A simplified mesoscale 3D model for characterizing fibrinolysis under flow conditions.

One of the routine clinical treatments to eliminate ischemic stroke thrombi is injecting a biochemical product into the patient's bloodstream, which breaks down the thrombi's fibrin fibers: intravenous or intravascular thrombolysis. However, this procedure is not without risk for the patient; the worst circumstances can cause a brain hemorrhage or embolism that can be fatal. Improvement in patient management drastically reduced these risks, and patients who benefited from thrombolysis soon after the onset of the stroke have a significantly better 3-month prognosis, but treatment success is highly variable. The causes of this variability remain unclear, and it is likely that some fundamental aspects still require thorough investigations. For that reason, we conducted in vitro flow-driven fibrinolysis experiments to study pure fibrin thrombi breakdown in controlled conditions and observed that the lysis front evolved non-linearly in time. To understand these results, we developed an analytical 1D lysis model in which the thrombus is considered a porous medium. The lytic cascade is reduced to a second-order reaction involving fibrin and a surrogate pro-fibrinolytic agent. The model was able to reproduce the observed lysis evolution under the assumptions of constant fluid velocity and lysis occurring only at the front. For adding complexity, such as clot heterogeneity or complex flow conditions, we propose a 3-dimensional mesoscopic numerical model of blood flow and fibrinolysis, which validates the analytical model's results. Such a numerical model could help us better understand the spatial evolution of the thrombi breakdown, extract the most relevant physiological parameters to lysis efficiency, and possibly explain the failure of the clinical treatment. These findings suggest that even though real-world fibrinolysis is a complex biological process, a simplified model can recover the main features of lysis evolution.

Shear induced diffusion of platelets revisited.

The transport of platelets in blood is commonly assumed to obey an advection-diffusion equation with a diffusion constant given by the so-called Zydney-Colton theory. Here we reconsider this hypothesis based on experimental observations and numerical simulations including a fully resolved suspension of red blood cells and platelets subject to a shear. We observe that the transport of platelets perpendicular to the flow can be characterized by a non-trivial distribution of velocities with and exponential decreasing bulk, followed by a power law tail. We conclude that such distribution of velocities leads to diffusion of platelets about two orders of magnitude higher than predicted by Zydney-Colton theory. We tested this distribution with a minimal stochastic model of platelets deposition to cover space and time scales similar to our experimental results, and confirm that the exponential-powerlaw distribution of velocities results in a coefficient of diffusion significantly larger than predicted by the Zydney-Colton theory.

Thrombolysis: Observations and numerical models.

This perspective paper considers thrombolysis in the context of ischemic strokes, intending to build eventually a numerical model capable of simulating the thrombolytic treatment and predicting patient outcomes. Numerical modeling is a scientific methodology based on an abstraction of a system but requires understanding their spatio-temporal interactions. However, although important, the current knowledge on thrombolysis is fragmented in contributions from which it is difficult to obtain a complete picture of the process, especially in a clinically relevant setup. This paper discusses, from a general point of view, how to develop a numerical model to describe the evolution of a patient clot under the action of a thrombolytic drug. We will present critical, yet fundamental, open questions that have emerged during this elaboration and discuss original experimental observations that challenge some of our current knowledge of thrombolysis.

Investigating the two regimes of fibrin clot lysis: an experimental and computational approach.

It has been observed in vitro that complete clot lysis is generally preceded by a slow phase of lysis during which the degradation seems to be inefficient. However, this slow regime was merely noticed, but not yet quantitatively discussed. In our experiments, we observed that the lysis ubiquitously occurred in two distinct regimes, a slow and a fast lysis regime. We quantified extensively the duration of these regimes for a wide spectrum of experimental conditions and found that on average, the slow regime lasts longer than the fast one, meaning that during most of the process, the lysis is ineffective. We proposed a computational model in which the properties of the binding of the proteins change during the lysis: first, the biochemical reactions take place at the surface of the fibrin fibers, then in the bulk, resulting in the observed fast lysis regime. This simple hypothesis appeared to be sufficient to reproduce with a great accuracy the lysis profiles obtained experimentally.

Discovering functional evolutionary dependencies in human cancers.

Cancer cells retain genomic alterations that provide a selective advantage. The prediction and validation of advantageous alterations are major challenges in cancer genomics. Moreover, it is crucial to understand how the coexistence of specific alterations alters response to genetic and therapeutic perturbations. In the present study, we inferred functional alterations and preferentially selected combinations of events in >9,000 human tumors. Using a Bayesian inference framework, we validated computational predictions with high-throughput readouts from genetic and pharmacological screenings on 2,000 cancer cell lines. Mutually exclusive and co-occurring cancer alterations reflected, respectively, functional redundancies able to rescue the phenotype of individual target inhibition, or synergistic interactions, increasing oncogene addiction. Among the top scoring dependencies, co-alteration of the phosphoinositide 3-kinase (PI3K) subunit PIK3CA and the nuclear factor NFE2L2 was a synergistic evolutionary trajectory in squamous cell carcinomas. By integrating computational, experimental and clinical evidence, we provide a framework to study the combinatorial functional effects of cancer genomic alterations.

Traction Forces Control Cell-Edge Dynamics and Mediate Distance Sensitivity during Cell Polarization.

Traction forces are generated by cellular actin-myosin system and transmitted to the environment through adhesions. They are believed to drive cell motion, shape changes, and extracellular matrix remodeling [1-3]. However, most of the traction force analysis has been performed on stationary cells, investigating forces at the level of individual focal adhesions or linking them to static cell parameters, such as area and edge curvature [4-10]. It is not well understood how traction forces are related to shape changes and motion, e.g., forces were reported to either increase or drop prior to cell retraction [11-15]. Here, we analyze the dynamics of traction forces during the protrusion-retraction cycle of polarizing fish epidermal keratocytes and find that forces fluctuate together with the cycle, increasing during protrusion and reaching maximum at the beginning of retraction. We relate force dynamics to the recently discovered phenomenological rule [16] that governs cell-edge behavior during keratocyte polarization: both traction forces and probability of switch from protrusion to retraction increase with the distance from the cell center. Diminishing forces with cell contractility inhibitor leads to decreased edge fluctuations and abnormal polarization, although externally applied force can induce protrusion-retraction switch. These results suggest that forces mediate distance sensitivity of the edge dynamics and organize cell-edge behavior, leading to spontaneous polarization. Actin flow rate did not exhibit the same distance dependence as traction stress, arguing against its role in organizing edge dynamics. Finally, using a simple model of actin-myosin network, we show that force-distance relationship might be an emergent feature of such networks.

Dynamic Emergence of Observed and Hidden Intra-tumor Heterogeneity.

Intra-tumor heterogeneity is frequently observed in cancer patients, and it is associated with therapeutic resistance and disease relapse. However, its systematic assessment is still limited and often unfeasible. Here, we use a mathematical model of tumor progression to decipher how multiple clones emerge and organize into complex architectures. We found a trade-off between cancer cell alteration and proliferation rates that defines a transition between low and high heterogeneity, the latter characterized by branching tumor phylogenies. We predict the existence of observed and hidden intra-tumor heterogeneity, which challenges the correct estimation of intrinsic tumor complexity. Although the numbers of observed and hidden clones do not always correlate, we demonstrate that population frequencies of observed clones can be used to estimate the extent of hidden heterogeneity in both simulated and human tumors. The characterization of complex clonal architectures is a critical first step toward understanding their organizing principles and predicting their emergence.

EZH2 oncogenic mutations drive epigenetic, transcriptional, and structural changes within chromatin domains.

Chromatin is organized into topologically associating domains (TADs) enriched in distinct histone marks. In cancer, gain-of-function mutations in the gene encoding the enhancer of zeste homolog 2 protein (EZH2) lead to a genome-wide increase in histone-3 Lys27 trimethylation (H3K27me3) associated with transcriptional repression. However, the effects of these epigenetic changes on the structure and function of chromatin domains have not been explored. Here, we found a functional interplay between TADs and epigenetic and transcriptional changes mediated by mutated EZH2. Altered EZH2 (p.Tyr646* (EZH2Y646X)) led to silencing of entire domains, synergistically inactivating multiple tumor suppressors. Intra-TAD gene silencing was coupled with changes of interactions between gene promoter regions. Notably, gene expression and chromatin interactions were restored by pharmacological inhibition of EZH2Y646X. Our results indicate that EZH2Y646X alters the topology and function of chromatin domains to promote synergistic oncogenic programs.

Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability.

Genomic instability is a major driver of intra-tumor heterogeneity. However, unstable genomes often exhibit different molecular and clinical phenotypes, which are associated with distinct mutational processes. Here, we algorithmically inferred the clonal phylogenies of ~6,000 human tumors from 32 tumor types to explore how intra-tumor heterogeneity depends on different implementations of genomic instability. We found that extremely unstable tumors associated with DNA repair deficiencies or high chromosomal instability are not the most intrinsically heterogeneous. Conversely, intra-tumor heterogeneity is greatest in tumors exhibiting relatively high numbers of both mutations and copy number alterations, a feature often observed in cancers associated with exogenous mutagens. Independently of the type of instability, tumors with high number of clones invariably evolved through branching phylogenies that could be stratified based on the extent of clonal (early) and subclonal (late) instability. Interestingly, tumors with high number of subclonal mutations frequently exhibited chromosomal instability, TP53 mutations, and APOBEC-related mutational signatures. Vice versa, mutations of chromatin remodeling genes often characterized tumors with few subclonal but multiple clonal mutations. Understanding how intra-tumor heterogeneity depends on genomic instability is critical to identify markers predictive of the tumor complexity and envision therapeutic strategies able to exploit this association.

Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response.

Comprehensive Genetic Landscape of Uveal Melanoma by Whole-Genome Sequencing.

Uveal melanoma (UM) is a rare intraocular tumor that, similar to cutaneous melanoma, originates from melanocytes. To gain insights into its genetics, we performed whole-genome sequencing at very deep coverage of tumor-control pairs in 33 samples (24 primary and 9 metastases). Genome-wide, the number of coding mutations was rather low (only 17 variants per tumor on average; range 7-28), thus radically different from cutaneous melanoma, where hundreds of exonic DNA insults are usually detected. Furthermore, no UV light-induced mutational signature was identified. Recurrent coding mutations were found in the known UM drivers GNAQ, GNA11, BAP1, EIF1AX, and SF3B1. Other genes, i.e., TP53BP1, CSMD1, TTC28, DLK2, and KTN1, were also found to harbor somatic mutations in more than one individual, possibly indicating a previously undescribed association with UM pathogenesis. De novo assembly of unmatched reads from non-coding DNA revealed peculiar copy-number variations defining specific UM subtypes, which in turn could be associated with metastatic transformation. Mutational-driven comparison with other tumor types showed that UM is very similar to pediatric tumors, characterized by very few somatic insults and, possibly, important epigenetic changes. Through the analysis of whole-genome sequencing data, our findings shed new light on the molecular genetics of uveal melanoma, delineating it as an atypical tumor of the adult for which somatic events other than mutations in exonic DNA shape its genetic landscape and define its metastatic potential.

Collective motion of self-propelled particles interacting without cohesion.

We present a comprehensive study of Vicsek-style self-propelled particle models in two and three space dimensions. The onset of collective motion in such stochastic models with only local alignment interactions is studied in detail and shown to be discontinuous (first-order-like). The properties of the ordered, collectively moving phase are investigated. In a large domain of parameter space including the transition region, well-defined high-density and high-order propagating solitary structures are shown to dominate the dynamics. Far enough from the transition region, on the other hand, these objects are not present. A statistically homogeneous ordered phase is then observed, which is characterized by anomalously strong density fluctuations, superdiffusion, and strong intermittency.

Linear patterning of magnetically labeled Dictyostelium cells to display confined development.

In severe nutriment conditions, the social amoeba Dictyostelium discoideum enters a particular life cycle where it forms multicellular patterns to achieve aggregation. Extensively observed from an initial dispersed state, its developmental program can usefully be studied from a confined population to implement theoretical developments regarding biological self-organization. The challenge is then to form a cell assembly of well-defined geometrical dimensions without hindering cell behavior. To achieve this goal, we imposed transient constraints by applying temporary external magnetic gradients to trap magnetically labeled cells. Deposits of various numbers of cells were geometrically characterized for different magnetic exposure conditions. We demonstrated that the cell deposit was organized as a three-dimensional (3D) structure by both stacking layers of cells and extending these layers in the substrate plane. This structure evolves during the aggregation phase, forming periodic aggregative centers along the linear initial pattern.

Spreading of a granular droplet.

The influence of controlled vibrations on the granular rheology is investigated in a specifically designed experiment in which a granular film spreads under the action of horizontal vibrations. A nonlinear diffusion equation is derived theoretically that describes the evolution of the deposit shape. A self-similar parabolic shape (the "granular droplet") and a spreading dynamics are predicted that both agree quantitatively with the experimental results. The theoretical analysis is used to extract effective friction coefficients between the base and the granular layer under sustained and controlled vibrations. A shear thickening regime characteristic of dense granular flows is evidenced at low vibration energy, both for glass beads and natural sand. Conversely, shear thinning is observed at high agitation.