Biology subjects

Guzzo, F.

Publications and source records attributed to Guzzo, F..

3 recordsLinked to original sources

bioRxiv2026

Disrupting Pregnane X Receptor Signaling Overcomes Temozolomide Resistance in Glioblastoma via Succisa pratensis-Derived Metabolites

Glioblastoma remains a highly aggressive and therapy-resistant brain tumor, with limited benefit from the current standard-of-care regimen combining surgery, radiotherapy, and temozolomide. Overcoming chemoresistance therefore represents a critical unmet clinical need. Here, we investigate the anticancer potential of Succisa pratensis and its ability to enhance TMZ efficacy in GBM models. Treatment with S. pratensis markedly reduced cell proliferation and migration while significantly increasing sensitivity to TMZ. Integrated multi-omics analyses revealed extensive metabolic rewiring, characterized by suppression of central carbon metabolism and activation of stress-adaptive pathways. Mechanistically, we identify the Pregnane X Receptor, a key regulator of drug metabolism and chemoresistance, as a central node affected by treatment. Although S. pratensis increased PXR expression, this was not accompanied by induction of canonical downstream targets, including MDR1 and ALDH1A1, indicating a functional impairment of PXR transcriptional activity. Consistently, pharmacological inhibition of PXR using the antagonist SPA70 further potentiated the cytotoxic effects of S. pratensis and TMZ. Docking analyses suggest that specific secondary metabolites, including apigenin-derived compounds, may interact with the PXR ligand-binding domain, providing a potential molecular basis for this effect. Collectively, our findings indicate that S. pratensis enhances TMZ efficacy by inducing metabolic vulnerability and functionally impairing PXR signaling. These results highlight the therapeutic potential of plant-derived metabolites as adjuvant strategies to overcome chemoresistance in glioblastoma. Article HighlightsO_LISuccisa pratensis enhances temozolomide efficacy in glioblastoma by reducing proliferation, migration, and clonogenic growth. C_LIO_LIIntegrated proteomic and metabolomic analyses reveal extensive metabolic rewiring, with suppression of central carbon metabolism and induction of stress-adaptive pathways. C_LIO_LIPregnane X Receptor (PXR), a key regulator of chemoresistance, is functionally impaired despite increased expression, resulting in reduced activation of drug-resistance genes. C_LIO_LIPharmacological inhibition of PXR further potentiates the antitumor effects of Succisa pratensis and temozolomide, promoting apoptotic cell death. C_LIO_LIApigenin-derived metabolites show high affinity for the PXR ligand-binding domain and emerge as promising candidates to overcome temozolomide resistance in glioblastoma. C_LI

cancer biology↗

bioRxiv2023

Role of the metallo-reductase FADING and vacuolinos in anthocyanin degradation in flowers and fruits.

Anthocyanins are vacuolar pigments that confer red-violet colors to plant tissues. Pigmentation patterns result from spatio-temporally regulated anthocyanin synthesis and degradation. Mutational inactivation of a conserved MYB-bHLH-WDrepeat-WRKY transcriptional complex (MBWW) causes degradation of anthocyanins and fading of flower color via a pathway that involves FADING (FA). Here we show that FA encodes a vacuolar membrane Fe-reductase-oxidase that promotes anthocyanin degradation. In wild type petals anthocyanins in the central vacuole (CV) are stable, because FA-GFP is upheld in small vacuoles (vacuolinos) and kept away from the CV, indicating that vacuolinos act as gatekeepers in protein trafficking. In cells lacking vacuolinos, including mbww- mutant petals, FA-GFP reaches the CV and triggers anthocyanin degradation. Virus-induced gene silencing (VIGS) of an FA-homolog in pepper fruits prevented the "fading" of anthocyanins during fruit maturation. These findings provide new insights to breed ornamental and food crops with increased anthocyanin-content and enhanced nutritional value of edible parts.

plant biology↗

bioRxiv2022

The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles

Functional genomics experiments are invaluable for understanding mechanisms of gene regulation. However, comprehensively performing all such experiments, even across a fixed set of sample and assay types, is often infeasible in practice. A promising alternative to performing experiments exhaustively is to, instead, perform a core set of experiments and subsequently use machine learning methods to impute the remaining experiments. However, questions remain as to the quality of the imputations, the best approaches for performing imputations, and even what performance measures meaningfully evaluate performance of such models. In this work, we address these questions by comprehensively analyzing imputations from 23 imputation models submitted to the ENCODE Imputation Challenge. We find that measuring the quality of imputations is significantly more challenging than reported in the literature, and is confounded by three factors: major distributional shifts that arise because of differences in data collection and processing over time, the amount of available data per cell type, and redundancy among performance measures. Our systematic analyses suggest several steps that are necessary, but also simple, for fairly evaluating the performance of such models, as well as promising directions for more robust research in this area.

bioinformatics↗