De Martino, D. | Search bioRxiv

bioRxiv2025

A genetic signature predicts aggressive paraganglioma sensitivity to dual PI3K-CDK4/6 inhibition therapy

Effective medical therapies for metastatic paraganglioma (mPPGL) are currently lacking, leading to dismal prognosis. Building on our knowledge of molecular mechanisms driving PPGL progression, we assessed the therapeutic potential of targeting two critical processes: PI3K signaling and cell cycle regulation. The efficacy of buparlisib (PI3Ki) and ribociclib (CDK4/6i), individually and combined, was assessed in vitro using PPGL cell lines, rat- and patient-derived primary cells, and in vivo using PPGL cells-derived mouse xenografts. The combination therapy demonstrated superior antitumor activity compared to single agents, particularly in vivo. Mechanistically, the efficacy of the combination therapy was associated to the downregulation of FOXM1-controlled genes implicated in mitotic spindle assembly and chromosomal segregation, leading to mitotic catastrophe. Data mining and qRT-PCR showed this genetic signature to be upregulated in human mPPGLs. This suggests that aggressive PPGLs exhibit heightened vulnerability to dual PI3K and CDK4/6 inhibition, offering a promising therapeutic avenue for these challenging cancers.

cancer biology↗

bioRxiv2024

Modelling the prebiotic origins of regulation & agency in evolving protocell ecologies

How did natural systems develop the first mechanisms of regulation and what for? How could they turn into adaptive agents in a minimal (though deeply meaningful) biological sense? A novel simulation platform, Araudia, has been implemented to address these questions, which are deeply interrelated, in a prebiotic scenario where metabolically diverse protocells are allowed to modify their dynamic behaviour in response to changes in their boundary conditions (e.g., nutrient concentrations in the medium) and/or in the activity of other protocells, including cross-feeding relationships. We extend consumer-resource models (CRMs) to a stochastic evolutionary framework in which novelty appears bottom-up (i.e., from small changes at the individual protocell level), and a short-term memory may also come forth and spread in the population, to demonstrate that simple adaptive/learning processes can have relevant effects at somatic times (i.e., within the lifetime of single protocells). Our interest in exploring the interplay between metabolic-physiological aspects and ecological-evolutionary ones derives from the fact that it provides a complex causal domain, where various spatial and temporal scales intermingle, and where both the actual and the potential (pathways/behaviours) must be considered. It is in such a complex domain where the appearance of regulation acquires full significance, as an effective means to navigate phenotypic spaces that become too big for unguided exploration, given the large number of possible functionalities (or functional states) accessible to each proto-cellular agent. The results obtained for several minimalist cases below show that, despite the non-trivial combination of --both endogenous and exogenous--factors involved in the constitution of regulatory mechanisms, these are bound to play a critical role in the survival of infra-biological systems, especially under rapidly changing environmental conditions that longer-term adaptive mechanisms would not be able to cope with.

ecology↗

bioRxiv2017

Quantifying the entropic cost of cellular growth control

We quantify the amount of regulation required to control growth in living cells by a Maximum Entropy approach to the space of underlying metabolic states described by genome-scale models. Results obtained for E. coli and human cells are consistent with experiments and point to different regulatory strategies by which growth can be fostered or repressed. Moreover we explicitly connect the inverse temperature that controls MaxEnt distributions to the growth dynamics, showing that the initial size of a colony may be crucial in determining how an exponentially growing population organizes the phenotypic space.

systems biology↗