Regulation of migration of chemotactic tumor cells by the spatial distribution of collagen fiber orientation

Mechanoimmunology in the solid tumor microenvironment

The tumor microenvironment (TME) is a complex and dynamic ecosystem that adjoins the cancer cells within solid tumors and comprises distinct components such as extracellular matrix, stromal and immune cells, blood vessels, and an abundance of signaling molecules. In recent years, the mechanical properties of the TME have emerged as critical determinants of tumor progression and therapeutic response. Aberrant mechanical cues, including altered tissue architecture and stiffness, contribute to tumor progression, metastasis, and resistance to treatment. Moreover, burgeoning immunotherapies hold great promise for harnessing the immune system to target and eliminate solid malignancies; however, their success is hindered by the hostile mechanical landscape of the TME, which can impede immune cell infiltration, function, and persistence. Consequently, understanding TME mechanoimmunology - the interplay between mechanical forces and immune cell behavior - is essential for developing effective solid cancer therapies. Here, we review the role of TME mechanics in tumor immunology, focusing on recent therapeutic interventions aimed at modulating the mechanical properties of the TME to potentiate T cell immunotherapies, and innovative assays tailored to evaluate their clinical efficacy.

Modelling the complex nature of the tumor microenvironment: 3D tumor spheroids as an evolving tool

Cancer remains a serious burden in society and while the pace in the development of novel and more effective therapeutics is increasing, testing platforms that faithfully mimic the tumor microenvironment are lacking. With a clear shift from animal models to more complex in vitro 3D systems, spheroids emerge as strong options in this regard. Years of development have allowed spheroid-based models to better reproduce the biomechanical cues that are observed in the tumor-associated extracellular matrix (ECM) and cellular interactions that occur in both a cell-cell and cell-ECM manner. Here, we summarize some of the key cellular interactions that drive tumor development, progression and invasion, and how successfully are these interactions recapitulated in 3D spheroid models currently in use in the field. We finish by speculating on future advancements in the field and on how these can shape the relevance of spherical 3D models for tumor modelling.

Tumor Vaccines: Unleashing the Power of the Immune System to Fight Cancer

This comprehensive review delves into the rapidly evolving arena of cancer vaccines. Initially, we examine the intricate constitution of the tumor microenvironment (TME), a dynamic factor that significantly influences tumor heterogeneity. Current research trends focusing on harnessing the TME for effective tumor vaccine treatments are also discussed. We then provide a detailed overview of the current state of research concerning tumor immunity and the mechanisms of tumor vaccines, describing the complex immunological processes involved. Furthermore, we conduct an exhaustive analysis of the contemporary research landscape of tumor vaccines, with a particular focus on peptide vaccines, DNA/RNA-based vaccines, viral-vector-based vaccines, dendritic-cell-based vaccines, and whole-cell-based vaccines. We analyze and summarize these categories of tumor vaccines, highlighting their individual advantages, limitations, and the factors influencing their effectiveness. In our survey of each category, we summarize commonly used tumor vaccines, aiming to provide readers with a more comprehensive understanding of the current state of tumor vaccine research. We then delve into an innovative strategy combining cancer vaccines with other therapies. By studying the effects of combining tumor vaccines with immune checkpoint inhibitors, radiotherapy, chemotherapy, targeted therapy, and oncolytic virotherapy, we establish that this approach can enhance overall treatment efficacy and offset the limitations of single-treatment approaches, offering patients more effective treatment options. Following this, we undertake a meticulous analysis of the entire process of personalized cancer vaccines, elucidating the intricate process from design, through research and production, to clinical application, thus helping readers gain a thorough understanding of its complexities. In conclusion, our exploration of tumor vaccines in this review aims to highlight their promising potential in cancer treatment. As research in this field continues to evolve, it undeniably holds immense promise for improving cancer patient outcomes.

Collagen architecture and signaling orchestrate cancer development

The tumor microenvironment (TME) controls tumor progression and maintenance. Accordingly, tumor-centric cancer treatment must adjust to being more holistic and TME-centric. Collagens are the most abundant TME proteins, and their dynamic remodeling profoundly affects both TME architecture and tumor development. Recent evidence shows that in addition to being structural elements, collagens are an important source of nutrients and decisive growth controlling and immunoregulatory signals. This review focuses on macropinocytosis-dependent collagen support of cancer cell metabolism and the role of collagen fiber remodeling and trimer heterogeneity in control of tumor bioenergetics, growth, progression, and response to therapy. If properly translated, these basic advances may alter the future of cancer treatment.

Fabrication and multiscale modeling of polycaprolactone/amniotic membrane electrospun nanofiber scaffolds for wound healing

BACKGROUND

Enhancing the efficiency of cell-based skin tissue engineering (TE) approaches is possible via designing electrospun scaffolds possessing natural materials like amniotic membrane (AM) with wound healing characteristics. Concentrating on this aim, we fabricated innovative polycaprolactone (PCL)/AM scaffolds through the electrospinning process.

METHODS

The manufactured structures were characterized by employing scanning electron microscope (SEM), attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy, tensile testing, Bradford protein assay, etc. In addition, the mechanical properties of scaffolds were simulated by the multiscale modeling method.

RESULTS

As a result of conducting various tests, it was concluded that the uniformity and distribution of fibers decreased with an increase in the amniotic content. Furthermore, PCL-AM scaffolds contained amniotic and PCL characteristic bands. In the case of protein release, greater content of AM led to the release of higher amounts of collagen. Tensile testing revealed that scaffolds' ultimate strength increased when the AM content augmented. The multiscale modeling demonstrated that the scaffold had elastoplastic behavior. In order to assess cellular attachment, viability, and differentiation, human adipose-derived stem cells (ASCs) were seeded on the scaffolds. In this regard, SEM and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assays showed significant cellular proliferation and viability on the proposed scaffolds, and these analyses illustrated that higher cell survival and adhesion could be achieved when scaffolds possessed a larger amount of AM. After 21 days of cultivation, particular keratinocyte markers, such as keratin I and involucrin, were identified through utilizing immunofluorescence and real-time polymerase chain reaction (PCR) tests. The markers' expressions were higher in the PCL-AM scaffold with a ratio of 90:10 v v-1 compared with the PCL-epidermal growth factor (EGF) structure. Moreover, the presence of AM in the scaffolds resulted in the keratinogenic differentiation of ASCs even without employing EGF. Consequently, this state-of-the-art experiment suggests that the PCL-AM scaffold can be a promising candidate in skin bioengineering.

CONCLUSION

This study showed that mixing AM with PCL, a widely used polymer, in different concentrations can overcome PCL disadvantages such as high hydrophobicity and low cellular compatibility.

Collagen-Specific Molecular Magnetic Resonance Imaging of Prostate Cancer

Constant interactions between tumor cells and the extracellular matrix (ECM) influence the progression of prostate cancer (PCa). One of the key components of the ECM are collagen fibers, since they are responsible for the tissue stiffness, growth, adhesion, proliferation, migration, invasion/metastasis, cell signaling, and immune recruitment of tumor cells. To explore this molecular marker in the content of PCa, we investigated two different tumor volumes (500 mm3 and 1000 mm3) of a xenograft mouse model of PCa with molecular magnetic resonance imaging (MRI) using a collagen-specific probe. For in vivo MRI evaluation, T1-weighted sequences before and after probe administration were analyzed. No significant signal difference between the two tumor volumes could be found. However, we detected a significant difference between the signal intensity of the peripheral tumor area and the central area of the tumor, at both 500 mm3 (p < 0.01, n = 16) and at 1000 mm3 (p < 0.01, n = 16). The results of our histologic analyses confirmed the in vivo studies: There was no significant difference in the amount of collagen between the two tumor volumes (p > 0.05), but within the tumor, higher collagen expression was observed in the peripheral area compared with the central area of the tumor. Laser ablation with inductively coupled plasma mass spectrometry further confirmed these results. The 1000 mm3 tumors contained 2.8 ± 1.0% collagen and the 500 mm3 tumors contained 3.2 ± 1.2% (n = 16). There was a strong correlation between the in vivo MRI data and the ex vivo histological data (y = −0.068x + 1.1; R2 = 0.74) (n = 16). The results of elemental analysis by inductively coupled plasma mass spectrometry supported the MRI data (y = 3.82x + 0.56; R2 = 0.79; n = 7). MRI with the collagen-specific probe in PCa enables differentiation between different tumor areas. This may help to differentiate tumor from healthy tissue, potentially identifying tumor areas with a specific tumor biology.

Collagen Remodeling along Cancer Progression Providing a Novel Opportunity for Cancer Diagnosis and Treatment

The extracellular matrix (ECM) is a significant factor in cancer progression. Collagens, as the main component of the ECM, are greatly remodeled alongside cancer development. More and more studies have confirmed that collagens changed from a barrier to providing assistance in cancer development. In this course, collagens cause remodeling alongside cancer progression, which in turn, promotes cancer development. The interaction between collagens and tumor cells is complex with biochemical and mechanical signals intervention through activating diverse signal pathways. As the mechanism gradually clears, it becomes a new target to find opportunities to diagnose and treat cancer. In this review, we investigated the process of collagen remodeling in cancer progression and discussed the interaction between collagens and cancer cells. Several typical effects associated with collagens were highlighted in the review, such as fibrillation in precancerous lesions, enhancing ECM stiffness, promoting angiogenesis, and guiding invasion. Then, the values of cancer diagnosis and prognosis were focused on. It is worth noting that several generated fragments in serum were reported to be able to be biomarkers for cancer diagnosis and prognosis, which is beneficial for clinic detection. At a glance, a variety of reported biomarkers were summarized. Many collagen-associated targets and drugs have been reported for cancer treatment in recent years. The new targets and related drugs were discussed in the review. The mass data were collected and classified by mechanism. Overall, the interaction of collagens and tumor cells is complicated, in which the mechanisms are not completely clear. A lot of collagen-associated biomarkers are excavated for cancer diagnosis. However, new therapeutic targets and related drugs are almost in clinical trials, with merely a few in clinical applications. So, more efforts are needed in collagens-associated studies and drug development for cancer research and treatment.

Breast cancer microenvironment and obesity: challenges for therapy

Women with obesity who develop breast cancer have a worsened prognosis with diminished survival rates and increased rates of metastasis. Obesity is also associated with decreased breast cancer response to endocrine and chemotherapeutic treatments. Studies utilizing multiple in vivo models of obesity as well as human breast tumors have enhanced our understanding of how obesity alters the breast tumor microenvironment. Changes in the complement and function of adipocytes, adipose-derived stromal cells, immune cells, and endothelial cells and remodeling of the extracellular matrix all contribute to the rapid growth of breast tumors in the context of obesity. Interactions of these cells enhance secretion of cytokines and adipokines as well as local levels of estrogen within the breast tumor microenvironment that promote resistance to multiple therapies. In this review, we will discuss our current understanding of the impact of obesity on the breast tumor microenvironment, how obesity-induced changes in cellular interactions promote resistance to breast cancer treatments, and areas for development of treatment interventions for breast cancer patients with obesity.

Local extensional flows promote long-range fiber alignment in 3D collagen hydrogels

Randomly oriented type I collagen (COL1) fibers in the extracellular matrix are reorganized by biophysical forces into aligned domains extending several millimeters and with varying degrees of fiber alignment. These aligned fibers can transmit traction forces, guide tumor cell migration, facilitate angiogenesis, and influence tissue morphogenesis. To create aligned COL1 domains in microfluidic cell culture models, shear flows have been used to align thin COL1 matrices (<50µm in height) in a microchannel. However, there has been limited investigation into the role of shear flows in aligning 3D hydrogels (>130µm). Here, we show that pure shear flows do not induce fiber alignment in 3D atelo COL1 hydrogels, but the simple addition of local extensional flow promotes alignment that is maintained across several millimeters, with a degree of alignment directly related to the extensional strain rate. We further advance experimental capabilities by addressing the practical challenge of accessing a 3D hydrogel formed within a microchannel by introducing a magnetically coupled modular platform that can be released to expose the microengineered hydrogel. We demonstrate the platform's capability to pattern cells and fabricate multi-layered COL1 matrices using layer-by-layer fabrication and specialized modules. Our approach provides an easy-to-use fabrication method to achieve advanced hydrogel microengineering capabilities that combine fiber alignment with biofabrication capabilities.

Multi-Cue Kinetic Model with Non-Local Sensing for Cell Migration on a Fiber Network with Chemotaxis

Cells perform directed motion in response to external stimuli that they detect by sensing the environment with their membrane protrusions. Precisely, several biochemical and biophysical cues give rise to tactic migration in the direction of their specific targets. Thus, this defines a multi-cue environment in which cells have to sort and combine different, and potentially competitive, stimuli. We propose a non-local kinetic model for cell migration in which cell polarization is influenced simultaneously by two external factors: contact guidance and chemotaxis. We propose two different sensing strategies, and we analyze the two resulting transport kinetic models by recovering the appropriate macroscopic limit in different regimes, in order to observe how the cell size, with respect to the variation of both external fields, influences the overall behavior. This analysis shows the importance of dealing with hyperbolic models, rather than drift-diffusion ones. Moreover, we numerically integrate the kinetic transport equations in a two-dimensional setting in order to investigate qualitatively various scenarios. Finally, we show how our setting is able to reproduce some experimental results concerning the influence of topographical and chemical cues in directing cell motility.

Computer-assisted quantification of tumor-associated collagen signatures to improve the prognosis prediction of breast cancer

BACKGROUND

Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients.

METHODS

In this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS).

RESULTS

TCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873-0.938]; 0.896, [0.860-0.931]; 0.882, [0.840-0.925] in the three cohorts).

CONCLUSION

These results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.

Invasion front dynamics in disordered environments

Invasion occurs in environments that are normally spatially disordered, however, the effect of such a randomness on the dynamics of the invasion front has remained less understood. Here, we study Fisher's equation in disordered environments both analytically and numerically. Using the Effective Medium Approximation, we show that disorder slows down invasion velocity and for ensemble average of invasion velocity in disordered environment we have [Formula: see text] where [Formula: see text] is the amplitude of disorder and [Formula: see text] is the invasion velocity in the corresponding homogeneous environment given by [Formula: see text]. Additionally, disorder imposes fluctuations on the invasion front. Using a perturbative approach, we show that these fluctuations are Brownian with a diffusion constant of: [Formula: see text]. These findings were approved by numerical analysis. Alongside this continuum model, we use the Stepping Stone Model to check how our findings change when we move from the continuum approach to a discrete approach. Our analysis suggests that individual-based models exhibit inherent fluctuations and the effect of environmental disorder becomes apparent for large disorder intensity and/or high carrying capacities.

Tumor-associated collagen signatures: pushing tumor boundaries

In 2006, a new model of invasive breast tumor emerged and, since 2011, is gaining recognition and research momentum. "Tumor-associated collagen signatures" describe 3 distinct layers of collagen which radiate outward in shells from the main body of the tumor. The outermost layer (TACS3) features branches of collagen radiating away from the tumor, 90° perpendicular to the tumor surface. TACS3 increases tumor span and correlates directly with metastasis, though presently difficult to detect in breast tissue. TACS is an emerging model but has been validated by multiple labs in vitro and in vivo, specifically for breast cancer prognostics. Newly recognized and accepted tumor borders will impact both R0 resections and downstream surgical reconstruction. This review aims to comprehensively introduce and connect the ranging literature on linearized collagen of invasive tumor borders. Using PubMed keyword searches containing "aligned," "linear," "oriented," and "organized," we have gathered the studies on TACS, integrated the concept into the clinic, and projected future platforms.

Effect of heterogeneity and spatial correlations on the structure of a tumor invasion front in cellular environments

Analysis of invasion front has been widely used to decipher biological properties, as well as the growth dynamics of the corresponding populations. Likewise, the invasion front of tumors has been investigated, from which insights into the biological mechanisms of tumor growth have been gained. We develop a model to study how tumors' invasion front depends on the relevant properties of a cellular environment. To do so, we develop a model based on a nonlinear reaction-diffusion equation, the Fisher-Kolmogorov-Petrovsky-Piskunov equation, to model tumor growth. Our study aims to understand how heterogeneity in the cellular environment's stiffness, as well as spatial correlations in its morphology, the existence of both of which has been demonstrated by experiments, affects the properties of tumor invasion front. It is demonstrated that three important factors affect the properties of the front, namely the spatial distribution of the local diffusion coefficients, the spatial correlations between them, and the ratio of the cells' duplication rate and their average diffusion coefficient. Analyzing the scaling properties of tumor invasion front computed by solving the governing equation, we show that, contrary to several previous claims, the invasion front of tumors and cancerous cell colonies cannot be described by the well-known models of kinetic growth, such as the Kardar-Parisi-Zhang equation.