Multicellular Systems Research Articles

Abstract PO-069: Modeling the tumor microenvironment using tissue engineering technologies

Abstract Tissue engineering technologies provide controllable and reproducible approaches to reconstruct the extracellular and cellular elements of pancreatic cancer. In a reductionist approach they allow the modelling of the complex tumor microenvironment (TME) and the study of disease biology and anti-cancer treatments. Our objective is that an engineered TME model, that mimics the tissue and matrix composition, architecture and cell types, will behave like a real tumor and is suitable for preclinical drug testing. Using biomimetic materials, we recreated the desmoplastic tissue characteristics of the pancreatic TME. Our natural and synthetic biomaterials were tailored to achieve the mechanical properties that resembled the stiffness and viscoelasticity of patient-derived tissues, providing a supportive cell-matrix interface for 3D cell culture conditions. Pancreatic cancer cells grown embedded in the matrix scaffolds formed tumor spheroids. Cell-based assays and microscopic analysis indicated a high cell viability and proliferation of the tumor spheroids as well as the expression of cancer-associated markers. Incorporation of cancer-associated fibroblasts and myeloid cells led to a multicellular 3D systems and matrix stiffening due to the secretion of extracellular matrix proteins. Transcriptomic analysis of the 3D cell cultures identified differentially regulated pathways related to cell proliferation, mechano-transduction and the secretion of pro-inflammatory cytokines, indicative of a malignant behavior. Treatment with mechano-modulating inhibitors and anti-cancer compounds increased the efficacy of chemotherapeutics, thereby reducing matrix stiffness and the release of cytokines. Our engineered TME model provides an easily translatable technology to ease the burden of pancreatic cancer, allowing us to characterize combination treatments that slow down or reduce tumor growth. Citation Format: Rodrigo Curvello, Verena Kast, Daniela Loessner. Modeling the tumor microenvironment using tissue engineering technologies [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-069.

Evidence-Based Network Modelling to Simulate Nucleus Pulposus Multicellular Activity in Different Nutritional and Pro-Inflammatory Environments.

Initiation of intervertebral disc degeneration is thought to be biologically driven. This reflects a process, where biochemical and mechanical stimuli affect cell activity (CA) that compromise the tissue strength over time. Experimental research enhanced our understanding about the effect of such stimuli on different CA, such as protein synthesis or mRNA expression. However, it is still unclear how cells respond to their native environment that consists of a “cocktail” of different stimuli that might locally vary. This work presents an interdisciplinary approach of experimental and in silico research to approximate Nucleus Pulposus CA within multifactorial biochemical environments. Thereby, the biochemical key stimuli glucose, pH, and the proinflammatory cytokines TNF-α and IL1β were considered that were experimentally shown to critically affect CA. To this end, a Nucleus Pulposus multicellular system was modelled. It integrated experimental findings from in vitro studies of human or bovine Nucleus Pulposus cells, to relate the individual effects of targeted stimuli to alterations in CA. Unknown stimulus-CA relationships were obtained through own experimental 3D cultures of bovine Nucleus Pulposus cells in alginate beads. Translation of experimental findings into suitable parameters for network modelling approaches was achieved thanks to a new numerical approach to estimate the individual sensitivity of a CA to each stimulus type. Hence, the effect of each stimulus type on a specific CA was assessed and integrated to approximate a multifactorial stimulus environment. Tackled CA were the mRNA expressions of Aggrecan, Collagen types I & II, MMP3, and ADAMTS4. CA was assessed for four different proinflammatory cell states; non-inflamed and inflamed for IL1β, TNF-α or both IL1β&TNF-α. Inflamed cell clusters were eventually predicted in a multicellular 3D agent-based model. Experimental results showed that glucose had no significant impact on proinflammatory cytokine or ADAMTS4 mRNA expression, whereas TNF-α caused a significant catabolic shift in most explored CA. In silico results showed that the presented methodology to estimate the sensitivity of a CA to a stimulus type importantly improved qualitative model predictions. However, more stimuli and/or further experimental knowledge need to be integrated, especially regarding predictions about the possible progression of inflammatory environments under adverse nutritional conditions. Tackling the multicellular level is a new and promising approach to estimate manifold responses of intervertebral disc cells. Such a top-down high-level network modelling approach allows to obtain information about relevant stimulus environments for a specific CA and could be shown to be suitable to tackle complex biological systems, including different proinflammatory cell states. The development of this methodology required a close interaction with experimental research. Thereby, specific experimental needs were derived from systematic in silico approaches and obtained results were directly used to enhance model predictions, which reflects a novelty in this research field. Eventually, the presented methodology provides modelling solutions suitable for multiscale approaches to contribute to a better understanding about dynamics over multiple spatial scales. Future work should focus on an amplification of the stimulus environment by integrating more key relevant stimuli, such as mechanical loading parameters, in order to better approximate native physiological environments.

Mapping Tumor Spheroid Mechanics in Dependence of 3D Microenvironment Stiffness and Degradability by Brillouin Microscopy.

Simple SummaryLittle is known about how cancer cells adapt their mechanical properties in complex 3D microenvironments. Here we generated different types of tumor spheroids within compliant or stiff hydrogels. We then quantitatively mapped the mechanical properties of these spheroids in situ using Brillouin microscopy. Maps acquired for tumor spheroids grown within stiffer hydrogels showed elevated Brillouin shifts, hence spheroids became “stiffer” compared to the ones cultured within compliant gels. The spheroid’s mechanical properties were modulated by various microenvironment properties including matrix stiffness and degradability and the resultant compressive stress but also depending on whether single cells or cell aggregates were analyzed. Moreover, spheroids generated from a panel of invasive breast, prostate and pancreatic cancer cell lines within degradable stiff hydrogels became stiffer and at the same time, less invasive compared to those in compliant hydrogels. Taken together, our findings contribute to a better understanding of the interplay between cancer cells and their microenvironment, which is relevant to better understand cancer progression.Altered biophysical properties of cancer cells and of their microenvironment contribute to cancer progression. While the relationship between microenvironmental stiffness and cancer cell mechanical properties and responses has been previously studied using two-dimensional (2D) systems, much less is known about it in a physiologically more relevant 3D context and in particular for multicellular systems. To investigate the influence of microenvironment stiffness on tumor spheroid mechanics, we first generated MCF-7 tumor spheroids within matrix metalloproteinase (MMP)-degradable 3D polyethylene glycol (PEG)-heparin hydrogels, where spheroids showed reduced growth in stiffer hydrogels. We then quantitatively mapped the mechanical properties of tumor spheroids in situ using Brillouin microscopy. Maps acquired for tumor spheroids grown within stiff hydrogels showed elevated Brillouin frequency shifts (hence increased longitudinal elastic moduli) with increasing hydrogel stiffness. Maps furthermore revealed spatial variations of the mechanical properties across the spheroids’ cross-sections. When hydrogel degradability was blocked, comparable Brillouin frequency shifts of the MCF-7 spheroids were found in both compliant and stiff hydrogels, along with similar levels of growth-induced compressive stress. Under low compressive stress, single cells or free multicellular aggregates showed consistently lower Brillouin frequency shifts compared to spheroids growing within hydrogels. Thus, the spheroids’ mechanical properties were modulated by matrix stiffness and degradability as well as multicellularity, and also to the associated level of compressive stress felt by tumor spheroids. Spheroids generated from a panel of invasive breast, prostate and pancreatic cancer cell lines within degradable stiff hydrogels, showed higher Brillouin frequency shifts and less cell invasion compared to those in compliant hydrogels. Taken together, our findings contribute to a better understanding of the interplay between cancer cells and microenvironment mechanics and degradability, which is relevant to better understand cancer progression.

Configurational fingerprints of multicellular living systems

Cells cooperate as groups to achieve structure and function at the tissue level, during which specific material characteristics emerge. Analogous to phase transitions in classical physics, transformations in the material characteristics of multicellular assemblies are essential for a variety of vital processes including morphogenesis, wound healing, and cancer. In this work, we develop configurational fingerprints of particulate and multicellular assemblies and extract volumetric and shear order parameters based on this fingerprint to quantify the system disorder. Theoretically, these two parameters form a complete and unique pair of signatures for the structural disorder of a multicellular system. The evolution of these two order parameters offers a robust and experimentally accessible way to map the phase transitions in expanding cell monolayers and during embryogenesis and invasion of epithelial spheroids.

Blood-Brain Barrier Dysfunction in CNS Disorders and Putative Therapeutic Targets: An Overview.

The blood-brain barrier (BBB) is a fundamental component of the central nervous system (CNS). Its functional and structural integrity is vital to maintain the homeostasis of the brain microenvironment by controlling the passage of substances and regulating the trafficking of immune cells between the blood and the brain. The BBB is primarily composed of highly specialized microvascular endothelial cells. These cells’ special features and physiological properties are acquired and maintained through the concerted effort of hemodynamic and cellular cues from the surrounding environment. This complex multicellular system, comprising endothelial cells, astrocytes, pericytes, and neurons, is known as the neurovascular unit (NVU). The BBB strictly controls the transport of nutrients and metabolites into brain parenchyma through a tightly regulated transport system while limiting the access of potentially harmful substances via efflux transcytosis and metabolic mechanisms. Not surprisingly, a disruption of the BBB has been associated with the onset and/or progression of major neurological disorders. Although the association between disease and BBB disruption is clear, its nature is not always evident, specifically with regard to whether an impaired BBB function results from the pathological condition or whether the BBB damage is the primary pathogenic factor prodromal to the onset of the disease. In either case, repairing the barrier could be a viable option for treating and/or reducing the effects of CNS disorders. In this review, we describe the fundamental structure and function of the BBB in both healthy and altered/diseased conditions. Additionally, we provide an overview of the potential therapeutic targets that could be leveraged to restore the integrity of the BBB concomitant to the treatment of these brain disorders.

The Use of Artificial Neural Networks to Forecast the Behavior of Agent-Based Models of Pathophysiology: An Example Utilizing an Agent-Based Model of Sepsis.

Introduction: Disease states are being characterized at finer and finer levels of resolution via biomarker or gene expression profiles, while at the same time. Machine learning (ML) is increasingly used to analyze and potentially classify or predict the behavior of biological systems based on such characterization. As ML applications are extremely data-intensive, given the relative sparsity of biomedical data sets ML training of artificial neural networks (ANNs) often require the use of synthetic training data. Agent-based models (ABMs) that incorporate known biological mechanisms and their associated stochastic properties are a potential means of generating synthetic data. Herein we present an example of ML used to train an artificial neural network (ANN) as a surrogate system used to predict the time evolution of an ABM focusing on the clinical condition of sepsis.Methods: The disease trajectories for clinical sepsis, in terms of temporal cytokine and phenotypic dynamics, can be interpreted as a random dynamical system. The Innate Immune Response Agent-based Model (IIRABM) is a well-established model that utilizes known cellular and molecular rules to simulate disease trajectories corresponding to clinical sepsis. We have utilized two distinct neural network architectures, Long Short-Term Memory and Multi-Layer Perceptron, to take a time sequence of five measurements of eleven IIRABM simulated serum cytokine concentrations as input and to return both the future cytokine trajectories as well as an aggregate metric representing the patient’s state of health.Results: The ANNs predicted model trajectories with the expected amount of error, due to stochasticity in the simulation, and recognizing that the mapping from a specific cytokine profile to a state-of-health is not unique. The Multi-Layer Perceptron neural network, generated predictions with a more accurate forecasted trajectory cone.Discussion: This work serves as a proof-of-concept for the use of ANNs to predict disease progression in sepsis as represented by an ABM. The findings demonstrate that multicellular systems with intrinsic stochasticity can be approximated with an ANN, but that forecasting a specific trajectory of the system requires sequential updating of the system state to provide a rolling forecast horizon.

Bioengineering methods for organoid systems.

Organoids have been widely used in fundamental, biomimetic, and therapeutic studies. These multicellular systems form via cell-autonomous self-organization where a cohort of stem cells undergoes in vivo-like proliferation, differentiation, and morphogenesis. They also recapitulate a series of physiological cell organization, complexity and functions that are untouchable by conventional bio-model systems using immortal cell lines. However, the development of organoids is often not easily controlled and their shape and size are yet fully physiological. Recent research has demonstrated that multiple bioengineering tools could be harnessed to control important internal and external cues that dictate stem cell behavior and stem-cell based organoid development. In this review, we introduce the current development of organoid systems and their potentials, as well as their limitations that impede their further utility in research and clinical fields. In comparison to conventional autonomous organoid system, we then review bioengineering approaches that offer improved control over organoid growth and development. We focus on the genetic editing tools that allow the program of build-in responses and phenotypes for organoid systems with enhanced physiological relevance. We also highlight the advances in bioengineering methods to modify cellular external milieus to generate desirable cell composition, 3D micro-architectures, and complex microfluidic systems. We conclude that the emerging biomimetic methods that employ multidisciplinary approaches could prevail in the future development of organoid systems.

Potassium transporter TRH1/KUP4 contributes to distinct auxin-mediated root system architecture responses.

In plants, auxin transport and development are tightly coupled, just as hormone and growth responses are intimately linked in multicellular systems. Here we provide insights into uncoupling this tight control by specifically targeting the expression of TINY ROOT HAIR 1 (TRH1), a member of plant high-affinity potassium (K+)/K+ uptake/K+ transporter (HAK/KUP/KT) transporters that facilitate K+ uptake by co-transporting protons, in Arabidopsis root cell files. Use of this system pinpointed specific root developmental responses to acropetal versus basipetal auxin transport. Loss of TRH1 function shows TRHs and defective root gravitropism, associated with auxin imbalance in the root apex. Cell file-specific expression of TRH1 in the central cylinder rescued trh1 root agravitropism, whereas positional TRH1 expression in peripheral cell layers, including epidermis and cortex, restored trh1 defects. Applying a system-level approach, the role of RAP2.11 and ROOT HAIR DEFECTIVE-LIKE 5 transcription factors (TFs) in root hair development was verified. Furthermore, ERF53 and WRKY51 TFs were overrepresented upon restoration of root gravitropism supporting involvement in gravitropic control. Auxin has a central role in shaping root system architecture by regulating multiple developmental processes. We reveal that TRH1 jointly modulates intracellular ionic gradients and cell-to-cell polar auxin transport to drive root epidermal cell differentiation and gravitropic response. Our results indicate the developmental importance of HAK/KUP/KT proton-coupled K+ transporters.

The Role of Drosophila CtIP in Homology-Directed Repair of DNA Double-Strand Breaks.

DNA double-strand breaks (DSBs) are a particularly genotoxic type of DNA damage that can result in chromosomal aberrations. Thus, proper repair of DSBs is essential to maintaining genome integrity. DSBs can be repaired by non-homologous end joining (NHEJ), where ends are processed before joining through ligation. Alternatively, DSBs can be repaired through homology-directed repair, either by homologous recombination (HR) or single-strand annealing (SSA). Both types of homology-directed repair are initiated by DNA end resection. In cultured human cells, the protein CtIP has been shown to play a role in DNA end resection through its interactions with CDK, BRCA1, DNA2, and the MRN complex. To elucidate the role of CtIP in a multicellular context, CRISPR/Cas9 genome editing was used to create a DmCtIPΔ allele in Drosophila melanogaster. Using the DSB repair reporter assay direct repeat of white (DR-white), a two-fold decrease in HR in DmCtIPΔ/Δ mutants was observed when compared to heterozygous controls. However, analysis of HR gene conversion tracts (GCTs) suggests DmCtIP plays a minimal role in determining GCT length. To assess the function of DmCtIP on both short (~550 bp) and long (~3.6 kb) end resection, modified homology-directed SSA repair assays were implemented, resulting in a two-fold decrease in SSA repair in both short and extensive end resection requirements in the DmCtIPΔ/Δ mutants compared to heterozygote controls. Through these analyses, we affirmed the importance of end resection on DSB repair pathway choice in multicellular systems, described the function of DmCtIP in short and extensive DNA end resection, and determined the impact of end resection on GCT length during HR.

Generation of multicellular spatiotemporal models of population dynamics from ordinary differential equations, with applications in viral infection

BackgroundThe biophysics of an organism span multiple scales from subcellular to organismal and include processes characterized by spatial properties, such as the diffusion of molecules, cell migration, and flow of intravenous fluids. Mathematical biology seeks to explain biophysical processes in mathematical terms at, and across, all relevant spatial and temporal scales, through the generation of representative models. While non-spatial, ordinary differential equation (ODE) models are often used and readily calibrated to experimental data, they do not explicitly represent the spatial and stochastic features of a biological system, limiting their insights and applications. However, spatial models describing biological systems with spatial information are mathematically complex and computationally expensive, which limits the ability to calibrate and deploy them and highlights the need for simpler methods able to model the spatial features of biological systems.ResultsIn this work, we develop a formal method for deriving cell-based, spatial, multicellular models from ODE models of population dynamics in biological systems, and vice versa. We provide examples of generating spatiotemporal, multicellular models from ODE models of viral infection and immune response. In these models, the determinants of agreement of spatial and non-spatial models are the degree of spatial heterogeneity in viral production and rates of extracellular viral diffusion and decay. We show how ODE model parameters can implicitly represent spatial parameters, and cell-based spatial models can generate uncertain predictions through sensitivity to stochastic cellular events, which is not a feature of ODE models. Using our method, we can test ODE models in a multicellular, spatial context and translate information to and from non-spatial and spatial models, which help to employ spatiotemporal multicellular models using calibrated ODE model parameters. We additionally investigate objects and processes implicitly represented by ODE model terms and parameters and improve the reproducibility of spatial, stochastic models.ConclusionWe developed and demonstrate a method for generating spatiotemporal, multicellular models from non-spatial population dynamics models of multicellular systems. We envision employing our method to generate new ODE model terms from spatiotemporal and multicellular models, recast popular ODE models on a cellular basis, and generate better models for critical applications where spatial and stochastic features affect outcomes.

Morphology changes induced by intercellular gap junction blocking: A reaction-diffusion mechanism

Complex anatomical form is regulated in part by endogenous physiological communication between cells; however, the dynamics by which gap junctional (GJ) states across tissues regulate morphology are still poorly understood. We employed a biophysical modeling approach combining different signaling molecules (morphogens) to qualitatively describe the anteroposterior and lateral morphology changes in model multicellular systems due to intercellular GJ blockade. The model is based on two assumptions for blocking-induced patterning: (i) the local concentrations of two small antagonistic morphogens diffusing through the GJs along the axial direction, together with that of an independent, uncoupled morphogen concentration along an orthogonal direction, constitute the instructive patterns that modulate the morphological outcomes, and (ii) the addition of an external agent partially blocks the intercellular GJs between neighboring cells and modifies thus the establishment of these patterns. As an illustrative example, we study how the different connectivity and morphogen patterns obtained in presence of a GJ blocker can give rise to novel head morphologies in regenerating planaria. We note that the ability of GJs to regulate the permeability of morphogens post-translationally suggests a mechanism by which different anatomies can be produced from the same genome without the modification of gene-regulatory networks. Conceptually, our model biosystem constitutes a reaction-diffusion information processing mechanism that allows reprogramming of biological morphologies through the external manipulation of the intercellular GJs and the resulting changes in instructive biochemical signals.

Exploring rare cellular activity in more than one million cells by a transscale scope

In many phenomena of biological systems, not a majority, but a minority of cells act on the entire multicellular system causing drastic changes in the system properties. To understand the mechanisms underlying such phenomena, it is essential to observe the spatiotemporal dynamics of a huge population of cells at sub-cellular resolution, which is difficult with conventional tools such as microscopy and flow cytometry. Here, we describe an imaging system named AMATERAS that enables optical imaging with an over-one-centimeter field-of-view and a-few-micrometer spatial resolution. This trans-scale-scope has a simple configuration, composed of a low-power lens for machine vision and a hundred-megapixel image sensor. We demonstrated its high cell-throughput, capable of simultaneously observing more than one million cells. We applied it to dynamic imaging of calcium ions in HeLa cells and cyclic-adenosine-monophosphate in Dictyostelium discoideum, and successfully detected less than 0.01% of rare cells and observed multicellular events induced by these cells.

A novel multi-functionalized multicellular nanodelivery system for non-small cell lung cancer photochemotherapy

BackgroundA red blood cell membrane (RBCm)-derived drug delivery system allows prolonged circulation of an antitumor treatment and overcomes the issue of accelerated blood clearance induced by PEGylation. However, RBCm-derived drug delivery systems are limited by low drug-loading capacities and the lack of tumor-targeting ability. Thus, new designs of RBCm-based delivery systems are needed.ResultsHerein, we designed hyaluronic acid (HA)–hybridized RBCm (HA&RBCm)-coated lipid multichambered nanoparticles (HA&RBCm-LCNPs) to remedy the limitations of traditional RBCm drug delivery systems. The inner core co-assembled with phospholipid-regulated glycerol dioleate/water system in HA&RBCm-LCNPs met the required level of blood compatibility for intravenous administration. These newly designed nanocarriers had a honeycomb structure with abundant spaces that efficiently encapsulated paclitaxel and IR780 for photochemotherapy. The HA&RBCm coating allowed the nanocarriers to overcome the reticuloendothelial system barrier and enhanced the nanocarriers specificity to A549 cells with high levels of CD44. These properties enhanced the combinatorial antitumor effects of paclitaxel and IR780 associated with microtubule destruction and the mitochondrial apoptotic pathway.ConclusionsThe multifunctional HA&RBCm-LCNPs we designed expanded the functionality of RBCm and resulted in a vehicle for safe and efficient antitumor treatment.Graphical abstract

A self-exciting point process to study multicellular spatial signaling patterns

Multicellular organisms rely on spatial signaling among cells to drive their organization, development, and response to stimuli. Several models have been proposed to capture the behavior of spatial signaling in multicellular systems, but existing approaches fail to capture both the autonomous behavior of single cells and the interactions of a cell with its neighbors simultaneously. We propose a spatiotemporal model of dynamic cell signaling based on Hawkes processes-self-exciting point processes-that model the signaling processes within a cell and spatial couplings between cells. With this cellular point process (CPP), we capture both the single-cell pathway activation rate and the magnitude and duration of signaling between cells relative to their spatial location. Furthermore, our model captures tissues composed of heterogeneous cell types with different bursting rates and signaling behaviors across multiple signaling proteins. We apply our model to epithelial cell systems that exhibit a range of autonomous and spatial signaling behaviors basally and under pharmacological exposure. Our model identifies known drug-induced signaling deficits, characterizes signaling changes across a wound front, and generalizes to multichannel observations.

Advances on colorectal cancer 3D models: The needed translational technology for nanomedicine screening.

Colorectal cancer (CRC) is a heterogeneous and molecularly complex disease, associated with high mortality worldwide, exposing the urgent need for novel therapeutic approaches. Their development and translation to the clinic have been hampered, partially due to the absence of reliable cellular models that resemble key features of the human disease. While traditional 2D models are not able to provide consistent and predictive responses about the in vivo efficiency of the formulation, animal models frequently fail to recapitulate cancer progression and to reproduce adverse effects. On its turn, multicellular 3D systems, by mimicking key genetic, physical and mechanical cues of the tumor microenvironment, constitute a promising tool in cancer research. In addition, they constitute more physiological and relevant environment for anticancer drugs screening and for predicting patient's response towards personalized approaches, bridging the gap between simplified 2D models and unrepresentative animal models. In this review, we provide an overview of CRC 3D models for translational research, with focus on their potential for nanomedicines screening.

Quantitative developmental biology in vitro using micropatterning.

ABSTRACTMicropatterning encompasses a set of methods aimed at precisely controlling the spatial distribution of molecules onto the surface of materials. Biologists have borrowed the idea and adapted these methods, originally developed for electronics, to impose physical constraints on biological systems with the aim of addressing fundamental questions across biological scales from molecules to multicellular systems. Here, I approach this topic from a developmental biologist's perspective focusing specifically on how and why micropatterning has gained in popularity within the developmental biology community in recent years. Overall, this Primer provides a concise overview of how micropatterns are used to study developmental processes and emphasises how micropatterns are a useful addition to the developmental biologist’s toolbox.

Integrated analysis of glycan and RNA in single cells

SummarySingle-cell sequencing has emerged as an indispensable technology to dissect cellular heterogeneity but never been applied to the simultaneous analysis of glycan and RNA. Using oligonucleotide-labeled lectins, we first established lectin-based glycan profiling of single cells by sequencing (scGlycan-seq). We then combined the scGlycan-seq with single-cell transcriptome profiling for joint analysis of glycan and RNA in single cells (scGR-seq). Using scGR-seq, we analyzed the two modalities in human induced pluripotent stem cells (hiPSCs) before and after differentiation into neural progenitor cells at the single-cell resolution. The combination of RNA and glycan separated the two cell types clearer than either one of them. Furthermore, integrative analysis of glycan and RNA modalities in single cells found known and unknown lectins that were specific to hiPSCs and coordinated with neural differentiation. Taken together, we demonstrate that scGR-seq can reveal the cellular heterogeneity and biological roles of glycans across multicellular systems.

Tunneling nanotubes, TNT, communicate glioblastoma with surrounding non-tumor astrocytes to adapt them to hypoxic and metabolic tumor conditions

Cell-to-cell communication is essential for the development and proper function of multicellular systems. We and others demonstrated that tunneling nanotubes (TNT) proliferate in several pathological conditions such as HIV, cancer, and neurodegenerative diseases. However, the nature, function, and contribution of TNT to cancer pathogenesis are poorly understood. Our analyses demonstrate that TNT structures are induced between glioblastoma (GBM) cells and surrounding non-tumor astrocytes to transfer tumor-derived mitochondria. The mitochondrial transfer mediated by TNT resulted in the adaptation of non-tumor astrocytes to tumor-like metabolism and hypoxia conditions. In conclusion, TNT are an efficient cell-to-cell communication system used by cancer cells to adapt the microenvironment to the invasive nature of the tumor.

Mechanical properties of cell sheets and spheroids: the link between single cells and complex tissues.

Cell aggregates, including sheets and spheroids, represent a simple yet powerful model system to study both biochemical and biophysical intercellular interactions. However, it is becoming evident that, although the mechanical properties and behavior of multicellular structures share some similarities with individual cells, yet distinct differences are observed in some principal aspects. The description of mechanical phenomena at the level of multicellular model systems is a necessary step for understanding tissue mechanics and its fundamental principles in health and disease. Both cell sheets and spheroids are used in tissue engineering, and the modulation of mechanical properties of cell constructs is a promising tool for regenerative medicine. Here, we review the data on mechanical characterization of cell sheets and spheroids, focusing both on advances in the measurement techniques and current understanding of the subject. The reviewed material suggest that interplay between the ECM, intercellular junctions, and cellular contractility determines the behavior and mechanical properties of the cell aggregates.

Abstract 266: Differential collective cell migratory behaviors modulated by phospholipid nanoparticles

Abstract Phospholipid nanoparticles have been actively explored for biological and biomedical applications. These nanoparticles display excellent cargo encapsulation efficiency, high water dispersibility, and outstanding biocompatibility, rendering them highly attractive for cancer nanomedicine applications. While the promising utilizations of phospholipid nanoparticles for cancer theranostic have been widely documented, the cellular biophysical responses elicited by phospholipid nanoparticles have been less investigated. Notably, the effects of phospholipid nanoparticles on collective cancer cell behaviors have not been well delineated. In fact, most of the studies examining nanoparticle-cancer interactions have focused largely on the nanoparticle toxicity on individual cells, but paid little attention to other nanoparticle effects on multicellular systems and their collective behaviors. A better appreciation of the effects of nanoparticles on multicellular system dynamics is necessary as collective cancer cell behaviors are central to the regulation of various processes, particularly cancer invasion and metastasis. Motivated by this, we sought to interrogate the effects of 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-poly(ethylene glycol) (DSPE-PEG) nanoparticles, which are some of the most commonly used phospholipid nanoparticles for cancer nanomedicine, on the collective behaviors of healthy and cancerous breast epithelial cell monolayers. DSPE-PEG nanoparticles with two sizes (i.e., 20 and 60 nm) and three surface functional groups (i.e., COOH, OCH3, and NH2) as well as three types of breast epithelial cell sheets with varying malignancy potential (i.e., MCF-10A, MCF-7, and MDA-MB-231) were used in this work. Utilizing a series of microscopy and molecular biology techniques and quantitative image analysis, we comprehensively examined the collective cell migratory dynamics in the absence and presence of DSPE-PEG nanoparticles. We noted that DSPE-PEG nanoparticles retarded the migration of the healthy MCF-10A epithelial cell sheets. In contrast, the cancerous MCF-7 and MDA-MB-231 cell sheets experienced accelerated collective migration in the presence of the nanoparticles. Moreover, these nanoparticles altered the migration directionality of the cancerous breast cell sheets. We ascribed the differential nanoparticle-modulated collective cell migratory behaviors to changes in the stiffness of the cell nuclei, cytoplasm, and cell-cell junctions, as well as the reorganization of the cellular actin filament networks after the nanoparticle-cell interactions. We anticipate that this study will provide a deeper insight into the nanomaterial-cancer interactions and aid the formulation of phospholipid nanoparticles for more effective and safer cancer theranostic and nanomedicine applications. Citation Format: Kenry, Bin Liu. Differential collective cell migratory behaviors modulated by phospholipid nanoparticles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 266.