synergistic associations. The therapeutic potential of the top drug combination was validated in two different clinically-relevant models: an organotypic ex vivo model and a syngeneic orthotopic mouse model of glioblastoma. ResultsLarge-scale monotherapy drug screening identified 83 potent anti-glioblastoma compounds. Target deconvolution using public chemoinformatic databases uncovered 1,100 targets and interactors of the hit compounds. Screening of a focused siRNA library targeting the top 292 drug interactors revealed 22 targetable vulnerabilities, 9 of which were confirmed as core glioblastoma vulnerabilities by mining the CRISPR screen cohort data from the online Cancer Dependency Map portal. Six selective inhibitors of the core vulnerabilities were then screened in combination with a custom-made library of 88 compounds and synergies amongst the 528 tested pairwise combinations were predicted. The combinations of CHK1 / MEK and AURKA / BET inhibitors were highlighted and validated in 3D tumor spheroids. Using an organotypic ex vivo model and a syngeneic orthotopic mouse model, we definitively ascertained the efficacy of dual AURKA / BET inhibition in glioblastoma. ConclusionsCollectively, we uncovered that dual inhibition of BET proteins and aurora kinase A is highly synergistic against GBM. Moreover, our study indicates that our approach to exploit drug poly-pharmacology for the rational design of drug combination screens represent a valuable strategy to discover synergistic treatments against refractory cancers.

pharmacology and toxicology↗

bioRxiv2019

miRViz: a novel webserver application to visualize and interpret microRNA datasets

MicroRNAs (miRNAs) are small non-coding RNAs that are involved in the regulation of major pathways in eukaryotic cells through repression of their target genes at the post-transcriptional level1. While high-throughput approaches are broadly used to decipher the biological relevance of miRNAs, extraction of significant information from large miRNA datasets remains challenging. For example, sequencing technologies can quantify the relative expression of up to thousands of mature miRNAs under various experimental conditions. However, in such datasets, small subsets of miRNAs can often show significant differential expression, and deciding which one(s) should be further analyzed can prove difficult. Thus, the current challenge resides in objective analysis, interpretation and visualization of these large datasets, for which specifically suited methods are lacking.

genomics↗

bioRxiv2018

Mathematical Modeling Reveals the Factors Involved in the Phenomena of Cancer Stem Cells Stabilization

Cancer Stem Cells (CSC), a subset of cancer cells resembling normal stem cells with self-renewal and asymmetric division capabilities, are present at various but low proportions in many tumors and are thought to be responsible for tumor relapses following conventional cancer therapies. In vitro, most intriguingly, when isolated, CSCs return to their original proportion level as shown by various investigators. This phenomenon still remains to be explained.\n\nWe suggest a mathematical model of cancer cell population dynamics, based on the main parameters of cell population dynamics, including the proliferation rates, the rates of cell death and the frequency of symmetric and asymmetric cell divisions both in CSCs and in non-CSCs. This model should help elucidating some important factors underlying the dynamics of the two populations, first of all, the phenomena of cancer stem cell population stabilization.\n\nAuthor SummaryCancer Stem Cells (CSC) present a subset of cancer cells which is thought to be responsible for tumor growth. That is why CSC are also named \"tumor initiation cells\". Additionally, it was shown that CSC are resistant to chemo- and radio-therapies which suggests that these cells can be responsible for tumor relapses after these treatments. Experimental data in cancer cell lines have shown the intriguing phenomena of CSC population stability, which means that isolated CSC population rapidly stabilizes at its characteristic level (the relative proportion of CSC in a whole cancer population). We suggest a mathematical model of cancer cell population dynamics, based on experimentally measured dynamics of CSC population stabilization and including main parameters of cell population growth.\n\nWe have computationally predicted probability of different scenarios of cancer cell behavior for each experimental case with measurable growth parameters. Moreover, we provide an analytical tool for elucidating important biochemical factors responsible for a particular dynamics of CSC population.\n\nThe results may have important implications in therapeutic, because the destroying of a set of factors underlying CSC stability may help to avoid tumor relapses.

cancer biology↗

bioRxiv2018

MasterPATH: network analysis of functional genomics screening data

Functional genomics employs several experimental techniques to investigate gene functions. These techniques such as loss-of-function screening and transcriptome profiling performed in a high-throughput manner give as result a list of genes involved in the biological process of interest. There exist several computational methods for analysis and interpretation of the list. The most widespread methods aim at investigation of biological processes significantly represented in the list or at extracting significantly represented subnetworks. Here we present a new exploratory network analysis method that employs the shortest path approach and centrality measure to uncover members of active molecular pathways leading to the studied phenotype based on the results of functional genomics screening data. We present the method and we demonstrate what data can be retrieved by its application to the terminal muscle differentiation miRNA loss-of-function screening and transcriptomic profiling data and to the druggable loss-of-function RNAi screening data of the DNA repair process.

systems biology↗