Multicellular Clusters Research Articles

N-Cadherin based adhesion and Rac1 activity regulate tension polarization in the actin cortex.

Tension-adhesion interplay is a crucial mechanism in multicellular organisms that determines the tension differential among internal and external interfaces, which in turn, mediates tissue surface tension and cell sorting, morphogenesis and remodeling, and cancer progression. Cadherins are widely believed to be involved, yet key aspects of the process are neither well characterized nor quantified. This study demonstrates the critical role of N-cadherin in driving tension polarization throughout the actin cortical network. N-cadherin regulates both tension increase at the cell-medium (external) interface and decrease at the cell-cell (internal) interface, and their quantitative magnitudes, both absolute and relative, strongly depend on the surface density of N-cadherin. Furthermore, the strength of tension polarization also increases with respect to the number of cell-cell interfaces for cells within a multicellular cluster. The cadherin-actin contractility linkage is mediated by Rac1, which serves as a molecular switch to trigger cortex remodeling and contraction via myosin II. Inhibition of Rac1 activity decreases tension polarization and leads to reduced coherence in both small clusters and spheroids. These results provide a pathway to reconcile opposing theories for tissue surface tension generation and perspectives in cancer treatment.

MIRD Pamphlet No. 31: MIRDcell V4-Artificial Intelligence Tools to Formulate Optimized Radiopharmaceutical Cocktails for Therapy.

Radiopharmaceutical cocktails have been developed over the years to treat cancer. Cocktails of agents are attractive because 1 radiopharmaceutical is unlikely to have the desired therapeutic effect because of nonuniform uptake by the targeted cells. Therefore, multiple radiopharmaceuticals targeting different receptors on a cell is warranted. However, past implementations invivo have not met with convincing results because of the absence of optimization strategies. Here we present artificial intelligence (AI) tools housed in a new version of our software platform, MIRDcell V4, that optimize a cocktail of radiopharmaceuticals by minimizing the total disintegrations needed to achieve a given surviving fraction (SF) of tumor cells. Methods: AI tools are developed within MIRDcell V4 using an optimizer based on the sequential least-squares programming algorithm. The algorithm determines the molar activities for each drug in the cocktail that minimize the total disintegrations required to achieve a specified SF. Tools are provided for populations of cells that do not cross-irradiate (e.g., circulating or disseminated tumor cells) and for multicellular clusters (e.g., micrometastases). The tools were tested using model data, flow cytometry data for suspensions of single cells labeled with fluorochrome-labeled antibodies, and 3-dimensional spatiotemporal kinetics in spheroids for fluorochrome-loaded liposomes. Results: Experimental binding distributions of 4 211At-antibodies were considered for treating suspensions of MDA-MB-231 human breast cancer cells. A 2-drug combination reduced the number of 211At decays required by a factor of 1.6 relative to the best single antibody. In another study, 2 radiopharmaceuticals radiolabeled with 195mPt were each distributed lognormally in a hypothetical multicellular cluster. Here, the 2-drug combination required 1.7-fold fewer decays than did either drug alone. Finally, 2 225Ac-labeled drugs that provide different radial distributions within a spheroid require about one half of the disintegrations required by the best single agent. Conclusion: The MIRDcell AI tools determine optimized drug combinations and corresponding molar activities needed to achieve a given SF. This approach could be used to analyze a sample of cells obtained from cell culture, animal, or patient to predict the best combination of drugs for maximum therapeutic effect with the least total disintegrations.

Metabolically-driven flows enable exponential growth in macroscopic multicellular yeast.

The ecological and evolutionary success of multicellular lineages is due in no small part to their increased size relative to unicellular ancestors. However, large size also poses biophysical challenges, especially regarding the transport of nutrients to all cells; these constraints are typically overcome through multicellular innovations (e.g., a circulatory system). Here we show that an emergent biophysical mechanism - spontaneous fluid flows arising from metabolically-generated density gradients - can alleviate constraints on nutrient transport, enabling exponential growth in nascent multicellular clusters of yeast lacking any multicellular adaptations for nutrient transport or fluid flow. Surprisingly, beyond a threshold size, the metabolic activity of experimentally-evolved snowflake yeast clusters drives large-scale fluid flows that transport nutrients throughout the cluster at speeds comparable to those generated by the cilia of extant multicellular organisms. These flows support exponential growth at macroscopic sizes that theory predicts should be diffusion limited. This work demonstrates how simple physical mechanisms can act as a 'biophysical scaffold' to support the evolution of multicellularity by opening up phenotypic possibilities prior to genetically-encoded innovations. More broadly, our findings highlight how co-option of conserved physical processes is a crucial but underappreciated facet of evolutionary innovation across scales.

Experimental evolution of multicellularity via cuboidal cell packing in fission yeast

Abstract The evolution of multicellularity represents a major transition in life’s history, enabling the rise of complex organisms. Multicellular groups can evolve through multiple developmental modes, but a common step is the formation of permanent cell–cell attachments after division. The characteristics of the multicellular morphology that emerges have profound consequences for the subsequent evolution of a nascent multicellular lineage, but little prior work has investigated these dynamics directly. Here, we examine a widespread yet understudied emergent multicellular morphology: cuboidal packing. Extinct and extant multicellular organisms across the tree of life have evolved to form groups in which spherical cells divide but remain attached, forming approximately cubic subunits. To experimentally investigate the evolution of cuboidal cell packing, we used settling selection to favor the evolution of simple multicellularity in unicellular, spherical Schizosaccharomyces pombe yeast. Multicellular clusters with cuboidal organization rapidly evolved, displacing the unicellular ancestor. These clusters displayed key hallmarks of an evolutionary transition in individuality: groups possess an emergent life cycle driven by physical fracture, group size is heritable, and they respond to group-level selection via multicellular adaptation. In 2 out of 5 lineages, group formation was driven by mutations in the ace2 gene, preventing daughter cell separation after division. Remarkably, ace2 mutations also underlie the transition to multicellularity in Saccharomyces cerevisiae and Candida glabrata, lineages that last shared a common ancestor >300 million years ago. Our results provide insight into the evolution of cuboidal cell packing, an understudied multicellular morphology, and highlight the deeply convergent potential for a transition to multicellular individuality within fungi.

A dynamic network model predicts the phenotypes of multicellular clusters from cellular properties

Cell division without cell separation produces multicellular clusters in budding yeast. Two fundamental characteristics of these clusters are their size (the number of cells per cluster) and cellular composition: the fractions of cells with different phenotypes. Using cells as nodes and links between mother and daughter cells as edges, we model cluster growth and breakage by varying three parameters: the cell division rate, the rate at which intercellular connections break, and the kissing number (the maximum number of connections to one cell). We find that the kissing number sets the maximum possible cluster size. Below this limit, the ratio of the cell division rate to the connection breaking rate determines the cluster size. If links have a constant probability of breaking per unit time, the probability that a link survives decreases exponentially with its age. Modeling this behavior recapitulates experimental data. We then use this framework to examine synthetic, differentiating clusters with two cell types, faster-growing germ cells and their somatic derivatives. The fraction of clusters that contain both cell types increases as either of two parameters increase: the kissing number and difference between the growth rate of germ and somatic cells. In a population of clusters, the variation in cellular composition is inversely correlated (r2= 0.87) with the average fraction of somatic cells in clusters. Our results show how a small number of cellular features can control the phenotypes of multicellular clusters that were potentially the ancestors of more complex forms of multicellular development, organization, and reproduction.

Abstract SY34-01: Plasticity, dormancy, and glycosylation of circulating tumor cell clusters in response to therapy

Abstract Cellular plasticity and stemness properties enable dynamic changes of circulating tumor cells (CTCs) during cancer dissemination, such as aggregation or cohesion of single CTCs into multicellular CTC clusters with 20-100 times higher metastatic propensity than the singles. Our work demonstrated that stemness glycoproteins on breast cancer stem cells, such as CD44, CD81, and ICAM1 drive CTC aggregation in metastatic breast cancer, such as triple negative breast cancer (TNBC). To determine the glycosylation patterns in CTCs and its association with clinical outcomes, we established multiple CTC analysis approaches including CellSearch, flow cytometry, and immunohistochemistry using patient blood and tissue sections collected at the pre-treatment baseline and after-therapy timepoints. We found that chemotherapy-evasive CTC clusters are relatively quiescent with a specific loss of terminal sugar residues α2,6-sialic acids in glycoproteins. CTCs showed dynamic hypo-sialylation in the blood with loss of the sialyl-transferase ST6GAL1, promoting CTC cluster formation with cellular quiescence (proliferative dormancy) and evading chemotherapy in breast cancer. Seeded tumor cells regained ST6GAL1 to enable metastatic colonization. Many adhesion proteins and stemness drivers as glycoprotein substrates of ST6GAL1 drive CTC clustering and metastatic seeding. Neutralizing antibodies against these clustering drivers inhibit CTC cluster formation and improve therapy response, thereby blocking lung metastasis in TNBC. Citation Format: Huiping Liu. Plasticity, dormancy, and glycosylation of circulating tumor cell clusters in response to therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY34-01.

Rare, Tightly-Bound, Multi-Cellular Clusters in the Pancreatic Ducts of Adult Mice Function Like Progenitor Cells and Survive and Proliferate After Acinar Cell Injury.

Pancreatic ductal progenitor cells have been proposed to contribute to adult tissue maintenance and regeneration after injury, but the identity of such ductal cells remains elusive. Here, from adult mice, we identify a near homogenous population of ductal progenitor-like clusters, with an average of 8 cells per cluster. They are a rare subpopulation, about 0.1% of the total pancreatic cells, and can be sorted using a fluorescence-activated cell sorter with the CD133highCD71lowFSCmid-high phenotype. They exhibit properties in self-renewal and tri-lineage differentiation (including endocrine-like cells) in a unique 3-dimensional colony assay system. An in vitro lineage tracing experiment, using a novel HprtDsRed/+ mouse model, demonstrates that a single cell from a cluster clonally gives rise to a colony. Droplet RNAseq analysis demonstrates that these ductal clusters express embryonic multipotent progenitor cell markers Sox9, Pdx1, and Nkx6-1, and genes involved in actin cytoskeleton regulation, inflammation responses, organ development, and cancer. Surprisingly, these ductal clusters resist prolonged trypsin digestion in vitro, preferentially survive in vivo after a severe acinar cell injury and become proliferative within 14 days post-injury. Thus, the ductal clusters are the fundamental units of progenitor-like cells in the adult murine pancreas with implications in diabetes treatment and tumorigenicity.

Comparison of holotomographic microscopy and coherence-controlled holographic microscopy.

Quantitative phase imaging (QPI) is a powerful tool for label-free visualisation of living cells. Here, we compare two QPI microscopes - the Telight Q-Phase microscope and the Nanolive 3D Cell Explorer-fluo microscope. Both systems provide unbiased information about cell morphology, such as individual cell dry mass, perimeter and area. The Q-Phase microscope uses artefact-free, coherence-controlled holographic imaging technology to visualise cells in real time with minimal phototoxicity. The 3D Cell Explorer-fluo employs laser-based holotomography to reconstruct 3D images of living cells, visualising their internal structures and dynamics. Here, we analysed the strengths and limitations of both microscopes when examining two morphologically distinct cell lines - the cuboidal epithelial MDCK cells which form multicellular clusters and solitary growing Rat2 fibroblasts. We focus mainly on the ability of the devices to generate images suitable for single-cell segmentation by the built-in software, and we discuss the segmentation results and quantitative data generated from the segmented images. We show that both microscopes offer slightly different advantages, and the choice between them depends on the specific requirements and goals of the user.

Bidirectionally validated in silico and in vitro formation of specific depth zone-derived chondrocyte spheroids and clusters.

3D multicellular self-organized cluster models, e.g., organoids are promising tools for developing new therapeutic modalities including gene and cell therapies, pharmacological mechanistic and screening assays. Various applications of these models have been used extensively for decades, however, the mechanisms of cluster formation, maintenance, and degradation of these models are not even known over in-vitro-life-time. To explore such advantageous models mimicking native tissues or organs, it is necessary to understand aforementioned mechanisms. Herein, we intend to clarify the mechanisms of the formation of cell clusters. We previously demonstrated that primary chondrocytes isolated from distinct longitudinal depth zones in articular cartilage formed zone-specific spherical multicellular clusters in vitro. To elucidate the mechanisms of such cluster formation, we simulated it using the computational Cellular Potts Model with parameters were translated from gene expression levels and histological characteristics corresponding to interactions between cell and extracellular matrix. This simulation in silico was validated morphologically with cluster formation in vitro and vice versa. Since zone specific chondrocyte cluster models in silico showed similarity with corresponding in vitro model, the in silico has a potential to be used for prediction of the 3D multicellular in vitro models used for development, disease, and therapeutic models.

Upregulation of CELSR1 expression promotes ovarian cancer cell proliferation, migration, and invasion.

Cadherin epidermal growth factor and laminin-G seven-pass G-type receptor 1 (CELSR1) is a planar cell polarity protein involved in the transmission of directional cues to align either individual cells within an epithelial sheet or multicellular clusters. CELSR1 has been suggested to play a role in glioma, breast cancer, and chronic lymphocytic leukemia development; however, whether it has a role in the pathogenesis of ovarian cancer remains unknown. The aim of this study was to determine the role of CELSR1 in ovarian cancer and elucidate its underlying molecular mechanisms. By analyzing gene expression data downloaded from the Cancer Genome Atlas database,we found that CELSR1 expression was upregulated in ovarian cancer tissues compared to that in normal ovarian tissues. High CELSR1 expression levels were associated with poor prognosis in patients with ovarian cancer. Cell proliferation, scratch, and transwell assays revealed that CELSR1 promoted the proliferation, migration, and invasion of ovarian cancer cells in vitro. In addition, transcriptome sequencing analysis revealed that CELSR1 knockdown in T29H cells resulted in the dysregulation of the expression of 1320 genes. Further analysis revealed that genes involved in proliferation- and migration-associated signaling pathways were regulated by CELSR1. Our study demonstrates that CELSR1 is highly expressed in ovarian cancer cells and regulates their proliferation and migration, suggesting its potential as a diagnostic marker and therapeutic target.

Polarization and motility of one-dimensional multi-cellular trains

Collective cell migration, whereby cells adhere to form multi-cellular clusters that move as a single entity, play an important role in numerous biological processes, such as during development and cancer progression. Recent experimental work focused on migration of one-dimensional cellular clusters, confined to move along adhesive lanes, as a simple geometry in which to systematically study this complex system. One-dimensional migration also arises in the body when cells migrate along blood vessels, axonal projections, and narrow cavities between tissues. We explore here the modes of one-dimensional migration of cellular clusters (“trains”) by implementing cell-cell interactions in a model of cell migration that contains a mechanism for spontaneous cell polarization. We go beyond simple phenomenological models of the cells as self-propelled particles by having the internal polarization of each cell depend on its interactions with the neighboring cells that directly affect the actin polymerization activity at the cell’s leading edges. Both contact inhibition of locomotion and cryptic lamellipodia interactions between neighboring cells are introduced. We find that this model predicts multiple motility modes of the cell trains, which can have several different speeds for the same polarization pattern. Compared to experimental data, we find that MDCK cells are poised along the transition region where contact inhibition of locomotion and cryptic lamellipodia roughly balance each other, where collective migration speed is most sensitive to the values of the cell-cell interaction strength.

Soft Hydrogels with Double Porosity Modified with RGDS for Tissue Engineering.

This study develops and characterizes novel biodegradable soft hydrogels with dual porosity based on N-(2-hydroxypropyl)methacrylamide (HPMA) copolymers cross-linked by hydrolytically degradable linkers. The structure and properties of the hydrogels are designed as scaffolds for tissue engineering and they are tested in vitro with model mesenchymal stem cells (rMSCs). Detailed morphological characterization confirms dual porosity suitable for cell growth and nutrient transport. The dual porosity of hydrogels slightly improves rMSCs proliferation compared to the hydrogel with uniform pores. In addition, the laminin coating supports the adhesion of rMSCs to the hydrogel surface. However, hydrogels modified by heptapeptide RGDSGGY significantly stimulate cell adhesion and growth. Moreover, the RGDS-modified hydrogels also affect the topology of proliferating rMSCs, ranging from single-cell to multicellular clusters. The 3D reconstruction of the hydrogels with cells obtained by laser scanning confocal microscopy (LSCM) confirms cell penetration into the inner structure of the hydrogel and its corresponding microstructure. The prepared biodegradable oligopeptide-modified hydrogels with dual porosity are suitable candidates for further in vivo evaluation in soft tissue regeneration.

Analyzing force measurements of multi-cellular clusters comprising indeterminate geometries.

Multi-cellular biomimetic models often comprise heterogenic geometries. Therefore, quantification of their mechanical properties-which is crucial for various biomedical applications-is a challenge. Due to its simplicity, linear fitting is traditionally used in analyzing force-displacement data of parallel compression measurements of multi-cellular clusters, such as tumor spheroids. However, the linear assumption would be artificial when the contact geometry is not planar. We propose here the integrated elasticity (IE) regression, which is based on extrapolation of established elastic theories for well-defined geometries, and is free, extremely simple to apply, and optimal for analyzing coarsely concave multi-cellular clusters. We studied here the quality of the data analysis in force measurements of tumor spheroids comprising different types of melanoma cells, using either the IE or the traditional linear regressions. The IE regression maintained excellent precision also when the contact geometry deviated from planarity (as shown by our image analysis). While the quality of the linear fittings was relatively satisfying, these predicted smaller elastic moduli as compared to the IE regression. This was in accordance with previous studies, in which the elastic moduli predicted by linear fits were smaller compared to those obtained by well-established methods. This suggests that linear regressions underestimate the elastic constants of bio-samples even in cases where the fitting precision seems satisfying, and highlights the need in alternative methods as the IE scheme. For comparison between different types of spheroids we further recommend to increase the soundness by regarding relative moduli, using universal reference samples.

Collective heterogeneity of mitochondrial potential in contact inhibition of proliferation

In the epithelium, cell density and cell proliferation are closely connected to each other through contact inhibition of proliferation (CIP). Depending on cell density, CIP proceeds through three distinct stages: the free-growing stage at low density, the pre-epithelial transition stage at medium density, and the post-epithelial transition stage at high density. Previous studies have elucidated how cell morphology, motion, and mechanics vary in these stages. However, it remains unknown whether cellular metabolism also has a density-dependent behavior. By measuring the mitochondrial membrane potential at different cell densities, here we reveal a heterogeneous landscape of metabolism in the epithelium, which appears qualitatively distinct in three stages of CIP and did not follow the trend of other CIP-associated parameters, which increases or decreases monotonically with increasing cell density. Importantly, epithelial cells established a collective metabolic heterogeneity exclusively in the pre-epithelial transition stage, where the multicellular clusters of high- and low-potential cells emerged. However, in the post-epithelial transition stage, the metabolic potential field became relatively homogeneous. Next, to study the underlying dynamics, we constructed a system biology model, which predicted the role of cell proliferation in metabolic potential toward establishing collective heterogeneity. Further experiments indeed revealed that the metabolic pattern spatially correlated with the proliferation capacity of cells, as measured by the nuclear localization of a pro-proliferation protein, YAP. Finally, experiments perturbing the actomyosin contractility revealed that, while metabolic heterogeneity was maintained in the absence of actomyosin contractility, its ab initio emergence depended on the latter. Taken together, our results revealed a density-dependent collective heterogeneity in the metabolic field of a pre-epithelial transition-stage epithelial monolayer, which may have significant implications for epithelial form and function.

Geometrical control of interface patterning underlies active matter invasion

Interaction between active materials and the boundaries of geometrical confinement is key to many emergent phenomena in active systems. For living active matter consisting of animal cells or motile bacteria, the confinement boundary is often a deformable interface, and it has been unclear how activity-induced interface dynamics might lead to morphogenesis and pattern formation. Here, we studied the evolution of bacterial active matter confined by a deformable boundary. We found that an ordered morphological pattern emerged at the interface characterized by periodically spaced interfacial protrusions; behind the interfacial protrusions, bacterial swimmers self-organized into multicellular clusters displaying +1/2 nematic defects. Subsequently, a hierarchical sequence of transitions from interfacial protrusions to creeping branches allowed the bacterial active drop to rapidly invade surrounding space with a striking self-similar branch pattern. We found that this interface patterning is geometrically controlled by the local curvature of the interface, a phenomenon we denote as collective curvature sensing. Using a continuum active model, we revealed that the collective curvature sensing arises from enhanced active stresses near high-curvature regions, with the active length scale setting the characteristic distance between the interfacial protrusions. Our findings reveal a protrusion-to-branch transition as a unique mode of active matter invasion and suggest a strategy to engineer pattern formation of active materials.

Epithelial multicellular clustering enabled by polarized macrophages on soft matrices.

Formation of epithelial structures of variegated geometries and sizes is essential for organogenesis, tumor growth, and wound repair. Although epithelial cells are predisposed with potential for multicellular clustering, it remains unclear whether immune cells and mechanical cues from their microenvironment influence this process. To explore this possibility, we cocultured human mammary epithelial cells with prepolarized macrophages on soft or stiff hydrogels. In the presence of M1 (proinflammatory) macrophages on soft matrices, epithelial cells migrated faster and subsequently formed larger multicellular clusters compared to cocultures with M0 (unpolarized) or M2 (anti-inflammatory) macrophages. By contrast, stiff matrices disabled active clustering of epithelial cells due to their enhanced migration and cell-ECM adhesion, regardless of macrophage polarization. We found that the copresence of soft matrices and M1 macrophages reduced focal adhesions, but enhanced fibronectin deposition and nonmuscle myosin-IIA expression, which altogether optimize conditions for epithelial clustering. Upon ROCK inhibition, epithelial clustering was abrogated, indicating a requirement for optimized cellular forces. In these cocultures, TNF-α secretion was the highest with M1 macrophages and TGF-β secretion was exclusively detectable in case of M2 macrophages on soft gels, which indicated potential role of macrophage secreted factors in the observed epithelial clustering. Indeed, exogenous addition of TGF-β promoted epithelial clustering with M1 coculture on soft gels. According to our findings, optimization of both mechanical and immune factors can tune epithelial clustering responses, which could have implications in tumor growth, fibrosis, and would healing.

Bacteria evolve macroscopic multicellularity by the genetic assimilation of phenotypically plastic cell clustering

The evolutionary transition from unicellularity to multicellularity was a key innovation in the history of life. Experimental evolution is an important tool to study the formation of undifferentiated cellular clusters, the likely first step of this transition. Although multicellularity first evolved in bacteria, previous experimental evolution research has primarily used eukaryotes. Moreover, it focuses on mutationally driven (and not environmentally induced) phenotypes. Here we show that both Gram-negative and Gram-positive bacteria exhibit phenotypically plastic (i.e., environmentally induced) cell clustering. Under high salinity, they form elongated clusters of ~ 2 cm. However, under habitual salinity, the clusters disintegrate and grow planktonically. We used experimental evolution with Escherichia coli to show that such clustering can be assimilated genetically: the evolved bacteria inherently grow as macroscopic multicellular clusters, even without environmental induction. Highly parallel mutations in genes linked to cell wall assembly formed the genomic basis of assimilated multicellularity. While the wildtype also showed cell shape plasticity across high versus low salinity, it was either assimilated or reversed after evolution. Interestingly, a single mutation could genetically assimilate multicellularity by modulating plasticity at multiple levels of organization. Taken together, we show that phenotypic plasticity can prime bacteria for evolving undifferentiated macroscopic multicellularity.

Fiber density and matrix stiffness modulate distinct cell migration modes in a 3D stroma mimetic composite hydrogel.

The peritumoral stroma is a complex 3D tissue that provides cells with myriad biophysical and biochemical cues. Histologic observations suggest that during metastatic spread of carcinomas, these cues influence transformed epithelial cells, prompting a diversity of migration modes spanning single cell and multicellular phenotypes. Purported consequences of these variations in tumor escape strategies include differential metastatic capability and therapy resistance. Therefore, understanding how cues from the peritumoral stromal microenvironment regulate migration mode has both prognostic and therapeutic value. Here, we utilize a synthetic stromal mimetic in which matrix fiber density and bulk hydrogel mechanics can be orthogonally tuned to investigate the contribution of these two key matrix attributes on MCF10A migration mode phenotypes, epithelial-mesenchymal transition (EMT), and invasive potential. We develop an automated computational image analysis framework to extract migratory phenotypes from fluorescent images and determine 3D migration metrics relevant to metastatic spread. Using this analysis, we find that matrix fiber density and bulk hydrogel mechanics distinctly contribute to a variety of MCF10A migration modes including amoeboid, single mesenchymal, clusters, and strands. We identify combinations of physical and soluble cues that induce a variety of migration modes originating from the same MCF10A spheroid and use these settings to examine a functional consequence of migration mode -resistance to apoptosis. We find that cells migrating as strands are more resistant to staurosporine-induced apoptosis than either disconnected clusters or individual invading cells. Improved models of the peritumoral stromal microenvironment and understanding of the relationships between matrix attributes and cell migration mode can aid ongoing efforts to identify effective cancer therapeutics that address cell plasticity-based therapy resistances. STATEMENT OF SIGNIFICANCE: Stromal extracellular matrix structure dictates both cell homeostasis and activation towards migratory phenotypes. However decoupling the effects of myriad biophysical cues has been difficult to achieve. Here, we encapsulate electrospun fiber segments within an amorphous hydrogel to create a fiber-reinforced hydrogel composite in which fiber density and hydrogel stiffness can be orthogonally tuned. Quantification of 3D cell migration reveal these two parameters uniquely contribute to a diversity of migration phenotypes spanning amoeboid, single mesenchymal, multicellular cluster, and collective strand. By tuning biophysical and biochemical cues to elicit heterogeneous migration phenotypes, we find that collective strands best resist apoptosis. This work establishes a composite approach to modulate fibrous topography and bulk hydrogel mechanics and identified biomaterial parameters to direct distinct 3D cell migration phenotypes.

Alternating selection for dispersal and multicellularity favors regulated life cycles

The evolution of complex multicellularity opened paths to increased morphological diversity and organizational novelty. This transition involved three processes: cells remained attached to one another to form groups, cells within these groups differentiated to perform different tasks, and the groups evolved new reproductive strategies.1,2,3,4,5 Recent experiments identified selective pressures and mutations that can drive the emergence of simple multicellularity and cell differentiation,6,7,8,9,10,11 but the evolution of life cycles, particularly how simple multicellular forms reproduce, has been understudied. The selective pressure and mechanisms that produced a regular alternation between single cells and multicellular collectives are still unclear.12 To probe the factors regulating simple multicellular life cycles, we examined a collection of wild isolates of the budding yeast S.cerevisiae.12,13 We found that all these strains can exist as multicellular clusters, a phenotype that is controlled by the mating-type locus and strongly influenced by the nutritional environment. Inspired by this variation, we engineered inducible dispersal in a multicellular laboratory strain and demonstrated that a regulated life cycle has an advantage over constitutively single-celled or constitutively multicellular life cycles when the environment alternates between favoring intercellular cooperation (a low sucrose concentration) and dispersal (a patchy environment generated by emulsion). Our results suggest that the separation of mother and daughter cells is under selection in wild isolates and is regulated by their genetic composition and the environments they encounter and that alternating patterns of resource availability may have played a role in the evolution of life cycles.

Abstract 1326: Perineural invasion and bone metastases in prostate cancer - is there a link

Abstract Bone metastases are the most common secondary lesions in prostate cancer (PCa) patients. Typically, initial bone metastases develop in the lower part of the spine and pelvis. While this metastatic pattern is not consistent with the random nature of the arterial osseous dissemination, previous reports suggested the role of the retrograde venous spread in this phenomenon. However, clinical data also indicate a positive association between the degree of perineural invasion (PNI) and bone metastases in PCa patients. Yet, the mechanism linking these two means of dissemination remains unknown. To identify the processes involved in the initial PCa dissemination we used the PC3-ML cell line, which was previously shown to trigger bone metastases, in the orthotopic xenograft model. To this end, the cells were injected into the prostates of male SCID/Bg mice and tumor development and progression was followed by magnetic resonance imaging (MRI) and histopathology. MRI indicated local invasion of the primary tumor, which later resulted in the formation of multiple secondary lesions along the lower spine. However, histopathological analysis revealed that these lesions were initiated in the soft tissues surrounding the vertebral column, while the subsequent invasion of the vertebra was the secondary event. The staining for neuronal markers, neurofilament (NF), tyrosine hydroxylase (TH) and neuropeptide Y (NPY), revealed that PCa cells created multicellular clusters spreading longitudinally along the small nerve fibers, particularly in the paraspinal muscle compartment. The staining for the endothelial cell marker, CD31, detected small vessels present within PCa clusters. However, no evident encapsulation of the PCa cells within blood vessels consistent with the retrograde venous spread was observed. Altogether, these results suggest PNI as the main route of the initial local dissemination of the PCa cells toward the bone, which then triggers bone invasion and subsequent hematogenous spread to distant bones. Further mechanistic studies are required to confirm this hypothesis. Citation Format: Dawid Sigorski, Susana Galli, Sung Hyeok Hong, Ewa Iżycka-Świeszewska, Joanna B. Kitlinska. Perineural invasion and bone metastases in prostate cancer - is there a link [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1326.