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Azzopardi, N.

Publications and source records attributed to Azzopardi, N..

2 recordsLinked to original sources

Forecasting tumor growth kinetics and hypoxia levels in mice using mathematical modelling

Quantitative description of tumor growth is challenged by vascular heterogeneity and hypoxia. In this study, mammary tumor growth was investigated in mouse model using caliper and ultrasound imaging measurements, bioluminescence imaging (BLI), and pimonidazole imaging. Tumor volume increased monotonically when assessed by caliper and ultrasound imaging, whereas BLI exhibited oscillating dynamics despite continued tumor growth, consistent with hypoxia-related signal attenuation. A mathematical compartmental model was developed primarily to describe tumor growth dynamics, incorporating latent vascular capacity as a key regulatory variable. The model accounts for reciprocal interactions between tumor expansion and vascular limitation. BLI was integrated as an auxiliary observable to reveal hypoxia-driven modulation of signal production rather than as a direct surrogate of tumor size. Model parameters were estimated using nonlinear mixed-effects modelling with population approach, allowing quantification of population-level behavior and inter-individual variability. The model adequately described tumor growth while explaining BLI dynamics through vascular and hypoxic effects. This framework provides the first semi-mechanistic description of tumor growth and supports the use of BLI as an indirect marker of hypoxia and, consequently, of tumor growth. This model may provide a useful framework for quantifying the effects of vascular-modulating therapeutics and genetic polymorphisms involved in tumor progression.

cancer biology↗

Hormone-regulated dynamics of mRNA distribution on ribosomes in Sertoli cells

The effects of hormone stimulation on the cell translational profile remain poorly understood. Here, using polysome profiling combined to RNA sequencing, we analyzed the translational response to follicle-stimulating hormone (FSH) of primary rat Sertoli cells, that exhibit an active anabolic activity regulated by reproductive hormones in the male gonad. We first established that mRNA distribution to polysomes follows a bimodal pattern, with 15% of mRNAs enriched in polysomes and exhibiting high expression. Critically, this basal polysomal enrichment had a major impact on FSH-induced mRNA recruitment to the polysomes, since FSH stimulation promoted the release of polysome-enriched mRNAs, while mRNAs that were the least associated to polysomes were preferentially recruited to polysomes upon stimulation. The FSH signal did not alter the core biological functions of Sertoli cells, but shifted the proteins involved in these functions, suggesting a molecular rewiring of the FSH-induced gene expression. These findings underscore how ribosomal reallocation dynamically adapts the cellular translatome to microenvironmental changes, enabling cells to fine-tune protein production in response to external stimuli. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/629416v1_ufig1.gif" ALT="Figure 1000"> View larger version (19K): org.highwire.dtl.DTLVardef@27334forg.highwire.dtl.DTLVardef@199c630org.highwire.dtl.DTLVardef@a28b92org.highwire.dtl.DTLVardef@1794172_HPS_FORMAT_FIGEXP M_FIG C_FIG Bullet points* In Sertoli cells, most mRNAs distribute similarly between monosomes and polysomes, but a sub-population is specifically enriched in polysomes * Basal polysomal enrichment level has a major impact on FSH-induced mRNA recruitment or release from the polysomes * The FSH signal induced a global rewiring of the proteins involved in Sertoli cell basal activity * FSH-induced reassignment of ribosomes to specific mRNAs has to comply with a tightly maintained mRNA distribution landscape

systems biology↗