Biology subjects

Tonon, G.

Publications and source records attributed to Tonon, G..

5 recordsLinked to original sources

bioRxiv2023

The Minimal Dataset for Cancer of the 1+Million Genomes Initiative

For a real impact on healthcare, precision cancer medicine requires accessibility and interoperability of clinical and genomic data across centres and countries. Due to the heterogeneous digitization in Europe and worldwide, the definition of models for standardised data collection and usability becomes mandatory if countries want to work together on this mission. The European Union 1+Million Genomes (1+MG) initiative, supported by the Horizon 2020 Beyond 1 Million Genomes project, aims at outlining data models, guidance, best practices, and technical infrastructures for transnational access to sequenced genomes, including cancer genomes. Within the framework of the cancer-focused Working Group 9, we developed the 1+MG-Minimal Dataset for Cancer (1+MG-MDC)-a data model encompassing 140 items and organized in eight conceptual domains for the collection of cancer-related clinical information and genomics metadata. The 1+MG-MDC, which results from a multidisciplinary effort, leverages pre-existing models and emphasizes the annotation and traceability of multiple aspects relevant to the complex longitudinal path of the cancer disease and its treatment. We strived to make the 1+MG-MDC easy to adopt, yet comprehensive, addressing the needs of both clinicians and researchers. We will periodically revise and update it to ensure it remains fit for purpose. We propose the 1+MG-MDC as a model to create homogeneous databases, which would, in turn, guide discussions on clinical and genomic features with prognostic or therapeutic value and foster real-world data research.

cancer biology↗

bioRxiv2023

Evolutionary fingerprints of EMT in pancreatic cancers

Mesenchymal plasticity has been extensively described in advanced and metastatic epithelial cancers; however, its functional role in malignant progression, metastatic dissemination and therapy response is controversial. More importantly, the role of epithelial mesenchymal transition (EMT) and cell plasticity in tumor heterogeneity, clonal selection and clonal evolution is poorly understood. Functionally, our work clarifies the contribution of EMT to malignant progression and metastasis in pancreatic cancer. We leveraged ad hoc somatic mosaic genome engineering, lineage tracing and ablation technologies and dynamic genetic reporters to trace and ablate tumor-specific lineages along the phenotypic spectrum of epithelial to mesenchymal plasticity. The experimental evidences clarify the essential contribution of mesenchymal lineages to pancreatic cancer evolution and metastatic dissemination. Spatial genomic analysis combined with single cell transcriptomic and epigenomic profiling of epithelial and mesenchymal lineages reveals that EMT promotes with the emergence of chromosomal instability (CIN). Specifically tumor lineages with mesenchymal features display highly conserved patterns of genomic evolution including complex structural genomic rearrangements and chromotriptic events. Genetic ablation of mesenchymal lineages robustly abolished these mutational processes and evolutionary patterns, as confirmed by cross species analysis of pancreatic and other human epithelial cancers. Mechanistically, we discovered that malignant cells with mesenchymal features display increased chromatin accessibility, particularly in the pericentromeric and centromeric regions, which in turn results in delayed mitosis and catastrophic cell division. Therefore, EMT favors the emergence of high-fitness tumor cells, strongly supporting the concept of a cell-state, lineage-restricted patterns of evolution, where cancer cell sub-clonal speciation is propagated to progenies only through restricted functional compartments. Restraining those evolutionary routes through genetic ablation of clones capable of mesenchymal plasticity and extinction of the derived lineages completely abrogates the malignant potential of one of the most aggressive form of human cancer.

cancer biology↗

bioRxiv2023

Scalable Integration of Multiomic Single Cell Data Using Generative Adversarial Networks

Single cell profiling has become a common practice to investigate the complexity of tissues, organs and organisms. Recent technological advances are expanding our capabilities to profile various molecular layers beyond the transcriptome such as, but not limited to, the genome, the epigenome and the proteome. Depending on the experimental procedure, these data can be obtained from separate assays or from the very same cells. Despite development of computational methods for data integration is an active research field, most of the available strategies have been devised for the joint analysis of two modalities and cannot accommodate a high number of them. To solve this problem, we here propose a multiomic data integration framework based on Wasserstein Generative Adversarial Networks (MOWGAN) suitable for the analysis of paired or unpaired data with high number of modalities (>2). At the core of our strategy is a single network trained on all modalities together, limiting the computational burden when many molecular layers are evaluated. Source code of our framework is available at https://github.com/vgiansanti/MOWGAN.

bioinformatics↗

bioRxiv2023

A novel method for characterising the inter- and intra-lake variability of CH4 emissions: validation and application across a latitudinal transect in the Alpine region

Lakes in the Alpine region are recognised as critical CH4 emitters, but a robust characterisation of the magnitude and variability of CH4 fluxes is still needed. We developed a mobile platform for CH4 eddy covariance (EC) flux measurements to tackle this gap. Our approach was shown to be well suited to catch all CH4 emission pathways and overcome the limitations of other methods (e.g., gradient-based). This is by surpassing their local nature and thus being suited for characterising the variability of the within-lake emissions, primarily because of CH4 emissions by ebullition stochasticity. The mobile system was deployed at nine lakes across a latitudinal transect in the Alps and validated by comparing the measured fluxes with a fixed EC station and to chambers and boundary layer estimates. Methane fluxes were explained by water turbidity, dissolved organic carbon, dissolved nitrogen, elevation, particulate organic carbon, and total phosphorus. The highest fluxes and most substantial seasonal variability were found in a shallow low-altitude lake in the Southern Alps. Additionally, the mobile EC permitted to resolve the spatial structure of fluxes at the selected lakes. Finally, we demonstrated the usability of our novel mobile system to characterise intra- and inter-lake variability of fluxes. We suggest that characterising the intra-lake emission heterogeneity and a deeper understanding of inter-lake emission magnitude differences is fundamental for a solid estimate of freshwater CH4 budgets. Key PointsO_LICH4 emissions from alpine lakes are recognised to be an important component to the global methane budget but they are poorly characterized C_LIO_LIWe developed and validated a mobile eddy covariance platform for capturing CH4 fluxes across lakes in the alpine region for two years C_LIO_LIA robust statistical model based on a few in-situ physicochemical and biological parameters can be generally used to predict CH4 fluxes C_LI

ecology↗

bioRxiv2021

Rapid longitudinal SARS-CoV-2 intra-host emergence of novel haplotypes regardless of immune deficiencies

On February 2020, the municipality of Vo, a small town near Padua (Italy), was quarantined due to the first coronavirus disease 19 (COVID-19)-related death detected in Italy. The entire population was swab tested in two sequential surveys. Here we report the analysis of the viral genomes, which revealed that the unique ancestor haplotype introduced in Vo belongs to lineage B and, more specifically, to the subtype found at the end of January 2020 in two Chinese tourists visiting Rome and other Italian cities, carrying mutations G11083T and G26144T. The sequences, obtained for 87 samples, allowed us to investigate viral evolution while being transmitted within and across households and the effectiveness of the non-pharmaceutical interventions implemented in Vo. We report, for the first time, evidence that novel viral haplotypes can naturally arise intra-host within an interval as short as two weeks, in approximately 30% of the infected individuals, regardless of symptoms severity or immune system deficiencies. Moreover, both phylogenetic and minimum spanning network analyses converge on the hypothesis that the viral sequences evolved from a unique common ancestor haplotype, carried by an index case. The lockdown extinguished both viral spread and the emergence of new variants, confirming the efficiency of this containment strategy. The information gathered from household was used to reconstructs possible transmission events. AUTHOR SUMMARYIt is of great interest and importance to understand SARS-CoV-2 ability to mutate generating new viral strains, and to assess the impact of containment strategies on viral transmission. In this study we highlight the rapid intra-host haplotype evolution regardless of symptom severity and immune deficiencies that we observed during the first wave of the pandemic in the municipality of Vo in Italy. The confirmation that all the haplotypes found in this small community derive from a common ancestor haplotype, has allowed us to track the rapid emergence of new variants but lockdown and mass testing efficiently prevented their spread elsewhere.

evolutionary biology↗