Physical constraints on accuracy and persistence during breast cancer cell chemotaxis

Expression and prognostic impact of hypoxia- and immune escape-related genes in triple-negative breast cancer: A comprehensive analysis

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that lacks effective therapeutic options. Hypoxia and immune escape are critical factors that contribute to the progression of and resistance to therapy in patients with TNBC. Nevertheless, few studies have comprehensively analyzed hypoxia and immune escape in patients with TNBC. This study aimed to examine the expression of hypoxia- and immune escape-related genes in TNBC and their influence on prognosis. TNBC datasets were downloaded and processed from The Cancer Genome Atlas and Gene Expression Omnibus. Differential expression analysis identified 4949 differentially expressed genes, between TNBC and normal tissues. The intersection yielded 116 hypoxia- and immune escape-related differentially expressed genes (H&IERDEGs), including KIF4A, BIRC5, and BUB1. Enrichment analyses indicated that H&IERDEGs were significantly enriched in biological processes, including cell chemotaxis, leukocyte migration, and cytokine-cytokine receptor interaction. Subsequently, weighted gene co-expression network analysis identified 43 module genes that were found to define two TNBC subtypes. We constructed a prognostic risk model consisting of eight signature genes, which demonstrated a high predictive performance to predict the overall survival (OS) of patients with TNBC with an area under the curve (AUC) exceeding 0.9 at 1 year survival. This indicates that the model effectively differentiates between outcomes, reflecting its robust performance. This study investigated the roles and potential mechanisms of hypoxia- and immune escape-related genes in TNBC and constructed a prognostic risk model with a high predictive performance. These findings offer novel molecular markers and potential therapeutic targets for TNBC.

Receptor polarization through localized activity and global sensitization

Eukaryotic cells chemosense concentration gradients of extracellular ligands using membrane-bound receptors that polarize their activity. Receptors from several chemosensing families are preferentially degraded after activation and undergo significant lateral diffusion, both of which may blunt their polarization. To explore the combined role of these two seemingly detrimental phenomena on active receptor polarization, we use a reaction/diffusion model. The model elucidates a counterintuitive principle that governs receptor polarization under external gradients: Localized Activity and Global Sensitization (LAGS). In LAGS, receptor activity is localized through receptor degradation or ligand unbinding. In contrast, uniform sensitivity to ligands is maintained over the plasma membrane through lateral receptor diffusion. Surprisingly, increasing preferential degradation of active receptors and increasing lateral diffusion of all receptors both sharpen active receptor polarization. Additionally, when combined with receptor oligomerization, an increase in preferential degradation allows cells to sense relative ligand gradients over a larger range of background ligand concentrations. An analytical model identifies parameter regimes that dictate which processes dominate receptor polarization. A survey of kinetic parameters suggests that receptor polarization in many mammalian pathways can be modeled using LAGS.

Size-dependent self-avoidance enables superdiffusive migration in macroscopic unicellulars

Many cells face search problems, such as finding food, mates, or shelter, where their success depends on their search strategy. In contrast to other unicellular organisms, the slime mold Physarum polycephalum forms a giant network-shaped plasmodium while foraging for food. What is the advantage of the giant cell on the verge of multicellularity? We experimentally study and quantify the migration behavior of P. polycephalum plasmodia on the time scale of days in the absence and presence of food. We develop a model which successfully describes its migration in terms of ten data-derived parameters. Using the mechanistic insights provided by our data-driven model, we find that regardless of the absence or presence of food, P. polycephalum achieves superdiffusive migration by performing a self-avoiding run-and-tumble movement. In the presence of food, the run duration statistics change, only controlling the short-term migration dynamics. However, varying organism size, we find that the long-term superdiffusion arises from self-avoidance determined by cell size, highlighting the potential evolutionary advantage that this macroscopically large cell may have.

The ability to sense the environment is heterogeneously distributed in cell populations

Channel capacity of signaling networks quantifies their fidelity in sensing extracellular inputs. Low estimates of channel capacities for several mammalian signaling networks suggest that cells can barely detect the presence/absence of environmental signals. However, given the extensive heterogeneity and temporal stability of cell state variables, we hypothesize that the sensing ability itself may depend on the state of the cells. In this work, we present an information-theoretic framework to quantify the distribution of sensing abilities from single-cell data. Using data on two mammalian pathways, we show that sensing abilities are widely distributed in the population and most cells achieve better resolution of inputs compared to an 'average cell'. We verify these predictions using live-cell imaging data on the IGFR/FoxO pathway. Importantly, we identify cell state variables that correlate with cells' sensing abilities. This information-theoretic framework will significantly improve our understanding of how cells sense in their environment.

Onco-Breastomics: An Eco-Evo-Devo Holistic Approach

Known as a diverse collection of neoplastic diseases, breast cancer (BC) can be hyperbolically characterized as a dynamic pseudo-organ, a living organism able to build a complex, open, hierarchically organized, self-sustainable, and self-renewable tumor system, a population, a species, a local community, a biocenosis, or an evolving dynamical ecosystem (i.e., immune or metabolic ecosystem) that emphasizes both developmental continuity and spatio-temporal change. Moreover, a cancer cell community, also known as an oncobiota, has been described as non-sexually reproducing species, as well as a migratory or invasive species that expresses intelligent behavior, or an endangered or parasite species that fights to survive, to optimize its features inside the host's ecosystem, or that is able to exploit or to disrupt its host circadian cycle for improving the own proliferation and spreading. BC tumorigenesis has also been compared with the early embryo and placenta development that may suggest new strategies for research and therapy. Furthermore, BC has also been characterized as an environmental disease or as an ecological disorder. Many mechanisms of cancer progression have been explained by principles of ecology, developmental biology, and evolutionary paradigms. Many authors have discussed ecological, developmental, and evolutionary strategies for more successful anti-cancer therapies, or for understanding the ecological, developmental, and evolutionary bases of BC exploitable vulnerabilities. Herein, we used the integrated framework of three well known ecological theories: the Bronfenbrenner's theory of human development, the Vannote's River Continuum Concept (RCC), and the Ecological Evolutionary Developmental Biology (Eco-Evo-Devo) theory, to explain and understand several eco-evo-devo-based principles that govern BC progression. Multi-omics fields, taken together as onco-breastomics, offer better opportunities to integrate, analyze, and interpret large amounts of complex heterogeneous data, such as various and big-omics data obtained by multiple investigative modalities, for understanding the eco-evo-devo-based principles that drive BC progression and treatment. These integrative eco-evo-devo theories can help clinicians better diagnose and treat BC, for example, by using non-invasive biomarkers in liquid-biopsies that have emerged from integrated omics-based data that accurately reflect the biomolecular landscape of the primary tumor in order to avoid mutilating preventive surgery, like bilateral mastectomy. From the perspective of preventive, personalized, and participatory medicine, these hypotheses may help patients to think about this disease as a process governed by natural rules, to understand the possible causes of the disease, and to gain control on their own health.

The ability to sense the environment is heterogeneously distributed in cell populations

Channel capacity of signaling networks quantifies their fidelity in sensing extracellular inputs. Low estimates of channel capacities for several mammalian signaling networks suggest that cells can barely detect the presence/absence of environmental signals. However, given the extensive heterogeneity and temporal stability of cell state variables, we hypothesize that the sensing ability itself may depend on the state of the cells. In this work, we present an information theoretic framework to quantify the distribution of sensing abilities from single cell data. Using data on two mammalian pathways, we show that sensing abilities are widely distributed in the population and most cells achieve better resolution of inputs compared to an " average cell ". We verify these predictions using live cell imaging data on the IGFR/FoxO pathway. Importantly, we identify cell state variables that correlate with cells' sensing abilities. This information theoretic framework will significantly improve our understanding of how cells sense in their environment.

Single-cell directional sensing from just a few receptor binding events

Identifying the directionality of signaling sources from noisy input to membrane receptors is an essential task performed by many cell types. A variety of models have been proposed to explain directional sensing in cells. However, many of these require significant computational and memory capacities for the cell. We propose and analyze a simple mechanism in which a cell adopts the direction associated with the first few membrane binding events. This model yields an accurate angular estimate to the source long before steady state is reached in biologically relevant scenarios. Our proposed mechanism allows for reliable estimates of the directionality of external signals using temporal information and assumes minimal computational capacities of the cell.

Short-time diffusive fluxes over membrane receptors yields the direction of a signalling source

An essential ability of many cell types is to detect stimuli in the form of shallow chemical gradients. Such cues may indicate the direction that new growth should occur, or the location of a mate. Amplification of these faint signals is due to intra-cellular mechanisms, while the cue itself is generated by the noisy arrival of signalling molecules to surface bound membrane receptors. We employ a new hybrid numerical-asymptotic technique coupling matched asymptotic analysis and numerical inverse Laplace transform to rapidly and accurately solve the parabolic exterior problem describing the dynamic diffusive fluxes to receptors. We observe that equilibration occurs on long timescales, potentially limiting the usefulness of steady-state quantities for localization at practical biological timescales. We demonstrate that directional information is encoded primarily in early arrivals to the receptors, while equilibrium quantities inform on source distance. We develop a new homogenization result showing that complex receptor configurations can be replaced by a uniform effective condition. In the extreme scenario where the cell adopts the angular direction of the first impact, we show this estimate to be surprisingly accurate.

Cells function as a ternary logic gate to decide migration direction under integrated chemical and fluidic cues

Cells sense various environmental cues and subsequently process intracellular signals to decide their migration direction in many physiological and pathological processes. Although several signaling molecules and networks have been identified in these directed migrations, it still remains ambiguous to predict the migration direction under multiple and integrated cues, specifically chemical and fluidic cues. Here, we investigated the cellular signal processing machinery by reverse-engineering directed cell migration under integrated chemical and fluidic cues. We imposed controlled chemical and fluidic cues to cells using a microfluidic platform and analyzed the extracellular coupling of the cues with respect to the cellular detection limit. Then, the cell's migratory behavior was reverse-engineered to build a cellular signal processing system as a logic gate, which is based on a "selection" gate. This framework is further discussed with a minimal intracellular signaling network of a shared pathway model. The proposed framework of the ternary logic gate suggests a systematic view to understand how cells decode multiple cues and make decisions about the migration direction.

Tumor spheroids accelerate persistently invading cancer cells

Glioblastoma brain tumors form in the brain’s white matter and remain one of the most lethal cancers despite intensive therapy and surgery. The complex morphology of these tumors includes infiltrative growth and gain of cell motility. Therefore, various brain-mimetic model systems have been developed to investigate invasion dynamics. Despite this, exactly how gradients of cell density, chemical signals and metabolites influence individual cells’ migratory behavior remains elusive. Here we show that the gradient field induced by the spheroid—accelerates cells’ invasion of the extracellular matrix. We show that cells are pushed away from the spheroid along a radial gradient, as predicted by a biased persistent random walk. Thus, our results grasp in a simple model the complex behavior of metastasizing cells. We anticipate that this well-defined and quantitative assay could be instrumental in the development of new anti-cancer strategies.

IGDQ motogenic peptide gradient induces directional cell migration through integrin (αv)β3 activation in MDA-MB-231 metastatic breast cancer cells

In the context of breast cancer metastasis study, we have shown in an in vitro model of cell migration that IGDQ-exposing (IsoLeu-Gly-Asp-Glutamine type I Fibronectin motif) monolayers (SAMs) on gold sustain the adhesion of breast cancer MDA-MB-231 cells by triggering Focal Adhesion Kinase and integrin activation. Such tunable scaffolds are used to mimic the tumor extracellular environment, inducing and controlling cell migration. The observed migratory behavior induced by the IGDQ-bearing peptide gradient along the surface allows to separate cell subpopulations with a "stationary" or "migratory" phenotype. In this work, we knocked down the integrins α5(β1) and (αv)β since they are already known to be implicated in cell migration. To this aim, a whole proteomic analysis was performed in beta 3 integrin (ITGB3) or alpha 5 integrin (ITGA5) knock-down MDA-MB-231 cells, in order to highlight the pathways implied in the integrin-dependent cell migration. Our results showed that i) ITGB3 depletion influenced ITGA5 mRNA expression, ii) ITGB3 and ITGA5 were both necessary for IGDQ-mediated directional single cell migration and iii) integrin (αv)β3 was activated by IGDQ fibronectin type I motif. Finally, the proteomic analysis suggested that co-regulation of recycling transport of ITGB3 by ITGA5 is potentially necessary for directional IGDQ-mediated cell migration.

Signal processing capacity of the cellular sensory machinery regulates the accuracy of chemotaxis under complex cues

Chemotaxis is ubiquitous in many biological processes, but it still remains elusive how cells sense and decipher multiple chemical cues. In this study, we postulate a hypothesis that the chemotactic performance of cells under complex cues is regulated by the signal processing capacity of the cellular sensory machinery. The underlying rationale is that cells in vivo should be able to sense and process multiple chemical cues, whose magnitude and compositions are entangled, to determine their migration direction. We experimentally show that the combination of transforming growth factor-β and epidermal growth factor suppresses the chemotactic performance of cancer cells using independent receptors to sense the two cues. Based on this observation, we develop a biophysical framework suggesting that the antagonism is caused by the saturation of the signal processing capacity but not by the mutual repression. Our framework suggests the significance of the signal processing capacity in the cellular sensory machinery.