KRAS-mediated upregulation of CIP2A promotes suppression of PP2A-B56α to initiate pancreatic cancer development.

Oncogenic mutations in KRAS are present in approximately 95% of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) and are considered the initiating event of pancreatic intraepithelial neoplasia (PanIN) precursor lesions. While it is well established that KRAS mutations drive the activation of oncogenic kinase cascades during pancreatic oncogenesis, the effects of oncogenic KRAS signaling on regulation of phosphatases during this process is not fully appreciated. Protein Phosphatase 2A (PP2A) has been implicated in suppressing KRAS-driven cellular transformation. However, low PP2A activity is observed in PDAC cells compared to non-transformed cells, suggesting that suppression of PP2A activity is an important step in the overall development of PDAC. In the current study, we demonstrate that KRASG12D induces the expression of both an endogenous inhibitor of PP2A activity, Cancerous Inhibitor of PP2A (CIP2A), and the PP2A substrate, c-MYC. Consistent with these findings, KRASG12D sequestered the specific PP2A subunit responsible for c-MYC degradation, B56α, away from the active PP2A holoenzyme in a CIP2A-dependent manner. During PDAC initiation in vivo, knockout of B56α promoted KRASG12D tumorigenesis by accelerating acinar-to-ductal metaplasia (ADM) and the formation of PanIN lesions. The process of ADM was attenuated ex vivo in response to pharmacological re-activation of PP2A utilizing direct small molecule activators of PP2A (SMAPs). Together, our results suggest that suppression of PP2A-B56α through KRAS signaling can promote the MYC-driven initiation of pancreatic tumorigenesis.

Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data.

Despite the remarkable advances in cancer diagnosis, treatment, and management over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be enabled by personalizing the delivery of therapies according to the predicted response for each individual patient. The design of personalized therapies requires the integration of patient-specific information with an appropriate mathematical model of tumor response. A fundamental barrier to realizing this paradigm is the current lack of a rigorous yet practical mathematical theory of tumor initiation, development, invasion, and response to therapy. We begin this review with an overview of different approaches to modeling tumor growth and treatment, including mechanistic as well as data-driven models based on big data and artificial intelligence. We then present illustrative examples of mathematical models manifesting their utility and discuss the limitations of stand-alone mechanistic and data-driven models. We then discuss the potential of mechanistic models for not only predicting but also optimizing response to therapy on a patient-specific basis. We describe current efforts and future possibilities to integrate mechanistic and data-driven models. We conclude by proposing five fundamental challenges that must be addressed to fully realize personalized care for cancer patients driven by computational models.

Inverse resolution of spatially varying diffusion coefficient using Physics-Informed neural networks.

Resolving the diffusion coefficient is a key element in many biological and engineering systems, including pharmacological drug transport and fluid mechanics analyses. Additionally, these systems often have spatial variation in the diffusion coefficient which must be determined, such as for injectable drug-eluting implants into heterogeneous tissues. Unfortunately, obtaining the diffusion coefficient from images in such cases is an inverse problem with only discrete data points. The development of a robust method that can work with such noisy and ill-posed datasets to accurately determine spatially-varying diffusion coefficients is of great value across a large range of disciplines. Here, we developed an inverse solver that uses physics informed neural networks (PINNs) to calculate spatially-varying diffusion coefficients from numerical and experimental image data in varying biological and engineering applications. The residual of the transient diffusion equation for a concentration field is minimized to find the diffusion coefficient. The robustness of the method as an inverse solver was tested using both numerical and experimental datasets. The predictions show good agreement with both the numerical and experimental benchmarks; an error of less than 6.31% was obtained against all numerical benchmarks, while the diffusion coefficient calculated in experimental datasets matches the appropriate ranges of other reported literature values. Our work demonstrates the potential of using PINNs to resolve spatially-varying diffusion coefficients, which may aid a wide-range of applications, such as enabling better-designed drug-eluting implants for regenerative medicine or oncology fields.

Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data.

Despite the remarkable advances in cancer diagnosis, treatment, and management that have occurred over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be enabled by personalizing the delivery of therapies according to the predicted response for each individual patient. The design of personalized therapies requires patient-specific information integrated into an appropriate mathematical model of tumor response. A fundamental barrier to realizing this paradigm is the current lack of a rigorous, yet practical, mathematical theory of tumor initiation, development, invasion, and response to therapy. In this review, we begin by providing an overview of different approaches to modeling tumor growth and treatment, including mechanistic as well as data-driven models based on ``big data" and artificial intelligence. Next, we present illustrative examples of mathematical models manifesting their utility and discussing the limitations of stand-alone mechanistic and data-driven models. We further discuss the potential of mechanistic models for not only predicting, but also optimizing response to therapy on a patient-specific basis. We then discuss current efforts and future possibilities to integrate mechanistic and data-driven models. We conclude by proposing five fundamental challenges that must be addressed to fully realize personalized care for cancer patients driven by computational models.

Transcriptomic alterations in hypertrophy of the ligamentum flavum: interactions of Rho GTPases, RTK, PIK3, and FGF.

PURPOSE: To analyze the differential transcriptome expression in hypertrophic ligaments flavum (HLF) compared to normal ligaments. METHODS: A case-control study was conducted that included 15 patients with hypertrophy of LF and 15 controls. Samples of LF were obtained through a lumbar laminectomy and analyzed by DNA microarrays and histology. The dysregulated biological processes, signaling pathways, and pathological markers in the HLF were identified using bioinformatics tools. RESULTS: The HLF had notable histological alterations, including hyalinosis, leukocyte infiltration, and disarrangement of collagen fibers. Transcriptomic analysis showed that up-regulated genes were associated with the signaling pathways of Rho GTPases, receptor tyrosine kinases (RTK), fibroblast growth factors (FGF), WNT, vascular endothelial growth factor, phosphoinositide 3-kinase (PIK3), mitogen-activated protein kinases, and immune system. The genes PIK3R1, RHOA, RPS27A, CDC42, VAV1, and FGF5, 9, 18, and 19 were highlighted as crucial markers in HLF. The down-expressed genes in the HLF had associations with the metabolism of RNA and proteins. CONCLUSION: Our results suggest that abnormal processes in hypertrophied LF are mediated by the interaction of the Rho GTPase, RTK, and PI3K pathways, which have not been previously described in the HLF, but for which there are currently therapeutic proposals. More studies are required to confirm the therapeutic potential of the pathways and mediators described in our results.

PLA-PCL microsphere formulation to deter abuse of prescription opioids by smoking.

Opioids are commonly prescribed across the United States (US) for pain relief, despite their highly addictive nature that often leads to abuse and overdose deaths. Abuse deterrent formulations (ADFs) for prescription opioids make the non-therapeutic use of these drugs more difficult and less satisfying. Although approximately one-third of surveyed abusers in the US reported smoking opioids, to our knowledge, no commercialized ADF effectively prevents opioid smoking. Here, we report a novel approach to deter smoking of a model prescription opioid drug, thebaine (THB), by using polymer blend microspheres (MS) comprising polylactic acid (PLA) and polycaprolactone (PCL). We utilized high-performance liquid chromatography (HPLC) and thermogravimetric analysis (TGA) to test the ability of PLA-PCL MS to limit the escape of vaporized THB. Additionally, we compared the abuse-deterrent potential of PLA-PCL MS to that of activated carbon (AC) and mesoporous silica (MPS), two materials with excellent drug-adsorbing properties. Our MS formulation was effective in reducing the amount of both active drug and thermal degradation products in the vapor generated upon heating of THB. These results support that PLA-PCL microspheres can be co-formulated in a tablet with common prescription opioids to deter their abuse via the smoking route.

Transglutaminase-2 mediates acquisition of neratinib resistance in metastatic breast cancer.

Acquisition of resistance to targeted therapies remains a major clinical obstacle for the HER2+ subtype of breast cancer. Using an isogeneic progression series of HER2+ breast cancer metastasis we demonstrate that metastatic cells have an increased capacity to acquire resistance to the covalent, pan-ErbB inhibitor, neratinib. RNA sequencing analyses comparing parental and metastatic cells identified upregulation of transglutaminase 2 (TG2). Genetic depletion and overexpression approaches established that TG2 is both necessary and sufficient for acquisition of neratinib resistance. Mechanistically, we describe a pathway in which TG2-mediates activation of NF-κB signaling leading to upregulation of IL-6 in metastatic cells. This autocrine expression of IL-6 functions to maintain enhanced levels of TG2 via JAK:STAT3 signaling. This drug persistence feedback loop can be interrupted through the use of the JAK1/2 inhibitor ruxolitinib. In vivo application of ruxolitinib had no effect on tumor growth under non-treated conditions, but effectively prevented acquisition of resistance, leading to tumor regression upon coadministration with neratinib. Overall, our studies reveal a mechanism in metastatic breast cancer cells that predisposes them to acquisition of resistance to ErbB-targeted therapeutics. Clinically, immediate application of ruxolitinib could prevent acquisition of resistance and improve patient responses to HER2-targeted therapies.

Tumor Cell-Autonomous SHP2 Contributes to Immune Suppression in Metastatic Breast Cancer.

SH2 containing protein tyrosine phosphatase-2 (SHP2) is recognized as a druggable oncogenic phosphatase that is expressed in both tumor cells and immune cells. How tumor cell-autonomous SHP2 contributes to an immunosuppressive tumor microenvironment (TME) and therapeutic failure of immune checkpoint blockades in metastatic breast cancer (MBC) is not fully understood. Herein, we utilized systemic SHP2 inhibition and inducible genetic depletion of SHP2 to investigate immune reprogramming during SHP2 targeting. Pharmacologic inhibition of SHP2 sensitized MBC cells growing in the lung to α-programmed death ligand 1 (α-PD-L1) antibody treatment via relieving T-cell exhaustion induced by checkpoint blockade. Tumor cell-specific depletion of SHP2 similarly reduced pulmonary metastasis and also relieved exhaustion markers on CD8+ and CD4+ cells. Both systemic SHP2 inhibition and tumor cell-autonomous SHP2 depletion reduced tumor-infiltrated CD4+ T cells and M2-polarized tumor-associated macrophages. Analysis of TCGA datasets revealed that phosphorylation of SHP2 is important for immune-cell infiltration, T-cell activation and antigen presentation. To investigate this mechanistically, we conducted in vitro T-cell killing assays, which demonstrated that pretreatment of tumor cells with FGF2 and PDGF reduced the cytotoxicity of CD8+ T cells in a SHP2-dependent manner. Both growth factor receptor signaling and three-dimensional culture conditions transcriptionally induced PD-L1 via SHP2. Finally, SHP2 inhibition reduced MAPK signaling and enhanced STAT1 signaling, preventing growth factor-mediated suppression of MHC class I. Overall, our findings support the conclusion that tumor cell-autonomous SHP2 is a key signaling node utilized by MBC cells to engage immune-suppressive mechanisms in response to diverse signaling inputs from TME. Significance: Findings present inhibition of SHP2 as a therapeutic option to limit breast cancer metastasis by promoting antitumor immunity.

Sustained degradation of hyaluronic acid using an in situ forming implant.

In pancreatic cancer, excessive hyaluronic acid (HA) in the tumor microenvironment creates a viscous stroma, which reduces systemic drug transport into the tumor and correlates with poor patient prognosis. HA can be degraded through both enzymatic and nonenzymatic methods to improve mass transport properties. Here, we use an in situ forming implant to provide sustained degradation of HA directly at a local, targeted site. We formulated and characterized an implant capable of sustained release of hyaluronidase (HAase) using 15 kDa poly(lactic-co-glycolic) acid and bovine testicular HAase. The implant releases bioactive HAase to degrade the HA through enzymatic hydrolysis at early timepoints. In the first 24 h, 17.9% of the HAase is released, which can reduce the viscosity of a 10 mg/mL HA solution by 94.1% and deplete the HA content within primary human pancreatic tumor samples and ex vivo murine tumors. At later timepoints, as lower quantities of HAase are released (51.4% released in total over 21 d), the degradation of HA is supplemented by the acidic by-products that accumulate as a result of implant degradation. Acidic conditions degrade HA through nonenzymatic methods. This formulation has potential as an intratumoral injection to allow sustained degradation of HA at the pancreatic tumor site.

High-Throughput Magnetic Actuation Platform for Evaluating the Effect of Mechanical Force on 3D Tumor Microenvironment.

Accurately replicating and analyzing cellular responses to mechanical cues is vital for exploring metastatic disease progression. However, many of the existing in vitro platforms for applying mechanical stimulation seed cells on synthetic substrates. To better recapitulate physiological conditions, a novel actuating platform is developed with the ability to apply tensile strain on cells at various amplitudes and frequencies in a high-throughput multi-well culture plate using a physiologically-relevant substrate. Suspending fibrillar fibronectin across the body of the magnetic actuator provides a matrix representative of early metastasis for 3D cell culture that is not reliant on a synthetic substrate. This platform enables the culturing and analysis of various cell types in an environment that mimics the dynamic stretching of lung tissue during normal respiration. Metabolic activity, YAP activation, and morphology of breast cancer cells are analyzed within one week of cyclic stretching or static culture. Further, matrix degradation is significantly reduced in breast cancer cell lines with metastatic potential after actuation. These new findings demonstrate a clear suppressive cellular response due to cyclic stretching that has implications for a mechanical role in the dormancy and reactivation of disseminated breast cancer cells to macrometastases.

A Bayesian approach to estimate the diffusion coefficient of Rhodamine 6G in breast cancer spheroids.

Multicellular spheroids have emerged as a robust platform to model tumor growth and are widely used for studying drug sensitivity. Diffusion is the main mechanism for transporting nutrients and chemotherapeutic drugs into spheroids, since they are typically avascular. In this study, the Bayesian inference was used to solve the inverse problem of determining the light attenuation coefficient and diffusion coefficient of Rhodamine 6G (R6G) in breast cancer spheroids, as a mock drug for the tyrosine kinase inhibitor, Neratinib. Four types of breast cancer spheroids were formed and the diffusion coefficient was estimated assuming a linear relationship between the intensity and concentration. The mathematical model used for prediction is the solution to the diffusion problem in spherical coordinates, accounting for the light attenuation. The Gaussian likelihood was used to account for the error between the measurements and model predictions. The Markov Chain Monte Carlo algorithm (MCMC) was used to sample from the posterior. The posterior predictions for the diffusion and light attenuation coefficients were provided. The results indicate that the diffusion coefficient values do not significantly vary across a HER2+ breast cancer cell line as a function of transglutaminase 2 levels, even in the presence of fibroblast cells. However, we demonstrate that different diffusion coefficient values can be ascertained from tumorigenic compared to nontumorigenic spheroids and from nonmetastatic compared to post-metastatic breast cancer cells using this approach. We also report agreement between spheroid radius, attenuation coefficient, and subsequent diffusion coefficient to give evidence of cell packing in self-assembled spheroids. The methodology presented here will allow researchers to determine diffusion in spheroids to decouple transport and drug penetration changes from biological resistivity.

In Vitro Magnetic Techniques for Investigating Cancer Progression.

Worldwide, there are currently around 18.1 million new cancer cases and 9.6 million cancer deaths yearly. Although cancer diagnosis and treatment has improved greatly in the past several decades, a complete understanding of the complex interactions between cancer cells and the tumor microenvironment during primary tumor growth and metastatic expansion is still lacking. Several aspects of the metastatic cascade require in vitro investigation. This is because in vitro work allows for a reduced number of variables and an ability to gather real-time data of cell responses to precise stimuli, decoupling the complex environment surrounding in vivo experimentation. Breakthroughs in our understanding of cancer biology and mechanics through in vitro assays can lead to better-designed ex vivo precision medicine platforms and clinical therapeutics. Multiple techniques have been developed to imitate cancer cells in their primary or metastatic environments, such as spheroids in suspension, microfluidic systems, 3D bioprinting, and hydrogel embedding. Recently, magnetic-based in vitro platforms have been developed to improve the reproducibility of the cell geometries created, precisely move magnetized cell aggregates or fabricated scaffolding, and incorporate static or dynamic loading into the cell or its culture environment. Here, we will review the latest magnetic techniques utilized in these in vitro environments to improve our understanding of cancer cell interactions throughout the various stages of the metastatic cascade.

Design and validation of a modular micro-robotic system for the mechanical characterization of soft tissues.

The mechanical properties of tissues are critical design parameters for biomaterials and regenerative therapies seeking to restore functionality after disease or injury. Characterizing the mechanical properties of native tissues and extracellular matrix throughout embryonic development helps us understand the microenvironments that promote growth and remodeling, activities critical for biomaterials to support. The mechanical characterization of small, soft materials like the embryonic tissues of the mouse, an established mammalian model for development, is challenging due to difficulties in handling minute geometries and resolving forces of low magnitude. While uniaxial tensile testing is the physiologically relevant modality to characterize tissues that are loaded in tension in vivo, there are no commercially available instruments that can simultaneously measure sufficiently low tensile force magnitudes, directly measure sample deformation, keep samples hydrated throughout testing, and effectively grip minute geometries to test small tissues. To address this gap, we developed a micromanipulator and spring system that can mechanically characterize small, soft materials under tension. We demonstrate the capability of this system to measure the force contribution of soft materials, silicone, fibronectin sheets, and fibrin gels with a 5 nN - 50 µN force resolution and perform a variety of mechanical tests. Additionally, we investigated murine embryonic tendon mechanics, demonstrating the instrument can measure differences in mechanics of small, soft tissues as a function of developmental stage. This system can be further utilized to mechanically characterize soft biomaterials and small tissues and provide physiologically relevant parameters for designing scaffolds that seek to emulate native tissue mechanics. STATEMENT OF SIGNIFICANCE: The mechanical properties of cellular microenvironments are critical parameters that contribute to the modulation of tissue growth and remodeling. The field of tissue engineering endeavors to recapitulate these microenvironments in order to construct tissues de novo. Therefore, it is crucial to uncover the mechanical properties of the cellular microenvironment during tissue formation. Here, we present a system capable of acquiring microscale forces and optically measuring sample deformation to calculate the stress-strain response of soft, embryonic tissues under tension, and easily adaptable to accommodate biomaterials of various sizes and stiffnesses. Altogether, this modular system enables researchers to probe the unknown mechanical properties of soft tissues throughout development to inform the engineering of physiologically relevant microenvironments.

Epigenetic targeting of neuropilin-1 prevents bypass signaling in drug-resistant breast cancer.

Human epidermal growth factor receptor 2 (HER2)-amplified breast cancers are treated using targeted antibodies and kinase inhibitors, but resistance to these therapies leads to systemic tumor recurrence of metastatic disease. Herein, we conducted gene expression analyses of HER2 kinase inhibitor-resistant cell lines as compared to their drug-sensitive counterparts. These data demonstrate the induction of epithelial-mesenchymal transition (EMT), which included enhanced expression of fibroblast growth factor receptor 1 (FGFR1) and axonal guidance molecules known as neuropilins (NRPs). Immunoprecipitation of FGFR1 coupled with mass spectroscopy indicated that FGFR1 forms a physical complex with NRPs, which is enhanced upon induction of EMT. Confocal imaging revealed that FGFR1 and NRP1 predominantly interact throughout the cytoplasm. Along these lines, short hairpin RNA-mediated depletion of NRP1, but not the use of NRP1-blocking antibodies, inhibited FGFR signaling and reduced tumor cell growth in vitro and in vivo. Our results further indicate that NRP1 upregulation during EMT is mediated via binding of the chromatin reader protein, bromodomain containing 4 (BRD4) in the NRP1 proximal promoter region. Pharmacological inhibition of BRD4 decreased NRP1 expression and ablated FGF-mediated tumor cell growth. Overall, our studies indicate that NRPs facilitate aberrant growth factor signaling during EMT-associated drug resistance and metastasis. Pharmacological combination of epigenetic modulators with FGFR-targeted kinase inhibitors may provide improved outcomes for breast cancer patients with drug-resistant metastatic disease.

SHP2 is a multifunctional therapeutic target in drug resistant metastatic breast cancer.

Metastatic breast cancer (MBC) is an extremely recalcitrant disease capable of bypassing current targeted therapies via engagement of several growth promoting pathways. SH2 containing protein tyrosine phosphatase-2 (SHP2) is an oncogenic phosphatase known to facilitate growth and survival signaling downstream of numerous receptor inputs. Herein, we used inducible genetic depletion and two distinct pharmacological inhibitors to investigate the therapeutic potential of targeting SHP2 in MBC. Cells that acquired resistance to the ErbB kinase inhibitor, neratinib, displayed increased phosphorylation of SHP2 at the Y542 activation site. In addition, higher levels of SHP2 phosphorylation, but not expression, were associated with decreased survival of breast cancer patients. Pharmacological inhibition of SHP2 activity blocked ERK1/2 and AKT signaling generated from exogenous stimulation with FGF2, PDGF, and hGF and readily prevented MBC cell growth induced by these factors. SHP2 was also phosphorylated upon engagement of the extracellular matrix (ECM) via focal adhesion kinase. Consistent with the potential of SHP2-targeted compounds as therapeutic agents, the growth inhibitory property of SHP2 blockade was enhanced in ECM-rich 3D culture environments. In vivo blockade of SHP2 in the adjuvant setting decreased pulmonary metastasis and extended the survival of systemic tumor-bearing mice. Finally, inhibition of SHP2 in combination with FGFR-targeted kinase inhibitors synergistically blocked the growth of MBC cells. Overall, our findings support the conclusion that SHP2 constitutes a shared signaling node allowing MBC cells to simultaneously engage a diversity of growth and survival pathways, including those derived from the ECM.

Fibronectin-Expressing Mesenchymal Tumor Cells Promote Breast Cancer Metastasis.

Tumor metastasis is connected to epithelial-mesenchymal heterogeneity (EMH) and the extracellular matrix (ECM) within the tumor microenvironment. Mesenchymal-like fibronectin (FN) expressing tumor cells enhance metastasis within tumors that have EMH. However, the secondary tumors are primarily composed of the FN null population. Interestingly, during tumor cell dissemination, the invasive front has more mesenchymal-like characteristics, although the outgrowths of metastatic colonies consist of a more epithelial-like population of cells. We hypothesize that soluble FN provided by mesenchymal-like tumor cells plays a role in supporting the survival of the more epithelial-like tumor cells within the metastatic niche in a paracrine manner. Furthermore, due to a lower rate of proliferation, the mesenchymal-like tumor cells become a minority population within the metastatic niche. In this study, we utilized a multi-parametric cell-tracking algorithm and immunoblotting to evaluate the effect of EMH on the growth and invasion of an isogenic cell series within a 3D collagen network using a microfluidic platform. Using the MCF10A progression series, we demonstrated that co-culture with FN-expressing MCF10CA1h cells significantly enhanced the survival of the more epithelial MCF10CA1a cells, with a two-fold increase in the population after 5 days in co-culture, whereas the population of the MCF10CA1a cells began to decrease after 2.5 days when cultured alone (p < 0.001). However, co-culture did not significantly alter the rate of proliferation for the more mesenchymal MCF10CA1h cells. Epithelial tumor cells not only showed prolonged survival, but migrated significantly longer distances (350 µm compared with 150 µm, respectively, p < 0.01) and with greater velocity magnitude (4.5 µm/h compared with 2.1 µm/h, respectively, p < 0.001) under co-culture conditions and in response to exogenously administered FN. Genetic depletion of FN from the MCF10CA1h cells resulted in a loss of survival and migration capacity of the epithelial and mesenchymal populations. These data suggest that mesenchymal tumor cells may function to support the survival and outgrowth of more epithelial tumor cells within the metastatic niche and that inhibition of FN production may provide a valuable target for treating metastatic disease.

The Dynamic Relationship of Breast Cancer Cells and Fibroblasts in Fibronectin Accumulation at Primary and Metastatic Tumor Sites.

In breast cancer (BC), tissue stiffening via fibronectin (FN) and collagen accumulation is associated with advanced disease progression at both the primary tumor and metastatic sites. Here, we evaluate FN production in 15 BC cell lines, representing a variety of subtypes, phenotypes, metastatic potentials, and chemotherapeutic sensitivities. We demonstrate that intracellular and soluble FN is initially lost during tumorigenic transformation but is rescued in all lines with epithelial-mesenchymal plasticity (EMP). Importantly, we establish that no BC cell line was able to independently organize a robust FN matrix. Non-transformed mammary epithelial cells were also unable to deposit FN matrices unless transglutaminase 2, a FN crosslinking enzyme, was overexpressed. Instead, BC cells manipulated the FN matrix production of fibroblasts in a phenotypic-dependent manner. In addition, varied accumulation levels were seen depending if the fibroblasts were conditioned to model paracrine signaling or endocrine signaling of the metastatic niche. In the former, fibroblasts conditioned by BC cultures with high EMP resulted in the largest FN matrix accumulation. In contrast, mesenchymal BC cells produced extracellular vesicles (EV) that resulted in the highest levels of matrix formation by conditioned fibroblasts. Overall, we demonstrate a dynamic relationship between tumor and stromal cells within the tumor microenvironment, in which the levels and fibrillarization of FN in the extracellular matrix are modulated during the particular stages of disease progression.

Transglutaminase-2 facilitates extracellular vesicle-mediated establishment of the metastatic niche.

The ability of breast cancer cells to interconvert between epithelial and mesenchymal states contributes to their metastatic potential. As opposed to cell autonomous effects, the impact of epithelial-mesenchymal plasticity (EMP) on primary and metastatic tumor microenvironments remains poorly characterized. Herein we utilize global gene expression analyses to characterize a metastatic model of EMP as compared to their non-metastatic counterparts. Using this approach, we demonstrate that upregulation of the extracellular matrix crosslinking enzyme tissue transglutaminase-2 (TG2) is part of a novel gene signature that only emerges in metastatic cells that have undergone induction and reversion of epithelial-mesenchymal transition (EMT). Consistent with our model system, patient survival is diminished when primary tumors demonstrate enhanced levels of TG2 in conjunction with its substrate, fibronectin. Targeted depletion of TG2 inhibits metastasis, while overexpression of TG2 is sufficient to enhance this process. In addition to being present within cells, we demonstrate a robust increase in the amount of TG2 and crosslinked fibronectin present within extracellular vesicle (EV) fractions derived from metastatic breast cancer cells. Confocal microscopy of these EVs suggests that FN undergoes fibrillogenesis on their surface via a TG2 and Tensin1-dependent process. Upon in vivo administration, the ability of tumor-derived EVs to induce metastatic niche formation and enhance subsequent pulmonary tumor growth requires the presence and activity of TG2. Finally, we develop a novel 3D model of the metastatic niche to demonstrate that conditioning of pulmonary fibroblasts via pretreatment with tumor-derived EVs promotes subsequent growth of breast cancer cells in a TG2-dependent fashion. Overall, our studies illustrate a novel mechanism through which EMP contributes to metastatic niche development and distant metastasis via tumor-derived EVs containing aberrant levels of TG2 and fibrillar FN.

Engineered Fibrillar Fibronectin Networks as Three-Dimensional Tissue Scaffolds.

Extracellular matrix (ECM) proteins, and most prominently, fibronectin (Fn), are routinely used in the form of adsorbed pre-coatings in an attempt to create a cell-supporting environment in both two- and three-dimensional cell culture systems. However, these protein coatings are typically deposited in a form which is structurally and functionally distinct from the ECM-constituting fibrillar protein networks naturally deposited by cells. Here, the cell-free and scalable synthesis of freely suspended and mechanically robust three-dimensional (3D) networks of fibrillar fibronectin (fFn) supported by tessellated polymer scaffolds is reported. Hydrodynamically induced Fn fibrillogenesis at the three-phase contact line between air, an Fn solution, and a tessellated scaffold microstructure yields extended protein networks. Importantly, engineered fFn networks promote cell invasion and proliferation, enable in vitro expansion of primary cancer cells, and induce an epithelial-to-mesenchymal transition in cancer cells. Engineered fFn networks support the formation of multicellular cancer structures cells from plural effusions of cancer patients. With further work, engineered fFn networks can have a transformative impact on fundamental cell studies, precision medicine, pharmaceutical testing, and pre-clinical diagnostics.