Multiscale modeling of solid stress and tumor cell invasion in response to dynamic mechanical microenvironment

Systematic simulation of tumor cell invasion and migration in response to time-varying rotating magnetic field

Cancer invasion and migration play a pivotal role in tumor malignancy, which is a major cause of most cancer deaths. Rotating magnetic field (RMF), one of the typical dynamic magnetic fields, can exert substantial mechanical influence on cells. However, studying the effects of RMF on cell is challenging due to its complex parameters, such as variation of magnetic field intensity and direction. Here, we developed a systematic simulation method to explore the influence of RMF on tumor invasion and migration, including a finite element method (FEM) model and a cell-based hybrid numerical model. Coupling with the data of magnetic field from FEM, the cell-based hybrid numerical model was established to simulate the tumor cell invasion and migration. This model employed partial differential equations (PDEs) and finite difference method to depict cellular activities and solve these equations in a discrete system. PDEs were used to depict cell activities, and finite difference method was used to solve the equations in discrete system. As a result, this study provides valuable insights into the potential applications of RMF in tumor treatment, and a series of in vitro experiments were performed to verify the simulation results, demonstrating the model's reliability and its capacity to predict experimental outcomes and identify pertinent factors. Furthermore, these findings shed new light on the mechanical and chemical interplay between cells and the ECM, offering new insights and providing a novel foundation for both experimental and theoretical advancements in tumor treatment by using RMF.

Biomechanical Aspects in Bone Tumor Engineering

In the past decades, anticancer drug development brought the field of tumor engineering to a new level by the need of robust test systems. Simulating tumor microenvironment in vitro remains a challenge, and osteosarcoma-the most common primary bone cancer-is no exception. The growing evidence points to the inevitable connection between biomechanical stimuli and tumor chemosensitivity and aggressiveness, thus making this component of the microenvironment a mandatory requirement to the developed models. In this review, we addressed the question: is the "in vivo - in vitro" gap in osteosarcoma engineering bridged from the perspective of biomechanical stimuli? The most notable biomechanical cues in the tumor cell microenvironment are observed and compared in the contexts of in vivo conditions and engineered three-dimensional in vitro models. Impact statement The importance of biomechanical stimuli in three-dimensional in vitro models for drug testing is becoming more pronounced nowadays. This review might assist in understanding the key players of the biophysical environment of primary bone cancer and the current state of bone tumor engineering from this perspective.

Mechano-induced homotypic patterned domain formation by monocytes

Matrix stiffness and corresponding mechano-signaling play indispensable roles in cellular phenotypes and functions. How tissue stiffness influences the behavior of monocytes, a major circulating leukocyte of the innate system, and how it may promote the emergence of collective cell behavior is less understood. Here, using tunable collagen-coated hydrogels of physiological stiffness, we show that human primary monocytes undergo a dynamic local phase separation to form highly regular, reversible, multicellular, multi-layered domains on soft matrix. Local activation of the β2 integrin initiates inter-cellular adhesion, while global soluble inhibitory factors maintain the steady state domain pattern over days. Patterned domain formation generated by monocytes is unique among other key immune cells, including macrophages, B cells, T cells, and NK cells. While inhibiting their phagocytic capability, domain formation promotes monocytes' survival. We develop a computational model based on the Cahn-Hilliard equation of phase separation, combined with a Turing mechanism of local activation and global inhibition suggested by our experiments, and provides experimentally validated predictions of the role of seeding density and both chemotactic and random cell migration on domain pattern formation. This work reveals that, unlike active matters, cells can generate complex cell phases by exploiting their mechanosensing abilities and combined short-range interactions and long-range signals to enhance their survival.

Mechano-induced homotypic patterned domain formation by monocytes

Matrix stiffness and corresponding mechano-signaling play indispensable roles in cellular phenotypes and functions. How tissue stiffness influences the behavior of monocytes, a major circulating leukocyte of the innate system, and how it may promote the emergence of collective cell behavior is less understood. Here, using tunable collagen-coated hydrogels of physiological stiffness, we show that human primary monocytes undergo a dynamic local phase separation to form highly patterned multicellular multi-layered domains on soft matrix. Local activation of the β2 integrin initiates inter-cellular adhesion, while global soluble inhibitory factors maintain the steady-state domain pattern over days. Patterned domain formation generated by monocytes is unique among other key immune cells, including macrophages, B cells, T cells, and NK cells. While inhibiting their phagocytic capability, domain formation promotes monocytes' survival. We develop a computational model based on the Cahn-Hilliard equation, which includes combined local activation and global inhibition mechanisms of intercellular adhesion suggested by our experiments, and provides experimentally validated predictions of the role of seeding density and both chemotactic and random cell migration on pattern formation.

Modelling the Tumour Microenvironment, but What Exactly Do We Mean by "Model"?

The Oxford English Dictionary includes 17 definitions for the word "model" as a noun and another 11 as a verb. Therefore, context is necessary to understand the meaning of the word model. For instance, "model railways" refer to replicas of railways and trains at a smaller scale and a "model student" refers to an exemplary individual. In some cases, a specific context, like cancer research, may not be sufficient to provide one specific meaning for model. Even if the context is narrowed, specifically, to research related to the tumour microenvironment, "model" can be understood in a wide variety of ways, from an animal model to a mathematical expression. This paper presents a review of different "models" of the tumour microenvironment, as grouped by different definitions of the word into four categories: model organisms, in vitro models, mathematical models and computational models. Then, the frequencies of different meanings of the word "model" related to the tumour microenvironment are measured from numbers of entries in the MEDLINE database of the United States National Library of Medicine at the National Institutes of Health. The frequencies of the main components of the microenvironment and the organ-related cancers modelled are also assessed quantitatively with specific keywords. Whilst animal models, particularly xenografts and mouse models, are the most commonly used "models", the number of these entries has been slowly decreasing. Mathematical models, as well as prognostic and risk models, follow in frequency, and these have been growing in use.

Gastrointestinal pan-cancer landscape of tumor matrix heterogeneity identifies biologically distinct matrix stiffness subtypes predicting prognosis and chemotherapy efficacy

Gastrointestinal (GI) cancers are a heterogeneous group of primary solid tumors, arising in GI tract from the esophagus to rectum. Matrix stiffness (MS) is a critical physical factor for cancer progression; however, its importance in tumor progression remains to be comprehensively recognized. Herein, we conducted a comprehensive pan-cancer analysis of MS subtypes across seven GI-cancer types. Using unsupervised clustering based on literature-derived MS-specific pathway signatures, the GI-tumor samples were divided into three MS subtypes, termed as the Soft, Mixed and Stiff. Then, distinct prognoses, biological features, tumor microenvironments and mutation landscapes among three MS subtypes were revealed. The Stiff tumor subtype was associated with the poorest prognosis, the most malignant biological behaviors, and the immunosuppressive tumor stromal microenvironment. Furthermore, multiple machine learning algorithms were used to develop an 11-gene MS-signature to identify the MS subtypes of GI-caner and predict chemotherapy sensitivity, which were further validated in two external GI-cancer cohorts. This novel MS-based classification on GI-cancers could enhance our understanding of the important role of MS in tumor progression, and may have implications for the optimization of individualized cancer management.

Biological role of matrix stiffness in tumor growth and treatment

In recent years, the biological role of changes in physical factors in carcinogenesis and progression has attracted increasing attention. Matrix stiffness, also known as ECM stress, is a critical physical factor of tumor microenvironment and remains alternating during carcinogenesis as a result of ECM remodeling through activation of cancer-associated fibroblasts and extracellular collagen accumulation, crosslinking and fibrosis. Different content and density of extracellular collagen in ECM endows matrix with varying stiffness. Physical signals induced by matrix stiffness are transmitted to tumor cells primarily by the integrins receptor family and trigger a series of mechanotransduction that result in changes in tumor cell morphology, proliferative capacity, and invasive ability. Importantly, accumulating evidence revealed that changes in matrix stiffness in tumor tissues greatly control the sensitivity of tumor cells in response to chemotherapy, radiotherapy, and immunotherapy through integrin signaling, YAP signaling, and related signaling pathways. Here, the present review analyzes the current research advances on matrix stiffness and tumor cell behavior with a view to contributing to tumor cell growth and treatment, with the hope of improving the understanding of the biological role of matrix stiffness in tumors.

Multiscale modeling in disease

Multiscale computational modeling aims to connect the complex networks of effects at different length and/or time scales. For example, these networks often include intracellular molecular signaling, crosstalk, and other interactions between neighboring cell populations, and higher levels of emergent phenomena across different regions of tissues and among collections of tissues or organs interacting with each other in the whole body. Recent applications of multiscale modeling across intracellular, cellular, and/or tissue levels are highlighted here. These models incorporated the roles of biochemical and biomechanical modulation in processes that are implicated in the mechanisms of several diseases including fibrosis, joint and bone diseases, respiratory infectious diseases, and cancers.