Biology subjects

Geraci, F.

Publications and source records attributed to Geraci, F..

4 recordsLinked to original sources

bioRxiv2026

From Single-Cell Emergent Behaviors to Clinical Outcome: PTEN-driven Migratory Efficiency as a Potential New Vulnerability in Glioblastoma

BackgroundGlioblastoma (GB) is a highly aggressive brain tumor with a median survival of approximately 14 months, primarily due to its ability to infiltrate healthy brain tissue both as single cells and in collectives. A deeper understanding of GB cell motility, both individual and collective, is crucial for developing patient-specific therapies. We aimed to characterize migration in patient-derived GB cells using advanced modeling to identify stratification markers and therapeutic vulnerabilities. MethodsWe developed Single-Cell Behavior Live Imaging (ScBLI), an approach integrating live imaging with computational analysis, applied to 30 GB primary cell cultures. Trajectories and morphological features were tracked and analyzed. Diffusion Entropy Analysis (DEA) was applied to classify trajectories based on the Delta Scaling parameter ({delta} scaling). We evaluated functional responses correlating all findings with clinical outcomes and transcriptomic profiles. ResultsWe analyzed 4,279 cell trajectories. Based on {delta} scaling (range 0.28-0.837), we defined three distinct motility groups: Low (L, {delta} scaling [≤]0.5), Medium (M, 0.5 < {delta} scaling [≤] 0.7), and High (H, {delta} scaling >0.7). Functional assays demonstrated that Group H cells are more performant in both positive and negative chemotaxis. Clinically, the three groups showed a clear linear progression with patient survival: High {delta} scaling correlated with the shortest survival (poorer prognosis), while Low {delta} correlated with the longest survival, suggesting that structured motility drives invasiveness. Integrative multi-omic analysis, encompassing both exome and transcriptome profiling, demonstrated that these groups are defined by distinct molecular landscapes rather than poor behavioral traits. Moreover, exome data revealed that Group H is significantly enriched in PTEN alterations (75% vs. 8% in Group L), with PTEN gain-of-function (GoF) mutations exclusively restricted to this group (100% vs 0% in Group L). Notably, within our extended cohort (n=51) currently characterized by whole-exome sequencing, we observed that specific PTEN GoF mutations were associated with a significantly shorter survival compared to PTEN wild-type cases (median OS 6.4 vs 16.6 months; p=0.02), which typically harbor the canonical loss of chromosome 10q. A similar clinical trend was observed when comparing directly GoF carriers to patients with truncating (Ter) alterations (median OS 6.4 vs 14.3 months; p=0.09). Conversely, no survival difference was found between truncating (Ter) mutations and wild-type cases. ConclusionOur findings demonstrate for the first time that migratory efficiency, quantified through DEA, represents a powerful predictor of glioblastoma aggressiveness. Tumor cells adopting highly efficient exploration strategies are strongly associated with poor clinical outcomes and are characterized by distinct molecular signatures, notably PTEN gain-of-function alterations. Statement of significanceOur multi-scale computational framework elucidates emergent behavioral phenotypes as pivotal drivers of glioblastoma progression. By demonstrating a correlation between enhanced migratory efficiency, PTEN gain-of-function, and significantly reduced overall survival, we establish a foundational paradigm for deciphering the emergent complexity governing tumor invasiveness.

cancer biology↗

bioRxiv2024

Individual differences in the expression and control of anger are encoded in the same fronto-temporal GM-WM network

Anger can be deconstructed into distinct components: a temporary emotional state (state anger), a stable personality trait (trait anger), a tendency to outwardly express it (anger-out), or to internally suppress it (anger-in), and the capability to manage it (anger control). These aspects exhibit individual differences that vary across a continuum. Notably, the capacity to express and control anger are of great importance to modulate our reactions in interpersonal situations. The aim of this study was to test the hypothesis that anger expression and control are negatively correlated and that both can be decoded by the same patterns of grey and white matter features of a fronto-temporal brain network. To this aim, a data fusion unsupervised machine learning technique, known as transposed Independent Vector Analysis (tIVA), was used to decompose the brain into covarying GM-WM networks and then backward regression was used to predict both anger expression and control from a sample of 212 healthy subjects. Confirming our hypothesis, results showed that anger control and anger expression are negatively correlated, the more individuals control anger, the less they externalize it. At the neural level, individual differences in anger expression and control can be predicted by the same GM-WM network. As expected, this network included fronto-temporal regions as well as the cingulate, the insula and the precuneus. The higher the concentration of GM-WM in this brain network, the higher level of externalization of anger, and the lower the anger control. These results expand previous findings regarding the neural bases of anger by showing that individual differences in anger control and expression can be predicted by morphometric features.

neuroscience↗

bioRxiv2020

Graph-based integration of histone modifications profiles: haematopoietic cell differentiation as a case study

In this paper, we show that quantifying histone modifications by counting the number of high- resolution peaks in each gene allows to build profiles of these epigenetic marks, associating them to a phenotype. The significance of this approach is verified by applying graph-cut techniques for assessing the differentiation between myeloid and lymphoid cells in haematopoiesis, i.e. the process through which all the different types of blood cells originate starting from a unique cell type. The experiments are conducted on a population of samples from 24 cell types involved in haematopoiesis. Six profiles are constructed for each cell type, based on a different histone modification signal. Following the experimentally verified idea that the peak number distribution per gene behaves similarly to gene expression, the profile computation employs standard differential analysis tools to find genes whose epigenetic modifications are related to a given phenotype. Next, six similarity networks of cell types are constructed, based on each histone modification, and then combined into a unique one through similarity network fusion. Finally, the similarity networks are transformed into dissimilarity graphs, to which two different cuts are applied and compared to evaluate the classic differentiation between myeloid and lymphoid cells. The results show that all histone modifications contribute almost equally to the myeloid/lymphoid differentiation, and this is also confirmed by the analysis of the fused network. However, they also suggest that histone modifications may not be the only mechanism for regulating the differentiation of hematopoietic cells.

bioinformatics↗

bioRxiv2017

Dot2dot: Accurate Whole-Genome Tandem Repeats Discovery

The advent of sequencing technologies and the consequent computational analysis of genomes has confirmed the evidence that DNA sequences contain a relevant amount of repetitions. A particularly important category of repeating sequences is that of tandem repeats (TRs). TRs are short, almost identical sequences that lie adjacent to each other. The abundance of TRs in eukaryotic genomes has suggested that they play a role in many cellular processes and, indeed, are also involved in the onset and progress of several genetic disorders.\n\nBuilding upon the idea that similar sequences can be easily displayed using graphical methods, we formalized the structure that TRs induce in dot plot matrices where a sequence is compared with itself. We further observed that a compact representation of these matrices can be built and searched in linear time in the size of the input sequence. Exploiting this observation, we developed an algorithm fast enough to be suitable for whole-genome discovery of tandem repeats.\n\nWe compared our algorithm with seven state of the art methods using as a gold standard five collections of tandem repeats: pathology-linked, forensic, for population analysis, genealogic-oriented, and variable TRs in regulatory regions. In addition, we run our algorithm on seven reference genomes to test the suitability of our approach for whole-genome analysis. Experiments show that our method: is always more accurate than the other methods, and completes the analysis of the biggest available reference genome in about one day running at a rate of 0.98Gbp/h on a standard workstation.

genomics↗