Biology subjects

Giovannini, M.

Publications and source records attributed to Giovannini, M..

6 recordsLinked to original sources

bioRxiv2026

Merlin restoration prevents schwannoma progression in a genetically engineered mouse model of NF2-SWN

Patients with NF2-related schwannomatosis (NF2-SWN) present with hallmark bilateral vestibular schwannomas, but also schwannomas on other cranial, spinal, and peripheral nerves, as well as meningiomas and ependymomas, caused by germline mutations in the tumor suppressor gene NF2. Current therapies involving surgery and radiosurgery are effective for individual tumors but are not always a viable option for patients with multiple tumors, and harbor significant risk of neurological deficits and morbidity. Gene replacement therapy is becoming a promising new treatment strategy for several neurologic diseases. This study aims to understand if restoration of a functional merlin protein, gene product of the Nf2 gene, in Nf2-deficient tumor cells, can provide preclinical therapeutic efficacy in a NF2-SWN genetically engineered mouse model. We have developed a new Nf2 allele (Nf2FRT) that allows to conditionally restore Nf2 expression by activation with the Flp recombinase. We generated a new mouse model using the Nf2FRT allele in combination with Nf2flox and Postn-Cre alleles. Using the new conditional schwannoma mouse model Postn-Cre;Nf2FRT/flox;R26FlpoER, we validated the hypothesis that restoration of Nf2 reduces the growth of schwannoma. Demonstrating that merlin restoration effectively controls schwannoma growth is a crucial first step toward developing this concept as a new therapeutic strategy for potentially treating schwannomas. The new mouse model will be used to better understand the cellular and molecular mechanisms involved in stopping the growth of Nf2-deficient tumors.

cancer biology↗

bioRxiv2026

From code to natural language: MErlin - a multiomics toolkit for bacterial epigenomics delivered as Claude agent skill.

Interpreting a bacterial methylome is a multi-omics problem. It requires integrating modified-base calls with genome annotation, motif inventories, methyltransferase genotypes, transcript abundance, replichore position and, increasingly, chromosome conformation. These data types are commonly generated in incompatible formats, use inconsistent sequence and gene identifiers, and originate from different analytical workflows. The relevant algorithms are available, but assembling them into a coherent and statistically defensible analysis remains a substantial data-integration and interface problem. We present MErlin (Methylation-driven Expression & Regulation Linkage in Interacting Nuclear-domains), a multi-omics toolkit comprising seventeen composable modules, from basecalled modBAM files to ranked gene-level evidence and a self-contained HTML report. MErlin is distributed both as a conventional Python package and as an agent skill: a structured, version-controlled layer of procedural knowledge that enables a compatible large language model (LLM) assistant to select and operate the audited package without generating a new analysis implementation for each request. This design treats natural language as an interface to fixed analytical operations rather than as a substitute for tested scientific software. The skill encodes module-selection rules, mandatory preflight checks, questions that require human input, design-to-inference constraints, and interpretation guidance. We describe MErlin's architecture and statistics, validate it against a synthetic dataset with planted ground truth, and illustrate the conversational interface on a real methylome-transcriptome comparison in Pseudoalteromonas haloplanktis TAC125. MErlin is open source and available at https://github.com/IacopoPasseri/MErlin

bioinformatics↗

bioRxiv2026

Quantitative imaging of schwannoma captures heterogeneity and accelerates preclinical testing, revealing distinct impacts of targeted therapies

Schwannomas are debilitating hallmarks of familial schwannomatoses and common sporadic tumors that form on spinal and cranial nerves. Drug-based therapies for schwannoma are desperately needed but their development has been extremely slow and disappointing, impeded particularly by the poorly understood and surprisingly complex and heterogeneous biology of schwannomas, and by the inefficient use of physiologically relevant in vivo preclinical models. We have addressed these gaps by developing a quantitative imaging-centered workflow that allows both a deep analysis of schwannoma development and accelerated preclinical testing in a widely used genetically engineered mouse model of neurofibromatosis type 2-related schwannomatosis (NF2-SWN). We deployed our workflow to study schwannoma development and to test two clinically relevant drugs (rapamycin and brigatinib) head-to-head. Our results uncovered the very early onset of heterogeneity and macrophage recruitment to initiating schwannomas, and the unexpectedly distinct impacts of the two drugs on both, highlighting the value of the pipeline for rapid, innovative future drug-testing.

cancer biology↗

bioRxiv2021

Cellular mechanisms of heterogeneity in NF2-mutant schwannoma

Schwannomas are common sporadic nervous system tumors and diagnostic features of familial neurofibromatosis type 2 (NF2) that develop predominantly on cranial and spinal nerves and cause severe neurological deficits and significant morbidity. Virtually all schwannomas result from inactivation of the NF2 tumor suppressor gene with few, if any, cooperating mutations. Despite their genetic uniformity schwannomas exhibit remarkable clinical and therapeutic heterogeneity, which has impeded the success of early rational therapies. An understanding of how heterogeneity develops in NF2-mutant schwannomas is critically needed to improve therapeutic options for these patients. We have found that loss of the membrane:actin cytoskeleton-associated NF2 tumor suppressor protein, merlin, yields unstable intrinsic polarity and enables Nf2-/- Schwann cells to adopt distinct programs of coordinated ErbB ligand production and polarized signaling, suggesting a self-generated model of schwannoma heterogeneity. We validated the heterogeneous distribution of biomarkers of these programs in human schwannoma tissue and took advantage of the synchronous development of multiple lesions in a well-studied mouse model to establish a quantitative pipeline that can be used to study how schwannoma heterogeneity evolves and impacts nerve function and therapeutic response in mouse, and ultimately human schwannomas. Our studies inform a mounting appreciation that intrinsic mechanisms are major contributors to heterogeneity across many human cancers.

cancer biology↗

bioRxiv2020

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer

BACKGROUNDA significant gap in pancreatic ductal adenocarcinoma (PDAC) patients care is the lack of molecular parameters characterizing tumors and allowing a personalized treatment. The goal of this study was to examine whole PDAC transcriptomic profiles to define a signature that would predict aggressiveness and treatment responsiveness better than done until now. METHODS AND PATIENTSTumors were obtained from 76 consecutive resectable (n=40) or unresectable (n=36) tumors. PDAC were transplanted in mice to produce patient-drived xenografts (PDX). PDX were classified according to their histology into five groups, from highly undifferentiated to well differentiated. This classification resulted strongly associated with tumors aggressiveness. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n=598) of resected tumors; ii/ 60 advanced tumors obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumors. RESULTSA unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumors (e.g. 308 consecutive resected PDAC, HR=0.321 95% CI [0.207;0.5] and 60 locally-advanced or metastatic PDAC, HR=0.308 95% CI [0.113;0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumor response: -0.67, p-value < 0.001). CONCLUSIONWe identified a transcriptomic signature (PAMG) that, unlike all other stratification schemas already proposed, classifies PDAC along a continuous gradient. It can be performed on formalin-fixed paraffin-embedded samples and EUS-guided biopsies showing a strong prognostic value and predicting mFOLFIRINOX responsiveness. We think that PAMG could unify all PDAC preexisting classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient. Trial RegistrationThe PaCaOmics study is registered at www.clinicaltrials.gov with registration number NCT01692873. The validation BACAP study is registered at www.clinicaltrials.gov with registration number NCT02818829.

cancer biology↗

bioRxiv2019

Diauxie and co-utilization are not exclusive during growth in nutritionally complex environments

The classic view of microbial growth strategy when multiple carbon sources are available states that they either metabolize them sequentially (diauxic growth) or simultaneously (co-utilization). This perspective is biased by the fact that this process has been mainly analysed in over-simplified laboratory settings, i.e. using a few model microorganisms and growth media containing only two alternative compounds. Models concerning the mechanisms and the dynamics regulating nutrients assimilation strategies in conditions that are closer to the ones found in natural settings (i.e. with many alternative carbon/energy sources) are missing. Here, we show that bacterial co-utilization and sequential uptake of multiple substrates can coexist when multiple possible nutrients are provided in the same growth experiment, leading to an efficient exploitation of nutritionally complex settings. The order of nutrient uptake is determined by the actual biomass yield (and growth rate) that can be achieved when the same compounds are provided as single carbon sources. Finally, using two alternative theoretical models we show that this complex metabolic phenotype can be explained by a tight regulation process that allows microbes to actively modulate the different assimilatory pathways involved.

systems biology↗